This paper develops a nonparametric methodology for treatment evaluation with multiple outcome periods under treatment endogeneity and missing outcomes. We use instrumental variables, pre-treatment characteristics, and short-term (or intermediate) outcomes to identify the average treatment...

In this paper, the regression discontinuity design (RDD) is generalized to account for differences in observed covariates X in a fully nonparametric way. It is shown that the treatment effect can be estimated at the rate for one-dimensional nonparametric regression irrespective of the dimension...

This note argues that nonparametric regression not only relaxes functional form assumptions vis-a-vis parametric regression, but that it also permits endogenous control variables. To control for selection bias or to make an exclusion restriction in instrumental variables regression valid,...

We estimate the effects of active labour market policies (ALMP) on subsequent employment by nonparametric instrumental variables and matching estimators. Very informative administrative Swiss data with detailed regional information are combined with exogenous regional variation in programme...

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...

The effects of active labour market policies (ALMP) on individual employment chances and earnings are evaluated by nonparametric instrumental variables based on Swiss administrative data with detailed regional information. Using an exogenous variation in the participation probabilities across...

This paper presents a methodology to identify net demand shocks as well as wage rigidities in heterogeneous labor markets on the basis of nonparametric regression. We show how this approach can be used to make suggestions for immigration policy in economies with labor market rigidities. In an...

Propensity score matching is widely used in treatment evaluation to estimate average treatment effects. Nevertheless, the role of the propensity score is still controversial. Since the propensity score is usually unknown and has to be estimated, the efficiency loss arising from not knowing the...

This paper develops a nonparametric methodology for treatment evaluation with multiple outcome periods under treatment endogeneity and missing outcomes. We use instrumental variables, pre-treatment characteristics, and short-term (or intermediate) outcomes to identify the average treatment...

This paper discusses the nonparametric identification of causal direct and indirect effects of a binary treatment based on instrumental variables. We identify the indirect effect, which operates through a mediator (i.e. intermediate variable) that is situated on the causal path between the...