Abstract
What makes a successful entrepreneur? Using Danish register data, we find strong support for the hypothesis that theoretical skills from schooling and practical skills acquired through wage-work are complementary inputs in the human capital earnings function of entrepreneurs. In fact, we find that schooling only pays off in combination with wage-work experience, as the returns to schooling are insignificant when the entrepreneur has no wage-work experience. The results are extremely robust toward more flexible specifications, including fixed-effect estimations dealing with unobserved heterogeneity. Furthermore, the interaction term is negligible for non-entrepreneurs, suggesting that the complementarity between wage-work experience and schooling is a distinctive characteristic of entrepreneurs.
This is a preview of subscription content, access via your institution.
Notes
Lazear (2012) states: “In fact, entrepreneurs are a subset of leaders and the distinction between entrepreneurs and leaders is somewhat blurred. Most successful entrepreneurs view themselves as leaders because they had the vision that enabled them to provide a valuable good or service cost effectively. Starting a successful business requires the ability to navigate through a vast array of potential hazards. Conversely, most leaders of large corporations think of themselves as entrepreneurial, whether they founded the company or not. High-profile CEOs include a few founders, but are comprised primarily of those who improved or redesigned existing companies to produce higher profits and shareholder value” (p. 93).
We have actually tried to use the father’s years of schooling as an instrument for years of schooling, see also Hoogerheide et al. (2012). The results are reported in footnote 18 of Sect. 6.2. Here we assume that \( X \) is exogenous and treat \( S \) as endogenous, and thereby instrument \( S \cdot X \) and \( S \). In doing this, we follow the method suggested by Balli and Sørensen (2013).
Note that we cannot identify the coefficient of \( S \cdot X \) for self-employed, since neither schooling nor wage-work experience varies over time for these individuals.
Bloom et al. (2012) use a similar estimation strategy when studying the relationship between IT and people management for firm performance.
Data also exist for 2003. However, since 2003 was a recession year, we use 2002 that is a more normal year in the analysis.
According to Hamilton (2000), net profit is analogous to the amount reported to the Internal Revenue Service. Similarly, annual surplus is also the surplus that is reported to the Danish tax authorities.
We also use an alternative measure of wage-employment experience, which converts years of wage-work experience into full-time equivalents, see Sect. 6.1.
Self-employed individuals with negative earning are excluded from the sample because the Mincer equation is formulated using log of income as the dependent variable. Since we cannot take the log of negative income, the observations drop out. To be precise, 3266 self-employed with negative income are excluded from the sample. If we estimate the earnings function using income levels instead of log income, self-employed individuals with negative income can be included. The results with and without self-employed with negative income are qualitatively similar.
Managers with previous self-employment experience have been excluded from the sample, because we want to study as clear-cut a group of managers as possible. Therefore, we do not want to include individuals with experience in both self-employment and leadership. A total of 1555 individuals with both managerial experience and self-employment experience are excluded from the sample. The qualitative results are, however, robust to the inclusion of these individuals.
Note that age can be included in the regressions together with S and X when X is measured as actual instead of potential experience.
We have also estimated (2) using an additional control variable that is similar to weeks worked. As stated in Sect. 3, Mincer (1974) found that when weeks worked were included as control variable in regressions of individual earnings, these interaction term became insignificant. Specifically, we include the share of time within a year an individual is unemployed. The results of Table 4 are robust to the inclusion of this variable.
The profiles for managers and self-employed are not directly comparable due to the different income measures used for the two groups of entrepreneurs and the presence of different controls in the underlying regressions, c.f. Table 4. Also note that the curves are computed for a given level of self-employment experience. Hence, in contrast to the curves for managers, the curves for self-employed cannot be interpreted as earnings profiles for self-employed individuals with different schooling levels.
The difference in earnings is calculated as the exponential of the difference in log earnings minus 1.
Since we extend the term \( X^{2} \) to include three types of industry experience, both squared and interaction terms of different types of experience are included in the equation.
A potential problem with the full-time equivalent experience measure is that the maximum number of hours worked follows the normal work week in the Danish labor market. This implies that nobody is registered to work more than 37 h per week. This restriction reduces the quality of the experience measure, especially for managers since survey data suggest that a high share of managers work more than 37 h. Thus, the results presented in column 8 of Table 7 should be interpreted with caution.
Note that the coefficient of schooling is not identified because the relatively few individuals changing their level of schooling between 1996 and 2002 have been excluded. Furthermore, with year dummies included, the coefficient of wage-work experience is only identified from individuals with multiple spells as managers in the panel. Hence, we do not wish to push the interpretation of this coefficient too far.
We have restricted the sample to exclude workers with self-employment experience, implying that wage-work experience equals total experience.
As mentioned in footnote 2, we have also addressed the relationship between years of schooling and the interaction term between years of schooling and wage-work experience using the father’s years of schooling as an instrument, see also Hoogerheide et al. (2012). More precisely, we treat wage-work experience as exogenous and therefore instrument \( S \) and \( S \cdot X \) by father’s years of schooling and father’s years of schooling interacted with wage-work experience of the individual, following the approach in Balli and Sørensen (2013). For managers, we find similar results as in Table 4, i.e., schooling and wage-work experience in itself bear no returns, whereas the interaction term does with a point estimate of around 0.005. For self-employed, the results are not as clear-cut. Here, we find a negative and significant direct return to years of schooling of −0.12 and a positive and significant interaction term of 0.009.
References
Abowd, J. M., & Kramarz, F. (1999). The analysis of labor markets using matched employer–employee data. In O. Ashenfelter & D. Card (Eds.), Handbook of labor economics (pp. 2629–2710). Amsterdam: Elsevier.
Balli, H. O., & Sørensen, B. E. (2013). Interaction effects in econometrics. Empirical Economics, 45(1), 583–603. doi:10.1007/s00181-012-0604-2.
Bloom, N., Sadun, R., & Van Reenen, J. (2012). Americans do I.T. better: US multinationals and the productivity miracle. American Economic Review, 102(1), 167–201. doi:10.1257/aer.102.1.167.
Bublitz, E., & Noseleit, F. (2014). The skill balancing act: When does broad expertise pay off? Small Business Economic, 42, 17–32. doi:10.1007/s11187-013-9474-z.
Card, D. (1999). The causal effect of education on earnings. In O. Ashenfelter & D. Card (Eds.), Handbook of labor economics (pp. 1801–1863). Amsterdam: Elsevier.
Card, D. (2001). Estimating the return to schooling: Progress on some persistent econometric problems. Econometrica, 69, 1127–1160. doi:10.1111/14680262.00237.
Carneiro, P., & Heckman, J. J. (2002). The evidence on credit constraints in post-secondary education. Economic Journal, 112, 705–734.
Chowdhury, S., Schulz, E., Milner, M., & Van De Voort, D. (2014). Core employee based human capital and revenue productivity in small firms: An empirical investigation. Journal of Business Research, 67, 2473–2479. doi:10.1016/j.jbusres.2014.03.007.
Griliches, Z. (1977). Estimating the returns to schooling: Some econometric problems. Econometrica, 45, 1–22.
Hamilton, B. H. (2000). Does entrepreneurship pay? An empirical analysis of the returns to self-employment. Journal of Political Economy, 108, 604–631. doi:10.1086/262131.
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(4), 947–989. doi:10.1111/j.1530-9134.2010.00274.x.
Heckman, J. J., Lochner, L. J., & Todd, P. E. (2006). Fifty years of Mincer earnings regressions. In E. Hanushek & F. Welch (Eds.), Handbook of education economics (Vol. 1). Amsterdam: Elsevier.
Hoogerheide, L., Block, J., & Thurik, R. (2012). Family background variables as instruments for education in income regressions: A Bayesian analysis. Economics of Education Review, 31(5), 515–523. doi:10.1016/j.econedurev.2012.03.001.
Iversen, J., Malchow-Møller, N., & Sørensen, A. (2010). Returns to schooling in self-employment. Economics Letters, 109, 179–182. doi:10.1016/j.econlet.2010.05.014.
Lazear, E. P. (2004). Balanced skills and entrepreneurship. American Economic Review, 94, 208–211. doi:10.1257/0002828041301425.
Lazear, E. P. (2005). Entrepreneurship. Journal of Labor Economics, 23, 649–680. doi:10.1086/491605.
Lazear, E. P. (2012). Leadership: A personnel economics approach. Labour Economics, 19(1), 92–101. doi:10.1016/j.labeco.2011.08.005.
Lechmann, D. S. J., & Schnabel, C. (2014). Are the self-employed really jacks-of-all-trades? Testing the assumptions and implications of Lazear’s theory of entrepreneurship with German data. Small Business Economic, 42(1), 59–76. doi:10.1007/s11187-012-9464-6.
Martin, B. C., McNally, J. J., & Kay, M. J. (2013). Examining the formation of human capital in entrepreneurship: A meta-analysis of entrepreneurship education outcomes. Journal of Business Venturing, 28(2), 211–224. doi:10.1016/j.jbusvent.2012.03.002.
Mincer, J. (1974). Schooling, experience, and earnings. New York: NBER Press.
Ministry of Higher Education and Science. (2013). Universities in numbers 2009. Copenhagen (in Danish).
OECD. (2008). Entrepreneurship and higher education. Paris: Organisation for Economic Co-operation and Development.
Parker, S. C. (2004). The economics of self-employment and entrepreneurship. Cambridge: Cambridge University Press.
Parker, S. C., & van Praag, M. (2006). Schooling, capital constraints, and entrepreneurial performance: The endogenous triangle. Journal of Business & Economic Statistics, 24(4), 416–431. doi:10.1198/073500106000000215.
Unger, J. M., Rauch, A., Frese, M., & Rosenbusch, N. (2011). Human capital and entrepreneurial success: A meta-analytical review. Journal of Business Venturing, 26(3), 341–358. doi:10.1016/j.jbusvent.2009.09.004.
van der Sluis, J., van Praag, M., & Vijverberg, W. (2008). Education and entrepreneurship selection and performance: A review of the empirical literature. Journal of Economic Surveys, 22, 795–841. doi:10.1111/j.1467-6419.2008.00550.x.
Acknowledgments
The views expressed in this paper are solely the responsibility of the authors and should not be interpreted as reflecting the views of the Executive Board of Sveriges Riksbank. We thank an editor and two referees, Ed Lazear, Steve Machin, Knut Roed, and Jan Rose Skaksen for comments. The usual disclaimer applies. Mikael Bjørk Andersen and Jonas Helth Lønborg provided efficient research assistance. Financial support from the National Agency for Enterprise and Housing and the Tuborg Foundation is gratefully acknowledged.
Funding
Financial support from the National Agency for Enterprise and Housing and The Tuborg Foundation is gratefully acknowledged.
Author information
Authors and Affiliations
Corresponding author
Ethics declarations
Conflict of interest
The authors declare that they have no conflicts of interest.
Appendix: Detailed estimation results
Appendix: Detailed estimation results
This appendix contains the full set of estimation results from the regressions in Tables 4, 6, and 10 in the paper (see Tables 11, 12, 13).
Rights and permissions
About this article
Cite this article
Iversen, J., Malchow-Møller, N. & Sørensen, A. Success in entrepreneurship: a complementarity between schooling and wage-work experience. Small Bus Econ 47, 437–460 (2016). https://doi.org/10.1007/s11187-016-9732-y
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11187-016-9732-y