Misspecified Discrete Choice Models and Huber-White Standard Errors

Guggisberg Michael ()
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Guggisberg Michael: Institute for Defense Analyses, Strategy, Resources and Forces Division, 4850 Mark Center DrAlexandria, United States of America

Journal of Econometric Methods, 2019, vol. 8, issue 1, 17

Abstract: I analyze properties of misspecified discrete choice models and the efficacy of Huber-White (sometimes called ‘robust’) standard errors. The Huber-White correction provides asymptotically correct standard errors for a consistent estimator from a misspecified model. There is little justification for using Huber-White standard errors in discrete choice models since misspecification usually leads to inconsistent estimators. I derive necessary and sufficient conditions for consistency of the maximum likelihood estimator of any potentially misspecified random utility model (e.g. conditional logit). I also derive (easily satisfied) sufficient conditions for consistent estimation of the sign of the data generating parameter. It follows the researcher can consistently test the sign (or nullity) of the parameter from the data generating process using the (possibly) misspecified conditional logit. I investigate small sample properties of the Huber-White estimator via a simulation study and find the correction provides little to no improvement for inferences.

Keywords: discrete choice; Huber-White standard errors; misspecified models (search for similar items in EconPapers)
Date: 2019
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DOI: 10.1515/jem-2016-0002

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