A family of empirical likelihood functions and estimators for the binary response model

Ron Mittelhammer (mittelha@wsu.edu) and George Judge (gjudge@berkeley.edu)

Journal of Econometrics, 2011, vol. 164, issue 2, 207-217

Abstract: The minimum discrimination information principle is used to identify an appropriate parametric family of probability distributions and the corresponding maximum likelihood estimators for binary response models. Estimators in the family subsume the conventional logit model and form the basis for a set of parametric estimation alternatives with the usual asymptotic properties. Sampling experiments are used to assess finite sample performance.

Keywords: Binary; response; models; and; estimators; Conditional; moment; equations; Cressie-Read; family; of; likelihood; functions; Information; theoretic; methods; Minimum; power; divergence; Minimum; discrimination; information (search for similar items in EconPapers)
Date: 2011
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:164:y:2011:i:2:p:207-217

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