It is often argued that the labor market outcomes of several "problem groups" of German workers suffer disproportionately in an economic downturn. These groups are women, the unskilled, and young and old workers, respectively. Using monthly individual-level data for West Germany for the period 1983 to 1994, this paper explores both the demographic heterogeneity of German unemployment in the long term, and the cyclical sensitivity of the unemployment experience across demographic groups. The analysis moves beyond that of unemployment rates to a detailed investigation of transition rates from employment to unemployment and vice versa. While long-term differences across demographic groups are dominating the structure of both job loss and re-employment, estimation of a nonlinear regression model reveals additional aspects of cyclical sensitivity. In particular, young workers experience drastically more pronounced swings in their labor market performance than the average worker, whereas old workers seem basically isolated from the economic cycle. By contrast, in terms of its cyclical sensitivity, the labor market performance of women and of unskilled workers is not dramatically different from that of the average worker.
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.