Rainer Winkelmann

Why Are the Unemployed So Unhappy? Evidence from Panel Data

This paper tests for the importance of non-pecuniary costs of unemployment using a longitudinal data-set on life-satisfaction of working-age men in Germany. We show that unemployment has a large detrimental effect on satisfaction after individual specific fixed effects are controlled for. The non-pecuniary effect is much larger than the effect that stems from the associated loss of income.

Markov Chain Monte Carlo Analysis of Correlated Count Data

This article is concerned with the analysis of correlated count data. A class of models is proposed in which the correlation among the counts is represented by correlated latent effects. Special cases of the model are discussed and a tuned and efficient Markov chain Monte Carlo algorithm is developed to estimate the model under both multivariate normal and multivariate-t assumptions on the latent effects. The methods are illustrated with two real data examples of six and sixteen variate correlated counts.

Employment Prospects and Skill Acquisition of Apprenticeship-Trained Workers in Germany.

Using data from the German Socio-Economic Panel for 1984–90, the author analyzes the entrance of young individuals into the German labor market, comparing the experience of apprenticeship graduates to that of graduates from universities, full-time vocational schools, and secondary schools. Apprentices experienced fewer unemployment spells in the transition to their first full-time employment than did non-apprentices. Among apprentices, those trained in large firms had the smoothest transition to employment; once employed, however, apprentices (whether they stayed in their training firm or not) and non-apprentices had similar job stability (as measured by tenure). An estimated 70% of apprenticeship trainees left their training firm within a five-year period. These findings are consistent with the view that apprenticeship training develops general, portable skills rather than firm-specific skills.

Duration Dependence and Dispersion in Count-Data Models

This paper explores the relation between non-exponential waiting times between events and the distribution of the number of events in a fixed time interval. It is shown that within this framework the frequently observed phenomenon of overdispersion, i.e. a variance that exceeds the mean, is caused by a decreasing hazard function of the waiting times, while an increasing hazard function leads to underdispersion. Using the assumption of i.i.d. gamma distributed waiting times, a new count data model is derived. Its use is illustrated in two applications: the number of births, and the number of doctor consultations. Duration Dependence and Dispersion in Count-Data Models Author(s): Rainer Winkelmann Source: Journal of Business & Economic Statistics, Vol. 13, No. 4 (Oct., 1995), pp. 467-474 Published by: American Statistical Association Stable URL: http://www.jstor.org/stable/1392392 Accessed: 28/04/2009 06:19 Your use of the JSTOR archive indicates your acceptance of JSTORs Terms and Conditions of Use, available at http://www.jstor.org/page/info/about/policies/terms.jsp. JSTORs Terms and Conditions of Use provides, in part, that unless you have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive only for your personal, non-commercial use. Please contact the publisher regarding any further use of this work. Publisher contact information may be obtained at http://www.jstor.org/action/showPublisher?publisherCode=astata. Each copy of any part of a JSTOR transmission must contain the same copyright notice that appears on the screen or printed page of such transmission. JSTOR is a not-for-profit organization founded in 1995 to build trusted digital archives for scholarship. We work with the scholarly community to preserve their work and the materials they rely upon, and to build a common research platform that promotes the discovery and use of these resources. For more information about JSTOR, please contact support@jstor.org. American Statistical Association is collaborating with JSTOR to digitize, preserve and extend access to Journal of Business & Economic Statistics. http://www.jstor.org @ 1995 American Statistical Association Journal of Business & Economic Statistics, October 1995, Vol. 13, No. 4 Duration Dependence and Dispersion in Count-Data Models Rainer WINKELMANN Department of Economics, University of Canterbury, Christchurch, New Zealand This article xplores the relation between nonexponential waiting times between events and the distribution f the number of events in a fixed time interval. It is shown that within this framework the frequently observed phenomenon of overdispersion-that is, a variance that exceeds the mean-is caused by a decreasing hazard function of the waiting times, whereas an increasing hazard function leads to underdispersion. Using the assumption of lid gamma-distributed waiting times, a new count-data model is derived. Its use is illustrated intwo applications, the number of births and the number of doctor consultations.

Ordered Response Models

We discuss regression models for ordered responses, such as ratings of bonds, schooling attainment, or measures of subjective well-being. Commonly used models in this context are the ordered logit and ordered probit regression models. They are based on an underlying latent model with single index function and constant thresholds. We argue that these approaches are overly restrictive and preclude a flexible estimation of the effect of regressors on the discrete outcome probabilities. For example, the signs of the marginal probability effects can only change once when moving from the smallest category to the largest one. We then discuss several alternative models that overcome these limitations. An application illustrates the benefit of these alternatives.

Posterior simulation and Bayes factors in panel count data models

This paper is concerned with the problems of posterior simulation and model choice for Poisson panel data models with multiple random effects. Efficient algorithms based on Markov Chain Monte Carlo methods for sampling the posterior distribution are developed. A new parameterization of the random effects and fixed effects is proposed and compared with a parameterization in common use. Computation of marginal likelihoods and Bayes factors from the simulation output is also considered. The methods are illustrated with several real data applications involving large samples and multiple random effects. This version corrects some typographical errors in the earlier submission.

Is job stability declining in Germany? Evidence from count data models

The macro evidence of increased adjustment pressure since the early 1970s suggests that job mobility should have increased. Hence, retrospective and spell data from the German Socio-Economic Panel are combined in order to test the hypothesis that job stability for German workers declined between 1974 and 1994. Using count data regression models in which we control for labour market experience, various demographic factors, and occupation, we find that job stability did not decrease, but if anything increased, between 1974 and 1994. Our finding suggests that labour market inflexibility is an important factor in explaining the European unemployment problem.

Ageing, Migration and Labour Mobility

This paper provides insights into the relationship between the substantial ageing of the European labour force, large migration movements, and individual labour mobility. First, qualitative predictions are derived using the theory of production with multiple inputs. Second, quantitative relationships are measured using a large sample of German individual data. Mobility is measured by the number of job changes of an individual during a ten-year period. We address some methodological issues raised by the use of non-negative integer data in an econometric investigation. The estimates are used to evaluate the interactions in several simulations: What is the age-mobility profile? How is it affected by migration? What are the potential effects of labour-force ageing as predicted for Germany and Europe up to the beginning of the next century?

An empirical analysis of the decision to train apprentices

It is a widely held belief that apprenticeship training represents a net investment for training firms, the cost of which needs to be recouped after the training period. A new firm-level data set for Switzerland reveals large variation in net costs across firms and, remarkably, negative net costs for 60 per cent of all firms. We use these data to estimate the effect of net costs on the number of apprentices hired by a firm. The results show that the costs have a significant impact on the training decision but no significant influence on the number of apprentices, once the firm has decided to train. For policy purposes, these results indicate that subsidies for firms that already train apprentices would not boost the number of available training places.

Two aspects of labor mobility: A bivariate Poisson regression approach

SummaryThe study introduces a distinction between two types of labor mobility. Direct job to job changes (which are assumed to be voluntary) and job changes after experiencing an unemployment spell (assumed to be involuntary). Exploiting the close relationship between those two phenomena we adopt a bivariate regression framework for our empirical analysis of data on male individuals in the German labor market. To account for the non-negative and discrete nature of the two counts of job changes in a ten year interval a new econometric model is proposed: the bivariate Poisson regression proves to be superior to the univariate specification. Further, the empirical content of distinguishing between two types of mobility is subject to a test, and, in fact, supported by the data: The hypothesis that both measures are observationally equivalent can be rejected.