Entrepreneurship is considered to be an important mechanism for economic development through employment, innovation and welfare effects (Schumpeter 1934; Acs and Audretsch 1988; Wennekers and Thurik 1999; Baumol 2002). The dynamics of entrepreneurship can be vastly different depending on institutional context and level of economic development. There are considerable differences across countries in the orientation of entrepreneurial activities (Autio 2007). The nature and structure of entrepreneurial activities varies across countries as reflected by, for example, the relative volumes of necessity and opportunity entrepreneurship. Acs and Varga (2005) studied 11 countries and found that opportunity entrepreneurship has a positive significant effect on economic development, whereas necessity entrepreneurship has no effect.

The environment shaping the economy affects the dynamics of entrepreneurship within any given country. This environment is marked by interdependencies between economic development and institutions, which affect other characteristics, such as quality of governance, access to capital and other resources, and the perceptions of entrepreneurs. Institutions are critical determinants of economic behavior (North 1990) and economic transactions (Williamson 1998) in general, and they can impose direct and indirect effects on both the supply and demand of entrepreneurs. Therefore, if one is interested in studying entrepreneurship within or across countries, the broad nexus between entrepreneurship, economic development and institutions is a critical area of inquiry. This nexus is especially important in helping understand why the relative contributions of entrepreneurship can vary significantly across countries and regions.

Understanding this nexus is crucial to gain insight into what can work for economic development. This is for two reasons. First, the international economic development community has learned that a one-size-fits-all approach simply does not work (Easterly 2001). Second, economic importance attributed to “the entrepreneur” and concurrent policy interest in his/her activities has exploded in recent years. This combination suggests that public policy needs to be informed by the dynamics of entrepreneurship and economic development, as well as relevant local institutional conditions and context-specific variables.

The articles in this special issue represent papers presented at the 3rd Global Entrepreneurship Monitor (GEM) research conference. The first conference in Berlin, Germany, focused on variation in entrepreneurial activity in developed countries (Sternberg and Wennekers 2005), while the second conference in Budapest, Hungary, expanded the focus to transition countries (Acs and Szerb 2008). The third conference in Washington, D.C., organized by George Mason University and Babson College, and expanded the focus to developing countries. It was dedicated to the nexus between entrepreneurship, economic development and institutions in the global economy. The next section outlines the relationship between economic development and globalization. Section III focuses on the relationship between entrepreneurship and economic development and asks the question, “How well do existing measures of entrepreneurship measure the relationship between entrepreneurship and economic development?” Section IV summarizes the papers in the special issue, and the concluding section examines the policy implications.

Economic development and globalization

Porter (1990) and Porter et al. (2002) define competitiveness according to country economic development, distinguishing three specific stages: (1) factor-driven stage, (2) efficiency-driven stage and (3) innovation-driven stage; and two transitions between these stages. Countries in the factor-driven stage compete through low cost efficiencies in the production of commodities or low value-added products. The first stage is marked with high rates of non-agricultural self-employment. Sole proprietorships—i.e., the self-employed—probably account for most small manufacturing firms and service firms. Almost all economies experience this stage. These countries neither create knowledge for innovation nor use knowledge for exporting.

To move into the second stage, the efficiency-driven stage, countries must increase their production efficiency and educate the workforce to be able to adapt in the subsequent technological development phase. To compete in this second stage, countries must have efficient productive practices on large markets, which allow companies to exploit economies of scale. Industries in this stage are manufacturers or provide basic services (Syrquin 1988). The efficiency-driven stage is marked by decreasing rates of self-employment. There are several reasons to expect entrepreneurial activity will decrease as economies become more developed (Kuzents 1966; Schultz 1988).Footnote 1 If we assume individuals have different endowments of managerial ability, then as an economy becomes wealthier, the average firm size should increase as better managers run the companies. Average firm size is an increasing function of the wealth of the economy if capital and labor substitute. When capital and labor are substitutes, an increase in the capital stock increases returns from working and lowers returns from managing.

In other words, marginal managers find they can earn more money when employed by somebody else. In this model of economic development, increases in the capital stock (through private enterprise, direct foreign investment or government ownership) will increase returns to wage work relative to entrepreneurial activity. In this model, the relationship between entrepreneurial activity and economic development would be negative. That is, as the economy becomes more developed, we should find fewer people pursuing entrepreneurial activity.Footnote 2

The innovation-driven stage is marked by an increase in entrepreneurial activity. For over a century there has been a trend in economic activity, exhibited in virtually every developed industrialized country, away from small firms and towards larger organizations. It was, therefore, particularly striking when a series of studies identified this trend had not only ceased sometime during the mid 1970s, but had actually begun to reverse itself (Blau 1987; Evans and Leighton 1989). More recent studies have confirmed this result for most developed countries in the 1970 and 1980s (Acs et al. 1994b). The empirical evidence clearly shows that firm size distribution in developed countries began to shift away from larger corporations and towards entrepreneurial activity.

There are three reasons entrepreneurial activity rises in the final stage of economic activity. First, the innovation-driven stage is marked by decreases in the share of manufacturing in the economy. Virtually all industrialized market economies experienced a decline in manufacturing over the last 30 years. The business service sector expanded relative to manufacturing. Service firms are smaller on average than manufacturing firms; therefore, economy-wide average firm size may decline. Moreover, service firms provide more opportunities for entrepreneurship. This is clearly the case in the United States, as well as in several EU countries, including Germany and Sweden.

Second, technological change during the postwar period has been biased towards industries in which entrepreneurial activity is important (Jorgenson 2001). Improvements in information technologies, such as telecommunications, may increase returns to entrepreneurship. Express mail services, photocopying services, personal computers, the internet, web services and mobile phones services make it less expensive and less time consuming for geographically separate individuals to exchange information.

Third, Aquilina et al. (2006) have come to the conclusion that a high value of the elasticity of factor substitution not only leads to more per capita capital, but makes it at the same time easier for an individual to become an entrepreneur if the aggregate elasticity of substitution is also negative. In an economy characterized by higher values of the aggregate elasticity of substitution, we should expect a higher level of development, more entrepreneurs and smaller firms.

In recent years, economists have come to recognize the input-completing and gap-filling capacities of entrepreneurial activity in innovation and growth, and the significant contribution of innovation and growth to prosperity and economic welfare (Acs and Armington 2006; Schramm 2006; Audretsch 2007). Therefore, while most developed countries are in the innovation-driven stage, most developing economies, including Brazil, Russia, India and China (BRIC countries), are in the efficiency-driven stage. In addition to differences in the nature of competition across stages, there are also differences in the degree of integration of countries into the world economy. In particular, since innovation contributes to competitive advantage in foreign markets (Roper and Love 2002; Sterlacchini 1999; Wakelin 1998), developed economies are better integrated globally (UNCTAD 2006) and tend to have higher levels of export-oriented entrepreneurship than developing economies (De Clercq et al. 2008). In order for economies to move into the innovation-driven stage, it is necessary for them to develop environmental conditions conducive to entrepreneurship. Several countries have achieved this in the past decade, including Korea, Ireland, Israel and Taiwan to name few (Acs and Szerb 2007).

Entrepreneurship data and economic development

The Global Entrepreneurship Monitor (GEM) research program is an annual assessment of the national level of entrepreneurial activity. Initiated in 1999 with 10 countries, expanded to 21 in the year 2000 and over 60 countries in 2008, the program covers both developed and developing countries. The research program, based on a harmonized assessment of the level of national entrepreneurial activity for all participating countries, involves exploration of the role of entrepreneurship in national economic growth. Representative samples of randomly selected adults, ranging in size from 1,000 to almost 27,000 individuals, are surveyed annually in each participating country to provide harmonized measures of the prevalence of entrepreneurial activity. There is, further, a wealth of national features and characteristics associated with entrepreneurial activity.Footnote 3

The GEM project is unique in that while all countries collect official data on self- employment, the size distribution of firms, census data on all or most plants and firms, firm and plant entry, almost none of these registry sources are comparable across countries, even developed countries. Official data sources differ in the way they define when an establishment enters a file, when it leaves and how they handle self-employment, which makes cross-national comparisons almost impossible.Footnote 4 Therefore, one of the major strengths of the GEM project is the application of uniform definitions and data collection across countries for international comparisons.

The intent of GEM data is to systematically assess two things: The level of start-up activity or the prevalence of nascent firms and the prevalence of new or young firms that have survived the start-up phase. First, start-up activity is measured by the proportion of the adult population (18–64 years of age) in each country that is currently engaged in the process of creating a nascent business. Second, the proportion of adults in each country who are involved in operating a business that is less than 42 months old measures the presence of new firms. The distinction between nascent and new firms is made in order to determine the relationship of each to national economic growth. For both measures, the research focus is on entrepreneurial activity in which the individual involved has a direct, but not necessarily full ownership interest in the business. The GEM model serves as a vehicle to interpret both the data collection process and provide a framework for theory and policy (Levie and Autio 2008).

A major shortcoming of GEM data has been the fact that it has not been able to effectively deal with the ‘issue’ of how to compare entrepreneurial activity in developed and developing countries. For example, low-income countries, such as Uganda, Peru and Ecuador, have very high levels of self-employment and therefore, have high levels of entrepreneurial activity as measured by the GEM program. High-income countries like Japan, Sweden and Germany have much lower levels of entrepreneurial activity as measured by the GEM program.

In order to address this issue for developing countries, GEM researchers started to collect data on both opportunity entrepreneurship (starting a business to exploit a perceived business opportunity) and necessity entrepreneurship (starting a business because you were pushed into it). However, both measures show higher levels in developing countries than in developed countries. Many respondents are probably tempted to state they are pursuing an opportunity rather than being involved in entrepreneurial activities because they have no other option for work, even if the latter statement describes the activity best. Moreover, the relationship between necessity entrepreneurship and economic development is most likely negative in low-income countries, while the relationship between entrepreneurship and economic development in high-income countries is most likely positive. This must be further balanced by the fact that some countries like India and China have high levels of opportunity entrepreneurship, at least in certain parts, and countries like Japan have very low levels of opportunity entrepreneurship and low growth.

Therefore, we would expect that in economies in the early or middle stage of economic development, the efficiency-driven stage, entrepreneurial activity would be negatively related to economic development since most people would be trying to move from self-employment to wage employment. In developed economies, we would expect entrepreneurial activity to be positively related to economic development as people shift from wage work to entrepreneurial activity, the innovation driven stage. This framework seems to imply that a U-shaped relationship may in fact exist between entrepreneurial activity and economic development in the global economy. Countries like Uganda, Peru and Ecuador are all countries with high levels of entrepreneurial activity—but low levels of per capita income. Countries with much lower levels of entrepreneurial activity, for example, Brazil and Argentina, appear to have higher levels of per capita income and are moving toward lower levels of entrepreneurial activity. The middle represents a set of countries that appear to be transitioning from a middle-income level to a higher income level, and some have rising levels of entrepreneurial activity. High-income countries, such as Germany, France, Belgium, Italy and Finland, have relatively low levels of entrepreneurial activity. Two countries stand out as outliers: Japan, with one of the lowest levels of entrepreneurial activity, and the United States, with one of the highest levels of entrepreneurial activity.

The story for developed countries is different and has its origins in the work of David Blau (1987), who was the first to document the upturn in self-employment rates after they declined for the better part of a century. There is tremendous diversity in the level and time-series pattern of entrepreneurship across countries. They show that the major explanation for this diversity is the stage of economic development. They also show that the negative relationship between entrepreneurship and economic development remains after controlling for a number of other factors. Although economic development is an extremely powerful force behind the secular decline in entrepreneurship, the convergence of several factors in the 1970 s tended to stem the secular decline in entrepreneurship for many countries. Of 23 OECD countries examined by Acs et al. (1994b), 15 had a U-shaped relationship during the 1970s or 1980s.

What caused the upturn in small-scale economic activity? Acs et al. (1994a) explored six possible sources of inter- and intra-country variations in self-employment: (1) stages of economic development, (2) the bias of technological change, (3) changes in industry composition, (4) changes in female labor-force participation, (5) unemployment and (6) cultural factors. The paper also compared and contrasted self-employment in OECD countries and in less developed countries. A major explanation for this diversity is the stage of economic development. While the tendency for the self-employment rate to decline with economic development was recognized as earlier as Kuzents (1966), this paper was the first attempt to estimate the statistical relationship between self-employment and economic development and to test a theoretical explanation for this relationship. Recent studies confirm that during the last 2 decades, the development of new technologies, and the emergence of new business models, has shifted from large corporations to small and new ventures (Jorgenson 2001; Audretsch and Thurik 2001). The literature shows that entrepreneurship contributes to economic performance by introducing innovation, enhancing rivalry and creating competition.

This line of research has greatly expanded in the past decade. An important paper by Carree et al. (2002) examined the relationship between economic development and business ownership for OECD countries, and reaffirmed the existence of a U-shaped relationship. In a second important paper, Wennekers et al. (2005) for the first time regressed GEM data for nascent entrepreneurship on the level of economic development. They also found support for the U-shaped relationship between countries at different stages of development (see Fig. 1).

Fig. 1
figure 1

Nascent entrepreneurship versus per capita income, the U-curve. Source: Wennekers et al. (2005)

However, this literature is not without limitations for the study of entrepreneurship and development. There are three observations. First, the U-shaped approach is useful in understanding the decline in self-employment in developing countries both across countries and over time, but not useful or at least less useful in explaining entrepreneurship (broadly defined). Second, the U-shaped approach is not very useful in explaining the role of entrepreneurship in developing countries in the efficiency-driven stage of development, either as they enter the efficiency-driven stage or leave the efficiency-driven stage (Acs and Amorós 2008). Finally, while the U-shaped framework was originally developed to understand the increase in entrepreneurship in high-income OECD countries, the model is also of limited value here, as many have questioned the U-shaped model. Carree et al. (2007) suggested that the L-shaped and U-shaped relationship between entrepreneurship and economic development couldn’t be distinguished empirically because not all countries are in the upward part yet.

In some sense, the “chapter” on this line of research has reached a dead end. First, the U-shaped relationship does not provide an adequate explanation for the relationship between entrepreneurial activity and economic development. Second, the family of TEA measures, as well as other measures, reflects various activities or components related to “entrepreneurship” in both developed and developing countries (Acs et al. 2008), and can independently be inadequate for policy planning.

The 2004 Global Entrepreneurship Report (Acs et al. 2005) started to pursue the idea of using the opportunity-necessity ratio as a composite indicator of entrepreneurial activity and economic development. Global Entrepreneurship Monitor (GEM) data are used to identify the type of activity in countries at different levels of development. Opportunity entrepreneurship represents the voluntary nature of participation and necessity, reflecting the individual’s perception that such actions presented the best option available for employment, but not necessarily the preferred option, as explained earlier. Opportunity entrepreneurship differs from necessity by sector of industry and with respect to growth aspirations. Opportunity entrepreneurs expect their ventures to grow more and provide more new jobs.

A clearly discernible trend occurs between the ratio of opportunity to necessity entrepreneurship and the per capita income of a country. Figure 2 illustrates this trend. On the x-axis, countries are ranked from lowest to highest opportunity to necessity entrepreneurship ratio. Opportunity to necessity entrepreneurship ratio is a short-hand approach to describe the importance of the desirable, opportunity entrepreneurship relative to the necessity-induced entrepreneurship. The advantage of this ranking is that countries with high levels of necessity entrepreneurship are ranked with low levels of entrepreneurship. The values of opportunity to necessity entrepreneurship ratio are measured on the y-axis. The right-hand-side y-axis is for country per capita income data in 2002, with individual values also shown on the diamond line.

Fig. 2
figure 2

Opportunity–necessity entrepreneurship ratio and income per capita. Note: entrepreneurship data are for 2004, income data for 2002 (the latest available). The sample of countries is defined by the Global Entrepreneurship Monitor database. Source: entrepreneurship data GEM 2004 Global Report, accessible at; income data United Nations Development Program, Human Development Report 2004, Table 13. Source: Acs (2006)

We have fitted a polynomial regression line to estimate the relationship between the opportunity-necessity entrepreneurship ratio and country income. While some fluctuations occur, a positive relationship appears between income level and the entrepreneurship ratio. In other words, countries where more entrepreneurship is motivated by an economic opportunity recognized than by necessity have higher levels of income. Immediately, the ranking of countries looks more reasonable. Brazil with an Opp/Nec of 1.1 is at the bottom, Japan is in the middle next to New Zealand, and Denmark is near the top.

Finally, if the U-shaped measures are inadequate for understanding entrepreneurship in developed and developing countries, can we rely on other measures? This introduction takes a step in this direction. Acs and Szerb (2008), Acs and Stenholm (2008), Ahmad and Hoffmann (2008) and Klapper et al. (2007), among others, are developing a new family of global entrepreneurship indices. For example, as shown in Fig. 3, the startup rate (Startuprte) is constructed as the total number of new corporations in a given year as a percentage of the total number of corporations in that year, between 2003 and 2005, and is based on data from the World Bank database. GDP per capita is based on purchasing power parity in US dollars. A more or less linear relationship is exhibited between entrepreneurship and economic development.Footnote 5 That is, the index is not U-shaped, but rises with the level of development.

Fig. 3
figure 3

World Bank startup data and income per capita. Source: Virgill (2008)

The Complex Global Entrepreneurship Context Index (CEC) uses 26 variables and measures entrepreneurial activity, strategy and attitudes for 54 countries, including developed and developing countries across the years 2003–2006 (see Fig. 4). The index takes a value from 0 to 1 and is plotted against income per capita based on purchasing power parity in US dollars. The results are again positively related with development.

Fig. 4
figure 4

The Complex Entrepreneurship Context CEC Index and Per Capita GDP. Source: Acs and Szerb (2008)

We can already measure entrepreneurship in developed and developing countries using existing measures, but they cannot easily be used in the same analysis. The development of measures like the World Bank Group Entrepreneurship Survey and the Complex Entrepreneurship Context index can be helpful in providing a broader and more encompassing picture of entrepreneurship. That is, the picture of the relationship between entrepreneurship and economic development appears to be more or less mildly S-shaped, not U-shaped. These measures can enable comparison of developed and developing countries in the same analysis (Virgill 2008).

We now turn to the papers in this special issue. The papers, in one way or another, address the issues surrounding the need for a global entrepreneurship index. The results of this section on the empirical relationship between entrepreneurship and economic development are revealing. The CEC index is broadly consistent with the factor-driven stage, the efficiency-driven stage and the innovation-driven stage of development (Porter et al. 2002). In other words, in the efficiency-driven stage, entrepreneurial activity is mildly increasing or relatively flat as necessity entrepreneurship is steadily reduced and innovation comes from the outside, since developing countries are far from the technological frontier (Acemoglu et al. 2007). In fact, this was demonstrated in the case of Ireland by Acs et al. (2007) and is addressed by two papers in this issue (De Clercq et al. 2008; Acs and Amoros 2008). The role of foreign direct investment becomes critical in creating efficiency in the efficiency-driven stage and knowledge spillovers to move a country to the technological frontier, which is synonymous with the innovation-driven economy (Baumol et al. 2006).

Overview of the papers

This special issue on the nexus between entrepreneurship, economic development and institutions is structured to present multiple levels of analysis, beginning with a broad conceptual model of the GEM framework that addresses the relationship between national-level business activity and institutional environments. The first paper, by Jonathan Levie and Erkko Autio, provides a theory-grounded examination of the GEM Model, and empirically tests several hypotheses that emerge from the model. In the second paper, Zoltan Acs, Sameeksha Desai and Leora Klapper present a cross-country study comparing two datasets on entrepreneurship against several important institutional variables. The third paper is authored by Dirk de Clerq, Jolanda Hessels and André van Stel, and examines the link between several macro-level environmental factors and entrepreneurs’ export orientation across 34 countries. In a paper focused on the regional level, Zoltan Acs and José E. Amorós examine competitiveness and entrepreneurial dynamics in Latin America. Finally, Jolanda Hessels, Marco van Gelderen and Roy Thurik examine the drivers of entrepreneurial aspirations and start-up motives using data at the country level, including the role of economic development and welfare state institutional arrangements. Table 1 provides an overview of some of the main features of the papers in the special issue.

Table 1 Main characteristics of papers

In the early days of GEM, a conceptual model including various Entrepreneurial Framework Conditions (EFCs) was developed. These EFCs indicate various conditions in which entrepreneurship is likely to flourish. It includes aspects such as access to finance, existence of government support policies for entrepreneurship, presence of entrepreneurship-specific training and education, and access to and transfer of R&D and technology. The general idea of the GEM model is that the various EFCs affect entrepreneurial activity by enhancing opportunity recognition and skills perception. The Levie-Autio paper presents the GEM model and shows that there is a sound theoretical backing for the GEM conceptual model and EFCs. They ground the analysis in the Austrian tradition and examine how broad environmental conditions can affect the individual. Agents choose to engage in new business activity when they perceive opportunities and have the skills to start a business. However, a range of entrepreneurial framework conditions influence opportunity recognition and skills perception.

At the time when the GEM model was developed, proper testing of the suggested impact of the EFCs was not possible due to lack of data. The Levie-Autio paper is among the first to empirically test the impact of EFCs on early stage entrepreneurial activity and high-expectation entrepreneurship using data for the years 2000–2006. In their analysis, the authors focus specifically on the impact of one EFC, entrepreneurial education and training, on new business activity. This choice was guided by strong policy interest toward entrepreneurship education. Their main finding is that in high-income countries, post-secondary entrepreneurship education and training are positively related to the level of new business creation activity. It is also positively related to high-growth-expectation new-business activity, more by enhancing opportunity perception and less by enhancing skills perception. The importance of opportunity perception in determining action, rather than skills perception, is in line with the ideas of Kirzner (1979).

As mentioned above, comparable cross-country datasets on entrepreneurship were unavailable, and GEM was one of the first initiatives to collect harmonized international data. Recently, continued policy interested in entrepreneurship has led to several large-scale initiatives to collect data. These include Eurostat, OECD and the World Bank. The Acs–Desai–Klapper paper provides a comparison of two datasets that are developed to capture entrepreneurial dynamics: GEM and the World Bank. They illustrate various differences between these two datasets. GEM, for example, focuses on early-stage entrepreneurial activity, and the World Bank data capture formal business registration. GEM uses a research design that has been harmonized across all participating countries, while cross-country harmonization has not yet been achieved in national business registries. GEM data tend to report significantly higher levels of early stage entrepreneurship in developing economies than does the World Bank business entry data, while the World Bank business entry data tend to be higher than GEM data for developed countries.

The authors undertake a number of empirical exercises linking both data sources to institutional variables and find that the magnitude of the difference in rates reported across countries in the two databases is related to local institutional and environmental conditions for entrepreneurs, after controlling for level of economic development. An explanation for this discrepancy is that the World Bank measures rates of entry in the formal economy, while GEM data are reflective of entrepreneurial “intent” and capture informality of entrepreneurship, particularly in developing countries. Therefore, this discrepancy might be interpreted as the spread between individuals who could potentially operate businesses in the formal sector – and those that choose to do so, i.e., GEM data may represent the potential supply of entrepreneurs, whereas World Bank Group data would represent the actual rate of entrepreneurship. The findings of this paper suggests entrepreneurs in developed countries have greater ease and incentives to incorporate, both for the benefits of greater access to formal financing and labor contracts, as well as for tax and other purposes not related to business activities.

Institutional and environmental factors may also be important for explaining country variation in the extent to which entrepreneurship is export-oriented. Exports are an important means through which small and new ventures are able to create value, generate growth and access new knowledge and technologies (Yeoh 2004). High-tech exports play an especially important role in economic growth in both low-income and high-income countries. Exporting firms generally perform better than non-exporting firms, and in particular tend to be more productive, more capital intensive, more innovative and more efficient (Clerides et al. 1998; Kneller and Pisu 2007). However, previous research with respect to the importance of export for national economies has strongly focused on established corporations and large multinational enterprises and has paid less relative attention to the role of start-ups in international markets.

An emerging body of research focuses on the effect of spillovers on the export decision of domestic firms, or export spillovers (Aitken et al. 1997; Greenaway et al. 2004; Kneller and Pisu 2007). Domestic firms may be more inclined to engage in export activities if exposed to other economic actors’ international activities. The De Clercq-Hessels-van Stel paper focuses on such export spillover effects, with the assumption that export spillovers should be particularly relevant in the context of new ventures because emerging firms are more likely to benefit from (external) knowledge spillovers than their more established counterparts (Acs et al. 1994b; Henderson and Clark 1990). They draw on the knowledge spillover literature to suggest that a country’s proportion of export-oriented new ventures, compared to its total number of new ventures, represents an outcome of knowledge spillovers (export spillovers) that stem from foreign direct investment (FDI) and international trade.

In addition, they suggest that a country’s proportion of export-oriented new ventures is a source of knowledge spillovers (entrepreneurship spillovers) that positively influences the total level of entrepreneurial activity. The basic idea of such entrepreneurship spillovers is that exporting new ventures have preferential access to knowledge related to foreign markets and technologies that may generate novel insights into unexploited opportunities for new businesses. Also, export-oriented new ventures may act as role models; following the premises of institutional theory, individual economic actors may imitate the behavior of highly visible and successful peers. Such imitation may then provide support and legitimacy to entrepreneurship as a career choice, resulting in the creation of more new businesses within the country. In the analysis they distinguish between higher income and lower income countries. To test the hypotheses, macro-level data from 34 countries are used for the period 2002–2005.

They find that the relationship between FDI and international trade on the one hand and a country’s proportion of export-oriented new ventures on the other differs for higher and lower income countries. Specifically, the results provide indications for export spillovers to new ventures for outward FDI and international trade in higher income countries. The findings also provide some support that a country’s proportion of export-oriented new ventures functions as a catalyst for new business creation within its borders.

Various studies have shown that outcomes and antecedents of entrepreneurship differ for different groups of countries according to level of development. The Acs-Amorós paper starts with a review of the literature on economic development, focusing first on import substitution, followed by export promotion and finally the role of export promotion in developing countries. If exports are important for an economy, as suggested above, what role does entrepreneurship play? Using the traditional U-shaped model, the paper investigates how countries at the efficiency-driven stage of development are influenced by entrepreneurial behavior. They find that the traditional model of development holds when they test the U-shaped model. They find three insights. First, countries at the efficiency-driven level need to reduce necessity-driven entrepreneurship. Second, export-oriented entrepreneurs have a negative effect in developing countries, but a positive effect in developed countries. This suggests that exports in the efficiency-driven stage come from large firms and multinationals and not small firms. Third, high-impact entrepreneurs are also negatively related to development. In other words, high-impact firms operate more in the innovation-driven stage, and not the efficiency-driven stage.

Since its beginning, the GEM project has provided valuable insight into the nature of entrepreneurship by distinguishing between the opportunity and necessity motives. Since 2005, GEM data have made it possible to distinguish between independence and increased wealth within the opportunity motive. The Hessels-van Gelderen-Thurik paper investigates drivers of entrepreneurial aspirations and entrepreneurial motivations using country-level GEM data from 2005 and 2006. Aspirations have been shown to be a strong predictor of outcomes (Cassar 2007; Wiklund and Shepherd 2003). They estimate a two-equation model explaining aspirations using motivations and socio-economic variables, and explaining motivations using socio-economic variables. One of the main findings of the paper is countries with a higher incidence of increase-wealth-motivated entrepreneurs tend to have higher rates of job-growth-oriented and export-oriented entrepreneurship. The country level of social security is found to relate negatively to the prevalence of innovative, job-growth- and export-oriented entrepreneurship.

Furthermore, they find that the increase-wealth motive mediates the relationship between country levels of economic development/growth and entrepreneurial aspirations. In particular, GDP per capita has a direct positive relationship with high job growth and export aspirations, but also an indirect negative relationship with these aspiration variables through its negative relationship with the increase-wealth motive, as richer countries tend to have lower indices of increase-wealth-motivated entrepreneurs. GDP growth has a direct positive association with high job growth aspirations, and also an indirect positive relationship with high job growth and export aspirations through the increase-wealth motive.

Conclusion and policy implications

The papers included in this issue contribute to understanding the nexus among entrepreneurship, economic development and institutions. Table 2 provides a detailed overview of various policy implications that follow from the papers. The conclusions of the papers in this special issue support the findings that the global economy is divided into thee stages—the factor-driven stage, the efficiency-driven stage and the innovation-driven stage—and that in order to understand entrepreneurship in all three stages, entrepreneurship data need to reflect the stages of development. This means moving away from simple measures of entrepreneurship across countries illustrating a U-shaped relationship to more complex measures, which are positively related to development and are S-shaped.

Table 2 Policy implications of the papers

Several of the papers in this special issue have illustrated that institutional arrangements, including educational provisions, social security arrangements and other businesses, may affect various types of entrepreneurial activity directly or indirectly. Also, the papers illustrate that the impact of institutional arrangements on various types of entrepreneurial activity may differ depending on country level of economic development and even on the type of “entrepreneurship” measure examined. This collection of papers highlights the critical importance of the nature of entrepreneurship—for example, formal versus informal—and the ultimate purpose and effects of the activities—for example, necessity, opportunity, export-oriented, etc. For countries in the innovation-driven stage the results highlight that policy makers can positively affect entrepreneurship, including several ambitious types of entrepreneurship, by fostering entrepreneurship education and training, by stimulating outward FDI and international trade to facilitate export spillovers and by supporting role models. Countries in the factor-driven stage should work towards the efficiency-driven stage by focusing on achieving stable institutional and macro-economic environments and by increasing entrepreneurial capacity, e.g., by enabling individuals and businesses to absorb knowledge spillovers.

Finally, the papers reveal that complex interdependencies may exist between individual level factors, such as opportunity perception and start-up motivations on the one hand, and between national environmental or institutional conditions on the other hand. In particular, the results suggest individual-level perceptions and motivations can have a mediating role between national environmental conditions on the one hand, and levels of entrepreneurial activity in general and ambitious entrepreneurial activity, on the other hand. The examination of institutional and environmental conditions is especially useful for public policy planning because they are more quickly sensitive to policy reforms, whereas individual-level factors may require more time to be affected by public policy.