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New Misspecification Tests for Multinomial Logit Models

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Listed:
  • Fok, D.
  • Paap, R.

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

Suggested Citation

  • Fok, D. & Paap, R., 2019. "New Misspecification Tests for Multinomial Logit Models," Econometric Institute Research Papers EI2019-24, Erasmus University Rotterdam, Erasmus School of Economics (ESE), Econometric Institute.
    • Handle: RePEc:ems:eureir:116745
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    References listed on IDEAS

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    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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