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Are entrepreneurship and cognitive skills related? Some international evidence

Abstract

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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Fig. 1
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Notes

  1. 1.

    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).

  2. 2.

    The evidence, though mixed, suggests that entrepreneurship (in various forms) plays an important and positive role in economic growth models. Useful reviews of this can be found in Acs and Audretsch (2003), Caree and Thurik (2003), Acs and Armington (2006) and Audretsch et al. (2006).

  3. 3.

    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).

  4. 4.

    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).

  5. 5.

    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.

  6. 6.

    See Rindermann (2008b, 2012) and Rindermann and Thompson (2011) for more on this area of research.

  7. 7.

    See Acs and Szerb (2010), footnote 17, for references. Acs et al. (2014) provide a further discussion of the GEDI measure within the context of alternative measures of entrepreneurship at the country level.

  8. 8.

    The index consists of several sub-indexes, which we describe below.

  9. 9.

    The TIMSS assessments occurred in 4-year cycles, including 1995, 1999, 2003 and 2007. These data are available at http://timss.bc.edu/timss2003html. The PISA assessments were carried out in 3-year cycles, including 2000, 2003 and 2006. These data are available at http://pisacountry.acer.edu.au.

  10. 10.

    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.

  11. 11.

    For a related analysis, see Rindermann (2007).

  12. 12.

    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.

  13. 13.

    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.

  14. 14.

    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.

  15. 15.

    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).

  16. 16.

    Heckelman and Stroup (2000) suggested that potential problems of specification bias from using the broad index may be mollified by using the subcomponent measures along with the overall measure of freedom. This is the approach is used in Garrett and Rhine (2011) and Belasen and Hafer (2012).

  17. 17.

    This discussion draws on Acs and Szerb (2010), p. 7.

  18. 18.

    See Reynolds et al. (2005) for a more complete description of the GEM collection and measurement methods.

  19. 19.

    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).

  20. 20.

    We use the “entry density” figure to adjust for scale.

  21. 21.

    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).

  22. 22.

    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.

  23. 23.

    The results are not different qualitatively if the Heritage measure of economic freedom is used.

  24. 24.

    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.

References

  1. Acs, Z. J. (2006). How is entrepreneurship good for economic growth? Innovations, 1, 97–107.

    Article  Google Scholar 

  2. Acs, Z. J., & Armington, C. (2006). Entrepreneurship, geography, and American economic growth. New York: Cambridge University Press.

    Book  Google Scholar 

  3. Acs, Z. J., & Audretsch, D. (Eds.). (2003). International handbook of entrepreneurial research. The Netherlands: Kluwer.

    Google Scholar 

  4. Acs, Z. J., Autio, E., & Szerb, L. (2014). National systems of entrepreneurship: Measurement issues and policy implications. Research Policy, 43, 476–494.

    Article  Google Scholar 

  5. Acs, Z., Desai, S., & Klapper, L. (2008). What does entrepreneurship data really show? A comparison of the global entrepreneurship monitor and World Bank Group data sets. Small Business Economics, 31, 219–239.

    Article  Google Scholar 

  6. Acs, A. J., & Szerb, L. (2010). The Global Entrepreneurship and Development Index (GEDI). In Paper presented at “Opening up Innovation: Strategy, Organization and Technology”. London: Imperial College.

  7. Ahmetoglu, G., Leutner, F., & Chamorro-Premuzic, T. (2011). EQ-nomics: Understanding the relationship between individual differences in trait emotional intelligence and entrepreneurship. Personality and Individual Differences, 51, 1028–1033.

    Article  Google Scholar 

  8. Andrews, D., & Leigh, A. (2009). More inequality, less social mobility. Applied Economics Letters, 16, 1489–1492.

    Article  Google Scholar 

  9. Audretsch, D. B., Keilbach, D. B., & Lehmann, E. E. (2006). Entrepreneurship and economic growth. Oxford: Oxford University Press.

    Book  Google Scholar 

  10. Barro, R., & Lee, J. (2011). Barro-Lee Educational Attainment Dataset. Accessed at BarroLee.com.

  11. Belasen, A., & Hafer, R. W. (2012). Well-being and economic freedom: Evidence from the states. Intelligence, 40, 306–316.

    Article  Google Scholar 

  12. Bjornskov, C., & Foss, N. J. (2008). Economic freedom and entrepreneurial activity: Some cross-country evidence. Public Choice, 134, 307–328.

    Article  Google Scholar 

  13. Boettke, P., & Coyne, C. J. (2009). Context matters: Institutions and entrepreneurship. Hanover, MA: Now Publishers.

    Google Scholar 

  14. Bowles, S., Gintis, H., & Osborne, M. (2001). The determinants of earnings: Skills, preferences, and schooling. Journal of Economic Literature, 39, 1137–1176.

    Article  Google Scholar 

  15. Burks, S., Carpenter, J., Goette, L., & Rustichini, A. (2009). Cognitive skills affect economic preferences, strategic behavior, and job attachment. Proceedings of the National Academy of Sciences, 106, 7745–7750.

    Article  Google Scholar 

  16. Caree, M. A., & Thurik, A. R. (2003). The impact of entrepreneurship on economic growth. In Acs, Z. J & Audretsch, D. (Eds.), International handbook of entrepreneurial research.

  17. Deary, I. (2001). Intelligence: A very short introduction. New York: Oxford University Press.

    Book  Google Scholar 

  18. Gallup. (2009). Entrepreneurship in the EU and beyond. In: Flash Eurobarometer Series, European Commission, Brussels.

  19. Garrett, T. A., & Rhine, R. M. (2011). Economic freedom and employment growth in the U.S. states. Federal Reserve Bank of St. Louis. Review, 93, 1–18.

    Google Scholar 

  20. Gennaioli, N., La Porta, R., Lopez-de-Silanes, F., & Shleifer, A. (2013). Human capital and regional development. Quarterly Journal of Economics, 128, 105–164.

    Article  Google Scholar 

  21. Gwartney, J., Lawson, R., & Hall, J. (2011). Economic freedom of the World 2011 annual report. Vancouver: The Fraser Institute.

    Google Scholar 

  22. Hansen, K. J., Heckman, J., & Muller, K. (2004). The effect of schooling and ability on achievement test scores. Journal of Econometrics, 121, 39–49.

    Article  Google Scholar 

  23. Hartog, J., Van Praag, M., & Van Der Sluis, J. (2010). If you are so smart, why aren’t you an entrepreneur? Returns to cognitive and social ability: Entrepreneurs versus employees. Journal of Economics & Management Strategy, 19, 947–989.

  24. Heckelman, J. C. (2005). Proxies for economic freedom: A critique of the Hanson critique. Southern Economic Journal, 72, 492–501.

    Article  Google Scholar 

  25. Heckelman, J. C., & Stroup, M. D. (2000). Which economic freedoms contribute to growth? Kyklos, 53, 527–544.

    Article  Google Scholar 

  26. Heckman, J. J. (2008). Schools, skills, and synapses. Economic Inquiry, 46, 289–324.

    Article  Google Scholar 

  27. Henrekson, M. (2005). Entrepreneurship: a weak link in the welfare state? Industrial and Corporate Change, 14, 437–467.

    Article  Google Scholar 

  28. Hoffman, A. (2007). A rough guide to entrepreneurship policy. In R. A. Thurik, D. B. Audretsch, & I. Grilo (Eds.), Handbook of research on entrepreneurship policy (pp. 140–161). Cheltenham: Edward Elgar.

  29. Holcombe, R. G. (1998). Entrepreneurship and economic growth. The Quarterly Journal of Austrian Economics, 1, 45–62.

    Article  Google Scholar 

  30. Hunt, E., & Wittmann, W. (2008). National intelligence and national prosperity. Intelligence, 36, 1–9.

  31. Jones, G. (2011a). National IQ and national productivity: The hive mind across Asia. Asian Development Review, 28, 58–71.

    Google Scholar 

  32. Jones, G. (2011b). IQ and national productivity. New Palgrave dictionary of economics. New York: Palgrave Macmillan.

  33. Jones, G., & Schneider, W. J. (2006). Intelligence, human capital, and economic growth: A Bayesian averaging of classical estimates (BACE) approach. Journal of Economic Growth, 11, 71–93.

    Article  Google Scholar 

  34. Jones, G., & Schneider, W. J. (2010). IQ in the production function: Evidence from immigrant earnings. Economic Inquiry, 48, 743–755.

    Article  Google Scholar 

  35. Kirzner, I. (1973). Competition and entrepreneurship. Chicago: University of Chicago Press.

    Google Scholar 

  36. Kirzner, I. (1997). Entrepreneurial discovery and the competitive market process: An Austrian approach. Journal of Economic Literature, 35, 60–85.

    Google Scholar 

  37. Knight, F. (1921). Risk, uncertainty, and profit. Boston: Hart, Schaffner & Marx; Houghton Mifflin Co.

    Google Scholar 

  38. Lazear, E. P. (2004). Balanced skills and entrepreneurship. American Economic Review, 94, 208–211.

    Article  Google Scholar 

  39. Lazear, E. P. (2005). Entrepreneurship. Journal of Labor Economics, 23, 649–680.

    Article  Google Scholar 

  40. Lewis, W. W. (2004). The power of productivity. Chicago: University of Chicago Press.

    Book  Google Scholar 

  41. Lucas, R. E. (1978). On the size distribution of business firms. Bell Journal of Economics, 9, 508–523.

    Article  Google Scholar 

  42. Lucas, R. E. (1988). On the mechanics of economic development. Journal of Monetary Economics, 22, 3–42.

    Article  Google Scholar 

  43. Lynn, R., & Meisenberg, G. (2010). National IQs calculated and validated for 108 nations. Intelligence, 38, 353–360.

    Article  Google Scholar 

  44. Lynn, R., & Vanhanen, T. (2002). IQ and the wealth of nations. Westport: Praeger.

    Google Scholar 

  45. Lynn, R., & Vanhanen, T. (2006). IQ and global inequality. Athens: Washington Summit.

    Google Scholar 

  46. Lynn, R., & Vanhanen, T. (2012). Intelligence: A unifying construct for the social sciences. London: Ulster Institute for Social Sciences.

    Google Scholar 

  47. Meisenberg, G. (2012). National IQ and economic outcomes. Personality and Individual Differences, 53, 103–107.

    Article  Google Scholar 

  48. Miller, T., Holmes, K. R., & Feulner, E. J. (2012). 2012 Index of Economic Freedom. Washington, D.C.: The Heritage Foundation and Dow Jones & Company.

    Google Scholar 

  49. Nystrom, K. (2008). The institutions of economic freedom and entrepreneurship: Evidence from panel data. Public Choice, 136, 262–282.

    Article  Google Scholar 

  50. Oesterdiekoff, G. W., & Rindermann, H. (2007). The spread of AIDS in developing countries: A psycho-cultural approach. Journal of Social, Political and Economic Studies, 32, 201–222.

    Google Scholar 

  51. Parker, S. C., & van Praag, C. M. (2006). Schooling, capital constraints, and entrepreneurial performance: The endogenous triangle. Journal of Business & Economic Statistics, 24, 416–431.

    Article  Google Scholar 

  52. Potrafke, N. (2012). Intelligence and corruption. Economics Letters, 114, 109–112.

    Article  Google Scholar 

  53. Powell, B., & Rodet, C. (2012). Praises and profits: Cultural and institutional determinants of entrepreneurship. Journal of Private Enterprise, 27, 19–42.

    Google Scholar 

  54. Ram, R. (2007). IQ and economic growth: Further augmentation of the Mankiw-Romer-Weil model. Economics Letters, 94, 7–11.

    Article  Google Scholar 

  55. Reynolds, P. D., Bosma, N., & Autio, E. (2005). Global entrepreneurship monitor: data, collection design and implementation 1998–2003. Small Business Economics, 24, 205–231.

    Article  Google Scholar 

  56. Rindermann, H. (2007). The g-factor of international cognitive ability comparisons: The homogeneity of results with PISA, TIMSS, PIRLS and IQ-tests across nations. European Journal of Personality, 21, 667–706.

    Article  Google Scholar 

  57. Rindermann, H. (2008a). Relevance of education and intelligence at the national level for the economic welfare of people. Intelligence, 36, 127–142.

    Article  Google Scholar 

  58. Rindermann, H. (2008b). Relevance of education and intelligence for the political development of nations: Democracy, rule of law and political liberty. Intelligence, 36, 306–322.

    Article  Google Scholar 

  59. Rindermann, H. (2012). Intellectual classes, technological progress and economic development: The rise of cognitive capitalism. Personality and Individual Differences, 53, 108–113.

    Article  Google Scholar 

  60. Rindermann, H., & Meisenberg, G. (2009). Relevance of education and intelligence at the national level for health: The case of HIV and AIDS. Intelligence, 37, 383–395.

    Article  Google Scholar 

  61. Rindermann, H., Sailer, M., & Thompson, J. (2009). The impact of smart fractions, cognitive ability of politicians and average competence of peoples on social development. Talent Development & Excellence, 1, 3–25.

    Google Scholar 

  62. Rindermann, H., & Thompson, J. (2011). Cognitive capitalism: The effect of cognitive ability on wealth, as mediated through scientific achievement and economic freedom. Psychological Science, 22, 754–763.

    Article  Google Scholar 

  63. Sala-i-Martin, X. (1997). I just ran two million regressions. American Economic Review, 87, 178–183.

    Google Scholar 

  64. Smith, A. (1776)[1937] An inquiry into the nature and causes of the wealth of nations. New York: The Modern Library.

  65. Strenze, T. (2007). Intelligence and socioeconomic success: A meta-analytic review of longitudinal research. Intelligence, 35, 401–426.

    Article  Google Scholar 

  66. van Praag, C. M., & Cramer, J. S. (2011). The roots of entrepreneurship and labour demand: Individual ability and low risk aversion. Economica, 68, 45–62.

    Article  Google Scholar 

  67. Van Praag, M., van Witteloostuijn, A., & van der Sluis, J. (2013). The higher returns to formal education for entrepreneurs versus employees. Small Business Economics, 40, 375–396.

  68. van Stel, A., Caree, A. M., & Thurik, A. R. (2005). The effect of entrepreneurial activity on national economic growth. Working Paper, Max Planck Institute of Economics.

  69. Vinogradov, E., & Kolvereid, L. (2010). Home country national intelligence and self-employment rates among immigrants in Norway. Intelligence, 38, 151–159.

    Article  Google Scholar 

  70. Weede, E., & Kämpf, S. (2002). The impact of intelligence and institutional improvements on economic growth. Kyklos, 55, 361–380.

    Article  Google Scholar 

  71. Wicherts, J. M., Dolan, C. V., Carlson, J. S., & van der Maas, H. L. J. (2009). Raven’s test performance of sub-Saharan Africans: Average performance, psychometric properties, and the Flynn effect. Learning and Individual Differences, 20, 135–151.

    Article  Google Scholar 

  72. Wicherts, J. M., Dolan, C. V., Carlson, J. S., & van der Maas, H. L. J. (2010). A systematic literature review of the average IQ of sub-Saharan Africans. Intelligence, 38, 1–20.

    Article  Google Scholar 

  73. World Bank. (2014). New business registration database. Washington, D.C.: World Bank.

    Google Scholar 

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Acknowledgments

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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Correspondence to R. W. Hafer.

Appendix

Appendix

See Tables 7 and 8.

Table 7 Countries used in analysis, with individual GEDI and CS
Table 8 Data sources

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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

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Keywords

  • Entrepreneurship
  • Cognitive skills
  • Economic freedom

JEL Classifications

  • A1
  • F2
  • K00
  • M2
  • L26