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Predictive Tests for Structural Change with Unknown Breakpoint

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  • Ghysels, E.
  • Guay, A.
  • Hall, A.

Abstract

This paper considers predictive tests for structural change in models estimated via Generalized Method of Moments. Our analysis extends earlier work by Ghysels and Hall (1990a) by allowing for the instability to occur at an unknown point in the sample. We analyze various statistics based on continuous mappings of the sequence of predictive tests calculated for a set of possible breakpoints in the sample. The limiting distribution of these statistics is derived under both the null hypothesis and local alternatives. Percentiles are reported for the distribution under the null. A side product of our analysis is that we can illuminate the power properties of the predictive test and also compare its properties to those of the Wald, LR and LM tests for parameter variation. We study those power properties both via local asymptotic analysis and Monte Carlo. Cette étude généralise la procédure proposée par Ghysels et Hall (1990a) pour tester le changement structurel pour des modèles estimés par la méthode de moments généralisée. Nous ne supposons plus le point de rupture comme étant connu et proposons plusieurs statistiques prédictives avec changement structurel inconnu. Comme les distributions asymptotiques sont non standard, nous fournissons les valeurs critiques. Finalement, nous étudions la puissance des tests et faisons des comparaisons avec des tests du type Wald, LM et LR.
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Suggested Citation

  • Ghysels, E. & Guay, A. & Hall, A., 1995. "Predictive Tests for Structural Change with Unknown Breakpoint," Cahiers de recherche 9524, Universite de Montreal, Departement de sciences economiques.
  • Handle: RePEc:mtl:montde:9524
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    File URL: http://hdl.handle.net/1866/2073
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    References listed on IDEAS

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    1. Ghysels, Eric & Hall, Alastair, 1990. "A Test for Structural Stability of Euler Conditions Parameters Estimated via the Generalized Method of Moments Estimator," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 31(2), pages 355-364, May.
    2. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    3. Sowell, Fallaw, 1996. "Optimal Tests for Parameter Instability in the Generalized Method of Moments Framework," Econometrica, Econometric Society, vol. 64(5), pages 1085-1107, September.
    4. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-856, July.
    5. Andrews, Donald W K & Monahan, J Christopher, 1992. "An Improved Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimator," Econometrica, Econometric Society, vol. 60(4), pages 953-966, July.
    6. Epstein, Larry G & Zin, Stanley E, 1991. "Substitution, Risk Aversion, and the Temporal Behavior of Consumption and Asset Returns: An Empirical Analysis," Journal of Political Economy, University of Chicago Press, vol. 99(2), pages 263-286, April.
    7. Andrews, Donald W K & Ploberger, Werner, 1994. "Optimal Tests When a Nuisance Parameter Is Present Only under the Alternative," Econometrica, Econometric Society, vol. 62(6), pages 1383-1414, November.
    8. Kramer, Walter & Ploberger, Werner & Alt, Raimund, 1988. "Testing for Structural Change in Dynamic Models," Econometrica, Econometric Society, vol. 56(6), pages 1355-1369, November.
    9. Ghysels, Eric & Hall, Alastair, 1990. "Are consumption-based intertemporal capital asset pricing models structural?," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 121-139.
    10. Newey, Whitney & West, Kenneth, 2014. "A simple, positive semi-definite, heteroscedasticity and autocorrelation consistent covariance matrix," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 33(1), pages 125-132.
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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
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection

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