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What Makes an Employer?
(2019)
As the policy debate on entrepreneurship increasingly centers on firm growth in terms of job creation, it is important to better understand which variables influence the first hiring decision and which ones influence the subsequent survival as an employer. Using the German Socio-economic Panel (SOEP), we analyze what role individual characteristics of entrepreneurs play in sustainable job creation. While human and social capital variables positively influence the hiring decision and the survival as an employer in the same direction, we show that none of the personality traits affect the two outcomes in the same way. Some traits are only relevant for survival as an employer but do not influence the hiring decision, other traits even unfold a revolving door effect, in the sense that employers tend to fail due to the same characteristics that positively influenced their hiring decision.
Germany experienced a unique rise in the level of self-employment in the first two decades following unification. Applying the nonlinear Blinder-Oaxaca decomposition technique, we find that the main factors driving these changes in the overall level of self-employment are demographic developments, the shift towards service sector employment and a larger share of population holding a tertiary degree. While these factors explain most of the development in self-employment with employees and the overall level of self-employment in West Germany, their explanatory power is much lower for the stronger increase in solo self-employment and in self-employment in former socialist East Germany.
Why do entrepreneurship rates differ so markedly by gender? Using data from a large representative German household panel, we investigate to what extent personality traits, human capital, and the employment history influence the start-up decision and can explain the gender gap in entrepreneurship. Applying a decomposition analysis, we observe that the higher risk aversion among women explains a large share of the entrepreneurial gender gap. We also find an education effect contributing to the gender difference. In contrast, the Big Five model and the current employment state have effects in the opposite direction, meaning that the gender gap in entrepreneurial entry would be even larger if women had the same scores and the same employment status as men. (JEL codes: L26, J16, D81, J24, M13).