Maximum likelihood estimation and uniform inference with sporadic identification failure

Donald Andrews () and Xu Cheng

Journal of Econometrics, 2013, vol. 173, issue 1, 36-56

Abstract: This paper analyzes the properties of a class of estimators, tests, and confidence sets (CSs) when the parameters are not identified in parts of the parameter space. Specifically, we consider estimator criterion functions that are sample averages and are smooth functions of a parameter θ. This includes log likelihood, quasi-log likelihood, and least squares criterion functions.

Keywords: Asymptotic size; Binary choice; Confidence set; Estimator; Identification; Likelihood; Nonlinear models; Test; Smooth transition threshold autoregression; Weak identification (search for similar items in EconPapers)
JEL-codes: C12 C15 (search for similar items in EconPapers)
Date: 2013
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (23)

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Related works:
Working Paper: Maximum Likelihood Estimation and Uniform Inference with Sporadic Identification Failure (2012)
Working Paper: Maximum Likelihood Estimation and Uniform Inference with Sporadic Identification Failure (2011)
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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:173:y:2013:i:1:p:36-56

DOI: 10.1016/j.jeconom.2012.10.003

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