Showing 1 - 10 of 1,617
Propensity score matching is widely used in treatment evaluation to estimate average treatment effects. Nevertheless …
Persistent link: https://www.econbiz.de/10011412472
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/10011413605
due to mismeasured variables. We consider sample merger by matching on identifiers that may be imperfect in the case that …
Persistent link: https://www.econbiz.de/10014024940
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/10011760113
This paper compares the inverse-probability-of-selection-weighting estimation principle with the matching principle and … derives conditions for weighting and matching to identify the same and the true distribution, respectively. This comparison …
Persistent link: https://www.econbiz.de/10012728898
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/10003975413
We consider nonparametric identification and estimation in a nonseparable model where a continuous regressor of interest is a known, deterministic, but kinked function of an observed assignment variable. This design arises in many institutional settings where a policy variable (such as weekly...
Persistent link: https://www.econbiz.de/10011345869
In a treatment effect model with unconfoundedness, treatment assignments are not only independent of potential outcomes given the covariates, but also given the propensity score alone. Despite this powerful dimension reduction property, adjusting for the propensity score is known to lead to an...
Persistent link: https://www.econbiz.de/10011486511
We consider nonparametric identification and estimation in a nonseparable model where a continuous regressor of interest is a known, deterministic, but kinked function of an observed assignment variable. This design arises in many institutional settings where a policy variable (such as weekly...
Persistent link: https://www.econbiz.de/10010467807
We consider nonparametric identification and estimation in a nonseparable model where a continuous regressor of interest is a known, deterministic, but kinked function of an observed assignment variable. This design arises in many institutional settings where a policy variable (such as weekly...
Persistent link: https://www.econbiz.de/10010472511