2 The global entrepreneurship and development index across stages of development
Abstract
This chapter examines the impact of productive, unproductive, underproductive, and destructive entrepreneurship on social value creation. We construct a global entrepreneurship and development index (GEDI) that captures the contextual feature of entrepreneurship across countries and stages of development. We find the relationship between entrepreneurship and economic development to be mildly S-shaped. Better institutions create the incentives to shift agents from less productive activity to more productive activity. Implications for public policy suggest that institutions need to be strengthened before entrepreneurial resource can be fully deployed.
Introduction
Joseph Alois Schumpeter pointed out over one hundred years ago that entrepreneurship is crucial for understanding economic development. Today, despite the global downturn, entrepreneurs are enjoying a renaissance the world over according to a recent survey in The Economist magazine (Woolridge, 2009). The dynamics of the process can be vastly different depending on the institutional context and level of development within an economy. As Baumol (1990) classified, entrepreneurship within any country can be productive, destructive, or unproductive. If one is interested in studying entrepreneurship within or across countries, the broad nexus between entrepreneurship, institutions, and economic development is a critical area of inquiry and one which can determine the eventual impact of that entrepreneurial activity. The interdependence between incentives and institutions affect other characteristics, such as quality of governance, access to capital and other resources, and the perceptions of what entrepreneurs perceive. Institutions are critical determinants of economic behavior and economic transactions in general, and they can have both direct and indirect effects on the supply and demand of entrepreneurs (Busenitz and Spencer, 2000).
Historically, all societies may have a constant supply of entrepreneurial activity, but that activity is distributed unevenly between productive, unproductive, and destructive entrepreneurship because of the incentive structure. To change the incentive structure you need to strengthen institutions, and to strengthen institutions you need to fix government. The role incentives play in economic development has become increasingly clear to economists and policy makers alike. People need incentives to invest and prosper. They need to know that if they work hard, they can make money and actually keep that money. As incentive structures change, more and more entrepreneurial activity is shifted toward productive entrepreneurship that strengthens economic development (Acemoglu and Johnson, 2005). This entrepreneurial activity tends to explode during the innovation-driven stage that culminates in a high level of innovation, with entrepreneurship leveling out as institutions are fully developed (Fukuyama, 1989).
The purpose of this chapter is to contribute to our understanding of economic development by constructing a GEDI that captures the essence of the contextual features of entrepreneurship and fills a gap in the measure of development (Szerb et al., 2012; Acs and Szerb, 2012). We develop a GEDI that offers a measure of the quality and quantity of the business formation process in 71 of the most important countries in the world. The GEDI captures the contextual feature of entrepreneurship by focusing on entrepreneurial attitudes, entrepreneurial activity, and entrepreneurial aspirations. These data and their contribution to the business formation process are supported by three decades of research into entrepreneur-ship across a host of countries. The index construction integrates 30 variables, 16 from Global Entrepreneurship Monitor (GEM) and 15 from other data sources, into 14 pillars, three sub-indexes, and a “super-index.”
Entrepreneurship
Baumol (1990) proposed a theory of the allocation of entrepreneurial talent in a seminal article, titled “Entrepreneurship: Productive, Unproductive and Destructive.” He makes an important observation that although entrepreneurship is typically associated with higher incomes, innovation, and growth, the entrepreneur is fundamentally engaged only in activity aimed at increasing wealth, power, and prestige (Baumol 1990: 898). Therefore, entrepreneurship is not inherently economically healthy and can be allocated among productive, unproductive, and destructive forms.
The framework presented by Baumol is useful in that it brings attention to the importance of the full range of entrepreneurial activity. The tradeoff between productive and unproductive activity has been studied, typically in developed countries, most often from the perspective of economic organization. Strong regulatory regimes often mean that policies typically oversee the direction of entrepreneurship in the economy. In contrast, many developed countries have designed economic policies specifically to minimize the ability of entrepreneurs to engage in unproductive activities, and to support productive entrepreneurship.
In many developing countries, unproductive and destructive activities are substantial components, if not the substantial components in the economy. Even in rapidly developing countries, opportunities for profit can outpace the evolution of institutions, and this mismatch widens the scope of rent-seeking or worse activities. In the underdeveloped countries, economic activities are found to be predatory and extractive.
Baumol originally proposed a framework to understand the allocation, rather than the supply, of entrepreneurship. He assumes that a certain proportion of entrepreneurs exist across and within societies. Baumol hypothesizes that the allocation of entrepreneurial talent is influenced by a structure of rewards in the economy. He suggests that the rules of the game determine the outcome of entrepreneurial activity for the economy, rather than the objectives or supply of the entrepreneurs.
According to Baumol (1990: 897), Schumpeter's analysis was not elaborate enough because it did not place value on moving between these forms of entrepreneurship. If activities are chosen based on perceived opportunity for profit (or other personal gain), it should not be assumed that the activities will be of a certain type. For this reason, Baumol (1990: 897) extends Schumpeter's list of entrepreneurial activities to include activities of “questionable value” to society, such as innovative new practices of rent-seeking. These activities of questionable value form Baumol's conception of unproductive entrepreneurship.
Unproductive entrepreneurship is what Baumol refers to as a range of activities that threaten productive entrepreneurship. Specifically, he notes rentseeking, tax evasion, and tax avoidance as the dominant forms of unproductive entrepreneurship. Within rent-seeking, he includes excessive legal engagement; within taxation, he notes that high-tax societies host a certain set of incentives for entrepreneurial effort. Unproductive entrepreneurship shifts income from one group to another group without increasing the level of wealth.
Baumol makes several useful propositions about productive and unproductive entrepreneurship, but he offers no insight into destructive entrepreneurship. In order to shed light on destructive entrepreneurship that is not captured in his existing framework, Acs and Desai proposed the theory of destructive entrepreneurship. They assume entrepreneurs operate to maximize utility and accept Baumol's proposition that the supply of entrepreneurs remains relatively constant. Acs and Desai then find most treatments of entrepreneurship allocation assuming the existence of occupational choice and limiting applicability (Desai and Acs, 2007; Desai et al., 2010, 2013).
Our new context allows us to shift the lens from Baumol's focus on entrepreneurship that creates output (productive) and entrepreneurship that is redistributive (unproductive). From this framework, we make the following propositions:
Proposition 1: destructive entrepreneurship has a negative effect on social value1
This is implicit both in Baumol and in related treatments of the concept. However, we suggest the following additional proposition to clarify why it has a negative effect on the economy.
Proposition 2: destructive entrepreneurship is rent-destroying
The distinction between unproductive and destructive entrepreneurship has been tenuous (and therefore, often ignored) because the furthest frontier of research tends to end with “rent-seeking.” For example, Murphy et al. (1993) modeled the effect of rent-seeking economic activities on growth in two ways: First, there are general equilibrium increasing returns to scale2 and, second, bureaucratic agents engaged in rent-seeking stifle innovation by discouraging entrepreneurship (i.e. through corruption). These effects of rent-seeking (stifling innovation and creating inefficiencies such as corruption) prevent the proverbial “pie” from growing, thereby generating unproductive overall results. However, this does not explain the existence of entrepreneurship, leading to actual shrinking of the pie. We consider destructive entrepreneurship to have a negative effect on gross domestic product (GDP) because the activity is not merely rent-seeking, it is rent-destroying. We outline the principal differences in forms of entrepreneurial allocation in Table 2.1.
In all cases, we broadly accept the entrepreneur to engage creatively to increase wealth, power, or prestige (Baumol, 1990) and to be motivated to capture rents. However, in the case of productive entrepreneurship, the entrepreneur is creating social value, whereas he is destroying social value as a destructive entrepreneur. In the case of unproductive entrepreneurship, he is not destroying social value but is rent-seeking, which remains consistent with Baumol's conception of unproductive entrepreneurship as redistributive.
Proposition 3: whenever resources are shifted from destructive to productive entrepreneurship, or from less productive to more productive activities, social value is created
Our assumption of uncertain political economy means that destructive entrepreneurship is most likely to occur in developing countries with some degree of political instability (although it occurs in some forms across countries). As these countries tend to rely on primary and secondary economic industries, inputs for tertiary and quaternary sector activities are not of immediate relevance. Therefore, we emphasize the effect of productive entrepreneurship on the creation of social
| Productive entrepreneurship | Unproductive entrepreneurship | Destructive entrepreneurship | |
| How does the entrepreneur treat rents | Rent-creating | Rent-seeking | Rent-destroying |
| Does the entrepreneur capture rents? | Yes | Yes | Yes |
| Net effect on social value | (+) | (0) | (-) |
value as activity is shifted out of destructive and unproductive entrepreneurship (or activity shifting to more productive uses in general) (Weitzel et al., 2010).
Productive entrepreneurship
In order to understand the role that entrepreneurship and innovation plays in economic development, it is important to review some economic theory. Technical change and economic development for most of the first part of the twentieth century was assumed to be a function of capital and labor inputs. Douglas (1934) at the University of Chicago compiled a time series of US labor supply (L) and a series of “capital”-plant and equipment (K) for the time period 1899–1922. The results suggested that labor received about 0.75 percent of output and 0.25 percent of capital, and that K/L ratio deepening (more capital per worker) was important to technological change. Of course the static interpretation was subject to much criticism.
Solow (1957) at MIT updated the date, wages, and capital returns, and improved on Douglas's simple estimation regressions by bringing in yearly data on profit/wages sharing. Now, for the 1909–49 time-span, Solow modified Douglas's earlier findings by a kind of exponential growth factor suggested by Schumpeter early on in the century. As the Nobel Laureate, Samuelson (2009: 76), recently pointed out, “This ‘residual’ Solow proclaimed, demonstrated that much of post-Newtonian enhanced real income had to be attributed to innovational change (rather than, as Douglas believed, being due to ‘deepening’ of the capital/labor K/L ratio).”
In other words, Solow found that 87 percent of economic growth was not accounted for by the accumulation of traditional factors of capital and labor. The increase in productivity not accounted for by existing factors (capital and labor) is today called total factor productivity. How does the latter growth come about? It comes about when people acquire new knowledge or use existing knowledge better. This is why economists often refer to total factor productivity as technical progress.3
Total factor productivity is a function of creating new knowledge and improving existing institutions. Over the centuries, rich countries have devised institutions that allow the accumulation of capital, have healthier lives, and better education. The Oxford English Dictionary defines institutions as an established law, custom, usage, practice, organization, or other element of the political and social life of a people. By institutions, we shall mean very loosely the arrangements that govern collective undertakings. The effectiveness of an institution depends on the rules governing it and on whether its members obey the rules (North, 1990).
This suggests that total factor productivity is dependent on the quality of knowledge and institutions. Knowledge and institutions, however, have to be combined, as Schumpeter himself pointed out, to produce what he called “new combinations” of economic activity. Successful entrepreneurs are, by definition, builders of new production functions that take the form of new approaches to providing goods and services to society – that are innovations.
All countries in the global economy in the mid-1900s faced a period of transition from a more or less planned economy to a market economy. In other words, all countries needed to worry about the level of their technology and the quality of their institutions. Again it is worthwhile to go back in time to get a better handle on this. In his classic text, Rostow (1960) suggested that countries go through five stages of economic growth: (1) the traditional society; (2) the preconditions for take-off; (3) the take-off; (4) the drive to maturity; and (5) the age of high mass-consumption. While these stages are a simplified way of looking at the development of modern economies, they identify critical events. When the Soviet Union did not develop into a mass-consumption society (in part on account of a lack of total factor productivity), the stages approach to economic growth went out of fashion.
However, growth is not an end in itself as Rostow thought. The beginning and the end of growth is opportunity. A generation's worth of work on the determinants of growth has put the cart before the horse, focusing on the factors that result in growth rather than on the dynamics of the societies within which growth occurs. As a consequence, for a generation, political leaders and policy makers alike have systematically neglected the vital role of entrepreneurship in capitalist development. As Schumpeter described over a century ago, entrepreneurs are vital to economic development not because they take risks (as we have seen recently in financial markets, risk-taking does in itself not correlate with the creation of social value), but rather because they create “new combinations” of economic activity.
Influenced by recent developments in economics, Porter et al. (2002) have provided a modern rendition of this approach by identifying three stages of development as opposed to growth: (1) a factor-driven stage; (2) an efficiency-driven stage; and (3) an innovation-driven stage and two transitions. While Rostow focused on the age of high mass-consumption, Porter et al., following recent developments in the economics of innovation, focus on the innovation-driven stage. Historically, an elite entrepreneurial class appears to have played a leading role in economic development. Today we believe that they are also crucial for the innovation-driven stage.
The factor-driven stage is marked by high rates of agricultural self-employment. Countries in this stage compete through low-cost efficiencies in the production of commodities or low value-added products. Sole proprietorships – i.e. the self-employed – probably account for most small manufacturing firms and service firms. Almost all economies experience this stage of economic development. 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: the preconditions for take-off play a crucial role. The drive to efficiency describes the first transition that is predominantly institutional in nature.
To compete in the efficiency-driven stage, countries must have efficient productive practices in large markets, which allow companies to exploit economies of scale. Industries in this stage are manufacturers that provide basic services. The efficiency-driven stage is marked by decreasing rates of self-employment. When capital and labor are substitutes, an increase in the capital stock increases returns from working and lowers returns from managing.4 For over a century there has been a trend in economic activity – exhibited in virtually every developing country – toward larger firms. The transition to the innovation-driven stage is characterized by increased activity by individual agents.
The innovation-driven stage is marked by an increase in knowledge-intensive activities (Romer, 1990). In the efficiency-driven economy, capital and labor play a crucial role in productivity; the firm is exogenous to our analysis and the focus is on technology in the decision-making process. In the innovation-driven stage, knowledge provides the key input. In this stage the focus shifts from firms to agents in possession of new knowledge (Acs et al., 2009). The agent decides to start a new firm based on expected net returns from a new product. The innovation-driven stage is biased toward high value-added industries in which entrepreneurial activity is important (Jorgenson, 2001). Aquilina, Klump, and Pietrobelli (2006) suggest that the easier it is to substitute capital for labor, the easier it is to become an entrepreneur.
According to Sala-I-Martin et al. (2007), the first two stages of development are dominated by institutions. In fact, innovation accounts for only about 5 percent of economic activity in factor-driven economies and rises to 10 percent in the efficiency-driven stage. However, in the innovation-driven stage, when opportunities have been exhausted in factors and efficiency, innovation accounts for 30 percent of economic activity. We see an S-shaped relationship between entrepreneurship and economic development because in the first transition stage entrepreneurship plays a role, but it increases at an increasing rate as the efficiency stage takes over. However, as we move from the efficiency-driven stage to the innovation-driven stage (the knowledge-driven stage) entrepreneurship plays a more important role, increasing at a decreasing rate.
Figure 2.1 shows the relationship between entrepreneurship and economic development. The S-shaped curve represents productive entrepreneurship as it increases over time. Entrepreneurship differs from innovation because it involves an organizational process. Schumpeter provided an early statement on this. In recent years, economists have come to recognize what Liebenstein (1968) termed the “input-competing” and “gap-filling” capacities of potential entrepreneurial activity in innovation and development. Entrepreneurship is considered to be an important mechanism for economic development through employment, innovation, and welfare. The intersection of the S-curve on the vertical axis is consistent with Baumol's (1990) observation that entrepreneurship is also a resource, and that all societies have some amount of economic activity, but that activity is distributed between productive, unproductive, and destructive entrepreneur-ship. As institutions are strengthened, more and more entrepreneurial activity is shifted toward productive entrepreneurship strengthening economic development (Acemoglu and Johnson, 2005). This entrepreneurial activity explodes through the efficiency-driven stage and culminates in a high level of innovation with entrepreneurship leveling out.
The valley of backwardness
Figure 2.1 explains the relationship between entrepreneurship and economic development. The figure answers one question but leaves two others unanswered. First, “how much productive entrepreneurship do we have in countries at different stages of development?” The S-curve suggests that in the factor-driven stage a relatively small amount of entrepreneurial activity is productive, that is, creates economic and/or social value. This explodes through the efficiency-driven stage and levels off in the innovation-driven stage of development. The second question is, “what are the other entrepreneurs doing?” The answer is that if the supply of entrepreneurship is constant then the majority of entrepreneurs are engaged in destructive entrepreneurship (destroying social value), underproduc-tive entrepreneurship (not increasing social value), or unproductive entrepreneur-ship (shifting social value). If a constant proportion of the population, X, is engaged in entrepreneurship and only a small fraction of this is in productive entrepreneurship, the rest are not increasing social and economic value.
This valley of backwardness above the S-curve can only be eliminated by building better institutions and changing the incentive structure of the society. All of this requires good government and governance. Our assumption of uncertain political economy means that destructive entrepreneurship is most likely to occur in developing countries with some degree of political instability (although it occurs in some forms across countries). As these countries tend to rely on primary and secondary economic industries, inputs for tertiary and quaternary sector activities are not of immediate relevance. Therefore, we emphasize the effect of productive entrepreneurship on the creation of social
The GEDI
Entrepreneurship is a complex creature which consists of numerous dimensions. It is distinct from small businesses, self-employment, craftsmanship, and usual businesses; it is not associated as a phenomenon with buyouts, change of ownership, or management succession. In light of the relevance of entrepreneurship to generating economic growth, one needs to get down to brass tacks in terms of finding a suitable measure or indicator for the level of entrepreneurship in an economy before embarking on policy initiatives. A number of attempts have been made in this respect to collect the relevant data and find suitable proxies for entrepreneurship (see, for example, Acs et al., 1994; Blanchflower, 2000; Blanchflower et al., 2001; Grilo and Thurik, 2008; Román, 2006).
Since its inception in 1999, the GEM research consortium has worked to measure and to compare entrepreneurial activity across countries. The best-known entrepreneurship measure used by GEM researchers is the Total Early-phase Entrepreneurial Activity (TEA) Index. However, the TEA index's usefulness as a measure of entrepreneurship has several limitations for cross-country comparisons (Hindle, 2006). Others have criticized the TEA for not capturing entrepreneurship in existing businesses, data inconsistency, and conflicting interpretations of the questions from one country to the next (Audretsch, 2002; Baumol et al., 2007; Godin et al., 2008; OECD, 2006).
Over the past decade, the contextual setting of entrepreneurship has received increasing attention. The widely applied indicators of entrepreneurship (self-employment, TEA, new venture creation) focus purely on individual or firm-level aggregates, failing to suitably account for the quality of the (institutional) environment. The “Ease of Doing Business Index,” the “Global Competitiveness Index,” and the “Index of Economic Freedom” try to capture the institutional features of the participating countries (Djankov et al., 2002; Miller and Holmes, 2010; Porter and Schwab, 2008; Porter et al., 2007; Sala-I-Martin et al., 2007). At the same time, in the context of entrepreneurship, while institutions are vital for development they provide only a part of the picture. The most important drawback of these indexes is their lack of microeconomic foundation.
From an examination of a vast pool of entrepreneurship-related data collected across countries, time periods, and surveys, one finds that a comprehensive, uniformly accepted, regularly assessed data-gathering effort for entrepreneurship does not exist yet. We agree with Ahmad and Hoffman (2007) that none of the existing measures fully captures the essence of entrepreneurship, empirically or conceptually. To this end, we create an independent index to provide a comprehensive measure of entrepreneurship. The index draws on previous measures of economic freedom, competitiveness, and entrepreneurial activity but improves on each of these by providing a more focused and quality-oriented approach (Acemoglu and Johnson, 2005; Acemoglu et al., 2001).
In this chapter, the impact that institutions have on the quality of entrepreneurial activity and how that affects the process of economic development is described. An index-building methodology and the data set that takes into account these dynamics when measuring entrepreneurship across countries are developed. The GEDI is a complex index reflecting the multidimensional nature of entrepreneurship. The GEDI consists of three sub-indexes, 14 pillars, and 31 variables. While some researchers insist on simple entrepreneurship indicators, none of the previously applied measures were able to explain the role of entrepreneurship in economic development.
There are several novelties in the GEDI design. First, the construction of the pillars combines together the individual and the institutional variables similar to the interaction variable methodology. In this case institutional-environmental variables can also be interpreted as country-level weights of the individual variables. Second, it is the first dynamic index that meets with the requirements of configuration theory. This approach is particularly useful in addressing the bottleneck problem of the low development of one or a few factors in entrepreneurship indicators and sub-indexes. According to the “penalizing for bottleneck method,” entrepreneurship policy can most efficiently remove barriers to entrepreneurship development by focusing on the bottleneck that is the “weakest link” amongst the indicators.
The index-building logic differs from other widely applied indexes in two respects: it incorporates individual as well as institutional variables, and takes into account the weakest link in the system. The institutional variables can also be viewed as country-specific weighting factors. Moreover, institutional variables can balance out the potential inconsistency of the GEM data collection. The weakest link refers to the decreased performance effect of the bottleneck. Practically, it means that the higher pillar values are adjusted to the weakest performing pillar value of the particular sub-index. While the exact measure of the penalty is unknown, meaning that the solution is not necessarily optimal, it still provides a better solution as compared to calculating the simple arithmetic averages. Consequently, the newly developed PFB (penalizing for bottleneck) can be applied in such cases where an imperfect substitutability exists amongst the variables and the efficiency of the system depends on the weakest performing variable. The method is particularly useful for policy making.
The sub-indexes
For the purposes of this chapter, entrepreneurship is defined as: a dynamic interaction of attitudes, activities, and aspirations that vary across stages of economic development. This approach is consistent with the revised version of the GEM conceptual model (Bosma et al., 2009). The process of building our index consists of: (1) selection of variables and weights; (2) calculation of pillars; (3) generation of sub-indexes; and finally (4) creation of the super-index. Data for the individual-level variables in the index comes from the GEM annual adult population surveys. A description of the individual variables is provided in Appendix A, Table 2A1, at the end of this chapter. Since GEM lacks the necessary institutional weighting variables, we make use of other widely used relevant data. A description of the institutional variables and their respective data sources is provided in Appendix A, Table 2A2. The variables are used to construct the 14 pillars which then go into the construction of the three sub-indexes. The three sub-indexes of activity, aspiration, and attitudes combine to constitute the entrepreneurship super-index, which we call the GEDI. Figure 2.2 contains a schematic diagram of the index's components.
For the first sub-index in Figure 2.2, entrepreneurial attitudes are defined as the general disposition of a country's population toward entrepreneurs, entrepreneur-ship, and business startups. The index involves measures for the population's opportunity perception potential, the perceived startup skills, feel of fear of failure, networking prospects, and cultural respect for the entrepreneur. Among the pillars that make up the index, the population's capacity for opportunity perception is seen to be an essential ingredient of entrepreneurial startups (Sørensen and Sorenson, 2003). Successful venture launching requires the potential entrepreneur
Note: The GEDI is a super-index made up of three sub-indexes, each of which is composed of several pillars. Each pillar consists of an institutional variable (denoted in bold) and an individual variable (denoted in bold italic). The data values for each variable are gathered from wide ranging sources.
to have the necessary level of startup skills (Papagiannidis and Li, 2005). Among the personal entrepreneurial traits, fear of failure is one of the most important obstacles hindering startups (Caliendo et al., 2009; Wagner, 2002). Better networked entrepreneurs are more successful, can identify more viable opportunities, and gain access to more and better resources (Minniti, 2005; Shane and Cable, 2003). And without strong cultural support, the best and the brightest individuals do not want to be entrepreneurs and decide to enter some other profession (Davidsson, 2004; Guiso et al., 2006). Moreover, culture can even influence entrepreneurial potential and traits (Mueller and Thomas, 2001).
For the second sub-index, entrepreneurial activity is defined as the startup activity in the medium- or high-technology sector initiated by educated entrepreneurs in response to business opportunities in a somewhat competitive environment. The choice of indicators used to build this sub-index reflects the belief that opportunity entrepreneurs are better prepared, possess superior skills, and earn more than necessity entrepreneurs (Bhola et al., 2006; Block and Wagner, 2006). Operating in the technology sector is important, as high rates of startups in most factor-driven countries are mainly in the traditional sectors and do not represent high potential (Acs and Varga, 2005). The entrepreneur's level of education is another important feature of a venture with high growth potential (Bates, 1990). And cut-throat competition may hinder business existence and growth, so a lower number of competitors improves the chance of survival, as well as future development prospects (Baumol et al., 2007).
The third sub-index, entrepreneurial aspiration, is defined as the efforts of the early-stage entrepreneur to introduce new products and services, develop new production processes, penetrate foreign markets, substantially increase the number of firm employees, and finance the business with either formal or informal venture capital, or both. Product and process innovation, internationalization, as well as high growth, are included in the measure. The capability to produce or sell products that customers consider to be new is one of Schumpeter's forms of creating “new combinations” (Schumpeter, 1934). Applying or creating new technology and production processes are another important feature of businesses with high growth potential (Acs and Varga, 2005). The role of “gazelles” or high-growth businesses is vital, and several empirical studies (Autio, 2007; Acs et al., 2008), support Birch and Medoff's (1994) finding that only a few businesses, perhaps 2–4 percent, are responsible for the vast majority of new job creation (60–80 percent). Internationalization is believed to be a major determinant of growth (De Clercq et al., 2005). Finally the availability of risk finance, in particular equity rather than debt, is an essential precondition for realizing significant entrepreneurial aspirations that are beyond the personal financial resources of individual entrepreneurs (Bygrave et al., 2003; Gompers and Lerner, 2004).
The sub-indexes are based on their constituent pillar scores. The pillars, in turn, are based on the interaction between their constituent individual and institutional variables. The incorporation of institutional variables is a unique feature of the GEDI and reflects the qualitative aspect of entrepreneurship. A detailed description of how the different variables are combined to form the 14 pillars and the three sub-indexes is provided in Appendix A, Tables 2A3–2A5. Table 2A6 provides a list of all the countries included in the GEDI and the year-wise sample sizes. Finally, Table 2B1 provides country scores and rankings on the GEDI and the three sub-indexes.
Discussion
The GEDI index represents the first attempt to measure productive entrepreneur-ship at the national level, embedded in a specific institutional context. As such, the rankings generated by the index go beyond those of traditional indicators of startup, such as the TEA index produced by the GEM, integrating measures of national entrepreneurial activity with country-specific measures of the quality of institutions. The GEDI framework is based on the idea that entrepreneurship represents the dynamic reaction of three factors, each representing an integration of individual behavioral variables and institutions. These are entrepreneurial attitudes; entrepreneurial activity; and entrepreneurial aspirations, respectively. For each, the particular talents of individuals for entrepreneurship are weighted by the national institutional context in which the entrepreneurial activity takes place. Thus, for example, entrepreneurial activity is measured by various indicators of startup activity, derived from the GEM database. However, in the GEDI, these are weighted by indicators of the quality of institutions, notably indicators of institutional quality from internationally recognized organizations such as the Heritage Foundation and the World Economic Forum. Thus, the index builds on the insights from Baumol that the effects of entrepreneurial effort on economic growth will depend upon the national institutional context in which those efforts are placed.
Specifically, in the GEDI, institutional influences are divided into the three sub-indices: entrepreneurial attitudes, actions, and aspirations. Institutional measures for entrepreneurial attitudes include market size, level of education, the general business riskiness of a country, the population's use of the Internet, and cultural support for entrepreneurship as a good career choice. The institutional variables included in the entrepreneurial action sub-index measure the business regulatory environment, technology adsorption capacity, the extent of existing human resources improvements through staff training, and the dominance of powerful business groups in the domestic market. Finally, the entrepreneurial aspirations sub-index includes institutional variables that measure R&D potential, the sophistication of the business and of innovation, the level of globalization, and the availability of venture capital.
Entrepreneurial activity will also be closely associated with the level of economic development, measured for example by GDP/capita. Moreover, this is highly correlated itself with the quality of institutions, which makes it hard to distinguish empirically between the impact of development and of institutional quality on entrepreneurial activity. However, by integrating the measures of entrepreneurial activity with those of institutional quality, the GEDI is able to produce a more credible interpretation of the way entrepreneurship is affected by development level.
This is illustrated in Figure 2.3, which shows that institutional development is rapid, whereas individual features change more slowly. Thus, we see that, while the average values of the institutional and individual variables are about the same, 0.49 and 0.44, respectively, their rates of change are very different. This supports the general wisdom that institutions can be changed relatively easily but people take a longer time to adjust to or to exploit the opportunities presented by economic progress. The explanatory power of the connection between institutional features and per capita GDP is high (R2 =0.80); it is much lower between individual variables and per capita GDP (R2 = 0.10). This also implies greater variation in individual entrepreneurial characteristics.
At lower levels of economic development, individual entrepreneurial capabilities are stronger than country-level institutional characteristics. However, institutions improve more rapidly than individual characteristics. As countries move into the efficiency-driven stage of development, the level of institutions reaches that of individual values, as the two curves cross. As institutions
become more highly developed in richer countries, the difference between institutional and individual variables increases. The advantages of well-functioning institutions cannot be exploited if individual capabilities are lagging, which is the challenge most developed countries face. The implication is that less developed factor-driven economies should focus on improving their institutions, efficiency-driven countries should balance improving institutions with improving individual entrepreneurial development, while the most developed countries should focus on maintaining a high level of institutional quality and improving individual entrepreneurial development.
Conclusion
As Baumol classified, entrepreneurship within any country can be productive, destructive, or unproductive. If one is interested in studying entrepreneurship within or across countries, the broad nexus between entrepreneurship, institutions, and economic development is a critical area of inquiry and one which can determine the eventual impact of that entrepreneurial activity. The interdependence between incentives and institutions 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 and economic transactions in general, and they can have both direct and indirect effects on the supply and demand of entrepreneurs.
In this chapter, we have argued that the level and form of entrepreneurial activity, and therefore its impact on economic development, will be greatly affected by the national economic context, notably the quality of institutions. We have summarized the rapidly growing literature on this topic, which has begun to identify the key institutions influencing the incentives for individuals to become entrepreneurs, as well as the complex inter-relationship between different forms of institutions, and between institutions and the level of development.
We have noted that the GEDI represents the first attempt to address systematically this complex issue. It does so in a very original way, by seeking to integrate measures of entrepreneurial activity in three broad areas with a large variety of indicators of institutional quality which will moderate or enhance the impact of entrepreneurship on economic growth and development.
Increasingly, national governments are interested in increasing economic growth and overall welfare through enhanced entrepreneurial performance. As pointed out in this chapter, a country's level of economic development is strongly related to their institutional environment. The GEDI is an invaluable tool for providing an overview at the country level for the specific constellation of institutional strengths and weaknesses.
Appendix A: Data construction
| Individual variable | Description |
| OPPORTUNITY | Percentage of the 18–64 aged population recognizing good conditions to start a business next 6 months in area he/she lives |
| SKILL | Percentage of the 18–64 aged population claiming to possess the required knowledge/skills to start a business |
| NONFEAR | Percentage of the 18–64 aged population stating that the fear of failure would not prevent starting a business |
| KNOWENT | Percentage of the 18–64 aged population knowing someone who started a business in the past 2 years |
| NBGOODAV | Percentage of the 18–64 aged population saying that people consider starting a business as a good career choice |
| NBSTATAV | Percentage of the 18–64 aged population thinking that people attach high status to successful entrepreneurs |
| CARSTAT | The status and respect of entrepreneurs calculated as the average of NBGOODAV and NBSTATAV |
| TEAOPPORT | Percentage of the TEA businesses initiated because of opportunity startup motive |
| TECHSECT | Percentage of the TEA businesses that are active in technology sectors (high or medium) |
| HIGHEDUC | Percentage of the TEA businesses owner/managers with more than a secondary education |
| COMPET | Percentage of the TEA businesses started in those markets where not many businesses offer the same product |
| NEWP | Percentage of the TEA businesses offering products that are new to at least some of the customers |
| NEWT | Percentage of the TEA businesses using new technology that is less than 5 years old, average (including 1 year) |
| GAZELLE | Percentage of the TEA businesses having high job expectation (averaging over 10 employees and 50 percent growth in five years) |
| EXPORT | Percentage of the TEA businesses where at least some customers are outside the country (over 1 percent) |
| INFINVMEAN | The mean amount of three-year informal investment |
| BUSANG | Percentage of the 18–64 aged population who provided funds for new business in past three years excluding stocks and funds, average |
| INFINV | The amount of informal investment calculated as INFINVMEANBUSANG |
Note: TEA is GEM's Total Early-phase Entrepreneurial Activity (TEA) Index. A TEA business is one of the survey subjects.
| Institutional variable | Description | Source |
| MARKETDOM | Domestic market size is the sum of GDP plus value of imports of goods and services, minus value of exports of goods and services, normalized on a 1–7 (best) scale data are from the World Economic Forum Competitiveness Index 2008–09 except 2009 countries that are from 2009–10. | Porter and Schwab (2008: 470); The Global Competitiveness Report 2009–10: 450. |
| URBANIZATION | Urbanization is the percentage of the population living in urban areas; data are from the Population Division of the United Nations; 2005, 2009 countries are from 2010. | United Nations, http://www.esa.un.org/unup/index.asp?panel=1. |
| MARKET-AGGLOM | The size of the market: A combined measure of the domestic market size and urbanization, which is later used to measure the potential agglomeration effect. Calculated as MARKETDOMURBANIZATION. | Author's calculation. |
| EDUCPOSTSEC | Gross enrollment ratio in post-secondary education, 2008 or latest available data. | UNESCO, http://www.stats.uis.unesco.org/unesco/TableViewer/tableView.aspx?ReportId=167 |
| BUSINESS RISK | The business climate rate “assesses the overall business environment quality in a country … It reflects whether corporate financial information is available and reliable, whether the legal system provides fair and efficient creditor protection, and whether a country's institutional framework is favorable to intercompany transactions.” It is a part of the Country Risk Rate. The alphabetical rating is turned to a 7-point Likert scale from 1 (“D” rating) to 7 (“A1” rating). Data are from 2008 except 2009 countries, which are from 2009. |
Coface, http://www.tradingsafely.com/. |
| INTERNETUSAGE | The number of Internet users in a particular country per 100 inhabitants, 2008, except 2009 countries, which are from 2009. | International Telecommunication Union, http://www.itu.int/ITU-D/ict/statistics/. |
| CORRUPTION | The Corruption Perceptions Index (CPI) measures the perceived level of public-sector corruption in a country. “The CPI is a ‘survey of surveys,’ based on 13 different expert and business surveys.” Overall performance is measured on a 10-point Likert scale. Data are from 2008 except 2009 countries, which are from 2009. | Transparency International, http://www.transparency.org/policy_research/surveys_indices/cpi/2009. |
| FREEDOM | Business freedom is a quantitative measure of the ability to start, operate, and close a business that represents the overall burden of regulation, as well as the efficiency of government in the regulatory process. The business freedom score for each country is a number between 0 and 100, with 100 being the freest business environment. The score is based on 10 factors, all weighted equally, using data from the World Bank's Doing Business study. | Heritage Foundation, http://www.heritage.org/ Index; World Bank's Doing Business study, http://www.heritage.org/index/PDF/2009/Index2009_Methodology.pdf. |
| TECHABSORP | Firm-level technology absorption capability: “Companies in your country are (1=not able to absorb new technology; 7=aggressive in absorbing new technology).” Values for
Iran and Syria are estimates since no data exists. Data are from 2007–08 except 2009 countries that are from 2008–09. |
Porter and Schwab (2008: 461); The Global Competitiveness Report 2009–10: 441. |
| STAFFTRAIN | The extent of staff training: “To what extent do companies in your country invest in training and employee development? (1=hardly at all; 7=to a great extent).” Iran is estimated as Syria. Data are from 2007–08 except 2009 countries, which are from 2008–09. | Porter and Schwab (2008: 419); The Global Competitiveness Report 2009–10: 401. |
| MARKDOM | Extent of market dominance: “Corporate activity in your country is (1=dominated by a few business groups; 7=spread among many firms).” Iran is estimated as Syria. Data are from 2007–08 except 2009 countries, which are from 2008–09. | Porter and Schwab (2008: 423); The Global Competitiveness Report 2009–10: 405. |
| GERD | Gross domestic expenditure on research and development (GERD) as a percentage of GDP, year 2007 or latest available data. Values for Puerto Rico, Dominican Republic, and United Arab Emirates are estimated. | UNESCO, http://www.stats.uis.unesco.org/unesco/TableViewer/tableView.aspx?ReportId=1782. |
| INNOV | Innovation index points from Global Competitiveness Index: a complex measure of innovation including investment in research and development by the private sector, the presence of high-quality scientific research institutions, the collaboration in research between universities and industry, and protection of intellectual property. | Porter and Schwab (2008: 18); The Global Competitiveness Report 2009–10: 20. |
| BUSS STRATEGY | Refers to the ability of companies to pursue distinctive strategies, which involves differentiated positioning and innovative means of production and service delivery. Iran is estimated as Syria. Data are from 2007–08 except 2009 countries, which are from 2008–09. | Porter and Schwab (2008: 18); The Global Competitiveness Report 2009–10: 20. |
| GLOB | A part of the Globalization Index measuring the economic dimension of globalization. The variable involves the actual flows of trade, foreign direct investment, portfolio investment, and income payments to foreign nationals, as well as restrictions of hidden import barriers, mean tariff rate, taxes on international trade and capital account restrictions. | KOF Swiss Economic Institute; Axel Dreher (2006). http://www.globalization.kof.ethz.ch/static/pdf/variables_2009.pdf. |
| VENTCAP | A measure of the venture capital availability on a 7-point Likert scale generated from the statement: “Entrepreneurs with innovative but risky projects can generally find venture capital in your country (1 = not true; 7 = true).” Iran is estimated as Syria. Data are from 2007–08 except 2009 countries, which are from 2008–09. | Porter and Schwab (2008: 453); The Global Competitiveness Report 2009–10: 433. |
| Individual variable | Institutional variable | Calculation | Pillar |
| OPPORTUNITY is defined as the percentage of the 18–64 population identifying good opportunity in the area they live. | MARKET AGGLOM is defined as the size of the market combined with the level of urbanization on a 7-point Likert scale. | OPPORTUNITY MARKET AGGLOM | OPPORTUNITY PERCEPTION |
| SKILL is defined as the percentage of the 18–64 population claiming to possess the required knowledge/skills to start a business. | EDUC is the percentage of the population enrolled in post-secondary education. | SKILLEDUC | STARTUP SKILLS |
| NONFEAR is defined as the percentage of the 18–64 aged population stating that the fear of failure would not prevent starting a business. | CRR is the Country Risk Rate that refers to the financial, macroeconomic, and business climate. The alphabetical rating is turned to a 7-point Likert scale to fit to our data set. | NONFEAR CRR | NONFEAR OF FAILURE |
| KNOWENT is defined as the percentage of the 18–64 population who knows an entrepreneur personally who started a business in the past two years. | INTERNET USAGE is the Internet users per 100 inhabitants. | KNOWENT INTERNET USAGE | NETWORKING |
| CARSTAT is the average of the percentages of the 18–64 population who say that entrepreneurship is a good carrier choice and has high social status. | CPI is the perceived levels of corruption, as determined by expert assessments and opinion surveys on a 7-point Likert scale. | CARSTATCPI | CULTURAL SUPPORT |
| Individual variable | Institutional variable | Calculation | Pillar |
| TEAOPPORT is the percentage of the 18–64 population who are nascent entrepreneurs or who own and manage a business aged less than 3.5 years and started the business because of opportunity motivation divided by the TEA. | FREEDOM is the freedom of the economy is one sub-index of the overall economic freedom score for each country, where 100 represents the maximum freedom. | TEAOPPORT FREEDOM | OPPORTUNITY STARTUP |
| TECHSECT is the percentages of TEA that are in the medium- or high-tech sector. | TECHABSORP indicates firm-level technology absorption capability. | TECHSECTTECH ABSORP | TECHNOLOGY SECTOR |
| HIGHEDUC is the percentage of TEA entrepreneurs having participated at least in post-secondary education. | STAFFTRAIN indicates the extent of staff training. | HIGHEDUCSTAFF TRAIN | QUALITY OF HUMAN RESOURCES |
| COMPET is the percentage of TEA started in those markets where not many businesses offer the same product. | MARKDOM indicates the extent of market dominance. | COMPETMARKDOM | COMPETITION |
Note: TEA is GEM's Total Early-phase Entrepreneurial Activity (TEA) Index. A TEA business is one of the survey subjects.
| Individual variable | Institutional variable | Calculation | Pillar |
| NEWP is the percentage of TEA businesses where entrepreneurs offer a product that is new to at least some customers. | GERD is the R&D percentage of GDP | NEWPRODGERD | NEW PRODUCT |
| NEWT is defined as the percentage of TEA business where the technology is less than five years old. | INNOVCAT is a measure of whether a business environment allows cutting edge innovations. | NEWTINNOVCAT | NEW TECH |
| GAZELLE is defined as the percentage of high-growth TEA businesses (employing 10 plus persons and over 50 percent growth in five years). | BUSS refers to the ability of companies to pursue distinctive strategies, which involves differentiated positioning and innovative means of production and service delivery. | GAZELLEBUSS | HIGH GROWTH |
| EXPORT is the percentage of TEA businesses exporting at least 1 percent of product. | GLOB is a part of the Index of Globalization measuring the economic dimension of globalization. | EXPORTGLOB | INTERNATIONALIZATION |
| INFINV is defined as the percentage of informal investors in the 18–64 aged population multiplied by the average amount of informal investment. | VENTCAP is a measure of the venture capital availability on a 7-point Likert scale. | INFINVVENTCAP | RISK CAPITAL |
Note: TEA is GEM's Total Early-phase Entrepreneurial Activity (TEA) Index. A TEA business is one of the survey subjects.
Table 2A6 Countries included in the GEDI: size of the sample by year
Appendix B: Country rankings
Table 2B1 The global entrepreneurship sub-index country scores and ranks
Notes
1. The conceptualization of destructive entrepreneurship as activity with a negative overall effect on GDP was suggested by Baumol, in personal correspondence.
2. Their general equilibrium model suggests that as more resources are focused on rent-seeking activities, the returns to productive activities can fall more rapidly than the resulting returns to rent-seeking. This can, then, trigger additional rent-seeking activities.
3. While total factor productivity increased by 87 percent in the USA, the Harvard economist, Martin Weitzman, who studies the Soviet Union, found that between 1950 and 1969 only 15–20 percent of growth in that country could be attributed to technical change and organizational innovation. In other words, the Soviet Union was good at equipping its workers with capital goods (factories) but, once that process ran its course, it was not very good at creating new knowledge, improving its institutions, or fostering entrepreneurship. Communism collapsed under its own weight and the Berlin Wall tumbled down.
4. There are other, more simplistic, explanations for why self-employment may decline as economies develop. Improvements in the economy's infrastructure such as transportation, telecommunications, and credit markets probably increase the advantages of larger firms over smaller firms. Improvements in transportation and telecommunications make it cheaper to distribute goods and services over larger areas. Assuming there are scale economies up to a point, better distribution systems enable firms to operate larger production units that can serve larger markets.
5. The United Arab Emirates' scores were outliers and removed from this figure.
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