so social overview 2006 Editor in Chief: Jana S. Javornik X\ VIMAD Institute of Macroeconomic Analysis and Development Janez Šušteršič, Director DTP: Katarina Cimprič, Saša Brečko Graphs: Marjeta Žigman Translators: Nina Barlič, Marko Capuder, Joint Translation, Interpreting and Language Editing Service, Sebastijan Maček, Tina Potrato, Nuša Rozman Language Editor: Murray Bales Technical Support: Alenka Bitenc, Irena Rink, Katja Ferfolja, Ana-Marija Pucelj, Ema Bertina Kopitar Layout: Sandi Radovan, studio DVA Printed by: SOLOS, Ljubljana Circulation: 600 Ljubljana, April 2007 Authors of the Social Overview 2006: Jana S. Javornik (Editor in Chief, Conceptual Framework, Indebtedness and Over-indebtedness of Households, Access to Goods and Services, Perceptions of Living Conditions, The Family and its New Forms, Health of Elderly People, The Challenges of a Long-living Society) (Living Conditions – Situation and Trends, Social Inclusion of Elderly People, The Challenges of a Long-living Society) (Health of Elderly People) (Access to Childcare and Education, The Challenges of a Long-living Society, Statistical Appendix) (Adult Education) (Indebtedness and Over-Indebtedness of Households) (Adult Education) (Labour Market and Employment, The Challenges of a Long-living Society) (Conceptual Framework, Movements of Cash Benefits from Public Sources, Social Exclusion, Poverty, Social Support Networks, The Family and its New Forms, Social Inclusion of Elderly People, The Challenges of a Long-living Society) (Projections of the Population until 2050, Economic and Financial Consequences of Population Ageing, The Challenges of a Long-living Society) (Wage Movements in the 1998-2005 Period) (Projections of the Population until 2050, Economic and Financial Consequences of Population Ageing) (The Family and its New Forms) (Indebtedness and Over-indebtedness of Households, Perceptions of Living Conditions) (Regional Dimension of Unemployment) (Health of Elderly People) (Good Intergenerational Relations) (The Family and its New Forms) (Health of Elderly People) (Impact of Wages and Other Income of Employees on Income Inequality) (Characteristics of the Slovenian Households, Socio-economic Stratification of the Population, Expenditure, Income Situation and Satisfaction with Income) (Health of Elderly People) (The Demographic Development, The Family and its New Forms) (Access to Goods and Services) (The Family and its New Forms) (Conceptual Framework, Social Exclusion) (Health of Elderly People, The Challenges of a Long-living Society) (Impact of Wages and Other Income of Employees on Income Inequality) (Access to Goods and Services, Economic and Financial Consequences of Population Ageing, The Challenges of a Long-living Society) Advisory Board: Matjaž Hanžek, Anjuta Bubnov-Škoberne, Irena Križman, Brina Malnar, Marjan Premik, Tanja Rener, Tine Stanovnik, Nada Stropnik, Ivan Svetlik Expert Advisers: Erika Žnidaršič, Tina Žnidaršič, Milivoja Šircelj, Apolonija Oblak Flander, Rihard-Tomaž Inglič, Anita Jacović, Tatjana Škrbec, Irena Svetin, Rade Pribaković, Milena Ilić, Janja Povhe, Maša Filipović, Bernarda Hribar Lidija Apohal Vučkovič Polona Brcar Tanja Čelebič Olga Drofenik Barbara Ferk Angelca Ivančič Alenka Kajzer Maja Kersnik Dušan Kidrič Saša Kovačič Tomaž Kraigher Metka Kuhar Brina Malnar Janja Pečar Silva Pečar-Čad Jože Ramovš Tanja Rener Mateja Rok-Simon Tine Stanovnik Nada Stropnik Jožica Šelb-Šemerl Milivoja Šircelj Irena Štemberger Alenka Švab Martina Trbanc Polonca Truden-Dobrin Miroslav Verbič Eva Zver ISBN- 978-961-6031-53-0 © IMAD, 2007. The contents of this publication may be reproduced in whole or in part provided that the source is acknowledged. CONTENTS Foreword viii Executive Summary 1 Introduction 7 Conceptual Framework 8 I. The Way We Live 13 1. LIVING CONDITIONS – SITUATION AND TRENDS 15 1.1 Characteristics of the Slovenian households 15 1.2 Socio-economic stratification of the population 16 1.3 The main income sources – income from employment and from public sources 19 1.3.1 Wage movements in the 1998-2005 period 19 1.3.2 Movements of cash benefits from public sources 22 1.4 Expenditure 23 1.4.1 Indebtedness and over-indebtedness of households 25 1.5 Access to goods and services 26 1.5.1 Access to health care 27 1.5.2 Access to social welfare services 30 1.5.3 Access to childcare and education 32 1.5.4 Access to housing 36 1.5.5 Access to the Internet 39 1.6 Social exclusion 40 1.7 Poverty 44 1.8 Social support networks 45 1.8.1 Social support networks of certain vulnerable population groups 47 2. PERCEPTIONS OF LIVING CONDITIONS 48 2.1 Income situation and satisfaction with income 48 2.2 Satisfaction with one’s personal situation 49 2.3 Satisfaction with health and the health care 51 2.4 Perceptions of the wider societal environment 52 2.4.1 Trust in institutions 52 2.4.2 Trust in other people 53 2.4.3 Criminality - feeling threatened 54 2.5 Perception of development trends in society (1995-2005) 55 2.6 Life optimism/pessimism 56 Conclusion 56 II. Slovenia – A Long-living Society 57 Introduction 59 1. THE DEMOGRAPHIC DEVELOPMENT 60 1.1 Size and age structure of the population 60 1.2 Fertility 62 1.3 Mortality – prolongation of life 64 1.4 Migration 66 1.5 Projections of the population until 2050 69 2. THE FAMILY AND ITS NEW FORMS 72 2.1 The family: concepts and definitions 72 2.2 The transformation of family life 73 2.3 A statistical portrait of families in Slovenia 76 2.3.1 Changes in nuptiality and divorciality 77 2.3.2 Changes in fertility 79 2.4 Parenthood and family life through the lens of public opinion 80 2.4.1 The public opinion on the family 81 2.5 Family life and ageing 84 3. LABOUR MARKET AND EMPLOYMENT 86 3.1 Unemployment trends 86 3.1.1 Regional dimension of unemployment 87 3.2 Employment rate 89 3.3 Flexible forms of employment 89 3.3.1 Part-time employment 89 3.3.2 Temporary employment 90 4. ADULT EDUCATION 92 5. HEALTH OF ELDERLY PEOPLE 95 5.1 Primary health care 95 5.2 Secondary and tertiary outpatient health care 97 5.3 Hospital health care 97 5.4 Consumption of medications 98 6. SOCIAL INCLUSION OF ELDERLY PEOPLE 99 6.1 Good intergenerational relations 99 6.2 Housing conditions of the elderly 100 6.3 Social support networks among the elderly 100 6.4 The poverty of the elderly 101 6.5 Long-term care 101 7. ECONOMIC AND FINANCIAL CONSEQUENCES OF POPULATION AGEING 104 7.1 Expenditure projections 105 7.1.1 Pension expenditure 105 7.1.2 Expenditures on health care and long-term care 106 7.1.3 Other public expenditure related to demographic changes 107 8. THE CHALLENGES OF A LONG-LIVING SOCIETY 108 III. STATISTICAL APPENDIX 113 Bibliography 150 Social Overview 2006 iii List of Tables Table 1: Increase in income, Slovenia, 1998-2002 17 Table 2: Distribution of persons and their income across income brackets, Slovenia, 1998 and 2002 17 Table 3: Structure of income sources by income brackets, Slovenia, 1998 and 2002 18 Table 4: Relative importance of social and family benefi ts, Slovenia, 1998 and 2002 19 Table 5: Growth rates of labour productivity and real gross wages per employee in the private and public sectors, Slovenia, 1998-2005 19 Table 6: Indicators of the distribution of employees with regard to gross wage amounts, Slovenia, 1998-2005 20 Table 7a: Structure of the gross income of taxable employees, Slovenia, 1994 and 2002 21 Table 7b: Structure of the gross income of employees whose income exceeds eight average wages, Slovenia, 1994 and 2002 22 Table 8: Structure of expenditure on consumer goods by income brackets, Slovenia, 1998 and 2002 24 Table 9: Household fi nal consumption expenditure, Slovenia (1999-2001) and the EU (1999) 24 Table 10: Percentage of people who cannot meet the running costs of living in due time with regard to their household income, Slovenia, 2005 26 Table 11: Assessment of the household material situation – fi nancial reserves, Slovenia, 1992-2005 26 Table 12: Structure of expenditure on health and shares in GDP, Slovenia, 1997-2003 30 Table 13: Expenditure on long-term care by sources of funds and by purpose, Slovenia, 2003 and 2004 31 Table 14: Expenditure on education institutions by source, Slovenia (1995-2003) and the EU25 (2002) 35 Table 15: Dwellings according to censuses, Slovenia, 1971-2002 37 Table 16: Households and dwellings without basic installations, Slovenia, census 2002 37 Table 17: Tenure status by income brackets, Slovenia, 1998 and 2002 38 Table 18: Number of newly acquired non-profi t and social dwellings in Slovenia, 1995-2004 39 Table 19: Subjective perceptions of social exclusion and (objective) multiple deprivation, 2001/2002 42 Table 20: Why do some people live in deprivation (opinions of Slovenian and EU citizens), 2001/2002 43 Table 21: At risk of poverty rates after and before social transfers in Slovenia and the EU member states (including income in kind), 1998-2003 45 Table 22: Average number of social support network members for the population by support type and vulnerable groups, Slovenia, 2004 46 Table 23: Subjective evaluation of the household income situation, by income brackets, Slovenia, 1998 and 2002 48 Table 24: Perceptions of fi nancial situation, Slovenia, 1995-2005 49 Table 25: Positions as to material situation, Slovenia, 1990-2005 49 Table 26: Satisfaction with family life, by gender, Slovenia, 2003 50 Table 27: Satisfaction with employment total, by gender, Slovenia, 2003 50 Table 28: Trust in institutions, Slovenia, 1995 and 2000-2005, sum total of responses ‘I trust completely’ and ‘I trust considerably’ 52 Table 29: Perceptions of development trends in society, Slovenia, 1995-2005 55 Table 30: Shares of the active population in the working age population (aged 15-64), Slovenia, 1961-2002 censuses 62 Table 31: Life expectancy at birth and at the age of 65 years in Slovenia during the 1931-2002 period 66 Table 32: Immigrants to Slovenia and emigrants from Slovenia by citizenship, 1996-2004 68 Table 33: Mean age of immigrants to Slovenia and emigrants from Slovenia, 1996-2004 68 Table 34: Internal migrations, Slovenia, 1965-2004 68 Table 35: Assumptions and certain results of the basic projection of the Slovenian population in 2004 and projections in 2010-2050 (according to Eurostat) 70 Table 36: Families by type and size, 1971, 1981, 1991 and 2002 Censuses, Slovenia 76 Table 37: Family types, at the 1981, 1991 and 2002 Censuses, Slovenia 77 Table 38: Crude marriage rates, crude divorce rates and total divorce rates, 1955-2005, Slovenia 77 Table 39: Total fi rst marriage rates of females and mean age of brides at fi rst marriage, Slovenia, 1980-2005 78 Table 40: Intensions to have children, by age groups, Slovenia, 2004 81 iv Social Overview 2006 Table 41: Attitudes on family life, comparison by gender, Slovenia, 2003; the respondent agrees or strongly agrees 81 Table 42: Attitudes on women’s employment, Slovenia, 2003 81 Table 43: Division of labour in the family, by gender, Slovenia, 2003 82 Table 44: Time spent on housework, by gender, Slovenia, 2003 83 Table 45: Attitudes about men’s family-life workload, by gender, Slovenia, 2003 83 Table 46: Attitudes on fairness of the division of domestic labour, by gender, Slovenia, 2003 83 Table 47: Reconciliation of paid work and family life, by gender, Slovenia, 2003 84 Table 48: Reconciliation of paid work and family life, by gender, Slovenia, 2003 84 Table 49: Unemployment rates, Slovenia, 1999-2005 86 Table 50: Unemployment rates by age groups, Slovenia, 1999-2005 86 Table 51: Registered unemployment rate at the regional level, Slovenia, 2000-2005 87 Table 52: Selected indicators of structural problems in unemployment by regions in Slovenia in 2005, based on data on registered unemployment 88 Table 53: Employment rate by age groups, Slovenia, 1999-2005 89 Table 54: Share of part-time workers in total employment, Slovenia and the EU25, 1999-2004 90 Table 55: Share of temporary employment in overall employment, Slovenia and the EU25, 1999-2004 90 Table 56: Participation of adults in education, Slovenia, 2004 94 Table 57: Share of the decided compulsorily insured persons in employed general practitioners and dentists by permanent residents, Slovenia, May 2006 95 Table 58: Rate of hospitalisations due to illness per 1,000 inhabitants by age groups, Slovenia, 1998-2004 98 Table 59: Number of dispensed prescriptions and value of medications by age, Slovenia, 2004 98 Table 60: Old people’s homes, Slovenia, 2000-2005 102 Table 61: Key demographic indicators in 2004 and projections for 2050, Slovenia and the EU15 and EU10 104 Table 62: Share of the elderly and projection of the share of the elderly based on different assumptions, Slovenia, 2005-2050 104 Table 63: Effects of ageing on public fi nances, Slovenia, 2005 and projections for the 2010-2050 period 105 Table 64: Total expenditure on health care, Slovenia, 1997-2003 107 Social Overview 2006 List of Figures Figure 1: Figure 2: Figure 3: Figure 4: Figure 5: Figure 6: Figure 7: Figure 8: Figure 9: Figure 10: Figure 11: Figure 12: Figure 13: Figure 14: Figure 15: Figure 16: Figure 17: Figure 18: Figure 19: Figure 20: Figure 21: Figure 22: Figure 23: Figure 24: Figure 25: Figure 26: Figure 27: Figure 28: Figure 29: Figure 30: Figure 31: Figure 32: Figure 33: Figure 34: Figure 35: Figure 36: Figure 37a: Figure 37b: Figure 38: Figure 39: Figure 40: Gross wages per employee in the private sector of the EU25, 2002, by PPS (EU25=100) 20 Household consumption by purchasing power standard and shares of household expenditure on food by EU countries, 1999 25 Number of practising physicians and nurses per 100,000 inhabitants, Slovenia, EU and the US, 2003 28 Provision of medical personnel for adults aged 20 and over in the sector of general/family medicine by statistical regions, Slovenia, 2004 29 Total, public and private expenditure on health in Slovenia, EU countries and the USA, 2003 (as share of GDP in USD PPP per inhabitant) 30 Places announced and applications of Slovenian citizens for higher education study programmes in the first term, Slovenia, academic period 2001/02-2005/06 34 Total public expenditure on tertiary education as a share of GDP, selected countries, 2002 35 Share of private expenditure in total expenditure on tertiary education institutions, Slovenia, EU and the US, 2002 36 Share of private expenditure in total expenditure on education institutions by levels of education, Slovenia, 1995 and 2003 36 Structure by the tenure status, Slovenia, 1998 and 2002 38 Share of households with access to the Internet, EU25, 2005 40 Satisfaction with life, selected countries, 2002, average value, scale (‘0’ very unsatisfied, ‘10’ very satisfied) 50 Significance of work in the life of an individual, selected countries, 2002 51 Significance of leisure time in the life of an individual, selected countries, 2002 51 Assessment of health, share of answers ‘very good’ and ‘good’, selected countries, 2002 51 Assessment of the situation of the health care by country, selected countries, 2002 51 Trust in the national parliament, average estimate, selected countries, 2002 53 Trust in politicians, average estimate, selected countries, 2002 53 Trust in the police, average estimate, selected countries, 2002 53 Trust in the legal system, average estimate, selected countries, 2002 53 Trust in other people, average estimate, selected countries, 2002 54 Personal experience of criminality and feeling of safety, selected countries, 2002 54 Feelings of safety, sum total of answers ‘very safe’ and ‘safe’, selected countries, 2002 54 Perceptions of improvement trends, Slovenia, 1995-2005 period 55 Shares of the young (aged 0-14) and shares of the elderly (aged 65 or over) in the population of Slovenia, 1921-2042 61 Shares of the working age population (aged 15-64) in the total population Slovenia, 1921-2042 61 Age-specific activity rates for men, Slovenia, 1961-2002 Censuses 62 Age-specific activity rates for women, Slovenia, 1961-2002 Censuses 62 Total fertility rate, Slovenia, 1950-2004 62 Number of women in their reproductive age (aged 15-49), Slovenia, 1921-2042 64 Life expectancy at birth by gender, EU25, 2003 65 Share of foreigners, EU25, 2004 67 Age specific rates of internal migration by gender, Slovenia, 1982 and 2004 69 Projection of the total number of population by age groups, Slovenia, 2004-2050 70 Share of age groups in the total Slovenian population, projection 2004-2050 71 Growth index of population size, Slovenia, projection 2004-2050 71 Employment rates by individual age groups in 2004 and projections, men 71 Employment rates by individual age groups in 2004 and projections, women 71 Marriages and divorces per 1000 population, Slovenia (1960-2004), the EU15 and EU25 (2003) 78 Total marriage rates and total divorce rates, EU25 countries, 2003 79 Total fertility rate, the EU25, 2003 79 v vi Social Overview 2006 Figure 41: Shares of extra-marital births, Slovenia (1960-2005), the EU15 and EU25 (1960-2002) 80 Figure 42: Adults participating in education by gender, age, education and employment status, Slovenia, 1998 and 2004 92 Figure 43: The rate of visits in the basic health care per 1,000 women and men aged 65 and over, by cause, Slovenia, 2004 96 Figure 44: Visit rates in primary level of health care per 1,000 inhabitants by age groups, Slovenia, 2004 96 Figure 45: Visit rates in specialist outpatient clinics at the secondary and tertiary levels of health care per 1,000 inhabitants by age groups and gender, Slovenia, 2004 97 Figure 46: Average weighting for groups of com-parable cases by age groups and gender, Slovenia, 2005 97 Figure 47: Rate of hospitalisation due to injuries and intoxications per 1,000 inhabitants by age groups and gender, Slovenia, 2004 98 Figure 48: Real annual growth in public expenditure on health and GDP, selected countries, 1997–2003 107 Map 1: Registered unemployment rate, statistical regions, Slovenia, 2005 88 Social Overview 2006 vii Abbreviations / Acronyms CJMMK – Public Opinion and Mass Communications Research Centre DURS – Tax Administration of the Republic of Slovenia ESS – European Social Survey ESS – Employment Service of Slovenia EU – European Union GDI – Gender-related Development Index GDP – gross domestic product GEM – Gender Empowerment Measure HBS – Household Budget Survey HDI – Human Development Index HDR – Human Development Report HIIS - Health Insurance Institute of Slovenia IER – Institute for Economic Research ILO – International Labour Organisation IMAD – Institute of Macroeconomic Analysis and Development ISCED – International Standard Classification of Education IVZ – Institute of Public Health of the Republic of Slovenia ICD – International Classification of Diseases MNZ – Ministry of the Interior MOP – Ministry of the Environment and Spatial Planning OECD – Organisation for Economic Co-operation and Development OGRS – Official Gazette of the Republic of Slovenia p.c. – per capita p.p. – percentage points PPP – purchasing power parity PPS – purchasing power standard SA – Statistical Appendix SDS – Slovenia’s Development Strategy SIAE – Slovenian Institute for Adult Education SIT – Slovenian Tolar SJM – Slovenian Public Opinion SORS – Statistical Office of the Republic of Slovenia UN – United Nations UNDP – United Nations Development Programme ZPIZ – Pension and Disability Insurance Institute of Slovenia ZZZS – Health Insurance Institute of Slovenia WHO – World Health Organisation Country Abbreviations AT - Austria, BE – Belgium, CZ - Czech Republic, CY – Cyprus, DE – Germany, DK – Denmark, ES – Spain, EE – Estonia, GB – Great Britain, GR – Greece, FR – France, FI – Finland, HU – Hungary, IE – Ireland, IL – Israel, IT – Italy, LU – Luxembourg, LT – Lithuania, LV- Latvia, MT – Malta, NL – Netherlands, NO – Norway, PT – Portugal, PL – Poland, SE – Sweden, SL – Slovenia, SK – Slovakia, UK - United Kingdom, US – United States of America viii Social Overview 2006 Foreword The Social Overview was born out of the authors’ desire to look at the general situation and development in Slovenia from a different viewpoint than the predominantly economic perspective which characterises most of the IMAD’s reports. This kind of ‘social’ analysis is regarded as an indispensable complement (rather than an alternative) to economic analyses. By looking at the same phenomena from different viewpoints, we can ultimately combine the snapshots to form a complex picture of the overall welfare in Slovenia. The Social Overview therefore covers many areas also dealt with in the IMAD’s other projects (labour market and employment, financial implications of population ageing, household consumption and savings etc.), yet these topics are covered from a different perspective and within a different framework. Nevertheless, we did not allow ourselves to use the smaller availability of ‘hard’ social indicators (compared with economic ones) as an excuse for a more subjective or a less systematic analysis. The Overview provides abundant explanations of the applied analytical concepts, methodologies and the quality of available data. This is particularly important in view of the fact that plenty of relevant raw data for the study of social development are available in Slovenia; however they are collected by several independent institutions and remain mostly fragmented. We have therefore made an effort to clearly present the analytical toolkit applied in the analysis and to back our arguments and conclusions firmly with the underlying data. Wherever we might have ventured some more thought-provoking or hypothetical reasoning, intended mainly to encourage further debate and research on these issues, this is clearly indicated in the text. The project’s main aim is to draw an analytical portrait of Slovenian society, the climate and conditions that prevail in it, along with the medium- and long-term development trends that affect social cohesion. The report is systematically structured along several major social concepts, such as social cohesion and social exclusion, social capital and trust, social welfare, quality of life, and others. These concepts are nowadays broadly used in scientific and research contexts as well as in political discourse and popular language and consequently tend to have overlapping and sometimes contesting meanings. For the sake of clarity, the Social Overview is therefore prefaced with our own agreed definitions of these terms which are by no means meant as standards for any other purposes than the scope of this analysis. However, we do hope that the framing of the analysis within the few well-known and clearly defined concepts that can be backed by sufficient data will allow us to evaluate future changes in subsequent editions of the Social Overview. For example, the next issue could look at the effects of the economic and social reform currently underway on the social structure and development of Slovenian society, which is presently one of the most disputed issues among supporters of the reforms and the sceptics. In that regard, two of the more ‘technical’ characteristics of our new analysis deserve to be mentioned. First, the Social Overview is a monograph rather than a periodical, despite its systematic and, hopefully, ‘reusable’ analytical framework described above. The reason is that the Overview, while planned to be prepared every two or three years, does not have a fixed publication schedule. In addition to the regular topics, each issue will feature a special analytical topic, focusing on one critical element or challenge concerning the social aspects of development. Inevitably, the selection of these special topics will be to some extent subjective but it will not necessarily render it less relevant for social development. Second, the Social Overview is not an official national report subject to government review and approval but is rather an independent work of the IMAD’s in-house experts and external collaborators. Of course, this is not exceptional since most of the IMAD’s analytical and methodological analyses are produced independently and intended to be used by decision-makers, researchers and the general public as they see fit. What are the main topics of the Social Overview? A detailed overview of the analysed topics and main findings is set out in the Executive Summary below. Here we would like to just briefly highlight some important new topics that have Social Overview 2006 ix hitherto not been analysed by the IMAD or have been analysed differently and often on a more limited scale. Many of these topics, intended to become regular features of the Social Overview, examine the living conditions in Slovenia; in other words, they show how Slovenians live. In analysing the social stratification we have defined four income brackets which, in our view, allow a satisfactory insight into the Slovenian social strata and have used these income brackets to analyse data on household income and expenditure. A large amount of data, in itself compelling for both the general public and researchers, has been analysed against a single coherent conceptual framework bringing together the notions of social cohesion, social capital and satisfaction with life. We have made an attempt at a systematic definition of access to those goods and services that are critical to the well-being of people and whose availability is also a matter of public interest and have taken the first steps towards a more systematic analysis of this important issue, for which available data sources are scarce. In short, our analysis attempts to take into consideration a wide range of elements that, in our view, crucially determine the quality of living and satisfaction with life. In addition to these main themes, the special topic in the first Social Overview – the long-living society – brings another important issue onto Slovenia’s public debate agenda on social development. We discuss the challenges and opportunities that society’s ageing, a fact which has been projected for a long time yet overlooked in policies, poses not only to social security systems but also to the increasingly (over)burdened support and interpersonal networks that can break under excessive load and expectations. Ageing is the result of the combined effect of improved living conditions (reflected in higher life expectancy) and declining birth rates. Almost without exception, European countries have responded in similar ways to this phenomenon. They have been examining, testing and/or implementing policies for the elderly (retired people, those older than 65 years or elderly employees) while also re-examining and revising their national youth policies. In Slovenia, discussions about the ageing of the population often focus on its implications for public spending, while the debate on related intergenerational conflicts concentrates on the redistribution aspects of the process. The preference to use the term ‘long-living society’ rather than ‘population ageing’ in this report indicates that our analysis also seeks to encompass the broader and more positive dimensions of the process. After all, population ageing essentially means that today people live longer than they used to. This is good and adds to people’s well-being and quality of living – provided that they can live decently and have the possibility to choose their lifestyle, of course. This is analysed in more detail in the chapters on the health and income status of the elderly. However, the quality of living of the elderly does not depend solely on the pension and health systems but also on availability of long-term care, opportunities and incentives for activity and education, adequate working conditions and society’s attitudes to ageing and the elderly, including their social inclusion. All these areas are levers through which longevity is changing the social structure and the interpersonal relations within society. It is also posing significant challenges to those governing our societies and to all of us who live in them. Yet, studying the long-living society does not only involve the position of the elderly. Quite the contrary: a society in which people live longer can sustain its vitality and development dynamics only if it is continually renewed by young people. Therefore, we have paid considerable attention to the changing family and its adjustment to new social matrix and the factors and circumstances that affect young people’s decisions about having their own families and children. Population trends and prospects are increasingly becoming a major issue of concern. The current demographic situation and trends may hamper social development or require radical changes in the development paradigm. However, in conducting analyses and more so in shaping policies in this area we should never forget that the number and structure of the population are the result of individuals’ independent actions and decisions and a reflection of the conditions they live in. People’s personal decisions, while made in a social and value-based context, are still autonomous. We hope that the approach set out above has enabled us to arrive at a coherent picture of that aspect of Slovenian society usually termed ‘social development’. Our work confirms that the Slovenian transition, in comparison with other countries, was carried out in a socially sustainable way and that Slovenia is ranked high among EU countries according to a number of indicators. What is perhaps new in this regard is that people are also quite aware of it as the shares of positive answers in surveys have risen despite the proverbial Slovenian criticism and dissatisfaction. At the same time, this approach also allows us to identify the weaknesses and to highlight critical areas. Some of them, e.g. the high levels of social and labour market exclusion of vulnerable population groups and the limited access of certain population groups to public services, can easily be improved by more systematic and better targeted activities of public-policy makers in these areas. On the other hand, issues such as the extremely low levels of trust and social capital, the unfriendly working conditions for both young people who want to start a family and the elderly wishing to remain active, the traditional division of family work and the low birth rates, will also require a change in the prevailing attitudes and values that affect the actions of various social players and individuals. In these areas, the government’s direct measures alone cannot achieve ground-breaking changes; they might actually even trigger the opposite effects from those desired. Nevertheless, these issues should by no means be brushed aside towards the periphery of our attention. x Social Overview 2006 The Social Overview is not the IMAD’s first analysis of social development. In the past, the four Human Development Reports it published attracted considerable public attention. The experience with these reports shows that the public is eager for studies providing an analysis of other than just economic aspects of welfare and development. The decision to discontinue these reports was mainly related to the cessation of funding previously provided by the United Nations Development Programme (due to Slovenia’s high development level) and the desire to overcome the limitations of UNDP’s standard format. The Human Development Reports certainly played an invaluable role in channelling the public and political focus onto some crucial development issues and developing the IMAD’s capacity to conduct social analysis. We hope that the Social Overview will perform a similar ‘social role’ by providing a comprehensive insight into Slovenia’s social development and engaging an even larger expert crew in its preparation. Finally, allow us to express our sincere thanks to all the people who contributed to this study. First, we would like to thank the authors of individual chapters from the IMAD and other research institutions. Members of the editorial and expert boards were indispensable in designing the concept of the Overview and directing the overall work, not to mention their ‘moral support’ to the new project. We should also not forget to thank the reliable technical team that enabled us to publish the publication in Slovenian and English. The names of all these colleagues are listed on the front page. Among the various contributing institutions we would like to single out the Statistical Office of the Republic of Slovenia, whose data and valuable clarifications facilitated our work and our thoughts. The Social Overview in Slovenian was published around that time of the year when people like to offer good wishes for the coming year to each other. Interestingly, these wishes usually emphasise health and personal happiness rather than material prosperity alone. The Social Overview confirms that these values and goals are very important to people. If anyone wanted to extend and reinforce their New Year’s or Christmas card wishes with our findings, they might add something like the following to their messages: ‘May you always have sufficient income sources, adequate education, a good and safe job and social security, firm support networks and good health; may you always feel autonomous, respected and esteemed at work etc’. This is how Slovenia could also hope for satisfied and happy citizens, a supportive and trustful environment, and high values of significant development indicators. These wishes are fully shared by Jana S. Javornik, Editor in Chief and Janez Šušteršič, Director Executive Summary The distribution of the Slovenian population into four income brackets shows that Slovenia’s socio-economic stratification underwent positive changes in 1998-2002. It confirms that inequality and poverty gaps narrowed, which is also supported by other indicators (the at risk of poverty rate, the Gini coefficient, the 80/20 quintile share ratio). This positive shift is reflected in both data on income growth across income brackets (income per person rose on average by a real 14.7%; the biggest increase was recorded in the low-income bracket and the smallest in the high-income bracket) and in data on the distribution of people across income brackets (there was an increase in the share of persons who can be classified in the middle income bracket). Income gaps narrowed and some people moved upwards from low and lower-middle brackets. There are no data or studies regarding the effect of property ownership on socio-economic stratification. In 1998-2002, the structure of both household income and household expenditure changed. Income from employment represented a significantly lower share of the income of the low-income bracket (24.8% in 2002) compared to the average share (59.1%) or the share in the high-income bracket (70.7%). The opposite is true of pensions. In 1998-2002, the percentage of pensions in the total income of the low-income bracket increased while the proportion of income from employment fell. The changes in the expenditure structure (and the increase in the real value of income) similarly reflect the improved income position and different way of life of Slovenian households. The share of expenditure on food decreased in all four income brackets (by 2.2 p.p.), as did the share of expenditure on transport (by 0.2 p.p.). Increases were observed in the shares of expenditure on communications (by 2.1 p.p.), housing, and recreation and culture (by 1.2 p.p. each). Households spent 19.3% of their income on housing and utilities (housing, water, heating, electricity), which is slightly less than in the EU25 (21.4%). The consumption pattern of Slovenian households turns out to be similar to that of Western European EU countries. Income from employment was the main income source of households in this period. In 2002, it amounted to 59.1% of the current monetary income, having decreased slightly from 1998 when it totalled 59.7% of the total sources. In 1998-2005, wages rose at an average real annual rate of 2.2%. Over two-thirds of employees earned below-average incomes; this share remained practically unchanged in the 1998-2002 period. The share of employees with an income of less than 40% of the average wage (the minimum wage introduced in 1995 totalled 40% of the average wage) has been falling since 1995, when it peaked at 7.4%, to total just 3.7% in 2002. Social Overview 2006 1 The second most important source of households’ current income was cash benefits from public sources (i.e. budgets and social insurance). In 2005, there were 70 different cash benefits. In 1993-2004, seven benefits were abolished and thirteen new ones were introduced, while the number of benefit claimants continued to rise steadily. Hence the number of cash benefits disbursed in this period rose by 25%, i.e. by 2.1% on average per year, while expenditure on benefits rose at an average annual rate of 4.0%. Legislative changes had an important upward effect on the number of benefits. Pensioners represented the largest share in the total number of cash benefits (43.2%) in 2004, followed by parents (20.7%). Pensioners were also allocated the highest share (49.6%) of funds. According to data from the household budget survey, the income situation of most households improved in 1998-2002. Disregarding those who managed with their income ‘with only some difficulty’, 31.9% of people managed with it ‘with difficulty’. Their share was the highest in the low-income bracket (72.8%), where it also exclusively rose slightly from 1998. According to the SJM (2005), 18.1% of people over-borrowed in 2004 (frequently or occasionally), 36% people paid off their loans easily and 42% did not borrow at all. In the lower income brackets, the share of the over-indebted was even higher; for these people, borrowing is usually synonymous with over-borrowing. Public opinion polls similarly show that the satisfaction of households with their material situation increased in 1995-2005, notably after 2000. In 2005, 50.3% of people were satisfied with their income situation, while 14.8% were dissatisfied. The share of people satisfied with their material situation rose in 1995-2005 by 21.3 p.p. Conversely, the share of those dissatisfied shrank in the same period by 15.7 p.p. The at risk of poverty rate has fallen in recent years. Calculated by including income in kind, the at risk of poverty rate stood at 10% in 2003, 1.7 p.p. less than the rate excluding income in kind. Data for 2003 show that income in kind reduced the risk of poverty by an average of 2 p.p. compared to 1998 (except for the self-employed, where income in kind reduced the at risk of poverty rate by 8.4 p.p. in 1998-2003). Slovenia has the second lowest at risk of poverty rate in the EU25 (second only to the Czech Republic with 8%; the EU25 average totals 15%) and is followed by Luxembourg and Finland (both 11%) and Hungary and the Netherlands (12%). Social transfers contribute significantly to the lowering of poverty risk. Excluding social transfers (and with pensions included in income), the at risk of poverty rate in Slovenia 2 Social Overview 2006 would have been 16.2% (26% in the EU25). Pensions significantly reduce the risk of poverty. Without any social transfers (not even pensions), the at risk of poverty rate would have amounted to 36.9% in 2003. Among all categories and socio-economic groups, the highest at risk of poverty rate was recorded in the group of people aged 65 and over and living alone (39.9%), followed by unemployed men (38.8%). The female at risk of poverty rate was higher than the male one in 1998-2003 (11.4% over 8.6% in 2003). If we look at the household type, single households ran the highest risk of poverty. A breakdown by housing relationship reveals the highest risk of poverty rate for tenants (23.5% in 2003). Slovenians do not perceive themselves as socially excluded and usually blame external factors for the fact that some people in society live in deprivation. There has been very little quantitative empirical research of social exclusion (defined as an accumulation of deprivation at distributional and relational dimensions) undertaken in Slovenia, mainly due to a lack of appropriate databases. Interviews with people from vulnerable groups (Trbanc, 2003) showed a high level of reproduction of (family) patterns that lead to vulnerability. The situation of the analysed vulnerable groups in terms of employment and inclusion in the labour market is weak (very few of them are employed, many are long-term unemployed and inactive, they often do occasional and undeclared work). In Slovenia 5.6% of the population feel socially excluded (the lowest percentage in the EU25, where the average is 12.4%). The feeling of social exclusion is strongly linked to the experience of being unemployed and to serious financial difficulties, and even more to multiple deprivation. Respondents largely associate social exclusion with injustice in society rather than the laziness of the socially excluded. Friends are the main source of support for people in Slovenia, followed by family members and close relatives. When people face problems and difficulties, they look for help and support in other people. Slovenian studies of support networks (Novak et al., 2004) show there are no significant differences in the structure of network members in the Slovenian population; the main differences occur in the size of individual network types. A person’s average support network includes 6.5 people. The size of the network increases in proportion to a person’s education. The number of network members decreases with the complexity of the support network (social networks are the widest and financial support networks the narrowest). Friends are the most important source of support, family members and close relatives come second in importance. Support networks are family-oriented. As a result, families, particularly their female members, are overburdened. Support people are also vulnerable, which is most obvious in the support networks of poor people, who generally have the smallest support networks. An established complementary institutional (formal) support system therefore provides the best protection against the disintegration of support networks. The complementarity between both types of support guarantees the optimum effectiveness of support networks. Slovenia has the fourth lowest share of adults (aged 18-59) living in jobless households in the EU25 (6.7% in 2005; EU25 average: 10.2%). The employment rate (of the population aged 15-64) rose in 1999-2005 (by 3.8 p.p.). It totalled 66% in 2005, more than the EU25 average. The ILO unemployment rate stood at 6.5% in 2005, which is below the EU25 average (8.7%). Slovenia’s long-term unemployment rate ranks the country 11th in the EU25 (3.1% in 2005; EU25: 3.9%). In 2000-2005, the registered unemployment rate also fell in most Slovenia’s (statistical) regions, as did the regional disparities in registered unemployment. Nevertheless, there was no substantial improvement in the key labour market indicators: the share of the long-term unemployed remains high, the employment rate of the elderly is still low and the unemployment rate of young people persists at a relatively high level. Access to public goods and services of general interest is improving. Services of general interest are an important mechanism for ensuring fundamental human rights and promoting social inclusion. The importance of services of general interest calls for their regulation because market mechanisms cannot guarantee that they are provided to everyone and in the required form. In practice, however, access to these services is still hampered by the inadequate network of services and programmes (insufficient capacity and unequal regional distribution), problems with financing and often a lack of information about these services. This is a particularly important fact for policy-makers since the accessibility of these services significantly determines the quality of life and the social inclusion of the population. The share of children attending kindergartens is rising, as is the share of young people enrolled in the education system. The number of tertiary-level students is growing as well. According to this indicator, Slovenia has already reached the level of EU countries with the highest ratios of students to the total population aged 20-29 (in Slovenia 38.9% in 2005 and 16.4% in 1995) and per 1,000 population (57.4% over 24.1%). Total public expenditure on education is comparatively fairly high (6.0% of GDP in 2003). More is earmarked than in other European countries for scholarships and other social benefits for students. Slovenians are quite satisfied with the education system; they trust education institutions and think that there are good opportunities for education. Compared with some other European countries, Slovenia has fewer staff and other healthcare capacities. Slovenia’s gap with the EU average according to the number of practising physicians per 100,000 inhabitants has widened. Slovenia is also ranked among the bottom half of the EU25 countries according to the number of practising dentists per 100,000 inhabitants. Although there is a shortage of nurses Social Overview 2006 3 and nursing assistants in some healthcare fields, Slovenia is ranked among the top half in the EU25 in terms of the number of these staff per 100,000 inhabitants. Slovenia also lags behind in the number of hospital beds: in 2004 we had 479.9 beds per 100,000 inhabitants (495.5 in 2003 and 574.1 in 1995). Waiting periods have been a pressing problem for a quite while. The total expenditure on healthcare as a share of GDP is above the EU average, however, Slovenia lags way behind in per capita expenditure on health. The share of public expenditure in the structure of total expenditure on health fell from 1997 to 2003 (from 79.2% to 76%), while the share of private expenditure rose from 20.8% to 23.7% in this period. Nevertheless, private expenditure on health is still low compared with other EU countries, and almost 60% of private funds come from voluntary health insurance. People rank the health system with a score of 4.75 on a 0-10 scale; older and less educated citizens are more satisfied with it. The accessibility of social services is reduced by the insufficient network of services and programmes and problems with funding, and potential claimants are often not properly informed about these services. The network of centres for social work, specialised social institutions for adults and institutions for children with special needs has not been expanded in a while. Networks of protection and training centres for adults with physical and mental problems and homes for the elderly have been enlarged significantly in the last few years, both in terms of capacity and the number of units. The supply of services began to grow notably after 2000 when private providers and nongovernmental organisations were included in the network. The rapidly growing need for long-term care is linked to the rising life expectancy, the growing number of the elderly and the reduced capability of families to take care of old people. According to the number of available placements in institutional care for people aged over 65 (4.4 per 100 inhabitants), Slovenia is roughly on a par with the more advanced EU countries. However, it does lag behind according to the scope of home care and other non-institutional types of assistance, which is provided to less than 2% of the population aged 65 and over. Waiting lists for homes for the elderly may vary due to differences in regional accessibility. The total expenditure on long-term care totalled 1.13% of GDP in 2004 (public expenditure 0.88% of GDP, private expenditure 0.25% of GDP). 60% thereof was allocated to long-term healthcare while 40% was spent on long-term social care services. Slovenia is comparable to the EU15 in terms of public expenditure whereas private expenditure accounts for less than a quarter of the total expenditure on long-term care in Slovenia. Providing adequate and affordable housing for all citizens remains a policy challenge. Almost 85% of the population live in their own dwellings, while others are either users or tenants. According to law, the state must create opportunities for citizens to obtain proper housing. Access to housing for socially vulnerable groups is provided through a council housing network and subsidised rent payments. Ever since 1995, the available new non-profit council housing has been grossly insufficient and failed to meet both the demand and the annual plans. The new Housing Act (adopted in 2003) slightly improved the subsidised rent system, yet these subsidies remain beyond the reach of many because only the tenants of non-profit housing qualify. Municipalities decide on the number of non-profit council flats available for rent and define the allocation criteria. The share of housing without basic utilities is decreasing. Nevertheless, 16.4% of households still had no central heating in 2002, 5.2% of dwellings had no bathroom facilities and 4.8% were without a toilet. Poorly equipped dwellings are more common in non-urban areas and mostly occupied by tenants or lodgers. The rate of Internet use in Slovenia is fairly high but we lag behind in the number of households with broadband Internet access. Data show that Slovenian households are the best equipped with the Internet among the new EU members. The main reasons for households not having Internet access include a lack of interest or need, excessive costs of access and equipment, or not having the skills required to use the Internet. In 2005, only 19% of Slovenian households had broadband Internet access, which is less than the averages of the EU25 (23%) and EU15 (25%). Satisfaction with life and trust in political institutions and people are relatively low in Slovenia. The social status of respondents defines their perspective from which they evaluate developments in society. Conversely, social developments are mirrored in people’s seemingly private realms, such as the feeling of happiness in life or a person’s health. In general, people in Slovenia are more satisfied with life when they feel healthy, are married (or live with a steady partner) and have a higher (self-perceived) social status. Gender- and age-related differences regarding satisfaction with life are relatively small. Analyses show that satisfaction also increasingly depends on work (paid employment), the quality of work and autonomy at work. People have strong trust in the family and education institutions and notably low trust in political parties, the parliament and the church and clergy. Slovenians also tend not to trust other people. Slovenia belongs to the group of countries with a low level of social capital; the social environment is perceived as largely egoistic and unsupportive. Nevertheless, Slovenians look to the future with moderate optimism and perceive changes in living standards and conditions as positive, albeit to a lesser degree and in lower percentages than we might expect given the statistically measured changes. According to public opinion polls, Slovenia shows the fewest features of a transition country of all the post-socialist countries included in the survey. Slovenia’s pattern partly overlaps with that of Western European countries, particularly regarding the objectively and subjectively perceived material standards of households. Satisfaction perceptions, especially at the personal level, are higher 4 Social Overview 2006 than in other post-socialist countries. Also high is the feeling of personal security and some indicators of general living standards (e.g. Internet access). Slovenia also scores higher than other transition countries with regard to trust and frequency of socialising. On the other hand, it has low values of satisfaction, authority and autonomy at work, as well as the influence of trade unions. Slovenia’s population is ageing. The country’s population totalled two million in the middle of 2005. The average age of people was 40.4 years in 2005. The ratio of the working-age to the old population is shifting in favour of the latter. Population ageing is the result of falling fertility rates, rising life expectancy and low net migration. In Slovenia, the total fertility rate has been declining for the last 100 years and is currently one of the lowest in the EU. Following the stagnation in 1993-2003, it rose to 1.26 in 2005. Lower fertility is related to numerous changes arising from living conditions. These values are expected to increase slightly in future, however they will remain below the level required for a positive natural increase. Few Slovenian women remain childless, but the more they are educated and the more demanding jobs they have, the fewer children they tend to give birth to. Fertility rates are lower in urban areas than elsewhere. With regard to life expectancy, Slovenia is ranked in the middle on a scale of European countries and in the lower half among the EU25; the female rate scores slightly better than the male one. More and more people are living to see the age of 65 (887 women and 748 men per 1,000 live-born). Slovenians, particularly men, therefore still have room to extend their life expectancy. According to the baseline scenario (projection), life expectancy should rise to 79.8 years for men and 85.2 years for women by 2050. Net migration in Slovenia is low, as is the share of foreigners. In the middle of 2005 there were 2.5% of foreigners living in Slovenia (the highest shares of foreigners – around 22% – are recorded in small European countries: Andorra, Luxembourg, Liechtenstein and Switzerland). The level of net migration in Slovenia has been changing according to economic development and employment opportunities; the strongest migration flows have been recorded between Slovenia and other countries that emerged in the territory of former Yugoslavia. Citizens from these countries accounted for 72% of all immigrants to Slovenia in 2004. People usually migrate when they are young, in search of work and when trying to start a family. However, as the entry to employment and consequently the starting of a family is moving further away to a later age, the average age of migrants is also rising slowly but steadily. In 1982-2004 the average age of people who moved within Slovenia rose from 25 to 30 years. The future trends in emigration and immigration flows remain open to speculation. The family is similarly undergoing multiple changes. The household and the family are facing massive changes due to the prolonged life cycle stages (both youth and old age). Abandoning traditional paths to maturity is one of the characteristic changes taking place today. Parenthood, one of the main signs of being an adult, is being shifted towards the age of 30 or even abandoned. Data show that, although young people appreciate having a partner and would like to have a family of their own, they defer parenthood (which is characterised by a ‘normative complex of responsible parenthood’) further into the future and continue to live in their primary families longer and longer. There is also greater variety in the types of existing family units: the number of nuclear families is decreasing while reorganised and one-parent families (where the mother-child/ren combination been falling (in 2005 there were 2.9 marriages per 1,000 inhabitants) while the age at first marriage rose (from 22.5 years in 1980 to 28.2 years in 2005), as did the age of mothers at first childbirth, and the number of divorces. At the same time, the number of children born out of wedlock is rising. In 1954, around one-tenth of children were born out of wedlock, while in 2005 there were already 46.7% of such children. At the beginning, these structural changes were regarded as signalling a crisis in the family, however nowadays they are viewed as indicators of the family’s successful adaptation to the changed social conditions. Parenthood is a great responsibility and young people tend to postpone the decision to start a family until all the preconditions (having a job, having a home etc.) are fulfilled. This process is called ‘the unbreakable chain’ (Ule and Kuhar, 2002). Young people think that the main condition for starting a family is the feeling that they are mature enough for such a demanding role as parenthood. No significant changes were observed in the last ten years in people’s opinions on family life. Most respondents still think that watching children grow up is the biggest happiness in life and that life without children is empty. Nevertheless, there are also no signs of a more equal division of household work between the partners. The ‘traditionally’ female chores remain a woman’s ‘duty’. Women aged 20-74 spend five hours a day doing household work, 2.5-times more than men, who generally take care of small repairs around the house. Women spend 88% of their private time (time off work) on household work, men only 49%. Neither women nor men think that this situation is fair, but it nevertheless causes no serious problems between the partners, which indicates that women have ‘successfully’ internalised the unequal division of work. These figures are significant since studies confirm that a woman’s decision to have children strongly depends on the participation of men in family life. The decision to have children is also linked to the possibility of a successful reconciliation of work and family obligations. Public opinion poll data show that balancing work and family life is a major problem, particularly for women. As many as half of the respondents report that family life is stressful, which is much less the case with men. The act of balancing is difficult because each sphere is time-consuming. Work often seems overly exhausting for higher-skilled respondents; conversely, lower-skilled interviewees find domestic life more tiring. The ageing of the population and family members often strongly affects Social Overview 2006 5 the intergenerational relationships within the family. The need for mutual help and co-operation is rising but it is also creating new problems, particularly for female family members who are frequently overburdened. Slovenia is lagging behind the European average in employment rates of both the elderly (55-64 years) and the young. The employment of these two groups, particularly the elderly, coupled with long-term unemployment that is rising in proportion to age, is a serious development problem. Slovenia has room for improvement in the employment rates of the elderly and the young. In order to increase the employment rate of young people (aged 15-24) we must reduce youth unemployment. The employment rate of the elderly should be raised by increasing the incentives for longer working lives and through active ageing strategies that would include measures aimed at preventing chronic illnesses and promoting lifelong learning. Participation in education is higher among younger employees with a higher level of education compared with older and less-skilled workers. A survey conducted in 2004 by the Slovenian Institute for Adult Education (SIAE) on the literacy of adults and their participation in education shows that the percentage of adults participating in education totalled 37% in 2004 and was higher than in 1998. Adult participation in education is higher among men, high-skilled people, employees and young people. In 2004, people with a higher education had a six-times higher participation rate in education than people with a lower education in 2004, while the participation of people aged 20-49 was twice as high as the participation of 50-65 year-olds. The elderly are the population group with the highest expected rate of chronic diseases and conditions. They visit doctors more often, have higher hospitalisation rates, and use more medicines and medical devices. They are mostly afflicted with chronic illnesses, especially cardiovascular diseases, neoplasms and injuries. These diseases are also the main causes of death, reduced capacity and hospitalisation, while their treatment requires the most medical staff, material and financial resources. Oral health also deteriorates strongly with age – the elderly develop diseases of dental and paradental tissues and lose their teeth. They receive less preventive care than other groups and the health care system generally takes relatively poor care of their specific needs. Elderly people face social exclusion and marginalisation. The third generation suffers from low social esteem and its potential is often overlooked and neglected. After the age of 65, people’s support networks shrink and the sources of support become increasingly variable. Elderly women living on their own have the weakest support systems. More than half of elderly people live alone, usually in rented flats of a size smaller than 50 square metres. They are mostly taken care of by family members and relatives, which means that they are ‘dependently independent’. The strain on informal support networks, particularly on women, is high. The percentage of the elderly in need of long-term care has been rising sharply; in 2004 there were an estimated 58,000 such people in Slovenia, which is 19% of the total population aged 65 and over. The demand and supply of individual services are at variance. So far Slovenia has mainly strengthened its institutional care while neglecting home care. The latter only began to develop in the late 1990s. The elderly are also more often affected by poverty; in 2003, almost twice as many elderly people (19.2%) than the average (10.0%) lived below the poverty line. Elderly people living in dwellings they do not own, and especially elderly women, are at high risk of poverty: 22.9% of elderly women and 11.1% of men lived below the poverty threshold in 2003. Projections suggest that the shares of Slovenians aged 65 and over and 85 and over will respectively double and treble by 2050. This will have a significant upward effect on expenditure on pensions, healthcare, long-term care and other costs related to old age and ageing. It is therefore vital for future development that we find an answer to the question of how to raise the activity rates of people aged 55 and over. Conclusion The 1990s were a period of profound economic and social changes in Slovenia. These changes had direct and indirect impacts on the living conditions of Slovenians and the quality of their lives. In the face of perhaps different expectations, the analyses presented in the Social Overview portray a fairly positive picture of the country’s development, proving that Slovenia has managed to retain a relatively high quality of life through to the present day. Many development indicators are good or even very good, particularly when compared with other countries but also across time series. Perhaps contrary to expectations, the perceptions of Slovenians have also taken a positive turn. Although generally lower than the ‘objective’ indicators, people’s subjective perceptions nevertheless convey moderate optimism, reflecting the Slovenian public image of social change. People are, for instance, more satisfied with the education system than with the healthcare and have greater trust in informal than formal institutions. Despite the relatively positive development trends, however, some areas remain critical and call for further action. Although Slovenia’s at risk of poverty rate is the second lowest in the EU25, poverty still strongly affects the elderly (especially women) living alone, and unemployed men. Long-term unemployment is the second biggest development problem that correlates strongly with old age and low education. The participation of the low-skilled and the elderly in education and training is still low. The Pomurska, Podravska and Zasavska regions continue to record high registered unemployment rates. Access to services and goods is still unequal due to insufficient resources, poor re- 6 Social Overview 2006 gional distribution and inadequate funding. Demand is often greater than supply. The two most obvious examples are waiting times in healthcare and differences in institutional care and home care: people in institutions have better access to health and social care than those who are taken care of at home. Providing adequate and especially affordable housing remains a policy challenge. The available new council housing has so far grossly failed to meet demand. Trust in other people and trust in institutions (particularly political ones) is among the lowest in Slovenia. Social support networks, which are an important element of the living standard and the quality of living, are strong yet family-oriented and overstrained. Poor people have low family support and also much weaker support networks in general than the population as a whole. Although families are overburdened there are still no significant signs of any greater equality between the partners. Moreover, the ‘traditionally’ female chores largely remain within the ‘competence’ of women. Informal family care for the elderly is an important part of family life, yet it mostly remains a ‘typically’ female duty which makes it even more difficult for women to reconcile their working and family obligations. Slovenia’s social capital is low, but the mechanisms that would enable Slovenia to increase its social capital in a society marked by a half-century history of socialism within the Central European cultural and political context have yet to be devised. Social Overview 2006 7 Introduction The Social Overview depicts an analytical portrait of the development, climate and conditions of Slovenian society along with the development trends that affect social cohesion. We explain the underlying concepts of the analysis in the Conceptual Framework, which is followed by two extensive analytical chapters and a statistical appendix. The selected indicators are based on statistical data collected by the national Statistical Office, Eurostat, the national Institute of Public Health, the Slovenian Institute for Adult Education, the calculations of colleagues from the Institute for Economic Research and on public opinion poll data from the Public Opinion and Mass Communications Research Centre at the Faculty of Social Sciences. The chapter entitled Conceptual Framework introduces the key concepts that were used in the Social Overview as the underlying terminological tools and guidelines. In accordance with the purpose and aim of the project, social cohesion was selected from among the many social welfare concepts as the leading principle of the analysis, and is defined and operationalised in this chapter. The first chapter (The Way We Live) is to become a regular feature of the Social Overview. It presents the objective picture and people’s subjective perceptions of the living conditions in Slovenia. The chapter comprises nine interrelated sections which, each from their own perspective, shed light on the living conditions of the Slovenian population and the changes in these conditions, mostly covering the period after 1995. We analyse the living conditions of the Slovenian population as a whole. In addition, we observe selected trends in the living conditions separately for four income brackets (low, lower-middle, upper-middle and high) that were defined for this project on the basis of Household Budget Survey data (HBS 1998-2002). We examine the factors that in our view significantly determine the quality of living and satisfaction with life: income, employment, access to public services and goods, poverty, support networks and social exclusion of the Slovenian population and, finally, the pulse of current public opinion based on people’s subjective perceptions of the living conditions in Slovenia. The second chapter (Slovenia – A Long-living Society) features a thematic analysis of the current development trends and challenges. The first Social Overview takes a close look at ageing and its implications. This chapter highlights the main development challenges, opportunities and problems arising from the ageing of society or escalating because of it. The chapter consists of eight interrelated sections. It promulgates a number of important arguments, which underpin the policies that serve as the basis for defining the key development challenges. In the last section, it introduces important policy guidelines and measures. Relevant data that enable the study of social development are abundant in Slovenia. However, these data are collected by various institutions and remain largely fragmented. The indicators for topics included in the Social Overview that were not used in the text are included in the Statistical Appendix. The Appendix provides a comprehensive compendium of information covering all dimensions of social development. It was compiled in co-operation with colleagues from the national Statistical Office and the national Institute of Public Health. The data presented were collected and prepared by the end of June 2006. Social Overview 2006 Conceptual Framework The dynamics and complexity of economic and social changes in modern societies reinforce social uncertainty and individual risks. The course of life is becoming increasingly unpredictable and unstable. Society is shifting from a vertically structured (i.e. class-based society with groups at the top and groups at the bottom) to an increasingly horizontally structured one. Being either at the top or at the bottom of the structure matters less today than being at the centre – social groups that are central are engaged in social developments, whereas the marginal, excluded social groups are pushed to the edge of social happenings. Hence, not only the definitions and indicators of welfare but also the social context of studying welfare itself are undergoing a process of change. Welfare concepts are becoming increasingly vague and unspecific; the boundaries between individual concepts are more and more blurred. The conceptual inconsistencies also complicate and narrow the interpretation of these concepts. The renaissance of the sociological concepts used as the theoretical background to the Social Overview creates considerable conceptual noise and numerous linguistic quandaries. Social science offers several alternative approaches to the assessment and statistical measurement of welfare. According to Parsons (1995, in Mandič, 2005: 112), a problem must be ‘defined, structured, placed within certain limits and given a name’. These concepts provide a framework for the creation of knowledge and data and hence play the role of ‘social diagnosis’ (Bauman, 2001 in Mandič, 2005), thereby helping to manage social processes. Research and public policy are becoming ever more fused; it is increasingly clear that policies can label and interpret social phenomena in their own way. Public policies use a ‘welfare rhetoric’ of their own, in which not only what is said matters but also ‘what is left unsaid and surrounds the silence’ (Culpit, in Mandič, 2005:117). The concepts used as a terminology tool for analysing so- along two main lines: the scientific and political line1 on cial phenomena and classifying the analysed objects mainly one hand and an administrative-statistical line2 on the other; depend on the identification and articulation of social phe- these two lines are gradually becoming more and more nomena in time and space, i.e. in a concrete social context intertwined and mixed. matters. The sweeping social changes that have taken place during the last two decades have been reflected in the inva-Since the Social Overview portrays Slovenian society, sion of complex and often overlapping concepts in political the climate and the living conditions in it, we were faced discourse. Among them, the key conceptions applied in with the dilemma of how to match the existing, ‘available’ concepts with the specific use of the applied and presented concepts; these are not only intertwined but also overlapping. Following the aim of the project (i.e. to help formulate the Social Overview include social cohesion, social exclusion/inclusion, social capital, social networks etc. When social policy looked for labels to name the modern social phenomena relevant for development, it had several classic policies) we chose one of the welfare concepts – social sociological concepts at its disposal. However, being ‘torn cohesion – as the core underlying concept of our study (for out’ of their ‘primary context of social sciences’ (Novak, discussion, see Mandič, 2005 and Filipović, 2005). 2001) these concepts have been used rather arbitrarily in the political discourse. Mandič (2005), for instance, examining the concept of welfare, finds that the processes involved in Being aware that the term ‘social cohesion’ is used in shaping such concepts are multi-faceted and intertwined. several different ways, we have no intention of interfering The concepts of welfare and social issues are articulated with the conceptual discourse. For the sake of clarity of 1 In science, welfare is the object of study, while in politics it surfaces as the issue that wins support of relevant stakeholders to be placed onto the political agenda (Mandič, 2005: 126). 2 This line has had a signifi cant impact on European public policies. It comprises the large centrally-managed standardised databases that include a wide range of administrative and other statistics which can, among other things, be used in analysing – and thus defi ning – welfare. 8 Social Overview 2006 9 the presented findings and to avoid oversimplification, we provide a definition of social cohesion as operationalised in the Social Overview below. The concept of social cohesion is a sociological concept that has become prominent in European and national policy discourse over the last twenty years. However, there are significant discrepancies between the classic (sociological) conception of cohesion and the ‘new’ definition applied in modern political discourse. Durkheim, for example, construes social cohesion as the ties in society. Social cohesion is a process materialised at the micro level through feelings of bonding and common identity. Lockwood (1999) uses the term ‘social cohesion’ to describe the strength of primary and secondary networks at the micro and mezzo social levels, i.e. the strength of ties particularly in primary social relationships. Münch (2002) explains social cohesion in the context of social networks, although his definition of the term is not limited to social ties but extends to other dimensions (see Filipović, 2005). More modern definitions of social cohesion are much broader, which causes confusion in the cognitive field. In modern European political discourse, social cohesion and social exclusion converge into a common problem framework. Similarly, a complex and broad definition of social cohesion applied in the Social Overview was also offered by Forrest and Kearns (2001). They see social cohesion as comprising five components: (1) common values and civic culture; (2) social order and social control; (3) solidarity and reductions in social stratification; (4) social networks and social capital; and (5) place attachment and identity. The concept of social cohesion applied in the Social Overview has two dimensions: (1) ‘social exclusion’, including social inequality and stratification; and (2) ‘social capital’, including the aspects of social bonds and ties. Social exclusion and social capital are defined and conceived as two aspects of social cohesion. This concept seemed to be the most pragmatic, applicable and adjusted to the needs and availability of public statistics. Social exclusion As already mentioned, the concept of social cohesion is closely linked to the concept of social exclusion. The boundary between the two is particularly vague in political discourse, where these concepts are sometimes even used as synonyms (Filipović, 2005: 168). Having several different and overlapping meanings, the concept of social exclusion can readily be used (and abused) for political and ideological purposes. The approach to examining social exclusion focuses on the study of social inequality through social polarisation at the horizontal level, among those ‘inside’ and those ‘outside’, or those ‘in the centre’ and those ‘on the periphery’. The key characteristics and definitions of social exclusion can be summarised in four key points (see e.g. Room, 1995; Atkinson, 1998; Sen, 2000; Mayes et al., 2001; Muffels et al., 2002): 1. Social exclusion denotes the exclusion (or weak inclusion) of individuals or groups from (in) the systems of political, economic and social functioning of the societies they live in. The term comprises exclusion from access to and participation in institutions and resources, exclusion from the generally available opportunities and possibilities ensuring people’s economic and social security, living resources and living conditions. Social exclusion often goes hand in hand with people’s poor integration into interpersonal networks and their weak participation in society (e.g. political, cultural participation). 2. Social exclusion is a relational concept – it examines the inclusion/exclusion of individuals in relation to other individuals in society (similarly to social rights, which also have a relational character since the specific situations and living conditions are studied in relation to other members in a society). 3. Rather than describing a static situation, the term refers to the processes of exclusion in which various long-term deprivations and exclusions add up to create a downward spiral of risks. Specific situations of deprivation and exclusion are interdependent and lead to other, increasingly complex forms. Social exclusion is a multi-dimensional phenomenon. 4. The emphasis in studying social exclusion is on seeking and interpreting the reasons that trigger exclusion processes and explaining their interconnections. Sen (2000), for example, distinguishes between active and passive social exclusion. Active exclusion refers to deliberate legal or regulatory exclusion, for example when certain population groups are denied some of the rights and possibilities generally granted in society (e.g. restricting refugees’ or economic migrants’ entitlement to citizenship), which results in a number of other restrictions, exclusions and deprivations for these people. Passive exclusion, on the other hand, applies to exclusion and deprivation caused by economic and social processes in which there is no deliberate attempt to exclude (e.g. economic trends leading to unemployment etc.). In studying social exclusion, we are not merely interested in the extreme ends of the social dichotomy (included, excluded) but also in the process of exclusion itself, which is gradual and continuous. The social inclusion/exclusion dichotomy captures a horizontally polarised picture of society, with a majority of individuals taking part in the ‘usual ways’ of living on one hand, and a minority of individuals or groups who, for various reasons, remain excluded from or driven to the periphery of these prevailing life patterns and participation in the institutions of society, on the other. 10 Social Overview 2006 Since actual social exclusion (both from social resources, However, if poverty is defined along broader lines, as rela-institutions and social participation on one hand and from tive deprivation, it also has a multi-dimensional meaning interpersonal networks and relationships on the other) is including not only material but also non-material aspects an extreme situation, only marginal groups or categories and implications of deprivation (this is where poverty and of individuals, e.g. the homeless, drug addicts, prostitutes, social exclusion interface). illegal migrants etc., are really socially excluded. However, in order to understand the processes and risks of social ex- Social exclusion and poverty refer to different aspects of clusion, we need to focus on decreased social participation social phenomena (Room, 1995). The concept of poverty and on the accumulation of deprivations rather than on the focuses primarily on the distribution aspects (unequal distri-extreme ends of the spectrum. bution of disposable resources, unequal access to resources etc.), while social exclusion concentrates more on the rela-At the level of EU policies, the notion of social exclusion tional aspects (lack of social, economic, political participais closely associated with inadequate access to possibilities tion or inclusion; poor access to institutions through which and institutions of education and training, the unfavourable integration into society is effected). Preventing poverty position of individuals in the labour market and low income. means ensuring a less unequal (more ‘fair’) distribution of Such an approach is based on the underlying assumption resources, while preventing social exclusion amounts to that unemployment and lower social expenditure jeopardise ensuring social (and societal) participation (co-operation) social participation and integration, thereby putting people’s and integration into society’s ‘mainstream’. The concept social inclusion at risk. Unemployment and insufficient in- of social exclusion thus adds socio-psychological aspects come cause the accumulation of deprivations in other areas to the debate and research on poverty and links economic of life. It is therefore not surprising that the social inclusion and social deprivation with individual social participation policies in EU countries place considerable emphasis on and the stability of society (Böhnke, 2001). employment policies and the reintegration of unemployed and inactive people into working life. The multiple meanings and complexity of the concept of social exclusion (and the process of excluding) make the Moreover, the notion of social exclusion also overlaps with operationalisation and measurement of this phenomenon the concept of poverty, despite the significant differences difficult. Social science has developed a wide range of between the two conceptions. ‘Poverty’ is conceptually indicators to measure poverty and deprivation, whereas the entrenched in the Anglo-Saxon tradition yet it turned out measuring of social exclusion is less well developed. It is to be politically unacceptable for the Francophone coun- also difficult to construct satisfactory indicators of social tries. ‘Exclusion’, on the other hand, was acceptable for all exclusion on which both researchers and social policy and hence began to supersede the concept of poverty (see makers can agree. e.g. Abrahamson, 1995; Mandič, 2005). ‘Poverty’ is often conceived either as part of social exclusion (i.e. its material The first list of 18 indicators of social exclusion and poverty dimension) or as the situation leading to social exclusion. was adopted in 2001 at the European Council’s meeting in If poverty is interpreted in a narrower sense, i.e. as material Laeken (hence the name ‘Laeken indicators’). Most of these deprivation (in terms of disposable income, expenses or the indicators measure material (income) poverty and long-term standard of living), social exclusion in comparison is a much unemployment. The areas of education and health are cov-broader, multi-dimensional and more dynamic concept. ered to a smaller extent, while other dimensions of exclusion Definition of social exclusion within the EU At the EU level, social exclusion has in recent years increasingly been regarded as a process. According to the definition provided in the European Commission’s Joint Report on Social Inclusion for 2004, social exclusion is ‘a process whereby certain individuals are pushed to the edge of society and prevented from participating fully by virtue of their poverty, or lack of basic competencies and lifelong learning opportunities, or as a result of discrimination. This distances them from job, income and education opportunities as well as social and community networks and activities They have little access to power and decision-making bodies and thus often feel powerless and unable to take control over the decisions that affect their day to day lives’ (EC, 2004: 10). Social inclusion is similarly defined as a process ‘which ensures that those at risk of poverty and social exclusion gain the opportunities and resources necessary to participate fully in economic, social and cultural life and to enjoy a standard of living and well-being that is considered normal in the society in which they live. It ensures that they have greater participation in decision making which affects their lives and access to their fundamental rights’ (EC, 2004: 10). Social Overview 2006 11 (e.g. housing) are not covered at all. Such a selection was partly linked to the fact that these indicators can be measured objectively (except for inequality regarding health, which is based on people’s perceptions of their health), while the unit of observation is usually the individual. In the last few years, the Laeken indicators have been further streamlined and amended, and most were a breakdown by age categories (with a special emphasis on children and elderly people), by gender and some other criteria (e.g. by type of household for some indicators). In order to ensure international comparability, data sources used to calculate individual indicators were also defined. Originally, the Laeken indicators were calculated from the European Community Household Panel (ECHP) data that contain detailed information about income, socio-economic characteristics, housing, possession of durable goods, employment and jobs, health, subjective perceptions of well-being etc. Recently, the ECHP was replaced by the European Statistics on Income and Living Conditions (EU-SILC), which is becoming the basic data source for the calculation of the Laeken indicators within the EU25. Slovenia began piloting the EU-SILC in October 2003 and the first data should be available in December 2006. Social capital Social capital is construed as an important component of social cohesion arising from social networks. It is a significant social good, defined by the varying levels of trust on one hand and by social networks on the other3. Like other complex concepts, social capital is also associated with a number of ambiguities, multiple meanings and vague methodological tools that may be applied in various ways. However, its conceptual advantage lies in the fact that it emphasises the links between individuals’ inclusion in networks, their exclusion from crucial areas of life and the general social inequality that is being reproduced through these links; at the same time, the concept is also sensitive in the opposite direction, i.e. regarding the dependence of network ties and their social capital potential on the processes of social inequality (Dragoš, 2004: 43). The dilemma surrounding social capital construed as a developmental component of modern societies also exists in the sociological theory. The theory is divided over which characteristics of social relationships provide the basis of social capital and how they contribute to the co-operation and to social cohesion on a more general scale. However, a number of studies have already confirmed that social capital at the micro social level (e.g. individual bonds and trust) has remarkable implications for the entire society (Dragoš, 2004). The reason is that social capital turns social relations into an object as well as a means of achieving goals that people pursue in their relations. The problems and advantages that societies face depend, among other things, on the level of social capital, which must be examined at three levels of the social system – micro, mezzo and macro (Iglič, 2004). Social capital cannot be expected to be equally strong at all three levels. The various mechanisms of creating social capital are responsible for the fact that social capital in a society may be strong at the micro level but weak at the macro level, or weak or strong at all three levels simultaneously. The Social Overview analyses the correlation between two aspects of social capital – trust and social networks. Where there is trust there is co-operation, and where people cooperate the trust among them is reinforced. Individual social networks, organisational systems and entire societies that possess this potential are capable of achieving more goals than the networks, organisations and communities that lack such potential (Dragoš and Leskošek, 2003). Social networks are a place where social capital is being created; at the same time, they are an indicator and an element of social inclusion and social cohesion. Social networks as a web of interpersonal relations ensure the inclusion of individuals in society. If an individual does not feel accepted, if they do not belong to anyone or experience a lack of social ties (are not connected with significant others), this strongly affects feelings of social exclusion. A social network comprises people who offer support and help to an individual. Individuals are knitting social networks with their significant others, who represent a (potential) source of support. The types and scope of social relations established within a person’s social network reflect their living conditions and hence significantly (co-)deter-mine the quality of their lives. As a rule, social networks have a relatively stable size and composition, except in periods of major life-cycle changes and transitions. The studies of social networks show how many people an individual can rely on, what kind of support is provided, whether support is mutual or not, which potential support sources a person may have within their social networks and how satisfied they are with the support received. The question of how and to what extent social networks form part of an individual’s quality of living and their satisfaction remains conceptually and empirically open. The utility of social capital is also highlighted by some economic studies. These show that societies with low levels of trust among people decrease the effi ciency of enterprises and consequently trigger other economic and political problems (Fukuyama, in Dragoš, 2004). 12 Social Overview 2006 Support means helping people in daily life or during a certain (financial, emotional or other) crisis. Support may be categorised in four main groups (Dremelj, Hlebec, Kogovšek, 2004): - instrumental (or material) support refers to material help (lending money or tools, helping with household work etc.); - informational support refers to providing information that a person needs at times of major changes in life (e.g. moving house, looking for a new job); - emotional support is help offered during major or minor life crises (death of a close person, divorce, problems in the family or at work etc.); and - social support refers to occasional informal socialising (trips, paying visits to each other, cinema etc). I. The Way We Live The Way We Live 15 1. LIVING CONDITIONS – SITUATION AND TRENDS The way we live depends on several different factors. In addition to the established tight economic factors there are also those which are not founded on market criteria and effects. Indeed, individuals do not only react to purely economic or material incentives nor are they in their choices restricted solely by income (HDR 2002/03). Significantly defined and determined by income, employment, housing, accessibility of services, social support networks etc., living conditions, however, have a direct impact on people’s lives and determine their quality. Therefore, Chapter 1 describes the living conditions of the Slovenian population and their respective changes, mostly for the period after 1995. In this section we discuss the living conditions of the Slovenian population as a whole, whereas some trends and changes in living conditions are presented by income brackets. The analysis of the status and socio-economic stratification of the Slovenian population and its households is based on the Household Budget Survey data (HBS). 1.1 Characteristics of the Slovenian households In Slovenia a decreasing trend in the household size may be observed. In 2002, the majority of persons (32.9%) lived in four-member households, followed by three-member (22.0%) and two-member households (16.6%). Although there were no major changes in the share of four-member and three-member households in the 1998-2002 period, a general decreasing trend in the household size may be observed. The share of persons living in single-member and two-member households increased, while the share of those living in households of 6 or more persons decreased (see SA: Tables 1a and 1b). Households are ageing. There are ever fewer households whose heads are less than 40 years old, whereas the share of households with heads aged 70 years and over is increasing (see SA: Tables 2a and 2b). In 1998, the share of households with the head aged 30 to 39 years (29.7%) was the largest, while in 2002 the lead was taken over by household heads aged 40 to 49 years (28.2%). The majority of persons (about one-third) live in households whose head has a secondary education. In the 1998-2002 period, the share of persons living in households with heads having less than a primary education decreased, while the share of those living in households with heads having more than secondary education increased. The latter applies regardless of the gender of the household head (see SA: Tables 4a and 4b). Generally, there are more persons living in households with a more educated head when the household is headed by a female. Approximately two-thirds of persons live in households whose head is employed (68.4%), and 21.6% of persons live in households with a retired head (see SA: Tables 5a and 5b). The share of persons in households with an unemployed head of the household is 2.4%. The share of persons in households with an employed or unemployed head slightly decreased between 1998 and 2002, while in the same period the share of households with a self-employed, retired or occasionally employed head slightly increased. There were only slight changes in the total structure of income sources in the 1998-2002 period. According to the HBS data, the current monetary disposable income per person rose by 14.7% in real terms between 1998 and 2002 (by 49.6% in nominal terms). The share of income from employment remained approximately the same. The share of social benefits slightly decreased due to a smaller number of the unemployment benefit recipients, while the share of family benefits slightly increased due to higher child allowances (see Box 2 for the explanation of the income sources). Taking all social benefits in 2002 into account, the highest share of persons (around 12%) received child allowances, followed by scholarships and unemployment benefits (received by 2-3% of persons). The altered structures of expenditure (and an increase in the real value of income) indicate the improved income Box 1: Key terms and methodology of the Household Budget Survey (HBS) The Household Budget Survey is carried out by the Statistical Office of the Republic of Slovenia (SORS). The sample stratification is designed in relation to 12 statistical regions and 6 types of settlements. In larger settlements (with over 10,000 inhabitants) simple sampling was applied, whereas in smaller settlements sampling of clusters with four persons defining a household was applied. Method The applied method was a personal interview based on a questionnaire and diaries in which household members entered data on their daily expenditure and quantities of purchased goods for a 14-day period. Households are evenly arranged throughout the year; every household participated in the 14-day survey. Households as observation units are either communities of persons who reside together and spend their income on basic life necessities together (housing, food and other), or single persons who live alone and spend their financial means and eat independently. Head of household is a reference person with the highest income in a household. Source: SORS – Household Budget Survey. 16 Social Overview 2006 situation of the Slovenian households and changes in the consumption pattern. The share of expenditure on food is one of the basic indicators used for assessing the income situation (or poverty) of a person/household. In the 1998-2002 period this share decreased by more than two percentage points. The share of expenditure on transport was also reduced, while the shares of expenditure on communications, housing, recreation activities and culture increased in particular. Changes in the socio-economic stratification are analysed through the clustering of all persons into four income brackets. The comparison of the distribution of all persons in Slovenia across income brackets (low, lower-middle, upper-middle and high) in 1998 and 2002 (carried out for the needs of this project) shows that certain changes in the socio-economic A large share of persons live in their own apartments or houses (about 85%), though this share slightly decreased between 1998 and 2002. The share of persons living in apartments or houses owned by their parents or other relatives increased. Only slightly more than 6% of households lived in rented apartments; among them, the share of those paying profit rent increased, whereas the share of persons with non-profit rents decreased. stratification of society occurred in that period. A positive shift towards the reduction of income inequality – also supported by other indicators (at risk of poverty rate, Gini coefficient, the 80/20 quintile share ratio) – is confirmed. That is evident from both the increase in income within individual brackets (see Table 1) and the distribution of persons across income 1.2 Socio-economic stratification of the population Box 2: Methodology used in analysing the socio-economic stratification of households The analysis of the socio-economic stratification of households is based on the Slovenian Household Budget Survey (HBS) data for 1998 and 2002 (SORS). The datasets for the respective years are based on an aggregate sample of three consecutive years and are calculated using the mean year as a reference (the 1998 dataset includes data for 1997, 1998 and 1999; the 2002 dataset includes data for 2001, 2002 and 2003). Income is defined as current monetary disposable income. It includes income from employment1, income from occasional work2 (against contracts and direct payments, as well as through the student employment brokerage service), income from self-employment3, pension4, social5 and family6 benefits, income from property7, and intra-family financial transfers and gifts8. Current income is reduced by granted transfers (alimony, maintenance allowances, pecuniary gifts and voluntary contributions). The household income thus defined does not include one-off high income, the value of own production spent in the household, unpaid rents (for proprietary housing), a reduction in savings or loans taken out. Household income is a net income, i.e. income after payment of social security contributions and personal income tax. In order to facilitate an adequate comparison between persons living in households of different sizes and composition, household income was divided by the number of equivalent members. The equivalent household income thus obtained is also the equivalent income of persons in respective households. The number of equivalent members is calculated on the basis of a modified OECD equivalent scale also used by the Eurostat and SORS: the first adult in the household is assigned the weight 1, every other adult 0.7, and every child under the age of 14 years 0.3. The sum of weights for household members is the number of equivalent members, i.e. the equivalent household size. With regard to the equivalent income, households are divided into four income brackets (household property not considered): 1. low – having an equivalent income below the level of 0.6 of the median equivalent income of all persons in Slovenia, i.e. below the at risk of poverty threshold according to the Eurostat’s definition; 2. lower-middle – having an equivalent income at a level between 0.6 and less than 1.2 of the median equivalent income; 3. upper-middle – having an equivalent income at a level between 1.2 and 2 times the median equivalent income; and 4. high – having an equivalent income in the amount exceeding 2 times the median equivalent incomes. 1 Wages (including wages earned abroad), holiday allowance, allowance for meals, allowance for transport to and from work and other cash benefits from the employer. 2 Copyright contracts and work contracts. 3 Income from farming activity, income from other activities, wage of an entrepreneur, holiday allowance, allowance for meals and allowance for transport to and from work. 4 This source of income also includes recreational allowance and pensions from abroad. 5 Unemployment benefits, other benefits from social insurance, financial social assistance, housing rent subsidy, disability and recognition allowances with bonuses and scholarships. 6 Child allowance, parental leave benefit, parental allowance, birth grant and child care allowance. 7 Net income from renting an apartment, house, garage or other real estate, dividends, interests and income relating to patents, licences and other rights. 8 Alimony from a former spouse and for a child, regular financial assistance, maintenance allowance for elderly people and pecuniary gifts. The Way We Live 17 brackets (see Table 2). Considering the average real increase in income per person by 14.7% in the period discussed, income grew the most in the low income bracket (by 17.5%) and the least in the high bracket (6.4%) (see Table 1). Table 1: Increase in income, Slovenia, 1998-2002 Income bracket Income per person (index) Nominal Real Low 152.4 117.5 Lower-middle 147.3 112.4 Upper-middle 150.0 115.1 High 141.3 106.4 Total 149.6 114.7 Source: SORS, HBS data fi les 1998 and 2002; calculations by Stropnik. Note: In 1998-2002, the infl ation rate was 34.9% (consumer price indices – Statistical Yearbook 2004; calculation by Stropnik). The majority of persons lived in household clustered into middle income brackets according to the method applied. There are about twice as many persons in the lower-middle bracket as in the upper-middle bracket. The low and the lower-middle brackets together account for approximately two-thirds of all persons, whereas the upper-middle and the high brackets cover one-third. In the 1998-2002 period the share of persons in the two middle income brackets increased from 81.0% to 83.2%. The increase was somewhat more pronounced in the upper-middle bracket. The shares of persons in the low and high income brackets decreased, more in the low bracket where the change in the share was the most pronounced of all. This means that the differences in income decreased and that some persons, particularly those from the low and lower-middle brackets, moved upwards (see Table 2). In the low income bracket, single-member households are the most frequent ones, while the three- and four-member households are the least frequent. In the high bracket, the two-and three-member households are the most frequent. Their shares were already the highest in 1998; by 2002 the share of three-member households further increased (see SA: Tables 1a and 1b). Couples with one child of up to 18 years of age and parents (one or both) with at least one child over 18 years of age are strongly represented in the high income bracket (see SA: Tables 3a and 3b). In the period 1998-2002, the situation of single households considerably worsened, therefore a large increase in the share of single households can be observed in the low bracket. The main reason was the deterioration in the financial situation of households with persons aged 65 years and over. Large households (those having six or more members) somewhat improved their situation and their share in the low bracket decreased accordingly. During the 1998-2002 period, in the low income bracket the share of persons in households with the head aged 70 years or over saw the largest increase, while the share of persons having a head of the household aged 30 to 39 years declined the most. The latter obviously managed to considerably improve their income situation (see SA: Tables 2a and 2b). That is the group whose share in the high bracket increased most and which moved upwards most evidently. In the high bracket, the largest (above-average) share of households has a head aged 50 to 59 years. The data demonstrate the correlation between the education of the head of the household and household income: the lower the attained education level of the head of the household, the lower the household income. In 2002, there were as many as three times more persons from households having a head with less than a primary education (14.8%) in the low income bracket than was the average share of these persons in the total population (4.5%). In the upper-middle and high income brackets there were 0.5% such persons at the most (see SA: Tables 4a and 4b). In the low income bracket the share of persons in households having a head with attained primary education was also more than two times higher than the Slovenian average. These conclusions apply irrespective of the gender of the household head; the situation is, however, worse in households with a female head. In the 1998-2002 period the structure of persons with regard to the educational level of the head of households worsened in the low income bracket, whereas in the upper-middle and high brackets – where the large majority of persons live in households headed by a person with a post-secondary or higher education a positive shift can be observed. The only exceptions are households with a male head in the upper-middle bracket. That bracket comprises most persons who live in households having a head with at least a higher education, although there are cases where male heads attained either less than a primary or just a primary education. Female heads of households in the high bracket hold at least a secondary education. The distribution of persons across income brackets by the formal status of the head of household shows that in 1998 7.6% of all persons with an employed head of the household were in the low income bracket, while in 2002 this share fell Table 2: Distribution of persons and their income across income brackets, Slovenia, 1998 and 2002 (in %) Income bracket 1998 2002 Persons (%) Income (%) Persons (%) Income (%) Low 14.0 6.1 11.9 5.3 Lower-middle 54.1 45.1 55.0 45.2 Upper-middle 26.9 36.5 28.2 38.3 High 5.1 12.2 4.9 11.1 Total 100.0 100.0 100.0 100.0 Source: SORS, HBS data fi les 1998 and 2002; calculations by Stropnik. 18 Social Overview 2006 to 5.7% (see SA: Tables 5a and 5b). Both in 1998 and in 2002, persons in households with an unemployed head were most frequently found in the low income bracket (in 2002, however, to a somewhat lesser degree). Income differences slightly decreased in the 1998-2002 period. In 1998, persons in the low income bracket accounted for 14.0% of all persons while their available income totalled 6.1% of the total income available to all persons in Slovenia (see Table 2). In 2002, the share of persons in the low income bracket dropped to 11.9%, and their available income amounted to 5.3% of the total income. On the other hand, in 1998, 5.1% of persons in the high income bracket had 12.2% of the total income at their disposal, while in 2002, there were 4.9% persons in this bracket with 11.1% of available income. Thus, the shares of persons in both extreme brackets were lower, and the same was true of the differences between the shares of persons and available income. In the same period the income structure somewhat changed. Income from employment accounts for a substantially lower share in the income of the low income bracket (24.8% in 2002) than on average (59.1%) or in the income of the high income bracket (70.7%). Opposite conclusions apply to pensions. In the 1998-2002 period, differences in both income sources increased; the share of income from employment in the total income of the low bracket declined, whereas the share of pensions grew (see Table 3 and SA: Table 6). In 1998-2002, the share of child allowances rose in both the total of social and family benefits (from 22.7% to 35.9%) and in the total current monetary disposable income (from 1.6% to 2.1%). That is the result of the substantial increase in child allowances in May 1999 (child allowances rose on average by 38%). In the observed period there were also changes in financial social assistance (the scope of eligible persons expanded due to a higher level of minimum income) whereas, on the other hand, the importance of the unemployment benefit decreased (see Table 4). In 2002, 11.9% of persons (low income bracket) acquired only 2.2% of the total income from employment and received 24.5% of the earmarked aggregate of unemployment benefits, 21.6% of other social benefits and 16.6% of child allowances. On the other hand, 4.9% of persons (high income bracket) acquired 13.3% of the total income from employment, 24.6% of the total income from contractual work and direct payments, 11.8% of the total income from self-employment, 15.6% of other family benefits (the main reason being the relatively high parental leave benefits that are nearly the same as the previous wage) and as much as 40.7% of the total income from property. Table 3: Structure of income sources by income brackets, Slovenia, 1998 and 2002 (in %) Source of income Share of income source in current monetary disposable income (in %) Low Lower-middle Upper-middle High Total (all persons) 1998 Income from employment 28.0 55.5 67.8 67.4 59.7 Contracts and direct payments 2.7 1.2 1.1 3.2 1.5 Student employment brokerage service 0.2 0.4 0.7 0.4 0.5 Self-employment 9.5 6.6 4.7 8.8 6.4 Pensions 40.5 28.5 21.7 16.7 25.3 Unemployment benefi t 5.9 1.8 0.7 0.2 1.4 Other social benefi ts1 6.0 2.1 0.9 0.6 1.7 Child allowance 4.8 2.2 0.9 0.1 1.6 Other family benefi ts2 1.0 1.0 0.7 1.2 0.9 Income from property 0.1 0.3 0.4 1.3 0.4 Intra-family fi nancial transfers and gifts 1.2 0.5 0.3 0.1 0.4 Total current monetary disposable income 100.0 100.0 100.0 100.0 100.0 2002 Income from employment 24.8 53.7 66.8 70.7 59.1 Contracts and direct payments 2.4 1.2 0.9 3.0 1.4 Student employment brokerage service 0.5 1.0 1.0 0.7 0.9 Self-employment 6.7 6.8 5.5 6.7 6.3 Pensions 46.1 28.9 22.4 14.3 25.7 Unemployment benefi t 4.3 1.1 0.5 0.2 0.9 Other social benefi ts1 7.0 2.1 0.9 0.8 1.7 Child allowance 6.4 3.1 0.7 0.4 2.1 Other family benefi ts2 0.8 1.3 0.5 1.4 1.0 Income from property 0.2 0.3 0.3 1.5 0.4 Intra-family fi nancial transfers and gifts 0.8 0.6 0.5 0.4 0.5 Total current monetary disposable income 100.0 100.0 100.0 100.0 100.0 Source: SORS, HBS data fi les 1998 and 2002; calculations by Stropnik. Notes: 1Other social benefi ts include fi nancial social assistance, housing rent subsidy, disability and recognition allowances with bonuses, scholarships, etc. 2Other family benefi ts are: parental leave benefi t, parental allowance, birth grant and child care allowance. The Way We Live 19 Table 4: Relative importance of social and family benefi ts, Slovenia, 1998 and 2002 (in %) Social and family benefi ts Recipients (% of all persons) Share of individual social and family benefi ts in the total of social and family benefi ts (%) in current monetary disposable income (%) 1998 2002 1998 2002 1998 2002 Financial social assistance 1.0 1.0 3.5 4.7 0.2 0.3 Other social benefi ts 1.1 1.5 4.7 8.3 0.3 0.5 Disability and recognition allowances with bonuses 0.7 0.9 2.7 2.6 0.2 0.2 Unemployment benefi t 3.0 3.3 20.3 14.8 1.4 0.8 Scholarships 3.4 2.0 13.0 16.4 0.9 0.9 Child allowance 12.2 12.3 22.7 35.9 1.6 2.1 Maternity leave benefi t 1.1 1.1 12.4 16.2 0.9 0.9 Parental allowance 0.1 0.1 0.2 0.4 0.0 0.0 Layette assistance 0.1 0.8 0.2 0.6 0.0 0.0 Child care allowance 7.0 0.1 20.4 0.1 1.5 0.0 Total - - 100.0 100.0 7.1 5.7 Source: HBS 1998 and 2002; calculations by Stropnik. 1.3 The main income sources – income from employment and from public sources Income from an employment is the single most important source of the population’s income. According to the HBS data, it accounted for 59.1% of all sources of current monetary income in 2002. In comparison to 1998, when it totalled 59.7% of all sources, its share decreased slightly. 1.3.1 Wage movements in the 1998-2005 period In the 1998-2005 period, wages rose at an average real annual rate of 2.2%, somewhat faster in the private than in the public sector (see Table 5). Their movement was significantly influenced, notably after 1997, by wage policy whose objective has been the achievement of stable wage growth that would at the same time correlate with labour productivity growth. At that time, wage policy involved mechanisms which facilitated the implementation of one of the main guidelines, according to which the real growth of the gross wage per employee should be slower than the growth of labour productivity in the private sector, and approximately consistent wage growth in the public and private sectors. The latter is being implemented on a long-term basis. In 1995, in the Social Agreement the social partners agreed on the introduction of the institution of the minimum wage as the lowest possible payment for work performed during full-time employment. The method of adjustment to inflation was the same as for wages. The transition period saw an increasing dispersion of wages. By introducing the institution of the minimum wage, the social partners therefore provided for the security of employed people and achieved the limitation of the lower part of the wage distribution. In 1997, an additional adjustment of minimum wages was introduced (once per year by the measured GDP growth for the previous year)4. The additional adjustment should push the lowest gross wage level slightly upwards, thus contributing to a reduction of wage dispersion in the part with the lowest wages. Table 6 shows a trend of a slight wage dispersion increase up until 2001, and a reduction from 2003 onwards. Table 5: Growth rates of labour productivity and real gross wages per employee in the private and public sectors, Slovenia, 1998-2005 Labour productivity Gross wage per employee Total Private sector Public sector 1998 3.6 1.6 2.2 -0.2 1999 4.1 3.3 3.2 3.7 2000 3.3 1.6 1.3 2.1 2001 2.2 3.2 2.3 5.1 2002 3.8 2.0 2.3 1.1 2003 2.9 1.8 2.1 0.7 2004 3.7 2.0 3.1 -0.8 2005 3.0 2.2 2.8 0.9 1998-2005 3.3 2.2 2.4 1.6 Source: SORS, calculations relative to gross wages by sectors and labour productivity by IMAD (Spring Report 2006). This minimum wage adjustment mechanism applied until 2006. 20 Social Overview 2006 Table 6: Indicators of the distribution of employees with regard to gross wage amounts, Slovenia, 1998-2005 1998 1999 2000 2001 2002 2003 2004 2005 9th decile/1st decile 3.34 3.39 3.46 3.51 3.46 3.57 3.51 3.46 median/1st decile 1.68 1.70 1.70 1.72 1.71 1.72 1.69 1.66 9th decile/median 1.98 1.99 2.04 2.04 2.03 2.08 2.08 2.08 Gini coeffi cient 0.287 0.293 0.295 0.299 0.293 0.292 0.288 0.289 Average gross personal income/Median*100 119.9 121.4 122.1 122.7 122.1 121.3 121.1 122.0 Source: SORS, calculations by IMAD. Box 3: Measurements in deciles Measurements in deciles indicate deviations from separate selected points in the wage distribution. We usually measure deviations between the ninth and first deciles, and deviations of both extreme deciles from the fifth decile or median, respectively. The gross wage of the ninth decile means that ten percent of employed people with the highest wages receive a gross wage which equals the ninth decile or higher. The gross wage of the first decile means that ten percent of employed people with the lowest wages receive a gross wage of the first decile or lower. The gross wage of the fifth decile or median means that 50% of wage recipients earn a gross wage that is higher than the median, while 50% receive a lower gross wage. Due to the point-to-point measurement model, the ratio between the ninth and first deciles and the median does not take into account developments in the lower and upper ten percentages of the distribution of employed people by wage amount. For further research purposes, two inequality indicators were therefore used in addition, i.e. a comparison between the gross wage per employee and the median gross wage, and an estimate of the Gini coefficient (the value of 0 means there is no inequality in the distribution, and the value of 1 indicates the highest inequality in the distribution). The wage dispersion and developments in the 1998-2005 period somewhat differ in the public and private sectors. Differences between the two sectors appear in the structure of employed people with regard to education, wage formation (being more uniform in the public sector) and in the wage adjustment mechanisms involved. Within the wage distribution in the private sector the relationship between the median gross wage and the first decile gross wage is quite rigid (see SA: Table 7). The effects of the wage policy measure on the introduction of the minimum wage and its subsequent adjustment to GDP growth were positive, as the relationship between the median gross wage and the first decile did not deteriorate, although the objective of a more constant wage distribution was not achieved. It can be assumed that the growth of gross wages at the managerial level is causing a departure of the highest wage average (expressed with the ninth decile) from the median gross wage. The highest wages, formed as a rule on the basis of individual contracts, are increasing faster than the median and the first decile gross wages, which are determined according to collective agreements. The previous wage policy in the public sector was only partly successful when seen from the position of a reduction of wage dispersion (see SA: Table 8). New legislation5 on wage regulation in the public sector was adopted in 2002, with its main objective being the elimination of wage disparities. Until 2001, the differences in wages (deviation between the gross wage of Figure 1: Gross wages per employee in the private sector of the EU25, 2002, by PPS (EU25=100) 140 120 100 80 60 40 20 0 LU UK DE NL AT DK BE FR IE IT FI SE ES CY GR PT SI CZ SK PL HU EE LT LV Source: (2006) Survey of Earnings Structure 2002. Eurostat. 5 The previous system of collective bargaining, decentralised to the ministry level, was a large obstacle to the achievement of macro-economic objectives, both with regard to the general gross wage movements in the public sector and with regard to wage distribution policies. A new Act on Pay System in Public Sector that provides for centralised collective bargaining was therefore adopted and enforced on 28 June 2002. The law itself also incorporates the objective of reducing the wage dispersion in the public sector. The Way We Live 21 the ninth and first deciles) of this sector have been increasing, whereas from 2001 onwards a reduction in the wage dispersion may be observed. However, at the turn of 2005 the reduction of wage dispersion came to a halt; the highest gross wages in that sector are growing faster than other wages. This process is occurring in all sectors, with the exception of health and social care. In 20026, the average gross wage per employee in the Slovenian private sector according to purchasing power reached the level of about 59% of the gross average wage per employee in the private sector of the EU25 (see Figure 1). 1.3.1.1 Impact of wages and other income of employees on income inequality Large changes in the distribution of income of employees were taking place until the mid-1990s. The analysis of data on the income of employees (see Box 4) shows that such distribution was mostly influenced by wages. However, a more detailed analysis of the upper end of the income distribution shows that among high income employees ‘other income’ sources (apart from wages) were more important than for the low or even middle income employees and that this trend is still continuing. The ‘stabilisation’ which has taken place since 1995 may be observed in almost all parts of the income distribution. Thus, there have been relatively modest changes in the share of low-income employees since 1995. That was due to a social partnership and new regulatory legal framework, through which the minimum wage (in an amount representing about 40% of the average wage) had been fixed in 1995. Such a ratio to the average wage was also maintained later on. It is thus no surprise that the share of employees with an income lower than 40% of the average wage decreased substantially since 1995, when it was the highest (it represented 7.4% of all employees). By 1998, their share had fallen to 5.7% and it also kept on decreasing during the following five years (excluding the increase in 2000). In 2002 the share of employees with an income lower than 40% of the average wage amounted to only 3.7% of all employees. Box 4: Methodology Based on the personal income tax data file, the SORS compiled a data file of employees and their income that facilitates an analysis of all income of employed people. The data file covers full-time employees employed with the same employer during the entire calendar year. By means of the Statistical Register of Employment, the register data were connected through a unique identifier with data on the personal income tax assessment communicated by the Tax Administration of the Republic of Slovenia (for more information, see Stanovnik, Verbič, 2005). Over two-thirds of all employees earn an income lower than the average wage. There were practically no changes in that share during 1998-2002. The data also show a considerable rise in this share during the first half of the 1990s, followed by stabilisation after 1995. The number of employees who earn an income exceeding three average wages has been increasing throughout the years. Thus, in 1995 11,233 wage recipients had an income that was higher than three average wages, followed by 11,837 in 1998, and 12,227 in 2002. Similar may also be said of employees whose income exceeds five average wages; following a rapid increase until 1995, further growth in the share of such employees stabilised. In 1995 the number of employees receiving an income higher than five times the average wage amounted to 2,128 persons, followed by 2,291 persons in 1998, and 2,375 in 2002. The group with the relatively highest relative increase is the group whose income exceeds eight average wages. This group is characterised by dynamics that strongly differ from the dynamics of the other two high income groups (above three or five average wages, respectively). This means that Table 7a: Structure of the gross income of taxable employees, Slovenia, 1994 and 2002 (in %) 1994 2002 Wage, wage compensation and cost reimbursement 90.29 90.93 Performance allowance and fringe benefi ts 0.39 0.33 Vacation allowance 5.01 4.58 Severance payments upon retirement, jubilee rewards and solidarity payments and other benefi ts from employment 0.19 0.36 Wages and pensions from abroad 0.86 0.00 Income from contractual work 0.73 0.72 Capital gains 0.03 0.15 Income from property 0.36 0.97 Income from property rights 1.25 0.97 Other 0.88 0.99 Total 100.0 100.0 Source: Personal income tax data fi le, processed by SORS, calculations by Stanovnik and Verbič. Notes: The category ‘other’ covers pensions and compensations paid by the Pension and Disability Insurance Institute of the Republic of Slovenia, the income of secondary school and university students received through student organisations, cadastre income from farmland and wooded areas reduced by exemptions, relief and fees, and income from trade. Latest data of the Eurostat survey of the wage structure in the EU25. 22 Social Overview 2006 Table 7b: Structure of the gross income of employees whose income exceeds eight average wages, Slovenia, 1994 and 2002 (in %) 1994 2002 Wage, wage compensations and cost reimbursement 89.33 80.59 Performance allowances and fringe benefi ts 1.20 2.33 Vacation allowance 2.53 1.16 Severance payments upon retirement, jubilee rewards and solidarity payments and other benefi ts from employment 0.91 7.72 Wages and pensions from abroad 1.76 0.00 Income from contractual work 1.03 2.49 Capital gains 0.48 0.93 Income from property 1.81 3.76 Income from property rights 0.92 0.90 Other 0.03 0.12 Total 100.0 100.0 Source: Personal income tax data fi le, processed by SORS, calculations by Stanovnik and Verbič. Notes: The category ‘other’ covers pensions and compensations paid by the Pension and Disability Insurance Institute of the Republic of Slovenia, the income of secondary school and university students received through student organisations, cadastre income from farmland and wooded areas reduced by exemptions, relief and fees, and income from trade. the latter two groups experienced a significant increase in the number of wage recipients by 1998 and stabilised afterwards. In contrast to these two groups, the number of wage recipients with the highest income has also been steadily increasing after 1998 (see Table 7b). The number of these recipients was 213 in 1995, 382 in 1998 and 464 in 2002; although relatively small, their number more than doubled. In identifying the reasons for the increase in the number of recipients with a high income (above three average wages), we should not ignore the fact that the new personal income tax legislation entered into force in 1994 and that, consequently, the increase may be the result of ‘neutralisation’ of the relevant legislation, which considerably increased the progressivity of the income tax. With regard to interpretations of the growth of the number of wage recipients with the highest income we may assume that during the final stage of the privatisation process the method of rewarding members of management also changed. The data show important changes in the income structure of wage recipients with the highest income between 1994 and 2002 (see Table 7b). Severance payments, jubilee rewards and other benefits from employment represented in 2002 as much as 7.7% of the total income of this group of employees, and only 0.9% in 1994. This is mostly due to very high annual rewards to members of company boards. The share of some other sources of income also substantially exceeds the corresponding income share for all employees. While performance allowances and fringe benefits in 2002 represented on average just 0.3% of the income of all employees, the performance allowances and fringe benefits for the group with the highest income amounted to 2.3% of their total income (and only 1.2% in 1994). High shares can be similarly observed for capital gains and income from property. Income from property in 2002 thus on average equalled 1% of the income of all employees, whereas in the group of employees with the highest income this share represented 3.8% (and just 1.8% in 1994). 1.3.2 Movements of cash benefits from public sources Cash benefits from public sources (i.e. from budgets and social insurances) are the second most important source of the population’s current income. Of these, the biggest share falls to pensions and wage allowances, i.e. benefits which provide for social security in case of the loss of income during old age, illness, disability, parenthood and unemployment. In 2005 there were 70 various types of cash benefits defined as a legal right in Slovenian legislation. During 1992-2005, thirteen cash benefits were newly introduced; nineteen were renamed and seven abolished. The financial analysis of data collected in the IMAD’s cash benefits database (see Box 5) shows that in 1993 the population was paid a total of 1,740,741 cash benefits (441,311 thereof were one-off benefits), and in 2004 a total of 2,173,386 cash benefits (562,630 thereof were one-off). In the 1993-2004 period, the number of cash benefits grew by 25%, which means that their number was increasing at an annual rate of 2.1%. Systemic amendments in the legislation regulating the eligibility for individual benefits had an important impact on the growth of the number of benefits. Besides, the number of benefits was also significantly influenced by other factors, in particular demographic changes and the related changes in the number of children and elderly people, along with changes in the labour market. SIT 1,067,8 bn. (17.1% of GDP) were spent on cash benefits in 2004. In the 1993-2004 period, the earmarked funds grew by a real average annual rate of 4.0%, which is somewhat slower than the growth of total public expenditure (4.5%). The real value of cash benefits was also increasing, although it varied quite distinctly in relation to individual benefits. In relation to the average wage, the development of the amount of benefits also differed: the benefits for the poor and parents increased the most while the largest decrease was seen in the benefits for pensioners, disabled and unemployed. The Way We Live 23 Box 5: Database of cash benefits IMAD In 1992, the IMAD began collecting data on the cash benefits of the Slovenian population. Its aim was to produce an analysis of the cash benefit system and to establish a catalogue of such benefits. The analysis, published in a working paper (see Kersnik et al., 2006), provides an insight into the system of cash benefits and basic information (in terms of contents and finance) on each cash benefit during 1992-2005. At the same time, it represents the basis of both further analyses for the needs of the IMAD and for analyses of the administrators of programmes of social protection, and for social policy planners. Cash benefits are any benefits in cash which may in compliance with the law (from public funds via the public purse) be received by eligible persons in Slovenia. In the database, cash benefits are divided into 15 target groups: pensioners, disabled, survivors, parents, sick, poor, unemployed, students, trainees, veterans, people in need of help, war victims, war-disabled, farmers and people with special merits. In the structure of total funds for cash benefits, the highest share of funds was earmarked for pensioners. They received 49.6% of funds, whereas the lowest share was earmarked for persons with special merits (0.1%). As regards the number of benefits, pensioners are again in the lead (43.2%), immediately followed by parents (20.7%). 1.4 Expenditure The structure of expenditure on consumer goods reflects both the income situation of a person/household and the socio-demographic characteristics of the people in a household that determine their needs. The first group relates, for instance, to expenditure on hotels, cafes and restaurants, and the second to expenditure on education. In 1998-2002 in Slovenia, the share of expenditure on food and non-alcoholic beverages decreased in all income brackets. According to the HBS data, the share of expenditure on food decreased by 2.2 percentage points in all of the four income brackets, and a similar movement was recorded with expenditure on transport, which decreased by 2.1 percentage points. Meanwhile, the share of expenditure on communications rose by 2.1 percentage points, while the shares of expenditure on housing and utilities, as well as on recreation and culture increased by 1.2 percentage points (see Table 8). The shares of expenditure on communications and recreation and culture increased in all income brackets, whereas the shares of expenditure on food and non-alcoholic beverages decreased in all income brackets. The upper-middle and high income brackets saw a rise in the share of expenditure on clothing and footwear, as well as furnishings, household equipment and routine maintenance, while the low and lower- middle brackets featured a decrease in expenditure on the same items. While the low, upper-middle and high income brackets reduced the share of expenditure on transport, the lower-middle bracket saw a slight increase in the corresponding share. The low, lower-middle and upper-middle brackets reduced the share of expenditure on alcoholic beverages and tobacco, while the high bracket slightly increased that share. At the same time, the low, lower-middle and upper-middle brackets increased the share of expenditure on education, while the high bracket saw a reduction in that share. The share of non-consumer expenditure7 in total expenditure is the lowest in the low income bracket (6.6% in 2002) and the highest in the high income bracket (14.3%), thus averaging out at 10.5%. The prevailing non-consumer expenditure is related to housing (see SA: Table 14). The pattern of Slovenian household consumption is similar to the pattern of Western European countries. When the Slovenian patterns are compared with the consumption patterns of the EU25, EU15 and EU10, the most obvious differences between the household consumption patterns in all three groups of countries are characterised by the following: (1) households of new member states spend on average substantially more on the most basic goods such as food and housing, which reflects their lower level of living; (2) conversely, households of old member states spend relatively more on goods such as recreation and culture, restaurants and hotels, purchase of vehicles, clothing and furniture; (3) the pattern of Slovenian household consumption resembles more the pattern of the old than the new EU member states; and (4) Slovenia contrasts with both groups of the countries under comparison by its low share of expenditure on housing and health (see Table 9). The low shares of expenditure on housing could perhaps be explained by the high share of proprietary housing in Slovenia having an impact on the amount of imputed rentals, which are exempted from the analysis; the low shares of expenditure on health could be attributed to the differences in the social and health care systems. In Slovenia, a well-functioning system of direct health care funding is in force, which may explain the lower household expenditure on health paid out of pocket. Figure 2 shows the correlation between the personal standard (household final consumption expenditure by purchasing power) and the share of expenditure earmarked by households for the most fundamental goods, i.e. food (see Tršelič-Selan, 2006). The share of household expenditure on food points out a strongly negative correlation (-0.81) with the level of total household final consumption expenditure; the higher the income level, and consequently consumption, the lower the share of food in the expenditure structure. With a higher standard of living, the basic needs of households can be met sooner and better, and households can thus afford more prestigious goods. According to the criteria shown in Figure 2 and with some rare exceptions, households of the entire EU Comprising non-consumer expenditure on apartments/houses (i.e. expenditure on large construction works and renovations, and the purchase of apartments/houses or building land for a house) and other non-consumer expenditure (i.e. expenditure on life insurance, voluntary retirement and health insurance, fi nes, compensation for damage, taxes and self-imposed contributions, savings and transfers such as alimonies, maintenance allowances, fi nancial gifts and voluntary contributions). 24 Social Overview 2006 Table 8: Structure of expenditure on consumer goods by income brackets, Slovenia, 1998 and 2002 (in %) Type of expenditure Share of separate types of expenditure (%) Low Lower-middle Upper-middle High Total (all persons) 1998 Food 26.0 21.2 17.6 14.4 19.7 Non-alcoholic beverages 3.3 2.7 2.2 1.8 2.5 Alcoholic beverages and tobacco 3.3 2.4 2.1 1.7 2.3 Clothing and footwear 7.5 8.9 9.7 10.4 9.2 Housing and utilities 13.4 11.3 9.1 7.6 10.4 Furnishings, household equipment and routine maintenance 7.0 7.4 7.0 8.3 7.3 Health 1.6 1.8 1.8 2.1 1.8 Transport 12.0 16.6 20.7 20.9 18.0 Communications 2.8 2.4 2.0 2.0 2.2 Recreation and culture 7.7 8.5 10.2 12.6 9.4 Education 0.5 0.6 0.8 1.2 0.7 Hotels, cafes and restaurants 4.3 6.0 7.0 7.0 6.3 Miscellaneous goods and services 10.6 10.3 9.9 9.8 10.1 Total expenditure on consumer goods 100.0 100.0 100.0 100.0 100.0 2002 Food 23.4 18.9 15.7 12.2 17.5 Non-alcoholic beverages 2.4 2.1 1.7 1.3 1.9 Alcoholic beverages and tobacco 2.4 2.3 1.9 1.8 2.1 Clothing and footwear 6.7 8.3 9.5 10.9 8.9 Housing and utilities 14.4 12.8 10.3 8.6 11.6 Furnishings, household equipment and routine maintenance 6.5 6.7 7.2 9.1 7.1 Health 1.8 1.8 1.8 2.4 1.9 Transport 12.4 14.9 17.6 17.3 15.9 Communications 4.9 4.5 4.1 3.9 4.3 Recreation and culture 8.4 9.5 11.6 14.3 10.6 Education 0.8 0.9 1.1 1.0 1.0 Hotels, cafes and restaurants 4.9 5.6 6.6 7.3 6.1 Miscellaneous goods and services 11.0 11.6 10.8 10.1 11.1 Total expenditure on consumer goods 100.0 100.0 100.0 100.0 100.0 Source: SORS, HBS data fi les 1998 and 2002; calculations by Stropnik. Table 9: Household fi nal consumption expenditure, Slovenia (1999-2001) and the EU (1999), in % Structure (in %) EU25 EU251 EU15 EU151 NMS-10 Slovenia Food and non-alcoholic beverages 16.4 18.5 13.8 16.4 30.4 22.5 Alcoholic beverages and tobacco 2.8 3.2 2.7 3.1 3.6 2.7 Clothing and footwear 6.3 7.2 6.1 7.2 6.9 8.1 Housing and utilities 26.3 15.5 27.8 15.1 18.2 11.6 Furnishings, household equipment and routine maintenance 6.7 7.7 6.8 8.0 6.4 7.2 Health 3.2 3.7 3.1 3.7 3.4 1.8 Transport 12.9 14.9 13.4 15.7 10.1 15.6 Communications 2.5 2.9 2.4 2.8 3.2 3.2 Recreation and culture 9.4 10.9 9.9 11.5 7.6 8.9 Education 0.9 1.0 0.8 1.0 1.0 0.8 Hotels, cafes and restaurants 5.6 6.6 6.1 7.2 2.8 7.3 Miscellaneous goods and services 6.9 7.9 7.0 8.3 6.5 10.3 Source: Tršelič-Selan, 2006. Note: 1Calculations without imputed rentals. The Way We Live 25 Figure 2: Household consumption by purchasing power standard1 and shares of household expenditure on food by EU countries2, 1999 _LU A A UK NL • 00 r, \ n 0 O BE O "~ 'rCY'N DK O FR GR MT _ \ DE O SE PT 0^ o^y XCZ SK 5000 V4 *HU»^^ • ' " EE LV L T 10 15 20 25 30 35 40 45 50 Share of household expenditure on food and non-alcoholic beverages Source: Tršelič-Selan, 2006. Note: 1Average expenditure on household final consumption (in PPS). 2For EU15 imputed rentals are exempted. automatically fell into two groups, i.e. the group of the old and the group of the new member states. Of all newcomers to the EU, only Malta, Cyprus and Slovenia were ranked in the group of developed European countries, whereas the households of other new member states lag strongly behind the first group in terms of purchasing power (and, contrary to the latter, they earmark a considerably higher share of their expenditure only for food). 1.4.1 Indebtedness and over-indebtedness of households Debt is an instrument commonly used by individuals and households to maintain their consumption levels over time. Individuals and households resort to indebtedness to a varying extent in different periods of their lives, depending on their income levels. A certain level of debt is inevitable for most households, particularly in the early periods of their life cycles. However, in less favourable macroeconomic conditions or due to certain events in the life of a family, the risk of a household not being able to meet their debt repayment obligations may increase, and some households find themselves in a situation where they cannot continue to repay their debt and thus become over-indebted. Different countries approach the problem of over-indebtedness differently. Countries that have adopted regulations on consumer bankruptcy and insolvency proceedings (e.g. Germany), and those that have set up networks of debt advising agencies for people in financial distress (e.g. Ireland) are the most advanced in this area. At the EU level there is no uniform definition of over-indebtedness yet, and the statistical data on over-indebtedness are based on various methodologies8. According to the seemingly least disputable definition of over-indebtedness, a household is over-indebted if it has difficulties repaying the debt, which means that, based on the expected income and other liquid assets, the debt is too large for the household to repay without reducing its other expenses below the minimum level. The debt thus becomes unsustainable and the household over-indebted (Betti et al., 2001). According to this definition, over-indebtedness is measured by means of subjective indicators. These are based on survey data, according to which households are classified as over-indebted if they self-report as such. In Slovenia, the issues of indebtedness and over-indebtedness are not analysed systematically9. There is still no official definition of over-indebtedness and there are also problems with data availability (indebtedness can only be measured on the basis of data on loans and savings in banks; however, this method is no longer very objective because financial markets have evolved, both in terms of the loan supply and in terms of the new possibilities for wealth accumulation). No data are published on credit card debt, secured and unsecured debt, and the share of non-performing loans (i.e. those not being repaid) or arrears, to mention only those data that have been analysed in different studies for most countries. Nevertheless, Slovenia has already adopted some measures to provide a higher level of consumer protection (the Consumer Credit Act, the Execution of Judgements in Civil Matters and Insurance of Claims Act, the Protection of Buyers of Apartments and Single Occupancy Buildings Act, all adopted in 2004, and Rules on Reporting by Creditors which introduced the registration of ‘non-banking’ creditors with the Consumer Protection Office), which reduce the possibility of the population’s over-indebtedness. Over-indebtedness can be measured in three ways, namely through: (1) objective (quantitative, mathematical); (2) subjective (qualitative); and (3) administrative measures. Due to difficulties in obtaining relevant data, the Social Overview only analyses (over-)indebtedness by means of subjective measures, i.e. through data from the public opinion survey. 8 Therefore, the European Commission published in April 2006 a public call for a study whose aim is to set up bases for a common defi nition of over-indebtedness within the EU, to determine a common methodology, to improve the comprehension of the phenomenon of indebtedness itself, and to introduce effi cient, i.e. ‘practical and legal measures’ to prevent and tackle the problem of over-indebtedness of households. 9 For a discussion of indebtedness and over-indebtedness, see Ferk, 2007. 26 Social Overview 2006 Table 10: Percentage of people who cannot meet the running costs of living in due time with regard to their household income, Slovenia, 2005 (in %) Total indebted up to 500 € 501 € - 1000 € 18.1% 60.6 40.7 1001 € - 2000 € 32.4 over 2000 € 8.1 Source: SJM 20051. Note: N (indebted) = 521 Although data on indebtedness and its nature in Slovenia are scarce, we may nevertheless assume that it comprises at least three different dimensions. It may act as an indicator of the material problems of a household or solely reflects rational economising with income by people and households, or it may also assume the function of income in itself. We assume that responses to the questions on borrowing asked in the SJM 200510 reflect the actual borrowing capacity/possibilities of the respondents and their households, which means that people without a (regular) income have lower borrowing capacity/possibilities, especially in ‘official’ institutions. Data on (non-)borrowing can thus also indirectly indicate the (in-)accessibility of financial instruments of the institutions which are controlled by the Bank of Slovenia (banks and insurance companies). In a certain sense borrowing is a privilege of the working population and the socio-economically stronger population. In 2005, there were 41% of adult respondents who in various ways incurred debts. The share of people in debt is above-average in the age range of 25 to 45 years (60.1%); in this period of life, most people make arrangements for their existence, primarily housing, and therefore invest more actively. Looking at the education structure, people with a higher level of education borrow more, whereas with regard to work activity the employed (59.4%) borrow essentially more than the unemployed (32.8%), pensioners (25.6%) or housewives (23.1%). In a certain sense, indebtedness seems to be a privilege of the working population and the socio-economically stronger strata and that in the majority of cases it does not necessarily mean over-indebtedness. Being over-indebted is an indicator of the actual threat to the material situation of an individual or a household. According to the SJM 2005 data11, 18.1% of people over-borrowed (frequently and occasionally haven’t been able to pay off their loans) in 2004, 36% paid off their loans without any difficulty, and 42.1% did not incur any debts at all. In the lower income brackets, the percentage of the over-indebted is even higher; for them borrowing (indebtedness) most often also means over-borrowing (over-indebtedness) (see Table 10). The percentage of households which were able to save in the past year rose from 13% in 1992 to 29.1% in 2005, whereas the percentage of households that spent their savings or incurred debts decreased in the same period from 31.2% to 17.6% (see Table 11). 1.5 Access to goods and services Access12 to goods and services importantly impacts the level of the standard of living, social security, equality/ inequality, and social inclusion. Therefore, improving access and providing equality in access are increasingly important elements of the policy of European and other developed countries. Satisfying the fundamental needs of human development cannot only depend on the relative prices of services and goods and the available income of a person. It should therefore also be organised in a different manner. For such services the European practice introduced the term ‘services of general interest’ denoting market and non-market services which individual countries define as services of general interest and for which public authorities assume a certain public responsibility. The latter is designed so that countries regulate the system of implementing such services separately by determining special conditions of their implementation that provide for realisation of the public interest. Many of those services are performed as a public service, while countries additionally take special care of access to some other important goods. Being an important element of services of general interest, it is especially true of the social services that they should be based on the principles of social justice, solidarity, equal opportunities and, consequently, on Table 11: Assessment of the household material situation – fi nancial reserves, Slovenia, 1992-2005 (in %) 1992 1995 2001 2003 2005 Saved money 13.0 16.1 23.2 27.4 29.1 Had just enough money 56.0 51.7 52.5 52.4 51.3 Spent savings 19.2 16.4 12.8 13.2 10.2 Borrowed money 12.0 13.9 10.0 4.4 7.4 Source: SJM 1992-2005. Note: the question read as follows: ‘Has your family in the last year...’ 10 Have you overborrowed or taken out a loan in the last fi ve years? Please include any type of borrowing: bank loans (including higher overdrafts), borrowing from relatives or friends, borrowing in the grey market, leasing, etc. 1 – yes; 2 – no (SJM 2005/1). 11 Does it happen to you that you cannot pay your living costs due to loan repayment or are forced to cut your expenditure on basic life necessity? 1 – yes, often; 2 – yes, sometimes; 3 – no, never or almost never; 4 – I have not been indebted in this period (SJM 2005/1). 12 Accessibility is signifi cantly determined by (1) rules on and criteria of access, (2) prices and way of funding, (3) regional organisation, (4) human and other resources. The Way We Live 27 the prevention of social exclusion. There are certainly at least two further important principles, i.e. choice and freedom, which are often neglected in economic implementations. It is necessary to point out that compromises among those principles are not rare in the concrete implementation of social policy measures (primarily due to conflicts between supply and demand). Within the framework of the EU common policy of enhancing the European social model, member states began tackling the problems of access by drafting strategies for greater social inclusion. Attention was paid to various areas, in the first stage primarily to access to so-called social services such as education, health, social care and similar services. Numerous member states also widened their focus on access to information and communication technology, judicial protection and legal assistance services, culture, leisure-time activities, public transport and other goods which impact social inclusion. The ongoing monitoring and evaluation of accessibility are crucial to the efficient implementation of strategies for enhancing social inclusion. A common wider set of indicators, which could demonstrate the accessibility level, has not yet been designed; within the reports on the implementation of social inclusion strategies every country applies its own indicators. The applied indicators mostly relate to the amount of funds spent or number of their recipients and the users of services, respectively, and less to their impact on the long-term enhancement of social inclusion. In any case, improvement of access to services remains one of the priorities of the European policy of social inclusion, with the need for the advancement of its quality being emphasised. This aspect was allotted a significant part of discussions within the framework of drafting the two recent documents of the European Commission, i.e. the Directive on internal market services and the Communication on social services of general interest. That document should indicate a step closer to common rules for their implementation in the member states. In Slovenia some vital utilities are defined as ‘services of general economic interest’ (e.g. electricity and drinking water supply, public transport etc.). The implementation of various social services (education, health care and social protection services as well as other social services), which are mostly provided as public services, is also regulated by law whereas access to certain goods (housing, information and similar) is similarly a policy issue. The set of measures to provide accessibility is broad and depends on the nature of separate activities ranging from regulation and subsidisation of prices, funding or partly funding investments and costs of service implementation and subsidies or exemption from payments by users, to measures for a proportionate spatial distribution of the public service network and other providers of services, etc. The issue of the relevance of the access to certain services and goods to social inclusion was discussed within the government policy in drafting the Joint Memorandum on Social Inclusion in 2003, the first National 13 The shares of the cost of social welfare services that are covered below, for each type of services separately. Action Plan on Social Inclusion in 2004 and National Report on Strategies for Social Protection and Inclusion 2006-2008. Although provided for in legislation, the equality of access and freedom of choice are often reduced due to insufficient spatial and personnel resources, poor regional coverage or regional diversity, the inability to finance payable services from one’s own resources13 and a lack of information, which makes a choice impossible. In Slovenia, access to goods and services has so far not been systematically analysed and this analytical area is only being developed. Therefore, the operationalisation of the accessibility concept has been left open for strictly pragmatic reasons. Consequently, access to key social services and goods (e.g. health care services, social security services, education, housing and the Internet as an increasingly important source of information and education) is here studied by means of a limited set of indicators. In other words, we used quantitative indicators already being collected by administrative sources for portraying some acknowledged or recognised accessibility elements, or those which we could calculate ourselves using the existing data and which, at least to some extent, facilitated a comparison with other EU countries. However, the lack of other, primarily more qualitative indicators which could be subject to analytical monitoring through statistics and might be of greater importance in terms of accessibility, has contributed to the considerable analytical sparseness and narrowness of the conclusions. 1.5.1 Access to health care Access to health care in Slovenia is mostly characterised by the high level of inclusion of the population in the compulsory health insurance system. The insured are entitled to health care services comprising preventive, curative and rehabilitation services at the primary, secondary and tertiary levels, emergency transportation, medicines and medico-technical devices. Insured persons can use health care services in public institutions or private undertakings having a concession to carry out the relevant service. In Slovenia, the health insurance system is composed of compulsory and voluntary health insurance. Compulsory insurance covers the legally stipulated proportion (mainly the predominant part) of the payment of services. The voluntary supplementary insurance enables insurance for the difference to the full value of services, and also provides for a higher standard and a wider scope of rights than the compulsory insurance. Almost the entire Slovenian population is included in the compulsory insurance system (98.9% as at 31 December 2004). The exception is a small group of people (as at 31 December 2004 there were 22,536 people in this group, i.e. 1.1% of the Slovenian population), including people without an income, without a permanent residence and without Slovenian citizenship. Therefore, they cannot be included in the compulsory insurance system. The majority of the population is also included in the voluntary supplementary insurance y the state and the shares paid by individuals are presented in detail 28 Social Overview 2006 involving the additional payment of services to full value (as at 31 December 2004 70.6% of the population was included). About 30% of the population is not included in this type of insurance, partly because there is no need for it (all services are completely covered by the compulsory insurance, e.g. for children), partly because they took such a decision and pay additional money when they use health care services, and partly because they are unable to pay the premiums due to their low income. Accordingly, it may be said that in Slovenia there are two groups of people whose access to health care services is seriously impeded: (1) people who cannot be included in compulsory insurance; and (2) people who are not additionally (voluntarily) insured because of their inability to pay the premiums. These two groups are only guaranteed urgent health care services. Compulsorily insured people have the right to select a personal physician, dentist and gynaecologist at the primary level and, if they need hospital treatment, the right to choose a hospital or specialist outpatient facility. In most cases, all people are guaranteed the same standard as the voluntary supplementary insurance, providing a wider scope of rights or a higher standard than that covered by the compulsory insurance, only includes a small share of the population (just 2.1% as at 31 December 2004). In comparison with some other European countries, Slovenia has fewer personnel and other health care capacities. In terms of the number of practising physicians per 100,000 inhabitants there is a growing gap between Slovenia and the European average. In the 1995-2004 period, the number of physicians per inhabitant grew in Slovenia at an average annual rate of 0.9%, while in the EU25 the annual growth rate in 1995-2003 was 1.3%. In Slovenia there were 229.8 practising physicians per 100,000 inhabitants in 200414 (224.6 in 2003 and 211.8 in 1995); while in 2003 the ratio in the EU25 equalled 314.0. Among the EU countries, only Great Britain (216.2) had a worse ratio than Slovenia (see Figure 3). Somewhat better is the ratio of the number of practising dentists per 100,000 inhabitants, which in the 2000-2004 period increased from 58.3 to 59.7. However, Slovenia is still ranked in the lower half of EU countries here. In 2004, the number of nurses and nursing assistants per 100,000 inhabitants in Slovenia was 745 (736.4 in 2003)15, which ranks Slovenia in the upper half of EU countries (see Figure 3) (the EU25 average in 2003 was 720). While in most EU countries and in the USA nurses hold, as a rule, a higher or university degree, only one-quarter of nurses in Slovenia hold such an education. Personnel capacities at the primary level vary among statistical regions quite strongly. The data analyses (IVZ) show a shortage of physicians at the primary level in some parts of the country, accompanied by an even bigger lack of specialists-paediatricians and dentists (see Figure 4). In comparison with the Slovenian average, the region best provided with physicians was Savinjska (1,359 inhabitants aged 20 or over per physician), whereas less provided regions were the Pomurska, Podravska and Koroška regions in the east of the country, and the Zasavska, Osrednjeslo-venska and Gorenjska regions. The ratio between inhabitants and medical technicians and nurses was worse than the Slovenian average in five regions (Obalno-Kraška, Notranjsko-Kraška, Gorenjska, Osrednjeslovenska and Podravska), and better in the Pomurska region (also see SA: Table 17). Figure 3: Number of practising physicians and nurses per 100,000 inhabitants, Slovenia, EU and the US, 2003 1600 1400 1200 1000 800 600 400 200 Practising physicians Nurses Source: Eurostat Queen Tree (2005), WHO Database: for Finland, the Netherlands, Italy, Malta, Ireland and France the source is Health at a Glance – OECD Indicators (2005). Notes: For Ireland and the Netherlands data refer to doctors holding a licence and not those actually employed; due to the lack of data, the EU25 average for nurses is the WHO estimate for the European region; for Slovenia, data on the number of nurses include nurses with a higher and university degree and nursing assistants, including midwives. 14 According to data of the Institute of Public Health (IVZ) there were 4,589 practising physicians in 2004 in Slovenia (including specialists, interns and trainees; 4,485 in 2003). According to the IVZ estimate, there was a shortage of 300 to 500 physicians in Slovenia at the end of 2003, taking into account the demographic characteristics of physicians, workloads and possibilities to rationalise work and modify work processes (Health in Slovenia 2003, 2005). 15 In 2003, there were 3,394 nurses holding higher or university degree in Slovenia and 11,311 medical technicians (including midwives), in total 14,705 (in 2002: 14,281) (Statistical Yearbook 2005) and 14,888 in 2004 (IVZ). 0 The Way We Live 29 Figure 4: Provision of medical personnel for adults aged 20 and over in the sector of general/family medicine by statistical regions, Slovenia, 2004 D Population per physician ¦ Population per other health care workers 1 I ¦ Obalno-kraška Goriška Notranjsko-kraška Gorenjska Osrednja Slovenija Jugovzhodna Slovenija Spodnjeposavska Zasavska Savinjska Koroška Podravska Pomurska Slovenia 0 500 1000 Source: IVZ. Note: Calculations relative to the hours worked (1,430/year). 1500 2000 2500 The comparison of Slovenia with other EU countries as regards the number of hospital beds also indicates smaller capacities; in 2004 there were 479.9 hospital beds per 100,000 inhabitants in Slovenia (495.5 in 2003 and 574.1 in 1995)16. According to the comparable Eurostat data, the highest ratio in 2003 was held by the Czech Republic (1,137.2 beds per 100,000 inhabitants), followed by Ireland (1,006.7), Germany (874.4) and Lithuania (866.1), whereas the lowest ratio was established in Denmark (389.0), Great Britain (396.9) and Cyprus (431.1); the EU25 average in 2002 amounted to 639. The downward trend in the number of hospital beds has over the years been typical not only of Slovenia but also of other EU countries. In the 1992-2002 period, the number of beds in the EU25 dropped by an average of 15%, in Slovenia by 16% during 1995-2002, which is largely associated with the shortening of the average length of hospitalisation. At the same time, the demand for beds earmarked for the long-term care of the elderly, the disabled or chronically ill in Slovenia is growing. In some hospitals, the problem is being dealt with by changing the intended use of hospital beds. The problem of waiting periods has remained unsolved for quite a while. The longest waiting periods relate to cataract surgical treatment, orthopaedic and open heart surgery, examinations by magnetic resonance imaging and cardiovascular operations. The average waiting periods for those operations are between a few months and a year and a half. The waiting periods cause inequalities among insured people as the better-off population tries to secure services through payments from their own funds, which other people either cannot afford or must face lengthy waiting periods for services that are paid for by some out of pocket. 1.5.1.1 Expenditure on health Total expenditure on health in Slovenia, measured as a share of GDP, exceeds the average of EU countries. During 1997-2003, the total expenditure on health increased in Slovenia by 45% in real terms (public expenditure by 39% and private by 68%; see Table 12). Its share in GDP equalled 8.7% in 2003 (6.6% public and 2.1% private), which is more than the average of the EU15 (8.8%) and EU25 (8.1%) (see Figure 5). In the whole period of 1997-2003, the share of expenditure on health in Slovenian GDP increased by as much as 1.5 percentage points, which is almost twice as much as the average in the EU15 and EU25 (by 0.7 p.p.). In 2003 there were nine countries of the EU25 that had a higher total expenditure on health than Slovenia; their expenditure exceeded 9% of GDP. Slovenia is among the countries with low total expenditure on health per capita. In 2003, Slovenia earmarked USD 1,669 in PPP per capita, which is the most among the new member states, however lower than the EU25 average (USD 1,964 in PPP; see Figure 5). In 2003, the EU15 average amounted to USD 2,538 in PPP per capita, whereas the highest expenditure on health per capita among the EU countries was in Luxemburg, Germany, the Netherlands and France. Private expenditure in Slovenia is still relatively low. In the structure of total expenditure on health the share of public expenditure decreased in the 1997-2003 period (from 79.2% in 1997 to 76.3% in 2003), while the share of private expenditure rose from 20.8% in 1997 to 23.7% in 2003. In spite of this increase, the share of private expenditure in The data relate to the number of all hospital beds (not for acute cases only); the 2004 fi gure also includes the Diagnostic Centre of Bled and MC Medicor (IVZ); for data on regional coverage see SA: Tables 15 and 16. 30 Social Overview 2006 Figure 5: Total, public and private expenditure on health in Slovenia, EU countries and the USA, 2003 (as share of GDP in USD PPP per inhabitant) 16 14 12 10 8 6 4 2 0 fi Private expenditure D Public expenditure • Total expenditure on health per capita (right axis) i—i m A — — — |—| i—i i—i w — • — • • — # — • 9 • # Z — • pq !—. _ • • • 9 • * - _ _ —i 9 • • m m • — 0 # # 6000 5000 4000 3000 2000 1000 0 Source: WHO, The World Health Report 2004, 2005, 2006. Slovenia is still lower than the average in the EU25 (26%) and the EU15 (25.4%). In 2003, thirteen countries of the EU25, led by Cyprus (50.9%), Greece and Latvia (48.7%) and the Netherlands (37.6%), featured a higher share of private expenditure on health than Slovenia. Except for Malta, all new member states recorded in the 1997-2003 period a rise in the share of private expenditure on health (on average by 2.3 p.p. and, without Malta, by almost 4 p.p.); given the high rise in public expenditure, the share of private expenditure on health fell in most countries of the EU15, on average by 0.3 p.p. In the structure of private expenditure almost 60% of expenditure is covered by voluntary health insurance. This is related to the system of supplementary health insurances that covers the additional payments for health services up to their full value. Therefore, the direct ‘out-of-pocket’ expenditure in Slovenia is low in comparison with the EU countries and accounts for 41% of the private expenditure structure, whereas in the EU25 it amounts on average to almost 78%. 1.5.2 Access to social welfare services According to the applicable regulations, the majority of the Slovenian population is guaranteed access to social welfare services in the Republic of Slovenia. Yet in practice accessibility is still limited by an inadequate network of services and programmes (insufficient capacities and uneven regional distribution), difficulties in financing and frequently the poor provision of information or even stigmatisation of potential system users. All people with a permanent residence are entitled to services; others only have access to the most urgent ones. In certain risky situations, people with no permanent residence (although there are not many) therefore find themselves in trouble, especially if they become dependent on the assistance of other persons and require institutional care, for which they are ineligible within the public service framework. Social welfare services are free of charge. The exception is long-term care which, however, has a built-in system of partial or full exemption from payment in cases where eligible persons or members of their families, although subject to payments, are unable to pay (see Chapter 7.1.2). The network of services is expanding. The service network of social work centres, special social institutions for adults and institutions for training children with special needs has remained unchanged over the years. Networks of protection and work centres for adults with physical and mental deve-lopmental disorders and old people’s homes have in the last 10 years undergone wide extensions both in terms of capacity and the number of units. In 1995 there were 39 protection and work centres in Slovenia with a total capac- Table 12: Structure of expenditure on health and shares in GDP, Slovenia, 1997-2003 (in %) Structure (in %) Shares of GDP (in %) 1997 2000 2003 1997 2003 Total expenditure on health1 100.0 100.0 100.0 7.2 8.7 Public expenditure2 79.2 77.7 76.3 5.7 6.6 Private expenditure 20.8 22.3 23.7 1.5 2.1 Voluntary health insurance 10.7 13.7 14.0 0.8 1.2 Households (‘out-of-pocket’ expenditure) 10.2 8.6 9.7 0.7 0.9 Source: WHO, The World Health Report 2004, 2005, 2006, calculations by IMAD. Notes: 1Total expenditure on health also comprises investments in health, with sickness benefi ts being exempted. 2Expenditure of the state, municipalities and the Health Insurance Institute of Slovenia (HIIS) included. The Way We Live 31 ity sufficing for 1,427 people in care, whereas in 2005 the number of such centres increased to 78 units, which included 2,695 people in care. There were 47 old people’s homes in 1995 with a total capacity of 10,757 places, while in 2005 their number increased to 68 with a total capacity of 13,641 places (see Table 60). There are also more systemic possibilities for home-care and more elderly day-care centres, and in some places sheltered housing for elderly people has begun to operate. In comparison with the past, the network of services is primarily expanding by opening smaller units in places where there were no such facilities before, and therefore both the regional accessibility and the quality of dwellings improved. The providers of services are public institutions, private providers with concessions operating as part of the public network, private entities with work permits ope-rating outside the public network, and nongovernmental organisations. The supply of services began to expand through private undertakings and non-governmental organisations, particularly after 2000. The demand for the care for elderly people is increasing. Although the access to long-term care has substantially improved, longer life expectancy, the increasing number of elderly people and the lower capacity (altered abilities and possibilities) of families to provide for care continue to increase the scope of services required rapidly. Usually, the previous development of long-term care was aimed primarily at setting up capacities of institutional care. In 2005, there were 4.4 places (5.3 if vacancies in special social welfare institutions are included) per 100 inhabitants aged 65 and over17 in Slovenia, which is close to the figures recorded in the more developed European countries. However, Slovenia does lag behind according to the scope of home care and other non-institutional forms of assistance, which are provided to less than 2% of the population aged 65 and over. There are still discrepancies in access to long-term care services. Long-term care comprises the organisation and provision of health and social services (see Box 22). The long-term care system is divided into benefits deriving from health, pension and disability insurance and social care rights. In practice, considerable differences in the rights of people who stay at home and those who are admitted for institutional care are occurring due to a lack of networking between the existing systems. Care-dependent people in institutions usually have essentially better access to health services and are also provided with a larger scope of social services. Owing to persisting differences in regional development and accessibility, the waiting period for admission to old people’s homes is in some environments longer than elsewhere. Recently the waiting lists have nevertheless been shortening, at least for those elderly people who most urgently need a particular service upon discharge from hospital. The latter can above all be attributed to the improved co-ordination of work of the relevant services. 1.5.2.1 Expenditure on long-term care Total expenditure on long-term care involves expenditure on long-term health care and expenditure on long-term social care. Total expenditure on long-term care in 2004 amounted to 1.13% of GDP (public expenditure 0.88% of GDP and private expenditure 0.25% of GDP). 60% thereof was earmarked for long-term health-care services and 40% for long-term social care services (see Table 13). Private expenditure accounts for less than one-quarter of all funds earmarked for long-term care. In 2004 over 2003, the share of private expenditure in the total expenditure structure even slightly decreased and amounted to 22.2% (or 0.25% of GDP). Long-term health care is mostly financed from public sources (95%). The latter primarily involves the Health Insurance Institute of Slovenia (HIIS) funds earmarked for health-care services in old people’s homes and special social institutions, for extended hospitalisation and community nursing service providing long-term care, as well as funds from the Slovenian Pension and Disability Insurance Community that are earmarked for attendance allowances. Within long-term social care, approximately one-half of the expenditure is covered by public sources (52% from both national and municipality budgets) and the other half by private sources (48%). People accommodated in old people’s homes and other institutional care facilities usually cover part of the cost of services in the area of social care (accommodation, nutrition and alike) themselves. Slovenia is comparable to the EU15 with regard to its level of public expenditure on long-term care. In 2004, general government expenditure on long-term care in Slovenia accounted for 0.9% of GDP. The EU countries earmark different amounts of public funds for long-term care. As a rule, however, the amount in the old member states is conside- Table 13: Expenditure on long-term care by sources of funds and by purpose, Slovenia, 2003 and 2004 of which: of which: SIT, in mio Structure, in % Share of GDP, in % 2003 2004 2003 2004 2003 2004 care 65,519 70,739 100.0 100.0 1.13 1.13 public sources 49,607 55,042 75.7 77.8 0.85 0.88 private sources 15,911 15,696 24.3 22.2 0.27 0.25 long-term health care 38,410 42,377 58.6 59.9 0.66 0.68 long-term social care 27,109 28,362 41.4 40.1 0.47 0.45 Source: SORS and IMAD – Preliminary estimates for the Joint Questionnaire of the Eurostat, OECD and WHO for Slovenia, September 2006. The calculation is based on the number of vacant places in general and special social institutions for adults in 2005. 17 32 Social Overview 2006 rably higher than in the new ones. In 2004, on average, public expenditure on long-term care in the EU15 (old member states) totalled 0.9% of GDP (the most in Sweden 3.8%, Finland 1.7% and Denmark 1.1%), whereas the expenditure of the new member states (EU10) amounted on average to 0.2% of GDP (Poland 0.1%, Czech Republic 0.3% and Latvia 0.4%)18. 1.5.3 Access to childcare and education The main determinants of access to education are the number of vacant enrolment places by types19 of education programmes and mode of study (full-time and part-time), the spatial arrangement of education institutions and the financial accessibility of education. The indicator of accessibility most frequently used in international comparisons is participation in education at different levels20. Participation in education usually shows that the inhabitants indeed had an opportunity to participate in education and were consequently provided with access to education. The participation rates in education at different levels are influenced by various factors, which are partly presented in the rest of the chapter by using some available data and indicators21. Pre-school education and childcare are carried out by public kindergartens and private concessionaires. In the 2005/2006 school year there were 777 kindergartens in Slovenia, of which 18 were private facilities. Public kindergartens were attended by 57,134 children, while the share of children in private kindergartens was minimal (1.5%). Preschool education and care are financed by public and private funds, with the amount of parents’ payments depending on their material situation. Parents are classified in payment categories according to their income (per family member against the Slovenian average wage per employed person) and family assets22. The share of children attending kindergartens is increasing. In the 2005/2006 school year there were 77.8% of three- to five-year-old children in kindergartens, while the attendance rate of younger children (less than three years old) was 25.6%23 (see SA: Table 18). Compared with 2000/2001, the share of children aged three to five years attending kindergartens increased by 10.9 p.p. while the share of children less than three years old grew by 6.3 p.p. Slovenia is thus progressively approaching the objectives set by the 2002 European Council in Barcelona: in EU countries 90% of children from their third year of age until their enrolment in primary school and at least 33% of children younger than three years should be attending kindergartens by 2010. Access to kindergartens and other forms of pre-school childcare is in fact also important in light of the reconciliation of family and working life and has a considerable impact on the scope and ways of involving women in the labour market and, consequently, on the level of household income. Box 6: Children’s attendance at kindergarten, Eurostat* A survey carried out in 2003 in the EU15 by the Eurostat showed that the full-time kindergarten attendance of pre-school children is the highest in Denmark (92% for three- to five-year-olds and 58% for up to and including two-year-olds), followed by Sweden (84% and 42%, respectively), Germany (72% and 7%), Finland (50% and 18%) and Austria (52% and 9%, whereas in the Netherlands 51% of children of up to 4 years, thus reaching school-age, attend kindergarten. On this scale Slovenia can be ranked third, behind Sweden. * Statistical data on pre-school childcare for the EU25 are not collected using a common methodology, since the latter is only being established. National statistical bureaus acquired data by surveying institutions with different attendance times, which may have resulted in the doubling of children attending kindergarten (the same child attending one institution in the morning and another one in the afternoon). These deficiencies are the reason why the national statistics on pre-school childcare should be treated with some caution. 8 Internationally comparable estimates of public expenditure on long-term care were fi rst prepared within the study on the economic implications of population ageing (EC, 2005) and were already partly based on the methodology of the System of Health Accounts (OECD, 2000), which also includes the expenditure on long-term care and other health related services. Expenditure on long-term care was fi rst assessed for Slovenia in 2005 for the purposes of that study (Sambt J., 2005). In 2006, the SORS prepared the fi rst detailed estimates of the total (public and private) expenditure on long-term care (as part of the project that introduced the system of health accounts in Slovenia), which are presented in Table 14. 9 Types of education programmes within the secondary education include lower and secondary vocational programmes, general secondary school programmes and others; higher education studies include university and higher professional programmes. 0 The same defi nition of access to education is used in the European Commission’s ‘Study on Access to Education and Training’ (Otero, M.S. and McCoshan, 2004). The study mentions two other defi nitions of access to education: one emphasises the right of an individual to participate in education programmes irrespective of whether this right is claimed or not; the second one emphasises the completion of education and essentially equates access to education and its completion. 1 An in-depth analysis of access to education would actually require indicators of participation in secondary and higher education with regard to socio-economic origin of the participants in education, and indicators of the participation of various socio-economic groups of the population in education (including data on the participation of social groups such as the disabled and pensioners, minority members, prisoners, etc.). 2 Parents receiving fi nancial social assistance are exempted from payment pursuant to the Kindergarten Act (OGRS No. 72/05). Where more than one child from the family goes to a kindergarten, parents pay for older children a price lower by one bracket. Parents who are not liable for personal income tax in the Republic of Slovenia pay the full price of the programme. 3 In Slovenia, parental leave (the right to absence from work due to childbirth and childcare) lasts in most cases up to a child’s 1 full year of age, which is why the share of children younger than one year in kindergartens is low. This also lowers the share of children below three years of age attending kindergartens. If children aged 0 were excluded, the share of children aged up to three years attending kindergarten would total 38.7%. The Way We Live 33 Primary education is compulsory. Parents have the right to the ratio of the number of students per 1,000 inhabitants choose between public schools or private schools holding a reached as much as 57.4 (24.1 in 1995), whereas the ratio concession, and home schooling. In Slovenia, primary edu- to the population aged 20-29 (gross enrolment ratio in terti-cation is free of charge according to law, the data however ary education) equalled 38.9% (16.4% in 1995) (see SA: show that the share of private expenditure (e.g. for one-week Table 19). Slovenia has thus already achieved the level of excursions, meals etc.) is not insignificant (see Figure 9). those EU member states with the highest ratio of students to the number of the population. The number of full-time The number of primary schools is decreasing. In the students is rising; together with graduation candidates and 2004/2005 school year there was a total of 799 primary postgraduate students in full-time programmes, it already schools (817 in the 2000/01 school year). Considering the includes more than 50% of the generation aged 19-23 (23.6% reduction in the size of generations we may expect this de- in 1994/1995). However, the number of part-time students creasing trend in the number of primary schools to continue, is also on the increase. Their share among all students has particularly in smaller subsidiary primary schools which reached 36.7%25 in 2005/2006 (24% in 1995). The number could aggravate the issue of geographical accessibility of of part-time students is rising notably in vocational colleges primary education. and postgraduate programmes, whereas in universities and professional colleges it is slowly falling. Young generations are shrinking in number, yet the share of the population aged 15-19 participating in secondary The number of enrolment places is increasing. Another education grew during 1999-2004 from 72.2% in 1999 key element of the accessibility of education at the tertiary to 77.9% in 2004. As the generations in secondary schools level is the number of enrolment places, since it indicates shrank, the number of secondary schools for youth also the possibilities of the population to continue studying declined from 149 in 1999 to 143 in 2004. Looking at secon- after the completion of secondary education. Universities dary education programmes, enrolment in professional and and independent/autonomous higher education institutions general secondary schools rose while enrolments in lower and publish their terms of enrolment in the first academic year middle vocational programmes and vocational professional and the number of vacancies for full-time and part-time programmes declined. This may cause an imbalance between studies of a particular study programme by way of an the supply of labour force and labour market requirements. annual notice. The analysis of applications and enrolment The state is boosting the financial accessibility of secondary (University of Ljubljana, 2006) shows that the number of school education for young people with transfers to individu- enrolment places rose by 10.7% from 2001/02 to 2005/06 als (scholarships and child allowances) and by subsidising for both university and higher education study programmes. transport, food and accommodation. For the 2005/2006 academic year 24,794 enrolment places were announced (1,189 places more than the year before; The number of participants in secondary schools for adults see Figure 6). 73.8% of students enrolled in full-time study rose in the 1999-2004 period by 12% (from 19,449 in 1999 to programmes in 2005/06, while 26.2% of students enrolled in 21,732 in 2004). The number of secondary schools for adults part-time programmes, which was less than in the previous also increased; there were 138 such schools in 2004 and 126 year. The comparison of the number of applications with the in 1999. The secondary education of adults is financed either number of enrolment places in the 2005/2006 academic year by themselves or by their employers, or they participate in shows that the surplus in applications is being reduced. In education within the programmes for unemployed people the 2005/2006 academic year, 10.7% more candidates than (e.g. ‘Programme 10,000+’ organised by the Employment available competition places were registered in higher profe-Service of the RS). ssional programmes (17% in 2004/05 and 14% in 2003/04), and 10.9% in university programmes (16% in 2004/05 and Another increase may be observed in the number of stu- 14% in 2003/04). dents at the tertiary level. The participation of the population in tertiary education24 is influenced by various factors such Higher education institutions are unevenly distributed across as the graduation rates in secondary education, demographic Slovenia. Currently there are four universities, namely in trends, the anticipated individual economic benefits from Ljubljana, Maribor, Koper and Nova Gorica. In the 2005/2006 education (e.g. the expected income), social inequality, pub- academic year there was a total of 54 higher education in-lic expenditure on education and student assistance. In the stitutions (49 in 2003/2004), 44 of which were within the 2005/2006 academic year, a total of 114,794 students were framework of universities while 10 functioned as autonomous enrolled at all three tertiary education levels; 14,246 thereof higher education institutions. Higher education institutions are were enrolled in vocational colleges, 92,204 in undergradu- concentrated in four statistical regions, i.e. the Osrednjeslo-ate studies and 8,344 in postgraduate programmes. In 2005, venska, Podravska, Obalno-kraška and Goriška regions. 24 The gross enrolment ratio is used as the main indicator of measuring access to education in the European Commission’s report (Otero and McCoshan, 2004). The advantage of the indicator is that it measures the capacity of the national education system for the participation of individual age groups of the population in education at each level. The indicator is calculated by including the total number of students in a selected type of the educational programme regardless of age in the numerator and the total number of citizens of appropriate age for the given education level in the denominator. 25 IMAD’s estimate based on the available data published by SORS. 34 Social Overview 2006 Figure 6: Places announced and applications of Slovenian citizens for higher education study programmes in the fi rst term, Slovenia, academic period 2001/02-2005/06 28068 27476 29000 28000 27000 26000 25000 24000 23000 22000 21000 20000 2001/2002 2002/2003 2003/2004 2004/2005 Source: (2006) Analysis of applications and enrolment. University of Ljubljana: Ljubljana. 22131 Registrations Candidate vacancies 2005/2006 Full-time studies are free of charge, while part-time and postgraduate studies involve course fees although postgraduate studies are partly co-financed by the state. Further, the state is boosting the financial accessibility of tertiary education for full-time students through transfers to individual persons (scholarships and child allowances) and subsidies for transport, food and accommodation. 1.5.3.1 Expenditure on education Total public expenditure on education is relatively high. The level of total public expenditure on education is determined by a number of factors, among others the demographic structure, the participation rates in education, the level of wages of teaching staff, the organisation of the education system and the system of education funding. Total public expenditure on education in Slovenia was 6.0% of GDP in 2003 (5.9% in 1995; see SA: Table 23). This figure positions Slovenia above the level achieved by most European countries (between 4% and 6% of GDP), and above the EU25 average (5.2% in 2002). Slovenia’s relatively high proportion is nevertheless still much lower than the proportions seen in certain Northern European countries, notably Denmark, Sweden and Norway (over 7% of GDP). Slovenia also earmarks a higher share of public expenditure on education than other European countries for scholarships and other social benefits for students. Countries differ primarily in the ways they finance tertiary education. Some earmark more money directly for education institutions, while others reserve more funds for transfers to households, loans for tuition fees and other forms of assistance. High public transfers to households and other forms of assistance to improve access to secondary and tertiary education are also typical of countries with high public expenditure levels on education. In 2003 Slovenia earmarked as much as 25% of its total public expenditure at the tertiary level for transfers to households (16% at the secondary level); similarly high transfers are also characteristic of the Scandinavian countries Box 7: Key terms Total public expenditure on education (according to the UOE methodology – Unesco, OECD, Eurostat) comprises the total budgetary expenditure on the formal education of youth and adults at national and municipal levels. This includes public direct expenditure on education institutions (both instructional and non-instructional) and transfers to households and non-profit institutions (national scholarships, Zois scholarships, government and municipal scholarships, training scho-larships for the unemployed, child allowances in that part in which payments are additionally conditioned by inclusion in education, and subsidies for one-week excursions; to private entities: subsidised tickets, subsidised textbooks and technical literature, expenditure on curricular reform and evaluation costs). Expenditure on education institutions (according to the UOE methodology) covers all public and private expenditure on instructional and non-instructional institutions for formal education. Public expenditure on education institutions does not cover public transfers to individuals and households, which are usually included in the total public expenditure on education. Private expenditure on education institutions includes the expenditure of households and other private entities paid directly to education institutions (expenditure on school fees, meals, one-week excursions, accommodation for pupils and students in residence halls). (see Figure 7). On the other hand, however, the Czech Republic, Greece, Spain, France, Poland and Portugal earmark the bulk of their public expenditure on education (over 90% in 2002) directly for education institutions, with the EU25 average being 83.6% (Slovenia 75%). Compared with other countries, private expenditure on education institutions is also high in Slovenia. In 2003 The Way We Live 35 Figure 7: Total public expenditure on tertiary education as a share of GDP, selected countries, 2002 (in %) 3.0 2.5 2.0 1.5 1.0 0.5 0.0 2.7 Transfers to households and non-profit institutions 2.2 2.1 2.1 Direct expenditure on educational institutions " 1.4 1.4 1.4 1.4 1.3 1.2 1.2 1.1 1.1 1.1 1.1 1.0 1.0 1.0 09 1----, 0.9 0.9 0.5 3.0 2.5 2.0 1.5 1.0 0.5 0.0 Source: Population and Social Condition - Eurostat (2005), Statistics in Focus (18/2005). it equalled 0.9% of GDP (0.8% in 2002; the EU25 average in 2002 was 0.6%; see Table 14). In terms of the level of education, the highest expenditure can be found in tertiary education (0.3% of GDP; the EU15 average is 0.2% of GDP). High private expenditure has also been confirmed by an international comparison of the ratios between public and private expenditure on education institutions26. In 2003, the Slovenian ratio was 86.1:13.9. Among European countries a higher share of private expenditure was only recorded by Cyprus (19.4%), Germany (16.7%) and the United Kingdom (15.6%), with the EU25 average being 17.2% (see Figure 8). In 2003, in higher education the Slovenian ratio between public and private expenditure was 75:25. In recent years the share of private expenditure on education institutions has decreased somewhat, with a rise only being registered at the tertiary level. In the 1995-2003 period, the share of private sources in the structure of expenditure on preschool, primary and secondary education decreased somewhat (a rise was only registered in tertiary education institutions) (see Figure 9). However, the share of public funding at these three levels increased, the main reason being the high growth Box 8: Impact of public expenditure on inclusion in tertiary education In terms of improving access to tertiary education public financing should be essential, however not necessarily as a means of direct aid to students. The results of an econometric study by the European Commission (Otero, McCoshan, 2004) analysing factors impacting on tertiary education accessibility according to data from EU countries for the 1998-2002 period showed a strong positive correlation between the inclusion in tertiary education and the level of public expenditure on education as a share of GDP. A rise in public expenditure by 1% of GDP should thus increase the gross enrolment ratio in tertiary education (as an indicator of tertiary education accessibility) by 21%. However, the analysis did not confirm the correlation between the level of direct financial aid to students (the share of transfers to households in total public expenditure on education) and participation in education (the gross enrolment ratio in tertiary education). Table 14: Expenditure on education institutions by source, Slovenia (1995-2003) and the EU25 (2002), in % Structure, in % Share of GDP, in % Slovenia EU25 Slovenia EU25 1995 2000 2003 2002 1995 2000 2003 2002 Total 100.0 100.0 100.0 100.0 6.2 6.1 6.3 5.5 Public 83.9 85.1 86.1 89.1 5.2 5.2 5.4 4.9 Private 16.1 14.9 13.9 10.9 1.0 0.9 0.9 0.6 Source: Education - Statistical Information No. 149, SORS (2005) and Education – First Release No. 86, SORS (2006); National accounts – SORS (Sept. 2005); calculations by IMAD; Population and social conditions – Eurostat (2005). As regards these data it should be noted that international comparisons are not fully reliable since they are partly based on estimates, which are usually higher for countries with better data sources, which is also true of Slovenia. 36 Social Overview 2006 Figure 8: Share of private expenditure in total expenditure on tertiary education institutions, Slovenia, EU and the US, 2002 (in %) 60 50 40 30 20 10 D jzl Source: Population and Social Condition – Eurostat (2005), Education at a Glance 2005 – OECD (2005), calculations by IMAD. of wages of educational personnel. The highest increase in the share of public sources was seen in the funding of kindergartens (from 75% in 1995 to 81% in 2003), where municipalities took over the major part of the burden of the increase in prices of public kindergarten programmes. Secondary education also experienced an increase in the share of public sources in the financing structure (from 84% to 91%) despite the substantial rise in the enrolment of adults, who are financing their education by themselves. Private expenditure at the tertiary level rose during 1995-2000 (from 20% in 1995 to 28% in 2000), when there was an extraordinary increase in enrolments in part-time studies, for which the fees are mostly paid by the students themselves. After 2000, the rise in enrolment places for full-time studies and the restriction on part-time studies contributed to a decrease in the share of private sources to 25%27. 1.5.4 Access to housing Like in other social policy areas, the key principles of the regulation of housing policy are efficiency and equality. Since housing is a life necessity, the regulation of hou- sing policy is primarily based on the principle of equality (LeGrand et al., 1992). When we think housing in terms of accessibility we think minimum housing standards, which should be guaranteed to all people under equal conditions. In Slovenia, these standards are defined in the Housing Act. Pursuant to this act a ‘suitable dwelling’ is a dwelling ‘...in a building constructed in accordance with minimum technical conditions for the construction of residential buildings and dwellings and for which a permit for use has been issued in compliance with regulations on the construction of buildings. A dwelling shall have a separate sleeping and living parts (except in the case of a studio) and shall satisfy the housing needs of the owner or tenant and immediate family members who live with the owner or tenant in a common household, and shall correspond to spatial standards as set out by the Rules on renting non-profit dwellings’ (OGRS No. 69/2003). The state must create opportunities for citizens to obtain proper housing. The mechanisms facilitating access to housing defined by the said act comprise the possibilities of renting non-profit dwellings through an open housing application procedure, Figure 9: Share of private expenditure in total expenditure on education institutions by levels of education, Slovenia, 1995 and 2003 (in %) 30 25 20 D 1995 D 2003 15 10 5 0 A ll lev educ els of ation Pre-s educ chool ation Prim educ ar y ation Seco educ ndary ation Tert educ iary ation Source: Education – Statistical Information No. 149, SORS (2005) and Education – First Release No. 86, SORS (2006); calculations by IMAD. 0 According to data from annual statements, private sources on average account for about 15% of the institutions’ total revenue. In some social sciences faculties with a high number of part-time students, this share can even exceed one-third. The Way We Live 37 Table 15: Dwellings according to censuses, Slovenia, 1971-2002 19711 19811 19911 2002 Dwellings2 total 477,273 607,682 683,137 777,772 Average useful fl oor space3 (m2) 56.5 63.2 67.3 74.6 Average useful fl oor space per person4 (m2) 15.5 19.3 22.0 26.3 Average number of persons in a dwelling 3.7 3.3 3.1 2.9 Source: SORS, Censuses 1971-2002. Notes: 1Data for the 1971-1991 period are recalculated according to the concept of the number of dwellings used in the 2002 Census. In the census, 2A dwelling is any structurally unified whole intended for residence. It has one or more rooms with or without appropriate utility spaces (kitchen, bathroom, toilet, hallway, larder etc.), and with at least one separate entrance. All dwellings (occupied, unoccupied, for occasional use) are included, the exception being dwellings only used for business activity, and other occupied premises and collective living quarters. 3The average useful floor space of a dwelling is the ratio between the sum total of the floor space of all dwellings and the number of all dwellings. 4The average useful floor space of dwellings per person is the ratio between the sum total of the floor space of all occupied dwellings and the number of all persons in occupied dwellings. Data for occupied dwellings only. subsidised rents and long-term loans for obtaining or renovating dwellings. The Housing Act imposes on municipalities the obligation to provide funds for the construction and acquisition of residential buildings for the provisional solution of the housing needs of people at social risk. Due to the lack of indicators (at both national and European levels) that could show how people reside in Slovenia28, this subchapter only uses the available census and survey data (HBS) on the tenure status of Slovenian households29 in relation to their income level. Between the 1971-2002 censuses, the average number of persons per dwelling decreased (by 22%), while the average floor space of a dwelling per person increased (by 70%) (see Table 15). According to the 2002 census, most households resided in their own dwellings, while 9.1% lived in rental housing (81% thereof in urban settlements). Most households lived in dwellings with an average floor space of between 41 and 80 m2 and the fewest in dwellings with a space of up to 20 m2 (1%). The share of households in smaller dwellings is higher among tenants; 71% of all tenants and almost less than one-half of all owners (32%) lived in dwellings with 60 m2 in floor area. In the course of the censuses the share of all30 dwellings without basic utilities has been decreasing, as has the share of households in such dwellings. In the 1991-2002 period, the share of dwellings without central heating fell from 38.9% to 21.4% (see Table 16). The share of dwellings without piped water and sewage disposal system was reduced to half, while the share of dwellings without electricity slightly increased (from 0.8 to 0.9%). According to the 2002 census, 16.4% of all households lived in dwellings without central heating (among tenants as many as 30%), 5.2% without a bathroom and 4.8% without a toilet. Poorly equipped dwellings are more common in non-urban areas (46% of all households) and mostly occupied by tenants and lodgers (81% of whom live in urban settlements). Table 16: Households and dwellings without basic installations, Slovenia, census 2002 (in %) Households total1 Owners Tenants Share of all dwellings2 without bathroom 5.2 4.3 9.8 n.a. without a fl ush toilet 4.8 4.2 8.7 n.a. without kitchen 1.3 0.8 5.1 n.a. without piped water 0.6 0.4 1.4 1.5 without sewage disposal system 0.5 0.4 1.3 1.4 without central heating 16.4 14.7 30.0 21.4 Source: SORS, census 2002, calculations by IMAD. Notes: 1According to the 2002 census there was a total of 678,950 households living in dwellings and a total of 777,772 of dwellings (occupied and unoccupied). 2SORS collects data on piped water, sewage, electricity supply and central heating systems for each dwelling separately. If a dwelling has adequate electricity, the sewage disposal system and central heating installations in at least one room regardless of whether the installations are connected to a public network or not, such a dwelling is be considered to be equipped with these installations. ‘n.a.’ not available The number of people living in inadequate housing, price developments in the housing market that allow for an estimate of the affordability of housing, the number of new constructions, types of fi nancing, (over-)indebtedness due to home purchase etc. The average prices of new constructions were analysed and published by the SORS until 2003; this survey was abandoned. In accordance with the Real Estate Agencies Act, real estate agencies report to the Surveying and Mapping Administration of the RS certain data on the real estate they deal with (the achieved purchase price, fl oor space of the real estate, the amount of rental and other technical data). To the same database they also report data of the Tax Administration based on the received contracts for tax returns. Categories of the tenure status are classifi ed according to income brackets into: housing owner/co-owner, user of a dwelling belonging to parents or other relatives, tenant in private profi table dwelling, tenant (employee) in a company-owned dwelling, tenant in non-profi t housing. A dwelling is any structurally unifi ed unit intended for residence, with one or more rooms, with or without appropriate auxiliary rooms (kitchen, bathroom, toilet, hallway, larder etc.) and with at least one separate entrance. Collective living quarters, dwellings only used for business activity and other occupied premises which are not considered as dwellings are not included. 38 Social Overview 2006 Figure 10: Structure by the tenure status, Slovenia, 1998 and 2002 (in %) 90 80 70 60 50 40 30 20 10 85.4 D 1998 D 2002 7.8 9.2 | | .--------------,--------------, I I-------.-------1 Ow ner/co-ow ner User of a housing Tenant in a Tenant Tenant in a of a housing unit unit ow ned by profitable (employee) in a non-profit parents or other housing unit company-ow ned housing unit relatives housing unit TP Tenant in a social housing unit Source: SORS, HBS data files 1998 and 2002; calculations by Stropnik. The HBS data show that in 2002 the majority of people lived in their own dwellings (84.6%). Compared to 1998, the share of people living in dwellings owned by their parents or other relatives and the share of tenants in profit housing rose, while the share of tenants in non-profit housing decreased (see Figure 10). In households with a low income (income below the poverty risk threshold, i.e. below 60% of the equivalent income median) the structure regarding the tenure status differs somewhat from the average Slovenian structure (yet not substantially). While the share of owners is somewhat lower but still high (80.4%), the share of tenants in social and nonprofit housing is a little higher (2.2 and 4.3%). There are also more users of dwellings belonging to parents and other relatives (see Table 17 and SA: Table 25). Comparisons with the EU15 for 2001 (there are no data for the EU25) show that in some countries the income level has a greater influence on the tenure status. The EU15 average thus indicates that in households ranked in the low income bracket (below 60% of the median) there are only 50% owners, while the high income bracket (above 140% of the median) comprises substantially more owners, i.e. 74%. Within the EU15 there is a difference between the Southern European and other countries; in Southern European countries there is also a very high share of owners among households with a low income, in some countries even higher than in Slovenia (e.g. in Greece 91% and in Spain 85%), whereas the lowest shares were recorded in Germany (28%) and Sweden (36%). Slovenian households earmark 19.3% of their income for covering the cost of housing and utilities (dwellings, water, Table 17: Tenure status by income brackets, Slovenia, 1998 and 2002 (in %) Type of tenure status Share of persons by income brackets (%) Low Lower-middle Upper-middle High Total (all persons) 1998 Owner/co-owner of a dwelling 80.3 85.7 86.4 91.4 85.4 User of a dwelling of parents or other relatives 8.0 7.5 8.6 5.5 7.8 Tenant in profi table dwellings 0.9 1.1 0.4 0.8 0.8 Tenant (employee) living in a company-owned dwelling 1.1 0.9 1.7 0.9 1.1 Tenant in a non-profi t dwelling 7.3 4.5 3.0 1.3 4.3 Tenant in a social dwelling 2.4 0.4 0.0 0.0 0.5 Total 100.0 100.0 100.0 100.0 100.0 2002 Owner/co-owner of a dwelling 80.4 83.5 88.7 83.9 84.6 User of a dwelling of parents or other relatives 10.4 9.3 8.1 10.8 9.2 Tenant in a profi table dwelling 1.7 1.9 0.5 1.3 1.5 Tenant (employee) living in a company-owned dwelling 1.0 1.2 0.5 0.0 0.9 Tenant in a non-profi t dwelling 4.3 3.6 2.1 4.0 3.3 Tenant in a social dwelling 2.2 0.5 0.1 0.0 0.6 Total 100.0 100.0 100.0 100.0 100.0 Source: SORS, HBS data files 1998 and 2002; calculations by Stropnik. 0 The Way We Live 39 electricity, heating). In the 1995-2001 period this share was increasing and then fell slightly. The costs of Slovenian households are on average slightly lower than the European average (21.4% in the EU25 and 21.3% in the EU15 in 2004). The highest shares of income were spent to cover housing costs in Sweden (28.6%) and Slovakia (27.5%), and the lowest in Malta (8.6%) and Greece (15.4%). Access to housing for socially weaker groups is provided by the state through a non-profit housing network, the possibility of obtaining subsidies for paying rent, and the possibility to apply for a temporary dwelling unit. Up until 2003 there was a division into non-profit and social dwellings. As the new Housing Act (OGRS, No. 69/03) entered into force, the previously separated housing categories were combined into the ‘non-profit rental housing’. Materially deprived tenants in non-profit housing have the right to subsidised rents granted and paid by municipalities. Municipalities may also exceptionally grant subsidies to the tenants of a dwelling not defined as non-profit housing. Non-profit housing is allocated for rent by municipalities. Since 2003, municipalities have published one public announcement for the allocation of such housing per year. They may set up two lists with respect to the number and quality of housing intended for renting (an A list for tenants with a lower income and a B list for tenants with a higher income). The decision about how many dwellings a municipality will allocate for rental by individual lists is subject to the municipal policy31. According to the 2002 census, there were 43,504 nonprofit and social dwellings in Slovenia, which accounted for 6.6% of all occupied dwellings. In the 1995-2004 period, the number of acquired non-profit dwellings in Slovenia declined by 55% (see Table 18), however the Ministry of the Environment and Spatial Planning (hereinafter the MESP) does not collect data on the number of dwellings let for rent according to individual lists. The ceiling of the permissible non-profit rent is stipulated by law and depends on the age of the dwelling and the floor space, and on whether the owner of a non-profit dwelling applies the highest permissible percentage (they may also decide on a lower one). In Slovenia the average annual level of non-profit rents is merely estimated, while the level of market rents is monitored only by administrative units on the basis of rental contracts accepted for registration. Temporary dwellings were introduced by law in 2003 as an instrument of assistance. They are a form of solving acute housing problems and such dwellings are therefore allocated for a limited period. In the 2004-2006 period, 551 dwellings were provided which, according to the assessment of the competent ministry, should suffice to cover urgent needs. Table 18: Number of newly acquired non-profi t1 and social2 dwellings in Slovenia, 1995-2004 Number of acquired non-profi t dwellings Number of acquired social dwellings 1995 587 132 1996 724 216 1997 659 60 1998 415 80 1999 281 42 2000 675 33 2001 444 121 2002 538 220 2003 411 (2) 2004 264 (2) Source: MESP-Housing Sector. Notes: municipal data collected by means of biannual questionnaires. 1The number of non-profi t dwellings at the national level by individual years represents the newly acquired dwellings which municipalities may let for rent as non-profi t dwellings. The majority of dwellings thus acquired are new constructions, whereas other dwellings are acquired through the purchase of old dwellings placed on the market by legal or natural entities, and through full renovations and modifi cations of their intended use. 2According to the amended legislation, only data on non-profi t dwellings are kept, 2003 inclusive. The provision of adequate and affordable housing for Slovenian population remains a policy challenge. The scope of non-profit housing construction in Slovenia has been very modest since 1995 and failed to meet both the demand and the annual plans. By adopting the new Housing Act the possibilities of subsidising rents have indeed improved somewhat, however for many people these subsidies remain unattainable because they are restricted to tenants of non-profit dwellings only. The deficiency of the Slovenian housing market continues to be the lack of dwellings for people with special needs (disabled persons, people with mental health problems etc.). It would also be worth examining the sufficiency and adequacy of the spatial distribution of units for emergency and temporary accommodation. 1.5.5 Access to the Internet The rapid development of information and communication technology (ICT) and information society services raises the risk of the (IT) exclusion of individuals. IT literacy at various levels is a precondition for the inclusion and participation in the information society. At the same time, ICT offers new opportunities for flexible forms of work, which increases the employability (inclusion) of groups with special needs. To this end, we monitor the accessibility of the Internet, which not only provides access to information and educational contents but is an indispensable element of functional literacy. The rate of Internet use in Slovenia is relatively high. Internet accessibility is one of the recent indicators of access to goods and services32. Among the new member states, 31 Municipalities usually decide on the basis of the type of the available non-profi t dwellings. ‘ A’ list: low-rent older dwellings are allocated to citizens with lower income (tenant does not have to participate in the investment). ‘B’ list: new and recently constructed dwellings with higher rents, subject to a stipulated own investment share of the tenant, are allocated to tenants with a higher income. 32 In Slovenia, the fi rst statistical survey on the use of information and communication technologies in households was carried out in 2004. 40 Social Overview 2006 Slovenian households are best equipped with access to the Internet. According to the 2005 data, 48% of households33 had access to the Internet from home, which equals the EU25 average and is slightly lower than the EU15 average (53%)34 (see Figure 11). The second highest share among the new member states was recorded in Estonia (39%) and the lowest in Lithuania (19%). The most frequent reasons for an absence of the Internet stated by Slovenian households are the lack of need and interest, excessive costs of access and equipment or not having the skills required to use the Internet. Slovenia lags behind the European average in terms of the number of households with broadband access to the Internet. Broadband access to the Internet is becoming an important indicator of the quality of access to the Internet as it provides for a much higher speed of data transfer and, consequently, the use of multimedia. In 2005, 19% of households in Slovenia had broadband access to the Internet, which is less than the EU25 average (23%) and the EU15 average (25%). The share of older Internet users is quite low. Like in all EU countries, there are more Internet users among the younger population (see SA: Table 28). According to the SORS’ data, there were 2% of users aged 65-74 in 2004, 13% in the EU15 (Eurostat) and 11% in the EU25 (in Sweden, for example, as many as 49%). According to the share of users aged 16-24 Slovenia is ranked 13th in the EU25 (Slovenia 71%; EU15 77% and EU25 75%). Internet use is particularly widespread among the younger population, which can also be indirectly gathered from data which show that in 2005 access to the Internet was recorded in 64% of households with children and in 41% of households without children (see SA: Table 29). 1.6 Social exclusion Very little quantitative empirical research on social exclusion (defined as the accumulation of deprivation at the distributional and relational dimensions) has been undertaken in Slovenia, primarily due to the lack of appropriate databases. There is a particular lack of those databases which would provide data on individuals for various areas of life and diverse forms of interpersonal and social participation. Researchers dealing with vulnerable and marginalised groups more often focus on qualitative methods of surveying the population at risk (those groups which are above averagely excluded in the field of education and employment, culturally diverse and legally or socially unprotected groups or groups with various specific problems determining their marginal position in society). They also concentrate on investigating and proposing measures for the prevention of marginalisation and for social inclusion of marginalised social groups. The first quantitative analysis of an objective risk of social exclusion was based on data from the survey ‘Quality of Life in Slovenia’35. The concept of social exclusion was empirically operationalised and the risk of social exclusion measured as the accumulation of exclusion and deprivation of individuals in the fields of housing conditions, public services and basic institutions in their living environment, education and functional literacy, consumption, household equipment and economic resources, employment and working conditions, and social contacts and support networks (Trbanc, 1996). All types of Internet connection Figure 11: Share of households with access to the Internet, EU25, 2005 100 90 80 70 60 50 40 30 20 10 0 Broadband access Source: Eurostat. 33 The observation unit is a person aged 16-74 and his/her household. 34 Note that the two-year calculations years do not include the same countries. 35 The Quality of Life in Slovenia Survey 1994 was carried out on a representative sample of people having a permanent residence in Slovenia and over 17 years old. 1,806 persons were surveyed. All the data related to the individuals or the households in which they lived. Most collected data are objective (which is also true of all data applied in the analysis). The Way We Live 41 Box 9: Study on the objective risk of social exclusion (Trbanc, 1996) The respondents with deprivation and exclusion accumulated in at least four out of six observed fields were identified as people at risk of social exclusion. There were 13.7% of such persons among the respondents. Only 17.2% were not deprived in any of the fields under observation. The majority, i.e. as many as 45.1%, were deprived in the field of education and functional literacy (less than vocational qualification and no formal or nonformal education and training after leaving school, or poor functional literacy) and housing (disadvantaged housing status or living in a sub-standard dwelling) featuring 43.1%. The fewest people were deprived in the field of social contacts and support networks (14.2%). Further analysis of the structure of people facing the risk of social exclusion demonstrated the strongest and a statistically significant linkage between social exclusion and both the size of the settlement in which the respondents lived and their education level. Among those living in very small settlements (with less than 500 inhabitants) 32% were at risk of social exclusion. Most people at risk of social exclusion in 1994 were older and poorly educated, people living in very small (isolated) towns alone or in extended families, farmers (mostly aged farmers), the unemployed or people performing odd jobs. A fairly traditional image of exclusion concentrated in small and poorly developed towns and among elderly and poorly educated people could thus still be observed in Slovenia about ten years ago. The risk of social exclusion was also present among unemployed people (mostly the low-educated) and those who had occasional jobs (were engaged in temporary and occasional work) (the pattern of performing untypical and unsteady work already showed its problematic nature). In 2003, a study on objective social and economic inclusion of vulnerable groups was carried out. The main purpose of the study (Trbanc, Boškić, Kobal, Rihter, 2003) was to identify feasible measures to increase the employability of people with low employment prospects and inactive people. The survey covered seven groups with high risk of social exclusion, among them some who actually were socially excluded36. These groups are: - homeless people; - people with mental health problems; - people with drug addiction problems; - people with alcohol addiction problems; - people with experience of (domestic) violence; - people in post-penal treatment; and - people without a work permit. Interviews with people from the vulnerable groups showed a high level of (family) reproduction of patterns leading to vulnerability. These are particularly patterns of addiction, family violence and criminal offences that the majority of respondents from the above groups already faced in their youth and in their primary families. Although the majority of respondents from vulnerable groups (see Box 11) were involved in social networks (except the homeless), their social networks were quite small, closed and they frequently included people who had similar problems themselves. People from vulnerable groups can therefore mobilise only little support from their social networks and their participation in society is weak. The situation of vulnerable groups in terms of employment and inclusion in the labour market is unfavourable (very few of them are employed, many are long-term unemployed and inactive, and they frequently do occasional and undeclared work). Their poor situation in the labour market is influenced by several interweaving factors which reduce their working capability. These are: often a low education level and problems with functional literacy, prolonged absence from the work environment, apathy and low motivation for seeking work or employment (as a consequence of a bad experience, a lack of self-confidence and belief in potential opportunities and/or the development of other survival strategies such as receiving financial social assistance, undeclared work etc.), the attached stigma and employers’ distrust. The survey established that people from vulnerable groups also had negative experience associated with work, notably non-formal work (occasional and undeclared work): ‘employers’ often disregard non-formal agreements and exploit workers. The respondents also mentioned bad experience with formal employment (various ways of sidestepping laws by official employers, e.g. failing to sign agreements, irregular payment of wages, suspension of employment due to sick leave or maternity leave, etc.). Individuals from vulnerable groups also often express their own incapacity to assert their rights. The analysis of the objective risk of social exclusion can be complemented with an examination of subjective perceptions of social exclusion. The issue is about perceptions and assessments of individuals regarding their possibilities in life, opportunities for participation and inclusion, and the sense of belonging. Being an important factor of social policy-making, the values and notions of social justice and solidarity in society also reflect subjective perceptions of exclusion and being excluded. The heterogeneity within groups is relatively high. In each observed group there were individuals with very different problems, in different stages of acute problems and with different life stories and experiences. Nevertheless, the interweaving (overlapping) of the problems of different groups was very high. 42 Social Overview 2006 A complex comparative study of subjective perceptions of social exclusion, reasons for the exclusion from society and conditions for social integration, and the importance of various integration aspects for individual people in different EU countries are presented in the analysis of the European Foundation for the Improvement of Living and Working Conditions37 (2004c). The analysis is based on data for 28 European countries that were collected in 2001 and 2002. Slovenia is also included in the analysis with data for 2002, when it was in the group of 10 accession countries of the EU. Among the citizens of all countries included in the survey, Slovenians felt the least socially excluded. The sense of social exclusion was measured by means of perceptions of alienation, helplessness and inferiority, a lack of recognition and feeling of social marginality. People who reported two, three or four subjective integration deficits were regarded as being socially excluded (according to subjective perceptions). Differences across countries in the share of people who have a subjective feeling of being socially excluded are considerable; from 5.6% in Slovenia to 26.6% in Slovakia. The EU25 average was 12.4%, in the EU15 12.1% and in the new member states 14.1%. The highest shares of people perceiving themselves as socially excluded were recorded in Turkey (34%), Bulgaria (29.4%) and Slovakia (26.6%), and the lowest, beside Slovenia, in Denmark (6.6%), the Netherlands (7%), Spain (7.8%), Sweden (8.2%) and Luxembourg (9%). Although citizens of the EU15 report social exclusion more seldom than the population of new member states (EU10), the polarisation between the groups of ‘insiders’ and ‘outsiders’ (employed vs. unemployed, people with a high income vs. people with a low income, employees in the service sector vs. unskilled workers, people without objective integration deficits vs. multiple deprived) is substantially higher in the EU15 (see Table 19). In the EU15 the feelings of marginalisation and social exclusion are more concentrated within deprived (vulnerable) groups. While there are more subjective feelings of social exclusion in the populations of new EU member states, they are more dispersed across these populations and do not concentrate within the deprived groups or groups which are the ‘worst off’. Slovenia combines the ‘positive’ characteristics of both groups of countries. On one hand, it has the lowest share of the population among the observed countries having a feeling of being marginalised and subjectively excluded and, on the other hand, the polarisation between various groups which are either in a better or worse position is also comparatively small. It can be concluded (at least for 2002 when the data were collected) that there was a relatively high degree of population homogeneity in Slovenia in terms of subjective perceptions of social positioning, participation in society and control over life and future (both individual and social). It seems that such homogeneity is the consequence of a relatively high population consensus about the key developments and social decisions taken since the gaining of independence, as well as the result of the gradualism of reforms during the transition period. Therefore, there was no pronounced social stratification or polarisation. The author of the analysis (Böhnke, 2004) also assessed the factors that might help explain most of the differences between countries in the shares of the subjectively excluded. At least four general patterns were confirmed that help understand these differences or how the perceptions of social exclusion are distributed: - the lower the GDP per capita in society, the higher the shares of subjective social exclusion; - the higher the overall unemployment rate in society, the higher the shares of subjective social exclusion; - in countries with a low unemployment rate, the polarisation in the perception of subjective social exclusion among the employed and unemployed is much more pronounced; and - the higher the incidence of acute poverty in society, the higher the shares of subjective social exclusion. Slovenians most often blame external (structural) factors for the fact that some people live in deprivation. The three most important reasons given by Slovenian respondents as to why certain people are poor or socially excluded are alco- Table 19: Subjective perceptions of social exclusion and (objective) multiple deprivation, 2001/2002 (in %) Slovenia EU25 EU15 EU10 Subjective perception of social exclusion in the total population 5.6 12.4 12.1 14.1 Share of people with a subjective perception of social exclusion within groups: - Without integration defi cits 4 9 9 10 - Financial diffi culties 10 21 22 20 - Financial diffi culties and experience of unemployment 8 37 41 28 - Financial diffi culties and lack of social support - 34 33 37 Polarisation (ratio) between the non-deprived and multiple deprived 2 4.1 4.6 2.8 Source: Böhnke, 2004: 17, 32. Note: ‘-’ too few examples. European Foundation for the Improvement of Living and Working Conditions is the institution of the European Commission. The Way We Live 43 Table 20: Why do some people live in deprivation1 (opinions of Slovenian and EU citizens), 2001/2002 (in %) Slovenia EU25 EU15 EU10 Social injustice 45 37 35 50 Inevitable consequence of modern development 22 22 23 20 Laziness or lack of will 15 18 18 16 Bad luck 13 17 19 9 None of the above 5 5 6 5 Source: Böhnke, 2004: 9-10. Note: 1One answer only. holism (53%), unemployment (47%) and illness (36%). The same answers were given by respondents in other new EU member states (see Table 21). The comparative analysis across countries showed that respondents in wealthier countries (in countries in which within the social policy the principles and practices of exercising individual responsibility prevail over the social protection provided by the state) more frequently interpret social exclusion as an individual failure (Böhnke, 2004: 9). The analysis of the subjective perception of social exclusion (Böhnke, 2004) showed that in EU countries the feeling of social exclusion (measured as the feeling of alienation, helplessness and inferiority, lack of recognition and margi-nality in the society) at the individual level is in all countries strongly associated with the experience of unemployment and serious financial difficulties and even more with the condition of multiple deprivation. It should be noted that the analysis repeatedly confirmed that the connection between exclusion from employment (unemployment) and the feeling of social exclusion is more pronounced in the old EU countries (EU15) than in the new ones; in this respect, Slovenia, as a new member, is no exception. Subjective feelings of social exclusion can be supplemented with the objective Laeken indicators of social exclusion and poverty. As regards the comparison with other EU25 countries, Slovenia is ranked relatively well according to the indicators38 of the key dimensions. (i) Among all countries of the EU25, Slovenia has the second lowest at risk of poverty rate39 (10% in 2003; EU25 15%). The first is the Czech Republic (8%), followed by Luxembourg and Finland (11%) and Hungary and the Netherlands (12%). (ii) Slovenia features the fourth lowest share of adult people (18-58 years) living in jobless households (6.7% in 2005; EU25 10.2%). (iii) According to long-term unemployment, Slovenia is ranked 11th among the EU25 (3.1% in 2005; EU25 3.9%). (iv) Life expectancy in Slovenia is lower than the EU25 average. In 2003, life expectancy was 73.2 for men (EU25 75.1 years) and 80.7 for women (EU25 91.2 years). Box 10: Development documents in the area of the reduction of social exclusion As one of its priority policies, Slovenia adopted the Programme to Fight Poverty and Social Exclusion in spring 2000. The Programme primarily aimed at poverty reduction in order to help those who had already fallen into poverty or were at risk of sliding into it, with special emphasis being put on the inter-ministerial co-ordination of measures. Slovenia has since 2002 been included in the Programme of the European Commission for the prevention of social exclusion and at the end of 2003 a Joint Inclusion Memorandum (JIM) was signed which gave Slovenia the basis for drafting the National Action Plan on Social Inclusion 2004-2006 (NAP Inclusion, 2004) while, for the 2006-2008 period, it prepared the National Report on Strategies for Social Protection and Social Inclusion. The key challenges of social inclusion in Slovenia set out in the NAP Inclusion (and previously in the Joint Memorandum) are the following: further development of an inclusive labour market and the promotion of employment as a right and opportunity for all, the provision of adequate education, the supply of adequate housing conditions for all, the reduction of regional disparities, an improvement in providing social services and the provision of an adequate income and means for a decent standard of living (NAP Inclusion, 2004: 5-7). (continued on the next page) 38 Data on the share of early school leavers are not reliable for Slovenia. 39 In the previous IMAD’s publications (also for reasons of continuity with data from previous years), calculations of the risk of poverty rates excluding income in kind were used for the comparison with the EU15. Since the measurements of poverty started to be carried out consistently for all new members, the Eurostat has been publishing data for the EU10 that includes income in kind in the calculations of the risk of poverty rates. That is why Slovenia is ranked so high. 44 Social Overview 2006 Box 10: (continued from the previous page) The NAP inclusion defines the following groups as the most vulnerable (i.e. groups with the highest risk of poverty and social exclusion): certain groups of disabled people (persons without status, with severe disability, unemployed, with unsuitable housing conditions), unemployed young people (first-time job-seekers), children (where owing to poverty or social exclusion their physical, mental/emotional and social development are at risk and have negative and long-term consequences), adolescents with developmental difficulties, homeless people (health and housing problems), the Roma (unemployment, low education level, poor housing conditions), people with a low income (unemployed and sole parent families), other vulnerable groups (victims of abuse, addicts, persons with mental health problems, persons without work permits) (NAP Inclusion, 2004: 5). The social inclusion measures concentrated around four key elements, i.e.: (1) facilitating participation in employment (measures of active employment policy understood as social inclusion instruments); (2) improving access to sources, rights, goods and services (social protection system and access to housing, health care, social care, education, judicial protection, culture and leisure activities, and reducing regional disparities); (3) preventing the risk of exclusion (preventing exclusion from employment, preventing discrimination and other risks of exclusion, and promoting e-inclusion); and (4) assisting the most vulnerable groups, which primarily concerns to measures for the disabled and the Roma (assistance in employment, education and training, and in meeting their housing needs). 1.7 Poverty In Slovenia the at risk of poverty rate has fallen. In the from 22.3% in 1998 to 22.1% in 2003. In the EU25 it equalled analysed 1998-2003 period (the latest available data), 29% in 2003. The lowest coefficient was recorded in Slovenia it declined by 1.8 percentage points. In 2003, the at risk and the highest in Great Britain and Greece (35%). of poverty rate (calculated by income in kind) was 10%, which was 1.7 percentage points less than the rate exclu- Among all categories and socio-economic groups, the ding income in kind (see Table 21). Compared to 1998, the highest at risk of poverty rate in Slovenia can be found in 2003 data show that income in kind (in all categories and people aged 65 and over and living in single households socio-economic groups analysed below) reduces the risk of (39.9%), followed by unemployed men (38.8%). With regard poverty by an average of 2 percentage points (the exception to special categories and socio-economic groups (by gender, being the self-employed, where income in kind reduced the age, the most frequent activity status, household type and at risk of poverty rate during 1998-2003 by as much as 8.4 tenure status), the risk of poverty in Slovenia in 2003 was percentage points). as follows. A considerable contribution to the reduction of risk of As to gender, women are more vulnerable to poverty. The poverty is provided by social transfers. Without them, the at risk of poverty rate among women is almost 3 p.p. higher at risk of poverty rate would have been 16.2% (26% in the (11.4% for women and 8.6% for men). The gap in the risk of EU25). A considerable contribution to the reduction of the poverty between men and women in the 1998-2003 period risk of poverty is provided primarily by pensions. If the even widened to the detriment of women (see SA: Table population had had no pensions, the at risk of poverty rate 31). While totalling 1.8 percentage points in 1998, it rose to in 2003 would have been as much as 36.9%. 2.8 p.p. in 2003. The at risk of poverty rate in women was lower than in men within only four socio-economic groups In the 1998-2003 period, the income inequality measured observed: among persons in paid employment, the employed, by the quintile and Gini coefficients40 decreased along with the unemployed and among people aged 50-64. The highest at income poverty (see SA: Table 30). Among the EU countries risk of poverty rate can be found in women aged 65 and over, Slovenia is ranked best according to both indicators, meaning namely 22.9% (men of the same age account for 11.1%). that its income inequality is among the lowest. The quintile share ratio (80/20 ratio) fell from 3.2 in 1998 to 3.1 in 2003 Broken down by age, the at risk of poverty rate was highest (in the EU25 it was 4.6, which means that the income of among people aged 65 and over, i.e. 18.5% (irrespective of people in the upper twentieth of the income scale was 4.6 the number of members of a household in which they lived). times higher than the income of people from the lower twen- The at risk of poverty rate of children was, like poverty of tieth of this scale). The lowest quintile ratio was registered persons in employment , below average; with children it was in Hungary (3.0) and the highest in Portugal (7.4). The Gini 8.8% and with people aged 16-64 8.5%. In both cases, the at coefficient decreased somewhat more in Slovenia, namely risk of poverty rate decreased in the 1998-2003 period. Both ratios are calculated by including income in kind. The quintile share ratio shows the ratio between the 20% of income richest people and the 20% of income poorest people, whereas the Gini coeffi cient takes into account the total income distribution. In the event of complete income equality, the Gini coeffi cient would total 0%. The Way We Live 45 Table 21: At risk of poverty rates after and before social transfers in Slovenia and the EU member states (including income in kind), 1998-2003 (in %) At risk of poverty rate after social transfers At risk of poverty rate before social transfers (pensions included in income) 1998 1999 2000 2001 2002 2003 1998 1999 2000 2001 2002 2003 Slovenia 11.8 11.6 11.3 10.6 9.9 10.0 17.4 17.6 17.5 17.3 16.3 16.2 EU25 15(s) 16(s) 16(s) 15(s) n.a. 15(s) 24(s) 24(s) 23(s) 24(s) n.a. 26(s) EU15 15(s) 16(s) 15(s) 15(s) n.a. 15(s) 24(s) 24(s) 23(s) 24(s) n.a. 25(s) Austria 13 12 12 12 n.a. 13(bs) 24 23 22 22 n.a. 24(bs) Belgium 14 13 13 13 n.a. 15(s) 25 24 23 23 n.a. 29(bs) Denmark n.a. 10 n.a. 10 n.a. 12(bs) n.a. n.a. n.a. 29 n.a. 32(bs) Germany 11 11 10 11 15 15(bs) 22 21 20 21 23(bs) 23 Greece 21 21 20 20 n.a. 21(bs) 22 22 22 23 n.a. 24(bs) Spain 18 19 18 19 19(bs) 19 25 23 22 23 22(bs) 22 France 15 15 16 13(bs) 12 12 25 24 24 26(bs) 26 24 Ireland 19 19 20 21 n.a. 21(bs) 32 30 31 30 n.a. 36(bs) Italy 18 18 18 19 n.a. n.a. 21 21 21 22 n.a. n.a. Luxembourg 12 13 12 12 n.a. 11 23 24 23 23 n.a. 23(bs) Netherlands 10 11 11 11 11 12 21 21 22 22 22 23 Portugal 21 21 21 20 20 19 27 27 27 24 26 26 Finland 9 11 11 11(bs) 11 11 22 21 19 29(bs) 28 28(bs) Sweden n.a. 8 n.a. 9 11 n.a. n.a. n.a. n.a. 17 29(bs) n.a. Great Britain 19 19 19 19 19 19 30 30 29(bs) 28 28 29 Cyprus n.a. n.a. n.a. n.a. n.a. 15 n.a. n.a. n.a. n.a. n.a. 20 Czech Republic n.a. n.a. n.a. 8 n.a. 8 n.a. n.a. n.a. 18 n.a. 21 Estonia n.a. n.a. 18 18 18 18 n.a. n.a. 26 25 25 25 Latvia n.a. n.a. 16 n.a. 16 16 n.a. n.a. 22 n.a. 24 24 Lithuania n.a. n.a. 17 17 17 15 n.a. n.a. 23 24 24 23 Hungary n.a. n.a. 11 11 10 12 n.a. n.a. 17 17 15 17 Malta n.a. n.a. 15 n.a. n.a. n.a. n.a. n.a. 19 n.a. n.a. n.a. Poland n.a. n.a. 16 16 17 17 n.a. n.a. 30 31 32 31 Slovakia n.a. n.a. n.a. n.a. n.a. 21 n.a. n.a. n.a. n.a. n.a. 28 Source: Eurostat, New Cronos database. Notes: ‘s’ Eurostat’s assessment, ‘n.a.’ not available; ‘bs’: break in the series. Data for 2003 are the latest available data. As regards employment, the risk of poverty was highest among the unemployed, notably among men. In the 1998-2003 period, the at risk of poverty rate declined among the employed but not among the unemployed and the retired (see SA: Table 33). Thus, the highest at risk of poverty rate in the entire group was held by the unemployed (38.4%), followed by persons not at work (17.2%) and other economically inactive persons (16.3%). Unemployment both creates the risk of poverty and signals the beginning of the social exclusion process. With respect to household type, single households are at the greatest risk of poverty. Among them, single households with people aged 65 and over are the poorest (see also SA: Table 31). In all types of households with children the at risk of poverty rate was below the average, the exception being single-parent households (see SA: Table 34) in which it was above-averagely high (24.5% in 2003, which is 7.3 p.p. more than in 2002 and 4.2 p.p. more than in 1998). In the 1998-2003 period, the at risk of poverty rate fell the most, i.e. by 6.5 percentage points, in large families (having three or more children) and totalled 10.3%. With regard to the tenure status, the at risk of poverty rate is still the highest among tenants (23.5%) although it fell by 3.5 percentage points compared to 1998. Among home owners the at risk of poverty rate was 9.8%. 1.8 Social support networks When people face problems and distress they tend to seek help and support with other people. The study of personal support networks helps us establish who people turn to when they need a certain kind of help. The support networks in Slovenia were studied in a 2004 study entitled ‘Support Networks of the Population in Slovenia’ (Novak et al., 2004) conducted by the Social Protection Institute of the Republic of Slovenia, in collaboration with the Faculty of Social Sciences. The authors of the research established the following key characteristics of personal (non-formal) support networks in Slovenia: - a person’s average support network includes 6.5 persons (it should nevertheless be noted that the same person may be the source of several different social supports); - with respect to marital status the largest network is 46 Social Overview 2006 held by the unmarried (6.5 persons) and the smallest by widowed people (5.8 persons); - urban population networks are somewhat smaller (6.3 persons) than the rural population networks (6.6 persons); - the higher the education level the larger the network; - among families the largest networks are held by extended families (in which the respondent lives with a partner and/or a child and other relatives, usually members of the family) and the smallest by single-parent families (these are generally the most disadvantaged in emotional, social and material terms; it even happens that single-parent families have no support at all, i.e. they live in isolation). In families with children, intergenerational assistance has proved to be highly important; - the more complex the support the lower the number of network members (social networks are the most extensive while financial support networks are the smallest). The density (frequency) of contacts among network members is high, meaning that networks are very strong (compared to certain European countries the Slovenian networks are the strongest), yet also overburdened. Due to their density and relative smallness, networks are highly sensitive since they may be subject to a sudden breakdown (i.e. when an individual needs help no network member is accessible at that moment). Individual network breakdowns are also indicated by data showing that a formal form of assistance is mostly sought by individuals included in very small social networks; the data also show that such support is predominantly of instrumental (financial or material) while emotional support is rare and also the weakest. Friends and close relatives are the main source of financial support. When material support is weak, individuals mostly turn to their friends and neighbours, followed by other relatives, whereas in the event of stronger material support they usually turn to friends, other relatives and siblings. The main source of emotional support and support in the event of sickness is a partner (also important are children, parents and friends). Men are mostly offered support by female partners, while women obtain support from female friends and children. In the event of sickness, men are mostly offered support by female partners and mothers, while women also obtain support, in addition to their partners, from children (more often daughters), mothers and female friends. The frequency of this kind of assistance is also shown by data indicating that the formal assistance of institutions and other types of organised assistance in the event of the need for care during an illness is sought by less than 5% of the population. Social support networks are family-oriented and highly burdened. In all types of support and irrespective of social and structural differences and age, more than half of the network members involved are immediate family members (the principle source of support being one’s partner) and other relatives. The family is thus displayed as a highly important element within the support networks of the Slovenian population. Wider kinship also appears to be important and the share of friends in a network is considerable. This means that an individual’s access to non-formal support is primarily determined by their access to kinship networks. In the event of sickness the highest share of the support network falls on the family (in 82.5% of cases). Therefore, the formal forms of assistance also need to be increasingly oriented towards the family as a whole rather than towards the individual only (Novak et al., 2004). Social support networks are vulnerable. This is particularly true of support networks in Slovenia, where such networks are small and, within them, the density of contacts is high. Networks may break down when they are overburdened and due to expectations that are too high to be met41. The best protection against the disintegration of non-formal support networks is the established complementarity with the institutional and formal network, respectively. Only the complementarity of both types of support provides the optimum efficiency of support. There are no significant differences in the structure of social network members among the population; differences notably exist in the size of the individual types of networks. The data indicate the largest differences between the poor and the entire population (see Table 22). The networks of some of the most vulnerable social groups are therefore presented below. Table 22: Average number of social support network members for the population by support type and vulnerable groups, Slovenia, 2004 Socialising Financial aid Small material support Large material support Emotional support Sickness Total network Total 4.29 1.66 2.05 2.08 1.86 1.78 6.5 Elderly 3.49 1.80 1.82 1.89 1.70 1.61 5.8 Physically-impaired 4.03 1.05 1.49 1.39 1.64 1.71 6.0 Poor 3.86 1.11 1.42 1.36 1.62 1.63 5.7 Single-parent families 4.13 1.18 1.49 1.26 1.84 1.65 6.04 Source: Novak, M. (2004): Support networks of the Slovenian population. Calculations by the Social Protection Institute of the Republic of Slovenia. When an individual network member cannot offer support because s/he is overburdened. 41 The Way We Live 47 1.8.1 Social support networks of certain vulnerable population groups Social support is an important element of the standard of living and quality of life, particularly in vulnerable social groups which are deprived of certain vital sources of living. Support networks strengthen the access to important sources or significantly widen it and are therefore an integral part of strategies that help to overcome social isolation and exclusion and, consequently an integral part of social inclusion strategies. Below are the results of the above-mentioned research on the support networks of the three most vulnerable social groups, namely the poor, the physically-impaired and the elderly (see Box 11). Their support networks are somewhat smaller than the networks of the entire Slovenian population. The key source of providing social support to vulnerable groups is their children. 1.8.1.1 Social support networks of the poor The poor, who are defined in the survey (Novak, Nagode in: Novak et al., 2004) as those whose monthly income per household does not amount to SIT 130,000, have considerably weaker networks in comparison with the total population, which is shattering the belief that this population group substitutes its material disadvantage with a larger network. In spite of the smaller scope of networks (a network on average includes 5.7 persons, the average figure for the population as a whole being 6.5), the survey showed no major differences in the structure of support networks among the poor when compared to the total population. Support to the poor is offered by a handful of relatives and some friends. The poor generally expect help from the same sources as other people. The consequence is the ‘accumulation of requests for help mainly addressed to the partner or parents, which causes a large deficit in help in the event of death of parents or loss of a partner. Due to the smaller network, this is an even bigger problem for the poor than for the population in general because the network members are strongly burdened but have a low ability to activate additional sources of help. The survey also shows that in offering formal assistance to its poor members (various forms of non-financial and other services) the family’s participation is low. 1.8.1.2 Social support networks of the physically-impaired The physically-impaired (people who walk with difficulty, have bad sight, use various medical devices etc., disabled people including those who are officially registered as such) are a group of people who need assistance with their daily household chores, maintenance of personal hygiene and dressing, or visiting a physician and going to the bank, etc. Approximately one-tenth of the adult Slovenian population have motoric difficulties while performing their daily chores. The research (Nagode, Dremelj in: Novak et al., 2004) indicated that over 16% of the physically-impaired required constant assistance in maintaining their personal hygiene and dressing. Assistance with minor daily household chores was required by 35% of them, and almost one-third needed help to deal with various matters (e.g. visiting a physician or a bank). Among them there were more women than men, while motoric difficulties increased with age. In setting up their networks, the physically-impaired are not disadvantaged compared with the total population. On average there are 6 persons in their network. In comparison with the total population they have a slightly smaller network at their disposal involving ‘lower material support’, however in the case of illness this informal network is somewhat larger. Due to larger requirements they nevertheless resort to formal assistance for their health problems more often than the total population. Like other groups, the physically-impaired people regard their family as the most important source of social support. This is particularly true of support in the event of illness. Among family members social support is primarily provided by children doing this to a much greater extent than is typical for population as a whole (this is primarily the consequence of the average age of the physically-impaired, which is 58 years). In this group of people the family network tends to be heavily burdened. The most burdened in providing care for physically-impaired people are women, especially with regard to emotional support and support during illness. Although they are satisfied with the informal social support, the satisfaction of physically-impaired people is lower than in the population as a whole. We can therefore conclude that this group has highly demanding (larger and constant) needs which cannot be met within the non-formal network at a suitable level of quality. Box 11: Vulnerable groups The term ‘vulnerable social group’ (Zaviršek and Škerjanc, 1998: 3-4) denotes social groups which are (in certain situations) exposed to the conditions that trigger the process of exclusion. This is a process of lacking and losing control over significant areas of an individual’s life. The term ‘vulnerability’ signals that people may find themselves in a certain situation (violence, addiction, unemployment, physical injury, old age or sickness) or are born into it (poor family, membership of historically discriminated ethnic minority, or organic injury since birth etc.). This makes them more vulnerable and (increasingly) susceptible to the accumulation of negative situations, which eventually leads to the state of being excluded. 48 Social Overview 2006 2. PERCEPTIONS OF LIVING CONDITIONS Against the background of the relatively favourable statistical indicators of the economic and social situation it is also very important to find out how satisfaction with living conditions is assessed by people themselves. Their satisfaction may be observed narrowly only by assessing the adequacy of income, or in a wider manner, i.e. by assessing the entire personal and family situation of an individual, and satisfaction with various aspects of society’s functioning. In analysing perceptions of a personal, family and social situation, we focused on a relatively wide spectrum of living conditions. The first level covers the personal and family situation, which includes indicators of subjective happiness and satisfaction with life, health, life optimism, social inclusion and feelings of safety, and the household material situation. The second level encompasses satisfaction with various aspects of the functioning of wider society, ranging from the political, economic and social systems to health and education. There is no borderline between the two levels as the respondents’ and their family’s social status represent a prism through which they assess developments in wider society. The same, of course, is true of the contrary. The general social developments are reflected on the seemingly most intimate/private levels, such as feelings of happiness in life and individual health. The set of applied indicators is based on statistical data from the Household Budget Survey (SORS), the two recent surveys of the Centre for the Public Opinion Research carried out in autumn 2004 (ESS – second wave)42 and spring 2005 (SJM 2005/1 – Slovenian Public Opinion, hereinafter ‘SJM’), and on the application of data from several previous SJM surveys43. 2.1 Income situation and satisfaction with income Information concerning the income situation of Slovenian households was first analysed by means of the Household Budget Survey data (HBS; for a methodological explanation see Boxes 1 and 2). According to the subjective evaluation, the income situation of the population in Slovenia improved in 1998-2002. When compared with 1998, 2002 saw more people who could manage on their own income (fairly to very) easily, while fewer people reported (great to some) financial difficulties. Subjective evaluation of the income situation depends on the income of a person (and the household he/she lives in). As many as 80% of people had (great to some) Table 23: Subjective evaluation of the household income situation, by income brackets, Slovenia, 1998 and 2002 (%) Household manages on its income… Persons by income brackets (in %) Low Lower- middle Upper- middle High Total (all persons) 1998 with great diffi culty 33.8 11.3 2.3 0.0 11.4 with diffi culty 38.8 30.8 12.3 2.6 25.5 with some diffi culty 23.3 47.2 48.1 19.8 42.7 fairly easily 3.9 8.0 23.1 34.7 12.8 easily 0.3 2.8 13.6 36.0 7.0 very easily 0.0 0.0 0.6 7.0 0.5 Total 100.0 100.0 100.0 100.0 100.0 2002 with great diffi culty 35.8 8.3 1.8 0.0 9.3 with diffi culty 37.0 28.8 8.5 0.0 22.6 with some diffi culty 22.4 49.5 47.9 24.3 44.6 fairly easily 2.9 10.5 29.1 30.1 15.8 easily 1.9 2.7 11.5 38.2 6.8 very easily 0.0 0.2 1.2 7.3 0.8 Total 100.0 100.0 100.0 100.0 100.0 Source: SORS, HBS databases1998 and 2002; calculations by Stropnik. 42 In Slovenia, the European Social Survey is carried out by the Public Opinion and Mass Communications Research Centre (CJMMC) at the Faculty of Social Sciences in Ljubljana. The survey includes 22 countries (21 European countries and Israel). The fi rst measurement took place in 2002; the observation unit is a country; the sample (N) is 42,358 people aged 18 years and over. 43 The surveys are carried out by the CJMMC. The SJM survey takes the form of a personal interview. The sample comprises a random selection of persons from the population register with a permanent residence in the Republic of Slovenia for Slovenian citizens aged 18 years and over. The sample size ranges from 1,000 to 1,100 surveyed units. The Way We Live 49 Table 24: Perceptions of fi nancial situation1, Slovenia, 1995-2005 (in %) 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 Unsatisfi ed (0, 1-4) 30.5 22.7 19.8 25.7 22.2 16.8 14.7 15.1 14.5 - 14.8 Median (5-6) 39.9 44.7 49.5 42.0 45.4 38.6 40.5 45.5 39.2 - 34.4 Satisfi ed (7-10) 29.0 31.4 29.3 31.4 30.9 43.8 44.0 37.4 45.8 - 50.3 Source: SJM 1995-2005. Note: 1The question reads as follows: ‘How do you assess material conditions in which you and your family live on a 0-10 scale?’ difficulties managing on their income in 1998; in 2002, the same was true of 77% of people. In both years analysed, the question ‘How does your household manage on its income?’ was answered ‘with difficulty’ mostly by people from the low income bracket; the majority of people from the lower-middle and upper-middle income brackets could manage on their income ‘with some difficulty’, whereas the majority of people from the high income bracket could manage on their income ‘easily’ (see Table 23 and SA: Table 36). Disregarding those who managed with their income ‘with some difficulty’, 31.9% of persons managed on their income with difficulty. The majority of those were in the low income bracket (72.8%) and their proportion was the only one to have (slightly) increased since 1998. On the other hand, the proportion of people who managed on their income with ease (easily and very easily) was low and did not substantially change in the 1998-2002 period. Subjective evaluation of the income situation may be affected by (at least) three factors: (1) the ratio between income and cost of living; (2) the fact that the welfare state only provides assistance in certain difficult or critical periods for an individual and a household but should not and must not provide income that may weaken the incentive for people to provide for themselves and other household members by earning an income themselves; and (3) people’s too high aspirations and expectations. Given the fact that the proportions of people managing on their income with difficulty are falling sharply from the low to the high income bracket and that they concentrate around ‘some difficulty’ (except for the low income bracket), we may conclude that the first two reasons stated above are most explanatory. The third reason for a lower evaluation of one’s own income situation primarily applies to the 24.3% of people from the high-income bracket for whom the level of income causes ‘some difficulty’. Against this background we might conclude that 4.8% of people from the low-income bracket, who according to the evaluation by their heads of households ‘easily’ manage on their income, live in households with a very modest household head. The public opinion data (SJM and ESS) also indicate that in the 1995-2005 period the satisfaction of people with their income situation (material situation) increased, particularly after 2000. In 2005, 50.3% of people (29% in 1995) were satisfied with their income situation compared with 14.8% of those unsatisfied (30.5% in 1995). The proportion of people satisfied with their material situation increased in the 1998-2002 period by six p.p., and during the 10-year period (1995-2005) by 21.3 p.p. Conversely, the proportion of people unsatisfied with their material situation decreased in the 1998-2002 period by 10.6 p.p. and during the 1995-2005 period by 15.7 p.p. (see Table 24). Comparisons of responses about the need to save and cut down on consumption in the 1995-2005 period show a positive shift. This period saw a substantial reduction of the proportion of those who economise on clothing, food and essential goods and think that they live in poverty, whereas the proportion of those who believed they lacked nothing or economised only with ‘luxuries’ increased. The feeling of being disadvantaged is most frequently expressed by people aged 46 to 60 years, people with a primary education, unemployed people and housewives. Still, these data nevertheless substantiate that in two-thirds of households there is no relative disadvantage. 2.2 Satisfaction with one’s personal situation The most frequently used indicators of satisfaction with one’s personal situation are evaluations of satisfaction with life and happiness (which are often used synonymously). Perceived life satisfaction is statistically correlated with a number of factors. Results of a longitudinal analysis in Slovenia (Bernik, 2004) show that self-perceived health and marital status have the highest explanatory power, while education and self-perceived social status are less significant. On average, people in Slovenia are more satisfied with life when they feel healthy, are married (or live in extramarital Table 25: Positions as to material situation1, Slovenia, 1990-2005 (in %) 1990 1992 1997 1999 2001 2003 2005 lacking nothing 5.5 9.5 16.9 11.6 13.6 17.6 19.4 economising only on luxuries 29.6 33.6 40.1 47.8 46.3 48.6 48.9 economising on clothing 49.7 45.7 37.1 33.3 35.0 29.4 26.0 economising on food, essential goods (poverty) 14.1 9.8 4.4 4.6 4.9 3.6 4.9 Source: SJM2005/1. Note: 1the question read as follows: ‘Could you say that you and your family are...’ 50 Social Overview 2006 Table 26: Satisfaction with family life, by gender, Slovenia, 2003 (in %) satisfi ed (completely, very, fairly) neither-nor unsatisfi ed (completely, very, fairly) N%N%N% men, aged 21-56 years 317 90.3 15 4.3 8 2.3 women, aged 21-56 years 326 90.5 25 6.9 8 2.3 Total 21-56 years 643 90.5 40 5.6 16 2.2 Source: SJM 2003/2 Table 27: Satisfaction with employment total, by gender, Slovenia, 2003 (in %) satisfi ed (completely, very, fairly) neither-nor unsatisfi ed (completely, very, fairly) does not apply N%N%N%N% men, aged 21-56 years 231 65.9 37 10.6 28 8.0 50 14.3 women, aged 21-56 years 211 58.6 39 10.8 20 5.6 90 25.0 Total 21-56 years 442 62.3 76 10.7 48 6.7 140 19.7 Source: SJM 2003/2 partnerships) and have a higher (self-perceived) social status. Differences in individual satisfaction based on age or gender are relatively small. Researches show that the level of satisfaction is also being (increasingly) influenced by employment, the quality of work and the level of work autonomy (European Foundation for the Improvement of Living and Working Conditions, 2004a and 2004b). According to the assessments of satisfaction (6.6), Slovenia is ranked within the lower third of countries included in the ESS (together with three other new member states and Southern Mediterranean countries). The average values in these countries are lower than those in Scandinavia, Western European countries and Switzerland (see Figure 12). Data for the 1994-2005 period in Slovenia initially show a decreasing trend, followed by a gradual increase in satisfaction with life. When only the 1998-2002 period is observed, we can see that 1998 has the worst results for the entire 1994-2005 period. The relevant values are on the decrease in the second half of the 1990s, a period still characterised by the transition wave of the dismissal of workers, mass retirements and increased social risks and stress. Thus, the proportions of ‘happy people’ in the 1996-1998 period oscillate between 45% and 49%, whereas in 1999 this trend starts to turn upwards, which roughly corresponds to developments seen in the economic and social areas. In 2005, the average score of satisfaction with life in Slovenia (on a 0-10 scale) of people with a household income of up to EUR 500 was 6.15, while the score of people having a household income in excess of EUR 2,000 was 7.72. With regard to income these differences tend to persist in all age groups, yet considerably more with people aged over 60: those with a household income of less than EUR 500 assess their life with a score of 5.95, whereas people with a household income exceeding EUR 2,000 assess their life with a value of 7.71. Slovenians (aged 21 to 56) are mostly satisfied with their family life and substantially less with their employment. 90% of respondents aged 21 to 56 are ‘fairly, very or completely’ satisfied with their family life; only 2% are unsatisfied (see Table 26). There are almost no differences between genders; the same is true with regard to education levels. The satisfaction of people aged 21 to 56 with employment is considerably lower. Only one-sixth of respondents are ‘fairly, very or completely’ satisfied (see Table 27). Gender differences are small, but large with regard to attained education; higher education is associated with a significant rise in satisfaction with employment. Work as a value (still) ranks very high. On the scale of significance (0-10) Slovenians rate work with an 8.3, which is the second highest rating among the countries included in the survey (see Figure 13). The Slovenians also value their leisure time highly, whose significance is rated with 8.18 (see Figure 14). Figure 12: Satisfaction with life1, selected countries, 2002, average value, scale (‘0’ very unsatisfi ed, ‘10’ very satisfi ed) DK CH FI I SE l NO 1 NL 1 AT 1 IE 1 BE 1 ES UK DE I IT I IL I SI CZ I FR I GR I PT I PL I HU I Source: European Social Survey, 2002. Note: 1The question reads as follows: ‘Considering all things, how satisfied are you with your life?’ Figure 13: Signifi cance of work in the life of an individual, selected countries, 2002 The Way We Live 51 Figure 14: Signifi cance of leisure time in the life of an individual, selected countries, 2002 GR 1 SI IT 1 PL ZI IL 1 ES 1 PT 1 CH 1 AT l BE 1 FI 1 HU 1 FR 1 SE 1 CZ l NO 1 DE l IE 1 DK 1 NL 1 UK 1 DK FI 1 SE 1 SI Z3 AT ES NO IL 1 IE 1 GR l BE 1 CH 1 UK 1 DE 1 IT 1 PL l CZ 1 HU 1 PT 1 FR 5 6 7 8 9 105 Source: ESS 2002. Note: average value on a 0-10 scale (‘10’ very important). 2.3 Satisfaction with health and the health care Slovenians assess their health relatively low. By this indicator too, Slovenia is ranked within the lower third of the European countries included in the survey. In Slovenia, 54% of the inhabitants assessed their health as good (the sum total of answers ‘very good’ and ‘good’), while the percentage of the European countries included averaged 56.4%. There are large differences between the groups of respondents when assessing their health. Women, for example, assess their health on average lower than men. Health is assessed as good by 48.1% of women and 61.1% of men. This can partly be attributed to the effect of the higher average age of women due to longevity, and partly to the effect of social stereotypes; in their social interactions women are much more ready to admit their potential health problems than men. Through socialisation, men and women learn to react to bodily conditions in different ways. The presence of a disease is less stigmatising for women (‘the weaker gender’) because power and health have traditionally been considered male values. Therefore, women are more inclined to report disease symptoms than men who, on the other hand, are Figure 15: Assessment of health, share of answers ‘very good’ and ‘good’, selected countries, 2002 (in %) expected to endure diseases ‘stoically’, without complaining, and to deal with the problem ‘like a man’. Men tend to discuss disease symptoms quite rarely, whereas a chronic disease may ‘naturally’ compromise the attributes of their virility in general (White, 2002:149). With this issue, social norms partly reflect overestimated gender differences in assessing health. Among respondents up to 45 years of age, 60% to 80% assess their health as good, while with respondents aged over 60 years this percentage varies between 20% and 25%. Being strongly correlated with education and income, the relationship between the self-perception of health and age is more complicated than it might seem. In fact, the score increases with income and education by age groups. Respondents of all age groups with a household income of less than EUR 500 assess their health as good in smaller proportions than those respondents whose household income exceeds EUR 2,000 (31.1% against 61.9% in the 45-60 years age group). The same also applies to education; the higher the education the higher the health score. This shows the presence of a psychosomatic element in the health self-assessments, which obviously strongly reflect the health condition of individuals and, through that, the stress caused by increased actual and potential social risks. Figure 16: Assessment of the situation of the health care by country, selected countries, 2002 CH IE BE DK AT NL NO IL UK GR SE FI ES IT FR SI PL CZ PT HU i BE AT FI DK CH IL FR NL NO ES SE CZ UK DE SI IT GR IE PL HU PT i i i i i ;=] i rü i i i i 1—i i Xu i p i i b i 1 ZU i 1 i 1 z: 0 Source: ESS, 2002. Source: ESS 2002. Note: average value on a 0-10 scale (‘10’ very good). 52 Social Overview 2006 Slovenians are not very satisfied with the health care. According to the ESS data, the functioning of the health care in 2002 was scored with 4.75 (on a 0-10 scale). The Slovenian satisfaction with the health care is one of the lowest among the countries covered by the survey. The same is true of the remaining three post-socialist countries included. The expectations regarding health in those countries are anyway and as a rule higher because they emerged from socialist systems. Against such a frame of reference, any change results in a lower level of satisfaction. A higher satisfaction is observed both in countries with a wider health care network and in those where there are no streamlining programmes underway. Older and lower educated people are more satisfied with the health care in Slovenia (people with a primary school education rate it with 5.36 and people with a higher education with 4.38). Dissatisfaction is somewhat higher among the unemployed and housewives, as well as among the higher income brackets. 2.4 Perceptions of the wider societal environment 2.4.1 Trust in institutions In Slovenia there is a high level of trust in family and low trust in political institutions. It is easier for people to trust the institutions with positive attributes ascribed. Thus, symbols of the informal, cultural and economic institutional environment and values of knowledge and economic stability are ranked high on the trust scale, while symbols of the political environ- ment score low (Rus and Toš, 2005). People trust their family and relatives the most, followed by the education system, the Slovenian tolar and the Bank of Slovenia, while trust in political parties, the National Assembly, and the church and clergy is remarkably low (see Table 28). The relatively high level of trust in political and national institutions recorded in the early 1990s dropped sharply until 1998; trust in the church and clergy is notably low, while trust in family and the education system is high. Data for 1991-1998 show serious distrust of political parties and the National Assembly (less than 10% of people trust them), trade unions and the church with clergy, followed by the government, courts of justice, the Prime Minister (who enjoys less trust than the President of the Republic), the army and the police. On average, less than 50% of respondents expressed trust in these institutions. On the other hand, trust in the family (around 90% throughout the analysed period) and the education system has been traditionally strong, and a rising trend has been observed in trusting the media, the Slovenian tolar and the Bank of Slovenia (and banks in general).. In 1999-2005, trust in political and national institutions oscillated, while the already high trust levels in the family and the education system rose further. At the turn of the 1990s many institutions surpassed their previously extremely low levels of trust, notably the trade unions, the media and the church, whose levels of trust were rising. Political parties and the National Assembly enjoyed the lowest trust while economic institutions (including banks and the tolar) Table 28: Trust in institutions, Slovenia, 1995 and 2000-2005 (in %), sum total of responses ‘I trust completely’ and ‘I trust considerably’ 1995 2000 2001 2002 2003 2005 Family, relatives 89.7 93.6 91.0 88.1 95.0 94.4 Education institutions 71.6 82.7 80.3 77.2 83.3 77.3 Bank of Slovenia 45.8 68.7 68.2 60.0 57.7 61.9 Slovenian tolar 55.2 69.2 69.8 64.6 66.1 61.8 Banks 40.2 65.5 65.5 58.0 56.5 58.6 European Union n.a. 41.0 41.8 42.2 56.3 54.8 Economy, enterprises 28.8 53.2 45.3 42.4 51.9 50.8 Human Rights Ombudsman n.a. n.a. n.a. 51.4 55.3 50.8 UN n.a. 51.0 49.9 41.6 53.6 49.3 Army 29.0 53.3 45.9 38.9 53.1 47.8 Trade unions 14.5 39.9 36.3 40.6 44.1 44.4 Police 28.3 53.1 46.9 40.0 44.6 40.8 Media 25.7 52.2 46.1 36.1 47.1 38.6 NATO n.a. 44.7 38.4 31.5 36.0 37.9 President of the Republic 36.3 59.2 55.6 45.9 42.1 36.6 Government of the Republic of Slovenia 27.9 43.9 41.3 29.7 35.8 35.0 Prime Minister 32.4 48.3 48.6 36.2 39.5 35.0 Courts of law 25.7 45.3 41.7 35.6 36.4 32.6 Church and clergy 21.1 30.1 26.8 21.4 24.3 25.2 National Assembly 10.1 23.6 17.7 14.6 22.7 20.8 Political parties 4.5 13.6 9.4 6.3 10.1 11.4 Source: Slovenian Public Opinion Polls Database, Ljubljana: CJMMK, IDV, Faculty of Social Sciences. Note: data for 2004 are not included due to methodological incomparability. ‘n.a.’ not available. The Way We Live 53 Figure 17: Trust in the national parliament, average Figure 18: Trust in politicians, average estimate1, estimate1, selected countries, 2002 selected countries, 2002 DK CH NL FI SE NO BE HU UK IE FR IT AT DE GR ES IL CZ SI PT PL 0 1 2 3 4 5 6 7 8 910 01 Source: ESS 2002. Note: 1average estimate on a 0-10 scale (‘10’ I trust completely’). DK 1 SE 1 FI 1 CH 1 NO 1 NL ] ZI AT HU BE IT 1 GR 1 ES 1 UK 1 IL 1 DE 1 FR 1 PT 1 IE 1 CZ 1 PL Figure 19: Trust in the police, average estimate1, selected countries, 2002 Figure 20: Trust in the legal system, average estimate1, selected countries, 2002 FI 1 DK 1 NO CH 1 SE 1 DE 1 IT 1 IE 1 AT ZZI GR 1 IL ZI UK FR 1 NL 1 BE 1 ES 1 PT 1 CZ PL 1 HU 1 SI DK FI i IL i NO Xd GR I3 CH ZI AT ] SE DE i IT i NL ^n IE 2 HU 5 UK FR 1 BE zzi ES ZJ 5 CZ 1 PL 0 1 2 3 4 5 6 7 8 910 0 1 Source: ESS 2002. Note: 1average estimate on a 0-10 scale (‘10’ I trust completely’). still scored high. Data for 2003-2005 indicate a slowdown in this trend and a decline in trust. Trust in political parties, the church with clergy and national institutions (except the army) remains weak while trust in the family, relatives and the education system continues to be strong. Slovenia falls into a cluster of countries with distinctive distrust of institutions. The ESS data for 2002 show that the population of 20 European countries generally ascribes the lowest trust in politicians (3.87; Slovenia 3.07), followed by the European (4.74; Slovenia 4.65) and national parliaments (4.88; Slovenia 4.04). From among the six institutions covered – the parliament, the police, the legal system, politicians, the European Parliament and the UN – the residents of 20 European countries have the highest trust in the police (arithmetic mean of 6.15 on a 0-10 scale). The lowest level of trust in the police can be found in the four post-socialist countries (the least in Slovenia – 4.89, and the most in Czech Republic – 4.98), while the highest trust has been established in the Scandinavian countries (e.g. Finland 7.95). The biggest variation across countries is observed in the trust in the legal system. Trust in the legal system is particularly low in three post-socialist countries (Poland 3.68; Czech Republic 3.81 and Slovenia 4.28). Among the EU15, ratings in 2002 were low in Portugal (4.26), Spain (4.31), Belgium (4.39) and France (4.83) and high in the Scandinavian countries: Denmark (7.13), Finland (6.75) and Norway (6.35). 2.4.2 Trust in other people Trust in other people involves expectations about other people’s actions. It is a prerequisite for participation in society and the most frequently used indicator of social capital at the macro level. The level of trust in anonymous others (people without a clearly perceived identity with whom we have no lasting contact) is followed up by answers to questions about the anticipated conduct of other people (can the majority of people be trusted or does one have to be cautious in one’s contacts with other people; do the majority of people try to act honestly or do they try to take advantage of others and are people in general willing to help others or do they only care about themselves. The answers are the reflection of people’s (first-hand or second-hand) experience of the actions of others. In Slovenia trust in others is low. The patterns of trust in other people generally resemble those relating to trust in institutions since it is indeed part of the same phenomenon. According to the SJM data, 15.5% of the adult citizens interviewed trusted others in 1995, and 84.5% were of the opinion that one should be cautious in relations with (anonymous) others. The proportion of ‘the cautious’ remained equally high throughout the 1990s, i.e. between 82% and 85%. From 2000 to 2003, the data show an increase in trust (to 32.1% in 2003); the measurement for 2005, however, indicates a new 54 Social Overview 2006 decline of trust down to 17.8%. Only the future surveys can indicate the direction of the trend. With a score of 3.9844, Slovenia is ranked among the European countries with the minimum positive collective expectations regarding people’s actions. Among the ESS countries, Slovenia is in the same group as Greece (last place with a 3.63 value), Portugal (4.16), Poland (3.69) and Hungary (4.08). Trust in others is the highest in the Scandinavian countries where it averages between 6 and 7. The highest trust levels can be found in Denmark (6.99), Norway (6.94) and Finland (6.46). Trust is also high in the Netherlands and Switzerland (see Figure 21). Figure 21: Trust in other people, average estimate1, selected countries, 2002 DK NO 1 FI i SE NL J 1 CH 1 IE 1 AT 3 UK ES 1 IL 1 BE 1 DE 1 IT 1 FR ZZI CZ m PT 3 HU SI PL 1 GR 0 1 2 3 4 5 6 7 8 910 Source: ESS 2002. Note: 1average estimate on a 0-10 scale (‘10’ I trust completely’). In Slovenia (and in Eastern and Southern Europe) the image of an egoistic and unsympathetic environment is prevailing. Within the context of measuring and expressing trust and co-operation, the distributions of answers to the following question are also quite interesting: ‘Would you say that people in general are willing to help others or do they only care about themselves?’. The average estimates in countries referred to above oscillate between 3 and 5. In 2002, the average estimate in Slovenia was 4.24, which is Figure 22: Personal experience of criminality1 and feeling of safety, selected countries, 2002 (in %) FI FR UK 1 SE 1 BE l CZ 1 ES 1 DK 1 PT IH IT m PL rj NO 3 HU CH 1 IE 1 GR 1 IL 1 SI AT DE 1 the highest assessed solidarity among the four post-socialist countries included in the survey. The highest ratings were given in the Scandinavian countries and Western Europe (averages between 5 and 7), whereas in terms of answers they are classified similarly as with trust in other people. The prevailing assessment is that people in general are willing to help others, which is particularly true of Denmark (6.12), Norway (6.09) and Sweden (6.01). Among all countries included in the survey, the lowest ratings given to solidarity were established in Greece (3.01) and Poland (3.16). 2.4.3 Criminality - feeling threatened Slovenians, Austrians and Germans have the least experience with violent criminality. In the 1997-2002 period, violent criminality in most of the countries covered by the ESS was indirectly or directly experienced by 20% to 34% of respondents, mostly in Finland (34%). The Scandinavian countries can generally be found high on the scale (see Figure 22), while the fewest such encounters were reported by Slovenia, Austria and Germany (11%). Assessing on the basis of real personal experience, one could actually suggest that these environments were safe. However, the indicator of feeling safe or threatened, which is of a more subjective nature, paints a somewhat different picture (see Figure 23). The Scandinavian countries, which in 2002 were placed relatively high regarding the reporting on experience with such offences, do not rank quite so high considering their perception of (potential) endangerment. 10% of Slovenian and 12% of Finnish respondents feel highly endangered, while even more Finnish (36%) than Slovenian respondents (29%) feel very safe. We can thus conclude that a negative personal experience is not (fully) conveyed into feelings of potential threat. Based on these findings, no evident correlation can be established but it would be worthwhile to look for it in trust in constitutional institutions. The ESS data show that it was Finland where citizens in 2002 showed the highest level of trust in police, while this was the lowest in Slovenia (see Figure 19). Figure 23: Feelings of safety1, sum total of answers ‘very safe’ and ‘safe’, selected countries, 2002 (in %) AT SI NO DK FI CH IL SE NL BE DE PT ES IT HU FR IE PL GR CZ UK Source: ESS 2002. Note: 1the question reads as follows: ‘Have any of the household members been a victim of a burglary/assault?’ Source: ESS 2002. Note: 1the question reads as follows: ‘How safe do you feel walking through the neighbourhood in the evening?’ 0 0 On a 11-degree scale (0 – one should be cautious with people, 10 – most people can be trusted). The Way We Live 55 2.5 Perception of development trends in society (1995-2005) The SJM surveys provide a series of retrospective indicators whereby the respondents evaluate medium-term trends in various social areas from the current point in time. Accordingly, the respondents compare the situation such as it is now with the situation which in their opinion prevailed a certain number of years ago. The comparisons include the majority of the most relevant areas of social life, primarily those related to the socio-economic situation of the population and the functioning of a democratic political system. The selected time frameworks range from 1995 onwards. Considering that the period of the retrospective assessment in 1995 was shorter (by 5 years, i.e. compared with 1990), the ratings relate to the time following the transition to a market economy and a multiparty system. What we are interested in are the perceptions of changes within the democratic system: which of the respondents’ perceptions show increasing or decreasing trends and where there are no changes whatsoever. The Slovenians have been noticing more pronounced positive shifts from 1995 onwards in the fields of education and democratic rights, and to a certain extent also in the field of the health care and the general standard of living. This perception is, however, weaker than one might have expected in light of the data on the increase in prosperity of the majority of population that was presented in previous chapters. This indicates significant discrepancies between the statistical reality and the actual experience. The largest improvements perceived by the Slovenians relate to education opportunities (see Table 29 and Figure 24). That the possibilities are (significantly) better today when compared with the reference point in the past was the opinion of 33.6% of people in 1995 and 59.4% in 2005, followed by the ratings of democratic decision-making (33.0%) where in 1999 to 2003 a decreasing trend can be observed. The rise in the 2005 survey is probably related to the proximity of the (last) parliamentary elections and therefore, only the subsequent surveys will indicate in which direction this trend will move. Similar observations may be found in the perceived respect for human rights, i.e. another major indicator of the level of democracy. Younger people evaluate development trends more positively, with the exception of aspects which affect them most directly (having and providing for children, housing). The lowest scores have been established within the 45-60 years age group that also regards future development much less optimistically. We could say that this group felt the transition in a more direct way than other age groups. There are no systematic differences between the education groups or employment status. The unemployed evaluate the trends somewhat worse than the employed, but the differences are not large. Considering income, differences can in particular be observed in assessing democracy and legality; members of higher income brackets estimate these trends more positively than members of lower income brackets. A possible explanation could be attached to theoretical discussions on the legitimacy of a democratic system, which suggest that a system is more democratic in the eyes of those who are economically more successful within the system. Figure 24: Perceptions of improvement trends, Slovenia, 1995-2005 period (in %) Education possibilities Democracy of decision-making Respect for human rights Health care How do people live Legality Impact of academic research on government policies Having and providing for children | Possibility of obtaining housing ~\ Possibility of obtaining employment [] 0 10 20 30 40 50 60 70 80 90 100 Source: SJM 1995-2005. CJMMK at the Faculty of Social Sciences. Table 29: Perceptions of development trends in society1, Slovenia, 1995-2005 (in %) 1995 1997 1999 2001 2003 20052 average % in 10 surveys 1995-2005 negative estimates 20053 Education possibilities 33.6 38.7 36.9 52.1 53.9 59.4 42.8 16.7 Democracy of decision-making 41.0 40.3 29.0 27.2 27.6 38.7 33.0 21.6 Respect for human rights 33.0 34.7 24.6 25.4 24.6 31.4 29.0 30.5 Health care 16.6 17.4 17.4 24.0 19.2 23.9 19.0 41.2 How do people live 17.2 15.9 18.5 20.6 19.2 25.7 18.6 47.2 Legality 14.8 14.9 11.9 13.9 12.1 15.4 13.9 28.6 Impact of academic research on government policies 19.0 15.1 7.5 13.5 11.7 14.3 13.2 27.8 Having and providing for children 8.3 7.5 8.1 12.5 11.9 13.1 9.6 60.2 Possibility of obtaining housing 6.3 4.2 7.5 7.6 6.5 6.3 6.3 76.5 Possibility of obtaining employment 3.8 2.8 7.2 7.8 5.2 4.4 4.9 82.0 Source: SJM 1995-2005. Notes: 1The questions reads as follows: ‘Would you say that when you compare today’s life in our country with the circumstances about five years ago the circumstances regarding the listed items are much better, better, approximately the same, worse or much worse today?’ (SJM1995-2003). ‘If you compare today’s life in our country with the circumstances about ten years ago…’ (SJM2005). Sum total of the answers ‘much better today’ and ‘better today’. 2Longer time frame of comparisons. 3Share of the assessments ‘much worse today’ + ‘worse today’. 56 Social Overview 2006 2.6 Life optimism/pessimism Conclusion When thinking about the future, some people are quite worried (pessimists), while others see the future through rose-coloured glasses (optimists). Their assessment of life optimism or pessimism is therefore a good expression of the general dis/satisfaction with life. The average adult Slovenian is a moderate optimist; optimism decreases with age. In 2005, Slovenians assessed their optimistic/pessimistic attitude45 with 6.62 (on a 0-10 scale). In the age group of up to 25 years, the average score was 7.13, and with the age group of 60 years and above the score was slightly lower, i.e. 6.30. It is interesting that optimism is at its lowest level within the 45 to 60 years age group. The reasons could be looked for in the fact that there is fear of losing one’s employment in the relatively least favourable period of life present in the ‘younger part’ of this group, whereas the ‘older part’ is approaching retirement in relatively less favourable circumstances than was the case with previous generations. Optimism increases with the education level. The average estimate of the population group with a primary school education is 6.18, with vocational training 6.60, with elementary school or upper-secondary education 6.72 and of the respondents with a tertiary education 7.35. The influence of household income is slightly less pronounced (6.22 in the income bracket with less than EUR 500 and 6.89 in the bracket with an income above EUR 1,900), which could signify the higher importance (of the lack) of adequate education within the context of a changeable labour market. Optimism is somewhat more prominent in the group of the employed (6.82) than the unemployed (6.47). On one hand, the fear of losing a job has a similar negative impact on their optimism as the loss of employment. On the other hand, due to the small sample of the unemployed it is impossible to separately observe the unemployed who lost their employment and first-time job-seekers. As a rule, these are young and better educated people and therefore their optimism is proportionally higher. Slovenians look upon their future with moderate optimism and positively evaluate changes in the living standards and conditions in time. However, they evaluate the latter lower and in a smaller proportion than one would have expected in light of the statistically measured changes to living conditions. Although we cannot give a comprehensive answer, we can attribute the discrepancies to the discord between the retrospective assessment and the perceptions of the current living environment. In other words, the ex post subjective perceptions hardly reflect positive shifts since a respondent’s perspective is strongly characterised by the presence of current problems. Because of their proximity, the latter always make the present moment look worse and thus create an unfavourable reference point for the ex post comparisons. Accordingly, the past seen from the present always seems better than it actually was ‘at the time’. Nevertheless, policy-makers should understand the extremely negative ratings given to the development shifts as an important indicator, since they show the image of development trends as seen by the Slovenian public. This certainly is an important message for policy-makers. How would you defi ne yourself on a 0-10 scale, where 0 means that you are a big pessimist and 10 that you are a big optimist? (SJM 2005/1). II. Slovenia – A Long-living Society Slovenia – A Long-living Society 59 Introduction The ageing of society and/or its long living are considerably tem of the increasingly (over)burdened support networks and new phenomena that were predicted long ago; however they mutual relationships they offer numerous opportunities and have been overlooked by policies in the majority of states, pose challenges. Social security systems have been adapted to including Slovenia. Long living is a consequence of the current needs to a considerable extent and provide relatively opposite effects of improved living conditions resulting in the good security and at present do not cause an unacceptable prolongation of the life period on one hand and of the decline burden on public finance. They meet the needs of the present in the number of births on the other hand. The outcome is demographic structure; however, they will not entirely meet an intensified decline in the level of the natural increase. In the needs of the future demographic structure. Slovenia, it has been negative since the second half of the 1990s. Net migration has been positive, however until 2004 The ageing of the population means alteration in the age it was relatively low. The age structure of the population has structure of a population in the direction of an increase in the therefore changed, while the dependency ratio has been on relative importance of the elderly and decrease of the relative the rise. The share of children has been decreasing while the importance of the young46. This is a process every society share of the working age population and the share of elderly has to face sooner or later; European countries are the first people have been increasing. At present, this process is still to face it. Throughout Europe, almost without exception, slow (due to relatively significant demographic losses in both all countries are responding in a similar way. They seek, World Wars), however it could already become critical in the test and/or introduce policies concerning older generations next century and later on, when large generations born after (who are old, retired or could retire) and check, change and the Second World War will enter the elderly population group improve policies oriented to younger generations. The size while the share of children and the share of the working age and structure of the population are the result of people’s population will start to decrease. individual decisions and their living conditions; every time we take our decisions in the specific context of society and The structure of the population and, even more, its perspec- values, however, we take them by ourselves. In the second tive (i.e. projections) are increasingly becoming a source of part of the Social Review we therefore present those changes social concern. The population situation and development can that have taken place since the end of the 1990s till today have a restrictive impact on social development or require which characterise Slovenia as a long-living society; the fundamental changes to the development paradigm. Not only opportunities related to it along with the resulting challenges through the system of social security but also through the sys- and problems. Box 12: Key definitions A society is a long-living one if it is mainly composed of members who have already lived for a long time (they are old) and if its younger members can also expect to live for a long time. An important element of a long-living society is a restructured but equal attention paid to all age groups in order to provide for social inclusion and (a new, different) intergenerational solidarity. There is no full agreement on what constitutes the length of the period of youth and at what age old age starts. In a demographic meaning, these limits are set at the ages of 15 and 65, respectively. According to demographic statistics: The young are people aged 0-14; The elderly are people aged 65 and over; The very old are people aged 80 and over. The working age population includes all people aged 15-64 and/or 15 and over (according to the ILO definition: Labour Force Survey). The ageing index is the ratio of old population (aged 65 and over) to young population (aged 0-14). The dependency ratio is the ratio of the sum of the elderly (65+) and the young (0-14) populations to the working age population (15-64). The old-age dependency ratio is the ratio of the elderly population to the working age (aged 15-64). Natural increase is the difference between the number of live-births and number of deaths in a calendar year. Net migration is the difference between the number of immigrants and the number of emigrants in a calendar year. Total increase is the sum of the natural increase and net migration in a calendar year. Projection of the population is the computation of the future size and structure of the population, usually elaborated in several variants. Life expectancy at birth is the average number of years expected to be lived by a generation of live-born children if the age-specific mortality rate during their life span equals the age-specific mortality rate in the calendar year for which the indicator was calculated. (continued on the next page) There is no consensus on how long the youth lasts and at what age old age starts. 60 Social Overview 2006 Box 12: (continued from the previous page) Fertility rate is the ratio of live births and the average number of women in their reproductive age. Birth rate is the ratio of live births to the average population. Reproductive age is the period when a woman is aged 15-49. Total fertility rate is a sum of age-specific birth rates in a calendar year. It represents the average number of live-born children that would be born by a woman living till her 50 birthday if her birth rates equalled the birth rates in the observed calendar year. Total marriage rate is the sum of age-specific rates of first marriages (between the ages of 15-49) in a calendar year. It represents the average number of first marriages that would be entered by a woman or a man living till their 50 birthday if their nuptiality were equal to that of the observed calendar year. Total divorce rate is the sum of age-specific divorce rates in a calendar year. The calculation of rates takes into account the duration of a marriage and not the age of married people. It represents the probability of a divorce within 30 years after entering into a marriage if the frequency of divorces in the cohort of marriages were to equal the frequency of divorces within the observed calendar year. Active population is composed of employed and unemployed persons. Labour force (in the LFS survey) means people who during the reference week (from Monday till Sunday) performed any type of work for payment (in cash or kind), profit or family budget, or were not working but had jobs from which they were temporarily absent. Unpaid family workers, persons on maternity/paternity leave and workers on temporary or permanent lay-off are included as well. According to data from the population census, all people who were employed, self-employed or acted as unpaid family workers at the time the census was conducted form the active working population. Employed population working part-time describes people who usually work less than 36 hours a week. Non-active population is people aged 15 and over who are not classified among the active working population or unemployed persons. Activity rate is the percentage share of the active population in the working age. Employment rate is the percentage share of employed or self-employed population in the working age popu-lation. Unpaid family workers are persons who are neither formally employed nor self-employed but who, in the week prior to the survey, worked on a family farm, were engaged in a family craft or enterprise or any other form of family gainful activity and did not receive regular payments for their work. Unemployment rate is the percentage of unemployed people within the active population. 1. THE DEMOGRAPHIC DEVELOPMENT The history of demographic development in Slovenia has been marked by three significant turning points. They coincide with three periods: with the end of the 19th century, beginning of the 1980s and start of the 21st century. In the last years of the 19th century the fertility started to decline. At the beginning of the 1980s, the average age of women at first childbirth started to increase, life expectancy at birth exceeded the age of 70 and the total fertility rate dropped below 2.1. The ageing of the population intensified. In the first years of the 21st century, the consequences of the described changes resulted in a decrease in those groups of the population that are essential to the further social and economic development of Slovenia. In 2000, the number of women in their reproductive age started to fall, in 2003 the number of elderly people exceeded the number of young people for the first time while in 2004 the share of the working age population (aged 15–64) stopped rising. This share will start to decrease within a few years. 1.1 Size and age structure of the population In the middle of 2005, Slovenia’s population was 2 million. That is 25% more than in 1953 and, according to the Euro-stat’s projections, 5% more than in it will be in 2050. In the 20th century the population of Slovenia increased slowly; at first due to a significant negative net migration and later due to an increasing decline in the natural increase. The population increase was the fastest in the 1970s when the natural increase was quite high and the net migration was the highest seen do far. After 1996, the population of Slovenia has only been growing due to immigration. In 1993, the natural increase was negative for the first time, the following three years it was a zero increase and since 1996 the negative increase experienced has been more intensive every year. The negative natural increase results from the long-term decline in the birth rate and the prolongation of life. The population has been ageing. For the population’s social and economic development, its age structure is more important than its size. At the beginning of a demographic transition a rejuvenation of the population was observed, while towards the end and after a demographic transition, the population is ageing. Measured by the average age of the population, the ageing of the population in Slovenia started in the middle of the 20th century: in 1921, the average population age in Slovenia was 29 years, in 1961 it was 32 years and in 2004 it was 40 years. Ageing of the population is a process triggered by a decline in fertility and Slovenia – A Long-living Society 61 Figure 25: Shares of the young (aged 0-14) and shares of the elderly (aged 65 or over) in the population of Slovenia, 1921-2042 (in %) 35 30 25 20 15 10 5 0 1921 1931 1941 1951 1961 1971 1981 1991 2002 2012 2022 2032 2042 Source: SORS, Eurostat. Notes: Data for 1951 are estimated on the basis of 1948 and 1953 census data. No data are available for 1941. ¦ 0-14 D 65+ the prolon-gation of life. Its intensity can be increased or decreased by migration trends, but cannot be redirected. The ratio between the working age population (aged 15-64) and the non-working age population has been changing in favour of the latter. During the period of the fertility decline, the ratio between the working age population and the non-working age population has changed by an increase in the share of the working age population; the burden of non-working age population to the working age population was falling since the share of young people (low birth rate) has been decreasing faster than the share of elderly people has been growing. In the long term, however, the decline in the birth rate and the prolongation of the life of elderly people result in a decrease in the share of the working age population and in an increase in the share of young and elderly people. We are currently witnessing such a turn in Slovenia. In Slovenia the age dependency ratio was 42.2% in 2004 while in the same year it was 53.7% in both France and Sweden. After World War II, the share of active population in the working age population was increasing until the beginning of the 1980s when it started to decrease. The increase was the result of the increased rate of economic activity of women since the male rate was decreasing throughout all this time. In 1961 male activity rate was high because of a large share of the farming population that is economically active through until the late years of their life. The reduction of the share of farmers, extension of schooling and early retirement, in particular following the country’s independence, have reduced the activity rates of elderly men as well as young men. Following the Second World War, the economic activity level of women was considerably lower than that of the men, however it was increasing up to the beginning of the 1980s due to the entering of women in the labour market; since then, it has been gradually decreasing (see Table 30). The decrease in the female activity rate is caused by the same factors as for men: especially extended education and early retirement. Figure 26: Shares of the working age population (aged 15 - 64) in the total population Slovenia, 1921-2042 (in %) 72 70 68 66 64 62 60 58 56 54 52 1921 1931 1941 1951 1961 1971 1981 1991 2002 2012 2022 2032 2042 Source: SORS, Eurostat. Notes: Data for the 1951 are estimated on the basis of 1948 and 1953 census data. No data are available for 1941. 62 Social Overview 2006 Figure 27: Age-specifi c activity rates for men, Slovenia, 1961-2002 Censuses 100 90 80 70 60 50 40 30 20 10 0 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 Source: SORS. s7 ¦<>-_, ______ - 1961 ' 1 1981 ' t \\ \ 1 \ N- / A ' I I / ' \ ' — ' / \__ Figure 28: Age-specifi c activity rates for women, Slovenia, 1961-2002 Censuses 100 T 90 80 -70 60 -50 40 -30 20 10 -0 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 The share of the working age population will soon begin to fall. Within just 20 years it will reach the 1961 value. In order to maintain the present ratio between the economically active and economically non-active population, the activity rate of working age population should be increased. We can choose between the prolongation of activity to a higher age, the earlier start of economic activities or a combination of both. Table 30: Shares of the active population in the working age population (aged 15-64), Slovenia, 1961-2002 censuses (in %) 1.2 Fertility All Men Women 1961 70.7 88.1 54.9 19711 69.8 81.1 59.0 1981 73.7 81.1 66.6 1991 71.0 76.7 65.4 2002 68.9 74.2 63.4 S Source: SORS. Note: 1Emigrants are included in the 1971 calculations. Figure 29: Total fertility rate, Slovenia, 1950-2004 3.2 t 3.0 2.8 2.6 2.4 2.2 2.0 1.8 1.6 1.4 1.2 1.0 - 0.8 0.6 0.4 0.2 0.0 During the 20th century fertility declined throughout Europe. Following the Second World War some European countries experienced an increase in the number of births, the »Baby Boom« as we call it, however the rise in fertility was only temporary. The decline continued in the middle of the 1960s. In less developed European countries where fertility was relatively high prior to the Second World War, the decline in fertility following the Second World War continued. In the middle of the 1970s it significantly dropped and, after ten years, the level of annual fertility indicators in those countries was among the lowest in Europe. Prior to the Second World War in Eastern European countries (socialist countries), excluding Czechoslovakia, the period fertility was considerably above the European average. In spite of that, following the Second World War the period fertility at first slowly declined then stagnated and started to decline quickly only at the beginning of the 1990s. The transition from socialist to capitalist social systems affected fertility so strongly that, by the end of the 20th century, the total fertility rate in those countries was the S Source: SORS. Slovenia – A Long-living Society 63 lowest in Europe and in the world; it ranged between 1.1 and 1.4 children per woman. Even though Slovenia belonged to this group of countries, a fast decline in its total fertility rate has already started in 1980. Slovenia is in the group of European countries with the lowest fertility. In Slovenia, the total fertility rate, representing the average number of live-born children per woman in a calendar year, has been declining for a good 100 years. In the final years of the 19th century, the total birth rate totalled to 5 to 6 children per woman. In 1980, the total fertility rate was 2.1 and twenty years later just 1.2. Reasons for the decline in the total fertility rate are equal to those seen elsewhere in Europe. One of them is the postponement of births to a later age. In Slovenia, due to the postponement of births to a later age the total fertility rate compared to completed fertility (a generation indicator) is underestimated by approximately one-quarter. The process of postponing births to a later age started at the beginning of the 1980s. At the end of the 19th century a woman was aged 26 to 27 at the birth of her first child. Until the middle of the 1970s, the average age of a woman at the birth of her first child had fallen to 23 years and this age has been increasing ever since. In 2004, the mentioned age exceeded that from the end of the 19th century; it was 27.5 years. After several years of stagnation within the 1999-2003 period, the total fertility rate slightly increased. In 2005 it was 1.26 children per woman. In future years, these values will probably rise slightly yet they will be well below the values providing a positive natural increase. The number of births does not only depend on the fertility level but also on the number of women in reproductive age. However, this number has already started to drop. Very few women remain childless. There are approximately 7% of childless women among women aged 40-44. This share is similar in all social groups. The difference is small even between the urban and non-urban population. However, the difference becomes noticeable with the second and, in particular, with the third child. The probability of a woman and/or a couple deciding to have their third child is much greater if the woman lives outside of a town or a city. The average number of children per woman decreases with the level of education and occupational demands. At the beginning, deliberate birth limiting started in towns and cities in higher social classes among more educated and employed women and gradually spread to all classes and groups. For this reason, at the beginning of the 20th century differences between social classes were significant whereas they are small nowadays. In spite of that, it is still true that those women who are more educated or work in more demanding professions have fewer children. Of the women born in the years 1957-1961, those with an uncompleted primary education gave birth to the highest number of children and those with a higher or university level of education gave birth to the lowest number of children. On average, the former gave birth to 2.2 children and the latter to 1.7. When the same women are grouped according to the nine main occupational groups, the differences are even larger, from 1.7 to 2.4 children. By far the highest fertility rate is held by women farmers (the group of farmers, foresters, fishers and hunters), i.e. 2.4 children per woman. Women working in non-industrial occupations, women who operated machines and equipment or performed simple, non-demanding works on average gave birth to 1.9 children; women working in the legislature, high officials and managers on average gave birth to 1.7 children. The fertility level is lower in towns and cities than outside towns and cities. Women born in the 1957-1961 period on average gave birth to 2 children if they lived in non-urban areas and to 1.7 children if they lived in a town or a city. The difference is not significant; according to statistical definitions half of Slovenia’s population lives in towns and cities. There is also a similar difference among the seven largest towns of Slovenia. Women in Kranj, Velenje and Novo mesto gave birth to the highest number of children (1.9), while women in Koper, Celje and Ljubljana gave birth to a somewhat lower number of children (1.7) and women in Maribor gave birth to the lowest number of children (1.6). In Ljubljana, fewer women decided to have their first child than in Maribor; however those women in Ljubljana who decided to have a first child more often decided to also have a second and third child than the women of Maribor. The process of declining fertility is connected to several changes in people’s living conditions. Since the mortality rate of children and youth dropped, the need to give birth to several children in order for some of them to survive no longer exists. The restructuring of production, together with the transition from rural to urban life-styles, transferred solidarity from the family to the community; for ensuring (economic) security in old age children are no longer necessary and it is also no longer necessary to remain married. More and more often men and women have to choose between family life and their profession (mobility and promotion). These changes in life-styles are reinforced by some changes in fundamental values and processes of secularisation and individualisation. Modern means of birth control provide an effective form for birth control and/or realisation of the planned number of births. The fertility level of immigrants cannot considerably change the fertility level in Slovenia. Many people believe that the fertility rate of Slovenia’s population can be increased by immigration since the fertility rate of immigrants is greater than the fertility rate of the native population. However, in the long run this is not true. Completed fertility of immigrants born before 1964 was even slightly lower than completed fertility of people born in Slovenia; however, it is slightly higher in younger generations. The reason probably lies in the different religious beliefs of immigrants. Since the difference is small and the share of immigrants in the population is low, their fertility cannot significantly change the fertility indicators for the total population of Slovenia. In addition, 64 Social Overview 2006 Figure 30: Number of women in their reproductive age (aged 15-49), Slovenia, 1921-2042 600,000 500,000 400,000 300,000 200,000 100,000 0 1921 1931 1941 1951 1961 1971 1981 1991 2002 2012 2022 2032 2042 Source: SORS and Eurostat. Notes: Data for the 1951 are estimated on the basis of 1948 and 1953 census data. No data are available for 1941. until now the completed fertility of the second generation of immigrants born in Slovenia, with a non-Slovenian mother tongue, has always been lower than the completed fertility of women born in Slovenia with Slovenian as their mother tongue. Women with Serbo-Croat as their mother tongue born in the 1957-1961 period on average gave birth to 1.8 children if they were born in Slovenia and 1.9 children if they were born outside Slovenia. The number of births will grow for some years and after 2015 it will start to fall. According to the basic variant of the Eurostat’s projection, the total fertility rate in Slovenia should increase from the present value of 1.2 children per woman to 1.5 children by 2027; it should remain at this level until 2050 (see Table 35). The immigration increase should be approximately 6,000 people per year, with a slight decrease around 2015. On the basis of such assumptions, the number of births (due to the postponement of birth to a later age) is supposed to rise for some years and decrease after 2015. In 2034, only 15,000 children are expected to be born. In the event that the total fertility rate is lower than expected in the basic projection variant, the number of children will be lower and vice versa. 1.3 Mortality – prolongation of life At the beginning of the 20th century the life expectancy at birth in Europe was approximately 45 years whilst it is currently already 80 in the most developed countries. In the first half of the century, the prolongation of life was rapid while it was slower in the second half. The first life expectancy data on Slovenia refer to the 1930-1932 period when life expectancy at birth was 52; it is currently 77 years. Social and economic changes have a considerable effect on life expectancy. Up until the end of the 1950s, life expectancy rose particularly due to the decrease in the infant mortality, young children mortality and the reduction in mortality caused by infectious diseases. Over time, the mortality of children and mortality due to infectious diseases has declined in such a way that any further reduction did not considerably affect the prolongation of life expectancy at birth. In addition, new causes of death occurred that are more or less related to social and economic changes seen in the 20th century: alcoholism, smoking and traffic accidents. This was also why the prolongation of life expectancy slowed down or even stopped in the 1960s. For the purposes of the further prolongation of life expectancy it has been necessary to combat diseases related to smoking and excessive alcohol consumption, to reduce the number of deaths in traffic accidents and reduce mortality due to diseases of the circulatory system and neoplasms which have become the main causes of death after the eradication of infectious diseases. Success in combating the mentioned diseases has been attained since the beginning of the 1970s. Life expectancy at birth began to rise again, however, it differed from that seen in the first half of the 20th century in two characteristic ways: (1) it was slower; and (2) it was the consequence of the reduction of mortality in higher age groups. The development so described was quicker in Western than in Eastern Europe. Consequently, since the end of the 1960s the differences have begun to grow. The greatest differences were noted in the 1990s when they were affected by consequences of the economic crisis in Eastern Europe. At that time, the difference between Western and Eastern Europe expressed in life expectancy at birth was 11-15 years. At the beginning of the 21st century, the difference between the EU states with the shortest and longest life expectancies at birth was 12 years for men and 7 years for women. Slovenia is positioned in the middle of the scale for European countries and in the lower part of the scale for EU countries according to the life expectancy; the position of women is slightly better than the position of men. Slovenia has acquired this position gradually. From research (Šircelj, 2003) in which not all European countries are included, it can be concluded, for instance, that Slovenian women could expect a slightly longer life than Italian women at the beginning of the 1960s when life expectancy values at birth were the most uniform in Europe. In 1965, the life expectancy of Slovenian and Italian women was the same whereas five Slovenia – A Long-living Society 65 years later, i.e. in 1970, Italian women already had a 2 year longer life expectancy than Slovenian women. Such a difference has been maintained up till today. From the beginning of the 1960s, the life expectancy of men in Slovenia was shorter than in Italy, however, the small difference in 1960 gradually rose and reached 4 years in 1995. Since then, it has oscillated around this value. This means that in ‘competing’ with its Western neighbour, Slovenia lost most of its benefits in the 1960s when stagnation and even a fall in life expectancy for men was noted in Slovenia. These differences could not be made up for in later periods. If the difference is converted into years, this means approximately 15 years of delay: the life expectancy at birth currently seen in Slovenia was recorded in Italy approximately 15 years ago. In Slovenia, there are many possibilities for the prolongation of life, particularly for men. Slovenia experienced stagnation in the prolongation of life in the first half of the 1990s as a result of the transition to a new social system. The reason lay in the increased mortality in the middle-aged population and not in a stagnation of the decrease in death rates in all age groups; the mortality of children and the elderly continued to drop. In the second half of the 1990s, mortality began to decrease again in all age groups. Consequently, life expectancy measured at birth in the period from 1990-1992 to 2000-2002 was prolonged for men by 2.85 years and for women by 2.98 years; more than in any decade since 1960. This is clearly a good sign which, however, does not change the fact that there are still many possibilities to prolong life, particularly for men in Slovenia. The too high mortality of men, particularly those in medium ages, remains one of the main health problems in Slovenia. In the 1998-1999 period probabilities of dying for men aged 15-24 years old were approximately the same as at the beginning of the 1990s (see SA: Tables 41 and 42). With the prolongation of life, the difference in life expectancy between men and women increased. In the 1931-1933 period, the difference in life expectancy at birth between men and women in Slovenia was 4 years in favour of women. Since then, it increased, particularly in the 1960s and reached the value of 7.5 years. This difference was maintained until the beginning of the 1990s. It reached 8 years and since then it has decreased again to 7.5 years. If the trend from the past years continues, Slovenia might gradually approach those European countries with the smallest difference between men and women. In Iceland, this difference was 3.5 years in 2003, whilst in Sweden and the Netherlands it was 4.5 years etc. According to the basic variant of the Eurostat’s projection, the gender difference should be reduced to 5.4 years by 2050 in Slovenia; the life expectancy at birth should be prolonged to 79.8 years for men and 85.2 years for women (see Table 35). Life expectancy at birth is an indicator that summarises the mortality rate of all age groups. Since particularly the life of the elderly has recently been prolonged, Table 31 shows the relevant values for the ages of 0 and 65 years. In the last decade, life expectancy measured at the age of Figure 31: Life expectancy at birth by gender, EU25, 2003 Spain i Women Men i France i i Italy i i Sweden i i Finland l i Austria i Luxembourg Cyprus l i Germany l i Malta i i Greece l i Belgium i i 1 Slov enia i Portugal i U. Kingdom i Ireland i Denmark i Poland Czech R. i i Lithuania i i Slov akia i i Estonia i i Latv ia i i Hungary 50 60 70 80 90 100 Source: Eurostat. 66 Social Overview 2006 Table 31: Life expectancy at birth and at the age of 65 years in Slovenia during the 1931-2002 period (years) Year Life expectancy at birth Life expectancy at the age of 65 years men women men women 1931-1933 50.1 54.2 11.2 11.6 1952-1954 63.0 68.1 12.1 13.2 1960-1962 66.3 71.9 12.1 13.8 1970-1972 65.4 72.9 11.5 14.5 1980-1982 67.5 75.1 12.7 15.7 1990-1992 69.4 77.2 13.2 16.6 2000-2002 72.3 80.2 14.4 18.9 Source: SORS. 65 years has been prolonged to a greater extent than life expectancy at birth. If the death rates occurring among the population older than 64 years do not change in the following 20 years, today’s 65-year olds will live another 14.4 years (men) or 18.9 years (women)47. If mortality continues to drop, the average number of years lived by a birth cohort will increase. The age of 65 years will be reached by an increasing number of people. Under the mortality conditions prevailing in Slovenia in the 1931-1933 period, 515 women reached the age of 65 years out of 1000 live-born women and 411 men reached the age of 65 years out of 1,000 live-born men. In the conditions prevailing at the beginning of the 21st century, 887 women and 748 men are reaching this age. Opinions of experts differ on a further decrease in mortality. Some believe the possibilities of a further prolongation of life expectancy are limited and that life expectancy will never exceed 85 years. If this thesis is realised, the majority of the population would reach the age of 75 years and only a few would live more than 95 or 100 years. This would mean an explicit concentration of death at high ages. Others believe that a new phase of life prolongation has already begun. In the last two decades, the mortality rates of the population older than 75 years and even for centenarians decreased in the majority of developed European countries. This may be a sign of the beginning of new changes. According to the basic variant, life expectancy at birth in Slovenia should be prolonged to 79.8 years for men and 85.2 years for women by 2050. This certainly does not change the upper limit of life. It cannot be determined yet. Therefore, achievements in a certain environment can only be assessed by comparing the achievements with the achievements seen in other environments. The comparison shows that Slovenia is somewhere in the European middle according to life expectancy at birth, and among those countries with the lowest infant mortality rates in Europe and in the world according to the infant mortality rate. 1.4 Migration Europe is a centre of international migration trends. More people emigrated than immigrated from the majority of European countries until the end of the 1970s. Not earlier than in the 1970s, when more and more European countries completed the demographic transition and thus exhausted their emigrating potential, the countries changed progressively from predominantly emigrant to predominantly immigrant countries. Most Eastern European countries achieved a similar level of migration potential exhaustion. Their migration increase is not positive yet although they have become interesting for Far East immigrants as an intermediate station on their way to the West. When the population of Eastern European countries gained the freedom of movement in 1989, it was expected that migration in the east-west direction would strongly increase. They did increase but they have never achieved the predicted extent of migration. The nature of immigration in Europe has been changing. In the first years after the end of the Second World War, displaced persons and refugees from Eastern Europe as well as the return immigrants from former colonies immigrated particularly to Western Europe. In the 1960s and 1970s, temporary working migrants started to come to Western, Central and Northern Europe from Southern Europe along with former Yugoslavia and afterwards from Turkey and North Africa. This was a period of economic prosperity which coincided with less numerous war generations entering the working age. The oil crisis in the 1970s and xenophobic reactions of the domestic population to foreigners who wanted to settle in their host countries for good resulted in the adoption of restrictive policies which limited immigration to immigration through a family member, to political refugees and asylum applicants. Consequently, the size of immigration flows has been falling since the second half of the 1970s. The immigration structure consists of ever more refugees, asylum-seekers and illegal migrants. Nowadays, every European country has a certain part of its population with foreign citizenship. The smallest European countries Regional data are shown in the SA: Table 44. Slovenia – A Long-living Society 67 Figure 32: Share of foreigners, EU25, 2004 (in %) Luxembourg Latvia Estonia Austria Cyprus Germany Belgium Greece Ireland Spain France Sweden Denmark U. Kingdom Netherlands Italy Malta Slovenia Portugal Finland Czech R. Poland Hungary Lithuania Slovakia z 10 15 20 25 30 35 40 Source: Eurostat. (Andorra, Luxembourg, Liechtenstein) and Switzerland (22%) (see Figure 32) have a major share of foreigners. Slovenia is a country with a small share of foreigners; there were 2.4% foreigners in the middle of 2005. In the second half of the 20th century, Slovenia changed from a predominantly emigrating to a predominantly immigrating region. The net migration had been negative until the end of the 1950s. Since then, it has been positive every year according to official data. The only exceptions were in 1991 and 1992 when more people left Slovenia than returned to Slovenia for political reasons, and in 1998, probably due to difficulties encountered with the collection of data. The level of net migration changed in line with the economic development and/or employment possibilities. The largest positive net migration was noted in the 1970s. It accounted, on average, for 7,700 people per year in the 1975-1979 period. Moreover, it was the only decade when women predominated numerically in the Slovenian migration increase. The immigrants came particularly from Croatia, Bosnia and Herzegovina and Serbia. It was there where most of the population also emigrated. These migrations had the nature of internal migrations until the end of 1991. Migrations beyond the border of former Yugoslavia (so-called external migrations) were rare until the end of 1991 (see Table 32). Slovenia (and/or Yugoslavia) had not been attractive for immigrants from Western and Northern Europe. Besides, the emigration of the Slovenian population to these countries that had been made possible on a larger scale since the middle of the 1960s were legally not of the nature of migration. Those who temporarily went abroad to work, including their family members, were not considered emigrants but as being temporarily absent from Slovenia. They maintained their permanent residence in Slovenia. The expression ‘zdomci’ was used for these people. It was not known how many of the Slovenian population left for abroad temporarily each year and how many returned every year. According to census data, which must be underestimated (data were collected with the aid of relatives or neighbours of those who emigrated), more than 50,000 people lived outside Slovenia (Yugoslavia) in the 1971-1991 period. If these people had been considered emigrants the net migration of Slovenia would have become positive only at the end of the 1970s or in the 1980s. The independence of Slovenia caused a temporary change in the direction, size and structure of migration flows; however, the traditional migration flows were soon restored. After Slovenia’s independence, the strongest migration flows were observed between Slovenia and other countries of former Yugoslavia as before its independence. It is evident from Table 32 that the citizens of these countries represented 73% of all immigrants to Slovenia in 2004 and 52% of all emigrants from Slovenia in the same year. The migration of Slovenian citizens rank second in numerical terms. The net migration of Slovenian citizens was positive in the 1995-1999 period, however it is getting smaller from year to year. It became positive in 2000 and has been increasing since then. Slovenian citizens emigrate mostly to Germany, Croatia and Austria. Those emigrating to neighbouring or nearer countries represent approximately half of all emigrants with Slovenian citizenship. There are approximately half women and half men among immigrated and emigrated Slovenian citizens, whereas men predominate among foreigners. The age structure also differs. The immigrated Slovenian citizens are older than the immigrated foreigners, whereas the emigrated Slovenian citizens are older than emigrated foreigners (see Table 33). The 0 5 68 Social Overview 2006 Table 32: Immigrants to Slovenia and emigrants from Slovenia by citizenship, 1996-2004 1996 1998 2000 2002 2004 Immigrants All 9,495 4,603 6,185 9,134 10,171 Slovenian citizens 1,500 857 935 1,432 1,574 Citizens of other republics of former Yugoslavia 6,916 2,848 4,458 6,275 7,386 Citizens of other European states 736 679 615 1,109 890 Citizens of the states from Asia and Africa 116 114 92 176 218 Citizens of the states of America, Australia and Oceania 68 47 75 119 103 Citizens of unknown citizenship 159 58 10 22 0 Emigrants All 2,985 6,708 3,570 7,269 8,269 Slovenian citizens 803 705 1,559 2,624 2,265 Citizens of other republics of former Yugoslavia 1,606 4,804 1,378 3,856 4,329 Citizens of other European states 371 667 478 570 1451 Citizens of the states from Asia and Africa 76 104 43 126 108 Citizens of the states of America, Australia and Oceania 51 45 52 87 56 Citizens of unknown citizenship 78 383 60 6 60 Source: SORS. Table 33: Mean age of immigrants to Slovenia and emigrants from Slovenia, 1996-2004 (years) 1996 1998 2000 2002 2004 Immigrants Slovenian citizens 35.9 37.2 40.4 39.0 38.8 Foreigners 30.2 30.5 31.8 32.5 31.7 Emigrants Slovenian citizens 33.9 35.8 35.2 36.8 36.1 Foreigners 28.6 34.7 37.1 33.2 33.4 Source: SORS. average age is higher than 30 years in all groups. These are very high values. In 1990, the average age of all immigrants irrespective of their citizenship was 26 years and of emigrants 28 years. The average age of immigrants increased by 10 in only two years and of emigrants by 8 years in four years. This great and rapid increase in age indicates an essential change in the break up of migration flows. Political and ethnic migration replaced economic migration. After a few years when the flows of economic migration were restored, the average age was reduced, however, to a higher level than prior to the country’s independence. According to data on the gender and age structure of immigrated and emigrated aliens, women remain in Slovenia more often than men. In the second half of the 20th century, the extent of internal migration (migration inside Slovenia) was much greater than the extent of external migration. Deagrari-sation, industrialisation and urbanisation have stimulated migration, particularly from the countryside to towns. At the end of the 1980s, a weak opposite migration flow was seen, however, from bigger towns to suburban areas. Internal migration rates (changes of permanent residence per 1000 inhabitants) were the highest in the 1960s and 1970s. It was reduced until the end of the century and increased slightly again in the first years of the new millennium. Table 34: Internal migrations, Slovenia, 1965-2004 Period: Average annual number of migrations Migrations per 1000 inhabitants 1965-1969 59,800 35.4 1970-1974 54,800 31.3 1975-1979 59,100 32.1 1980-1984 52,700 27.4 1985-1989 43,100 21.7 1990-1994 37,000 18.5 1995-1999 28,700 14.4 2000-2004 30,735 15.4 Source: SORS. Migration is characteristic of the young. Migration is most frequent in the period when the young people are looking for a job and creating their own families. Since both entering on the labour market and family formation are being postponed to higher ages, the average age of internal migrants is rising slowly but persistently. In the 1982-2004 period, the average age of those who migrated within Slovenia increased Slovenia – A Long-living Society Figure 33: Age specifi c rates of internal migration by gender, Slovenia, 1982 and 2004 69 100 T 90 -80 70 60 50 40 30 20 10 0 ¦\ 1982 Women / \ 2004 Women l '* ; A V* ,' % \\* * * % s Vk * * * j/ *\% * ¦^wK^X. 5^ ' ' ^----m-** / » ii*^*% _ * " =*=^=i .—--"S" 0-4 5-9 10-14 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 75-79 80-84 85-89 Source: SORS. by 5 years, i.e. from 25 to 30 years. This is half a year more compared to the mean age of women at birth of their first child. In the same period, the mean age of migrants has been increasing due to the decreasing share of migrants younger than 24 years and due to the increasing share of migrants older than 34 years. The proportion of people aged 25-34 years remains unchanged at around 30% (see Figure 33). Women migrate more frequently than men. The internal and external migration has been the main factor determining the spatial distributions of the population and its age structure. In the areas with high emigration rates population was ageing quickly, whereas in the areas with high immigration rates, particularly in the cities and towns, the process of ageing was slower or even a rejuvenation was observed. There are at least three consequences of such developments: the ever greater concentration of the population in the areas of big cities, the depopulation outside these areas and the demographic threat to the latter. We speak about a demographic threat when natural growth is clearly insufficient to maintain the population size. This means that the size of the population will continue to decline in these areas unless immigration flows are for any reason directed to those regions. The possibility of the realisation of such a scenario is very small. 1.5 Projections of the population until 2050 The projection of the total number of the population and its age structure is very interesting in itself but it is urgent for assessing the consequences in the future48. The results of the projection depend on the initial situation and on the assumptions of how the population will react in the future and what the results of policies in a country will be. The assumptions of the projection of the population of Slovenia carried out by the Eurostat envisage a further increase in life expectancy for men and women and an increase in the total fertility rate in Slovenia. The migration increase should rise from the current extent to a little less than 7,000 persons per year, whereas the total size of the population will not change fundamentally. Since 2004 when the population was 1,997,000 in the middle of the year, the population will first slightly increase to around 2,020,000 inhabitants until 2015, and will then start to decline and reach (given the described assumptions) 1,897,100 inhabitants in 2050. Under these assumptions the population will develop as shown in Table 35. In the 2004-2050 period, the size of individual age groups of the population will change differently under these assumptions. The number of the population older than 65 years will almost double and at the same time the number of the population aged 14 and younger and those aged 15-64 old will decline. The changed number of the population by individual age groups will result in changes in the age structure of the population. The shares of the population aged 65 years or over will increase from the current 15% to 31%, whereas the share of those aged 15-64 will decrease from 70% to 56%. The changes in the age structure of the population would considerably increase public expenditure if all other parameters remained unchanged, particularly the sample of retirement and activity (the economic consequences of changes in the number and structure of the population are described in the Chapter 7). Since the financing of this would considerably increase the tax burden on employers and employees and, consequently, worsen business conditions and competitiveness, the only possible way of balancing needs and possibilities would be an increase in activity rates. The economic consequences of changes in the number and structure of the population are described in a chapter on economic and fi nancial consequences of ageing of the population. 70 Social Overview 2006 Table 35: Assumptions and certain results of the basic projection of the Slovenian population in 2004 and projections in 2010-2050 (according to Eurostat) 2004 2010 2015 2020 2030 2040 2050 PROJECTION ASSUMPTIONS: Life expectancy: - men 73.5 73.9 75.0 76.1 77.9 79.0 79.8 - women 81.1 81.2 82.0 82.8 83.8 84.6 85.2 Total fertility rate 1.25 1.27 1.38 1.46 1.50 1.50 1.50 Net migration 1902 5879 3809 5298 6998 6878 6653 PROJECTION RESULTS: Number of the population on 30 June (in thousands) 1,997 2,016 2,019 2,017 2,005 1,963 1,897 0-14 years 288 272 272 273.1 256.3 237.2 244 15-64 years 1,405 1,412 1,383 1,327 1,241 1,165 1,061 65 years of age and over 303 332 364 416 507 561 592 80 years of age and over 59 80 94 104 129 180 200 Old-age dependency ratio 21.6 23.5 26.3 31.4 40.9 48.1 55.8 Population by age group in % 0-14 years 14.5 13.5 13.5 13.5 12.8 12.1 12.9 15-64 years 70.4 70.0 68.5 65.8 61.9 59.3 55.9 65 years of age and over 15.2 16.5 18.0 20.6 25.3 28.6 31.2 Growth index (year 2004 = 100) Number of inhabitants on 30 June 100.0 101.0 101.1 101.0 100.4 98.3 95.0 0-14 years 100.0 94.2 94.1 94.6 88.7 82.1 84.5 15-64 years 100.0 100.5 98.4 94.5 88.3 82.9 75.5 65 years of age and over 100.0 109.7 120.1 137.3 167.4 185.0 195.4 Source: SORS: http://www.stat.si/pxweb/Database/Dem_soc/05_prebivalstvo/07_05197_projekcije/07_05197_projekcije.asp It is assumed that the average retirement age in the follow- more active than retired people). If such an increase is not ing twenty years will rise from the current 58 for women achieved, the number of retired persons will exceed the and 60 years for men to 65 years, which would enable to number of the active population within a period of thirty maintain the relationship between the active and retired years. population above the quotient of 1 (meaning there will be Figure 34: Projection of the total number of population by age groups, Slovenia, 2004-2050 (in thousands) 2100 1800 1500 1200 900 600 300 2004 2010 2015 2020 2030 2040 2050 Source: SORS: http://www.stat.si/pxweb/Database/Dem_soc/05_prebivalstvo/07_05197_projekcije/07_05197_projekcije.asp 0 Slovenia – A Long-living Society 71 Figure 35: Share of age groups in the total Slovenian population, projection 2004-2050 (in %) 100 90 80 70 60 * ', 65 y ears and ov er 15-64 y ears 50 40 30 20 10 0 2004 2010 2015 2020 2030 2040 2050 Source: SORS: http://www.stat.si/pxweb/Database/Dem_soc/05_prebivalstvo/07_05197_projekcije/07_05197_projekcije.asp Figure 36: Growth index of population size, Slovenia, projection 2004-2050 200 0-14 y ears 180 - 160 140 120 100 80 60 —X— 0-14 years -D— 15-64 years -¦— 65 years and over Number of the population on 30 June 2004 2010 2015 2020 2030 2040 2050 Source: SORS: http://www.stat.si/pxweb/Database/Dem_soc/05_prebivalstvo/07_05197_projekcije/07_05197_projekcije.asp Figure 37a and b: Employment rates by individual age groups in 2004 and projections1 a: men 100 90 80 70 60 50 40 30 20 10 0 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 Age groups b: women 100 90 80 70 60 50 40 30 20 10 0 15-19 20-24 25-29 30-34 35-39 40-44 45-49 50-54 55-59 60-64 65-69 70-74 Age groups Source: (2005) Country Fiche – Slovenia. IMAD: Ljubljana. Note: 1with and without taking changes in retirement behaviour into consideration. 72 Social Overview 2006 2. THE FAMILY AND ITS NEW FORMS Creating the conditions for the early social and economic independence of the young, for helping those setting up a family while starting a career as well as children-raising families may, among other things, significantly enhance the quality of life and improve the population’s prospects. Hence, this Chapter describes in some detail the characteristics of the family in Slovenia and the related development trends and challenges. Late modernity has been characterised by the transformation of individuals’ life courses49. That is to say, individual phases of these courses have been prolonged, shortened or fused. Transitions (from youth to adulthood, from education to employment, from employment to unemployment and back, from adulthood to old age etc.), where these changes are most apparent, are becoming atypical. One of the most characteristic life-course changes is the transition from youth to adulthood. Since life courses, particularly individual transitions, have become unpredictable, every transitional period may trigger an identity crisis (Ule and Kuhar, 2003: 8). Such changes also significantly affect the family whose form and structure have been undergoing continual change. Despite this, however, it has persisted since pre-industrial societies as an institution of privacy with two key social functions: reproduction and socialisation. 2.1 The family: concepts and definitions A definition of the family as such is in a way a ‘social directive and diagnosis’ that impacts and reflects the moral-ideological conceptions and functioning of social and family policies. What is generally accepted in society as moral and hence normative is usually rewarded by political measures, and vice versa. With a linguistic (definitional) intervention into reality we actually create this reality rather than merely neutrally describing it. Hence a definition and classification of the family must satisfy (at least) three criteria, i.e. they must be: (1) distinguishing (distinctive) – they must comprise those vital dimensions that constitute family life while distinguishing them from similar forms of people’s everyday life such as the household or cohabitation (marriage); (2) inclusive (non-discriminatory) – they must include all those types and styles of family life that actually occur without discriminating among them on the basis of ideological judgements (e.g. same-sex families, being only exceptionally recognised as a legitimate and legal family type); and (3) operative (operational for social-policy, statistical and research purposes) – they must be efficient enough to be used within the state administration and for research and intelligence-gathering. Today a number of different definitions of the family exist that can be roughly grouped into statistical and sociological ones. Statistical definitions of the family are predominately reduced to an economic union where people are tied to a particular locality. The family is a union of two or more persons living together in one household, who are tied together by marriage, cohabitation and/or blood. Statistically, the family is distinguished from the household by the presence of cohabitation and/or parenthood50. The household is a union of people who live together and share fundamental life resources such as shelter, food and other living essentials, or a person living alone. Sociological definitions of the family are relatively numerous and diverse. They differ from the statistical ones in that they determine the family as being constituted by the parent-child relation as a social relation. They mainly define it as ‘a union of at least two generations’ and ‘a social institution that cares for child/ren’. Care for child/ren is the single (truly) constitutional element of the sociological definitions of the family and one that demarcates it from cohabitation, marriage, household and kinship, where a parent-child relation is neither necessary nor vital. According to the sociological definition, the family is thus: (1) a group of persons living in one household and comprising at least one child and at least one adult who are tied to one another by marriage or cohabitation and the parent-child relation (Nowotny, Fux, Pinnella, 2004:28) or, as was formulated by the UN within preparations for the International Year of the Family in 1994; (2) at least one (adult) person or a group of persons caring for child/ren and being recognised as such in the member states’ legislations or customs. Just like there are several definitions, there are also several classifications of the family: 1. Statistical classification: • married couples with or without child/ren; 49 A life course means an individual’s journey through their life cycle from birth to death. The notion of travelling refers to the life route or biography. 50 Statistically, a childless couple, a couple with child(ren) and a single parent with child(ren) are all families. In this, no role is played by how old the child is as long as they have not yet got a family (spouse or cohabiter and/or child) of thier own. Hence, a household of one parent and a child with thier own family, for example, is not statistically considered a family. A household of one adult and their grandchild(ren) or siblings living together without parents are also not families in statistical terms. Slovenia – A Long-living Society 73 • unmarried (cohabiting) couples with or without child/ren; and • mothers or fathers living together with their child/ren. 2. The UN’s classification: • nuclear families51, including both biological and social nuclear families, i.e. two-parent, one-parent and adoptive nuclear families; • extended families, including those consisting of three- or more-generations, polygamist and tribal extended families; and • reorganised families, including those of one parent and one social parent, of one parent and members of a commune, and of one parent and his or her same-sex cohabiter or spouse (Cseh-Szombathy, 1992:5). 3. For the purposes of the Social Overview, we are using a typology that distinguishes six family types (see Ule and Kuhar, 2003): • two-parent family (two biological parents); • reorganised family (one biological, one social parent); • one-parent family (biological or social parent); • vertically extended family; • horizontally extended family; and • foster family, institutional childcare. 4. Rener, Švab, Žakelj and Humer (2005) suggested that, considering the family life arrangements in Slovenia, it would make sense to distinguish between two types of families: • nuclear families (two-parent, one-parent and reorganised families); and • extended families, including traditional ones (such as three-generation families) and dispersed ones (geographically separated families maintaining kin contacts and providing support to one another). In Slovenia, two family life styles are highly common although we do not (yet) know much about them: 1. Dispersed extended families, which in our view are the most common family life style in Slovenia. These are formally separate family households (usually of parents and their children but sometimes of siblings or other relatives) who live either at relatively close-by locations (in separate apartment units of one house or in the near proximity) or at different locations but who provide one another with continual support and help at different levels: material, work/service and emotional. 2. Delayed leaving of home or the LAT51 phase. Increasingly more young people in Slovenia are living an extended youth with their parents. Unlike the first family life style, this is one family, albeit it has a ‘half-familial’ life style. The reasons for the postponed leaving of home are various. They may be ‘external’, such as difficulties in attaining economic independence, unemployment, shortage of housing, delayed completion of education etc., or ‘subjective’ such as leisure and the ‘cheapness’ of living at home, harmonious relations with one’s parents, material and emotional security along with high personal autonomy. At the 2002 census in Slovenia, 37.1% of the young aged 25-34 still lived with their parents. 2.2 The transformation of family life Many things that used to be taken for granted in human life have lost importance and social impact over the last decades. We are confronted with daily choices among different possibilities, different life styles or life plans, which all affect the family and family life. One of the most characteristic changes in the traditional life course is the abandonment of traditional adulthood entry. What is meant is the transition from youth to adulthood with parenting and the assumption of responsibility for one’s own family being a key feature of adulthood. The young have been postponing parenthood and family formation or have even stopped desiring them. Although parenthood remains very important for them and they carefully plan it, the actual decision on it depends on whether they have resolved their fundamental life problems (employment, housing) and on subjective factors (the desire to enjoy freedom and autonomy, the sense of being psychologically mature etc.). All European countries have been confronted with delayed parenting in recent years. This is a clear phenomenon of extended youth, which in sociological terms means an interpolation of the so-called ‘LAT phase’ between the periods of youth and adulthood. Other features of adulthood (e.g. completion of education, economic independence from one’s parents, and entry to the labour force) have also been moving on into the thirties. Moreover, increasingly more young people do not even have the desire or capacity to attain a transition to adulthood. This indicates that not only youth but adulthood, with its standard institutions of work and family, has also been experiencing a number of disturbances. Despite the numerous changes, however, the large majority of EU residents, including Slovenia’s, still regard the family as a vital segment of life (Švab, 2001: 186). Family life has maintained its key social functions: reproduction and therapy. What is meant is child socialisation and adult personality stabilisation. Due to the ever more dynamic (and at times chaotic) environment, the family has even been an increasingly important locus of its members’ Living Apart Together (LAT). This is an intermediate phase between family dependence of the young and their living wholly independently from their parental family. It is characterised by economic dependence or semi-dependence on parents along with social independence. 74 Social Overview 2006 Box 13: The family – a source of emotional support Emotional support that family members provide to one another may well be the most important ‘family function’. There is no doubt that in modernity the importance of this function has been rising, even to the extent that some authors have suggested that families are ‘the last emotional and supportive unions, and the last havens in a heartless world’ (Lasch, 1977). The emotionally supportive, therapeutic function of the family, particularly of women (mothers) within them, has clearly been growing to the point when it is often hardly possible to bear it anymore. Research on social networks has confirmed that what the sociologist Zaretsky noted thirty years ago also applies to Slovenia: ‘In capitalism nearly all personal needs are narrowed down to the family. This is what gives it such flexibility and vitality despite all the predictions of its decline while at the same time it suggests its inner plight: it simply cannot meet the pressures of being the only refuge in a brutal society. The dilemmas that particularly its women are confronted with typically reflect this contradiction: family income may be growing, the technology may ease their work, but they remain subordinate since they are involuntarily isolated and since we expect them in their private isolations to take upon themselves or at least cushion the deepest troubles of this world that we continue to bring before them’ (Zaretsky, 1976). Research of social networks in Slovenia has indicated that family ties are by far the most important area of social support. In general, social networks in Slovenia are relatively small and intense, and thus highly vulnerable (Dremelj, Kogovšek, Hlebec, 2004). Research of youth has also shown that in the large majority of cases, young people experiencing distress turn to their mothers. At the same time, however, a study of youth carried out by the Centre for Social Psychology at the Faculty of Social Sciences revealed that about one-quarter of Slovenian children have missed parental support and encouragement (Rener, 2000, 2002). When in need of help, families do not turn to formal support but much more to non-formal social networks; in both the emotional and material support dimensions. This suggests that non-formal networks serve as a substitute (compensation) for the inappropriate functioning of the formal social networks and support. Researchers (see Ule and Kuhar, 2003) have also found that emotional and material deprivation is the strongest in one-parent families and the weakest in two-parent families. According to some important deprivation indicators, reorganised and extended families are closer to one-parent than two-parent families. The researchers have therefore suggested that formal family support types should be transformed and that non-formal networks, especially those of relatives and friends, should be supported. As a third possibility, they also suggest that local-level ‘family centres’ be formed to provide support and information in the handling of – in particular – administrative and bureaucratic matters for family members’ needs (the study has proven the strong distrust of professional services as concerns e.g. children’s emotional problems). Namely, the centres for social work are mainly focused on curative activities (as well as providing financial aid) while the area of family counselling with regard to everyday life issues remains unorganised. revitalisation. Its importance has also been growing in eco- education and employment styles and the changed relations nomic terms52. That is to say, the number of (unpaid) hours between the public and the private (professional vs. familial worked at home has not dropped in the last century, only the roles), we have been seeing the biggest changes in the family types of work have changed (Rener, 2000). The family has structure precisely in the stage of family union formation (Ule thus maintained (and even enhanced) its importance53, a great and Kuhar, 2002; Ule and Kuhar, 2003). deal is expected from it and such expectations have only been growing (see Box 13). The young have been living in their original families for prolonged periods of time (Ule and Kuhar, 2002; Ule and The diversity of family types (co-existence of different family Kuhar, 2003) and have been deciding on parenthood later in types and family life styles resulting from individuals’ choices) their lives. Increasingly more young people cohabit for at least has been growing. In the late modernity marked by changes some time, i.e. until they have children. Public opinion data in the traditional life course and a growing complexity of show that the importance of formalised marriage has been interpersonal relations and their social organisation, the family declining in the eyes of the young. Nevertheless, parenthood is has been ever more diverse (with nuclear families declining in very important for them, they carefully plan it, but it depends number to the benefit of reorganised and one-parent as well on whether they have resolved their fundamental life problems as same-sex families); its demography has been changing (as (employment, housing) and on personal factors (the desire to a result of lower natality, for example, the number of family enjoy freedom and autonomy, the sense of being psychologi-members has been on a gradual decrease). Due to the changed cally mature etc.). 52 The myth that modernisation, having separated economically productive work from the home, has left families with economic consumption activities alone, has long been refuted. The same goes for the myth that today there is less domestic, i.e. family and household work (Rener, 2000). 53 Only the importance of marriage and family as a social institution has been declining in the family de-institutionalisation processes seen in modern societies, opening up space for the individualisation of family members’ life courses. Slovenia – A Long-living Society 75 Box 14: New fatherhood The concept of active fathering is part of responsible parenting. It is an integral part of the phenomena and social change that families in Western societies have been experiencing for several decades, and it means more active involvement of fathers in family life (e.g. their more active participation in childcare). In Slovenia, the practice of active fathering is still in its beginning phase and mainly seen in values and attitudes (Rener et al., 2005). The formation of a new paternal identity is significantly facilitated by paternal leave (introduced by the Parental Care and Family Relations Act – Official Gazette No. 97/01 – as one of the four types of parental leave, which began to be gradually implemented in 2003 to become fully effective on 1 January 2005). In addition, ‘new fatherhood’ is expedited by fathers’ participation in childbirth and parents’ education classes and by their use of the childcare leave, which the new act stipulates to be an exclusive right of one parent (instead of the mother alone). However, the gap between the formation of paternal identity and fathering practices is still obvious; while at the level of values and attitudes changes have already begun to show, they are less visible at the level of practices. Thus, for example, less fathers took paternal leave in 2004 (62%) than the year before (72%) although, for various reasons, on average they only used 8 instead of 15 (calendar) days; however, increasingly more fathers have been taking unpaid paternal leave. Meanwhile, only negligibly few fathers (1.2%) take childcare leave. Data also show that fathers largely take on care for the household and older children during their paternal leave. When they go back to work, however, they quickly slip back to the traditional division of labour in the family (Rener et al., 2005). This has resulted from the highly developed networks providing help and support to the ‘young’ mother (mainly consisting of grandparents) and employers’ non-understanding (including fathers’ career orientation), with a lack of family-friendly working environments also being a factor. Efficient birth control methods have given rise to the nor- of them. Theoretically speaking, the present low fertility is mative complex of responsible parenthood, which is binding also attributable to the responsible parenting complex, which on both parents. Parenting is seen as an increasingly respon- also includes fathering (see Box 14). sible task in modern society, with the growing responsibility functioning as a burden and barrier when deciding to have At first, changes in the structure of the family led to conjec-a child. Parents wish to do well in child raising even to the tures about it being in crisis, while today they are interpreted point of being afraid of failing. Hence, couples only decide as indicating its successful adaptation to the changed social to have children when they are really able to take good care conditions. The diversity of family types and life styles is Box 15: A crisis of the family or its transformation? Throughout the modern age, people’s family life styles, particularly their family relations, have been a privileged object of desire of large ideologies which had – mainly for the purposes of their own preservation – began to suggest that the family was in crisis. This is actually a clash between two ideological systems (the conservative, with a strict hierarchical structure, and the radically leftist, more open and democratic) in the soft field of the private and individual; it is the mistrust of specific people and their numerous life styles, which are hard to control. Within conservative ideologies, this fundamental distrust usually manifests itself in the discourse about a crisis of the family, which is supposed to be the foundation of the state, the cradle of the nation and the safeguard of morals and values being endangered and undermined by external and internal processes that have recently weakened and injured it. Particularly within the rightwing ideological spectrum, the view is therefore often turned back to a mythical past when families and family life were supposedly better, more stable, more secure, less selfish and more altruistic. However, family life was neither more stable nor static in the past. Like today, family types or forms of the family were numerous and diverse (Flandrin, 1986; Aries, 1991; Goody, 2003); also, there is no historical evidence whatsoever that there were fewer dark sides of family life such as violence, neglect, indifference, poverty, alcoholism and sexual abuse (Puhar, 2004). Two things surface in relation with those speculations that the family was in crisis: Is it not that only a certain conception, a certain ideology of the family is in crisis? And, in addition, who are those (and why?) who interpret family transformation as a ‘loss’ and a crisis? Today’s sociological considerations point to two interesting peculiarities of the ‘crisis-of-the-family’ jargon. Firstly, to the fact that worries about a supposed crisis of the family are nothing new as the crisis discourse has been recurring cyclically throughout modern history. It has always been intensified at times when there was economic depression and political instability and when the population in a certain area stopped growing. The crisis discourse usually has the effect of translating social and political problems into personal and individual ones, thus inciting feelings of guilt. These, however, are not equally distributed. Since women are mainly considered to be primarily responsible for families and their well-being, difficulties in attaining it are often designated as individual and collective women’s fault (Rener, 1995). Secondly, to the fact, that it is not that the family has been in crisis but rather that change and diversity have increasingly conditioned its existence. Moreover, it seems that it is precisely its pluralisation that has enabled it to endure as a social phenomenon (Švab, 2001: 83). 76 Social Overview 2006 questionable only for those who believe that the ideologically most desirable, religiously and legally sanctioned type of the ‘classic’ (nuclear) married couple family with hierarchical relations between the generations and patriarchal relations between the genders should have prevailed for good. Today, the ideal-type nuclear family comprising a married couple of a working father and housewife mother raising their two children represents less than 20% of all families in Europe (Muncie, Langan, 1997: 11). Therefore we should, instead of suggesting that the family is in crisis, acknowledge that new types have evolved in its attempts to adapt to the changes in the contemporary world by trying to achieve, above all, a greater balance between individual rights and social responsibility (see Box 15). The main reason for transformed family types is the family’s internal transformation while broader social changes have also played a role. In itself, the phenomenon of diverse family types is not the decisive feature of family transformation but only its indicator (Švab, 2001: 42). The following social phenomena have led to the pluralisation of family types: marriage deformalisation, rising divorce rates, non-dependence of reproduction on marriage, life style pluralisation etc. What is important is that the transformation of family life has resulted in transformed family types, and not vice versa (Švab, 2001). Due to all these changes, researchers of privacy and of families are faced with a number of dilemmas and challenges. In the process of change, the abovementioned ‘classic’ nuclear family type has been joined by numerous others, e.g. single-parent families, cohabiting couples with children, reorganised families, same-sex parent/partner families etc. As regards the wider social change, two processes conditioning the transformation of families may be highlighted: (1) changes in labour markets, particularly women’s employment, which affects, for example, their childbearing behaviour; and (2) the ageing of the population, which has already significantly affected family life organisation; in the future, its impacts will only grow. However, the statistics do not encompass all the transformations that have characterised family life over the past few decades, or cannot explain them with their conceptual apparatus. Although a vital source of information concerning family life, they only register family types while they do not recognise the reasons for them; family types are not to be equated with family life styles (Švab, 2001). For example, they fail to distinguish between an apparently equal one-parent family that has resulted from divorce from one that has been like that from the start. 2.3 A statistical portrait of families in Slovenia At the last (2002) census, there were 555,945 families living in Slovenia. Compared with the 1991 census, they increased in number, whereas the number of their members declined. This trend has persisted from at least 1971 (see Table 36). Over the 1991-2002 period, the number of one-child families grew. At the same time, childless families also grew in number, but the figure includes families in the so-called empty nest stage – the stage where children have already grown up and moved away. Hence this particular figure cannot be interpreted as a rising number of (reproductive-age) couples that choose to remain childless (although we do know that their number has also been on the rise). As statistics have also detected in Slovenia, the young are deciding to have children increasingly late, after they have perhaps lived in a consensual (either marital or non-marital) union for several years. Over the past few decades, the predominant family type in Slovenia has been a married couple with children; however, its share has been declining. At the same time, a rise has Table 36: Families by type and size, 1971, 1981, 1991 and 2002 Censuses, Slovenia Census 1971 1981 1991 2002 All families 440,679 100.0% 522,314 100.0% 551,899 100.0% 555,945 100.0% Families without children 78,941 17.9% 111,374 21.3% 114,560 20.8% 127,642 23.0% Families with children 361,738 82.1% 410,940 78.7% 437,339 79.2% 428,303 77.0% With 1 child 153,592 34.9% 191,270 36.6% 205,571 37.2% 208,018 37.4% With 2 children 135,401 30.7% 168,371 32.2% 189,562 34.3% 181,865 32.7% With 3 children 48,518 11.0% 38,259 7.3% 34,368 6.2% 32,137 5.8% With 4 children 14,650 3.3% 9,185 1.8% 5,928 1.2% 4,845 0.9% With 5 or more children 9,577 2.2% 3,855 0.7% 1,910 0.3% 1,438 0.3% Average size of all families 3.36 3.20 3.13 3.06 Average size of families with children n.a. n.a. 3.42 3.38 Average size of households1 n.a. n.a. 3.0 2.8 Source: SORS. Note: 1Statistically, a household is a union of residents living together and sharing the fundamental life resources (such as shelter, food and other living essentials) or a resident living alone. ‘n.a.’ not available. Slovenia – A Long-living Society 77 Table 37: Family types, at the 1981, 1991 and 2002 Censuses, Slovenia Census 1981 1991 2002 Total 522,314 100.0% 551,899 100.0% 555,945 100.0% Married couple without children 110,934 21.2% 109,594 19.9% 114, 835 20.7% Married couple with children 336,549 64.4% 325,622 59.0% 294,726 53.0% Unmarried couple without children n.a. n.a. 4,966 0.9% 12,807 2.3% Unmarried couple with children n.a. n.a. 12,408 2.2% 29,285 5.3% All single-parent families 74,831 14.3% 99,309 18.0% 104,292 18.8% - mother with child/ren 65,251 12.5% 85,214 15.4% 89,683 16.1% - father with child/ren 9,580 1.8% 14,095 2.6% 14,609 2.6% Source: SORS. Note: ‘n.a.’ not available. been recorded in the number and share of unmarried couples with children – i.e. so-called cohabitation, which has long ceased to be a mere form of a ‘pre-marital’ live-in union since it often continues after children are born, and is becoming a legitimate family type. That is to say, the number of children born out of wedlock (see Figure 41) has been growing quickly. Growth has also been recorded in the number of one-parent families composed, like in Western countries, in significantly more cases of mothers with child/ren (89,683), although the number of fathers with child/ren (14,609) has also been on the rise. At the 2002 census, 86% of one-parent families were mothers with child/ren and 14% were fathers with child/ren (see Table 37). 2.3.1 Changes in nuptiality and divorciality Individuals’ life courses have been undergoing significant changes in the form of the delay of individual events. The number of marriages has been dropping since the mid-1970s. In a way, marriage is losing its social importance, although the number of re-marriages has been rising. The age at one’s first marriage and the divorce rate have also been on the rise, with the exception of the early 1990s when there was a slight drop in the number of divorces54; this drop is perhaps attributable to the wider social (transitional) changes in society, having brought increased insecurity, unemployment and exposure to poverty. The long-term trend, however, still points to a growing divorce rate. The number of marriages dropped by almost two-thirds between the mid-1950s and 2004. While the number of marriages per 1000 population (i.e. the crude marriage rate) was 9.2 in 1965 and 6.5 in 1980, it reached its lowest point so far in 2005, i.e. 2.9. Slovenia has the lowest crude marriage rate among European countries. Countries with the highest rates in 2004 include Cyprus (7.2), Denmark (7.0), Malta (6.0), Finland and Lithuania (both 5.6). Table 38: Crude marriage rates, crude divorce rates and total divorce rates1, Slovenia, 1955-2005 Crude marriage rates (marriages per 1000 population) Crude divorce rates (divorces per 1000 population) Total divorce rate 1955 9.2 0.8 n.a. 1960 8.9 1.0 n.a. 1965 9.2 1.1 0.10 1970 8.3 1.1 0.13 1975 8.5 1.2 0.15 1980 6.5 1.2 0.15 1985 5.4 1.3 0.19 1990 4.3 0.9 0.15 1995 4.2 0.8 0.14 2000 3.6 1.1 0.21 2001 3.5 1.1 0.22 2002 3.5 1.2 0.25 2003 3.4 1.2 0.24 2004 3.3 1.2 0.24 2005 2.9 1.3 0.27 Source: Recent demographic developments in Europe, SORS. Notes: 1The total divorce rate is the average number of divorces per marriage. If all marriages ended in divorce, the value of the total divorce rate would be 1. ‘n.a.’ not available. Today, divorce no longer implies a discontinuation of the socially prescribed life-course pattern but only a transition in this course, which thereafter continues in a new form of family life (Švab, 2001). 78 Social Overview 2006 Table 39: Total fi rst marriage rates of females1 and mean age of brides at fi rst marriage, Slovenia, 1980-2005 Year Total fi rst marriage rate of females Mean age of brides at fi rst marriage 1980 0.79 22.5 1985 0.64 22.8 1990 0.51 23.7 1995 0.51 25.1 1999 0.48 26.3 2000 0.45 26.7 2001 0.43 27.0 2002 0.43 27.4 2003 0.42 27.5 2004 0.41 27.8 2005 0.37 28.2 Source: Recent demographic developments in Europe, SORS. Note: 1The total fi rst marriage rate of women is the average number of fi rst marriages of women aged 15-49. If all women in this age group got married, the value of the total marriage rate would be 1. The decrease in total first marriage rates has resulted from a smaller frequency of first marriages as well as a rise in the mean age at first marriage. The total first marriage rate of women was 0.79 in 1980 and only 0.37 in 2005 (see Table 39). If the 2005 value does not change in the future, 63% of women will not get married until the age of 50. Over the 1980-2005 period, the mean age of women at first marriage rose by almost 6 years (from 22.5 to 28.2 years). The mean age of men at first marriage also increased to come in at 30.6 years in 2005 (see SA: Table 45). Between the early 1990s (1990-1994) and 2003, the mean age of grooms and brides (including first and all subsequent marriages) also rose – the former by 2.9 years and the latter by 3.2 years. In 2003, the mean age at marriage was 32.3 years for men and 29.2 for women. In 2003, 1.2 divorces were recorded per 1000 population in Slovenia (see Figure 38), which is considerably less than in the EU25 countries, where the figure totalled 2.1. The number of divorces is the biggest in the Czech Republic (3.2), Estonia (2.9) and Belgium (3.0), and the lowest in Ireland (0.7) and Italy (0.8). If the frequency of divorces is judged by the number of divorces per 1000 population, no major changes have occurred in Slovenia over the last 50 years (see Table 38). However, if it is judged by an indicator that takes into account the changing number of marriages (i.e. the total divorce rate), it turns out that it has been rising since the mid-1990s. In 2005, the value of the total divorce rate was 0.27; if it remained the same in the coming years, one-quarter of marriages would end in divorce (while about one-half of marriages would eventually dissolve under the same suppositions in certain developed European countries). Despite the rising trend, the total divorce rate in Slovenia thus remains among the lowest in the EU25 (see Figure 39). In Sweden, Finland, Norway, the Czech Republic, Denmark and Luxembourg the rate was 0.5 in 2003, while in Austria and Lithuania it was 0.4. Figure 38: Marriages and divorces per 1000 population, Slovenia (1960-2004), the EU15 and EU25 (2003) 1960 _ 1965 _ 1970 _ 1975 _ 1980 _ 1985 1990 1995 _ 2000 2001 2002 2003 2004 ¦ Crude divorce rates D Crude marriage rates EU15 2003 EU25 2003 ------------ ------------ ------------ ------------ 0123456789 10 Source: SORS for Slovenia, and Eurostat: Statistics in Focus, 15/2005. Slovenia – A Long-living Society Figure 39: Total marriage rates and total divorce rates, EU25 countries, 2003 79 Cy prus Malta les) ages of fema i Denmark i Portugal i Greece i Italy Finland Spain Ireland i Poland France Total div orce rates Total marriage rates (f irst marri i Netherlands i Lithuania U. Kingdom ™ Germany i Sweden Austria Slov akia Luxembourg i Hungary Belgium Latv ia i Czech R. Slov enia 0 0.2 0.4 0.6 0.8 1 Source: Eurostat. Note: No data are available for total divorce rates in Malta and Ireland. 1.2 1.4 1.6 1.8 2.3.2 Changes in fertility In addition to the abovementioned postponement of marriages, fertility has been declining and the mean age of women at first childbirth has been rising. Fertility already began to drop in the early 1970s. After having stagnated for some years in 1999-2003, the total fertility rate55 slightly increased to total 1.26 child per woman in 2005; this remains over 50% less than in 1955, when it totalled 2.58. Compared with other EU countries, the total fertility rate in Slovenia is among the lowest; only the Czech Republic Figure 40: Total fertility rate, the EU25, 2003 (1.18) and Slovakia (1.20) had lower rates in 2003, while the rates were the biggest in Ireland (1.98), France (1.89), Denmark and Finland (1.76 both); (see Figure 40). Since 1965, when it totalled 24.2 years, the mean age of women at first birth had been falling in Slovenia. It reached its lowest value (22.8 years) in 1975, and thereafter began to rise. In the early 1990s (1990-1994) it reached on average 24.3 years, while in the second half of the 1990s (1995-1999) it already totalled on average 25.6 years. Between the early 1990s and 2005, the average mother’s age at first Ireland I France I Finland I Denmark I Netherlands I U. Kingdom Sweden Luxembour I Belgium I Cyprus Malta I Portugal I Austria I Estonia I Germany Spain Latv ia I Italy I Hungary I Greece I Lithuania I Poland I Slov akia Slov enia Czech R. I 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 1.9 2.0 Source: Eurostat. The total fertility rate is the average number of live births per woman of reproductive age (15-49 years) in a calendar year. 80 Social Overview 2006 childbirth increased by almost 4 years (to 27.8 years); however, it remains somewhat lower than the European average (i.e. 27.9 years in the EU25 and 28.5 years in the EU15 in 2003). The number of extra-marital births has been growing. While slightly more than one-tenth of children were born out of wedlock in 1954, this share totalled no less than 46.7% in 2005 (see Figure 41). The share of extra-marital births did not substantially change in the 1960s and the early 1970s; it actually fell from 9.1% in 1960 to 8.5% in 1970. These data suggest that, like in Western countries, a nuclear-family ideology was also present in Slovenia, favouring marriage as a condition of family life. Marriage began to lose its importance in the 1970s – in 1975, for example, 9.9% of children were born out of wedlock – and especially in the 1980s, when this share rose to 13.1% in 1980 and has since than been rising steeply (see SA: Table 41). The share of extra-marital births varies considerably across the EU25. In 2004, it was the highest in Iceland (63.7%) and Sweden (55.4%). Slovenia is among those countries exceeding the EU25 average. 2.4 Parenthood and family life through the lens of public opinion Slovenia is a family-oriented society. The public opinion data presented in this part of the chapter show that Slovenians demonstrate no anti-family (or anti-natality) orientations, with a large majority of them being satisfied with their family life. In the value hierarchy of Slovenians, family has long held the foremost place. The reasons clearly include an ideologised image of the family. ‘To have a family’ is therefore a socially expected response, being desired in terms of values, and attitudes of the young correspond to this. That is to say, values are the nexus of both highly personal and socially conditioned life orien-tations, attitudes and judgements. Hence public declarations of values must be distinguished from private or personal value orientations. Empirical research of personal value orientations of the young in Slovenia shows that their life plans continue to include a desire to set up a family and have children, although it has a number of objective barriers and rivals in other life goals, such as professional career, personal self-development, enjoyment of life etc. (Ule and Kuhar, 2002). A gap between desires and their realisation has been large everywhere in Europe. Parenthood is a carefully weighed and highly responsible decision for the young which they, when considering it, usually set at the very end of an entire series of preconditions to be fulfilled (employment, housing etc.), i.e. a so-called ‘unbreakable chain’ (Ule and Kuhar, 2002). The young state that the most important condition for deciding to have children is their feeling of being sufficiently mature for such a demanding and responsible task as parenting. A survey among students aged 24 and less (conducted in 2003 on a sample of 400 students) showed that no less than 10% of the respondents saw themselves without children in the next 10 years. Other public opinion surveys, which examined a somewhat older population (i.e. potential parents), also reveal a non-encouraging picture of intentions to have children. That is to say, over 60% of respondents aged 21-29 report that they definitely or probably are not going to have a child in the next three years, while this share totals nearly 70% among those aged 30-38, with the answers of childless respondents not differing with any statistical significance from those having child/ren; see Table 40. Figure 41: Shares of extra-marital births, Slovenia (1960-2005), the EU15 and EU25 (1960-2002) 50 j 45 40 35 30 25 20 15 10 5 0 1960 1965 1970 1975 1980 1985 1990 1995 2000 2005 Source: SORS. Slovenia – A Long-living Society 81 Table 40: Intensions to have children, by age groups, Slovenia, 2004 (%) Defi nitely not Probably not Probably yes Defi nitely yes N%N%N%N % 21-29 years 48 22.2 83 38.4 61 28.2 24 11.1 30-38 years 68 35.1 66 34.0 42 21.6 18 9.3 39-47 years 134 77.0 34 19.5 4 2.3 2 1.1 48-56 years 20 90.9 0 0 1 4.5 1 4.5 All, 21-56 years 493 31.7 183 30.2 108 17.8 45 7.4 Source: SJM 2004/2. Note: The question reads: ‘Do you plan to have a child in the next three years?’ In a study of fertility in Slovenia (Obersnel Kveder et al., 2001), the authors found that nevertheless, almost the entire cohort of women born in the early 1960s gave birth to at least one child until 1995 and that it was impossible to make any definitive conclusions as to what percentage of women from the younger generations would remain childless. On the other hand, a survey carried out by the IVZ in 2005 showed that in Slovenia, the percentage of births given by women aged 35 and over is relatively low compared to other EU countries. Given proper encouragement and conditions, these women could thus potentially still decide to have children. 2.4.1 The public opinion on the family56 Attitudes on family life have not changed substantially over the past decade. Also, there are no significant age- or gender-related differences in attitudes. No less than 93% of people aged 21-56 thus believe that watching the children grow up is the greatest happiness in life, while over one-half agree that the life of those who never had children is empty (see Table 41). Agreement with the latter statement drops with a higher level of education. It is of interest that despite attributing such exceptional importance to children as a source of personal happiness, one-half of respondents think that other things also make life meaningful in important ways. 36.7% of those aged 21-29, and 41.6% of those aged 48-56, agree with the statement that ‘being a housewife is equally fulfilling for a woman as working for payment’. We may say that attitudes on gender roles lean on the acceptance of woman’s double workload as both an employee and housewife also caring for family members in need of help. As regards most attitudes on female and male roles, women are slightly more liberal; however, age and education rather than gender are the variables that most strongly affect those attitudes. In part, attitudes on the female and male social roles can also be inferred from answers to ‘how a woman should be employed in different stages of maternity’ (see Table 42). The majority of respondents (about 90%) believe – regardless of their gender, age and education – that she Table 41: Attitudes on family life, comparison by gender, Slovenia, 2003; the respondent agrees or strongly agrees (%)1 Men Women All People who want to have children should get married. 31.6 22.5 27.0 It is perfectly okay if a couple live together without planning to get married. 71.2 75.8 73.5 It is wise if a couple planning to get married priorly live together for some time. 87.2 81.2 84.1 One parent alone can raise a child equally well as the two together. 23.4 34.2 28.9 Watching the children grow up is the greatest happiness in life. 93.2 92.8 93.0 The life of people who never had children is empty. 54.0 53.6 53.8 Source: SJM 2003/2. Note: 1The respondents were all persons aged 21-56. Table 42: Attitudes on women’s employment, Slovenia, 2003 (%)1 work full-time work part-time stay at home When a couple have not yet got children. 93.0 4.0 2.0 When they have a small child who still does not attend school. 24.2 46.9 27.4 When the youngest child begins to attend school. 50.4 39.9 8.3 After children have left home. 89.7 5.9 2.8 Source: SJM 2003/2. Note: 1The respondents were all persons aged 21-56. The question reads: ‘Outside the home, should a woman work full-time, part-time or not at all in the following cases?’ 56 The data in this section result from analysing the SJM (Slovenian Public Opinion) 2003/2 – International Study of the Family and National Identity – and 2004/2 databases. When repetition of questions allowed this, SJM survey results were used for comparison. The analysis was made on age groups potentially being in different active cycles of family development: 21-29 years, 30-38 years, 39-47 years and 48-56 years. 82 Social Overview 2006 should work full-time before the couple have children and after children have already left home. Almost one-half think that a woman with a pre-school child should work part-time, while one-quarter believe that she should work full-time, and another one-quarter that she should stay at home. Especially those with a lower education are favourably disposed to the opinion that the woman should stay at home until the child begins to attend school. 2.4.1.1 Division of labour in the family The division of labour in the family still shows no clear signs of equality between the partners. The distribution of roles and relations in the family has been, according to research since 1977, rather traditional (Ule and Kuhar, 2003; SJM). It also seems that parents in all family types, including single-parent ones, restrain from involving children in housework, although they thus deprive them of important life and work experiences. That is to say, children are notably absent from those types of family work where they could have participated. Tasks that have already been tied up with women by tradition continue to be primarily their domain. Women do laundry, tidy up and clean the house or apartment, prepare food and cook more than men. Men are responsible for small repairs in the house. The care of family members who are sick and needing help is predominately left to women. Grocery shopping is also mainly their domain, although here men participate slightly more than e.g. in the care of ill family members. The figures on the amount of time spent on household work57 demonstrate an unequal division of domestic labour between genders even more clearly. In Slovenia, women aged 20-74 spend almost 5 hours per day on domestic work (including childcare), which is about two times more than men do (spending slightly more than 2.5 hours); see Table 43. The average time spent on childcare shows approximately the same ratio (nearly 3.5 hours per week by women and slightly less than 1.5 hours by men). In the structure of housework, women in Slovenia spend 88% (and men 49%) of their time on standard household tasks58 while men spend more time (51%) than women (12%) on other household tasks (see SA: Table 48 and Table 49). There are no considerable differences in the division of domestic labour among the nine EU countries included in Eurostat’s 2004 study. On average, women do between 60% and 66% of all housework. Estonian, Hungarian and Slovenian women spend the most time (i.e. about 5 hours daily) on domestic work while women in Sweden, Norway and Finland spend less than 4 hours on it. The most balanced division of labour is seen in Swedish families where men do the greatest share of housework compared with women. Estonian, Slovenian, Hungarian and Belgian men spend more time per day (between 2 hours, 48 minutes, and 2 hours, 39 minutes) for housework than men in other countries included in the study. The amount of time spent by women on childcare alone (excluding other tasks) per day is the biggest in Belgium, Hungary (35 minutes in each) and Norway (34 minutes), Table 43: Division of labour in the family, by gender, Slovenia, 2003 (%)1 Always or usually me Always or usually my partner Both the same Someone else Laundry Men 3.8 80.6 11.8 3.4 Women 90.4 2.0 5.0 2.7 Small repairs in the house Men 83.1 3.8 9.7 3.0 Women 4.6 72.2 19.3 3.5 Care of sick family members Men 5.1 29.6 60.8 1.7 Women 44.0 3.8 48.3 1.5 Grocery shopping Men 11.7 31.9 53.8 2.1 Women 41.9 6.5 49.2 2.3 Tidying up and cleaning the house or apartment Men 4.2 52.6 38.6 4.2 Women 63.3 2.7 31.3 2.7 Food preparation, cooking Men 8.0 58.2 27.8 5.1 Women 63.6 6.2 26.7 3.5 Source: SJM 2003/2. Note: 1Answers of persons living with a spouse or partner and aged 21-56; the question was: ‘Who in your household does the following tasks?’ 57 The fi gures were calculated so as to cover the population aged 20-74 in order to be comparable with Eurostat’s fi gures. Certain data and fi ndings should therefore be taken with reserve; if the fi gures on the more appropriate age group were used, they would be substantially different. The survey on time use was conducted in Slovenia between April 2000 and March 2001 by the SORS. 58 Household tasks included in the survey are statistically classifi ed into so-called ‘standard’ household tasks – i.e. food preparation, dish washing, cleaning, clothes care, shopping and childcare – and other household tasks: gardening, construction and repairs, vehicle maintenance and help to other households. Slovenia – A Long-living Society 83 while being the lowest in Germany (26 minutes), France and Finland (28 minutes). Slovenia’s place is somewhere around the average of those countries (29 minutes daily). Another important figure is the amount of time that men spend on childcare, as a woman’s decision to have a child largely depends on her partner’s participation in the family. Namely, research conducted in Scandinavian countries showed that it is more likely for a woman to have a second child if the father was actively involved in the care of the first one (Rrnsen, 2001, in Ule and Kuhar, 2002). Possibilities that partners would decide on another child also increase with the duration of the paternal and parental leave taken by the father (as reported by Olah, 2003, and Duvander and Andersson, 2005, in Rener et al., 2005). Among all the countries included, time spent by men on childcare is the longest in Belgium (19 minutes per day), Norway (17 minutes) and Sweden (16 minutes), and the shortest in Germany (10 minutes), and Estonia and Finland (11 minutes). With 12 minutes per day, Slovenian men fall short of the average, doing slightly worse than in the case of all domestic tasks. Table 44: Time spent on housework, by gender, Slovenia, 2003 (hours per week)1 Table 46: Attitudes on fairness of the division of domestic labour, by gender, Slovenia, 2003 (%)1 Respondent Partner No. of hours (Standard deviation) No. of hours (Standard deviation) Men 8.02 (7.63) 20.26 (13.25) Women 19.8 (12.47) 7.46 (8.01) Source: SJM 2003/2. Note: 1Answers of persons living with a spouse or partner and aged 21-56. The 2003 public opinion data reveal the respondents’ attitudes on how just the existing division of domestic labour is (see Tables 45 and 46). Although women do most of the work in the house, they find this unjust/unfair. Men are themselves admitting that they do less work in the home than they consider fair. At the same time, both strongly agree that men should spend more time on housework, particularly childcare. Nevertheless, most couples do not often have disagreements over this. That is to say, women come to ‘accept’ their unequal workload (which they internalise); men, although agreeing on the declarative level that they should do substantially more in the household and childcare, fail to act upon this or simply evade the housework. Table 45: Attitudes about men’s family-life workload, by gender, Slovenia, 2003 (%)1 Agree or Strongly agree Men Women Men should do more housework than they do now. 49.7 63.7 Men should spend more time on childcare than they do now. 69.4 79.6 Men Women I do a much bigger share of housework than I consider fair. 1.7 24.8 I do a slightly bigger share of housework than I consider fair. 5.5 23.6 I do approximately such share of housework as I consider fair. 44.1 45.0 I do a slightly smaller share of housework than I consider fair. 31.5 2.7 I do a much smaller share of housework than I consider fair. 12.6 1.9 Source: SJM 2003/2. Note: 1Answers of persons living with a spouse or partner and aged 21-56. Source: SJM 2003/2. Note: 1Answers of persons living with a spouse or partner and aged 21-56. 2.4.1.2 Reconciliation of paid work and family life An environment allowing women (and men) to successfully reconcile work with family life – and the other way round – importantly encourages the decision to have children. Women try to do the housework the best they can, despite significant difficulties in balancing their work and family life. They even do not complain much about their double workload in the survey (see Table 47). Dissatisfaction can be detected in the more indirect questions. As Ule and Kuhar (2002) found, the dissatisfactory, asymmetrical division of labour in the family is one possible reason for the falling number of children, as women often endeavour to establish a harmony between work and family at the cost of sleep, entertainment, rest and self-fulfilment59. It is not only that the shares of housework and childcare done by the partners should be perfectly equal; a sense of fairness is also important. Slovenian women come to ‘accept’ their ascribed family role and the large workload resulting from it. This can be indirectly inferred from their responses to the question on how they are managing to reconcile paid work and family life (see Table 48). Nevertheless, those same answers suggest a heavy workload of women, as no less than one-half of them report their family life to be stressful while significantly less men do so. Other public opinion data also testify to difficulties in balancing family and work duties. One-fifth of women (and one-sixth of men) aged 21-56 come home from work too tired to do all the housework several times a week; slightly less than one-quarter (of both men and women) do so several times a month. The percentage of those too tired for domestic work greatly increases with higher education. Since the population’s educational level has been on the rise and the jobs are ever more demanding, we may expect that the share of overtired and overloaded women will only grow, especially if men do not take on more responsibility for domestic tasks. Considering women’s heavy housework load, one would therefore expect that they have more difficulties reconciling Data on the time spent on work and on leisure-time activities are shown in SA: Tables 47 and 49. 84 Social Overview 2006 Table 47: Reconciliation of paid work and family life, by gender, Slovenia, 2003 (%)1 I agree Neither nor I disagree There is so much work at home that I often run out of time before I manage to do it all. Men 43.2 17.6 36.4 Women 51.9 17.6 28.2 My home life is rarely stressful. Men 56.8 16.2 24.2 Women 48.4 19.8 30.5 I have so much to do at work that I often run out of time before I can do it all. Men 38.3 14.5 30.6 Women 36.3 12.5 25.2 My job is rarely stressful. Men 20.5 15.6 47.1 Women 17.5 12.8 44.1 Source: SJM 2003/2. Note: 1All respondents aged 21-56; the difference to 100% in the sums by lines is represented by those to whom the question does not refer. work and family life than men. The public opinion data, however, do not entirely confirm this supposition. We judge this to be a consequence of giving socially desirable, trained answers and partly – as already mentioned – of having accepted their ascribed role of the woman in the family. The respondents reported that it was rather demanding to reconcile the two spheres as they are both highly time-consuming. Those with a higher education often feel excessively pressed for time because of the working sphere, and those with a lower education because of the domestic one. Women have been achieving high educational levels. Their desires to assert themselves both professionally and personally are high. If family policies continue to idealise the two-parent family as a value, accepting the unequal division of labour within it instead of doing more to improve everyday family practices (especially men’s involvement in household duties), we cannot expect long-term positive changes in the form of increased fertility. That is to say, it definitely seems that in the future, women will be increasingly less willing to bear the unfair double workload. And as for the state itself, it would make no sense to lose the investment in their education by pushing them from the labour market into the maternal and housewife role for almost fifteen years and impede their career development with an excessive workload in the domestic sphere. 2.5 Family life and ageing Changes in the transitions from adulthood to old age and extension of old age have progressed continually. The third life-period (beginning with the age of 65) has been changing from a passive period into an ever more active one; however, the group of people in the fourth life-period has been growing, i.e. the very old (aged 80 and over), whose needs for care and help have been rapidly increasing. In the family life context, the ageing of the population has at least two important implications. The first is the issue (relevant for social policy makers) of care for the elderly, being primarily centred on the relationship between the state and the family and on how the responsibility of care for old people should be divided between the two. That is to say, informal family or kin care of old people is an important segment of family life where, however, the issue of gender division of labour is conspicuous. Namely, care of the elderly is still ascribed to women as their ‘traditional’ task and duty within the family and kin, something that public opinion data and research (see e.g. Ule and Kuhar, 2003; Novak et al., 2004) also confirm (in more detail, this is considered in the Chapter 6). The second implication refers to the fact that the elderly (particularly those in the third life-period) also play an important role in family life as the providers Table 48: Reconciliation of paid work and family life, by gender, Slovenia, 2003 (%)1 Several times a week Several times a month Once or twice Never I came home from work too tired to be able to do all the housework. Men 14.2 24.4 17.9 23.0 Women 19.5 22.8 17.3 13.1 I found it hard to carry out my family duties because I spent too much time on paid work. Men 9.1 17.9 21.4 28.5 Women 8.6 20.1 17.5 25.6 Due to the housework, I came to the workplace too tired to be able to do my job well. Men 1.1 2.0 10.0 67.8 Women 1.4 4.7 12.8 53.5 Due to my family duties, I found it hard to concentrate at workplace. Men 1.1 3.7 12.5 60.8 Women 0.8 6.4 13.4 51.0 Source: SJM 2003/2. Note: 1All respondents aged 21-56; the difference to 100% in the sums by lines is represented by those to whom the question does not refer. The question was: ‘How often in the past three months did you experience anything of the following?’ of care. Grandparents (especially grandmothers) are an important factor within the pre-school childcare provision system. The ageing of the population and family members thus significantly affects intergenerational relations and ties in the family. The need for mutual help and co-operation has been growing, entaling a need for closer communication (also because of the prolonged ‘empty nest’ period). Due to the population’s ageing, children’s care of their aged parents is becoming increasingly important. Care and support in the family relations network first go (in young families) from parents to their (grand)children, and then from children to their aged parents. The third life-period has been changing from a socially (until-recently-regarded-as) passive period into an ever more active one while in the fourth life-period, passivisation has been growing, entailing more and more needs for care and help; in the context of family life, both factors imply closer intergenerational ties. Although the increasing diversity of family types (divorces, one-parent families, re-marriages, same-sex families) has made such contacts unpredictable, it is clear that the prolonged life expectancy has strengthened the ties between the generations, something that data on the social networks of the elderly (see Chapter 6.3) also reveal. Slovenia – A Long-living Society 85 86 Social Overview 2006 3. LABOUR MARKET AND EMPLOYMENT The ageing of the population is increasing the need for longer working lives – only greater employment rate of the elderly can cushion the pressure on expenditures for pensions and health care. However, the employment rate of the elderly (50-64 years) cannot be increased by merely extending the minimum retirement age, we must also create conditions and incentives for longer activity. The following is a presentation of the current situation in the Slovenian labour market60 which indicates that the objective set out in the Lisbon Strategy (a 50% employment rate in the 55-64 age group) is not achievable in Slovenia without the framing of an active ageing strategy. 3.1 Unemployment trends The unemployment rate was reduced in the 1999-2005 period by 1.1 percentage points and stood at 6.5% in 2005. This is below the average in the EU25 (8.7% in 2005). The male unemployment rate was reduced more rapidly than the female one in the 1999-2005 period (see Table 49)61. Although the unemployment gender gap is not great, it did increase in the last five years. This is why special emphasis should be placed on reducing unemployment among women (special programmes, greater representation of women in active employment policy programmes). Unemployment rates by age group in the 1999-2005 period indicate a reduction of the unemployment rate across all age groups. The reduction was higher in the 15-24 and 50-64 age groups (see Table 50). One of the reasons for the relatively low unemployment rate among the elderly (50-64 years) according to the Labour Force Survey data is probably the fact that the elderly frequently do not actively seek work, thus failing to achieve one of the Labour Force Survey criteria for unemployment. The data are, however, not (necessarily) a reflection of high employment among the elderly as the employment rate of the elderly in Slovenia is among the lowest in the EU. Table 49: Unemployment rates, Slovenia, 1999-2005 (in %) Table 50: Unemployment rates by age groups, Slovenia, 1999-2005 (in %) 15-24 25-49 50-64 Total 1999 18.1 6.3 5.6 7.6 2000 16.8 5.7 6.2 7.0 2001 18.1 5.1 4.8 6.4 2002 16.7 5.4 4.3 6.4 2003 17.4 5.9 4.3 6.7 2004 16.3 6.8 4.3 6.3 2005 16.0 5.9 4.4 6.5 Difference 2005-1999 in p.p. -2.1 -0.4 -1.2 -1.1 Total Men (2) Women (3) (3)-(2) 1999 7.6 7.3 7.9 0.6 2000 7.0 6.8 7.3 0.5 2001 6.4 5.9 7.0 1.1 2002 6.4 5.9 6.8 1.1 2003 6.7 6.4 7.1 0.7 2004 6.3 5.5 6.4 0.9 2005 6.5 6.1 7.1 1.0 Source: SORS, Statistical Information. Source: SORS, Statistical Information. Despite the drop in the unemployment rate, long-term unemployment remains a concern. The share of the long-term unemployed even increased in the 1999-2005 period, from 41.8% of total unemployed in the second quarter of 1999 to 51.0% in the second quarter of 2005. The data suggest that long-term unemployment in Slovenia had not decreased in the analysed period, so active employment policy measures will have to focus more on reducing and preventing long-term unemployment. The problem of long-term unemployment typically becomes more acute with age, which also indicates that there are bigger issues in the employment of the elderly. Data from the unemployment register suggest that long-term unemployment most frequently occurs in combination of age and low education and in the case of greater obstacles to employment (e.g. disability). Over the past few years the share of first-time job-seekers among the long-term unemployed has increased as well. Despite the reduction of unemployment rates, youth employment remains a serious development problem. In the 1999-2005 period the youth unemployment rate dropped by 2.1 percentage points, from 18.1% in 1999 to 16.0% in 2005. The unemployment of youth measured as the share of unemployed youth in the 15-24 age group62 also fell, from 7.4% in 1999 to 6.4% in 2005. According to Eurostat, the share of unemployed youth in the total youth population stood at 6.5% in 2004, which is below the average in the EU25 (8.3%) or the EU15 (7.6%). Data on the duration of unemployment reveal that long-term youth unemployment is also common. According to the Labour Force Survey, over a third of the people in the 15-24 age group qualify as long-term unemployed (unemployed for over 12 months). According to data from the Employment Service of Slovenia (which monitors youth registered as unemployed), youth unemployment is closely related to a lack 60 For details of labour market trends in the past decade, see Kajzer et al., 2006. 61 Data on unemployment rates by education level are shown in the SA: Table 50. 62 The increasing share of young people in education means that the share of young people in the active population is dropping, so the criterion of youth unemployment is more appropriate. Slovenia – A Long-living Society 87 of education (dropouts from full-time/formal education) and the problem of employing youth with a secondary vocational education or general and technical secondary education. 3.1.1 Regional dimension of unemployment At the level of the 12 statistical regions unemployment can only be monitored with data on registered unemployment, which is different to that obtained in the Labour Force Survey (see Box 16). The gap between the two sets of data has been closing, but it is still relatively large In the 2000-2005 period the registered unemployment rate decreased in most statistical regions. Data for this period highlight the Pomurska, Podravska and Zasavska as regions with persistently high registered unemployment rates, whereas the regions with low registered unemployment rates include Goriška, Obalno-kraška and Osrednje-slovenska (see Map 1). Box 16: Difference between Labour Force Survey and registered unemployment In the analysis of the regional distribution of unemployment it is impossible to use the Labour Force Survey data – due to an insufficiently large sample the regional data are not statistically significant. Unemployment in regions is therefore presented based on data on registered unemployment. Registered unemployment is measured by the number of registrations of unemployed people at employment services. In the measuring of unemployment according to the Labour Force Survey, which is internationally comparable, a person must meet three criteria: (i) did not work and did not do any paid work in the week before the survey and not being employed or self-employed; (ii) actively sought work in the last four weeks before the survey; and (iii) is currently available for work immediately or within two weeks of the day of the survey. In 2005 the average number of registered unemployed people was 92,000, of whom 54,000 were unemployed according to the criteria of the Labour Force Survey and 38,000 did not meet one of the conditions for unemployment. In the latter group, 77.7% did not actively seek work and 16.5% did at least one hour of paid work. In addition to the differences in definition, the reasons for the relatively large gap between registered and Labour Force Survey unemployment include: (1) the ‘inactivity’ of some of the registered unemployed people who are not actively seeking work. This is closely related to the high share of the long-term unemployed who become passive, thinking that they cannot get work (discouraged workers); and (2) the employment of registered unemployed people in the shadow economy (the size of the shadow economy is considerable according to several estimates) or the work they do as unpaid family workers in a family enterprise (craft industry, company, farm). Compared to the EU, Slovenia has a relatively high share of unpaid family workers among persons in employment. The large difference is definitely the result of: (i) the tying of certain rights in social security systems to the status of being an unemployed person. The individual is entitled to these rights by registering as unemployed, which increases the interest of the unemployed to register; and (ii) not a favourable ratio between the number of employment counsellors per unemployed people, which makes it more difficult to intensively monitor and provide counselling to the unemployed or monitor their activity. Table 51: Registered unemployment rate at the regional level, Slovenia, 2000-2005 (in %) 2000 2001 2002 2003 2004 2005 SLOVENIA 11.8 11.2 11.3 10.9 10.3 10.2 Osrednjeslovenska 8.8 8.0 7.7 7.5 7.5 7.6 Obalno-kraška 8.8 8.7 8.3 8.0 7.9 7.5 Gorenjska 9.7 8.7 8.2 8.0 7.6 7.3 Goriška 5.9 5.6 6.1 6.3 6.7 6.5 Savinjska 13.1 13.1 13.6 13.1 12.5 12.7 Jugovzhodna Slovenija 10.4 9.6 9.7 8.4 8.2 8.8 Pomurska 16.7 16.3 17.7 17.6 16.8 17.1 Notranjsko-kraška 10.4 9.4 8.8 8.6 8.1 7.9 Podravska 18.1 17.4 17.1 15.8 14.2 13.5 Koroška 9.9 9.9 11.3 12.2 11.4 10.6 Spodnjeposavska 13.4 13.9 14.1 14.6 12.7 11.5 Zasavska 14.9 14.3 14.8 15.6 14.4 13.8 Source: SORS. 88 Social Overview 2006 Map 1: Registered unemployment rate, statistical regions, Slovenia, 20051 Note: 1For the purpose of collecting regional statistics, Slovenia is divided into 12 statistical regions. When Slovenia joined the EU, these regions also became regions at the NUTS 3 level and are included in the Regulation (EC) No 1059/2003 on the establishment of a common classification of territorial units for statistics (NUTS) and the Regulation (EC) No 1888/2005 amending Regulation (EC) No 1059/2003. Intra-regional differences in registered unemployment rates became less pronounced in the 2000-2005 period if we consider the ratio between the least and most successful regions in terms of registered unemployment (see Table 51). In 2000 the ratio between the least and most successful region was 1:3.1, whereas in 2005 it stood at 1:2.6. The ratio thus calculated decreased not only because of the lower registered unemployment in the region with the highest unemployment rate, but also because of the higher registered unemployment in the region with the lowest registered unemployment rate, which is certainly not favourable. It is therefore better to measure intra-regional differences with the variation Table 52: Selected indicators of structural problems in unemployment by regions in Slovenia in 2005, based on data on registered unemployment (in %) Share of youth (under 25 years) Share of the elderly (over 50 years) Share of the unemployed without an education Share of the long-term unemployed SLOVENIA 19.9 22.7 40.8 47.3 Osrednjeslovenska 17.3 26.4 39.1 44.9 Obalno-kraška 17.9 24.6 36.1 39.3 Gorenjska 17.4 30.5 40.0 35.8 Goriška 16.5 25.9 36.7 44.7 Savinjska 22.7 19.8 38.7 50.3 Jugovzhodna Slovenija 20.0 22.1 52.9 50.6 Pomurska 22.3 21.8 51.2 53.3 Notranjsko-kraška 18.4 25.3 38.4 44.7 Podravska 20.2 19.5 36.6 47.7 Koroška 22.2 18.8 36.6 50.0 Spodnjeposavska 15.5 25.3 42.6 51.6 Zasavska 26.1 18.2 45.5 48.4 Source: SORS, ESS. IMAD’s calculations. Slovenia – A Long-living Society 89 coefficient (the ratio between the standard deviation and the arithmetical mean, taking the size of the regions into account). The coefficient of variation stood at 31.5% in 2000. It increased to its highest value (35.1%) in 2002, whereupon it started dropping to reach 30.9% in 2005, just below its level in 2000. At the level of the entire country as well as the regions, the problem of structural unemployment is evident in the high share of long-term unemployed people (the highest share is in the Pumurska region) and the high share of the unemployed without education (the highest share is in Jugovzhodna Slovenija), whereby the elderly also face problems in finding employment (see Table 52). 3.2 Employment rate In the 1999-2005 period the employment rate in the 15-64 age group increased by 3.4 percentage points in Slovenia (see Table 53). While it hovered near the EU25 average (63.0%) in 2003, it increased significantly in 2004 to exceed the averages in both the EU25 and EU15. The employment rate also rose in 2005 and is still above the average in the EU25 (65.0%) and EU15 (63.6%). Slovenia lags behind the European average in employment rates of youth and the elderly. The main reason for the low employment rate among youth (15-24 years) is their high participation in education (which is crucial for their ability to enter the labour market and for productivity). On the other hand, the employment rate among the elderly (55-64 years) reflects the effects of the pension reform, which is geared towards raising the activity rate; the employment in the 50-54 age group increased by as much as 10.5 p.p. in the period following implementation of the law63. The employment rate in the 55-64 age group has been increasing as well. There are ‘reservoirs’ in reducing unemployment in the 15-24 age group and increasing the employment rate in the 55-64 age group. 3.3 Flexible forms of employment The Slovenian labour market is often described as rigid. Labour market flexibility is a very broad concept64; the incidence of two most typical forms of flexible employment, which are often used as partial measures of labour market flexibility, are presented below. The international survey ‘Households, Work and Flexibility’ has shown that the Slovenian labour force is very flexible in terms of the place of work, which means that many people commute to work due to the non-overlapping distribution of settlements and jobs (Sicherl, 2003)65. A comparative analysis of human resources management – a survey by the Centre for Organisational and Human Resources Research (see Svetlik, Ilič, 2004) – shows that Slovenian companies mostly use flexible forms of employment that are unfriendly to the individual: most Slovenian companies use fixed-term employment, overtime work, shift work and work on weekends. These forms of flexible work appear more frequently in Slovenia than in the other developed and transition countries that were included in the survey. 3.3.1 Part-time employment Slovenia is in the group of EU member states in which parttime employment is infrequent. The only countries where part-time employment is less widespread than in Slovenia are Hungary and Greece (4.5%), the Czech Republic (4.4%), and Slovakia (2.5%). The low part-time employment rate in Slovenia may be attributed to the lower share of jobs in service industries, the low employment rate of the elderly (55-64 years) and the fact that, because of lower salaries and limited opportunities for promotion, such work is not attractive to job-seekers. Moreover, due to the disproportionality of some costs associated with this type of employment employers prefer to resort to other forms of employment. Table 53: Employment rate by age groups, Slovenia, 1999-2005 (in %) 15-24 years 25-49 years 50-64 years 55-64 years 15-64 years 1999 34.3 85.3 35.3 22.2 62.5 2000 33.6 85.6 37.3 22.5 62.9 2001 31.4 86.6 41.1 25 63.9 2002 30.6 86.3 41.3 24.4 63.4 2003 29.3 85.5 41.1 23.5 62.6 2004 34.0 86.3 45.8 29.0 65.3 2005 34.1 86.3 47.3 30.5 65.9 Difference 2005 /1999 in p.p. -0.2 +1.0 +12.0 +8.3 +3.4 Source: SORS. Note: data on the employment rates by level of school attainment, total and by gender, are shown in the SA: Table 51. 63 The amendments to the Pension and Disability Insurance Act entered into force on 1 Jan 2000. 64 See Kajzer, 2005 for a defi nition and measurement of labour market fl exibility. 65 These are the results of the comparative study within the project ‘Households, Work and Flexibility’, which was carried out as part of the 5th Framework Programme in research. 90 Social Overview 2006 Table 54: Share of part-time workers in total employment, Slovenia and the EU25, 1999-2004 (in %) Slovenia EU25 Total Men Women Total Men Women 1999 4.2 3.3 5.2 16.1 6.1 29.5 2000 4.5 3.5 5.6 16.2 6.1 29.5 2001 4.4 3.4 5.4 16.3 6.2 29.6 2002 4.6 3.5 5.8 16.6 6.5 29.7 2003 4.9 3.8 6.0 17.0 6.6 30.3 2004 6.5 5.0 8.2 17.7 7.0 31.4 Source: SORS for Slovenia, Employment in Europe 2005 for the EU25. Part-time employment is appropriate in particular at the beginning and end of one’s career. The share of youth (men and women) in part-time employment (29.1% in Q2 of 2004) exceeds the average in the EU25 (24.5%). However, we have no data on the type of work they do. We can only guess that they mostly work through student employment brokerage services, which for the employers is the most tax-favourable type of youth employment and is widespread in Slovenia. Among the elderly (55-64 years), the share of part-time work is approaching the EU average for men, but for women it is far behind the average for the EU25 and even further behind that for the EU15. In both Slovenia and the EU, part-time work is more widespread among women than among women, however in Slovenia the share of women in part-time employment is among the lowest in the EU (see Table 54). It is necessary to emphasise that Slovenia still has the highest employment rate among mothers with children (85% in 2003), which is a reflection of the long socialist tradition of high employment levels among women and the good acceptance, development, extent and financial availability of the public childcare network. In the 1999-2005 period the share of part-time jobs (shorter than full-time work; Art. 64 of the Employment Relationship Act) in Slovenia increased, but it is still well behind that seen in developed countries. In Q2 of 2005 the share of part-time jobs in the total number of jobs in Slovenia was 7.8% in the 15-64 age group (18.9% in the EU25, 19.8% in the EU15). The share of part-time jobs could increase in Slovenia. The largest ‘reservoirs’ lie in activation of the elderly, whose employment rate is low. To increase their employment rate, it is necessary to create conditions for combining part-time employment with partial retirement and to examine the possibility of promoting the employment and redeployment of the elderly in social care services. In this respect, it may make sense to assess the price elasticity of demand for domestic work and to create mechanisms to promote formal employment in this field. Taking into account the trends and current situation of part-time employment in the EU15, Slovenia should also consider introducing part-time employment to the civil service, which would improve the flexibility of the public administration. 3.3.2 Temporary employment The share of temporary employment (various forms of work for a fixed or limited term) has doubled over the last ten years. Despite the general perception that temporary employment is widespread, the data suggest that the share of temporary jobs is only slightly above the EU average (see Table 55). The employment of youth is an exception, however, where Slovenia is exceeding the EU average. The increasing share of temporary employment typically suggests that the regulation of the labour market is rigid and high employment protection. Kahn (2005), for example, shows that the stronger the job protection, the more frequently employers employ for a fixed term. What is more, this raises temporary employment in particular among youth, those with a lower education and women. A similar flexibilisation of the labour market has taken place Table 55: Share of temporary employment in overall employment, Slovenia and the EU25, 1999-2004 (in %) Slovenia EU25 Total Men Women Total Men Women 1999 10.2 9.6 10.8 12.3 11.7 13.0 2000 13.7 12.7 14.8 12.6 12.0 13.4 2001 13.0 12.1 14.0 12.9 12.1 13.7 2002 14.3 12.6 16.1 12.9 12.1 13.8 2003 13.7 12.6 14.9 13.0 12.4 13.8 2004 17.8 16.7 19.1 13.7 13.2 14.3 Source: SORS for Slovenia, Employment in Europe 2005 for the EU25. Slovenia – A Long-living Society 91 in Slovenia in recent years: age segmentation has created a labour market that is more flexible for youth than it is for the rest of the workforce. Age segmentation is a phenomenon that sociologists (Kanjuo Mrčela, Ignjatovič, 2004) have also highlighted. The introduction of flexible forms of employment may lead to a segregation of the labour market. Introducing such employment forms may result in the creation of so-called primary and secondary markets: in the primary labour market, jobs are permanent and better paid; in the secondary market jobs are less well paid and less permanent. This could also generate pressure on the creation of jobs that require low qualifications while those who have such jobs often have fewer opportunities for additional training (Sicherl, 2003: 101) and promotion. This is one reason why the EU has been increasingly active in looking for a balance between flexibility and security in the labour market, hence the coining of the term flexicurity (see Box 17). Policies that draw on this concept are based on the Danish model from the 1990s (see Box 18). Box 17: Flexicurity Withagen and Tros (2004: 4) define flexicurity as a policy and strategy that attempts, synchronically, to enhance the flexibility of labour markets, work organisation and labour relations and, on the other hand, to enhance security – employment security and social security. They provide the following definition which combines typical definitions of security and flexibility: (1) a degree of job, employment and income security that facilitates labour market careers, activity and social inclusion even for workers with a relatively weak position in the labour market, but which at the same time (2) ensures a degree of numerical, functional and wage flexibility that allows the labour market and individual companies to adapt quickly and appropriately to altered conditions in order to retain competitiveness and productivity. Box 18: Golden labour market triangle*/ The Danish model of a dynamic labour market *Taken from: OECD (2004: 97) and Kanjuo Mrčela, Ignjatovič, 2004: 243. The Danish model from the 1990s is considered a role model of a dynamic labour market because it produced good results in the labour market. In particular, it raised employment significantly. Denmark has a functioning combination of a dynamic labour market and a relatively high degree of social security. Its welfare model is an efficient combination of flexibility (great mobility of workers as a result of the relatively low job security), social security (generous unemployment benefits) and an active labour market policy. Madsen (2002) describes the specificity of the Danish model as the dominance of small and medium-sized enterprises, high unemployment benefits, a welfare state underpinned by the high employment of men and women, a developed public education and training system, and a system of industrial relations which gives the social partners a big role (from Kanjuo Mrčela, Ignjatovič, 2004: 242). The success of the active labour market policy is attributed to the very precisely defined goals for both employers and employees (Kanjuo Mrčela, Ignjatovič, 2004: 243). 92 Social Overview 2006 4. ADULT EDUCATION The era of swift changes demands from individuals and economic entities an aptitude for expeditious adaptation. It is ever more important that individuals are well educated and trained for work and life and, above all, that they continually improve their knowledge. Individuals may be participating in education because of work-related needs or because of needs relating to personal growth and interests. For people in employment both aspects are important, whereas among retired people training is highly regarded because of their need for personality growth. Education has several positive impacts at the individual level and at the level of the economy and society. It has a positive impact not only on the personal growth and people’s inclusion in the labour market, but also on society’s development and social cohesion, along with economic development. Within the context of a progressive extension of working life and an ageing society, it is therefore important that both young and elderly people are broadly included in learning activities. Learning is something that should last from birth until death. The latter involves the concept of lifelong learning, which comprises three types of learning activities: formal and non-formal education, and informal learning (see Box 19). Box 19: Formal and non-formal education and informal learning Formal education leads to formally attested educational outcomes, such as the attained level of education. Non-formal education is intended to satisfy other, often direct interests and needs of adults rather than providing a formal certificate or a higher education level. This type of education covers all organised educational programmes that are not part of the formal education system. Informal (occasional) learning is education decided on deliberately by either the learner or the source of learning (but not both). Informal learning can, for example, take the form of guided excursions and visiting museums and galleries, participation at trade fairs, consultations and congresses, rotation within various sections of organisations, practical tests, the use of computer programmes and the Internet etc. According to Eurostat, Slovenia exceeded the target level of participation in lifelong learning for the EU countries by 2010 (i.e. 12.5%) as early as in 2003, when its percentage totalled 15.1%. With 17.8% of the adult population aged 25 to 64 participating in lifelong learning66, it was also well above the EU25 average (10.8%) in 2005. It is worth noting that in Slovenia the gap in the participation in education between less educated (ISCED67 0-2) and more educated people (ISCED 5-6) is wider than in the EU25. In Slovenia the percentage of less educated people participating in education is 8.4 times lower than the percentage of more educated people, whereas in the EU25 this ratio is 7.368. Figure 42: Adults participating in education by gender, age, education and employment status, Slovenia, 1998 and 2004 (in %) Women _30 39 38 48 7 48 D 1998 I35 D 2004 Men \32 16-19 years 3 \17 20-24 years 25-39 years 41 4 40-49 years D35 Z 42 50-65 years ¦ 14 21 7 Unfinished primary school Z 4 19 7 14 Primary education 3 13 Completed 2-year vocational school ¦ Zp 21 Completed 3-year vocational school 24 2 Completed 4 or 5-year secondary school I 42 Tertiary education ¦ 172 H 68 141 7 7 7 Employed Z 44 Self-employed 4 15 Farmers ¦ 14 I5 Unemployed Z 16 30 ^6 12 ]11 20 Other 112 Z 21 0 10 20 30 40 50 60 70 80 Source: SIAE datasets: (2004) Participation of adults in education; (1998) Literacy and participation of adults in education. 66 The indicator of participation in lifelong learning measures the participation of population aged 25 to 64 in formal and non-formal education during the four-week period before the survey is carried out. 67 The revised International Standard Classifi cation of Education (ISCED), adopted in 1997, provides a classifi cation framework for the structuring of data and demonstration of national statistics, international statistics and statistical indicators. 68 (2005) Progress towards the Lisbon Objectives in Education and Training, pp. 72-73. Slovenia – A Long-living Society 93 The participation of adults in education in Slovenia is There are several reasons for the differences in partici-being monitored by a study carried out by the Slovenian pation in education between individual age groups of Institute for Adult Education (SIAE) in 200469. The sur- the population. The first one is that in the age of 20-49 the vey measures the participation of the population aged 16 share of employed people is much higher than in the 50-to 65 years in education (respondents with the status of a 65 years age group, and that a major part of education is pupil or student are excluded) within the 12 months before work-related. The opposite may be found in the age group the survey is carried out. Using the results of the survey of 50-65 years where part of the population has already we present below: (1) the differences in the participation retired and is less inclined to participate in education than of adults in education (formal and non-formal education the employed population. There are most probably also combined; hereinafter ‘education’) with regard to the some people who, although still employed, decide less often selected socio-demographic characteristics in the 1998- to participate in education as their expectations regarding 2004 period; and (2) the share of adults participating in benefits are smaller. Elderly people quite often also suffer formal and non-formal education separately with regard from a prejudice implying that they are ‘already too old’ to to socio-demographic characteristics in 2004. The study participate in education. In addition, elderly people are often shows that the proportion of adults receiving education less educated which, as a rule, represents a serious obstacle and training rose from 31.9% in 1998 to 37% of the adult to their taking part in formal and non-formal education. population in 2004. Gender, age, education attained and employment status all have an important impact on par- The low share of people with a low education level70 participation in education. ticipating in education is a serious problem. In Slovenia, the highest rates of participation in education can be found The share of men participating in education is higher among persons with a tertiary education, and the lowest than that of women. Both in 2004 and in 1998 the share among people without a primary education. The diffe-of men participating in education was higher than the share rence in shares between those two groups of population of participating women. Moreover, the male share grew in 2004 was still very large, but decreased in comparison more than the female one from 1998 to 2004 (7 p.p. for with 1998. The participation rate of people with a tertiary men and 5 p.p. for women; see Figure 42). In 2004, the education is much higher, namely five times higher than participation of women in formal education was higher the participation of people without a completed primary than that of men, whereas quite the opposite was true of school (see Figure 42). It was, however, this group that saw the participation in non-formal education. The difference the highest increase (by 10 p.p.) in the 1998-2004 period, is in favour of men as their share is no less than 9 p.p. while the participation of people with a tertiary education higher than the percen-tage of women. slightly decreased. The participation rates of other groups by level of education increased. The correlation between Participation rates in education decline with age. In the the achieved level of education and participation in further 1998-2004 period, participation in education increased in education is even more evident in non-formal education, all age groups (in each by about 7 p.p.), with the exception where it increases with each subsequent higher education of the group aged 16 to 19 years. The participation of that degree than in the formal education (see Table 56). The group in education decreased during the same period by participation of people with a university degree or higher approximately one-half, which was the reason to be ranked in non-formal education in 2004 was more than six times lowest among all groups with regard to participation in higher than the participation of those with an uncompleted 2004. In 1998, the last place went to the group aged 50-65. primary school. In 2004, participation of that group was twice as low as the participation of age groups between 20 and 49 years. The differences in the shares of adults participating in for-The same is true of participation in non-formal education. mal and non-formal education as regards their occupational Approximately one-fifth of the population belonging to status are large. In 2004, the highest rates of participation in the oldest age group participated in that type of education. formal education could be found among employed, self-em-The same was the rate of participation of the youngest age ployed and unemployed people (about 10%), and the lowest group (16-24 years). On the other hand, in formal educa- within the groups of farmers, retired persons and house-tion participation rates strongly decline after the age of wives (there were practically none). Hardly ever taking part 40, and after the age of 50 people practically no longer in formal education, farmers are quite frequent participants participate in it. in non-formal education, mostly owing to their participation The SIAE carried out the survey according to the methodology applied as early as in 1998 in the international survey on the literacy of adults and participation in education (OECD, 2000). The fi gure essentially differs from the Eurostat’s fi gure due to the different data collection methodology: the Eurostat measures the participation in education during the last 4 weeks before the survey, while the OECD (and the SIAE) does the same during the last 12 months before the survey. The Eurostat includes the adults aged 25 to 64, while the OECD and the SIAE cover the population between 16 and 65 years of age (respondents with the status of a secondary-school or university student are excluded). Persons with a fi nished or unfi nished primary school (ISCED 2 or lower). 94 Social Overview 2006 in training courses organised by the Agricultural Advisory Service. They are followed by the self-employed (51.3%) and, in third place, employed people (38.8%). While the participation of the unemployed in formal education was almost the same as among employed persons in 2004, the participation in non-formal education was nearly two times lower than that of the employed. Since people participating in non-formal education obtain important working skills, which are certainly needed by the unemployed, it would be worth considering more intensive promotion of their participation in non-formal education. In the 1998-2004 period, participation in education increased in all population groups irrespective of their employment status. The highest rise was seen in the share of farmers and self-employed people. Although the participation rates of other population groups grew as well, several categories of the population (retired people, housewives) still exhibit low participation rates. The unemployed also continue to lag behind the employed, although in the 1998-2004 period the gap between both groups narrowed substantially in favour of the unemployed (from 25 p.p. in 1998 to 14 p.p. in 2004). Table 56: Participation of adults in education, Slovenia, 2004 (in %) Share of the population participating in formal education Total By gender Women Men By age 16-24 years 25-39 years 40-49 years 50-65 years By education degree Unfi nished primary school Primary education Completed two-year vocational school Completed three-year vocational school Secondary education Higher education University education By employment status Employed Self-employed Unemployed Farmers Housewives Pensioners Source: SIAE, Research Report 2005. 7.9 8.3 7.4 16.4 14.3 5.4 0.5 9.6 2.7 6.5 3.9 12.1 13.1 14.0 10.2 7.9 10.1 0.0 0.0 0.6 Share of the population participating in non-formal education Share of the population not participating in education 32.2 25.8 34.8 21.2 40.6 38.7 20.1 9.6 16.5 16.7 23.3 40.5 54.9 66.0 38.8 51.3 19.2 57.4 20.4 11.6 63.0 65.4 61.6 60.9 53.7 58.4 79.4 85.6 81.9 78.7 73.6 53.3 39.9 29.1 54.6 43.5 72.0 42.6 79.6 87.9 Slovenia – A Long-living Society 95 5. HEALTH OF ELDERLY PEOPLE Elderly people are the group of the population with the anticipated highest rate of chronic morbidity and disease conditions, among which cardiovascular diseases, neoplasms and injuries prevail. These diseases are also the primary causes of mortality, reduced abilities and hospital treatment. Their consideration within the health care requires most personnel, material and financial resources. The prevalence of diabetes, dementia and mental health problems is on the increase. Old age is also strongly associated with visual and auditory impairment, diminished mobility, dental problems (loosing chewing abilities and related communication problems). All these reduce functional abilities and affect the quality of life and social inclusion/exclusion of elderly people. With age, the requirements of people for health care are thus changing; the latter is primarily reflected in the increase in long-term care requirements (see Chapter 6.5). 5.1 Primary health care In Slovenia, the prevailing concept is that of the World Health Organisation stating that successful and efficient health care needs to be built on the concept of primary health care71. A significant emphasis is put on the implementation of programmes relating to health promotion and the early detection of risk factors being a potential cause of chronic or degenerative illnesses. The community health care is also part of the primary level organisation that includes preventive and health education services, services of treatment and care at home and, within a certain scope, assistance services at home. Within the primary level, insured persons are additionally guaranteed home treatment which in the case of a lengthy duration represents the medical treatment component of long-term health care. In 2004, there were 68% of elderly people in Slovenia with a selected personal physician, and 46% with a selected dentist. The compulsorily insured people have a possibility of selecting a general practitioner/family physician (children and adolescents have the same rights in respect of a specialist-paediatrician and a school medicine specialist) and a dentist, whereas women may also select a personal gynaecologist. The provision of medical personnel by age groups may be assessed against the background of the ZZZS data on persons opting for a selected physician. Since the introduction of the institution of a personal physician in Slovenia (general practitioners/family physicians, specialists-paediatricians and school medicine specialists with regard to the age of an insured person), 98% of insured persons have until now selected a personal physician, 72% of women a gynaecologist, and three-quarters of the insured people a dentist. IVZ analyses72 indicate that by 2006 numerous selected physicians and dentists have already retired, moved away or died, as in 2006 there were 68% of persons aged 65 or over having a selected personal physician, while even less than half of the population had a selected dentist. The share of elderly women with a selected gynaecologist is less than half of that in women aged 20-64 (see Table 57). The lack of general practitioners and dentists at the primary level is emerging to be increasingly critical. In Slovenia elderly people visit a physician at the primary level more frequently73. Visits of people aged 65 and over constituted 20.5% of all visits at the primary level of health care in 200474. The total number amounted to over 10 million visits. In 2004, men visited a physician 6.3 times and women 6.8 times (there are no data on visits to dentists). Women and men aged 65 and over visit a physician at the primary level most often due to cardiovascular diseases. Second in the order of precedence is the group of visits by reason affecting health condition and contact with the health care75, third is the group including visits paid due to musculoskeletal and connective tissue diseases, and fourth are respiratory diseases (see Figure 43). Table 57: Share of the decided compulsorily insured persons in employed general practitioners and dentists by permanent residents, Slovenia, May 2006 (in %) Practitioners of dentistry General practitioners Gynaecologists Total 53.6 69.5 60. 7 up to 19 47.7 72.6 10.5 20-64 57.2 68.9 82.3 65+ 46.4 67.7 41.3 Source: ZZZS, calculations by IVZ. 71 Primary health care comprises basic health care and pharmacy activities; access toit requires no referral form. 72 IVZ data according to the annual programme of tasks for the national programme of the Ministry of Health, unpublished. 73 The reason for doctors’ appointments indicates health problems which cause elderly people to see a physician, however it does not allow for a conclusion relating to the incidence or prevalence of an illness. It is only an orientation regarding the health problems suffered by the elderly and dealt with by general practitioners at the primary level. 74 There are no comparable data from regular databases in other countries; estimates are generally prepared on the basis of public surveys. 75 This group, for example, includes control check-ups after therapy, vaccination, screening tests, visits for administrative reasons (e.g. a repeated prescription of a medication) etc. 96 Social Overview 2006 Figure 43: The rate of visits in the basic health care per 1,000 women and men aged 65 and over, by cause, Slovenia, 2004 Circulatory diseases Contact with health care service Respiratory diseases Musculoskeletal diseases Symptoms and abnormal medical reports Injuries and intoxications Gastrointestinal diseases Urinary and genital diseases Cutaneous and subcutaneous diseases Endocrine and metabolism diseases Ear and mastoid diseases Eye and adnex diseases Neoplasms Infectious and parasitic disease Mental and behavioural disorders Neurological diseases Blood and hematopoietic organ diseases -- Congenital malformations D Women D Men ----------r —i--------------------- ? 0 100 200 300 400 The number of visits per 1000 population 500 600 Source: IVZ. A strong deterioration may with age also be observed in oral health associated with the occurrence of dental and paradental tissue disorders, and the loss of teeth. The data show that almost one-quarter of the population in the age group above 60 years has not even one natural tooth left in their mouths. Only 1% of persons aged 75 and over have healthy paradental tissue (Premik, 2005). The Slovenian population older than 64 years has in recent years been provided with more preventive health care, however still less than for younger population groups. The visit rates reflect the implementation of preventive programmes for population groups anticipating mostly preventive visits for children, pupils and secondary school students. The share of women treated preventively Figure 44: Visit rates in primary level of health care per 1,000 inhabitants by age groups, Slovenia, 2004 65 + 60-64 r3 50-59 40-49 D Preventive attendance ¦ Home visit ¦ Curative attendance 30-39 - 20-29 10-19 - 1-9 j - <1year ------------------ ------------------ ------------------ ------------------ ------------------ ------------------ 1000 2000 3000 4000 5000 6000 7000 8000 Source: IVZ. 0 Slovenia – A Long-living Society 97 Figure 45: Visit rates in specialist outpatient clinics at the secondary and tertiary levels of health care per 1,000 inhabitants by age groups and gender, Slovenia, 2004 0 - 19 20 - 64 65+ Total I Women Men I I I Source: IVZ. 500 1000 1500 2000 Visit rates 2500 3000 3500 4000 is higher than the share of men (see Figure 44). Preventive programmes for adults are carried out within the services of general family medicine (national programme for the prevention of cardiovascular diseases) and health protection of women (the ZORA national programme), as well as within the occupational, transport and sports medicine (examinations relating to work and ability to operate motor vehicles). 5.2 Secondary and tertiary outpatient health care A substantial part of the outpatient health care for people older than 65 years is also performed within specialist outpatient services at the secondary76 and tertiary77 levels. In 2004, specialist outpatient services at the secondary and tertiary levels saw a total of 3,696,755 visits. Visits of people older than 65 years accounted for 28% of all visits. People older than 65 years visit an outpatient facility at the secondary or tertiary level more than three times a year. Men are more frequent visitors than women; in 2004, men visited an outpatient facility 3.7 times and women 3.3 times. Most visits to specialist outpatient clinics at the secondary and tertiary levels are recorded in internal medicine, followed by surgery and ophthalmology. Specialist outpatient clinics are more often visited by men (1.7 visits in internal medicine and 0.8 in surgery) than women (1.4 in internal medicine and 0.5 in surgery). The prevailing causes are to be found in the field of general internal medicine, cardiology, diabetology and pulmonology, whereas in surgery the predominant area is urology. 5.3 Hospital health care The gradual restructuring of health care services by increasing the scope of work in outpatient health services and the introduction of a non-acute treatment and extended hospitalisation in nursing wards helps reduce the extent of hospitalisation. The inpatient length of stays in hospitals is getting shorter and the principle of a ‘day hospital’ is increasingly being implemented. Figure 46: Average weighting for groups of comparable cases by age groups and gender, Slovenia, 2005 2.0 1.0 0.5 0.0 Women Total 0-19 20-64 65+ Source: IVZ. Note: The weight is the coefficient of the estimated cost of treatment based on diagnosis, the patient’s age and the diagnostic and therapeutic procedures. The rate of hospitalisation due to illness is, as expected, higher with elderly people than with other age groups. In 1998-2004, the rate amounted to about 300 hospitalisations per 1,000 inhabitants in that age group (see Table 58). The elderly represent 34% of all hospitalisations by reason of illness. The rate of hospitalisation of elderly people is twice as high as the average; with elderly men even 2.9 times higher. The reason elderly people undergo hospital treatment more often is the higher frequency of chronic diseases (see SA: Table 53). The hospital treatment of elderly people is, as a rule, also lengthier and their recovery is slower. Data on 76 Health care at the secondary level includes specialist outpatient and hospital services. Treatment at that level requires a referral from a general practitioner at the primary level. 77 Health services at the tertiary level include services of clinics and institutes and other authorised health institutions. Treatment at that level requires a referral from a general practitioner at the primary or secondary level. 0 98 Social Overview 2006 Table 58: Rate of hospitalisations due to illness per 1,000 inhabitants by age groups, Slovenia, 1998-2004 1998 1999 2000 2001 2002 2003 2004 0-19 109.4 111.5 113.3 112.5 107.2 103.3 105.4 20-64 112.5 112.3 112.4 111.9 106.8 102.0 101.5 65+ 292.1 297.2 302.5 300.2 298.0 296.3 302.8 Source: IVZ. Figure 47: Rate of hospitalisation due to injuries and intoxications per 1,000 inhabitants by age groups and gender, Slovenia, 2004 35 30 25 20 15 10 5 0 Men Women i—i n i—i __ n~v LII Source: IVZ. 0 let 1-3 4-6 7-9 10-14 15-19 20-29 30-39 40-49 50-59 60-64 65-74 75-84 Age group acute hospital treatments78 show that the highest rate of acute treatments can be observed in the age group of 65 years and over, such cases also being more costly, and that the average weighting79 in all age groups is higher for men than for women (see Figure 46 and SA: Table 54). Injuries are more common among persons older than 65 years than among other population groups, and occur even more often in very old people, particularly women. After having suffered injuries, no less than a third of people require lengthy assistance and care. Elderly people represent 22% of hospitalisations due to injuries and intoxications. The duration of their hospitalisation is longer and lasts on average 12 days. The age and gender-specific rate of hospitalisation begins to rise sharply after the age of 65, resulting in a rate which is twice as high in women than in men, with both genders being over 65 years old (see Figure 47). The most frequent reason for admission to hospital due to injuries (77%) and death caused by injuries (43%) are falls, followed by injuries suffered by elderly people in road accidents. The most frequent fall-related injury is a hip-joint fracture resulting in the annual hospitalisation of about 2,200 people, 79% of whom are elderly. 10-25% of the elderly people who had fallen suffer serious injuries resulting in diminished mobility and independence, and an increased risk of death. Approximately 130 people, thereof as many as 96% in the group of elderly people, die every year from hip-joint fracture. Due to injuries, 1,100 people older than 65 years were admitted for rehabilitation treatment in 2004, which represented 32% of all injury-related rehabilitation. Among women aged 65 and over the share amounts to 38%, and 26.5% in men from the same age group. Among those dying from injuries the share of elderly people is 39%. Owing to their frequent and numerous chronic diseases and poor general health condition, elderly people die from equally serious injuries more often than the rest of the population. 5.4 Consumption of medications In Slovenia 38% of all dispensed medications were prescribed to elderly people in 2004, representing 44% of the dispensed medication value. (Insured) persons in Slovenia aged 65 and over spent on average 6.5 times more money on medications than a person aged 20-40, with this ratio in the group of people aged over 85 achieving no less than 8.5. Among both men and women most medications dispensed to elderly people related to cardiovascular diseases, followed by medications having an effect on the nervous system, and medications against gastrointestinal and metabolic diseases. Those three groups of medications are also in the lead according to the value of dispensed medications. Table 59: Number of dispensed prescriptions and value of medications by age, Slovenia, 2004 Age groups Number of prescriptions Value (in SIT) 0-19 1,606,808 4,961,296,041 20-64 7,375,069 46,093,765,515 65 + 5,479,267 39,479,545,586 Total 14,461,144 90,534,607,142 Source: IVZ. 78 In Slovenia acute hospital treatments are monitored separately. Data on activities (observation, diagnostics, medical treatment) relating to the entire acute health care of a hospitalised person are by means of a classifi cation programme arranged in one of more than 600 groups of comparable cases (SPP). 79 The weight is the coeffi cient of the estimated cost of treatment based on the diagnosis, the age of the patient and the diagnostic and therapeutic procedures. Slovenia – A Long-living Society 99 6. SOCIAL INCLUSION OF ELDERLY PEOPLE Population ageing80 is almost a world-wide phenomenon; the exceptions are Africa, India and some Asian countries, where the population structure is still young. It is particularly Europe that faces demographic changes which are in terms of their extent and severity beyond comparison in recent history; the fertility rate in EU member states is falling below the replacement rate, the proportion between the young, middle-aged and elderly is being destroyed, while Europe’s population is ageing. The demographic structure of the population in EU countries will undergo significant changes in the next few decades. In the decades after the Second World War, Europe’s fertility rate was twice what it is today, and life expectancy has been rising. The total population of the EU25 member states will slightly decrease, however, a dramatic drop is expected in the size of the working-age population aged between 15 and 64 (projections for 2050 forecast a 16-percent decrease, which accounts for 48 million inhabitants). On the contrary, the number of inhabitants aged 65 and over (65+) will significantly increase (the projections for 2050 suggest an increase by 58 million or 77%); inhabitants aged 65+ will thus account for more than 30% of the total European population. An outstanding increase is noted in the number of very old people, aged 80 or more (80+), who generally need intensive nursing and medical care; their share in the total population stood at 1.2% in 1950, 3.4% in 2000 and, according to the projections, it will rise to 11.8% of the total population in 2050. In the coming decades, Slovenia is also expected to undergo significant changes as regards the size and structure of its population. Slovenia’s population is ageing rapidly. These changes will result in a decrease of the middle-aged and young generations and an increase of the old generation (see Table 35). In Slovenia, the ratio between the size of the population aged 65+ and the population aged 15-64 (the old-age dependency ratio) will rise dramatically by 2050. According to the Eurostat projections for 2050, Slovenia will have twice as many people aged 65+ than in 2005. The old-age dependency ratio amounted to 21.7% in 2005, however, its increase to as much as 55.6% is envisaged for 2050. In other words, in the 2005-2050 period the ratio between the population aged 65 and over and the working-age population is expected to grow from 1:4.6 (in 2005) to 1:1.8 (in 2050). Rapid changes are expected particularly after 2015, notably in Slovenia, which is to undergo more profound changes than the average of the EU25. These countries are envisaged to increase their old-age dependency ratio from 24.9% in 2005 to 52.8% in 2050. Ageing opens up several issues concerning the sustain-ability of social protection systems and, consequently, issues concerning the solidarity and good intergenerational relations. Inappropriate systemic responses may even result in creating conflicts between generations. Each generation defends the interests and rights that, according to their belief, pertain to them. 6.1 Good intergenerational relations An individual’s life is an indivisible whole comprising youth, middle and old age. Each stage imposes certain tasks; all three stages together form a life cycle. Thus, society consists of members belonging to young, middle and old generations that are complementary to each other. A society that lacks such complementarity (or discriminates against one of the generations) is confronted with a serious social and policy issue. Old age has become a social taboo, giving rise to prejudice of various kinds and negative stereotypes. The consumer society worships audacity, beauty, promptness, youth, success and power. Such social conditions hamper a positive image of old age and its pertaining advantages. One consequence is the feeling of loneliness experienced by the elderly. However, they too do not accept old age and many times do not see the opportunities that the third life-stage offers them. Good intergenerational relations are being destroyed. The way of life and division of work in an urbanised society deteriorate intergenerational relations; be it at work, entertainment or other activities of everyday life. In the past, the elderly were a major source of information, skills and knowledge for young generations; but in a highly computerised world, members of the third generation are hardly coping with fast development. Despite the 19th and 20th century being periods of rapid knowledge development in numerous fields, knowledge in the field of personal growth has been lagging far behind. While younger generations are still in need of knowledge, which was usually passed on to them by the elderly, the third generation is no longer able to convey their positive personal and life experience as well as the findings in the field of personal growth and good interpersonal relations. By gaining professional and other knowledge, the younger generation is no longer interested in them, which eradicates an important element of experiencing the meaning of old age – passing on experience on to younger generations. The low appreciation of the third generation stems from a social controversy, which was caused by the fact that the system of organised solidarity with pension insurance provided social security and independence of the elderly at an individual level, but it neglected to include the great In statistical terms, the population is elderly if 10% of the inhabitants are aged 65 years or more. 100 Social Overview 2006 potential of the old generation in the social division of work; in doing so, the third generation became both maintained and independent (Hojnik-Zupanc, 1999: 18). In the coming years, this inconsistency of ‘dependent independence’ of the third generation will have to be overcome by adapting social protection systems to demographic changes. A new paradigm of intergenerational interdependence – providing maximum autonomy and independence from social conditions and available resources – is required; as is a focus on social networks of the elderly. 6.2 Housing conditions of the elderly Data on the housing conditions of the elderly in Slovenia are not systematically collected. A picture of the existing situation and needs may be obtained from the survey carried out in 2002 by the Faculty of Social Sciences and the Urban Planning Institute of the RS for the purposes of the Pension and Disability Insurance Real Estate Fund81. The housing units of the elderly are mostly small. The size of a housing unit they occupy corresponds to the type and/or size of the household. Since these are mostly single households, the housing units are predominantly small. 51.5% of the surveyed elderly occupy units of a size of up to 50 square metres; housing units greater than 100 square metres in size are rarely occupied by the elderly. The majority of the elderly are satisfied with their housing conditions. The satisfaction of the elderly mostly relates to access to the housing unit, the vicinity of public services, the size of the unit and the vicinity of their relatives and friends. Therefore, in the last few years the vast majority (80%) have not thought of moving. 6.3 Social support networks among the elderly Even though the social support networks of the elderly are being significantly reduced, their support is satisfactory. Research conducted by the Social Protection Institute of the Republic of Slovenia (Novak et al., 2004) shows that the prevailing models of care for the elderly in Slovenia are home care and/or family and neighbour care and that the positive impact of social support networks is primarily associated with the intensity of ties (one person providing several types of support). The social networks of the elderly are associated with their health status and the level of their functional ability. Social networks, regarded as protective factors of the elderly (Dragoš, 2004), depend primarily on the income, physical condition (more useful for those in poor physical shape) and gender (more important for men, especially for those with low physical condition). Box 21: Comparing the social networks of the young and elderly If social support between the persons aged from 18 to 64 years and those, aged 65 and over is compared, several differences and similarities may be noticed: (1) the networks of the elderly are on average smaller compared to the networks of the young; (2) in financial distress, the elderly more than the young seek help from their relatives; (3) in socialising, the share of women relatives among the elderly is slightly higher than among the young; (4) the emotional support provided to the elderly by women relatives is greater than the support of men relatives; and (5) another important source of support for the elderly is neighbours. In illness, both the young and the elderly seek help from their female relatives. Social support is most scarce for elderly women living alone. The social network of the elderly on average consists of 5.8 persons (6.5 at the level of the total population), with the most important source of their support being children. Many of the elderly live alone. 48.2% of respondents live alone, while 31.5% live in a two-person household. Not many live in multi-person households (only 4% in 5 or more-person households). Taking the total Slovenian population into account, a significantly lower number of them occupy private-owned dwellings: 51.9% live in their own house or apartment (their share accounts for 84.6% of the total population), 41% rent a house or apartment, 3.8% live in sheltered housing and 3.3% in another arrangement. 81 2,359 elderly persons participated in the telephone and mail survey. Box 20: Experiencing old-age emptiness Nowadays there are many doubts about the value and meaning of ageing and old age (regarded as ‘old-age emptiness’). All three generations, notably the third one, do not experience old age as a meaningful period such as youth and middle age. The reasons leading to this form of existential vacuum are the same as those for breaking the intergenerational ties. Suffering from a crisis of old age emptiness means that elderly experience the aimlessness of everything they do or that happens to them. Instead, they experience their or someone else’s old age as a gloomy dead-end, even though in reality they stand on a solid and safe life path with many opportunities. Such a disturbance among the elderly is characterised by aimless-ness, discouragement, non-activity, negative attitudes and behaviour towards the young, indulgence in stupefaction and addiction, depression, attempted suicide; among the young it is characterised by avoiding the elderly, thinking and talking about old age. Experiencing old-age emptiness among the elderly paralyses and blocks their capacities and abilities to look after themselves and make an active contribution to society. The consequences are manifested in psychosomatic illness, notably in apathy, bitterness, pessimism, which makes them unpleasant for themselves and their surroundings. Slovenia – A Long-living Society 101 Informal social support is most available to the elderly li- for elderly persons when living alone; in 2003, as many as ving within an extended family in a rural environment but 39.9% of single elderly persons lived below the at risk of also most scarce for elderly women living alone and whose poverty threshold. Elderly women live alone more frequently networks are geared mainly towards children. In case their than men; being single is one of the most important causes needs increase, alternative informal support for these elderly of a higher at risk of poverty rate among women. women is very scarce. Persons aged 65 years and over who are not owners of their The prevailing types of social networks among the elderly housing face a higher incidence of risk of poverty. The risk in Slovenia are family and/or kin networks. This may be- of poverty by housing tenure status shows no significant come an issue in at least two aspects: support networks often differences among the group of the population aged 64 and consist of women relatives, which may cause difficulties less (a considerably higher risk is identified only among te-when re-conciliating their numerous responsibilities and, nants); however, among the group of the population aged 65 consequently, a source of their overburdening. Given the years and over, people who are not owners of their housing changing structure of the family and the increasing share of (tenants or rent free) are at a greater risk of poverty; in 2003, single people, the issue stems from the fact that the family, 30.2% of the rent-free lived below the at risk of poverty currently the main provider of care for the elderly, is often threshold. The at risk of poverty rate among this group is powerless while society lacks an appropriate institutional slightly higher compared with that of tenants (29.4%) and arrangement. Increasing needs for public services may be almost double that of owners (17%). The share of owners expected particularly among the elderly with scarce informal among the elderly is lower compared to the average among support, for whom the only option is institutional care. These the country’s population. issues can only be addressed by means of complementary co-operation between the informal and public sectors, which is to become more actively involved and to provide access to 6.5 Long-term care support and care to all the elderly in need of service support, Many elderly are chronically ill, helpless and incapable of irrespectively of their material, family or other resources. taking care of themselves. Their survival and life depends on the help of other people; they need health and social care 6.4 The poverty of the elderly services, which are not provided by family members. Since these needs, when they arise, are permanent and growing over The living standard is one of the essential elements of social time, they are identified as needs for long-term care. With inclusion or exclusion. This equally applies to the first, se- age, these needs become more complex and time consuming, cond and third generation; however, the latter is threatened which lasts until the end of one’s life (see Box 22). by poverty much more than the other two generations. In the future, the share of people needing long-term care will The risk of poverty among the elderly is almost twice as increase rapidly (see Table 35). The reason is, on the one high as for the total population. In 2003 (latest available hand, the rising number of dependents, which is projected data), the number of people living below the at risk of poverty on account of the increased number of the elderly and, on the threshold accounted for 10.0% of the population (9.9% in other hand, the changing role of the family and its capacity to 2002); in the same year, among the population aged 65 and provide care. While in the past care used to be strictly a family over, there were 18.5% of people living below the at risk of matter, today, when this responsibility is divided between the poverty threshold (19.2% in 2002). family and the state, the question remains how this division should be made in the most appropriate way. The majority For women aged 65 and over, the risk of poverty is higher wish not to be placed in an institution because of their need than for men from the same age group. In 2003, the share of for care. Care should be organised so as to enable the taking the elderly living under the at risk of poverty threshold stood of that option, however in this case it should not strictly be at 11.1% for men and 22.9% for women. The risk increases a family matter. Delegating a large part of responsibility to Box 22: Joint OECD, Eurostat and WHO definition of long-term care The term ‘long-term care services’ encompasses the organisation and delivery of a broad range of services and assistance to people who are limited in their ability to function independently on a daily basis over an extended period of time. Functional dependency can result from either physical or mental limitations and is defined in terms of the inability to perform essential activities of daily living (ADLs), such as eating, bathing, dressing, using the toilet, getting into and out of bed, and moving about the house, or activities necessary to remain independent, known as instrumental activities of daily living (IADLs) such as shopping, cooking, doing laundry, managing household finances, and housekeeping. Source: (JOINT OECD, EUROSTAT AND WHO HEALTH ACCOUNTS (SHA). Guidelines for estimating long-term care expenditure in the joint 2006 SHA data questionnaire, p. 22) 102 Social Overview 2006 the family may result in family overburdening, in particular women, who take care of others more frequently, and in a financial burden. Within this context, it is undoubtedly important that the family itself is changing. The importance of the state is thus increasing; responsibilities for care should be appropriately shared between public and private spheres. Nevertheless, the research conducted with respect to care for the elderly in Slovenia and elsewhere in Europe is poor; so far, this extremely important social security network has not received any professional nor socio-political attention or support. Only in the last few years have Slovenia and other EU countries seriously addressed the issue of providing the long-term care for the elderly who for various reasons urgently need the help of others. Demographic changes will create a significant rise in long-term care demands. These are not only related to age but they increase with age. Research carried out within the SHARE82 project shows that 20% of the people aged 65 and over have a certain type of disability causing their dependence on the help of others when performing activities of daily living. Dependence tends to grow with age. Dependency rates also significantly rise with age: the mentioned survey shows the share of dependent persons in EU countries in 2004: among people aged 65-70 there were 7.1% dependent men and 9.4% of women, while among people aged 80+ there were 27.7% dependent men and 36.6% of women. In Slovenia, the estimated long-term care needs for 2004 (based on the SHARE survey) amounted to 58,000 inhabitants (14% of men and 22% of women, totalling 19% of the population aged 65 and over). If the estimates are correct, it can be assumed that a considerable share of the dependent population in Slovenia merely received informal support from their family, neighbours, friends or non-governmental organisations or that assistance, in spite of their needs, was not received at all. Such dependence has been partly relieved by the receipt of an attendance allowance. So far, the development of long-term care in Slovenia has been aimed at strengthening mainly institutional care rather than home care. According to data available for 2004, between 30,000 and 35,000 inhabitants were included in the system of long-term care as well as the attendance allowance system. Of these, 14,000 people received institutional care, nearly 5,000 received home care and nearly 30,000 received an attendance allowance. Old people’s homes provide institutional care for elderly people and through organised meals, care and health care replace or supplement the function of the home or family. In 2005, institutional care, which is organised in ten regional units, was provided to 13,641 people by 68 public and private old people’s homes. However, in the last five years the available capacities have considerably increased (see Table 60 and SA: Tables 55 and 56). Home help (home care) started at the end of the 1990s. However, even public social assistance at home cannot replace family and other informal network providers: by providing support and partial relief it enables the family to continue providing home care. In addition to home care, other non-institutional forms of assistance developed at the end of the 1990s, such as day-care centres, sheltered housing, distance help and the home delivery of meals. They, however, are still lacking enough users. The failure to develop home care is largely due to the poor interoperability and co-ordination of social, health and other services and their scarce resources and capacities. For this reason, the extent of available assistance often cannot meet the needs for more demanding and extensive care. Compared to the elderly receiving institutional care, the scope of public services is smaller for those who decide to receive home care or do not have any other option – in spite of their needs being identical to the needs of people receiving institutional care (see Box 23). Table 60: Old people’s homes, Slovenia, 2000-2005 Institutions People in care total Share of women 2000 49 11,905 72.3 2001 55 12,346 72.6 2002 58 13,051 72.9 2003 61 13,498 73.0 20041 63 13,098 74.1 20051 68 13,641 74.1 Source: SORS. Note: 1In 2004 and 2005, the statistical survey carried out by the SORS included people living in seven social welfare institutions, eight units providing a special form of adult care and functioning as special units of old people’s homes i.e. as their branch units. Up to and including 2003, the residents of these eight units were included in the statistical survey of old people’s homes and/or combined social welfare institutions. Due to changes made to the statistical survey in 2004, the number of people living in old people’s home decreased in comparison with 2003. The research was fi nanced by the European Commission and has been carried out in 10 EU countries in the last few years. Slovenia – A Long-living Society 103 Box 23: Care for the elderly in Slovenia For the majority of the elderly institutional care is not a desired form of assistance. In 2002, a survey was carried out by the Urban Planning Institute concerning where the elderly would like to spend their old age (the place and environment they would move to). Only 7.5% of them would choose to live in an old people’s home and 8% would opt for sheltered housing. For the majority the most desirable social contacts in the vicinity of their residence would be relatives (29.5%) and people from different generations (26.4%). Only 12.2% of the elderly would choose the company of people from the same generation. Research and experience of the Anton Trstenjak Institute show that the possibilities for family and/or home care are shrinking for various reasons: - the increasing share of the elderly, especially very old people in need for care, while the share of the young and middle generation has been decreasing; - the growing share of the elderly living alone or with another elderly person; - family care of the elderly is mostly provided by employed women who are not educated about caring for the elderly; being employed and caring for their own family providing care for the elderly represents an additional burden on them; - cultural taboo against old age causes a subconscious aversion to elderly people and their helplessness, which contributes to the greater family marginalisation of an elderly person; - communication alienation and a lack of mutual knowledge of generations lessen the possibility of mutually satisfactory family care for an elderly person; - people from all generations, in particularly the elderly, have great expectations as regards social relations but very little applied knowledge and intergenerational communication skills; - elderly people, who have so far lived in a society of relative prosperity, are not prepared for the personal, social and health problems associated with old age; therefore their company is too demanding and unpleasant for younger family members; and - the attitude of elderly people to family care is ambivalent: on one hand, they take the attention and assistance of their relatives for granted while, on the other hand, they are highly aware of their autonomy and self-sufficiency, which causes behavioural and verbal refusals of family assistance (they do not want to be ‘a burden’). 104 Social Overview 2006 7. ECONOMIC AND FINANCIAL CONSEQUENCES OF POPULATION AGEING The ageing of the population is a process triggered by diminishing fertility in combination with extension of life. It is expressed as higher life expectancy and the changes of relations between age groups. This is very evident in the ratio between people aged over and below 65. Increasing life expectancy means that in the future a growing share of the population will be inactive due to old age, whereas the size of the active population, which creates domestic product, will shrink as fertility rates become lower. EU member states have drawn up projections until 2050. Such a distant horizon is needed because some of the current demographic facts already strongly define the economic, financial and societal consequences far into the future. Population projections are made for each country based on a commonly agreed assumptions; Table 62 shows the projections for Slovenia83, the EU15 and the EU10. By 2035 GDP growth could more than halve due to demographic reasons. The reduction in the number and share of active people (at the same time the overall population will shrink only marginally) will reduce potential GDP growth. The model- estimated84 effect of the changes in the population structure and the size of population groups on GDP growth in Slovenia (and consequently on productivity and employment) shows that GDP growth would more than halve by 2050. Slovenia has also made population projections based on alternative assumptions. Over such a long period the development of the population could take a different course than that projected with the assumptions listed in Table 62. For the analytical assessment of the effects of demographic changes, Slovenia has, in addition to Eurostat’s official projections, also prepared alternative projections based on Table 61: Key demographic indicators in 2004 and projections for 2050, Slovenia and the EU15 and EU10 EU15 EU10 SLOVENIA 2004 2050 2004 2050 2004 2050 Fertility rate 1.5 1.6 1.2 1.6 1.2 1.5 Life expectancy at birth - men 76.4 82.1 70.1 78.7 72.6 79.8 Life expectancy at birth - women 82.2 87.0 78.2 84.1 80.2 85.1 Net migration fl ows (in 1000) 1,347 778 -3 101 6.1 6.7 Net migration fl ows (as % of population) 0.4 0.2 0 0.1 0.3 0.4 Source: Materials for Population Ageing Workshop. IMAD: Ljubljana, June 2006, taken from: EUROPEAN ECONOMY, Special report no/2006, The impact of ageing on public expenditure: projections for the EU25 Member States on pensions, health care, long-term care, education and unemployment transfers (2004-2050), Report prepared by the Economic Policy Committee and the European Commission (DG ECFIN). Table 62: Share of the elderly and projection of the share of the elderly based on different assumptions, Slovenia, 2005-2050 (in thousands and in %) 1 Jan 2005 1 Jan 2010 1 Jan 2020 1 Jan 2030 1 Jan 2040 1 Jan 2050 Low 1,992,113 1,963,853 1,890,415 1,801,674 1,663,014 1,490,760 65 and over 15.3 16.7 20.8 25.8 29.4 32.7 85 and over 3.0 3.9 5.1 6.2 8.8 10.0 Middle 1,999,722 2,014,802 2,016,694 2,005,999 1,965,314 1,900,839 65 and over 15.3 16.5 20.4 25.1 28.4 31.1 85 and over 3.0 3.8 5.1 6.3 9.1 10.6 High 2,007,369 2,069,175 2,170,058 2,271,619 2,383,601 2,520,801 65 and over 15.3 16.3 19.7 23.8 26.5 28.0 85 and over 3.0 3.8 5.1 6.2 9.0 10.3 Source: Sambt, J. (2006): Material for Workshop on Population Ageing. IMAD: Ljubljana, June 2006. 83 Data for the basic variant of Eurostat’s population projection for Slovenia are also available from the SI-STAT database (see http://www. stat.si/pxweb/Database/Demographics/05_population/07_05197_projections/07_05197_projections.asp). Data for all EU member states are available on Eurostat’s web portal. 84 Majcen, B., Verbič, M., van Nieuwoop, R., Sambt, J. (2005): ‘Analiza prihodnjih trendov slovenskega pokojninskega sistema z dinamičnim modelom splošnega ravnovesja’ in IB revija, No. 3. IMAD: Ljubljana. Slovenia – A Long-living Society 105 other than commonly agreed assumptions85 and various variant parameters. The low variant retains the fertility rate but does not take into account such a high life expectancy, whereas the high variant is based on assumptions of higher fertility rates and higher life expectancy (see Table 62). system and the parameters that define the system. According to the projections, pension expenditure will swell from the present 11.2% of GDP to 18.5% of GDP in 2050, with pension contributions rising from 9.9% to 10.9% (see Table 63, and SA: Table 57). Regardless of the parameters used in the projections, the share of people older than 65 and those older than 85 (the very old) doubles and trebles, respectively. These changes place the sustainability, efficiency and fairness of the systems of financing among the key development issues of social security systems. The rising share of people older than 65 will significantly increase spending on pensions, health, long-term care and other age-related expenditure. 7.1 Expenditure projections Projections of age-related expenditure have been prepared by the European Commission86. The pension expenditure projections were prepared by the member states themselves using their own models, whereas projections on expenditure on health care, long-term care, education and unemployment were made by the European Commission using a common methodology87. Since the fiscal effects in individual countries had to be compared across the EU, only the middle (EU) variant was used in the assessment of financial consequences. 7.1.1 Pension expenditure Since age is the main criterion for obtaining pension rights, pension expenditure is directly correlated to the population age picture and trends and they depend on the nature of the Compared to other systems in Europe and elsewhere, the Slovenian pension system is regarded as quite generous. The ratio between the average old-age pension and the average wage (replacement rate) was about 80% at the beginning of the 1990s when age and insurance criteria for retirement were exceptionally beneficial (low retirement age, relatively high annual accrual rate). The pension system had mitigated the adverse conditions in the labour market and allowed for the retirement of redundant workers under more favourable conditions. In the 1990s the number of pensioners grew rapidly: from 393,000 in 1991 it soared to 460,000 in 1999 (up 17%) and to 505,000 in 2005 (up 10%). The total number of old-age, invalidity, family and, in the years following the pension reform, widowers’ pensions, increased by 112,000 or 18%. Pension expenditure (except for expenditures for the health care of pensioners) stood at about 11% of GDP in this period. From the vantage point of public finances, the pension system was barely sustainable in the 1990s; projections at the time suggested that over the long term pension expenditure would grow very rapidly, exceeding 24% of GDP by about 2035. The financing of future pension expenditure was unsustainable in that system. The pension reform of 2000 severely tightened the main parameters of the public compulsory pension system. The pension reform raised the minimum retirement age, intro- Table 63: Effects of ageing on public fi nances, Slovenia, 2005 and projections for the 2010-2050 period 2005 2010 2020 2030 2040 2050 Share of GDP, in % Age-related expenditure 18.8 18.9 20.9 24.2 27.7 30.1 Pensions 11.2 11.2 12.5 14.6 17.0 18.5 Health care 6.7 6.7 7.3 8.2 9.0 9.6 Long-term care 0.9 1.0 1.1 1.4 1.7 2.0 Pension contributions 9.9 10.3 10.9 11.0 10.9 10.9 Assumptions Participation rate, men (15-64) 73.5 76.4 77.9 77.0 75.4 76.4 Participation rate, women (15-64) 63.9 66.3 69.0 69.8 69.0 70.5 Total participation rate (15-64) 68.8 71.5 73.6 73.5 72.3 73.5 Unemployment rate 6.0 5.5 5.4 5.4 5.4 5.4 Source: (2005) Convergence Programme. Ministry of Finance. 85 See, for example, Kraigher (2005), Sambt (2005). 86 Projections of pension expenditure were prepared by the member states themselves using their own models. They were presented to a working group during the testing procedure (open method of co-ordination). 87 Slovenia also prepared its own projections of expenditure on health insurance and long-term care. The results of the projections made by Slovenia and the European Commission do not differ substantially. 106 Social Overview 2006 duced the new notion of full retirement age, reduced the accrual rate (the value of one year of pensionable service), extended the qualifying period for the establishment of the pension base, equated the old-age pension income with the income of those retiring after 2000 under the new conditions, eliminated the option of early retirement, introduced permanent bonuses for activity beyond full retirement age and permanently reduced the pensions of those retiring before their full retirement age. With the implementation of these changes pension expenditures stabilised at about 11% of GDP. However the replacement rate decreased (in 1999 the ratio between the average old-age pension and the average wage was 75.8, in 2005 it was 69.1). In public this reduction of the relative value of pensions was attributed to the indexation formula88 so the indexation was changed in 2005 based on a political decision in order to equalise pension growth with wage growth in nominal terms. Whereas pensions will grow appropriately as a result, the deteriorating ratio between elderly and active populations will further aggravate the provision of sufficient financial resources for pension expenditures. The best way to increase one’s pension is to extend work activity; that is to postpone retirement. The answer to how to increase activity beyond the age of 55, and even more so beyond 60, is one of the key tasks and a great challenge. The low activity rate between 55 and 64 is partially a consequence of the mass early retirement seen in the 1990s, but it is also affected by the poor employment and qualification structure of older employees. The best way to increase one’s pension is to extend work activity and postpone retirement as a later retirement involves incentives such as an increased accrual rate and an increase in the pension with bonuses for service beyond full retirement age. Yet another way to secure appropriate pension earnings is supplementary pension insurance. The reform made it a constituent part of the pension system. Since supplementary pension insurance is not compulsory and universal but voluntary, whether employers and individuals will actually opt for it depends on their income as well as the available tax incentives. Presently over 50% of employees have supplementary pension insurance coverage. However, many of those with a low income have no supplementary insurance so in the future they will get relatively low pensions from the mandatory pension coverage. 7.1.2 Expenditures on health care and long-term care The health care in Slovenia has undergone many changes. Whereas the private provision of health care used to be explicitly banned and the system was purely public and publicly-funded, public and private forms are currently used side by side both in the provision of health care and in financing. These changes, however, have also had their downsides and shortcomings. The concept of a public health care network has been adopted, but the network itself has not been determined so it remains inactivated. Private providers participate in the public network as concessionaires, but the state and the local government units as concession grantors have no clear guidelines regarding the concession granting procedure. In several instances there has been the migration of health staff from public health institutions that have provided the adequate availability of health services to private practices whose basic principles (returns and profits) make it harder to secure such availability. The combination of public and private funding has improved the sustainability of the health care but it has also increased the participation of individuals (private funds) in the financing. After it was introduced, voluntary complementary health insurance became an ever more important source of financing and now accounts for about 15% of the financing of health care that is provided by the public health network (see Table 12). Total expenditures for health care in Slovenia increased by 45% in real terms in the 1997-2003 period (public by 39% and private by 68%), growing as a share of GDP from 7.2% in 1997 to 8.7% in 2003 (see Table 64). The annual growth of total expenditures averaged out at 6.4% in this period, 2.7 percentage points above real GDP growth (3.7%). The growth in public expenditure on health care, which averaged 5.7%, also exceeded GDP growth. Similar trends have been recorded in all other EU members in the 1997-2003 period, except for Slovakia (see Figure 48)89. To retain the sustainability of the public financing of health care in the face of these trends, the importance of measures designed to keep public expenditure on health care from exceeding GDP growth has been underlined at the EU level. In most countries, including Slovenia, private expenditure on health care has been growing faster than public expenditure (see Table 64). 88 The changes in the ratio between wages and pensions are also affected by the changed structure of wages and pensions and the equalisation of old pensions with the new ones. 89 The World Health Report 2006 (WHO) was used as the source of data for total expenditure for Slovenia and other countries. Data for the 1995-2003 period were submitted to the WHO by the SORS, which co-ordinates the introduction of the System of Health Accounts (SHA) in Slovenia as an internationally comparable methodology for the monitoring of health expenditure. In the EU member states the SHA project is managed by the Eurostat in conjunction with the OECD and the WHO. Data published in the latest reports by the WHO and the OECD has been unifi ed to a certain degree and adjusted to the SHA methodology in order to ensure their international comparability. Slovenia – A Long-living Society 107 Table 64: Total expenditure on health care, Slovenia, 1997-2003 Share of GDP, in % Real indices 1997 2000 2001 2002 2003 2004 2003/1997 Total expenditure on health1 7.2 8.5 9.0 8.8 8.7 n.a. 145 Public expenditure2 5.7 6.6 6.9 6.7 6.6 6.6 139 Private expenditure 1.5 1.9 2.1 2.0 2.1 n.a. 168 Voluntary health insurance 0.8 1.2 1.2 1.2 1.2 n.a. 189 Households (‘out-of-pocket expenditure’) 0.7 0.7 0.9 0.8 0.9 n.a. 145 Source: for 1997-2003: (WHO) The World Health Report 2004, 2005, 2006; for 2004: SORS, First Release no. 301 (30 December 2005); IMAD calculations. Notes: 1Total expenditure on health includes investment in health and excludes sickness benefi ts. 2Including expenditure by the government, local government and Health Insurance Institute of Slovenia. ‘n.a.’ not available expenditure in the 2005-2050 period will grow from 6.7% of GDP to 9.6% of GDP (see Table 64). On top of higher expenditure on health care in the future, we can certainly expect higher expenditure on long-term care. If the current policies remain unchanged, the higher number of people over 65 or over 85, and the doubling or trebling of their share in the total population, will demand 2.5-times the share of GDP that Slovenia is currently earmarking for long-term care from various public and private sources (see Table 64 and Section 1.5.2.1). 7.1.3 Other public expenditure related to demographic changes Changes in the size and structure of the population also affect other public expenditure. It is thus assumed that expenditure on education is defined by the number of students, whereas spending on unemployment benefits is defined by the number of unemployed people. However, projections of the number of people in education and in the welfare system predominantly depend on the system, the policies in individual fields and economic policy. For the 2002-2050 period the European Commission also prepared projections of expenditure on formal education in Slovenia, with the assumption being that the number of students enrolled in formal education will dwindle due to demographic changes. In this projection, enrolment in all levels of education would be 28.1% lower by 2050, which would reduce public expenditure by 0.5 percentage points (to 4.9% of GDP in 2050). Slovenia has not made its own long-term projections for education. First, it does not have sufficiently disaggregated bases and, second, it is expected that education policy measures will be put in place which (combined with other factors) will make it possible to influence the quality of education and the participation of adults in formal education and, subsequently, the range of education expenditure. The OECD (2005) found that most of the increase in health care expenditure over the past 20 years cannot be attributed to demographic changes; a large part of the expenditure is associated with treatment in the last few years before death. Figure 48: Real annual growth in public expenditure on health and GDP, selected countries, 1997–2003 10 9 7 6 4 0 IE| BE, IT« " ¦ UK NO OECD PTsf D SE FI LU SI PL GR CZ FR E: 01234567 Real annual GDP growth, % Source: The World Health Report 2006, WHO. OECD Health at a glance 2005, for Slovenia IMAD calculations. The assessment of future expenditure on health care is not as methodologically unified as projections for pension expenditure. In addition to the size and structure of the population, and purchasing power (which determines demand), health care expenditure depends on altered health doctrines, new technologies and new or changed life-styles. The European Commission has made projections that take into account increased demand for health services in the future, the costs associated with treatment before death90, changes in lifestyle due to greater purchasing power and growing incomes, higher costs of medical staff (which will be paid in proportion to growing productivity) and the fact that people will live longer and healthier in the future. Slovenia has also made its own projections of expenditure on health care and long-term care. The results of these projections do not differ significantly from those made by the European Commission. It is projected that health 8 108 Social Overview 2006 8. THE CHALLENGES OF A LONG-LIVING SOCIETY The ageing of society is a consequence of several factors that result in a long-living society. Such a society is fundamentally different to one in which the size of various age groups is different. In a long-living society, the issues of fiscal sustainability, efficiency and social justice are raised in a completely different way; demographic changes profoundly define the social, economic and financial consequences in the future. Both in Slovenia and in many other European countries, the altered age structure of the population (provided that all other parameters and conditions remain unchanged, especially the mode of retirement and activity) will cause a huge increase in public expenditure on the elderly (pensions, health care, long-term care and other ageing-related expenditure). The reduction of the number of active people and share of the active population (with the total population shrinking just marginally) will fundamentally affect potential economic growth and determine taxes and contributions. In such altered conditions, it will be necessary to adapt education, employment policies and welfare (health, long-term care and pension systems) in order to create solid foundations for social security and enable and promote social inclusion. The later such actions are taken, the more drastic the measures will have to be. The following is a presentation of the development challenges and issues that Slovenia can expect in particular in the labour market, education, health, long-term care and pensions. Youth today is subjected to many risks and growing individualisation. Young people face new demands and restrictions. Compared to previous generations, they are entering the labour market later, becoming independent and creating families later in their lives. One major source of pressure on youth which needs to be eased is time: once they have entered the labour market they have to sacrifice a lot of their (leisure) time. These and other main problems mean that many delay having children. Sometimes this decision is pushed so far into the future that the health conditions for the birth of a second child are no longer in place. Temporal, psychological and physical pressures could be mitigated through mutual help, different expectations of employers regarding the intensity and amount of work at the start of one’s career and a change in employers’ attitudes to the parenthood of their employees. We should work to live, not live to work. The policy-makers must therefore consider the fact that many burdens and obstacles are placed before young people but they are offered little support especially at the beginning of their career and when they decide to create their own families. Public services must help individuals to live quality lives, not just increase their productivity. Slovenia needs a comprehensive family policy and social strategy, which will take into account the altered conditions in which people create families (and the varying needs of different families), which will be universal as well as diffe- rential (considering and addressing the different needs of different groups) and which will promote the implementation of equality between men and women in practice. Profound changes in family life, which are further augmented by the longevity of society, dictate a long-term social strategy and the co-ordination of diverse policy measures which the state should put in place to support the family as a key social institution. The conditions for creating a family in Slovenia are becoming harsher (it is more difficult to get a first job, first apartment etc) and families, in particular women, are under ever greater strain. Slovenia has no policy for reconciling work and private life. Indeed, policies in different areas (housing, employment and education) are often contradictory; they are frequently excessively focused on drawing on the potential of their primary families, thus supporting the late leaving of the parents’ family and making it more difficult for young people to become independent and fully grown-up. Slovenia should therefore draw up a comprehensive family policy that includes measures by different departments with which the state will create conditions that facilitate an earlier transition to independence and the earlier birth of one’s first child. This would also help families who already have one child to decide to have a second one. It is necessary to: - Create good living conditions for families. It makes sense for the measures to target families with a low income, families with small children and those with one child, which are potential candidates to have another child. The first child is a reflection of the desire to have children, but the decision to have a second child involves other motives and (pre)conditions such as trust in the partner and the expectation that the partners will share responsibilities. - Prepare measures to curb youth unemployment. The employment pattern of young people suggests that they are more exposed to the risks produced by the altered conditions seen in the labour market. With increasing frequency they are employed for a fixed term (the share of young people in fixed-term employment is higher than in the EU25), which reduces the security (permanence) of their employment. Surveys show that a secure job is a major precondition for a decision to become a parent so such measures can substantially affect births as well as the activity rate. - Provide job flexibility as well as security. Slovenian research (Kanjuo Mrčela, Ignjatovič, Stanojević, in: Svetlik et al., 2004) suggests that where flexibility is being introduced employers prefer unfriendly forms of employment (weekend and shift work, overtime, temporary or odd jobs). These ‘require greater work intensity and/or increase the uncertainty of employment. Forms that are friendly to employees and families, such as annual scope of work, shorter working hours, division of jobs, flexible working hours, work at home and telework, are used less frequently’ (Svetlik, 2004: 11). Results of Slovenian public opinion surveys show a relatively high level of support in principle for part-time employment as one option for balancing professional and family obligations, especially before children go to school. But the introduction of part-time employment and other ‘less friendly’ forms of employment requires a degree of caution, as some forms of employment impede the income security of families and career opportunities, especially for women. - Pay special attention to housing and to enable young people to move away from their parents earlier. In the 2002 (Census) about 37.1% of Slovenians aged between 25 and 34 still lived with their parents (LAT phase). Addressing housing issues would therefore promote parenthood considering the prevalence in Slovenia of the ‘broken chain’ principle: before the birth of a child the couple must meet all the (pre)conditions for parenthood. By bringing such independence forward, this principle would lend itself more easily to be replaced by the ‘broken chain’ principle (characteristic of Scandinavian countries), where young couples frequently have children as early as during their studies. - Promote the more active participation of men in family life by raising the importance and role of the father. This is also an important measure for the promotion of births since surveys carried out in Scandinavian countries (see Ule and Kuhar, 2002) show that the decision to have a second child largely depends on the father’s participation in taking care of the first child. Surveys confirm that the likelihood the partners will decide to have another child increases if the father has used more of his paternal leave (Rener et al., 2005). According to Ule and Kuhar (2002), it is not only important that the partners share housework and childcare equally but what is crucial is the feeling that the division is fair. The implementation of equality between men and women must therefore be promoted in practice. - Take measures which create conditions for the successful reconciliation of work and private life, career and parenthood. Creating a family and family life also depend on the circumstances in society, foremost employment and the way it is organised. With the dominant ‘culture of long working hours’, life is becoming faster and families are often short on free time. In the presently dominant division of work in the family, women in particular often confront the dilemma of how to reconcile work and private life. The attractiveness of a career does not mean that women find children less important. On the contrary, in an individualised society with a high degree of anonymity, uncertainty and mobility, the desire to have children is part of one’s quest for sense, identity and rootedness. To make this measure work it is essential to promote a different model of workplace relations. People work longer hours and they are often concerned that they will lose their job if they do not meet, or exceed, the demands of their employer. Very few companies in Slovenia realise (Ule and Kuhar, Slovenia – A Long-living Society 109 2003: 125) that a motivated and satisfied worker is more efficient, productive and committed so it is necessary to promote the fact that a family-friendly company is also conducive to higher profits. The Council of Europe lists as examples of best practice those measures of reconciliation policies that allow flexible working hours (the chance to select working hours that best suit the requirements of family life), work from home, flexible and accessible family services (kindergartens and family help centres) and where employers promote parenthood. - The dominant ‘sprint’ career model should be replaced with the ‘marathon’ model (Gilbert in Ule and Kuhar, 2002). The ‘sprint’ model demands huge sacrifices in the starting years of one’s career, when the person must work with maximum speed because this is a ‘short-track race’. However, this period also coincides with the most (biologically) suitable time for reproduction. The financial rewards for the long hours spent in the office and commitment to work usually materialise in the future. Meanwhile, the ‘marathon’ model requires permanent and uninterrupted contributions over the long run. The wage is more in tune with current work so it grows gradually over the years. This model allows for a more balanced distribution of income over the life cycle so the employees have a higher income at the start of one’s career but work shorter hours. Demographic changes require changes in the labour market. In a relatively short time Slovenia will have exhausted the possibility of filling new job positions with younger persons whose unemployment is currently a big development problem. At the same time, improving work activity is one of the key objectives whose fulfilment will determine the economic growth and social stability of society with a fundamentally altered ratio between the active and dependent populations. In the present conditions, pensions and other financial as well as non-financial benefits for the elderly cannot remain at the attained relative level in the future. It is therefore essential to increase work activity especially among the young and the elderly (55-64 years). The state should create opportunities for and focus social regulation on providing conditions for earlier and later work activity. The normative conditions for increasing and extending the work activity of the elderly are already in place in Slovenia, but the health and work conditions necessary for its full implementation are still absent. The occasionally poorer performance of elderly workers is often a cause of the covert and overt dislodging of the elderly from their jobs. For many elderly people, retiring is a way out of trouble at work; given different conditions and attitudes to the needs of the elderly, they could continue working. What is needed then is additional incentives (beyond the mere extension of the required years of service for retirement) and conditions to help young people enter the labour market and the elderly to stay active for longer: - It is necessary to promote young people’s earlier work activity. Young people get jobs relatively late, 11 0 Social Overview 2006 one of the factors being the duration of their studies. The implementation of the Bologna Declaration is expected to contribute to the shortening of studies, but it is also necessary to frame measures for increasing the efficiency of studies. Greater co-operation between educational establishments and companies and the greater influence of companies on curricula would help towards earlier employment and reducing imbalances in the labour market. The second major factor is the existence of parallel labour markets (e.g. student work). In addition to measures which have already been planned and adopted, it might make sense to reform student work with the introduction of ‘odd jobs’ for which lower social security contributions are paid. One measure of the active employment policy that is aimed at reducing unemployment among young people is the reimbursement of social security contributions for employers who hire young unemployed people or first-time job-seekers, but it would also be worth considering additional measures to help first-time job-seekers. - It is necessary to draw up a strategy of active ageing. Considering the current situation in the labour market, Slovenia will not achieve the Lisbon Strategy goal (50% employment in the 55-64 age group) unless it drafts a strategy of active ageing that includes: (1) measures aimed at reducing the occurrence of occupational diseases and improving safety at work; (2) programmes for improving work conditions; and (3) measures that will translate life-long learning from principle to practice. - It is necessary to promote the inclusion of the elderly in education and training. Life-long learning is useful for the individual as well as society and the economy so it is necessary to promote the enhanced inclusion of elderly workers. Life-long learning improves their adaptability to the labour market. - The employment of the elderly could also be raised through the greater use of part-time employment as a means of gradually leaving the labour market, and the development of certain services, especially social services. This would create employment opportunities even for less educated and older women, whose employment rate is very low. Economic policy-makers should consider promoting the development of employment in personal household services and long-term care. Demographic changes will also affect the number of children and youth in primary and secondary education and hence the need for teachers. Factors to be taken into account in youth education include both demographic trends and certain general trends in education for which we assume that they will continue. At the tertiary level, the impact of demographic changes is not evident yet and enrolment is increasing, which is in accordance with the policy of raising enrolment in tertiary education and improving the education structure of the population. But the lower number of children and youth in schools is already reducing the need for teachers. It is expected that layoffs will be necessary, but there will also be problems with the employment of fu- ture graduates of teacher-training programmes. Addressing redundancies among teachers will be an important issue. One of the options is to reduce classroom sizes, redirect potentially redundant teachers to other professions and reduce enrolment in teacher-training programmes. The longevity of society is leading to changes in the health care. The demand for health care is changing as the population ages. Chronic and degenerative diseases are becoming increasingly frequent, which means higher spending on detection, treatment and rehabilitation. The desire and need of people to live independently in their own home environment will increase the need for primary health care. The ageing of the population therefore requires that the authorities: - Create measures for ensuring the efficiency and financial stability of the health care and welfare system. The essential aspect of this measure is to ensure equality of access and an appropriate public/private balance in the health care. - Create measures to increase the number of ‘healthy years’. As life expectancy increases, it will also be crucial to observe to what extent the number of years in which disease is still infrequent and functional abilities are still not deteriorating will increase too. This could significantly reduce the demand for health services, long-term care and the social inclusion of the elderly. Expenditure on health care and long-term care could be reduced in particular with the beneficial effects of: (i) prevention in health care such as preventive programmes, healthy living (healthy food, physical activity etc.) and good social contacts; and (ii) appropriate medical and psycho-social rehabilitation. - Develop programmes for educating and training health staff for work with the elderly. The demand of the elderly for health care is changing and increasing but the response of the health system is relatively poor. It is necessary to develop new and adjust old health programmes, implement new approaches and realise the altered role of certain health professions and their work with patients. Programmes for the education of various health professions and other programmes teaching work with the elderly (e.g. social workers) should place greater stress on gerontology. The only way to efficiently provide for the elderly is to address these issues in an interdisciplinary way. - Funnel financing in research and development to those fields where population ageing is expected to produce the greatest extra demand, including the promotion of elderly people’s health. - Include the elderly in active life and prevent social exclusion as much as possible and for as long as possible. It is clear that different social causes affect health and the demand for health care and long-term care so this aspect may not be overlooked in the efforts to reduce the demand for such services. We should also bear in mind the importance of accessibility of medical devices, which improve the quality of life and inclusion in society. Slovenia – A Long-living Society 111 The system of long-term care is in the most acute need of reform. The swelling demand for long-term care, the speed of the increase and the projected soaring of expenditure show that tackling this is an issue that all European countries will have to deal with. An increasing number of countries are treating the demand for long-term care as a new social risk whose resolution cannot be left primarily to the family; instead it needs to be regulated in a deliberated and systematic manner. The main reasons to seek a comprehensive systematic solution include: (i) the lack of integration among the existing systems; (ii) inequality in rights and access to services; (iii) the altered role and ability of the family to provide for the long-term care of its elderly members; (iv) demographic changes; and (v) the need to ensure the long-term financial sustainability of the system. In Slovenia there is already a certain share of the population which conceivably needs long-term care but it is not getting it. It will also be necessary to ensure the greater equality of access. Slovenia can therefore expect mounting pressure to increase expenditure, not only because the number of the elderly will rise but also because more elderly people will want to be included in an organised system of care. It is necessary to: - Establish a uniform system of long-term care that will be efficient, rational and socially fair. Activities are under way to create a new system of long-term care by introducing a type of special social security coverage. In the new system it will be exceptionally important to find a proper balance between public and private expenditure that will secure sustainability in terms of public finances and provide equality of access to people with a lower income. - Expand the provision of care at home. People’s desire to live in their own home environment will increase the demand for complex health care and home care, which has to be coupled with appropriate forms of the provision thereof. In the past, the network of institutional forms of long-term care, which are often more expensive and less user-friendly, has expanded faster whereas problems that have hampered the growth of home care remain unresolved. The new system must promote the provision of home care with the introduction of mechanisms that will: (i) give this form priority over other forms; (ii) provide for an appropriate system of co-ordination for the provision of services for people who want to remain at home; and (iii) promote and incentivise the informal care that is provided by family members, who provide most of the household assistance in the case of sickness, and non-governmental and voluntary organisations. People’s health and their functional abilities also have a decisive impact on the increase in demand for long-term care. This determines the degree of their independence (or dependence) and the need to be helped by others. In order to preclude the need for long-term care or push it further to older age, it is necessary to develop health promotion programmes, prevention, rehabilitation and other activities that were highlighted in the section on the extension of the number of ‘healthy years’. The quality of ageing is crucially determined by interpersonal relations, the relations of the elderly with the second and third generations, and the prevention of loneliness. Tackling the challenges of an ageing society involves more than just resolving financial issues and adapting and ensuring the financial sustainability of the pension, health, welfare and other systems; it is also about overcoming prejudice against old age and eliminating the marginalisation of the elderly. This is the only way that the main obstacles to improving the quality of ageing and inter-generational relations can be eliminated. Material issues need to be addressed alongside non-material needs. An ageing society cannot and should not allow itself to have elderly people (who already account for a large share of the population that will however continue to grow) be merely passive onlookers or treated merely as a group that puts a burden and a cost on the active population. By formulating a set of different measures, it is necessary to make ageing less unfriendly for the elderly and less burdensome for those who (will) take care of them. It is necessary to facilitate and promote the inclusion of the elderly in (leisure time) activities. Inclusion in various activities in retirement can improve wellbeing and the quality of life for the elderly. People who attend educational courses or have hobbies strengthen their mental abilities, maintain more social contacts and are on average capable of taking care of themselves for longer. It would be prudent to consider the introduction of educational programmes and leisure-time activities adapted to the needs of the elderly, a network of providers of such activities and appropriate prices thereof. The population outlook is directly related to pension expenditures, which will exert even more pressure on the pension system in the future. The share of the elderly will double and the share of the very old will treble. Yet what is even more important for the pension system is the old-age dependency ratio; as the share of the active population shrinks, we can expect greater tensions in the pension system (the ‘baby boom’ generations are retiring too). Model simulations (Majcen et al., 2005) show that the additional deficit of the pension system could increase significantly (in the period up until 2050 it could increase to 8%-12% of GDP depending on the scenarios applied). A pension reform has been carried out in Slovenia, but the gradualness of some measures is extended over a very long period. Additional interventions in the systems will certainly be necessary, it will have to be modernised, adapted to social changes and made sustainable. However, special attention will also have to be paid to making it socially acceptable. Action will have to be taken to address poverty among the elderly. Many of the effects of the pension reform on the income and, more broadly, socio-economic status of pensioners will only become evident over a long period. However, certain analyses already indicate that one of the consequences of securing the financial sustainability of 11 2 Social Overview 2006 the pension system with the pension reform is the relative deterioration of the income status of pensioners (Stanovnik, Kump, 2006). This is a sensitive issue that requires ongoing and in-depth monitoring as the poverty of the elderly is a problem in Slovenia. The risk of poverty is almost twice as high for people over 65 as the average for the entire population. The risk is the most acute for older women, in particular those who live alone. This problem has not been dealt with sufficiently so the fact that it is a problem, the reasons for it and possible changes should be researched in-depth and measures subsequently taken within the framework of social security policy to combat it. Slovenia shares this problem with most other European countries, in particular the old EU member states. The measure most frequently used to reduce the risk of poverty for the elderly is to provide appropriate income and improve the scheme of minimum pensions. Other changes in the pension system, the way pensions are indexed, the extension of work activity and the situation in the labour market can also make important contributions. Another important issue is the inter-generational redistribution effects of the measures chosen. Analyses of the welfare of individual generations in Slovenia (Majcen et al., 2005) indicate that possible strategies and measures in the public finance system that are designed to ensure long-term sustainable growth and appropriate social development, have different inter-generational redistribution effects. The most important conclusion of these analyses is that generations born after 1970 will lose out with the reform of the pension system. Finally, in view of the demographic changes and trends Slovenia must design a migration policy that determines the scope of migration and introduces measures for the integration of immigrants. Greater mobility is the constituent part of any population outlook. Migration from poorer to richer regions is taking place within the country and between countries. Migration – yes or no? – is not the right question. The relevant question is how much and what kind of migration to help alleviate the problems caused by the ageing of the population. It is errant to expect that immigration can solve the problems that society faces because of ageing; this can only be done by increasing and extending work activity. Migration will address some structural problems, but if it is not appropriately structured and focused it could also create new problems. It is not until an integration policy is framed and the scope of immigration is determined that immigrants can (meaningfully) contribute to the more balanced development of Slovenia. III. STATISTICAL APPENDIX Editor: Tanja Čelebič Statistical Appendix 11 5 List of Tables Table 1a: Distribution of persons by household size, 1998 in 2002 117 Table 1b: Distribution of persons in income brackets by household size, 1998 and 2002 117 Table 2a: Distribution of persons by age of the head of the household in which they live, 1998 and 2002 118 Table 2b: Distribution of persons in income brackets by age of the head of the household in which they live, 1998 and 2002 118 Table 3a: Distribution of persons by household type, 1998 and 2002 119 Table 3b: Distribution of persons in income brackets by household type, 1998 and 2002 120 Table 4a: Distribution of persons by gender and education of the head of the household in which they live, 1998 and 2002 121 Table 4b: Distribution of persons by gender and education of the head of the household in which they live, 1998 in 2002 121 Table 5a: Distribution of the population by formal (employment) status of the head of the household in which they live, 1998 and 2002 122 Table 5b: Distribution of the population by formal (employment) status of the head of the household in which they live, 1998 and 2002 122 Table 6: Distribution of income sources in income brackets by source of income, 1998 and 2002 123 Table 7: Indicators of the distribution of employees with regard to gross wage amounts in the private sector (from A to K), 1998-2005 124 Table 8: Indicators of the distribution of employees with regard to gross wage amounts in the public sector (from L to O), 1998-2005 124 Table 9: Share of one-off high income in current monetary disposable income of persons by income class, 1998 and 2002 124 Table 10a: Structure of monetary disposable income including one-off high income in income brackets, by source of income, 1998 and 2002 125 Table 10b: Distribution of sources of monetary disposable income including individual high income in income brackets, by source of income, 1998 and 2002 125 Table 11: Social protection expenditure by function as a share of GDP, 1999-2003 126 Table 12: Social protection expenditure per capita in PPS, 1996 and 2002 126 Table 13: Income tax basis per capita by region, index (Slovenia = 100), 1999-2004 126 Table 14: Structure of total (consumable and non-consumable) expenditure by income bracket, 1998 and 2002 127 Table 15: The number of (acute) hospital beds by region, 1995-2004 128 Table 16: The number of inhabitants per acute hospital bed by region, 1995-2004 128 Table 17: Physicians at primary level by region, 2003 in 2004 129 Table 18: Share of children attending kindergartens, by age, 1999-2006 129 Table 19: Participation rate of the population in tertiary education, 1999-2005 129 Table 20: Structure of the population aged 25 or over by education attainment, 2000-2005 130 Table 21: Population aged 25 or over by (highest) level of education attained and by age, 1999-2005, 2nd quarter 130 Table 22: Average number of schooling years attained by the population aged 15 and over by region, 1991 and 2002 census 131 Table 23: Total public expenditure on formal education1 as a share of GDP by level of education, 1995-2003 131 Table 24: Expenditure on education institutions as a share of GDP by level of education, 1995-2003 131 Table 25: Distribution of persons in income brackets by type of tenure status, 1998 and 2002 132 Table 26: Share of households with own housing by available assets, 1999-2003 132 Table 27: Average number of rooms by person by tenure status, 1999-2003 132 Table 28: Internet users by age, 2004 in 2005 133 Table 29: Household access to the Internet, 2004 in 2005 133 Table 30: Gini coeffi cient, Income quintile share ratio (80/20), 1999-2003 133 Table 31: At risk of poverty rate by gender and age, 1999-2003 133 Table 32: At risk of poverty threshold (in SIT, EUR), 1999-2003 134 Table 33: At risk of poverty rate with a breakdown by most common activity status, total and by gender, 1999-2003 134 Table 34: At risk of poverty rate with a breakdown by household type, 1999-2003 134 11 6 Social Overview 2006 Table 35: Persons entitled to fi nancial social assistance in regions, (December) 2001-2005 135 Table 36: Distribution of persons in income brackets by subjective evaluation of one’s household income situation, 1998 and 2002 135 Table 37: The number and the share of the population by selected age groups, 1999-2005 136 Table 38: The number and the age structure of the population, 2005, and the growth index of the total population, 1999-2005, by region 136 Table 39: Population size and projections, 1990-2050 136 Table 40: Mean age of the population and the ageing index, 1999-2005 137 Table 41: Basic data on live births, 1999-2005 137 Table 42: Some basic data on deaths, 1999-2005 137 Table 43: Structure of deaths by age, 1999-2004 137 Table 44: Life expectancy by region (by abridged life tables for 1999-2003) 138 Table 45: Mean age of bride and groom at fi rst marriage and mean age of mother at fi rst birth, 1999-2005 138 Table 46: Average number of live births per woman aged 15 or over by education attainment, 1991 and 2002 Census 138 Table 47: Average time per week spent on job by employees, total and by gender, April 2000-March 2001 139 Table 48: Average time per day spent on housework and child care by people aged 20-74, by gender, April 2000-March 2001 139 Table 49: Average time per day spent on free time activities by people aged 20-74, by gender, April 2000-March 2001 139 Table 50: Unemployment rate by education attainment of the unemployed, 2000-2005 140 Table 51: Employment rate by level of school attainment, total and by gender, 1999-2005 141 Table 52: Participation of the population aged 25-64 in lifelong learning, 2001-2005 142 Table 53: Number of hospitalisations due to diseases by main cause of admission, by gender and for persons aged 65+, 2004 142 Table 54: Diagnostic related groups (DRG), cases of acute care per 1000 inhabitants and average weight by age group, 2004 and 2005 143 Table 55: People in old people’s homes and structure by reason for admission, 2000-2005 144 Table 56: People in old people’s homes by the mode of payment for care, 2000-2005 144 Table 57: Expenditure on pensions (in SIT million) total and by statistical categories, 1999-2003 145 Table 58: GDP and infl ation, 1999-2005 146 Table 59: GDP per capita (in 1000 SIT), by region, 1999-2003 146 Table 60: GDP per capita, index (Slovenia = 100), by region, 1999-2003 146 Table 61: Development Defi ciency Index by region, 2007-2013 147 Table 62: Human Development Index (HDI) and structural indicators, 1999-2003 147 Table 63: Gender-related Development Index (GDI) and structural indicators, 1999-2003 148 Table 64: Gender Empowerment Measure (GEM) and structural indicators, 1999-2003 148 Table 65: Human Development Index (HDI) by region, 2002 and 2003 149 Statistical Appendix 11 7 LIVING CONDITIONS – SITUATION AND TRENDS Table 1a: Distribution of persons by household size, 1998 in 2002 (in %) Number of household members % of persons in income bracket1 Low Lower- middle Upper-middle High Total (all persons) Year 1998 1 12.9 5.1 2.3 2.1 5.3 2 20.0 14.3 14.5 22.4 15.5 3 18.2 17.9 30.7 32.8 22.1 4 19.8 35.4 37.0 31.2 33.5 5 12.9 14.6 11.2 10.2 13.2 6+ 16.4 12.7 4.3 1.2 10.3 Total 100.0 100.0 100.0 100.0 100.0 Year 2002 1 21.5 6.3 3.4 4.4 7.2 2 19.7 15.6 16.5 22.3 16.6 3 14.6 19.1 28.3 36.8 22.0 4 21.3 33.0 38.1 30.7 32.9 5 10.8 15.8 10.0 4.3 13.0 6+ 12.2 10.2 3.8 1.6 8.2 Total 100.0 100.0 100.0 100.0 100.0 Source: SORS, HBS fi les 1998 and 2002; calculations by Stropnik. Note: 1Income brackets: 1. Low – having an equivalent income below the level of 0.6 of the median equivalent income of all persons in Slovenia, i.e. below the at risk of poverty threshold according to the Eurostat’s defi nition. 2. Lower middle – having an equivalent income at a level between 0.6 and less than 1.2 of the median equivalent income. 3. Upper middle – having an equivalent income at the level between 1.2 and 2 times the median equivalent income. 4. High – having an equivalent income in the amount exceeding 2 times the median equivalent incomes. Table 1b: Distribution of persons in income brackets by household size, 1998 and 2002 (in %) Number of household members % of persons in income bracket Low Lower-middle Upper-middle High Total (all persons) Year 1998 1 33.9 52.3 11.7 2.0 100.0 2 17.9 49.6 25.1 7.3 100.0 3 11.4 43.7 37.3 7.5 100.0 4 8.2 57.2 29.8 4.7 100.0 5 13.6 59.7 22.8 3.9 100.0 6+ 22.1 66.2 11.1 0.6 100.0 Total 14.0 54.1 26.9 5.1 100.0 Year 2002 1 35.7 48.1 13.2 3.0 100.0 2 14.1 51.5 27.9 6.5 100.0 3 7.9 47.7 36.3 8.1 100.0 4 7.7 55.2 32.6 4.5 100.0 5 9.9 67.0 21.6 1.6 100.0 6+ 17.7 68.4 13.0 0.9 100.0 Total 11.9 55.0 28.2 4.9 100.0 Source: SORS, HBS fi les 1998 and 2002; calculations by Stropnik. 11 8 Social Overview 2006 Table 2a: Distribution of persons by age of the head of the household in which they live, 1998 and 2002 (in %) Age of head of household (years) % of persons in income bracket Low Lower-middle Upper-middle High Total (all persons) Year 1998 under 29 (incl.) 12.0 14.5 13.4 6.3 13.5 30-39 23.6 31.4 29.3 30.4 29.7 40-49 24.8 26.3 28.0 26.4 26.5 50-59 11.3 12.1 17.0 23.4 13.9 60-69 13.3 9.0 7.3 11.3 9.3 70+ 15.0 6.7 5.0 2.2 7.2 Total 100.0 100.0 100.0 100.0 100.0 Year 2002 under 29 (incl.) 11.8 11.6 12.7 2.5 11.5 30-39 14.5 29.3 28.4 36.3 27.6 40-49 26.2 29.7 26.4 26.8 28.2 50-59 14.2 12.8 19.6 22.9 15.4 60-69 13.0 8.6 7.8 7.0 8.9 70+ 19.8 8.0 5.1 4.4 8.4 Total 100.0 100.0 100.0 100.0 100.0 Source: SORS, HBS fi les 1998 and 2002; calculations by Stropnik. Table 2b: Distribution of persons in income brackets by age of the head of the household in which they live, 1998 and 2002 (in %) Age of head of household (years) % of persons in income bracket Low Lower-middle Upper-middle High Total (all persons) Year 1998 under 29 (incl.) 12.5 58.4 26.8 2.4 100.0 30-39 11.1 57.2 26.5 5.2 100.0 40-49 13.0 53.5 28.4 5.0 100.0 50-59 11.3 47.1 33.0 8.6 100.0 60-69 20.0 52.5 21.4 6.2 100.0 70+ 29.3 50.3 18.7 1.6 100.0 Total 14.0 54.1 26.9 5.1 100.0 Year 2002 under 29 (incl.) 12.2 55.5 31.2 1.1 100.0 30-39 6.3 58.4 29.0 6.4 100.0 40-49 11.1 57.9 26.4 4.6 100.0 50-59 11.0 45.8 35.9 7.2 100.0 60-69 18.2 53.3 24.6 3.8 100.0 70+ 28.0 52.3 17.1 2.6 100.0 Total 11.9 55.0 28.2 4.9 100.0 Source: SORS, HBS fi les 1998 and 2002; calculations by Stropnik. Statistical Appendix 11 9 Table 3a: Distribution of persons by household type, 1998 and 2002 (in %) Household type % of persons in income bracket Low Lower-middle Upper-middle High Total (all persons) Year 1998 One person household, 65 and over 8.0 3.0 1.1 0.4 3.0 One person household, between 30 and 64 years 4.4 1.9 1.2 1.7 2.1 One person household, under 30 years 0.4 0.2 0.1 0.0 0.2 Couple, no children, oldest member 65 and over 6.6 4.6 4.3 5.4 4.9 Couple, no children, oldest member under 65 years 4.9 4.8 6.7 12.3 5.7 One person household, children under 18 years 2.2 1.5 0.6 0.0 1.3 Couple, one child under 18 years 7.3 7.3 12.7 11.8 9.0 Couple, two children under 18 years 10.0 17.8 18.0 14.7 16.6 Couple, three children under 18 years 6.7 4.4 2.6 2.4 4.1 Single parent, at least one child 18 and over 6.3 4.5 3.9 5.0 4.6 Couple, at least one child 18 and over 14.3 23.5 29.7 30.6 24.2 Other households, all members related 28.0 25.4 18.7 13.2 23.3 Other households, at least one member not related 0.8 1.0 0.6 2.6 1.0 Total 100.0 100.0 100.0 100.0 100.0 Year 2002 One person household, 65 and over 13.3 4.1 1.0 0.8 4.2 One person household, between 30 and 64 years 6.4 1.9 2.0 3.5 2.6 One person household, under 30 years 1.7 0.2 0.4 0.0 0.4 Couple, no children, oldest member 65 and over 8.4 5.2 5.8 5.3 5.8 Couple, no children, oldest member under 65 years 4.5 5.0 6.9 11.5 5.8 One person household, children under 18 years 2.5 1.8 0.7 0.0 1.5 Couple, one child under 18 years 4.6 6.8 8.9 16.9 7.6 Couple, two children under 18 years 8.6 16.5 15.8 15.9 15.3 Couple, three children under 18 years 6.6 5.0 1.4 3.6 4.1 Single parent, at least one child 18 and over 5.8 5.0 4.2 3.5 4.8 Couple, at least one child 18 and over 19.6 26.6 35.7 28.8 28.4 Other households, all members related 17.1 20.4 16.7 10.2 18.4 Other households, at least one member not related 1.0 1.5 0.6 0.0 1.1 Total 100.0 100.0 100.0 100.0 100.0 Source: SORS, HBS fi les 1998 and 2002; calculations by Stropnik. 120 Social Overview 2006 Table 3b: Distribution of persons in income brackets by household type, 1998 and 2002 (in %) Household type % of persons in income bracket Low Lower-middle Upper-middle High Total (all persons) Year 1998 One person household, 65 and over 37.0 52.8 9.5 0.7 100.0 One person household, between 30 and 64 years 29.8 50.7 15.3 4.2 100.0 One person household, under 30 years 28.9 62.7 8.4 0.0 100.0 Couple, no children, oldest member 65 and over 19.0 51.4 23.9 5.7 100.0 Couple, no children, oldest member under 65 years 11.9 45.7 31.6 10.9 100.0 One person household, children under 18 years 24.8 63.1 12.1 0.0 100.0 Couple, one child under 18 years 11.4 43.9 38.0 6.7 100.0 Couple, two children under 18 years 8.4 57.9 29.2 4.5 100.0 Couple, three children under 18 years 22.6 57.4 17.0 2.9 100.0 Single parent, at least one child 18 and over 19.0 53.0 22.6 5.5 100.0 Couple, at least one child 18 and over 8.2 52.4 32.9 6.4 100.0 Other households, all members related 16.7 58.9 21.5 2.9 100.0 Other households, at least one member not related 11.9 57.3 17.4 13.4 100.0 Total 14.0 54.1 26.9 5.1 100.0 Year 2002 One person household, 65 and over 38.1 54.1 6.8 1.0 100.0 One person household, between 30 and 64 years 29.9 41.7 21.6 6.7 100.0 One person household, under 30 years 47.8 27.1 25.1 0.0 100.0 Couple, no children, oldest member 65 and over 17.4 50.0 28.1 4.5 100.0 Couple, no children, oldest member under 65 years 9.2 47.6 33.5 9.6 100.0 One person household, children under 18 years 20.2 66.5 13.3 0.0 100.0 Couple, one child under 18 years 7.2 49.0 33.0 10.8 100.0 Couple, two children under 18 years 6.7 59.1 29.1 5.0 100.0 Couple, three children under 18 years 19.0 67.0 9.9 4.2 100.0 Single parent, at least one child 18 and over 14.4 57.4 24.6 3.5 100.0 Couple, at least one child 18 and over 8.2 51.5 35.3 4.9 100.0 Other households, all members related 11.0 60.7 25.5 2.7 100.0 Other households, at least one member not related 10.5 74.3 15.1 0.0 100.0 Total 11.9 55.0 28.2 4.9 100.0 Source: SORS, HBS fi les 1998 and 2002; calculations by Stropnik. Statistical Appendix 121 Table 4a: Distribution of persons by gender and education of the head of the household in which they live, 1998 and 2002 (in %) School attainment of head of household % of persons in income bracket Low Lower-middle Upper-middle High Total (all persons) MWMWMWMWMW Year 1998 Less than primary education 7.8 15.2 2.5 4.1 0.2 0.5 0.5 0.0 2.4 4.9 Primary education 38.9 52.0 22.2 22.4 5.1 6.0 1.8 0.0 18.3 22.3 Vocational education 37.2 19.7 41.1 23.1 22.7 8.4 10.0 0.0 33.6 18.0 Secondary education 13.4 11.7 31.4 44.6 48.9 55.6 25.5 35.6 33.8 41.5 Post-secondary education (not higher education) 0.4 0.0 1.5 3.9 7.3 12.3 12.2 5.3 3.6 5.4 At least a higher education 2.3 1.3 1.3 1.9 15.9 17.2 50.1 59.0 8.3 7.9 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Year 2002 Less than primary education 14.8 20.5 3.5 2.9 1.0 0.5 0.8 0.0 3.9 4.5 Primary education 36.7 47.4 18.5 19.8 4.7 2.3 1.0 0.0 15.5 17.9 Vocational education 31.1 21.1 42.5 23.1 24.4 5.3 2.9 0.0 33.7 17.2 Secondary education 13.1 8.9 29.0 41.8 36.5 35.3 21.5 15.5 28.9 34.8 Post-secondary education (not higher education) 2.9 0.2 3.2 7.1 12.8 23.8 10.1 14.5 6.3 11.0 At least a higher education 1.3 1.9 3.4 5.2 20.6 32.8 63.7 70.0 11.6 14.6 Total 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 100.0 Source: SORS, HBS fi les 1998 and 2002; calculations by Stropnik. Note: M = male head of household, W = female head of household. Table 4b: Distribution of persons by gender and education of the head of the household in which they live, 1998 in 2002 (in %) School attainment of head of household % of persons in income bracket Low Lower-middle Upper-middle High Total (all persons) M W M W M W M W M W Year 1998 Less than primary education 40.4 51.7 56.2 45.7 2.3 2.6 1.1 0.0 100.0 100.0 Primary education 26.1 38.6 65.4 54.7 7.9 6.7 0.6 0.0 100.0 100.0 Vocational education 13.6 18.2 65.7 70.2 19.0 11.6 1.7 0.0 100.0 100.0 Secondary education 4.9 4.7 50.0 58.6 40.9 33.2 4.3 3.5 100.0 100.0 Post-secondary education (not higher education) 1.4 0.0 22.1 39.3 57.2 56.6 19.3 4.1 100.0 100.0 At least a higher education 3.3 2.8 8.4 12.9 54.0 53.7 34.2 30.7 100.0 100.0 Year 2002 Less than primary education 42.5 59.8 48.7 37.0 7.5 3.2 1.2 0.0 100.0 100.0 Primary education 26.5 34.4 64.5 62.1 8.7 3.5 0.4 0.0 100.0 100.0 Vocational education 10.3 15.9 68.2 75.7 20.9 8.4 0.5 0.0 100.0 100.0 Secondary education 5.1 3.3 54.3 67.6 36.4 27.5 4.3 1.6 100.0 100.0 Post-secondary education (not higher education) 5.1 0.3 27.2 36.5 58.5 58.6 9.2 4.6 100.0 100.0 At least a higher education 1.3 1.7 15.7 20.2 51.3 61.2 31.7 16.9 100.0 100.0 Source: SORS, HBS fi les 1998 and 2002; calculations by Stropnik. Note: M = male head of household, W = female head of household. 122 Social Overview 2006 Table 5a: Distribution of the population by formal (employment) status of the head of the household in which they live, 1998 and 2002 (in %) Formal (employment) status of head of household % of persons in income bracket Low Lower-middle Upper-middle High Total (all persons) Year 1998 Employee 38.1 71.7 80.0 79.3 69.6 Self-employed 8.6 5.3 3.6 8.6 5.5 Unpaid family worker 2.1 0.4 0.1 0.0 0.5 Occasional work 0.3 0.1 0.1 0.3 0.2 Unemployed 13.9 1.1 0.6 0.0 2.7 Pensioner 34.5 21.1 15.4 11.8 21.0 Other1 2.5 0.2 0.1 0.0 0.5 Total 100.0 100.0 100.0 100.0 100.0 Year 2002 Employee 32.6 69.7 78.9 81.3 68.4 Self-employed 7.3 6.6 5.0 7.4 6.3 Unpaid family worker 2.0 0.3 0.0 0.0 0.4 Occasional work 0.8 0.3 0.1 0.3 0.3 Unemployed 12.6 1.2 0.5 0.7 2.4 Pensioner 40.5 21.7 15.3 10.3 21.6 Other1 4.1 0.2 0.4 0.0 0.7 Total 100.0 100.0 100.0 100.0 100.0 Source: SORS, HBS fi les 1998 and 2002; calculations by Stropnik. Note: 1The group ‘Other’ includes pupils/students, housewives, persons incapacitated for work, etc. Table 5b: Distribution of the population by formal (employment) status of the head of the household in which they live, 1998 and 2002 (in %) Formal (employment) status of head of household % of persons in income bracket Low Lower-middle Upper-middle High Total (all persons) Year 1998 Employee 7.6 55.7 30.9 5.8 100.0 Self-employed 21.8 52.4 17.8 8.0 100.0 Unpaid family worker 56.6 37.7 5.6 0.0 100.0 Occasional work 27.1 40.6 21.8 10.4 100.0 Unemployed 71.4 22.6 6.0 0.0 100.0 Pensioner 22.9 54.4 19.8 2.8 100.0 Other1 68.8 24.0 7.3 0.0 100.0 Total 14.0 54.1 26.9 5.1 100.0 Year 2002 Employee 5.7 56.0 32.5 5.8 100.0 Self-employed 13.9 58.2 22.3 5.7 100.0 Unpaid family worker 58.0 42.0 0.0 0.0 100.0 Occasional work 33.3 55.4 6.0 5.3 100.0 Unemployed 64.0 28.9 5.7 1.5 100.0 Pensioner 22.4 55.3 19.9 2.3 100.0 Other1 69.7 15.9 14.4 0.0 100.0 Total 11.9 55.0 28.2 4.9 100.0 Source: SORS, HBS fi les 1998 and 2002; calculations by Stropnik. Note: 1The group ‘Other’ includes pupils/students, housewives, persons incapacitated for work, etc. Statistical Appendix 12 3 Table 6: Distribution of income sources in income brackets by source of income, 1998 and 2002 (in %) Source of income Share of the source of income in current monetary disposable income1 by income bracket (in %) Low Lower-middle Upper-middle High Total (all persons) Year 1998 Income from employment2 2.9 41.9 41.4 13.8 100.0 Contracts3 and direct payments 11.1 36.1 27.2 25.5 100.0 Student employment brokerage service 2.9 36.6 51.6 9.0 100.0 Self-employment4 9.1 46.7 27.2 17.0 100.0 Pensions5 9.8 50.8 31.3 8.1 100.0 Unemployment benefi t 25.0 54.7 18.7 1.5 100.0 Other social benefi ts6 21.6 55.2 18.7 4.4 100.0 Child allowance 18.3 61.5 19.3 0.9 100.0 Other family benefi ts7 6.8 49.4 28.5 15.3 100.0 Income from property8 1.2 27.1 35.5 36.2 100.0 Intra-family fi nancial transfers and gifts9 17.6 51.6 28.0 2.8 100.0 Year 2002 Income from employment2 2.2 41.1 43.3 13.3 100.0 Contracts3 and direct payments 9.3 39.7 26.5 24.6 100.0 Student employment brokerage service 3.0 48.3 40.6 8.1 100.0 Self-employment4 5.7 48.9 33.7 11.8 100.0 Pensions5 9.6 50.9 33.4 6.1 100.0 Unemployment benefi t 24.5 54.2 19.1 2.3 100.0 Other social benefi ts6 21.6 53.3 20.2 5.0 100.0 Child allowance 16.6 67.8 13.8 1.9 100.0 Other family benefi ts7 4.1 59.5 20.8 15.6 100.0 Income from property8 3.0 29.3 26.9 40.7 100.0 Intra-family fi nancial transfers and gifts9 8.3 50.8 32.3 8.6 100.0 Source: SORS, HBS fi les 1998 and 2002; calculations by Stropnik. Notes: Here, account should be taken of the distribution of persons in income brackets.1Current monetary disposable income includes income from employment, income from occasional work (against contracts and direct payments, as well as through the student employment brokerage service), income from self-employment, pension, social and family benefi ts, income from property, and intra-family fi nancial transfers and gifts. Current income is reduced by granted transfers (alimony, maintenance allowances, pecuniary gifts and voluntary contributions). The household income thus defi ned does not include one-off high income, the value of own production spent in the household, unpaid rents (for proprietary housing), a reduction in savings or loans taken out. 2Income from employment includes wages (including wages earned abroad), holiday allowance, allowance for meals, allowance for transport to and from work and other cash benefi ts from the employer. 3Contracts include copyright contracts and work contracts. 4Income from self-employment includes income from farming activity, income from other activitiesm wage of an enterpreneur, holiday allowance, allowance for meals and allowance for transport to and from work. 5Pensions also include recreation allowances and pensions from abroad. 6Other social benefi ts include fi nancial social assistance, housing rent subsidy, disability and recognition allowance with bonuses, scholarships etc. 7Other family benefi ts include child allowance, parental leave benefi t, parental allowance, birth grant and child care aloowance. 8Income from property includes net income from renting an apartment, house, garage or other real estate, dividends, interests and income relating to patents, licences and other rights. 9Intrafamily fi nancial transfers include alimony from former spouse and for the child, regular fi nancial assistance, maintenance allowance for elderly people, and pecuniary gifts. 124 Social Overview 2006 Table 7: Indicators of the distribution of employees with regard to gross wage amounts in the private sector (from A to K), 1998-2005 1998 1999 2000 2001 2002 2003 2004 2005 9th decile /1st decile 3.17 3.20 3.22 3.30 3.22 3.32 3.28 3.31 median /1st decile 1.61 1.63 1.61 1.61 1.60 1.63 1.59 1.57 9th decile /median 1.96 1.97 2.00 2.05 2.01 2.04 2.07 2.10 Gini coeffi cient 0.282 0.288 0.293 0.294 0.286 0.289 0.286 0.287 GPI1/Median*100 120.5 121.7 122.6 123.8 123.3 122.9 123.0 124.3 Source: SORS; calculations by IMAD. Notes: In 2002 changes were introduced to health and social work activities, which mostly affected the public sector. 1Gross personal income. Table 8: Indicators of the distribution of employees with regard to gross wage amounts in the public sector (from L to O), 1998-2005 1998 1999 2000 2001 2002 2003 2004 2005 9th decile /1st decile 3.35 3.43 3.46 3.45 3.28 3.24 3.22 3.31 median /1st decile 1.80 1.81 1.85 1.87 1.80 1.81 1.77 1.78 9th decile /median 1.86 1.89 1.86 1.84 1.82 1.79 1.82 1.86 Gini coeffi cient 0.270 0.277 0.273 0.270 0.258 0.256 0.252 0.256 GPI1/Median*100 114.1 114.9 112.8 112.2 112.4 112.1 112.3 113.3 Source: SORS; calculations by IMAD. Notes: In 2002 changes were introduced to the health and social work activities, which mostly affected the public sector. 1Gross personal income. Table 9: Share of one-off high income1 in current monetary disposable income of persons by income class, 1998 and 2002 (in %) Year Share of one-off high income, by income bracket (%) Low Lower-middle Upper-middle High Total (all persons) 1998 2.5 2.7 4.4 5.1 3.6 2002 9.6 4.3 2.9 4.4 4.0 Source: SORS, HBS fi les 1998 and 2002; calculations by Stropnik. Notes: 1One-off high income includes income from the sale of intangible and tangible goods, sale of securities and other capital shares as well as old car value and other receipts (compensation for nationalised or dispossessed property, winnings from gambling, inheritance and legacy, income from life insurance, income from insurance companies for destroyed and damaged property). Statistical Appendix 12 5 Table 10a: Structure of monetary disposable income1 including one-off high income in income brackets, by source of income, 1998 and 2002 (in %) Structure of monetary disposable income by income bracket (%) Low Lower-middle Upper-middle High Total (all persons) Year 1998 Current monetary disposable income 97.5 97.4 95.7 95.2 96.5 Receipts from sale 2.4 2.2 3.7 3.7 3.0 Other receipts 0.1 0.4 0.6 1.1 0.5 Total 100.0 100.0 100.0 100.0 100.0 Year 2002 Current monetary disposable income 91.3 95.9 97.2 95.8 96.1 Receipts from sale 6.7 3.7 2.2 3.5 3.3 Other receipts 2.0 0.4 0.6 0.8 0.6 Total 100.0 100.0 100.0 100.0 100.0 Source: SORS, HBS fi les 1998 and 2002; calculations by Stropnik. Note: 1Disposable monetary income includes current disposable monetary income, receipts from sale, and other receipts. Table 10b: Distribution of sources of monetary disposable income including individual high income in income brackets, by source of income, 1998 and 2002 (in %) Structure of monetary disposable income by income bracket (%) Low Lower-middle Upper-middle High Total (all persons) Year 1998 Current monetary disposable income 6.1 45.1 36.5 12.2 100.0 Receipts from sale 4.8 33.6 45.9 15.7 100.0 Other receipts 1.3 32.2 40.0 26.6 100.0 Year 2002 Current monetary disposable income 5.3 45.2 38.3 11.1 100.0 Receipts from sale 11.5 51.3 25.5 11.7 100.0 Other receipts 19.1 28.4 38.1 14.4 100.0 Source: SORS, HBS fi les 1998 and 2002; calculations by Stropnik. Note: In interpreting the data in the table, account should be taken of the distribution of persons in income brackets; see Table 2 in text. 126 Social Overview 2006 Table 11: Social protection expenditure1 by function as a share of GDP, 1999-2003 (in %) 1999 2000 2001 2002 2003 Social protection expenditure 25.0 25.2 25.5 25.4 24.8 Social benefi ts expenditure2 by function: 24.4 24.6 24.8 24.8 24.3 - Sickness/health care 7.5 7.5 7.8 7.8 7.9 - Disability 2.2 2.2 2.2 2.1 2.0 - Old age 10.5 10.6 10.8 11.1 10.5 - Survivors 0.5 0.5 0.5 0.5 0.4 - Family/Children 2.1 2.3 2.2 2.1 2.1 - Unemployment 1.2 1.0 0.9 0.8 0.8 - Housing3 n.a. n.a. n.a. n.a. n.a. - Social exclusion not classifi ed elsewhere 0.4 0.4 0.4 0.4 0.6 Source: SORS. Notes: 1Social protection by ESSPROS methodology encompasses all intervention from public and private bodies intended to relieve households and individuals of the burden of a defi ned set of risks or needs, provided that there is neither a simultaneous reciprocal nor an individual arrangement involved. The risk or needs, or the functions, are: Sickness/health care, Disability, Old age, Survivors, Family/children, Unemployment, Housing, and Social exclusion not elsewhere classifi ed. Data on social protection expenditure is slightly different from data on social benefi ts in total as the fi rst also covers administrative and manipulative costs of distribution. 2Social benefi ts is the main category of expenditure on social protection schemes. They include transfers in cash or in kind by social protection schemes to household and individuals to relieve them of the burden of a defi ned set of risks or needs. 3No data on housing expenditure is available. Table 12: Social protection expenditure per capita in PPS, 1996 and 2002 1996 Social protection expenditure per capita in PPS1 3,178 Source: SORS. Note: 1PPS ‘Purchasing Power Standard’. Table 13: Income tax basis per capita by region, index (Slovenia = 100), 1999-2004 1999 2000 2001 2002 2003 2004 Slovenia 100.0 100.0 100.0 100.0 100.0 100.0 Osrednjeslovenska 122.9 123.5 122.3 122.3 119.1 121.7 Obalno-kraška 114.8 110.9 111.5 111.4 111.3 109.1 Gorenjska 100.1 101.5 102.2 101.8 103.2 101.7 Goriška 111.6 110.1 110.4 108.8 109.3 108.2 Savinjska 89.5 89.6 90.2 86.8 91.2 90.7 Jugovzhodna Slovenia 92.4 90.8 94.2 95.0 96.0 95.8 Pomurska 74.8 75.2 74.0 80.3 74.6 74.4 Notranjsko-kraška 100.4 101.5 99.8 100.6 101.1 99.7 Podravska 83.7 84.6 84.5 85.5 86.9 86.4 Koroška 87.0 86.1 86.4 85.5 86.9 86.0 Spodnjeposavska 87.9 85.8 86.0 85.6 85.9 85.4 Zasavska 96.2 94.6 92.7 91.5 91.9 89.2 Source: DURS; calculations by IMAD. 2002 4,253 Statistical Appendix 127 Table 14: Structure of total (consumable and non-consumable) expenditure by income bracket, 1998 and 2002 (in %) Type of expenditure Share of individual types of expenditure (%) Low Lower-middle Upper-middle High Total (all persons) Year 1998 Food 24.2 19.5 16.2 11.8 18.0 Non-alcoholic beverages 3.1 2.5 2.0 1.5 2.3 Alcoholic beverages and tobacco 3.0 2.2 1.9 1.4 2.1 Clothing and footwear 7.0 8.2 8.9 8.6 8.4 Housing and utilities 12.4 10.4 8.4 6.3 9.5 Furnishing, household equipment and routine maintenance 6.5 6.8 6.4 6.8 6.6 Health 1.5 1.6 1.6 1.8 1.6 Transport 11.1 15.3 19.0 17.2 16.4 Communications 2.6 2.2 1.8 1.7 2.0 Recreation and culture 7.2 7.9 9.4 10.3 8.6 Education 0.4 0.6 0.8 1.0 0.7 Hotels, cafes and restaurants 4.0 5.6 6.4 5.8 5.7 Miscellaneous goods and services 9.8 9.5 9.1 8.0 9.2 Total consumption expenditure 92.8 92.2 91.9 82.1 91.0 Non-consumer expenditure on apartments /houses1 4.6 5.5 5.8 14.5 6.5 Other non-consumer expenditure2 2.6 2.3 2.3 3.4 2.5 Total expenditure 100.0 100.0 100.0 100.0 100.0 Year 2002 Food 21.9 16.9 14.0 10.4 15.6 Non-alcoholic beverages 2.3 1.9 1.6 1.1 1.7 Alcoholic beverages and tobacco 2.2 2.1 1.7 1.5 1.9 Clothing and footwear 6.3 7.5 8.5 9.3 7.9 Housing and utilities 13.5 11.5 9.2 7.3 10.4 Furnishing, household equipment and routine maintenance 6.1 6.0 6.4 7.8 6.3 Health 1.7 1.6 1.6 2.0 1.7 Transport 11.6 13.3 15.7 14.8 14.2 Communications 4.5 4.1 3.7 3.3 3.9 Recreation and culture 7.8 8.6 10.4 12.2 9.5 Education 0.7 0.8 1.0 0.9 0.9 Hotels, cafes and restaurants 4.6 5.0 5.9 6.3 5.4 Miscellaneous goods and services 10.3 10.4 9.6 8.6 9.9 Total consumption expenditure 93.4 89.8 89.4 85.6 89.5 Non-consumer expenditure on apartments /houses1 4.4 7.5 7.1 9.2 7.3 Other non-consumer expenditure2 2.2 2.7 3.5 5.1 3.2 Total expenditure 100.0 100.0 100.0 100.0 100.0 Source: SORS, HBS fi les 1998 and 2002; calculations by Stropnik. Notes: 1Non-consumer expenditure on apartments/houses covers expenditure on large construction works and renovations, and the purchase of apartments/houses or building land for a house. 2Other non-consumer expenditure covers expenditure on life insurance, voluntary retirement and health insurance, fi nes, compensation for damage, taxes and self-imposed contributions, savings and transfers such as alimonies, maintenance allowances, fi nancial gifts and voluntary contributions. 128 Social Overview 2006 Table 15: The number of (acute)1 hospital beds by region, 1995-2004 1995 2000 2001 2002 2003 2004 Slovenia 9,457 8,868 8,438 8,268 8,007 7,689 Osrednjeslovenska 3,137 3,031 2,808 2,810 2,753 2,717 Obalno-kraška 692 632 602 572 563 522 Gorenjska 690 614 614 586 580 592 Goriška 438 446 446 446 446 446 Savinjska 988 986 976 943 913 832 Jugovzhodna Slovenija 518 454 450 430 364 343 Pomurska 512 480 372 372 400 279 Notranjsko-kraška 54 54 54 54 54 54 Podravska 1,726 1,542 1,535 1,486 1,379 1,353 Koroška 369 344 323 323 308 308 Spodnjeposavska 173 127 127 127 127 127 Zasavska 160 158 131 119 120 116 Source: Training Institutions Report (No. 3-21-60), IVZ. Note: 1Acute hospital bed (based on WHO defi nitions) is a regularly maintained and cared for hospital bed for the accommodation and 24hour treatment and care of inpatients, located in a hospital ward or other part of the hospital where inpatients are provided with continuous medical care. Acute hospital beds do not include hospital beds intended for long-term psychiatric treatment, patients with tuberculosis, elderly persons and other patients with long-term medical treatment. Nor do they include: hospital beds for new-borns without diseases or disorders, day beds, provisional and makeshift beds and beds for special purposes, such as dialysis, special beds in obstetrics, and beds belonging to specifi c medical devices. Table 16: The number of inhabitants per acute hospital bed by region, 1995-2004 1995 2000 2001 2002 2003 20041 Slovenia 210 224 236 241 249 260 Osrednjeslovenska 155 162 175 175 179 182 Obalno-kraška 149 164 173 183 187 201 Gorenjska 282 320 321 337 341 335 Goriška 276 269 270 269 269 268 Savinjska 259 260 263 273 282 309 Jugovzhodna Slovenija 265 304 307 322 382 405 Pomurska 248 260 334 333 308 440 Notranjsko-kraška 940 936 939 941 942 943 Podravska 186 207 208 215 232 236 Koroška 201 215 229 229 240 240 Spodnjeposavska 412 550 550 552 553 552 Zasavska 295 293 353 387 382 394 Source: Training Institutions Report (No. 3-21-60), IVZ; calculations by IMAD. Note: 1Including the Diagnostic Centre Bled and MV Medicor. Statistical Appendix 12 9 Table 17: Physicians at primary level by region, 2003 in 2004 Physicians in primary health care network1 Number Number per 1000 inhabitants Index Slo= 100 Growth index 2003 2004 2003 2004 2003 2004 2003-2004 Slovenia 1,533 1,511 0.77 0.76 100.0 100.0 98.6 Osrednjeslovenska 464 462 0.94 0.93 122.3 123.2 99.3 Obalno-kraška 90 90 0.86 0.86 111.6 113.3 100.1 Gorenjska 146 140 0.74 0.71 96.1 93.3 95.7 Goriška 105 102 0.88 0.85 114.2 112.8 97.3 Savinjska 185 181 0.72 0.70 93.6 93.0 98.0 Jugovzhodna Slovenija 102 105 0.73 0.76 95.7 99.9 103.0 Pomurska 94 88 0.76 0.72 99.3 94.6 94.0 Notranjsko-kraška 36 35 0.71 0.69 92.2 90.8 97.1 Podravska 177 177 0.55 0.55 72.2 73.3 100.1 Koroška 43 42 0.58 0.57 75.8 75.2 97.7 Spodnjeposavska 50 49 0.71 0.70 92.7 92.4 98.2 Zasavska 41 40 0.89 0.88 116.4 115.8 98.0 Source: Training Institutions Report (No. 3-21-60), IVZ; calculations by IMAD. Note: 1Health care centres and private providers. Table 18: Share of children1 attending kindergartens, by age, 1999-2006 (in %) 1999/2000 2000/2001 2001/2002 2002/2003 2003/2004 2004/2005 2005/2006 Under 3 years 17.6 19.3 20.0 22.1 24.7 24.9 25.6 3-5 years 64.0 66.9 69.8 71.2 76.42 75.4 77.8 Source: SORS; calculations by IMAD. Notes: 1Calculations for 2003/2004 refer to children attending kindergartens aged from 1 year or less to 5 years or over and the population from 0 years to 5 years as on 30 June. For other years calculations are based on children attending kindergartens from 1 year or less to 5 years and the population from 0 years to 5 years as on 30 June. 2Calculations for 2003/2004 concerning children in kindergartens aged 3 to 5 years include children attending kindergartens aged from 3 to 5 years or over and the population from 3 years to 5 years as on 30 June. Table 19: Participation rate of the population in tertiary education1, 1999-2005 (in %) 1999 2000 2001 2002 2003 2004 2005 Full-time students2 as share of the population aged 19-23 years 36.5 39.1 41.9 43.2 46.1 49.73 52.33 Tertiary education students as share of the population aged 20-29 years 28.6 30.9 33.1 33.8 34.9 37.9 38.9 Source: SORS; calculations by IMAD. Notes: 1Tertiary education includes post-secondary vocational education, higher undergraduate studies and higher post-graduate studies. 2Includes full-time students, full-time graduation candidates and full-time post-graduate students. 3IMAD’s estimate based on available data published by SORS. 130 Social Overview 2006 Table 20: Structure of the population aged 25 or over by education attainment, 2000-2005 (in %) 2000 2001 2002 2003 2004 2005 Total (in 1000) 1,378 1,392 1,403 1,415 1,431 1,447 Structure of the population aged 25 or over by education attainment (in %): Without education, incomplete primary education (1-3 years) 1.2 0.8 0.7 0.6 0.7 0.8 Incomplete primary education (4-7 years) 5.5 5.3 5.2 5.6 5.3 4.9 Primary education 24.4 24.4 23.3 22.3 21.0 20.7 Lower or middle vocational education 26.4 26.9 27.1 27.3 27.0 26.8 Secondary technical education 22.9 23.7 24.4 24.0 24.9 24.8 Secondary general education 5.2 4.3 4.1 4.2 4.1 3.9 Post-secondary education (not higher education) 6.7 6.2 6.1 6.0 5.9 6.1 Higher education, professionally oriented 1.9 1.9 1.9 1.9 2.4 2.7 Higher education, academic type 5.1 5.7 6.4 6.9 7.5 8.0 Post-graduate education (specialisation, master’s and doctor’s degree) 0.8 0.8 0.8 0.9 1.0 1.3 Source: SORS. Table 21: Population aged 25 or over by (highest) level of education attained and by age, 1999-2005, 2nd quarter (in %) 1999 2000 2001 2002 2003 2004 2005 Share of the population with tertiary education by selected age group (in %) 25-34 17.3 19.2 16.4 18.6 24.0 24.2 24.6 35-44 16.7 15.2 14.4 14.9 17.7 17.6 21.2 45-54 14.5 14.8 12.6 12.2 15.1 16.9 17.3 55-64 11.3 12.2 11.2 n.a. n.a. n.a. n.a. 25-64 15.4 15.7 13.8 14.5 17.8 18.8 20.0 65-74 7.7 9.8 9.0 8.4 8.9 11.9 13.8 75-84 6.3 6.6 4.7 5.6 8.3 7.1 6.8 Share of the population with secondary education1 by selected age group (in %) 25-34 67.1 66.0 65.4 64.9 64.9 65.7 66.6 35-44 60.5 62.8 63.4 64.1 64.2 65.2 62.9 45-54 56.0 56.0 57.1 59.2 58.5 54.8 57.6 55-64 47.4 48.4 52.1 n.a. n.a. n.a. n.a. 25-64 58.6 59.1 59.9 60.8 60.7 60.5 60.5 65-74 36.5 37.2 39.0 41.9 41.1 41.6 40.0 75-84 29.1 30.3 29.4 28.1 32.3 36.4 33.0 Source: Eurostat; calculations by IMAD. Notes: The indicator is calculated on the basis of the Labour Force Survey. Data refer to the 2nd quarter. 1Population with secondary education: persons who have completed secondary education programmes. Statistical Appendix 131 Table 22: Average number of schooling years attained by the population aged 15 and over by region, 1991 and 2002 census 1991 2002 Slovenia 9.6 10.6 Osrednjeslovenska1 10.3 11.3 Obalno-kraška 9.7 10.7 Gorenjska 9.4 10.7 Goriška 9.4 10.4 Savinjska 9.0 10.4 Jugovzhodna Slovenija1 9.1 10.1 Pomurska 9.2 10.0 Notranjsko-kraška 9.6 10.3 Podravska 9.3 10.6 Koroška 9.0 10.3 Spodnjeposavska 9.3 10.2 Zasavska 9.6 10.3 Source: SORS; calculations by IMAD. Note: 1Data for 1991 refer to the planned regions of Osrednjeslovenska and Dolenjska. Table 23: Total public expenditure on formal education1 as a share of GDP by level of education, 1995-2003 (in %) 1995 1996 1997 1998 1999 2000 2001 2002 2003 Total 5.87 5.85 5.98 5.93 5.89 5.95 6.08 5.98 6.02 Pre-school education 0.56 0.51 0.46 0.48 0.47 0.48 0.58 0.59 0.56 Primary education 2.42 2.49 2.61 2.62 2.52 2.58 2.49 2.60 2.66 Secondary education 1.54 1.61 1.69 1.63 1.59 1.58 1.67 1.47 1.46 Tertiary education 1.34 1.24 1.22 1.20 1.31 1.31 1.32 1.32 1.34 Source: SORS. Note: 1Total public expenditure on formal education (by UOE methodology – Unesco, OECD, Eurostat) comprises the total budget expenditure on the formal education of youth and adults at the national and municipal levels. Table 24: Expenditure on education institutions1 as a share of GDP by level of education, 1995-2003 (in %) 1995 1996 1997 1998 1999 2000 2001 2002 2003 Total 6.16 6.15 6.02 6.01 5.92 6.05 6.18 6.26 6.31 Pre-school education 0.78 0.67 0.61 0.63 0.61 0.64 0.74 0.73 0.68 Primary education 2.72 2.80 2.85 2.84 2.72 2.78 2.77 2.88 2.94 Secondary education 1.31 1.40 1.37 1.35 1.30 1.30 1.38 1.35 1.35 Tertiary education 1.35 1.27 1.19 1.18 1.28 1.33 1.30 1.29 1.33 Source: SORS; calculations by IMAD. Note: 1Expenditure on education institutions (by UOE methodology) includes all public and private expenditure on instructional and non-instructional institutions offering formal education. 132 Social Overview 2006 Table 25: Distribution of persons in income brackets by type of tenure status, 1998 and 2002 (in %) Type of tenure status % of persons by income bracket Low Lower-middle Upper-middle High Total (all persons) Year 1998 Owner/co-owner of a dwelling 13.1 54.2 27.2 5.4 100.0 User of a dwelling of parents or other relatives 14.4 52.2 29.7 3.6 100.0 Tenant in a profi table dwelling 14.9 68.5 11.6 5.0 100.0 Tenant (employee) in a company-owned dwelling 13.1 42.9 39.8 4.3 100.0 Tenant in a non-profi t dwelling 23.7 56.1 18.7 1.5 100.0 Tenant in a social dwelling 63.7 36.3 0.0 0.0 100.0 Total 14.0 54.1 26.9 5.1 100.0 Year 2002 Owner/co-owner of a dwelling 11.3 54.3 29.5 4.8 100.0 User of a dwelling of parents or other relatives 13.5 55.9 24.8 5.7 100.0 Tenant in a profi table dwelling 14.0 72.6 9.0 4.5 100.0 Tenant (employee) in a company-owned dwelling 12.7 71.2 16.1 0.0 100.0 Tenant in a non-profi t dwelling 15.6 60.1 18.3 6.0 100.0 Tenant in a social dwelling 46.4 48.0 5.5 0.0 100.0 Total 11.9 55.0 28.2 4.9 100.0 Source: SORS, HBS fi les 1998 and 2002; calculations by Stropnik. Table 26: Share of households with own housing by available assets, 1999-2003 (in %) 1999 2000 2001 2002 2003 Total households 93.0 92.7 93.2 93.3 93.4 Share of households with own housing: - Households with income of less than 60% compared to median actual current income 90.1 89.5 90.7 89.3 88.6 - Households with income between 60% and 100% compared to median actual current income 91.1 91.0 91.1 91.3 92.0 - Households with income between 100% and 140% compared to median actual current income 94.2 94.0 94.7 95.3 95.2 - Households with income higher than 140% compared to median actual current income 96.2 96.0 96.3 97.0 97.5 Source: SORS, Household Budget Survey. Table 27: Average number of rooms by person by tenure status, 1999-2003 1999 2000 2001 2002 2003 Total 1.5 1.5 1.5 1.5 1.5 Owners 1.5 1.6 1.5 1.5 1.6 Tenants 1.0 1.1 1.1 1.1 1.1 Source: SORS, Household Budget Survey. Statistical Appendix 133 Table 28: Internet users1 by age, 2004 in 2005 (in %) 2004 2005 16-74 years 37 47 16-34 years 62 77 35-54 years 33 45 55-74 years ((8)) (11) Source: SORS. Notes: Data refer to the 1st quarter of the year. ( ) less accurate estimate, (( )) inaccurate estimate. 1Internet users are persons who have used the Internet within the last three months. Table 29: Household access to the Internet1, 2004 in 2005 (in %) 2004 2005 Total 47 48 Households without children 40 41 Households with children 62 64 Source: SORS. Note: Data refer to the 1st quarter of the year. 1Share of households with Internet access. Table 30: Gini coeffi cient1 (in %), Income quintile share ratio (80/20)2, 1999-2003 1998 1999 2000 2001 2002 2003 Gini coeffi cient (%) 22.3 22.5 22.3 22.0 21.9 22.1 The income quintile share ratio (80/20)2 3.2 3.2 3.2 3.1 3.1 3.1 Source: SORS, Household Budget Survey; Eurostat, New Cronos Database. Notes: The Gini coeffi cient and the income quintile share ratio (80/20) are calculated for income including income in kind. Survey data for three consecutive years are combined and calculated for the medium year used as the reference year. 1The Gini coeffi cient is the measure of income concentration. The higher it is, the greater the income inequality. 2The income quintile share ratio (80/20) is the ratio between the average equivalent household income of the top quintile (20% of the population with the highest income) and the average equivalent household income of the lowest quintile (20% of the population with the lowest income). Table 31: At risk of poverty rate1 by gender and age, 1999-2003 (in %) 1998 1999 2000 2001 2002 2003 Total 11.8 11.6 11.3 10.6 9.9 10.0 - Men 10.9 10.8 10.5 9.6 8.5 8.6 - Women 12.7 12.4 12.0 11.6 11.2 11.4 0-64 years 10.6 10.1 9.7 9.1 8.3 8.6 - Men 10.7 10.4 10.1 9.2 8.3 8.3 - Women 10.5 9.8 9.3 9.1 8.4 8.9 65+ 20.1 21.4 21.2 19.5 19.2 18.5 - Men 12.7 14.9 14.0 12.9 10.8 11.1 - Women 24.3 25.2 25.4 23.5 24.1 22.9 Source: SORS, Household Budget Survey. Notes: Survey data for three consecutive years are combined and calculated for the medium year used as the reference year. 1The at risk of poverty rate is the percentage of persons living in households where the equivalised net household income is below the at risk of poverty threshold. The at risk of poverty rate is calculated for income including income in kind. Income including income in kind means that income in cash is supplemented by income in kind, i.e. one’s own production and other non-monetary forms of income. The calculations are based on yearly income. 134 Social Overview 2006 Table 32: At risk of poverty threshold1 (in SIT, EUR), 1999-2003 1998 1999 2000 2001 2002 2003 In SIT/month 59,840 63,113 71,414 79,180 86,291 92,407 In EUR/month 322 425 346 363 382 395 Source: SORS; Eurostat. Notes: The at risk of poverty threshold is calculated for income including income in kind. 1The at risk of poverty threshold is defi ned as 60% of the median equivalised net income of all households using the OECD modifi ed equivalence scale. The equivalised net income of a household is obtained by dividing the household income by the number of its members. The number of equivalent members is calculated using the OECD modifi ed equivalence scale: the fi rst adult in the household has a weight of 1, every other adult person has a weight of 0.5, and every child under 14 a weight of 0.3. The sum of all weights of the members of a household is the number of equivalent members. The OECD modifi ed equivalence scale is used by the SORS and the Eurostat. Table 33: At risk of poverty rate with a breakdown by most common activity status1, total and by gender, 1999-2003 (in %) 1998 1999 2000 2001 2002 2003 Persons in employment 6.1 5.8 5.2 4.8 3.7 3.6 - Men 5.8 5.8 5.6 5.4 4.1 3.8 - Women 6.5 5.7 4.8 4.1 3.3 3.3 Unemployed 36.9 37.6 42.1 40.8 38.4 38.4 - Men 40.0 38.7 41.6 36.9 39.3 38.8 - Women 33.0 36.3 42.8 45.8 37.5 38.1 Pensioners 14.3 14.7 15.0 14.5 15.3 14.4 - Men 11.3 12.4 12.3 11.7 12.1 11.3 - Women 16.3 16.2 16.9 16.4 17.4 16.4 Source: SORS, Household Budget Survey. Note: The at risk of poverty rate is calculated for income including income in kind. Survey data for three consecutive years are combined and calculated for the medium year used as the reference year. 1The at risk of poverty rate, broken down by most common activity status, is based on the current activity status and calculated for persons aged 16 years or over. Table 34: At risk of poverty rate with a breakdown by household type, 1999-2003 (in %) 1998 1999 2000 2001 2002 2003 Households without dependent children 15.0 15.5 14.8 13.6 13.8 13.1 Households with dependent children1 10.1 9.5 9.2 8.7 7.5 8.1 Single parent - household, one or more dependent children 20.3 22.5 21.1 19.8 17.2 24.5 Source: SORS, Household Budget Survey. Notes: The at risk of poverty rate by household type is calculated for income including income in kind. Survey data for three consecutive years are combined and calculated for the medium year used as the reference year. 1Households without dependent children include one-person households with a high at risk of poverty rate. Therefore, the at risk of poverty rate in households without dependent children is higher than in households with dependent children. Statistical Appendix 135 Table 35: Persons entitled to1 fi nancial social assistance2 in regions, (December) 2001-2005 (in %) Share of the population entitled to fi nancial social assistance in the regions (%) Eligible persons per 1000 inhabitants Index, Sl=100 Growth index 2001 2002 2003 2004 2005 2005 2001-2005 Slovenia 2.1 3.5 4.4 4.7 4.7 100.0 220.8 Osrednjeslovenska 1.0 1.6 2.2 2.5 2.6 55.4 263.3 Obalno-kraška 1.3 2.1 2.7 3.0 3.0 63.0 228.5 Gorenjska 1.3 2.0 2.4 2.6 2.6 54.5 192.8 Goriška 0.5 1.1 1.5 1.9 1.9 41.2 369.2 Savinjska 32 5.2 6.2 6.6 6.5 138.9 201.3 Jugovzhodna Slovenija 1.8 3.3 4.0 4.4 4.6 98.8 258.9 Pomurska 4.5 8.0 8.8 9.1 8.8 187.2 193.5 Notranjsko-kraška 1.3 1.9 2.9 2.8 2.7 57.1 200.3 Podravska 3.4 5.7 6.9 7.4 7.6 163.1 227.6 Koroška 2.2 3.4 4.4 4.9 4.6 99.0 209.1 Spodnjeposavska 2.9 5.3 6.5 6.5 6.1 129.4 212.1 Zasavska 3.0 5.5 6.4 6.5 6.5 138.0 215.3 Source: Ministry of Labour, Family and Social Affairs; calculations by IMAD. Notes: 1Persons entitled to fi nancial social assistance are persons who received fi nancial social assistance because they were not able to provide for themselves or their family members funds equal to the minimum income for reasons over which they have had no infl uence. 2Financial social assistance is a cash benefi t intended to satisfy the minimum living needs in the amount that enables survival in accordance with the Social Security Act. The table presents data on the persons entitled to the basic fi nancial social assistance, extraordinary cash social assistance and permanent cash social assistance as well as the persons entitled to attendance allowance (home care). PERCEPTIONS OF LIVING CONDITIONS Table 36: Distribution of persons in income brackets by subjective evaluation of one’s household income situation, 1998 and 2002 (in %) The household manages on its income... % of persons in income bracket Low Lower-middle Upper-middle High Total (all persons) Year 1998 with great diffi culty 41.2 53.3 5.5 0.0 100.0 with diffi culty 21.2 65.3 12.9 0.5 100.0 with some diffi culty 7.6 59.7 30.3 2.3 100.0 fairly easily 4.2 33.6 48.5 13.7 100.0 easily 0.5 21.6 51.9 26.0 100.0 very easily 0.0 0.0 32.7 67.3 100.0 total 14.0 54.1 26.9 5.1 100.0 Year 2002 with great diffi culty 45.7 49.0 5.3 0.0 100.0 with diffi culty 19.5 69.9 10.6 0.0 100.0 with some diffi culty 6.0 61.1 30.3 2.7 100.0 fairly easily 2.2 36.6 51.9 9.3 100.0 easily 3.3 21.9 47.5 27.2 100.0 very easily 0.0 11.9 43.9 44.2 100.0 total 11.9 55.0 28.2 4.9 100.0 Source: SORS, HBS fi les 1998 and 2002; calculations by Stropnik. 136 Social Overview 2006 THE DEMOGRAPHIC DEVELOPMENT Table 37: The number and the share of the population by selected age groups, 1999-2005 1999 2000 2001 2002 2003 2004 2005 Population (on 30 June) 1,985,557 1,990,272 1,992,035 1,995,718 1,996,773 1,997,004 2,001,114 Shares as on 30 June (in %): 0 years 0.89 0.90 0.90 0.88 0.87 0.88 0.90 0-14 years 16.4 15.9 15.6 15.2 14.8 14.5 14.2 15-64 years 69.9 70.1 70.1 70.2 70.4 70.4 70.3 65+ 13.7 14.0 14.3 14.6 14.9 15.2 15.5 80+ 2.2 2.3 2.4 2.6 2.8 2.9 3.1 Source: SORS, Ministry of the Interior – Central Population Register, Internal Administrative Affairs Directorate. Table 38: The number and the age structure of the population, 2005, and the growth index of the total population, 1999-2005, by region Population, 2005 Share of the population aged 0-14 (in %), 2005 Share of the population aged 15-641 (in %), 2005 Share of the population aged 65 or over (in %), 2005 Growth index of the total population, 1999-2005 Slovenia 2,001,114 14.2 70.3 15.5 100.8 Osrednjeslovenska 498,378 14.6 70.1 15.4 102.6 Obalno-kraška 105,313 12.1 71.1 16.8 102.0 Gorenjska 198,713 15.3 69.4 15.3 101.2 Goriška 119,541 13.7 69.1 17.2 99.6 Savinjska 257,525 14.6 71.0 14.3 100.4 Jugovzhodna Slovenija 139,434 15.6 69.5 14.9 101.1 Pomurska 122,483 13.7 70.9 15.4 98.0 Notranjsko-kraška 51,132 14.0 69.4 16.6 100.3 Podravska 319,282 13.4 70.9 15.7 99.9 Koroška 73,905 14.5 71.4 14.1 99.9 Spodnjeposavska 69,940 14.3 69.5 16.2 99.8 Zasavska 45,468 12.9 71.0 16.0 97.7 Source: SORS, Ministry of the Interior – Central Population Register; calculations by IMAD. Notes: as of 30 June. 1People aged 15-64 are considered to be the ‘working age’ population. Table 39: Population size and projections1, 1990-2050 1990 2000 2010 2020 2030 2040 2050 Population 1,999,945 1,990,272 2,014,802 2,016,690 2,005,997 1,965,321 1,900,849 Source: Eurostat. Notes: Eurostat prepared population projections for Slovenia for 2004-2050. 1The term ‘population projection’ refers to the calculation of the future size and characteristics of the population based on hypotheses about the future developments in fertility, mortality and migration. Statistical Appendix 137 Table 40: Mean age of the population1 and the ageing index2, 1999-2005 1999 2000 2001 2002 2003 2004 2005 The average age (in years) 38.5 38.8 39.1 39.5 39.8 40.1 40.4 Ageing index 83.7 87.8 91.9 96.4 100.8 104.9 108.7 Source: SORS, Ministry of the Interior – Central Population Register. Notes: 1The average age of the population is the weighted arithmetic mean of age of a certain population group. 2The ageing index is the ratio of old population (aged 65 and over) to young population (aged 0-14). Table 41: Basic data on live births, 1999-2005 1999 2000 2001 2002 2003 2004 2005 Live births 17,533 18,180 17,477 17,501 17,321 17,961 18,157 Live births per 1000 inhabitants 8.8 9.1 8.8 8.8 8.7 9.0 9.1 Total fertility rate1 1.21 1.26 1.21 1.21 1.20 1.25 1.26 Net reproduction rate2 0.58 0.60 0.58 0.58 0.57 0.61 0.60 Extra-marital live births 6,203 6,746 6,881 7,037 7,354 8,053 8,475 Share of extra-marital live births (%) 35.4 37.1 39.4 40.2 42.5 44.8 46.7 Source: SORS, Ministry of the Interior - Central Population Register. Notes: 1The total fertility rate is the average number of children per one woman in reproductive age (15-49 years) in the calendar year. It is obtained by adding all values of age-specifi c general fertility rates in the calendar year. 2The net reproduction rate for a given year of observation is the average number of live-born girls which a generation of women in their reproductive age (15-49 years) would give birth to if their age-specifi c fertility and mortality rates remained equal to those in the observed year. Table 42: Some basic data on deaths, 1999-2005 1999 2000 2001 2002 2003 2004 2005 Deaths 18,885 18,588 18,508 18,701 19,451 18,523 18,825 Deaths per 1000 population 9.5 9.3 9.3 9.4 9.7 9.3 9.4 Average age at death (in years) (total) 71.5 71.8 71.7 72.3 72.5 72.5 73.3 - men 67.3 67.2 67.3 67.9 68.2 68.3 68.9 - women 75.3 75.6 76.6 77.0 77.2 76.9 77.8 Source: SORS, Ministry of the Interior – Central Population Register, Institute of Public Health. Table 43: Structure of deaths by age, 1999-2004 (in %) 1999 2000 2001 2002 2003 2004 2005 Total 0-14 years 0.7 0.7 0.6 0.6 0.6 0.6 0.6 15-64 years 26.6 26.0 26.5 25.4 24.6 24.7 22.9 65+ 72.7 73.3 72.9 74.0 74.8 74.7 76.5 Men 0-14 years 0.9 0.8 0.7 0.8 0.6 0.6 0.7 15-64 years 36.4 35.5 36.2 35.0 34.2 33.7 32.1 65+ 62.7 63.7 63.0 64.2 65.2 65.6 67.2 Women 0-14 years 0.6 0.6 0.5 0.5 0.5 0.6 0.6 15-64 years 16.3 16.0 15.8 15.0 14.3 15.3 13.7 65+ 83.2 83.4 83.7 84.6 85.2 84.1 85.7 Source: SORS, Ministry of the Interior – Central Population Register, Institute of Public Health. 138 Social Overview 2006 Table 44: Life expectancy1 by region (by abridged life tables2 for 1999-2003) Total Men Women Slovenia 76.2 72.2 80.0 Osrednjeslovenska 77.8 74.0 81.3 Obalno-kraška 77.1 73.4 80.8 Gorenjska 77.3 73.5 80.9 Goriška 77.6 73.6 81.4 Savinjska 75.2 71.4 79.0 Jugovzhodna Slovenija 75.2 70.8 79.7 Pomurska 73.8 69.2 78.5 Notranjsko-kraška 77.1 73.4 80.8 Podravska 75.3 71.2 79.2 Koroška 75.2 71.4 79.0 Spodnjeposavska 74.5 70.6 78.5 Zasavska 74.5 70.6 78.5 Source: SORS. Notes: Due to the smallness of statistical regions, the Notranjsko-kraška region is joined with Obalno-kraška, Koroška with Savinjska, while Zasavska and Spodnjeposavska are combined. The two joined or combined regions each have the same value. 1Life expectancy is the ratio between the sum of additional number of years expected to be lived beyond age x and the number of persons aged x years. 2A life table is a tabular presentation of the intensity of dying and its distribution by age. The calculated values are comparable in time and space. Abridged tables are calculated for fi ve-year age groups. THE FAMILY AND ITS NEW FORMS Table 45: Mean age of bride and groom at fi rst marriage and mean age of mother at fi rst birth, 1999-2005 (in years) 1999 2000 2001 2002 2003 2004 2005 Mean age of bride at fi rst marriage 26.0 26.6 27.0 27.4 27.2 27.8 28.2 Mean age of groom at fi rst marriage 29.1 29.4 29.6 30.1 30.1 30.3 30.6 Mean age of mother at fi rst birth 26.2 26.5 26.7 27.2 27.3 27.5 27.8 Source: SORS, Ministry of the Interior – Central Population Register. Table 46: Average number of live births per woman aged 15 or over by education attainment, 1991 and 2002 Census Education 1991 2002 Total 1.65 1.55 Without education, incomplete primary education 2.32 2.34 Primary education 1.70 1.72 Total secondary education 1.36 1.37 - secondary vocational education 1.53 1.61 - secondary technical and general education 1.24 1.19 Post-secondary (not higher education) and higher education n.a. 1.31 Post-secondary education (not higher education) 1.32 1.54 Higher education 1.22 n.a. Higher professional and university education n.a. 1.13 Specialisation, master’s and doctor’ degree. n.a. 1.30 Source: SORS, Censuses. Statistical Appendix 139 Table 47: Average time per week spent on job by employees, total and by gender (in hours and minutes), April 2000-March 2001 Total Men Women Total 32’42” 36’0” 29’3” Source: Eurostat, HETUS Pocketbook: Harmonised European Time Use Survey, 2005. Note: the source of data for measuring the indicator is the Time Use Survey carried out with interruptions from 1 April 2000 to 31 March 2001. Table 48: Average time per day spent on housework and child care by people aged 20-74 (in hours and minutes), by gender, April 2000-March 2001 Men Women Total 2:39 4:57 Food preparation 0:17 1:25 Dish washing 0:04 0:28 Cleaning and upkeep 0:32 0:56 Laundry, ironing and handicrafts 0:01 0:32 Gardening 0:32 0:25 Construction and repairs 0:24 0:02 Shopping and services 0:16 0:21 Childcare 0:12 0:29 Other domestic work 0:23 0:16 Source: Eurostat, How Europeans spend their time – Every day life of women and men – Data 1998-2002, 2004. Note: the source of data for measuring the indicator is the Time Use Survey carried out with interruptions from 1 April 2000 to 31 March 2001. Table 49: Average time per day spent on free time activities by people aged 20-74 (in hours and minutes), by gender, April 2000-March 2001 Men Women Total 5:32 4:27 TV and videos 2:12 1:44 Socialising 0:59 0:57 Reading 0:23 0:23 Sports and exercise 0:36 0:26 Resting 0:38 0:30 Hobbies and games 0:16 0:07 Volunteer work and help 0:11 0:06 Entertainment and culture 0:05 0:04 Other 0:12 0:10 Source: Eurostat, How Europeans spend their time – Every day life of woman and men – Data 1998-2002, 2004. Note: the source of data for measuring the indicator is the Time Use Survey carried out with interruptions from 1 April 2000 to 31 March 2001. 14 0 Social Overview 2006 LABOUR MARKET AND EMPLOYMENT Table 50: Unemployment rate1 by education attainment of the unemployed2, 2000-2005 (in %) 2000 2001 2002 2003 2004 2005 Total 7.0 6.4 6.4 6.7 6.3 6.5 Without education, incomplete primary education (10.7) (14.2) (9.5) (11.9) (9.7) (9.1) Primary education 10.4 8.7 9.0 9.1 9.0 9.4 Lower or middle vocational education 7.5 6.9 7.5 8.2 7.5 7.3 Secondary technical education 6.6 5.9 55 5.9 5.7 6.3 Secondary general education 7.5 (7.0) (7.5) (6.4) (7.1) (8.4) Post-secondary education (not higher education) (2.3) (2.2) (2.3) (2.7) (3.6) (3.1) Higher professional and university education (2.4) (2.7) (3.0) (3.7) (2.9) 3.4 Post graduate education (specialisation, master’s and doctor’ degree) n.a. n.a. n.a. n.a. n.a. n.a. Source: SORS, Labour Force Survey. Note: ( ) less precise estimate (10<=CV<20); ‘n.a.’ not available. 1The unemployment rate represents unemployed persons as a percentage of the labour force. The labour force includes persons in employment and unemployed persons. 2Unemployed persons are those who during the last week prior to the interview did not work (they were not employed or self-employment and did not do any paid work), but were actively seeking work (specifi c steps were taken in the past four weeks to seek paid employment or self-employment etc.) and were currently available for work. Persons who had found a job to start later are also included among unemployed persons. Statistical Appendix 141 Table 51: Employment rate1 by level of school attainment, total and by gender, 1999-2005 (in %) 1999 2000 2001 2002 2003 2004 2005 Total 53.5 53.9 54.5 53.8 52.8 55.3 55.4 - Without education, incomplete primary education 23.0 21.8 22.2 20.3 18.5 19.5 16.4 - Primary education 33.4 35.2 36.2 34.2 32.9 35.1 34.8 - Secondary education 62.7 61.6 61.7 60.6 59.1 61.5 61.7 - Post-secondary education (not higher education) 73.1 72.5 72.1 70.7 69.2 68.7 66.5 - Higher professional and university education 81.4 79.2 79.7 81.4 81.2 81.6 81.7 - Post graduate education (specialisation, master’s and doctor’ degree) 79.8 80.2 81.9 83.7 88.4 88.7 86.3 Men 60.0 60.2 61.3 60.3 59.4 62.0 62.0 - Without education, incomplete primary education 31.4 32.1 32.1 31.1 27.9 29.6 26.0 - Primary education 41.0 41.8 44.9 42.0 41.7 44.5 44.2 - Secondary education 67.0 66.6 66.7 65.6 64.3 66.6 66.8 - Post-secondary education (not higher education) 69.3 67.6 69.7 68.2 68.2 70.0 67.5 - Higher professional and university education 79.2 75.9 75.1 77.9 77.0 77.9 77.6 - Post graduate education (specialisation, master’s and doctor’ degree) 80.4 82.4 82.6 79.7 86.1 86.9 (85.2) Women 47.4 48.0 48.2 47.7 46.5 48.9 49.2 - Without education, incomplete primary education 17.1 14.8 15.7 13.9 12.7 13.4 10.6 - Primary education 28.7 31.0 30.7 29.0 27.0 29.0 28.6 - Secondary education 57.5 55.8 55.7 54.6 53.0 55.4 55.8 - Post-secondary education (not higher education) 76.1 76.1 73.8 72.5 70.1 67.6 65.7 - Higher professional and university education 83.6 82.6 83.9 84.5 84.8 84.7 85.0 - Post graduate education (specialisation, master’s and doctor’ degree) (78.8) (77.2) (80.7) (90.9) 92.0 91.0 (87.8) Source: SORS, Labour Force Survey. Note: less precise estimate (10<=CV<20). 1The employment rate represents persons in employment as a percentage of the working age population. Persons in employment are those who during the last week (from Monday to Sunday) prior to the interview did any work for payment (in cash or kind), profi t or family gain. Persons who were not working but had a job from which they were temporarily absent are also included. The same applies to workers on lay-offs, persons on maternity leave and unpaid family workers. Unpaid family workers are those who were not in paid employment or self-employment during the last week prior to the interview, but did some work on the family farm, in the family enterprise or some other kind of family gainful activity and who normally do not receive regular payment. Working age population comprises all persons aged 15 and over. 14 2 Social Overview 2006 ADULT EDUCATION Table 52: Participation of the population aged 25-641 in lifelong learning, 2001-2005 (in %) 2001 2002 20032 2004 2005 Total 7.6 9.1 15.1 17.9 17.8 Men 6.9 8.8 13.9 16.1 16.0 Women 8.2 9.4 16.3 19.8 19.6 Source: SORS, Eurostat, Labour Force Survey. Notes: 1The percentage of the population aged 25-64 who were involved in any kind of education and training in the four weeks before the survey. 2In 2003 the methodology for calculating the indicator changed. HEALTH OF ELDERLY PEOPLE Table 53: Number of hospitalisations1 due to diseases by main cause of admission, by gender and for persons aged 65+, 2004 By diagnosis ICD-102 Number of hospitalisations Number of hospitalisations Number of hospitalisations Total Men Women per 1000 persons per 1000 persons 65+ per 1000 men per 1000 men 65+ per 1000 women per 1000 women 65+ Total diseases 132.84 302.80 122.69 358.33 142.56 269.12 Neoplasms 18.40 51.04 17.60 68.35 19.15 40.54 Circulatory diseases 18.71 76.78 19.93 93.65 17.54 66.55 Respiratory system diseases 12.39 28.81 14.57 42.35 10.30 20.59 Digestive system diseases 14.45 31.59 16.01 39.91 12.95 26.55 Musculoskeletal diseases 9.31 19.41 8.33 15.32 10.25 21.89 Source: Institute of Public Health. Notes: 1Hospitalisation means uninterrupted, more than 24-hour period (or at least overnight) health care of a person in a bed unit of a hospital. It commences with admission, continues with one or more episodes and ends with release from hospital. 2International statistical classifi cation of diseases and related health problems, 10th revision – ICD-10 is a system of categories or groups classifying diseases according to a system that complies with the epidemiological objectives and evaluation of health care. ICD is published by the WHO. Table 54: Diagnostic related groups (DRG)1, cases of acute care2 per 1000 inhabitants and average weight3 by age group, 2004 and 2005 Total population Men Women Total 0-19 20-64 65+ Total 0-19 20-64 65+ Total 0-19 20-64 65+ 2004 Number of DRG 330,860 53,561 176,900 100,399 139,209 28,727 67,168 43,314 191,651 24,834 109,732 57,085 Cases of acute care per 1000 inhabitants 165.68 128.80 138.40 331.35 142.47 134.55 103.46 378.68 187.91 122.73 174.47 302.66 Average DRG weight 1.28 0.98 1.13 1.71 1.46 1.01 1.44 1.80 1.15 0.95 0.94 1.63 2005 Number of DRG 340,861 55,719 178,816 106,326 145,192 30,240 68,693 46,259 195,669 25,479 110,123 60,067 Cases of acute care per 1000 inhabitants 170.14 137.34 139.18 339.84 147.93 145.07 105.12 386.98 191.48 129.17 174.44 310.69 Average DRG weight 1.37 1.06 1.19 1.84 1.56 1.09 1.51 1.93 1.23 1.03 0.99 1.77 Source: IVZ. Notes: Diagnostic related groups (DRG): Acute hospital care is categorised in diagnostic related groups based on the complexity of treatment which includes diagnostic and therapeutic procedures carried out. 2Acute hospital care means all activities (observation, diagnostic, treatment) relating to the entire acute health care of a person in hospital. It commences with admission for the first of hospital health services providing acute care and ends with release from hospital, transfer to the health service of the same hospital that does not provide acute hospital care, or death of the patient. Persons in acute care are those admitted to hospital due to a new (suddenly) incurred disease or injury, aggravation of a chronic disease or other illness, planned or unplanned surgery, or diagnostic. 3Weight: each diagnostic related group has a certain weight which serves as basis for the payment of hospital services. 14 4 Social Overview 2006 SOCIAL INCLUSION OF ELDERLY PEOPLE Table 55: People in old people’s homes1 and structure by reason for admission, 2000-2005 (in %) 2000 2001 2002 2003 20042 20052 Number of people in care 11,905 12,346 13,051 13,498 13,098 13,641 People in care in old people’s homes by reason for their admission (in %): Age 59.0 57.2 58.6 59.5 66.0 64.3 Unsettled housing conditions 5.2 4.7 4.7 4.5 4.7 4.1 Unsettled family conditions 4.6 4.9 4.4 4.4 4.2 3.7 Serious illnesses 26.3 27.4 26.7 26.6 20.5 22.2 Other 4.9 5.8 5.7 4.9 4.6 5.6 Source of data: SORS; calculations by IMAD. Notes: 1Includes public old people’s homes only. 2In 2004 and 2005 the SORS included people in care in eight units of old people’s homes providing special forms for mentally and physically handicapped adults and seven social welfare institutions. Until 2003 people in care in special units of old people’s homes were counted together with people in old people’s homes or combined social welfare institutions. Such a change in the classifi cation in 2004 brought about a decrease in the number of people in care in old people’s homes compared to 2003. Table 56: People in old people’s homes by the mode of payment for care, 2000-2005 (in %) Mode of payment for care 2000 2001 2002 2003 2004 2005 People in care 36.0 36.2 35.2 36.1 36.9 34.3 Relatives 6.5 6.5 6.7 7.1 9.9 10.9 People in care, relatives 24.3 26.3 28.2 29.5 29.8 31.7 People in care, municipality 22.9 22.8 23.0 21.5 18.3 17.1 Relatives, municipality 1.0 0.8 1.0 0.4 0.4 0.7 People in care, relatives, municipality 2.3 2.1 1.8 2.1 2.4 2.4 Municipality 7.1 5.2 4.0 3.3 2.3 2.9 Source: SORS; calculations by IMAD. Statistical Appendix 14 5 ECONOMIC AND FINANCIAL CONSEQUENCES OF POPULATION AGEING Table 57: Expenditure on pensions (in SIT million) total and by statistical categories1, 1999-2003 (in %) 1999 2000 2001 2002 2003 Expenditure on pensions (in SIT million) 440,127 489,703 553,338 625,648 648,825 Expenditure on pensions by statistical categories (in %) Function Disability - Disability pension 10.3 10.0 9.3 8.6 8.2 - Early retirement benefi t due to reduced capacity to work 0.3 0.3 0.3 0.3 0.3 Function Old age - Old age pension 64.5 65.7 65.6 66.1 69.0 - Anticipated old age pension 19.0 18.4 19.5 20.0 17.9 - Partial pension 0.0 0.0 0.0 0.0 0.0 Function Survivors - Survivors’ pension 3.2 3.1 3.0 2.0 2.7 Function Unemployment - Early retirement benefi t for labour market reasons 2.8 2.5 2.2 2.0 1.9 Source: SORS; calculations by IMAD. Notes: As the fi gures have been rounded up, the sum of all shares is not always equal to 100.0. 1National pension categories are classifi ed into statistical categories defi ned by the ESSPROS methodology according to the age of entitled persons and national pension form. The defi ned age for men is 65 years and for women 60 years. The category ‘old age pension’ includes expenditure on all old age, disability and survivors’ pensions to persons above the defi ned age; the category ‘disability pension’ includes expenditure on disability pensions to persons under the defi ned age. The category ‘early retirement benefi t due to reduced capacity to work’ includes expenditure on anticipated old age pensions to disabled workers under the defi ned age. The category ‘anticipated old age pension’ includes expenditure on all old age pensions to persons under the defi ned age, etc. 14 6 Social Overview 2006 MACROECONOMIC INDICATORS OF DEVELOPMENT Table 58: GDP and infl ation, 1999-2005 1999 2000 2001 2002 2003 2004 2005 GDP (in SIT million), current prices 3,918,974 4,300,350 4,799,552 5,355,440 5,813,540 6,251,244 6,557,698 GDP (in SIT million), constant previous year prices 3,684,010 4,079,676 4,414,601 4,965,320 5,497,364 6,055,773 6,493,107 GDP per capita (in EUR) 10,194 10,543 11,094 11,866 12,461 13,103 13,677 GDP per capita (PPS)1 13,900 14,600 15,400 16,000 16,500 17,900 18,700 GDP per capita (PPS) (EU25=100) 74 73 74 75 76 79 80 GDP - real growth rates in % 5.4 4.1 2.7 3.5 2.7 4.2 3.9 Infl ation - annual average 6.1 8.9 8.4 7.5 5.6 3.6 2.5 Source: SORS, Eurostat/New Cronos. Note: 1Purchasing Power Standards. Table 59: GDP per capita (in 1000 SIT), by region, 1999-2003 1999 2000 2001 2002 2003 Slovenia 1,974 2,162 2,409 2,684 2,912 Osrednjeslovenska 2,758 3,020 3,387 3,782 4,196 Obalno-kraška 2,083 2,268 2,503 2,785 3,011 Gorenjska 1,736 1,890 2,127 2,362 2,531 Goriška 1,958 2,122 2,378 2,607 2,779 Savinjska 1,794 1,952 2,131 2,397 2,585 Jugovzhodna Slovenija 1,791 1,981 2,213 2,429 2,625 Pomurska 1,415 1,526 1,701 1,864 1,995 Notranjsko-kraška 1,534 1,717 1,885 2,111 2,226 Podravska 1,623 1,790 1,998 2,257 2,426 Koroška 1,588 1,768 1,965 2,158 2,272 Spodnjeposavska 1,649 1,827 2,057 2,266 2,328 Zasavska 1,611 1,715 1,809 1,953 2,089 Source: SORS. Table 60: GDP per capita, index (Slovenia = 100), by region, 1999-2003 1999 2000 2001 2002 2003 Slovenia 100.0 100.0 100.0 100.0 100.0 Osrednjeslovenska 139.7 139.7 140.6 140.9 144.1 Obalno-kraška 105.5 104.9 103.9 103.7 103.4 Gorenjska 88.0 87.4 88.3 88.0 86.9 Goriška 99.2 98.2 98.7 97.1 95.4 Savinjska 90.9 90.3 88.5 89.3 88.8 Jugovzhodna Slovenija 90.8 91.6 91.9 90.5 90.2 Pomurska 71.7 70.6 70.6 69.5 68.5 Notranjsko-kraška 77.7 79.4 78.2 78.6 76.4 Podravska 82.2 82.8 82.9 84.1 83.3 Koroška 80.4 81.8 81.5 80.4 78.0 Spodnjeposavska 83.6 84.5 85.4 84.4 79.9 Zasavska 81.6 79.3 75.1 72.8 71.7 Source: SORS. Statistical Appendix 147 INDICATORS OF DEVELOPMENT Table 61: Development Defi ciency Index1 by region, 2007-2013 Index Rank Osrednjeslovenska 8.7 12 Obalno-kraška 82.4 11 Gorenjska 83.1 10 Goriška 93.8 8 Savinjska 92.3 9 Jugovzhodna Slovenija 101.7 7 Pomurska 159.5 1 Notranjsko-kraška 127.0 2 Podravska 116.8 3 Koroška 103.9 6 Spodnjeposavska 116.8 4 Zasavska 113.9 5 Source: SORS, Tax Administration of Slovenia, Agency for Public and Legal Records and Services, Ministry of the Environment and Spatial Planning; calculations by IMAD. Note: 1The Development Defi ciency Index is a composite index calculated on the basis of 11 indicators (indicators of development, development defi ciency and development possibilities). Its primary purpose is to rank the regions by development defi ciency level. It is also a criterion for regional incentives. Table 62: Human Development Index (HDI) and structural indicators, 1999-2003 1999 2000 2001 2002 2003 2004 HDI 0.874 0.879 0.881 0.895 0.904 0.910 Rank (no. of countries covered) 29 (162) 29 (173) 29 (175) 27 (177) 26 (177) 27 (177) Life expectancy at birth (years) 75.3 75.5 75.9 76.2 76.4 76.6 - LE index 0.84 0.84 0.85 0.85 0.86 0.86 Gross enrolment ratio1 (%) 83 83 83 90 95,0 95,0 - Education index 0.94 0.94 0.94 0.96 0.98 0.98 GDP per capita (PPP, USD) 15,977 17,367 17,130 18,540 19,150 20,939 - GDP index 0.85 0.86 0.86 0.87 0.88 0.89 Source: (2001-2005) Human Development Reports. UNDP, Oxford University Press: New York, Oxford; calculations by UNDP. Note: 1All persons participating in primary, secondary and tertiary education as a percentage of the population theoretically eligible for enrolment. Calculating the Human Development Index HDI (as the average sum of all three indices) = 1/3 (life expectancy index) + 1/3 (education index) + 1/3 (GDP index) Dimension A long and healthy life Indicator LE at birth Sub-index LE index Knowledge A decent standard of living literacy rate gross enrolment ratio GDP(PPP USD) Education index GDP index Human Development Index (HDI) 14 8 Social Overview 2006 Table 63: Gender-related Development Index (GDI1) and structural indicators, 1999-2003 1999 2000 2001 2002 2003 GDI 0.871 0.877 0.879 0.892 0.901 Rank (no. of countries covered) 27 (146) 27 (146) 29 (144) 26 (144) 25 (140) Life expectancy (years) Men 71.5 71.7 72.2 72.5 72.7 Women 78.9 79.1 79.5 79.7 80.0 Gross enrolment ratio2 (%) Men 80 80 80 86 92 Women 85 85 85 94 99 GDP per capita (PPP, USD) 15,977 17,367 17,130 18,540 19,150 Estimated earned income (PPP, USD)3 Men 19,942 21,642 21,338 22,832 23,779 Women 12,232 13,327 13,152 14,082 14,751 Difference between GDI and HDI4 -0.003 -0.002 -0.002 -0.003 -0.003 Source: (2005-2001) Human Development Report. Oxford, New York: Oxford University Press, UNDP. Notes: 1The GDI is composed of the same indicators as the HDI except that they are gender-adjusted (including the indicators representing the three areas of development). The GDI (ranging between 0 and 1) and its indicators refl ect (in)equalities in the distribution of goods needed for (quality) living – health, income and education – between men and women. The main message of the GDI is: the more a country’s GDI approaches its HDI, the smaller the gender gap in benefi ting from basic human resources. As the gender gap widens, the GDI falls. Since inequality (in opportunities) exists in all countries, GDI tends to be lower than HDI; this does not necessarily indicate a country’s lower ranking. In calculating the GDI, each of the structural gender-disaggregated values is combined into equally distributed indices, which give a harmonic mean. The GDI is calculated by combining those indices in which each index has a weight of one-third. The methodology ‘penalises’ differences in achievement between men and women. 2The number of students enrolled in primary, secondary and tertiary level of education, regardless of age, as a percentage of the eligible offi cial school-age population. 3The UNDP methodology takes into account the total male and female population, male and female shares of the economically active population, the ratio of the female to male non-agricultural wage, and GDP per capita (PPP, USD). 4Negative values indicate that the GDI is lower than the HDI. Table 64: Gender Empowerment Measure (GEM)1 and structural indicators, 1999-2003 1999 2000 2001 2002 2003 GEM 0.574 0.585 0.582 0.584 0.603 Rank (no. of countries covered) 22 (64) 25 (66) 27 (70) 31 (78) 30 (80) Seats in parliament held by women (as a % of total) 12.2 12.2 12.2 12.2 12.2 Senior offi cials and managers (as a % of total) 31.0 31.0 31.0 29.0 33.0 Female professionals and technical workers (as a % of total) 51.0 51.0 54.0 55.0 56.0 Ratio of estimated female to male earned income 0.61 0.62 0.62 0.62 0.62 Difference between GEM and HDI -0.300 -0.294 -0.299 -0.311 -0.301 Source: (2005-2001) Human Development Report. Oxford, New York: Oxford University Press, UNDP; calculations by IMAD. Notes: 1The gender empowerment measure (GEM) measures women’s active participation in the public sphere. It captures (in)equality in opportunities in three areas: the representation and participation of women in politics (measured by the share of women’s parliamentary seats); employment and the power of decision-making (measured by the share of women in senior and executive positions and the share of women in professional and technical positions); and the availability of economic resources (estimated income ratio). The GEM has values in an interval of [0,1], while its total value shows the differences in empowerment between women and men. A value of 1 indicates that women and men are equally empowered, while the shares of men and women are equal in all key indicators. Statistical Appendix 14 9 Table 65: Human Development Index (HDI) by region, 2002 and 2003 2002 2003 Slovenia 0.867 0.873 Osrednjeslovenska 0.898 0.906 Obalno-kraška 0.874 0.877 Gorenjska 0.867 0.873 Goriška 0.873 0.880 Savinjska 0.855 0.859 Jugovzhodna Slovenija 0.855 0.861 Pomurska 0.828 0.830 Notranjsko kraška 0.857 0.862 Podravska 0.853 0.856 Koroška 0.851 0.853 Spodnjeposavska 0.847 0.849 Zasavska 0.839 0.842 Source: SORS; calculations by IMAD. Note: The HDI is calculated on the basis of data on life expectancy, gross enrolment ratio (students enrolled in post-secondary education (not higher education), higher education and post-graduate education full-time and part-time, as share of the potential population, i.e. population aged 7-26) and data on GDP per capita in PPS by indices (Slovenia = 100). 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Analiza položaja izključenih družbenih skupin v Sloveniji in predlogi za zmanjšanje njihove izključenosti v sistemu socialnega varstva. Raziskovalna naloga. Ljubljana: Inštitut RS za socialno varstvo. (2005) Za vsako mamo in vsakega otroka. Strokovni posvet ob Svetovnem dnevu zdravja. Ljubljana: IVZ RS. Wilthagen, T., Tros, F. (2004). The concept of Flexicurity: A new approach to regulating Employment and labour markets. URL: http://www.tilburguniversity.nl/faculties/frw/research/schoordijk/ flexicurity/publications/papers/fxp2003_4.pdf (2005) The World Health Report 2005. Make every mother and child count. Geneva: WHO. URL: http://www.who.int/whr/en/. (2006) The World Health Report 2006. Working together for health. Geneva: WHO. URL: http://www.who.int/whr/en/. The IMAD’s Other Publications Working papers 11/2006: Firm of Private Value: What is Behind the Creation of Multiple Blockholder Structure?, A. Brezigar Masten, A. Gregorič, K. Zajc 2/2006: Does Exporting Boost Capital Investments? The Evidence from Slovenian Manufacturing Firms’ Balance Sheets, A. Burger, M. Ferjančič 5/2004: On the possibility of negative effects of EU entry on output, employment, wages and infl ation in Slovenia, A. Brezigar 4/2004: Future GDP growth in Slovenia: Looking for room for improvement, E.L.W. Jongen 3/2004: An analysis of past and future GDP growth in Slovenia, E.L.W. Jongen 1/2004: Productivity growth and functional upgrading in foreign subsidiaries in the slovenian manufacturing sector, M. Rojec, B. Majcen, A. Jaklič, S. Radošević More Working papers are available in Slovene. Analysis, Research and Development Slovenia’s Development Strategy (SDS 2006-2013), 2005 Spring Report 2006 Autumn Report 2006 Human Development Report Slovenia 2002-2003 Development Report 2006 Slovenia – On the Way to the Information Society IB Revija IB revija 4/2006 VSEBINA: Boris Gramc: Dejavniki notranjega podjetništva: Primer Slovenije. Matija Rojec: Struktura in politika nabav podjetij s tujim kapitalom v Sloveniji. Marijana Bednaš: Reforma pakta stabilnosti in rasti. Ana Murn: Ugotavljanje učinkovitosti državnih pomoči. Milena Bevc: Reforma fi nanciranja visokega šolstva v Sloveniji za povečano zasebno fi nanciranje – potrebnost in pogoji za uspeh. Razprave Alenka Kajzer: Kako povečati stopnjo zaposlenosti v Sloveniji? – uvod v okroglo mizo demografsko socialni izzivi Slovenije. Miroljub Ignjatović: Položaj mladih na trgu delovne sile. Nada Stropnik: Položaj in problemi mladih družin z vidika zaposlovanja ter usklajevanja dela in družine. Milena Bevc: Položaj mladih na trgu dela v luči sistema fi nanciranja visokega šolstva ter meddržavne mobilnosti in migracij mladih. Monika Šlebinger, Ksenja Pušnik, Barbara Bradač: Pristopi k politiki aktivnega staranja. Tine Stanovnik: Trg dela in možne smeri razvoja pokojninskega sistema v Sloveniji. Dušan Kidrič: Spodbude delodajalcem za podaljšanje aktivnosti starejših zaposlenih. Janez Malačič: Mladi in starejši v pasteh sprememb na trgu dela. Internet http://www.gov.si/umar Subscription Form Subscription *The subscription fee covers one print issue and one fre subsequent edition in either format is charged separati e ele ely. A pies sctronic issue 10% discou (for p nt is g catiot 478 r@go php the c< ublications av ranted for el n: up to 25%) ailable in electronic form). Each ectronic-only subscriptions. Discounts Quantity discounts (for orders of fi ve or more extra co series subscriptions (2 series: 20%; 3 series: 25%). of each publ ; discounts for multiple monthly Subscription and info IMAD, Gregorčičeva 27, 1000 Ljubljana, S and invoices are delivered by regular mail. ! publications is available at the website: http:// lovenia; ph E-mail: publ www.gov.si/ ear. ike effect fro ione +386 1 cistika.uma umar/public 1043; fax + v.si. All infor 386 1 478 1070. 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