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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.

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.

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 in the production process. References
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Bojan Nastav
Štefan Bojnec

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