Do national differences in cognitive skills (CS) predict a nation’s likelihood of generating high-quality entrepreneurs who create and expand high-value businesses? We answer this question by estimating cross-country regressions that use the Acs and Szerb Global Entrepreneurship Development Index (GEDI) and a measure of national CS. After including conventional controls we find for a sample of 60 countries that our measure of CS robustly predicts the GEDI (unconditional correlation = 0.65, standardized beta = 0.42), an index that gives weight to both entrepreneurial attitudes within a nation and the institutional and economic prerequisites for creating high-value, high-growth firms. We find that this result also holds for an alternative measure of entrepreneurship.
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We use the term “cognitive skills” because it is a widely used in the academic literature. It is frequently treated as a set of outcomes predicted in part by IQ scores. For instance, see Burks et al. (2009) and Heckman (2008). In this instance, cognitive skills encompass a wide array of mental skills, positively correlated with each other, which psychologists refer to as intelligence. For a useful survey of the relevant intelligence literature, see Deary (2001).
The ongoing debate concerning the causal direction between cognitive ability and educational attainment, whether in terms of year so schooling or in scores on standardized tests, is not resolved in this paper. For example, Hansen et al. (2004) found that increased schooling has a “small equalizing effect” on standardized test scores, but mostly for students with low initial levels of cognitive ability and schooling. Lynn and Meisenberg (2010) and Lynn and Vanhanen (2012) argued that while cognitive skill and test scores are highly correlated, individuals with greater cognitive skills are more likely to attain more education (years in school) since they are relatively more adept at it. A useful overview of the large set of empirical findings is found in Heckman (2008).
Trying to answer the question of why some countries have a higher level of cognitive skill than others would take us far afield from our current purpose and outside of our area of expertise. We rely on the fact that, as amply demonstrated in Lynn and Vanhanen’s (2012) extensive survey, cognitive skill appears to be a dominant, pervasive factor that helps explain why individuals and groups, other factors held constant, strive economically, enjoy better health and establish and maintain better functioning political structures. This is not to deny the fact that environmental influences on intelligence are well documented in the literature, especially the well-known Flynn Effect, which is the long-term rise in IQ scores documented around the world (inter alia, Deary 2001, Jones 2011b).
Lynn and Vanhanen (2012) provided yet another data set that updates the Lynn and Meisenberg data. This data, which became available after completion of this paper, does not extend our sample of countries and, when comparing our data with the more recent vintage, there are only minor differences in the values. Consequently, we continue to use the Lynn–Meisenberg data.
The index consists of several sub-indexes, which we describe below.
Lynn and Meisenberg (2010) also used several additional assessment tools in their analysis. To conserve space, we refer the reader to their paper, especially p. 356.
For a related analysis, see Rindermann (2007).
Other control variables tested were the Gender-related Development Index, a measure of government spending relative to GDP, life expectancy, the percent of labor in agriculture and the percent of the adult population with a bachelor’s degree. In each instance the estimated coefficient never achieved statistical significance at a reasonable level (better than 10 %). More importantly, including these alternative measures did not affect the significance of the estimated coefficient on cognitive skill.
Theoretical arguments linking entrepreneurship and institutions are found in Boettke and Coyne (2009) with Bjornskov and Foss (2008) providing supporting empirical evidence. Nystrom (2008) found that size of government and legal structure and regulation are negatively and significantly related to the rate of self-employment in a given country. Both studies indicated that a smaller government, a better legal structure within which property rights are secured, and an economy characterized by less regulation of credit, labor and business sectors are factors that increase the likelihood of entrepreneurship.
This result is not affected by including a measure of education. When the Barro-Lee measure of “years of schooling” is included in the regression, the estimated coefficient on the cognitive skills variable is positive and statistically significant at better than a 1 % level of significance. This finding is similar to previous work where cognitive skills tend to dominate education, especially if the latter is measure as a “years in school” type of measure. This suggests that the cognitive skills variable is capturing something different than education alone. Indeed, the gist of Lynn and Meisenberg (2010) is that their measure is more related to educational attainment, in terms of cognitive skills, than cruder measures such as degree attained or average years in school.
For example, the estimated coefficient on CS in the regression comparable to column 1 in Table 3 is 0.007 (t = 3.30). The coefficient/t-statistic comparable to column 2 is 0.007 (t = 3.23); to column 3 it is 0.004 (t = 3.32).
This discussion draws on Acs and Szerb (2010), p. 7.
See Reynolds et al. (2005) for a more complete description of the GEM collection and measurement methods.
We would argue that this criticism also applies to other survey-based measures, such as the Flash Eurobarometer survey conducted by the Gallup organization. (Gallup 2009). The Gallup series also is available for only a limited number of countries (27).
We use the “entry density” figure to adjust for scale.
Acs et al. (2014) argue that “attitude surveys provide an insight into the opinion climate that prevails in a given country, [but] tend to suffer from the obvious disassociation from actual activity… and tell us little about how opinions and attitudes translate into action within a given country…”(480).
The sample of countries is slightly smaller than that for which the GEDI is available. Countries for which the World Bank measure is not available includes Bosnia, China, Egypt, Iran, Portugal, Saudi Arabia, Serbia, the United States and Venezuela.
The results are not different qualitatively if the Heritage measure of economic freedom is used.
Admittedly ad hoc, we began with a regression of New Incorporations on real GDP per capita and regionals. We then added each of the control variables individually. If the control variable was not significant at the 10 % level or better, it was excluded and the next variable was added. This process produced a “baseline” regression that included the Gini and real GDP per capita variables (plus regionals). What appears in column two of Table 6 is the outcome of adding CS to that baseline regression.
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We would like to thank Zoltan Acs, Ari Belasen, Randall Holcombe, Gerhard Meisenberg, the editor and two anonymous referees for their comments and suggestions that significantly improved an earlier version of this paper. We of course retain all responsibility for any errors.
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Hafer, R.W., Jones, G. Are entrepreneurship and cognitive skills related? Some international evidence. Small Bus Econ 44, 283–298 (2015). https://doi.org/10.1007/s11187-014-9596-y
- Cognitive skills
- Economic freedom