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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...
Persistent link: https://www.econbiz.de/10005822913
We introduce a nonparametric estimator for local quantile treatment effects in the regression discontinuity (RD) design …
Persistent link: https://www.econbiz.de/10011052292
This paper shows nonparametric identification of quantile treatment effects (QTE) in the regression discontinuity …-dimensional nonparametric regression. We apply the proposed estimators to estimate the effects of summer school on the distribution of school …
Persistent link: https://www.econbiz.de/10008602732
In this paper nonparametric instrumental variable estimation of local average treatment effects (LATE) is extended to … on much weaker assumptions than the identification of average treatment effects in other nonparametric instrumental … of LATE rely on parametric or semiparametric methods. In this paper, a nonparametric estimator for the estimation of LATE …
Persistent link: https://www.econbiz.de/10010262665
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...
Persistent link: https://www.econbiz.de/10010262697
nonparametric matching and weighting estimators of the average treatment effects and their properties are examined. …
Persistent link: https://www.econbiz.de/10010262703
Choosing among a number of available treatments the most suitable for a given subject is an issue of everyday concern. A physician has to choose an appropriate drug treatment or medical treatment for a given patient, based on a number of observed covariates X and prior experience. A case worker...
Persistent link: https://www.econbiz.de/10010267863
This note argues that nonparametric regression not only relaxes functional form assumptions vis-a-vis parametric …. Nonparametric approaches are still consistent, though. A few examples are examined and it is found that the asymptotic bias of OLS …
Persistent link: https://www.econbiz.de/10010268065
This paper shows nonparametric identification of quantile treatment effects (QTE) in the regression discontinuity …-dimensional nonparametric regression. We apply the proposed estimators to estimate the effects of summer school on the distribution of school …
Persistent link: https://www.econbiz.de/10010269846
This paper discusses the nonparametric identification of causal direct and indirect effects of a binary treatment based … obtain nonparametric identi-fication of (natural) direct and indirect as well as controlled direct effects for continuous and …
Persistent link: https://www.econbiz.de/10011440163