OECD-Eurostat Entrepreneurship Indicators …areadocenti.eco.unicas.it/ferrante/OECD-EUROSTAT.pdfOECD-Eurostat Entrepreneurship Indicators Programme ... In 2006 the joint OECD-Eurostat

Measuring Entrepreneurship

A Collection of Indicators

2009 Edition

OECD-Eurostat Entrepreneurship Indicators Programme

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OECD Statistics Directorate

MEASURING ENTREPRENEURSHIP

A Collection of Indicators

2009 Edition

OECD-Eurostat Entrepreneurship Indicators Programme

ORGANISATION FOR ECONOMIC CO-OPERATION AND DEVELOPMENT

The OECD is a unique forum where the governments of 30 democracies work together to address the economic, social and environmental challenges of globalisation. The OECD is also at the forefront of efforts to understand and to help governments respond to new developments and concerns, such as corporate governance, the information economy and the challenges of an ageing population. The Organisation provides a setting where governments can compare policy experiences, seek answers to common problems, identify good practice and work to co-ordinate domestic and international policies.

The OECD member countries are: Australia, Austria, Belgium, Canada, the Czech Republic, Denmark, Finland, France, Germany, Greece, Hungary, Iceland, Ireland, Italy, Japan, Korea, Luxembourg, Mexico, the Netherlands, New Zealand, Norway, Poland, Portugal, the Slovak Republic, Spain, Sweden, Switzerland, Turkey, the United Kingdom and the United States. The Commission of the European Communities takes part in the work of the OECD.

• • •

This work is published on the responsibility of the Secretary-General of the OECD. The opinions expressed and arguments employed herein do not necessarily reflect the official views of the Organisation or of the governments of its member countries.

© OECD 2009

MEASURING ENTREPRENEURSHIP: A COLLECTION OF INDICATORS – 3

© OECD 2009

Foreword

Entrepreneurship is even higher on the policy agenda today than in the past, as governments look for remedies and ways out of the economic crisis. The economic dynamism inherent in entrepreneurship is believed to be an important way to safeguard the long-run viability and competitiveness of national economies.

While entrepreneurship has attracted greater attention, measurement of entrepreneurship has long been a problem, and remains so. There have been numerous initiatives at the local, regional or national level, and even a few at the international level, but internationally comparable data are scarce. The OECD has addressed entrepreneurship in the past through various analytical studies and reports, but no systematic effort has been made to establish an ongoing database specifically devoted to entrepreneurship across OECD countries.

In 2006 the joint OECD-Eurostat Entrepreneurship Indicators Programme (EIP) was started. Its objective is to develop internationally comparable data on entrepreneurship and to make international comparisons possible and meaningful.

Last year saw the publication of the first results of the EIP and the initiative attracted a good deal of attention from policy makers, researchers and journalists. Encouraged by this, further efforts have been undertaken to develop the EIP programme. The results of these efforts appear in this publication.

First, the geographical coverage has been considerably extended from 18 countries in 2008 to 23 countries in the 2009 publication. Important, too, is the fact that it has been possible to extend the scope of the EIP to emerging countries such as Brazil, which is included in this year’s results. Equally important, this publication also presents data at the regional level; for instance, it is very rewarding to see that the region of Andalucia in Spain has applied EIP definitions at the regional level.

Second, this year’s publication extends the range of indicators significantly not only by calculating more detailed indicators (by industry and by size class), but also by presenting several indicators of entrepreneurial determinants. This allows countries to benchmark their entrepreneurial performance and entrepreneurial determinants and policies.

Third, this year’s entrepreneurship data are more timely. The EIP’s close co-operation with national statistical offices had resulted in the collection of high-quality data, but sometimes at the expense of the timeliness. Following the economic crisis, many requests for more recent empirical evidence were received. This publication therefore presents a first set of timely indicators for a subset of countries and the EIP plans further research on this topic.

This report has been prepared by Benoit Arnaud and Koen De Backer of the Structural Economic Statistics Division of the OECD Statistics Directorate. It should be stressed, however, that the EIP is a strong collaborative effort with Eurostat and its achievements are due to a willing commitment by many national statistics offices to harmonise methods and produce results. The continuing financial and intellectual support of the Kauffman Foundation has allowed the EIP to advance the data collection and indicator development work.

4 – MEASURING ENTREPRENEURSHIP: A COLLECTION OF INDICATORS

© OECD 2009

In addition, the Entrepreneurship Indicators Steering Group plays an important role in the EIP. It discusses the work programme and explores new directions for further research. The input from national delegates, as members of this group, along with representatives from international organisations such as Eurostat, the World Bank and the OECD, is invaluable. A list of their names and affiliations can be found at the end of this report.

We look forward to further developing the EIP in the years to come by engaging more countries, producing more indicators and doing more analytical research. Measuring entrepreneurship has become an integral part of the statistical activities of the OECD. Data and indicators, publications and working papers, and other background information can be found at www.oecd.org/statistics/entrepreneurshipindicators. The OECD will continue its work on measuring entrepreneurship and welcomes the participation of all countries and regions in this important project.

Paul Schreyer Acting Chief Statistician

and Director of the Statistics Directorate


© OECD 2009

The Importance of Entrepreneurship

It is abundantly clear that entrepreneurship is important for economic growth, productivity, innovation and employment, and many OECD countries have made entrepreneurship an explicit policy priority. As globalisation reshapes the international economic landscape and technological change creates greater uncertainty in the world economy, entrepreneurship is believed to offer ways to help to meet new economic, social and environmental challenges.

Entrepreneurship has gained additional attention in the current economic crisis, as it is widely viewed as a key aspect of economic dynamism. Economic crises are historically times of industrial renewal, or creative destruction, as less efficient firms fail while more efficient ones emerge and expand. New business models and new technologies, particularly those leading to cost reductions, often emerge in downturns.

Hence, policy makers look at entrepreneurship in combination with innovation to return to a period of sustained economic growth. Both entrepreneurship and innovation are associated with “doing something new” and policies, if designed appropriately, can be mutually reinforcing in (re-)creating economic dynamism. The dynamic process of new firm creation introduces and disperses innovative products, processes and organisational structures throughout the economy.

Policy makers need to understand the determinants of and obstacles to entrepreneurship because they must analyse the effectiveness of different policy approaches. Ultimately, policy making must be guided, as far as possible, by evidence and facts. The lack of internationally comparable empirical evidence has constrained the understanding of entrepreneurship and many questions remain unanswered.

Of course, entrepreneurship objectives and policies differ considerably among countries, owing to different policy needs and diverse perspectives on what is meant by entrepreneurship. In some countries, entrepreneurship is linked to regional development programmes, and the creation of new firms is stimulated to boost employment and output in depressed regions. In others, entrepreneurship is a key element of strategies designed to facilitate the participation of certain target groups, such as women or minorities, in the economy. Some countries simply seek to increase firm creation as such, while others set out to support high-growth firms.

The OECD aims to provide policy makers and governments with internationally comparable indicators on entrepreneurship, but remaining mindful of the different policy contexts across countries. Different indicators are proposed, each of which represents one element of the broad and complex entrepreneurship phenomenon. As such, the OECD, in association with Eurostat and many others, has developed a new, and more robust, international knowledge base on entrepreneurship.


© OECD 2009

The OECD-Eurostat Entrepreneurship Indicator Programme (EIP)

Over the past ten years, the OECD has addressed entrepreneurship issues in various analyses and reports. While these studies compiled relevant data to support specific research or policy tasks, no effort was made to establish an ongoing database of entrepreneurship across OECD countries. In 2004, the 2nd OECD Ministerial Conference on SMEs in Istanbul, “Promoting Entrepreneurship and Innovative SMEs in a Global Economy”, concluded that the statistical base for entrepreneurship research was weak and urged the OECD to develop “a robust and comparable statistical base on which SME policy can be developed”.

The OECD launched the Entrepreneurship Indicators Programme (EIP) in 2006 in order to build internationally comparable statistics on entrepreneurship and its determinants. In 2007, Eurostat joined forces with the OECD to create a joint OECD-Eurostat EIP, and work began with the development of standard definitions and concepts as a basis for the collection of empirical data.

Entrepreneurship is a multifaceted concept that manifests itself in many different ways, with the result that various definitions have emerged and no single definition has been generally agreed upon. Several definitions have an essentially theoretical basis and are not concerned with measurement. Another strand of research has largely bypassed the question of definition by “defining” entrepreneurship in terms of a specific empirical measure, such as self-employment or the number of small firms. Not surprisingly, these are measures that are readily available.

The OECD-Eurostat approach has tried to combine the more conceptual definitions of entrepreneurship with (available) empirical indicators. Building on the theoretical contributions of Richard Cantillon, Adam Smith, Jean Baptiste Say, Alfred Marshall, Joseph Schumpeter, Israel Kirzner and Frank Knight, among others,1 the following definitions were established:

• Entrepreneurs are those persons (business owners) who seek to generate value through the creation or expansion of economic activity, by identifying and exploiting new products, processes or markets.

• Entrepreneurial activity is enterprising human action in pursuit of the generation of value through the creation or expansion of economic activity, by identifying and exploiting new products, processes or markets.

• Entrepreneurship is the phenomenon associated with entrepreneurial activity.

Given the multifaceted nature of entrepreneurship and the myriad factors that may affect it, establishing a realistic yet relevant set of measures to be produced as core entrepreneurship indicators was a major challenge. Inspired by a number of previous scholarly and policy-oriented studies, a simple entrepreneurship model was proposed

1. For an overview, see N. Ahmad and R. Seymour (2008), “Defining Entrepreneurial Activity: Defining

Supporting Frameworks for Data Collection”, OECD Statistics Working Paper.


© OECD 2009

as a first step towards establishing a framework for the development of empirical indicators that are both relevant and available.2

The first stage of this model (Figure 1) comprises various determinants which policy can affect and which in turn influence entrepreneurial performance, or the amount and type of entrepreneurship that takes place. The final stage is the impact of entrepreneurship on higher-level goals such as economic growth, job creation or poverty reduction. Within each of the three main stages of this model, several sub-categories are identified to flesh out the overall framework and guide the selection of indicators. While the entrepreneurship framework is presented here in a linear fashion, it was explicitly recognised that there are complex relationships among the different main components and subcomponents.

Figure 1.Topic categories for entrepreneurship indicators

Culture

Other indicators of entrepreneurial performance

Poverty reduction

Economic growth

Determinants Entrepreneurialperformance

Impact

Regulatory framework

R&D and technology

Entrepreneurial capabilities Firm-based indicators Job creation

Access to finance

Market conditions Employment-based indicators

The goal of the Entrepreneurship Indicators Programme was to establish a framework of relevant indicators for the study of entrepreneurship and to encourage countries to use the definitions, methodologies and classifications of the framework as much as possible when producing the data. Because the 2005 Feasibility Study on Entrepreneurship Indicators revealed that no OECD country national statistics office (NSO) explicitly included “entrepreneurship statistics” within its programme, the EIP sought to change this by involving the NSOs in designing the specifications for the relevant variables and by involving them in the production of data. As a result, NSOs from several countries have participated in the collection of data.

Given the multifaceted nature of entrepreneurship, the EIP does not propose any single measure as a key to understanding and comparing the amount and type of entrepreneurship that takes place across countries. Since entrepreneurship is a very broad phenomenon which encompasses, for example, virtually all new firm creation, it is extremely important for policy analysts to be able to understand and distinguish different types of entrepreneurial performance.

The rationale for developing entrepreneurship indicators is to help policy makers to understand how the policies they put in place or adjust will affect entrepreneurship and, eventually, higher-level objectives for the economy and society. For countries to benefit from the experience of others, it is also essential that the entrepreneurship indicators allow for comparisons across countries by type of entrepreneurship.

2. N. Ahmad and A. Hoffmann (2008), “A Framework for Addressing and Measuring Entrepreneurship”, OECD

Statistics Working Paper.


© OECD 2009

Results of the Second Round of Empirical Data Collected under the EIP

This publication contains the results of the second round of data collection under the EIP and presents, like last year’s publication, different indicators of entrepreneurial performance. Indicators of firm births, deaths, high-growth firms, gazelles, etc., all capture different aspects of entrepreneurship and different types of entrepreneurs. For example, high priority is placed on measuring the creation of firms with employees, the number of high-growth firms, and the number of young, high-growth firms (gazelles). One might view these indicators as reflecting the evolution of entrepreneurship on a scale of economic importance: high-growth firms require the creation of a firm, typically with employees, and many firms with employees started out initially as individual traders.

The EIP works closely with national statistical offices on developing these indicators of entrepreneurial performance. Indicators are typically calculated on the basis of business registers, with a clear focus on “employer enterprises” (i.e. enterprises with positive employment), in order to safeguard international comparability. When countries’ business registers use different definitions, and especially different thresholds, international comparisons of these data are endangered (especially for enterprises with 0 employees). Table 1 (page 11) presents an overview of the availability of indicators on entrepreneurial performance in different countries.

Compared to last year’s publication, this year’s is more extensive. This reflects the increasing importance accorded to the EIP. First, the geographical coverage has increased significantly, as indicators are collected for 23 geographical units, including one emerging country (Brazil) and one region (Andalucia, Spain). In addition (some) indicators of entrepreneurial performance are calculated at a more detailed level (e.g. size class and industry).

Second, given the growing demand for more timely indicators (notably as a consequence of the economic crisis), this year’s edition makes a first attempt to produce more recent empirical evidence. While business registers allow for the development of solid, internationally comparable indicators, they are not very timely. This edition therefore presents some first results based on different data sources (e.g. administrative data) to analyse more recent trends in entrepreneurship. In the coming years, the EIP will analyse this issue in more detail.

Third, the number of indicators presented has increased significantly, as indicators of entrepreneurial determinants are also included. In filling out this aspect of the EIP framework, various data sources have been used to address this very broad and diverse group of determinants. Survey data are presented in addition to hard data for some indicators, as these are the only available data. Four indicators for each of the six entrepreneurial determinants are presented, but many more could have been included. This represents another area for future EIP work: to collect all possible indicators of entrepreneurial determinants and to analyse them in terms of availability, relevance, international comparability, etc.


© OECD 2009

In this edition, the definition and comparability of the most important indicators are discussed together with the main observations. In order to facilitate the discussion, the indicators have been grouped into sections.

Section A, “Structural indicators on enterprise population”, sketches out the importance of different size classes in terms of enterprises, employment, value added and exports. These indicators can be considered the result of past entrepreneurship, but they also determine the opportunities and boundaries of present and future entrepreneurship.

A.1. Number of enterprises by size class

A.2. Employment by size classA.3. Value added by size class

A.4. Exports by size class Section B, “Entrepreneurial performance”, presents different performance

measures of entrepreneurship such as birth, death and survival rates of employer firms, high-growth firms and gazelles.

B.1. Employer enterprise birth rates (manufacturing and services by industry, by size class)

B.2. Employer enterprise death rates (manufacturing and services, by industry, by size class)

B.3. One- and two-year survival rates (manufacturing and services) B.4. Share of one- and two-year-old employer enterprises in the population

(manufacturing and services) B.5. Share of high-growth firms (employment)B.6. Share of high-growth firms (turnover)

B.7. Share of gazelles (employment)B.8. Share of gazelles (turnover)

B.9. Employment creation by enterprise birthsB.10 Employment creation by enterprise deaths

Section C, “Timely indicators of entrepreneurship” shows the first results of using other data sources to develop insights on recent trends in entrepreneurship. Data are presented for a subset of countries, but as already mentioned, more countries are to be included in the future.

C.1. Timely indicators on enterprise entries for selected countries C.2. Timely indicators on enterprise exits for selected countries


© OECD 2009

Section D, “Entrepreneurial determinants” presents different indicators for the six groups of entrepreneurial determinants within the EIP framework. The choice of indicators is based on their availability and the possibility to update them on a regular basis. Information on the quality of the indicators (comparability in terms of accuracy and availability) is also discussed.

D.1. Knowledge creation and diffusion D.1.a. Business R&D intensity, by size class of firms D.1.b. Firms with new-to-market innovations, by size

D.1.c. Firms collaborating on innovation, by size D.1.d Turnover from e-commerce

D.2. Access to finance D.2.a Ease of access to loans

D.2.b. Business angels (networks) D.2.c. Venture capital investments D.2.d. Share of high-technology sectors in total venture capital

D.3. Entrepreneurial capabilities D.3.a. Population with tertiary education

D.3.b. Self-employment by place of birth D.3.c. International students in tertiary education D.3.d. Population aged 18-64 with training in starting a business

D.4. Regulatory framework D.4.a. Ease of doing business

D.4.b. Barriers to entrepreneurship D.4.c. Top statutory personal income tax rate

D.4.d. Top statutory corporate income tax rateD.5. Market conditions D.5.a./b. Competition law and policy indicator (main components)

D.5.c. Import burden D.5.d. Export burden

D.6. Entrepreneurial culture D.6.a. Preference for self-employment

D.6.b. Entrepreneurial perceptions D.6.c. Positive image of entrepreneurship and entrepreneurs D.6.d. Negative image of entrepreneurship and entrepreneurs

The graphs in the following pages present the indicators of entrepreneurship performance and determinants across countries. They give interesting information but should not be understood to rank individual countries in terms of their level of entrepreneurship. Indeed, one of the main observations arising from the empirical evidence is the difference in countries’ entrepreneurial regimes and thus the need for a differentiated analysis, while controlling for differences among countries, industries and enterprises.


© OECD 2009

Table 1. Availability of indicators across countries

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© OECD 2009

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© OECD 2009

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Bulgaria x x x x x x x x x x x x x x x x x x x x x

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Israel x x x x x x x x x

Lithuania x x x x x x x x x x x x x x x x x x x x x x x

Latvia x x x x x x x x x x x x x

Romania x x x x x x x x x x x x x x x x x x x x x

Slovenia x x x x x x x x x x x x

Andalucia x x x x x x x x x


© OECD 2009

A. STRUCTURAL INDICATORS ON ENTERPRISE POPULATION

Definitions

An enterprise is a legal entity possessing the right to conduct business on its own, for example to enter into contracts, own property, incur liabilities for debts and establish bank accounts. It may consist of one or more local units or establishments corresponding to different production units situated in a geographically separate place and in which one or more persons work for the enterprise to which they belong.

The total number of persons engaged is defined as the total number of persons who worked in or for the concerned unit during the reference year.

Total employment excludes directors of incorporated enterprises and members of shareholders’ committees who are paid solely for their attendance at meetings, labour force made available to the concerned unit by other units and charged for, persons carrying out repair and maintenance work in the unit on the behalf of other units, and home workers. It also excludes persons on indefinite leave, military leave or those whose only remuneration from the enterprise is by way of a pension.

Comparability

All countries present information using the enterprise as the statistical unit except Japan, Korea and Mexico, which use establishments. This may create some lack of comparability but, because most enterprises are also establishments, this is not expected to be significant.

An area, in which considerable differences do arise, however, is the coverage of data on enterprises or establishments. In many countries, this information is based on business registers, economic censuses or surveys that may have a size-class cut-off. Indeed, all countries have thresholds of one sort or another, depending, often, on the tax legislation and permissible business burdens in place across countries. For Ireland, only enterprises with three or more persons engaged are covered, while the data for Japan and Korea do not include establishments with fewer than four and five persons engaged, respectively (for information, see OECD SDBS database).

Enterprises that operate purely in the underground economy will naturally be very difficult, if not impossible, to capture, and these are most likely to be small. However, despite these differences, it is possible to make sensible comparisons across countries.

The size-class breakdown used provides for the best comparability given the varying data collection practices across countries. Some countries use slightly different conventions. Data shown for “20-49” actually refer to “20-99” for the United States; data shown for “50-249”

actually refer to “50-199” for Australia and Korea, “50-99” for New Zealand and “100-499” for the United States; data shown for “250+” actually refer to “200+” for Australia and Korea, “100+” for New Zealand and “500+” for the United States.

Data typically refer to the total market economy excluding financial intermediation (ISIC 65-67), but for the “Number of enterprises” it also excludes Mining and Electricity, gas and water supply for Belgium, Greece and Hungary, while for “Employment”, it also excludes Mining and Electricity, gas and water supply for Austria, Belgium, Estonia, Finland, Greece, Hungary, the Netherlands, Portugal and Slovenia. Data for Ireland, Japan, Korea, Luxembourg and the Slovak Republic refer to manufacturing only.

Overview

Since the presented indicators reflect structural characteristics of the business sector across countries, observations do not change much from one year to the next. Hence, they are in line with the observations made last year.

The large majority of enterprises are so-called micro-firms: firms with fewer than ten employees represent three-quarters or more of the employer firm population in most countries. Their importance is somewhat smaller in a couple of countries but this seems due to differences in data collection and coverage (Ireland, Korea, Japan, Luxembourg and the Slovak Republic). In the United States micro-firms are less prominent.

The importance of micro-firms is much smaller in terms of employment with a share below 40% in all countries. In most countries micro-firms are responsible for between 20% and 30% of total employment in the economy. The employment share of large firms averages between 30% and 40% across countries. The employment share of the middle size classes of firms, especially firms with 10-50 employees, is significantly lower in all countries. This largely reflects the claim made in empirical research that young entrepreneurial firms face difficulties for attaining higher growth after their first years of existence.

Source OECD Structural and Demographic Business Statistics

(SDBS) Database.

For further reading Statistical publication

OECD (forthcoming), Structural and Demographic Business Statistics 2000-2007, OECD, Paris.


© OECD 2009

A.1-A.2 Number of enterprises and employment by size class

Number of enterprises1,2

By size class, 20063

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1-9 10-19 20-49 50-249 250+

1. Market economy, excluding financial intermediation. Manufacturing sectors only for Ireland, Japan, Korea, Luxembourg and the Slovak Republic. 2. Number of establishments for Korea, Japan and Mexico. 3. 2005 for Iceland, 2004 for the United States, 2003 for Mexico. 4. Enterprises with 3 or more persons engaged. 5. Establishments with 5 or more persons engaged. 6. Establishments with 4 or more persons engaged. 7. Data are based on the Establishments& Business Frame of the Regional Statistical Institute of Andalucia (IEA). The data refer to establishments and enterprises with 4 or more persons engaged in an economic activity in Andalucia; they contain active enterprises with headquarters in Andalucia as well as active establishments with headquarters outside Andalucia.

Employment1,2

Number of persons engaged, by size class, 20063

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1-9 10-19 20-49 50-249 250+

1. Market economy, excluding financial intermediation. Manufacturing sectors only for Ireland, Japan, Korea, Luxembourg and the Slovak Republic. 2. Number of employees for New Zealand and the United States. 3. 2004 for the United States, 2003 for Mexico. 4. Enterprises with 3 or more persons engaged. 5. Establishments with 4 or more persons engaged. 6. Establishments with 5 or more persons engaged. 7. Data are based on the Establishments& Business Frame of the Regional Statistical Institute of Andalucia (IEA). The data refer to establishments and enterprises with 4 or more persons engaged in an economic activity in Andalucia; they contain active enterprises with headquarters in Andalucia as well as active establishments with headquarters outside Andalucia.


© OECD 2009

A. STRUCTURAL INDICATORS ON ENTERPRISE POPULATION

Definitions

Value added

Value added corresponds to the difference between production and any intermediate consumption; the definition used here for intermediate consumption varies, depending on the valuation used for value added.

The valuation of value added can be made according to any of the following: factor costs, basic prices, market prices and producers’ prices, depending on the treatment applied to indirect taxes and subsidies.

Trade

Export data are compiled according to the EU harmonised concept (special trade), including processing. Exports by size classes describe the contribution of enterprises of different sizes to total exports. This allows for analysing the impact of trade on employment.

Comparability

Value added

Data refer to value added at factor costs in the EU countries and value added at basic prices for Australia, Japan and Korea.

All countries present information using the enterprise as the statistical unit except Japan, Korea and Mexico, which use establishments.

For Ireland, only enterprises with three or more persons engaged are covered, while the data for Japan and Korea do not include establishments with fewer than four and five persons engaged, respectively.

The size class breakdown used provides for the best comparability across countries given the varying data collection practices across countries. Some countries use slightly different conventions. Data shown for “50-249” actually refer to “50-199” for Australia, and Korea; data shown for “250+” actually refer to “200+” for Australia and Korea.

Data typically refer to the total market economy excluding financial intermediation (ISIC 65-67), but for a certain number of countries, they also exclude Mining and Electricity, gas and water supply. Data for Japan, Korea, Luxembourg, the Netherlands and the Slovak Republic refer to Manufacturing only.

Trade

Data on intra-EU and extra-EU exports are treated separately, owing to different data collection systems and thresholds. Total exports are compiled by adding intra-EU and extra-EU exports. Since the data refer to years before the recent EU enlargement, exports between the pre-enlargement EU countries and the new EU countries are treated as extra-EU exports.

Overview

The importance of large firms, i.e. firms with more than 250 employees, is more pronounced in terms of value added and exports. In the majority of countries large firms account for close to 50% of value added. In countries such as Italy and Greece, however, firms in smaller size classes are responsible for more than 40% of the value added created in the country. The group of smallest firms (i.e. micro-firms) accounts for a major share of the creation of value added in these countries.

Because of the importance of scale economies and fixed costs in exporting, micro (1-9 employees) and small (10-49 employees) firms represent only a small share of total exports. Large firms are responsible for the majority of exports in most countries. Previous research has shown that multinational enterprises play a major role, as they often localise production and exporting facilities in one country to service not only that country’s market but also markets in neighbouring countries.

Source Eurostat (2009), External Trade by Enterprise

Characteristics

OECD Structural and Demographic Business Statistics (SDBS) Database.

For further reading Eurostat (2006), External Trade by Enterprise

Characteristics, Methodologies and Working Papers (trade data).

OECD (forthcoming), Structural and Demographic Business Statistics 2000-2007, OECD, Paris

OECD (2008), “Linking Trade with Structural Business Statistics: OECD Progress Report”, paper prepared for the Working Party on International Trade in Goods and Trade in Services Statistics, OECD, Paris.


© OECD 2009

A.3-A.4 Value added and exports by size class

Value added1

By size class, 20062

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

1-9 10-19 20-49 50-249 250+

1. Market economy, excluding financial intermediation. Manufacturing sectors only for Ireland, Japan, Korea, Luxembourg, Netherlands and the Slovak Republic. 2. 2003 for Mexico. 3. Enterprises with 3 or more persons engaged. 4. Establishments with 4 or more persons engaged. 5. Establishments with 5 or more persons engaged.

Exports1

2003, as a percentage of total value

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

0-9 10-49 50-249 250+ Unknown

1. Total economy.

Source: OECD Trade by Enterprise Characteristics (TEC) Database.


© OECD 2009

B. ENTREPRENEURIAL PERFORMANCE

Definitions An employer enterprise birth refers to the birth of an enterprise with at least one employee. The population of employer enterprise births consists first of "new” enterprise births, i.e. new enterprises reporting at least one employee in the birth year; and second, enterprises that existed before the year under consideration but were then below the threshold of one employee (and reported 1 or more employees in the current, i.e. birth, year).

Symmetrically, an employer enterprise death occurs either as the death of an enterprise with at least one employee in the year of death or by moving below the threshold of one employee.

The employer enterprise birth and death rates are compiled as the number of births and deaths of employer enterprises, respectively, as a percentage of the population of active enterprises with at least one employee.

Comparability

“Employer” indicators are found to be more relevant for international comparisons than indicators covering all enterprises, as the latter are sensitive to the coverage of business registers.

In the EU, in theory, all enterprises should be included in the business register and so, again in theory, enterprise births should be comparable. But even in EU countries, not all enterprises are in fact included, as all countries adopt some size threshold for inclusion in the business register; therefore, there are international differences, typically in the coverage of smaller enterprises. The difference with non-EU countries is even greater.

The concept of employer enterprise birth itself is not without problems. Many countries have sizeable populations of self-employed. If a particular country creates incentives for the self-employed to become employees of their own company the total number of employer enterprise births will increase. While it is arguable that, from an economic and entrepreneurial perspective, little has changed, this can distort comparisons over time and of course across countries.

Overview

Birth and death rates were relatively stable over the years 2005 and 2006: most countries report rather small (less than 1 percentage point) changes in both the number of births and deaths; exceptions are Canada, Italy, Romania and the Slovak Republic (in birth rates) and Estonia, Luxembourg, the Slovak Republic and the United States (in death rates).

This stable pattern confirms the observation already made for 2005, namely that birth and death rates are

fairly similar across countries. Birth and death rates are still higher in eastern European countries but only in manufacturing. The economic restructuring in these countries after their accession to the EU still seems to play an important role in this sector. Also Brazil shows relatively high birth and death rates; the high rates for the region of Andalucia might partially reflect the relocation within Spain of firms to and from Andalucia.

Turbulence is structurally higher in services than in manufacturing. In all countries birth and death rates are significantly higher in services, resulting in a net entry of enterprises in most countries. The picture is less clear in manufacturing since the relatively lower birth and death rates result in some (especially eastern European) countries in a net entry, while in others there was a net exit of enterprises in 2006.

Presenting birth and death rates for a subset of individual industries largely confirms these observations. Turbulence is especially significant in “Other business activities” (consulting, software, etc.) and markedly lower in manufacturing of food and beverages and electrical and optical equipment. Maybe surprisingly, no major differences are observed between these low- and high-technology industries.

Analysing birth and death rates by size class of enterprises provides some additional insights. First, births and deaths are concentrated in the smaller size classes. Most entry happens on a smaller scale as firms work towards their optimal size. This is directly correlated to large exits of smaller firms since a significant part of small entrants typically exit in their first years after entry.

A second observation is that births and deaths of small enterprises are concentrated in the services sector. In manufacturing industries the need for scale economies requires a large minimum efficient scale, so that entry (and exit) more often occur on a larger scale.


(SDBS) Database.

For further reading Ahmad, N. (2006), A Proposed Framework for

Business Demography Statistics, OECD, Paris.

Eurostat/OECD (2007), Eurostat-OECD Manual on Business Demography Statistics, OECD, Paris.



© OECD 2009

B.1-B.2 Employer enterprise births and deaths

Employer enterprise birth and death rates in manufacturing1

As a percentage of the population of active enterprises with at least one employee (figures above the bar indicate change from previous year)

0 0 -0.4 -0.3 -0.1 0.2

0.5-0.3 0 0.1 2.1 -1.4 -0.6 0.1 0.6 -3.2 4.1 2.4

+ 0.3 -0.3

-1.4 -0.2

-0.7

-1.4 0.11.3

-0.5

0.3 5.4

0

-1.70.8 0.8

0

2

4

6

8

10

12

14

16

18

Employer birth rate (2006) Employer death rate (2005)

Change from previous year

1. Mining and quarrying; Manufacturing; Electricity, gas and water. 2. Employer enterprises with less than 250 employees. 3. Data are based on the Establishments & Business Frame of the Regional Statistical Institute of Andalucia (IEA). The data refer to establishments and enterprises with 4 or more persons engaged in an economic activity in Andalucia; they cover active enterprises with headquarters in Andalucia as well as active establishments with headquarters outside Andalucia. Birth (death) rates also include enterprises and establishment relocations within Spain to (from) Andalucia.

Employer enterprise birth and death rates in services1

As a percentage of the population of active enterprises with at least one employee (figures above the bar indicate change from previous year)

0.6

-0.1 -0.5 -0.4 0.6-0.8

-4 0.6 -0.6 -0.5 -1 -3.9 0.8 1.7 3.3 0.11.4

2.1

0

1 1.5

-0.2

7.4-1.6

-0.3

0.61.3

-0.2 0.6

0.7

0.7

-0.4-0.2

0

2

4

6

8

10

12

14

16

18


Change from previous yearChange from previous yearChange from previous yearChange from previous yearChange from previous yearChange from previous year

-1.2

1. Wholesale and retail trade; Hotels and restaurants; Transport, storage and communications; Financial intermediation; Real estate, renting and business activities. 2. Employer enterprises with fewer than 250 employees. 3. Data are based on the Establishments & Business Frame of the Regional Statistical Institute of Andalucia (IEA). The data refer to establishments and enterprises with 4 or more persons engaged in an economic activity in Andalucia; they cover active enterprises with headquarters in Andalucia as well as active establishments with headquarters outside Andalucia. Birth (death) rates also include enterprises and establishment relocations within Spain to (from) Andalucia.


© OECD 2009


Employer enterprise birth rates in manufacturing1 by size class, 2006

As a percentage of the population of active enterprises with at least one employee

0

4

8

12

16

20

24

1 to 4 5 to 9 10+

1. Mining and quarrying; Manufacturing; Electricity, gas and water. 2. Employer enterprises with fewer than 250 employees.

Employer enterprise death rates in manufacturing1 by size class, 2005


0

4

8

12

16

20

24

1 to 4 5 to 9 10+

1. Mining and quarrying; Manufacturing; Electricity, gas and water. 2. Employer enterprises with fewer than 250 employees.


© OECD 2009


Employer enterprise birth rates in services1 by size class, 2006


0

4

8

12

16

20

24

1 to 4 5 to 9 10+

1.Wholesale and retail trade; Hotels and restaurants; Transport, storage and communications; Financial intermediation; Real estate, renting and business activities. 2. Employer enterprises with fewer than 250 employees.

Employer enterprise death rates in services1 by size class, 2005


0

4

8

12

16

20

24

1 to 4 5 to 9 10+

1.Wholesale and retail trade; Hotels and restaurants; Transport, storage and communications; Financial intermediation; Real estate, renting and business activities. 2. Employer enterprises with fewer than 250 employees.


© OECD 2009


Employer enterprise birth and death rates in manufacture of food, beverage and tobacco1


0

2

4

6

8

10

12

14

16

18


1.15-16, ISIC Rev. 3.

Employer enterprise birth and death rates in manufacture of electrical and optical equipment1


0

2

4

6

8

10

12

14

16

18


1.30-33, ISIC Rev. 3.


© OECD 2009


Employer enterprise birth and death rates in wholesale and retail trade1


0

2

4

6

8

10

12

14

16

18


1.50-52, ISIC Rev. 3. 2. Employer enterprises with fewer than 250 employees.

Employer enterprise birth and death rates in other services activities1


0

2

4

6

8

10

12

14

16

18


1.74, ISIC Rev. 3.


© OECD 2009


Definitions

The survival rate reflects the number of enterprises of a specific birth cohort that have survived over different years. The (t-n) survival rate is calculated as the number of n-year survival enterprises as a percentage of all enterprises that reported at least one employee for the first time in year (t-n).

The number of n-year survival enterprises for a particular year (t) refers to the number of enterprises which had at least one employee for the first time in year (t-n) and did not die in year (t).

An enterprise is also considered to have survived if the linked legal unit(s) has(ve) ceased to be active, but their activity has been taken over by a new legal unit set up specifically to take over the factors of production of that enterprise (survival by takeover).

This definition of survival excludes cases in which enterprises merge or are taken over by an existing enterprise in year (t-n).

The survival of an enterprise is an event that should always be observed between two consecutive years. For instance, an enterprise born in year (t-2) should be considered as having survived to (t) only if it was active also in year (t-1), and so forth.

Comparability


Owing to the recent start of the collection of entrepreneurship indicators, only one-year survival (for two different cohorts of enterprises) and two-year survival rates (for only one cohort) are presented. Survival rates are displayed for cohorts of employer firms started in 2005 and 2004. Further rounds of data collection will allow for additional survival rates (one-year, two-year, three-year, etc.).

Overview

Survival rates reflect how companies perform in the years after their start-up if they are able to survive. Empirical research has shown that a significant number of new entrants leave the industry in the first year(s) after start-up.

The data on one-year survival seem to show that in most countries the cohort of enterprises started in 2005 survived slightly better than the cohort started in 2004 in their first year. This may be related to a better economic climate as 2006 was characterised by strong economic growth in most countries. It will be interesting to collect data during the coming years in order to analyse the impact of the economic crisis on the survival of new firms.

Nevertheless some countries, among which eastern European countries such as Lithuania, Romania and the Slovak Republic, show lower one-year survival rates for the 2005 cohort, in manufacturing as well as services. The high birth rates reported for 2005 in these countries seem to result in a significant fallout during the first year.

Data on two-year survival show that a number of enterprises also exit the industry in their second year after start-up, but fewer than in the first year. While the one-year survival rate varies between 75% and 90% for the cohort of 2004 births, the second-year survival rate seems to lie between 65% and 80%.

As observed for 2005, survival rates are slightly higher in manufacturing. This may be due to the typically higher entry (and exit) costs in these industries. The smaller entry and exit costs in the services sector allow more readily for trial and error by firms (e.g. active and passive learning, experimentation).

A related observation is that there is a slightly smaller difference between the two-year and one-year survival rates in manufacturing. This may again be related to higher entry and exit costs: in order not to incur these costs unnecessarily, enterprises in manufacturing become better informed about their true potential and correspondingly self-select better before entering.


(SDBS) Database.



Eurostat/OECD (2007), Eurostat-OECD Manual on Business Demography Statistics, OECD, Paris



© OECD 2009

B.3 Survival rates

One- and two-year survival rates in manufacturing,1 2006

As a percentage of the respective 2004 and 2005 population of employer enterprise births

0

10

20

30

40

50

60

70

80

90

100

1-year survival rate (2004 cohort) 2-year survival rate (2004 cohort) 1-year survival rate (2005 cohort)

1. Mining and quarrying; Manufacturing; Electricity, gas and water. 2. Employer enterprises with less than 250 employees. 3. Data are based on the Establishments & Business Frame of the Regional Statistical Institute of Andalucia (IEA). The data refer to establishments and enterprises with 4 or more persons engaged in an economic activity in Andalucia; they cover active enterprises with headquarters in Andalucia as well as active establishments with headquarters outside Andalucia.

One- and two-year survival rates in services,1 2006

As a percentage of the respective 2004 and 2005 population of employer enterprise births

0

10

20

30

40

50

60

70

80

90

100

1-year survival rate (2004 cohort) 2-year survival rate (2004 cohort) 1-year survival rate (2005 cohort)

1. Wholesale and retail trade; Hotels and restaurants; Transport, storage and communications; Financial intermediation; Real estate, renting and business activities. 2. Employer enterprises with fewer than 250 employees. 3. Data are based on the Establishments & Business Frame of the Regional Statistical Institute of Andalucia (IEA). The data refer to establishments and enterprises with 4 or more persons engaged in an economic activity in Andalucia; they cover active enterprises with headquarters in Andalucia as well as active establishments with headquarters outside Andalucia.


© OECD 2009


Definitions

The share of n-year-old employer firms for a particular year (t) refers to the number of n-year survival enterprises as a percentage of the total enterprise population in year (t).

The number of n-year survival enterprises for a particular year (t) is the number of enterprises which have at least one employee for the first time in year (t-n) and which have not died in year (t).

An enterprise is also considered to have survived if the linked legal unit(s) has(ve) ceased to be active, but their activity has been taken over by a new legal unit set up specifically to take over the factors of production of that enterprise (survival by takeover).

This definition of survival excludes cases in which enterprises merge or are taken over by an existing enterprise in year (t-n).

The survival of an enterprise is an event that should always be observed between two consecutive years. For instance, an enterprise born in year (t-2) should be considered as having survived to (t) only if it was active also in year (t-1), and so forth.

Comparability


Owing to the recent start of the collection of entrepreneurship indicators, only shares of one-year-old and two-year-old employer firms are presented, i.e. for cohorts of employer firms started in 2005 and 2004, respectively. Further rounds of data collection will allow for additional shares of employer enterprises by age (one-year-old, two-year-old, three-year-old, etc.).

Overview

The share of the group of one- and two-year-old firms gives an idea of the (beginning) age distribution of enterprises across countries. The indicator presented expresses the importance of young firms in the total number of enterprises active in the industry. It would be interesting also to have information on the share in total employment, for instance. As such, not only the survival of new entrants, but also their growth performance in the industry would be taken into account.

Young firms are observed to be important players across countries; in a number of countries, among which several

eastern European countries, one- and two- year old firms represent 15% or more of the total number of enterprises. This reflects the specific entrepreneurial regime in these countries following their accession to the EU and the benefits for start-ups and young enterprises of the increased economic space.

The share of two-year-old enterprises is a bit smaller than the share of one-year-old enterprises, owing to relatively high birth rates in 2005 combined with the enterprise exits in the second year. It is clear that the importance in terms of employment rather than number of enterprises might lead to different results, if two-year old firms are able to grow significantly after their start-up year.

Younger firms are observed to be more important in the services sector than in manufacturing. The lesser importance of one-year-old firms in manufacturing industries may be related to lower birth rates in these industries and higher survival rates (resulting in more active firms). At the same time, it reflects the lesser degree of turbulence of manufacturing, where older, large incumbent firms have acquired a strong competitive position over the years.


(SDBS) Database.





.


© OECD 2009

B.4 Share of enterprises by age

Share of one- and two-year-old employer enterprises in manufacturing,1 2006

As a percentage of the total population of employer enterprises

0

2

4

6

8

10

12

14

16

18

20

Share of one-year old enterprises Share of two-year old enterprises

1. Mining and quarrying; Manufacturing; Electricity, gas and water. 2. Employer enterprises with fewer than 250 employees. 3. Data are based on the Establishments & Business Frame of the Regional Statistical Institute of Andalucia (IEA). The data refer to establishments and enterprises with 4 or more persons engaged in an economic activity in Andalucia; they cover active enterprises with headquarters in Andalucia as well as active establishments with headquarters outside Andalucia.

Share of one- and two-year-old employer enterprises in services,1 2006

As a percentage of the total population of employer enterprises

0

2

4

6

8

10

12

14

16

18

20

Share of one-year old enterprises Share of two-year old enterprises

1. Wholesale and retail trade; Hotels and restaurants; Transport, storage and communications; Financial intermediation; Real estate, renting and business activities. 2. Employer enterprises with fewer than 250 employees. 3. Data are based on the Establishments & Business Frame of the Regional Statistical Institute of Andalucia (IEA). The data refer to establishments and enterprises with 4 or more persons engaged in an economic activity in Andalucia; they cover active enterprises with headquarters in Andalucia as well as active establishments with headquarters outside Andalucia.


© OECD 2009


Definitions

High-growth enterprises, as measured by employment (or by turnover), are enterprises with average annualised growth in employees (or in turnover) greater than 20% a year, over a three-year period, and with ten or more employees at the beginning of the observation period.

The share of high-growth enterprises is compiled as the number of high-growth enterprises as a percentage of the population of enterprises with ten or more employees.

Comparability

A size threshold of ten employees was set to avoid having the growth of very small enterprises distort the picture. On the other hand, the size threshold has to be low enough to avoid excluding too many enterprises. It is clear that an absolute threshold will affect countries and industries differently, depending on their size.

The size threshold of ten or more employees holds for both the turnover and employment measures. The advantage is that the initial population is the same, regardless of whether growth is measured in employment or turnover. Moreover, it would be difficult to apply a consistent turnover threshold across all countries because of exchange rates, inflation, etc.

Overview

In addition to enterprise births (and deaths), policy makers prioritise high-growth enterprises as a source of entrepreneurial dynamism. It is believed that these are an important driver of increased economic growth and net employment growth.

Comparing the data for high-growth enterprises between 2005 and 2006 leads to observations similar to those made for enterprise births and deaths. First, the importance of high-growth enterprises is relatively stable over these two years, with rather small changes for most countries. It will be interesting to see in the coming years whether the economic crisis affects these enterprises, as is widely expected.

Second, as in 2005, eastern European countries report a greater importance of high-growth enterprises (both in employment and in turnover), but their performance is less strong in 2006. Other countries report a high degree of entrepreneurial dynamism, especially in the services sector, in terms of enterprise births and deaths and high-growth enterprises. Brazil also reports a large number of high-growth enterprises in 2006.

Further on, enterprises appear to grow faster in terms of turnover than of employment, as witnessed by the significantly higher shares of high-growth enterprises for which high growth is defined in terms of turnover. This is most likely related to the relatively high costs of labour in most countries.

Finally, high-growth manufacturing enterprises are quite concentrated in a limited number of countries. The importance of high-growth enterprises (in terms of employment and of turnover) is more equal across countries in the services sector.


(SDBS) Database. For further reading Ahmad, N. (2006), A Proposed Framework for

Business Demography Statistics, OECD, Paris

Ahmad, N. and D. Rude Petersen (2007), High-Growth Enterprises and Gazelles – Preliminary and Summary Sensitivity Analysis, OECD-FORA, Paris.

Ahmad, N. and E. Gonnard, (2007), “High-growth Enterprises and Gazelles”, paper prepared for the International Consortium on Entrepreneurship (ICE), Copenhagen, Denmark.


Hoffmann, A. and M. Junge (2006), “Comparing the Number of High-growth Entrepreneurs across 17 Countries”, FORA Working Paper.


The OECD Entrepreneurship Indicators Programme: Workshop on the Measurement of High-growth Enterprises, 19 November 2007, Paris, www.oecd.org/document/31/0,3343,en_2649_34233_39151327_1_1_1_100.html.


© OECD 2009

B.5-B.6 High-growth enterprises

Share of high-growth enterprises (employment definition), 2006

As a percentage of all enterprises with 10 or more employees (figures above the bar indicate change from previous year)

-0.2

0.5 0-0.1

1.2-0.5

0.2

0.9

-1.6

61.2

0.2

-0.1

0.1

0.2 0.1 0.6-0.2

0.60.3

-1.2

2.9

1

0

1

2

3

4

5

6

7

8

9

10

Manufacturing (1) (2006) Services (2) (2006)


1. Mining and quarrying; Manufacturing; Electricity, gas and water. 2. Wholesale and retail trade; Hotels and restaurants; Transport, storage and communications; Financial intermediation; Real estate, renting and business activities. 3. Employer enterprises with fewer than 250 employees.

Share of high-growth enterprises (turnover definition), 2006


1.1

2.8 1.4 1.10.8

42.4

3.7 4.6

2.50.7

-0.4

-0.80.4

2.4

0.5

5.74.9

0

5

10

15

20

25

Manufacturing(1) (2006) Services(2) (2006)




© OECD 2009


Definitions

Gazelle enterprises form a subset of the group of high-growth enterprises; they are high-growth enterprises born five years or less before the end of the three-year observation period.

In other words, measured in terms of employment (or of turnover) gazelles are enterprises which have been employers for a period of up to five years, with average annualised growth in employees (or in turnover) greater than 20% a year over a three-year period and with ten or more employees at the beginning of the observation period.

As in the case of high-growth enterprises generally, the share of gazelles is expressed as a percentage of the population of enterprises with ten or more employees.

Comparability

A size threshold of ten employees was set to avoid having the growth of very small enterprises distort the picture. On the other hand, the size threshold has to be low enough to avoid excluding too many enterprises. It is clear that an absolute threshold like this will affect countries and industries differently, depending on their size.

The size threshold of ten or more employees holds for both the turnover and employment measures. The advantage is that the initial population is the same, regardless of whether growth is measured in employment or turnover. Moreover, it would be difficult to apply a consistent turnover threshold across all countries because of exchange rates, inflation, etc.

Overview

As in 2005, the group of young high-growth firms or gazelles is quite small in most countries. Except in Bulgaria, the share of gazelles is less than 1% in manufacturing and services when high growth is measured in terms of employment and less than 2% when measured in terms of turnover.

As such, the group of gazelles represents roughly 10% to 15% of the total group of high-growth enterprises. It would be interesting to contrast this figure (number of enterprises) with the importance of gazelles in terms of employment, as academic research claims that high- growth firms and especially gazelles are responsible for the largest part of net employment growth.

The importance of gazelles has not changed significantly across countries, even less than the group of high-growth

enterprises. However, in contrast to high-growth companies in general, gazelles seem to be more prominent in eastern European countries.

A couple of observations about high-growth enterprises also hold for gazelles. First, gazelles are more important when high growth is defined in terms of turnover rather than employment.

Second, high growth in young manufacturing firms is more likely to occur in terms of turnover, while in services high growth in gazelles occurs in terms of both employment and turnover

Third, the number of gazelles in manufacturing is concentrated in a couple of countries, while the importance of gazelles in services is more evenly spread over the different countries.


(SDBS) Database.


Business Demography Statistics, OECD, Paris

Ahmad, N. and E. Gonnard, (2007), “High-growth Enterprises and Gazelles”, paper prepared for the International Consortium on Entrepreneurship (ICE), Copenhagen, Denmark.

Ahmad, N. and D. Rude Petersen (2007), High-Growth Enterprises and Gazelles – Preliminary and Summary Sensitivity Analysis, OECD-FORA, Paris.

Hoffmann, A. and M. Junge (2006), “Comparing the Number of High-growth Entrepreneurs across 17 Countries”, FORA Working Paper.



The OECD Entrepreneurship Indicators Programme: Workshop on the Measurement of High-growth Enterprises, 19 November 2007, Paris, www.oecd.org/document/31/0,3343,en_2649_34233_39151327_1_1_1_100.html.


© OECD 2009

B.7-B.8 Gazelles

Share of gazelles (employment definition), 2006


-0.2 0 -0.3 0.2 0 0.2 -0.1

-0.10.2

0.5

-0.2

-0.1

0

0.2

-0.1-0.1 -0.1 -0.4

-0.1

0

0

0.5

1

1.5

2

2.5

3



1. Mining and quarrying; Manufacturing; Electricity, gas and water. 2. Wholesale and retail trade; Hotels and restaurants; Transport, storage and communications; Financial intermediation; Real estate, renting and business activities. 3. Employer enterprises with fewer than 250 employees. 4. 2008.

Share of gazelles (turnover definition), 2006


-0.9-0.1 0.1 -0.2

0.7

0.20.3

1

-0.2-0.2 -0.1

-0.50.8

-0.2 -0.1

0.9

0

0.5

1

1.5

2

2.5

3

3.5

4

4.5

5





© OECD 2009


Definitions

Creation of employment is measured as the number of persons employed in the reference period (t) in enterprises newly born in (t) divided by the number of persons employed in (t) in the stock of active enterprises.

Symmetrically, the destruction of employment is measured as the number of persons employed in the reference period (t) in exiting enterprises divided by the number of persons employed in (t) in the stock of active enterprises.

Comparability

“Employer” indicators are more relevant for international comparisons than indicators covering all enterprises, as the latter are sensitive to the coverage of business registers.

In the EU, in theory, all enterprises should be included in the business register and so, again in theory, enterprise births should be comparable. But even in EU countries, not all enterprises are in fact included, as all countries use some size threshold for businesses included in the business register. Therefore, there will be international differences, typically in the coverage of smaller enterprises. The difference with non-EU countries is even greater.

Even the concept of employer enterprise birth is not without problems. Many countries have sizeable populations of self-employed. If a particular country creates incentives for the self-employed to become employees of their own company, the total number of employer enterprise births will increase. While it is arguable that, from an economic and entrepreneurial perspective, little has changed, this can distort comparisons over time and of course across countries.

Overview

The birth of new enterprises and the death of existing enterprises characterise the entrepreneurial dynamism of countries and contribute directly to the aggregate growth of employment in national economies. Previous research has discussed the contributions of enterprise births and deaths, as well as high-growth enterprises and gazelles.

Overall, employment creation through enterprise births exceeds employment destruction, i.e. the churning of firms through entry and exits results in a net employment gain on average. Nevertheless, important differences exist among countries: in Romania and Spain (to a lesser extent) there is clear net creation of employment as the result of the birth and death of

enterprises, while in Hungary and Denmark there is net destruction of employment.

Comparing the data for 2005 and 2006 does not afford clear insights. In some countries, the contribution to employment creation (destruction) by enterprise births (deaths) has fallen, while it has increased in others. In each case the link between employment and birth and deaths rates, which are measured in terms of numbers of enterprises, does not appear to differ markedly across countries.

The employment effects of enterprise births and deaths clearly differ between manufacturing and services industries in all countries. Employment creation by enterprise births seems to be especially realised in services industries. This is in line with the typically higher birth rates reported earlier. The number of extra jobs created by start-ups in manufacturing is on average smaller. Nevertheless, new firms seem to contribute relatively more to the expansion of manufacturing industry in eastern European countries.

Also, the destruction of employment by enterprise deaths is more concentrated in services. This clearly reflects the higher turbulence and death rates in services industries. At the same time, destruction of employment by enterprise deaths is relatively greater than employment creation by enterprise births in manufacturing: this is most likely related to the broader shift towards deindustrialisation in developed countries.


(SDBS) Database.






© OECD 2009

B.9-B.10 Employment creation by births and deaths

Employment creation by enterprise births, 2005 and 2006

As a percentage of the total number of persons employed in manufacturing and services

0

1

2

3

4

5

6

7

Manufacturing1 (2005)


Services2 (2005) Services2 (2006)

1. Mining and quarrying; Manufacturing; Electricity, gas and water. 2. Wholesale and retail trade; Hotels and restaurants; Transport, storage and communications; Financial intermediation; Real estate, renting and business activities.

Employment destruction by enterprise deaths, 2004 and 2005

As a percentage of the total number of persons employed in manufacturing and services

0

1

2

3

4

5

6

7


Services2 (2004)Services2 (2005)


1. Mining and quarrying; Manufacturing; Electricity, gas and water. 2. Wholesale and retail trade; Hotels and restaurants; Transport, storage and communications; Financial intermediation; Real estate, renting and business activities.


© OECD 2009

C. TIMELY ENTREPENEURSHIP INDICATORS

Definitions

The economic crisis has created increasing demand for more timely indicators of entrepreneurship. The EIP typically develops solid but less timely indicators, as a result of the (pure) definitions used (e.g. excluding re-activation in enterprise births) and of validation by national statistical offices.

An attempt has been made to collect more recent evidence on entrepreneurship across countries, focusing on administrative data sources accessible through the Internet. Data on firm entry have been collected for 12 countries:

- Australia: new business registrations

- Austria: new company registrations

- Belgium: new company registrations

- Denmark: new business registrations

- Finland: enterprise openings

- France: enterprise creations

- Germany: new company registrations

- Italy: new company registrations

- the Netherlands: new business

- Spain: new business registrations

- United Kingdom: new incorporated registrations

- United States: establishment openings excluding seasonal businesses

Comparability

As the names of the data series clearly suggest, the concepts on which the data are based differ across countries (see the specific websites for the methodology used in the different countries) and hence may differ from the EIP definitions of enterprise births. First, the unit of analysis is not always the enterprise (e.g. establishment in the United States) and in some countries the unit of analysis is not always clear.

Second, the data presented are administrative data, and most likely do not take into account the data consequences of mergers and acquisitions, re-activations, etc. As such, these indicators may not correspond exactly to the “official” EIP indicators.

Given the differences (among individual countries and with the EIP), changes in firm entry are presented rather than data on levels, on the assumption that the coverage of the data does not change over the time period considered. Data are based on year totals (except for Finland and the United States); 2009 data refer to the first half of 2009 and reflect the change from the corresponding period in 2008, but should be interpreted as preliminary data.

More broadly, the data presented are the result of an experimental data collection in order to discuss the impact of the economic crisis on entrepreneurship. The EIP plans to undertake further research on the development of timely indicators in order to identify data sources, to analyse differences in concepts and to examine differences with the EIP definitions.

Overview

Timely data on firm entries show a (remarkably) similar pattern across countries and clearly suggest that the economic crisis has had a significant impact on entrepreneurship. Firm entries seem to have slowed following the crisis, although there are differences in timing among countries.

The United States and the United Kingdom (and to a lesser extent Spain) observed a decrease in firm entries already in 2007, when most other countries were still reporting a steady rise. Germany reported a decrease in firm entries over the whole period considered; this may be related to the ending in 2005 of a government programme stimulating start-ups.

The subsequent strong fall in firm entries during 2008 and 2009 has resulted in fewer firm entries than in 2005 (except for France and Belgium). The data for the first half of 2009 should be interpreted with care, however, given the reported signs of economic recovery in recent months in some countries.

Source and for further reading Australia: Business.gov.au (www.business.gov.au).

Austria: Wirtschaftskammer Osterreich (www.wko.at).

Belgium: Graydon Belgium (www.graydon.be).

Denmark: Danish Commerce and Companies Agency, Denmark Statistik (www.dst.dk).

Finland : Statistics Finland (www.stat.fi).

France: National Institute of Statistics and Economic Studies (INSEE) (www.insee.fr).

Germany: Institut for Mittelstandsforschung (IFM) Bonn (www.ifm-bonn.org).

Italy: Business Register of the Chambers of Commerce – MOVIMPRESE (www.infocamere.it).

The Netherlands: Central Bureau of Statistics (CBS) (www.cbs.nl).

Spain : National Institute of Statistics (INE) (www.ine.es).

United Kingdom: Companies House (www.companieshouse.gov.uk).

United States: US Bureau of Labor Statistics (www.bls.gov).


© OECD 2009

C.1 Timely indicators on enterprise entries

Timely indicators on enterprise entries for selected countries, 2005-09

2005 = 100

70

80

90

100

110

120

130

140

2005 2006 2007 2008 2009 (1st half)

Australia Austria Belgium Denmark (1) Finland (2) France (3)

70

80

90

100

110

120

130

140

2005 2006 2007 2008 2009 (1st half)

Germany Italy (4) Netherlands Spain United Kingdom (4) United States (5)

1. Data for Denmark only available from 2006 onwards (hence 2006 = 100). 2. Data refer to the first quarter of each year. 3. Data for France exclude registrations of self-employed in order to mitigate the bias in the 2009 results as a consequence of a change in data collection (régime de l’auto-entrepreneur). 4. 2009 data based only on the first quarter. 5. Data refer to first quarter of each year. Source: National sources (see left page for more details).


© OECD 2009

C. TIMELY ENTREPENEURSHIP INDICATORS

Definitions

The economic crisis has created strong demand for more timely indicators of entrepreneurship. The EIP typically develops solid but less timely indicators, as a result of the (pure) definitions used (e.g. distinguishing enterprise deaths from lack of data for active enterprises) and of validation by national statistical offices.

An attempt has been made to collect more recent evidence on entrepreneurship across countries, focusing on administrative data sources accessible through the Internet. Data on firm exits have been collected for 12 countries:

- Australia: bankruptcies

- Austria: insolvent companies

- Belgium: bankruptcies

- Denmark: bankruptcies

- Finland: enterprise closings

- France: bankruptcy filings

- Germany: liquidations of companies

- Italy: company closings

- The Netherlands: bankruptcies

- Spain: closing downs

- United Kingdom: dissolved companies

- United States: establishment closings excluding seasonal businesses

Comparability

The data on firm exits are based on different concepts across countries (see the specific websites for the methodology used in the different countries) and may differ from the EIP definitions on enterprise deaths. First, the unit of analysis is not always the enterprise (e.g. establishment in the United States) and in some countries the unit of analysis is not always clear.

Second, the data are administrative data and most likely do not take into account the data consequences of mergers and acquisitions, etc. Further, deaths of firms are typically calculated with a two-year lag in order to account for active companies that do not fulfil their administrative requirements. As such, these indicators may not correspond exactly to the “official” EIP indicators.

Given the differences (among the individual countries and with the EIP), changes in firm exits are presented rather than data on levels, on the assumption that the coverage of the data does not change over time. Data are based on year totals (except for Finland and the United States); 2009 data refer to the first half of 2009 and present the change from the corresponding period in 2008, but should be interpreted as preliminary.

More broadly, the data presented are the result of an experimental data collection in order to discuss the impact of the economic crisis on entrepreneurship. The EIP plans to undertake further research in order to identify data sources, to analyse differences in concepts and to examine differences with the EIP definitions.

Overview

More timely data on firm exits show larger differences across countries (this is probably due to the different concepts used), but the impact of the economic crisis also seems prominent. Firm exits are relatively stable until 2007, although some countries reported a small increase in that year. All countries (except Germany and the Netherlands) report a very strong rise in firm exits in 2008 and 2009. Denmark, Italy and the United Kingdom report especially numerous exits in 2008 and 2009, but 2009 data have to be interpreted with care.

The number of firms exiting in 2008/09 is significantly higher in all countries (except Germany) than in 2005. Given that there is typically a time lag in firm exits, owing to the nature of liquidation, bankruptcy, etc., it can be expected that firm exits will remain high in the rest of 2009 (and maybe later).

Source and for further reading

Australia: Australian Government, Insolvency and Trustee Service (www.itsa.gov.au).

Austria: Wirtschaftskammer Osterreich (www.wko.at).

Belgium: Graydon Belgium (www.graydon.be).

Denmark: Denmark Statistik (www.dst.dk).

Finland : Statistics Finland (www.stat.fi).

France: National Institute of Statistics and Economic Studies (INSEE) (www.insee.fr).

Germany: Institut for Mittelstandsforschung (IFM) Bonn (www.ifm-bonn.org).

Italy: Business Register of the Chambers of Commerce – MOVIMPRESE (www.infocamere.it).

The Netherlands: Central Bureau of Statistics (CBS) (www.cbs.nl).

Spain: National Institute of Statistics (INE) (www.ine.es).

United Kingdom: Companies House (www.companieshouse.gov.uk).

United States: US Bureau of Labor Statistics (www.bls.gov).


© OECD 2009

C.2 Timely indicators on enterprise exits

Timely indicators on enterprise exits for selected countries, 2005-09

2005 = 100

60

80

100

120

140

160

180

200

2005 2006 2007 2008 2009 (1st half)

Australia Austria Belgium Denmark Finland (1) France (2)

60

80

100

120

140

160

180

200

2005 2006 2007 2008 2009 (1st half)

Germany Italy (3) Netherlands Spain United Kingdom (3) United States (4)

1. Data refer to the last quarter of each year. 2. 2009 data based only on first 4 months. 3. 2009 data based only on the first quarter. 4. Data refer to the first quarter of each year.

Source: National sources (see left page for more details).


© OECD 2009

D. ENTREPRENEURIAL DETERMINANTS

Definitions

Business enterprise expenditures on R&D (BERD) covers R&D activities carried out in the business sector by performing firms and institutes, regardless of the origin of funding. The business enterprise sector includes all firms, organisations and institutions whose primary activity is the production of goods and services for sale to the general public at an economically significant price, as well as the private and non-profit institutes mainly serving them.

BERD data by firm size class are aggregated using the size groups: fewer than 50, 50 to 249, and >250 employees.

Innovation is defined as the implementation of a new or significantly improved product (good or service) or process, a new marketing method, or a new organisational method in business practices, workplace organisation or external relations.

In analysing these four types of innovation (product, process, marketing and organisational), three levels of novelty can be distinguished: new to the firm, new to the market and new to the world. While new to the firm covers the diffusion of an existing innovation to a firm, the other concepts cover innovations newly developed by firms.

SMEs (small and medium-sized enterprises) were identified as firms with 10-249 employees (10-99 for New-Zealand); correspondingly large firms were >250 employees (>100 for New Zealand).

Comparability

The OECD has undertaken significant efforts to develop internationally comparable indicators on R&D and innovation. Data on enterprise expenditures are collected based on the standards of the Frascati Manual; this results in a wide range of internationally comparable BERD data. Nevertheless, some caution is warranted, especially when assessing changes in BERD over time since changes in methods and breaks in series may occur, notably in terms of the extension of survey coverage, particularly in the services sector and the privatisation of publicly owned firms.

Data on innovation are increasingly collected by innovation surveys in OECD and many non-member economies, based on the Oslo Manual. Although cross-country comparability of innovation surveys is generally good and improving, certain differences may affect comparisons between CIS (Community Innovation Surveys) and non-CIS countries, such as industry coverage, size thresholds, sampling methods and unit of analysis, and the filtering of innovators/non-innovators.

Overview

Knowledge creation and diffusion has become intrinsically linked with (high-growth) entrepreneurship because of the increasing knowledge intensity of OECD countries. Successful entrepreneurship both in SMEs and in large firms depends heavily on innovation and R&D. Business R&D is especially important in this regard, since it is closely related to the creation of new products and production techniques.

While (business) R&D intensity has increased in all OECD countries with the gradual shift to a knowledge-based economy, large differences exist. Firms in Israel, Sweden, Finland and Korea invest heavily in R&D. Both small and large firms invest in R&D, but their relative importance for business R&D varies. Large firms (including multinational enterprises) appear responsible for the bulk of business R&D investments, owing to the high costs and scale economies of R&D-activities. The share of R&D performed by SMEs (defined as firms with fewer than 250 employees) tends to be somewhat larger in smaller economies.

Knowledge creation and diffusion are broader than R&D since a large and growing share of innovations is not necessarily linked to R&D and/or technology. By innovating in products, processes, marketing and organisational forms, firms (try to) seize entrepreneurial opportunities. Entrepreneurial opportunities are likely to be larger when firms develop innovations that are new to the market or new to the world, but the costs and risks are greater. The data indicate that large firms tend to introduce more novel innovations than SMEs, but again there are significant differences among countries. In some countries SMEs are responsible for a significant part of innovations that are new to the market or new to the world.

Source OECD (2009), Science, Technology and Industry

Scoreboard.

For further reading OECD (2002), Frascati Manual: Proposed Standard

Practice for Surveys on Research and Experimental Development, OECD, Paris, www.oecd.org/sti/frascatimanual.

OECD and Eurostat (2005), Oslo Manual: Guidelines for Collecting and Interpreting Innovation Data, 3rd edition, OECD, Paris, www.oecd.org/sti/oslomanual.


© OECD 2009

D.1.a/b Knowledge creation and diffusion

Business R&D intensity, by size class of firms,1 2007

As a percentage of industry value added

0

1

2

3

4

5

6

7

< 50 employees 50-249 employees >250 employees

Notes: Share of size class: 2006 data for Australia, Austria, Belgium, Canada, France, Ireland, Italy, Slovenia, Spain, United States; 2005 data for Denmark, Germany, Greece, Luxembourg, Netherlands, New Zealand; 2004 data for Switzerland. Small firms (fewer than 50 employees): for the United States, 5-49 employees; for Luxembourg, the Netherlands and Sweden, 10-49 employees. Medium-sized firms (50-249 employees): for Japan, fewer than 299 employees. 1. No data on size class available for Iceland, Israel and Japan, Mexico, Turkey. Source: OECD (2009), Science, Technology and Industry Scoreboard.

Firms with new-to-market product innovations, by size,1 2004-06

As a percentage of all firms

0

10

20

30

40

50

60

70

SMEs (1) Large firms

1. SMEs: 10-249 employees; 10-99 for New Zealand. 2. France: manufacturing only. Source: OECD (2009), Science, Technology and Industry Scoreboard.


© OECD 2009


Definitions

Collaboration on innovation involves active participation in joint innovation projects with other organisations but excludes pure contracting out of work. Collaboration concerns the joint development of new products, processes or other innovations with customers and suppliers, as well as horizontal work with other enterprises or public research bodies.

Innovation is defined as the implementation of a new or significantly improved product (good or service), or process, a new marketing method, or a new organisational method in business practices, workplace organisation or external relations.

Internet commerce transactions are defined as the sale or purchase of goods or services, whether between businesses, households, individuals, governments, or other public or private organisations, conducted over the Internet. While the goods or services are ordered over the Internet, the payment or ultimate delivery of the good or service may be conducted on or off line.

The OECD concept of Internet commerce includes orders received or placed on any Internet application used in automated transactions such as web pages, extranets and other applications that run over the Internet (such as electronic data interchange), or over any other web-enabled application regardless of how the web is accessed (mobile phone, TV set, etc.). Orders received or placed by telephone, facsimile or conventional e-mail should be excluded.

Comparability

Innovation surveys are increasingly used in OECD and many non-member economies to better understand the role of innovation, including the importance of collaboration on innovation. Although cross-country comparability of innovation surveys based on the Oslo Manual is generally good and improving, certain differences may affect comparisons between CIS (Community Innovation Surveys) and non-CIS countries, such as industry coverage, size thresholds, sampling methods and unit of analysis, and the filtering of innovators/non-innovators.

Measuring electronic commerce is fraught with statistical challenges. While efforts have been made to harmonise definitions and concepts, differences across countries remain. The definition of Internet selling and purchasing varies between countries. Some explicitly include orders placed by conventional e-mail (e.g. Australia and Canada); others explicitly exclude them (e.g. Ireland, the United Kingdom and some other European countries). Most countries explicitly use the OECD concept of Internet commerce, that is, goods or services ordered over the Internet but payment and/or delivery may be off

line. For Australia, Internet income results from orders received via the Internet or the web for goods or services, where an order is a commitment to purchase.

Overview

Collaboration has become an integral part of the innovation strategies of small and medium-sized enterprises (SMEs) as well as large firms. Continuing technological progress, rapidly increasing investments, the integration of knowledge domains for multidisciplinary research, etc., make collaborating on innovation more attractive and in many cases necessary. Around one in ten of all firms (or one in four innovating firms) in Europe collaborated with a partner (other firms, education institutions or government institutions) for their innovation activities. Large firms are significantly more likely to collaborate than SMEs, although countries differ significantly in this respect. Following the increase in economic globalisation and the corresponding internationalisation of R&D/innovation, firms increasingly co-operate with foreign partners.

The diffusion of knowledge is to a large extent enabled by a country’s technological infrastructure. ICT has become an important driver of knowledge creation as well as diffusion, and this increasingly on a global scale. The Internet is redefining relations among companies but also between companies and their consumers, enabling companies to sell their products and services around the world. Data indicate that on average almost one-third of all businesses (with ten or more employees) use the Internet for purchasing and about one-fifth for selling goods or services. The volume of Internet and other e-commerce sales transactions is increasing; firms in Denmark, Ireland, Norway and the United Kingdom in particular realise a significant part of their turnover via the Internet.

Source OECD (2009), Science, Technology and Industry

Scoreboard.

For further reading OECD and Eurostat (2005), Oslo Manual: Guidelines

for Collecting and Interpreting Innovation Data, 3rd edition, OECD, Paris, www.oecd.org/sti/oslomanual.

OECD (2009), “Guide to Measuring the Information Society 2009”, www.oecd.org/sti/measuring-infoeconomy/guide.


© OECD 2009

D.1.c/d Knowledge creation and diffusion

Firms collaborating on innovation by size, 2004-06

As a percentage of all firms

0

10

20

30

40

50

60

70

80

SMEs Large firms

Notes: SMEs: 10-249 employees; 10-99 for New Zealand. France: manufacturing only. Source: OECD (2009), Science, Technology and Industry Scoreboard.

Turnover from e-commerce.1 2008

As a percentage of total turnover

0

5

10

15

20

25

1. Total sales via the Internet or other networks during the reference year, excluding VAT. Source: OECD (2009), Science, Technology and Industry Scoreboard.


© OECD 2009


Definitions

The indicator “ease of access to loans” is based on the World Economic Forum survey questionnaire and measures how easy it is to obtain bank loans with only a good business plan and no collateral (1 = impossible and 7 = easy).

Bank loans are an important source of financing for companies starting up or expanding their activities. In contrast to equity funding, the financial institution acquires no equity position in the firm and the borrower’s obligation is to repay the debt, usually with interest.

Within equity financing, business angels are an important source of financing, especially for start-ups. A business angel is a private investor who generally provides both finance and business expertise to an investee company in return for an equity share in the firm.

Some business angels form syndicates or networks in order to take on larger deals and to spread risk. While they are traditionally considered part of the informal investor component of risk capital, their character is changing following the emergence of these formal networks.

Comparability

The World Economic Forum’s Global Competitiveness Report is heavily based on its Executive Opinion Survey, which captures business executives’ perception of the environment in which they operate. The survey, which is based on a standardised questionnaire and undertaken by a large number of partner institutes in different countries, makes it possible to gather insights into the competitiveness of economies. Between January and May 2009 12 614 surveys were conducted in 133 countries, with an average of 95 respondents per country.

Data on business angels are very difficult to collect because of differences in definitions and data collection methods. For example, while business angels are commonly described as wealthy private individuals who invest part of their personal assets in a start-up and also share their personal management experience with the entrepreneur, definitions from different sources vary.

Most of the data are collected from their membership by national/regional business associations. Data in the OECD Entrepreneurship Financing database are collected by two major associations. The European Business Angel Network (EBAN) is an association of national and regional angel networks primarily in Europe but also in some non-European countries. The

Angel Capital Association (ACA) is a professional alliance of angel groups in the United States and Canada with a mandate to provide advice and guidance to members and to develop data and research for their members.

Overview

Debt financing and equity financing are the two main sources of finance for entrepreneurial firms. Debt financing involves the acquisition of resources with an obligation of repayment; the investor does not receive an equity stake. It includes a wide variety of financing schemes: loans from individuals, banks or other financial institutions; selling bonds, notes or other debt instruments; and other forms of credit such as leasing or credit cards.

Survey data for 2009 indicate that firms have recently found it more difficult to get loans. Following the financial crisis, banks have become less ready to approve companies’ loan applications. Ease of access to loans is also perceived rather differently across countries, suggesting important differences worldwide in companies’ ability to attract financial resources.

Business angels provide equity capital and are investors that fall somewhere between formal venture capital funds and informal FFF (founders, friends and family) investors. Recent evidence has shown that business angels play an important role especially in the early-stage financing of entrepreneurial firms.

In terms of the number of business angels and investments, the United States clearly predominates. While business angel activity is more developed in the United States, Europe (and also Asia) have been catching up. Within Europe, larger countries have larger numbers of business angel networks, although Sweden is a small country and has significant business angel activity. Caution is warranted in analysing these data given their shortcomings in terms of comparability.

Source World Economic Forum (2009), The Global

Competitiveness Report.

OECD (2009), Entrepreneurship Financing Database.

For further reading OECD (2008), Financing High-Growth and

Innovative SMEs: Report on Data Sources and Issues.


© OECD 2009

D.2.a/b Access to finance

Ease of access to loans, 2009

1 = impossible, 7 = easy

0

1

2

3

4

5

6

7

Source: World Economic Forum, Global Competitiveness Report 2009.

Business angels (networks), 2007

Number of business angel networks1

European Union

United States

Number of networks

297 245

Number of business angels

75 000 250 000

Investment per round

EUR 165 000 EUR 210 000

Total amount invested

EUR 3-5 billion

EUR 20 billion

Austria, 3 Belgium, 4

France, 66

Bulgaria, 2

Czech Rep., 2

Denmark, 3

Finland , 1

Germany, 38

Greece, 1

Hungary, 3Ireland, 4Italy, 11

Latvia, 1

Sweden, 22Norway, 7

Poland, 5

Portugal, 10

Slovenia, 1

Spain, 37

Switzerland, 8

Netherlands, 9

United Kingdom, 18

1. Estimates. Source: OECD Entrepreneurship Financing Database, based on EBAN and ACA.


© OECD 2009


Definitions

Venture capital is private equity provided by specialised firms acting as intermediaries between primary sources of finance (insurance, pension funds, banks, etc.) and private companies whose shares are not freely traded in any public stock market. Because of the high risk involved, venture capital funds take a hands-on approach to the management and governance of the financed firms.

Venture capital may be invested in all stages of an entrepreneurial firm’s development, from seed through expansion stages:

• Pre-seed stage: the earliest stage in the development of a business, when a business plan may be under development but no formal or concrete steps have been taken to set up the business.

• Seed stage: the development phase prior to start-up when founders conduct research, develop products and explore market potential. The future business entity is beginning to take shape but founders have not yet established commercial operations.

• Start-up stage: the stage at which a firm has established operations and has launched or is about to bring products or services to the market. This stage typically requires a lot of capital since revenues are not yet able to cover operational and development costs.

• Expansion stage: the stage at which capital is required by a more established firm to finance growth. Investments are made in activities such as R&D or production capacity.

Comparability

National and regional venture capital associations collect data on venture capital from their members. Statistics capture only formal venture capital. The data in the OECD Entrepreneurship Financing Database are collected from the European Venture Capital Association (EVCA), the Australian Bureau of Statistics (ABS), the Venture Enterprise Center (VEC) in Japan, the National Venture Capital Association (NVCA) in the United States, the Korean Venture Capital Association (KVCA) and the New Zealand Private Equity and Venture Capital Association (NZVCA).

Until recently, venture capital data were not completely comparable internationally, owing to differences in definitions and classification methods. However, given recent changes in methodology, especially for the collection of statistics by the investee or portfolio firm instead of the investor firm, data have become more comparable: inward and outward flows are treated in the same way across countries. In addition some streamlining in industry classifications has taken place,

further increasing the international comparability of venture capital data.

The data presented concern the venture capital invested in the country and thus include investments by foreign venture capital funds in domestic companies (inward flows of venture capital). Data invested abroad by domestic venture capital funds are not included (outward flows of venture capital).

Overview

Venture capital is an important source of funding for entrepreneurial firms, especially young, technology-based firms with high growth potential. There is a strong belief that, in general, financing is an important barrier to (high-growth) entrepreneurship. Hence, several countries have recently developed policies to improve access to finance, particularly venture capital for innovative high-growth firms. The financial crisis and the resulting scarcity of financial resources have heightened policy makers’ attention to this entrepreneurial determinant.

Venture capital differs significantly among countries; it is an especially important source of finance for companies in Finland, Sweden and the United Kingdom. A constant observation across countries is that venture capital funds invest more in the later stages, i.e. early development or start-up and expansion. Projects in the pre-seed and seed stages often have greater difficulty finding investors, as profit expectations are less clear and investment risk is much higher.

High-technology firms attract a large share of venture capital investments in some countries: in Canada, New Zealand and the United States, more than half of venture capital is invested in high-technology industries. Within this group, communications and consumer electronics seem to be responsible for the largest venture capital investments. In countries such as Canada, Hungary and Korea, it attracts more than 75% of these investments.

Source OECD (2009), Entrepreneurship Financing Database.

For further reading OECD (2008), Financing High Growth and Innovative

SMEs: Report on Data Sources and Issues.


© OECD 2009

D.2.c/d Access to finance

Venture capital investments, 2008

As a percentage of GDP

0%

5%

10%

15%

20%

25%

Seed/start-up Early development and expansion

Source: OECD Entrepreneurship Financing Database, based on ECVA, ABS, VEC, NVCA, KVCA, NZVCA.

Share of high-technology sectors in total venture capital, 2008

As a percentage of total venture capital investments

0

10

20

30

40

50

60

70

80

Life sciences Computer and consumer electronics Communications

1. IT, media, electronics and communication for computer and consumer electronics. 2. Information technology for computer and consumer electronics. 3. Information and communication for computer and consumer electronics. 4. IT/software for computer and consumer electronics. 5. Information technology for computer and consumer electronics. 6. Data by sector for Canada refer to all stages of development. Source: OECD Entrepreneurship Financing Database based on ECVA, ABS, VEC, NVCA, KVCA, and NZVCA.


© OECD 2009


Definitions

A country’s population with tertiary education or tertiary attainment includes persons with tertiary-type B education or tertiary-type A education and advanced research programmes.

Tertiary-type A programmes (ISCED classification 5A) are largely theory-based and are designed to provide sufficient qualifications for entry to advanced research programmes and professions with high skill requirements.

Tertiary-type B programmes (ISCED 5B) are typically shorter than tertiary-type A programmes and focus on practical, technical or occupational skills for direct entry into the labour market, although they may cover some theoretical foundations.

Using the definition of the Labour Force Survey, self-employed persons are defined as persons who work in their own business, professional practice or farm for the purpose of earning a profit. They may or may not have employees.

Self-employment (as a proxy for entrepreneurship) has been calculated separately for the native-born and foreign-born population. A country’s foreign-born population includes all persons who have that country as their usual residence and who were born in another country.

Comparability

The International Standard Classification of Education (ISCED 1997) is used by UNESCO and the OECD to develop internationally comparable indicators of educational attainment. Education statistics are collected for all OECD countries and a large number of non-OECD countries.

Educational attainment is widely used as a proxy for a population’s human capital. As such, it is typically assumed that the skills and competencies taught at each level of education are the same across countries.

The Labour Force Survey divides the population of working age (15 years and more) into three mutually exclusive groups: persons in employment, unemployed persons and inactive persons. Respondents are assigned to one of these groups on the basis of the most objective information obtained through the survey questionnaire, which principally relates to their actual activity within a particular reference period. Self-employment is a subcategory of persons in employment; they work in their own business and want to make profit.

The concepts and definitions used in the Labour Force Survey are based on the guidelines of the International Labour Organisation and guarantee broad availability and comparability across countries.

Overview

A well-educated and well-trained population/labour force is important for countries’ economic performance in general. The educational attainment level as a proxy for human capital is also important for entrepreneurship, as it directly determines the pool of potential entrepreneurs. Knowledge, skills and competencies have become more and more important for (successful) entrepreneurship given the increasingly knowledge-intensive character of OECD economies.

Around 25% of the population aged 25-64 years has tertiary education in OECD countries, but large differences exist between countries. Those aged 25 to 34 years have higher tertiary attainment, except in Israel and Germany. The relatively high educational level of these younger professionals is important as studies have shown that (technology) start-ups heavily rely on this group.

By attracting skilled labour from abroad, immigration is another way to increase the pool of capable entrepreneurs. Several studies have discussed the importance of foreign-born people for entrepreneurship e.g. in the United States, where many immigrants have set up very successful companies.

Data on self-employment suggest that the foreign-born population’s propensity to become an entrepreneur is very high in some countries (sometimes higher than that of the native-born). This may reflect immigrants’ good integration in the host country combined with a high level of competencies (so-called “opportunity entrepreneurship”). However, and some studies have clearly shown this, this high propensity may also illustrate the many difficulties (insufficient social capital, language, problems with recognition of qualifications) immigrants face in entering the labour market. Hence the choice of self-employment as an alternative (so-called “necessity entrepreneurship”), often in more traditional, less knowledge-intensive activities. More research on the educational attainment of immigrants is needed to learn if immigrants are self-employed by choice or by necessity.

Source and for further reading OECD (2009), Education at a Glance.

OECD (2009), International Migration Outlook.


© OECD 2009

D.3. a/b Entrepreneurial capabilities

Population with tertiary education, 2007

As a percentage of the total population

0

10

20

30

40

50

60

25-64 25-34

Source: OECD, Education at a Glance, 2009.

Self-employment1 by place of birth (15-to-64-year-olds), 2007

As percentage of total employment

0

5

10

15

20

25

30

35

Native-born Foreign-born

Note: Self-employment excludes agriculture; for Canada persons still in education are excluded. Source: OECD, International Migration Outlook, 2009.


© OECD 2009

D. ENTREPRENEURIAL CAPABILITIES

Definitions

International students in tertiary education are calculated as the share of international students in tertiary enrolments. “International” is defined on the basis of country of residence (which excludes students who are permanent residents). This indicator provides a picture of (inward) student mobility and the internationalisation of tertiary education in OECD and partner countries.

Tertiary education consists of tertiary-type B education or tertiary-type A and advanced research programmes (see definitions above). Advanced research programmes are second-stage tertiary studies that lead to the award of an advanced research qualification; the programmes are devoted to advanced study and original research and are not based on course work alone. They equate to Level 6 of the International Standard Classification of Education (ISCED).

Training in starting a business includes all voluntary or compulsory training/courses during or after school. Data are collected via surveys which count the number of respondents who have received such training. They give an idea of participation in entrepreneurship education and training in different countries.

Comparability

ISCED 1997 is used by UNESCO and the OECD to develop internationally comparable indicators of educational attainment. Education statistics are collected for all OECD countries and a large number of non-OECD countries. Educational attainment is largely used as a proxy for human capital in the population of a country. As such, it is typically assumed that the skills and competencies taught at each level of education are the same across countries.

Data on entrepreneurship education are largely unavailable, although there have been some recent efforts to develop common definitions and to collect data on an international scale. Different directions are explored to develop internationally comparable data on entrepreneurship education.

The Global Entrepreneurship Monitor (GEM) has used surveys in 54 developed and developing countries in 2009. The Adult Population Survey asks a representative sample of at least 2 000 adults in each country about their attitudes to and involvement in entrepreneurship. GEM takes a broad view of entrepreneurship and focuses on the role of the individual in the entrepreneurial process. The survey asks about personal assessments, attitudes and perceptions, in addition to intentions of starting a business in the near future. Given the importance of entrepreneurship education, specific questions have recently been included on this topic in the GEM 2008 study.

Overview

Education has become increasingly internationalised; 3 million tertiary students were enrolled outside their country of citizenship in 2007. Like knowledge and skills, international experience and exposure have become important competencies for entrepreneurship. The level of international enrolments indicates the level of openness of a country’s education system. At the same time, these international students form an important pool of potential future entrepreneurs. International student enrolments in advanced tertiary programmes seem to have significant potential. Experience has shown that these programmes more than others lead to entrepreneurship. Examples include (university) spin-offs (e.g. by Chinese and Indian tertiary students in the United States).

Specific entrepreneurship courses (e.g. starting up a business) are often not part of normal curricula, although the situation is changing. Several countries increasingly implement specific training courses on entrepreneurship at the tertiary level but also at lower levels (secondary and even primary). Depending on the level of this training, the education is aimed at increasing the skills needed for success or at creating an entrepreneurial mindset. Survey data show that until now relatively few people have received specific entrepreneurship training in or after school. In most countries less than a quarter of the population aged 18 to 64 years indicated having participated in training for starting a business. In Finland almost half of respondents had taken entrepreneurship courses.

Source OECD (2009), Education at a Glance.

A. Coduras, D. Kelley, J. Levie, R. Saemundson and T. Schøtt (2009), A Global Perspective on Entrepreneurship Education and Training: A Special Report of the Global Entrepreneurship Monitor, forthcoming.

For further reading NIRAS Consultants, FORA and Econ Pöyry (2008),

Survey of Entrepreneurship Education in Higher Education (report prepared for the European Commission).

World Economic Forum (2009), Educating the Next Wave of Entrepreneurs.


© OECD 2009

D.3.c/d Entrepreneurial capabilities

International students in tertiary education, 2007

As a percentage of total tertiary enrolment

0

5

10

15

20

25

30

35

40

45

50

Total tertiary Advanced research programmes

1. Excludes data for social advancement education. 2. Percentage in total tertiary underestimated because of the exclusion of programmes. 3. Year of reference 2006. 4. Excludes private institutions. 5. International students are defined based on their country of prior education. Source: OECD, Education at a Glance, 2009.

Population aged 18-64 with training in starting a business, 2008

As a percentage of total population

0

10

20

30

40

50

60

Source: A. Coduras, D. Kelley, J. Levie, R. Saemundson and T. Schøtt (2009), A Global Perspective on Entrepreneurship Education and Training: A Special Report of the Global Entrepreneurship Monitor, forthcoming.


© OECD 2009


Definitions

The “ease of doing business” indicator measures regulations applying to domestic small and medium-sized companies in different countries. The indicator ranks economies from 1 (the highest rank) to 183.

It is an average of the country's percentile rankings on ten topics, covering a variety of indicators: starting a business, dealing with construction permits, employing workers, registering property, getting credit, protecting investors, paying taxes, trading across borders, enforcing contracts, closing a business, getting electricity.

The “barriers to entrepreneurship” indicator measures different regulations pertaining to entrepreneurship on a scale of zero to six; lower values suggest lower barriers to entrepreneurship. The indicator encompasses sub-indicators on “regulatory and administrative opacity” (e.g. licences, simplified systems for permits such as one-stop shops, communication, simplification of rules); “administrative burdens for start-up” and “barriers to competition” (e.g. barriers to entry in different industries). Each of these sub-indicators is a weighted average of lower-level indicators developed from qualitative information that has been coded (also on a scale of zero to six).

Comparability

Information about regulations is generally scarce, or if available, often quantitative in nature. Moreover, to measure the real effects of specific regulations, the wider regulatory framework has to be taken into account.

The World Bank’s Doing Business project aims to measure the regulations and red tape companies face, using information in laws and regulations and calculating the time and costs involved in complying with these regulations. It uses standardised scenarios based on specific assumptions (e.g. the business is located in the economy’s largest business city) to achieve broad global coverage and enhance international comparability.

The OECD Indicators of Product Market Regulation (PMR) measures the degree to which policies promote or inhibit competition in product markets. The methodology for collecting information and constructing the indicators is the same across OECD countries since the broad regulatory environment is characterised with reference to a set of individual regulatory provisions.

“Barriers to entrepreneurship” concerns provisions relating to the entrepreneurship (policy) domain and are synthesised to form a set of detailed and summary measures. Given the OECD’s standardised data collection and standardised means of developing indicators, the PMR indicators form a comprehensive, internationally comparable set of indicators across OECD countries.

Overview

Doing business requires a good, clear and enforceable regulatory framework, e.g. property rights, institutions for resolving disputes, protection of contractual partners, etc. A strong regulatory framework is another determinant of entrepreneurship, on the condition that economic initiatives have enough space to flourish.

With their overall strong regulatory and legal systems, almost all OECD countries rank high on the “ease of doing business” indicator. Ease of doing business is high overall in New Zealand, the United Kingdom and the United States. The (smaller) differences among OECD countries are mostly due to differences in specific regulations concerning entrepreneurship (e.g. starting and closing a business). Less developed and emerging countries rank lower, a sign of the steps some of these countries have to take towards a favourable regulatory framework, both in general and for entrepreneurship.

When focusing on obstacles to entrepreneurship, PMR data for 1998 and 2008 clearly show that most OECD countries have lowered barriers to entrepreneurship during the last decade. Again the United Kingdom, but also the Netherlands and Sweden have low barriers to entrepreneurship.

In particular, easy-to-use licence and permits systems, better information, and simplification of regulations have led to a lower degree of regulatory and administrative opacity in many OECD countries. The administrative burdens for start-ups and other specific legal barriers to competition have been lowered only to a limited extent, with some countries even taking the opposite approach.

Source World Bank (2009), Doing Business Survey.

OECD (2008), Indicators of Product Market Regulation.

For further reading OECD (2008), Ten Years of Product Market Reform in

OECD countries – Insights from a revised PMR Indicator.


© OECD 2009

D.4.a/b Regulatory framework

Ease of doing business

Ranking (1 = most easy, 183 = most difficult)

0

20

40

60

80

100

120

140

Source: World Bank, Doing Business, 2009.

Barriers to entrepreneurship, 2008 and 1998

Scale from 1 to 6

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

1998 2008

Notes: The indicator values for Greece, Ireland and the Slovak Republic are preliminary. The 2008 data refer to beginning of 2008. Source: OECD, Indicators of Product Market Reform, 2008


© OECD 2009


Definitions

The top statutory tax rate is the highest statutory personal income tax rate. It first applies at an income level which can be expressed as a multiple of the average wage in a country. This top rate combines the central government and sub-central government (top marginal) rates, calculated as the additional central and sub-central government personal income tax rate resulting from a unit increase in gross wage earnings.

The average wage (in national currency) reflects the average annual gross wage earnings of adult, full-time manual and non-manual workers in industries C-K of the ISIC Rev. 3.1 Industry Classification.

The corporate income tax (CIT) rate is the (statutory) tax rate applicable to incorporated business. It combines the central and sub-central (statutory) corporate income tax rate given by the adjusted central government rate plus the sub-central rate.

The lowered tax rate for SMEs, where it exists, is the corporate tax rate applying to small (incorporated) businesses, where “small” is determined on the basis of size (e.g. number of employees, amount of assets, turnover or taxable income).

Comparability

The personal income tax rates on gross wage income are calculated using to the OECD Taxing Wages framework, which allows for broad international comparability across countries. The information provided by countries is further aligned by the OECD to take account of differences in tax regulations.

The corporate income tax rate is the nominal rate applied to an incorporated business; it does not take into account any deductible expenses that result in a lower effective corporate tax rate.

A small business corporate tax rate may be a special statutory corporate tax rate applicable to (all or part of) the taxable income of qualifying small firms or an effective corporate tax rate below the basic statutory corporate rate which is provided through a tax deduction or credit for small firms and determined as a percentage of the qualifying taxable income (e.g. up to a given threshold).

Countries that apply a special rate for small businesses use different rates and define “small” differently:

Belgium: applicable on the first EUR 25 000 of taxable income when taxable income is less than EUR 322 500. The rate is 31.93% (31) up to a taxable income of EUR 90 000, and 35.535% (34.5) on the remaining taxable income up to EUR 322 500.

France: applicable where turnover does not exceed EUR 7.63 million, and on the part of the profit that does not exceed EUR 38 120.

Hungary: a preferential tax rate of 10% is applicable on the first HUF 50 million, if the taxpayer is i) not enjoying any corporate tax relief; ii) employing at least one person; iii) paying a minimum of social security contributions; iv) paying corporate income tax at least on the basis of the minimum income/tax base; and v) fulfilling certain legal requirements relating to the employment of workers. The benefit resulting from the preferential 10% rate has to be used for investment or employment purposes. The surtax is payable on the total amount of (adjusted) profits before tax.

Korea: applicable on the first KRW 200 million.

Luxembourg: A reduced CIT rate of 19% and an exemption equivalent to a maximum of 200 minimum wages applies to companies exclusively involved in the primary sector.

Netherlands: applies to the first EUR 200 000 of taxable income.

Spain: qualifying small companies are taxed at 25% on the first EUR 120 202.41 of taxable income.

United Kingdom: for companies with tax-adjusted profits below GBP 300 000 the rate is 21%. Rates as of 1 April.

United States: applicable on first USD 50 000.

Japan: applicable on the first JPY 4 million of taxable income of corporations whose capital is JPY 100 million or less. The combined rate is 30.85% up to taxable income of JPY 8 million.

Overview

Taxes form an important part of a country’s regulatory framework. Looking at the top marginal personal income and corporate tax rates (partially) indicates how entrepreneurs (self-employed/not incorporated and incorporated businesses) are taxed on their income.

Nordic countries, but also Belgium and the Netherlands, have very high marginal personal tax rates (extra labour income is taxed at a very high rate). This seems to be combined with lower threshold levels for applying the top statutory tax rates.

Differences in corporate tax rates seem smaller because of the rate reductions countries have implemented to attract foreign direct investment and to create a more business-friendly domestic and international tax environment. It should be noted that nominal tax rates are presented; they do not take account of any deductible allowances and credits. Effective tax rates would show the impact of the whole of the fiscal system on businesses.

In countries that do not apply lowered tax rates to SMEs the statutory tax rate is the same for all incorporated businesses.

Source and for further reading OECD (2008), Taxing Wages 2007/2008.


© OECD 2009

D.4.c/d Regulatory framework

Top statutory personal income tax rate, 2008

Threshold expressed as a multiple of average wage (right axis)

0.0

5.0

10.0

15.0

20.0

25.0

30.0

0%

10%

20%

30%

40%

50%

60%

70%

Top statutory income tax rate Threshold (multiple AW)

Source: OECD, Taxing Wages 2007/2008, 2009.

Top statutory corporate income tax rate, 2009

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

Overall SMEs

1. For Australia, New Zealand and the United Kingdom, with a non-calendar tax year, rates are those in effect as of 1 July, 1 April and 1 April, respectively. 2. The effective CIT rate can be substantially reduced by a notional allowance for corporate equity (ACE), e.g. the effective tax rate is only half the nominal tax rate when the return on equity before tax is twice the notional interest rate (4.473% in 2009). 3. The rates include a surcharge but not the local business tax (taxe professionnelle) or the turnover-based solidarity tax (contribution de solidarité). 4. Rates include the regional trade tax (Gewerbesteuer) and the surcharge. 5. Rates do not include the turnover-based local business tax, the innovation tax and the credit institution surtax. 6. Rates do not include the regional business tax (imposta regionale sulle attività produttive – IRAP). 7. There is no sub-central government tax but local authorities (at each level) participate in tax revenue at a given percentage. 8. Church taxes, which cannot be avoided by enterprises, are included. 9. The sub-central rate is a weighted average state corporate marginal income tax rate. 10. Applies to taxable income over EUR 200 000. 11. Data for 2008. Source: OECD Tax Database.


© OECD 2009


Definitions

The competition law and policy (CLP) indicator summarises and compares policies aimed at promoting competition. The indicator encompasses application as well as formal legal and institutional structures and includes both general and sector-specific competition policies.

The indicator is composed of: i) the antitrust framework, i.e. policies enhancing competition in general, typically enforced by the competition authorities; and ii) network policies, i.e. policies encouraging competition in deregulated network industries, typically implemented by more or less independent sector regulators.

The indicator’s measure of the antitrust framework first covers the scope and enforcement of the antitrust law. The scope of the antitrust law is the legal framework for dealing with cartel behaviour and other anticompetitive activities, the extent of exemptions (of sectors and activities) from the competition law, and the effectiveness of merger control regimes. The effectiveness of enforcement is measured by the scope for private legal actions and the risk associated with engaging in anti-competitive activities.

Second, the antitrust framework indicator covers the degree of independence of the competition authorities. Competition authorities in most OECD countries have a relatively high degree of independence but, as they are part of the government, their degree of independence varies. The indicator assesses their status within the government structure, whether their decisions can be overruled by government, and how accountable they are for their actions.

The indicator’s measure of network policies covers: i) the independence of sector regulators; and ii) access issues. The indicator for measuring the independence of sector regulators contains elements such as institutional design, the regulator’s sectoral authority and powers, and the regulator’s accountability. Access issues include entry barriers and the degree of vertical integration in the sector.

Comparability

The overall CLP indicator is calculated using about 100 data points for each country, with each data point measured on a scale from 0 (the best score) to 6 (the worst score). A relatively higher weighting has been assigned to the antitrust framework (75%) relative to network policies (25%), since more data were available and collected for antitrust. Within the two categories, a random weights structure is used to construct the indicators of antitrust framework and network policies.

Uniform data collection across OECD countries contributes to the international comparability of the indicator and its sub-indicators.

Overview

Entrepreneurship thrives on economic initiative, hence the need for promoting competition in markets. The past decade has seen a convergence of competition policies in OECD countries. Competition laws are broadly similar across OECD countries, but institutions and methods for enforcing these laws differ quite significantly.

The CLP indicator shows relatively limited variation, as countries with a strong antitrust framework tend to have relatively weak network policies and vice versa. The antitrust framework seems to be quite similar across countries, while the liberalisation of network industries has proceeded differently and at different speeds within the OECD area.

In analysing the CLP indicator across countries, three broad groups of OECD countries can be distinguished: countries with relatively strong CLP (Australia, Canada, the Czech Republic, Denmark, Italy, Korea, the United Kingdom and the United States); countries with relatively weak CLP (Austria, Greece, Japan, Mexico, Norway, Portugal and Switzerland). The remaining countries were not statistically distinguishable from the first two groups.

A more detailed analysis of the CLP indicator and its sub-indicators suggests that countries characterised by strong overall CLP have pro-competition policies in place in all dimensions rather than strong performances on specific, isolated elements of the indicator.

Countries with policies less favourable to competition are characterised by the relatively limited independence of their regulators (network policies). This tends to go together with relatively weak policies for securing entry in liberalised network industries.

Source OECD (2007), Competition Law and Policy Indicators

for the OECD Countries.

For further reading OECD (2007), Product Market Competition in the

OECD Countries: Taking Stock and Moving Forward.


© OECD 2009

D.5.a/b Market conditions

Competition law and policy (CLP) indicator and its main components1

A. CLP indicator

0.0

1.0

2.0

3.0

4.0

5.0

6.0

B. Antitrust framework

0.0

1.0

2.0

3.0

4.0

5.0

6.0

C. Network policies

0.0

1.0

2.0

3.0

4.0

5.0

6.0

1. The CLP indicator measures the strength of overall competition policies. It can be divided into an indicator for antitrust (scope and enforcement of law and independence of competition authority) and an indicator for network policies (independence of sector regulators and network access). Source: OECD, CLP Indicators for the OECD Countries, 2007.


© OECD 2009


Definitions

The import and export burden indicators are the average of three measurements: i) the number of documents required to import/export goods; ii) the time (in days) necessary to comply with all procedures to import/export goods; and iii) the cost and fees (in USD) levied on a 20-foot container. The three sub-indicators have been normalised on a scale from 1 to 100 before taking the average and constructing the indicator. These indicators are part of the Ease of Doing Business Survey, under the heading, “Trading across borders”.

All documents required per shipment to export and import the goods are included, e.g. documents required for clearance by government ministries, customs authorities, port and container terminal authorities, health and technical control agencies and banks.

The time calculation for a procedure starts from the moment it is initiated and runs until it is completed. If a procedure can be accelerated for an additional cost, the fastest legal procedure is chosen. It is assumed that neither the exporter nor the importer wastes time and that each commits to completing each remaining procedure without delay. The waiting time between procedures – e.g. during the unloading of cargo – is included in the measure.

All the fees associated with completing procedures to export or import the goods are included: costs for documents, administrative fees for customs clearance and technical control, customs broker fees, terminal handling charges and inland transport. The cost measure does not include tariffs or trade taxes; only official costs are recorded.

Comparability

The World Bank’s Doing Business project uses standardised scenarios to measure regulation across countries in order to achieve broader global coverage and enhance international comparability. Procedural requirements for exporting and importing a standardised cargo of goods by ocean transport are compiled: official procedures for exporting and importing the goods is recorded along with the time and cost necessary for completion. The time and cost for ocean transport are not included. Payment is made by letter of credit, and the time, cost and documents required for the issuance or advising of a letter of credit are also taken into account.

Local freight forwarders, shipping lines, customs brokers, port officials and banks provide information on required documents and cost as well as the time to complete each procedure. To make the data comparable across economies, several assumptions about the business (e.g. private limited liability company, 60 or

more employees, domestically owned with no foreign ownership, located in the country’s most populous city) and the traded goods (e.g. the product is not hazardous nor does it include military items, does not require refrigeration).

Overview

Market conditions are important not only in the domestic market but also on international markets: entrepreneurship has become increasingly international in the global economy, often from the start-up phase.

Data on import and export burdens show marked variability, even among OECD countries. The empirical evidence shows that administrative requirements for exporting/importing goods are almost non-existent in some countries, while numerous in others. These result in longer delays and higher costs for international transactions.

The pattern of import and export burdens across countries is roughly the same, with countries characterised by higher (lower) import burdens also having higher (lower) export burdens.

On the import side, Denmark, Korea and Sweden are very open to goods from abroad, while importing these same goods in some eastern European countries is much more difficult.

Differences among countries for exporting goods are smaller, but the export burden seems to be highest in the same eastern European countries (as for the import burden), preceded by Brazil. Overall, import and export burdens seem to be correlated.

Source World Bank (2009), Doing Business Survey.

For further reading Djankov, S., C. Freund and C.S. Pham (2008), “Trading

on Time”, Review of Economics and Statistics, November 2008.


© OECD 2009

D.5.c/d Market conditions

Import burden1

Scale from 1 to 100

0

5

10

15

20

25

30

35

1. Average of: i) number of documents; ii) time; and iii) cost to import a specific good. Source: World Bank, Doing Business, 2009.

Export burden1

Scale from 1 to 100

0

5

10

15

20

25

30

35

1. Average of: i) number of documents; ii) time; and iii) cost to export a specific good. Source: World Bank, Doing Business, 2009.


© OECD 2009


Definitions

Preference for self-employment reflects the percentage of people who choose to be self-employed rather than work as employees. The question was asked in a broad survey (conducted by Gallup for the European Commission) specifically related to entrepreneurship in 2000, 2004 and 2007.

Entrepreneurial perceptions relate to the percentage of persons who see positive opportunities for starting up a business in the next six months in their country. This percentage is expressed relative to the adult population aged 18-64 years.

The risk perception measures the percentage of persons who indicate that the fear of failure would prevent them from starting a business. This percentage is also expressed relative to the adult population aged 18-64 years.

Comparability

A total of 20 647 people were interviewed by telephone for the Flash Eurobarometer survey in January 2007. Data are available for European countries including the (then) new EU member states, Iceland, Norway and the United States. Each national sample is representative of the population aged 15 years and above. In most large countries the target sample size was 1 000 respondents, while for smaller countries the target sample size was 500. The survey is based on the use of a standardised questionnaire in each country so that international comparability is likely to be good.

The Global Entrepreneurship Monitor (GEM) uses surveys in 54 developed and developing countries in 2009. The Adult Population Survey asks a representative sample of at least 2 000 adults in each country about their attitude to and involvement in entrepreneurship. GEM takes a broad view of entrepreneurship and focuses on the role played by individuals in the entrepreneurial process. The survey asks questions about personal assessments, attitudes and perceptions, in addition to intentions to start a business in the near future.

Overview

Assessing and benchmarking countries’ entrepreneurial culture is a difficult exercise and often has to rely on surveys, which by definition are more subjective and may lack some international comparability.

The data on the preference for self-employment (as a proxy, albeit rough, for entrepreneurship) show considerable variation across countries. EU countries

clearly show a lesser preference for self-employment than the United States. Within the European Union significant differences are clear, especially in new member states and some southern countries, with significantly more people, often more than 50%, choosing self-employment. Whether this is related to the perception of attractive opportunities (so-called opportunity entrepreneurship) or the lack of employment alternatives (so-called necessity entrepreneurship) requires further analysis.

Changes over time indicate that self-employment has become significantly less attractive in some countries. For example, Spain, Greece, France, etc., were characterised by a high preference for self-employment in earlier years.

Deciding to become an entrepreneur should take into account positive as well negative consequences. A prerequisite for starting a business is to identify positive opportunities. These typically depend on factors such as the economic climate, population growth, competition, and the country’s entrepreneurial culture and policy. Perceptions of entrepreneurial opportunities are quite high across countries, although they have dropped slightly as a consequence of the economic crisis.

Identifying attractive entrepreneurial opportunities is not sufficient, however, as the fear of failure may make people hesitate to start a business. Risk-adverse persons perceive this risk of failure (very) strongly and attach more importance to the potential negative consequences of an entrepreneurial failure. The data seem to suggest that lower opportunity perceptions go hand in hand with higher risk perceptions and vice versa.

Source and for further reading

Flash Eurobarometer (2007), “Entrepreneurship

Survey of the EU (25 Member States), United States, Iceland and Norway”.

Bosma, N.S., Z.J. Acs, E. Autio, A. Coduras and J. Levie, 2009, Global Entrepreneurship Monitor 2008, Executive Report, Babson College, Universidad del Desarollo, Global Entrepreneurship Research Association, data available on www.gemconsortium.org.


© OECD 2009

D.6.a/b Entrepreneurial culture

Preference for self-employment, 2007 and 20001

Percentage of respondents who choose being self-employed over being an employee

0

10

20

30

40

50

60

70

80

2000 2007

1. 2000 data are 2004 data for the Czech Republic, Estonia, Hungary, Latvia, Lithuania, Poland, the Slovak Republic and Slovenia. Source: EU Flash Eurobarometer, Entrepreneurship Survey 2007.

Entrepreneurial perceptions, 2009

Percentages

0

10

20

30

40

50

60

70

Good conditions to start business next 6 months in area I live Fear of failure would prevent starting a business

Notes: Denominator: non-entrepreneurially active adult population 18-64 years. Denominator: non-entrepreneurially active adult population 18-64 who see good opportunities to start a business. Source: Bosma, N.S., Z.J. Acs, E. Autio, A. Coduras and J. Levie, 2009, Global Entrepreneurship Monitor 2008, Executive Report, Babson College, Universidad del Desarollo, Global Entrepreneurship Research Association, data available on www.gemconsortium.org.


© OECD 2009


Definitions

The perceived image of entrepreneurship across countries has been assessed using specific survey questions. The indicators on the positive and negative image of entrepreneurs reflect the percentage of respondents agreeing with some (rather bold) statements on the role and importance of entrepreneurs in society.

The positive attitude towards entrepreneurship was surveyed using the following statements:

- ”Entrepreneurship is the basis of wealth creation, benefiting us all.”

- “Entrepreneurs are job creators.”

The negative attitude towards entrepreneurship was assessed by responses to the following statements:

- “Entrepreneurs exploit other people’s work.”

- “Entrepreneurs think only about their own wallet.”

Comparability

A total of 20 647 people were interviewed by telephone for the Flash Eurobarometer survey in January 2007. Data are available for European countries, including the (then) new EU member states, Iceland, Norway and the United States. Each national sample is representative of the population aged 15 years and above. In most large countries the target sample size was 1 000 respondents, while for smaller countries the target sample size was 500. The survey is based on the use of a standardised questionnaire in each country so that international comparability is likely to be good.

Overview

The perceived image which entrepreneurship benefits or suffers from is a very important element of a country’s entrepreneurial culture. It is clear that this perceived image may directly affect the perception of (potential) entrepreneurs but also the broader chances afforded to entrepreneurship in a society. Culture and image are typically affected by a large number of factors, among them the media and the school system.

Government policies can promote an entrepreneurial culture, for example through the support of events and media coverage, the creation of role models, the education system, etc. However these policies need to take a long-term perspective since culture is closely related to mentality and values, which typically change slowly, sometimes over a long time.

A detailed look at the data shows that the image of entrepreneurship and entrepreneurs is more positive than negative; this is the case for all countries. The most widespread notion about entrepreneurship is that “entrepreneurs are job creators”. Likewise, respondents generally agree with the positive statement that “entrepreneurship is the basis of wealth creation, benefitting us all”.

Much more disagreement exists concerning the negative statements. In a couple of countries, more than half of respondents agreed that “entrepreneurs exploit other people’s work” and/or “entrepreneurs think only about their own wallet”. Interestingly, some of these countries appear quite high in international rankings of corruption and fraud. More research is needed in order to establish the causal relationship, if any, between the two observations.

Source and for further reading Flash Eurobarometer (2007), Entrepreneurship

Survey of the EU (25 Member States), United States, Iceland and Norway.


© OECD 2009

D.6.c/d Entrepreneurial culture

Positive image of entrepreneurship and entrepreneurs

Percentage of respondents who agree

0

10

20

30

40

50

60

70

80

90

100

Entrepreneurship is the basis for wealth creation, benefiting us all Entrepreneurs are job creators

Source: EU Flash Eurobarometer, Entrepreneurship Survey, 2007.

Negative image of entrepreneurship and entrepreneurs

Percentage of respondents who agree

0

10

20

30

40

50

60

70

80

90

100

Entrepreneurs think only about their own wallet Entrepreneurs exploit other people's work

Source: EU Flash Eurobarometer, Entrepreneurship Survey, 2007.


© OECD 2009

–

Acknowledgements

Since the beginning of the EIP, the Entrepreneurship Indicators Steering Group has played a crucial role in harmonising definitions, collecting data and producing indicators. It continues to contribute significantly to the development of the EIP by charting the strategic orientations of the programme, reviewing past and current research, and suggesting future areas of work. With the increasing coverage of the EIP in terms of countries, regions and indicators, the composition of the Steering Group has changed. During the past year, the EIP has benefited significantly from their contributions.

Entrepreneurship Indicators Steering Group 2009

Andalucia Iria Enrique Regueira Regional Statistical Institute of Andalucia

Australia Richard Seymour University of Sydney

Canada Bob Pagnutti Statistics Canada

Klaus Kostenbauer Statistics Canada

Chris Parsley Small Business Policy, Industry Canada

Denmark Anders Hoffmann (Chair) Danish Ministry of Economics and Business

Peter Bøegh Nielsen Statistics Denmark

EU Commission Axel Behrens (Vice Chair) Eurostat

Manfred Schmiemann Eurostat

Hartmut Schroer Eurostat

Ludger Odenthal DG Enterprise

Finland Timo Laukkanen Statistics Finland

Hungary Zoltán Roman National Statistics Office

Italy Caterina Viviano ISTAT

Portugal Paula Bordelo Statistics Portugal

United Kingdom Karen Grierson Small Business Service, BERR

United States Rick Clayton (Vice Chair) Bureau of Labor Statistics

David Talan Bureau of Labor Statistics

Ron Jarmin Census Bureau

Javier Miranda Census Bureau

E.J. Reedy Kauffman Foundation

Leora Klapper Development Research Group

OECD Mariarosa Lunati Centre for Entrepreneurship, SMEs and Local Development

Benoit Arnaud Statistics Directorate

Tim Davis Statistics Directorate

Koen De Backer Statistics Directorate

Documents

OECD-Eurostat Entrepreneurship Indicators …areadocenti.eco.unicas.it/ferrante/OECD-EUROSTAT.pdfOECD-Eurostat Entrepreneurship Indicators Programme ... In 2006 the joint OECD-Eurostat