ECB: Estimation of Prostitution Services in Europe in the Context of the External Accounts


In the European Union, although all Member States are requested to include estimates of the output in prostitution in the national accounts, few are currently including estimates of the cross-border prostitution services in the external accounts. The later, when produced, are not separately published and the information available on the estimation methods is limited.

In the context of the national accounts, the impact of the estimated value added of the prostitution industry in GDP ranges from less than 0.1% in Sweden (in 2006) and the Netherlands (in 2008) to 0.1% in Denmark (in 2004) and slightly over 0.2% in Italy (in 2011) and Luxembourg (in 2013). In the U.K., the Office for National Statistics estimates prostitution to have generated close to 0.3% of GDP. Contributions below 0.5% of GDP have been reported also for other countries, e.g. Spain, Germany and Portugal.

Scope, Methodology, Compilation Practices and Data Sources

Prostitution services provided by residents to non-residents should be recorded as exports of services in the external accounts. Similarly, prostitution services bought by resident clients to non-residents should be recorded as imports of services.

Prostitution services between residents and non-residents should be classified as personal, cultural and recreational services except in those cases when clients purchase such services abroad while on holiday or business trips. In such cases, prostitution services should be included in travel.

Prostitution services can be estimated following a demand approach or a supply approach.

The general framework proposed by Eurostat (2018), which is followed by most EU countries, adopts a supply approach. An estimate of the number of prostitutes in the country is multiplied by the total number of visits per prostitute (per period) times the average price per visit:

total sales = number of prostitutes x number of contacts per prostitute x price

The domestic output is obtained by applying an estimate of the proportion of non-resident prostitutes:

domestic output = total sales x (1 – proportion of non-resident prostitutes)

The cross-border components are then to be estimated as follows:

Imports of services = proportion of non-resident prostitutes x total sales to residents

Exports of services = domestic output x proportion of non-resident clients

Figure 1 below summarises the concepts underlying this set of equations.

It is assumed that purchases of prostitution services from non-resident prostitutes by resident clients while traveling abroad are already being covered in the travel account. Similarly, in the case that purchases from resident prostitutes by non-resident clients while visiting the compiling country are already covered, at least partially, in the travel account, the inclusion of that share of exports in personal, cultural and recreational services would not only constitute a misclassification within the services sub items, but more importantly would lead to double counting.

Figure 1

Components of cross-border prostitution services transactions

Figure 1

In a demand approach, compilers estimate the average consumption by clients, i.e. the number of transactions which is then multiplied by the average price to obtain the total sales.

In practice, in both models several variables are often derived from ad hoc research conducted either in the country or in other countries. There are generic references to the use of data from police reports (in those countries where prostitution is illegal), from welfare and health organisations and from NGOs, but few information on how these data are used concretely.

Business surveys and fieldwork have been conducted in a number of European countries to estimate either the number of prostitutes and respective visits per period (supply approach) or the number of transactions (demand approach).

Some information on prices is being obtained from websites and internet fora where clients rate the prostitution services. In other cases, estimates of prices are also based on ad hoc studies assuming e.g. that benchmark average prostitution prices have evolved in line with inflation (CPI).

In some countries, estimates are produced separately by type of business - namely street and window prostitution, brothels, nightclubs and massage parlors, escort services and private (apartment) prostitution - and then aggregated to obtain the total. In others, only the total is estimated.

Current Challenges and Conclusions

The measurement of informal economic activities is naturally more difficult than that of transactions in the formal economy, precisely because those activities are usually not captured in the established data collection systems. Any estimates will necessarily lack the accuracy and reliability of official statistics on the formal economy, as they are based on substantial assumptions and few observed data.

The fact that, even when legal, prostitution is often linked to human rights’ violations and crimes such as pimping, human trafficking and exploitation of minors, adds a further layer of opacity and complexity as by definition only those transactions occurring under mutual agreement (i.e. someone intentionally paying for a service which is deliberately provided) are actual economic transactions.

The ad hoc studies used by some European countries as benchmarks to estimate the contribution of prostitution to the GDP are not always very recent; the estimates they provide often refer to periods earlier than 2010. Frequently these studies are sectorial; they tend to focus on regional patterns or specific branches of the industry (e.g. window prostitution), which are extrapolated for the whole country.

Surveys are expensive and can imply some degree of personal risk to those running the inquiries. In addition, surveys based on demand may not be representative as even in countries where both providing and purchasing prostitution services is legal clients may feel inclined not to disclose the right information.

Most estimation methods seem to assume the statistical irrelevance of male prostitution, or otherwise not address it.

The fact that this activity is treated differently across jurisdictions – from prohibition, to partial or complete decriminalisation – adds to the difficulties in homogenising the statistical measurement across countries.

In the case of cross-border prostitution services, much of the calculations rely on assumptions and there is no concrete guidance for instance on how the proportion of non-resident prostitutes or the proportion of non-resident clients should be obtained. In some countries, it is assumed, for instance, that half of the foreign prostitutes operating in the compiling economy are actually non-resident (i.e. stay in the country less than one year). In other countries, yet, it is assumed that prostitution services in the country are provided entirely by resident prostitutes or that there is no international trade in prostitution services besides the transactions recorded in the travel item.

To conclude, if the estimation of prostitution in the context of national accounts already proves challenging, the picture gets more complex in the context of the balance of payments. The identification of cross-border transactions is further complicated by the difficulty in estimating the shares of non-resident prostitutes in the compiling economy and of non-resident clients contributing to total sales. Additionally, the exports of prostitution services purchased by clients while traveling in the reporting economy may already be at least partially covered in the travel account – either via border surveys on expenditure or data on payments with cards - possibly leading to double counting.

References and Background Documents

Abramsky, J. and Drew, S. (2014). “Changes to National Accounts: Inclusion of Illegal Drugs and Prostitution in the UK National Accounts”, Office for National Statistics (U.K.)

Adriaenssens, S., Hendrickx, J., Heylen, W. and Machiels, T. (2015). “A direct measure of output in prostitution in Belgium”, Faculty of Economics and Business, KU Leuven and National Bank of Belgium

Baldassarini, A. and Sallusti, F. (2017). “Estimating illegal activities in the Italian national accounts”, National Institute of Statistics (Italy)

Björling, M., Engdahl, J., Magnusson Wärmark, B. and Pappila, M. (2008). “Illegal activities in the Swedish National Accounts: prostitution, narcotics, gambling, alcohol and tobacco”, Statistics Sweden

Bruil, A., Kazemier, B., Rensman, M. and van de Steeg, A. (2012). “The contribution of illegal activities to national income in the Netherlands”, Statistics Netherlands.

Eurostat (2018). “Handbook on the compilation of statistics on illegal economic activities in national accounts and balance of payments”, 2018 edition

Myllymäki, M. (2017). “Illegal economic activities in balance of payments and national accounts”, Statistics Finland

Statistics Denmark, “Estimating illegal activities in Denmark”