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An Omnibus Test to Detect Time-Heterogeneity in Time Series

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  • Dominique Guegan

    () (PSE - Paris School of Economics, CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

  • Philippe De Peretti

    () (CES - Centre d'économie de la Sorbonne - UP1 - Université Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

Abstract

In this paper, we present a procedure that tests for the null of time-homogeneity of the first two moments of a time-series. Whereas the literature dedicated to structural breaks testing procedures often focuses on one kind of alternative, i.e. discrete shifts or smooth transition, our procedure is designed to deal with a broader alternative including i) discrete shifts, ii) smooth transition, iii) time-varying moments, iv) probability-driven breaks, v) GARCH or Stochastic Volatility Models for the variance. Our test uses the recently introduced maximum entropy bootstrap, designed to capture both time-dependency and time-heterogeneity. Running simulations, our procedure appears to be quite powerful. To some extent, our paper is an extension of Heracleous, Koutris and Spanos (2008).

Suggested Citation

  • Dominique Guegan & Philippe De Peretti, 2012. "An Omnibus Test to Detect Time-Heterogeneity in Time Series," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-00721327, HAL.
  • Handle: RePEc:hal:cesptp:halshs-00721327 Note: View the original document on HAL open archive server: https://halshs.archives-ouvertes.fr/halshs-00721327
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    References listed on IDEAS

    as
    1. Lanouar Charfeddine & Dominique Guégan, 2007. "Which is the best model for the US inflation rate : a structural changes model or a long memory," Documents de travail du Centre d'Economie de la Sorbonne b07061, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    2. Andrews, Donald W. K. & Lee, Inpyo & Ploberger, Werner, 1996. "Optimal changepoint tests for normal linear regression," Journal of Econometrics, Elsevier, vol. 70(1), pages 9-38, January.
    3. Robert F. Engle & Aaron D. Smith, 1999. "Stochastic Permanent Breaks," The Review of Economics and Statistics, MIT Press, vol. 81(4), pages 553-574, November.
    4. Diebold, Francis X. & Inoue, Atsushi, 2001. "Long memory and regime switching," Journal of Econometrics, Elsevier, vol. 105(1), pages 131-159, November.
    5. Cătălin Stărică & Clive Granger, 2005. "Nonstationarities in Stock Returns," The Review of Economics and Statistics, MIT Press, pages 503-522.
    6. Perron, Pierre, 1989. "The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis," Econometrica, Econometric Society, vol. 57(6), pages 1361-1401, November.
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    9. Bai, Jushan, 1999. "Likelihood ratio tests for multiple structural changes," Journal of Econometrics, Elsevier, vol. 91(2), pages 299-323, August.
    10. Charfeddine Lanouar & Guégan Dominique, 2011. "Which is the Best Model for the US Inflation Rate: A Structural Change Model or a Long Memory Process?," The IUP Journal of Applied Economics, IUP Publications, vol. 0(1), pages 5-25, January.
    11. Hansen, Bruce E., 2000. "Testing for structural change in conditional models," Journal of Econometrics, Elsevier, vol. 97(1), pages 93-115, July.
    12. Spanos,Aris, 1999. "Probability Theory and Statistical Inference," Cambridge Books, Cambridge University Press, number 9780521424080, March.
    13. 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.
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    17. Andreas Koutris & Maria Heracleous & Aris Spanos, 2008. "Testing for Nonstationarity Using Maximum Entropy Resampling: A Misspecification Testing Perspective," Econometric Reviews, Taylor & Francis Journals, vol. 27(4-6), pages 363-384.
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    More about this item

    Keywords

    Time-homogeneity; maximum entropy bootstrap; Test; homogénéité temporelle; ré-échantillonnage; maximum d'entropie;

    JEL classification:

    • C01 - Mathematical and Quantitative Methods - - General - - - Econometrics
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C15 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Statistical Simulation Methods: General

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