Using 1985-1999 data from the German Socio-Economic Panel Study (GSOEP) to analyze wages we confirm the hypothesis that existing computer wage premiums are determined by individual ability or other unobserved individual characteristics rather than by productivity effects. While a rather large...

This paper produces first econometric estimates for Germany of the contemporanous wage gap associated with Temporary Help Service (THS) employment, as well as the long-term effects of THS work on the future earnings of workers. In addition, we present evidence showing that average male real...

Amid lively debate on the consequences of temporary employment, the paper examines the wages and transitions of temporary employees in Germany using socio-economic panel data from the late 1990s. Compared to simple OLS estimates, using a fixed effects model decreases wage differentials between...

This paper investigates the effect of displacement on reemployment wages of socially insured West German workers who became unemployed in 1986. Because detailed information on the cause of job loss is unavailable, displacement status is imputed using a probit estimated on the German...

The estimates of the structural parameters of a job separations model derived from the theory of on-the-job search are reported in this papers. Given that each employer pays the same wage to all observably equivalent workers and that wage dispersion across employers exists in the sense that...

East-West migration in Germany peaked at the beginning of the 90s although the average wage gap between Eastern and Western Germany continues to average about 25%. We analyze the propensity to migrate using microdata from the German Socioeconomic Panel. Fitting a parametric Generalized Linear...

We show in the paper that the decomposition proposed by Beveridge and Nelson (1981) for models that are integrated of order one can be generalized to seasonal Arima models by means of a partial fraction decomposition. Two equivalent algorithms are proposed to optimally (in the mean squared...