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A note on the identification in two equations probit model with dummy endogenous regressor

Author

Listed:
  • Romuald Meango
  • Ismael Mourifie

Abstract

This paper deals with the question whether exclusion restrictions on the exogenous regressors are necessary to identify two equation probit models with endogenous dummy regressor. Contradictory opinions have been exposed in the literature on the necessity of an exclusion restriction. Wilde (2000) argued that an exclusion restriction is not necessary, and proposed a simple criterion for identi fication in this model. We contradict his result, and show how the inherent incompleteness of the model leads to failure of (point) identi cation. We provide an exact identification proof when an exclusion restriction is available.

Suggested Citation

  • Romuald Meango & Ismael Mourifie, 2013. "A note on the identification in two equations probit model with dummy endogenous regressor," Working Papers tecipa-503, University of Toronto, Department of Economics.
  • Handle: RePEc:tor:tecipa:tecipa-503
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    References listed on IDEAS

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    1. Juan Carlos Escanciano & Lin Zhu, 2013. "Set inferences and sensitivity analysis in semiparametric conditionally identified models," CeMMAP working papers 55/13, Institute for Fiscal Studies.
    2. Sartori, Anne E., 2003. "An Estimator for Some Binary-Outcome Selection Models Without Exclusion Restrictions," Political Analysis, Cambridge University Press, vol. 11(2), pages 111-138, April.
    3. Sukjin Han & Edward J. Vytlacil, 2013. "Identification in a Generalization of Bivariate Probit Models with Endogenous Regressors," Department of Economics Working Papers 130908, The University of Texas at Austin, Department of Economics.
    4. Heckman, James J, 1978. "Dummy Endogenous Variables in a Simultaneous Equation System," Econometrica, Econometric Society, vol. 46(4), pages 931-959, July.
    5. Wilde, Joachim, 2000. "Identification of multiple equation probit models with endogenous dummy regressors," Economics Letters, Elsevier, vol. 69(3), pages 309-312, December.
    Full references (including those not matched with items on IDEAS)

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    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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