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INFERENCE ON TWO-COMPONENT MIXTURES UNDER TAIL RESTRICTIONS
Published online by Cambridge University Press: 04 April 2016
Abstract
Many econometric models can be analyzed as finite mixtures. We focus on two-component mixtures, and we show that they are nonparametrically point identified by a combination of an exclusion restriction and tail restrictions. Our identification analysis suggests simple closed-form estimators of the component distributions and mixing proportions, as well as a specification test. We derive their asymptotic properties using results on tail empirical processes and we present a simulation study that documents their finite-sample performance.
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- Copyright © Cambridge University Press 2016
Footnotes
We are grateful to Peter Phillips, Arthur Lewbel, and three referees for comments and suggestions, and to Victor Chernozhukov and Yuichi Kitamura for fruitful discussions. Parts of this paper were written while Henry was visiting the University of Tokyo Graduate School of Economics and while Salanié was visiting the Toulouse School of Economics. The hospitality of both institutions is gratefully acknowledged. Jochmans’ research has received funding from the SAB grant “Nonparametric estimation of finite mixtures”. Henry’s research has received funding from the SSHRC Grants 410-2010-242 and 435-2013-0292, and NSERC Grant 356491-2013. Salanié thanks the Georges Meyer endowment. Some of the results presented here previously circulated as part of Henry, Kitamura, and Salanié (2010), whose published version (Henry et al., 2014) only contains results on partial identification.
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