Volume 234, Issue 5

This paper deals with the medium-term effects of job mobility on the average wage growth of job-movers in eastern Germany. The analysis is based on all employees subject to social insurance contributions working in eastern Germany in 2004. Using a statistical matching procedure combined with a difference-in-differences estimator, we observe that job-movers achieve an average annual wage increase of 2.68% between 2004 and 2009, which is significantly higher than the annual wage growth of selected non-movers (1.34 %). The finding is very robust against changes in the matching procedure. The positive wage differential due to changing jobs was found for a variety of subgroups of individuals that were formed on the basis of sociodemographic and firm-specific characteristics. In contrast to the evidence in the 1990’s, the positive wage effect is now significantly lower for movers from eastern to western Germany compared to movers within eastern Germany.

We introduce an intuitive method of enhancing low-frequency volatility measures used to compute Value-at-Risk (VaR) by incorporating intradaily liquidity information from the limit order book. Using the quote slope of Hasbrouck and Seppi (2001), a compound liquidity measure comprising the dimensions of bid-ask spread and log depths, as a proxy for latent liquidity, we assign states of liquidity that the asset instantaneously resides in to allow only extremal liquidity shocks to influence volatility. To forecast the liquidity states, we use the autoregressive conditional multinomial model of Liesenfeld et al. (2006). We test the method on a number of stocks and find that (1) for stocks in financial and technological sectors, only the extremal shocks to liquidity affect volatility significantly and such a liquidity-state adjusted volatility is likely to improve VaR forecasts; (2) the volatility of stock returns in most other sectors are less affected by extremal shocks to liquidity but the continuous liquidity proxy is able to explain some of the dynamics of volatility and (3) the inclusion of liquidity in VaR becomes increasingly important as the quantile under consideration becomes more extreme.

This paper examines the predictive power of different estimation approaches for reservation wages. It applies stochastic frontier models for employed persons and the approach from Kiefer and Neumann (1979b) for unemployed persons. Furthermore, the question of whether or not reservation wages decrease over the unemployment period is addressed. This is done by a simulated panel with known reservation wages which uses data from the Socio-Economic Panel as a basis. The comparison of the estimators is carried out by a Monte Carlo simulation. In case of employed persons, the cross-sectional stochastic frontier model shows the best performance. The Kiefer-Neumann approach for unemployed persons is able to predict decreasing reservation wages but the rise of the mean reservation wage in case of a constant simulated reservation wage went undetected. In general, the Kiefer-Neumann approach overestimates the reservation wage.

Arent and Nagl (2013) use the BA Employment panel 1998-2007 to identify effects of the German Hartz reform and find that it caused a considerable reduction of wages. Our replication study suggests that their clear and strong conclusions are based on implausible assumptions regarding the error structure of their regression models and on a too coarse modelling of the time effects. They become blurred and weak once better estimates of the standard errors are obtained and the development of wages is investigated at a finer time grid. Furthermore, Arent and Nagl’s reform effects shrink considerably when a more appropriate price index is used to deflate the wages and when the censoring of wages is treated correctly. Methodological considerations suggest that their conclusions depend on several further daring and untested assumptions.