Censored Quantile Regressions and the Length of Unemployment Periods in West Germany

Abstract

In this paper, we estimate the effect of different macro and micro variables on thedistribution of unemployment duration in West Germany using censored quantile regressions. We analyze unemployment periods of more than 91,000 observations from the years 1981 to 1997 drawn from the IAB employment subsample. The latter is an administrative data set that is representative with respect to the socially insured workforce. Surprisingly, we find that the educational degree and variables indicating the macroeconomic environment such as the unemployment rate have a weak effect only. On the other hand, variables reflecting the (un-)employment history of an individual such as the length of tenure, recall to the same employer in the past, recent unemployment and the position in the population income distribution before unemployment have the strongest effects on unemployment duration. We conclude that work history variables are the ones most suitable in characterizing the unemployment duration of an individual. From a methodological point of view, it is interesting that some regression coefficients have a different sign depending on the quantiles of the unemployment duration distribution. This clearly is a violation of the classical proportional hazard assumption which is very common in unemployment duration analysis. --censored quantile regression,unemployment duration,administrative data