A Hausman test for non-ignorability

Using an empirical likelihood approach, we show that generalized linear models can still be consistently estimated even if dependent variables are not missing at random, and derive a Hausman test by comparing this estimator to the standard one.

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Year of publication:	2012
Authors:	Bücker, Michael ; Krämer, Walter ; Arnold, Matthias
Published in:	Economics Letters. - Elsevier, ISSN 0165-1765. - Vol. 114.2012, 1, p. 23-25
Publisher:	Elsevier
Subject:	Hausman test \| Missing data \| Empirical likelihood \| Reject inference \| Credit scoring \| Logistic regression

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Type of publication:	Article
Classification:	C12 - Hypothesis Testing ; C2 - Econometric Methods: Single Equation Models ; G24 - Investment Banking; Venture Capital; Brokerage
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10011041844