Statistics on small and medium-sized enterprises

Dependent and independent SMEs and large enterprises

Data extracted in September 2015. Further Eurostat information, Main tables and Database. Planned article update: April 2018.

Authors: Aarno Airaksinen, Henri Luomaranta (Statistics Finland), Pekka Alajääskö, Anton Roodhuijzen (Eurostat, Structural business statistics and global value chains)

Small and medium-sized enterprises (SMEs) are a focal point in shaping enterprise policy in the European Union (EU). The European Commission considers SMEs and entrepreneurship as key to ensuring economic growth, innovation, job creation, and social integration in the EU. However, in official statistics SMEs can currently only be identified by employment size as enterprises with fewer than 250 persons employed. This is a big category and encompasses enterprises with different ownership structures and varying numbers of employees and levels of economic activity. To facilitate better analysis and understanding of the heterogeneity of SMEs, the 2014 microdata-linking (MDL) project linked data from structural business statistics (SBS), international trade in goods statistics (ITGS) and business registers (BRs).

This article examines the statistical data from the MDL project, which produced linked datasets for analysing business structures and performance in a harmonised way, making cross-country comparisons possible. Nine countries participated in the 2014 MDL project. Six of those were able to break down their SMEs into dependent and independent enterprises. We analyse the SMEs (broken down in three size classes) and large enterprises in these six countries (Denmark, Germany, Latvia, the Netherlands, Finland, and Norway). The data spans the years 2008 to 2012, which allows us to consider the enterprises’ evolution by size class and economic performance in terms of value added and employment. We also analyse differences in four economic sectors in all six countries: medium-high and high technology manufacturing, low and medium-low technology manufacturing, knowledge-intensive business services, and other services. Compared with previous MDL projects, a new feature is the distinction between dependent SMEs (those belonging to an enterprise group) and independent SMEs.

This article is part of an online publication on Microdata linking in business statistics.

Table 1: Number of enterprises, persons employed and gross value added (GVA) and the share of SMEs, 2012
Source: Eurostat (sbs_sc_sca_r2)
Table 2: Criteria for medium, small and micro -sized enterprises
Table 3: Number of enterprises, value added and persons employed (FTE) broken down by type of SME, 2008 and 2012
Figure 1: Share of dependent and independent enterprises by size class and country, 2012
Figure 2: Share of value added of dependent and independent enterprises by size class and country, 2012
Figure 3: Share of employment of dependent and independent enterprises by size class and country, 2012
Figure 4: GVA development of dependent SME categories between 2008 and 2012
Figure 5: GVA development of independent SME categories between 2008 and 2012
Table 4: Export intensity, import intensity and trade openness broken down by size (SME/large) and type of enterprise (dependent/independent) in manufacturing, 2008 and 2012
Table 5: Composition of the special aggregates in the analysis
Table 6: Number of enterprises, GVA, persons employed (FTE), SME share, and percentage share of de-pendent enterprises in SME category in four special aggregates, 2012
Figure 6: GVA and persons employed (FTE) shares of large enterprises and SMEs in medium high and high technology manufacturing, 2012
Figure 7: GVA and persons employed (FTE) share of dependent and independent SMEs in medium high and high technology manufacturing, 2012
Figure 8: GVA and persons employed (FTE) shares of large enterprises and SMEs in low and medium low technology manufacturing, 2012
Figure 9: GVA and persons employed (FTE) share of dependent and independent SMEs in low and medium low technology manufacturing, 2012
Figure 10: GVA and persons employed (FTE) shares of large enterprises and SMEs in knowledge intensive business services, 2012
Figure 11: GVA and persons employed (FTE) share of dependent and independent SMEs in knowledge intensive business services, 2012
Figure 12: GVA and persons employed (FTE) share of dependent and independent SMEs in other services, 2012
Figure 13: GVA and persons employed (FTE) shares of large enterprises and SMEs in other services, 2012

Main statistical findings

  • SMEs are a very important part of the economy, as they represent around 99 % of all enterprises and employ an increasing number of persons.
  • Most enterprises are independent and do not belong to an enterprise group, but within the SMEs medium-sized enterprises are very often part of a group. This is most common in manufacturing and to a lesser degree in knowledge-intensive business services.
  • Dependent SMEs are important in terms of employment and gross value added (GVA), especially in smaller countries such as Denmark, Norway and Finland. However, they are also significant in Germany where they account for 43 % of GVA created by SMEs in total and employ 34 % of the total number of persons employed by SMEs. Therefore, a large proportion of total growth created by SMEs can be attributed to dependent SMEs.
  • Large enterprises create a higher proportion of value added in the ‘high and medium/low tech manufacturing’ sector, while SMEs create a higher proportion of value added in the services sector.
  • In most countries, dependent SMEs are more open to international trade than independent SMEs. In this regard dependent enterprises behave like large ones; they are also more exposed to shocks through international trade than independent SMEs.

Why is the 'SME vs large enterprise' discussion relevant?

The growth-generating potential of SMEs has been the subject of many academic studies[1]. Although there is no general agreement in the literature on whether SMEs generate more growth than large enterprises, some recent studies[2] suggest that large enterprises are more pro-cyclical, which means that they are more affected by international business cycles than SMEs are. This fact may have implications for how different business sectors and therefore national economies behave in times of economic depression.

Recently, economic literature [3] has shifted towards analysing the role of the largest enterprises in understanding aggregate fluctuations. Trade integration, globalisation and industry consolidation have the potential to make large enterprises ever larger and thus more important in explaining business cycles and economic developments. Large enterprises can account for a sizeable portion of a country’s economic output. Therefore, if global demand for even one product falls, a country can face severe consequences that show in the aggregated measures of economic activity. This has been the case for example in Finland[4]. These microeconomic shocks may also affect the large enterprises’ networks[5]; a fall in demand can have an adverse impact on the whole supply chain, across industries and countries[6].

Although it is important to consider which enterprises generate most value added in the economy, policy makers are often more interested in employment patterns than GVA. Enterprises that generate most GVA make the economy wealthier, but those that create jobs contribute to employment creation and thus help keep the unemployment rate low. Therefore, this article analyses both the gross value added and employment patterns in the different enterprise size categories, across the six countries participating in the project.

SMEs versus large enterprises - basic structures

Table 1[7] shows that SMEs make up over 99 % of all enterprises in all EU countries and in Norway. They account for around two-thirds of total employment, ranging from 53 % in the United Kingdom to 86 % in Greece. SMEs contribute 57 % of value added in the EU.

SME profiling — independent or dependent enterprises?

In the European Commission recommendation, the main factors determining whether an enterprise is an SME or not are the number of persons employed and either total turnover or the balance sheet total (see table 2). These ceilings apply to the figures of individual enterprises only. An enterprise which is part of an enterprise group may need to include data on persons employed, turnover and the balance sheet from the whole group. There are specific guidelines on how much of the group’s employment/turnover/balance sheet should be included to determine the SME status.


These guidelines are complex and are therefore difficult to use in statistical systems. For this reason, statistics often use size class information based only on the number of persons employed in the enterprise itself, without looking at the turnover or balance sheet data from the group that the enterprise belongs to. However, doing this has consequences for statistics, since enterprises belonging to a domestic enterprise group[8] may be different from independent enterprises, for example in their ability to access finance, their bargaining power, possibilities to expand to foreign markets, and various other aspects of doing business.

Consequently, statisticians have looked into ways of overcoming these limitations by linking data from structural business statistics (SBS) to business registers (BRs). This means that the statistics don’t completely reflect the recommended SME definition, but they do make it possible to distinguish between dependent and independent enterprises. For the remainder of this article, whenever a dependent SME is mentioned we mean an enterprise that employs fewer than 250 persons and for which the business register shows that it belongs to an enterprise group. An independent SME also employs fewer than 250 persons but according to the BRs does not belong to an enterprise group. A large enterprise employs at least 250 persons.

To gain some insight into how businesses are organised, the countries taking part in the MDL project created harmonised research databases that classify SMEs as either independent or dependent. In addition, SMEs were divided into micro, small and medium size categories, as this makes it possible to better understand SME structures and to identify which SME types contribute most to generating growth in the economy.

Table 3 presents the number of enterprises, value added, and employment levels for 2008 and 2012 across countries, by type of SME and size class. Aside from the totals, it includes the proportion of each size class in the total number of SMEs (independent + dependent). Most enterprises in the SME category are independent. However, a closer look at the data shows that the medium size category is often dominated by dependent enterprises, especially if one looks at the gross value added and employment figures. For example in the medium size category in 2012, Denmark has 68 %, Germany 53 %, Latvia 44 %, Finland 69 %, and Norway 82 % of dependent enterprises. The Dutch data are an exception, with most enterprises in all categories classified as independent in 2012. Overall, given the high proportion of dependent enterprises in the medium size category, a significant portion of total SME value added and employment comes from dependent enterprises. Table 3 shows that the proportion of GVA created by dependent SMEs in total SME-generated GVA is 53.9 % in Denmark, 42.8 % in Germany, 49.5 % in Latvia, 14.8 % in the Netherlands, 50.1 % in Finland, and 55.1 % in Norway. Figures 1, 2 and 3 show these observations and present the 2012 data.

Analysis of SME growth

In Figures 4 and 5, changes in GVA are compared for independent and dependent enterprises in different size classes between 2008 and 2012. This is important because dependent enterprises behave differently from independent enterprises, and are often more similar to large enterprises.

In Germany and Norway, independent SMEs have grown much faster than dependent SMEs across all size categories, while in Latvia and Finland the reverse seems to be true. In Germany and Norway, dependent SMEs are at the same level or slightly lower than in 2008, with the exception of small enterprises in Norway which show a 25 % increase between 2008 and 2012. In Latvia, the micro dependent category increased by 172 percentage points between 2008 and 2012, which could be due to the intensive restructuring work and privatisation of enterprises during the 2009 recession. In Denmark, growth in 2009-2012 was concentrated in dependent enterprises, with the exception of the micro dependent enterprises, which did not grow. In the Netherlands, only medium-sized, independent enterprises showed growth. In general, the observation that dependent SMEs have become more important in the analysed business sectors could partly be explained by large enterprises having been forced to prioritise investment, find ways of reducing costs, and streamline operations. All of these activities would show as increased GVA in the dependent category.

The countries that took part in the project have different types of industries, corporate laws and business cultures, so an in depth analysis of enterprises dynamics is not possible in the scope of this article. It is clear, however, that understanding the relationships between enterprises is crucial to understanding the economic importance of the size categories. This is especially true when discussing the impact of the largest enterprises with many connections to SMEs. The statistical data we present here show that dependent SMEs are an important part of the analysed economies and have in some countries become even more important over the years analysed. This is because they create a high proportion of the value added in the SME category.

Indicators of international trade for different types of enterprises

International integration can bring about many changes in the economy. Especially in the new era of the European single market, it is likely that international markets become increasingly accessible to SMEs. Large enterprises have traditionally been more international, given that it is costly to access foreign markets. The ongoing economic crisis has given another pressing reason to better understand how globalisation impacts a national economy. Globalisation exposes enterprises to international business cycles. This can have serious consequences if a national economy is dependent on a few large exporting enterprises. This section provides some insights into how the manufacturing sector is exposed to globalisation by showing how international different types of enterprises are.

Alongside the large enterprise category, we analyse SME structures and show how independent and dependent SMEs compare with each other across countries. Table 4 presents the SME size classes divided into independent and dependent categories next to large enterprises in the manufacturing sector, for 2008 and 2012. We use (exports + imports) / (turnover + purchases of goods and services) as our measure for trade openness. We provide also export intensity as the share of exports in turnover, and import intensity as the share of imports in purchases of goods and services[9] . Export and import intensities are used as a measure for export or import orientation of the size classes.

As expected, in table 4 we see that the highest degree of openness is often found in the large enterprise categories. Interestingly, in the Netherlands (in 2012) and in Latvia (in 2008) SMEs are more open to trade than large enterprises. Latvian enterprises have the highest degree of openness among the countries, both in large enterprises and SMEs. In all countries independent SMEs are less international than dependent SMEs. Except in Denmark, dependent SMEs are usually closer in terms of openness to trade to large enterprises than to independent SMEs. With the exception of large enterprises in the Netherlands and SMEs in Norway, all enterprises are more export intensive than import intensive. In Denmark, Finland, and Norway the export intensity of large enterprises has decreased from 2008 to 2012, while in Germany, the Netherlands and Latvia it has increased.

Sector-level analysis

In order to provide a deeper analysis of the observations set out in the previous section, we will now explore the economic structures present in each of the analysed countries. This section analyses the differences in four economic activity sectors based on the NACE classification, as presented in table 5.

Table 6 presents the sector-level classification of the number of enterprises, GVA, and persons employed for the year 2012. The medium-high and high technology manufacturing sector generates a significant part of total GVA in Germany (18 %), Finland (14 %), Denmark (10 %) and the Netherlands (9 %). Finland has the highest proportion of GVA created by the low- and medium-low technology manufacturing sector (18 %). The proportion of GVA created by the knowledge-intensive business services sector ranges from 9 % in Germany to 17 % in the Netherlands. In all the countries, the ‘other services’ sector accounts for most GVA created, and ranges from 31 % in Norway to 55 % in Latvia.

The rightmost column in table 6 presents the proportion of enterprises that are dependent SMEs. Denmark stands out here, with a very high proportion of dependent enterprises in medium-high and high technology manufacturing (45 %) and in low and medium-low technology manufacturing (30 %). In all countries, the proportion of dependent SMEs is higher in manufacturing than in services.

Another interesting comparison is possible if one compares the proportion of GVA and of persons employed. If the percentage of GVA created is much higher than the percentage of persons employed, the sector is producing more value added relative to how much employment it needs. This is the case for example in Finland, where the proportion of persons employed in the medium-high and high technology manufacturing sector is 4 percentage points lower than the proportion of GVA created in this sector.

In the remainder of the article, after having presented the broader picture of what each country’s economy is composed of, we provide a more in-depth analysis of how dependent enterprises impact the SME category in each of the analysed sectors. In order to provide a complete picture of the situation, we also provide comparisons between large enterprises and SMEs in terms of GVA and persons employed.

Medium-high and high technology manufacturing

Figure 6 shows that, in the medium-high and high technology manufacturing sector, large enterprises usually account for a far higher proportion of a country’s total GVA than SMEs do (except in Latvia). With the exception of the Netherlands, most SME-generated GVA seems to come from dependent SMEs (see Figure 7). The patterns are similar for the proportion of persons employed: large enterprises and dependent SMEs dominate the high-tech sector across all countries. Based on these observations, one can better understand changes in GVA created and the number of persons employed by large enterprises in different countries. For instance, one reason for the poor performance of large Finnish enterprises could stem from the performance of the medium-high and high technology manufacturing sector. When comparing GVA and FTE proportions, we see in Figure 6 that large enterprises have a higher proportion of GVA than of persons employed, which indicates higher productivity than SMEs. In Figure 7 there is not much difference between the proportion of GVA and FTE and therefore one cannot draw any clear conclusion about the difference in productivity between dependent and independent enterprises.

Medium-low and low technology manufacturing

The low and medium-low technology sector is composed of a roughly even proportion of large enterprises and SMEs, at least when it comes to the proportion of GVA and employment (see Figure 8). The ratio of large enterprises to SMEs is relatively low in Latvia and the Netherlands, and relatively high in Finland, in terms of both the proportion of GVA and employment. Dependent SMEs account for half or more of total SME-generated GVA in Denmark, Latvia, Finland, and Norway, as seen in Figure 9. When comparing the proportion of GVA to the proportion of FTEs, it is the larger enterprises in Figure 8 and the dependent enterprises in Figure 9 that are most productive.

Knowledge-intensive business services

Figure 10 shows that, judging by the proportion of GVA and FTEs, the knowledge-intensive business services sector consists mostly of SMEs. Unlike in the other analysed sectors, SMEs also seem to be more productive than large enterprises. However, a surprisingly high proportion of SME-generated GVA comes from dependent enterprises; roughly 60 % in Finland and Norway, 50 % in Denmark and Latvia, and 40 % in Germany, as shown in Figure 11. This Figure also shows that the proportion of persons employed in the sector is higher for independent SMEs in Germany, Latvia, Finland and the Netherlands. It appears that, in these countries, dependent SMEs create relatively more GVA compared with how much employment they require.

Other services

Based on Figure 12, the ‘other services’ sector consists mostly of SMEs. Therefore, a high proportion of the performance of SMEs in general can be attributed to this sector. We should bear in mind the observation from table 6, that the ‘other services’ sector is very important in the analysed economies. From Figure 13 we see that, in terms of GVA created, the SME category is roughly evenly divided into independent and dependent SMEs in Denmark, Latvia and Norway. In Germany, dependent SMEs produce 38 % of GVA, and account for only 29 % of employment in the ‘other services’ category. Latvia has a similar pattern: dependent SMEs produce 49 % of its GVA while accounting for only 27 % of employment.

Data sources and availability

In this article an SME is defined as an enterprise with fewer than 250 persons employed. New statistics on enterprises have traditionally been produced by carrying out surveys. Microdata linking presents an innovative approach to obtaining new information on the economic performance of enterprises by linking different existing statistical sources at individual enterprise level (microdata level). This approach does not require new surveys to be carried out and thus does not increase the burden placed on enterprises. Due to statistical confidentiality issues it is not possible to publish microdata on the Eurostat website. However in the future Eurostat aims at publishing aggregated tables based on microdata analysis in its database.

Context

Small and medium-sized enterprises (SMEs) are the backbone of Europe’s economy, providing the majority of all new jobs. The European Commission aims to promote entrepreneurship and improve the business environment for SMEs to allow them to realise their full potential in today’s global economy. The new Programme for the Competitiveness of Small and Medium-sized Enterprises (COSME) will run from 2014 to 2020, with a planned budget of EUR 2.5 billion.

See also

Further Eurostat information

Publications

Dedicated section

Source data for tables and figures (MS Excel)

Notes

  1. One early contribution was the Gibrat study (GIBRAT, R.(1931): Les Inegalites Economiques, Sirey. Paris.
  2. An empirical example with US data: Moscarini, Giuseppe, and Fabien Postel-Vinay. 2012. ‘The Contribution of Large and Small Employers to Job Creation in Times of High and Low Unemployment.’ American Economic Review, 102(6): 2509-39.
  3. An example: Xavier Gabaix. The granular origins of aggregate fluctuations, Econometrica, 79(3):733–772, 05 2011.
  4. See the discussion in: Jyrki Ali-Yrkkö (Ed.): Nokia and Finland in a Sea of Change. ETLA B244, pp. 37–67, Taloustieto Oy, Helsinki, Finland, 2010.
  5. This is closely related to the discussion on dependent enterprises.
  6. A theoretical discussion can be found at: Acemoglu, Daron, Vasco M Carvalho, Asuman Ozdaglar, and Alireza Tahbaz-Salehi (2012), ‘The Network Origins of Aggregate Fluctuations’, Econometrica.
  7. The numbers extracted from the Eurostat database may differ from those presented in the remainder of the article, because the SME definition used in the MDL project is based only on enterprises’ full-time-equivalent (FTE) employment.
  8. The forthcoming Statistic Explained "Statistics on trading and non-trading enterprises will develop the domestic/foreign-breakdown
  9. Imports and exports are of goods. Both turnover and purchases of goods and services include services. Thus nominator and denominator are slightly inconsistent in the calculation of both intensities. However, it is also likely that both exports and imports of goods include values of embedded services .