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A note on the different interpretation of the correlation parameters in the Bivariate Probit and the Recursive Bivariate Probit

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  • Filippini, Massimo
  • Greene, William H.
  • Kumar, Nilkanth
  • Martinez-Cruz, Adan L.

Abstract

This note shows that, if a Bivariate Probit (BP) model is estimated on data arising from a Recursive Bivariate Probit (RBP) process, the resulting BP correlation parameter is a weighted average of the RBP correlation parameter and the parameter associated to the endogenous binary variable. Two corollaries follow this proposition: i) the interpretation of the correlation parameter in the RBP is not the same as in the BP —i.e. the RBP correlation parameter does not necessarily reflect the correlation between the binary variables under study; and ii) a zero correlation parameter in a BP model, usually interpreted as evidence of independence between the binary variables under study, may actually mask the presence of an RBP process.

Suggested Citation

  • Filippini, Massimo & Greene, William H. & Kumar, Nilkanth & Martinez-Cruz, Adan L., 2018. "A note on the different interpretation of the correlation parameters in the Bivariate Probit and the Recursive Bivariate Probit," Economics Letters, Elsevier, vol. 167(C), pages 104-107.
  • Handle: RePEc:eee:ecolet:v:167:y:2018:i:c:p:104-107
    DOI: 10.1016/j.econlet.2018.03.018
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    More about this item

    Keywords

    Bivariate probit; Recursive Bivariate probit; Tetrachoric correlation; Monte Carlo simulation;
    All these keywords.

    JEL classification:

    • C35 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions

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