Showing 1 - 10 of 1,464
We consider nonparametric identification and estimation in a nonseparable model where a continuous regressor of … endogenous assignment variable (like previous earnings). We provide new results on identification and estimation for these …
Persistent link: https://www.econbiz.de/10013029646
Since the late 90s, Regression Discontinuity (RD) designs have been widely used to estimate Local Average Treatment Effects (LATE). When the running variable is observed with continuous measurement error, identification fails. Assuming non-differential measurement error, we propose a consistent...
Persistent link: https://www.econbiz.de/10012955015
dependent data and allowing for first-step estimation of the propensity score …
Persistent link: https://www.econbiz.de/10013325071
semiparametric estimation and inference are traditionally believed to be unreliable. We also illustrate the practical relevance of …
Persistent link: https://www.econbiz.de/10013076810
This chapter describes the main impact evaluation methods, both experimental and quasi-experimental, and the statistical model underlying them. Some of the most important methodological advances to have recently been put forward in this field of research are presented. We focus not only on the...
Persistent link: https://www.econbiz.de/10012843149
Across many disciplines, the fixed effects estimator of linear panel data models is the default method to estimate causal effects with nonexperimental data that are not confounded by time-invariant, unit-specific heterogeneity. One feature of the fixed effects estimator, however, is often...
Persistent link: https://www.econbiz.de/10014348300
Proxy variables are often used in linear regression models with the aim of removing potential confounding bias. In this paper we formalise proxy variables within the potential outcome framework, giving conditions under which it can be shown that causal effects are nonparametrically identified....
Persistent link: https://www.econbiz.de/10012986751
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/10013069679
We revisit the much-investigated relationship between schooling and health, focusing on cognitive abilities at older ages using the Harmonized Cognition Assessment Protocol in the Health & Retirement Study. To address endogeneity concerns, we employ a nonparametric partial identification...
Persistent link: https://www.econbiz.de/10014081950
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/10013325034