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Model selection criteria in multivariate models with multiple structural changes

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  • Kurozumi, Eiji
  • Tuvaandorj, Purevdorj

Abstract

This paper considers the issue of selecting the number of regressors and the number of structural breaks in multivariate regression models in the possible presence of multiple structural changes. We develop a modified Akaike information criterion (AIC), a modified Mallows' Cp criterion and a modified Bayesian information criterion (BIC). The penalty terms in these criteria are shown to be different from the usual terms. We prove that the modified BIC consistently selects the regressors and the number of breaks whereas the modified AIC and the modified Cp criterion tend to overfit with positive probability. The finite sample performance of these criteria is investigated through Monte Carlo simulations and it turns out that our modification is successful in comparison to the classical model selection criteria and the sequential testing procedure robust to heteroskedasticity and autocorrelation.

Suggested Citation

  • Kurozumi, Eiji & Tuvaandorj, Purevdorj, 2011. "Model selection criteria in multivariate models with multiple structural changes," Journal of Econometrics, Elsevier, vol. 164(2), pages 218-238, October.
  • Handle: RePEc:eee:econom:v:164:y:2011:i:2:p:218-238
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    References listed on IDEAS

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    9. Bai, Jushan, 1997. "Estimating Multiple Breaks One at a Time," Econometric Theory, Cambridge University Press, vol. 13(03), pages 315-352, June.
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    12. Jushan Bai & Pierre Perron, 2003. "Computation and analysis of multiple structural change models," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 1-22.
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    Cited by:

    1. Ibrahim Ahamada & Jose Luis Diaz Sanchez, 2013. "A Retrospective Analysis of the House Prices Macro-Relationship in the United States," International Journal of Central Banking, International Journal of Central Banking, vol. 9(4), pages 153-174, December.
    2. Pierre Perron & Tatsushi Oka, 2011. "Testing for Common Breaks in a Multiple Equations System," Boston University - Department of Economics - Working Papers Series WP2011-057, Boston University - Department of Economics.
    3. Eo, Yunjong & Morley, James C., 2008. "Likelihood-Based Confidence Sets for the Timing of Structural Breaks," MPRA Paper 10372, University Library of Munich, Germany.
    4. Harris, David & Leybourne, Stephen J. & Taylor, A.M. Robert, 2016. "Tests of the co-integration rank in VAR models in the presence of a possible break in trend at an unknown point," Journal of Econometrics, Elsevier, vol. 192(2), pages 451-467.
    5. Nakaota, Hiroshi & Fukuta, Yuichi, 2013. "The leading indicator property of the term spread and the monetary policy factors in Japan," Japan and the World Economy, Elsevier, vol. 28(C), pages 85-98.
    6. Hiroshi Nakaota & Yuichi Fukuta, 2013. "The Leading Indicator Property of the Term Spread and the Monetary Policy Factors in Japan," Discussion Papers in Economics and Business 13-09-Rev, Osaka University, Graduate School of Economics and Osaka School of International Public Policy (OSIPP).
    7. Yunjong Eo & James Morley, 2015. "Likelihood‐ratio‐based confidence sets for the timing of structural breaks," Quantitative Economics, Econometric Society, vol. 6(2), pages 463-497, July.
    8. Mutl, Jan & Sögner, Leopold, 2013. "Parameter Estimation and Inference with Spatial Lags and Cointegration," Economics Series 296, Institute for Advanced Studies.
    9. KUROZUMI, Eiji, 2016. "Monitoring Parameter Constancy with Endogenous Regressors," Discussion Papers 2016-01, Graduate School of Economics, Hitotsubashi University.
    10. Hiroshi Nakaota & Yuichi Fukuta, 2013. "The Leading Indicator Property of the Term Spread and the Monetary Policy Factors in Japan," Discussion Papers in Economics and Business 13-09, Osaka University, Graduate School of Economics and Osaka School of International Public Policy (OSIPP), revised Jul 2013.

    More about this item

    Keywords

    Structural breaks AIC Mallows' Cp BIC Information criteria;

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C32 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes; State Space Models

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