Showing 1 - 10 of 1,367
Propensity score matching is widely used in treatment evaluation to estimate average treatment effects. Nevertheless …
Persistent link: https://www.econbiz.de/10005822913
In this paper nonparametric instrumental variable estimation of local average treatment effects (LATE) is extended to incorporate confounding covariates. Estimation of local average treatment effects is appealing since their identification relies on much weaker assumptions than the...
Persistent link: https://www.econbiz.de/10010262665
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...
Persistent link: https://www.econbiz.de/10010269846
This paper reviews the main identification and estimation strategies for microeconomic policy evaluation. Particular … nonparametric matching and weighting estimators of the average treatment effects and their properties are examined. …
Persistent link: https://www.econbiz.de/10010262703
This paper reviews the main identification and estimation strategies for microeconomic policy evaluation. Particular … nonparametric matching and weighting estimators of the average treatment effects and their properties are examined. …
Persistent link: https://www.econbiz.de/10005566371
In this paper nonparametric instrumental variable estimation of local average treatment effects (LATE) is extended to incorporate confounding covariates. Estimation of local average treatment effects is appealing since their identification relies on much weaker assumptions than the...
Persistent link: https://www.econbiz.de/10005566385
This paper proposes a fully nonparametric kernel method to account for observed covariates in regression discontinuity designs (RDD), which may increase precision of treatment effect estimation. It is shown that conditioning on covariates reduces the asymptotic variance and allows estimating the...
Persistent link: https://www.econbiz.de/10011786988
This paper shows nonparametric identification of quantile treatment effects (QTE) in the regression discontinuity design (RDD) and proposes simple estimators. Quantile treatment effects are a very helpful tool to characterize the effects of certain interventions on the outcome distribution. The...
Persistent link: https://www.econbiz.de/10005233749
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...
Persistent link: https://www.econbiz.de/10005762088
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...
Persistent link: https://www.econbiz.de/10008602732