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Consistent covariance matrix estimation in probit models with autocorrelated errors

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  • Arturo Estrella
  • Anthony P. Rodrigues

Abstract

Some recent time-series applications use probit models to measure the forecasting power of a set of variables. Correct inferences about the significance of the variables requires a consistent estimator of the covariance matrix of the estimated model coefficients. A potential source of inconsistency in maximum likelihood standard errors is serial correlation in the underlying disturbances, which may arise, for example, from overlapping forecasts. We discuss several practical methods for constructing probit autocorrelation-consistent standard errors, drawing on the generalized method of moments techniques of Hansen (1982), Newey-West (1987) and others, and we provide simulation evidence that these methods can work well.

Suggested Citation

  • Arturo Estrella & Anthony P. Rodrigues, 1998. "Consistent covariance matrix estimation in probit models with autocorrelated errors," Staff Reports 39, Federal Reserve Bank of New York.
  • Handle: RePEc:fip:fednsr:39
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    References listed on IDEAS

    as
    1. Hansen, Lars Peter, 1982. "Large Sample Properties of Generalized Method of Moments Estimators," Econometrica, Econometric Society, vol. 50(4), pages 1029-1054, July.
    2. Avery, Robert B & Hansen, Lars Peter & Hotz, V Joseph, 1983. "Multiperiod Probit Models and Orthogonality Condition Estimation," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 24(1), pages 21-35, February.
    3. Bernard, Henri & Gerlach, Stefan, 1998. "Does the Term Structure Predict Recessions? The International Evidence," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 3(3), pages 195-215, July.
    4. Arturo Estrella & Frederic S. Mishkin, 1998. "Predicting U.S. Recessions: Financial Variables As Leading Indicators," The Review of Economics and Statistics, MIT Press, vol. 80(1), pages 45-61, February.
    5. Dale J. Poirier & Paul A. Ruud, 1988. "Probit with Dependent Observations," Review of Economic Studies, Oxford University Press, vol. 55(4), pages 593-614.
    6. Andrews, Donald W K, 1991. "Heteroskedasticity and Autocorrelation Consistent Covariance Matrix Estimation," Econometrica, Econometric Society, vol. 59(3), pages 817-858, May.
    7. Amemiya, Takeshi, 1981. "Qualitative Response Models: A Survey," Journal of Economic Literature, American Economic Association, vol. 19(4), pages 1483-1536, December.
    8. Eichengreen, Barry & Watson, Mark W & Grossman, Richard S, 1985. "Bank Rate Policy under the Interwar Gold Standard: A Dynamic Probit Model," Economic Journal, Royal Economic Society, vol. 95(379), pages 725-745, September.
    9. Estrella, Arturo & Hardouvelis, Gikas A, 1991. " The Term Structure as a Predictor of Real Economic Activity," Journal of Finance, American Finance Association, vol. 46(2), pages 555-576, June.
    10. James H. Stock & Mark W. Watson, 1988. "A Probability Model of The Coincident Economic Indicators," NBER Working Papers 2772, National Bureau of Economic Research, Inc.
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    Citations

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    Cited by:

    1. Esther Fernández Galar & Javier Gómez Biscarri, 2003. "Revisiting the Ability of Interest Rate Spreads to Predict Recessions: Evidence for a," Faculty Working Papers 04/03, School of Economics and Business Administration, University of Navarra.
    2. Dieter Gerdesmeier & Hans‐Eggert Reimers & Barbara Roffia, 2010. "Asset Price Misalignments and the Role of Money and Credit," International Finance, Wiley Blackwell, vol. 13(3), pages 377-407, Winter.
    3. António R. Antunes & Diana Bonfim & Nuno Monteiro & Paulo M.M. Rodrigues, 2016. "Forecasting banking crises with dynamic panel probit models," Working Papers w201613, Banco de Portugal, Economics and Research Department.
    4. Franck Sédillot, 2001. "La pente des taux contient-elle de l'information sur l'activité économique future ?," Economie & Prévision, La Documentation Française, vol. 147(1), pages 141-157.
    5. Javier Gomez-Biscarri, 2009. "The predictive power of the term spread revisited: a change in the sign of the predictive relationship," Applied Financial Economics, Taylor & Francis Journals, vol. 19(14), pages 1131-1142.
    6. Pons Novell, J., 2002. "Ciclo de la economía española y contenido informativo de los tipos de interés," Estudios de Economía Aplicada, Estudios de Economía Aplicada, vol. 20, pages 583-598, Diciembre.
    7. Gomez-Biscarri, Javier, 2008. "Changes in the informational content of term spreads: Is monetary policy becoming less effective?," Journal of Economics and Business, Elsevier, vol. 60(5), pages 415-435.
    8. Shang-Wu Yu & Shang-Wu Yu, 1999. "Estimation of the probit model with autocorrelated errors via the MCECM algorithm," Applied Economics Letters, Taylor & Francis Journals, vol. 6(7), pages 409-412.
    9. Arturo Estrella & Anthony P. Rodrigues & Sebastian Schich, 2003. "How Stable is the Predictive Power of the Yield Curve? Evidence from Germany and the United States," The Review of Economics and Statistics, MIT Press, vol. 85(3), pages 629-644, August.
    10. Andrew Berg & Rebecca N. Coke, 2004. "Autocorrelation-Corrected Standard Errors in Panel Probits; An Application to Currency Crisis Prediction," IMF Working Papers 04/39, International Monetary Fund.
    11. Cipollini, Andrea & Fiordelisi, Franco, 2012. "Economic value, competition and financial distress in the European banking system," Journal of Banking & Finance, Elsevier, vol. 36(11), pages 3101-3109.
    12. Grossman, Richard S., 2007. "Fear and greed: The evolution of double liability in American banking, 1865-1930," Explorations in Economic History, Elsevier, vol. 44(1), pages 59-80, January.
    13. Dieter Gerdesmeier & Hans-Eggert Reimers & Barbara Roffia, 2011. "Early Warning Indicators for Asset Price Booms," Review of Economics & Finance, Better Advances Press, Canada, vol. 1, pages 1-19, June.
    14. repec:ove:journl:aid:12012 is not listed on IDEAS
    15. repec:eee:intfor:v:34:y:2018:i:2:p:249-275 is not listed on IDEAS
    16. Jonathan H. Wright, 2006. "The yield curve and predicting recessions," Finance and Economics Discussion Series 2006-07, Board of Governors of the Federal Reserve System (U.S.).
    17. Javier Gómez, 2007. "Changes in the Informational Content of the Spread: Is Monetary Policy Becoming Less Effective?," Faculty Working Papers 05/07, School of Economics and Business Administration, University of Navarra.
    18. Michael J. Dueker & Katrin Wesche, 2001. "European business cycles: new indices and analysis of their synchronicity," Working Papers 1999-019, Federal Reserve Bank of St. Louis.
    19. Chauvet, Marcelle & Potter, Simon, 2002. "Predicting a recession: evidence from the yield curve in the presence of structural breaks," Economics Letters, Elsevier, vol. 77(2), pages 245-253, October.
    20. Gnabo, Jean-Yves & Laurent, Sébastien & Lecourt, Christelle, 2009. "Does transparency in central bank intervention policy bring noise to the FX market?: The case of the Bank of Japan," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 19(1), pages 94-111, February.
    21. M. Dueker & K. Wesche, 1999. "European Business Cycles: New Indices and Analysis of their Synchronicity," Discussion Paper Serie B 448, University of Bonn, Germany.
    22. Omay, Tolga, 2008. "The Term Structure of Interest Rate as a Predictor of Inflation and Real Economic Activity: Nonlinear Evidence from Turkey," MPRA Paper 28572, University Library of Munich, Germany.
    23. Karnizova, Lilia & Li, Jiaxiong (Chris), 2014. "Economic policy uncertainty, financial markets and probability of US recessions," Economics Letters, Elsevier, vol. 125(2), pages 261-265.
    24. Chan, Felix & Pauwels, Laurent L. & Wongsosaputro, Johnathan, 2013. "The impact of serial correlation on testing for structural change in binary choice model: Monte Carlo evidence," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 93(C), pages 175-189.
    25. Gerlach, Stefan, 1999. "Who targets inflation explicitly?," European Economic Review, Elsevier, vol. 43(7), pages 1257-1277, June.

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    Time-series analysis ; Regression analysis;

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