Efficient semiparametric estimation for endogenously stratified regression via smoothed likelihood

Stephen R. Cosslett

Journal of Econometrics, 2013, vol. 177, issue 1, 116-129

Abstract: This paper presents efficient semiparametric estimators for endogenously stratified regression with two strata, in the case where the error distribution is unknown and the regressors are independent of the error term. The method is based on the use of a kernel-smoothed likelihood function which provides an explicit solution for the maximization problem for the unknown density function without losing information in the asymptotic limit. We consider both standard stratified sampling and variable probability sampling, and allow for the population shares of the strata to be either unknown or known a priori.

Keywords: Semiparametric estimation; Asymptotic efficiency; Endogenously stratified regression (search for similar items in EconPapers)
JEL-codes: C14 C24 C25 (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:177:y:2013:i:1:p:116-129

DOI: 10.1016/j.jeconom.2013.07.003

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