Services trade by enterprise characteristics - STEC
- Data extracted in 2014. Most recent data: Further Eurostat information, Main tables and Database. Next update of the article: November 2017
What do we know about the businesses involved in international trade in services? How does trade in services affect employment, given the interconnected nature of our economies? This article describes how businesses trading in services operate, by analysing business-level data and examining in detail the characteristics of such businesses. The main characteristics discussed are: size (the number of employees), ownership (foreign-controlled or domestic) and economic activity. Data from a pilot survey carried out in six European Union (EU) Member States — the Czech Republic, Denmark, Estonia, Luxembourg, Austria and Poland — are used to illustrate this analysis. Due to the limited scope of the study, conclusions are descriptive and should not be generalised.
- 1 Main statistical findings
- 2 Context
- 3 Data sources and availability
- 4 See also
- 5 Further Eurostat information
- 6 External links
Main statistical findings
In small economies, small businesses are more involved in trade in services than large ones, while in large economies, larger companies are more active. Foreign-controlled businesses are especially dominant in trade in services in eastern European Member States. The graphs help to illustrate this analysis, and the conclusions drawn.
Trade in services by size of business
Small and medium-sized businesses are responsible for three quarters of the value of trade in services (exports and imports) in small economies (e.g. Estonia and Luxembourg), while in larger countries their trade in services accounts for less than half of the total value. In general, large businesses import more services than do smaller firms.
One of the most important results from the analysis of the characteristics of businesses trading in services is the proportion of trade in services attributable to businesses of different sizes. In 2011, small and medium sized enterprises were responsible for the largest share of trade in services in small countries (Estonia and Luxembourg), while in larger economies, their contribution was less than half of the total value of exports. Small businesses (those with up to 49 employees) were responsible for over half the value of trade in services in Luxembourg and Estonia, for around a quarter in Poland and Austria, and for only 20 % in Denmark and 13 % in the Czech Republic (Dashboard 1).
The pattern for imports is similar to that identified for exports. In the Czech Republic, Denmark and Poland, large companies are responsible for a very high percentage of service imports (73 %, 62 % and 61 %, respectively) (Dashboard 2). Small and medium-size businesses, meanwhile, imported the largest share of services in Luxembourg and Estonia (80 % and 71 %, respectively), as was the case on the export side.
It should be noted that, in four out of the six countries (the Czech Republic, Estonia, Austria and Poland), the proportion of exports attributable to small and medium size businesses is higher than that of imports. In Luxembourg and Denmark, the opposite is true.
When only trade in services with non-EU countries is considered, large businesses are again most active in larger economies. They are responsible for a significant proportion of extra-EU trade in services in Denmark, the Czech Republic and Poland.
Large businesses are responsible for over 60 % of extra-EU exports in Denmark, Poland and the Czech Republic, while small and medium size businesses have a more significant share in Estonia and Luxembourg (Figure 1).
In Denmark and the Czech Republic, large businesses imported the largest proportion of the total value of services imported from non-EU countries, over 70 % and 80 %, respectively (Figure 2). In Estonia and Luxembourg, small and medium size businesses were responsible for the largest share of extra-EU imports (over 80 %).
It is interesting to note that large businesses have a larger proportion of the market in extra-EU trade than in intra-EU trade (with the exception of Estonia). The same pattern can be observed for imports in Denmark, the Czech Republic and Poland. In Austria, Luxembourg and Estonia, meanwhile, the reverse was true — small and medium size enterprises are responsible for a larger proportion of extra-EU imports than of intra-EU imports.
Trade in services by business ownership
Domestic businesses are responsible for three quarters of Denmark’s services exports, while foreign-controlled firms are dominant in the Czech Republic and Luxembourg.
Dashboard 3 shows services exports broken down by business ownership (see the methodology section), in each of the six countries included in the study. In the Czech Republic, Luxembourg and Poland, services exports are clearly dominated by foreign-controlled businesses, responsible for 70 %, 68 % and 61 %, respectively, of the market. The situation is more balanced in Estonia and Austria, on the other hand, with domestic companies, nonetheless, holding slightly more of the market. The percentage of services exports attributable to domestically-owned companies is highest in Denmark (79 %).
The relative strength of foreign-controlled and domestic businesses in services imports also varies between the six countries (Figure 3). Again, Poland, the Czech Republic and Luxembourg show lower levels of services imports for domestically-owned companies. Foreign-controlled and domestic companies are, again, on a more similar footing in Estonia and Austria, with domestically-owned companies taking a slightly higher percentage of services imports than foreign-controlled businesses. As was the case for exports, Denmark has also the highest proportion of service imports controlled by domestic companies, 76 % of the total value.
Foreign-controlled businesses are also dominant in extra-EU trade in services in larger economies, being responsible for a significant proportion of trade in services in Denmark, the Czech Republic and Poland.
Foreign-controlled businesses’ exports to non-EU countries account for more than half the total value of extra-EU exports in most of the countries (Figure 4). Denmark was the exception to this, domestic firms dominating the market with 80 % of the total value of extra-EU exports.
Foreign-controlled businesses dominate the market for imports of services from outside the EU in Luxembourg, Poland and the Czech Republic (Figure 5), their imports accounting for around three quarters of the total value.
Domestic firms are more active in extra-EU exports than they are in intra-EU exports in four of the countries, namely Denmark, the Czech Republic, Poland and Luxembourg. In Estonia and Austria, meanwhile, the situation is reversed, with foreign-controlled businesses being stronger in extra- than in intra-EU exports. On the import side, the pattern is very similar. Domestic businesses are responsible for a larger proportion of extra- than intra-EU imports in Denmark, the Czech Republic, Poland and Estonia (Figure 6).
Trade in services by the business’s main economic activity
Businesses in the transport and storage sectors are the biggest exporters of services, with manufacturing following in second place.
Table 1 shows the value of services exports and imports attributable to businesses in different sectors, as defined by businesses’ main economic activity (under the NACE classification). It should be noted that transportation and storage companies are responsible for two thirds of Denmark’s service exports. This sector also represents the largest proportion of services trade in the Czech Republic, Poland, Austria and Estonia. In Luxembourg, businesses in the field of programming and information were responsible for 55 % of services exports.
Manufacturing companies are the second largest contributor to services exports, their exports accounting for 10 % of the total in Denmark and Poland, and around 16 % in Austria and the Czech Republic. Please note that travel services and financial services are excluded, and are therefore recorded in the column ‘non-classified by NACE’. This is because data relating to these services comes mainly from administrative sources, with no reference being made to the businesses themselves (see methodology).
Conclusions from the statistics produced on the characteristics (size and ownership) of businesses involved in trade in services
Businesses trading in services in the Czech Republic and Poland show the strongest similarities in their profiles; businesses in Luxembourg and Estonia are the next most closely matched pair, with Denmark and Austria also showing some, but weaker common characteristics.
We have used a visualisation technique called cluster analysis to gain greater insight into the data presented in Figures 1 to 4 and Dashboards 1 to 4. Cluster analysis is a way of grouping data rows (in this case, countries) into homogenous classes (clusters) where the items in each class are, relatively, more similar to each other and more different from the items in other clusters.
The results of cluster analysis can be presented in a graph called a dendrogram (Figure 5), which illustrates the relative level of similarity of the countries’ profiles. Starting from the left, the two counties making the most closely related pair (the Czech Republic and Poland) form the first cluster. The other pairs then follow, according to the degree of similarity between the two — Luxembourg and Estonia in this case appearing as the next two most closely related countries, followed by Denmark and Austria as the third cluster. The first and third pairs, being more similar to each other than either is to the second pair, are then connected to make a group of four countries. Depending on the total number of data items, progressively larger clusters can continue to be created. Cluster analysis thus allows us to produce a simple graphical presentation of the similarity structure of the numerical data, which would be impossible to see directly from the figures.
Figure 5 summarises the information on the six EU countries included in the survey by comparing the similarities and differences between the profiles of businesses trading in services in each, specifically their size and ownership. The results show the Czech Republic and Poland to be the two most closely related countries. This is probably due to their similar background and the proximity of both to a large economy (Germany). The countries showing the next strongest level of similarity in terms of the size and ownership of businesses trading in services are Luxembourg and Estonia, the main common factor being a large proportion of small businesses. The profiles of businesses in Denmark and Austria show some similarities, but they differ more from each other than was the case for the other two pairs. They are therefore the last of the connected pairs.
Policy makers, trade analysts and researchers have expressed a strong desire to have more comprehensive and integrated data on international trade and globalisation. They require this in order to better understand the effect of international trade on growth, economic development, employment and countries’ economic interdependency in respect of production, consumption and investment. The increasing importance of international trade in services has led to growing demand for data on this particular aspect of trade.
The development of statistics on the characteristics of businesses trading in services has been endorsed by the European Statistical System Committee. The main organisations active in this area at international level (including Eurostat, the UN, the OECD, the World Trade Organisation and the United Nations Conference on Trade and Development) have produced a paper International Trade Information System in 2020: a vision for the future, in which they call for an integrated approach to statistics on trade in goods and services and on businesses and multinational businesses. The proposal for the European Statistical Programme for 2013-17 reiterates the EU’s commitment to this approach.
Data sources and availability
The development of statistics on the characteristics of businesses trading in services represents a major step forward in integrating statistics on trade in services into business statistics. These new statistics make the link between the level of trade in services and the characteristics of the businesses involved. They provide information on particular classes of businesses, defined by the size of company, the industry in which they operate, and their ownership (domestic or foreign-controlled).
By reusing data that already exist, we are getting more value from these data. Using data from another source at the same time allows us to draw different information out of the original data set. The statistical results presented in this article were obtained using the ‘linking’ methodology (please see the methodological section), where data on the value of businesses’ exports and imports are linked to information from the business register. We were thus able to classify businesses either by the information available in the business register or by other known characteristics, in order to analyse trade in services by businesses of different types.
Statistics on ‘‘international trade in services’’ currently provide the monetary value of trade in services, broken down by service category (e.g. computer services or legal services) and by partner country. These statistics are produced from the transactions recorded under the country’s balance of payments, which captures all transactions that take place between an economy’s residents and non-residents. Linking the two datasets (the business register and data on trade in services from the balance of payments) at business level, using a common identifier (the business register code) has allowed a cross-classification to be created, providing us with new data on businesses involved in trade in services.
Statistics on the characteristics of businesses trading in services are produced by combining data from different sources (the business register and data on the value of businesses exports and imports of services) at the business (micro) level. This allows data on the value of each business’s exports and imports to be linked to the information provided in the business register. A common identifier (e.g. the business registration code) is used to link the items in the two data sets. Compiling data in this way means that data on businesses’ trade in services can be broken down by the businesses’ size (classified as small, medium or large), their activity and their ownership.
For simplicity, the term "business" is used in place of "enterprise" (legal unit).
The results produced using this method include several tables that combine two types of classification. Each table splits the data on the basis of two characteristics, e.g. size and activity, or activity and service category. The characteristics used in the tables are:
- Size (small: 0-49 employees; medium: 50-249 employees; and large: 250 or more employees),
- Main activity (NACE Rev.2),
- Ownership (domestic or foreign-controlled),
- Service category (EBOPS 2002),
- Trade partners: extra-EU (trade with non-EU countries); intra-EU (trade with EU countries); and world trade (extra-EU and intra-EU trade), and
- Flows: value of exports and imports.
Table 2 shows the proportion of imports and exports of services in each country that is covered by the linked data given in the tables described above (for "size class" and "ownership"). The total proportion of the value not covered is shown under ‘non-classified’ (e.g. 23 % of imports in Denmark). This includes data on travel and financial services, data from administrative sources, and estimations. See the individual data by country given in Figures 6 and 7 (not to be used for comparing the countries).
Table 3 shows the proportion of total imports and exports of services across the six countries that is covered by the linked data. For example, a weighted average (across the six countries) of 42 % of exports and 44 % of imports was not included in the linked data.
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Further Eurostat information
Source data for tables and figures (MS Excel)
- Manual of the Statistics on International Trade in Services 2010 (MSITS 2010)
- Compilers Guide for the Manual of the Statistics on International Trade in Services
- Sturgeon, T. J. "Global Value Chains and Economic Globalisation"- Towards a New Measurement Framework"