Social overview 2009 (original: Socialni razgledi 2009) ISBN 978-961-6031-96-7 Ljubljana, March 2010
Publisher: IMAD, Ljubljana, Gregorčičeva 27 Director: Boštjan Vasle, Msc Editor: Tanja Čelebič, Msc
Authors of the Social overview 2009:
Lidija Apohal Vučkovič (Social welfare network, Housing)
Tanja Čelebič, Msc (Introduction, Access to childcare and education, Culture, Statistical appendix) Barbara Ferk, Msc (Household income and expenditure)
Matjaž Hanžek (Graduates, education attainment of adult population and population mobility, Socio-economic implications of
unemployment and poverty)
Alenka Kajzer, PhD (Labour market and employment)
Maja Kersnik, Msc (Cash benefits of the population from public funds, Social cohesion and poverty, Social-protection expenditure)
Saša Kovačič (Household income and expenditure)
Rotija Kmet Zupančič, Msc (Internet)
Tomaž Kraigher (Population)
Ivo Lavrač, PhD (Housing)
Ana Murn, PhD (General government expenditure associated with social development)
Janja Pečar (Labour market and employment, Socio-economic implications of unemployment and poverty)
Sonja Primožič (Media)
Eva Zver (Access to health care, Expenditure on long-term care).
Editorial board: Lidija Apohal Vučkovič, Marijana Bednaš, Msc, Lejla Fajić, Alenka Kajzer, PhD, Rotija Kmet Zupančič, Msc, Janez Kušar, Boštjan Vasle, Msc.
Expert advisors:
Milena Ilić, Rihard -Tomaž Inglič, Stanka Intihar, Apolonija Oblak Flander, Msc, Janja Povhe, Rade Pribakovič, Irena Svetin, Tatjana Škrbec, Erika Žnidaršič, Tina Žnidaršič.
Translation:
Boris Panič, Nina Barlič, Sebastijan Razboršek Maček, Nataša Zajec Herceg, Marija Kavčič
Language editor: Amidas d.o.o.
Technical support: Irena Rink, Ana-Marija Pucelj
Figures: Marjeta Žigman
Concept and design: Katja Korinšek, Pristop
DTP: Saša Brečko
Printed by: Tiskarna Eurograf d.o.o. Circulation: 130
© The contents of this publication may be reproduced in whole or in part provided that the source is aknowledged.
CIP - Kataložni zapis o publikaciji
Narodna in univerzitetna knjižnica, Ljubljana
308(497.4)
SOCIAL overview 2009 / [authors Lidija Apohal
Vučkovič ... [et al.] ; editor Tanja Čelebič]. - Ljubljana : UMAR, 2 010
ISBN 978-961-6031-96-7
1. Apohal Vučkovič, Lidija 2. Čelebič, Tanja, 1976-250446848
Social overview 2009	3
Contents
Contents
INTRODUCTION............................................................................................................................7
SUMMARY......................................................................................................................................9
i. the way we live..............................................................................11
1.	population ..........................................................................................................................13
2.	labour market and employment..............................................................................17
2.1	Employment...........................................................................................................................................17
2.2	unemployment.....................................................................................................................................20
2.2.1	Movement of registered unemployment............................................................................................20
2.2.2	Regional dimension of registered unemployment...........................................................................21
2.3	Impact of labour market conditions on the number of social benefit recipients ....................23
2.4	Labour-policy measures in response to the crisis ..........................................................................25
3.	household income AND expenditure......................................................................27
3.1	Disposable income and household expenditure............................................................................27
3.2	wages.......................................................................................................................................................28
3.3	pensions...................................................................................................................................................34
3.4	cash benefits of the population from public funds.......................................................................36
3.5	Household expenditures......................................................................................................................37
3.6	Indebtedness.........................................................................................................................................39
4.	access To goods AND services....................................................................................41
4.1	Access to health care.............................................................................................................................42
4.1.1	Health-care resources...........................................................................................................................42
4.1.2	Expenditure on health.........................................................................................................................46
4.2	Access to social-welfare services........................................................................................................48
4.2.1	Social-welfare network........................................................................................................................48
4.2.2	Expenditure on long-term care............................................................................................................49
4.3	Housing...................................................................................................................................................51
4.4	Access to childcare and education.....................................................................................................52
4.4.1	Participation in education...................................................................................................................52
Participation of children in organised pre-school education and childcare..............................................53
Participation of young people in primary schools, upper secondary schools and tertiary education.......53
4.4.2	Graduates, educational attainment of adult population and population mobility.....................57
4.4.3	Expenditure on education...................................................................................................................61
4.5	culture.....................................................................................................................................................62
4.6	Media.......................................................................................................................................................64
4.7	Internet....................................................................................................................................................66
5.	social cohesion AND poverty.....................................................................................67
5.1	Social cohesion.......................................................................................................................................67
5.2	poverty ....................................................................................................................................................71
5.2.1	Monetary (relative) poverty.................................................................................................................71
5.2.2	Material deprivation.............................................................................................................................72
5.2.3	Socio-economic implications of unemployment and poverty..............................................74
6.	GENERAL GoVERNMENT expenditure ASSociATED wiTH SociAL DEVELoPMENT.... 76
6.1	General government expenditure by function...................................................................................................76
6.2	Social-protection expenditure...............................................................................................................................80
ii. statistical appendix................................................................83
bibliography AND sources.............................................................................................131
Social overview 2009	4
Contents
List of tables
Table 1: Components of population development in Slovenia, 1995-2008....................................................................14
Table 2: life expectancy and infant mortality in Slovenia, 1995-2008............................................................................15
Table 3: Age structure of population in Slovenia, 1995-2009............................................................................................15
Table 4: Basic assumptions and results of the projection of Slovenia's population by 2060, compared with
1995 and 2005..............................................................................................................................................................16
Table 5: Employment rates by age group, Slovenia, 2000-2008, in %..............................................................................18
Table 6: Growth of the number of employed persons by activity, Slovenia, 2007-2009, in %....................................19
Table 7: Registered unemployment rates, total and by gender, Slovenia, 2000-2008, in %........................................20
Table 8: Registered unemployment rates by region, 2000-2009 (I-VI), in %..................................................................21
Table 9: Shares of selected groups of registered unemployed persons by region, 2009 (I-VI), in %.........................22
Table 10: Unemployed persons by reason (% of all employed persons), by region, 2009 (I-VI), in % ........................23
Table 11: Participation of unemployed persons in active labour-market policy programmes (ALMP), Slovenia,
January-November 2008 to January-November 2009 .......................................................................................26
Table 12: Growth in real gross wage per employee in private and public sectors, Slovenia, 2001-2008 and
Jan-Nov 2009, in %.....................................................................................................................................................28
Table 13: Average nominal gross wage per employee by activities as % of gross wage in the private sector,
private sector = 100, Slovenia, 2000-2008..............................................................................................................29
Table 14: Average nominal gross wage per employee by activities as % of gross wage in the public sector,
public sector = 100, Slovenia, 2000-2008...............................................................................................................29
Table 15: Structure of employees by education, total, private and public sectors, Slovenia, 2000, 2002 and
2008, in %.......................................................................................................................................................................30
Table 16: Interdecile ratio, indicator of distribution of gross wages by sectors and groups of activities,
Slovenia, 2000-2008....................................................................................................................................................31
Table 17: Interdecile ratio and the share of employees with low wages, indicators of gross wage distribution,
EU, 2006..........................................................................................................................................................................32
Table 18: Minimum gross wage, average gross wage in the private sector and the ratio of minimum wage to
average gross wage in the private sector, Slovenia, 2000-2008.........................................................................33
Table 19: Growth rates of the number of pensioners by types of pensions, 2000-2008, Slovenia, in %.....................35
Table 20: Structure of pensioners by types of pensions, 2000-2008 and the first eleven months of 2009,
Slovenia, in %................................................................................................................................................................35
Table 21: Structure of new old-age pensioners by age groups, Slovenia, 2000 and 2008, in %...................................35
Table 22: Average nominal net old-age pensions and net wages, and the ratio between old-age, disability
and survivor's pension to net wages, Slovenia, 2000-2008 and the first ten months of 2009.....................36
Table 23: Assistance for socially disadvantaged people, number of recipients, average amount and total
funds, Slovenia, 2009 ..................................................................................................................................................37
Table 24: Structure of consumption expenditure by five consumption quintiles, Slovenia, 2000 and 2007, in % ....38
Table 25: Ability of households to make ends meet, by household income, EU-27, 2008, in %....................................40
Table 26: Burden of households with loans and delay in payment, share by income, Slovenia, 2008, in %...............41
Table 27: Expenditure on health, Slovenia, 2003 and 2007, and estimated expenditure for 2008...............................46
Table 28: Number of people in old people's homes per 100 inhabitants aged 65 or above, Slovenia, 2000-2008 ...49
Table 29: Expenditure on long-term care by source of financing and function, 2003-2007..........................................50
Table 30: Households living in bad dwelling conditions, Slovenia, 2005-2007, in %......................................................51
Table 31: Level of burden of total housing costs to households, Slovenia, 2005-2007, in %.........................................51
Table 32: Participation in tertiary education and structure of students by type of programme, Slovenia,
2000/2001-2008/2009................................................................................................................................................55
Table 33: Educational attainment of population aged 25-64, Slovenia, 2000-2008, in %............................................58
Table 34: Membership of libraries, library visits and library units loaned, total and public libraries, 2000-2007.....64
Table 35: Total sold and print circulation of daily newspapers, Slovenia, second quarter, 2005-2009, number.......64
Table 36: Internet use and access, Slovenia, 2004-2009, in %..............................................................................................67
Table 37: Social cohesion indicators, Slovenia and EU-27, 2008 .........................................................................................67
Table 38: Subjective perceptions of crime; feeling of safety and personal experience of crime, Slovenia,
2002, 2004, 2006 and 2008, in %...............................................................................................................................69
Table 39: Subjective feelings of happiness, Slovenia, 2000-2008, in %............................................................................70
Table 40: Satisfaction with life, Slovenia, 2002, 2004, 2006, 2008, in %.............................................................................70
Table 41: Trust in other people, Slovenia, 2002, 2004, 2006, 2008, in %............................................................................71
Table 42: Trust in institutions, Slovenia, 2002, 2004, 2006, 2008, in %...............................................................................71
Table 43: Selected indicators of poverty risk, 2005-2008, Slovenia...................................................................................72
Table 44: Material-deprivation rates (percentage of people that are deprived in at least three
material-deprivation indicators) and at-risk-of-poverty rates, EU-25, 2008, in %..........................................73
Social overview 2009	5
Contents
Table 45: Material-deprivation rates of the population living above the at-risk-of-poverty level and poor
population, Eu-27, 2008, in % ..................................................................................................................................74
Table 46: Total general government expenditure as a share of GDP, EU-27, 2000-2008, in %......................................78
Table 47: Structure of general government expenditure in 2007, as a share of GDP, EU-27, 2007, in %......................79
Table 48: Social-protection expenditure per head of population by function group, Slovenia and
EU-25 average, 2000, 2006 and 2007 (in PPS per capita).....................................................................................81
List of figures
Figure 1: Net migration of citizens and foreigners, Slovenia, 1995-2008..........................................................................13
Figure 2: Number of births and total fertility rate in Slovenia, 1979-2008.......................................................................14
Figure 3: Age-specific fertility rates, Slovenia, 1981, 1991, 2001 in 2007..........................................................................15
Figure 4: Age structure of Slovenia's population, according to basic projection, 1995-2060.......................................16
Figure 5: Employment rate, age group 15-64, EU-27, 2008, in %........................................................................................18
Figure 6: Number of formally employed foreigners in Slovenia, 30 June 2007-30 September 2009 .........................18
Figure 7: Mean response to whether immigration is good or bad for the economy, selected European
countries, 2006..............................................................................................................................................................19
Figure 8: Average number of people registered as unemployed, Slovenia, 2000-2008, in '000...................................20
Figure 9: Unemployment rate, by gender, Slovenia, January 2007-July 2009, in %.......................................................20
Figure 10: Numbers of recipients of unemployment benefits (UB), financial unemployment assistance
(FUA) and persons registered as unemployed, Slovenia, 2000-2008 ...............................................................23
Figure 11: Shares of recipients of unemployment benefits (UB) and financial unemployment assistance
(FUA) in the total number of the registered unemployed, Slovenia, 2008-2009, in %...................................24
Figure 12: Share of unemployment benefit recipients in the total registered unemployed by region,
2008 (I-VI) and 2009 (I-VI), in % ...............................................................................................................................25
Figure 13: Number of recipients of financial social assistance by month, Slovenia, January 2007-0ctober 2009.....25
Figure 14: Number of financial social-assistance recipients as a share of total population in the region,
June 2008 and June 2009, in %..................................................................................................................................25
Figure 15: Categories of disposable income in terms of resources and uses in share of disposable
income, Slovenia and EU-27, 2008, in %..................................................................................................................27
Figure 16: Reaching the European level of consumption of households and NPISH, EU-27, 2008, in %,
PPS per capita...............................................................................................................................................................28
Figure 17: Distribution of employees by gross wages, total, private and public sectors, Slovenia, 2000 and 2008....31 Figure 18: Share of employees with low wages, median to first decile ratio in the private sector,
Slovenia, 2000-2008....................................................................................................................................................33
Figure 19: Ratio of minimum wage to average wage in the private sector, EU Member States in which
minimum wage is paid, 2007, in %...........................................................................................................................34
Figure 20: The number of ensured persons and pensioners, and the ensured-persons-to-pensioners
ratio, Slovenia, 1992-2008.........................................................................................................................................34
Figure 21: Funds for cash benefits as % of GDP, Slovenia, 2000-2008.................................................................................36
Figure 22: Structure of funds for cash benefits by target groups, Slovenia, 2008, in %....................................................37
Figure 23: Structure of the number of cash benefits by target groups, Slovenia, 2008, in %.........................................37
Figure 24: Liabilities as % of GDP, households and NPISH, 2008 and 2001, EU...................................................................39
Figure 25: Number of practising physicians per 100,000 inhabitants in Slovenia and selected European
countries, 1998-2007..................................................................................................................................................42
Figure 26: Number of medicine graduates per 100,000 inhabitants in Slovenia in 2008 and in OECD countries.......43
Figure 27: Contribution of foreign-trained physicians to total growth in number of practising physicians in the period 2000-2007, and share of foreign-trained physicians in total number of practising
physicians in Slovenia and selected OECD countries in 2007, in %....................................................................43
Figure 28: Average stay in acute hospital treatment in Slovenia and selected European countries in
2007, in days..................................................................................................................................................................44
Figure 29: Gap between hospitalisation rate and population needs for acute hospital treatment
per 1000 inhabitants, Slovenia, 2003-2008............................................................................................................45
Figure 30: Average annual growth rates in real terms of public and private expenditure on health and
GDP, Slovenia and selected European countries, 2003-2007, in %....................................................................47
Figure 31: Private expenditure on health as share of total expenditure, and their structure by source of
financing, Slovenia and OECD countries, 2007, in %.............................................................................................47
Figure 32: Direct household out-of-pocket expenditure on health as share of total household consumption,
Slovenia and OECD countries, 2007, in %................................................................................................................47
Social overview 2009	6
Contents
Figure 33: Total (public and private) expenditure on health as a share of GDP and USD PPS
per capita, Eu-27, 2007...............................................................................................................................................48
Figure 34: People in care in social-welfare institutions by category, Slovenia, 2000-2008..............................................48
Figure 35: Share of population aged 65 or above in long-term care at institutions and at home; selected
European countries, 2005, in %.................................................................................................................................49
Figure 36: Cumulative real growth index for expenditure on long-term care in Slovenia in
2003-2007 (2003=100)...............................................................................................................................................50
Figure 37: Cumulative real growth index for total expenditure on long-term care in Slovenia and selected
European countries in 2003-2007 (2003=100)......................................................................................................50
Figure 38: Total expenditure on long-term care as a share of GDP, EU-25, 2006, in %......................................................50
Figure 39: Second-hand dwellings price trends, index 2005=100, Slovenia, 2003 - 2008...............................................52
Figure 40: Participation of children aged 1-2 and 3-5 in kindergartens, Slovenia, 2000/2001-2008/2009, in %.......53
Figure 41: Number of pupils enrolled in primary schools and projections of the number of pupils of
official primary school age (6-14 years) enrolled in primary schools, Slovenia, 2000-2020........................54
Figure 42: Share of young people aged 15-19 participating in upper secondary education, EU-27, 2007, in %........54
Figure 43: Ratio of number of participants in tertiary education to number of population
aged 20-29, EU-27, 2007............................................................................................................................................56
Figure 44: Participation of adults aged 25-64 in formal or non-formal education by selected socio-economic
characteristics, Slovenia, 2007, in % .......................................................................................................................57
Figure 45: Graduation rates in upper secondary education, Slovenia and OECD members, 2007, in %........................57
Figure 46: Number of graduates per 1,000 inhabitants aged 20-29, EU-27, 2007.............................................................58
Figure 47: Educational attainment of population aged 25-64, EU-27, 2008, in %.............................................................59
Figure 48: Classification of selected European countries by correlation coefficient of mobility, 2006.........................60
Figure 49: Inertia index of the educational attainment of spouses, European countries, 2006......................................61
Figure 50: Total public expenditure on education as a share of GDP, EU-27, 2000 and 2006, in %.................................61
Figure 51: Total public expenditure on education by level of education, as a share of GDP, Slovenia,
2000-2007, in %...........................................................................................................................................................61
Figure 52: Public expenditure on education, total and tertiary level, EU-27, 2006, in %..................................................62
Figure 53: Number of visitors in museums and number of visitors per exhibition, Slovenia, 2004-2008....................62
Figure 54: Number of visitors of theatrical performances and concerts at theatres, Slovenia, 2004-2008..................63
Figure 55: Attendance at screenings of foreign and Slovenian feature-length films, Slovenia, 2000-2008.................63
Figure 56: Number of titles of books (works), by language, Slovenia, 2000-2008.............................................................63
Figure 57: Interest in topics in selected payable daily newspapers, Slovenia, 2008, in %................................................65
Figure 58: Time dedicated to media, by type of media (newspapers, TV, radio), Slovenia, 2008, in %..........................65
Figure 59: Share of households with Internet access, EU-27, 2009, in %..............................................................................66
Figure 60: Income inequality as measured by the Gini coefficient, EU-27, 2008, in %......................................................68
Figure 61: Number of homicides per 100,000 inhabitants, EU-27, 2005-2007...................................................................68
Figure 62: Number of prisoners per 100,000 inhabitants, EU-27, 2005-2007 ....................................................................69
Figure 63: Number of deaths in road traffic accidents per 100,000 inhabitants, EU-27, 2007.........................................69
Figure 64: Number of suicides per 100,000 inhabitants, EU-27, 2007..................................................................................70
Figure 65: Total mortality and unemployment by Slovenia's administrative units, 2005-2007 average .....................75
Figure 66: Total mortality and personal income-tax base by Slovenia's administrative units, 2005-2007 average ...75
Figure 67: General government expenditure as a share of GDP, EU-27, 2000 and 2008, in %.........................................76
Figure 68: Social-protection expenditure as a share of GDP, EU-27, 2000 and 2007, in %................................................76
Figure 69: Social-protection expenditure as a share of GDP, 2007, EU-27, in %.................................................................80
Figure 70: Social-protection receipts by type, Slovenia and EU-27, 2007, in %..................................................................81
List of maps
Map 1: Registered unemployment rates by region, 2009 (I-VI), in %.............................................................................22
Social overview 2009	7
Introduction
Introduction
IMAD has to date published two issues of the Social Overview. Each issue covered a period of two years, focusing on the main dimensions of social development (The Way We Live and a selected current topic). However, as The Way We Live chapters deal with topical issues, and as current monitoring and analysis of social development is particularly vital during a time of great socio-economic changes, we also decided to publish an interim overview discussing only these topics. Social Overview 2009 is the first publication of this kind and a continuation of the first two Social Overview issues (2006 and 2008) and the previous four publications entitled Human Development Report that were published in 1998, 1999, 2000-2001 and 2002-2003.
The Way We Live chapters are an analytical presentation of social dimensions of Slovenia's development, which are equal in importance to the economic aspects. Economic growth and development, as measured by gross domestic product (GDP) per capita, is understood as the basis and the necessary condition to improving quality of life and social welfare. However, GDP per capita alone is not a sufficient measure in evaluating the living conditions of citizens and social development, as is pointed out by Stiglitz et al. (2009). Even if GDP is typically linked to a number of living standard indicators, high GDP per capita does not necessarily ensure high-quality living conditions for the entire population. The Social Overview shows a number of social dimensions of development. Using selected objective statistical data and indicators, we describe objective living conditions, complementing them with selected data on subjective perceptions of life based on public opinion surveys. Social Overview2009 mainly shows movements from 2000 onwards, with a special emphasis on the changes in the last recorded year (in 2008 in most cases). As the presentations refer to the period before the crisis, the data do not yet reflect the impact of the crisis on the social situation. To define Slovenia's position in its international environment, we also decided to show how Slovenia compares with other EU-27 countries in terms of social development.
Social Overview 2009 contains six chapters. The first (Population) presents population movements, highlighting future trends that will significantly influence areas such as the labour market, education, the social protection network and the need for long-term care, health services, etc. Since an individual's position on the labour market significantly affects his/ her socio-economic status, employment and unemployment trends are explained in the second chapter, Labour Market and Employment. The Household Income and Expenditure chapter analyses the movements of various types of household income, expenditure and receipts, with a special emphasis on wages and pensions, and income distribution as an indicator of social inequality, as income and its distribution have a significant impact on the population's standard of living. The comprehensive fourth chapter, Access to Goods and Services, shows the accessibility of goods and services (health, social services, child-care institutions and education, housing, the Internet, culture and media) that are significant determinants of living conditions. In the Social Cohesion and Poverty chapter, we present social cohesion by means of various indicators and describe the new indicator of material deprivation and the impact of unemployment and poverty on population health. The last chapter shows total public expenditure, which is important in terms of social development, according to a methodology that differs from that used to show expenditure on goods and services in the chapter on access. The Social Overview concludes with a statistical appendix of figures complementing the individual chapters.
Statistical data and indicators in individual chapters and in the statistical appendix are based on data collected by the Statistical Office of the Republic of Slovenia (SORS), the Statistical Office of the European Communities (Eurostat), the Organisation for Economic Co-operation and Development (OECD), the World Health Organisation (WHO), the Public Opinion and Mass Communications Research Centre (CJMMK) at the Faculty of Social Sciences of the University of Ljubljana, as well as a number of other sources. The Social Overview is largely based on data available by the end of November 2009.
We would like to thank all the external experts who helped us to prepare the publication.
9	Social overview 2009
Summary
Summary
The Social Overview has to date been issued every other year, comprising The Way We Live chapters and a selected current topic. This time we present the first interim issue of the report, featuring only the chapters on The Way We Live. Social Overview2009 thus consists of six chapters: Population, Labour Market and Employment, Household Income and Expenditure, Access to Goods and Services, Social Cohesion and Poverty, and General Government Expenditure Associated with Social Development. In the following summary, we highlight the main findings and challenges presented in the individual chapters.
Slovenia's populations has increased significantly in recentyears, largely thanks to high net migration as a result of favourable economic trends and the consequent increase in demand on the labour market after the enlargement of the EU. Since 2006, the population has also again been growing due to a positive natural increase. Slovenia recorded 2,042,335 inhabitants in June 2009. The number of births, which had declined for more than 20 years, has been rising since 2004. The age of women at first childbirth is ever higher. Life expectancy is increasing, and infant mortality, which is among the lowest in Europe, almost halved between 2000 and 2008. The share of old people (aged 65 and over) in the total population is therefore growing. In a few years, total population will start to decline, according to Eurostat's population projections, while the process of ageing will accelerate. These projected demographic changes call for systematic measures of population and employment policies as well as public finance policy.
Following an extended period of improvement, the labour market situation started to deteriorate in the last quarter of2008 with the impact of the crisis. In 2000-2008, the number of employed persons increased and unemployment declined, which was also reflected in a falling number of recipients of financial social assistance and unemployment benefits. These favourable trends were brought to a halt by the crisis. The number of employed persons declined, while the number of unemployed increased, which translated into a higher number of recipients of financial social assistance and unemployment benefits. Similar trends have been also observed for statistical regions. Given that the number of the unemployed increased more notably in 2009 in regions with below-average unemployment rates, regional disparities declined, but with a significantly higher registered unemployment rate. The government responded to the crisis by passing two interventive acts aiming to preserve jobs and by increasing the participation of the unemployed in active labour-market policy programmes, thus preventing even higher unemployment growth. Both acts have played an important role in preserving jobs; however, in certain sectors, they may only postpone urgently required restructuring. With no rapid improvement of the labour-market situation in sight, labour-market policy is faced with the great challenge of increasing participation of unemployed and employed persons in education and training programmes, and public works schemes, to increase their employability. Furthermore, it will also be necessary to gradually transform measures aimed at preserving jobs, which should be temporary and targeted to help enterprises to weather the crisis.
In 2000-2008, household income increased faster than household expenditure. The structure of disposable income, which did not change significantly in that period, shows that Slovenian households earn more income from employment and less from property than households in the EU-27 as a whole. The average income per inhabitant of the EU-27 improved between 2000 and 2008. The real gross wage per employee increased by an average of 2.3% per year in 2000-2008; growth in the private sector was slightly faster than in the public sector. In the private sector, there are great disparities in wage growth recorded by individual activities, and the gap is still growing, while in the public sector, wage growth is more evenly distributed by activities. In the private sector, the proportion of employees on low wages has increased over the past few years. The inappropriate mechanism for setting the minimum wage resulted in a lower ratio of minimum wage to average gross wage in the private sector, which called for an extraordinary adjustment in 2008. Further significant increases in the minimum wage as required by trade unions will expose the unfavourable distribution of wages, increasing the concentration at the lower end. The current wage policy must therefore address the challenge of using the adjustment period to adapt to new requirements for higher technology intensity and for a more stimulative wage policy. The number of all pensioners is growing faster than the number of those who make payments into the pension fund. In the structure of beneficiaries by type of pensions from compulsory insurance, the share of old-age pensioners increased in the 2000-2008 period. The average retirement age is rising, but is still relatively low. The ratio of old-age pension to net wage was decreasing in 2000-2007. In 2008, it was the same as in the previous year, whereas it increased slightly in the first ten months of 2009. The data on household expenditure show a lower ratio between the consumption of the fifth and first quintiles in 2007 compared with the previous year, while relative to 2000, the differences in consumption increased. In 2007, the fifth of households in the highest consumption quintiles spent 4.2 times more than the fifth of households with lowest consumption. Households with the highest consumption (4th and 5th quintiles) allocate the greatest share of expenditure for transport, followed by food, while the other quintiles spend the highest share on food, and then on housing. Household borrowing started to slow in the second half of 2008. In 2008, Slovenian households were among the least indebted in the EU, despite the relatively fast increase in borrowing over the last years.
Accessibility of public services and goods of general interest is improving in most areas, often because of payment from private sources, but there are still certain problems. Looking at the health-care system, Slovenia's households have been increasingly burdened by expenditure on health in recent years. In the structure of private expenditure on health, the share of out-of-pocket household expenditure has already exceeded expenditure from voluntary insurance. At the primary level, the persistent problem is uneven regional distribution of general practitioners and the provision of preventative services. Waiting
10	Social overview 2009
Summary
lines are particularly long in dental care for adults. Access to acute hospital treatment improved in the 2003-2008 period as a result of further investment for shortening the waiting lines. The accessibility of services and social-care programmes has been improving. Despite the growing need for long-term care as a result of population ageing, access to institutional care is increasing due to the growing capacity of homes for the elderly, while Slovenia still lags behind other European countries, especially in the provision of help for the elderly living at home. Expenditure on long-term care has been increasing in real terms at all times, in the last two years mainly from private sources. Total expenditure on long-term care as a share of GDP is hovering at the level of the EU-25 average. Housing conditions are generally improving, though they still tend to be rather unfavourable for low-income groups and tenants. About a half of low-income households and tenants find it hard to meet their housing costs. The housing fund is still increasing, but there is a problem of high prices, so that even average-income households are unable to purchase or rent an adequate dwelling. Movements in the areas of participation in education, completion of education and educational attainment are mostly favourable. Among the main challenges are how to ensure sufficient pre-school capacity, how to reduce the impact of socio-economic factors on students' learning achievements and decrease differences in participation of adults in education with regard to their socio-economic characteristics (age, educational attainment, activity status and profession). Trends in the area of books and libraries are favourable, by and large. Library membership, per capita number of library visits and per capita number of library units loaned increased in 2000-2007, while there is still room for improvement in terms of visits to cultural institutions (increasing the number of visitors to museums and exhibitions). Access of households to the Internet has increased markedly over recent years, in particular the share of households with a broadband connection, which is at the level of the EU average. The share of Internet users has also been on the rise, in the last year also more notably for groups where the potential to expand Internet use has been insufficiently developed (people with lower levels of education, people older than 35 years). Until a few years ago, people mainly relied on print media for information on daily events, while recently, due to higher rates of Internet access, increasing numbers of people are getting their daily news online, and this is also reflected in lower circulations for daily newspapers. People are inclined to dedicate less time to follow news and current affairs, in part made possible by newspaper articles on the web, which tend to be shorter and less detailed.
Based on the Laeken indicators we can conclude that social cohesion in Slovenia is relatively high, as Slovenia is ranked
at the top of the EU. Slovenia recorded the lowest income inequality in 2008, the lowest share of jobless households with dependent children and the lowest share of early dropouts. A relatively effective system of social transfers played an important role in lowering income inequality in Slovenia, given that the risk of poverty would almost double were it not for this social state aid. Slovenia also scores favourably in the EU in terms of other quality of life indicators (such as crime rate, number of homicides, as well as share of the population feeling threatened in their immediate neighbourhood). However, Slovenia notably exceeds the EU average as regards fatal road traffic accidents and suicide rate. Trust in other people and in institutions as an indicator of social capital is also low in Slovenia, although Slovenia does rank in the middle of European countries in terms of happiness and satisfaction with life. The new material deprivation indicator, which shows how people actually live, indicates that material deprivation increased in 2008, even if it is relatively low compared with the EU. The increase is largely due to high inflation in 2007 and 2008, by our estimate. The risk of poverty increased somewhat in 2008, though it was still among the lowest in the EU. Certain population groups remain highly vulnerable to the risk of poverty (the unemployed, the elderly, single parents, tenants, etc.), to which special attention must be paid in times of financial crisis and rising unemployment, as unemployment translates into deeper poverty, increasing mortality and suicide risk.
The share of general government expenditure that is directly and indirectly related to social development as a share of GDP has been declining in recent years, particularly the share of social protection expenditure. In 2007, Slovenia allocated close to two thirds of all general government expenditure as a share of GDP (according to the national accounts methodology and classification by function) for expenditure that is directly or indirectly related to social development (expenditure on social protection, health, education, and recreation and culture). Even if high in comparison with expenditure on other functions, this expenditure was below the EU-27 average in 2007 (Slovenia: 28.3% of GDP; EU-27: 30.8% of GDP) and lower than in the previous two years. The bulk of expenditure is allocated for social protection, but social protection expenditure as a share of GDP has dropped significantly since 2003 and is much below the EU-27 average. Also lower than the EU-27 average is expenditure on health. The share of expenditure on education is higher than the EU-27 average, but has been declining since 2005. If Slovenia is really striving for a knowledge-based society, expenditure should not be expected to drop. It would be sensible, however, to check individual education programmes for efficiency with regard to the needs of the economy and society development. Social protection expenditure as a share of GDP also declined according to the ESSPROS methodology in 2007, but expenditure in purchasing power standard per capita remained at the level of the previous year. As throughout the EU-27, Slovenia allocates the bulk of social protection expenditure for old age and sickness and health care. However, in the composition of sources of financing, Slovenia differs significantly from the EU-27, as contributions by insured persons account for the largest share in total social protection receipts in Slovenia, while in the EU-27, the largest share comes from contributions by employers. Slovenia will thus face a great challenge in terms of social protection reform, as it will have to ensure sustainable public finance systems amid comparably low current expenditure on social protection and health, with increasing needs for these types of expenditure expected.
the way we live
Social overwiew 2009	13
The way we live
1. Population
The population represents both a condition of and a target for economic and social development. The
population is the main source of the labour force, but at the same time, various contingents of the population are the main targets of social, health, employment, education and other policies affecting quality of life and consequently also demographic development. While demographic development is a consequence of past actions in the economy and of policies for balancing the quality of life, it is also a precondition for further economic development and a framework for setting policy goals. The demographic characteristics of the population can be considered one of the synthetic indicators of the effectiveness of other development components. These characteristics do, however, also depend on other factors and have their own causes, independent of the non-demographic development components. Therefore, analysis of the social dimensions of development in Slovenia should start with a survey of the main population characteristics. The population of Slovenia has grown considerably in the last few years, largely due to high net migration, while the coming years are likely to witness accelerated population ageing.
After a constant rise for several years, Slovenia's population was 2,042,335 persons in June 2009.1 The
main reason behind the rise was high net migration, which was largely of seasonal nature. It was spurred by the high economic growth after Slovenia's accession to the EU in 2004, and additionally after the adoption of the euro in 2007. Owing to skill shortages in specific occupations, especially in construction, companies increasingly hired foreign workers, which in turn led to a doubling of the number of foreigners working in Slovenia in this period.2 High economic growth, which contributed to a cut in registered unemployment numbers by one third in the
1	As of December 2008, SORS has used a new EU-compatible statistical definition of population. According to this definition, the population of Slovenia consists of persons (regardless of citizenship) with registered (permanent or temporary) residence in Slovenia who live or intend to live in Slovenia for one year or more and are not temporarily absent from Slovenia for one year or more. According to the previous definition, which applied in the period from 1995-2008, the population of Slovenia consisted of citizens of the Republic of Slovenia with permanent residence in Slovenia, excluding those who have been abroad for more than three months and gave notice of their departure at the administrative unit of their permanent residence; foreigners with issued permission for permanent or temporary residing in the Republic of Slovenia who have a registered permanent or temporary residence; and persons to whom asylum and refugee status were granted in the Republic of Slovenia according to the Asylum Act. In June 2008, Slovenia's population was 2,023,358 persons according to the new definition, which is 16,041 persons or 0.8% less than under the previous definition, which included also foreigners living in Slovenia for less than a year.
2	This is reflected in the rise in work permits issued to foreigners: in 2008 there were on average 81,113 such permits, i.e. 2.04 times the figure in 2004.
period 2004-2008, was also one of the likely reasons behind the change in birth dynamics. In 2006, the number of births exceeded the number of deaths for the first time in ten years; since then, the rise in population has also been fuelled by a positive natural increase. In the period 1991-2004, Slovenia's population grew slowly and only exceeded 2 million in 2005.
For a number of years, the population has grown largely
due to net migration. After being relatively low in the period 1993-2004, i.e. around 1.2 per 1,000 population, net migration has been on the rise since 2005,3 reaching 18,584 or 9.2 per 1,000 population in 2008.4 According to the provisional data for the first two quarters of 2009, net migration further increased in the first quarter, but was halved in the second quarter compared with the level recorded in the same period in the previous year.5 The number of foreign immigrants to Slovenia exceeded the number of emigrants, whereas the net migration of Slovenian citizens has been slightly negative since 2000.6
Figure 1: Net migration of citizens and foreigners, Slovenia, 1995-2008
^^m Emigrant citizens	^^m Emigrant foreigners
cssffls Immigrant citizens	^^ Immigrant foreigners
—■— Net migration of citizens -Net migration of foreigners
Source: SORS; calculations by IMAD.
3	In 2005 and 2006, net migration augmented to more than 6,000 persons or 3.2 per 1,000 population. Both, immigration and emigration were up, and this continued also in the following years. In 2007, it reached (by the definition of migration and population, which included foreigners who stayed temporarily) 14,250 or 7.0 per 1,000 population and in 2008 (by the same definition), it soared to 28,331 or 13.9 per 1,000 population.
4	By the new definition, which excludes migrants who are present in or absent from the country for less than a year.
5	In addition to deteriorated economic conditions, which halted the employment of foreigners, this has decreased also because of stricter conditions for the acquisition of residence permits; since Slovenia entered the Schengen regime, there have been cases of misuse, as foreigners with a Slovenian residence permit, which allows them to travel or live in any country within the Schengen regime up to three months, worked, applied for asylum or registered as job-seekers in these countries.
6	Average migration coefficient of citizens was -0.4 per 1,000
population in 2000-2008.
Social overwiew 2009	14
The way we live
Table 1: Components of population development in Slovenia, 1995-2008
	1995	2000	2005	2006	2007	2008
Population (in '000)	1987.5	1990.3	2001.1	2008.5	2019.4	2039.4
Live births	19.0	18.2	18.2	18.9	19.8	21.2
Deaths	19.0	18.6	18.8	18.2	18.6	18.3
Immigrants	5.9	6.2	15.0	20.0	29.2	43.8
Emigrants	3.4	3.6	8.6	13.7	14.9	15.5
Natural increase (per 1,000 popul.)	0.0	-0.2	-0.3	0.4	0.6	1.4
Net migration (per 1,000 popul.)	1.3	1.3	3.2	3.1	7.1	13.9
Total fertility rate	1.3	1.3	1.3	1.3	1.4	1.5
Source: SORS; calculations by IMAD.
The volume of migration of foreigners has also strongly exceeded the migration of citizens. Most foreign immigrants come from the countries of the former Yugoslavia, mostly Bosnia and Herzegovina. They migrate to Slovenia predominantly for economic reasons, in large part as seasonal workers in construction, agriculture, and hotels and restaurants. Most migrants are men, aged 20-29, and more than 50% of migrants are low skilled.7 Immigration from other EU Member States accounts for 10% of total immigration; in 2008, this amounted to 2,646 persons.
The number of births has been rising since 2004. After dropping from 30,604 to 17,321 in the period 1979-2003, with the total fertility rate down from 2.22 (still allowing for enlarged reproduction of the population) to 1.20, the number of births again started to rise in the period 2004-2008; this happened despite a further shrinking contingent of women in their reproductive age - resulting
Figure 2: Number of births and total fertility rate in Slovenia, 1979-2008
Number of births	-Total fertility rate
35	2.5
1-^COCOCOCOCOCftCftCftCftCftOOOO
Source: SORS; calculations by IMAD.
7 In 2007, 40% of immigrants had secondary education and only 3% had higher education.
from the low number of births in the past. In 2008, 21,213 children (1,390 more than in 2007) were born in Slovenia, and the total fertility rate was up to 1.53 (in 2007, it was 1.38); both the number of first-borns and other newly born children have grown. In the period 1997-2005, the number of births was lower than the number of deaths (the latter averaging at around 18,500 per year), resulting in a negative natural increase. Since 2006, however, the number of live births has again exceeded the number of deaths (in 2008, there were 18,308 of the latter), resulting in a positive natural increase; in 2008 this increase was 1.42 per 1,000 population. The number of live births also exceeded the number of deaths in the first and second quarter of 2009, according to provisional data. The rise in the number of births in the period 2004-2008 can be attributed to the improved economic situation, and consequently improved situation on the labour market, and partly also to the postponing of births in the past because of study, unemployment, unsolved housing problem, etc. After bottoming out in the second half of the 1990s, the fertility rate has also been increasing in other EU Member States for several years, although it remains below the level allowing for a simple reproduction of the population.
By postponing motherhood, the age of women at childbirth has risen. The rise in the total fertility rate over the last three years can be attributed to the rising fertility of women aged 31-36, and a slower drop in the fertility rate of women younger than 26. The fertility rates of women aged 27 and above have recorded an upward trend since 1990. The age at which women record the highest fertility rate has also been rising. In the mid-1990, the highest fertility rate was at the age of 26, but since 2004, it has been at 29. The average age of women at childbirth (figures for all children and also for first-borns alone) has also increased.8 By these figures, Slovenia has been catching up with the countries with a high average age at childbirth.
8 In 2007, the former age was 29.9 years (up by 1.7 years from 2000 or by 2.7 years more than in 1995) and the latter was 28.2 years (up by 1.7 years from 2000 or by 3.3 years from 1995).
Social overwiew 2009
The way we live
15
Figure 3: Age-specific fertility rates, Slovenia, 1981, 1991, 2001 in 2007
Age of mother at first birth
Source: SORS.
Life expectancy increased also in 2008 and infant mortality remains among the lowest in Europe. After a short halt in the early transition years, life expectancy has been constantly on the rise since 1994. In 2008, it stood at 75.4 years for men and 82.3 years for women. The difference between sexes has been narrowing, but remains high. On this indicator, Slovenia has been ranked right behind "old" EU Member States, Cyprus and Malta, with life expectancy rising in most European countries.
Slovenia still belongs to the group of countries with the lowest infant mortality rate. In 2008, this was the same as in 2007 (2.8 deaths of infants up to one year per 1,000 live births), when the lowest ever rate was recorded in Slovenia. For several years, infant mortality has recorded a downward trend, which has been largely a result of improved specific prevention measures in prenatal and neonatal healthcare. In 1980, the infant mortality rate was still 15.3 per 1,000 live births, and in the second half of the 1990s, it ranged from 4.5 to 5.5.
By rising life expectancy and declining number of children due to low fertility, the ageing of population has continued. For the first time since the late 1970s, the number of children aged 0-14 did not drop in 2008, but even slightly picked up; however, their share in the age structure of the population has continued to narrow. Conversely, the number of people aged 65 and above has continued to rise rapidly, as well as their share in the age structure of population. In 2003, the number of people aged 65 and above exceeded, for the first time, the number of children. The ageing index, representing the ratio of older people to children, edged above 100 and reached as much as 117.1 by 2008. The number of people aged 15-64 (according to statistical convention, defined as "working age population") has continued to slightly grow thanks to positive net migration, but its share in the age structure of population has declined since 2005. As the number of people aged 65 and above has been rising faster than the population aged 15-65, the ratio of older to working-age population (the old-
Table 2: Life expectancy and infant mortality in Slovenia, 1995-2008
		1995	2000	2005	2006	2007	2008
	Men	70.3	71.9	74.1	74.8	74.6	75.4
Life expectancy (in years)	Women	77.8	79.1	81.3	81.9	81.8	82.3
	Difference	7.5	7.2	7.2	7.1	7.2	6.9
Infant mortality (per 1,000 live births)		5.5	4.9	4.1	3.4	2.8	2.8
Source: SORS; calculations by IMAD.
Table 3: Age structure of population in Slovenia, 1995-2009
180
160
140
o 120
i 100
0
		1995	2000	2005	2006	2007	2008	20091
	0-14 years	18.4	15.9	14.2	14.0	13.9	13.8	14.0
Age structure of population (in %)	15-64 years	69.3	70.1	70.3	70.2	70.1	70.0	69.5
	65 years and over	12.3	14.0	15.5	15.7	16.0	16.2	16.5
Old-age dependency ratio		17.8	19.9	22.0	22.4	22.9	23.2	23.7
Ageing index		67.0	87.8	108.7	112.4	115.1	117.1	118.0
	Population	-0.1	0.2	0.2	0.4	0.5	1.0	1.0
Annual growth	0-14 years	-2.2	-2.6	-1.4	-1.2	-0.1	0.4	1.2
(in %)	15-64 years	-0.1	0.5	0.1	0.3	0.3	0.8	0.7
	65 years and over	3.4	2.2	2.2	2.2	2.3	2.1	2.0
Source: SORS; calculations by IMAD.
Note: 1Using the new definition of population.
Social overwiew 2009	16
The way we live
Table 4: Basic assumptions and results of the projection of Slovenia's population by 2060, compared with 1995 and 2005
Year		1995	2005	2010	2015	2020	2030	2040	2050	2060
Assumptions of population projections:										
Life expectancy	- men	70.3	74.1	75.1	76.1	77.1	78.9	80.6	82.2	83.7
	- women	77.8	81.3	82.2	83.0	83.7	85.1	86.4	87.6	88.8
Total fertility rate		1.3	1.26	1.33	1.35	1.37	1.40	1.44	1.48	1.52
Net migration		2507	6436	5177	5015	4435	3436	3313	3043	2254
Population 30.6. (in '000)		1987.5	2001.1	2036.6	2054.1	2057.6	2020.0	1954.4	1873.4	1773.3
In %: 0-14 years		18.4	14.2	13.9	14.1	14.1	12.7	12.1	12.8	12.8
15-64 years		69.3	70.3	69.5	67.8	65.2	61.8	58.7	54.6	53.8
65 years and over		12.3	15.5	16.6	18.1	20.7	25.5	29.3	32.6	33.4
Index growth (2008 = 100)										
Population total		97.5	98.1	99.9	100.7	100.9	99.1	95.8	91.9	87.0
0-14 years		129.5	100.9	99.9	102.3	103.1	90.9	83.6	84.9	80.3
15-64 years		96.5	98.6	99.2	97.7	94.0	87.5	80.4	71.7	66.9
65 years and over		74.1	93.7	102.5	112.6	128.9	156.1	173.0	184.9	179.2
Source: SORS; calculations by IMAD.
age dependency ratio) also widened; however, it remains below the EU average, which was 25.2 old-age persons per 100 working-age persons in 2007.
In a few years time, the population of Slovenia is expected to start shrinking. According to the most recent Eurostat projection of population in Slovenia,9 life expectancy is foreseen to further rise, and the total fertility rate and migration coefficient are predicted to remain low. The population is expected to rise until 2019 (when it should reach 2,058,000), at which point it is likely to start declining, to reach a level of less than 1.8 million in 2060.
The ageing of the population in Slovenia has so far been slow, but it is expected to accelerate very soon. This will happen when the numerous generations born after the Second World War enter the contingent of the old-age population and the working-age population starts to shrink. According to projections, the ratio of working-age to old-age population is expected to deteriorate to 4:1 by 2013. After 2020, it should drop to less than 3:1, and after 2040 to less than 2:1. This increasingly critical ratio will not significantly improve either by higher fertility or higher migration. In Slovenia, there are limited opportunities for a higher number of births. Owing to the declining number of births over the past 25 years, and consequently a smaller number of women of reproductive age, the number of births is expected to record a further downward trend. This could only be interrupted through extremely high net migration, together with a high rise in fertility.10 But given the future situation on the labour market, migration will likely be
limited. If migration in Slovenia nevertheless remains high - given the expected declining number of working age population - the share of migrants in population will increase. According to Eurostat population projections of 2008, foreseeing an average net migration of around 3,500 persons per year, this share could increase from the present 13% to around 20% by 2050, depending on the ratio of immigrants to emigrants, as well as the evolution of other demographic components of migrants.11
Theexpecteddemographicchangescallforsystematic measures in population and employment policies as well as public finance policy. Family and employment
Figure 4: Age structure of Slovenia's population, according to basic projection, 1995-2060
165 years and over ■ 0-14 years
15-64 years (65+)/(1 5-64)
9	Published also on the SORS web pages.
10	See also Kraigher (2005)
Source: SORS; calculations by IMAD.
11 Ibid.
1500
1000
0
Social overwiew 2009	17
The way we live
policies should aim at encouraging families to have more children and removing barriers that were previously hindering this. Migration policy should regulate immigration and emigration flows, taking into account future needs on the labour market, and should cater for the social integration of migrants. It will be necessary to increase labour productivity and the competitiveness of the economy, as well as the employment rate, in particular of individuals who have met the first age-related condition for retirement (the retirement age). This would have favourable effects for financing age-related expenditures as well as the expected situation on the labour market. Keeping social-protection costs within the given limits of general government expenditures, as well as increasing the share of private insurance schemes, will help in achieving long-term sustainability of general government expenditures for pensions, health-care and long-term care. All these measures have been put forward by Slovenia's Development Strategy, as well as by the European Commission back in 2006.
2. Labour market and employment
The socio-economic position of individuals in society is significantly determined by their situation on the labour market. Labour-market movements are related to economic activity, which decelerated significantly in the first three quarters of 2008 and declined in the last quarter of 2008. The economic crisis has also started to show on the labour market, albeit with a lag. This chapter analyses employment and unemployment trends in 2000-2008. For 2009, we used the available monthly data from the Statistical Register of Employment. As the economic crisis also affects the social position of the population, we also present the changes in the number of recipients of unemployment benefits and financial social assistance, which are strongly linked to the situation on the labour market. In 2000-2008, the situation on the labour market was improving, but started to deteriorate towards the end of 2008 due to the economic crisis.
2.1 Employment
This chapter first covers the movement of the employment rate in Slovenia according to the Labour Force Survey (LFS), which provides internationally comparable data on employment and unemployment rates. However, as the Labour Force Survey is conducted quarterly in Slovenia, detailed data are usually available with a lag of more than five months after the end of the relevant quarter. To present labour force movements in Slovenia for 2007-2009, we have therefore used data on persons in employment based on the Statistical Register of Employment (SRE), which are published monthly, 45 days after the end of each month.
The employment rate was increasing in2000-2008 (age group 15-64).12 Economic growth in 2004 contributed to a sizeable increase in the employment rate, which also continued to rise in 2008, when economic growth had already slowed. In the analysed period of 2000-2008, the employment rate increased by 5.5 p.p. for men (72.7% in 2008) and by 5.8 p.p. for women (to 64.2% in 2008). Broken down by age, the employment rate increased most notably for older age groups (see Table 5). Despite the higher employment rate for the age group 55-64, where the Lisbon strategy goal is set at 50% by 2010, Slovenia still has one of the lowest employment rates of the elderly in the EU.13
Box 1: Difference between unemployment according to the Labour Force Survey and registered unemployment
In Slovenia, there are different sources of collecting statistical information on labour force. According to the Labour Force Survey (LFS), persons in employment are those who during the last week before the survey did any work for payment (in cash or kind), profit or for the family budget. The Statistical Register of Employment (SRE), in contrast, covers employed and self-employed persons who have compulsory social insurance, irrespective of whether they work full time or less than full time. Not included are persons working under copyright contracts and contracts for work/service or for direct payment, unpaid family workers, self-employed persons who do not pay social insurance, and citizens of the Republic of Slovenia working in Slovenian representations, on construction sites, etc. abroad.
The employment rate in Slovenia is above the EU average. In 2008, the employment rate of the age group 15-64 totalled 68.6%, which is above the EU-27 average (see Table 5). The employment rate of women (age group 15-64) has exceeded the EU average ever since it started to be measured, and this is likely due to the high proportion of women that had already been employed before the transition. The employment rate of men almost reached the EU average in 2008, despite the gap having been still relatively wide in 2000 (3.6 p.p.).
Only the employment rate of women increased in 2008.
In 2008, the number of employed women increased more notably (3.5%) than the number of employed men (2.4%), though in 2000-2008, the number of employed women had risen at a slower pace than the number of
12	In 2000, the European Commission set the employment rate for the age group 15-64 as an indicator of how a country realised the target of increasing employment. We have therefore analysed the employment rate for this age group. The necessary data were collected with the Labour Force Survey. The analysis is limited to 2000-2008, as by the end of November, detailed data for 2009 were only available for the first quarter of the year.
13	In 2008, only three countries posted lower employment rates for the 55-64 age group: Malta, Hungary and Poland.
Social overwiew 2009	18
The way we live
Table 5: Employment rates by age group, Slovenia, 2000-2008, in %
	15-24 years	25-49 years	50-64 years	55-64 years	15-64 years
2000	31.2	85.6	37.9	22.7	62.8
2001	30.3	86.7	40.5	25.5	63.8
2002	31.1	86.7	42.6	24.5	63.4
2003	28.6	85.6	40.9	23.5	62.6
2004	33.8	86.5	46.7	29	65.3
2005	34.1	86.3	47.4	30.7	66.0
2006	35.0	86.3	49.1	32.6	66.6
2007	37.6	87.6	49.5	33.5	67.8
2008	38.4	88.6	49.8	32.8	68.6
2000/2008 difference in p.p.	7.2	3.0	11.9	10.1	5.8
Source: Eurostat.
Figure 5: Employment rate, age group 15-64, EU-27, 2008, in %
50
to "o	£	£ •
- £0,2
X o. KD u c 3 cc	on m i= m
a £± TO £ "ö :
'(.n 3 i- ^^ ^ ^ -j
3 TO ,<2
5	c
.'I — O u CL
!2 >• £ "O £ ro s
č i= iE i= o '5 4 o 5 Q.J2 "o S
sl'CšfA
U
3
Source: Eurostat.
employed man. In 2008, the employment rate of men was even slightly lower than in 2007 (by 0.1 p.p.), which can be attributed to the fact that in 2008, the economic crisis first hit sectors that mainly employ men. The employment rate of women increased by 1.6 p.p. in 2008, which also translated into a higher total employment rate.
In the first half of2009, the employment rate was lower than in 2008. The employment rate totalled 66.7% in the first quarter of 2009, 0.4 p.p. less than in the first quarter of 2008; in the second quarter of 2009, it was 0.7 p.p. lower than in the same period of 2008.
which had started in 2007 and totalled more than 3% y-o-y, also continued in the first three quarters of 2008, but decelerated significantly in the last quarter of 2008. The number of persons in formal employment (employed and self-employed), which had been increasing to October, began to decline in November. In December, all activities posted a significant drop, mainly due to the termination of temporary employment contracts. In December 2008, the number of employed persons increased by 1.8% y-o-y, while it had still been about 3% higher in September.
The number of persons in employment also continued to decline in the first half of2009. As shown in the Table 6, the number of employed persons mainly declined in private sector activities, most notably in manufacturing (C) as a result of domestic and foreign orders, which dropped especially in the period following October
2008.	Among manufacturing sectors, in the period from June 2008 to June 2009, the number of people in employment declined most notably in the manufacture of metal products except machinery and equipment, and in the manufacture of electrical appliances. The latter would have seen an even more dramatic drop in employment, had it not been for the interventive act on partial subsidising of full-time work adopted in January
2009.	Based on the applications filed for this subsidy, more than 50% of persons employed in the manufacture of electrical appliances started to work shorter hours in March-September 2009.
Figure 6: Number of formally employed foreigners in Slovenia, 30 June 2007-30 September 2009
80,000 70,000
60,000
50,000
20,000
70,327
68,296
65,776 65,415
Source: SORS.
Note: Data are provisional.
10,000
0
After growing rapidly in 2007 and in the first three quarters of 2008, employment started to decline in the last quarter of2008.14 Strong employment growth,
14 In the following paragraphs, we show the movement of
the number of employed persons according to the Statistical Register of Employment, which provides monthly data on people in employment, reflecting the impact of the economic crisis on the labour market.
Social overwiew 2009	19
The way we live
Table 6: Growth of the number of employed persons by activity,1 Slovenia, 2007-2009, in %
	2007	2008	I-VI 2009 / I-VI 2008
TOTAL	3.5	2.9	-1.2
A Agriculture, forestry and fishing	7.1	-1.8	-6.0
B Mining	-5.0	-5.2	-7.5
C Manufacturing	0.9	-0.5	-8.3
D Electricity, gas, steam and air-conditioning supply	0.7	-1.1	2.5
E Water supply, sewerage, waste-management and remediation activities	4.7	4.7	2.7
F Construction	12.9	12.2	3.1
G Wholesale and retail trade, repair of motor vehicles and motorcycles	3.4	3.5	0.1
H Transportation and storage	5.3	5.4	-0.9
I Accommodation and food service activities	3.7	1.7	1.3
J Information and communication	6.3	4.8	4.2
K Financial and insurance activities	3.4	4.2	2.9
L Real estate activities	8.6	9.6	7.4
M Professional, scientific and technical activities	6.4	7.1	5.3
N Administrative and support-service activities	8.7	5.2	-0.9
O Public administration and defence, compulsory social security	-0.3	1.3	0.9
P Education	0.7	1.5	2.7
Q Human health and social-work activities	0.8	2.7	2.3
R Arts, entertainment and recreation	4.1	6.5	1.9
S Other service activities	1.8	1.3	4.5
T Activities of households as employers	0.8	6.4	10.2
Source: SORS; calculations by IMAD. Note: 1SKD 2008.
The number of foreign workers in Slovenia increased significantly in 2007, but started to decline towards
the end of 2008. As a result of imbalances on the labour market and the high demand for labour, the rapid increase in the number of employed persons in 2007 and 2008 was also accompanied by increased hiring of foreigners. Data on the number of formally employed foreigners according to the Statistical Register of Employment show that in the second half of 2007 and first three quarters of 2008, the total number of persons in employment rose particularly due to increased employment of foreigners. As with the total number of persons in employment, the number of employed foreigners also started to decline in the
last quarter of 2008. In Slovenia, the share of formally employed foreigners in the total number of persons in employment has hovered between 6% and 8% in the last two years.
Figure 7: Mean response to whether immigration is good or bad for the economy, selected European countries, 2006
lï J| :
Ç -u -U a. JU JS
7
6
5
4
3
2
0
Box2: Opinion of respondents in selected European countries on whether immigration is good or bad for the economy
In the European Social Survey conducted in 2006 in 25 countries, respondents were, among other questions, asked whether they considered immigration to be good or bad for the economy. They were able to choose values between 0 (bad) and 10 (good). As shown in the figure, Slovenia is ranked among the countries, where respondent tended to agree that immigration was bad for the economy (complete answers to this question were only available for 23 countries).
20	Social overwiew 2009
The way we live
2.2 Unemployment
The unemployment rate declined in 2000-2008 according to both methodologies of measurement.15
The unemployment rate according to the Labour Force Survey declined from 7% in 2000 to 4.4% in 2008. Similar trends were also recorded for the rate of registered unemployment, the movement of which is presented in the following sections because of the availability of monthly data and a smaller delay in data release. However, these data only allow for analysis of unemployment rates by gender and number.
2.2.1 Movement of registered unemployment
The number of unemployed persons declined in 2000-2008, hitting its lowest level in September 2008, but starting to rise in the last quarter of 2008.
The number of unemployed persons started to decline more rapidly in 2004, which saw accelerated economic growth and increased employment. Even though the number of people registered as unemployed started to grow in October 2008, the average annual number of the registered unemployed declined by 11.4% in 2008 compared with 2007. Reflecting the impact of the economic crisis, the number of registered unemployed
Figure 8: Average number of people registered as unemployed, Slovenia, 2000-2008, in '000
101.9 102.6
15 Unemployment is measured according to two methodologies in Slovenia. One takes account of the number of the registered unemployed (unemployed people registered at the Employment Service of Slovenia). The other methodology relies on the Labour Force Survey (LFS), which provides internationally comparable data on the work activity of the population. According to the LFS, unemployed persons are those who during the last week prior to the interview had no employment, were not self-employed and did no work for payment, but were actively looking for work (having taken specific steps in the past four weeks to seek paid employment or self employment), and were available to start work immediately (within two weeks).
persons started to increase in the last quarter of 2008, reaching 95,446 by the end of November 2009, which is up 50.6% from November 2008.
The unemployment rate also declined in 2000-2008.
The average annual registered employment rate declined from 11.8% to 6.7% in 2000-2008. In the analysed period, the registered unemployment rate for women was higher than the registered unemployment rate for men. The gender gap, which had been widening up to 2006, narrowed in 2007 and 2008. Table 7 shows higher registered unemployment rates for women than for men in the entire period of 2000-2008, though the gap has been narrowing since 2006. Given that the economic crisis hit hardest those activities that mainly employ men, the above-mentioned trends also continued in 2009, while the share of women among the registered unemployed had already dropped below 50% in February 2009.
Table 7: Registered unemployment rates, total and by gender, Slovenia, 2000-2008, in %
	Men	Women	Total
2000	10.6	13.1	11.8
2001	10.1	12.6	11.2
2002	10.0	12.7	11.3
2003	9.4	12.6	10.9
2004	8.8	12.1	10.3
2005	8.6	12.1	10.2
2006	7.7	11.5	9.4
2007	6.2	9.6	7.7
2008	5.6	8.1	6.7
Figure 9: Unemployment rate, by gender, Slovenia, January 2007-July 2009, in %
Source: SORS, Labour Force Survey; calculations by IMAD.
120
106.6
100
11
10
9
0
8
7
6
5
4
Social overwiew 2009	21
The way we live
2.2.2 Regional dimension of registered unemployment
The long-term downward trend in the registered unemployment rate continued also at the level of regions, though this was interrupted by the economic crisis at the end of 2008. Movements on the labour market since 2000 and up to the last quarter of 2008 show that the number of persons in employment as well as the number of jobs16 more or less increased in all regions, while the number of unemployed people declined. The registered unemployment rate declined in 2008 relative to 2000 in all regions, most notably in the Podravska region (by 9 p.p.). The number of persons in employment rose in all regions (most notably in the Notranjsko-kraška region) and in most regions the number of jobs also rose (the most in Osrednjeslovenska region). The financial and economic crisis, coupled with a strong seasonal impact in the third quarter, brought about a significant change at the end of 2008. Most regions saw the lowest registered unemployment rates in September 2008, but these rates started to increase as early as October in all regions and have been growing steadily ever since. In the first six months of 2009, the greatest y-o-y increase was posted in the Koroška region (3.1 p.p.; Slovenian average 1.7 p.p.). Above-average unemployment growth was also observed in regions that had been characterised by low unemployment rates in the past (the Gorenjska and Goriška regions, Jugovzhodna Slovenija). With all regions posting higher registered unemployment rates, regional disparities in registered unemployment started to narrow.
The structure of unemployed persons also changed, as individual groups of the unemployed were differently affected by unemployment. The number of the unemployed is growing due to a rising number of unemployed persons who lost their jobs for business reasons or whose fixed-term employment contracts were not renewed, as well as due to lower recruitment. Owing to a higher number of dismissed workers, the structure of job seekers by region also started to change. In the first half of 2009, y-o-y unemployment growth was higher for men than for women, as the economic crisis mainly affected activities that predominantly employ men. In most regions, men account for more than half of all unemployed people. In the first half of 2009, the share of unemployed men was largest in the Goriška region (54.3), while the Koroška region posted the highest y-o-y growth, with the number of unemployed men having increased by two thirds, which is nearly twice as much as the Slovenian average. Young people and people with lower levels of education are also more vulnerable to unemployment. The number of unemployed people aged 30 and younger is highest in the Koroška region (35.3% of all the unemployed) and has increased most notably in the Gorenjska region (nearly 80%). Unemployed people with education levels I and II account for 40% of all the unemployed, on average; in Jugovzhodna Slovenija and Pomurska region, they represent more than half of all unemployed persons in the region (52.6% and 50.4%, respectively). This category of unemployed persons increased most notably in the Gorenjska region (by 63.1%). The share of long-term unemployed persons declined y-o-y as a result of the inflow of other groups
Table 8: Registered unemployment rates by region, 2000-2009 (I-VI), in %
											Change in p.p.1	
Regions	2000	2001	2002	2003	2004	2005	2006	2007	2008	2009 (I-VI)	20002009 (I-VI)	2008 (I-VI) -2009 (I-VI)
Slovenia	11.8	11.2	11.3	10.9	10.3	10.2	9.4	7.7	6.7	8.5	-3.2	1.7
Osrednjeslovenska	8.8	8.0	7.7	7.5	7.5	7.6	7.2	5.9	5.0	6.3	-2.5	1.1
Obalno-kraška	8.8	8.7	8.3	8.0	7.9	7.5	7.2	6.3	5.2	6.6	-2.3	1.1
Gorenjska	9.7	8.7	8.2	8.0	7.6	7.3	6.4	4.9	4.4	6.5	-3.2	2.2
Goriška	5.9	5.6	6.1	6.3	6.7	6.5	6.2	4.9	4.3	6.4	0.4	2.1
Savinjska	13.1	13.1	13.6	13.1	12.5	12.7	11.6	9.4	8.0	9.7	-3.4	1.6
Jugovzhodna Slovenija	10.4	9.6	9.7	8.4	8.2	8.8	8.6	7.0	6.3	8.4	-2.0	2.1
Pomurska	16.7	16.3	17.7	17.6	16.8	17.1	15.7	13.4	12.2	14.6	-2.1	2.1
Notranjsko-kraška	10.4	9.4	8.8	8.6	8.1	7.9	7.0	5.4	4.9	6.6	-3.8	1.6
Podravska	18.1	17.4	17.1	15.8	14.2	13.5	12.7	10.4	9.1	11.3	-6.9	2.0
Koroška	9.9	9.9	11.3	12.2	11.4	10.6	10.1	8.1	7.3	10.3	0.3	3.1
Spodnjeposavska	13.4	13.9	14.1	14.6	12.7	11.5	10.5	8.9	7.7	9.4	-4.0	1.5
Zasavska	14.9	14.3	14.8	15.6	14.4	13.8	12.0	9.7	8.2	10.2	-4.7	1.9
Source: SORS; calculations by IMAD.
Note: 1Due to rounding, figures may not add to total shown.
16 Persons in employment by regions of employment.
Social overwiew 2009	22
The way we live
Map 1: Registered unemployment rates by region, 2009 (I-VI), in %
Table 9: Shares of selected groups of registered unemployed persons by region, 2009 (I-VI), in %
Statistical region	Young people (aged 30 or younger)	Education levels I and II	Tertiary education	Women	Men	Over 40	Over 50	Long-term unemployed
Slovenia	28.3	40.1	9.6	49.5	50.5	51.6	30.8	38.0
Osrednjeslovenska	23.3	36.6	14.1	47.0	53.0	55.5	34.7	39.5
Obalno-kraška	24.1	38.0	11.9	46.4	53.6	56.4	36.7	33.3
Gorenjska	25.3	42.2	9.1	49.7	50.3	55.4	35.2	24.5
Goriška	28.0	38.8	12.1	45.7	54.3	50.7	31.8	31.8
Savinjska	32.2	37.5	8.0	51.7	48.3	47.6	27.9	39.0
Jugovzhodna Slovenija	30.2	52.6	7.7	50.5	49.5	49.9	28.3	41.3
Pomurska	28.5	50.4	6.6	49.2	50.8	52.9	31.7	45.5
Notranjsko-kraška	29.8	42.1	10.5	46.5	53.5	52.3	33.0	30.9
Podravska	29.7	35.6	8.6	51.3	48.7	50.1	28.2	38.3
Koroška	35.3	35.7	9.8	51.1	48.9	44.5	23.0	35.3
Spodnjeposavska	25.5	44.0	8.5	50.2	49.8	55.0	33.6	46.1
Zasavska	34.0	41.3	5.6	50.6	49.4	46.3	25.4	37.5
Source: ESS; calculations by IMAD.
of unemployed persons into unemployment (from 51.8% in the first half of the year to 38% in the first half of 2009). This is also the only group where the number of unemployed people declined in this period. With unemployment predicted to see further growth, the number of long-term unemployed people is expected to increase yet again at the end of the year.
Broken down by reasons for unemployment, the number of those who lost their jobs due to the termination of their fixed-term employment contracts is rising, most notably in the Goriška region (nearly 90%), while the Koroška region has the highest share of this category of unemployed persons in all unemployed persons (43.6%). The number of permanently redundant workers is also
Social overwiew 2009	23
The way we live
Table 10: Unemployed persons by reason (% of all employed persons), by region, 2009 (I-VI), in %
Statistical region	Redundant due to bankruptcy of employer	First-time job-seekers	Expiry of fixed-term contracts	Permanently redundant
Slovenia	6.6	14.2	36.7	19.0
Osrednjeslovenska	6.7	13.7	33.0	23.5
Obalno-kraška	10.5	10.1	32.5	20.6
Gorenjska	7.7	8.4	39.1	22.4
Goriška	8.5	11.1	39.4	22.5
Savinjska	6.7	14.1	36.6	18.7
Jugovzhodna Slovenija	5.0	18.9	33.8	18.4
Pomurska	6.5	17.6	31.4	13.0
Notranjsko-kraška	4.7	11.2	41.1	24.7
Podravska	6.1	15.5	41.6	15.4
Koroška	6.1	13.6	43.6	18.4
Spodnjeposavska	5.5	12.7	36.3	18.5
Zasavska	4.0	13.5	35.1	21.5
Source: ESS; calculations by IMAD.
rising - particularly in the Gorenjska region (almost by 80%) and in the Notranjsko-kraška region, where it is highest (around 25% of all unemployed people). The number of people losing jobs as a result of bankruptcies is also growing. In the Gorenjska region, the share of this group of the unemployed increased by as much as 184.8% in one year. The highest share of these unemployed persons was posted in the Obalno-kraška region (10.5%).
2.3 Impact of labour market conditions on the number of social benefit recipients
In a period of unemployment, income security of unemployed people is provided by unemployment insurance schemes and the right to financial social assistance. In Slovenia, social security of unemployed people should be ensured by unemployment benefits, but the conditions to qualify for the rights from unemployment insurance are relatively strict. According to Skledar (2009), the duration of entitlement to these rights is shorter in Slovenia than in most other EU countries, particularly for shorter periods of insurance. Individuals qualify for financial social assistance if they do not have sufficient resources to support themselves. Eligibility for financial social assistance is thus closely linked to the situation on the labour market. Financial social assistance is intended to provide the basic means of subsistence in a period when beneficiaries cannot earn their own living in any other way.
In 2000-2008, the movements of recipients of unemployment benefits and financial unemployment assistance were directly linked to the movement
of registered unemployment. In 2000-2008, when unemployment gradually declined, the number of unemployment benefit recipients was falling, dropping by around one half (from 27,264 to 14,166). The share of recipients of unemployment benefits in the total number of registered unemployed declined to 22.4% in 2008, down from 25.6% in 2000. The number of recipients of financial unemployment assistance paid by the Employment Service of Slovenia was, in contrast, rising constantly until 2005, when it started to decline at a rapid pace due to the above-mentioned regulatory change (from 6,201 in 2005 to a mere 200 in 2008).
Figure 10: Numbers of recipients of unemployment benefits (UB), financial unemployment assistance (FUA) and persons registered as unemployed, Slovenia, 2000-2008
■	Recipients of unemployment benefits (UB)
■	Recipients of financial unemploymentassistance (FUA)
■	Persons registered as unemployed
0
2000 2001 2002 2003 2004 2005 2006 2007 2008 Source: MLFSA, ESS.
100,000
80,000
Social overwiew 2009	24
The way we live
Box 3: Unemployment benefits and financial social assistance
Eligibility for unemployment benefit is regulated by the Employment and Insurance against Unemployment Act. In the time since Slovenia gained independence, eligibility criteria have been tightened twice: in 1998, by reducing the period of receiving unemployment benefits, and in 2006, by imposition of tighter conditions regarding the obligation to accept work. The Act stipulates that the right to unemployment benefit may be claimed by an insured person who was employed with one of more employers for at least 12 months during the last 18 months prior to the termination of the employment contract. This condition makes access to unemployment benefits harder for unemployed persons who were on fixed-term contracts with several and/or long job interruptions and is particularly tough on young people, who often hold fixed-term jobs. The basis for the assessment of unemployment benefit is the average monthly wage earned by the insured person in the 12 months prior to unemployment. The unemployment benefit totals 70% of the assessment basis for the first three months and 60% for subsequent months. The duration of the right depends on how long the person was insured (on the length of time worked) and can range from 3 months (for insurance of 1 to 5 years) to 24 months (for insured persons older than 55 or with more than 25 years of insurance). In 2006, the right to financial unemployment assistance was abolished, and the number of recipients of this assistance is therefore dropping rapidly. Until 2006, the right to financial unemployment assistance was also governed by the aforementioned Act, but this was abolished with an amendment adopted in 2006 to be combined with the right to financial social assistance, which can be claimed at social work centres. People who had been entitled to financial unemployment assistance before the changes came into force keep it until expiry of the term for which it had been granted.
People with no income or with earnings below the minimum specified income receive financial social assistance for the difference between their own income and the minimum specified income. According to the Social Security Act, financial social assistance is granted to citizens of the Republic of Slovenia with permanent residence in Slovenia and foreigners with a permit for permanent residence in Slovenia, on condition that they cannot provide means in the amount of the minimum income for themselves and their family members for reasons which were or are beyond their control.
Until September 2008, the number of unemployment benefit recipients recorded a declining trend (13,604 recipients or 22.9% of unemployed people), but has been rising gradually since October. It started to increase more notably in December 2008, when it totalled as much as 16,666, mounting to 28,684 by June 2009. The share of unemployment-benefit recipients among unemployed people is growing as well, having already climbed to 33.1% by June 2009 (the highest level since the change of law in 2006), after which time it slightly declined (to 32.0% in September).18
The number of unemployment benefit recipients increased in all regions in the first half of2009. I n y-o-y terms, the number of unemployment benefit recipients increased most notably in the Goriška region (by 144.1%) in the first half of 2009, while in the Gorenjska region, nearly half of all unemployed people qualified for unemployment benefits in this period, which is the largest figure among the statistical regions.
Tightening conditions on the labour market are also reflected in a higher number of recipients of financial social assistance. After September 2008, which saw the lowest number of recipients (37,799) since the new system became fully effective, this number started to rise, which in the autumn and winter months can be attributed to seasonal impacts. In 2009, however, it also continued to rise in the spring, when it had already started to fall as a result of seasonal factors in previous years. In January and February 2009, the number of financial
social-assistance recipients was still lower than in the same months of 2008, but in March 2009 it increased
18 In 2008 as a whole, this share totalled 22.4%.
Thenumberofunemployment-benefitrecipientsstarted to rise rapidly towards the end of 2008. The increase in the number of unemployment-benefit recipients is likely a result of the increased unemployment exposure of elderly people,17 who qualify for a longer period of receiving unemployment benefits according to the law.
Figure 11: Shares of recipients of unemployment benefits (UB) and financial unemployment assistance (FUA) in the total number of the registered unemployed, Slovenia, 2008-2009, in %
40
UB+FUA as a % of unemployed -2008 ■ UB+FUA as a % of unemployed -2009
Source: ESS; calculations by IMAD.
17 Unemployment exposure is measured as the ratio of the inflow into unemployment of unemployed persons in the age group over 50 to the number of employed persons in the same age group. See IMAD, Economic Issues 2009.
1 5
10
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Social overwiew 2009	25
The way we live
Figure 12: Share of unemployment benefit recipients in the total registered unemployed by region, 2008 (I-VI) and 2009 (I-VI), in %
Source: ESS; calculations by IMAD.
slightly relative to March 2008 (by 1.9%). According to the latest data for October 2009, as many as 49,404 persons received financial social assistance in October, 27.9 % more than in October 2008. In 2009, there was none of the usual seasonal decline in the number of financial social-assistance (FSA) recipients in the summer. The number of recipients is increasing mainly due to a higher number of unemployed persons, and in part also as a result of the lower earnings of the employed. In June 2009, the number of financial social assistance recipients who receive unemployment benefits was 173% higher than in December 2008. The share of financial social-assistance recipients who are employed is still relatively low (below 3%).
Figure 13: Number of recipients of financial social assistance by month, Slovenia, January 2007-0ctober 2009
53,000 51,000 49,000 47,000
£ 45,000 =j
43,000 41,000 39,000 37,000 35,000
c
Source: MLFSA.
The number of financial social-assistance recipients is increasing in all regions. The number of financial social-assistance recipients increased most notably in the Koroška region (by 37% y-o-y in June) and in the Goriška region (by 35%). As shown in Figure 14, the share of financial social-assistance recipients in the total population of the region was greatest in the Pomurska region, where unemployment surged in the last quarter of 2009.
Figure 14: Number of financial social-assistance recipients as a share of total population in the region, June 2008 and June 2009, in %
Source: MLFSA, SORS; calculations by IMAD.
2.4 Labour-policy measures in response to the crisis
The Government reacted to deteriorating labour-market conditions through labour market policy measures. It boosted implementation of active employment-policy measures, which include counselling and assistance in employment, training and education, encouraging employment and self-employment and programmes to promote social inclusion. The Government adopted two interventive acts, mainly aimed at preserving jobs. Based on the data on people included in both schemes at the end of November, we estimate that these schemes helped to preserve 28,000 jobs, though in certain sectors, they only postponed urgently needed restructuring.
January 2009 saw adoption of the Partial Subsidising of Full-time Work Act regulating subsidies for work time shortening to 36 or 32 hours per week. Enterprises are eligible for a subsidy of EUR 60-120 per month per employee included in the short-time working scheme. The Act does not define any criteria to tie eligibility for subsidies to the crisis. With an amendment to the Act adopted in the middle of July 2009, the period for
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Social overwiew 2009	26
The way we live
receiving subsidies was extended for another six months (12 months in total) and the deadline for enterprises to apply for subsidies shifted from 30 September 2009 to 31 March 2010. By the end of November 2009, 846 enterprises with 64,729 employees were included in the scheme, which is 7.5% of employed persons in September.
At the end of May, the government adopted the Partial Reimbursement of Payment Compensation Act, regulating partial reimbursement of wage compensations for employees on temporary layoff ("on waiting" at home). This is the second interventive act aimed at preserving jobs. An employer may place a maximum of 50% of its workers on temporary layoff, while paying them wage compensations in the amount of 85% of their average earnings in the last three months, with 50% of the compensation refunded to the employer by the state. Workers on temporary layoff have the right and obligation to spend 20% of their time on training. Training programmes must be provided by the employer, but are co-financed by the state in the amount of EUR 500 per employee. By the end of November 2009, the Employment Service of Slovenia (ESS) had signed contracts with 408 enterprises to include 14,541 employees in the scheme, which accounts for around 1.7% of people in employment in September. In the first three months, enterprises were much less interested in this than in the short-time working scheme.
The number of unemployed persons included in active labour-market policy programmes increased significantly in 2009, particularly in programmes promoting employment and self-employment. Since 2007, active labour-market policy (ALMP) in Slovenia has
comprised four groups of programmes. The active labour-market policy programme for 2007-2013, which set up new guidelines for ALMP, includes four main programme groups: (i) counselling and assistance in job searching, (ii) training and education, (iii) promotion of employment and self-employment, and (iv) programmes to boost social inclusion. Programmes have also been implemented according to this scheme during the economic crisis. In the first eleven months of 2009, the number of people included in ALMP programmes increased more than the number of registered unemployed people; what is not encouraging in terms of the exit strategy from the crisis is that the smallest increase was posted for the number of people included in education and training programmes (see Table 11). From the aspect of the crisis as an opportunity to gain new knowledge, the share of people participating in education and training programmes is much too low. By October, more than 12,000 persons found work through ALMP programmes leading to immediate transition into employment, which is nearly a third of all unemployed people who landed jobs in that period.
In 2010, labour-market policy is faced with challenges in the field of education and training of unemployed and employed people in a time of crisis and the need for transformation of the measures to preserve jobs. As it is
sensible to use the economic crisis for building new skills, it is necessary to increase the number of unemployed and employed people participating in education and training programmes that will enhance their employability. With no rapid improvement expected on the labour market yet, it is necessary to rethink the measures aimed at preserving jobs, which should be temporary and intended to help enterprises to weather the crisis.
Table 11: Participation of unemployed persons in active labour-market policy programmes (ALMP), Slovenia, January-November 2008 to January-November 2009
	Number of unemployed persons included in ALMP programmes		Growth index (I-XI 2008/I-XI 2009)
	I-XI 2008	I-XI 2009	
TOTAL	26,111	48,032	184.0
Counselling and assistance in job search	5,052	9,686	191.7
1.2 Assistance in job search	4,899	9,219	188.2
Training and education	11,676	19,156	164.1
2.1 Institutional education and NVQ programmes1	4,376	8,774	200.5
2.2 Practical training programmes	5,239	7,120	135.9
2.3 Education programmes	2,061	3,262	158.3
Promotion of employment and self-employment	4,873	14,633	300.3
3.1 Promotion of employment	3,962	10,801	272.6
3.2 Subsidies for employing unemployed persons with low employment prospects	911	2,573	282.4
3.4 Promoting flexibility of labour force and enterprises	-	1,259	-
Programmes promoting social inclusion	4,510	4,557	101.0
4.1. Promoting social inclusion of labour force	4,510	4,557	101.0
Source: ESS.
Note: 'National vocational qualification.
Social overwiew 2009	27
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3. Household income and expenditure
Data on household income and expenditure show the basic level of welfare and the capacity to satisfy needs. Disposable income of the population shows the material welfare of the population in a society, trends in consumption and borrowing, and changing patterns of spending. These patterns are changing due to the changing needs of households resulting from their lifestyle and economic and social development. For the standard of living of the population, wages are the main source of livelihood in addition to employment. Real wage growth is that which provides to the greatest extent an increase in living standards. The distribution of wages as a primary source is also important since a more even distribution provides improvement of living standards to a higher share of the population. This is shown by indicators that define the degree of inequality. Higher income and prosperity allow households to purchase higher quality food and to improve living conditions, which contributes to higher care for health and better health status, while greater expenditure on goods and services such as recreation and culture and education enable households more quality leisure time and the constant acquisition of new skills and experience. Most of the income of households in Slovenia is made up of wages and other receipts from employment. The distribution of employees by wages, for which differences increased in the 2000-2008 period, affects the increase in differences between consumption quintiles.
3.1 Disposable income and household expenditure
As regards average disposable income per person,19 Slovenia is still far behind the EU average, though it has been drawing closer. In 2008, Slovenia achieved 71.6% of the EU-27 average income per person. Since 2000, Slovenia has improved by 22 p.p against the EU-27 average.
The structure of disposable income20 shows that Slovenian households earn more income from employment and less from property than households in the EU-27 on average. Household disposable income is calculated by subtracting from gross income (so-called resources; see note under Figure 15) taxes, contributions and other transfers and some payments (so-called uses). The largest category of disposable income is
compensation of employees, followed by gross operating surplus and mixed income (income of individual private entrepreneurs and farmers, and income from dwelling activities of households) and social benefits. The largest category on the side of consumption is social contributions, followed by current taxes on income and wealth. On both the resources and uses sides, there are two categories: property income (payable and receivable) and other current transfers (e.g. insurance claims received and insurance premiums paid, fees and charges, etc.). In Slovenia, the share of compensation of employees in disposable income is higher than the EU-27 average, which means that households in Slovenia earn more income from employment and less from other sources. The difference is especially evident in the share of property income (dividends, interest, rents on land, etc.), which in 2008 represented 3.1% of household disposable income in Slovenia and on average 13.4% of household disposable income in the EU-27. In Slovenia, current taxes on income and wealth represent a lower share of disposable income, which is most probably the result of lower household wealth and differences in the systems of its taxation. The structure of household disposable income in Slovenia did not change significantly between 2000 and 2008.
Figure 15: Categories of disposable income in terms of resources and uses in share of disposable income, Slovenia and EU-27, 2008, in %
19	This is a calculation from data at current prices since data in PPS (purchasing power standard) for disposable income are not available. Therefore, this information can not be compared with information on reaching the European level of consumption (in PPS).
20	According to the System of National Accounts (SNA)
methodology, which is internationally comparable.
Source: Eurostat - National accounts; calculations by IMAD.
Note: Net values of disposable income components are shown (resource means that the component is higher on the side of resources than on the side of use); calculation from nominal data. Disposable income = (compensation of employees received + social transfers + gross operating surplus and mixed income + property income received + other current transfers received + social security contributions received) - (social contributions + tax on income and wealth + various current transfers + property income paid + other current transfers paid + compensation of employees paid + social transfers paid).
After high growth a year before, in 2008, growth in consumption slowed. In 2007, household consumption increased by 6.7% in real terms, which is the same as in 1999 when Slovenia recorded the highest growth in
Social overwiew 2009	28
The way we live
consumption to date as a result of the introduction of VAT; however, in 2007 growth was caused by favourable economic trends which increased incomes and consumer optimism. Despite high growth in recent years, household expenditure for the purchase of durable goods in real terms increased again by 17.1%. Households are also spending much more than in previous years on eating out and on holiday expenses. Because consumption increased faster than income and because loan conditions were favourable, households continued to borrow; the net value of consumer loans increased to EUR 456 million, the highest ever. In 2008, growth of both income (from 4.8% to 3.1%) and consumption (in real terms 2.1%) slowed down; especially in the second half of the year, purchases of durable goods decreased (see also the Borrowing chapter). The contribution of goods and services, which previously contributed most to growth (transport, hotels, cafes, restaurants, furniture and household equipment, and recreation and culture), was visibly reduced. For purchasing vehicles, households spent only 3.6% more than in the previous year (when they spent slightly over a fifth more) and for furniture and household equipment 2.8% less (in 2007 a tenth more, also because of increased investment in housing and the fitting out of new dwellings). In 2008, households borrowed only about a third of the consumer loans they had in 2007.
Figure 16: Reaching the European level of consumption of households and NPISH1, EU-27, 2008, in %, PPS per capita
160
140
120
js CD $ IT (u"-< !SU-13 E iE
O m £	13 2 S
aj	X
z	3 =
years and to the significant expansion of opportunities for saving (alternatives to saving in banks, which have been used abroad for many years). In 2008, 83.3% of the consumption per capita of the EU-27 (conversion from PPS) was achieved in Slovenia, which is 2.2 p.p. more than a year earlier and 5.7 p.p. more than in 2000, with both consumption and income per capita in Slovenia growing faster than the EU average.
3.2 Wages
In the2000-2008period, real gross wage peremployee22 increased on average by 2.3% per year; the growth in the private sector (2.6%) was slightly faster than the growth in the public sector23 (1.6%). In the entire period, except in 2001 and 2008, gross wages in the public sector grew more slowly than gross wages in the private sector. In 2008, the average gross wage per employee increased by 2.5%; in the private sector more slowly (2%) than in the public sector (3.9%). Negotiations on wage reform in the public sector were the reason for a very modest growth of wages in the public sector. In 2008, the new system started to be implemented, and accordingly wages in the public sector increased significantly, just at the start of the economic crisis, while the slow growth of wages in the private sector reflected the decline in economic activity. In the first eleven months of 2009, the growth of real gross wage per employee in the public
Table 12: Growth in real gross wage per employee in private and public sectors, Slovenia, 2001-2008 and Jan-Nov 2009, in %
Source: EUROSTAT - National accounts; calculations by IMAD. Note: 1Non-profit institutions serving households.
	Growth in real gross wage per employee, in %		
Year	Total	Private sector	Public sector
2001	3.2	2.3	5.1
2002	2.0	2.3	1.1
2003	1.8	2.1	1.0
2004	2.0	3.1	-0.7
2005	2.2	2.8	0.9
2006	2.2	2.8	1.0
2007	2.2	3.2	0.5
2008	2.5	2.0	3.9
I-XI 2009	2.7	1.0	6.3
2001-2008	2.3	2.6	1.6
Source: SORS, SCA 2002, for 2009 SCA 2008; calculations by IMAD.
In 2008, households in Slovenia on average spent a lower share of income than households in the EU-27.21 I n
Slovenia the share was 84.0%, 6.2 p.p. less than the EU-27 average. This could be due to relatively larger investment in housing by Slovenian households (buying a home is considered investment and not consumption) in recent
21 Propensity to consume is the ratio of consumption to disposable income.
22	The source of data on the gross wage per employee is SORS's ZAP/M survey, which covers all persons in paid employment but does not cover individual private entrepreneurs and persons employed by them, own-account workers and farmers.
23	Wages in the public sector are the sum of activities of public administration, education, health and social work, and other community, social and personal service activities, even though, especially in the latter two activities, some activities are in the private sector. According to SCA 2002, these are activities L to O.
Social overwiew 2009	29
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Table 13: Average nominal gross wage per employee by activities as % of gross wage in the private sector, private sector = 100, Slovenia, 2000-2008
Years	2000	2001	2002	2003	2004	2005	2006	2007	2008
Private sector	100.0	100.0	100.0	100.0	100.0	100.0	100.0	100.0	100.0
Agriculture	96.7	94.2	92.8	89.4	87.8	86.7	86.8	87.8	88.6
Fishing	93.6	87.7	84.5	85.1	83.8	84.5	86.5	87.3	84.1
Mining and quarrying	123.2	126.0	126.6	128.4	131.8	133.2	132.0	132.1	139.2
Manufacturing	90.9	90.7	91.0	90.9	91.2	92.4	92.5	92.3	92.1
Electricity, gas and water supply	123.5	127.0	128.6	129.2	130.8	136.8	137.0	136.1	137.5
Construction	89.9	87.9	87.3	88.0	88.3	86.9	87.5	87.2	86.9
Wholesale and retail	97.5	96.3	95.7	95.7	95.6	94.7	94.8	95.4	95.4
Hotels and restaurants	84.8	83.9	82.4	81.5	80.7	78.4	77.7	77.0	77.6
Transport	117.4	118.1	116.5	117.3	117.2	115.7	113.7	112.4	112.4
Financial intermediation	157.2	159.1	156.9	159.8	158.5	160.0	162.7	163.2	160.1
Real estate, renting and business activities	117.1	118.6	119.4	117.9	116.6	113.2	111.6	111.8	113.0
Source: SORS, SCA 2002; calculations by IMAD.
Table 14: Average nominal gross wage per employee by activities as % of gross wage in the public sector, public sector = 100, Slovenia, 2000-2008
Years	2000	2001	2002	2003	2004	2005	2006	2007	2008
Public sector	100.0	100.0	100.0	100.0	100.0	100.0	100.0	100.0	100.0
Public administration	106.1	106.1	102.0	102.9	100.5	100.8	100.5	101.5	103.8
Education	95.7	97.2	98.0	99.2	101.4	103.1	104.5	104.4	101.8
Health and social work1	97.4	96.4	99.1	98.5	97.2	95.8	95.1	94.3	96.4
Other community, social and personal service activities	106.5	104.1	99.9	98.3	101.3	98.4	97.1	97.0	94.0
Source: SORS, SCA 2002; calculations by IMAD.
Note: 1In 2002, SORS reclassified disabled persons in employment into activities in which they are employed, while prior to that all disabled persons in employment were classified into health and social work, representing about a fifth of employees in this activity. As regards their educational structure, most have basic education, which is why wages of disabled persons amounted to about 60% of average wages in the activity, so that their reclassification had a significant impact on the level of gross wages in the activity.
sector was thus about six times higher than the growth of gross wage per employee in the private sector.
Differences in the growth of wages in individual activities of the private sector are large and continue to grow. In the entire period, the lowest gross wages among private sector activities were paid in hotels and restaurants (EUR 1,018 in 2008), while gross wages in financial intermediation were the highest (EUR 2,101 in 2008), which means that they were more than twice as high as those in hotels and restaurants (2.06:1). In 2000, the gap was smaller (1.85:1). These two activities stand out as extremes in most EU Member States.
The growth of wages in public sector activities in the observed period was more even, with significantly smaller differences, which also did not increase.
Activities with the highest and lowest average gross wages were not always the same. In 2008, the highest average gross wages were paid in public administration (EUR 1,691), more than 10% higher than the lowest average gross wages in other community, social and
personal service activities (where only a third of activities are in the public sector) with EUR 1,532. In 2000, the highest gross wages were paid in other community, social and personal service activities, over 11% higher than the lowest gross wages in education. In the period until 2007, the ratio of gross wage to average wage in the public sector increased only in education, due to the annex to the collective agreement for education, which in this activity enabled a wage increase every July (of about 3%) in the 2002-2006 period. With the introduction of the new wage system in 2008, the relationships between the levels of wages in the public sector changed in favour of public administration, and health and social work.
Such large differences in average gross wages by activities are partly the result of a very different educational structure for employees by activities. In
public sector activities, the structure of employees by education is more even; most employees have tertiary or upper secondary education and only about 10% of employees have basic education. In the private sector, most employees have upper secondary education, but
Social overwiew 2009	30
The way we live
Table 15: Structure of employees by education, total, private and public sectors, Slovenia, 2000, 2002 and 2008, in %
	2000			2002			2008		
	Tertiary	Upper secondary	Basic	Tertiary	Upper secondary	Basic	Tertiary	Upper secondary	Basic
Total	18.0	59.1	22.9	19.4	59.2	21.4	23.6	57.9	18.6
Private sector	11.5	62.6	25.9	12.4	62.8	24.8	16.2	62.0	21.8
of which:									
Industry (C to F)	8.2	57.5	34.4	8.8	57.9	33.3	10.9	58.9	30.2
Manufacturing services (GHI)	9.2	75.4	15.4	9.8	75.6	14.7	13.1	73.6	13.3
Business services (JK)	31.9	53.9	14.3	33.3	53.2	13.4	38.4	49.1	12.4
Public sector (L to O)	39.6	47.4	12.9	43.4	46.9	9.7	48.2	44.1	7.7
Source: SORS, SCA 2002; calculations by IMAD.
activities differ significantly in terms of the share of employees with tertiary education. In the 2000-2008 period, the share of employees with tertiary education increased most in the public sector; from 2002 on (which is a more appropriate comparison due to statistical changes24), the share increased even more in business services.
In 2008, the average gross wage in the public sector was about 24% higher than the average gross wage in the private sector, which reflects the difference in the educational structure of employees. Education to a large extent determines the quality of the job and its valuation. In the private sector, a similar structure of employees to that in the public sector was observed in business services (J and K). In 2008, the average gross wage in Slovenia amounted to EUR 1,391; in the private sector, it was EUR 1,312 and in the public sector, EUR 1,629. Wages in industry (EUR 1,226) and manufacturing services (EUR 1,283) were at the average of the private sector, while in business services they were much higher (EUR 1,635) since employees were more educated than the average in the private sector.
The educational structure of employees has a strong impact on the distribution of employees by gross wages.25 In activities where the share of employees with basic education is high, there is a concentration
24	In 2002, SORS reclassified disabled persons in employment into activities in which they are employed, while prior to that all disabled persons in employment were classified into health and social work, representing about a fifth of employees in this activity. As regards their educational structure, most have basic education, which had an impact on the structure in both the activity and the sector.
25	SCA 2002, ZAP-STRU/L survey on persons in paid employment by amount of gross earnings, conducted once a year for September, all persons in full-time employment are taken into account, individual private entrepreneurs and persons employed by them, own-account workers and farmers are not taken into account.
of employees by gross wages at the lower end of the distribution (e.g. in industry and in manufacturing services). In 2008 (September), at the bottom of the wage distribution scale, 50% of employees in industry (C to F) received gross wages of EUR 512 (minimum wage) to EUR 1,046 and in manufacturing services to EUR 1,075. In activities with higher shares of employees with tertiary education and much lower shares of employees with basic education, the distribution of employees by gross wages is more even; this is true for business services and for the public sector. It should be mentioned that the group of business services includes the activity of real estate, renting and business activities (SCA 2002 K), which is very diverse as it includes, for example, research and development as well as cleaning of buildings. In business services, at the bottom of the wage distribution scale, 50% of employees received gross wages of EUR 512 to EUR 1,338 and in the public sector to EUR 1,527. The distribution can be clearly shown by the interdecile ratio, which measures the ratio between the first decile, the median and the ninth decile. The distribution is equal in the case of an approximately equal ratio between the median and the first decile and between the median and the ninth decile. The ratio between the ninth and the first deciles in Slovenia increased from 3.46 in 2000 to 3.66 in 2008, more on account of the increase in higher wages, since the ninth decile is drawing away from the median more than the first decile. This tendency is present in the private sector, while in the public sector the deviation from the median is reducing.
Compared to 2007, in 2008 the differences in the distribution of wages continued to increase in the private sector while in the public sector they decreased. The increase in the differences in private-sector wages is confirmed by the mentioned data on the increase in the differences among average gross wages by private-sector activities. The increase in the interdecile ratio value (ninth decile/first decile) in this period is characteristic of the groups of industry and
Social overwiew 2009	31
The way we live
Table 16: Interdecile ratio, indicator of distribution of gross wages by sectors and groups of activities, Slovenia, 2000-2008
Slovene gross wages, total
	2000	2001	2002	2003	2004	2005	2006	2007	2008
Ninth decile/first decile	3.46	3.51	3.46	3.57	3.51	3.47	3.48	3.61	3.66
median/first decile	1.70	1.72	1.71	1.72	1.69	1.67	1.69	1.73	1.73
Ninth decile/median	2.04	2.04	2.03	2.08	2.08	2.08	2.06	2.08	2.12
Private sector (A to K)									
	2000	2001	2002	2003	2004	2005	2006	2007	2008
Ninth decile/first decile	3.22	3.30	3.22	3.32	3.28	3.31	3.36	3.44	3.55
Median/first decile	1.61	1.61	1.60	1.63	1.59	1.58	1.60	1.66	1.67
Ninth decile/median	2.00	2.05	2.01	2.04	2.07	2.10	2.10	2.07	2.13
Industry (C+D+E+F)									
	2000	2001	2002	2003	2004	2005	2006	2007	2008
Ninth decile/first decile	2.97	2.97	2.94	3.06	2.98	2.95	3.00	3.14	3.17
median/first decile	1.56	1.55	1.54	1.59	1.54	1.53	1.56	1.62	1.62
Ninth decile/median	1.90	1.91	1.91	1.93	1.94	1.92	1.92	1.94	1.96
Manufacturing services (G+H+I)									
	2000	2001	2002	2003	2004	2005	2006	2007	2008
Ninth decile/first decile	3.08	3.14	3.00	3.02	2.94	3.04	3.17	3.20	3.27
median/first decile	1.59	1.59	1.57	1.57	1.53	1.51	1.55	1.60	1.61
Ninth decile/median	1.94	1.98	1.91	1.93	1.93	2.01	2.04	2.01	2.03
Business services (J+K)									
	2000	2001	2002	2003	2004	2005	2006	2007	2008
Ninth decile/first decile	4.85	4.84	4.79	4.91	4.87	4.71	4.61	4.71	4.76
median/first decile	2.13	2.13	2.09	2.13	2.10	2.04	2.02	2.06	2.08
Ninth decile/median	2.28	2.28	2.29	2.31	2.32	2.3	2.28	2.28	2.29
Public sector (L to O)									
	2000	2001	2002	2003	2004	2005	2006	2007	2008
Ninth decile/first decile	3.46	3.45	3.28	3.24	3.22	3.31	3.36	3.39	3.13
median/first decile	1.85	1.87	1.80	1.81	1.77	1.78	1.79	1.83	1.78
Ninth decile/median	1.86	1.84	1.82	1.79	1.82	1.86	1.87	1.86	1.76
Source: SORS, SCA 2002, ZAP-STRU/L survey on persons in paid employment by amount of gross earnings, conducted once a year for September; calculations by IMAD.
manufacturing services, while in the group of business services the increase was not present because here the existing value of the interdecile ratio was very high, probably due to the mentioned large diversity of the activity of real estate, renting and business activities within business services (SCA 2002 K). In public-sector activities, where the educational structure of employees is much better than in the group of business services, the value of the interdecile ratio (ninth decile/first decile) is lower because gross wages in this activity are centrally regulated. The increase in the value of the interdecile ratio in the period until 2007 is partly the result of a real increase in gross wages in education until 2006 inclusive,26 while gross wages in other activities stagnated. In 2008, data on gross wages in the public sector already took into account the effect of the first quarter of the elimination of wage disparities, which had an impact on the reduction of wage differences.
26 The annex to the collective agreement for education signed in 2002 allowed for a wage increase in this activity every July by
about 3% in the 2002-2006 period.
Figure 17: Distribution of employees by gross wages, total, private and public sectors, Slovenia, 2000 and 2008
1.7 1.6 1.5 1.4 1.3 1.2 1.1 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0
■Total 2000 - Public 2000 ■ Private 2000 Total 2008 Public 2008 Private 2008
1								
								
	A.							
" 1 /	[ * i							
	\ \ 'i 71 \i							
1	...«rl	-						
1	viy	\						
/ 1		, i__ l: 1						
1		J>\\ \						
			k—.					
								
Relative gross wage of the class expressed as % of the average current year wage
Source: SORS, SCA 2002; calculations by IMAD.
Note: Due to the comparability of both years, on the x axis, instead of the amount of wages, the ratio to the average wage was taken into account for the calculation.
Social overwiew 2009	32
The way we live
Table 17: Interdecile ratio and the share of employees with low wages, indicators of gross wage distribution, EU, 2006
	'ninth decile / first decile	'median / first decile	'ninth decile / median	Share of low wages in %
Belgium	2.5	1.4	1.8	7.0
Bulgaria	4.5	1.8	2.5	27.1
Czech Republic	3.1	1.7	1.8	16.3
Denmark	2.3	1.4	1.6	8.0
Germany	3.7	2.0	1.8	19.6
Estonia	4.1	1.9	2.1	21.5
Ireland	3.6	1.9	1.9	21.5
Greece	3.6	1.7	2.2	16.8
Spain	3.4	1.6	2.1	15.2
France	2.9	1.5	1.9	8.8
Italy	2.8	1.6	1.8	13.3
Cyprus	4.2	1.9	2.2	21.5
Latvia	6.0	2.5	2.4	30.9
Lithuania	4.6	2.1	2.2	27.7
Luxembourg	3.4	1.6	2.1	15.2
Hungary	4.5	2.0	2.3	23.5
Malta	2.5	1.5	1.6	11.2
Netherland	3.0	1.6	1.8	13.9
Austria	3.3	1.7	2.0	14.5
Poland	4.1	1.9	2.1	21.9
Portugal	5.3	1.8	3.0	20.3
Romania	5.6	2.3	2.5	26.7
Slovenia	3.3	1.7	2.0	16.4
Slovakia	3.5	1.7	2.0	17.4
Finland	2.4	1.4	1.7	6.0
Sweden	2.5	1.5	1.6	10.5
United Kingdom	3.9	1.9	2.0	21.6
Source: EUROSTAT, 2006 Structure of Earnings Survey (SES).
Note: Enterprises with 10 or more employees, SCA 2002, activities C to O excluding L.
According to survey data on the distribution of employees by gross wages for 2006,27 it is characteristic that EU Member States from Northern Europe have a value for the ratio between the ninth and first deciles of around 2.5. On the other hand, in Latvia, Portugal and Romania, the value is between 5 and 6. In as many as eleven Member Sates (including Slovenia) the value of the ratio between the ninth and first deciles is between 3 and 4.
27 SCA 2002, Eurostat survey only takes into account enterprises with 10 or more employees and does not take into account data for activities A, B and L according to SCA 2002. Therefore, it is not fully comparable with SORS's ZAP-STRU/L survey on persons in paid employment by amount of gross earnings (once a year for September), which takes into account all persons in full-time employment, but does not take into account individual private entrepreneurs and persons employed by them, own-account workers and farmers.
In recent years, the share of employees with low wages in the private sector increased. The share of employees with low wages28 is a relative indicator; it depends on the median value and thus also on how employees are distributed by gross wages. The higher the wage concentration at the lower end of the distribution, the closer the values of the lower decile and the median, which means that the share of employees with low wages is decreasing. Before 2005, with the accelerated minimum wage adjustment mechanism, the concentration at the lower end of the distribution of employees by gross wages in the private sector increased and the share of employees with low wages thus decreased (in 2005, it was 12.7%). Due to a less favourable adjustment mechanism after 2005, the minimum wage increased more slowly than the average wage in the private
28 According to the OECD methodology, these are employees who have wages the same as or lower than 66% of the median value.
Social overwiew 2009	33
The way we live
sector. Low wages close to the minimum wage were also increasing more slowly, which resulted in a bigger difference between the median and the first decile (in 2008, it was 16%). According to survey data on the distribution of employees by gross wages for 2006 in the EU, the share of employees with low wages ranged between 6% in Finland and 30.9% in Latvia. Twelve EU Member States have lower values than Slovenia, which is thus ranked around the middle.29 The figure shows a
Figure 18: Share of employees with low wages, median to first decile ratio in the private sector, Slovenia, 2000-2008
Share of employees with low wages (left axis) -Median / l.decile (right axis)
2000 2001 2002 2003 2004 2005 2006 2007 2008
Source: SORS, SCA 2002, ZAP-STRU/L survey on persons in paid employment by amount of gross earnings (once a year for September); calculations by IMAD.
29 Data on the share of employees with low wages are slightly higher according to Eurostat than according to SORS, because Eurostat only takes into account enterprises with 10 or more
employees, while SORS takes into account all enterprises.
clear dependence between the share of employees with low wages and the ratio between the first decile and the median in the distribution of private-sector employees in Slovenia.
The institute of the minimum wage can have an important impact on the degree of inequality of wages determined by collective agreements. The purpose of determining the minimum wage is to provide essential security to employees so that they receive appropriate payment for working full time. In addition to determining the level of the minimum wage, social partners agree on the adjustment mechanism, which is not necessarily the same as for the starting and basic wage according to collective agreements. Since the minimum wage was adjusted twice in 2008, it maintained the ratio to the average gross wage in the private sector from the previous year. Before 2003, the minimum wage adjustment percentage was higher than the inflation rate by real GDP growth, which is why the ratio to the average gross wage in the private sector was constantly increasing, since the minimum wage was increasing faster than the average wage. In the next two years, the minimum wage adjustment was slightly higher than the inflation rate and higher than the adjustment by collective agreements for the private sector, so that the gap between the minimum wage and the average wage continued to decrease, but more slowly than in previous years. Since 2006, the minimum wage, as per the Minimum Wage Act, has been adjusted with the inflation rate used as the basis for preparing the state budget and there was no safeguard in case of a more rapid increase in inflation than that taken into account in the adjustment. In 2006, the minimum wage lagged behind the nominal growth of gross wages in the private sector by more than 2 p.p. and in 2007 by almost 4.5 p.p. In 2007, the minimum wage even decreased in real terms by more than 1%. Due to such trends in the minimum wage, the ratio to the average wage also
Table 18: Minimum gross wage, average gross wage in the private sector and the ratio of minimum wage to average gross wage in the private sector, Slovenia, 2000-2008
	Minimum wage	Nominal growth of minimum wage, in %	Real growth of minimum wage, in %	Average gross wage in the private sector	Nominal growth of gross wage in the private sector, in %	Real growth of gross wage in the private sector, in %	Ratio of minimum wage to average wage
2000	322	-	-	741	-	-	43.5
2001	366	13.5	4.7	822	10.9	2.3	44.5
2002	408	11.5	3.7	904	10.0	2.3	45.1
2003	445	9.0	3.2	969	7.1	1.4	45.9
2004	476	7.0	3.3	1.035	6.8	3.1	46.0
2005	499	4.9	2.3	1.080	5.4	2.8	46.2
2006	516	3.3	0.8	1.138	5.4	2.8	45.3
2007	529	2.5	-1.1	1.217	6.9	3.2	43.5
2008	571	8.0	2.2	1.312	7.8	2.0	43.5
Source: SORS, SCA 2002; calculations by IMAD.
Note: From 2005 on, more wage recipients are covered because employers with one or two employees are also taken il
17
1.70
6
1.68
15
1.66
4
1.64
3
1.62
12
1.60
1
1.58
10
1.56
9
1.54
Social overwiew 2009	34
The way we live
decreased significantly; in both years by almost 3 p.p. Therefore, in 2008 the minimum wage was adjusted twice (in March and in August). In 2009, the minimum wage was adjusted in August by 1.4% and in 2009 on average increased by 3.7% over 2008. Because the minimum wage was adjusted twice, the achieved level of minimum wage at the end of 2008 contributed 3.1 p.p. to the average growth in 2009, while the adjustment in August on average contributed 0.6 p.p. On the basis of the estimates of trends in private sector wages, by the end of the year the ratio of minimum wage to average gross wage in the private sector should slightly improve, reaching around 44%.
As regards the indicator of the ratio of minimum wage to average wage in the private sector, Slovenia belongs in the upper half of EU Member States, which have ratios higher than 40%.
Figure 19: Ratio of minimum wage to average wage in the private sector, EU Member States in which minimum wage is paid, 2007, in %
55
III	
	
Source: EUROSTAT, SCA 2002, activities C to K.
Note: Data for Estonia are for 2006. No data for Belgium and Greece.
3.3 Pensions
The number of pensioners is growing faster than the number of insured persons30 who contribute to the pension fund, so in 2008 the ratio was 1.71 insured persons per pensioner. In 2008, there were 527,933 beneficiaries of all types of pensions from compulsory pension insurance (old-age, disability, survivor's and widower's) and 904,667 insured persons. In the 20002008 period, the number of pensioners was growing on
30 The majority (around 95%) of insured persons are persons in employment, i.e. employed by legal persons, employed by private persons, individual private entrepreneurs and farmers. The remaining 5% are voluntary insurance holders, unemployed persons, students and other categories.
average by 1.5% per year, while the number of insured persons was growing at an average annual rate of 1%. The insured-to-pensioners ratio decreased from 1.8 in 2000 to 1.7 in 2008. In the period between 1992 and 1999, the number of all types of pensioners was growing slightly more slowly at an average annual rate of 1.3%, while the number of insured persons was growing by about 0.8% per year, so that in this period, too, the ratio was decreasing; it was only higher because not all insured persons were taken into account.31
Figure 20: The number of ensured persons and pensioners, and the ensured-persons-to-pensioners ratio, Slovenia, 1992-2008
All pensioners
I Ratio (right axis)
1,000 900
200 100
2.00 1.95 1.90 1.85 1.80 1.75 1.70 1.65 1.60 1.55 1.50
Source: Pension and Disability Insurance Institute of Slovenia.
In the 2000-2008 period, the insured-persons-to-pensioners ratio went down in the first half and started to grow in the second half. Before 2006, the number of pensioners was growing more rapidly than the number of insured persons, which is why the insured-persons-to-pensioners ratio was decreasing (in 2000 1.8 and in 2006 1.67 insured persons per pensioner). In the last two years, due to more rapid employment as a result of favourable economic trends, the ratio slightly increased in favour of the insured and in 2008 reached 1.71. In the first ten months of 2009, the number of pensioners increased by 1.9%, while, due to the economic crisis, the number of insured persons dropped significantly, so the ratio is again decreasing.
Trends in the number of beneficiaries differ by types of pensions from compulsory insurance. In the 2000-2008 period, the number of old-age pensioners was growing at
31 The source of data for employed and self-employed persons is SORS. To obtain these data, in 2005 SORS started using the Statistical Register of Employment (SRE). With a different source the number of persons increased by about 25,000. On the basis of SORS's calculations of persons employed by legal persons, SORS showed data from the new source from 2000 onwards. Comparisons for the period before 2000 are possible only on the basis of old data and only a relative presentation of the insured-persons-to-pensioners ratio is possible.
Social overwiew 2009	35
The way we live
Table 19: Growth rates of the number of pensioners by types of pensions, 2000-2008, Slovenia, in %
	Old-age	Disability	Survivor's	Widower's	Total
2000	2.1	0.4	0.4	-	1.6
2001	2.1	-0.1	-3.1	596.4	1.5
2002	2.6	-0.1	-3.1	101.1	2.0
2003	2.4	-0.2	-3.5	43.2	1.7
2004	2.0	-0.9	-3.5	26.3	1.2
2005	2.2	0.1	-3.7	19.0	1.4
2006	2.4	-0.6	-4.8	13.0	1.2
2007	3.1	-1.7	-5.9	14.8	1.5
2008	3.1	-1.2	-4.5	11.6	1.8
20002008	2.4	-0.5	-3.5	103.2	1.5
Source: Pension and Disability Insurance Institute of Slovenia.
an average annual rate of 2.5%. A gradual upward trend is characteristic; in 2008, the number of old-age pensioners increased by 3.1% whereas in 2000, the growth rate over the previous year was 2.1%. The number of disability and survivor's pensioners is falling, while the number of widower's pensioners is growing. In 2000, widower's pensioners were separated from survivor's pensioners; because of the gradual transition, by 2003 the trend in this type of pensions is not comparable. Since 2004, the growth in numbers of this type of pensioners has been rapid, although it has recently slowed.
In the structure of beneficiaries by types of pensions from compulsory insurance, the share of old-age pensioners was increasing in the 2000-2008period. In
2008, the share of old-age pensioners was 65%, while in 2000 it was 60%, which is, of course, the consequence of the constant increase in the number of beneficiaries. In the structure of beneficiaries by types of pensions, disability pensioners and survivor's pensioners represent ever-lower shares, while beneficiaries of widower's pensions represent an ever-higher share. According
Table 20: Structure of pensioners by types of pensions, 2000-2008 and the first eleven months of 2009, Slovenia, in %
	Old-age	Disability	Survivor's	Widower's	Total
2000	60.3	20.9	18.6	0.1	100.0
2001	60.7	20.6	17.8	1.0	100.0
2002	61.0	20.2	16.9	1.9	100.0
2003	61.5	19.8	16.0	2.7	100.0
2004	62.0	19.4	15.3	3.4	100.0
2005	62.4	19.1	14.5	4.0	100.0
2006	63.1	18.8	13.6	4.4	100.0
2007	64.1	18.2	12.6	5.0	100.0
2008	65.0	17.7	11.9	5.5	100.0
I-XI 2009	65.8	17.1	11.2	5.9	100.0
Source: Pension and Disability Insurance Institute of Slovenia.
to data for the first eleven months of 2009, this trend continued.
The age of new old-age pensioners is increasing as a result of the pension reform that came into force in 2000. As regards new female pensioners, in 2000 more than half retired before reaching 54, while in 2008, the vast majority retired between 55 and 59 years of age. As regards new male pensioners, in 2000, more than half retired between 55 and 59 years of age, and in 2008, between 60 and 64 years of age. A gradual shift in the age of new pensioners had an impact on the increase in their mean age. In 2000, the mean age of new female pensioners was 56 years and 1 month and in 2008, 57 years and 7 months. In 2000, the mean age of new male pensioners was 61 years and in 2008, 61 years and 11 months. Gradual changes in the conditions for retirement, i.e. the increase in the full retirement age and extension of the period of employment for entry into retirement, had an impact on a slower growth in the number of new pensioners. In this way a long-term slowdown in decreasing the ensured-persons-to-pensioners ratio was achieved; if there had been no reform, people would retire earlier and the increase in the number of pensioners would be much greater.
Table 21: Structure of new old-age pensioners by age groups, Slovenia, 2000 and 2008, in %
	Women		Men	
	2000	2008	2000	2008
Up to 54	57.3	6.9	9.3	6.8
55 to 59	36.2	71.3	56.2	24.8
60 to 64	5.6	19.6	29.9	58.6
65 and over	0.9	2.2	4.6	9.8
Total	100	100	100	100
Source: Pension and Disability Insurance Institute of Slovenia.
In 2008, and even more in the first ten months of2009, the ratio of the net old-age pension to the net wage was increasing. A slower growth of the average net old-age pension than of the average net wage in the 2000-2007 period resulted in a decrease in the ratio of the net old-age pension to the net wage. This was partly the result of personal income tax changes between 2005 and 2007, when because of a lower burden of personal income tax rates alone, net wages increased on average by 2 p.p. However, this was not the case for pensions, because valorisation mechanisms for pension rating bases and pensions did not contain adjustment to changes in average personal income tax rates. The ratio of the net old-age pension to the net wage was decreasing in the 2000-2007 period; in 2008, it remained at the level of the previous year and in the first ten months of 2009 it increased slightly. Already by the end of 2008, and even more in 2009, the economic crisis had a powerful impact on the levelling off in growth of wages in the private sector and, with government measures in 2009, also in
Social overwiew 2009	36
The way we live
Table 22: Average nominal net old-age pensions and net wages, and the ratio between old-age, disability and survivor's pension to net wages, Slovenia, 2000-2008 and the first ten months of 2009
	Net old-age pension	Growth rates in %	Net wage	Growth rates in %	Ratio between net old-age pension and net wage	Ratio between net disability pension and net wage	Ratio between net survivor's pension and net wage
2000	379.17	-	503.63	-	75.3	61.1	53.0
2001	411.92	8.6	562.74	11.7	73.2	59.4	51.4
2002	449.17	9.0	617.37	9.7	72.8	59.1	51.1
2003	471.66	5.0	663.80	7.5	71.1	57.6	49.9
2004	492.40	4.4	701.90	5.7	70.2	56.7	49.2
2005	508.28	3.2	735.73	6.1	69.1	55.4	48.0
2006	530.80	4.4	773.42	5.1	68.6	55.1	47.8
2007	559.55	5.4	834.50	5.9	67.1	53.7	46.0
2008	603.72	7.9	899.80	7.8	67.1	53.8	46.3
I-X 2009	619.56	7.3	920.47	3.7	67.3	54.0	46.5
Source: Pension and Disability Insurance Institute of Slovenia.
Note: From 2005 onwards, more wage recipients are covered because employers with one or two employees are also taken into account.
the public sector. However, this is not present in pensions, where the valorisation mechanism has a delayed impact on the growth of pensions. The trend is similar in other types of pensions, i.e. disability and survivor's pensions.
In September 2008, around 55% of old-age pensioners were receiving pensions up to the amount of the average old-age pension; in September 2001, the share was around54%. A slight deterioration in the distribution of old-age pensioners is partly the result of the deterioration in the distribution of wages in Slovenia.
3.4 Cash benefits of the population from public funds
Cash benefits of the population were analysed on the basis of the database on cash benefits that are paid in Slovenia from public funds, the state budget and municipal budgets, and social insurance funds. Data on cash benefits of the population have been collected by IMAD since 1992 (IMAD's Database of Cash Benefits). Observation units are legally stipulated cash benefits that people receive personally or to a bank account (nonmonetary benefits are not included32) and are classified into 14 target groups.33
In 2008, EUR 5.3 billion was intended for cash benefits.
In 2008, EUR 5,377,546,000 was intended for cash
32	Benefits do not include various social services or any subsidy or other material or financial benefit that people can receive indirectly (e.g. via subsidies to institutions) or directly (e.g. exemption from payment).
33	These are: unemployed persons, persons in education, parents, retired persons, relatives, poor people, disabled persons, war-disabled persons, sick, veterans, victims of war violence, people with special merits, people in need of help and farmers.
benefits, which is 14.48% of GDP. Average real growth of funds in the 2000-2008 period was 0.9%. Compared with a year before, in 2008, funds for cash benefits grew in real terms by 2.6% (in 2007 by only 0.5%). In the 2000-2008 period, growth was more rapid only in 2003. After falling in the 2000-2007 period, in 2008, the share of funds for cash benefits in GDP slightly increased.
Figure 21: Funds for cash benefits as % of GDP, Slovenia, 2000-2008
18
17
16 15
14
13
Source: Database of cash benefits (ZDPU); calculations by IMAD.
Both in the structure and as a share in GDP, in 2008, most funds were intended for pensioners. In the 20002008 period, the structure of funds by target groups did not change much; the bulk of funds are still intended for pensioners (52.53%). As regards the share of funds in GDP, pensioners are also first with 7.61%.
Social overwiew 2009	37
The way we live
Figure 22: Structure of funds for cash benefits by target groups, Slovenia, 2008, in %
Sick 3.7%
Unemployed 2.3%
Poor 2.0%
.-.>. Disabled
People with _ special merits 0.0%
Farmers 0.1 %
People in school 1.7%
People in eed of help 1.4
War veterans 0.9%
War victims 0.4%
War-disabled persons 0.3%
Source: Collection of cash benefits ZDPU; calculations by IMAD.
As regards the number of received benefits, again pensioners are first. In 2008, the state provided 68 cash benefits from public funds, which is the same as a year before. As of December 2008, people, who are classified into 14 target groups, received monthly or as a lump sum 2,235,538 cash benefits, which was 1.1% more than in 2007. Most benefits were received by pensioners, followed by parents, sick and disabled persons.
Figure 23: Structure of the number of cash benefits by target groups, Slovenia, 2008, in %
People with special merits Farmers War-disabled persons Unemployed War veterans People in need of help War victims Poor
People in school Relatives Disabled Sick Parents Retired
					
					
					
					
					
					
					
					
					
					
					
					
					
					45.7
0 5 10 15 20
%
Source: Database of cash benefits (ZDPU); calculations by IMAD.
In the second half of2009, 103,638 of people at social risk received single social assistance. In order to alleviate social and economic crisis and improve social
security of the population of Slovenia, on 15 July 2009 the National Assembly adopted the Special Allowance for Socially Disadvantaged Persons Act, on the basis of which 103,638 beneficiaries34 received a special benefit for people at social risk. Funds in the amount of EUR 13,784,059.46 for this purpose were provided by the Republic of Slovenia from the state budget. Benefits were paid in four amounts (EUR 80, 120, 160 and 200), depending on the amount of earnings received by beneficiaries, i.e. beneficiaries of cash social assistance, of pensions and pension supplements, of disability benefits,35 of parental compensation and of parental allowance. On average, every beneficiary received about EUR 133.
Table 23: Assistance for socially disadvantaged people, number of recipients, average amount and total funds, Slovenia, 2009
Recipients:	Number of payments	Average amount (estimate) in euros	Funds in euros
Parental compensation	579	104	60,440.00
Parental allowance	1,955	120	234,600.00
Unemployment benefit	5,610	91	512,480.00
Cash social assistance	42,621	172	7,310,240.00
Pensions1	52,873	107	5,666,299.46
Total	103,638	133	13,784,059.46
Source: RAIS.
Note: 'including recipients of disability allowance.
3.5 Household expenditures
In 2007, an average household in Slovenia spent EUR 19,282, which is in real terms 0.7% more than a year previously;36 non-consumption expenditure increased more than consumption expenditure.37 Households spent almost the same amount on consumption expenditure, while for non-consumption expenditure 3.8% more was spent. The highest share among household consumption expenditure was that for food and transport; however, expenditure for food decreased in real terms by more than 4%, while expenditure
34	As a rule, these are individuals, in some cases also families.
35	On the basis of the Act Concerning Social Care of Mentally and Physically Handicapped Persons.
36	Expenditure per household member increased in real terms by 1.3%. Households are becoming smaller, so expenditure per household is only gradually increasing. In this chapter, expenditure is shown per average household, since data by quintiles are only available in this form.
37	Other expenditure that is not part of consumption expenditure is total expenditure for a dwelling or a house and other expenditures.
Social overwiew 2009	38
The way we live
for transport remained the same. The structure of expenditure is changing slowly. In comparison with 2006, there were no major changes; only the share of expenditure for transport38 decreased and the share of expenditure for housing increased. For the second consecutive year, expenditure for health39 increased most (in real terms by 11.0%), while expenditure for education decreased the most (by 10.1%). The share of other expenditure for a dwelling or a house fell to the lowest level in the past four years, while expenditure increased by 2.4%. This could be the result of high growth in housing expenditure in the past few years (on average in real terms by 15% per year) and the HBS methodology.40
38	This is probably also the result of lower prices (the share calculated from real data, where prices in the group transport are used as a deflator, is namely the same as in 2008).
39	This group does not include health insurance; the growth is mostly the result of expenditure for health care services paid by people themselves (especially dental care services) and therapeutic appliances and equipment.
40	HBS data for the reference year (e.g. 2007) are calculated using
Households with the highest consumption (fourth and fifth quintiles) put the highest share of their expenditure towards transport, followed by food, while other households put the highest share of their expenditure towards food, followed by housing. In 2007, the first three quintiles spent a higher share and the other two a lower share of income for housing and food than in the previous year. The first quintile spent 22% of funds for food (in 2000, 28.4%), which is the same as a year previously, while the fifth quintile spent only 11.7% (in 2000, 17.2%), which is 0.4 p.p. less than in 2006. This means that, according to this indicator, the situation of households in higher-consumption quintiles improved significantly over the previous year, since they were able to spend relatively more on luxury goods and services. The share of non-consumption expenditure is also growing with quintiles, which means that households with higher consumption (which in
data from the three consecutive years (e.g. 2006-2008), so that in these data the impact of the decline in consumption and borrowing at the end of 2008 can already be felt.
Table 24: Structure of consumption expenditure by five consumption quintiles, Slovenia, 2000 and 2007, in %
Types of expenditures
Share of individual types of expenditures (%)
Year	2000	2007	2000	2007	2000	2007	2000	2007	2000	2007	2000	2007
Quintile	I		II		III		IV		V		Total	
Total consumption expenditure	94.8	91.4	91.3	88.3	91.2	85.7	90.5	84.7	88.2	82.0	90.3	85.0
Food and non-alcoholic beverages	28.4	22.0	24.8	19.1	21.9	16.8	19.9	14.6	17.2	11.7	20.8	15.2
Alcoholic beverages and tobacco	3.1	3.6	2.9	3.2	2.4	2.8	2.6	2.3	2.1	1.5	2.5	2.3
Clothing and footwear	5.7	4.1	6.2	5.1	7.7	6.9	8.1	6.7	8.9	7.8	7.8	6.7
Housing, water, electricity, gas and other fuels	15.6	18.6	12.4	15.8	11.3	12.5	9.9	10.2	7.5	7.6	10.2	11.2
Furnishings, household equipment	7.5	6.0	6.3	7.2	6.7	6.8	6.5	6.7	6.4	5.9	6.6	6.4
Health	2.3	2.3	1.8	1.8	1.6	1.7	1.5	1.4	1.4	1.4	1.6	1.6
Transport	8.0	8.6	11.8	11.0	13.9	12.4	15.4	16.1	19.2	18.5	15.2	14.9
Communication	3.2	5.4	2.9	5.0	2.8	4.7	2.7	4.3	2.5	3.7	2.7	4.4
Recreation and culture	7.5	7.1	7.3	7.6	7.8	7.8	8.5	8.5	8.7	10.2	8.2	8.7
Education	0.3	0.4	0.6	0.4	0.7	0.7	0.9	0.7	0.9	1.2	0.8	0.8
Restaurants and hotels	3.0	3.1	4.9	2.7	4.6	2.9	4.9	3.6	4.7	3.8	4.6	3.4
Miscellaneous goods and services	10.3	10.2	9.4	9.5	9.8	9.9	9.4	9.6	8.8	8.9	9.3	9.4
Other expenditure that is not part of consumption expenditure	8.8	11.7	8.8	14.3	9.5	15.3	11.8	18.0	2.8	4.4	5.3	8.6
Expenditure for a dwelling or a house	6.6	8.0	6.2	10.3	6.6	11.3	8.6	12.6	2.8	4.4	3.2	5.2
Other expenditures1	2.2	3.7	2.6	4.1	2.9	4.0	3.2	5.4	0.0	0.0	2.1	3.4
Total expenditure	100.0	100.0	100.0	100.0	100.0	100.0	100.0	100.0	100.0	100.0	100.0	100.0
Source: SORS - Household Budget Survey.
Notes: Taking into account the money value of own production; the first quintile represents the fifth of households with the lowest consumption, while the fifth quintile represents the fifth of household with the highest consumption. 1Taxes and self-imposed contributions, saving, cash transfers and gifts, life insurance, voluntary pension and disability insurance, fines for minor offences and compensation for damage.
Social overwiew 2009	39
The way we live
principle means higher income41) spend a higher share of their expenditure for these purposes.
The fifth of households with the highest consumption spent in 2007 4.2 times more (almost EUR 34,000) than the fifth of households with the lowest consumption (EUR 8,000)42. Compared with 2006, growth in consumption was highest in the first quintile (in real terms by 5.6%). Consumption of an average household was 3.4% higher than in 2000; in real terms, consumption of the first quintile remained at a similar level, while consumption of the second quintile decreased by as much as 6.2%, and in the other quintiles increased by 3.9%, 6.4% and as much as 8% in the highest quintile.43 Compared with the previous year, the difference between the consumption of the fifth and first quintiles decreased (the ratio was 4.4), and compared with 2000, it meant greater inequality in consumption (at that time the ratio was 3.9). Households are closest in terms of expenditure for housing (these are mostly urgent cost of living) and alcohol (1.7 times higher consumption of the fifth quintile than of the first quintile), and the most far apart in terms of consumption for education, where households of the fifth quintile spend EUR 393 per year and households of the first quintile only EUR 28 (it is, however, true that the ratio decreased from 23.6 in 2006 to 13.9). Compared with 2006, in 2007 the ratio between those who spend the most and those who spend the least is lower in all groups of consumption expenditure, except recreation and culture, and non-consumption expenditure. Compared to 2000, inequality in expenditure is lower in the following groups: food, alcohol, housing, transport, communication, miscellaneous goods and services, and expenditure for a dwelling or a house.
3.6 Indebtedness
If funds received are not sufficient for households to buy goods and services, they are forced to borrow money. However, households can run into debt even if they do not have any loans; e.g. if they are late paying for the cost of living. For calculating indicators of indebtedness, mostly aggregate (macro) data are used (e.g. the ratio of liabilities to financial assets, disposable income or GDP), while for measuring over-indebtedness, micro data are
41	It should be mentioned that these are consumption quintiles (see also the note under Table 24) and not division of consumption by income quintiles; the richest households spend the most in absolute terms (in relative terms, however, the richest households save the most).
42	Again, it should be pointed out that expenditure is analysed regarding the average household and that results could be different if data by household members were available. Households are becoming smaller, so expenditure per household is increasing more slowly than expenditure per household member. This could indicate that expenditure per household could eventually become incomparable.
43	This could also be the consequence of changes in the size of households in the seven years, since it is possible that newly
formed households with fewer members fall into a higher consumption class.
used; these include survey data in which households evaluate their position themselves (one such survey is the EU-SILC Survey on Living Conditions).
After several years of relatively high household borrowing, in the second half of 2008, borrowing started to slow. This was mainly due to lower expenditure for durable goods and partly also due to the onset of the economic crisis. Partly this was also a normal consumption cycle of durable goods (see the Disposable Income and Household Expenditure chapter). In 2009 (to the end of November), households took loans mostly for housing (slightly over EUR 469 million or 30% less than in the same period of 2008), while the net value of consumer loans was only EUR 14 million (i.e. just over a tenth of the value in 2008). By the end of November 2009, households borrowed about a half less than in the first eleven months of 2008.
Despite relatively high borrowing in the past few years, in 2008 households in Slovenia were still among the least indebted households in the EU. Between 2001 and 2008, the average indebtedness (measured here as the share of liabilities in GDP) of EU Member States increased significantly (most of all in Eastern European countries, where in some, such as Latvia and Slovakia, households have become the most indebted in the EU). The relatively lower indebtedness of Slovenia could be the result of a lower share of housing loans,44 which are paid off over a longer time and in higher amounts, and the fact that after 2004 (data are available since then), Slovenia has not experienced such a strong increase in loans (a so-called credit boom) as, for example, in the Baltic States (where the volume of loans between
Figure 24: Liabilities as % of GDP, households and NPISH, 20081 and 2001, EU
160
2001	2008
-----Average 2001	-Average 2008
120 100
as 80
SZ
£ 60

Source: Eurostat - Financial accounts; calculations by IMAD.
Notes: Only European countries for which data are available are shown. Simple average is shown.
44 Which is among the lowest in the EU (it is only lower in Romania and Bulgaria); at the end of 2008 the share for Slovenia was 45.9%, while the EU average was 66%.
Social overwiew 2009	40
The way we live
Table 25: Ability of households to make ends meet, by household income, EU-27, 2008, in %
	Households making ends meet with great difficulty	Households making ends meet with difficulty	Households making ends meet with some difficulty	Households making ends meet fairly easily	Households making ends meet easily	Households making ends meet very easily	Arrears (mortgage or rent, utility bills or hire purchase)
Belgium	31	33	29	6	2	0	35
Greece	20	35	27	13	5	1	24
Romania	19	31	33	12	4	1	13
Cyprus	19	29	37	11	4	0	25
Latvia	24	22	36	13	4	1	6
Hungary	17	27	43	11	1	0	16
Poland	18	21	39	18	4	1	16
Portugal	13	26	38	20	2	0	14
Italy	13	24	34	23	6	1	8
Malta	14	21	37	19	7	1	11
Slovakia	12	23	42	20	3	1	5
Spain	13	17	31	26	12	1	7
Czech Republic	8	20	39	25	7	1	4
EU-27	8	18	41	21	10	1	16
Lithuania	10	15	30	28	13	4	10
Ireland	6	19	56	16	3	0	8
Euro area	9	14	28	29	16	4	9
Slovenia	9	14	36	28	9	3	11
Belgium	7	14	23	27	23	5	7
France	3	13	40	30	12	2	10
United Kingdom	6	10	28	37	12	6	5
Estonia	5	10	27	29	22	7	7
Netherland	3	8	29	51	8	1	9
Austria	3	8	14	15	47	13	4
Finland	4	5	11	44	19	17	6
Sweden	3	5	12	23	35	23	4
Denmark	3	5	20	37	22	13	10
Luxembourg	2	5	14	46	24	9	6
Germany	2	5	14	31	38	10	2
Source: Eurostat - Survey on Living Conditions (EU-SILC).
Note: Countries and ranked according to the sum of shares in columns 1 and 2, which is here the estimate of the risk of over-indebtedness.
2004 and 2008 increased by 5.8 times; in Slovenia it approximately doubled. As regards GDP per capita by purchasing power parity, these countries also lag behind the EU average much more than Slovenia, and therefore their expenditure was linked to the acquisition of goods that households in Slovenia could already afford.
The relationship between the aggregate indebtedness and over-indebtedness is not clear. Over-indebtedness involves both raising a loan and inability to pay the cost of living, which leads to late payment of bills and running into debt. So it may happen that in a country in which the debt at the aggregate level is relatively lower, a higher share of households have problems paying off debt.
In terms of risk of over-indebtedness,45 households in Slovenia can be compared to the EU average.
According to the Survey on Living Conditions (EU-SILC) data, when asked how they manage with their income in 2008, a quarter of households answered that they managed with great difficulty (in Slovenia 9%, in the EU 8%) or with difficulty (in Slovenia 18%, in the EU 14%). In 2008, 67% of households in Slovenia that took part in in this survey reported that they did not have hire-
45 It should be mentioned that there exists no official definition of over-indebtedness or of the risk of over-indebtedness. The latter is here evaluated on the basis of two indicators (the sum of the shares of households in the first and second columns in Table 25) - as a share of households that declared that they have (great) difficulty managing with their income.
Social overwiew 2009	41
The way we live
Table 26: Burden of households with loans and delay in payment, share by income, Slovenia, 2008, in %
	Level of burden of repayments of debts from hire-purchase or other non-housing loans for households, by household income			Arrears on hire-purchase instalments or other non-housing loan payments in the last 12 months due to inability to pay		Household has no repayment of debts
	Repayment is a heavy burden	Repayment is somewhat a burden	Repayment is not a burden at all	Yes	No	
Household income - TOTAL	12	18	4	2	31	67
First quintile	11	9	1	3	19	79
Second quintile	16	16	2	4	31	65
Third quintile	13	22	3	3	35	62
Fourth quintile	11	24	4	1	38	61
Fifth quintile	7	22	9	1	37	62
Source: Eurostat - Survey on Living Conditions (EU-SILC).
Note: Households are ranked according to the total income in five quintiles. The first quintile includes the poorest 20% and the fifth quintile the richest 20% of households.
purchase instalments, while for 12% of households hire-purchase and consumer loans presented a large burden (the highest share was observed in the second income quintile); only 2% of households were late paying, while housing costs represented a large burden for more than a third of households (for more than half of households in the first income quintile).46
In Slovenia, consumer bankruptcy has been possible since October 2008, while the general discussion on the problem of over-indebtedness has not yet begun.
From a legal point, the problem of over-indebtedness is regulated by the Consumer Bankruptcy Act; the SISBON47 credit bureau was introduced, and years ago also regular reporting by non-bank creditors to the Consumer Protection Office of the Republic of Slovenia, which may partly help prevent borrowing on the black market, thus preventing over-indebtedness. In December 2007, the Financial Operations, Insolvency Proceedings and Compulsory Dissolution Act was adopted, which started to be used in October 2008; the act contains the legal definition of over-indebtedness (long-term insolvency - over-indebtedness - happens when the value of a person's property is less than the sum of liabilities). By September 2009, slightly fewer than 300 decisions on the start of consumer bankruptcy proceedings were issued. However, there is no"national strategy" of identifying and monitoring the extent of the problem and dealing with the consequences of over-indebtedness. In addition, institutions that are in any way dealing with the problem are not co-operating. This would result in a commitment to the collection of data from already available sources, which could facilitate the assessment of over-indebtedness; and on the basis of this assessment, the
46	According to Politbarometer data (11/2009), due to repayment of loans, 28% of respondents could not pay current expenses for consumer goods in time.
47	The collected data refer to indebtedness and meeting of
contractual obligations and present additional information on determining the capacity to repay loans, on which granting of loans and conditions for individual services depend.
most suitable measures to tackle the problem could be selected. Due to lack of data, Slovenia was not included in any survey in the field of over-indebtedness (Ferk, 2007), while the International Monetary Fund (IMF, 2006) asked Slovenia to prepare extensive data on household borrowing, including concentration and debt-servicing indicators.
4. Access to goods and services
Access to goods and services of general interest has an important impact on the living conditions of the population and on social cohesion. The accessibility of goods and services of general interest (health care, social-welfare services, education, housing, culture, media, the Internet) significantly affects the population's possibilities for quality of life. Accessible and high-quality health care is crucial for the overall health and well-being of the population. Access to housing importantly influences the population's standard of living, and affects young people's decision to start a family. Housing prices and rental costs are the main factors underlying the choice of either renting or purchasing a dwelling and contribute to the property function of the dwelling. Purchasing or rental prices shape the available income left after having paid housing-related expenses, i.e. income that may be spent on other goods or services (leisure activities, cultural goods, quality food, etc.), which is another aspect of quality of life. Moreover, it affects the population's saving capacity. The accessibility of social-welfare services is an indicator of the quality of life of the elderly and of some other population groups (people with special needs, etc.). Social welfare and social cohesion also depend on the accessibility of education, culture, media, and the Internet. Individuals with a higher level of formal education tend to have higher earnings, while those with a low level of education
Social overwiew 2009	42
The way we live
(with completed primary school at most) are more likely to become unemployed, which in turn increases the at-risk-of-poverty rate. Furthermore, there seems to be a correlation between the attained educational level and health condition, satisfaction, and personal development. Participation in cultural activities is another way of spending quality free time. Moreover, it affects the values and the value system of the society, cultural identity, cultural awareness and social responsibility, and promotes tolerance and pluralism. The media update the public on political and other events in their country and abroad. Other key factors influencing the quality of life and the welfare of the population include access to and use of information and communication technologies (ICT), particularly the Internet. The accessibility of ICT, most importantly the Internet, significantly improves access to various information as well as to services of general interest. Despite certain problems, over the past years, accessibility of goods and services has presented favourable trends.
4.1 Access to health care
The accessibility of health care may be monitored from several viewpoints, most of which are analysed below. The first aspect concerns the provision of physicians and health-care facilities, in which equal regional accessibility also plays a role; the second aspect is adequate access to health-services schemes at various levels of health care, which is also related to measures for shortening waiting times. The third aspect is the financial accessibility of health care, in which importance is given to health-insurance coverage, the ratio between public and private expenditure for health care, and an adequate amount of total expenditure on health, which directly or indirectly affects all aspects of accessibility of health-care services, including the possible introduction of (access to) new medical technologies and products.
4.1.1 Health-care resources
The number of physicians in Slovenia is gradually increasing yet nevertheless continues to lag behind the EU average. After a slight improvement in 2007, the number of practising physicians in Slovenia was again very low in 2008. Their number rose by only 40 to reach a total of 4,854, while the number of practising physicians per 100,000 inhabitants was 238.8 (237.6 in 2007). In 2007, the EU-27 average for this was 322.4 physicians per 100,000 population. Slovenia lags considerably behind mainly as regards the number of general practitioners. In 2006 there were only 48.8 general practitioners per 100,000 inhabitants,48 while the EU-25 average was 96.7. These doctors present a particularly pressing lack, mainly owing to their unequal regional distribution. For this purpose, over the past years, the Health Insurance Institute (HIIS) has been providing priority funding for
48 Source of data: WHO (Health for All database)
additional teams of general practitioners, and children and school dispensaries, in those regions where their number is below average, enabling all the institute's regional units to meet the minimum standard in 2008. Comparisons with European countries reveal a wide gap in specialist anaesthesiologists and gynaecologists, which is also observed in practice.
Figure 25: Number of practising physicians per 100,000 inhabitants in Slovenia and selected European countries, 1998-2007
—■—Slovenia -Belgium —*—Denmark
-----Latvia	-_.■__ Austria--Poland
—-♦—- Finland
Source: Eurostat.
The number of graduates in medicine is still too low, while the inflow of foreign-trained physicians to Slovenia is relatively modest. The key reasons for this low number of physicians per 100,000 population include: insufficient enrolment in the Faculty of Medicine, as well as insufficient provision and inadequate planning of specialist studies, long specialisation periods,49 and a relatively low inflow of foreign doctors, which may be due to strict licence requirements.50 In 2008, the number of students graduating in medicine reached 175 or 8.5 per 100,000 inhabitants, which was the highest number of graduates since 2000 (the average indicator for 20002008 was only 6.9), yet still lagged behind the OECD average (9.9 in 2007) and most developed European countries. The above ratio is expected to improve in 2010 with the first generation of graduates from the Maribor Faculty of Medicine,51 with the indicator then reaching about 9.5-10.0.
49	According to data provided by the Medical Chamber, the duration of specialisation is 3-6 years; however, taking into account possible suspensions due to maternity leave, sickness, etc., specialisations normally last 3.5-7 years.
50	To obtain a licence, candidates must have their diplomas recognised, must know Slovenian and must have passed a professional examination in Slovenia.
51	The first 89 students began their studies at the Maribor Faculty
of Medicine in 2004/2005.
Social overwiew 2009	43
The way we live
Figure 26: Number of medicine graduates per 100,000 inhabitants in Slovenia in 2008 and in OECD countries
I
y^^C ^CQ TO c	P "O ^"O ^
^
Source: OECD Health Data 2009, Institute of Public Health: Health Statistical Yearbook 2008.
Figure 27: Contribution of foreign-trained physicians to total growth in number of practising physicians in the period 2000-2007, and share of foreign-trained physicians in total number of practising physicians in Slovenia and selected OECD countries in 2007, in %
■ Contribution of foreign-trained physicians to total growth in no. of
practising physicians, 2000-2007 ♦ Share of foreign-trained physicians in the total no. of physicians, 2007 (right axis)
	100
	90
	
t	80
o	
ct	70
o	60
o	
d	50
o	
=! J2	40
sz	30
O	
U	
	20
	10
	0
54.8 ^ ^ 47.6
325 ♦ 26.1
♦	
16.2	
	8.0
	■
116.2
8.0
50	"o	
45	jš £	
40	C	
35	O a;	
30	C	
25	C	
	'Ü	C
20		—
		
15		
	"O	
	OI	
	C	
10	's	
5	C .i? £	
0	o	
Some countries have tackled a lack of physicians by relaxing the requirements for obtaining a licence, thus considerably increasing the employment of foreign-trained physicians52 in the past years. Among the European countries for which data are available, the most outstanding figures were observed in Ireland, Sweden, Switzerland, Finland and the UK, where in the period 2000-2007 foreign-trained physicians made up over 50% of the total growth of the number of practising physicians, while Slovenia recorded just above 26% in this category. In the same period, most foreign-trained doctors in Slovenia were general practitioners, followed by internal medicine specialists, anaesthesiologists, family-medicine specialists, and paediatricians. Considering the above data by specialisation, it may be concluded that the recruitment of foreigners indeed contributes to a partial solution of the problem of accessibility of health care in areas where the number of doctors is particularly low. In terms of nationality, most foreign-trained physicians in Slovenia originate from other countries of former Yugoslavia. In 2008, foreign-trained doctors and dentists accounted for 17.9% and 24.9% of the total number of practising physicians, with an increase of 1.1 p.p. and 3.0 p. p., respectively, recorded compared with 2000.
After a few years' growth, in 2008 the number of dentists per 100,000 population fell to 59.8 (from 60.9 in 2007). In absolute terms, the number of dentists decreased by 18 (to 1,216). On this indicator, Slovenia does not lag behind the EU average (59.9 in 2007), and the ratio is better than in the case of physicians, partly because of the expansion of private practice in dental care. In 2008, 48.6% of
Source: OECD Health Data 2009; for Slovenia: Medical Chamber. Notes: (1) Foreigners include: foreign-born nationals, foreign nationals, and graduates from foreign schools. (2) Data on the share of foreign-trained physicians in the total number of physicians (right axis) refer to 2008 for Slovenia and 2006 for Sweden.
dentists were private providers with a concession and 11.8% were purely private providers.53 On the issue of accessibility of dental care, mention should be made of the long waiting periods in public institutes, mainly for adults, and of the fact that more than a fifth of insured people do not have a selected dentist.54
2008 saw a slight increase in the number of acute hospital beds.55 In 2008, Slovenia had 473.2 hospital beds per 100,000 inhabitants56 (2007: 468.3), of which 382.5 were acute hospital beds (2007: 378.4); the EU average was 570.2 (2007) for all beds and 389.4 for acute beds (2005). In the period 2000-2007, the total number of hospital beds per 100,000 inhabitants in Slovenia recorded a rapid decrease and dropped by 15.8% (with a yearly average of 2.1%), whereas the EU average was lower by only 9.7% (1.3% yearly). The major decline was observed in the number of acute hospital beds,
52 According to OECD methodology (and also in Slovenia), foreign-trained physicians include foreign-born nationals, foreign nationals, and graduates from foreign medical schools.
53	Data provided by the Medical Chamber. Also includes dentists specialists.
54	Resolution on the National Health Care Plan 2008-2013, January 2008.
55	Acute hospital treatment means diagnostic and curative treatment related to health care in stationary institutes (hospitals). Acute hospital treatment does not include specialist care, dialysis, psychiatric care, transplantation, tertiary health care, non-acute hospital treatment (extended hospitalisation, health care and palliative care), rehabilitation treatment, hospital treatment of healthy newborns, disabled youth, escort during hospital treatment, and treatment of clinically dead organ donors.
56	Data refer to the total number of all hospital beds (not only
acute) and include the Diagnostic Centre Bled and MC Medicor (IVZ).
1 5
91.8
87.7
84.0
73.5
10
5
0
Social overwiew 2009	44
The way we live
which complied with the policy of reducing the average hospital stays and promoting "day hospitals". Between 2003 and 2007, the average hospital stay in acute hospital treatment went down from 6.5 to only 5.4 days (calculated based on HIIS data: taken from Marušič D., Ceglar J., 2009), ranking Slovenia among the countries with low average inpatient stay (compared with European countries for which data are available).57 In the same period, the average accessibility of health services in acute hospital treatment improved (see below), which leads us to conclude that the dynamics of reducing the number of acute hospital beds and the length of hospital stays was not after all too fast, since it also contributed to greater cost-efficiency among hospitals (the share of hospital losses decreased).
Figure 28: Average stay in acute hospital treatment in Slovenia and selected European countries in 2007, in days

I "O ro -o T3 ^ J
> ^ =J ^ O c
O u < ^ cl ^

t^ m —
Source: OECD Health Data 2009; for Slovenia: HIIS, taken from Marušič D., Ceglar J., 2009.
Note: Data for Ireland, the Netherlands, Spain, Italy and Belgium is for 2006.
The accessibility of health-care resources largely depends on adequate regulation of the work of private andpublic health-service providers. Over the past years, the share of private health-care providers increased mainly in the public health-care network, where the largest number of private providers is recorded by general practitioners (and dentists). According to HIIS data for 2008, private general practitioners made up over a quarter (27.6%) of the public health-care network, and private specialists slightly more than a tenth (11.8%). It needs to be stressed that the growing share of private providers in the public network also reflects that the number of physicians employed at public health institutes is declining. On the other hand, there are very few purely private providers without concession who could importantly contribute to the offer of health
57 According to data for all hospital beds (not only acute), the average hospital stay in Slovenia fell from 8.3 days in 2003 to 6.8 days in 2007; the comparable EU average was 9 days in 2009. WHO (Health for all database)
services in Slovenia through private investments; in 2008, they were only 210 (156 of which were dentists). At the same time, the absence of an adequate concession-awarding policy based on the previously defined network of public health-care providers had already led to staffing problems in relation to accessibility of health services, mainly at primary level; the most evident consequences are insufficient provision of prevention and physiotherapy, and problems in organising on-call duties at primary level. In this regard, another pressing issue is the further activity of health centres, which in some regions fail to provide the entire range of primary health-care services.
Managing waiting lists and better accessibility of health services at various levels of health care is a key priority for HIIS. For some years now, particular emphasis has been given to uniform accessibility of health programmes at various levels of health care. The Strategic Development Programme for 2008-2013 envisages, for example, the introduction of additional (new forms of) financial incentives, further expansion of selected programmes, and promotion of certain priority programmes.
At the primary level, waiting lists are observed mainly in dental care, and additional incentives are needed for the implementation of prevention programmes. As
previously mentioned, the problem at primary level58 is the regional distribution of physicians and dentists and the provision of certain services, mainly prevention. In the past years, the visit rate per 1,000 inhabitants aged 20 in preventive services of general medicine has not improved, the average ranging around 62 for the last five years. Waiting lists are observed mainly in dental care. In 2008, particular attention and additional incentives at primary level were given also to priority preventive programmes. Measures to improve accessibility and efficiencyatprimarylevelinclude renewable prescriptions valid for one year. Currently, such prescriptions are used only for hormonal contraception and are expected to reduce the number of visits of women using hormonal contraceptives by 330,000 per year (HIIS Business Report for 2008).
Waiting periods are still too long, particularly in orthopaedics and orthodontics. At secondary59 and tertiary60 levels, HIIS has been closely monitoring waiting lists and the number of persons waiting for individual specialist services and acute hospital treatment; such data were used as the basis for negotiations on the
58	Health care at primary level comprises basic health care (general practice, children and school dispensaries, gynaecologists, dentists and pharmacies). Health services at the primary level are available without referral.
59	The secondary level comprises specialist medicine and hospitals. A referral from primary-level physicians is necessary (Institute of Public Health website: definitions).
60	The tertiary level refers to the activity of clinics, institutes,
and other authorised public health institutions. A primary-level
referral is required.
9
5
4
3
2
0
Social overwiew 2009	45
The way we live
expansion of programmes. Despite a considerable reduction in 2008, there are still long waiting periods in orthopaedics (25 months for knee endoprosthesis, 17 months for hip endoprosthesis) as well as in orthodontics (22 months for retainer). In most other health-care areas, waiting times in 2008 did not exceed 6 months. In the same year, an additional EUR 15.57 million was intended for reducing waiting lists. Compared with 2007, lists were shorter in 10 programmes but longer in 15 programmes (HIIS Business Report for 2008).
As regards acute hospital treatment, HIIS has more than doubled (compared with 2007) the number of prospectively61 planned cases, mainly for services with longer waiting lists as well as for child delivery and treatment of cancer patients where - although there are no waiting lists - needs can be adequately anticipated. The share of prospective cases in acute hospital treatment was 14.4% in 2007 and 32% in 2008. However, for most services the implementation of the prospective programme was not fully completed owing to lack of capacity or the low efficiency of providers. In 2008, HIIS also launched a new financial incentive, i.e. to cover up to 20% of the exceeded plan for operations involving knee and hip endoprosthesis, yet providers took either no or only partial advantage of this opportunity (HIIS Business Report for 2008).
In the period 2003-2008, access to acute hospital treatment improved. As regards acute hospital treatment, data since 2003 - when payment by groups of comparable cases was introduced - allow for promptly monitoring of the realisation of acute treatment and of people waiting for this, thus providing for a more adequate distribution of funds or a targeted allocation thereof in order to reduce waiting lists and improve accessibility. In 2003-2008, the number of acute hospital patients grew by over 10%, while the number of people waiting for acute treatment decreased by almost a third. Based on this data, Marušič and Ceglar (2009) tested Slovenia's indicator of population needs62 for acute hospital treatment, the ratio between the number of realised acute treatments of all public health providers in a given year and the number of people waiting for such treatment at the beginning of the following year per 1,000 inhabitants. Since acute hospital treatment is usually also the final treatment of a patient, this indicator could also be suitable for measuring the responsiveness of the health-care system. Between 2003 and 2008, the estimated needs grew by a total of 9.2% or by an average 1.8% per year (the indicator rose from 170.7 to 186.4), mainly owing to the increased volume of
61	Prospectively planned cases imply advance planning of the type and extent of the services.
62	Due to differing registers and definitions of persons waiting, there is as yet no internationally accepted indicator to monitor population needs for health services, although analysis of needs usually examines data on the level of hospitalisation and on changes in the number of people waiting for acute hospital treatment.
realised acute treatments, which in the same period rose by 12.6% (2.4% per year). It may be concluded that the gap between the hospitalisation rate (the number of realised acute treatments per 1,000 inhabitants) and the needs rate in the above period diminished by 2.9 p.p., indicating that the average accessibility of acute hospital treatment is improving. In 2007 and 2008, the upward trend of both indicators slightly slowed, while realisation continued to grow faster than the estimated population needs (Marušič D., Ceglar J., 2009).
Figure 29: Gap between hospitalisation rate and population needs for acute hospital treatment per 1000 inhabitants, Slovenia, 2003-2008
							
	—— Hospitalisation rate —■— Needs rate						
					184.5	185.5	186.4
			178.5				______»
		/176.4		r— 172		______«------ 174 6	175.5
170.7			__.»''165	.5			
		y ,»■''1 60	.4				
Vl 55		.9					
							
2003 2004 2005 2006 2007 2008
Source: Marušič D., Ceglar J., 2009; HIIS data.
A new regulation concerning the national register of waiting lists could contribute to reducing waiting periods and improving the accessibility of healthcare services. To help provide the best information and selection options to insured persons, HIIS has, since 2004, been keeping records and publishing data on contractually agreed waiting periods at individual providers, as well as the average realised waiting periods. Since 2009, providers of health services have been required to keep data on waiting lists and report on these in accordance with new legislation adopted in 2008. Monitoring waiting periods and keeping waiting lists are required by the Patient's Rights Act63 and the Rules on waiting times for individual medical services64 and direction of waiting lists. The Rules specify, inter alia, the longest permissible waiting times for individual health services at providers in the public health-care network (six months for non-urgent cases is acceptable) and priority criteria for the inclusion of patients on the list. Waiting lists are kept by providers, who later report these data to the national waiting list kept by the Institute of Public Health; unfortunately, owing to complex technical issues, reporting in line with the new law was not yet fully implemented in 2009.
63	OG RS No. 15/08.
64	OG RS No. 91/08.
Social overwiew 2009	46
The way we live
4.1.2 Expenditure on health
Public expenditure on health continued to grow slowly in 2007 but gained more impetus in 2008, mainly owing to the increase of salaries in health care. In
the period 2003-2007, Slovenia recorded a low rise in total expenditure on health in real terms, accounting on average for only 2.5% annually and lagging greatly behind GDP growth (5.3% per year); public expenditure on health on average rose by only 2.3% annually in real terms, while private expenditure increased by 2.8% (and direct household expenditure by 6.3%). Such gentle growth in public expenditure was partly a consequence of measures intended to manage expenditure on medicinal products (the average annual real growth of public expenditure on medicines was only 0.1%), although it was mainly related to the moderate growth of salaries of doctors and other health-care staff, as a result of the transition following the introduction of the new wage system. In contrast, in the period of high economic growth, most European countries recorded even higher rises in health expenditure. In fact, in recent years, pressure for ever-greater investments into health care has been related to the introduction (and accessibility) of new medical technologies and new medicines; other factors contributing to rapid growth include demographic trends and the increasing demand for health services. In Slovenia, the period 2003-2007 was marked by low salary growth and by a pressing lack of doctors and medical staff, while the savings65 generated
65 In the period 2005-2007, HIIS savings were achieved by reducing absenteeism and managing the prices of medicinal
in this period began to be more systematically directed into additional programmes to improve the accessibility of services at all levels and shorten waiting lists for acute hospital treatment. A significant increase was also recorded in the use of new (biological and expensive) medicines in Slovenia. In 2008, the share of financing intended for compulsory health insurance for biological and other expensive medicines was 12.3% (2007: 9.9%).66 In the same year, HIIS estimated that public expenditure on health increased by 6.1% in real terms, mostly in relation to wage growth in health care as a result of the reduction of wage imbalances in the public sector. Compared with 2007, HIIS expenditure on salaries grew by 5.3% in real terms (HIIS Business report for 2008).
In Slovenia, the accessibility of health services is improving on account of out-of-pocket expenditure.
After a long period of slow increase in public expenditure on health care, the share of total private expenditure on health in 2007 was 28.4% (the first estimates indicate that it stayed at the same level in 2008), which is above the EU average. Direct household expenditure, i.e. out-of-pocket expenditure, recorded a much faster rise than expenditure from voluntary insurance, particularly in 2007. It accounted for 48.6% (2006: 42.8%) of the private
products and technical equipment; in addition to savings in expenditure, higher profit was achieved parallel to higher economic growth (as a result of higher employment and salaries in the private sector).
66 According to HII, the average cost of an expensive medicine (expensive means over EUR 1,000 per patient per year) in 2008 was EUR 6,313 per patient.
Table 27: Expenditure on health, Slovenia, 2003 and 2007, and estimated expenditure for 2008
	EUR million			Structure, in			GDP share in %			Total real growth in 20032007, in %	Average annual real growth in 2003-2007, in %
	2003	2007	2008 1	2003	2007	20081	2003	2007	20081		
EXPENDITURE ON HEALTH	2,174.9	2,701.7	3,029.6	100.0	100.0	100.0	8.7	7.8	8.2	10.2	2.5
PUBLIC EXPENDITURE	1,564.9	1,935.1	2,169.3	72.0	71.6	71.6	6.2	5.6	5.8	9.7	2.3
Central government	96.9	126.6	N/A	4.5	4.7	N/A	0.4	0.4	N/A	15.9	3.8
Local government	13.0	14.4	N/A	0.6	0.5	N/A	0.1	0.0	N/A	-1.7	-0.4
Social-security funds	1,455.0	1,794.1	N/A	66.9	66.4	N/A	5.8	5.2	N/A	9.4	2.3
PRIVATE EXPENDITURE	610.0	766.6	860.4	28.0	28.4	28.4	2.4	2.2	N/A	11.5	2.8
Private insurance	280.2	347.7	N/A	12.9	12.9	N/A	1.1	1.0	N/A	10.1	2.4
Households	258.6	372.6	N/A	11.9	13.8	N/A	1.0	1.1	N/A	27.8	6.3
Corporations (other than health insurance)	70.7	45.3	N/A	3.3	1.7	N/A	0.3	0.1	N/A	-43.2	-13.2
Non-profit institutions	0.5	1.0	N/A	0.0	0.0	N/A	0.0	0.0	N/A	63.0	13.0
Source: Data for 2003 and 2007: SORS; Data for 2008: HIIS Business report for 2008.
Note: 1 HIIS estimate for 2008. The estimate follows the international methodology of the System of Health Accounts.
Social overwiew 2009	47
The way we live
Figure 30: Average annual growth rates in real terms of public and private expenditure on health and GDP, Slovenia and selected European countries, 2003-2007, in %
10 9 8 7
#
■E. 6 &
2 5 ? 4
2 4
I3 2
1
I GDP
I Public expenditure on health I Private expenditure on health
Source: OECD Health Data 2009; for Slovenia, SORS (as of 26 October 2009). Data calculated according to the international methodology of the System of Health Accounts.
expenditure on health and already exceeded the share of expenditure from voluntary health insurance (45.4%). Compared with EU countries, however, the share of direct household expenditure is still rather modest (the EU average is around 75%) which is due to Slovenia's system of supplementary health insurance covering the difference to the full value of health services.
Another indicator of the aggregate impact of out-of-pocket expenditure is the ratio of this expenditure in final household consumption. In 2007, this indicator rose to 2.1% (2006: 1.9%; 2000-2006 average: 1.8%), which might not be much compared to other EU countries, yet nevertheless brings Slovenia closer to those countries where no system of supplementary health insurance exists. In any case, within the expenditure on health burdening Slovenia's households, it is also necessary to take account of the increase in insurance premiums for supplementary health insurance.67
In relative terms, expenditure on health as a share of GDP in 2007 fell below the EU average; similarly, Slovenia lags behind the most developed European countries in terms of per-capita expenditure on health. In 2007, expenditure on health as a share of
67 According to Vzajemna, supplementary insurance premiums between March 2006 and March 2009 recorded no growth in real terms. The average premium rise for all supplementary insurance may be calculated only since the introduction of the balancing scheme of supplementary health insurance intended to balance the differences in the cost of health services, medicines and medical devices among insurance companies, which derive from different structures of insured persons based on age, sex and medical condition.
Figure 31: Private expenditure on health as share of total expenditure, and their structure by source of financing, Slovenia and OECD countries, 2007, in %
50 45 40 35 30 25 20 15 10
I Other (enterprises, non-profit inst.) I Out-of-pocket payments I Private insurance
ro c Q "D ro
(U	—
i -£ u
Source: OECD Health Data 2009; for Slovenia SORS (as of 26 October 2009). Data calculated according to the international methodology of the System of Health Accounts.
Figure 32: Direct household out-of-pocket expenditure on health as share of total household consumption, Slovenia and OECD countries, 2007, in %
-E >Ö>= gïTS-lP
fD	^^ CTl Cil ^
:	— ^	— sz P LJ_ &
Source: OECD Health Data 2009; for Slovenia SORS (as of 26 October 2009). Data calculated according to the international methodology of the System of Health Accounts.
GDP decreased to 7.8% (2006: 8.3%) but is estimated to have grown in 2008 to 8.2%, which has been the EU-27 average for several years. It is expected that the sharp decline of GDP in 2009 will cause a considerable "improvement" of this central indicator. Expressed in USD PPS per capita, Slovenia in 2007 allocated 2,096 USD PPS per capita (2006: 2,056 USD PPS), which is more than any new Member State (except Malta), yet still below the EU-27 average (2006: 2,432 USD PPS).
50.0
13.5
0
5
0
6
5
4
3
2
0
Social overwiew 2009	48
The way we live
Figure 33: Total (public and private) expenditure on health as a share of GDP and USD PPS per capita, EU-27, 2007
■	Private expenditure
■	Public expenditure
■	Total expenditure on health in USD PPS per capita
12 11 10 9 8 7 6 5 4 3 2 1 0
C ro E 2 EJ?
öiro i Q
(U c ^-uf^roro-u^olroQjro-u^rororo
z"-	m S m u	£
Source: OECD Health Data 2009, WHO The World Health Report 2009; for Slovenia, SORS (as of 26 October 2009). Data calculated according to the internationally comparable methodology of the System of Health Accounts (SHA).
4.2 Access to social-welfare services
Access to social-welfare services largely depends on the capacity of the social-welfare network and the population's involvement in the provision of services, on the regional distribution of capacities, and on the financial accessibility of services. Based on available statistical data, Social Overview measures participation in the provision of public social-welfare services and trends related to expenditure on payable services, i.e. expenditure on long-term care (other social-welfare services are free of charge).
4.2.1 Social-welfare network
Compared with 2007, the network of social-welfare institutions significantly expanded in 2008, along with the variety of services and the spatial distribution of capacities, all of which contributed to better accessibility. The number and territorial distribution of social-work centres and special social institutions have remained unchanged since 2000. As in previous years, however, Slovenia has been expanding its network of old people's homes, the number of home-care providers and centres for protection and training, as well as the number of programmes run by non-governmental organisations.
As in previous years, the most rapid growth was observed in the capacity of centres for protection
and training of adults with special needs. They accommodated 3,016 people in 2008, 15% more than in 2007 and 53% more than in 2000. An increase was also recorded in the network of social-welfare programmes mainly operated by the non-governmental sector and in the extent of their co-financing from public sources (maternity homes and safe houses, residential communities for persons with long-term mental illnesses, therapeutic communities and other programmes for drug addicts, centres offering psycho-social assistance to victims of violence, centres for children and minors with adolescence problems, etc.). On the other hand, a downward trend was observed in the number of people in care in special social-welfare centres intended for the institutional care of adults with special needs, which was the result of a planned deinstitutionalisation policy for these groups.
Figure 34: People in care in social-welfare institutions by category, Slovenia, 2000-2008
Centres for protection and training Special social welfare institutions I Old people's homes
15,000
10,000
Source: SORS.
Note: Until 2003, people in care in old people's homes' units for special forms of adult care were statistically counted as being in old people's homes, but since 2004 SORS has shifted them to special social-welfare institutions. Consequently, this reduced the number of people in care at old people's homes in 2004 and caused a jump in the number of people in care at special institutions.
In 2008, the capacities of long-term care institutions increased more than in previous years. Several new old people's homes or home units were opened, improving accessibility and increasing the number of people in homes. Old people's homes thus accommodated 15,235 persons, which is 10% more than in the previous year and 28% more than in 2000. In accordance with the Resolution on the National Social Assistance Programme for 2006-2010, at least 5% of the population aged 65 or over will be living in old people's homes by 2010, while the actual share in 2008 was 4.6%. The provision of home care also expanded,68 although four municipalities
68 In 2008, there were 78 providers of home care (3 more than in 2007).
1500
5,000
0
Social overwiew 2009	49
The way we live
still had no service of this kind available (2007: six municipalities). Although rising by 3% compared with the previous year, the number of users of home care (5,780 in 2008) remains below the number of people in care at old people's homes. On home care, the objective of the resolution - 3% of the population by 2010 - is still far from being achieved, since the relevant share in 2008 was only around 1.7%.
Table 28: Number of people in old people's homes per 100 inhabitants aged 65 or above, Slovenia, 2000-2008
Year	Number of people in care	Size of population aged 65 or above	Per 100 inhabitants aged 65 or above
2000	11,905	281,406	4.2
2001	12,346	288,548	4.3
2002	13,051	294,654	4.4
2003	13,498	300,155	4.5
2004	13,098	306,484	4.3
2005	13,641	312,874	4.4
2006	13,699	319,631	4.3
2007	13,856	326,847	4.2
2008	15,235	334,029	4.6
Source: SORS; calculations by IMAD.
Figure 35: Share of population aged 65 or above in long-term care at institutions and at home; selected European countries, 2005, in %
27
Home care ■Institutional care
24 21 18 15 12 9
0lllllllllllllll.
S	°-°F ? s -S S .S-
Source: OECD Health Data, SORS, Social Protection institute; calculations by IMAD. Note: For some countries, data for 2005 are not available. Since changes at annual levels in individual countries are relatively modest, in such cases the most recent available data are used for comparison. This applies to France (last data on institutional care for 2003), Belgium (last data on both forms for 2004), Slovenia (last data on home care for 2008, no data for 2005), the United Kingdom (last data on both forms for 2004) and Austria (last data on both forms for 2003). For certain countries (Ireland, Slovakia, Spain), there are no data on home care.
In long-term care, Slovenia lags behind other European countries mainly with regard to home care. Higher participation of elderly population in institutional care is mostly recorded by developed Northern-European countries, although Slovenia is certainly not a country with modest capacities. Based on comparable data, a particularly pressing lack is observed in participation in home care. In all other countries for which data are available, a considerably larger share of the elderly population uses home-care services rather than institutional care: in Slovenia, use of home-care services is considerably below use of institutional care services. In those countries, home care plays an important role in the total provision of long-term care services to the elderly population, while in Slovenia its underdevelopment implies a lack of capacity to satisfy these needs and increases the pressure for admittance to old people's homes.
4.2.2 Expenditure on long-term care
The year 2007 saw a clear increase of expenditure on long-term care from private sources. Total long-term care69 expenditure growth, however, slowed to 2.4% in real terms. After the significant upward trend in public expenditure on long-term care recorded in 2004 and 2005, 2006 and 2007 were marked by an increase in expenditure from private sources (2006: by 7.2%; 2007: by 10.1%). A significant rise was observed both in private expenditure on long-term health-care services and in private expenditure on long-term social services, the latter mainly comprising supplements for accommodation and food in old people's homes, which rose as a result of larger capacity and the possibility of opting for a higher (more expensive) standard in the new homes. At the same time, the growing private expenditure on long-term social care in 2006 and 2007 also depended on higher household expenditure on home care. In 2007, this increase may have been partly due to changes in the system for financing family assistants or a considerable reduction in the public expenditure for this purpose. This affected the extremely slow growth in public expenditure on long-term social care, which in 2007 amounted to only 0.1%. Compared with the year before, public expenditure on long-term health care slightly increased. Total expenditure on long-term care saw a rise in private expenditure by source of financing (to 24.1%), and an increase in expenditure on social care (to 38.5%) by function.
Cumulatively speaking, in the period 2003-2007, expenditure on long-term care in Slovenia grew by 20.8% in real terms (with an annual average of 4.8%). A similarly high increase in total expenditure on long-term care was recorded in Finland, and even higher rates in Spain and France, but increases were lower in Germany and Sweden, where the system of long-term care is better developed.
69 Total expenditure on long-term care includes expenditure in long-term health care (also included under expenditure on health) and expenditure on long-term social care.
50	Social overwiew 2009
The way we live
Figure 36: Cumulative real growth index for expenditure on long-term care in Slovenia in 2003-2007 (2003=100)
Figure 37: cumulative real growth index for total expenditure on long-term care in Slovenia and selected European countries in 2003-2007 (2003=100)
-Total expenditure on long-term care
----Public expenditure
-----Private expenditure
Source: SORS; calculations by IMAD.
Although only a small quarter of the total expenditure on long-term care is intended for long-term home care, this amount is increasing. Data on expenditure indicate that most long-term care (both health and social) in Slovenia is still provided in institutions, yet the share of expenditure for long-term home care has been on the increase, accounting for 23.3% in 2007, a slight increase on the previous year (by 0.7 p.p.).
Total expenditure on long-term care as a share of GDP went down to 1.02% in 2007 (2006: 1.08%), while expenditure on long-term health care was 0.63% of GDP and expenditure on long-term social care was 0.39% of GDP. Slovenia's share corresponds to the average of 25 EU countries for which data are available; figures are lower in more developed EU countries and higher in most new Member States.
-----Finland
----France
-Germany
—a— Netherlands —■-■- Spain —*■— Sweden —•— Slovenia
7/ ///' / /	
* /■'	
' A'	
' j-'	
/ y	
/ / / / ^—..	
2003	2004	2005	2006	2007
Source: OECD Health Data 2009; for Slovenia: SORS.
Figure 38: Total expenditure on long-term care as a share of GDP, EU-25, 2006, in %
2.5 «-
ilJiliifl-Pi
"C ^ -- --
^ ü
Source: Eurostat, SORS.
Table 29: Expenditure on long-term care by source of financing and function, 2003-2007
	In EUR million			Share of GDP, in %			Structure, in %			Real growth, in %	Real growth, in %	Aver. annual real growth, in %
	2003	2006	2007	2003	2006	2007	2003	2006	2007	07/06	07/03	03-07
Long-term care	260	334	354	1.04	1.08	1.02	100.0	100.0	100.0	2.4	20.8	4.8
By source of financing:												
Public sources	198	258	267	0.79	0.83	0.77	76.1	77.1	75.4	0.1	19.7	4.6
Private sources	62	76	87	0.25	0.25	0.25	23.9	22.9	24.6	10.1	24.1	5.5
By function:												
Health care	157	206	218	0.62	0.66	0.63	60.3	61.7	61.5	2.1	23.4	5.4
Social care	103	128	136	0.41	0.41	0.39	39.7	38.3	38.5	2.8	16.9	4.0
Source: SORS, Labour Force Survey; calculations by IMAD.
135
125
130
120
125
™ 120
115
115
o 110
110
105
105
100
100
3.6
2.0
1.5
1.0
0.5
0.0
51	Social overwiew 2009
The way we live
4.3 Housing
There was an increase in the housing fund in 2008. At
the end of 2008, the housing fund comprised 830,047 dwellings,70 6.7% up on the 2002 census. Growth followed the trend in previous years, i.e. around 1% annually. The number of completed dwellings rose significantly compared with previous years (by around 11% compared to 2007), while the number of dwellings under construction, which had shown a continuous upward trend up to 2008, decreased (at the end of 2008, the number of dwellings under construction was around 16% lower than a year before). The average useful floor area of dwellings had been slightly increasing over past years (in 2008, the average useful floor area of dwellings in the housing fund was 76.9 m2 and of newly built dwellings 110 m2). Dwellings in non-urban settlements were just over 10 m2 bigger on average than those in urban settlements. As in 2007, a total of 20% of all dwellings were without central heating and 7% did not have a bathroom.
Although housing conditions are generally improving, they remain rather unfavourable for low-income population groups and tenants. According to the results of the survey on living conditions EU-SILC, the share of Slovenian households living in bad dwelling conditions71 decreased to the EU average (EU 27: 18%
70	All dwellings on the territory of the Republic of Slovenia. According to SORS, a dwelling is any structurally unified unit intended for residence, with one or more rooms, with or without appropriate utility spaces, and with at least one separate entrance.
71	The share of households with problems such as a leaking roof,
Table 30: Households living in bad dwelling conditions, Slovenia, 2005-2007, in %
Households	2005	2006	2007
Total	20	22	18
By income:			
1st quintile	27	31	28
2nd quintile	21	25	19
3rd quintile	19	19	16
4th quintile	14	19	14
5th quintile	12	14	11
By tenure status:			
Owners	18	22	17
Tenants	32	33	28
Users	17	20	19
Source: SORS.
in 2007). However, conditions significantly depend on household income and on whether the dwelling is rented or privately owned: in the quintile of the households with lowest income, 28% of households lived in bad dwelling conditions, and the same percentage applied to tenants.
About a half of low-income households and about a half of the tenants find it hard to meet their housing costs.
While only a third of all households (precisely 31%, which is the same as the EU average) reported housing costs to
damp walls/floors/foundation, or rot in window frames or the floor.
Table 31: Level of burden of total housing costs to households, Slovenia, 2005-2007, in %
	2005			2006			2007		
Households	A heavy burden	Somewhat a burden	Not burden at all	A heavy burden	Somewhat a burden	Not burden at all	A heavy burden	Somewhat a burden	Not burden at all
Total	32	57	10	34	54	11	31	56	13
By income:									
1st quintile	48	46	6	51	41	7	49	42	9
2nd quintile	40	54	6	41	51	8	36	55	9
3rd quintile	32	60	8	32	58	10	29	60	11
4th quintile	23	66	11	26	62	12	22	63	15
5th quintile	13	64	22	14	65	20	13	64	23
By tenure status:									
owners	31	59	10	33	55	11	30	57	13
tenants	53	41	6	59	36	5	53	41	6
users	22	63	15	27	58	15	24	60	16
Source: SORS, Labour Force Survey; calculations by IMAD.
Social overwiew 2009	52
The way we live
be a heavy burden, these expenses were hardly met by about a half of low-income households and tenants: 49% of households within the lowest income quintile and 53% of renting households considered housing costs a heavy burden. The quintile with highest income found housing significantly less of a problem, although the cost of housing was a burden for 13% of them. Owners of dwellings were burdened less than tenants, yet their burden was nevertheless also rather heavy (housing costs were a heavy burden for 30% of owners).
Given the high housing prices, average-income households are unable to purchase an adequate dwelling. After reaching a peak in 2008, housing prices eventually began to fall. Although annual statistics point merely to a slowdown in the dynamic growth of prices of second-hand dwellings, which has also been typical of the last five years, over which time trends have been systematically monitored, more detailed analysis reveals that a turn-around occurred in 2008, triggered by the recession, bringing prices down by the second quarter of 2009 by more than 11% from their peak in the third quarter of 2008. According to data from the Surveying and Mapping Authority, the average price of a second-hand dwelling in 2008 reached 1,900 EUR/ m2 (i.e. 2.1 average net wages in 2008), but there were considerable differences among regions, with prices in Ljubljana peaking at 2,700 EUR/m2. In the period 2004-2009, the total volume of housing loans increased significantly; at the end of September 2009, it was 4.7 times higher than at the end of 2004. High housing prices prevent even average income households from obtaining - by purchase or rent - a dwelling that Slovenian regulations72 define as adequate. Therefore, various measures are taken by the state to encourage purchase through the housing fund, at lower prices and non-profit rent, yet because of limited funds, the state does not succeed in meeting needs; at the same time, there is also a considerable surplus of housing at market prices.
Housing policy continues to encourage home ownership. The majority of the older generation took advantage of privatisation and other measures to successfully solve its housing problems, placing Slovenia among the top European countries as far as home ownership is concerned. Over 80% of all dwellings in Slovenia are owner occupied, which - in addition to negative impacts on population mobility and housing-fund maintenance - also has a positive role as it provides an additional source of social security, since this is mostly not mortgaged and can be turned into additional income in case of distress. However, the Surveying and Mapping Authority finds that the market value of a typical family house differs considerably depending on the location (up to ten times), which means that the potential social role of property ownership is very
72 Rules on renting non-profit apartments, OG RS No. 14/2004. An adequate dwelling is defined by floor area and construction standards.
Figure 39: Second-hand dwellings price trends, index 2005=100, Slovenia, 2003 - 2008
160
70 60
2003 2004 2005 2006 2007 2008 Source: SORS; calculations by IMAD.
unequal. The share of rented dwellings is very low (less than 10% of the housing fund) and a considerable share of privately owned housing is unoccupied, which could be influenced by the tax policy. Housing policy is too much oriented toward encouraging ownership, and too little into promoting non-profit renting and making market renting a normal economic activity. This could facilitate the spatial mobility of the population and improve the maintenance of the housing fund. The current relatively high73 taxes on profits from renting for natural persons are also reflected in a high share of the underground economy. The general legalisation of renting relationships could be partly triggered by the anticipated tax on real property value, provided that it introduced a tax exemption for reported residence.
4.4 Access to childcare and education
In international analyses, the most commonly used indicator of the accessibility of education is the participation rate, which shows that an individual had the opportunity to participate in education. Less often, accessibility is measuredthrougheducational attainment. Expenditure on education is another important aspect of accessibility. An additional aspect is the educational mobility of the population.
4.4.1 Participation in education
The following section outlines the participation of children in organised pre-school education and primary school, and the participation of young people in upper
73 Natural persons' profit from renting is not taxed separately, as with other capital income, but falls into the total income-tax base.
Social overwiew 2009	53
The way we live
secondary and tertiary education. Along with youth enrolment, the participation of adults in education and their related socio-economic characteristics are also important in social development.
Participation of children in organised pre-school education and childcare
The inclusion of children in organised pre-school education can have a positive influence on a child's development, while accessible pre-school education and childcare can also contribute to achieving a balance between work and family life. Participation of children in kindergartens is important in terms of their oral, cognitive and social development, as well as their readiness for school (Gaber, Marjanovič Umek, 2009, p. 71). International surveys show that children attending kindergartens on average achieve better results in the international OECD PISA survey74 (Lohmann et al., 2009, p. 41), while surveys on the effects of children's participation in kindergartens carried out in Sweden and Finland have shown that those children had better learning achievements in school (The child-care transition, 2008, p. 10), and that long-term positive implications are also seen in better educational attainment rates (Plevnik et al., 2009, p. 31). Organised pre-school programmes offer children from less privileged backgrounds the opportunity to develop their skills and potentials more than would otherwise be the case. Research conducted in Slovenia has indicated that participation in kindergarten75 exerts a positive effect on the readiness for school of children whose parents attained lower levels of education. Inclusion in kindergartens primarily stimulates the school readiness of children whose parents have attained lower education levels, or compensates for deficits in development and learning that are probably due to less privileged backgrounds (Gaber, Marjanovič Umek, 2009, p. 85). Providing access to organised forms of pre-school education and childcare may, in addition to the positive influence on the development of children attending kindergartens, also contribute to the employability of women, and, according to international surveys, a positive correlation also exists between the accessibility of organised pre-school education and the fertility rate (Lohmann et al., 2009, p.41).
The share of children attending kindergartens is rising; however, in the following years, an increase in demand for kindergarten capacity is to be expected. In the school year 2008/2009, 49.2% of children aged 1-2 and 84.1% of children aged 3-5 were attending kindergartens. In comparison with the previous school year, the increase in the number of children attending kindergartens was observed mostly in the first age group (1-2 years: by 5.5
p.p.). According to the last internationally comparable data available for 2007, the share of children aged 3-5 attending organised forms of pre-school education in Slovenia amounted to 79.5%, exceeding the EU-27 average by 0.7 p.p.; indeed, in the past year (2007) and in the period 2000-2007, the share of children attending organised forms of pre-school education increased by more than the EU-27 average. The participation of children in kindergartens is rising steeply, in 2000/20012008/2009, an increase of 20.0 p.p. was observed in the first age group, and of 16.2 p.p. in the second age group. A growing need for kindergarten capacity is driven by the rise in the total fertility rate and number of children born76 in the last years, as well as the adoption of the Act Amending the Pre-School Institutions Act (ZVrt-D), which has provided free kindergarten for the second child since 2008. Considering that the number of children born in 2008 rose substantially (by 10.1% or 1,994), even greater pressure on pre-school capacity is to be expected in the coming years. Sweden can be mentioned here as an example of good practice in assuring accessibility of organised forms of pre-school education and childcare, in which municipalities must ensure an available place in organised forms of pre-school education and childcare from year 1 to enrolment in a pre-school programme or obligatory school programme, where an available place needs to be ensured within 3 or 4 months after the receipt of the application for a child's enrolment, without exceptions and undue delay (Plevnik et al., 2009, p. 70).
Figure 40: Participation of children aged 1-2 and 3-5 in kindergartens, Slovenia, 2000/2001-2008/2009, in %
Children aged 1 - 2 I Children aged 3 - 5
74	Programme for International Student Assessment. PISA is an international survey on reading, mathematical and scientific literacy conducted under the auspices of OECD. It studies 15-year-old pupils, regardless of the type of school in which they are enrolled.
75	When checking child's oral competency and intellectual skills.
20 10 0
2000/2001	2007/2008	2008/2009
Source: SORS; calculations by IMAD.
Participation of young people in primary schools, upper secondary schools and tertiary education
In the period 2000/2001-2008/2009, the number of pupils in primary schools decreased, yet the number
76 Number of live-born children.
100
Social overwiew 2009	54
The way we live
of enrolled pupils is expected to increase over the following years due to rising birth rates. A total of 163,458 pupils were enrolled in primary schools77 in the school year 2008/2009,78 a drop of 0.8% on the year before and 11.1% lower than in 2000. The number of pupils enrolled in primary schools in 2007 and in the period 2000-2007 declined more than the EU-27 average. The drop in the number of children attending primary schools is related to demographic changes (low birth rates) and the decrease in the size of generations for enrolment in primary school. However, since the number of live-born children has been on the increase since 2004, a rise in the number of pupils enrolled in primary schools is expected in the coming years. All pupils attending primary school in the year 2008/2009 were enrolled in nine-year primary school.
Figure 41: Number of pupils enrolled in primary schools and projections of the number of pupils of official primary school age (6-14 years) enrolled in primary schools, Slovenia, 2000-2020
190000 185000 180000 175000 E 170000
=s
-z.
165000 160000 1 55000 150000
Source: SORS, Eurostat; calculations by IMAD.
Note: The data report on the number of children enrolled at the beginning of the school year. Projections of the number of pupils enrolled are shown from 2009 onwards. The table shows Eurostat's population projections for Slovenia, EUROPOP 2008, baseline scenario, convergence scenario, convergence year 2150. Method: assessment of projection by growth dynamics of the population quota aged 6-14.
Slovenia enjoys a high international position in students' learning achievements; however, these are strongly influenced by an individual's socio-economic status. The findings of the international 2007 Timms study79 show that the mathematics achievement of fourth- and eight-grade Slovenian pupils is slightly above the international average,80 while their science achievement is significantly higher. Given the relatively favourable position of Slovenia in international
77	Pupils enrolled in primary schools and primary schools with special curriculum.
78	At the beginning of the school year.
79	Trends in International Mathematics and Science Study.
80	The study was conducted in 62 countries.
comparisons, pupils' learning achievements are strongly marked by the socio-economic status of their parents. Higher education of parents81 is associated with higher levels of achievement by children, with the highest levels of education being attained by children of parents with university education and the lowest by children of parents with completed primary-school education only. These differences in learning achievements are also suggested by national examinations in elementary schools. In the school year 2007/2008, the highest levels in mathematics performance were achieved by students in Central Slovenia, the Goriška region and Notranjsko-kraška region. In the first and the third region there is an above-average share of population with tertiary education. The poorest results, meanwhile, were obtained by students of the Pomurska region, which has the highest share of people aged 15 or more years with low educational attainment, followed by the Podravska and Zasavska regions.
The number of young people enrolled in upper secondary schools is declining due to demographic reasons. Participation in upper secondary schools still remains rather high, but has witnessed a slight drop in 2007. According to the latest internationally available data, the participation rate of those aged 15-19 in upper secondary education82 was the highest among EU-27 countries, thus substantially exceeding the EU-27 average, as was already the case in the previous years of the period 2000-2007 (2007: Slovenia: 79.7%; EU-27: 59.0%). However, a slight drop was recorded compared
Figure 42: Share of young people aged 15-19 participating in upper secondary education, Eu-27, 2007, in %
85 80 75 70 65 60 55 ^ 50 45
Source: Eurostat; calculations by IMAD.
Note: This covers pupils enrolled in ISCED programmes 3.4.
81	The highest educational attainment of one parent is considered.
82	ISCED 3,4.
projections
Social overwiew 2009	55
The way we live
with the previous year. The share of young people enrolled in upper secondary education is declining as a result of the decrease in size of the generation for enrolment in upper secondary schools. In the school year 2008/2009,83 a total of 87,501 students were enrolled in upper secondary schools. Their number had dropped by 4.5% compared with the previous year and by 16.5% compared to 2000.
The structure of young people participating in upper secondary education by type of educational programme has undergone a significant change in the period 2000/01 to 2007/08. In 2008/09, the share of young people enrolled in two-year lower vocational and three-year upper secondary vocational programmes from the period after 2000/01 continued to decrease, and enrolment rates in vocational technical programmes and in the preparatory course for the matura exam have also been in decline for several years, while the share of pupils enrolled in grammar schools and four- and five-year upper secondary technical and other vocational programmes has continued to grow.
compared with 2006 and in the period 2000-2007, it rose faster than the stated average.
In 2008/2009, the number of applications86 for higher-professional and undergraduate university programmes was for the first time in the period 2000/2001-2008/2009 smaller than the number of enrolmentplaces. The number of applications exceeding admissions in higher-professional and undergraduate university programmes has been dropping since 2004/2005, and in 2008/2009 the number of applications for the first time fell below the number of enrolment places, by 7.8%. The number of available places increased by 2.9% in the last year, to a total of 25,647, while the number of applications decreased by 6.2%, to a total of 23,658. In the period 2000/2001-2008/2009, the number of enrolment places rose, mostly due to growth in the number of higher-education institutions, while the number of applications declined, primarily as a result of demographic changes (decreasing number of pupils enrolled in upper secondary schools and in graduates from upper secondary schools).
The share of young people enrolled in programmes which provide direct enrolment in tertiary education has been rising and was slightly above the EU-27 average in 2007. In terms of accessibility of tertiary education, the share of young people enrolled in or completing upper secondary programmes that provide direct access to tertiary education is of major importance. In 2008/2009,84 the share of young people enrolled in programmes that provide direct access to tertiary education totalled 83.7%, which is an increase of 0.9 p.p. on the year before, signifying a continuation of the positive trend from previous years. Compared with 2000/2001, this share increased by 11.5 p.p. In 2007, the share of young people enrolled in programmes providing direct enrolment in tertiary education85 was just above the EU-27 average (Slovenia: 81.8%; EU-27: 81.0%), while
83	At the beginning of the school year.
84	At the beginning of the school year.
85	In ISCED 5a or ISCED 5b programmes.
The ratio between the number of students enrolled in tertiary education and the total population in the 2029 age group increased slightly in 2008-2009. It was
40.0%, an increase of 0.1% compared with the previous year, putting a halt to the positive trend established in the years since 2000-2001. As regards the ratio between the number of students enrolled in tertiary education and the total population in the 20-29 age group,87 Slovenia outpaces the growth of the EU-27 average and is ranked among the leading EU-27 countries on this indicator. Moreover, in 2000-2007 the stated ratio increased more than the EU-27 average. In 2008/2009, the number of
86	First application period.
87	The ratio of the number of students enrolled in tertiary education to the total population in the 20-29 age group is used to measure the capacity of the educational system for participation in tertiary education. Calculation of the indicator: (number of all enrollments in tertiary education/number of people in 20-29 age group)*100.
Table 32: Participation in tertiary education and structure of students by type of programme, Slovenia, 2000/2001-2008/2009
	Number of enrolled students	Growth in number of students, in %		Participation by type of programme, in %		
		2007-2008	2000-2008	2000	2007	2008
Total	114,391	-0.9	25.0	100	100	100
Post-secondary vocational	16,263	-1.0	237.3	5.3	14.2	14.2
Higher-professional (adjusted to Bologna Declaration compliant and old programmes)	34,923	-5.4	-12.0	43.4	32.0	30.5
University (adjusted to Bologna Declaration compliant and old programmes)	51,674	-1.4	19.9	47.1	45.4	45.2
Specialist	485	-2.0	155.3	0.2	0.4	0.4
Master's (adjusted to Bologna Declaration compliant and old programmes)	9,052	19.0	142.6	4.1	6.6	7.9
Doctoral (adjusted to Bologna Declaration compliant and old programmes)	1,994	26.0	N/A	N/A	1.4	1.7
Source: SORS; calculations by IMAD. Note: N/A - not available.
Social overwiew 2009	56
The way we live
Figure 43: Ratio of number of participants in tertiary education to number of population aged 20-29, EU-27, 2007
: ™ -o tJ^-S £ E £ .E .2 s "5 ™ -S I
ll^S^J
c .E o 1
Š ID i 3 > Ï -i? E cPunUrn
Source: Eurostat; calculations by IMAD.
students enrolled in tertiary education saw a drop for the second year running, but rose substantially compared with 2000/2001. However, the favourable picture of participation in tertiary education conceals certain problems (fictive enrolment, low efficiency in studies).
The participation of adults in lifelong learning is relatively high, but has been on the decline for several years. According to the labour-force survey (LFS), 13.9% of the population aged 25-64 took part in formal and non-formal education88 in 2008, putting Slovenia above the EU-27 average (9.6%),89 but still behind the countries with the highest participation rates in lifelong learning (Denmark, Finland and the United Kingdom). However, despite the relatively favourable international standing of Slovenia, it should be noted that participation in lifelong learning has been gradually decreasing over recent years.
The participation of adults in formal and non-formal education is above the EU-27 average. According to the international Adult Education Survey, there were
40.6% of adults90 aged 25-64 participating in formal or non-formal education in 2007,91 exceeding the EU-27 average by 4.6 p.p. Participation in formal education totalled 8.7%, 2.4 p.p. above the EU-27 average, while 36.2% of adults attended non-formal education, which is 3.5 p.p. above the EU-27 average. In Slovenia, the most frequent barriers to education among those that did not pursue education but wished to do so were: education conflicted with their work schedule (55.5%), education was too expensive or they could not afford education (48.5%), family responsibilities (37.7%), and, least frequently, they were not confident with the idea of returning to something resembling school (7.3%), did not have the prerequisites (7.6%), and age or health reasons (15.5%).
As regards the participation of adults aged 25-64 in formal or non-formal education, there are differences in terms of the selected socio-economic characteristics.
The participation in education of the population aged 25-34 is almost twice as high as the participation of the oldest age group observed (55-64 years). This has several causes. Compared with the young population, the older population on average expect to have less benefit from education; a large part of education is related to the needs of work and the labour-activity rate is relatively low among the older age group. A frequent barrier to education is age or health reasons, which were reported by 31.6% of people aged 55-64 who did not pursue education but wished to do so. Participation in education also reveals great differences in terms of educational attainment. The participation rate increases with higher levels of education, with the participation rate of those who have completed no more than primary school far behind the participation rate of those with an upper secondary and tertiary education. The share of people who stated that education was too expensive or that they could not afford education is much higher among people with a lower level of education than those with an upper secondary and tertiary education (68.1%; upper secondary: 48.9%; tertiary: 33.2%), which is also related to the lower income received by individuals who have completed no more than primary school. People with a lower level of education often regarded age or health reasons as the biggest barrier to education, which is also related to the relatively high proportion of people with a lower level of education in older age groups. Data on participation in education by activity status
10
0
88	The indicator of participation in lifelong learning measures the share of the population in the 25-64 age group participating in education and training in the four weeks preceding the survey. The indicator is calculated on the basis of the annual average and refers to just one quarter of the year. The altered calculation was introduced in October 2006. The European Commission's experts point to the methodological shortcomings of the indicator, particularly as regards measurement of participation in education and training in just the weeks preceding the survey. This means that the results strongly depend on the time the survey is carried out.
89	Provisional figure.
90	The Adult Education Survey is a pilot survey conducted between 2005 and 2008, with reference year 2007. The survey is to be carried out every five years. It measures the participation of adults aged 25-64 in formal and non-formal education during the last 12-month period preceding the survey or the last calendar year. In Slovenia, respondents reported on their educational activities pursued during the 12 months prior to the carrying out of the survey. Due to methodological differences in the calculation of the indicator, the data on participation in education derived from the Adult Education Survey are not fully comparable with those of the Labour Force Survey.
91	According to the international Adult Education Survey - a pilot survey, data is only available for 2007.
Social overwiew 2009	57
The way we live
indicate the highest percentage for people performing intellectually more demanding professions which require a higher level of education (1-392 according to Standard Classification of Activities), and the lowest for people performing less-skilled professions (8-993 according to Standard Classification of Activities). Participation in education is also characterised by differences depending on population density, which are still relatively small due to the daily migration of the population from intermediate-urbanised and sparsely populated areas to their workplace in larger urban centres that also offer a wide variety of education options.
Figure 44: Participation of adults aged 25-64 in formal or non-formal education by selected socio-economic characteristics, Slovenia, 2007, in %
Figure 45: Graduation rates in upper secondary education, Slovenia and OECD members, 2007, in %
Total Men Women Aged 25-34 Aged 35-54 Aged 55-64 Basic or less Upper secondary
40.6 38.1 43.1
12.7
39
		
		47.7
	27.5	
	21.5	
Employed Unemployed Inactive ISCO 1-3 ISCO 4-5 ISCO 6-7 ISCO 8-9
Densely-populated area fSSHSSHSSHSSR 44.1
Intermediate populated areas ^SSSSSSSSSSSSSSÎ 40
Sparsely populated area ^SSSSSSSSSSSSSS 39.5
0 10 20 30 40 50 60 70
Source: Eurostat, Adult Education Survey.
Note: According to the International Standard Classification of Occupations (ISCO), legislators, senior officials and managers are Group 1; professionals Group 2; technicians and associate professionals Group 3; clerks Group 4; service workers and shop and market sales workers Group 5; skilled agricultural, forestry workers, fishery workers, hunters Group 6; craft and related trade workers Group 7; plant and machine operators and assemblers Group 8; and elementary occupations Group 9.
4.4.2 Graduates, educational attainment of adult population and population mobility
The completion rate in upper secondary94 education is high, but in 2007 a drop was recorded. In 2007, it stood at 91%, exceeding the EU-19 average, and also that of
92	Legislators, high officials and managers (Standard Classification of Activities - Group 1), experts (Standard Classification of Activities - Group 2), technicians and other associate professionals (Standard Classification of Activities -Group 3).
93	Plant and machine operators and assemblers (Standard Classification of Activities - Group 8) and elementary professions (Standard Classification of Activities - Group 9).
94	The completion rate in upper secondary education is the share of young people who have completed upper secondary
education compared with the total population at the typical age of upper secondary school completion.
1...
m ZD
Source: Education at a Glance 2009, 2009.
OECD members, by 7 p.p. However, compared with 2006, this level fell by 6 p.p. Considering the high level of upper secondary education qualification, the share of early school leavers remains rather low compared to the E-27 average, amounting to 4.3% in 2007 (EU-27: 15.2%).
The number of young people completing secondary school is declining due to less numerous generations.
As a result of declining enrolment in upper secondary schools, fewer students are completing upper secondary school. In 2007/2008, 21,762 of students completed upper secondary school, which is a drop of 6.1% on the year before. Compared with 2000/2001, this number decreased by 13.0%.
By changing the structure of young people enrolled in upper secondary education by type of programme, the structure of young people completing upper secondary education is also altered. In the period 2000/01-2007/08, the highest increase was registered in the share of young people who completed the grammar-school programme,95 totalling 39.8% in 2007/08, which was a rise of 14.7 p.p. on 2000/01. Moreover, another rise was observed in the share of students completing vocational courses, while there was a drop in the share of young people completing other programmes. The increase in the share of young people completing grammar school may be attributed to better opportunities for further education at tertiary level in comparison with those who completed other educational programmes.
In the period 2000-2008, the number of tertiary education graduates increased considerably. The
growth in number of higher-education institutions and
95 Includes young people who completed grammar school and matura preparatory course.
90
80
70
60
50
40
30
52.2
42.6
22.2
67.6
58	Social overwiew 2009
The way we live
enrolment places in higher education, and the correlated accessibility to tertiary education and the situation in the labour market, was marked by increased enrolment in tertiary education, and consequently also by the number of graduates. In 2008, there were 17,221 graduates, 3.2% more than the year before and 49.8% more compared with 2000. A substantial increase was also observed in the number of graduates per 1,000 people aged 20-29. In 2008, they amounted to 60.3%, an increase of 21.5% compared with 2000/2001. According to the number of graduates per 1,000 people aged 20-29, Slovenia ranks in the upper half of EU-27 countries. Furthermore, it is also ranked in the upper half of the EU-27 in terms of the increase observed in the period 2000-2007.
The educational attainment of the population is gradually improving. The higher levels of educational attainment of the adult population aged 25-64 are due to higher participation rates in upper secondary and tertiary education. According to the Labour Force Survey (LFS), the share of the population within the 25-64 age group who have completed no more than primary-school education decreased in the period 2000-2008, and the share of adults with lower or middle-level vocational education, general upper secondary or post-secondary vocational education also slightly dropped, while the share of population with upper secondary technical education, higher undergraduate education (higher professional and university undergraduate) and higher postgraduate education slightly rose.
Slovenia is above the EU-27 average in terms of a low share of adult population with low levels of education and tertiary education and in terms of a higher share of population with upper secondary education. According to the Labour Force Survey, the share of population with low levels of education amounted to 18.0%, 10.5 p.p. less than the EU-27 average. There were also 59.4% of people with an upper secondary education, exceeding the EU-27 average by 12.3 p.p. As to share of population with
Table 33: Educational attainment of population aged 25-64, Slovenia, 2000-2008, in %
	2000	2005	2006	2007	2008
Total	100.0	100.0	100.0	100.0	100.0
No formal education, incomplete primary education (1-3 grades)	0.7	0.4	0.4	0.5	0.5
Incomplete primary education (4-7 grades)	3.3	2.1	2.0	1.7	1.8
Primary education	20.8	17.2	16.0	16.0	15.7
Lower or middle vocational education	28.2	28.3	28.2	28.2	27.9
Upper secondary technical education	25.5	27.9	27.8	27.6	27.5
General upper secondary education	5.5	4.0	4.1	3.7	4.1
Higher vocational, short-term higher education, specialisation after short-term-higher education	7.3	6.4	6.5	6.4	6.4
Higher professional education	2.1	3.2	3.9	4.1	4.4
University undergraduate education	5.6	9.1	9.4	10.0	10.2
Post-graduate education (specialisation, master's degree, doctoral degree)	0.9	1.4	1.6	1.6	1.6
Source: SORS, Labour Force Survey; calculations by IMAD.
Figure 46: Number of graduates per 1,000 inhabitants aged 20-29, EU-27, 2007
3-2 C "O J5	rn-2 O TO ^	TO ;
3 o i «
i Är^ 00	^ (^^O-^^US
) C f ^ - •— u C 3 S u m
E
; v s
1 u
— ü
Source: Eurostat.
tertiary education, Slovenia, with 22.6%, lagged behind the EU-27 average by 1.6 p.p. In the period 2000-2008, the share of population with a low level of education decreased more than the EU-27 average. The increase in the share of people with upper secondary education was moderate; however, in the previous years observed, this share was significantly above the EU-27 average. The share of population with tertiary education rose above the EU-27 average.
The large volume of educational mobility reveals two social processes: social and economic changes and the democratic character of society, which provides every individual with the opportunity to obtain the education for which he/she strives and has the skills for. Every society is composed of more or less closed classes on
10
0
Social overwiew 2009	59
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Figure 47: Educational attainment of population aged 25-64, EU-27, 2008, in %
■ Low	■ Upper secondary	«Tertiary
Source: Eurostat, Labour Force Survey; calculations by IMAD, 2009.
the hierarchical ladder of social power, wealth, influence or knowledge. It is also characteristic of all societies for the classes with more power to make every effort to protect their privileges, thus preventing those with little social influence to substitute them - that is to preserve the existing hierarchy of social power. Moreover, every individual usually strives to improve his/her position in society by moving up to a higher or more influential class.
Indeed, social mobility is a process in which individuals are rising and falling from one social class to another.
These two processes are in constant opposition - one tries to preserve an unaltered state (e.g. the caste system), while the other demands changes. Most societies fall somewhere between the two extremes. Still, it is not just social justice, but also modernisation, with the related growing need for educated people, that forces societies to transform closed caste systems into open societies in which, in principle, access to any education and social position is guaranteed in accordance with people's capacities. Moreover, the volume of transitions between (educational) classes reveals the open and democratic nature of any individual society - the greater the level of transition, the more open the society. This is why intergenerational mobility depends so heavily on both the openness of society and the pace of technological change. However, the most important part of mobility is educational mobility: the transition of people from one educational group to another, both within groups as well as between generations.
Several research studies on values show that there are common patterns in people's views that affect their actions and are strongly related to the national culture or the predominate system of values. (Human Development Report 2000, Schwartz, 2007). We were therefore interested whether educational mobility is primarily influenced by the prevailing values, or if it depends on accidental influences. The volume of educational mobility inter alia shows if a society has witnessed great changes in methods of production
Box 4: Analysis of educational mobility of population based on information from the European Social Survey
To determine the existence of differences or similarities in educational mobility among European countries, the analysis used data gathered from the European Social Survey for 2006 (ESS), namely five variables: level of education of respondent, his/her partner, father and mother, and the sex of respondent. Answers on education were grouped into the following five classes: 1) no more than completed primary school, 2) three-year secondary school, 3) grammar school or four-year secondary school, 4) two-year college or university, 5) completed university education or more. We obtained data for 19 countries where this survey was carried out, and which had data for at least some of these indicators.
To establish what differences, if any, are in educational mobility among European countries, we used three measurements: index of mobility, correlation coefficient and inertia index. The index of mobility is a unit denoting the ratio of actual number of steps of individuals on the educational ladder between generations to the expected number of steps, i.e. the number we would get if the society had been fully open (the theoretical frequency). The greater the value of the index of mobility, the more open the society. The correlation coefficient shows the reverse transformation: the more its value departs from 0 to 1 or -1, the more closed the society, i.e. the education of children largely depends on the education of their parents. The inertia index is the conversion rate between the number of individuals who attained the same education level as their parents in comparison with the expected number (the theoretical frequency) that we would obtain if the society had been fully open.
To determine whether any patterns of similarities and differences in education mobility exist among European countries, we used the statistical method of multidimensional scaling (Cluster analysis, Ward's method using Euclidean distances). All six of the above-mentioned types of mobility were included in the analysis (father-son, mother-daughter, father-daughter, mother-son, respondent-partner and father-mother). Data for analysis were represented by the correlation coefficients, i.e. the value indicating the correlations between variables which implies the closed character of social (educational) classes.
60	Social overwiew 2009
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(mostly movements up the education ladder between generations), which led to an altered educational structure of the population. Moreover, based on the differences of educational attainment of spouses, we may indirectly determine the open or closed character of social classes.
To determine whether differences or similarities in education mobility between European countries exist, we used information contained in the European Social Survey 2006, for five variables: level of education of respondent, his/her partner, father and mother, and the sex of respondent (for methodological explanations: correlation of education levels between spouses (for the generation of parents and of respondents), correlation between educational attainment of father and mother, and their son or daughter were determined by means of the index of mobility, correlation coefficient and inertia index.
A glance at figure 48 immediately shows that educational mobility largely depends on the prevailing values and that there are obvious patterns of mobility. We may notice that European countries are divided into two groups according to their similarities: the Mediterranean group and the Continental-Nordic group. Only fifteen countries, for which we had all of the necessary information, were included in the analysis. However, these proved to be sufficient to give us a clear picture.
According to the pattern of educational mobility, Slovenia falls into the Continental group. The
Mediterranean group is composed of two subgroups: the first being "completely Mediterranean" (Spain,
France, Greece), while the other is slightly more mixed. In addition to Israel and Italy, there are also Poland and Ireland (characterised by prominence of religion and traditional values). The second group is slightly more heterogeneous, since it comprises three subgroups, with the most prominent being Switzerland and Germany. It appears that these two countries have a rather similar pattern of mobility which separates them from the other two subgroups, as was also shown by some other analyses (mortality patterns, patterns of desired child characteristics - Human Development Report). The second subgroup comprises three Nordic countries (Denmark, Norway and Netherlands), and the third includes the remainder - the United Kingdom, Luxembourg and Slovenia. We may therefore conclude that generation transitions in terms of educational attainment, as well as differences in the level of education between spouses, are largely dependent upon the patterns of values that prevail within a certain society. Societies with greater mobility allow greater and more frequent transitions among different socio-economic and education groups.
The cluster analysis only shows patterns of similarities between analysed units, and not their values, i.e. which of these groups are more and which are less open. We analysed only the relationship between spouses (the differences in educational attainment of spouses), as we assume that a greater difference in the level of education between spouses implies a more open character of educational classes, and thus also of other classes. The analysis was conducted using the inertia index. Figure 49 shows that countries linked to the "Mediterranean" group are more traditional or more closed than the
Figure 48: Classification of selected European countries by correlation coefficient of mobility, 2006
Source: ESS; calculations by IMAD.
40	60
Ward's method, Euclidean distances
Social overwiew 2009	61
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Figure 49: Inertia index of the educational attainment of spouses, European countries, 2006
Source: ESS; calculations by IMAD.
Figure 50: Total public expenditure on education as a share of GDP, EU-27, 2000 and 2006, in %

• caon ^ .
J2 C O ' 3 o.
g 5-5
Nordic countries or the countries from the Continental Europe. The most open are Germany and Switzerland, while Slovenia ranks in the middle of the two groups. We may thus conclude that the pattern of mobility for Slovenia is a mixture of the two extremes.
4.4.3 Expenditure on education
Total public expenditure on education96 has decreased as a share of GDP in recent years. In 2007, it dropped 0.47 p.p. over the previous year to 5.19% of GDP.97 This decline in total expenditure on education is associated primarily with demographic change (less numerous school-age generations) and the consequent drop in formal-education enrolment. In 2006, the most recent year for which international data are available, Slovenia exceeded the EU-27 average in public expenditure on education as a share of GDP, as it did over the entire 2000-2006 period; this relatively high expenditure is primarily a result of a high participation rate among young people.
Source: Eurostat, SORS; calculations by IMAD.
However, expenditure on pre-school education also dropped, despite an increase in enrolment. In the period 2000-2007, total public expenditure on education rose at all levels; the biggest rise was recorded in pre-school education and the smallest at the upper secondary level. Year-on-year, public expenditure on education as a share of GDP dropped most at the upper secondary level.
The share of total public expenditure on education earmarked for transfers to households has been dropping since 2001. In 2007, it stood at 8.0%, down
Figure 51: Total public expenditure on education by level of education, as a share of GDP, Slovenia, 20002007, in %
In 2007, total public expenditure on education declined for the first time since 2000, shrinking by 1.5% year-on-year. The biggest drop was registered in upper secondary education, where there was a drop in enrolment.
96	Total public expenditure on education includes all budget expenditure for formal education of young people and adults at state and municipal level. It includes direct expenditure on educational institutions and transfers to households (scholarships, subsidies for food, transport, accommodation, textbooks etc.). Financial data for Slovenia are collected based on the internationally comparable UOE methodology (a joint questionnaire of Unesco, OECD, Eurostat).
97	Data on expenditure on education as a share of GDP are
calculated based on the revised GDP figures of 16 October 2009.
Source: SORS; calculations by IMAD.
Note: Data on expenditure on education as a share of GDP calculated based on the revised GDP figures of 16 October 2009.
2.5
9
8
2.0
7
1.5
6
5
1.0
4
0.5
3
2
0.0
0
6
5
4
3
2
0
Social overwiew 2009	62
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Figure 52: Public expenditure on education, total and tertiary level, EU-27, 2006, in %
Source: Eurostat.
0.5 p.p. over the previous year and 5.5 p.p. lower than in 2000, but this level still puts Slovenia above the EU-27 average. As in most other European countries, tertiary education accounts for the biggest share of the transfers; in 2007, it accounted for 22.8%.
Private expenditure on education has levelled off in recent years. In 2007, it amounted to 13.2%, a marginal increase over the year before. The share of private expenditure on education is highest at the tertiary level, followed by pre-school, primary and upper secondary levels. In the last year, the share of private expenditure increased at pre-school and upper secondary levels, and dropped in primary and tertiary education. In the period 2000-2007, the share of private expenditure dropped at all levels of education bar primary level, where it increased. In 2006, Slovenia exceeded the EU-27 average in the share of private expenditure on education, while in the 2000-2006 period, this type of expenditure dropped (in contrast to the EU-27 average).
4.5 Culture
Participation in cultural activities is determined by a variety of factors: socio-economic characteristics (sex, age, education, income, etc.), individual preferences, the cultural environment in which an individual grew up and socialisation patterns during the coming-of-age, the available time (Frateschi, Lazzaro, 2008), the variety of cultural events, goods and services on offer and their local availability, the network of cultural institutions and ticket prices.
In 2008 the number of collections,98 museum objects and exhibitions increased, but the number of visitors
dropped. The number of museum objects99 and collections in museums and exhibition grounds100 rose, as did the number of exhibitions. One would expect that this rising number of exhibitions would be matched by swelling ranks of visitors, but this was not the case. Their number dropped by 1.8% in 2008, to 2,454,878. Visitor numbers are affected by the number and variety of exhibitions on display, along with their content, and people's interest in a topic. In the period 20051012008, the average number of days that museums and exhibition grounds opened to visitors rose, which improved accessibility of these institutions to the public. In the period 2004-2008, the number of exhibitions and visitors decreased.
Figure 53: Number of visitors in museums and number of visitors per exhibition, Slovenia, 2004-2008
■	Number of visitors per exhibition (left axis)
■	Number of visitors in '000 (right axis)
2,600 2,400 2,200 2,000 1,800 1,600 1,400 1,200 1,000 800 600 400 200 0
Source: SORS; calculations by IMAD.
2,600 2,400 2,200 2,000 1,800 1,600 1,400 1,200 1,000 800 600 400 200 0
The number of theatrical performances and visitors increased in 2008, but the number of concert-goers dropped, even as the number of concerts increased. The
number of performances at theatres102 was up in 2008, but it was still about a third lower than in 2004. The rise in the number of exhibitions was matched by higher visitor numbers, which increased to 867,220, about a fifth more than in 2004. One of the indicators showing accessibility of performances is the number of theatre seats, which rose in the period 2005103-2008. In 2008, the number of concerts at theatres also increased, but the number of visitors dropped substantially, to 17,112.
98 Including visual-art, art-history, archaeological, historical, natural-science, technical-science, ethnological, general and other collections.
99	Museum objects include visual-art, art-history, archaeological, historical, natural-science, technical-science and ethnological objects.
100	Includes museums, museum collections, special museums for art heritage, exhibition grounds and galleries, and other types of museums or exhibition grounds. Museum collections are not independent organisations, they form part of other institutions. The data are for institutions that reported on their activities.
101	Data for 2005 and 2008 are multi-year data.
102	Includes institutions that reported on their activities.
103	Multi-year data.
Social overwiew 2009	63
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Figure 54: Number of visitors of theatrical performances and concerts at theatres, Slovenia, 2004-2008
■ Concerts in theatres ■ Theatrical performances
1,000,000 900,000 800,000 700,000 S 600,000
-Q
iE
z 500,000 400,000 300,000 200,000 100,000 0
2004	2005
Source: SORS; calculations by IMAD.
attendance rose in the period 2004-2008 due to higher attendance at foreign-film screenings, but the number of people who watched Slovenian films declined.
The number of titles of books and brochures soared in 2008, in a continuation of a longstanding trend.
This indicates that variety and choice are improving. The number of titles of books and brochures rose by roughly a quarter year-on-year in 2008, to 6,358. This is the biggest relative increase since 2002, in a period of constant growth. In 2008, 70.5% of titles were original works and 29.5% were translations. Over the 20002008 period, the number of published titles of books and brochures rose substantially. In relative terms, the number of translations saw the biggest increase, but in absolute terms, the number of original works increased by more.
Figure 56: Number of titles of books (works), by language, Slovenia, 2000-2008
Attendance at feature-length film screenings rose in 2008. Over the 2004-2008 period, the number of films produced and screened for the first time104 soared (to 45 in 2008), largely as a result of a robust rise in the number of short films. The number of feature-length films increased by 1 to 8 in the 2004-2008 period and total attendance at screenings of Slovenian films also rose: attendance at screenings of feature-length films increased in 2008 to 2,417,994, of which 4.3% saw Slovenian films. At screenings of feature-length films,
Figure 55: Attendance at screenings of foreign and Slovenian feature-length films, Slovenia, 2000-2008
I Foreign

1,500
-Q £
0
2000 2001 2002 2003 2004 2005 2006 2007 2008 Source: Fivia, d.o.o., Slovenian Film Fund.
104 The methodology changed in 2004. Since 2004, data for produced films include produced films screened publicly for the first time.
■ Translations «Original works

nil
I
0
2000 2001 2002 2003 2004 2005 2006 2007 2008 Source: Institute of Information Science, National and University Library.
Library membership dropped in 2007 but the per-capita number of library units loaned edged up.
Reading contributes to the general knowledge of the population and improves (functional) literacy105. In 2007, membership of all types of libraries dropped.106 However, the number of library units loaned per capita nevertheless rose slightly. In the period 2000-2007, membership, per-capita number of library visits and per-capita number of library units loaned increased in all types of libraries.
105	In the international study Literacy in the information age (2000) literacy is defined as the capability to understand and use printed information in everyday activities at home, at work and in the community to achieve goals and develop knowledge and capabilities.
106	Includes the National and University Library (NUK), university libraries, special libraries, public libraries and school libraries.
7,000
5,000
4,000
3,000
2,000
1,000
3,500
Slovenian
3,000
2,500
2,000
1,000
Social overwiew 2009	64
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Table 34: Membership of libraries, library visits and library units loaned, total and public libraries, 2000-2007
	2000	2001	2002	2003	2004	2005	2006	2007
Libraries total1								
Share of population with library membership, in %	50.3	51	50.5	54.1	52.4	63.9	66.3	63.1
Per-capita library visits	7.2	7.4	7.6	7.8	8.0	10.2	10.8	10.8
Per-capita number of loaned library units	14.3	15.8	14.1	14.8	15.1	15.1	17.3	17.4
Public libraries								
Share of population with public-library membership, in %	24.7	24.4	24.7	25.3	26.6	25.7	26.8	26.0
Per-capita library visits	3.7	3.9	4.1	4.3	4.4	4.5	4.6	4.7
Per-capita number of loaned library units	9.7	11	9.3	9.4	10.2	10.4	12.4	12.7
Source: SORS, National and University Library; calculations by IMAD.
Note: Includes the National and University Library (NUK), university libraries, special libraries, public libraries and school libraries. For 2005, 2006 and 2007, the figures for school libraries include students, staff and others.
4.6 Media
According to the latest National Readership Survey,107 from July 2008 to July 2009,108 there were 151 regular print publications with a sold circulation of at least 10,000 copies, nearly a tenth more than in 2002, when the first such survey was conducted. In the last period for which data are available, 3 print publications were discontinued and 5 new publications were launched. The latest National Readership Survey included 8 daily newspapers (7 payable and 1 freesheet), which came with a total of 22 supplements (2 more than in the previous year). There are also 4 newspapers that are published several times a week, 18 weeklies and 7 biweekly papers. Readers can choose between 66 monthly magazines (2 more than in the year before), 4 bimonthly or less frequently published magazines and 22 free non-daily publications.
Even though the choice of print media is becoming more varied, circulation has been dropping since 2005.
In the second quarter of 2009, the total sold109 circulation of payable daily newspapers110 was 237,031, down 7.4% year-on-year, in a continuation of a longstanding trend.
107	Valicon, July 2009.
108	The last period for which data are available.
109	Sold circulation means subscription and news-stand sales (number of issues actually sold at the listing price) in Slovenia and abroad. Includes package sale.
110	Slovenian Advertising Chamber, October 2009.
Among the payable daily newspapers, the highest sold circulation in the second quarter of 2009 was approximately 79,500, while the circulation of the other dailies was at least 30% lower. The best selling weekly had a sold circulation of 105,500 (down 6.8% year-on-year), while the second-placed had less than half of that. For the daily freesheet, the only available data are for the print111 circulation, which exceeded the sold circulation of the best-selling payable daily by 28.5% in the second quarter of 2009. For the supplements, only print circulation data are available: the most widely read supplement had a print circulation of 184,000, down 7.0% over the same period of 2008.
Another indicator illustrating the declining interest in print media is the reach of individual editions.112
National Readership Survey analysis shows that the reach of newspapers and magazines was rising until 2005, whereupon it began a steady decline. In the period from July 2008 to June 2009, the reach of print media suffered a substantial drop. The reach of daily newspapers declined by as much as 30,000 compared with the first half of
111	Print circulation means the number of copies delivered by the printers (as per the delivery note) or as evident from the invoice delivered by the printer to the publisher (Slovenian Advertising Chamber).
112	The reach of one issue includes all people who read or browsed an issue in the issue period (the past week for weekly magazines, the past month for monthly magazines etc.) (Valicon).
Table 35: Total sold and print circulation of daily newspapers, Slovenia, second quarter, 2005-2009, number
	2005	2006	2007	2008	2009
Total sold circulation	277,375	270,549	263,595	255,970	237,031
Total print circulation	324,415	318,231	318,406	407,759	395,056
Source: Slovenian Advertising Chamber, October 2009.
Note: In the second quarter of 2008, publication started of a high print-run freesheet, hence the significant rise in print circulation.
Social overwiew 2009	65
The way we live
2008. Overall, the supplements of daily newspapers have the broadest reach (up to 367,000), followed by certain weekly magazines and dailies. Despite the overall decline in readership, the relative market positions of the three most widely circulated dailies, supplements and weeklies remain largely unchanged, in particular among payable publications.
The Slovenian Public Opinion113 survey indicates that most people spend less than half an hour a day reading daily newspapers, but the number of people who do not read newspapers at all has been on the increase; most readers spend only up to half an hour a day on politics and current affairs. In 2008, 46.3% of respondents said they read daily newspapers less than half an hour a day, down from about 43% in previous years. From 2004, the share of people reading newspapers for between half an hour and one hour a day has steadily declined (2008: 23.8%). Just under a fifth of respondents did not read newspapers at all in 2008, a similar proportion to that in 2002. The latest data114 suggest that those with unfinished primary school education read newspapers the least and those with a completed two-year higher education programme the most.115 Newspaper readers are also showing scant interest in politics and current affairs. Of the time spent reading print media, most dedicate less than half an hour to politics and current affairs (2008: 62%). However, the share of people not paying any attention to politics and current affairs declined (2008: 22%).
Even though newspaper readers do not spend a lot of time reading about politics and current affairs, these are the topics they are most interested in payable
dailies.116 Over 60% of respondents said current affairs and politics were topics of interest in daily newspapers. There is also a lot of interest in local news and health, but fewer than 20% look for news on the arts, religion, finance, dieting, prize competitions and horoscopes.
The number of radio and television programmes has been rising. In 2008,117 there were 86 radio stations and 60 TV channels, an increase of 4 and 2 respectively over 2007. This is a significant increase over 2006, when there were only 63 radio stations and 51 TV channels.118
The habits of radio listeners and TV viewers are very different. According to the Slovenian Public Opinion study, the largest share of people (22.8%) watch TV for between half an hour and one hour a day, followed by the groups that on average watch TV for one to one and
Figure 57: Interest in topics in selected payable daily newspapers, Slovenia, 2008, in %
113	Centre for Public Opinion and Mass Media Research, Slovenian Public Opinion 2008/2. 2009.
114	Centre for Public Opinion and Mass Media Research, Slovenian Public Opinion 2006/1. 2006.
115	For detailed data, see Social Overview 2008, p. 57.
116	Annual survey of the state of media pluralism in Slovenia in 2008 in print, broadcast and electronic media, 2009
117	Source: SORS
118	Source: SORS
, 40 30
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a half hours and one and a half to two hours respectively. Only about 10% spend more than three hours a day in front of the TV. The figures for radio reflect the fact that radio can be listened to even during work. Nearly 28% of respondents said they listened to the radio for more than three hours a day, while smaller proportions listen for less than half an hour and up to one hour, respectively. The latest data show that time spent listening to the radio decreases the more educated people are.
Reflecting the findings for print media, the figures suggest that most listeners and viewers do not spend much time on current affairs and politics. Among TV
Figure 58: Time dedicated to media, by type of media (newspapers, TV, radio), Slovenia, 2008, in %
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Source: Slovenian Public Opinion, European Social Survey, 2009
10
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15
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Social overwiew 2009	66
The way we live
viewers, the bulk (just over 41%) watch programming of this kind for between half an hour and one hour a day, while a smaller proportion spend less than half an hour watching current affairs and politics. Almost half of radio listeners spend less than half an hour a day on serious topics.
People increasingly get their news and current affairs reporting on the Internet rather than in print media or on radio and TV. Many print and electronic media have their own web pages which are fully fledged portals with the latest news rather than just outlets for content from their broadcasts or print editions. The reach119 of the most popular news sites has been rising; indeed, the web page of one media outlet is the most popular Slovenian website overall. A comparison of the reach of the most widely read daily newspaper and the most popular website shows that the newspaper (324,000 readers per issue, according to the latest available data), is far behind the most popular news site (607,685 according to the latest available data).
4.7 Internet
Households' access to the Internet has improved markedly in recent years, in particular the share of households with a broadband connection, a trend observed throughout the EU. 64% of households had Internet access in 2009, an increase of 5 p.p. over the year before. Internet uptake in Slovenia has been increasing rapidly since 2005 (when it stood at 48%). It was above the EU average until 2007, but in 2008 and 2009 it fell below the average (by 1 p.p.). It is encouraging that in the past few years there has been a significant increase in the number of households with broadband access, which provides more reliable and faster access as well as the ability to use new services (in particular, streaming multimedia content). The share of households with broadband120 reached 56% in 2009, almost three times the rate in 2005. Broadband uptake accelerated in 2005 following the unbundling of the ISDN-ADSL loop, which led to an increase in the number of xDSL service providers. In the last three years (after 2007), xDSL penetration slowed down considerably, but cable access and increasingly cost-effective UMTS access have been making significant gains. With the gradual expansion of the technologically advanced fibre-optic network, the currently small share of users of other broadband connections trebled, from 2% in 2008 to 6%, in 2009. Between 2006 and 2008, the share of households with broadband was slightly above the EU average, but the advantage shrank every year, and in 2009 the penetration rate was on a par with the EU average. Figures show that Internet access is less widespread in more sparsely populated areas, which is expected. International comparisons show that the share
of households with Internet access in such settlements121 in Slovenia is above the EU average.
In the period 2004-2009,122 Slovenia made significant progress on Internet use and the changes last year were structurally favourable. Following a slowdown in Internet use in 2007 and 2008, when Slovenia's gap to the EU average widened, the share of Internet users123 in the 16-74 age group jumped by 6 p.p. in 2009 to 62%. This gain narrowed the gap to the EU, where 65% used the Internet in 2009. The progress last year was also structurally encouraging, as the share of Internet users increased the most in the 35-54 age group, and there was a notable increase among the oldest population (55-74 years). In terms of education, the biggest increase was registered among those with lower education. Comparisons with the EU for 2007 and 2008 showed that the potential to increase Internet use had been under-exploited, in particular among the older population and those with lower levels of education. The changes in 2009 reduced the shortfall in these segments, in particular for less educated Internet users. In Slovenia, as in the EU, Internet use is most widespread among young people; in Slovenia, the share of young Internet users (16-24) has been above the EU average throughout the studied period and the gap has been increasing over the years. The difference in the share of Internet users between men and women had been relatively small in Slovenia, and in 2009 it almost disappeared (men 65%, women 64%).
Figure 59: Share of households with Internet access, EU-27, 2009,1 in %
70 60 50 40 30 20
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Note: 1 Data for first quarter of the year.
Industry, trade and services - Information
119	Slovenian Advertising Chamber, MOSS.
120	Broadband connections include: xDSL, cable, UMTS, other broadband connections (e.g. fibre-optics).
121	Sparsely populated settlements are settlements with fewer than 100 inhabitants per km2. Overall, Slovenia has a relatively low population density which, at 100 inhabitants per km2, is at the threshold level for sparsely populated areas.
122	SORS data on ICT use in Slovenia are available from 2004.
123	Includes people who used the Internet in the last three months.
100
10
0
Social overwiew 2009	67
The way we live
Table 36: Internet use and access, Slovenia, 2004-2009,1 in %
	2004	2005	2006	2007	2008	2009
Households with Internet access, in %	47	48	54	58	59	64
Households with a broadband connection, in %	10	19	34	44	50	56
Total Internet users2						
16-74 years	37	47	51	53	56	62
By age:						
16-34 years	62	77	81	84	88	91
35-54 years	33	45	50	53	56	66
55-74 years	83	114	14	14	17	22
Source: SORS.
Notes: 1All data are for the first quarter of the year. 2Those who used the Internet in the last three months. 3Imprecise estimate. 4Less precise estimate.
5. Social cohesion and poverty
The concept of social cohesion pertains to all aspects of society, especially the strength of primary ties, solidarity, common values, commitment to society and trust. This broad definition of social cohesion includes the conceptions of social exclusion and social capital. To analyse social exclusion, it is important to know the dimensions of income inequality, monetary poverty and material deprivation, as prolonged poverty may lead to social exclusion of certain social strata. Unemployment and poverty also impact on the population's health. Besides social support networks, trust in other people also plays an important role in the context of social capital. Indicators of social cohesion and poverty (financial poverty and material deprivation) still show a favourable picture for Slovenia, but the at-risk-of-poverty rate increased in 2008.
5.1 Social cohesion
Social exclusion/inclusion and financial (relative) poverty are measured by social-cohesion indicators adopted by the European Council in Laeken (Laeken
indicators). In Slovenia, we monitor the following social cohesion indicators: at-risk-of-poverty rate (after social transfers), share of young people (aged 18-24) who dropped out of school (early school leavers), long-term unemployment rate, inequality of income distribution (S80/S20 quintile share ratio), jobless households (in which none of the persons aged 18-59 works) and within the last, the share of children living in such households.
Slovenia scores favourably within the EU-27 in terms of social cohesion indicators, being ranked first for three indicators according to the most recent figures.
Slovenia had the lowest income inequality (quintile share ratio), the lowest share of jobless households with dependent children and the lowest share of early dropouts. In terms of the at-risk-of-poverty rate, Slovenia is ranked third in the EU-27, along with Denmark, Hungary, Austria and Sweden, and sixth by the share of jobless households. According to the long-term unemployment rate, Slovenia scores 12th in the EU-27.
Income inequality as measured by the Gini coefficient,124 which is otherwise not one of the Laeken indicators, ranks Slovenia in the group of countries with the lowest inequality. In 2008, the Gini coefficient in Slovenia was
124 The Gini coefficient is a measure of income concentration. The higher it is, the greater the income inequality. A value of 0%
indicates complete income equality.
Table 37: Social cohesion indicators, Slovenia and EU-27, 2008
	Slovenia	EU-27
At-risk-of-poverty rate (%)	12.3	17
Early school leavers (%)	5.1	14.9
Long-term unemployment rate2	1.9	2.6
S80/S20 quintile share ratio	3.4	5
Jobless households (%)	6.4	9.2
Jobless households with children (%)	2.6	9.2
Source: Eurostat.
Notes: Unreliable data. 2The long-term unemployment rate means total long-term unemployed people (12 months or more) as a proportion of total active population.
Social overwiew 2009	68
The way we live
Figure 60: Income inequality as measured by the Gini coefficient, EU-27, 2008, in %
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below-average crime rate for Slovenia (3,810 crimes per 100,000 inhabitants), the highest crime rate for Sweden (13,995/100,000) and the lowest for Cyprus. Similar rates to Slovenia were also recorded for Poland, Portugal, the Czech Republic and Estonia in 2003.
The number of homicides per 100,000 inhabitants in Slovenia is among the lowest in the EU-27. While the number of homicides has been declining in the EU-27 throughout the period since 1998 (except in 2000), Slovenia has posted very uncharacteristic movements in this period. In 2007, the number of homicides was higher than in 1998, but the annual rate in the period of 2005 to 2007 was only 0.93,127 compared with 1.40 in the EU-27. In Slovenia, the number of homicides per 100,000 inhabitants is among the lowest in the EU-27; lower figures were only posted in three countries: Germany (0.90), Malta (0.66) and Austria (0.64).
Source: Eurostat.
23%, which indicates a fairly even distribution of income. The average Gini coefficient across the EU-27 was 31%. (See Figure 60).
Social cohesion is also reflected and directly and indirectly impacted by certain other indicators, such as: crime rate, number of homicides, number of prisoners, number of police officers, number of people killed in road traffic accidents and number of suicides. The feeling of safety is also influenced by people's subjective perceptions of the living conditions, such as: feeling threatened in their immediate neighbourhood and personal experience of crime. However, we have also used some other subjective perceptions of living conditions to describe the population's social capital and quality of life. These are feelings of happiness, satisfaction with life, trust in other people and trust in institutions.
Figure 61: Number of homicides per 100,000 inhabitants, EU-27, 2005-2007
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The feeling of personal security is one important aspect in assessing quality of life. Moreover, subjective perceptions of being threatened are even more important for the feeling of security than objectively measured criminality (Malnar, Social Overview 2008, p. 65). According to (objective) data by Eurostat, crime rose steadily in the EU-27 in 1998-2007, peaking in 2002, but has been falling consistently in the last five years. In Slovenia, the number of crimes had been increasing (with minor exceptions in 2003 and 2005) up to 2006, when it peaked, but it dropped somewhat in 2007. Data on the crime rate125 compiled by the Council of Europe, which are only available for 2003,126 show a
125	The crime rate is the number of serious offences against the penal code per 100,000 population recorded by the police (criminal complaints), excluding less serious crimes (misdemeanours such as thefts, motor vehicle thefts, etc.). As individual countries have different criminal justice systems, it is difficult to make comparisons between countries.
126	Council of Europe: European Sourcebook of Crime and
Source: Eurostat.
Although low compared with the EU-27, the feeling of being threatened in the immediate environment increased somewhat in Slovenia in 2002-2008. Data on subjective perceptions of crime in Slovenia show that respondents' feelings of being threatened in the immediate neighbourhood increased in 2002-2008. In 2008, 12% of inhabitants felt threatened walking in their neighbourhood at night, which means that they were excluded from certain evening activities for fear of assault. The feeling of being threatened was strong, even though in 2008 fewer persons had personal experience of crime than in 2006. Compared with certain European countries, Slovenia posts very low rates in terms of feeling threatened in one's neighbourhood and direct personal experience of crime.
Criminal Justice Statistics - 2006.
127 According to Eurostat.
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Social overwiew 2009	69
The way we live
Table 38: Subjective perceptions of crime; feeling of safety and personal experience of crime, Slovenia, 2002, 2004, 2006 and 2008, in %
Feeling of safety 11					Personal experience of crime 2)				
	ESS02	ESS04	ESS06	ESS08		ESS02	ESS04	ESS06	ESS08
Very safe	29.0	28.3	27.0	26.4	yes	11.5	11.8	13.5	11.4
Safe	60.5	61.0	61.3	60.9	no	88.5	87.9	86.2	88.6
Unsafe	8.9	8.5	9.2	10.7					
Very unsafe	0.9	1.0	1.0	1.1					
Source: ESS 2002-2008, Faculty of Social Sciences (FDV) - CJMMK.
Notes: 1How safe do you feel walking alone in your neighbourhood in the evening? ESS 2002-2008; 2Have you yourself or any member of your household been a victim of burglary/ assault in the last five years? ESS 2002-2008.
Slovenia has the lowest number of prisoners per 100,000 inhabitants in the EU-27. In the period of 19982007, the number of prisoners increased at an annual rate of approx. 1% in the EU-27, according to Eurostat. In Slovenia, the number of prisoners was relatively stable, but increased by 16% in 2007 compared with a year before. In the period of 2005 to 2007, the EU-27 posted 123 prisoners per 100,000 inhabitants, on average, and Slovenia 60, which is the lowest figure in the entire EU-27. Finland and Denmark also recorded low prisoner rates in 2005-2007 (68 and 71 prisoners per 100,000 inhabitants, respectively), while the highest rates were posted in Estonia and Latvia (302 and 293 per 100,000 inhabitants, respectively).
Figure 62: Number of prisoners per 100,000 inhabitants, EU-27, 2005-2007
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police officers per 100,000 inhabitants, according to the Council of Europe data. Slovenia was ranked on this indicator roughly in the middle of the selected European countries, along with Austria, Belgium, France, Ireland, Lithuania and Slovakia. Fewer than 200 police officers were recorded in Denmark, Finland and Sweden; Cyprus recorded 500 or more police officers per 100,000 inhabitants.
The number of fatal road traffic accidents in Slovenia is still notably higher than in the EU-27 average.
Slovenia recorded as many as 13.7 fatal road accidents per 100,000 inhabitants in 2006 (the EU-27, 9.1; the latest figure for the EU-27 as a whole). In the EU-27, the number of accidents per 100,000 inhabitants declined by 24% in 2000-2006, while in Slovenia, the decline was less than 12%. The number of fatal road accidents in Slovenia was even increasing, according to the figures for 2007; in 2008, this number declined (according to SORS129 data), as a result of efforts to enhance road traffic safety.
Figure 63: Number of deaths in road traffic accidents per 100,000 inhabitants, EU-27, 2007
In terms of the number of police officers per 100,000 inhabitants, Slovenia is ranked in the middle of European countries.128 In the 2005-2007 period, Slovenia was in the group of European countries with 300-399
Source: Eurostat.
128 According to the Council of Europe, these data are not available for all EU-27 countries.
129 SORS: Road-traffic accidents, Slovenia, 2008, First Release, September 10, 2009.
150
100
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15
10
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Social overwiew 2009	70
The way we live
According to the happiness indicator, Slovenia is ranked highest among the transition countries. Even if happiness and satisfaction with life are highly subjective feelings, they tend to reflect the general social climate. In 2008, the proportion of people who consider themselves happy reached the highest level (70.2%) in the period since 2000, according to the Slovenian Public Opinion poll (SJM). Satisfaction with life also improved, albeit less strongly. On the indicators of happiness and satisfaction with life, Slovenia thus ranks in the middle of European countries and is regarded as the happiest among the transition countries.
Trust in other people is low in Slovenia. Trust in other people involves expectations about other people's actions and is an important indicator of social capital, and thus also social cohesion as understood in this chapter. Countries posting trust levels up to 60% are regarded as countries with a high level of trust and those with trust levels below 20% as countries where trust is low. According to data for 2006, the former group largely comprises Scandinavian countries (Denmark 69%, Norway 66.2%, Finland 61.3%), while the latter consists of certain Southern and Eastern European countries, including Slovenia (which is, with 21%, somewhere on the border of this group). According to the ESS data, the level of trust in other people remains low in Slovenia, with only around 20% of respondents believing that the majority of people can be trusted, even though the proportion of people who do not trust others and think that one has to be cautious in one's contacts with other people declined somewhat in 2008.
Trust in institutions is at a very low level in Slovenia.
Looking at the four social system institutions, in 2008, Slovenia recorded the highest level of trust in police (30.1%) and the lowest level of trust in politicians (7.3%).
Table 39: Subjective feelings of happiness, Slovenia, 2000-2008, in %
	2000	2001	2002	2003	2004	2005	2006	2007	2008
Not happy (0-3)	5.3	5.1	5.7	5.5	4.1	4.1	4.9	4.3	4.2
Medium (4-6)	36.6	35.6	31.3	35.9	28.2	28.8	34.1	26.9	25.1
Happy (7-10)	57.2	58.7	62.3	57.6	67.0	66.0	59.7	67.1	70.2
Source: Faculty of Social Sciences (FDV) - CJMMK, Slovenian Public Opinion (SJM 2000-2008).
Note: The question reads: Please use a 0-10 scale to assess your feelings as to your personal happiness in general, with 0 meaning that you are not happy at all and 10 that you are very happy. Difference from 100% is made up of answers "Don't know" or "No answer".
Table 40: Satisfaction with life, Slovenia, 2002, 2004, 2006, 2008, in %
Year	2002	2004	2006	2008
Not satisfied (0-3)	10.4	6.3	6.8	6.9
Medium (4-6)	46.7	47.3	44.7	45.3
Satisfied (7-10)	41.6	46.2	45.3	46.8
Source: European Social Survey (ESS), Faculty of Social Sciences (FDV) - CJMMK.
Note: The question reads: All things considered, how satisfied are you with your life, with 0 meaning that you are very unsatisfied and 10 that you are very satisfied. Difference from 100% is made up of answers "Don't know" or "No answer".
Suicide is the most frequent cause of violent death in Slovenia. Slovenia ranks right at the head of the EU countries as regards the suicide rate. The suicide rate (the number of suicides per 100,000 inhabitants) declined somewhat in the 2000-2007 period. In 2006, for which the most recent data for the EU-27 are available, the suicide rate in Slovenia (22.8) was 2.2 times higher than the EU-27 average (10.3). In 2007, the suicide rate in Slovenia declined somewhat (18.4), but Slovenia is still at the top of the list; higher suicide rates were recorded only in Lithuania (28.4 suicides per 100,000 inhabitants) and Hungary (21.4). In Slovenia, suicides shorten life by an average of 20 years, according to SORS; (the mean age of people who died by suicide is 51 years). As in the EU, men commit suicide four times more frequently than women.
Figure 64: Number of suicides per 100,000 inhabitants, EU-27, 2007
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10
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Social overwiew 2009	71
The way we live
Table 41: Trust in other people, Slovenia, 2002, 2004, 2006, 2008, in %
	2002	2004	2006	2008
Does not trust (0-3)	43.3	41.5	42.6	36.8
Medium (4-6)	38.6	38.2	36.4	41.6
Trusts (7-10)	17.6	20.1	20.9	21
Source: European Social Survey (ESS), Faculty of Social Sciences (FDV) - CJMMK.
Note: The question reads: Generally speaking, can the majority of people be trusted or does one have to be cautious in one's contacts with other people? Choose the appropriate value on a 0-10 scale where 0 means that one has to be cautious in one's contacts with other people and 10 that the majority of people can be trusted. Difference from 100% is made up of answers "Don't know" or "No answer".
Table 42: Trust in institutions, Slovenia, 2002, 2004, 2006, 2008, in %
National assembly					Legal system				
	ESS02	ESS04	ESS06	ESS08		ESS02	ESS04	ESS06	ESS08
Does not trust (0-4)	40.3	39.8	35.8	45.2	Does not trust (0-4)	38.5	46.0	39.5	48.8
Medium (5-6)	39.8	39.1	42.5	32.2	Medium (5-6)	35.3	33.9	36.7	28.8
Trusts (7-10)	15.9	17.3	16.8	19.3	Trusts (7-10)	21.9	15.6	18.4	19
Police					Politicians				
	ESS02	ESS04	ESS06	ESS08		ESS02	ESS04	ESS06	ESS08
Does not trust (0-4)	30.9	32.7	29.7	37.8	Does not trust (0-4)	57.0	57.4	56.0	62.1
Medium (5-6)	37.8	38.3	37.9	30.6	Medium (5-6)	34.3	33.5	32.9	28.5
Trusts (7-10)	29.1	26.2	29.8	30.1	Trusts (7-10)	6.1	6.2	8.1	7.3
Source: European Social Survey (ESS), Faculty of Social Sciences (FDV) - CJMMK.
Note: The question reads: "Assess on a 0-10 scale how much you personally trust each of the following institutions, 0 indicating that you do not trust it at all and 10 that you trust it completely."
This is the same relationship as in 2002, even if trust in the other three institutions except the legal system increased somewhat. A similar relationship between the shares of trust between the four social system institutions (people trust police the most and politicians least) was also recorded in certain Eastern European countries (Poland, Slovakia and Bulgaria) (ESS data, 2006). In Slovenia, trust in institutions is very low compared with other, particularly Scandinavian countries, included in the European Social Survey (ESS). Trust in all four institutions is highest in Denmark (55% of people trust in the national assembly, 74.2% in the legal system, 34.8% in police and 34.8% in politicians).
5.2 Poverty
In this section we show indicators of monetary poverty and a new indicator of material deprivation of the population, which gives a more comprehensive picture of the quality of life in a country. A combination of complementary monetary-poverty and material-deprivation indicators provides in-depth understanding of poverty. The indicators are based on data from the Survey of Living Conditions (EU-SILC). The level of poverty in the population is, in addition to income, also related to their property conditions, about which we lack appropriate data. We also show how low income and unemployment affect the population's health.
5.2.1 Monetary (relative) poverty
The risk of poverty increased somewhat in 2008. In
2008,130 12.3% of people earned less than EUR 545 per month in Slovenia (the at-risk-of-poverty threshold for a single household131), which means that the at-risk-of-poverty rate was 12.3%; in 2007, the at-risk-of-poverty rate was 0.8 p.p. lower. Considering also income in kind, the threshold is accordingly higher (EUR 557) and the risk of poverty slightly lower (11.9%).
Certain population groups are very vulnerable to poverty risk. Even if the at-risk-of-poverty rate reflecting the distribution of income across the population (income poverty) shows a fairly low level of income inequality within the population, certain population groups remain highly vulnerable to poverty risk. Among the most vulnerable groups are people living alone, single parents or those living in single households; in 2008, the poverty risk for some population groups (unemployed people and the elderly) even increased. At highest risk of poverty are persons in jobless households (39.1%), particularly those with dependent children (57%), and single households (41.9%) and single-parent families
130	Data on poverty risk in 2008 are based on disposable household income in 2007.
131	The at-risk-of-poverty threshold for a household of two adults with two children younger than 14 was appropriately higher -
EUR 1,144.
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Table 43: Selected indicators of poverty risk, 2005-2008, Slovenia
Income excluding income in kind
Income including income in kind
	2005	2006	2007	2008	2005	2006	2007	2008
At-risk-of-poverty rate, in %	12.1	11.7	11.5	12.3	11.4	11.1	11.0	11.9
At-risk-of-poverty threshold, in euros	440	466	495	545	460	480	509	557
At-risk-of poverty threshold for household consisting of two adults and two children - monthly, in euros	924	978	1.040	1.144	965	1.009	1.069	1.169
At-risk-of-poverty rate before social transfers (old-age pensions and family pensions included as income), in %	25.8	24.2	23.1	23	24.8	23.2	22.8	22.2
At-risk-of-poverty rate before all social transfers,1 in %	42.2	40.7	39.7	38.6	40.9	39.3	39.2	37.8
At-risk-of-poverty rate for men, in %	10.6	10.3	10.1	11	9.6	9.5	9.4	10.4
At-risk-of-poverty rate for women, in %	13.6	13	12.9	13.6	13.2	12.6	12.4	13.2
At-risk-of-poverty rate for children (0-15 years)	11.9	11.8	11.7	11.5	11	11.1	11.0	11.1
At-risk-of-poverty rate for the youth (16-24 years)	10.4	9.1	9.2	10.3	10	8.9	8.7	10
At-risk-of-poverty rate for the active population (16-54 years)	10.4	9.8	9.8	10.5	9.9	9.3	9.3	10.1
At-risk-of-poverty rate for the elderly (65 and older)	18.8	18.4	17.8	19.1	19.2	19	18.5	18.2
Source: SORS; Survey on income and living conditions (EU-SILC). Note: 1Income excluding age and family pensions.
(28.8%); unemployed persons and tenants also have high at-risk-of-poverty rates (37.6% and 25.2%, respectively); see Table 43. These socio-economic categories also tend to be at highest poverty risk throughout the EU-27.
The at-risk-of-poverty rate would be much higher without social transfers. To maintain and improve the population's standard of living, a social state provides for various mechanisms of social insurance and redistribution of income, ensuring a decent standard of living for individuals and families, and reducing poverty. This is the purpose of the social transfer system, which is very effective in Slovenia, as the risk of poverty would almost double (23%), if the government did not provide social transfers (social and family benefits132). In Slovenia, social transfers play a more vital role in reducing poverty than on average in the EU-27 (where social transfers reduce poverty by close to one third), which is a consequence of a well-targeted allocation of social receipts intended for most vulnerable social groups.
5.2.2 Material deprivation
Material deprivation measures provide a more comprehensive and deeper understanding of poverty and reveal the long-term effects of a bad financial situation on households. Income-based data on poverty and inequality, though important, fail to give a comprehensive picture of diversity of the living conditions in the EU-27. In assessing at-risk-of-poverty level based on income, there is a realistic limitation in the availability of data, for example on the self-employed and people working in the grey economy, as well as on
132 Not including pensions. If the population did not receive pensions, the at-risk-of-poverty rate would total 38.6%.
non-monetary transfers, debts and profits of households, if any, etc., most of which are not included in the survey. Material-deprivation measures can, however, provide the necessary additional information on the overall financial situation and long-term impacts of poverty on households. When recognising the limits of the monetary approach, we do not argue that deprivation measures are superior; they are only a combination of complementary measures to deepen our understanding of poverty.133 This is the idea that has been pursued for several years by the Indicator Subgroup of the Social Protection Committee in trying to define a set of material deprivation indicators.
Material deprivation items that show a lack of resources were adopted in February 2009 on the basis of data from the EU-SILC. They will be additionally tested in the EU-SILC 2009 module and will constitute a basis for further studies in this area. The selected nine items134 refer to possession or lack of durable goods and to what is called economic strain on households. They will help to highlight two core elements of the poverty definitions: a) inability to participate in society and b) lack of resources. It should be noted that these indicators measure material deprivation as a consequence of
133	Source: Eurostat; What can be Learned from Deprivation Indicators in Europe; Methodologies and working papers, 2009
134	They are: The household cannot afford: 1. to face unexpected expenses, 2. one week of annual holiday away from home, 3. a meal with meat, chicken or fish (or vegetarian equivalent) at least every second day, 4. to pay for arrears (mortgage or rent, utility bills or hire purchase instalments), 5. to keep home adequately warm, 6. to have a washing machine, 7. to have a colour TV, 8. to have a telephone, 9. to have a personal car. For the last four indicators it is assumed that people would like to possess these goods.
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Table 44: Material-deprivation rates (percentage of people that are deprived in at least three material-deprivation indicators) and at-risk-of-poverty rates, EU-25, 2008, in %
	Material-deprivation rate	At-risk-of-poverty rate
Luxembourg	4	13
Norway	5	11
Sweden	5	12
Netherland	5	11
Denmark	87	12
Spain	9	20
Finland	9	14
United Kingdom	11	19
Belgium	12	15
Estonia	12	19
France	13	13
Germany	13	15
Austria	14	12
Ireland	14	16
Czech Republic	16	9
Italy	16	19
Slovenia	17	12
Greece	22	20
Portugal	23	18
Cyprus	23	16
Lithuania	27	20
Slovakia	28	11
Poland	32	17
Latvia	35	26
Hungary	37	12
Romania	50	23
Bulgaria	51	21
Source: Eurostat, EU-SILC 2008.
Notes: These are the first calculations by Eurostat. The figures may therefore still change. SORS has not calculated the material deprivation for Slovenia yet.
limited resources of households rather than differences in tastes, lifestyle preferences, personal choices and living conditions. The latter were tested in an EU-wide Eurobarometer survey in 2007, according to which all items listed in the EU-SILC survey were considered necessary or absolutely necessary for a decent standard of living by at least 50% of respondents. The adequacy of the choice of nine material deprivation indicators was thus confirmed and the possibility excluded that households (individuals) did not have certain items because they chose not to have them. Recognising each item as more or less equally important to assess the standard of living of the population, researchers decided to consider deprived those households that lacked three material-deprivation items out of nine.
The material-deprivation rate showing the percentage of people that are deprived in at least three items of material deprivation is relatively low in Slovenia. It
totalled 16.9% in 2008 and was 2.6 p.p. higher than a year before. The deterioration was, by our estimate, mainly
due to high inflation in 2007 and 2008. Analysing the EU-SILC data, Eurostat found the highest deprivation rates in the new Member States (also in those with low at-risk-of-poverty rates). According to Eurostat, data on material deprivation show much greater disparities between the EU-27 countries than data on relative poverty. The material-deprivation rate ranges between 4% and 51% and the relative poverty rate between 9% and 26%. Table 44 shows that Slovenia is ranked in the first third of countries with relatively low material-deprivation rates, next to Italy, the Czech Republic, Ireland and Austria, and that it does not have significant differences between the two rates (which is also characteristic of Belgium, Germany and Austria).
The correlation between the material deprivation and at-risk-of-poverty rates is weak. It is 0.42 (at the level of countries), which means that in the majority of countries these rates pertain to different population groups. In the old Member States, less than a third of the population that is below the relative poverty threshold is also
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Table 45: Material-deprivation rates of the population living above the at-risk-of-poverty level and poor population, EU-27, 2008, in %
	Material-deprivation rate of the population above the at-risk-of-poverty level1	Material deprivation rate of the population below the at-risk-of-poverty level
EU-27	13	40
Austria	10	41
Belgium	7	39
Bulgaria	40	93
Cyprus	19	47
Czech Republic	13	50
Denmark2	5	20
Estonia	7	34
Finland	6	28
France	10	37
Greece	15	47
Ireland	11	29
Italy	11	38
Latvia	25	66
Lithuania	20	53
Luxembourg	1	17
Hungary	33	67
Malta	10	26
Germany	8p	41
Netherland	3	21
Poland	27	59
Portugal	18	46
Romania	42	78
Slovakia	24	59
Slovenia	13	43
Spain	6	18
Sweden	3	14
United Kingdom	7 p	25 p
Source: Eurostat, EU-SILC 2008.
Notes: Data for Bulgaria are not available; p) provisional data. 1Share of materially deprived people in the population with income above the at-risk-of-poverty threshold. 2Figure for 2007.
materially deprived; on the other hand, relative poverty is sometimes just another name for material deprivation. This is the case in Bulgaria (with as many as 93% of poor people also being materially deprived), Romania (76%) and Latvia (76%). With 43% of poor people also materially deprived, Slovenia is ranked somewhere in the middle.
Material deprivation is higher among women and children. In all EU-27 countries except Sweden, the material-deprivation rate is higher for women than for men. In most countries, the material-deprivation rate for children is higher than that for the total population. The only exception is Cyprus, where this rate is 3 p.p. lower, followed by Greece and Latvia (with 2 p.p.) and a group with a 1 p.p. lower rate, which also includes Slovenia (besides Estonia, Spain and Lithuania).
5.2.3 Socio-economic implications of unemployment and poverty
Unemployment is one of the main generators of poverty and social exclusion of the population. Slovenia's statistical regions are relatively small and their economic situation thus often relies on one or two companies. If these fail to perform or even go bankrupt, the economic situation of the whole region can change completely in a very short time (as has happened in the Pomurska region), which is first reflected in growing unemployment. Higher unemployment has a pronounced impact on social exclusion of the population. Unemployment affects quality of life, financially, as well as from social and psychological aspects. "...employment has an
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indirect influence on our life in five ways: it determines the daily time structure, (ii) it offers social contacts outside the family, (iii) it unites individual and collective purposes, (iv) it is a source of status and identity, and (v) a source of regularity and control. The deprivation of the unemployed therefore emerges because these latent consequences of employment have become indispensable to functioning in a modern society. Employment should thus be regarded from the aspect of prevention of economic, social and cultural exclusion" (Human Development Report - Slovenia, 1998).
Slovenija and in Zasavje. Eastern Slovenia is also an area with an above-average registered-unemployment rate. Since 2008, the registered-unemployment rate has been increasing in all regions, which is indirectly weakening the economic power of the population. All this, as already discussed, contributes to a poorer health condition and higher mortality of the population. We can therefore expect that the current economic crisis will have serious implications for the population's health and will lead to a further deterioration of the situation in eastern Slovenia.
Numerous studies in various fields have shown a close association between population health and welfare. According to a number of studies (Wilkinson 1996, 2007, WHO 2008, etc.), the health outcomes of a group of individuals (as measured by life expectancy or mortality rate) are closely and statistically importantly linked to their socio-economic position in society. Data from World Health Organization studies show that there are high disparities in life expectancy between poor and rich neighbourhoods in large cities (of a decade or more) and that morbidity and disability rates strongly reflect the overall educational and socio-economic situation of individual strata or regions.
A similar situation has been observed in Slovenia, where regional health indicators are closely linked to a region's economic situation or level of unemployment.
Analysis of mortality135 at the level of Slovenian statistical regions and administrative units has shown a strong correlation between most mortality causes, particularly suicide, and low income as indicated by a low personal-income tax base per capita and a high registered-unemployment rate. Statistically important, if somewhat smaller, is the correlation between various mortality causes and education. Regions boasting high economic power and a low unemployment rate also record higher educational levels of the population (Osrednjeslovenska, Obalno-kraška regions). Slovenia is divided in two parts in terms of mortality per 100,000 inhabitants - higher mortality is recorded in eastern Slovenia, which has a high unemployment rate, lower income of the population and worse education structure. "Soft" indicators (how inhabitants themselves perceive their situation), which were analysed using data by the Public Opinion and Mass Communication Research Centre (CJMMK) for 2005-2007, show statistically characteristic regional disparities in how people assess their feelings with regard to different aspects that are directly or indirectly related to health. Self-assessment of health tends to be higher in regions with a higher level of education, lower unemployment and higher earnings. In most cases, self-assessment of health was highest in the Osrednjeslovenska, Obalno-kraška and Goriška regions, while negative feeling were most frequent in the Koroška region, Jugovzhodna
Figure 65: Total mortality and unemployment by Slovenia's administrative units, 2005-2007 average
					Lendava ♦
					. Sobota +
				♦ ♦	Trbovlje
			♦ >t ♦	♦ ♦	
Velenie		Koniice		♦ ♦<	
♦	♦	♦ #	♦ ♦<	♦ ♦	Tolmin + ♦
Domža ♦	le ♦		♦ ♦	Il	. Bistrica
♦ * * Vrhnika Kamni				► S	♦ ežana
♦ Šk. Loka Logatec					
			Idrija		
800	900	1000
Deaths per 100 000 inhabitants
Source: SORS; calculations by IMAD.
Figure 66: total mortality and personal income-tax base by Slovenia's administrative units, 2005-2007 average
Ê 7000
		♦ Ljubljana			
					
Domžale					
Vrhn Log^	ka ec	o	♦		Sežana
w ^ Velenje Šk 1 oka		♦	♦ ♦ ♦		♦
		♦♦ ♦ ♦	v	► ♦ ♦	Trbovlje
S	. Konjice +		♦	♦ ♦♦« ♦	♦ t? Tolmi
					♦ Bre2 M. Sobo
			+ Ljutome^ Šmarje pri J. Ormtž«^		
700	800	900 1000
Deaths per 100 000 inhabitants
5 Regionalni razvoj 2. Razvojni izzivi Slovenije, 2009.
Source: SORS; calculations by IMAD.
0
1100
1200
n
a
1200
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6. General government
expenditure
associated with social development
The government seeks to preserve and improve the population's quality of life by maintaining the system of general government expenditure on social protection and other expenditures related to social development.
Social development is associated with expenditure on social protection, but also relies on certain other expenditures. General government expenditures that promote social development have yet to be clearly defined (see Box 5). This chapter thus focuses on expenditure on social protection, health, education, and recreation and culture, which are considered most closely related to social development. By maintaining the system of social protection and other expenditures related to social development, the government takes care of the quality of life and contributes to social cohesion. General government expenditure that is directly and indirectly related to social development has seen its share of GDP diminish in recent years, particularly social-protection expenditure.
6.1 General government expenditure by function
In terms of the level of development (91% of the EU-27 average in GDP per capita in purchasing power standards - PPS), general government expenditure in Slovenia was not high in 2007 and 2008. Slovenia is among those Member States with general government expenditure below the EU-27 average, according to Eurostat.136 While having posted a higher share of GDP of general government expenditure than the EU-27 average as recently as in 2000, Slovenia was ranked in the last third of the EU-27 countries in 2007 and 2008, following a rapid decline in expenditure in Slovenia (2000-2007 by 4.3 p.p. of GDP; 2000-2008 by 3.1 p.p. of GDP) and a concurrent increase in the EU-27 (2000-2008 by 1.6 p.p. of GDP). Of the countries with higher GDP per capita than Slovenia, only Germany, Ireland and Spain had a lower general government expenditure share of GDP. Among the countries with lower GDP per capita in PPS, a higher general government expenditure share of GDP than in Slovenia was recorded in three countries -Portugal, Malta and Hungary. Countries with higher GDP per capita in PPS thus also tend to have a higher general government expenditure share of GDP, while the general
Figure 67: General government expenditure as a share of GDP, EU-27, 2000 and 2008, in %
■ 2000 ■ 2008
IJiftflKÏJ!
Source: Eurostat.
Note: Countries are listed left to right in descending order according to GDPs per capita in PPS in 2008.
government expenditure share in countries with lower GDP per capita in PPS is generally lower.
In 2007, close to two thirds of general government expenditure was directly or indirectly related to social development, i.e. social protection, health, education, and recreation and culture. General government expenditure accounted for 30.8% of GDP in the EU-27, while in Slovenia, this figure was 2.5 p.p. lower (28.3% of GDP). Lower expenditure than in Slovenia in this area was recorded for only five countries with
Figure 68: Social-protection expenditure as a share of GDP, EU-27, 2000 and 2007, in %
"KM!
136 On December 31, 2009, SORS published new data for 2008 and also changed the figures for previous years (2005-2007), while Eurostat data for Slovenia are still unchanged.
Source: Eurostat.
Note: For the whole EU-27, Hungary, Poland and Romania, data for 2000 are not available; the figure thus takes account of data for 2005. Countries are listed left to right in descending order according to GDP per capita in PPS in 2008.
10
0
15
10
5
0
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Box 5: Definition of general government expenditure related to social development
Theory provides no clear definition of which general government expenditures are directly and which indirectly related to social development. In terms of development indicators, the European Commission has identified development-oriented general government expenditure ("productive expenditure") according to three definitions (Developing Indicators for Assessing the Quality of Public Finances, 2008). According to a broad definition, productive expenditure is expenditure aimed at research and development, transport, education, health, public order and safety, and environmental protection. Expenditure on health and education is indisputably related to social development. Certain elements promoting social development can also be found in expenditure on environmental protection, as a healthy environment diminishes the need for health services, and in expenditure on environmental protection, which contributes to higher safety and reduces crime. Expenditure on transport belongs in expenditure on economic affairs, which also impacts social development through better infrastructure that improves accessibility of social services. Expenditure on economic affairs also includes expenditure on employment, which boosts employment as one key element to ensuring financial safety and social integration. Other expenditure groups are regarded as unproductive according to the European Commission's definition. Expenditure on social protection is also indisputably directly related to social development. Indirectly, social development can also be associated with the bulk of expenditure on recreation and culture.
That general government expenditure related to social development is still to be theoretically defined is attributable to the lack of appropriate data from different categories of general government expenditure, as well as the lack of adequate indicators to show the correlation of general government expenditure and development; these are only now beginning to be formed. Two methodologies have been developed to collect data on general government expenditure by function in individual countries across the world, the national accounts methodology (United Nations, Eurostat) and the Government Finance Statistics approach (International Monetary Fund). Slovenia and all other EU Member States use the methodological standards of the system of national accounts. To arrange expenditure by purpose, a classification of the functions of government (COFOG) is used. According to the national accounts and classification by function (COFOG), general government expenditure is, at level 1, classified into ten divisions: general public services, defence, public order and safety, economic affairs, environmental protection, housing and community amenities, health, recreation, culture and religion, education and social protection. Data for Slovenia and EU Member States have so far been collected at level 1, while data at level 2 are only being prepared. For Slovenia, level 2 data have been collected only for health, education and social protection. Indicators are being developed by various institutions. In the EU, the first indicators were only proposed in 2008, but social development indicators have not yet been set (Developing Indicators for Assessing the Quality of Public Finances, 2008).
Given the lack of a clear definition of which general government expenditure is related to social development, and as the database for the classification by function at level 2 is yet to be developed, section 6.1 treats expenditure on social protection, education, health and recreation, culture and religion as expenditure related to social development. Section 6.2 gives a detailed overview of expenditure on social protection according to the ESSPROS methodology; as it differs from the national accounts methodology and classification by purpose, data sets are not comparable. Data on general government expenditure on health care and public expenditure on education, presented in detail in chapters on access to health care and access to childcare and education, are also not comparable with the national accounts methodology and classification by function.
higher GDP per capita in PPS than Slovenia, while among those countries with lower GDP per capita in PPS, expenditure in this area as a share of GDP was higher in only two (Portugal and Hungary). There are, however, significant differences in how countries allocate general government expenditures.
Slovenia is not among the countries where social protection expenditure is high. Expenditure of this kind accounted for 15.5% of GDP in 2007 and was notably below the EU-27 average (18% of GDP). Only nine of the EU-27 countries recorded lower social-protection expenditure shares than Slovenia, and only four of those that have higher GDP per capita in PPS (Ireland, United Kingdom, Spain and Cyprus). Among countries with lower GDP per capita in PPS than Slovenia, higher
expenditure in this area was recorded in three, Portugal, Hungary and Poland. In the EU-27, expenditure on social protection as a share of GDP began to decline after 2003, as in Slovenia. In 2000-2007, Slovenia's expenditure in this area declined by 1.8 p.p., most notably (by 1.4 p.p. of GDP) in 2007 compared with 2006. This relative decline in expenditure was due to the effects of pension reform and the unified mechanism for adjusting social transfers for inflation introduced in 2007.
Within social-protection expenditure, social benefits, except social transfers in kind, account for 93.6%. This share remained unchanged between 2000 and 2007. More than half of expenditure in 2007 (52.5%) was allocated for support in old age, followed by expenditure on sickness and disability (17.8%), family and children
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Table 46: Total general government expenditure as a share of GDP, EU-27, 2000-2008, in %
Countries by GDP per capita in PPS	GDP per capita in PPS, 2008	2000	2005	2006	2007	2008	2000-2008 (change in p.p.)
EU-27	100	45.2	46.9	46.3	45.7	46.8	+1.6
Luxembourg	276	37.6	41.6	38.6	37.2	40.7	+3.1
Ireland	135	31.5	33.7	34.0	35.7	41.0	+9.5
Netherland	134	44.2	44.8	45.6	45.3	45.5	+1.3
Austria	123	52.1	49.9	49.4	48.7	48.7	-3.4
Sweden	120	55.6	55.2	54.1	52.5	53.1	-2.5
Denmark	120	53.6	52.8	51.6	51.0	51.7	-1.9
Finland	117	48.3	50.3	48.7	47.3	48.4	+0.1
United Kingdom	116	39.1	44.1	44.2	44.0	47.7	+8.6
Germany	116	45.1	46.8	45.3	44.2	43.9	-1.2
Belgium	115	49.2	52.2	48.5	48.3	49.9	+0.7
France	108	51.6	53.4	52.7	52.3	52.7	+1.1
Spain	103	39.1	38.4	38.5	38.8	40.5	+1.4
Italy	102	46.2	48.2	48.7	47.9	48.7	+2.5
Cyprus	96	37.0	43.6	43.4	42.9	44.0	+7.0
Greece	94	46.7	43.3	42.2	44.0	44.9	-1.8
Slovenia	91	46.7	45.3	44.6	42.4	43.6	-3.1
Czech Republic	80	41.8	45.0	43.8	42.6	42.4	+0.6
Malta	76	41.0	44.7	43.7	42.6	45.3	+4.3
Portugal	76	43.1	47.6	46.3	45.8	45.9	+2.8
Slovakia	72	50.9	38.2	36.9	34.4	43.9	-7.0
Estonia	67	36.5	34.0	34.2	35.5	40.9	+4.4
Hungary	64	46.5	50.1	51.9	49.7	49.8	+3.3
Lithuania	62	39.1	33.3	33.6	34.9	37.2	-1.9
Latvia	57	37.3	35.6	38.2	35.9	39.5	+2.2
Poland	56	41.1	43.4	43.8	42.1	43.1	+2.0
Romania	47	38.5	33.5	35.3	36.6	38.5	0.0
Bulgaria	41	42.6	39.9	36.5	41.5	37.4	-5.2
Source: Eurostat.
Notes: Countries are listed by GDP per capita in PPS; N/A - not available; PPS - purchasing power standards.
(11.1%) and survivors (9.8%). Owing to a relatively low unemployment rate, expenditure on unemployment accounted for a mere 3.3% of social-protection expenditure.
Slovenia also has low expenditure on health.
Expenditure on health accounted for 5.9% of GDP in 2007, being 0.7 p.p. lower than the EU-27 average (6.6% of GDP). Lower GDP shares of health expenditure than in Slovenia were recorded for only five countries with higher GDP per capita in PPS than Slovenia, and among lower-GDP countries, only for those with GDP per capita in PPS below 70% of the EU-27 average. Nearly all EU-27 countries recorded a rise in expenditure on health as a share of GDP in 2000-2007. In Slovenia, expenditure
on health started gradually to decline after 2001 (2001: 6.7% of GDP), hitting a low in 2007. The relative decline was due to slow nominal growth in the compensation of employees, and intermediate and final consumption expenditures.
Within expenditure in 2007, the highest share was recorded for expenditure on hospital services (41.0%), followed by expenditure on out-patient services (32.9%) and expenditure on medical products, appliances and equipment (18.1%). Other expenditure groups account for just 8% of expenditure on health.137 In the period up
137 These are: public health services, R&D health, and health not elsewhere classified.
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Table 47: Structure of general government expenditure in 2007, as a share of GDP, EU-27, 2007, in %
Countries by GDP per capita in PPS	GDP per capita in PPS, 2008	General government expenditure, total	Expenditure on social protection, health, education, and recreation and culture	Social-protection expenditure	Health expenditure	Education expenditure	Expenditure on recreation, culture and religion
EU-27	100	45.7	30.8	18.0	6.6	5.1	1.1
Luxembourg	276	37.2	26.7	15.8	4.5	4.5	1.9
Ireland	1135	35.7	22.2	10.0	7.0	4.5	0.7
Netherland	134	45.3	28.4 (p)	16.3 (p)	5.7 (p)	5.1 (p)	1.3 (p)
Austria	123	48.7	33.6	19.9	7.5	5.2	1.0
Sweden	120	52.5	36.4	21.6	6.8	6.9	1.1
Denmark	120	51.0	38.0	21.7	7.3	7.4	1.6
Finland	117	47.3	33.4	19.9	6.6	5.8	1.1
United Kingdom	116	44.0	30.1	15.3	7.5	6.2	1.1
Germany	116	44.2	31.3	20.4	6.3	3.9	0.7
Belgium	115	48.3	31.1	17.1	7.0	5.8	1.2
France	108	52.3	36.8	22.2	7.2	5.9	1.5
Spain	103	38.8	24.7	13.0 (p)	5.7 (p)	4.4 (p)	1.6 (p)
Italy	102	47.9	30.5	18.2	6.8	4.7	0.8
Cyprus	96	42.9	21.5	9.9	2.9	7.4	1.3
Greece	94	44.0	26.9	18.6	4.9	3.0	0.4
Slovenia	91	42.4	28.3	15.5	5.9	5.8	1.1
Czech Republic	80	42.6	26.0	12.9	7.1	4.7	1.3
Malta	76	42.6	25.5	13.7	5.8	5.4	0.6
Portugal	76	45.8	31.2	17.5	6.8	5.8	1.1
Slovakia	72	34.4	21.8 (p)	10.6 (p)	6.5 (p)	4.0 (p)	0.7 (p)
Estonia	67	35.5	22.6	9.8	4.5	6.2	2.1
Hungary	64	49.7	29.0	17.3	4.9	5.3	1.5
Lithuania	62	34.9	21.9	11.1	4.6	5.2	1.0
Latvia	57	35.9	20.7	8.4	4.6	5.8	1.9
Poland	56	42.1	27.1	15.7	4.6	5.7	1.1
Romania	47	36.6	19.4	9.9	4.3	4.2	1.0
Bulgaria	41	41.5	20.9	13.1 (p)	3.1 (p)	3.9 (p)	0.8 (p)
Source: Eurostat.
Notes: Countries are listed by GDP per capita in PPS; N/A - not available; (p) - provisional data; PPS - purchasing power standards.
to 2007, expenditure on hospital services increased by 0.6 p.p. and expenditure on medical products, appliances and equipment by 1.3 p.p. compared with 2000, while expenditure on out-patient services decreased by 0.7 p.p. and other expenditures by 1.2 p.p.
Expenditure on education in Slovenia is higher than the EU-27 average. In Slovenia, expenditure on education accounted for 5.8% of GDP in 2007, while in the EU, expenditure was on average 0.7 p.p. lower (5.1% of GDP). Slovenia is ranked in the middle of the EU Member States. Higher expenditure than in Slovenia was recorded for four Member States that have higher GDP per capita in PPS, and by two with lower per capita PPS GDP. Expenditure on education has been on a
slight downward trend since 2005 (2005-2007: 0.2 p.p. of GDP). Expenditure in Slovenia had been higher, but declined by 0.5 p.p. of GDP in 2007 compared with 2006, largely due to a slower nominal growth in intermediate consumption.
Within expenditure on education138 in 2007, the largest share was for secondary education (41.5%), followed by pre-primary and primary education (36.0%) and tertiary
138 Expenditure on formal education is divided according to the International Standard Classification of Education (ISCED 1997), according to which primary education includes the first six primary school grades, while the last three grades (from 7 through 9) are already defined as secondary education.
Social overwiew 2009	80
The way we live
education (16.7%). A total of 5.8% of expenditure on education was allocated for other functions.139 Broken down by structure, expenditures on pre-primary and primary education increased compared with 2000 (by 0.7 p.p.), while the share of expenditure on tertiary education declined (by 0.7 p.p.).
Expenditure on recreation, culture and religion in Slovenia is the same as in the EU-27 average (1.1% of GDP). Only a few Member States stand out in terms of this expenditure (with significantly higher or lower shares), while EU average expenditure as a share of GDP has remained unchanged since 2002. In Slovenia, this share of expenditure has also remained unchanged since 2000.
6.2 Social-protection expenditure
Slovenia allocated EUR 7.381 m or 21.4% of GDP for social protection in 2007, which is 1.3 p.p. less than a year before and 4.8 p.p. less than the EU-27 average.
Social protection encompasses services and benefits intended to relieve households and individuals of the burden of a defined set of risks or social needs. Social protection is carried out according to eight social-protection functions.140 The expenditure decline in 2007 is a result of GDP growing faster than social-protection receipts. Social-protection expenditure increased by nearly 5% in nominal terms compared with 2006, but only slightly more than 1% in real terms. In Slovenia, the share of expenditure on social protection accounted for 24.2% of GDP in 2000 and has been declining steadily since 2001. The share of social-protection expenditure in the EU-25141 increased from 2000, when it totalled 26.5%, until 2003, but then in 2004 started to decline. Slovenia's lag behind the EU-25 in terms of social-protection expenditure as a share of GDP was increasing in 2000-2007. While Slovenia had been 2.3 p.p. behind the EU-25 in 2000, this gap widened to as much as 5 p.p. by 2007 (see Figure 69). In terms of expenditure for social protection, Slovenia was ranked in the middle of the EU-27 in 2007.
In terms of expenditure on social protection in purchasing-power standards, Slovenia reached 70% of expenditure allocated for social protection in the EU-25. The data on social-protection expenditure in purchasing-power standards (PPS) per capita probably show a somewhat more realistic picture, i.e. that in 2007, Slovenia reached 70% of the level of expenditure allocated for social protection in the EU-25. Social-
Figure 69: Social-protection expenditure as a share of GDP, 2007, EU-27, in %
139	These are: post-secondary non-tertiary education, education not definable by level, subsidiary services to education, R&D education, and education not elsewhere classified.
140	According to ESSPROS (Eurostat) methodology, these are: sickness/health care, disability, old age, survivors, family/ children, unemployment, housing (for which data are not available till 2005 in Slovenia), and social exclusion not elsewhere classified.
141	For the EU27, data are only available from 2005 onwards.
rocuräE fö^ C — =3 — "O 3 U TO^ Œo-l
2 « TO e .2 3 E

OI
KD
<v
ÎJ23J
wrnii;
Source: Eurostat/ESSPROS.
protection expenditure increased slightly in 2000-2006, while in 2007, it posted a small decline compared with the level the previous year. Due to methodological changes, expenditure on survivors increased significantly in 2006, while the volume of old-age benefits was somewhat lower.142
As shown in Table 48, in terms of expenditure on social protection in purchasing power standards, Slovenia comes closest to the EU-25 average in the following functions: survivors, sickness/health care, and family/ children. It exceeds significantly the EU-25 average in expenditure on social exclusion not elsewhere classified (probably also due to differences in social programmes).
Slovenia, as the EU-27, allocates the bulk of social-protection expenditure for old age and sickness/ health-care benefits combined. Looking at the structure of expenditure on total social protection in Slovenia, the largest shares are allocated for old age (39.3%; in the EU-27, 39.6%) and sickness/health-care functions (32.1%; in the EU-27, 39.3%), followed by family/children (8.7%; in the EU-27, 8.0%), disability (7.8%; in the EU-27, 8.1%), survivors143 (7.4%; in the EU-27, 6.6%), unemployment (2.3%; in the EU-27, 5.1%), social exclusion not elsewhere classified (2.3%; in the EU-27, 1.3%) and housing, where Slovenia stands out most compared with the EU-27 (0.1%; in the EU-27, 2.3%).
Broken down by sources of finance, social protection in Slovenia is mostly financed from contributions by the insured, while social-protection receipts in the EU-27 mainly come from employers' contributions. In
Slovenia, social-protection receipts are mostly financed by contributions by insured persons (41%), while in
142	Due to the transfer of expenditure on survivors' pensions from the old-age function to the survivors function.
143	Mainly expenditure on survivors' and widows' pensions.
15
10
5
0
Social overwiew 2009	81
The way we live
Table 48: Social-protection expenditure per head of population by function group, Slovenia and EU-25 average, 2000, 2006 and 2007 (in PPS per capita)
Social protection function	Slovenia			EU-25			Slovenia level index		
							EU-25 = 100		
	2000	2006	2007	2000	2006	2007	2000	2006	2007
Social protection expenditure, total	3685.3	4703.3	4760.5 p	5301.9	6604.8 p	6805.5 p	69	71	70
Sickness/health care	1100.6	1477.8	1487.8 p	1394.9	1853.1 p	1911.2 p	79	80	78
Disability	323.7	375.5	363.4 p	420.3	506.7 p	527.6 p	77	74	69
Old age	1552.3	1746.7	1824.6 p	2032.2	2496.4 p	2592.0 p	76	70	70
Survivors	71.0	344.31	344.3 p	340.1	428.0 p	436.2 p	21	80	79
Family/children	330.7	394.1	402.2 p	419.9	496.4 p	519.7 p	79	79	77
Unemployment	153.0	139.9	106.2 p	308.8	357.1 p	332.7 p	49	39	30
Housing	N/A	3.2	3.3 p	110.6	144.4 p	149.2 p	N/A	2.2	2.2
Social exclusion not elsewhere classified	66.2	112.3	107.6 p	59.2	83.2 p	87.2 p	112	135	123
Source: EUROSTAT/ESSPROS; calculations by IMAD.
Notes: PPS - purchasing power standards; N/A - not available; 1change in methodology; p - provisional data.
the EU-27, social-protection receipts come mainly from contributions by employers (38.5%), immediately followed by general government contributions from taxes (38%), which is to a great extent a consequence of different systems for financing social protection. Contributions of insured persons increased further in Slovenia in the last year, while general government contributions (taxes) declined. The share of contributions by insured persons in the EU-27 is half lower (20%) than in Slovenia, while the share of employers' contributions is 11.4 p.p. higher (38.5%). Slovenia boasts a more efficient distribution of social-protection programmes than the EU-27, with administration costs representing 2.1% of all social-protection expenditure, while in the EU-27 these costs are 0.9 p.p. higher (3.0%).
Figure 70: Social-protection receipts by type, Slovenia and EU-27, 2007, in %
45
■ Slovenia	EU-27
Contributions Contributions Government	Other
of	of persons contributions contributions
employers	insured
Source: Eurostat/ESSPROS.
statistical appendix
Social overview 2009
Statistical appendix
85
List of tables
Table 1: Number and share of population by selected age groups, Slovenia, 2000-2009, in %................................87
Table 2: Population projections, Slovenia, 2008-2060.......................................................................................................87
Table 3: Number and age structure of population by region, 2000-2009......................................................................87
Table 4: Some basic data on population, EU-27, 2000-2008.............................................................................................88
Table 5: Selected indicators on births, Slovenia, 2000-2008............................................................................................88
Table 6: Crude marriage rates and mean age of mother at first birth, Slovenia, 2000-2008......................................89
Table 7: Selected family and fertility indicators, EU-27, 2007 (2008)...............................................................................89
Table 8: Some basic data on deaths, Slovenia, 2000-2008................................................................................................90
Table 9: Employment rate by school attainment, total and by gender, Slovenia, 2000-2008, in %..........................90
Table 10: Unemployment rate by educational attainment of the unemployed, Slovenia, 2000-2008, in %............91
Table 11: Employment and unemployment rates according to the Labour Force Survey
(persons aged 15-64), EU-27, 2000-2008, in %....................................................................................................92
Table 12: Temporary employees as percentage of total number of employees for age group 15-64, according
to Labour Force Survey, EU-27, 2000-2008, in %..................................................................................................93
Table 13: Persons entitled to financial social assistance by region, 2001-2009, in %...................................................94
Table 14: Personal income tax base per capita by region, indices (Slovenia=100), 2000-2007...................................94
Table 15: Structure of household consumption according to COICOP,2 EU-27, 2008......................................................95
Table 16: Expenditure on health care, EU-27, 2000 and 2007.............................................................................................96
Table 17: Number of (acute) hospital beds and number of inhabitants per acute hospital bed,
by region, 2000-2008................................................................................................................................................97
Table 18: Physicians at primary level by region, 2003-2008...............................................................................................97
Table 19: Hospitalisations due to diseases by main causes for admission, by age and gender, Slovenia, 2008.......98
Table 20: Diagnostic related groups (DRG), cases of acute care per 1,000 inhabitants and average
weight by age groups, Slovenia, 2005-2008.........................................................................................................99
Table 21: People in old people's homes and structure by reason for admission, in %, Slovenia, 2000-2008.........100
Table 22: People in old people's homes by mode of payment for care, 2000-2008, in %............................................100
Table 23: Share of households with own housing by available assets, Slovenia, 2000-2007, in %..........................101
Table 24: Average number of rooms per equivalent household member by tenure status,
Slovenia, 2000-2007................................................................................................................................................101
Table 25: Share of children attending kindergartens, by age, Slovenia, 2000/2001-2008/2009, in %.....................102
Table 26: Number and structure of young people enrolled in upper secondary education, by type of
education programme, Slovenia, 2000/2001-2008/2009.................................................................................102
Table 27: Participation rate of population in tertiary education, Slovenia, 2000/2001-2008/2009, in %................102
Table 28: Ratio between number of students in tertiary education and number of population
aged 20-29, participation rate of young people aged 20-24 in tertiary education and share of total public expenditure on education allocated for financial assistance to students and transfers,
EU-27, 2000-2006 (2007), in %...............................................................................................................................103
Table 29: Participation rate of population aged 25-64 in lifelong learning, Slovenia, 2003-2008, in %.................104
Table 30: Participation of adults aged 25-64 in formal and non-formal education, by socio-economic
characteristics, Slovenia, 2007, in %......................................................................................................................104
Table 31: Number and structure of young people who compyearsed upper secondary education,
Slovenia, 2000/2001-2007/2008...........................................................................................................................105
Table 32: Number and structure of graduates from tertiary education, Slovenia, 2000-2008..................................105
Table 33: Graduates from tertiary education, EU-27, 2000-2007.....................................................................................106
Table 34: Structure of population aged 15 or over by educational attainment, Slovenia, 2000-2008, in %...........107
Table 35: Total public expenditure on formal education as share of GDP by level of education,
Slovenia, 2000-2007, in %.......................................................................................................................................107
Table 36: Education structure of population aged 25-64 years, 2000 in 2008, EU-27, in %........................................108
Table 37: Public expenditure on formal education (all levels) as share of GDP, total and by level
of education, EU-27, 2000-2006, in %..................................................................................................................109
Table 38: Number of exhibitions and visitors in museums, galleries and exhibition grounds,
Slovenia, 2004-2008.................................................................................................................................................110
Table 39: Number of theatrical performances and visitors in theatres, Slovenia, 2004-2008....................................110
Table 40: Attendance in cinemas and structure of viewers by film origin, Slovenia, 2000-2008...............................110
Table 41: Titles of published books and brochures, by origin, Slovenia, 2000-2008...................................................110
Table 42: Attendance, loans per registered user, total and in public libraries, 2000-2007.........................................111
Table 43: Time dedicated to media and news on actual or political events on a regular day in the week,
in hours, 2002-2008.................................................................................................................................................111
Table 44: Internet users by type of settlement, Slovenia, 2004-2009, in %...................................................................112
86 Social overview 2009
Statistical appendix
Table 45:	Share of households with Internet access and Internet users, Slovenia and EU-27, 2004-2009, in % ....112
Table 46: Subjective feelings of happiness, 2000-2008, in %...........................................................................................113
Table 47: Satisfaction with life, 2002, 2004, 2006 and 2008, in %.....................................................................................113
Table 48: Trust in other people, 2002, 2004, 2006 and 2008, in %....................................................................................113
Table 49: Trust in institutions, Slovenia, 2002, 2004, 2006 and 2008, in %.....................................................................113
Table 50:	Subjective perceptions of crime in Slovenia; feeling of safety and personal experience of crime,
Slovenia, 2002, 2004, 2006 and 2008, in %..........................................................................................................114
Table 51: Number of suicides per 100,000 inhabitants, EU-27, 2000-2007.....................................................................114
Table 52: Number of deaths in road traffic accidents per 100,000 inhabitants, EU-27, 2000-2007...........................115
Table 53:	Number of prisoners 2000-2007, and number of prisoners per 100,000 inhabitants,
EU-27, 2005-2007.....................................................................................................................................................116
Table 54: Number of police officers per 100,000 inhabitants, selected European countries, 2003...........................117
Table 55: Number of crimes per 100,000 inhabitants, EU-27, 2000-2003 .....................................................................117
Table 56: Number of homicides per 100,000 inhabitants, EU-27, 2000-2007 ...............................................................118
Table 57:	Risk of poverty rates after and before social transfers (excluding income in kind), EU-27,
2000-2008, in %........................................................................................................................................................119
Table 58: Gini coefficient (%), income quintile share ratio (80/20), Slovenia, 2000-2008...........................................120
Table 59: At risk of poverty rate by gender and age, Slovenia, 2000-2008, in %..........................................................120
Table 60: At-risk-of-poverty threshold (in SIT, EUR), Slovenia, 2000-2008.....................................................................120
Table 61:	At-risk-of-poverty rate with breakdown by most common activity status,
total and by gender, Slovenia,...............................................................................................................................121
Table 62: At-risk-of-poverty rate with a breakdown by household type, Slovenia, 2000-2008, in %......................121
Table 63: Social protection expenditure as share of GDP, EU-25, 2000-2007, in %......................................................122
Table 64: Social protection expenditure by function as share of GDP,Slovenia, 2000-2007, in %.............................123
Table 65: Social protection per capita in PPS, Slovenia, 2000-2007................................................................................123
Table 66: GDP, Slovenia, 2000-2008.......................................................................................................................................124
Table 67: GDP per capita (EUR, current exchange rate), Slovenia, by region, 2000-2006...........................................124
Table 68: GDP per capita, index (Slovenia=100), by region, 2000-2006.........................................................................125
Table 69: GDP per capita in PPS, EU-27=100, Slovenia and EU-27, 2000-2008.............................................................126
Table 70: Development Deficiency Index by region, 2007-2013......................................................................................127
Table 71: Human Development Index, EU-27, calculations 2000-2009..........................................................................128
Table 72: Human Development Index (HDI) and structural indicators, Slovenia, 2000-2007....................................129
Table 73: Gender-related Human Development Index (GDI) and structural indicators, Slovenia, 2000-2007........130
Table 74: Gender Empowerment Measure (GEM) and structural indicators, Slovenia, 2000-2007...........................130
87 Social overview 2009
Statistical appendix
DEMOGRAPHY
Table 1: Number and share of population by selected age groups, Slovenia, 2000-2009, in %
	2000	2001	2002	2003	2004	2005	2006	2007	2008	2009
Population (as of 30 June)	1,990,272	1,992,035	1,995,718	1,996,773	1,997,004	2,001,114	2,008,516	2,019,406	2,022,629	2,042,335
Shares as of 30 June (%):										
0-14 years	15.9	15.6	15.2	14.8	14.5	14.2	14.0	13.9	13.9	14.0
15-64 years	70.1	70.1	70.2	70.4	70.4	70.3	70.2	70.1	69.7	69.5
65 years and over	14.0	14.3	14.6	14.9	15.2	15.5	15.7	16.0	16.3	16.5
80 years and over	2.3	2.4	2.6	2.8	2.9	3.1	3.3	3.5	3.7	3.8
Ageing index1 (as of 30 June)	87.8	91.9	96.4	100.8	104.9	108.7	112.4	115.1	117.1	118.0
Source: SORS.
Note. 1 Ageing index is the ratio between the old population (aged 65 and over) and the young population (aged 0-14) multiplied by 100.
Table 2: Population projections,1 Slovenia, 2008-2060
	2008	2009	2010	2020	2030	2040	2050	2060
Number of population	2,022,644	2,028,743	2,034,220	2,058,003	2,022,872	1,957,942	1,878,003	1,778,573
Structure of population (in %):								
0-14 years	13.9	13.9	13.8	14.2	12.8	12.1	12.8	12.8
15 - 64 years	70.0	69.8	69.5	65.4	61.9	58.9	54.7	53.8
65+ years	16.1	16.4	16.6	20.4	25.3	29.1	32.5	33.4
80+ years	3.5	3.7	3.9	5.4	6.7	9.9	12.0	13.9
Source: SORS, Eurostat (Europop 2008, convergence scenario).
Notes: 1The term population projection refers to the calculation of the future size and characteristics of the population based on hypotheses about future developments in fertility, mortality and migration. Eurostat made projections of the Slovenian population for 2008-2060 (EUROPOP 2008).
Table 3: Number and age structure of population by region, 2000-2009
	Number of population1	Age structure of population,1 %		
		Aged 0-14 years	Aged 15-64 years	Aged 65 or over
	2009	2009	2009	2009
Slovenia	2,042,335	14.0	69.5	16.5
Pomurska	119,691	13.2	69.6	17.2
Podravska	323,110	12.9	69.9	17.2
Koroška	72,839	14.2	69.9	15.9
Savinjska	259,741	14.3	69.9	15.8
Zasavska	44,740	12.7	69.5	17.7
Spodnjeposavska	70,091	13.8	69.2	17.1
Jugovzhodna Slovenija	141,935	14.9	69.5	15.6
Osrednjeslovenska	526,636	14.5	69.7	15.8
Gorenjska	202,470	15.0	68.4	16.6
Notranjsko-kraška	52,163	13.8	69.0	17.2
Goriška	119,055	13.5	68.4	18.1
Obalno-kraška	109,864	12.2	70.6	17.2
Source: SORS. Note: 1As of 30 June.
88 Social overview 2009
Statistical appendix
Table 4: Some basic data on population, EU-27, 2000-2008
	Number	Population growth, %		Starostna struktura prebivalstva, v %			Ageing index1
	(1 January)			Aged 0-14	Aged 15-64	Aged 65 and over	
	2008	2007-2008	2000-2008	2008	2008	2008	2008
Austria	8,336,926	0.4	4.1	15.2	67.5	17.2	113.3
Bulgaria	7,623,395	-0.5	-6.7	13.4	69.2	17.4	129.4
Cyprus	7,93,072	1.2	14.3	17.3	70.1	12.6	73.0
Czech Republic	10,424,336	0.9	1.5	14.2	71.1	14.7	103.8
Denmark	5,493,621	0.6	2.9	18.4	65.9	15.7	85.7
Estonia	1,340,675	-0.1	-2.1	14.9	68.0	17.2	115.2
Finland	5,313,399	0.5	2.7	16.8	66.6	16.6	99.0
France	64,166,820	0.6	5.6	18.5	65.1	16.5	89.2
Greece	11,237,094	0.4	2.9	14.3	67.0	18.7	130.4
Ireland	4,425,675	1.6	16.3	20.7	68.3	11.0	52.8
Italy	59,832,179	0.8	5.1	14.0	65.9	20.1	142.9
Latvia	2,266,094	-0.4	-4.5	13.7	69.0	17.2	125.5
Lithuania	3,358,115	-0.5	-4.0	15.2	68.9	15.9	104.6
Luxembourg	488,650	1.8	12.0	18.1	68.0	14.0	77.4
Hungary	10,038,188	-0.2	-1.7	14.9	68.8	16.3	108.8
Malta	411,950	0.7	6.8	16.0	70.0	14.0	87.0
Germany	82,110,097	-0.2	-0.1	13.7	66.1	20.2	148.3
Netherland	16,445,593	0.4	3.3	17.8	67.3	14.9	83.4
Poland	38,125,759	0.0	-0.9	15.4	71.1	13.5	87.6
Portugal	10,622,413	0.1	3.9	15.3	67.2	17.5	114.5
Romania	21,513,622	-0.2	-4.1	15.2	69.9	14.9	97.9
Slovakia	5,406,626	0.2	0.3	15.6	72.4	12.0	77.1
Slovenia	2,021,316	0.5	1.6	14.0	69.7	16.4	117.1
Spain	45,555,716	1.5	13.1	14.7	68.7	16.6	113.2
Sweden	9,219,637	0.8	3.9	16.7	65.6	17.6	105.5
Source: Eurostat.
Notes: Data for Belgium and the United Kingdom are not available. 1The ageing index is the ratio of old population (aged 65 and over) to young population (aged 0 to 14) multiplied by 100.
Table 5: Selected indicators on births, Slovenia, 2000-2008
	2000	2001	2002	2003	2004	2005	2006	2007	2008
Live births	18,180	17,477	17,501	17,321	17,961	18,157	18,932	19,823	21,817
Live births per 1,000 population	9.1	8.8	8.8	8.7	9.0	9.1	9.4	9.8	10.8
Total fertility rate1	1.26	1.21	1.21	1.20	1.25	1.26	1.31	1.38	1.53
Net reproduction rate2	0.60	0.58	0.58	0.57	0.61	0.60	0.63	0.67	0.74
Live births outside marriage	6,746	6,881	7,037	7,354	8,053	8,475	8,943	10,071	11,531
Share of live births outside marriage, %	37.1	39.4	40.2	42.5	44.8	46.7	47.2	50.8	52.9
Source: SORS.
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-specific 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 of reproductive age (15-49 years) would give birth to if their age-specific fertility and mortality rates remained equal to those in the observed year.
89 Social overview 2009
Statistical appendix
Table 6: Crude marriage rates and mean age of mother at first birth, Slovenia, 2000-2008
	2000	2001	2002	2003	2004	2005	2006	2007	2008
Crude marriage rates (marriages per 1,000 population)	3.6	3.5	3.5	3.4	3.3	2.9	3.2	3.2	3.3
Mean age of bride at first marriage (in years)	26.6	27.0	27.4	27.5	27.8	28.2	28.1	28.3	28.4
Mean age of groom at first marriage (in years)	29.4	29.6	30.1	30.1	30.3	30.6	30.6	30.9	30.9
Mean age of mother at first birth (in years)	26.5	26.7	27.2	27.3	27.5	27.8	28.0	28.2	28.4
Source: SORS.
Table 7: Selected family and fertility indicators, EU-27, 2007 (2008)
	Marriages per 1,000 population	Divorces per 1,000 population	Share of live births outside marriage, %	Mean age of mother at first birth	Total fertility rate1
	2008	2008	2007	2008	2007
Austria	4.2	N/A	38.3	29.5	1.38
Belgium	4.4	2.8	39.0	N/A	N/A
Bulgaria	3.6	1.9	50.2	26.8	1.42
Cyprus	N/A	N/A	8.7	30.4	1.39
Czech Republic	5.0	3.0	34.5	29.3	1.44
Denmark	6.8	2.7	46.1	30.4	1.84
Estonia	4.6	2.6	57.8	28.8	1.63
Finland	5.8	2.5	40.6	30.1	1.83
France	4.3	N/A	51.7	29.9	1.98
Greece	4.6	N/A	5.8	30.9	1.41
Ireland	N/A	N/A	N/A	31.1	2.01
Italy	4.1	0.9	20.7	31.1	N/A
Latvia	5.7	2.7	43.0	28.3	1.41
Lithuania	7.2	3.1	29.2	28.2	1.35
Luxembourg	3.9	2.0	29.2	31.1	1.61
Hungary	4.0	2.5	37.5	29.3	1.32
Malta	6.0	N/A	24.9	28.6	1.37
Germany	4.6	2.3	30.8	30.3	1.37
Netherland	4.6	2.0	39.5	27.7	1.72
Poland	6.8	1.7	19.5	28.1	1.31
Portugal	4.1	N/A	33.6	30.2	1.33
Romania	7.0	1.7	26.7	27.1	1.30
Slovakia	5.2	2.3	28.8	28.3	1.25
Slovenia	3.3	1.1	50.8	30.1	1.38
Spain	N/A	N/A	N/A	30.8	1.40
Sweden	5.5	2.3	54.8	N/A	1.88
Source: Eurostat, SORS.
Notes: Data for the United Kingdom are not available. 1The total fertility rate is the average number of children per one woman in reproductive age (15-49 years) in the calendar year. The table shows calculations by national statistical offices; N/A - not available.
90 Social overview 2009
Statistical appendix
Table 8: Some basic data on deaths, Slovenia, 2000-2008
	2000	2001	2002	2003	2004	2005	2006	2007	2008
Deaths	18,588	18,508	18,701	19,451	18,523	18,825	18,180	18,584	18,308
Deaths per 1,000 population	9.3	9.3	9.4	9.7	9.3	9.4	9.1	9.2	9.1
Mean age at death (in years), total	71.8	71.7	72.3	72.5	72.5	73.3	73.2	73.6	74.1
Men	67.2	67.3	67.9	68.2	68.3	68.9	68.5	69.1	69.9
Women	75.6	76.6	77.0	77.2	76.9	77.8	78.1	78.2	78.8
Infant mortality per 1000 live births	4.9	4.2	3.8	4	3.7	4.1	3.4	2.8	2.4
Source: SORS.
LABOUR MARKET AND EMPLOYMENT
Table 9: Employment rate1 by school attainment, total and by gender, Slovenia, 2000-2008, in %
	2000	2001	2002	2003	2004	2005	2006	2007	2008
Total	53.9	54.5	53.8	52.8	55.3	55.4	55.8	56.8	56.9
Without education, incomplete primary education	21.8	22.2	20.3	18.5	19.5	16.4	18.8	18.7	17.5
Primary education	35.2	36.2	34.2	32.9	35.1	34.8	33.9	35.4	34.7
Secondary education	61.6	61.7	60.6	59.1	61.5	61.7	61.3	61.8	62.2
Post-secondary education (not higher education)	72.5	72.1	70.7	69.2	68.7	66.5	66.8	69.2	64.8
Higher professional and university education	79.2	79.7	81.4	81.2	81.6	81.7	82.8	82.7	83.0
Post-graduate education (specialisation, master's and doctor's degree)	80.2	81.9	83.7	88.4	88.7	86.3	85.6	85.5	88.2
									
Men	60.2	61.3	60.3	59.4	62.0	62.0	62.5	63.7	63.0
Without education, incomplete primary education	32.1	32.1	31.1	27.9	29.6	26.0	28.0	(25.8)	26.0
Primary education	41.8	44.9	42.0	41.7	44.5	44.2	43.2	46.4	45.2
Secondary education	66.6	66.7	65.6	64.3	66.6	66.8	67.0	67.7	67.1
Post-secondary education (not higher education)	67.6	69.7	68.2	68.2	70.0	67.5	67.9	69.2	65.4
Higher professional and university education	75.9	75.1	77.9	77.0	77.9	77.6	80.0	79.2	78.7
Post-graduate education (specialisation, master's and doctor's degree)	82.4	82.6	79.7	86.1	86.9	(85.2)	(83.7)	85.7	87.1
Women	48.0	48.2	47.7	46.5	48.9	49.2	49.4	50.2	51.0
Without education, incomplete primary education	14.8	15.7	13.9	12.7	13.4	10.6	12.7	(14.4)	12.3
Primary education	31.0	30.7	29.0	27.0	29.0	28.6	27.6	28.1	27.5
Secondary education	55.8	55.7	54.6	53.0	55.4	55.8	54.8	54.8	56.2
Post-secondary education (not higher education)	76.1	73.8	72.5	70.1	67.6	65.7	66.0	69.2	64.3
Higher professional and university education	82.6	83.9	84.5	84.8	84.7	85.0	85.2	85.4	86.5
Post-graduate education (specialisation, master's and doctor's degree)	(77.2)	(80.7)	(90.9)	92.0	91.0	(87.8)	(88.4)	(85.4)	89.4
Source: SORS, Labour Force Survey.
Notes: less precise estimate (10<=CV<20). 1The employment rate represents persons in employment as a percentage of the labour force. Persons in employment are those who during the reference week (from Monday to Sunday) did any work for payment (in cash or in kind), profit or family gain, or those employed or self-employed persons who were not working because they were temporarily absent. Unpaid family workers, persons on maternity leave and workers on temporary or permanent lay-off i.e. until the termination of their employment are included in persons in employment. Unpaid family workers are people 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 payment for their work. The working age population comprises all persons aged 15 or more.
91 Social overview 2009
Statistical appendix
Table 10: Unemployment rate1 by educational attainment of the unemployed,2 Slovenia, 2000-2008, in %
	2000	2001	2002	2003	2004	2005	2006	2007	2008
Total	7.0	6.4	6.4	6.7	6.3	6.5	6.0	4.9	4.4
Without education, incomplete primary education	(10.7)	(14.2)	(9.5)	(11.9)	(9.7)	(9.1)	(9.7)	(10.9)	9.2M
Primary education	10.4	8.7	9.0	9.1	9.0	9.4	7.4	6.2	5.8
Lower or middle vocational education	7.5	6.9	7.5	8.2	7.5	7.3	6.6	4.5	4.3
Secondary technical education	6.6	5.9	5.5	5.9	5.7	6.3	6.2	5.2	4.3
Secondary general education	7.5	(7.0)	(7.5)	(6.4)	(7.1)	(8.4)	(8.3)	(6.7)	5.3M
Post-secondary education (not higher education)	(2.3)	(2.2)	(2.3)	(2.7)	(3.6)	(3.1)	(3.6)	(2.5)	2.7M
Higher professional and university education	(2.4)	(2.7)	(3.0)	(3.7)	(2.9)	3.4	3.4	3.9	3.9
Post-graduate education (specialisation, master's and doctor's degree)	N/A	N/A	N/A	N/A	N/A	N/A	N/A	N/A	N
Source: SORS, Labour Force Survey.
Notes: ( ) less precise estimate (10<=CV<20) 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-employed and did not do any paid work), but were actively seeking work (specific 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. N/A - not available. M - less accurate estimate - cautious use. N - estimate not accurate enough to be published.
92 Social overview 2009
Statistical appendix
Table 11: Employment and unemployment rates according to the Labour Force Survey (persons aged 15-64), EU-27, 20002008, in %
	Employment rates, %			Unemployment rates, %		
	2000	2007	2008	2000	2007	2008
EU-27	62.2	65.4	65.9	9.4	7.2	7.1
Austria	68.5	71.4	72.1	4.7	4.5	3.9
Belgium	60.5	62.0	62.4	6.6	7.5	7.0
Bulgaria	50.4	61.7	64.0	16.4	6.9	5.7
Cyprus	65.7	71.0	70.9	5.1	4.0	3.8
Czech Republic	65.0	66.1	66.6	8.8	5.4	4.4
Denmark	65.6	69.4	70.7	8.0	8.7	7.6
Estonia	60.4	69.4	69.8	13.4	4.8	5.6
Finland	67.2	70.3	71.1	11.2	6.9	6.4
France	62.1	64.6	65.2	10.3	8.0	7.4
Greece	56.5	61.4	61.9	11.5	8.4	7.8
Ireland	65.2	69.1	67.6	4.4	4.6	6.1
Italy	53.7	58.7	58.7	11.0	6.2	6.8
Latvia	57.5	68.3	68.6	14.5	6.1	7.7
Lithuania	59.1	64.9	64.3	16.3	4.4	5.9
Luxembourg	62.7	64.2	63.4	2.4	4.1	5.1
Hungary	56.3	57.3	56.7	6.6	7.4	7.9
Malta	54.2	54.6	55.2	6.4	6.5	6.1
Germany	76.3	77.1	78.1	4.5	3.8	3.4
Netherland	72.9	76.0	77.2	2.7	3.2	2.7
Poland	55.0	57.0	59.2	16.6	9.7	7.2
Portugal	68.4	67.8	68.2	4.0	8.5	8.1
Romania	63.0	58.8	59.0	7.7	6.8	6.1
Slovakia	56.8	60.7	62.3	19.1	11.2	9.5
Slovenia	62.8	67.8	68.6	7.1	5.0	4.5
Spain	56.3	65.6	64.3	13.9	8.3	11.4
Sweden	73.0	74.2	74.3	5.5	6.2	6.3
United Kingdom	71.2	71.5	71.5	5.6	5.4	5.7
Source: Eurostat.
93 Social overview 2009
Statistical appendix
Table 12: Temporary employees as percentage of total number of employees for age group 15-64, according to Labour Force Survey, EU-27, 2000-2008, in %
	Total			By gender	
				Men	Women
	2000	2007	2008	2008	2008
EU-27	12.2	14.5	14.0	13.2	14.9
Austria	8.0	8.9	9.0	8.9	9.1
Belgium	9.0	8.6	8.3	6.6	10.2
Bulgaria	N/A	5.1	4.9	5.5	4.3
Cyprus	10.7	13.3	14.0	8.2	20.0
Czech Republic	7.2	7.8	7.2	5.7	9.1
Denmark	12.8	14.6	14.7	14.8	14.7
Estonia	2.3	2.2	2.4	3.5	N/A
Finland	17.7	15.9	14.9	11.1	18.7
France	15.4	14.4	14.1	12.9	15.4
Greece	13.8	10.9	11.5	9.9	13.7
Ireland	5.3	7.2	8.4	7.1	9.8
Italy	10.1	13.2	13.3	11.5	15.7
Latvia	6.7	4.2	3.3	4.6	1.9
Lithuania	3.8	3.5	2.4	2.9	1.9
Luxembourg	3.4	6.8	6.2	5.9	6.6
Hungary	6.8	7.3	7.8	8.6	7.0
Malta	3.9	5.1	4.2	3.3	5.8
Germany	10.2	8.6	8.3	7.5	9.1
Netherland	13.8	17.9	17.9	16.2	19.8
Poland	5.6	28.2	26.9	26.2	27.6
Portugal	19.8	22.4	22.9	21.7	24.2
Romania	2.9	1.6	1.3	1.3	1.1
Slovakia	4.0	5.0	4.5	4.4	4.7
Slovenia	12.8	18.4	17.3	15.2	19.6
Spain	32.4	31.7	29.3	27.7	31.4
Sweden	14.3	17.2	15.8	13.2	18.5
United Kingdom	6.6	5.7	5.3	4.7	5.9
Source: Eurostat.
94	Social overview 2009
Statistical appendix
Table 13: Persons1 entitled to financial social assistance2 by region, 2001-2009, in %
		Share of population entitled to financial social assistance in region, %								Eligible persons per 1,000 inhabitants	
										Index (SI=100)	Growth index
	2001	2002	2003	2004	2005	2006	2007	2008 (June)	2009 (June)	2009 (June)	08-09
Slovenia	2.1	3.5	4.4	4.7	4.7	4.2	3.2	2.8	3.3	100.0	117.8
Osrednjeslovenska	1.0	1.6	2.2	2.5	2.6	2.3	1.7	1.5	1.7	51.8	115.4
Obalno-kraška	1.3	2.1	2.7	3.0	3.0	2.9	2.3	2.0	2.4	72.3	119.0
Gorenjska	1.3	2.0	2.4	2.6	2.6	2.0	1.5	1.2	1.6	49.8	131.0
Goriška	0.5	1.1	1.5	1.9	1.9	1.5	1.2	1.0	1.3	39.7	131.0
Savinjska	3.2	5.2	6.2	6.6	6.5	5.8	4.5	3.8	4.5	136.6	115.8
Jugovzhodna Slovenia	1.8	3.3	4.0	4.4	4.6	4.3	3.5	3.2	4.0	121.4	124.0
Pomurska	4.5	8.0	8.8	9.1	8.8	7.8	6.4	5.7	6.2	189.7	107.7
Notranjsko-kraška	1.3	1.9	2.9	2.8	2.7	2.2	1.8	1.6	2.1	64.4	133.3
Podravska	3.4	5.7	6.9	7.4	7.6	7.0	5.3	4.5	5.2	160.7	115.4
Koroška	2.2	3.4	4.4	4.9	4.6	4.2	3.0	2.4	3.5	106.2	142.4
Spodnjeposavska	2.9	5.3	6.5	6.5	6.1	5.6	4.3	3.5	4.1	124.5	114.5
Zasavska	3.0	5.5	6.4	6.5	6.5	5.7	4.3	3.5	4.6	139.7	128.3
Source: MDDSZ; calculations by IMAD.
Notes: 1 Persons entitled to financial social assistance are persons who received financial 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 influence. 2Financial social assistance is a cash benefit 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 financial social assistance, extraordinary cash social assistance and permanent cash social assistance as well as the persons entitled to attendance allowance (home care).
HOUSEHOLD INCOME AND EXPENDITURE
Table 14: Personal income tax base per capita by region, indices (Slovenia=100), 2000-2007
	2000	2001	2002	2003	2004	2005	2006	2007
Slovenia	100.0	100.0	100.0	100.0	100.0	100.0	100.0	100.0
Osrednjeslovenska	123.5	122.3	122.3	119.1	121.7	121.9	121.5	122.0
Obalno-kraška	110.9	111.5	111.4	111.3	109.1	107.1	107.2	104.3
Gorenjska	101.5	102.2	101.8	103.2	101.7	102.4	101.8	103.0
Goriška	110.1	110.4	108.8	109.3	108.2	104.4	103.6	101.0
Savinjska	89.6	90.2	86.8	91.2	90.7	90.8	90.8	90.7
Jugovzhodna Slovenia	90.8	94.2	95.0	96.0	95.8	95.6	95.9	95.9
Pomurska	75.2	74.0	80.3	74.6	74.4	74.2	75.5	74.2
Notranjsko-kraška	101.5	99.8	100.6	101.1	99.7	98.1	99.6	97.1
Podravska	84.6	84.5	85.5	86.9	86.4	86.7	86.8	87.9
Koroška	86.1	86.4	85.5	86.9	86.0	89.1	88.8	90.2
Spodnjeposavska	85.8	86.0	85.6	85.9	85.4	85.7	86.6	85.8
Zasavska	94.6	92.7	91.5	91.9	89.2	91.3	90.5	89.3
Source: DURS; calculations by IMAD.
95 Social overview 2009
Statistical appendix
Table 15: Structure of household consumption1 according to COICOP,2 EU-27, 2008
	Skupaj	013	024	035	046	057	068	079	0810	0911	1012	1113	1214
EU-27	100	13	3.4	5.4	22.3	6.0	3.5	13.4	2.7	9.2	1.1	8.7	11.4
Austria15	100	10.5	3.1	6.1	20.8	6.9	3.3	12.8	2.6	11.6	0.8	11.3	10.1
Belgium	100	12.8	3.5	5.0	23.9	5.7	5.8	12.0	2.6	9.4	0.5	5.8	13.2
Cyprus	100	15.9	6.1	5.9	13.1	5.2	3.8	15.9	1.9	7.9	3.0	11.2	10.2
Czech Republic	100	16.3	7.6	4.2	21.8	5.1	2.8	11.5	3.5	10.7	0.7	6.8	9.0
Denmark	100	11.2	3.3	4.6	27.4	5.5	2.6	12.8	2.0	11.1	0.7	6.1	12.7
Estonia	100	19.6	7.3	5.2	21.2	4.6	3.2	16.0	2.9	7.8	0.8	6.2	8.5
Finland	100	12.9	4.8	4.9	24.7	5.5	4.4	11.8	2.4	11.6	0.4	6.4	10.0
France	100	13.4	2.9	4.4	25.2	5.9	3.6	14.5	2.7	8.9	0.8	6.2	11.5
Greece	100	16.5	4.3	6.7	16.2	5.5	6.4	10.4	1.1	7.6	3.2	13.2	8.9
Ireland	100	9.6	5.1	4.5	22.4	6.0	3.8	12.3	3.2	7.0	1.2	13.1	11.8
Italy	100	14.7	2.6	7.6	21.2	7.5	3.1	12.9	2.6	6.8	0.9	10.0	10.2
Latvia15	100	18.1	6.6	8.9	21.7	4.4	4.2	12.5	4.0	8.1	2.0	4.7	4.8
Lithuania	100	22.9	6.0	5.9	12.3	5.9	4.2	18.7	2.5	8.1	0.9	3.7	8.9
Luxembourg	100	8.5	8.5	3.5	22.4	7.2	1.8	19.2	1.7	8.1	0.5	7.0	11.6
Hungary	100	17.5	9.9	3.3	19.3	5.5	3.4	15.5	3.9	7.4	1.1	5.1	8.0
Malta	100	18.0	2.9	4.3	11.9	7.9	2.3	12.9	4.8	11.7	1.2	13.1	8.8
Germany	100	11.4	3.2	5.3	24.3	6.8	4.7	13.8	2.8	9.4	0.9	5.7	11.7
Netherland15	100	11.0	2.8	5.6	22.6	6.5	2.5	11.9	4.5	10.6	0.5	5.4	16.2
Romania15	100	27.9	3.6	3.7	22.5	5.5	3.5	16.1	2.1	4.9	1.7	5.1	3.4
Slovakia	100	17.7	4.8	4.4	24.4	6.7	3.6	7.6	3.6	9.6	1.4	6.6	9.7
Slovenia	100	14.4	4.9	5.7	18.5	5.7	3.5	16.2	3.1	9.7	1.3	7.2	9.8
Spain	100	14.0	2.8	5.4	17.7	5.0	3.5	11.5	2.7	8.6	1.3	17.7	9.6
Sweden	100	12.7	3.6	5.1	26.6	5.1	3.2	12.8	3.1	11.1	0.3	6.0	10.3
United Kingdom	100	8.9	3.4	5.3	21.1	5.2	1.6	15.4	2.1	11.6	1.4	10.7	13.2
Source: Eurostat.
Notes: 1According to the national accounts methodology. 2COICOP is a classification of individual (final) consumption (of households) by purpose. 3(01) Food and non-alcoholic beverages. 4(02) Alcoholic beverages, tobacco and narcotics. 5(03) Clothing and footwear. 6(04) Housing, water, energy. 7(05) Furnishings, household equipment and routine household maintenance. 8(06) Health. 9(07) Transport. 10(08) Communications. 11(09) Recreation and culture. 12(10) Education. 13(11) Hotels and restaurants. 14(12) Miscellaneous products and services. 15Data from 2007; data for Bulgaria, Poland and Portugal are not available.
96 Social overview 2009
Statistical appendix
ACCESS TO HEALTHCARE
Table 16: Expenditure on health care, EU-27, 2000 and 2007
	Total expenditure on health as share of GDP,4 %		Public expenditure on health, as share of GDP,3 %		Private expenditure, share of total expenditure, %		Health expenditure per capita, in USD PPS
	2000	2007	2000	2007	2000	2007	2007
EU-27	7.3	8.2	5.3	5.9	27.5	27.6	2,432
Austria	9.9	10.1	7.5	7.7	24.1	23.6	3,606
Belgium	8.6	10.2	6.5	7.3	24	24.0	3,462
Bulgaria1	6.2	7.2	3.7	4.1	40.6	43	744
Cyprus1	5.7	6.2	2.4	2.8	58.4	55.2	2,754
Czech Republic	6.5	6.8	5.9	5.8	9.7	14.8	1,509
Denmark	8.3	9.8	6.8	8.2	17.6	15.5	3,362
Estonia1	5.3	5.2	4.1	3.8	22.5	26.7	958
Finland	7.0	8.2	5.1	6.1	24.9	25.4	2,668
France	10.1	11.0	8.0	8.7	21.7	21.0	3,449
Greece	7.8	9.6	4.7	5.8	55.8	39.7	2,483
Ireland	6.3	7.6	4.6	6.1	27.1	19.3	3,082
Italy	8.1	8.7	5.8	6.7	27.5	23.5	2,614
Latvia1	5.9	6.6	3.2	3.9	46.1	40.8	1,018
Lithuania1	6.5	6.2	4.5	4.3	30.3	30.0	981
Luxembourg1	5.8	7.3	5.2	6.6	10.7	9.1	4,303
Hungary	6.9	7.4	4.9	5.2	29.3	29.4	1,504
Malta1	7.5	8.4	5.6	6.5	25.8	23.0	4,223
Germany	10.3	10.4	8.2	8.0	20.3	23.1	3,371
Netherland1	8.0	9.8	5.0	5.0	36.9	36.9	N/A
Poland	5.5	6.4	3.9	4.6	30	30.0	910
Portugal1	8.8	9.9	6.4	7.1	27.5	29.1	2,120
Romania1	5.1	4.5	3.4	3.5	32.7	23.1	472
Slovakia	5.5	7.7	4.9	5.2	10.6	33.2	1,308
Slovenia2	8.3	7.8	6.1	5.6	26	28.4	2,056
Spain	7.2	9.1	5.2	7.4	28.4	18.3	3,202
Sweden	8.2	10.8	7.0	6.4	15.1	40.7	4,311
United Kingdom	7.2	8.4	5.8	6.9	19.1	18.3	2,760
Source: OECD Health Data 2009 for all countries except Belgium (OECD Health Data 2008) and Bulgaria, Cyprus, Estonia, Latvia, Lithuania, Malta and Romania; source for these countries WHO World Health Report 2009; source for Slovenia for 2007 Health expenditure (SORS), 26 October 2009, and for 2000 SORS calculation according to the OECD methodology, based on data from state and local government budgets, HIIS, PDII and SORS; EU-27 averages calculated by IMAD, except for the average for expenditure in USD PPS. Notes: 12006; 2taking account of the GDP revision in September 2009; N/A - not available.
97 Social overview 2009
Statistical appendix
Table 17: Number of (acute)1 hospital beds and number of inhabitants per acute hospital bed, by region, 2000-2008
	Number of (acute)1 hospital beds					Number of persons per acute hospital bed				
	2000	2005	2006	2007	2008	2000	2005	2006	2007	2008
Slovenia	8,868	7,754	7,701	7,608	7,748	224	258	261	265	263
Osrednjeslovenska	3,031	2,687	2,695	2,620	2,605	162	185	186	193	197
Obalno-kraška	632	536	534	534	540	164	196	199	200	202
Gorenjska	614	660	608	584	587	320	301	328	343	345
Goriška	446	459	459	456	456	269	260	261	263	265
Savinjska	986	848	835	842	834	260	304	310	309	316
Jugovzhodna Slovenia	454	336	338	343	342	304	415	415	411	418
Pomurska	480	279	279	279	434	260	439	438	437	281
Notranjsko-kraška	54	54	54	54	54	936	947	952	960	972
Podravska	1,542	1,353	1,356	1,356	1,356	207	236	236	237	237
Koroška	344	308	308	308	308	215	240	239	239	240
Spodnjeposavska	127	127	126	126	126	550	551	556	557	563
Zasavska	158	107	109	106	106	293	425	416	265	263
Source: Training Institutions Report (No. 3-21-60), IVZ.
Notes: 1 Acute hospital bed (based on WHO definitions) is a regularly maintained and cared for hospital bed for the accommodation and 24-hour 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 departments, and beds belonging to specific medical devices.
Table 18: Physicians at primary level by region, 2003-2008
Physicians in primary health care network1
	Number			Number per 1,000 inhabitants			Index (SI=100)			Growth index
	2003	2007	2008	2003	2007	2008	2003	2007	2008	07-08
Slovenia	1,533	1,532	1,535	0.77	0.76	0.75	100.0	0.76	0.75	0.76
Osrednjeslovenska	464	448	462	0.94	0.88	0.90	122.3	0.88	0.90	0.88
Obalno-kraška	90	92	90	0.86	0.86	0.82	111.6	0.86	0.82	0.86
Gorenjska	146	148	144	0.74	0.74	0.71	96.1	0.74	0.71	0.74
Goriška	105	102	104	0.88	0.85	0.86	114.2	0.85	0.86	0.85
Savinjska	185	184	180	0.72	0.71	0.68	93.6	0.71	0.68	0.71
Jugovzhodna Slovenia	102	100	105	0.73	0.71	0.73	95.7	0.71	0.73	0.71
Pomurska	94	84	85	0.76	0.69	0.70	99.3	0.69	0.70	0.69
Notranjsko-kraška	36	37	35	0.71	0.71	0.67	92.2	0.71	0.67	0.71
Podravska	177	200	196	0.55	0.62	0.61	72.2	0.62	0.61	0.62
Koroška	43	46	44	0.58	0.63	0.60	75.8	0.63	0.60	0.63
Spodnjeposavska	50	53	54	0.71	0.75	0.76	92.7	0.75	0.76	0.75
Zasavska	41	38	36	0.89	0.84	0.79	116.4	0.84	0.79	0.84
Source: Training Institutions Report (No. 3-21-60), IVZ, calculations by IMAD. Note: 1Health care centres and private providers.
98 Social overview 2009
Statistical appendix
Table 19: Hospitalisations1 due to diseases by main causes for admission, by age and gender, Slovenia, 2008
	Number of hospitalisations per 1,000 persons			
By diagnosis ICD- 102	Total	By age		
		0-19 years	20-64 years	65+
Total				
Total diseases	135.7	111.5	99.2	309.6
Neoplasms	18.1	2.0	14.5	52.0
Circulatory diseases	19.9	1.8	11.3	75.8
Respiratory diseases	13.0	25.3	5.4	28.7
Digestive system diseases	14.5	9.7	11.9	30.6
Musculoskeletal diseases	9.7	3.3	8.3	23.2
Men				
Total diseases	125.7	114.4	83.9	364.1
Neoplasms	17.9	1.9	12.5	71.7
Circulatory diseases	21.3	2.0	13.5	92.7
Respiratory diseases	15.1	28.4	6.5	39.0
Digestive system diseases	15.8	9.9	13.4	37.8
Musculoskeletal diseases	8.5	3.1	8.1	18.7
Women				
Total diseases	145.6	108.5	115.7	274.8
Neoplasms	18.4	2.2	16.6	39.4
Circulatory diseases	18.6	1.5	9.0	65.0
Respiratory diseases	11.0	22.1	4.2	22.1
Digestive system diseases	13.2	9.5	10.2	26.1
Musculoskeletal diseases	11.0	3.5	8.4	26.1
Source: IVZ.
Notes: hospitalisation 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. international statistical classification of diseases and related health problems, 10th revision -
ICD-10 is a system of categories or groups classifying diseases according to a scheme that complies with the epidemiological objectives and evaluation of health care. ICD is published by the WHO.
99 Social overview 2009
Statistical appendix
Table 20: Diagnostic related groups (DRG),1 cases of acute care2 per 1,000 inhabitants and average weight3 by age groups, Slovenia, 2005-2008_
	Total population				Men				Women			
	Total	0-19	20-64	65+	Total	0-19	20-64	65+	Total	0-19	20-64	65+
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 1,000 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
2006												
Number of DRG	338,149	55,209	171,672	111,268	142,574	29,935	64,102	48,537	195,575	25,274	107,570	62,731
Cases of acute care per 1,000 inhabitants	168.20	137.80	133.07	348.11	144.45	145.25	97.47	393.86	191.10	129.90	170.09	319.41
Average DRG weight	1.37	1.01	1.18	1.84	1.57	1.02	1.54	1.93	1.23	0.99	0.97	1.76
2007												
Number of DRG	328,527	50,384	169,138	109,005	139,532	27,245	64,071	48,216	188,985	23,139	105,063	60,783
Cases of acute care per 1,000 inhabitants	162.17	127.35	129.77	333.50	139.44	133.74	95.63	379.90	184.33	120.55	165.88	304.02
Average DRG weight	1.38	0.94	1.19	1.87	1.58	0.94	1.54	1.97	1.24	0.94	0.98	1.79
2008												
Number of DRG	351,481	53,712	182,211	115,558	149,250	29,104	68,256	51,890	202,221	24,608	113,949	63,664
Cases of acute care per 1,000 inhabitants	172.94	136.63	139.60	345.95	148.66	143.91	101.72	396.98	196.63	128.91	179.67	313.13
Average DRG weight	1.38	0.94	1.2	1.89	1.57	0.96	1.53	1.97	1.25	0.92	1	1.82
Source: IVZ.
Notes: 1Diagnostic related cases (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 that serves as a basis for the payment of hospital services.
100 Social overview 2009
Statistical appendix
ACCESS TO SOCIAL SERVICES
Table 21: People in old people's homes1 and structure by reason for admission, in %, Slovenia, 2000-2008
	2000	2001	2002	2003	20042	20052	20062	2007	2008
Number of people in care	11,905	12,346	13,051	13,498	13,098	13,641	13,699	13,856	15,235
Structure of by reason for admission, %:									
Age	59.0	57.2	58.6	59.5	66.0	64.3	66.8	67.5	70.6
Unsettled housing conditions	5.2	4.7	4.7	4.5	4.7	4.1	3.7	3.2	2.7
Unsettled family conditions	4.6	4.9	4.4	4.4	4.2	3.7	3.2	2.6	2.6
Serious illnesses	26.3	27.4	26.7	26.6	20.5	22.2	22.0	22.4	21.1
Other	4.9	5.8	5.7	4.9	4.6	5.6	4.3	4.3	3.0
Source: SORS; calculations by IMAD.
Notes: Includes public old people's homes only. 2In 2004, 2005 and 2006, SORS included people in care in eight units of old people's homes providing special forms of care for adults with mental and physical disabilities 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 classification in 2004 brought about a decrease in the number of people in care in old people's homes compared with 2003.
Table 22: People in old people's homes by mode of payment for care, 2000-2008, in %
Mode of payment for care	2000	2001	2002	2003	2004	2005	2006	2007	2008
People in care	36.0	36.2	35.2	36.1	36.9	34.3	35.7	35.6	35.0
Relatives	6.5	6.5	6.7	7.1	9.9	10.9	11.4	10.8	10.4
People in care, relatives	24.3	26.3	28.2	29.5	29.8	31.7	31.0	32.7	33.7
People in care, municipality	22.9	22.8	23.0	21.5	18.3	17.1	16.8	15.9	15.5
Relatives, municipality	1.0	0.8	1.0	0.4	0.4	0.7	0.5	0.5	0.7
People in care, relatives, municipality	2.3	2.1	1.8	2.1	2.4	2.4	2.1	2.4	2.7
Municipality	7.1	5.2	4.0	3.3	2.3	2.9	2.5	2.2	2.1
Source: SORS; calculations by IMAD.
101 Social overview 2009
Statistical appendix
HOUSING
Table 23: Share of households with own housing1 by available assets,2 Slovenia, 2000-2007, in %
	2000	2001	2002	2003	2004	2005	2006	2007
Total households	92.7	93.2	93.3	93.4	93.2	93.1	93.2	92.4
Households with income of less than 60% compared to median actual current income	89.5	90.7	89.3	88.6	88.4	88.9	89.7	87.8
Households with income of 60-100% of median actual current income	91.0	91.1	91.3	92.0	91.7	91.8	91.3	90.7
Households with income of 100-140% of median actual current income	94.0	94.7	95.3	95.2	94.9	93.5	94.1	93.2
Households with income higher than 140% of median actual current income	96.0	96.3	97.0	97.5	97.4	97.7	97.4	97.2
Source: SORS, Household Budget Survey.
Notes: 1Housing owners/co-owners, users of a housing unit belonging to parents or other relatives. 2The available assets also include income in kind (benefits in kind and the value of own production spent in the household).
Table 24: Average number of rooms per equivalent1 household member by tenure status, Slovenia, 2000-2007
	2000	2001	2002	2003	2004	2005	2006	2007
Total	1.5	1.5	1.5	1.5	1.6	1.6	1.6	1.6
Owners2	1.6	1.5	1.5	1.6	1.6	1.7	1.7	1.6
Tenants	1.1	1.1	1.1	1.1	1.1	1.1	1.1	1.0
Source: SORS, Household Budget Survey.
Notes: 1The number of equivalent members is calculated using the OECD modified-equivalence scale: the first 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. 2Housing owners/co-owners, users of a housing unit belonging to parents or other relatives.
102 Social overview 2009
Statistical appendix
ACCESS TO CHILDCARE AND EDUCATION
Table 25: Share of children attending kindergartens, by age, Slovenia, 2000/2001-2008/2009, in %
	2000/2001	2001/2002	2002/2003	2003/2004	2004/2005	2005/2006	2006/2007	2007/2008	2008/2009
1-2 years	29.2	29.8	32.7	36.8	37.4	38.5	40.8	43.7	49.2
3-5 years	67.9	70.3	72.0	76.2	75.5	77.6	79.5	82.1	84.1
Source: SORS; calculations by IMAD.
Table 26: Number and structure of young people enrolled in upper secondary education, by type of education programme, Slovenia, 2000/2001-2008/2009_
	Number	Growth of the number of enrolled pupils, in %		Structure of enrolled pupils by type of education programme, in %		
	2008/2009	2007-2008	2000-2008	2000/2001	2007/2008	2008/2009
Total	87,501	-4.5	-16.5	100.0	100.0	100.0
2-year lower vocational programmes	1,124	-14.8	-67.3	3.3	1.4	1.3
3-year middle vocational programmes	13,123	-8.7	-48.8	24.4	15.7	15
4- and 5-year technical and other professional programmes	30,929	-1.2	-8	32.1	34.2	35.3
Grammar schools	35,126	-3.6	3.6	32.4	39.8	40.1
3+2 model and differential programmes, +2 and vocational technical programmes	5,693	-13.3	-26.7	7.4	7.2	6.5
Vocational course	372	-1.1	291.6	0.1	0.4	0.4
Matura preparatory course	1,134	-9.8	200	0.4	1.4	1.3
Source: SORS; calculations by IMAD.
Table 27: Participation rate of population in tertiary education,1 Slovenia, 2000/2001-2008/2009, in %
	2000/2001	2001/2002	2002/2003	2003/2004	2004/2005	2005/2006	2006/2007	2007/2008	2008/2009
Full-time students2 as share of population aged 19-23	39.9	42.6	44.2	46.8	50.8	53.1	56.2	57.3	59.7
Tertiary education students as share of population aged 20-29	30.9	33.1	33.8	34.9	37.9	38.9	39.8	39.9	40.0
Source: SORS; calculations by IMAD.
Notes: 'Tertiary education includes post-secondary vocational studies, higher undergraduate studies and postgraduate studies. 2Full-time students together with full-time graduation candidates and postgraduate students in full-time programmes.
103 Social overview 2009
Statistical appendix
Table 28: Ratio between number of students in tertiary education and number of population aged 20-29,1 participation rate of young people aged 20-24 in tertiary education and share of total public expenditure on education allocated for financial assistance to students and transfers,2 EU-27, 2000-2006 (2007), in %
	Ratio between number of students in tertiary education and number of population aged 20-29,1 %			Enrolment of young people aged 20-24 in tertiary education, in %			Share of total public expenditure on education, allocated for financial assistance transfers,2 in %
	2000	2006	2007	2000	2006	2007	2006
EU-27	23.7	28.4	28.6	24.0	28.2	28.4	16.6
Austria	25.4	24.1	24.6	20.1	22.3	23.8	17.0
Belgium	26.9	30.1	29.8	29.5	31.2	31.2	13.6
Bulgaria	22.0	22.0	23.7	24.8	27.1	29.1	9.5
Cyprus	10.5	16.1	16.9	10.5	16.9	17.3	55.1
Czech Republic	14.8	21.9	23.9	17.5	28.6	30.4	4.0
Denmark	26.4	36.8	37.3	23.7	28.2	28.5	29.5
Estonia	28.3	34.2	34.0	27.2	30.7	31.0	8.9
Finland	42.7	46.5	46.7	38.0	40.1	39.9	16.2
France	24.8	27.3	26.8	29.2	29.0	28.8	8.0
Greece	25.1	41.9	39.8	22.4	39.2	37.5	N/A
Ireland	26.5	25.4	25.4	20.9	23.0	23.4	14.4
Italy	22.2	29.4	30.1	24.8	30.2	31.1	16.6
Latvia	28.0	38.5	37.4	23.3	32.5	32.3	7.7
Lithuania	25.3	40.6	40.1	26.2	38.4	39.6	15.2
Luxembourg	4.3	4.5	N/A	N/A	5.7	N/A	N/A
Hungary	19.2	29.8	30.2	20.5	30.6	31.0	15.1
Malta	11.3	15.0	16.4	13.1	18.3	16.2	N/A
Germany	21.3	23.5	23.3	18.4	22.7	22.6	19.5
Netherland	23.1	29.6	30.1	27.1	30.7	31.5	29.5
Poland	26.7	33.5	33.6	29.0	39.5	40.5	1.7
Portugal	23.5	24.6	25.3	24.9	25.8	25.8	11.6
Romania	12.9	24.6	27.4	14.5	25.8	27.7	N/A
Slovakia	15.1	21.6	24.1	16.8	25.3	27.5	14.1
Slovenia	28.3	39.5	40.1	32.2	45.1	46.1	23.3
Spain	27.7	27.3	27.5	30.7	29.2	28.7	7.9
Sweden	31.2	39.1	37.6	26.9	30.1	28.8	26.1
United Kingdom	26.8	29.4	29.0	19.3	19.7	19.6	26.4
Source: Eurostat.
Notes: Calculation of the indicator: number of full-time and part-time students in all levels of tertiary education/number of the population aged 20-29 years*100. 2Total public expenditure on tertiary education includes funds paid directly to educational institutions and public transfers, payments to households and other private entities. Public transfers for households and other private entities comprise: financial assistance to students (scholarships, child benefits in the part where an additional condition for payment is participation in education, student loans) and transfers and payments to other private entities (subsidies to transport operators for cheaper tickets, subsidies for textbooks, professional literature, etc.). N/A - not available.
104 Social overview 2009
Statistical appendix
Table 29: Participation rate of population aged 25-64 in lifelong learning,1 Slovenia, 2003-2008, in %
	20032	2004	2005	2006	2007	2008
Total	13.3	16.2	15.3	15.0	14.8	13.9
By gender						
Men	12.0	14.8	13.6	13.8	13.5	12.5
Women	14.7	17.6	17.2	16.3	16.1	15.4
By age:						
25-39	22.7	27.8	24.4	23.9	23.2	22.5
40-54	8.9	13.5	11.1	11.3	11.5	10.1
55-64	3.7	7.2	5.8	5.4	5.3	5.4
65-74	1.6	2.9	3.0	3.5	3.0	3.2
Sources: SORS, Eurostat, ADS.
Notes: ]The value of this indicator represents the percentage of the population aged 25-64 years who were involved in any kind of education or training in the four weeks before the survey. 2In 2003, the methodology for calculating the indicator was changed.
Table 30: Participation of adults aged 25-64 in formal and non-formal education, by socio-economic characteristics, Slovenia, 2007, in %_
	Formal or non-formal	Formal	Non-formal
Total	40.6	8.7	36.1
By sex:			
Men	38.1	7.7	34.5
Women	43.1	9.7	37.9
By age:			
25-34 years	52.1	22.3	40
35-49 years	45	6.9	42
50-64 years	27.1	0.8	26.8
By educational attainment:			
Primary of less	12.7	2.1	10.9
Upper secondary	39	8.9	33.7
Tertiary	67.6	13.6	63.3
By labour status:			
Employed	47.7	9.1	43.6
Unemployed	27.5	8.7	22.1
Inactive	21.5	7.2	16.5
By occupation:			
Total	47.5	9	43.4
SCO 1-3	65.6	13	61
SCO 4-5	47.4	10.5	41.2
SCO 6-7	31.9	3.2	30
SCO 8-9	25.6	4.1	23.2
By degree of urbanisation:			
Densely-populated area (min. 500 inhabitants/km2)	44.1	10.6	38.2
Intermediate area (between 100 and 499 inhabitants/km2)	40	8.5	35.7
Sparsely populated area (below 100 inhabitants/km2)	39.5	8.1	35.6
Source: SORS, Eurostat, Adult Education Survey.
105 Social overview 2009
Statistical appendix
Table 31: Number and structure of young people who compyearsed upper secondary education, Slovenia, 2000/2001-2007/2008
	Number	Growth of the number, in %		Structure of young people who compyearsed upper secondary education, by educational programme, in %		
	2007/2008	2007-2008	2000-2008	2000/2001	2006/2007	2007/2008
Total	21,762	-6.1	-13	100.0	100.0	100.0
2-year lower vocational programmes	418	-22.2	-59.6	4.1	2.3	1.9
3-year middle vocational programmes	4,173	-7.6	-39.4	27.5	19.5	19.2
2+3 model and differential programmes (vocational technical programmes	2,052	-9.4	-27.4	11.3	9.8	9.4
4- and 5-year technical and other professional programmes	6,325	-3.9	-20.5	31.8	28.4	29.1
Grammar schools	8,367	-5.3	35.5	24.7	38.1	38.4
Vocational course	129	-3.7	760	0.1	0.6	0.6
Matura preparatory course	298	-5.4	181.1	0.4	1.4	1.4
Source: SORS; calculations by IMAD. Table 32: Number and structure of graduates from tertiary education, Slovenia, 2000-2008						
	Number	Growth of the number, in %		Structure of graduates by type of programme, in %		
	2008	2007-2008	2000-2008	2000	2007	2008
Total	17,221	3.2	149.8	100	100	100
Short-term higher	3,435	19.5	181.8	16.4	17.2	19.9
Professional higher (Bologna and former)	5,416	-3.5	149.6	31.5	33.7	31.4
Academic higher (Bologna and former)	6,320	0.6	128	42.9	37.6	36.7
Master (Bologna and former) and specialisation (former)	1,645	10	218.2	6.6	9	9.6
Doctorate (Bologna and former)	405	-2.4	136.8	2.6	2.5	2.4
Source: SORS; calculations by IMAD.
106 Social overview 2009
Statistical appendix
Table 33: Graduates from tertiary education,1 EU-27, 2000-2007
	Number of graduates from tertiary education per 1,000 population, aged 20-29				Number of female graduates per 100 male graduates from tertiary education			
	2000	2005	2006	2007	2000	2005	2006	2007
EU-27	N/A	N/A	N/A	N/A	130.8	142.5	144.5	144.4
Belgium	51.4	61.4	62.5	79.0	126.6	140.4	142.6	138.8
Bulgaria	38.1	40.9	40.8	44.7	181.2	143.2	150.5	149.6
Czech Republic	22.4	37.0	44.4	50.9	124.7	130.0	132.1	133.0
Denmark	54.0	77.9	76.1	82.0	128.9	143.6	138.0	134.6
Germany	31.0	35.7	37.0	38.6	101.4	112.7	130.2	130.7
Estonia	34.0	60.0	58.0	62.8	192.5	235.4	249.2	221.5
Ireland	70.4	86.9	82.5	79.2	122.6	125.5	127.5	130.3
Greece	N/A	37.1	40.8	39.3	N/A	159.6	N/A	146.9
Spain	39.5	43.8	43.4	43.0	134.3	138.1	140.0	140.3
France	64.3	N/A	80.3	76.9	126.1	126.9	124.6	122.6
Italy	24.8	55.2	60.8	37.8	126.6	139.9	145.2	141.5
Cyprus	28.6	30.9	30.6	34.2	187.0	156.3	159.8	143.6
Latvia	46.7	78.2	78.2	78.0	173.3	239.4	240.5	255.7
Lithuania	51.8	86.7	89.5	87.3	167.7	197.7	195.2	200.0
Luxembourg	12.1	N/A	N/A	N/A	N/A	N/A	N/A	N/A
Hungary	37.5	48.1	46.7	46.3	123.6	181.4	188.5	198.3
Malta	36.9	45.3	45.3	45.8	108.4	154.0	138.1	134.5
Netherland	36.1	54.4	60.0	49.1	118.1	129.7	126.8	129.8
Austria	24.1	31.9	33.3	34.6	90.3	106.8	106.9	110.3
Poland	58.1	78.7	78.5	83.2	184.7	193.4	190.3	187.2
Portugal	30.5	45.1	47.5	56.6	190.8	187.5	189.2	159.2
Romania	18.0	45.8	51.5	60.8	110.5	133.3	145.2	148.4
Slovenia	39.0	53.6	58.6	57.7	133.4	161.5	162.5	161.6
Slovakia	25.4	39.4	43.7	50.9	121.8	133.0	146.9	161.4
Finland	56.3	60.0	60.2	63.8	161.1	164.8	167.3	171.4
Sweden	38.0	53.9	56.7	55.3	140.1	172.7	175.3	175.3
United Kingdom	66.4	83.5	82.7	80.9	121.8	138.4	138.6	138.7
Source: Eurostat.
Notes: 1 ISCED 5,6 according to the international classification of education ISCED 97. N/A - not available.
107 Social overview 2009
Statistical appendix
Table 34: Structure of population aged 15 or over by educational attainment, Slovenia, 2000-2008, in %
	2000	2001	2002	2003	2004	2005	2006	2007	2008
Total (in thousand)	1,672	1,680	1,690	1,700	1,707	1,714	1,724	1,734	1,751
Structure of population aged 25 or over by educational attainment, %:									
Without education, incomplete primary education (1-3 years)	1.2	0.8	0.6	0.6	0.6	0.8	0.9	1.0	1.0
Incomplete primary education (4-7 years)	4.9	4.7	4.5	4.9	4.7	4.4	3.8	3.4	3.4
Primary education	27.0	26.8	25.8	24.8	23.9	23.7	23.0	22.6	22.1
Lower or middle vocational education	25.2	25.5	25.5	25.8	25.4	25.0	24.9	25.1	24.8
Secondary technical education	22.9	23.9	24.6	24.2	24.7	24.8	24.7	24.9	24.9
Secondary general education	6.6	5.9	6.0	6.3	6.0	5.8	6.0	6.0	6.3
Post-secondary education (not higher education)	5.6	5.2	5.1	5.0	5.1	5.2	5.5	5.2	5.4
Higher education, professionally oriented	1.7	1.7	1.6	1.7	2.1	2.4	2.8	3.0	3.2
Higher education, academic type	4.3	4.8	5.4	5.9	6.5	6.9	7.1	7.5	7.6
Post-graduate education (specialisation, master's and doctor's degree)	0.7	0.7	0.6	0.8	0.9	1.1	1.2	1.3	1.2
Source: SORS; calculations by IMAD.
Table 35: Total public expenditure on formal education1 as share of GDP2 by level of education,3 Slovenia, 2000-2007, in %
Public expenditure on formal education1 as share of GDP, %
	2000	2001	2002	2003	2004	2005	2006	2007
Total	5.78	5.89	5.78	5.82	5.76	5.67	5.67	5.19
Pre-school education 4	0.46	0.57	0.57	0.54	0.48	0.59	0.62	0.56
Primary education5	2.51	2.42	2.51	2.57	2.64	2.45	2.39	2.26
Secondary education6	1.54	1.62	1.42	1.41	1.34	1.38	1.42	1.16
Tertiary education	1.27	1.28	1.27	1.30	1.31	1.25	1.23	1.21
Source: SORS.
Notes: 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; 2shares of GDP are calculated according to the released data on GDP. 3The criterion for distribution by level of education is expenditure at the level of the educational institution. Expenditure for pre-school education covers the estimated share of expenditure related to the implementation of the programme for the second age period of children in kindergartens. 5Until 2004, expenditure for primary education included part of expenditure for pre-school education (units of kindergartens in elementary schools). From 2005 onwards, this expenditure is added to expenditure for pre-school education. Expenditure for upper secondary education includes part of expenditure for tertiary education (departments/units of higher education in upper secondary schools).
108 Social overview 2009
Statistical appendix
Table 36: Education structure of population aged 25-64 years, 2000 in 2008, EU-27, in %
Education structure of population aged 25-64 years, %
	Lower education1	Secondary education2	Tertiary education3	Lower education	Secondary education	Tertiary education
	2000	2000	2000	2008	2008	2008
Austria	23.8	61.9	14.2	19.0	63.0	18.1
Belgium	41.7	31.2	27.1	30.4	37.3	32.3
Bulgaria	32.9	48.7	18.4	22.5	54.8	22.8
Cyprus	38.5	36.4	25.1	26.9	38.6	34.5
Czech Republic	13.9	74.5	11.5	9.1	76.4	14.5
Denmark	19.8	52.8	25.2	21.9	42.2	33.7
Estonia	15.3	55.8	28.9	11.5	54.2	34.3
EU-27	34.6	43.5	18.9	28.4	47.1	24.2
Finland	26.6	40.2	32.3	18.9	44.5	36.6
France	37.7	40.6	21.6	30.2	42.4	27.4
Greece	48.6	34.5	16.9	38.9	38.4	22.6
Ireland	41.8	34.9	21.2	29.5	34.3	32.7
Italy	53.3	34.6	9.4	46.7	39.0	14.4
Latvia	16.9	65.1	18.0	14.2	60.6	25.2
Lithuania	15.8	42.4	41.8	9.4	60.1	30.4
Luxembourg	38.3	41.7	17.9	32.1	40.3	27.7
Hungary	30.7	55.3	14.0	20.3	60.5	19.2
Malta	81.8	12.8	5.4	72.5	14.4	13.1
Germany	17.7	54.2	22.5	14.6	59.8	25.3
Netherland	33.8	41.9	24.0	26.5	40.8	31.9
Poland	20.3	68.3	11.4	12.9	67.6	19.6
Portugal	80.4	10.6	9.0	71.8	13.9	14.3
Romania	30.7	60.1	9.2	24.7	62.5	12.8
Slovakia	16.4	73.3	10.2	10.1	75.2	14.8
Slovenia	25.2	59.1	15.7	18.0	59.4	22.6
Spain	61.7	15.8	22.5	49.0	21.7	29.2
Sweden	22.7	47.3	29.5	14.9	52.7	31.8
United Kingdom	31.3	31.0	24.4	26.4	41.1	31.8
Source: Eurostat; calculations by IMAD.
Notes: 'ISCED1,2, 2ISCED 3,4, 3ISCED 5,6 according to the international classification of education ISCED 97.
109 Social overview 2009
Statistical appendix
Table 37: Public expenditure on formal education (all levels) as share of GDP, total and by level of education, EU-27, 2000-2006, in %_
Public expenditure on formal education as share of GDP, %
				By level of education			
		Total		Pre-school1 education	Lower2 education	Secondary3 education	Tertiary4 education
	2000	2005	2006	2006	2006	2006	2006
EU-27	4.88	5.04	5.05	0.51	1.18	2.24	1.13
Austria	5.74	5.46	5.44	0.4	1.01	2.55	1.48
Belgium	N/A	5.95	6	0.71	1.41	2.55	1.32
Bulgaria	3.97	4.51	4.24	0.77	0.84	1.9	0.73
Cyprus	5.35	6.92	7.02	0.34	1.95	3.08	1.65
Czech Republic	3.97	4.26	4.61	0.54	0.62	2.22	1.23
Denmark	8.29	8.3	7.98	0.87	1.89	2.95	2.27
Estonia	6.1	4.92	4.8	0.36	1.19	2.33	0.92
Finland	5.89	6.32	6.14	0.34	1.27	2.59	1.94
France	6.03	5.65	5.58	0.63	1.12	2.63	1.19
Greece	3.39	4	N/A	N/A	N/A	N/A	N/A
Ireland	4.28	4.75	4.86	0	1.61	2.11	1.14
Italy	4.55	4.43	4.73	0.5	1.19	2.24	0.8
Latvia	5.64	5.06	5.07	0.66	1.29	2.21	0.91
Lithuania	5.9	4.9	4.84	0.59	0.73	2.52	1
Luxembourg	N/A	3.78	3.41	N/A	1.83	1.58	N/A
Hungary	4.42	5.46	5.41	1	1.06	2.33	1.04
Malta	4.49	6.76	N/A	N/A	N/A	N/A	N/A
Germany	4.46	4.53	4.41	0.47	0.65	2.18	1.11
Netherland	4.96	5.48	5.46	0.41	1.37	2.18	1.5
Poland	4.89	5.47	5.25	0.53	1.71	2.05	0.96
Portugal	5.42	5.39	5.25	0.54	1.58	2.12	1
Romania	2.86	3.48	N/A	N/A	N/A	N/A	N/A
Slovakia	3.93	3.85	3.79	0.47	0.67	1.76	0.9
Slovenia	5.78	5.67	5.67	0.62	2.39	1.42	1.23
Spain	4.28	4.23	4.28	0.55	1.1	1.68	0.95
Sweden	7.21	6.97	6.85	0.6	1.71	2.68	1.84
United Kingdom	4.46	5.37	5.48	0.39	1.61	2.37	1.1
Source: Eurostat.
Notes: 1Pre-school education includes (according to the Slovenian education system): education in kindergartens for children of the second age period; 2lower education includes (according to the Slovenian education system) education at the lower level (grades 1-4) of 8-year primary schools or the first and second cycles of 9-year primary schools. For Slovenia, expenditure on primary education is included within the primary education; 3secondary education includes (according to the Slovenian education system): education at the higher level (grades 5-8) of 8-year primary schools or the 3rd cycle of 9-year primary schools and total secondary school education (lower, middle vocational, professional, general). For Slovenia, expenditure on secondary school education is included within secondary education. 4Tertiary education includes (according to the Slovenian education system): post-secondary vocational and higher undergraduate and postgraduate education. N/A - not available.
110 Social overview 2009
Statistical appendix
CULTURE
Table 38: Number of exhibitions and visitors in museums, galleries and exhibition grounds, Slovenia, 2004-2008
	2004	2005	2006	2007	2008
Number of exhibitions	2,429	1,809	1,898	1,819	2,119
Number of visitors per exhibition	1,011.5	1,262.8	1,238.0	1,375.0	1,158.5
Number of visitors per 1,000 inhabitants1	1,230.3	1,141.5	1,169.8	1,238.6	1,203.7
Source: SORS, calculations by IMAD.
Note: According to the size of the population as of 30 June.
Table 39: Number of theatrical performances and visitors in theatres, Slovenia, 2004-2008
	2004	2005	2006	2007	2008
All performances at theatre headquarters	6,124	5,226	4,264	3,864	4,160
Number of visitors per 1,000 inhabitants1	360	464.2	419.2	407.1	425.1
Average number of visitors per performance	117.5	177.7	197.5	212.8	208.5
Source: SORS, calculations by IMAD.
Note: According to the size of the population as of 30 June.
Table 40: Attendance in cinemas and structure of viewers by film origin, Slovenia, 2000-2008
	2000	2004	2005	2006	2007	2008
Attendance	2,221,437	3,003,516	2,443,776	2,685,234	2,406,568	2,417,994
Attendance per 1,000 inhabitants1	1,116.1	1,504.0	1,221.2	1,336.9	1,191.7	1,185.6
Attendance at long films in cinemas by origin, in %:						
Total	100.0	100.0	100.0	100.0	100.0	100.0
Slovenian	6.1	3.4	3.0	0.9	5.6	4.3
Foreign	93.9	96.6	97	99.1	94.4	95.7
Source: Fivia, d. o. o., and Slovenian Film Fund; calculations by IMAD. Note: According to the size of the population as of 30 June.
Table 41: Titles of published books and brochures, by origin, Slovenia, 2000-2008
	Number of titles of books and brochures	Growth of the number of titles of books and brochures, in %		Structure of titles of books and brochures, in %		
	2008	2007-2008	2000-2008	2000	2007	2008
Total	6,358	24.0	62.3	100.0	100.0	100.0
Original works	4,481	23.4	50.1	76.2	70.8	70.5
Translations	1,877	25.3	101.4	23.8	29.2	29.5
Source: SORS, Institute of Information Science (IZUM), National and University Library; calculations by IMAD.
111 Social overview 2009
Statistical appendix
Table 42: Attendance, loans per registered user, total and in public libraries, 2000-2007
	2000	2001	2002	2003	2004	2005	2006	2007
Libraries, total								
Attendance per registered user	14.3	14.4	15	14.5	15.2	15.3	15.6	17.2
Loans per registered user	28.4	31	27.8	27.3	28.9	28.9	31.6	27.6
Public libraries								
Attendance per registered user	15.1	16.1	16.8	16.8	16.7	17.3	17.1	18.2
Loans per registered user	39.3	45	37.8	37	38.4	40.6	46.2	48.8
Source: SORS, NUK; calculations by IMAD.
Note: 1 Including the National and University Library (NUK), university libraries, special libraries, public and school libraries. Data for school libraries for 2005, 2006 and 2007 cover pupils, professional staff and other persons.
MEDIA
Table 43: Time dedicated to media and news on actual or political events on a regular day in the week, in hours, 2002-2008
Time dedicated to media	2002			2004			2006			2008		
	Newspaper	TV	Radio	Newspaper	TV	Radio	Newspaper	TV	Radio	Newspaper	TV	Radio
- No time at all	18.8	4.6	11.8	15.6	3.7	11.1	19.7	4.8	12.5	19.0	3.4	13.4
- Less than 0.5 hour	40.9	11.1	17.0	43.1	10.5	16.4	43.0	11.0	18.1	46.3	9.2	17.5
- 0.5-1 hour	27.5	23.5	20.3	29.3	25.0	17.3	25.6	24.0	17.2	23.8	22.8	16.7
- 1-1.5 hours	6.6	15.4	8.2	6.6	14.9	7.2	6.6	14.8	7.6	6.1	17.3	7.6
- 1.5-2 hours	3.1	17.7	6.3	3.2	17.5	6.3	2.3	15.4	7.0	2.6	17.2	7.8
- 2-2.5 hours	1.7	10.5	6.1	1.0	11.0	6.2	1.6	11.9	5.1	0.6	11.5	5.0
- 2.5-3 hours	0.4	6.8	4.9	0.2	7.8	4.9	0.7	7.9	3.7	0.6	7.9	4.0
- More than 3 hours	0.5	10.3	25.5	0.7	9.2	30.4	0.4	9.8	28.7	0.7	10.7	27.8
- Don't know	0.6	0.1	0.1	0.3	0.3	0.2	0.0	0.0	0.1	0.1	0.1	0.1
- No answer	N/A	N/A	N/A	N/A	N/A	N/A	0.1	0.5	0.1	0.1	N/A	0.1
												
Of which for following current or political topics	Newspaper	TV	Radio	Newspaper	TV	Radio	Newspaper	TV	Radio	Newspaper	TV	Radio
- No time at all	32.0	8.5	23.1	29.7	9.0	23.0	32.7	11.7	25.3	22.2	6.6	16.4
- Less than 0.5 hour	53.2	36.1	41.7	56.1	37.0	42.0	52.6	35.6	40.3	62.0	34.7	45.8
- 0.5-1 hour	11.1	40.2	21.7	11.1	38.7	21.6	10.5	35.0	20.3	12.9	41.3	23.3
- 1-1.5 hours	2.2	8.8	6.3	2.0	9.6	6.5	1.7	10.5	4.4	1.5	9.7	5.8
- 1.5-2 hours	0.7	3.3	2.7	0.6	3.7	1.9	1.4	3.6	2.9	0.3	3.9	2.9
- 2-2.5 hours	0.3	1.2	1.7	0.3	0.8	2.2	0.1	1.6	1.5	0.1	1.7	1.4
- 2.5-3 hours	0.1	0.9	0.9	0.1	0.6	0.7	0.0	0.6	1.0	0.5	0.8	1.3
- More than 3 hours	0.1	0.8	1.9	0.2	0.5	2.1	0.3	1.1	3.3	0.1	1.1	3.0
- Don't know	0.4	0.1	0.1	0.0	0.1	0.1	0.5	0.2	0.8	0.3	0.2	0.2
- No answer	N/A	N/A	N/A	N/A	N/A	N/A	0.3	0.1	0.2	0.2	N/A	N/A
Source: FDV- Inštitut za družbene vede, CJMMK: SJM 2006/2 in 2008/2, ESS, 2006 in 2009.
Notes: Circulation increased significantly, as a free, widely circulated daily newspaper entered the market in the second quarter of 2008. N/A - not available.
112 Social overview 2009
Statistical appendix
INTERNET
Table 44: Internet users1 by type of settlement, Slovenia, 2004-2009, in %
	2004	2005	2006	2007	2008	2009
Densely populated settlements (more than 500 inhabitants/km2)	52	56	68	60	64	72
Intermediate settlements (100-499 inhabitants/km2)	39	46	49	58	56	60
Sparsely populated settlements (less than 100 inhabitants/km2)	30	44	45	47	53	59
Source: SORS.
Note: 1Internet users are individuals who have used the Internet in the last three months.
Table 45: Share of households with Internet access and Internet users, Slovenia and EU-27, 2004-2009, in %
	Share of households with Internet access, %							Regular Internet users,1			%	
	2004	2005	2006	2007	2008	2009	2004	2005	2006	2007	2008	2009
EU-27	40	48	49	54	60	65	45	51	52	57	62	65
Belgium	-	50	54	60	64	67	-	58	62	67	69	75
Bulgaria	10	-	17	19	25	30	16	-	24	31	35	42
Czech Republic	19	19	29	35	46	54	32	32	44	49	58	60
Denmark	69	75	79	78	82	83	76	77	83	81	84	86
Germany	60	62	67	71	75	79	61	65	69	72	75	77
Estonia	31	39	46	53	58	63	50	59	61	64	66	71
Ireland	40	47	50	57	63	67	34	37	51	57	63	65
Greece	17	22	23	25	31	38	20	22	29	33	38	42
Spain	34	36	39	45	51	54	40	44	48	52	57	60
France	34	-	41	49	62	63	-	-	47	64	68	69
Italy	34	39	40	43	47	53	31	34	36	38	42	46
Cyprus	53	32	37	39	43	53	32	31	34	38	39	48
Latvia	15	31	42	51	53	58	33	42	50	55	61	64
Lithuania	12	16	35	44	51	60	29	34	42	49	53	58
Luxembourg	59	65	70	75	80	87	65	69	71	78	81	86
Hungary	14	22	32	38	48	55	28	37	45	52	59	59
Malta	-	41	53	54	59	64	-	38	38	45	49	58
Netherland	-	78	80	83	86	90	69	79	81	84	87	89
Austria	45	47	52	60	69	70	52	55	61	67	71	72
Poland	26	30	36	41	48	59	29	35	40	44	49	56
Portugal	26	31	35	40	46	48	29	32	36	40	42	46
Romania	6	-	14	22	30	38	12	-	21	24	29	33
Slovenia	47	48	54	58	59	64	37	47	51	53	56	62
Slovakia	23	23	27	46	58	62	46	50	50	56	66	70
Finland	51	54	65	69	72	78	70	73	77	79	83	82
Sweden	-	73	77	79	84	86	82	81	86	80	88	90
United Kingdom	56	60	63	67	71	77	63	66	66	72	76	82
Source: Eurostat.
Notes: Data refer to the first quarter of the year. Internet users in the last three months.
113 Social overview 2009
Statistical appendix
SOCIAL COHESION
Table 46: Subjective feelings of happiness, 2000-2008, in %
	2000	2001	2002	2003	2004	2005	2006	2007	2008
Not happy (0-3)	5.3	5.1	5.7	5.5	4.1	4.1	4.9	4.3	4.2
Medium (4-6)	36.6	35.6	31.3	35.9	28.2	28.8	34.1	26.9	25.1
Happy (7-10)	57.2	58.7	62.3	57.6	67.0	66.0	59.7	67.1	70.2
Source: Faculty of Social Sciences (FDV) - CJMMK, Slovenian Public Opinion (SJM 2000-2008).
Note: The question reads: Please use a 0-10 scale to assess your feelings as to your personal happiness in general, with 0 meaning that you are not happy at all and 10 that you are very happy. Difference from 100% is made up of answers "Don't know" or "No answer".
Table 47: Satisfaction with life, 2002, 2004, 2006 and 2008, in %
	2002	2004	2006	2008
Not satisfied (0-3)	10.4	6.3	6.8	6.9
Medium (4-6)	46.7	47.3	44.7	45.3
Satisfied (7-10)	41.6	46.2	45.3	46.8
Source: Faculty of Social Sciences (FDV) - CJMMK, European Social Survey (ESS).
Note: The question reads: All things considered, how satisfied are you with your life, with 0 meaning that you are very unsatisfied and 10 that you are very satisfied. Difference from 100% is made up of answers "Don't know" or "No answer".
Table 48: Trust in other people, 2002, 2004, 2006 and 2008, in %
	2002	2004	2006	2008
Does not trust (0-3)	43.3	41.5	42.6	36.8
Medium (4-6)	38.6	38.2	36.4	41.6
Trusts (7-10)	17.6	20.1	20.9	21
Source: Faculty of Social Sciences (FDV) - CJMMK, European Social Survey (ESS).
Note: The question reads: Generally speaking, can the majority of people be trusted or does one have to be cautious in one's contacts with other people? Choose the appropriate value on a 0-10 scale where 0 means that one has to be cautious in one's contacts with other people and 10 that the majority of people can be trusted. Difference from 100% is made up of answers "Don't know" or "No answer".
Table 49: Trust in institutions, Slovenia, 2002, 2004, 2006 and 2008, in %
National Assembly					Legal system				
	ESS02	ESS04	ESS06	ESS08		ESS02	ESS04	ESS06	ESS08
Does not trust (0-4)	40.3	39.8	35.8	45.2	Does not trust (0-4)	38.5	46.0	39.5	48.8
Medium (5-6)	39.8	39.1	42.5	32.2	Medium (5-6)	35.3	33.9	36.7	28.8
Trusts (7-10)	15.9	17.3	16.8	19.3	Trusts (7-10)	21.9	15.6	18.4	19
Police					Politicians				
	ESS02	ESS04	ESS06	ESS08		ESS02	ESS04	ESS06	ESS08
Does not trust (0-4)	30.9	32.7	29.7	37.8	Does not trust (0-4)	57.0	57.4	56.0	62.1
Medium (5-6)	37.8	38.3	37.9	30.6	Medium (5-6)	34.3	33.5	32.9	28.5
Trusts (7-10)	29.1	26.2	29.8	30.1	Trusts (7-10)	6.1	6.2	8.1	7.3
Source: Faculty of Social Sciences (FDV) - CJMMK, European Social Survey (ESS).
Note: Assess on a 0-10 scale how much you personally trust each of the following institutions, 0 indicating that you do not trust it at all and 10 that you trust it compyearsely.
114 Social overview 2009
Statistical appendix
Table 50: Subjective perceptions of crime in Slovenia; feeling of safety and personal experience of crime, Slovenia, 2002, 2004, 2006 and 2008, in %_
Feeling of safety 1					Personal experience of crime2				
	ESS02	ESS04	ESS06	ESS08		ESS02	ESS04	ESS06	ESS08
Very safe	29.0	28.3	27.0	26.4	Yes	11.5	11.8	13.5	11.4
Safe	60.5	61.0	61.3	60.9	No	88.5	87.9	86.2	88.6
Unsafe	8.9	8.5	9.2	10.7					
Very unsafe	0.9	1.0	1.0	1.1					
Source: Faculty of Social Sciences (FDV) - CJMMK, ESS 2002-2008.
Notes: 'How safe do you feel walking alone in your neighbourhood in the evening? (ESS 2002-2008); 2Have you yourself or any member of your household been a victim of burglary/ assault in the last five years? (ESS2002-2008).
Table 51: Number of suicides per 100,000 inhabitants, EU-27, 2000-2007
	2000	2001	2002	2003	2004	2005	2006	2007
EU-27	11.8	11.5	12.1	11.4	11.2	10.8	10.3	N/A
Austria	17.5	16.3	17.0	15.8	15.2	14.7	13.4	13.2
Bulgaria	15.0	13.9	14.3	11.9	11.0	10.7	10.5	9.5
Belgium	N/A	N/A	N/A	N/A	17.5	N/A	N/A	N/A
Cyprus	N/A	N/A	N/A	N/A	0.7	2.5	2.4	2.2
Czech Republic	14.8	14.5	13.7	15.3	14.0	13.8	12.2	11.9
Denmark	12.3	12.2	11.5	10.6	11.2	10.2	10.6	N/A
Estonia	26.2	28.1	26.0	23.7	22.7	18.7	16.2	16.8
Finland	21.5	22.0	19.9	19.4	19.3	17.6	19.0	17.6
France	16.8	16.1	16.4	16.6	16.3	15.9	15.4	14.7
Greece	3.2	2.7	2.6	3.1	2.8	3.1	3.1	2.6
Ireland	12.1	12.6	11.2	11.2	11.3	9.5	9.1	N/A
Italy	6.1	5.9	6.0	5.9	N/A	N/A	5.2	N/A
Latvia	30.8	28.6	27.3	24.1	22.3	22.6	19.3	17.8
Lithuania	45.4	43.7	44.0	41.1	38.9	37.0	28.9	28.4
Luxembourg	13.6	16.0	18.4	10.3	13.2	9.9	13.2	N/A
Hungary	29.5	26.6	25.4	24.8	24.3	23.2	21.8	21.4
Malta	5.8	7.1	4.6	4.7	5.4	4.2	6.0	6.0
Germany	11.7	11.7	11.5	11.5	11.0	10.4	9.8	9.4
Netherland	8.8	8.6	9.1	8.6	8.7	9.0	8.7	7.7
Poland	14.8	14.7	14.9	14.7	15.1	15.0	14.3	12.9
Portugal	4.3	6.3	10.1	9.4	9.6	7.2	6.8	N/A
Romania	12.7	12.1	13.6	12.8	11.6	11.4	11.9	10.5
Slovakia	13.5	12.7	13.0	13.7	12.0	12.0	9.4	8.8
Slovenia	27.1	26.5	24.5	25.0	22.7	22.0	22.8	18.4
Spain	7.2	6.7	7.0	7.1	7.0	6.6	6.2	6.1
Sweden	11.6	12.2	12.2	11.4	11.8	12.4	12.0	11.4
United Kingdom	6.8	6.7	6.7	6.4	6.7	6.4	6.5	6.1
Source: Eurostat.
Notes: N/A - not available. Eurostat's calculations are made using standardised mortality rates, which enable comparisons over time and between countries.
115 Social overview 2009
Statistical appendix
Table 52: Number of deaths in road traffic accidents per 100,000 inhabitants, EU-27, 2000-2007
	2000	2001	2002	2003	2004	2005	2006	2007
EU-27	11.9 p	11.6 p	11.7 p	10.7 p	10.1 p	9.7 11	9.1 p	N/A
Austria	11.0	10.9	11.0	10.9	9.8	8.9	8.2	7.9
Bulgaria	11.7	12.3	11.6	11.6	11.8	10.8	13.0	12.9
Belgium	N/A	N/A	N/A	N/A	11.1	N/A	N/A	N/A
Cyprus	N/A	N/A	N/A	N/A	15.9	29.5	10.8	12.8
Czech Republic	14.3	13.5	13.6	13.3	11.9	11.6	9.9	11.2
Denmark	9.2	8.4	8.4	8.1	6.9	6.4	5.8	N/A
Estonia	17.8	17.1	18.0	13.6	14.3	14.6	17.0	14.6
Finland	9.0	9.8	9.5	9.0	8.5	8.5	7.7	8.2
France	12.6	12.5	11.9	9.8	8.6	8.5	7.5	7.3
Greece	19.0	16.8	15.5	14.9	16.4	15.1	14.8	14.4
Ireland	10.6	10.1	9.3	7.5	7.7	6.5	6.5	N/A
Italy	12.1	12.3	11.9	10.9	N/A	N/A	9.7	N/A
Latvia	28.6	26.0	25.2	22.7	21.6	20.0	18.2	19.7
Lithuania	20.9	24.0	23.1	23.8	24.0	24.8	25.3	24.5
Luxembourg	18.4	17.1	18.5	12.5	11.3	10.3	8.4	N/A
Hungary	14.1	14.1	16.1	14.7	14.9	14.3	14.8	14.1
Malta	4.1	4.6	4.0	3.5	3.8	4.5	2.5	3.6
Germany	9.3	8.4	8.3	8.0	7.0	6.5	6.1	5.9
Netherland	6.9	6.2	6.3	6.5	5.1	4.6	4.5	4.6
Poland	17.8	15.7	16.1	15.5	15.8	14.5	13.5	14.7
Portugal	13.0	17.4	19.9	17.5	15.5	12.4	9.6	N/A
Romania	16.2	16.3	15.4	14.3	15.6	15.4	15.1	15.7
Slovakia	15.4	15.0	13.9	15.3	13.6	13.6	14.3	14.2
Slovenia	15.5	14.9	13.7	13.2	14.1	13.0	13.7	14.8
Spain	14.8	13.7	13.1	13.0	11.3	10.4	9.5	8.7
Sweden	6.5	6.8	6.0	5.9	5.4	5.1	5.3	5.0
United Kingdom	5.6	5.8	5.9	6.0	5.7	5.5	5.5	5.3
Source: Eurostat.
Notes: p) provisional data, N/A - not available.
116 Social overview 2009
Statistical appendix
Table 53: Number of prisoners 2000-2007, and number of prisoners per 100,000 inhabitants, EU-27, 2005-20072
	Number of prisoners								Prisoners/100,000 inhabitants2
	2000	2001	2002	2003	2004	2005	2006	2007	2005-20072
EU-27	N/A	N/A	N/A	N/A	N/A	N/A	N/A	N/A	123
Austria	6,896	6,915	7,511	7,816	9,000	8,955	8,780	8,887	107
Bulgaria	9,424	9,283	9,607	10,056	10,935	11,399	11,452	10,792	145
Belgium	8,688	8,544	8,605	9,308	9,249	9,330	9,573	9,950	91
Cyprus	287	369	351	355	546	536	599	671	79
Czech Republic	22,418	20,971	16,597	17,180	18,303	19,003	18,904	19,110	185
Denmark	3,382	3,236	3,435	3,641	3,767	4,041	3,932	3,646	71
Estonia	4,679	4,803	4,775	4,352	4,575	4,410	4,310	3,486	302
Finland	2,887	3,110	3,469	3,463	3,535	3,883	3,477	3,370	68
France	48,835	47,005	53,463	55,407	59,246	59,197	59,522	60,403	95
Greece	8,038	8,343	8,284	8,555	8,760	9,871	10,280	N/A	91
Ireland	2,887	3,025	3,028	2986	3,138	3,022	3,053	N/A	75
Italy	54,039	55,751	55,670	54,237	56,068	59,523	39,005	48,693	84
Latvia	8,831	8,673	8,358	8,222	7,666	6,998	6,636	6,548	293
Lithuania	8,667	10,750	11,345	8,957	7,838	7,951	7,982	7,770	232
Luxembourg	400	341	391	455	577	735	738	666	152
Hungary	15,539	17,275	17,838	16,507	16,543	15,720	14,740	14,743	149
Malta	246	257	283	278	277	294	376	382	87
Germany	70,252	70,203	75,025	79,183	79,329	79,519	77,166	73,319	93
Netherland	11,760	12,410	13,060	13,980	16,455	17,600	16,230	14,450	99
Poland	65,336	80,004	80,990	80,692	79,344	82,656	87,669	90,199	228
Portugal	12,728	13,210	13,772	13,635	12,956	12,687	12,446	11,587	116
Romania	48,267	49,840	48,075	42,815	39,031	36,700	34,038	29,390	154
Slovakia	7,136	7,509	7,849	8,829	9,504	9,282	8,657	8,235	162
Slovenia	1,136	1,155	1,120	1,099	1,126	1,132	1,127	1,336	60
Spain	45,309	46,594	50,537	54,497	58,087	60,707	64,215	67,100	146
Sweden	5,678	6,089	6,506	6,755	7,332	7,021	7,153	6,740	77
England and Wales1	65,666	67,056	71,324	72,992	75,057	76,896	79,085	79,730	146
Scotland1	5,883	61,86	6,475	6,621	6,779	6,857	7,183	7,376	139
Northern Ireland1	1,011	872	1,029	1,128	1,219	1,325	1,501	1,484	82
Source: Eurostat; Eurostat News Release: EU Crime Statistics 2005-2007, No. 91/2009, 19 June 2009.
Notes: N/A - not available; 1Figures for the United Kingdom are reported separately (as England & Wales, Scotland and Northern Ireland) owing to the existence of three separate jurisdictions. 2Average of years 2005-2007, except for Ireland (2004-2006) and Greece (2005-2006).
117 Social overview 2009
Statistical appendix
Table 54: Number of police officers per 100,000 inhabitants, selected European countries, 2003
Fewer than 200	200-299	300-399	400-499	500 and over
Denmark	Estonia	Albania	Croatia	Cyprus
Finland	Hungary	Austria	Czech Republic	Georgia
Sweden	Iceland	Belgium	Greece	Russia (2000)
	Netherland	France	Italy	
	Poland	Ireland	Portugal	
	Romania	Lithuania	Northern Ireland	
	Switzerland	Slovakia		
	England and Wales	Slovenia		
	Luxembourg	Scotland		
Source: Council of Europe: European Sourcebook of Crime and Criminal Justice Statistics, 2006.
Table 55: Number of crimes1 per 100,000 inhabitants, EU-27, 2000-2003
	2000	2001	2002	2003
EU-27	N/A	N/A	N/A	N/A
Austria	6,906	6,428	7,260	7,881
Bulgaria	1,773	1,796	1,780	1,729
Belgium	9,747	9,481	9,886	9,784
Cyprus	575	592	622	944
Czech Republic	3,812	3,494	3,630	3,490
Denmark	9,447	8,837	9,145	9,013
Estonia	4,189	4,270	3,918	3,968
Finland	10,259	9,964	10,017	10,343
France	6,352	6,808	6,865	6,605
Greece	3,496	4,153	4,409	4,158
Ireland	1,933	2,259	2,743	2,634
Italy	3,822	3,741	3,852	4,236
Latvia	N/A	N/A	N/A	N/A
Lithuania	2,254	2,174	1,999	2,352
Luxembourg	5,200	5,092	5,778	5,728
Hungary	4,446	4,607	4,173	4,110
Malta	4,364	4,065	4,326	4,489
Germany	7,622	7,734	7902	7,976
Netherland	8,207	8,476	8,825	8,530
Poland	3,278	3,597	3,635	3,799
Portugal	3,515	3,583	3,753	3,983
Romania	1,576	1,518	1,393	1,237
Slovakia	1,645	1,722	1,985	2,067
Slovenia	3,363	3,719	3,839	3,810
Spain	2,307	2,534	2,582	2,377
Sweden	13,615	13,304	13,790	13,995
England and Wales	9,917	10,552	11,220	11,241
Scotland	9,912	9,879	10,032	9,639
Northern Ireland	7,125	8,275	8,399	7,515
Source: Council of Europe: European Sourcebook of Crime and Criminal Justice Statistics, 2006.
Notes: ,Criminal complaints. Crimes are serious offences against the penal code. Less serious criminal acts (misdemeanours) are excluded.
118 Social overview 2009
Statistical appendix
Table 56: Number of homicides per 100,000 inhabitants, EU-27, 2000-2007
	2000	2001	2002	2003	2005-2007 average
EU-27	N/A	N/A	N/A	N/A	1.40
Austria	2.3	1.9	2.1	1.8	0.64
Bulgaria	6.5	6.2	5.5	5.3	2.37
Belgium	6.5	7.2	7.7	8.4	2.04
Cyprus	1.5	2.0	1.0	3.5	1.66
Czech Republic	2.7	2.3	2.3	2.3	1.99
Denmark	4.0	3.7	3.9	4.1	1.17
Estonia	13.7	12.0	11.4	12.4	7.301
Finland	9.8	10.7	10.2	9.2	2.23
France	3.9	4.2	4.3	3.9	1.46
Greece	2.7	2.6	2.2	2.3	-13
Ireland	1.4	1.4	1.4	1.3	1.451
Italy	3.9	3.8	3.9	3.9	1.13
Latvia	N/A	N/A	N/A	N/A	N/A
Lithuania	10.9	10.4	8.6	10.3	9.69
Luxembourg	13.9	11.2	13.5	12.9	1.42
Hungary	3.5	4.0	3.6	3.8	1.57
Malta	2.1	3.1	4.3	3.3	0.66
Germany	3.8	3.5	3.5	3.4	0.90
Netherland	10.9	11.0	11.2	11.4	1.06
Poland	3.7	3.7	3.4	3.0	1.37
Portugal	N/A	N/A	N/A	N/A	1.47
Romania	5.7	6.1	5.4	5.1	2.02
Slovakia	2.6	2.4	2.4	2.7	1.76
Slovenia	4.0	3.2	3.9	2.9	0.93
Spain	3.0	3.1	3.2	3.2	1.12
Sweden	N/A	N/A	N/A	N/A	1.05
England and Wales	3.0	3.3	3.5	3.3	1.43
Scotland	13.7	15.6	17.8	16.2	2.17
Northern Ireland	10.2	12.8	16.5	9	1.59
Source: For 2000-2003, Council of Europe: European Sourcebook of Crime and Criminal Justice Statistics, 2006. For 2005-2007, Eurostat. Note: ]Data for 2004-2006.
119 Social overview 2009
Statistical appendix
POVERTY
Table 57: Risk of poverty rates after and before social transfers (excluding income in kind), EU-27, 2000-2008, in %
	At-risk-of-poverty rate after social transfers									At-risk-of-poverty rate before social transfers (pensions included in income)								
	2000	2001	2002	2003	2004	2005	2006	2007	2008	2000	2001	2002	2003	2004	2005	2006	2007	2008
EU-27	N/A	N/A	N/A	N/A	N/A	'6	'6	'7	'7	N/A	N/A	N/A	N/A	N/A	26	26	26	25
EU-25	"16	'6	N/A	'5	'6	'6	'6	'6	'6	23	24	N/A	25	26	26	26	26	25
Austria	"12	'2	N/A	'3'	'3	'2	'3	'2	'2	22	22	N/A	25'	25	24	25	25	24
Belgium	■13	H	N/A	'5'	'4	'5	'5	'5	'5	23	23	N/A	29'	28	28	27	28	27
Bulgaria	M	'6	M	'4	'5	'4	'8	22'	2'	'8	'9	'7	N/A	'8	'7	25	26'	27
Cyprus	N/A	N/A	N/A	'5	N/A	'6	'6	'6	'6	N/A	N/A	N/A	20	N/A	22	22	2'	22
Czech Republic	N/A	8	N/A	N/A	N/A		'0	'0	9	N/A	'8	N/A	N/A	N/A	2''	22	20	20
Denmark	N/A		N/A	!2'	H	'2	'2	'2	'2	N/A	29	N/A	32'	30	30	28	27	28
Estonia	-18	'8	'8	'8	20'	'8	'8	'9	'9	26	25	25	25	26'	24	25	25	25
Finland	H		H	H	H'	'2	'3	'3	'4	'9	29	28	28	29	28	29	29	28
France	•16	'3'	'2	'2	'3'	'3	'3	'3	'3	24	26	26	24	26	26	25	26	23'
Greece	20	20	N/A	2''	20	20	2'	20	20	22	23	N/A	24'	23	23	23	24	23
Ireland	20	2'	N/A	20'	2'	20	'8	'8	'6	3'	30	N/A	3''	33	32	33	33	34
Italy	'8	'9	N/A	N/A	'9'	'9	20	20	'9	2'	22	N/A	N/A	24'	23	24	24	23
Latvia	'6	N/A	N/A	N/A	N/A	'9'	23	2'	26	22	N/A	N/A	N/A	N/A	26'	28	27	30
Lithuania	'7	'7	N/A	N/A	N/A	2' '	20	'9	20	23	24	N/A	N/A	N/A	26'	27	26	27
Luxembourg	'2	'2	N/A	'2	'3	'4	'4	'4	'3	23	23	N/A	23	22	24	24	23	24
Hungary	H	H	'0	'2	N/A	'3'	'6	'2	'2	'7	'7	'5	'7	N/A	29	30	29	30
Malta	'5	N/A	N/A	N/A	N/A	'4	'4	'4	'5	'9	N/A	N/A	N/A	N/A	2'	2'	22	23
Germany	'0	H	N/A	N/A	N/A	'2'	'3	'5	'5	20	2'	N/A	N/A	N/A	233	26	25	24
Netherland	H	H	H	'2	N/A		'0	'0	H	22	22	22	23	N/A	22'	2'	2'	20
Poland	'6	'6	N/A	N/A	N/A	2''	'9	'7	'7	30	3'	N/A	N/A	N/A	30'	29	27	25
Portugal	2'	20	20	'9	20'	'9	'8	'8	'8	27	24	26	26	27'	26	25	24	25
Romania	'7	'7	'8	'7	'8	'8	'9	25	23	2'	22	23	22	23	24	24	3''	3'
Slovakia	N/A	N/A	N/A	N/A	N/A	'3'	'2	H	H	N/A	N/A	N/A	N/A	N/A	22'	20	'8	'8
Slovenia	H	H	'0	'0	N/A	!2'	'2	'2	'2	'8	'7	'6	'6	N/A	26'	24	23	23
Spain	'8	'9	'9'	'9	20'	20	20	20	20	22	23	22	22	25'	24	24	24	24
Sweden	N/A	9	H'	N/A	H'	9	'2	H	'2	N/A	'7	29	N/A	30'	29	29	28	29
United Kingdom	'9	'8	'8	'8	N/A	'9'	'9	'9	'9	29	28	28	29	N/A	3''	30	30	29
Source: Eurostat, EU-SILC.
Notes: 'Break in series. N/A - not available. Data for Slovenia for 2000, 2001, 2002 and 2003 also include income in kind. Data on income from EU-SILC refer to the year before the survey. For most countries, figures for 2004 and 2005 are thus provided with a note "Break in series'" or, "Not available" and moved one year forward. The same also holds true for Slovenia. On 30 December 2008 onwards, SORS harmonised the way of publishing data by years with Eurostat, which means that the year of the EU-SILC survey is also the reference year for data release.
120 Social overview 2009
Statistical appendix
Table 58: Gini coefficient1 (%), income quintile share ratio (80/20),2 Slovenia, 2000-2008
	2000	2001	2002	2003	2004(bs)	2005	2006	2007	2008
Gini coefficient, %	22.3	22.0	21.9	22.1	22.4	23.0	23.0	22.6	22.9
Income quintile share ratio (80/20)	3.2	3.1	3.1	3.1	3.2	3.3	3.3	3.2	3.3
Source: SORS: Household Budget Survey; data from 2005 onwards are taken from the Statistics on Income and Living Conditions (EUSILC) and are not totally comparable with the previous period due to methodological changes.
Notes: (bs) Break in series. The Gini coefficient and the income quintile share ratio (80/20) are calculated for income including income in kind. 1The Gini coefficient 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 and the average equivalent household income of the lowest quintile.
Table 59: At risk of poverty rate1 by gender and age, Slovenia, 2000-2008, in %
	2000	2001	2002	2003	2004(bs)	2005	2006	2007	2008
Total	11.3	10.6	9.9	10.0	10.4	11.4	11.1	11.0	11.9
Men	10.5	9.6	8.5	8.6	8.9	9.6	9.5	9.4	10.4
Women	12.0	11.6	11.2	11.4	11.8	13.2	12.6	12.4	13.2
Children (aged 0-15)	9.3	8.7	7.4	8.8	7.9	11.0	11.1	11.0	11.1
Youth (aged 16-24)	10.3	10.3	10.0	10.6	10.0	10.0	8.9	8.7	10.0
Men	10.7	10.4	10.2	9.8	9.6	9.0	8.3	8.0	9.2
Women	9.9	10.3	9.9	11.6	10.4	11.0	9.6	9.4	10.8
Employed (aged 16-64)	9.8	9.2	8.5	8.5	8.7	9.9	9.3	9.3	10.1
Men	10.1	9.2	8.7	8.3	8.9	9.5	9.2	9.2	10.4
Women	9.5	9.2	8.4	8.7	8.5	10.3	9.3	9.4	9.8
65+	21.2	19.5	19.2	18.5	20.5	19.2	19.0	18.5	20.4
Men	14.0	12.9	10.8	11.1	10.3	9.2	9.7	9.2	10.7
Women	25.4	23.5	24.1	22.9	26.6	25.5	24.7	24.4	26.7
Source: SORS, Household Budget Survey; data from 2005 onwards are taken from the Statistics on Income and Living Conditions (EU-SILC) and are not totally comparable with the previous period due to methodological changes.
Notes: (bs) Break in series. 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.
Table 60: At-risk-of-poverty threshold1 (in SIT, EUR), Slovenia, 2000-2008
	2000	2001	2002	2003	2004(bs)	2005	2006	2007	2008
At-risk-of-poverty threshold for one person:									
SIT/month	71,414	79,180	86,291	92,407	98,839	109,909	115,095	N/A	N/A
EUR/month	346	363	382	395	413	460	480	509	557
At-risk of poverty rate for a four-member household:2									
SIT/month	149,969	166,278	181,212	194,056	207,561	230,809	241,700	N/A	N/A
EUR/month	726	763	802	830	868	965	1,009	1,069	1,169
Source: SORS; Household Budget Survey; data from 2005 onwards are taken from the Statistics on Income and Living Conditions (EU-SILC) and are not totally comparable with the previous period due to methodological changes.
Notes: (bs) Break in series. N/A - not available. 1The-at-risk-of-poverty threshold is defined for one person. It is calculated for income including income in kind. The at-risk-of-poverty threshold is defined as 60% of the median equivalised net income of all households using the OECD modified 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 modified equivalence scale: the fist 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 modified equivalence scale is used by SORS and Eurostat. 2This is the at-risk-of-poverty threshold for a household consisting of two adults and two children.
121 Social overview 2009
Statistical appendix
Table 61: At-risk-of-poverty rate with breakdown by most common activity status,1 total and by gender, Slovenia,
2000-2008, in %
	2000	2001	2002	2003	2004(bs)	2005	2006	2007	2008
Persons in employment	5.2	4.8	3.7	3.6	3.9	4.4	4.7	4.5	4.8
Men	5.6	5.4	4.1	3.8	4.1	4.5	5.0	5.0	5.1
Women	4.8	4.1	3.3	3.3	3.8	4.2	4.3	3.8	4.5
Unemployed	42.1	40.8	38.4	38.4	37.3	25.4	33.1	36.2	36.4
Men	41.6	36.9	39.3	38.8	41.2	23.0	34.9	38.9	37.6
Women	42.8	45.8	37.5	38.1	34.0	27.8	31.5	34.0	35.5
Pensioners	15.0	14.5	15.3	14.4	16.0	16.0	16.0	15.8	17.2
Men	12.3	11.7	12.1	11.3	11.0	9.3	9.8	9.8	12.0
Women	16.9	16.4	17.4	16.4	19.1	20.2	19.9	19.6	20.6
Source: SORS: Household Budget Survey for 2000-2004; data from 2005 onwards are taken from the Statistics on Income and Living Conditions (EU-SILC) and are not totally comparable with the previous period due to methodological changes.
Notes: (bs) Break in series. The at-risk-of-poverty rate is calculated for income including income in kind. 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 and under.
Table 62: At-risk-of-poverty rate with a breakdown by household type, Slovenia, 2000-2008, in %
	2000	2001	2002	2003	2004(bs)	2005	2006	2007	2008
Households without dependent children	14.8	13.6	13.8	13.1	14.4	14.8	14.2	14.0	15.1
Households with dependent children1	9.2	8.7	7.5	8.1	7.6	9.3	8.7	8.9	9.6
Single-parent household, one or more dependent children	21.1	19.8	17.2	24.5	21.4	24.8	22.0	28.9	30.3
Single household, persons aged 65 and over	42.4	39.8	40.2	39.9	46.0	45.9	46.2	44.6	47.1
Source: SORS, Household Budget Survey; data from 2005 onwards are taken from the Statistics on Income and Living Conditions (EU-SILC) and are not totally comparable with the previous period due to methodological changes.
Notes: (bs) Break in series. 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. households without dependent children include single 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.
122 Social overview 2009
Statistical appendix
SOCIAL PROTECTION EXPENDITURE
Table 63: Social protection expenditure as share of GDP, EU-25, 2000-2007, in %
	2000	2001	2002	2003	2004	2005	2006	2007
EU-25	26.5	26.7	27.0	27.4	27.2	27.3	26.9 (p)	26.4 (p)
Austria	28.4	28.8	29.2	29.6	29.3	28.9	28.5	28.0
Belgium	26.5	27.3	28.0	29.0	29.2	29.6	30.2	29.5
Bulgaria	N/A	N/A	N/A	N/A	N/A	16.0	14.9	15.1
Cyprus	14.8	14.9	16.3	18.4	18.1	18.4	18.4	18.5 (p)
Czech Republic	19.5	19.4	20.2	20.2	19.3	19.2	18.7	18.6
Denmark	28.9	29.2	29.7	30.9	30.7	30.2	29.3	28.9
Estonia	13.9	13.0	12.7	12.5	13.0	12.6	12.3	12.5
Finland	25.1	24.9	25.7	26.6	26.7	26.8	26.2	25.4
France	29.5	29.6	30.4	30.9	31.3	31.4	30.7	30.5 (p)
Greece	23.5	24.3	24.0	23.6	23.5	24.6	24.5	24.4
Ireland	13.9	14.9	17.5	17.9	18.1	18.2	18.3	18.9
Italy	24.7	24.9	25.3	25.8	26.0	26.4	26.6 (p)	26.7 (p)
Latvia	15.3	14.3	13.9	13.8	12.9	12.4	12.3	11.0 (p)
Lithuania	15.8	14.7	14.0	13.5	13.3	13.1	13.2	14.3 (p)
Luxembourg	19.6	20.9	21.6	22.1	22.3	21.7	20.3	19.3
Hungary	19.6	19.2	20.3	21.2	20.6	21.9	22.4	22.3
Malta	16.9	17.8	17.8	18.3	18.8	18.6	18.2	18.1
Germany	29.3	29.4	30.1	30.4	29.8	29.7	28.7	27.7 (p)
Netherland	26.4	26.5	27.6	28.3	28.3	27.9	28.8	28.4 (p)
Poland	19.7	21.0	21.1	21.0	20.1	19.7	19.4	18.1
Portugal	21.7	22.7	23.7	24.1	24.7	25.3	25.4	24.8
Romania	13.0	12.8	13.6	13.0	12.7 (p)	13.2	12.5	12.8
Slovakia	19.4	19.0	19.1	18.2	17.2	16.5	16.3	16.0 (p)
Slovenia	24.2	24.5	24.4	23.7	23.4	23.0	22.7	21.4 (p)
Spain	20.3	20.0	20.4	20.6	20.7	20.9	20.9 (p)	21.0 (p)
Sweden	30.1	30.8	31.6	32.6	32.0	31.5	30.7	29.7 (p)
United Kingdom	26.4	26.8	25.7	25.7	25.9	26.3	26.1	25.3 (p)
Source: Eurostat, ESSPROS.
Notes: p) - preliminary data; N/A - not available.
123 Social overview 2009
Statistical appendix
Table 64: Social protection expenditure1 by function as share of GDP,2 Slovenia, 2000-2007, in %
	2000	2001	2002	2003	2004	2005	2006	2007
Social protection expenditure	24.2	24.5	24.4	23.7	23.4	23.0	22.7	21.4
Social benefits expenditure3 by function:	23.6	23.9	23.8	23.2	22.8	22.5	22.2	20.9
Sickness/health care	7.2	7.5	7.5	7.5	7.4	7.3	7.1	6.7
Disability	2.1	2.1	2.0	1.9	1.9	1.9	1.8	1.6
Old age	10.2	10.4	10.6	10.0	9.9	9.5	8.4	8.2
Survivors	0.5	0.5	0.4	0.4	0.4	0.4	1.7	1.5
Family/children	2.2	2.1	2.0	2.0	2.0	1.9	1.9	1.8
Unemployment	1.0	0.9	0.7	0.7	0.7	0.7	0.7	0.5
Housing	n.p.	n.p.	n.p.	n.p.	n.p.	0.0	0.0	0.0
Social exclusion not classified elsewhere	0.4	0.4	0.5	0.6	0.6	0.6	0.5	0.5
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 defined 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 classified. Data on social protection expenditure is slightly different from data on social benefits in total as the first also covers administrative and manipulative costs of distribution. 2Gross domestic product, main aggregates of national accounts and employment, Slovenia 2000-20007, Corrected version, SORS, 24 September 2008. 3Social benefits is the main category of expenditure on social protection schemes. These include transfers in cash or in kind by social protection schemes to households and individuals to relieve them of the burden of a defined set of risks or needs.
Table 65: Social protection per capita in PPS,1 Slovenia, 2000-2007
	2000	2001	2002	2003	2004	2005	2006	2007
Social protection per capita in PPS	3,685.8	3,861.8	4,111.0	4,104.0	4,367.8	4,526.6	4,703.3	4,760.5
Source: Eurostat.
Note: 1Purchasing Power Standard (PPS).
124 Social overview 2009
Statistical appendix
MACROECONOMIC INDICATORS OF DEVELOPMENT
Table 66: GDP, Slovenia, 2000-2008
	2000	2001	2002	2003	2004	2005	2006	2007	2008
GDP in EUR (fixed exchange rate 2007, current prices)	18,480.7	20,654.3	23,128.5	25,114	27,073.4	28,749.6	31,050.4	34,568.2	37,135.4
GDP in EUR (fixed exchange rate 2007, (constant previous- year prices)	17,544.4	19,007.2	21,475	23,784.2	26,190.6	28,289.7	30,419.8	33,160.7	35,775.5
Growth rates (constant previous- year prices), %	4.4	2.8	4	2.8	4.3	4.5	5.8	6.8	3.5
GDP growth rates (constant previous- year prices, reference year 2000), in %	18,480.7	19,007.2	19,762.5	20,322.8	21,194	22,146.1	23,432.7	25,025.3	25,899.3
GDP, in mio EUR (current exchange rate)	21,600	22,790	24,500	25,752	27,162	28,750	31,055	34,568	37,135
GDP per capita, EUR (current exchange rate)	10,858	11,441	12,281	12,900	13,599	14,369	15,467	17,123	18,367
GDP per capita, USD	9,997	10,236	11,564	14,556	16,885	17,869	19,400	23,467	27,014
GDP per capita (PPS)	15,200	15,800	16,800	17,300	18,700	19,700	20,700	22,300	22,700
GDP per capita (PPS) (EU-27=100)	80	80	82	83	86	88	88	90	91
Source: SORS, Eurostat.
Table 67: GDP per capita (EUR, current exchange rate), Slovenia, by region, 2000-2006
	2000	2001	2002	2003	2004	2005	2006
Slovenia	10,858	11,441	12,281	12,900	13,599	14,346	15,446
Zahodna Slovenia	12,867	13,661	14,659	15,577	16,338	17,209	18,567
Obalno-kraška	11,440	11,945	12,884	13,411	14,055	14,575	15,747
Goriška	10,746	11,322	11,952	12,323	13,020	13,802	14,785
Gorenjska	9,512	10,135	10,804	11,182	11,635	12,223	12,980
Osrednjeslovenska	15,038	16,012	17,240	18,586	19,504	20,571	22,286
Vzhodna Slovenia	9,164	9,566	10,267	10,628	11,267	11,900	12,768
Notranjsko-kraška	8,740	9,103	9,849	10,049	10,489	10,918	11,505
Jugovzhodna Slovenia	9,953	10,509	11,138	11,598	12,476	13,298	14,341
Spodnjeposavska	9,228	9,720	10,342	10,281	10,913	11,802	12,505
Zasavska	8,606	8,580	8,915	9,154	9,610	10,127	10,497
Savinjska	9,832	10,147	11,002	11,436	12,085	12,857	13,749
Koroška	8,980	9,409	9,864	10,061	10,534	11,258	11,850
Podravska	9,089	9,526	10,340	10,780	11,471	11,978	13,052
Pomurska	7,559	7,978	8,446	8,775	9,240	9,606	10,223
Source: SORS.
125 Social overview 2009
Statistical appendix
Table 68: GDP per capita, index (Slovenia=100), by region, 2000-2006
	2000	2001	2002	2003	2004	2005	2006
Slovenia	100.0	100.0	100.0	100.0	100.0	100.0	100.0
Zahodna Slovenia	118.5	119.4	119.4	120.7	120.1	120.0	120.2
Obalno-kraška	105.4	104.4	104.9	104.0	103.3	101.6	101.9
Goriška	99.0	99.0	97.3	95.5	95.7	96.2	95.7
Gorenjska	87.6	88.6	88.0	86.7	85.6	85.2	84.0
Osrednjeslovenska	138.5	140.0	140.4	144.1	143.4	143.4	144.3
Vzhodna Slovenia	84.4	83.6	83.6	82.4	82.8	82.9	82.7
Notranjsko-kraška	80.5	79.6	80.2	77.9	77.1	76.1	74.5
Jugovzhodna Slovenia	91.7	91.9	90.7	89.9	91.7	92.7	92.8
Spodnjeposavska	85.0	85.0	84.2	79.7	80.2	82.3	81.0
Zasavska	79.3	75.0	72.6	71.0	70.7	70.6	68.0
Savinjska	90.6	88.7	89.6	88.7	88.9	89.6	89.0
Koroška	82.7	82.2	80.3	78.0	77.5	78.5	76.7
Podravska	83.7	83.3	84.2	83.6	84.3	83.5	84.5
Pomurska	69.6	69.7	68.8	68.0	67.9	67.0	66.2
Source: SORS.
126 Social overview 2009
Statistical appendix
Table 69: GDP per capita in PPS, EU-27=100, Slovenia and EU-27, 2000-2008
	2000	2001	2002	2003	2004	2005	2006	2007	2008
EU-27	100	100	100	100	100	100	100	100	100
Austria	131	125	126	127	127	124	124	124	123
Belgium	126	124	125	123	121	120	118	118	114
Bulgaria	28	29	31	32	34	34	37	37	40
Cyprus	89	91	89	89	90	91	90	91	95
Czech Republic	68	70	70	73	75	76	78	80	80
Denmark	132	128	128	124	126	124	123	120	118
Estonia	45	46	50	55	57	62	66	70	68
Finland	117	116	115	113	116	114	115	116	115
France	115	116	116	112	110	111	109	109	107
Greece	84	87	90	93	94	92	93	94	94
Ireland	131	132	138	141	142	144	147	150	137
Italy	117	118	112	111	107	105	104	102	101
Latvia	37	39	41	43	46	49	53	58	56
Lithuania	39	41	44	49	50	53	56	60	61
Luxembourg	244	234	240	248	253	255	269	275	271
Hungary	55	59	62	63	63	63	63	63	63
Malta	84	78	80	78	77	78	77	78	75
Germany	118	117	115	117	116	117	116	115	116
Netherland	134	134	133	129	129	131	131	131	135
Poland	48	48	48	49	51	51	52	54	58
Portugal	78	77	77	77	75	77	76	76	76
Romania	26	28	29	31	34	35	38	42	46
Slovakia	50	52	54	55	57	60	64	67	72
Slovenia	80	80	82	83	86	88	88	90	91
Spain	97	98	100	101	101	102	104	106	103
Sweden	127	121	121	123	125	120	121	122	122
United Kingdom	119	120	121	122	124	122	121	119	117
Source: Eurostat.
127 Social overview 2009
Statistical appendix
COMPOSITE INDICATORS OF DEVELOPMENT
Table 70: Development Deficiency 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 Slovenia	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, DURS, AJPES, MOP, calculations by IMAD.
Note: 1The Development Deficiency Index is a composite index calculated on the basis of 11 indicators (indicators of development, development deficiency and development possibilities). Its primary purpose is to rank regions by development deficiency level. It is also a criterion for regional incentives.
128 Social overview 2009
Statistical appendix
Table 7': Human Development Index, EU-27, calculations 2000-20091
	1997	2002	2005	2006	2007	2009
EU-272	0.8693	0.8923	0.899	0.905	0.9'0	0.92'
Austria	0.9M	0.933	0.936	0.944	0.948	0.955
Belgium	0.929	0.949	0.945	0.945	0.946	0.953
Bulgaria	0.785	0.800	0.808	0.8'6	0.824	0.840
Cyprus	0.858	0.883	0.89'	0.903	0.903	0.9M
Czech Republic	0.843	0.857	0.874	0.885	0.89'	0.903
Denmark	0.9'3	0.932	0.94'	0.943	0.949	0.955
Estonia	0.795	0.833	0.853	0.858	0.860	0.883
Finland	0.9M	0.940	0.94'	0.947	0.952	0.959
France	0.92'	0.932	0.938	0.942	0.952	0.96'
Greece	0.876	0.895	0.9'2	0.92'	0.926	0.942
Ireland	0.894	0.929	0.946	0.956	0.959	0.965
Italy	0.907	0.92'	0.934	0.940	0.94'	0.95'
Latvia	0.765	0.8'2	0.836	0.845	0.855	0.866
Lithuania	0.787	0.828	0.852	0.857	0.862	0.870
Luxembourg	0.9H	0.929	0.949	0.945	0.944	0.960
Hungary	0.8'2	0.843	0.862	0.869	0.874	0.879
Malta	0.852	0.874	0.867	0.875	0.878	0.902
Germany	0.9'3	0.927	0.930	0.932	0.935	0.947
Netherland	0.928	0.939	0.943	0.947	0.953	0.964
Poland	0.8'6	0.845	0.858	0.862	0.870	0.880
Portugal	0.878	0.898	0.904	0.904	0.897	0.909
Romania	0.772	0.780	0.792	0.805	0.8'3	0.837
Slovakia	N/A	N/A	0.849	0.856	0.863	0.880
Slovenia	0.853	0.884	0.904	0.9'0	0.9'7	0.929
Spain	0.904	0.9'8	0.928	0.938	0.949	0.955
Sweden	0.929	0.958	0.949	0.95'	0.956	0.963
United Kingdom	0.92'	0.948	0.939	0.940	0.946	0.947
Source: Human Development Report 2002-2009 (UNDP).
Notes: 'United Nations Development Programme measures HDI annually, using data with a two-year time lag due to data availability. The most recent calculations were released in 2007. The index has values in an interval of 0-1. 2Non-weighted average. 3Value excluding data for Slovakia.
129 Social overview 2009
Statistical appendix
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	Knowledge	A decent standard of living
Indicator	LE at birth	literacy rate	GDP(PPPUSD)
gross enrolment ratio
Table 72: Human Development Index (HDI) and structural indicators, Slovenia, 2000-2007
	2000	2001	2002	2003	2004	2005	2007
HDI	0.879	0.881	0.895	0.904	0.910	0.917	0.929
Rank (no. among countries covered)	29, (173)	29, (175)	27, (177)	26, (177)	27, (177)	27, (177)	29, (182)
Life expectancy at birth (years)	75.5	75.9	76.2	76.4	76.6	77.4	78.2
LE index	0.84	0.85	0.85	0.86	0.86	0.87	0.886
Gross enrolment ratio,1 %	83.0	83.0	90.0	95.0	95.0	94.3	92.8
Education index	0.94	0.94	0.96	0.98	0.98	0.97	0.969
GDP per capita (PPP, USD)	17,367	17,130	18,540	19,150	20,939	22,273	26,753
GDP index	0.86	0.86	0.87	0.88	0.89	0.90	0.933
Source: Human Development Reports (2001-2009).
Notes: 'All persons participating in primary, secondary and tertiary education as a percentage of the population theoretically eligible for enrolment.
130 Social overview 2009
Statistical appendix
Table 73: Gender-related Human Development Index (GDI) and structural indicators, Slovenia, 2000-2007
	2000	2001	2002	2003	2004	2005	2007
GDI1	0.877	0.879	0.892	0.901	0.908	0.914	0.927
Rank (no. among countries covered)	27. (146)	29. (144)	26. (144)	25. (140)	24. (136)	25. (157)	24. (155)
Life expectancy (years)							
Men	71.7	72.2	72.5	72.7	72.9	73.6	74.4
Women	79.1	79.5	79.7	80.0	80.2	81.1	81.7
Gross enrolment ratio,2 %							
Men	80	80	86	92	91	90	87.7
Women	85	85	94	99	100	99	98.1
GDP per capita (PPP, USD)	17,367	17,130	18,540	19,150	20,939	22,273	26,753
Estimated earned income (PPP, USD)3							
Men	21,642	21,338	22,832	23,779	26,129	27,779	33,398
Women	13,327	13,152	14,082	14,751	15,992	17,022	20,427
Difference between GDI and HDI4	-0.002	-0.002	-0.003	-0.003	-0.002	-0.003	-0.002
Source: Human Development Report (2001-2009).
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 and its indicators reflect (in)equalities in the distribution of goods needed for (quality) living - health, income and education - between men and women. The main idea of the GDI is: the more a country's GDI approaches its HDI, the smaller the gender gap in benefiting from basic human resources. As the gender gap widens, the GDI falls (in an interval of [0-1]). Since inequality (in opportunities) exists in all countries, the GDI tends to be lower than the 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 official 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 74: Gender Empowerment Measure (GEM)1 and structural indicators, Slovenia, 2000-2007
	2000	2001	2002	2003	2004	2005	2007
GEM	0.585	0.582	0.584	0.603	0.603	0.611	0.641
Rank (no. among countries covered)	25, (66)	27, (70)	31, (78)	30, (80)	32, (75)	41,(93)	34, (109)
Seats in parliament held by women (as % of total)	12.2	12.2	12.2	12.2	10.8	10.8	10
Senior officials and managers (as % of total)	31.0	31.0	29.0	33.0	34.0	33.0	34
Female professionals and technical workers (as % of total)	51.0	54.0	55.0	56.0	57.0	57.0	56
Ratio of estimated female to male earned income	0.62	0.62	0.62	0.62	0.61	0.61	0.61
Difference between GEM and HDI	-0.294	-0.299	-0.311	-0.301	-0.307	-0.306	-0.288
Source: Human Development Report (2001-2009).
Note: 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 parliamentary seats held by women); 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 (the 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, with the shares of men and women equal in all key indicators.
Social overview 2009	131
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Social overview 2009
Abbreviations / Acronyms
137
Abbreviations
AEP - active employment policy
AJPES - Agency for Public Legal Records and Related Services CJMMK - Public Opinion and Mass Communications Research Centre COFOG - classification of the functions of government
COICOP - classification of individual (final) consumption (of households) by purpose DO - long-term care
DURS - Tax Administration of the Republic of Slovenia
EACEA - Education, Audovisual and Culture Excutive Agency
ESS - European Social Survey
ESS - Employment Service of Slovenia
ESSPROS - European System of Social Protection Statistics
EU - European Union
EUROPOP - Eurostat's Population Projections for Slovenia
EUROSTAT - Statistical Office of the European Communities
EU-SILC - European Union Statistics on Income and Living Conditions
FDV - Faculty of Social Sciences.
GDP - gross domestic product
HBS - Household Budget Survey
HIIS - Health Insurance Institute of Slovenia
ICT - information and communication technologies
IMAD - Institute of Macroeconomic Analysis and Development
IMF - International Monetary Fund
IRSSV - Social Protection Institute of the Republic of Slovenia ISCED - International Standard Classification of Education IVZ - Institute of Public Health of the Republic of Slovenia IZUM - Institute of Information Science Maribor LFS - Labour Force Survey
MDDSZ - Ministry of Labour, Family and Social Affairs
MF - Ministry of Finance
MMC - Multimedia Centre
MNZ - Ministry of the Interior
MOL - Municipality of Ljubljana
MOSS - Measurement of Website Traffic
N/A - not available
NPISH - non-profit institutions serving households NRS - National Readership Survey NSVS - National Housing Savings Scheme NUK - National and University Library
OECD - Organisation for Economic Co-operation and Development
PDII - Pension and Disability Insurance Institute of the Republic of Slovenia
PISA - Programme for International Student Assessment
p.p. - percentage point
PPP - purchasing power parity
PPS - purchasing power standard
PTI - vocational technical programmes
RS - Republic of Slovenia
SCA - Standard Classification of Activities
SCO - Standard Classification of Occupations
SJM - Slovenian Public Opinion
SMARS - The Surveying and Mapping Authority of the Republic of Slovenia
SNA - System of National Accounts SORS - Statistical Office of the Republic of Slovenia
SRE - Statistical Register of Employment
TIMMS - Trends in International Mathematics and Science Study
VAT - value added tax
ZDPU - IMAD's Database of Cash Benefits
WHO - World Health Organization
138	Social overview 2009
Abbreviations / Acronyms
Acronyms of countries	
AT- Austria	MT- Malta
BE- Belgium	NL- Netherland
BG- Bulgaria	PL- Poland
CZ- Czech Republic	PT- Portugal
CY- Cyprus	RO- Romania
DE- Germany	SE- Sweden
DK- Denmark	SI- Slovenia
EE- Estona	SK- Slovakia
ES- Spain	UK- United Kingdom
FI- Finland	NO- Norway
FR- France	ZDA- United States of America
EL- Greece	CA- Canada
HU- Hungary	BiH- Bosnia and Hercegovina
IE- Ireland	ČG- Montenegro
IT- Italy	YU- Yugoslavia
LU- Luxembourg	SFRJ- Socialistic Federal Republic of Yogoslavia
LT- Lithuania	EGS-European Economic Community
LV- Latvia	
EU - European Union