In this paper we test the Rational Expectations hypothesis using longitudinal data on expectations and realizations of individual welfare for East Germans in the years following reunification. German reunification was unexpected and delivered a large shock to the future prospects of the...

Each worker belongs to either the majority or the minority group and, irrespective of the group she belongs to, can have good or bad work habits. These traits are transmitted from one generation to the next through a learning and imitation process which depends on parents' purposeful investment...

This paper argues that expectations are an important element that needs to be included into the analysis of the effects of the minimum wage on employment. We show in a standard matching model that the observed employment effect is higher the lower is the likelihood associated with the minimum...

This paper discusses the evaluation problem using observational data when the timing of treatment is an outcome of a stochastic process. We show that the duration framework in discrete time provides a fertile ground for effect evaluations. We suggest easy-to-use nonparametric survival function...

Applying a method suggested by Woodruff (1971), we derive the sampling variances of Generalized Entropy and Atkinson inequality indices when estimated from complex survey data. It turns out that this method also greatly simplifies the calculations for the i.i.d. case when compared to previous...

This paper introduces bias-corrected estimators for nonlinear panel data models with both time invariant and time varying heterogeneity. These include limited dependent variable models with both unobserved individual effects and endogenous explanatory variables, and sample selection models with...

We characterize the bias of propensity score based estimators of common average treatment effect parameters in the case of selection on unobservables. We then propose a new minimum biased estimator of the average treatment effect. We assess the finite sample performance of our estimator using...

A common approach to dealing with missing data is to estimate the model on the common subset of data, by necessity throwing away potentially useful data. We derive a new probit type estimator for models with missing covariate data where the dependent variable is binary. For the benchmark case of...