New Misspecification Tests for Multinomial Logit Models

Dennis Fok and Richard Paap

No EI2019-24, Econometric Institute Research Papers from Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute

Abstract: Misspecification tests for Multinomial Logit [MNL] models are known to have low power or large size distortion. We propose two new misspecification tests. Both use that preferences across binary pairs of alternatives can be described by independent binary logit models when MNL is true. The first test compares Composite Likelihood parameter estimates based on choice pairs with standard Maximum Likelihood estimates using a Hausman (1978) test. The second tests for overidentification in a GMM framework using more pairs than necessary. A Monte Carlo study shows that the GMM test is in general superior with respect to power and has correct size

Keywords: Discrete choices; Multinomial Logit; IIA; Hausman test; Composite Likelihood (search for similar items in EconPapers)
JEL-codes: C12 C25 C52 (search for similar items in EconPapers)
Pages: 20
Date: 2019-06-01
New Economics Papers: this item is included in nep-dcm and nep-ecm
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Journal Article: New misspecification tests for multinomial logit models (2025)
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