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We study voting over higher-education finance in an economy with two regions and two separated labor markets. Households differ in their financial endowment and their children's ability. Nonstudents are immobile. Students decide where to study; they return home after graduation with exogenous probability. The voters of the two regions decide on whether to subsidize higher-education costs or to rely on tuition fees only. We find that in equilibrium, in both regions a majority votes for subsidies when the return probability is sufficiently small. When that probability is large, both regions opt for full tuition finance.
The promotion of self-employment as part of active labor market policies is considered to be one of the most important unemployment support schemes in Germany. Against this background the main part of this thesis contributes to the evaluation of start-up support schemes within ALMP. Chapter 2 and 4 focus on the evaluation of the New Start-up Subsidy (NSUS, Gründungszuschuss) in its first version (from 2006 to the end of 2011). The chapters offer an advancement of the evaluation of start-up subsidies in Germany, and are based on a novel data set of administrative data from the Federal Employment Agency that was enriched with information from a telephone survey. Chapter 2 provides a thorough descriptive analysis of the NSUS that consists of two parts. First, the participant structure of the program is compared with the one of two former programs. In a second step, the study conducts an in-depth characterization of the participants of the NSUS focusing on founding motives, the level of start-up capital and equity used as well as the sectoral distribution of the new business. Furthermore, the business survival, income situation of founders and job creation by the new businesses is analyzed during a period of 19 months after start-up. The contribution of Chapter 4 is to introduce a new explorative data set that allows comparing subsidized start-ups out of unemployment with non-subsidized business start-ups that were founded by individuals who were not unemployed at the time of start-up. Because previous evaluation studies commonly used eligible non-participants amongst the unemployed as control group to assess the labor market effects of the start-up subsidies, the corresponding results hence referred to the effectiveness of the ALMP measure, but could not address the question whether the subsidy leads to similarly successful and innovative businesses compared to non-subsidized businesses. An assessment of this economic/growth aspect is also important, since the subsidy might induce negative effects that may outweigh the positive effects from an ALMP perspective. The main results of Chapter 4 indicate that subsidized founders seem to have no shortages in terms of formal education, but exhibit less employment and industry-specific experience, and are less likely to benefit from intergenerational transmission of start-ups. Moreover, the study finds evidence that necessity start-ups are over-represented among subsidized business founders, which suggests disadvantages in terms of business preparation due to possible time restrictions right before start-up. Finally, the study also detects more capital constraints among the unemployed, both in terms of the availability of personal equity and access to loans. With respect to potential differences between both groups in terms of business development over time, the results indicate that subsidized start-ups out of unemployment face higher business survival rates 19 months after start-up. However, they lag behind regular business founders in terms of income, business growth, and innovation. The arduous data collection process for start-up activities of non-subsidized founders for Chapter 4 made apparent that Germany is missing a central reporting system for business formations. Additionally, the different start-up reporting systems that do exist exhibit substantial discrepancies in data processing procedures, and therefore also in absolute numbers concerning the overall start-up activity. Chapter 3 is therefore placed in front of Chapter 4 and has the aim to provide a comprehensive review of the most important German start-up reporting systems. The second part of the thesis consists of Chapter 5 which contributes to the literature on determinants of job search behavior of the unemployed individuals by analyzing the effectiveness of internet search with regard to search behavior of unemployed individuals and subsequent job quality. The third and final part of the thesis outlines why the German labor market reacted in a very mild fashion to the Great Recession 2008/09, especially compared to other countries. Chapter 6 describes current economic trends of the labor market in light of general trends in the European Union, and reveals some of the main associated challenges. Thereafter, recent reforms of the main institutional settings of the labor market which influence labor supply are analyzed. Finally, based on the status quo of these institutional settings, the chapter gives a brief overview of strategies to adequately combat the challenges in terms of labor supply and to ensure economic growth in the future.
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).
We investigate whether people are more willing to become self-employed during boom periods or during recessions and to what extent business cycles and unemployment levels influence entries into entrepreneurship. Our analysis for Germany reveals that there is a positive relationship between unemployment rates and start-up activities. Moreover, new business formation is higher during recessions than in boom periods, implying that it is counter-cyclical. When disentangling periods of low and high unemployment we find that the effect of unemployment on new business formation is only statistically significant if the level of unemployment is below the trend, indicating a "low unemployment retain effect".