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Testing exogeneity of multinomial regressors in count data models: does two stage residual inclusion work?

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  • A. Geraci
  • D. Fabbri
  • C. Monfardini

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). Results from a broad Monte Carlo study provide novel evidence on important features of this approach in nonlinear settings. We find differences in the finite sample performance of various likelihood-based tests under correct specification and when the outcome equation is misspecified due to neglected over-dispersion or non-linearity. We compare alternative 2SRI procedures and uncover that standardizing the variance of the first stage residuals leads to higher power of the test and reduces the bias of the treatment coefficients. An original application in health economics corroborates our findings.

Suggested Citation

  • A. Geraci & D. Fabbri & C. Monfardini, 2014. "Testing exogeneity of multinomial regressors in count data models: does two stage residual inclusion work?," Working Papers wp921, Dipartimento Scienze Economiche, Universita' di Bologna.
  • Handle: RePEc:bol:bodewp:wp921
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      by Dave Giles in Econometrics Beat: Dave Giles' Blog on 2014-12-02 00:12:00

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    More about this item

    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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