The matching method for treatment evaluation does not balance selective unobserved differences between treated and non-treated. We derive a simple correction term if there is an instrument that shifts the treatment probability to zero in specific cases. Policies with eligibility restrictions,...

Many empirical questions in economics and other social sciences depend on causal effects of programs or policies. In the last two decades much research has been done on the econometric and statistical analysis of the effects of such programs or treatments. This recent theoretical literature has...

A fundamental identification problem in program evaluation arises when idiosyncratic gains from participation and the treatment decision depend on each other. Imbens and Angrist (1994) were the first to exploit a monotonicity condition in order to identify an average treatment effect parameter...

As opposed to many other school inputs, textbooks have frequently been demonstrated to significantly foster student achievement. Using the rich data set provided by the 'Program on the Analysis of Education Systems' (PASEC) for five francophone, sub-Saharan African countries, this paper goes...

We estimate the public wage gap in France for the period 1990-2002, both at the mean and at different quantiles of the wage distribution, for men and women separately. We account for unobserved heterogeneity by using fixed effects estimations on panel data and, departing from usual practice,...

In this paper, the framework of the aggregated Beveridge curve is used to investigate the effectiveness of the job matching process using German regional labour market data. For a fixed matching technology, the Beveridge curve postulates a negative relationship between the unemployment rate and...

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...

This paper proposes a new approach to identify the wage effects of training. The idea is to narrow down the comparison group by only taking into consideration the workers who wanted to participate in training but did not do so because of some random event. The point estimate of the return to...

Using unique geo-coded information on the residential address of a representative sample of American adolescents and their friends, we revisit the importance of geographical proximity in shaping education outcomes. Our findings reveal no evidence of residential neighborhood effects. Social...

If the disturbances of a linear regression model are skewed and/or thick-tailed, a maximum likelihood estimator is efficient relative to the customary Ordinary Least Squares (OLS) estimator. In this paper, we specify a highly flexible Generalized Tukey Lambda (GTL) distribution to model skewed...