The Regression Kink (RK) design is an increasingly popular empirical method, with more than 20 studies circulated using RK in the last 5 years since the initial circulation of Card, Lee, Pei and Weber (2012). We document empirically that these estimates, which typically use local linear...

The paper discusses gender differences with regard to the self- and reciprocal estimation of career expectations. Firstly, the theoretical background and the literature are identified. Within this frame, the instance of self-under-estimated career prospects of female workers and statistical...

We investigate the finite sample performance of causal machine learning estimators for heterogeneous causal effects at different aggregation levels. We employ an Empirical Monte Carlo Study that relies on arguably realistic data generation processes (DGPs) based on actual data. We consider 24...

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...

Recent studies that aim to estimate the causal link between the education of parents and their children provide evidence that is far from conclusive. This paper explores why. There are a number of possible explanations. One is that these studies rely on different data sources, gathered in...

Instrumental variables estimates of the effect of military service on subsequent civilian earnings either omit schooling or treat it as exogenous. In a more general setting that also allows for the treatment of schooling as endogenous, we estimate the veteran effect for men who were born between...

Based on new, exceptionally informative and large German linked employer-employee administrative data, we investigate the question whether the omission of important control variables in matching estimation leads to biased impact estimates of typical active labour market programs for the...

The purpose of this paper is two-fold. First, it compares the performance of various panel data models in estimating technical efficiency in production. Second, it applies various stochastic frontier panel data models to estimate the technical efficiency of Iran's cotton production and to...

We consider nonparametric identification and estimation in a nonseparable model where a continuous regressor of interest is a known, deterministic, but kinked function of an observed assignment variable. This design arises in many institutional settings where a policy variable (such as weekly...

Using normalized regression equations, we propose an alternative estimator of industrial gender wage gaps which is identified in the sense that it is invariant to the choice of an unobserved non-discriminatory wage structure, and to the choice of the reference groups of any categorical...