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A Martingale Representation for Matching Estimators
Abadie, Alberto; Imbens, Guido W. - Institute for the Study of Labor (IZA) - 2009
Matching estimators are widely used in statistical data analysis. However, the distribution of matching estimators has … matching estimators. This representation allows the use of martingale limit theorems to derive the asymptotic distribution of … matching estimators. As an illustration of the applicability of the theory, we derive the asymptotic distribution of a matching …
Persistent link: https://www.econbiz.de/10005566424
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Including Covariates in the Regression Discontinuity Design
Frölich, Markus; Huber, Martin - 2017
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
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Quantile treatment effects in the regression discontinuity design : process results and gini coefficient
Frölich, Markus; Melly, Blaise - 2010
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
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Identification and estimation of causal mechanisms and net effects of a treatment under unconfoundedness
Flores, Carlos A.; Flores-Lagunes, Alfonso - 2009
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...
Persistent link: https://www.econbiz.de/10003858863
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Nonlinear policy rules and the identification and estimation of causal effects in a generalized Regression Kink Design
Card, David E.; Lee, David S.; Pei, Zhuan; Weber, Andrea - 2012
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
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The value of knowing the propensity score for estimating average treatment effects
Rothe, Christoph - 2016
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
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Inference on causal effects in a generalized Regression Kink Design
Card, David E.; Lee, David S.; Pei, Zhuan; Weber, Andrea - 2015
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
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Inference on causal effects in a generalized Regression Kink Design
Card, David E.; Lee, David S.; Pei, Zhuan; Weber, Andrea - 2015
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
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Non-parametric inference for the effect of a treatment on survival times with application in the health and social sciences
DeLuna, Xavier; Johansson, Per - 2009
control group which are made comparable through matching on observed covariates. The inference is performed by conditioning on … ; heart transplant ; matching estimator ; observational study ; potential outcome ; survival function …
Persistent link: https://www.econbiz.de/10003801073
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Inference in regression discontinuity designs with a discrete running variable
Kolesár, Michal; Rothe, Christoph - 2016
We consider inference in regression discontinuity designs when the running variable only takes a moderate number of distinct values. In particular, we study the common practice of using confidence intervals (CIs) based on standard errors that are clustered by the running variable. We derive...
Persistent link: https://www.econbiz.de/10011493691