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More on confidence intervals for partially identified parameters
Stoye, Jörg (contributor) - 2008
This paper extends Imbens and Manski’s (2004) analysis of confidence intervals for interval identified parameters. For their final result, Imbens and Manski implicitly assume superefficient estimation of a nuisance parameter. This appears to have gone unnoticed before, and it limits the...
Persistent link: https://www.econbiz.de/10003739665
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Intersection bounds : estimation and inference
Chernozhukov, Victor; Lee, Sokbae; Rosen, Adam M. - 2011
We develop a practical and novel method for inference on intersection bounds, namely bounds defined by either the infimum or supremum of a parametric or nonparametric function, or equivalently, the value of a linear programming problem with a potentially infinite constraint set. Our approach is...
Persistent link: https://www.econbiz.de/10009375645
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A practical asymptotic variance estimator for two-step semiparametric estimators
Ackerberg, Daniel A.; Chen, Xiaohong; Hahn, Jinyong - 2010 - Final Version: July, 2010
The goal of this paper is to develop techniques to simplify semiparametric inference. We do this by deriving a number … of numerical equivalence results. These illustrate that in many cases, one can obtain estimates of semiparametric … purposes, an empirical researcher can ignore the semiparametric nature of the problem and do all calculations "as if" it were a …
Persistent link: https://www.econbiz.de/10009230390
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Practical and theoretical advances in inference for partially identified models
Canay, Ivan A.; Shaikh, Azeem M. - 2016
This paper surveys some of the recent literature on inference in partially identified models. After reviewing some basic concepts, including the definition of a partially identified model and the identified set, we turn our attention to the construction of confidence regions in partially...
Persistent link: https://www.econbiz.de/10011417422
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Inference under covariate-adaptive randomization
Bugni, Federico A.; Canay, Ivan A.; Shaikh, Azeem M. - 2015
This paper studies inference for the average treatment effect in randomized controlled trials with covariate-adaptive randomization. Here, by covariate-adaptive randomization, we mean randomization schemes that first stratify according to baseline covariates and then assign treatment status so...
Persistent link: https://www.econbiz.de/10011309722
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Intersection bounds : estimation and inference
Chernozhukov, Victor; Lee, Sokbae; Rosen, Adam M. - 2012
We develop a practical and novel method for inference on intersection bounds, namely bounds defined by either the infimum or supremum of a parametric or nonparametric function, or equivalently, the value of a linear programming problem with a potentially infinite constraint set. We show that...
Persistent link: https://www.econbiz.de/10009668003
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Inference for extremal conditional quantile models, with an application to market and birthweight risks
Chernozhukov, Victor; Fernández-Val, Iván - 2009 - This version: December 26, 2009
Quantile regression is an increasingly important empirical tool in economics and other sciences for analyzing the impact of a set of regressors on the conditional distribution of an outcome. Extremal quantile regression, or quantile regression applied to the tails, is of interest in many...
Persistent link: https://www.econbiz.de/10009419329
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Inference under covariate-Adaptive randomization
Bugni, Federico A.; Canay, Ivan A.; Shaikh, Azeem M. - 2016
This paper studies inference for the average treatment effect in randomized controlled trials with covariate-adaptive randomization. Here, by covariate-adaptive randomization, we mean randomization schemes that first stratify according to baseline covariates and then assign treatment status so...
Persistent link: https://www.econbiz.de/10011459651
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Inference on a distribution from noisy draws
Jochmans, Koen; Weidner, Martin - 2021
We consider a situation where the distribution of a random variable is being estimated by the empirical distribution of noisy measurements of that variable. This is common practice in, for example, teacher value-added models and other fixed-effect models for panel data. We use an asymptotic...
Persistent link: https://www.econbiz.de/10012792731
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Inference on a distribution from noisy draws
Jochmans, Koen; Weidner, Martin - 2019
We consider a situation where the distribution of a random variable is being estimated by the empirical distribution of noisy measurements of that variable. This is common practice in, for example, teacher value-added models and other fixed-effect models for panel data. We use an asymptotic...
Persistent link: https://www.econbiz.de/10012063831