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The Shadow Economy in Slovenia
by Bojan Nastav and Štefan Bojnec
The shadow economy is a phenomenon present in all societies,
regardless of their level of development. The 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 consistently. Williams (2004) discusses the use
of different adjectives and nouns, which are also frequently
subject to improper use. Nevertheless, expressions like the
shadow economy have been rooted in the researchers’ languages
and are as such widely used1. Therefore it is important to stress
what is meant under the shadow economy in this paper to avoid
possible wrong interpretations: shadow economy comprises all
productive activities, whose goods and services are legal, but
the activity itself is deliberately concealed from authorities,
usually to make financial gains (e.g. tax avoidance, noncompliance
with certain regulations and standards, etc.).
Measuring the shadow economy poses a challenge to researchers,
not only due to already mentioned problems with its definition,
but primarily due to its nature: by definition the shadow economy
is concealed and it is therefore impossible to directly measure
its size. Nevertheless, 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 enterprises on their shadoweconomy
behaviour. These methods are believed to represent the conservative
estimates as many people tend not to report (in questionnaires)
all the shadow economy they take part in. (2) Indirect methods
quantify the shadow economy through the marks this leaves in
the (official) economy. They can be further divided into several
groups: the monetary methods (the currency demand, transaction,
and cash/deposit ratio approach); the discrepancy methods (income/expenditure
discrepancy, supply/demand of labour discrepancy); and physical
output methods (electricity consumption method). These methods
give different estimates and some are upward (more energy intensive
industries in the electricity consumption method) and some downward
(monetary approach, since not all the shadow economy is taking
place in cash; electricity consumption, if the improved efficiency
is not taken into account) bias. (3) Modelling is the approach
reflecting relations of causes (determinants) and indicators
through latent shadow economy variable, which is then estimated.
The shadow economy causes the public finance to collect fewer
taxes, may causes damage to the official-economy firms as they
may face higher costs and are not competitive, and also, consumers
are 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 positive consequences as well. First, firms
can operate at lower (labour) costs and more people can become
employed; consumers pay less, since no value-added tax is charged
or some bureaucratic and administrative barriers, which demand
resources, are not dealt with. The latter can also increase
the entrepreneurial incentive and the shadow economy can serve
as an incubator for 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, by studying and evaluating
the shadow economy and its size, more information is gathered,
thus serving the implementation of appropriate development and
other policy tools.
Literature Review
Due to already mentioned significance of the shadow economy,
several studies have been conducted in order to gain more information
on the phenomenon, its causes and consequences. Only a brief
review of these is given bellow, with emphasis on transition
economies and mainly Slovenia.
Several authors have conducted an in-depth study and gathered
vital theoretical, methodological and empirical information
on shadow economy. Schneider and Enste (2002) for instance,
use the same naming, i.e. shadow economy, yet slightly different
definition. Nevertheless, their study, revealing causes and
consequences, dealing with some theoretical issues in economics,
and revealing the main methods, presents figures for a range
of countries and can therefore be used as a starting point in
the shadoweconomy research. Similarly, Williams (2004), focusing
on England, provides an insight into main terminological, methodological
and empirical issues of the phenomenon, which he addresses as
the cash-in-hand work.
Besides individual researchers, international and supranational
organisations (OECD, ILO, EU, and UN) have realised the importance
of the shadow economy and therefore, several definitions of
the phenomenon, instructions 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. In this manner the ILO 1993 International
Conference of Labour Statisticians (ICLS) put forward a definition
of the informal sector, which, although referring primarily
to the less developed countries and thus not directly appropriate
for the shadow economy, as understood in this paper, was later
used in the System of National Accounts 1993 (hereafter SNA
1993) (1993) and current reforms for the SNA 2008 (UNSD 2004b).
A step further has been made by the set up of the Delhi Group
on Informal Sector Statistics by the UN Statistics Division
(UNSD 2004a) in 1997, which is the international forum for the
informal-sector information and experience exchange. Furthermore,
OECD, together with the IMF, ILO and CIS STAT prepared ‘a Handbook:
Measuring the Non-Observed Economy’ (OECD 2002). By disaggregating
the nonobserved economy into the so called NOE Problem Areas
(underground, illegal, informal sector production, household
production for own final use, and production missed due to deficiencies
in data collection programme), the Handbook puts forward their
definitions and propositions of proper measurement in order
to obtain, in Eurostat’s words, an exhaustive figure of the
GDP. Despite some overlapping between these problem areas, the
underground production fits most to the definition of the shadow
economy used here. Eurostat and national statistical offices
of the EU member states follow this Handbook in obtaining the
most exhaustive GDP measures. EU has focused primarily on the
undeclared work in its member states in report Undeclared work
in an enlarged Union (European Commission 2004). Such work is
defined as “Productive activities that are lawful as regards
to 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
so-called transition economies, which comprise Central –and
East European (CEE) countries and Former Soviet Union (FSU)
countries. Many of the former have already been included in
the EU’s work mentioned above and are now believed to have completed
the transition period. Nevertheless, pointing to the past decade,
they had some common features of the shadow economy with the
FSU countries. This is important at this point, since Slovenia
also had a transition period and has therefore been studied
in this group of countries, or studies of the transition countries
can be (partially) applicable to Slovenia as well.
In 1993 OECD’s Statistics Directorate at Joint OECD/UNECE Meeting
of National Accounts Experts presented ‘Methods of Measuring
the Hidden Economy in the Transition Economies’ (Árvay 1993).
The definition is not completely 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.
Dobozi and Pohl (1995) used the electricity consumption method
in 18 transition countries (five CEE and 13 FSU countries).
They came across the expected conclusions: that the unofficial
economy2 was on a rise in some countries more than in others.
Kaufmann and Kaliberda (1996) studied the unofficial economy
in the post-socialist economies. They provide an insight into
the causes and reasons for the development of the unofficial
economy in transition countries, as well as its consequences.
The unofficial economy is defined as the “unrecorded value added
by and deliberate misreporting or evasion by a firm or individual”
(Kaufmann and Kaliberda 1996, 3). They, following partly Dobozi
and Pohl (1995), use the “macroelectric” approach to estimate
the unofficial economy and come across similar findings: its
size is increasing. Lackó (1999) and Feige and Urban (2005)
provide further applications of the electricity consumption
method to the transition countries. They proposed several adjustments,
but found similar results. Besides, Feige and Ott (1999) gather
some of these, and some additional studies in a comprehensive
guide to study the underground activities in transition countries.
The Shadow Economy in Slovenia
Slovenia, although being a CEE country, was seldom covered in
the above-mentioned studies of shadow economy in the transition
countries. 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 socialist regime. Mainly, these focus
on rigid legislative framework, centrally planned and controlled
supply of goods (which seldom followed the demand), unstable
macroeconomic environment, and increasing tax and contributions
burden in the period of transition. The need for increased efficiency
and more market-oriented production enterprises has increased
whereas the bureaucratic obstacles were only partially 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 economy3 in Slovenia in the late 1980s via
survey of the human resource departments in companies. The results
revealed that up to 43% of employed participates in the shadow
economy, corresponding to above 38% of additional income. The
trend was estimated to go even higher in the following years.
Kukar (1995) estimates the size of the shadow economy4 with
the labour method (measuring the activity rate of labour force).
For the year 1993 it was estimated, that around 26% of labour
force (partially) participated in the shadow economy, amounting
to almost 9% of fully employed people, which on the other hand
means around 10% as a share of GDP. In this study, other authors
estimated the size of the shadow economy using other methods,
mainly by estimating the unregistered activities by subgroups
of activities (related to main industry sectors, such as construction,
tourism, agriculture), and they sum up to between 16.8% and
21.3% of the GDP5 in Slovenia in 1993.
Berglez (2000) and Flajs and Vajda (2004) present more recent
calculations. Berglez (2000) presented the monetary approach
and the size of the shadow economy in Slovenia was recapitulated
to be around 22% of GDP in 1996. Flajs and Vajda (2004) on the
other hand, followed the Eurostat’s exhaustiveness measures
and revised the GDP for the 1995-2002 period and the non-observed
economy (without illegal activities) on average amounts to around
6.5%. Furthermore, the European Commission (2004) estimated
that the undeclared work in Slovenia in 2003 produced around
17% of official GDP. The undeclared work seems to be in decline,
which was anticipated, as the transition was coming to an end,
and the entry into the EU was on a doorstep, which all meant
more efficient and stable macroeconomic environment, legal framework
and market economy as opposed to the situation in the early
stages of the transition.
Methods and the Data
Despite the whole range of methods, we have chosen three of
the indirect methods: the electricity consumption, currency
demand, and supply/demand of labour discrepancy methods. We
now turn to each of them separately.
Electricity Consumption
The electricity consumption method compares the dynamics of
electricity consumption and the GDP. The method has been mainly
applied to transition countries. The choice to use this method
has been defended by the fact, that “…electric power consumption
is a far better indicator of true economic activity in Eastern
Europe and the former Soviet Union than any of the officially
reported economic statistics that are widely used…” (Dobozi
and Pohl 1995, 18). They build this method on the assumption
that the aggregate economic activity (official and unofficial)
and electric power consumption move in lockstep (with an electricity-GDP
elasticity close to one), which is valid for market economies.
They apply this to the transition economies as well. As Koen
(1995) and Lackó (1999) point out, their assumption was not
as firm as it was hoped to be, since applications of the method
to other countries (e.g. Finland) gave unreasonable conclusions.
Nevertheless, Dobozi (1995) aims to defend the assertions that
electricity consumption is a good proxy for overall economic
activity in transition countries and provides reasons, why the
electricity-GDP elasticity should be close to one. Even though
transition economies did experience massive restructuring (and
that the increase in electricity consumption can be the sign
of higher electricity intensity of GDP), energy efficiency and
prices of the electrical energy did go up at the same time,
thus (approximately) cancelling each other out to give a unit
elasticity. Kaufmann and Kaliberda (1996) further discussed
the method in more details and presented different scenarios
of an electricity-GDP elasticity (less and greater than one,
and equal to one). Over more, Lackó (1999) incorporates household
electricity consumption and investigates the effects of different
energy intensity and the structural changes in countries and
Feige and Urban (2005) take an additional step further and analyse
electricity prices and share of private sector in GDP.
The data used are the electricity consumption in the period
1994-2003. They are obtained from the Statistical Office of
the Republic of Slovenia (SORS). As the households are believed
to be the main driving force of the shadow economy, parallel
to the total use, households’ electricity consumption was used
as well. The (annual) growth rates of the electricity consumption
are presented in Table 1. Our calculations are based on the
original, simple method by use the same assumption, namely that
the electricity-GDP elasticity is equal to one. The same data
source stresses, that both the electricity efficiency and intensity
in use have stayed more or less unchanged in the period 2000-2003.
This allows us to make the elasticity assumption more freely.
Figures in Table 1 for GDP in the corresponding period are gathered
from the same source.
Table 1: Growth rates of total and households' electricity consumption,
and of GDP for Slovenia for the period 1995-2003.
Source: Statistical Office of the Republic of Slovenia (2005).
Currency Demand
The second method, the currency demand, builds on the assumption
that hidden activities are conducted in cash (to leave as little
traces as possible) and higher cash demand reveals the underground
activities. In fact, monetary methods have different forms and
only one will be used at this point. This is the currency demand
or more appropriate, the high-value banknotes (demand) method,
which states, that whenever there’s an increase (above some
normal level) in circulation of high-value banknotes in the
economy, more shadow economy activities are taking place. Yet,
as Berglez (2000) stresses, this method is highly unreliable
and some upward trends in keeping the cash at home (in high-value
banknotes) in 1999 and 2000 in Slovenia are due to the implementation
of the value-added tax (VAT) and the anticipated “millennium
bug” problems. Furthermore, such demands for high-value banknotes
include also the illegal, black economy, which cannot be separated
for the estimation of the shadow economy alone. On the other
hand, the rate of inflation was constantly decreasing and the
macroeconomic (and political) stability has been increasing,
which reduces the demand for high-value banknotes (for “normal”,
legal reasons). Moreover, the banking sector has become more
developed providing new opportunities for non-cash transactions.
Supermarkets and some other shops have also introduced greater
opportunities for noncash payments and thus likely to reduces
the demands for high-value banknotes. Williams (2004) also stresses
that the method has certain drawbacks: besides already mentioned
use of cash for illegal, criminal economy and for the shadow
economy, shadow economy is not always using high-value banknotes,
and these transactions do not always necessarily use cash as
a means of payment. Nevertheless, this simple approach will
be used as a first step in applying monetary methods. Other
monetary methods, such as the transaction and cash-deposit ratio
approach, which go more deeply into the phenomenon, are not
the point of interest here.
At this point it is extremely hard to determine the “normal”
level of their circulation. Comparing the movements of high-value
banknotes to the movement of the inflation and possible deviations
between them might reveal some shadow economy activities. Moreover,
higher (official) economic activity also requires more cash
in circulation and consequently also the high-value banknotes.
Thus, referring to the nominal, current prices GDP growth, the
movement of the value share of the high-value banknotes should
be in line – otherwise, pointing to shadow economy.
Labour Discrepancy
The last method employed studies the differences between the
registered unemployment by the Employment Service of Slovenia
(ESS) and the Labour Force Survey (LFS) unemployment. This discrepancy
could in a certain way point to hidden activities, as registered
unemployment is in many views less “strict” than the ILO unemployment,
used in the LFS. By definition, the registered unemployment
by the ESS does not require from the unemployed not to be working
in the (past) reference period for any payment, whereas in order
for the person to be LFS unemployed, that person should not
have worked in the reference period for any payment, regardless
of the formality of the work. Having these definitions in mind,
someone, who is registered as unemployed at ESS can have an
undeclared work somewhere and is thus not unemployed according
to the LFS. Thus, this might be a simple approximation of the
shadow economy activities in the country. Yet, one needs to
have in mind, that such LFS activities can (and probably do)
include illegal activities as well, as people probably tend
to underreport these in surveys. At the same time, some of the
people, that are LFS unemployed, they are not registered as
unemployed at ESS. Yet, this share is normally very small. Table
2 reveals the differences.
Table 2: Registered and LFS unemploymend in Slovenia from 1993
to 2004
Source: International Labour Organisation (2005).
Elsewhere, Kukar (1995) proposed the measurement of the potential
participants in the shadow economy, which comprises inactive
population, which is capable of working and all the registered
unemployed. Furthermore, as Williams (2004) sums up, some methods
rely on the assumption, that shadow economy activities take
place (only) in few types of employment (e.g. self-employment,
second-job holding) and that the figure we are looking for can
simply be determined by the summing up of employment in these
categories and paying attention to unaccountable increases.
Once the share of the labour force, active in the shadow economy
has been determined6, it is necessary, in order to obtain the
share of shadow economy in GDP, to make an assumption about
the productivity of the shadow economy (with respect to the
official one). Normally, it is assumed, that that the productivity
in both economies is approximately equal7 and this is also our
assumption. The official total real GDP per employee was actually
taken to be the measure of productivity. This was multiplied
by the number of the people that are estimated to take part
in the shadow economy. These figures provide estimates for the
shadow economy.
Results
Different methods, relying on different data and assumptions,
provide rather different estimates of the size of the shadow
economy. This is also the case in this paper. At this stage,
the two of the applied methods turned out to be completely inappropriate,
as they give even negative figures for the share of the shadow
economy in GDP. These are the electricity consumption and currency
demand methods. In the first one, the original figures alone
show an unexpected relationship between the variables, as the
GDP growth is higher then the electricity consumption. Further
research is necessary to resolve this puzzle, which seems to
indicate less the shadow economy relations, but rather some
deeper structural changes in the electricity consumption in
the economy that are less electricity demanded. For example,
one of the significant sectors for electricity consumption in
the early transition was large-scale aluminium and steal production.
As these activities have shrinked considerably over the analysed
period, they are likely to bias our results. By this, it seems
that electricity consumption cannot be the single best physical
indicator of overall economic activity in Slovenia in the studied
period. In the second one, regarding the high-value banknotes
demand, only the 10,000 and 5,000 Slovenian tolars (SIT) banknotes
have been taken into account. Their movement (together) stabilised
in the last few years. However, comparing them to the nominal
GDP figures this provides negative estimates of the shadow economy,
which seems to be less appropriate measure for the Slovenian
economy, as it moved (during the analysed period) in the banking,
financial and other payments in directions that reduce the demand
for cash and high-value banknotes demands and payments. Therefore,
both of the applied methods have relatively strong assumptions
that seem to be inconsistent and less appropriate in the application
for the Slovenian economy during deeper economic restructuring,
harmonization and adjustments to the EU.
The labour discrepancy method, however, provides some more reliable
results. Nevertheless, there is a slight fluctuation present,
with a slow downturn at the end of the studied period (which
was anticipated). Table 3 compares the results, obtained by
this method.
Table 3: Results from the labour force method and comparison
to Flajs and Vajda(2004) estimates of the shadow economy in
Slovenia.
Concluding Remarks
The paper studies the shadow economy in Slovenia during the
last decade using three of the indirect methods: electricity
consumption, high-value banknotes and labour discrepancy methods.
Our work was based on assumptions and procedures from other
studies for the transition economies and this produced some
flaw outcomes. The results have shown that two of the methods,
namely the electricity consumption and the highvalue banknotes
methods, relying on original and simple assumptions, are inappropriate.
The reason for this lies primarily in the improper assumptions
and the structural and composition backgrounds of the phenomenon,
which has some dissimilarity with other transition countries.
The third method, the labour discrepancy method, however, provided
reasonable results, the shadow economy in Slovenia ranging from
6% to around 8% and on a downturn since 1999. These figures
are also in line with exhaustiveness revision by Flajs and Vajda
(2004), which are much less than the figures presented by others,
as in Berglez (2000) and European Commission (2004).
The methods applied in this paper are indirect methods for measuring
and understanding of the phenomenon. They approximate the presence
of the shadow economy, but do not reveal much of the background
of it. Therefore, further and more in-depth research needs to
be conducted to properly tackle and understand the shadow economy
under different circumstances, its causes and consequences.
Further research thus relies heavily on deepening the methodology,
first by setting more realistic assumptions in these models
and second, and even more importantly, applying other methods,
developed and proposed in literature. They, in turn, can bring
new evidence and reveal other aspects on the phenomenon. On
the other hand, they have a much higher demand for the data,
which was a limiting factor in this, start-up paper.
Obtaining the country-specific information is vital in proper
application of the methods, its assumptions and the data, and
interpretation of the results. Therefore, the electricity consumption
method used here should be improved by gathering the information
on electricity intensity by composition of consumption by main
users and efficiency of the country, and the prices of the electricity
for different users. Furthermore, econometric based analysis
to obtain the proper estimates should be conducted. Monetary
methods to be used in future require data on monetary aggregates,
interest rates and other, theoretically determined variables,
to estimate the currency demand function econometrically. Labour
discrepancy method also needs alternative approaches, proposed
by some other authors. Moreover, direct methods and other indirect
methods and modelling approaches would require most needed micro
data and background information on the country specific phenomenon
of shadow economy in Slovenia.
Finally, the importance of such an analysis lies in the ambiguous
effects of the shadow economy. The relevance of such study is
thus important for decision-making process. By studying the
shadow economy, better insights into the labour and some other
markets can be given. Consequently, this brings us closer to
the proper policy activities that use official data for their
decision-making processes.
Notes
1. Despite some clear objections by Williams (2004), the term
‘shadow economy’ will be used.
2. Even though the authors do not clearly distinguish between
the unofficial as opposed to the official economy, the former
includes activities, concealed from the authorities, thus giving
room for illegal activities as well.
3. Defined as productive activities, not reported to the authorities
but exclude ownproduction of households.
4. The definition is (again) in line with the SNA 1993 unregistered
activities within the production boundary.
5. After 9.5 percentage points of unrecorded activities (estimated
by surveys) have already been added to the registered GDP by
the SORS, the hidden unregistered activity is estimated at 7.3%
to 11.8%.
6. There is also an assumption that these active persons that
are registered as unemployed, are working full-time in the shadow
economy, whereby the officially employed are excluded from undeclared
work. This is a rather unrealistic assumption.
7. In fact, this assumption is not so weak. The negative effects
on productivity (hiding, no protection, etc.) are usually levelled
off by the positive effects, since people, working for themselves
and for the living, are normally more involved and productive
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Contact
Bojan Nastav
bojan.nastav@fm-kp.si
Štefan Bojnec
stefan.bojnec@fm-kp.si
Prepared for Managing the Process of Globalisation in New and
Upcoming EU Members Proceedings of the 6th International Conference
of the Faculty of Management Koper Congress Centre Bernardin,
Slovenia, 24–26 November 2005
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