Shadow Economy in Slovenia:
The Labour Approach
Bojan Nastav
Štefan Bojnec
The all-around notorious shadow economy phenomenon is subject to
constant reshaping, regarding both time and place, which results in a
somewhat unclear definition. We use the following definition: all pro-
ductive activities, whose output is legal, but is deliberately concealed
from the authorities, usually for gaining financial benefits. Different
methods of quantifying the size of the shadow economy have been de-
veloped. We focus on the labour approach, with Slovenia as the case-
study during the last decade. The importance of such an analysis lies in
the ambiguous effects of the shadow economy and their policy impli-
cations. We found that the shadow economy that relates only to the un-
employment discrepancies in Slovenia amounts on average to around
6 percent of the official economy, and tends to slightly decline over the
most recent years. On the other hand, employment discrepancy and
more detailed activity-level results give much higher values and even
an increase in the shadow economy: on average around 20 percent in
the studied period.
Key Words: shadow economy, indirect methods, employment
discrepancies, labour approach
jEL Classification: j2i, E26
Introduction
Globalisation of the economy, cooperation and integration of countries
and their common policies, cooperation and internationalisation of en-
terprises and entrepreneurial activities set a demand for consistent and
internationally comparable evidences. Relating, for instance, to the gross
domestic product (gdp), true values should be obtained by international
methodologies and standards, where the true comprises both the official
gdp and the one that is not covered by the official statistics. Deficien-
cies in the official statistics due to various reasons omit some of the pro-
Bojan Nastav is an Assistant at the Faculty of Management Koper,
University of Primorska, Slovenia.
Dr Štefan Bojnec is an Associate Professor at the Faculty of
Management Koper, University of Primorska, Slovenia.
Managing Global Transitions 5 (2): 193-208
ductive activities that are otherwise within the production boundary. As
defined by the System of National Accounts (sna) (1993), these omit-
ted activities should be included in the gdp figures. Moreover, several
of such activities are hidden on purpose. This is where the phenomenon
of the shadow economy emerges, as it covers some of the missed and
hidden production.
Due to its definition of the unobserved (missed and hidden) produc-
tion, the shadow economy presents a methodological challenge to mea-
sure its size and determine its characteristics, but also for policy for-
mulation as it has different consequences. By studying and empirically
evaluating the shadow economy and its size, there is more information
gathered, thus serving the implementation of appropriate development
and other policy tools. Many studies have been conducted on this is-
sue, covering various approaches, data sources and countries. However,
country-specific studies turned out to be the most appropriate.
In this paper we deal with that part of the shadow economy that is em-
bodied in the labour market activities. Thus the labour approach alone
represents an indirect method that is used to study the phenomenon.
Furthermore, we restrict our investigation only to Slovenia. During the
analyzed period the country moved through the period of transition
from a self-managed centrally-planned economy to a market-oriented
economy and adjustment to European Union (eu) membership. Cur-
rently Slovenia is strongly included in the international cooperation, and
on 1 May 2004 Slovenia joined the enlarged eu.
Different studies have shown that the transition period is a hotbed
for the shadow economy activities (e. g. Kaufmann and Kaliberda 1996;
Feige and Ott 1999; Schnider and Enste 2002). The importance of the
shadow economy in the official one varies across countries, but the esti-
mated proportion of the shadow economy in a certain country depends
also on different approaches and methodologies that are used by differ-
ent studies. The same holds for Slovenia. We aim to show that develop-
ment level and developmental path determine the level of the shadow
economy, which is believed to be on a downturn in recent years.
The rest of the paper is structured in the following way. The next sec-
tions present the definition and characteristics of the shadow economy
and a brief literature review of this phenomenon in general, both in tran-
sition countries and in Slovenia. In the subsequent section the descrip-
tion of the methodology and the data used is given. A further section
explains the results. Conclusions are given in the final section.
The Shadow Economy
Shadow economy is a phenomenon present in all societies, regardless
of their level of development. That is the reason why definitions of the
shadow economy differ among researchers, countries and also between
various time frames. Besides, different terms are used for labelling the
studied phenomenon, sometimes interchangeably, and not always con-
sistently. Nevertheless, expressions like the shadow economy have been
rooted in the researchers' languages and are as such widely used.1 There-
fore it is important to stress the meaning of the shadow economy in this
paper to avoid possible misinterpretations: shadow economy comprises
all productive activities, whose goods and services are legal, but the activity
itself is deliberately concealed from the authorities, usually to make finan-
cial gains (e. g. tax avoidance, non-compliance with certain regulations
and standards, etc.).
Measuring the shadow economy poses a challenge to researchers pri-
marily due to its nature:2 by definition the shadow economy is concealed
and therefore it is often impossible to directly measure its size. Neverthe-
less, several of the methods to quantify the size of the shadow economy
have been developed. In general, three main groups can be identified:
1.	Direct methods, which comprise surveys of households and enter-
prises on their shadow-economy behaviour.
2.	Indirect methods quantify the shadow economy through the marks
it leaves on the (official) economy. They can be further divided
into several groups, for instance: monetary methods (the currency
demand, transaction, and cash/deposit ratio approach); discrep-
ancy methods (income/expenditure discrepancy, supply/demand of
labour discrepancy); and physical output methods (electricity con-
sumption method).
3.	Modelling is the approach investigating relations of causes (determi-
nants) and reflecting indicators through a latent shadow economy
variable, which is then estimated.
The phenomenon of the shadow economy has both the negative and
the positive sides. Shadow economy causes the public finance to collect
fewer taxes, may cause damages to the official-economy firms as they face
higher costs (and are thus not competitive), and also consumers may be
worse-off due to no warranty for the products and services they purchase
in the shadow economy. On the other side, the shadow economy has pos-
itive consequences as well. Firms engaged in the shadow economy can
operate at lower (labour) costs and more people can become employed.
Consumers pay less, since no value-added tax is charged, or they do not
deal with some operational and transactions costs that are caused by bu-
reaucratic and administrative barriers that demand additional resources.
This latter implicit taxation can also increase the entrepreneurial incen-
tive in the shadow economy that can serve as an incubator for emerg-
ing small enterprises, which once they are successfully 'on the road' turn
legal. It is a formidable task to determine, which, positive or negative,
consequences of the shadow economy prevail. Therefore, several studies
have been conducted across countries and over time to gain more infor-
mation on the phenomenon, its causes and consequences. A brief review
of some of them, with emphasis on the transition countries and Slovenia,
is given below.
LITERATURE REVIEW
Several authors have conducted an in-depth study and gathered vital
theoretical, methodological and empirical information on the shadow
economy. It is important to stress that authors use different notations
for the phenomenon and are not (always) consistent. Schneider and En-
ste (2002) for instance, use the same naming, i. e. shadow economy, yet
with a slightly different definition. Williams (2004) addresses the phe-
nomenon as the cash-in-hand work. Others, Breusch (2005) for instance,
use the non-observed or underground economy, whereas Feige (1990) de-
fined the phenomena as unrecorded and informal economies. Despite
different definitions (which demands caution when comparing), these
studies provide a valuable insight into the main terminological, method-
ological, and empirical issues of the phenomenon.
Besides individual researchers, international and supranational organ-
isations such as Organisation for Economic Cooperation and Develop-
ment (oecd), International Labour Organisation (ilo), United Nations
(un), and eu have realised the importance of the shadow economy and
therefore, several definitions of the phenomenon, instructions on how
to deal with it and estimates of its size have been put forward and some
sort of standards in this field have been set.3 Different recommendations
and terms have been proposed. oecd (2002), for instance, defines un-
derground, illegal, and informal sector production, household production
for own final use, and production missed due to deficiencies in data col-
lection programme, with the underground production being the most
consistent with our definition of the shadow economy. eu has focused
primarily on undeclared work in its member states and this is defined as
'productive activities that are lawful as regards their nature, but are not
declared to the public authorities, taking into account the differences in
the regulatory system between Member States' (European Commission
2004, 94) which is clearly in line with the above mentioned definition of
the shadow economy.
Special interest in the past decade(s) has been given to the transition
economies, which comprise Central and East European countries and
Former Soviet Union countries. As these countries have some common
features of the shadow economy they were normally studied and anal-
ysed jointly. For instance, within the oecd the 'Methods of measuring
the hidden economy in the transition economies' were presented (Är-
vay 1993). Their definition of the hidden economy is, however, not com-
pletely in line with the shadow economy used here, since illegal activities
are added, so one needs to have this in mind when comparison is made.
Furthermore, other authors (e. g. Dobozi and Pohl 1995; Kaufmann and
Kaliberda 1996) use the electricity consumption method and they use
the term unofficial economy defined as the 'unrecorded value added by
and deliberate misreporting or evasion by a firm or individual' and thus
giving room for illegal activities as well. Lacko (1999) and Feige and Ur-
ban (2005) provide further applications of the electricity consumption
method to measure the underground economy in the transition countries.
Besides, Feige and Ott (1999) gather some of these methods, and some
additional methods that are arranged in a comprehensive guide to study
the underground activities in transition countries.
shadow economy in slovenia
Slovenia was seldom covered in the above-mentioned studies of the
shadow economy in the transition countries and not all of these stud-
ies are directly comparable, since authors follow different definitions
and methodologies - which all contribute to different results. Schnei-
der (2003) applied the modelling approach and recorded 22.6 percent of
the shadow economy4 of the Slovenian official gdp in the period 1990-
1993, 23.9 percent in the period 1994-1995, and 26.7 percent in the period
2000-2001. This evidence suggests an increase in the degree and level
of the shadow economy in Slovenia to around one-fourth of the official
gdp.
The early transition period was covered and studied by Glas (1991)
and Kukar (1995). They both list similar causes for the existence and
development of the shadow economy, which all date back into the so-
cialist system. Mainly, these focus on the rigid legislative framework,
centrally planned and controlled supply of goods (which seldom fol-
lowed the demand), unstable macroeconomic environment, and increas-
ing tax and contributions burden in the period of transition. The need
for increased efficiency and more market-oriented production enter-
prises had increased, whereas the bureaucratic obstacles were only par-
tially removed. The latter caused many of the private businesses to start
'off the record', in the shadow economy. Glas (1991) estimated the size of
the shadow economy5 in Slovenia in the late 1980s via a survey of the
human resource departments in companies. The results revealed that
up to 43 percent of the employed participates in the shadow economy,
corresponding to above 38 percent of additional income. The trend was
estimated to go even higher in the following years. Kukar (1995) esti-
mates the size of the shadow economy6 with the labour method mea-
suring the activity rate of the labour force. For the year 1993, it was esti-
mated that around 26 percent of labour force (partially) participated in
the shadow economy, amounting to almost 9 percent of fully employed
people, which on the other hand means around 10 percent as a share of
GDP. In this study, other authors estimated the size of the shadow econ-
omy using other methods, mainly by estimating the unregistered activ-
ities by subgroups of activities (related to main industry sectors, such
as construction, tourism, and agriculture), and they sum up to between
16.8 percent and 21.3 percent of the gdp in Slovenia in 1993.
Flajs and Vajda (2004) present more recent calculations. They followed
the Eurostat's exhaustiveness measures and revised the gdp for the pe-
riod 1995-2002 and the non-observed economy (without illegal activi-
ties) on average amounts to around 6.5 percent. Furthermore, the Euro-
pean Commission (2004) estimated that the undeclared work in Slovenia
in 2003 produced around 17 percent of the official gdp. The undeclared
work seems to be in decline, which was anticipated, as the transition was
coming to an end, and entry into the eu was on the doorstep, which
all meant a more efficient and stable macroeconomic environment, legal
framework and market economy as opposed to the situation in the early
stages of the transition.
Methodology and the Data Used
Despite the whole range of methods, we have decided to focus on the
labour-market data approach alone, which relies in essence on the dif-
ferences in actual (real) and official (registered) use of labour.7 There
are two sources of evidence for these two aspects. On the one hand, the
Labour Force Survey (lfs) reveals the actual side. On the other hand, the
official records from the Employment Service of Slovenia (ess) or the
Statistical Office of the Republic of Slovenia (sors) (or some other data
source, where employers need to report their employees) provide the of-
ficial labour use side in the labour market. Simplified, the discrepancy
between the true and official labour use can be approximated by the data
on (un)employment from the actual (lfs) and registered (ess) labour
use. First, the unemployment discrepancies provide rather rough indica-
tion of the phenomena, the results of which are often inconsistent across
countries. We want to check the country-specific feature, i. e. whether
the majority of registered unemployed work in the shadow economy,
and thus we investigate the difference in unemployment rates or absolute
numbers of unemployed, obtained on the one hand by the lfs following
the more strict definition of the ilo, and by the ess on the other. This
difference provides a simple, but not very accurate number of the people
working in the shadow economy. Second, we direct ourselves to more di-
rect measurement of the discrepancy between the actual and registered
labour use, estimating the discrepancy between the actual (lfs) and reg-
istered (ess) number of employed. In Slovenia, these data are available
from 1993 onwards. The next step needs to provide some evidence on
the productivity of these people in order to obtain the final estimate of
the size of the shadow economy as a percentage of the official gdp. How-
ever, there are three main drawbacks to such a methodological approach.
First, it is almost impossible to determine the productivity measure for
the shadow economy, when using indirect measures alone. Second, the
assumptions that all unemployed work full-time in the shadow econ-
omy, and that no one with an official job participates (part-time) in the
shadow economy, are rather weak. Besides, the problem of underreport-
ing (understating) of the data to the lfs and ess is also present. And
third, different data sources on the labour force in the economy are very
limited in their consistency. These three shortcomings have been tackled
in the empirical analysis in the following way.
First, regarding the productivity, there is only limited work conducted
on this aspect in the literature. Jon Isachsen and Strom (1985) for in-
stance distinguish between those who have been laid off and those who
voluntarily switch to the shadow economy. They found that the two
types/categories differ in their productivity. In the unobserved sector
the 'payment more likely is according to productivity' (Jon Isachsen
and Strom 1985, 34) and thus the more productive workers shift to the
shadow economy. Schneider (2003, 34) also states that: '... the produc-
tivity in the shadow economy is quite likely to be considerably higher
than in the official economy.' At the same time, those who are laid off
are usually low productivity workers and this brings the productivity of
the shadow economy down. Thus, one can argue in both directions: as
people work for themselves, the motivation and productivity for a sim-
ilar job is normally higher in the shadow economy. On the other hand,
working in the shadow economy requires extra resources for staying un-
detected, therefore hindering the productivity. By nature, shadow econ-
omy activities are more labour intensive with very limited access to high
technology, which further reduces their productivity. Therefore, in order
not to be very limited in our approximations and to evaluate the sen-
sitivity of our results on the applied assumptions, we have used three
scenarios for productivity measures.8 Following the first one, the pro-
ductivity in the shadow economy is 10 percent less than in the official
economy. The second scenario approximates the same productivities,
and the last one states that the shadow economy is by 10 percent more
productive.
Second, the assumption on the full-time participation of the unem-
ployed in the shadow economy is not properly grounded, due to sam-
pling errors, underreporting and the fact that not all of those registered
as unemployed according to the lfs work full-time in the shadow econ-
omy. Jon Isachsen and Strom (1985, 35) stress that 'it is more common
to work part-time in both sectors.' Thus we shift our analysis to the dis-
crepancy between the registered and actual employment in the studied
country, which suffers less from these drawbacks.
Third, the data from two different sources are not consistent, as
the lfs measures the employment, whereas the administrative sources
usually report the jobs. To bridge these shortcomings, we applied the
methodological approach, which was developed by the Italian Statis-
tical Office. This is the so-called Labour Input Method (lim), which
is obtained by the following five steps (oecd 2002, 53, 72): first, esti-
mate the labour input underlying the gdp estimates. This registered use
of labour is obtained from the tailor-made enterprise surveys or data
from employment agencies. Second, estimate the labour input based on
household survey data or the lfs (the actual labour use). Third, stan-
dardise the labour input estimates, which convert both of the evidences
into the same units of labour input, either to hours worked or full-time
equivalents. Fourth, compare the two sets of estimates. Fifth, compute a
multiplication factor to adjust the output and value added estimates to
account for non-observed production obtained in the previous step.
The drawback of the lim is a very high demand for the in-depth lfs.
Also, some complementary special-purpose surveys are highly recom-
mended. If these are not available, 'data from enterprise surveys and ad-
ministrative files can be used' (oecd 2002,73). Standardisation of labour
input has been done through the number of hours worked, which are
available for Slovenia on the activity level for the years 1995 and 2000
only. The oecd's (2002) handbook proposes that for each activity branch
the value added per unit of labour input of non-observed production
and the measured one do not differ. Essentially, this states, that the pro-
ductivities are at the same level in both the shadow and official economy.
We, however, use the following approach: calculate the value-added per
official actually worked hour at the activity level and use it as the pro-
ductivity ratio. Further, we assume that activities, requiring high-level
skills are more likely to yield higher productivity in the shadow econ-
omy. Thus, activities of agriculture, fishery and mining (a, b, and c),
following the International Standard Industry Classification (isic Rev.
3),9 are below the official productivity by 10 percent; that the manufac-
turing and electricity, gas and water supply (activities d and e) are on
the same level of productivity in both economies; and finally, that other,
service-based activities are by 10 percent more productive in the shadow
economy than in the official economy (see also Nastav and Bojnec 2007).
At this point we add the sensitivity analysis in the way that we take up-
per/lower bounds to these productivity measures by plus/minus 5 per-
centage points, respectively. Further, multiplying the hours, estimated
to be worked in the shadow economy by the corrected level of the value
added per official working hour by activities, we obtain the shadow value
added by activity levels. By doing additional calculations we obtain the
final results (see table 3).
The final approach applied uses the data on activity levels in Slove-
nia and essentially follows the Crnkovic-Pozaic (1999) application to the
Croatian economy in the first half of the 1990s. By this approach, activity
is supposed to move in more or less constant and inverse direction with
the output. Crnkovic-Pozaic (1999, 220) argues that 'economic develop-
ment and growth make it possible for a section of the working age pop-
ulation to stop working and turn to other activities which expand their
table 1 Shadow economy in Slovenia (lower, middle, and upper bounds)
following the employment discrepancy and the activity level approaches,
1993-2004 (%)
Employment discrepancy	Activity level
Year	Lower	Middle	Upper	Lower	Middle	Upper
1993	9.2	10.2	11.3	14.5	16.1	17.7
1994	11.8	13.1	14.4	4.3	4.8	5.3
1995	15.8	17.6	19.3	2.8	3.1	3.4
1996	16.1	17.9	19.7	4.4	4.9	5.3
1997	18.7	20.8	22.9	2.3	2.6	2.8
1998	19.5	21.7	23.9	0.5	0.6	0.6
1999	15.8	17.6	19.4	3.4	3.8	4.2
2000	14.7	16.4	18.0	—	—	—
2001	15.6	17.3	19.1	4.0	4.5	4.9
2002	15.9	17.7	19.4	3.7	4.1	4.5
2003	13.8	15.3	16.8	6.9	7.6	8.4
2004	18.8	20.9	23.0	1-9	2.1	2.3
sources ilo (http://laborsta.ilo.org), ess (http://www.ess.gov.si), sors (http://www
.stat.si), Eurostat (http://epp.eurostat.ec.europa.eu), own calculations.
quality of living, but are not considered economic activities.' In essence,
the method proceeds as follows: the base year's activity rate is calculated
and then used as a constant for all the subsequent years. By this, the
so called hypothetical activity rates are calculated and then compared in
each of the years to the official, de-facto activity rates. The latter would
normally be (by assumption) lower and the difference between the hy-
pothetical and de-facto active population is the measure of the number
of people working in the shadow economy. Yet, the Slovenian case needs
extra calculations: the activity rate has on average risen and therefore the
base-year rate is not suitable for the hypothetical calculations.
Therefore, an assumption that the hypothetical activity rate was in-
creasing at a constant annual growth rate,10 surpassing the annual de-
facto rates, is applied. This adjustment enables the required calculations
to be made.
Results
Applying the unemployment discrepancy approach to the data available,
we found that, although the results are rather volatile, there is a down-
20
15
10
		Employment discrepancy O O				O
0		O O 0 O	O	O	n	
\	O					
1-1 *						
Activity rates						
" ° " 0 0 " 0 0						
1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004
figure 1 Shadow economy as a share in the official gdp for Slovenia in the studied
period, comparing (middle values of) approaches from table 1
5
0
ward tendency and the results vary at around 6 percent and stabilize at
around 4 percent of the shadow economy in the official gdp in 2004.
Table 1 presents results pertaining to the employment discrepancy and
activity rate methodological approaches. We can see that the shadow
economy's share in the official economy has been fluctuating, and that
the results differ substantially. While the activity rate approaches show
a downwards tendency, the employment discrepancy has the opposite
path. It can also be seen, that the activity rate approach indicates a rather
low share of the shadow economy (for all three scenarios), compared
to previous studies by other authors, which is consistent with liberaliza-
tion and more commercialized economic activities. Furthermore, it also
reveals a much higher variability in the size of the shadow economy, in-
dicating some deeper structural changes that have been induced by the
stabilization programmes, privatisation and structural reforms, and also
by eu enlargement. However, at the same time the results confirm the
approximate level and the downward patterns in the share of the shadow
economy as the country becomes more developed. On the other hand,
the employment discrepancy reveals a slight upwards trend, especially in
the last studied year, which is unexpected, but comparing it to the lim
approach (see below), these results seem reasonable. These movements
of the share of the shadow in the official economy are presented graphi-
cally in figure 1.
The lim approach, i. e. the comparison of the hours worked measured
by the official data sources and the lfs reveals that there is again the
table 2 Discrepancy between the official and lfs hours worked on average at annual
level by the activity break-down for Slovenia for the years 1995 and 2000
Year	a and b	c	d	e	f	g	h
1995	985.2	547.6	424.4	358.8	446	323.2	468.4
2000	780.4	501.2	391-6	400	437-6	371-2	464.4
Year	i	J	k	L	m	N	o
1995	504.4	311.2	323.2	364.8	105.6	371.6	184.8
2000	490.4	420.4	388.4	369.2	349-6	439-6	275.6
notes a - agriculture, hunting and forestry, b - fishing, c - mining and quarrying,
d - manufacturing, e - electricity, gas and water supply, f - construction, g - whole-
sale and retail trade; repair of motor vehicles, motorcycles and personal and household
goods, h - hotels and restaurants, 1 - transport, storage and communications, j - finan-
cial intermediation, k - real estate, renting and business activities, l - public administra-
tion and defence; compulsory social security, m - education, n - health and social work,
o - other community, social and personal service activities, p - private households with
employed persons.
sources ilo (http://laborsta.ilo.org), sors (http://www.stat.si), own calculations.
discrepancy. This is shown in table 2. We can see that in total, the dis-
crepancy has increased; this is inconsistent with our expectations, but in
line with the employment discrepancy method outlined above, and also
several of the activities have experienced an increase in this discrepancy,
comparing these two years alone. This holds particularly for e - elec-
tricity, gas and water supply, g - trade, j - financial intermediation, k
- real estate, renting and business activities, m - education, n - health
and social work, and o - other personal services. Especially the latter is
interesting, as it shows, that shadow economy activities are indeed con-
centrated (and expanded) in these activities. We can also add shadow tu-
toring and teaching, accompany them by renting and personal services
(which point to unstable real estate market conditions), and we obtain
what can be believed to be the major shadow economy activities.
From these data we can calculate the approximate shadow economy's
share in the official value added at the activity levels. Table 3 presents
the results. The figures show remarkably high shares in the value added
at activity levels, but these numbers would be slightly lower if calculat-
ing them in the gdp at activity levels using detailed input-output tables.
Nevertheless, looking at the dynamics, the results are consistent with the
previous finding by some other authors (e. g. Schneider 2003) regarding
the hours worked in the shadow economy by activities. The results for
table 3 Percentage of the shadow economy (lower, middle, and upper bounds) in the
official value added at activity level for Slovenia for the years 1995 and 2000
Year		a and b	c	d	e	f	g	h
1995 -	- upper	50.5	33.6	26.3	22.0	29.1	20.8	30.7
1995 -	- middle	47.8	31.8	25.1	20.9	27.8	19.9	29.4
1995 -	- lower	45.2	30.1	23.8	19.9	26.5	19.0	28.1
2000	- upper	42.3	30.1	24.1	25.0	28.1	24.5	31.3
2000	- middle	40.1	28.5	23.0	23.8	26.9	23.5	30.0
2000	- lower	37-9	26.9	21.8	22.6	25.7	22.4	28.6
Year		i	J	K	l	M	N	o
1995 -	- upper	33.8	19.9	20.8	23.5	6.5	24.1	11.7
1995 -	- middle	32.3	19.0	19.9	22.4	6.2	23.0	11.2
1995 -	- lower	30.9	18.2	19.0	21.4	6.0	22.0	10.7
2000	- upper	33.1	29.4	25.8	24.7	24.1	30.5	18.5
2000	- middle	31.7	28.1	24.7	23.7	23.1	29.2	17.7
2000	- lower	30.2	26.9	23.6	22.6	22.0	27.9	16.9
sources ilo (http://laborsta.ilo.org), sors (http://www.stat.si), own calculations.
activities e, g, j, k, m, n, and o show an increase in shadow activities.
Making the sum-up, we obtain that the shadow economy as a percent-
age of the official gdp at the country level was from 18.9 to 20.8 percent
in 1995, and from 20.4 to 22.5 percent in 2000. This confirms that the
shadow activities are present and their presence is by no means negligi-
ble. More specifically, the widespread shadow economy activities in table
3 comprise activities that are not typical seasonal work activities, such as
in agriculture, tourism or construction, but include mainly blue collar
service activities.
Concluding Remarks
Following the step-by-step evolvement of the labour approach, we have
seen that the shadow economy in Slovenia is by no means a negligible
phenomenon. The results at the level of the total economy, using the
unemployment discrepancy and activity rates approaches, show that the
shadow economy activities are, on average, on a downturn in the studied
period. While this is consistent with economic growth, reduction of the
transition impact, and socio-economic development that are believed
to hinder the shadow economy activities, there were also some fluctua-
tions present. Nevertheless, the discrepancies between the results of both
methods seem to converge at the end at a 4-6 percent level.
An employment discrepancy and more detailed, activity-level study,
however, gives much higher values and even an increase in the shadow
economy: on average at the level of around 20 percent of the official econ-
omy in the studied period. Accompanying results also point to several of
the activities that have gained their importance in the shadow economy,
namely: electricity, gas and water supply; trade; financial intermediation;
real estate; renting and business activities; education; health and social
work; and other personal services. More specifically, these are not typical
seasonal work activities such as in agriculture, tourism or construction,
but largely blue collar service activities. Thus, shadow economy policies
should primarily aim at these activities.
We have illustrated that the labour methods applied could provide
some evidence on the shadow economy activities in Slovenia. Yet, pri-
marily due to lack of accurate evidence, their use is limited for concrete
policy proposals. Thus, further research and detailed in-depth studies
are needed. These, however, strongly rely on the data from the official
sources or, especially, on the lfs results, which can reveal the true na-
ture of the national labour market condition and evolvement. Never-
theless, official, administrative sources are important, as they serve as a
benchmark, against which the shadow economy employment can be de-
termined. They can be supplemented by special-designed surveys. Fur-
thermore, it was assumed that the shadow and official economies were
operated in a separate way, in the sense that there were no multiplicative
effects of e. g. the shadow economy earnings spent in the official economy
and vice versa, where some of the official resources could be used for the
hidden activities. As the country develops and improves the data collec-
tion programmes, one is able to produce country-specific studies, rely-
ing on qualitative and long-run data, as well as specific-purpose surveys,
thus resulting in an in-depth insight into the true state of the shadow
economy. Such in-depth results can provide the basis for proper policy
tools to enhance development and wellbeing.
Notes
1	Despite some clear objections by Williams (2004), the term 'shadow
economy' is used.
2	And also due to some inconsistencies with its definition.
3	See for instance the ilo 1993 International Conference of Labour
Statisticians (icls) for the definition of the informal sector, sna (1993)
and its current reforms by unsd, the set up of the Delhi Group on
Informal Sector Statistics by the unsd (http://unstats.un.org/unsd/
methods/citygroup/delhi.htm) in 1997, the handbook Measuring the
Non-Observed Economy (oecd 2002), and the work of the European
Commission (2004) on undeclared work in the eu.
4	The author counts 'all economic activities which would generally be
taxable were they reported to the state (tax) authorities' Schneider
(2003, 24).
5	Defined as productive activities, not reported to the authorities but
excluding own-production of households.
6	The definition is (again) in line with the sna 1993 unregistered activi-
ties within the production boundary.
7	The labour market data were obtained from various sources, mainly
from the International Labour Organisation (ilo) website (http://
laborsta.ilo.org), the Statistical Office of the Republic of Slovenia
(sors, http://www.stat.si), and Employment Service of Slovenia (ess,
http://www.ess.gov.si). Additional (national accounts) data needed
were supplemented mainly by sors or the Eurostat statistics.
8	Total gdp (or value added by activities breakdown) per officially em-
ployed person has been used as a measure of productivity.
9	Or comparable national Standard Classification of Activities.
10 This could be a reasonable assumption, as the early transition years
induced shocks by the break-downs of big state-owned enterprises as
still the largest employers at that time. When the initial shocks were
over, the official employment again started to rise.
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