Advertisement

The global technology frontier: productivity growth and the relevance of Kirznerian and Schumpeterian entrepreneurship

  • Esteban LafuenteEmail author
  • Zoltan J. Acs
  • Mark Sanders
  • László Szerb
Article

Abstract

We evaluate how country-level entrepreneurship—measured via the national system of entrepreneurship—triggers total factor productivity (TFP) by increasing the effects of Kirznerian and Schumpeterian entrepreneurship. Using a database for 45 developed and developing countries during 2002–2013, we employ non-parametric techniques to build a world technology frontier and compute TFP estimates. The results of the common factor models reveal that the national system of entrepreneurship is a relevant conduit of TFP, and that this effect is heterogeneous across countries. Policies supporting Kirznerian entrepreneurship—e.g., increased business formation rates—may promote the creation of low value-adding businesses which is not associated with higher TFP rates. Policy interventions targeting Schumpeterian entrepreneurship objectives—e.g., innovative entrepreneurship and the development of new technologies—are conducive to technical change by promoting upward shifts in the countries’ production function and, consequently, productivity growth.

Keywords

National system of entrepreneurship Total factor productivity Technical change Parameter heterogeneity Common factor model International 

JEL codes

C23 E23 L26 M13 O1 

Notes

Acknowledgements

Esteban Lafuente acknowledges financial support by the Spanish Ministry of Economy, Industry and Competitiveness (grant no. ECO2017-86305-C4-2-R). Mark Sanders received financial support from the European Union through the Horizon2020 project “Financial and Institutional Reforms to build an Entrepreneurial Society” (FIRES) (grant no. 649378). László Szerb acknowledges financial support by the Higher Education Institutional Excellence Program of the Hungarian Ministry of Human Capacities, within the framework of the 4th thematic program ‘Enhancing the Role of Domestic Companies in the Reindustrialization of Hungary’ of the University of Pécs (reference number of the contract: 20765-3/2018/FEKUTSTRAT); and by the Hungarian National Foundation for Scientific Research (project: OTKA-K-120289 titled ‘Entrepreneurship and competitiveness investigations in Hungary based on the Global Entrepreneurship Monitor surveys 2017-2019’).

References

  1. Acemoglu, D. (2002). Directed technical change. Review of Economic Studies, 69(4), 781–809.Google Scholar
  2. Acemoglu, D., Aghion, P., Bursztyn, L., & Hemous, D. (2012). The environment and directed technical change. American Economic Review, 102(1), 131–166.Google Scholar
  3. Acemoglu, D., Johnson, S., & Robinson, J. A. (2005). Institutions as the fundamental cause of long-run growth. In P. Aghion & S. Durlauf, Handbook of Economic Growth (pp. 385–472). Amsterdam: North-Holland.Google Scholar
  4. Acemoglu, D., & Zilibotti, F. (2001). Productivity differences. Quarterly Journal of Economics, 116(2), 563–606.Google Scholar
  5. Acs, Z. J., & Audretsch, D. B. (1988). Innovation in large and small firms—an empirical analysis. American Economic Review, 78, 678–690.Google Scholar
  6. Acs, Z. J., Audretsch, D. B., Braunerhjelm, P., & Carlsson, B. (2012). Growth and entrepreneurship. Small Business Economics, 39(2), 289–300.Google Scholar
  7. Acs, Z. J., Audretsch, D. B., Lehmann, E. E., & Licht, G. (2016). National systems of entrepreneurship. Small Business Economics, 46(4), 527–535.Google Scholar
  8. Acs, Z. J., Autio, E., & Szerb, L. (2014). National systems of entrepreneurship: measurement issues and policy implications. Research Policy, 43(3), 476–494.Google Scholar
  9. Aghion, P., & Howitt, P. (1992). A model of growth through creative destruction. Econometrica, 60(2), 323–351.Google Scholar
  10. Arellano, M., & Bond, S. R. (1991). Some tests of specification for panel data. Review of Economic Studies, 58(2), 277–297.Google Scholar
  11. Atkinson, R. D., & Lind, M. (2018). Big is beautiful: debunking the myth of small business. Cambridge, MA: The MIT Press.Google Scholar
  12. Bai, J. (2009). Panel data models with interactive fixed effects. Econometrica, 77, 1229–1279.Google Scholar
  13. Barro, R. (1991). Economic growth in a cross section of countries. Quarterly Journal of Economics, 106(2), 407–443.Google Scholar
  14. Barro, R., & Sala-i-Martin, X. (1997). Technological diffusion, convergence, and growth. Journal of Economic Growth, 2, 1–26.Google Scholar
  15. Baumol, W. J. (1990). Entrepreneurship: productive, unproductive and destructive. Journal of Political Economy, 98(5), 893–921.Google Scholar
  16. Baumol, W. J., & Strom, R. J. (2007). Entrepreneurship and economic growth. Strategic Entrepreneurship Journal, 1, 233–237.Google Scholar
  17. Binswanger, H. P. (1974). The measurement of technical change bias with many factors of production. American Economic Review, 64, 964–976.Google Scholar
  18. Bjørnskov, C., & Foss, N. J. (2013). How strategic entrepreneurship and the institutional context drive economic growth. Strategic Entrepreneurship Journal, 7, 50–69.Google Scholar
  19. Bjørnskov, C., & Foss, N. J. (2016). Institutions, entrepreneurship, and economic growth: what do we know and what do we still need to know? Academy of Management Perspectives, 30(3), 292–315.Google Scholar
  20. Blundell, R., & Bond, S. R. (1998). Initial conditions and moment restrictions in dynamic panel data models. Journal of Econometrics, 87(1), 115–143.Google Scholar
  21. Bogetoft, P., & Otto, L. (2011). Benchmarking with DEA, SFA, and R. New York: Springer.Google Scholar
  22. Boussemart, J.-P., Briec, W., Kerstens, K., & Poutineau, J.-C. (2003). Luenberger and Malmquist productivity indices: theoretical comparisons and empirical illustration. Bulletin of Economic Research, 55(4), 391–405.Google Scholar
  23. Caselli, F., & Coleman, W. J., II. (2006). The world technology frontier. American Economic Review, 96(3), 499–522.Google Scholar
  24. Caves, D. W., Christensen, L. R., & Diewert, W. E. (1982). The economic theory of index numbers and the measurement of input, output, and productivity. Econometrica, 50, 1393–1414.Google Scholar
  25. Chudik, A., Pesaran, M. H., & Tosetti, E. (2011). Weak and strong cross-section dependence and estimation of large panels. The Econometrics Journal, 14(1), C45–C90.Google Scholar
  26. Cooper, W. W., Seiford, L. M., & Zhu, J. (2011). Handbook on data envelopment analysis (2nd ed.). New York: Springer.Google Scholar
  27. Dumitrescu, E.-I., & Hurlin, C. (2012). Testing for Granger non-causality in heterogeneous panels. Economic Modelling, 29, 1450–1460.Google Scholar
  28. Durlauf, S., Johnson, P.A., & Temple, J.R.W. (2005). Growth econometrics. In P. Aghion & S. Durlauf, Handbook of economic growth (pp. 555–677). Amsterdam: North Holland.Google Scholar
  29. Eberhardt, M., & Bond, S. (2009). Cross-section dependence in nonstationary panel models: a novel estimator. In MPRA Paper 17692. Germany: University Library of Munich.Google Scholar
  30. Eberhardt, M., Helmers, C., & Strauss, H. (2013). Do spillovers matter when estimating private returns to R&D? Review of Economics and Statistics, 95(2), 436–448.Google Scholar
  31. Eberhardt, M., & Teal, F. (2013). No mangoes in the tundra: spatial heterogeneity in agricultural productivity analysis. Oxford Bulletin of Economics and Statistics, 75(6), 914–939.Google Scholar
  32. Färe, R., Grosskopf, S., Lindgren, B., & Roos, P. (1989). Productivity developments in Swedish hospitals: a Malmquist output index approach. In A. Charnes, W.W. Cooper, A.Y. Lewin, & L.M. Seiford, Data envelopment analysis: theory, methodology and applications. Boston: Kluwer Academic Publishers.Google Scholar
  33. Färe, R., Grosskopf, S., Norris, M., & Zhang, Z. (1994). Productivity growth, technical progress, and efficiency change in industrialized countries. American Economic Review, 84(1), 66–83.Google Scholar
  34. Friedberg, L. (1998). Did unilateral divorce raise divorce rates? Evidence from panel data. American Economic Review, 88(3), 608–627.Google Scholar
  35. Grifell-Tatjé, E., & Lovell, C. A. K. (2015). Productivity accounting: the economics of business performance. New York: Cambridge University Press.Google Scholar
  36. Griffith, R., Redding, S., & Van Reenen, J. (2004). Mapping the two faces of R&D: productivity growth in a panel of OECD industries. Review of Economics and Statistics, 86(4), 883–895.Google Scholar
  37. Grossman, G. M., & Helpman, E. (1991). Quality ladders in the theory of growth. Review of Economic Studies, 58(1), 43–61.Google Scholar
  38. Kao, C. (1999). Spurious regression and residual-based tests for cointegration in panel data. Journal of Econometrics, 65, 9–15.Google Scholar
  39. Kapetanios, G., Pesaran, M. H., & Yamagata, T. (2011). Panels with non-stationary multifactor error structures. Journal of Econometrics, 160(2), 326–348.Google Scholar
  40. King, R. G., & Levine, R. (1993). Finance and growth: Schumpeter might be right. Quarterly Journal of Economics, 108(3), 717–737.Google Scholar
  41. Kirchhoff, B. A. (1994). Entrepreneurship and dynamic capitalism. Westport CT: Praeger.Google Scholar
  42. Kirzner, I. M. (1973). Competition and entrepreneurship. Chicago: University of Chicago Press.Google Scholar
  43. Kirzner, I. M. (1997). Entrepreneurial discovery and the competitive market process: an Austrian approach. Journal of Economic Literature, 35(1), 60–85.Google Scholar
  44. Koellinger, P. D., & Thurik, A. R. (2012). Entrepreneurship and the business cycle. Review of Economics and Statistics, 94(4), 1143–1156.Google Scholar
  45. Kumar, S., & Russell, R. R. (2002). Technological change, technological catch-up, and capital deepening: relative contributions to growth and convergence. American Economic Review, 92(3), 527–548.Google Scholar
  46. Lafuente, E., Acs, Z. J., & Szerb, L. (2018). The entrepreneurship paradox: more entrepreneurs are not always good for the economy—the role of the entrepreneurial ecosystem on economic performance in Africa. In SSRN working paper available at https://ssrn.com/abstract=3307617.Google Scholar
  47. Lafuente, E., Szerb, L., & Acs, Z. J. (2016). Country level efficiency and national systems of entrepreneurship: a data envelopment analysis approach. Journal of Technology Transfer, 41(6), 1260–1283.Google Scholar
  48. Litan, R., Baumol, W., & Schramm, C. J. (2009). Good capitalism, bad capitalism, and the economics of growth and prosperity. New Haven: Yale University Press.Google Scholar
  49. Lucas, R. E. (1988). On the mechanics of economic development. Journal of Monetary Economics, 22(1), 3–42.Google Scholar
  50. Maddala, G. S., & Wu, S. (1999). A comparative study of unit root tests with panel data and a new simple test. Oxford Bulletin of Economics and Statistics, 61, 631–652.Google Scholar
  51. Malmquist, S. (1953). Index numbers and indifference surfaces. Trabajos de Estadistica, 4, 209–242.Google Scholar
  52. Mankiw, N. G., Romer, D., & Weil, D. N. (1992). A contribution to the empirics of economic growth. Quarterly Journal of Economics, 107, 407–437.Google Scholar
  53. Melitz, M. J., & Ottaviano, G. I. (2008). Market size, trade, and productivity. Review of Economic Studies, 75(1), 295–316.Google Scholar
  54. Moll, B. (2014). Productivity losses from financial frictions: can self-financing undo capital misallocation? American Economic Review, 104(10), 3186–3221.Google Scholar
  55. Parente, S. L., & Prescott, E. C. (1994). Barriers to technology adoption and development. Journal of Political Economy, 102, 298–321.Google Scholar
  56. Parker, S. C. (2009). The economics of entrepreneurship. New York: Cambridge University Press.Google Scholar
  57. Pedroni, P. (1999). Critical values for cointegration tests in heterogeneous panels with multiple regressors. Oxford Bulletin of Economics and Statistics, 61, 653–670.Google Scholar
  58. Pedroni, P. (2004). Panel cointegration: asymptotic and finite sample properties of pooled time series tests with an application to the PPP hypothesis. Econometric Theory, 20, 597–625.Google Scholar
  59. Pesaran, M.H. (2004). General diagnostic tests for cross section dependence in panels. IZA Discussion Paper No. 1240.Google Scholar
  60. Pesaran, M. H. (2006). Estimation and inference in large heterogeneous panels with a multifactor error structure. Econometrica, 74(4), 967–1012.Google Scholar
  61. Pesaran, M. H. (2007). A simple panel unit root test in the presence of cross-section dependence. Journal of Applied Econometrics, 22, 265–312.Google Scholar
  62. Pesaran, M. H., & Smith, R. (1995). Estimating long-run relationships from dynamic heterogeneous panels. Journal of Econometrics, 68(1), 79–113.Google Scholar
  63. Pesaran, M. H., & Tosetti, E. (2011). Large panels with common factors and spatial correlations. Journal of Econometrics, 161, 182–202.Google Scholar
  64. Prescott, E. C. (1998). Needed: a theory of total factor productivity. International Economic Review, 49, 525–553.Google Scholar
  65. Prieger, J. E., Bampoky, C., Blanco, L. R., & Liu, A. (2016). Economic growth and the optimal level of entrepreneurship. World Development, 82, 95–109.Google Scholar
  66. Raphael, S., & Winter-Ebmer, R. (2001). Identifying the effect of unemployment on crime. Journal of Law and Economics, 44(1), 259–283.Google Scholar
  67. Reynolds, P., Bosma, N., Autio, E., Hunt, S., De Bono, N., Servais, I., Lopez-Garcia, P., & Chin, N. (2005). Global entrepreneurship monitor: data collection design and implementation 1998–2003. Small Business Economics, 24(3), 205–231.Google Scholar
  68. Romer, P. M. (1990). Endogenous technological change. Journal of Political Economy, 98, S71–S102.Google Scholar
  69. Samuelson, P. A., & Swamy, S. (1974). Invariant economic index numbers and canonical duality: survey and synthesis. American Economic Review, 64(4), 566–593.Google Scholar
  70. Shane, S. (2009). Why encouraging more people to become entrepreneurs is bad public policy. Small Business Economics, 33(2), 141–149.Google Scholar
  71. Schumpeter, J. A. (1934). The theory of economic development: an inquiry into profits, capital, credit, interest, and the business cycle. Cambridge, MA: Harvard University Press.Google Scholar
  72. Schumpeter, J. A. (1947). The creative response in economic history. Journal of Economic History, 7(2), 149–159.Google Scholar
  73. Solow, R. M. (1957). Technical change and the aggregate production function. Review of Economics and Statistics, 39(3), 312–320.Google Scholar
  74. Van Stel, A., Carree, M., & Thurik, R. (2005). The effect of entrepreneurial activity on national economic growth. Small Business Economics, 24(3), 311–321.Google Scholar
  75. Wong, P. K., Ho, Y. P., & Autio, E. (2005). Entrepreneurship, innovation and economic growth: evidence from GEM data. Small Business Economics, 24(3), 335–350.Google Scholar
  76. Wooldridge, J.M. (2002). Econometric analysis of cross section and panel data. Cambridge, MA: The MIT Press.Google Scholar
  77. Young, A. (1998). Growth without scale effects. Journal of Political Economy, 106(1), 41–63.Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of ManagementUniversitat Politècnica de Catalunya (BarcelonaTech) EPSEBBarcelonaSpain
  2. 2.Schar School of Policy and GovernmentGeorge Mason UniversityArlingtonUSA
  3. 3.Utrecht University School of EconomicsUtrechtThe Netherlands
  4. 4.Faculty of Business and EconomicsUniversity of PécsPécsHungary

Personalised recommendations