The Contribution of Illegal Activities to National Income in the Netherlands

Abstract

Illegal activities such as smuggling, prostitution, and the production and sales of illicit drugs contribute to the national income of a country. In practice, however, they are not included in the statistics, because there are hardly any reliable estimates about these activities. Recently, Statistics Netherlands has started research into the share of illegal activities in the national income. This article presents the estimates for 1995 through 2008. The total contribution of illegal activities to the national income of the Netherlands increased from 1,800 million euro in 1995 to almost 3,500 million euro in 2008, equaling 0.6 percent of gross domestic product. Drugs accounted for more than 50 percent of the total income from illegal activities in 2001. In 2008, this was down to less than 40 percent, whereas finding illegal employment rose from about 10 percent in 1995 to 33 percent in 2008.

Keywords

illegal economy national accounts illegal drugs prostitution

Two well-known economic indicators are national income and economic growth. Both are derived from the national accounts, a set of statistics that describes the economic process of a country and its economic relations with the rest of the world. The national accounts are produced along the lines of a comprehensive set of definitions, laid down in the System of National Accounts (SNA) (European Commission et al. 2008) and the European System of Accounts (Eurostat 2010). These systems define a production boundary to distinguish between activities that contribute to national income and those that do not. Whether an activity is legal or illegal (i.e., forbidden by law) is not important in this respect, since illegal activities contribute to national income as long as they fall within the production boundary.

It is noteworthy for some illegal activities that they are often carried out with the consent of both parties. Another characteristic of transactions is that there are two flows. Goods or services go in one direction, money flows in the opposite. One exception is agricultural production for own use, which lacks two parties and a money flow but which contributes to national income. The same applies for the production of cannabis for one’s own consumption, so raising cannabis for one’s own consumption is an illegal activity that contributes to the national income.

Although income from illegal activities contributes to the national income according to the definitions in the SNA, for most countries they do not do so in practice. The main reason is that these activities are difficult to measure and that estimates are far from precise. Also, within the European Union (EU), there is a great deal of discussion on whether illegal activities should be included in the estimates. This is especially relevant as about three-quarters of the division of the costs of the EU over its member states is based on gross national income.

For Statistics Netherlands, this has been an incentive to research this area. The first estimates were by Werf (1997, 1998), who estimated the value added of the illegal economy in 1995 at less than 1 percent of (gross) national income (at market prices). Smekens and Verbruggen (2005) repeated and extended this research, with similar results. In 2010, Statistics Netherlands started a third study, sponsored by Eurostat. Again the conclusion is that the illegal economy is less than 1 percent of the national income.

This article presents a time series for the illegal economy in the Netherlands since 1995. As there is a lack of data, the estimates heavily rely on assumptions so they are surrounded by wide margins. Various figures include an indication of these margins.

Illegal activities are part of the broader defined nonobserved economy, often also called the shadow economy. The second section describes the various components one may distinguish within the nonobserved economy, as well as how component, illegal activities, contributes to national income. Sections three through nine have estimates for the various illegal activities. The tenth section has the final conclusions. The data necessary to reproduce the estimates can be obtained from the authors.

Illegal Activities in the SNA

Our research attempts to estimate the size of the illegal economy that meets the definitions of the SNA (European Commission et al. 2008). The SNA describes the economy as a circular process: production of goods and services leads to the generation of income, and this income is distributed and redistributed over the different actors in the economy and used for financing and spending, which again leads to the production of goods and services.

Important is the definition of goods and services that are included in this cycle, the so-called production boundary. The SNA includes all goods and services that are sold for money, all goods and services that are provided (for free) by government, the (imputed) rent of owner-occupied dwellings, own account investments, and the production of agricultural products for own consumption.

With respect to illegal activities, the SNA is very explicit. Illegal activities that are productive in an economic sense are included. Nevertheless, illegal activities have long been excluded from national income for several reasons. One reason is that the income from illegal activities is difficult to measure. Another reason is that illegal activities do not add to the welfare of a country, but rather subtract from it because of the many negative externalities, and therefore should not contribute to national income.¹

However, there are also two important reasons to include illegal activities in the estimates of national income (Organisation for Economic Co-operation and Development [OECD] 2002). First, there is the need for overall consistency of the national accounts of a country. Excluding illegal activities causes discrepancies between production and consumption, between income, spending and savings. If spending on, for example, prostitution is not recorded as part of household consumption, then there is an unexplained gap between household income and household savings. Second, the national accounts should be comparable over time and between countries. National incomes are only comparable if all activities, including prostitution and the drugs trade, are treated the same way. This is especially important for the EU where (gross) national income determines about half of the total financial contributions of the member states.

Illegal activities are part of the broader defined nonobserved economy. The latter includes all activities that according to the definitions contribute to national income, but for one reason or another are not included in the estimates of national income (figure 1). The nonobserved economy is often called the shadow economy. However, the term shadow economy is sometimes also interpreted as tax evasion or tax evasion plus illegal activities, which is a bit different. To avoid confusion, we do not use the term shadow economy.

Figure 1.

The relationship between illegal activities, hidden activities, the informal sector, underreporting and national income.

Illegal activities are the production of goods or services whose sale, distribution, or possession is forbidden by law such as drugs and prostitution.² Hidden activities are in themselves legal but do not comply with the tax legislation, for example, teaching extra lessons without paying tax on the income. Both illegal and hidden activities contribute to the national income as long as they are performed with mutual consent of both transaction parties. Another part of the nonobserved economy is the informal sector as defined by the International Labour Organisation (ILO; 1993): small units engaged in the production of goods and services, operating on a small scale, on a low level of organization, mostly without labor contracts and primarily meant to generate incomes to the persons concerned. There may be other activities that are not (fully) covered by the estimates of national income because of underreporting and lack of observation.

Government agencies, statistical offices, and academia do much research on measuring (parts of) the nonobserved economy. Pioneers among many others are Gutmann (1977, 1985), the Inland Revenue Service (1979), and Tanzi (1980) with estimates for the United States; Frank (1977, 1979) for Belgium; Feige (1979, 1981) and Dilnot and Moris (1981) for the United Kingdom; Mirus and Smith (1981) for Canada; Albers (1974), Kirchgassner (1983), Petersen (1982), and Langfeldt (1984) for Germany; Isachsen, Klovland, and Strøm (1982) for Norway; and Frey and Weck (1983, 1984) with estimates for Switzerland and sixteen other countries. Early research for the Netherlands can be found in Eck (1983), Broesterhuizen (1985), and Eck and Kazemier (1988). In the archives of Statistics Netherlands, there are estimates for the period 1921–38. A good review of the state of the art at the beginning of the eighties can be found in Tanzi (1982) and Gaertner and Wenig (1985).

Most early research was devoted to the nonobserved economy or to the hidden economy (tax evasion). An important exception is Simon and Witte (1982). Besides tax evasion, they describe many other aspects of the illegal economy such as illegal immigration, illicit drugs, fraud arson, illegal gambling, loan sharking, and prostitution. More recent examples of measuring (parts of) the underground economy are Enste and Schneider (2006); Feige and Urban (2008); Ciccarone, Marchetti, and Pavlovaite (2009); Feld and Schneider (2010); Pickhardt and Sarda (2011); Feld and Larsen (2012); and Pacolet et al. (2012). Also many statistical agencies attempt to measure the nonobserved economy and for many countries at least part of the nonobserved activities is included in the estimates of national income (United Nations Economic Commission for Europe 2008). However, there are not many recent reports on estimates of the income from illegal activities. A summary of the many methods used can be found in Kazemier (2006).

In the Dutch case, most of the unobserved activities are explicitly included in the estimates of national income (Centraal Bureau voor de Statistiek [CBS] 2008a) as is in many other countries (United Nations Economic Commission for Europe 2008). However, this is not the case for illegal activities. This does not mean that illegal activities are fully absent as they are already implicitly taken into account. An example is the production of cannabis. Electricity and other costs related to cannabis production are currently implicitly recorded as household consumption, and as such they contribute to the national income.

For an adequate estimate of the size of illegal activities that should contribute to the national income, we have to identify the relevant illegal activities. These are for the Netherlands³:

The production and trade of illicit drugs: The sale of cannabis in so-called coffee shops is tolerated in the Netherlands, but it is nonetheless illegal.

Prostitution: Since 2000, some forms of prostitution are legal in the Netherlands.

Fencing, the handling of stolen goods

Illegal temporary employment through employment agencies

Illegal gambling

Illegally copying software, games, movies, and music

Smuggling cigarettes

The following sections present our estimates of the contribution of these illegal activities to national income.

The Consumption, Production, and Trade of Illicit Drugs

Introduction

The most widely used illicit drugs in the Netherlands are heroin, cocaine, cannabis, and the party drugs ecstasy (XTC) and amphetamines. Estimates are made for production, imports, exports, and domestic consumption of these illicit drugs. The consumption of these drugs increased from about 565 million euro in 1995 to 735 million euro in 2008. This increase is almost entirely due to the rising consumption of cannabis: from 230 million euro in 1995 to 425 million euro in 2008. The consumption of heroin, cocaine, and ecstasy, measured in euros, remained fairly constant in this period. As a share of gross domestic product (GDP), it fell from 0.18 percent in 1995 to 0.13 percent in 2008. Compared to other countries this is relatively low. In the United States, the consumption of illicit drugs was 0.6 percent of GDP in 2000; in Italy it was 0.7 percent in 2008 (United Nations Office on Drugs and Crime [UNODC] 2011).

The consumption of illicit drugs is computed as the product of the number of drug users, the average consumption per user, and the street price of drugs. The number of drug users is taken from Trimbos (1999–2008) and StatLine, the database of Statistics Netherlands. For heroin and cocaine, a distinction is made between heavy addicts and other users. Missing data are completed by interpolation or extrapolation. The average use per drug user is taken from Korf (2003), Werf (1997), and Heijden (Decorte 2008). The street prices of illicit drugs can be found in Werf (1997), UNODC (2000–2010), Smekens and Verbruggen (2005), Niesink et al. (2006–2008), Neve et al. (2007), Trimbos (2007), and European Monitoring Centre for Drugs and Drug Addiction (EMCDDA; 2009). The average price has steadily decreased over time.

To calculate the value added of the drugs sector (also called the income from illicit drugs), it is necessary to make an estimate of domestic production, imports and exports, and the costs of production and trade. The following identity applies:

V A = (P - S_{P}) - K_{P} + T_{M} - K_{M} .

The income from illicit drugs (VA) can be split into income from domestic production and income from imports. The first equals the net value of the domestically produced drugs (P) minus seizures (S_P ) minus the costs of production (K_P ). The second equals to the trade margins on imported drugs (T_M ) minus the costs of transport and storage (K_M ).

Heroin and Cocaine

Heroin and cocaine are not produced in the Netherlands, so the value added of heroin and cocaine equals the trade margins on imports minus the costs of transport and storage. Data on these costs are not available. However, it is reasonable to assume that the costs of production and trade are not high, while the risk premium on trading heroin and cocaine is high. Hence, we cautiously assume that the costs do not exceed 10 percent of the trade margins, or

V A = T_{M} - K_{M} = 0.9 \times T_{M} .

The trade margins in this case are the value of the domestic consumption (C_M ) of imported heroin and cocaine plus the trade surplus, that is, the difference between the values of the exports (E_M ), imports (M), and confiscated imports (S_M ):

T_{M} = C_{M} + (E_{M} - M - S_{M}) .

The export value is the difference between the volume of the imports (m) minus the volumes of the seizures (s_M ) and domestic consumption (c_M ),⁴ multiplied by the average export price of heroin and cocaine (p_E ), so

E_{M} = p_{E} \times (m - s_{M} - c_{M}) .

The export prices are taken form the World Drug Report (UNODC 2000–2010). As the destination of the exports is unknown, we use the average street price in the EU.

The imports are deduced from the seizures (s_M ), the risk of being caught or seizure rate (R_M ), and the import price (p_M ):

M = p_{M} \times m = p_{M} \times \frac{s_{M}}{R_{M}} .

So imports minus seizures (M_−S ) are

M_{- S} = p_{M} \times (m - s_{M}) = p_{M} \times \frac{(1 - R_{M})}{R_{M}} s_{M} .

The import prices are taken from the World Drug Report (UNODC 2000-10). The seizures come from the EMCDDA (2009). As the seizures strongly fluctuate over time, we use a five-year moving average.

Part of the heroin and cocaine that enters the Netherlands is not destined for the Netherlands. If the reexported heroin and cocaine are not owned by a Dutch resident and no change of ownership has taken place involving a Dutch resident, these reexports are considered transit trade. By definition, profits from transit do not contribute to national income. Therefore, transit (m_E ) should be deducted. Transit is calculated as a fraction (q) of total exports. There are no data on how much heroin and cocaine is traded in transit. The impression of occasional reports by the customs and police on seized drugs in mainport Rotterdam and other transit locations is that the Netherlands are a transit country for illicit drugs. Therefore, it is assumed that a fair but not too large part of export is transit, and q equals 0.5 for all years:

m_{E} = q \times (\frac{(1 - R_{M})}{R_{M}} \times s_{M} - c_{M}) .

No information is available on the seizure rate. Werf (1997) used a 25 percent rate in 1995; Smekens and Verbruggen (2005) assumed 15 percent in 2001. Neither is based on facts. Also, there is no indication that the intensity or effectiveness of the investigations has changed very much between 1995 and 2001, so there is no justification for this decrease in seizure rate. We assume a constant seizure rate of 15 percent for 1995 to 2001. In 2002, however, things changed (Trimbos 2009) when the preflight checks were introduced. In 2003, Schiphol Amsterdam Airport started 100 percent checks for flights from high risk countries. In 2004, body scanners were installed. This increase in investigation intensity is visible in the time series of seized cocaine and heroin with a 15 percent increase between 2002 and 2003. Therefore, we set the seizure rate at 17.5 percent in 2002 and at 20 percent in 2003.

The import prices are taken from the World Drug Report (UNODC 2000-10). These are rather constant with a peak in 2001 and 2002. Formula (2) now reduces to

V A = 0.9 \times \{(p_{E} - p_{M}) \times [\frac{(1 - R_{M})}{R_{M}} \times s_{M} - m_{E}] + (p_{C} - p_{E}) \times c_{M}\},

with p_C being the average street price of heroin and cocaine in the Netherlands and c_M the consumption of these drugs in (kilo)grams. The value added is generated by the difference between the import and export prices and the difference between the domestic and the export price.

Figure 2 shows the value added of the heroin and cocaine trade that contributes to the national income of the Netherlands. The assumed seizure rate is crucial. The lower the seizure rate, the higher the value added estimates. To show the influence of this assumption, figure 2 also shows the outcomes for alternative assumptions: a high with a seizure rate of 10 percent until 2002 and 15 percent thereafter, and a low with a seizure rate of 25 percent for the whole period.

Figure 2.

The value added of illegal production and trade in the Netherlands, 1995–2008.

According to the calculations, the heroin and cocaine trade in the Netherlands is less than 0.05 percent (low variant in 2007 and 2008) to almost 0.3 percent (high variant in 1998) of the GDP. The sudden decrease since 1998 is caused by a sudden change of the terms of exchange in that year. Until 1998, the export price was about twice the import price. The ratio was 1.6 in 1998 and steadily declined to 1.4 in 2008.

Ecstasy and Amphetamines

Almost all ecstasy and amphetamine tablets sold in the Netherlands are produced in the Netherlands. Therefore, it is assumed that the imports of these illicit drugs are nil. The value added (VA) of the production and sales of these drugs then equal domestic production (P) minus seizures (S_P ) minus production costs (K_P ). The latter include the costs of storage and transport:

V A = (P - S_{P}) - K_{P} .

The estimates of the production volume (p) of ecstasy and amphetamines are based on the seizures (s_P ) and the risk of detection (R_P ), or

p = \frac{s_{P}}{R_{P}} .

Data on seizures can be found in the annual report of the Kernteam Zuid Holland/Unit Synthetische Drugs (2003) and Neve et al. (2007). As with heroin and cocaine, we use five-year moving averages to compensate for large fluctuations in the seizures. For 2006 and 2007, we assume that the seizures were as large as in 2001.

Again, little is known about the rate of detection. Like Van der Werf (1998), we assume 10 percent in 1995 gradually increasing to 15 percent in 2001 (Smekens and Verbruggen 2005) and 20 percent in 2006 because of the steadily increasing investigation efforts (Ministry of Justice 2001).

There is much evidence that the production of ecstasy has fallen, as confiscations were halved from 2002 to 2007/2008, while the detection efforts were maintained. Also, the production of these drugs has spread to other countries (e.g., Canada and Australia), so the Netherlands plays a smaller role in this market (Neve et al. 2007; Trimbos/WODC 2009). The Kernteam Zuid-Nederland/Unit Synthetische Drugs (2003) and the EMCDDA (2009) also identify this development.

The cost of production and sales per tablet (p_P ) of ecstasy and amphetamines consists of laboratory costs, transport costs, and storage. In 1995, these costs were 11 cents per tablet (Werf 1997). Smekens and Verbruggen (2005) assumed that these costs had doubled by 2001. In 2002, the production costs would have been 25 cents per tablet (Ministry of Justice 2001). For the years in between, we interpolated; for later years, we assumed that the costs remained 25 cents per tablet.

The value added of the production and trade in ecstasy and amphetamines is

V A = (p_{E} - p_{P}) \times \frac{(1 - R_{P})}{R_{P}} \times s_{P} + (p_{C} - p_{E}) \times c_{P} - p_{P} \times s_{p} .

The value added is generated by the difference between the export price and the production costs and the difference between the domestic price and the export price. The production value of the confiscated tablets is then deducted.

Again, the estimates (see figure 2) strongly depend on assumptions of the seizure rate. Therefore, figure 2 also shows the outcomes for a seizure rate rising from 10 percent in 1995 to 15 percent in 2008 (high variant) and for a seizure rate of 25 percent during the whole period (low variant).

The value added of the production and trade of ecstasy and amphetamines fluctuates between less than 0.05 percent (low variant, all years) to 0.1 percent (high variant in 2001) of GDP.

Cannabis

The production and use of cannabis is illegal in most countries, but in the Netherlands possession and sales in “coffeeshops” of small quantities are tolerated. One advantage of this policy is that crime related to the use and sales of cannabis is partly reduced. The negative effects include drugs tourism, which has led to the tightening of the policy of tolerance in recent years (Decorte 2008; Korps Landelijke Politiediensten [KLPD] 2008).

Much of the cannabis consumed in the Netherlands is produced domestically, the so-called nederwiet. The total production of nederwiet is not known, but the confiscations are. This, plus the known average yield per plant and an assumption on the number of harvests per year, allows us to estimate the seized production capacity. The latter can be transformed into an estimate of the total domestic production capacity (q_P ):

q_{P} = \frac{3 \times s_{P}}{R_{P}},

with s_P being the five-year moving average of the number of seized cannabis plants times the potential yield per harvest per plant. Following Korf (2003), it is assumed that there are three harvests a year. R_P is the share of the cannabis stands dismantled. Heijden (2006) estimates a detection rate of 30 to 50 percent. We assume 40 percent.

The actual production (p) of nederwiet equals the production capacity minus the cannabis that could not be produced because of plantations were dismantled. The latter is half of the potential yearly yield of the confiscated cannabis plants (0.5 × 3 harvests × s_P ), as one may expect that the detection efforts and seizures are equally distributed over a year. The actual production also equals the domestically consumed nederwiet (c_P ) plus the exports of nederwiet (e_P ) and the confiscated ready to harvest yields, on average 0.5 × s_P :

p = q_{P} - 1.5 \times s_{P} = c_{P} + e_{P} + 0.5 \times s_{P} .

A large part (f_P ) of the consumption of cannabis (c) in the Netherlands is nederwiet. Spapens (Decorte 2008) mentions 50 percent for the mid-1990s; Jansen (Decorte 2008) states that this percentage had increased to 80 percent by the end of the century and has remained high ever since. We use the same percentages. The domestic consumption of cannabis is calculated autonomously. Nederwiet consumed by nonresidents (drugs tourists) does not count as consumption in the Netherlands but as export to Belgium, France, Germany, and elsewhere.

To estimate the value added of the production and sales of nederwiet (VA), we need the domestic consumption price (p_C ), the export price (p_E ), the costs of production, and the cost of sales via coffee shops. The cost of production is estimated at 20 percent of the consumption price of nederwiet. The sales costs via coffee shops are estimated at half the difference between purchasing and selling. Furthermore, it is assumed that the purchase price for coffee shops is equal to the export price of nederwiet. The market share of coffee shops (f_C ) in the sales of nederwiet is known for 2001, 2003, and 2007 (Trimbos 1999–2008) and is 40 percent on average. This percentage is assumed to be valid for the whole period:

\begin{aligned} V A = (p_{E} - 0.2 \times p_{C}) \times p + (p_{C} - p_{E}) \times f_{P} \times c \\ - 0.2 \times p_{C} \times 0.5 \times s_{P} - 0.5 \times f_{C} \times (p_{C} - p_{E}) \times f_{P} \times c . \end{aligned}

The value added of nederwiet equals the net profit in case all production less seizures was exported (first part of equation 14) plus what domestic sales yield more than sales abroad (second part of equation 14) minus the costs of the confiscated stands (third part) minus the costs of sales via coffee shops (fourth part).

Like the estimates earlier, the estimates for the value added of the production and trade of nederwiet (see figure 2) depend on the assumptions about the seizure rate, in this case the share of the production capacity dismantled by the police. To show the sensitivity of the estimates for this assumption, a high variant with a seizure rate of 30 percent and a minimum variant with a seizure rate of 50 percent are included.

According to the calculations above, the value added of the production and sales of nederwiet equals 0.05 (all variants, first years) to less than 0.2 percent (maximum variant in 2008) of GDP.

For the imports of cannabis, the same method applies as for the imports of heroin and cocaine. For the whole period, a seizure rate of 30 percent is assumed. The sales costs of cannabis sold via coffee shops are calculated in a similar way as for nederwiet. As with heroin and cocaine, the export costs of cannabis are fixed at 10 percent of the difference between the export and import price. As with heroin and cocaine, transit is assumed to be half of all cannabis that leaves the country.

The estimates are shown in figure 2, again with a high variant (with a 20 percent seizure rate) and a low variant (with a 40 percent seizure rate). A comparison of figures for nederwiet and cannabis produced abroad shows that there has been a substitution between both.

Summary

The value added of the production and sales of illicit drugs has increased from about 925 million euro in 1995 to almost 1325 million euro in 1998 and has been fluctuating between 1,150 and 1,300 million euro ever since. This constitutes a decrease from about 0.35 percent of GDP in the late 1990s to little over 0.20 percent in 2008. The main reasons are the steadily decreasing prices of illicit drugs since 1999 and the deteriorating terms of trade for heroin and cocaine. Also ecstasy production decreased due to more competition from abroad. Finally, the increased detection activity in heroin and cocaine made the Netherlands less attractive as a transit country for these illicit drugs.

The size of the illicit drugs market in the Netherlands does not differ much from its equivalent in Australia. There its size is estimated at 0.2 percent of GDP in 1998 and 0.3 percent in 2003 (UNODC 2011). Research for Austria yields almost similar results: 0.13 percent of GDP in 2004 (Schwarzl 2009). A similar decrease of the relative size of the illicit drugs market over time is found for Sweden and for the United Kingdom. In Sweden, the value added of narcotics decreased from 0.15 percent of GDP in 1995 to 0.07 percent in 2006 (Magnusson Wärmark 2008). In the United Kingdom, it went down from 0.5 to 1.1 percent in 1996 (Groom and Davies 1998) and to 0.4 to 0.6 percent in 2003/2004 (Pudney et al. 2006).

Prostitution

On October 1, 2000, brothels and sex clubs became legal in the Netherlands, provided that they have a license. These licenses are granted by the municipalities. The police are responsible for monitoring compliance with conditions. A major goal of lifting the ban on brothels was to combat trafficking, involuntary prostitution, and prostitution involving minors (Ministry of Foreign Affairs 2005; Utrecht City 2009).

As many prostitutes were afraid of losing their anonymity, they fled to the less visible parts of the sex industry. They became escorts, for which no permit was required until 2008, started working on the streets, or working from home. The law created a division into a visible and an underground sex industry.

Reliable information on the number of prostitutes, prices, earnings and the number of clients is virtually unavailable, even for legal prostitution. Mens and Van der Helm (1999) and Lehti (2003) estimated that there were 20,000 to 30,000 prostitutes at by the end of the century. Prices did not change very much until the legislation in 2000 (Slot and Kruize 1999), and increased sharply with the introduction of the euro in 2002 (www.volkskrant.nl, Prostituee prijst zichzelf uit de markt), reaching about 50 euro per client by 2008 (Flight and Hulshof 2009).

Although separate estimates for legal brothels, illegal brothels, clubs, escorts, street prostitution, and prostitution from home should be made, the available data do not allow this. Therefore, we estimate prostitution as a whole.

The turnover of the prostitution industry (P) is the product of the number of prostitutes (n_pros ), the number of clients per prostitute (n_clients ) and the price per client (p):

P = p \times n_{p r o s} \times n_{c l i e n t s} .

The prices are assumed to be 50 euro per client in 2008 and rising in tandem with the consumer price index, except for 2002. With the introduction of the euro, prices probably rose by at least 10 percent to a multiple of 5 euro. The number of prostitutes was fixed at 25,000 in 1999, and for other years follow the trend of the male population of fifteen to sixty-five years. The number of clients is set at 20 a week, and working weeks at 40 a year.

Part of the turnover is generated by providing prostitution services to people from abroad. In the national accounts, these are booked as exports (E).The remainder is consumed by Dutch residents, called domestic consumption (C):

P = C + E .

Since 2002, about half of the clients of window prostitutes in Amsterdam have been nonresidents (Flight and Hulshof 2009). The same applies for escorts (Eysink Smeets et al. 2007). Although, or because, one-third of the prostitution industry is concentrated in Amsterdam, it is not representative for the prostitution industry elsewhere in the Netherlands. Furthermore, reports by institutes on sexually transmitted diseases in the Netherlands suggest that the number of nonresident clients of prostitutes outside the Amsterdam area is much lower (Mens and Van der Helm 1999; Trienekens et al. 2012). We therefore assume that prostitutes outside Amsterdam only receive 10 percent customers from abroad. The average share of customers from abroad (f_e ) has been 23 percent since 2002. Eysink Smeets et al. (2007) argue that this share was higher before 9/11 and the economic downturn. Therefore, we assume an average share of 25 percent in the period 1995–2001.

The value added (VA) of the prostitution industry is the sum of the domestic consumption (C) and exports minus imports (M) minus costs (U). Imports are the prostitution services provided by foreign prostitutes who remain less than a year in the Netherlands plus the consumption of prostitution services by Dutch residents abroad. The latter is negligible; the first is not:

V A = C + E - M - U .

Many prostitutes in the Netherlands are nonresidents. Increased international mobility has led to an increase in nonresident prostitutes, especially after the recent accessions of new countries to the EU. Eysink Smeets et al. (2007) find that many women from the Balkan countries, Romania, and Bulgaria are working as escorts. Lehti (2003) estimates that about two-thirds of the prostitutes are foreign. Visser, Oomens, and Boerman (2000) state that most foreign prostitutes have no work permit and that half work in the Netherlands for less than a year and either go back home or start working in another country.

Based on the preceding information, we assume that one-third (f_M ) of total turnover in 1999 can be considered as imports. Because of the expansions of the EU in 2004 and 2007, this share is assumed to be 35 percent since 2004 and 37 percent since 2007.

The costs or intermediate consumption of the prostitution industry are the costs of the prostitutes themselves and the costs of their managers or pimps. The first relates to clothing, condoms, and travel expenses by escorts. Like Heij (2007), we assume that in 2001 prostitutes spent 125 euro a month on clothes and 0.5 euro on condoms per visitor. For escorts, we assume 7 euro per visit. Following Eysink Smeets et al. (2007), the escort sector is assumed to be 15 percent of the prostitution sector and that escorts have ten clients a week. The consumer price index is used to calculate these figures for the other years. The costs of the managers or pimps mainly relate to the rent and costs of rooms and brothels. It is assumed that half of the turnover of the prostitutes is paid to the managers and that half of that is intermediate consumption (Smekens and Verbruggen 2005).

The value added of the prostitution industry rose from 350 million euro in 1995 (0.11 percent of GDP) to a little over 500 million euro in 2008 (0.09 percent of GDP), which is less than in Austria (0.17 percent of GDP in 2004; Schwarzl 2009) and the United Kingdom (0.2 percent of GDP in 1996; Groom and Davies 1998) but far more than in Sweden (0.02–0.03 percent of GDP in 1995/2006; Magnusson Wärmark 2008). As our estimates are influenced by a large number of assumptions, we also show some alternative calculations.⁵

An important assumption is twenty visitors a week per prostitute. This number may well be higher. An alternative calculation is made assuming twenty-five visitors per week. Another is the price per visit. Dekker, Tap, and Homburg (2006) found that one-third of all prostitutes they interviewed earned less than 500 euro a week, and quotes a prostitute who is willing to provide her services for 15 euro. If this is representative of the whole sector, the average price used in our calculations may be too high. Therefore, figure 2 also presents an alternative with average prices that are 20 percent lower. According to these alternatives, the value added of the Dutch prostitution industry in 2008 ranged from 400 and 660 million euro.

Fencing

Earlier, we stated that theft does not contribute to national income, but fencing does. The sale of stolen goods is a transaction with mutual agreement that may generate income. We distinguish three types of transactions. The first is the sale of stolen goods by the thief to a consumer; this is comparable to the sale of secondhand goods within the sector households and does not generate value added. The second is the sale of stolen goods by the thief to a company; for that company, it is intermediate consumption and as a consequence its profits may diminish. We assume that the extent of this phenomenon is limited and therefore negligible. The third possibility is that stolen goods are sold via a receiver. The value added, consisting of the profit generated by the receiver, is estimated in the following.

The value added (VA) of fencing equals the trade margins (T) minus costs (U). As with illicit drugs, the costs are fixed at 10 percent of the trade margins. To estimate the trade margins, we distinguish four categories of stolen goods: motor vehicles excluding cargo, shoplifting, goods stolen from private individuals excluding motor vehicles, and goods stolen from companies excluding motor vehicles and shop lifting. The trade margins generated by fencing these goods are, respectively, T_v , T_s , T_p , and T_c . Shoplifting is usually for personal use and will therefore be disregarded:

V A = T - U = 0.9 \times (T_{v} + T_{p} + T_{c}) .

The trade margins on motor vehicles are estimated by multiplying the value of the nonretrieved motor vehicles (V_m ) with the profit margin (m_v ) of the receiver:

T_{v} = V_{v} \times m_{v} .

The value of nonretrieved motor vehicles equals the number of nonretrieved vehicles multiplied by the average market price of used cars. This is done for both motor vehicles stolen from individuals and from companies. The latter are split into light and heavy vehicles (Blaauw 2006, 2009). The average value is estimated based on data for 2003 (Rijksdienst voor het Wegverkeer [RDW] 2004). The other years are estimated using the consumer price index for new cars and occasions. The profit margin for the receiver is fixed at 50 percent (Smekens and Verbruggen 2005).

The margin on goods stolen from private individuals is the product of the market value of these goods, the percentage of the stolen goods sold via a receiver, and the profit rate:

T_{p} = V_{p} \times f_{p} \times m_{p} .

The market value of these stolen goods (V_p ) is considered to be 40 percent of the financial loss because of theft. Data on the latter can be found in Statistics Netherlands (CBS 2007, 2008b). Again, the profit margin of the receiver (m_p ) is fixed at 50 percent. This leaves the other 50 percent, being 20 percent of original value of the stolen goods, to the thief. This is in line with the findings of Gruter and Van de Mheen (2007) that a thief gets about 20 to 40 percent of the original value. The percentage of stolen goods sold via a receiver (f_p ) is assumed to be 67 percent (Van der Werf 1997).

The estimate of the trade margins on goods stolen from companies follows the same reasoning. The market value of the stolen goods (V_c ) is 40 percent of the financial losses because of burglary. Data on burglary in five industries can be found in Visser, Frederikse, and Hermans (2002) and Wetenschappelijk Onderzoek- en Documentatiecentrum (WODC 2009). These figures are raised to the whole economy. The years before 2001 are extrapolated by means of the number of burglaries in companies (CBS 2008b). As before, the percentage of goods sold via a receiver (f_c ) and the profit margin (m_c ) are fixed at 67 and 50 percent, respectively:

T_{c} = V_{c} \times f_{c} \times m_{c} .

Figure 2 presents the estimates of the consumption and exports of stolen goods (trade margin only) and the value added of fencing in the Netherlands. The profit margins and the percentage of stolen goods sold via a receiver may well be significantly higher or lower. If we assume a margin of 10 percent point, the value added might be about 40 percent higher or lower.

The value added of fencing decreased between 1995 and 1998 and has increased ever since as more cars were stolen from individuals. As a percentage of GDP, it decreases from 0.05 percent in 1995 to 0.03 percent in 2008.

The consumption of stolen goods is calculated as the value added of stolen goods minus exports plus imports. Motor vehicles are a very popular export product (Gruter and Van de Mheen 2007). Because of lack of data, these exports are assumed to be 75 percent of the trade margin (Smekens and Verbruggen 2005). Information on the imports of stolen goods is even more limited. These are assumed to be zero.

Illegal Temporary Employment Provided by Employment Agencies

The “Flexwet” of 1999 made it possible for employers to attract a flexible workforce and provide legal certainty to flex workers. The resulting increase in the administrative burden and workers’ rights were incentives for employers to circumvent this law (Zuidam and Grijpstra 2004) through illegal employment mediation. In 1998, compulsory licensing for temporary employment agencies was lifted, resulting in an increasing number of agencies. A significant number became involved in illegal mediation.

In order to separate the legal from the illegal employment agencies, registers for bona fide temporary employment agencies were set up. However, these were not binding (Bolhuis, Dijkema, and Engelen 2006). In 2009, the legislation for temporary employment agencies was extended so that both the employer and the agency are held responsible for the working conditions of the temporary worker.

Zuidam and Grijpstra (2004) distinguish three types of illegal mediation: people staying in the Netherlands legally but without a work permit or who work more hours than allowed, or work for less than the minimum wage; temporary labor migrants (mostly from Eastern Europe); and people staying in the Netherlands illegally. Research voor Beleid (Zuidam and Grijpstra 2004; Bolhuis, Dijkema, and Engelen 2006; De Bondt and Grijpstra 2008) estimated an increase in illegally mediated working years (fulltime equivalents) in the period 1999–2008. These estimates are used to construct time series for 1995 through 2010.

The value added (VA) of the illegal mediation of temporary workers is the difference of the gross value or turnover (P) of this mediation minus the costs (U), for example, the costs of transporting the workers to the work place. The latter are assumed to be 5 percent of the gross value. There are no exports and imports. People working for temporary employment agencies are on the payroll of the agency. This is a difference with prostitution. Prostitutes are considered self-employed, whereas illegally mediated people are employees.

The gross value of illegal mediation of temporary workers is the product of the number of mediated working years (Y), the number of hours per working year (H), and the hourly wage (W) plus mark up or profit margin (T). The hours per working year are fixed at 1,872 hours for the whole period, being 36 hours a week, 52 weeks a year. Part of the work concerned is seasonal work (agriculture), but usually seasonal workers make long working days and weeks:

V A = P - U = 0.95 \times (W + T) \times Y \times H .

The wages and profit margin are based upon Zuidam and Grijpstra (2004) and Smekens and Verbruggen (2005). They are set at 5 euro/hour in 2001 and 100 percent in all years. The wages in other years are assumed to follow the collectively agreed wage changes (www.statline.nl). The illegally mediated working years are taken from Zuidam and Grijpstra (2004); Bolhuis, Dijkema, and Engelen (2006); and Bondt and Grijpstra (2008). They provide estimates for four years: 1999, 2004, 2006, and 2008. For the other years, the illegal mediated working years were interpolated or assumed to follow the development of the volume of (legal) labor, as published by Statistics Netherlands.

Like all estimates presented in this article, there is much uncertainty about the validity of the figures. Therefore, figure 2 also shows the estimates if the number of illegally mediated working years were 20 percent higher or lower.

Although the Flexwet was already introduced in 1999, the estimates show a break after 2004. This coincides with Poland, the Baltic countries, Czech Republic, Slovakia, Hungary, Malta, and the Greek part of Cyprus joining the EU. People from these countries were not allowed to work in the Netherlands, but many did. As a percentage of GDP, the value added of illegal employment mediation tripled from 0.06 percent in 1995 to 0.19 percent in 2008.

Illegal Gambling

Illegal gambling is estimated for four types of games: illegal casinos and live poker, illegal lotto and pools, commercial bingo, and e-games. Illegal casinos hardly exist anymore. The illegal lotto and pools are lotteries, for which unlicensed operators sell tickets. Commercial bingo can be illegal if the prices exceed the allowed maximum or if bingo is the main activity of the company. E-gaming is playing interactive games of chance on the Internet, which can be digital casinos, slot machines, or poker.

For each activity, the value added (VA) is calculated as domestic production (P) minus costs (U). Production equals consumption (C) plus exports (E) minus imports (M). Imports and exports are only relevant for e-games. The amounts Dutch residents spent on illegal bingo, lotto, and so on, abroad are assumed to be negligible. The same applies for nonresidents playing these games in the Netherlands:

V A = P - U = C - M + E - U .

Most people who play gambling games lose all or part of their bets. Consistent with the definitions of the National Accounts, these net losses (bets minus payouts) are considered as the consumption of gambling games. In 2000, the net gaming receipts of illegal casinos in the Netherlands were 136 million euro, and the number of illegal casinos was rather constant until that year (Donker, van Gemert, and Homburg 2001). The Ministry of Justice and the tax authorities set up a special project, called Joker, and have closed down many illegal casinos since 2000. In 2001, the net gaming receipts fell to 50 million euro (Pemberton et al. 2002). Currently, almost all illegal casinos are closed down (Homburg and Oranje 2009).

Live poker still exists, although it is no longer played in illegal casinos. Tournaments have moved to other places. The net gaming receipts were 4.7 million euro in 2008 (Homburg and Oranje 2009). For the years before this figure is extrapolated using time series of the highly educated male population aged fifteen to thirty-five, as live poker is mainly played by this part of the population.

Donker, van Gemert, and Homburg (2001) also made an estimate for illegal lotto, pools, and bingo in 2000. According to Wilkinson, Vunderink, and van der Heijden (2008), the demand for these games is rather stable. Homburg and Oranje (2009) present some characteristics of the people playing these games. Lotto and pools are favorites with men and women aged thirty-five to sixty-five with secondary education or less while bingo is played mainly by thirty-five- to sixty-five-year-old women with secondary education or less. Time series of these populations are used to estimate the trend for these games.

The net receipts of e-gaming for 2001–2005, 2007, and 2008 are estimated using data from the Nationaal Kenniscentrum Kansspelen (downloaded from www.nationaalkenniscentrumkansspelen.nl, now defunct). These include the stakes paid by the players. Half of the stakes is paid out, so net receipts are also 50 percent (Homburg and Oranje 2009). About 45 percent of the e-games played in the Netherlands are Dutch (KLPD 2003). The remaining are imports of illegal gambling services. This 45/55 distribution is used for all years. No information is available on nonresidents playing e-games provided by Dutch companies. Therefore, these are kept at zero until information becomes available.

According to Donker, van Gemert, and Homburg (2001), the intermediate use for illegal casinos and live poker is 50 percent of the net receipts. As lotto, bingo, and e-games have little or no fixed costs for hiring a location or personnel (in contrast to illegal casinos and live poker), we assume that the intermediate costs are much lower for lotto and bingo, and particularly low for e-games. For lotto we assume 10 percent, for bingo 10 percent, and for e-games 5 percent. The value added of illegal gambling (see figure 2) amounts to between 0.05 percent of GDP in 1995 to 0.02 percent in 2002/2007. This is similar to the estimates for Sweden (Magnusson Wärmark 2008). The dip in value added after 2000 is caused by the closure of many illegal casinos. The rise after 2005, and especially after 2007, is due to e-gaming.

As exports are neglected, the estimates for e-games must be considered as a lower bound. Just as about half of the money spent on e-gaming by residents is spent on illegal e-gaming abroad, it is quite possible that half of the revenues of Dutch e-game companies comes from abroad. For the other estimates, a 20 percent margin is not unlikely.

Illegal Copying of Software, Games, Movies, and Music

Not all illegal copies of software, movies, and music contribute to the national income. Only those that are sold for money do. The “value” of copies for people’s own use, for friends, or for exchanges through the Internet that are not paid for, do not count. The former is similar to fencing; the latter is similar to theft.

The number of illegal copies of music, movies, and games sold (c_m ) is calculated as a percentage (f_m ) of the total (legal plus illegal) volume sold. The legal sales (c_m, legal ) are taken from www.npvi.nl. According to Breininfo (2003), the number of illegal copies in 2002 was one-fifth of the legal ones, of which 40 percent was sold professionally. So the number of illegal copies sold was 8 percent of the legal ones. Based on data from www.anti-piracy.nl, this was 11.6 percent for 2004 and 2006. The turnover (P_m ) is the number of illegal copies sold times the price of an illegal copy (p_m ). According to anti-piracy.nl (2004, 2006), the price of an illegal copy was 5.75 euro in 2004 and 6.00 euro 2006. For 2005 the price is interpolated, for the other years the price is extrapolated using the consumer price index of blank media. Or

P_{m} = c_{m} \times p_{m} = \frac{f_{m}}{(1 - f_{m})} \times c_{m, l e g a l} \times p_{m} .

The production of illegal copies of computer software (P_s ) is estimated at 10 percent of the value of this software, if it were legal (C_s, _legal). The original value, which they consider as the financial loss because of illegal copying, is estimated by Business Software Alliance (BSA 2002, 2007) and BSA and International Data Corporation (IDC; 2010):

P_{s} = 0.1 \times C_{s, l e g a l} .

Imports and exports are assumed to be of equal size and are therefore neglected. Based on impressions from the previously mentioned reports, the cost of production (U) are assumed to be rather low. Therefore, we fixed them at 10 percent of the production value. The value added (VA) of illegal copying is

V A = P_{m} + P_{s} - U = 0.9 \times (P_{m} + P_{s}) .

The estimates of the value added of illegal copying are presented in figure 2. The sharp increase after 2001 is caused by the hike in illegally copied software as shown in the figures of BSA (2002, 2007). The drop after 2004 is due to the sliding value of the dollar, resulting in lower prices for software in Europe.

Breininfo, anti-piracy.nl, and BSA have no reasons to underestimate the illegal copying of games, movies, and music, so their estimates for 2002, 2004, and 2006 should be reliable or even an overestimate. The margin will be larger for earlier and later years. Alternative calculations were made assuming that the number of illegal copies sold was between 6 and 12 percent of the number of legal copies in 1995, reaching 10 to 12 percent in 2002–2006 and expanding to 10 to 13 percent by 2008. A margin of 5 percentage points was considered for the production of illegal copies of computer software. The results of these calculations are shown in figure 2. In terms of GDP, illegal copying is negligible (0.01 percent).

Smuggling of Cigarettes

The differences in excise duties between countries are a major cause of smuggling of tobacco products. Duties in the Netherlands are comparatively low so cigarette smuggling is not all that prevalent.

The domestic consumption of illicit cigarettes (C) is the product of the number of illicit cigarettes consumed (c) and their price (p_C ). The latter is fixed at half of the price of legally sold cigarettes, based on an article on smuggling in newspaper the BN DeStem (2009). The price of a packet of twenty-five Marlboro cigarettes is used as reference.

The number of illicit cigarettes consumed is unknown. Although experts (e.g., Dijck 2007; Integis 2008; Broekhuis and Rotteveel 2009) have different opinions, no one thinks that it is over 8 percent of the consumption of legal cigarettes. According to Broekhuis and Rotteveel (2009), the consumption of illicit cigarettes had been rather constant for many years. This changed because of a sharp rise of duties on cigarettes in 2004. Data of the Dutch customs (www.minfin.nl) show that the share of illicit cigarettes intended for the Dutch market strongly increased from 10 percent in 2005 to 38 percent in 2008, then fell to 23 percent in 2009. Given this, it is assumed that until 2005 the domestic consumption of illicit cigarettes is 2.5 percent of total consumption of cigarettes (c _total) and that this percentage (f) has increased by half a percent-point a year since then. This results in an increase in the domestic consumption of illicit cigarettes from less than 25 million euro in 1995 to almost 80 million euro in 2008. The total consumption of cigarettes is the product of the consumption of cigarettes per capita and the size of the Dutch population:

C = p_{C} \times c = p_{C} \times f \times c_{t o t a l} .

As with illicit drugs, the imports of illicit cigarettes minus seizures (M_-S ) are calculated from the seizures by the customs (s), an estimate of the detection or seizure rate (R) and the import price (p_M ):

M_{- S} = p_{M} \times \frac{(1 - R)}{R} \times s .

Seizures are taken from the website of the Ministry of Finance. To smooth incidental fluctuations, we use three years’ moving averages. There are no data on the seizure rates of smuggling of cigarettes. However, the impression from the scarce reports on this subject (Dijck 2007; Integis 2008; Broekhuis and Rotteveel 2009) is that until very recently there was relatively little attention from the side of the customs and the police for smuggling cigarettes. Therefore, the seizure rate is fixed at a rather low level of 10 percent.

As with illicit drugs, part of all illicit copies that enter the Netherlands is transit (m_E ), which by definition is excluded from the calculation of national income. Again transit is calculated as a fraction (q) of total exports. For the same reason as for illicit drugs, it is assumed that q equals 0.5 for all years:

m_{E} = q \times (\frac{(1 - R)}{R} \times s - c) .

Until 2000, the import price is assumed to be 30 percent of the street price of illicit cigarettes. Most of the illegal imports originated from China and the former Warsaw Pact countries where cigarettes cost about 70 percent less than in the Netherlands. After 2000, the smuggling from China fell sharply due to increased investigations by the Chinese authorities. These illegal imports were replaced by imports from a wide variety of other countries and the import of imitation cigarettes.

In 2006, genuine cigarettes in the exporting (smuggling) countries cost about 30 percent of the price in the Netherlands. Broekhuis and Rotteveel (2009) reported that around 2006 genuine cigarettes were sold at 17 to 25 percent of the “official” price. As the margins on imitation cigarettes are much higher than on genuine cigarettes, their import price will be far lower. Therefore, it is assumed that the import prices had gradually declined from 25 percent of the street price in 2001 to 10 percent by 2008.

As the domestic production of illicit cigarettes is negligible, exports (e) equal imports (m) minus domestic consumption (c). Until 2005, the United Kingdom was the main destination of the exports, as the street price of illicit cigarettes there was 60 percent of the legal price (Integis 2008). To calculate the value of the exports (E), this price (p_E ) is used for all exports until 2005. After that, Ireland became the most popular destination as its excise duties on tobacco sharply increased. The Irish street price of illicit cigarettes was about 50 percent of the legal ones (Broekhuis and Rotteveel 2009). This price is used from 2006 on:

E = p_{E} \times e = p_{E} \times (m - c) .

No information is available on the costs of transport and storage. As with illicit drugs, these costs are assumed to be 10 percent of the trade margin. The value added (VA) generated on Dutch territory is now

V A = 0.9 \times \{(p_{E} - p_{M}) \times [\frac{(1 - R)}{R} \times s - m_{E}] + (p_{C} - p_{E}) \times c\} .

The value added generated by the smuggling and sales of illicit cigarettes (see figure 2) increases from 0.01 percent of GDP in 1995 to 0.02 percent of GDP in 2008. These figures are very close to those for Sweden (0.01 percent in 1995/2006; Magnusson Wärmark 2008) and lower than those for Austria (0.04 percent in 2006; Schwarzl 2009). Most of value added is generated by reexports. The estimates largely depend on the assumptions on the detection rate. Alternative calculations are made assuming detection rates of 5 and 15 percent.

Conclusion

Our estimates indicate that he contribution of illegal activities in the Netherlands to the national income increased from 1,800 million euro in 1995 to almost 3,500 million euro in 2008, equivalent to 0.6 percent of GDP. The main illegal sector is the production and trade of drugs, which accounted for more than 50 percent of total income from illegal activities until 2001. By 2008, its share was down to less than 40 percent. Illegal employment finding saw its share increase from 10 percent in 1995 to 33 percent in 2008. As reliable data on illegal activities are lacking, the estimates presented heavily depend on assumptions. Therefore, the margins around these estimates are quite large and may very well be 0.3 percent of GDP.

Note, however, that the figures presented in this article cannot be added to the national income without further corrections. Parts of the illegal activities may already contribute implicitly or explicitly (European Commission et al. 2008). Units providing illegal goods may be included in the business register and report to the statistical agency. In the Netherlands, this can be the case for coffee shops, registered prostitution, and employment agencies. Companies may report illegal activities under different headings, hiding these activities. Consumption of illegal services like prostitution may be reported in the annual household budget surveys labeled as other expenditures. Finally, intermediate costs of production may already be booked as household expenditures and contribute to the national income, for example, clothes and lingerie bought by prostitutes and the use of electricity to grow cannabis.

The main corrections for intermediate use of illegal activities already booked as household consumption are the sales of cannabis via coffee shops, prostitution, and illegal employment mediation. It is assumed that half of the sales of cannabis via coffee shops are already included in the current estimates of national income, spread over domestic consumption and exports. About one-third of the turnover of coffee shops is sales to nonresidents (Korf 2003). Some forms of prostitution have been legal since October 2000. This legal part is estimated at 50 percent of total prostitution (Goderie and Bouttelier 2006). It is assumed that half of the legal prostitution is already included in the current estimates of national income. Finally, illegal mediation of temporary employment is already included in the current estimates of national income.

If the value added of all illegal activities were included in the estimates of national account and all relevant corrections were made, (gross) national income in 2008 would be 0.4 percent higher than currently estimated. The margins, however, are quite large.

Footnotes

Authors’ Note

The authors themselves are civil servants, working for Statistics Netherlands. The research was commissioned by the European Community. Part 3 of DG-Eurostat Grant agreement 2009, Theme 01, The Improvement of the quality of National Accounts, No 20101.2009.001-2009.173

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Notes

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