Quasi-maximum likelihood estimation and testing for nonlinear models with endogenous explanatory variables

Jeffrey Wooldridge

Journal of Econometrics, 2014, vol. 182, issue 1, 226-234

Abstract: I propose a quasi-maximum likelihood framework for estimating nonlinear models with continuous or discrete endogenous explanatory variables. Joint and two-step estimation procedures are considered. The joint procedure is a quasi-limited information maximum likelihood procedure, as one or both of the log likelihoods may be misspecified. The two-step control function approach is computationally simple and leads to straightforward tests of endogeneity. In the case of discrete endogenous explanatory variables, I argue that the control function approach can be applied with generalized residuals to obtain average partial effects. I show how the results apply to nonlinear models for fractional and nonnegative responses.

Keywords: Quasi-maximum likelihood; Control function; Linear exponential family; Average structural function; Variable addition test (search for similar items in EconPapers)
JEL-codes: C13 C21 C25 (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (150)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:182:y:2014:i:1:p:226-234

DOI: 10.1016/j.jeconom.2014.04.020

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