revised version published in: Oxford Bulletin of Economics and Statistics, 2008, 70(3), 347-373
Turning unemployment into self-employment has become a major focus of German active labour market policy (ALMP) in recent years. If effective, this would not only reduce Germany’s persistently high unemployment rate, but also increase its notoriously low self-employment rate. Empirical evidence on the effectiveness of such programmes is scarce. The contribution of the present paper is twofold: first, we evaluate the effectiveness of two start-up programmes for the unemployed. Our outcome variables include the probability of being employed, the probability of being unemployed, and personal income. Second, based on the results of this analysis, we conduct an efficiency analysis, i.e., we estimate whether the Federal Employment Agency has saved money by placing unemployed individuals in these programmes. Our results show that at the end of the observation period, both programmes are effective and one is also efficient. The considerable positive effects present a stark contrast to findings from evaluations of other German ALMP programmes in recent years. Hence, ALMP programmes aimed at moving the unemployed into self-employment may prove to be among the most effective, both in Germany and elsewhere.
We use cookies to provide you with an optimal website experience. This includes cookies that are necessary for the operation of the site as well as cookies that are only used for anonymous statistical purposes, for comfort settings or to display personalized content. You can decide for yourself which categories you want to allow. Please note that based on your settings, you may not be able to use all of the site's functions.
Cookie settings
These necessary cookies are required to activate the core functionality of the website. An opt-out from these technologies is not available.
In order to further improve our offer and our website, we collect anonymous data for statistics and analyses. With the help of these cookies we can, for example, determine the number of visitors and the effect of certain pages on our website and optimize our content.