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Score Tests of Normality in Bivariate Probit Models

Author

Listed:
  • Anthony Murphy

    (Nuffield College, Oxford)

Abstract

A relatively simple and convenient score test of normality in the bivariate probit model is derived. Monte Carlo simulations show that the small sample performance of the bootstrapped test is quite good. The test may be readily extended to testing normality in related models.

Suggested Citation

  • Anthony Murphy, 2005. "Score Tests of Normality in Bivariate Probit Models," Econometrics 0512004, University Library of Munich, Germany.
  • Handle: RePEc:wpa:wuwpem:0512004
    Note: Type of Document - pdf; pages: 10
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    File URL: https://econwpa.ub.uni-muenchen.de/econ-wp/em/papers/0512/0512004.pdf
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    References listed on IDEAS

    as
    1. Horowitz, Joel L., 1994. "Bootstrap-based critical values for the information matrix test," Journal of Econometrics, Elsevier, vol. 61(2), pages 395-411, April.
    2. J. S. Butler & Patrali Chatterjee, 1997. "Tests of the Specification of Univariate and Bivariate Ordered Probit," The Review of Economics and Statistics, MIT Press, vol. 79(2), pages 343-347, May.
    3. Lee, Lung-Fei, 1983. "Generalized Econometric Models with Selectivity," Econometrica, Econometric Society, vol. 51(2), pages 507-512, March.
    4. Lee, Lung-Fei, 1984. "Tests for the Bivariate Normal Distribution in Econometric Models with Selectivity," Econometrica, Econometric Society, vol. 52(4), pages 843-863, July.
    5. Pagan, Adrian & Vella, Frank, 1989. "Diagnostic Tests for Models Based on Individual Data: A Survey," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 4(S), pages 29-59, Supplemen.
    Full references (including those not matched with items on IDEAS)

    More about this item

    Keywords

    Score test; bivariate probit; normality; Gram-Charlier series;

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities

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