In the practice of program evaluation, choosing the covariates and the functional form of the propensity score is an important choice that the researchers make when estimating treatment effects. This paper proposes a data-driven way of averaging the estimators over the candidate specifications...

This paper reviews methods that seek to draw causal inference from non-experimental data and shows how they can be applied to undertake ex-post evaluation of transport interventions. In particular, the paper discusses the underlying principles of techniques for treatment effect estimation with...

A simple shrinkage method is proposed to improve the performance of weighting estimators of the average treatment effect. As the weights in these estimators can become arbitrarily large for the propensity scores close to the boundaries, three different variants of a shrinkage method for the...

This paper estimates causal effects of two Polish active labor market policies - Training and Intervention Works - on employment probabilities. Using data from the 18th wave of the Polish Labor Force Survey we discuss three stages of an appropriately designed matching procedure and demonstrate...

After the Global Financial Crisis a controversial rush to fiscal austerity followed in many countries. Yet research on the effects of austerity on macroeconomic aggregates was and still is unsettled, mired by the difficulty of identifying multipliers from observational data. This paper...

The discriminatory component of the gender wage gap was found to be significant and to decrease over time by previous studies, most of them based on the Oaxaca-Blinder decomposition (OBD). Such evidence is disputable for being grounded on the assumption of full common support between men and...