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Testing Exogeneity of Multinomial Regressors in Count Data Models: Does Two-stage Residual Inclusion Work?

Author

Listed:
  • Geraci Andrea

    (INET, University of Oxford, Eagle House, Walton Well Road, Oxford, United Kingdom of Great Britain and Northern Ireland)

  • Fabbri Daniele

    (University of Bologna, Department of Economics, Via Zamboni, Bologna, Italy)

  • Monfardini Chiara

    (University of Bologna – Department of Economics, Piazza Scaravilli 2, Bologna 40126, Italy, Phone: 0039 051 2098148)

Abstract
We study a simple exogeneity test in count data models with possibly endogenous multinomial treatment. The test is based on Two Stage Residual Inclusion (2SRI), an estimation method which has been proved to be consistent for a general class of nonlinear parametric models. Results from a broad set of simulation experiments provide novel evidence on important features of this approach. We find differences in the finite sample performance of various likelihood-based tests, analyze their robustness to misspecification arising from neglected over-dispersion or from incorrect specification of the first stage model, and uncover that standardizing the variance of the first stage residuals leads to better results. An original application to testing the endogeneity status of insurance in a model of healthcare demand corroborates our Monte Carlo findings.

Suggested Citation

  • Geraci Andrea & Fabbri Daniele & Monfardini Chiara, 2018. "Testing Exogeneity of Multinomial Regressors in Count Data Models: Does Two-stage Residual Inclusion Work?," Journal of Econometric Methods, De Gruyter, vol. 7(1), pages 1-19, January.
    • Handle: RePEc:bpj:jecome:v:7:y:2018:i:1:p:19:n:1
    DOI: 10.1515/jem-2014-0019
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    1. Here's Your Reading List!
      by Dave Giles in Econometrics Beat: Dave Giles' Blog on 2014-12-02 00:12:00

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    More about this item

    Keywords

    count data; exogeneity test; healthcare utilization; multinomial endogenous treatment;
    All these keywords.

    JEL classification:

    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C31 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models; Quantile Regressions; Social Interaction Models
    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions
    • I11 - Health, Education, and Welfare - - Health - - - Analysis of Health Care Markets

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