This paper provides doubly robust estimators for treatment effect parameters which are defined in multivalued treatment effect framework. We apply this method on a unique data set of British Cohort Study (BCS) to estimate returns to different levels of schooling. Average returns are estimated...

This paper provides doubly robust estimators for treatment effect parameters which are defined in multivalued treatment effect framework. We apply this method on a unique data set of British Cohort Study (BCS) to estimate returns to different levels of schooling. Average returns are estimated...

This paper partially identifies population treatment effects in observational data under sample selection, without the benefit of random treatment assignment. Bounds are provided for both average and quantile population treatment effects, combining assumptions for the selected and the...

We partially identify population treatment effects in observational data under sample selection, without the benefit of random treatment assignment. We provide bounds both for the average and the quantile population treatment effects, combining assumptions for the selected and the non-selected...

Against the backdrop of Baumol’s model of ‘unbalanced growth’, a recent strand of literature has presented models that manage to reconcile structural change with Kaldor’s ‘stylized fact’ of the relative constancy of per-capita GDP growth. Another strand of literature goes beyond...

An important goal when analyzing the causal effect of a treatment on an outcome is to understand the mechanisms through which the treatment causally works. We define a causal mechanism effect of a treatment and the causal effect net of that mechanism using the potential outcomes framework. These...

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 shows nonparametric identification of quantile treatment effects (QTE) in the regression discontinuity design. The distributional impacts of social programs such as welfare, education, training programs and unemployment insurance are of large interest to economists. QTE are an...