We propose a simple way to improve the efficiency of the average treatment effect on propensity score based estimators. As the weights become arbitrarily large for the propensity scores being close to one or zero, we propose to shrink the propensity scores away from these boundaries. Using a...

In this paper, we show the inability of a recent average treatment effect estimator (ATE) to catch up the asymptotic semiparametric efficiency bound of Hahn (1998) although it minimises the mean squared error. Additionally, we propose the use of a minimum variance unbiased uniformly estimator of...

The overlap problem is crucial in propensity score matching. Recently, Crump et al. (2009) showed that trimming provides a simple and robust solution to the overlap problem. In this study, we use a simulation approach to show that trimming is inferior to the caliper mechanism. We show that in...

Under the assumption of no unmeasured confounders, a large literature exists on methods that can be used to estimating average treatment effects (ATE) from observational data and that spans regression models, propensity score adjustments using stratification, weighting or regression and even the...

Estimators of average treatment effects under unconfounded treatment assignment are known to become rather imprecise if there is limited overlap in the covariate distributions between the treatment groups. But such limited overlap can also have a detrimental effect on inference, and lead for...

We econometrically evaluate the performance effects of a six month e-learning programme in a large retail chain with monthly data on sales revenue, for four years using panel regressions. Participants in early cohorts show positive performance effects during training periods that depreciate...

The study estimates the employment effect of vocational training programs for the unemployed in urban Russia. The results of propensity score matching indicate that training programs had a non-negative overall effect on the program participants relative to non-participants.