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The asymptotically efficient version of the information matrix test in binary choice models. A study of size and power

  • Teresa Aparicio
  • Inmaculada Villanua
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    As Newey (1985) and Orme (1988) argue in the context of discrete binary choice models, the test of the information matrix (IM) is sensitive to heteroscedasticity and the incorrect distribution of the error term, with both these problems leading to inconsistency of the estimators obtained. This paper uses simulation experiments to analyse the size and power of the asymptotically efficient version of this test, with the aim of obtaining evidence on its capacity to detect such specification errors, considering different alternatives.

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    Article provided by Taylor & Francis Journals in its journal Journal of Applied Statistics.

    Volume (Year): 28 (2001)
    Issue (Month): 2 ()
    Pages: 167-182

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    Handle: RePEc:taf:japsta:v:28:y:2001:i:2:p:167-182
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    1. Klein, R.W. & Spady, R.H., 1991. "An Efficient Semiparametric Estimator for Binary Response Models," Papers 70, Bell Communications - Economic Research Group.
    2. Russell Davidson & James G. MacKinnon, 1982. "Convenient Specification Tests for Logit and Probit Models," Working Papers 514, Queen's University, Department of Economics.
    3. Lancaster, Tony, 1984. "The Covariance Matrix of the Information Matrix Test," Econometrica, Econometric Society, vol. 52(4), pages 1051-53, July.
    4. Skeels, C.L. & Vella, F., 1993. "The Robustness of Conditional Moment Tests in Tobit and Probit Models," Papers 252, Australian National University - Department of Economics.
    5. Orme, Chris, 1990. "The small-sample performance of the information-matrix test," Journal of Econometrics, Elsevier, vol. 46(3), pages 309-331, December.
    6. White, Halbert, 1982. "Maximum Likelihood Estimation of Misspecified Models," Econometrica, Econometric Society, vol. 50(1), pages 1-25, January.
    7. Peguin-Feissolle, A., 1999. "A Comparison of the Power of Some Tests for Conditional Heteroscedasticity," G.R.E.Q.A.M. 99a22, Universite Aix-Marseille III.
    8. Lechner, Michael, 1991. "Testing Logit Models in Practice," Empirical Economics, Springer, vol. 16(2), pages 177-98.
    9. Arabmazar, Abbas & Schmidt, Peter, 1982. "An Investigation of the Robustness of the Tobit Estimator to Non-Normality," Econometrica, Econometric Society, vol. 50(4), pages 1055-63, July.
    10. Newey, Whitney K, 1985. "Maximum Likelihood Specification Testing and Conditional Moment Tests," Econometrica, Econometric Society, vol. 53(5), pages 1047-70, September.
    11. Tauchen, George, 1985. "Diagnostic testing and evaluation of maximum likelihood models," Journal of Econometrics, Elsevier, vol. 30(1-2), pages 415-443.
    12. J. A. Hausman, 1976. "Specification Tests in Econometrics," Working papers 185, Massachusetts Institute of Technology (MIT), Department of Economics.
    13. Horowitz, Joel L., 1994. "Bootstrap-based critical values for the information matrix test," Journal of Econometrics, Elsevier, vol. 61(2), pages 395-411, April.
    14. Hurd, Michael, 1979. "Estimation in truncated samples when there is heteroscedasticity," Journal of Econometrics, Elsevier, vol. 11(2-3), pages 247-258.
    15. Horowitz, Joel L, 1992. "A Smoothed Maximum Score Estimator for the Binary Response Model," Econometrica, Econometric Society, vol. 60(3), pages 505-31, May.
    16. Orme, Christopher, 1988. "The Calculation of the Information Matrix Test for Binary Data Models," The Manchester School of Economic & Social Studies, University of Manchester, vol. 56(4), pages 370-76, December.
    17. Christopher Skeels & Franics Vella, 1997. "Monte carlo evidence on the robustness of conditional moment tests in tobit and probit models," Econometric Reviews, Taylor & Francis Journals, vol. 16(1), pages 69-92.
    18. Smith, Richard J, 1989. "On the Use of Distributional Mis-specification Checks in Limited Dependent Variable Models," Economic Journal, Royal Economic Society, vol. 99(395), pages 178-92, Supplemen.
    19. Yatchew, Adonis & Griliches, Zvi, 1985. "Specification Error in Probit Models," The Review of Economics and Statistics, MIT Press, vol. 67(1), pages 134-39, February.
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