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An Omnibus Test to Detect Time-Heterogeneity in Time Series

  • Dominique Guegan

    ()

    (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Paris I - Panthéon-Sorbonne, EEP-PSE - Ecole d'Économie de Paris - Paris School of Economics - Ecole d'Économie de Paris)

  • Philippe De Peretti

    ()

    (CES - Centre d'économie de la Sorbonne - CNRS : UMR8174 - Université Paris I - Panthéon-Sorbonne)

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).

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Paper provided by HAL in its series Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) with number halshs-00721327.

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Date of creation: 27 Jul 2012
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Handle: RePEc:hal:cesptp:halshs-00721327
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  1. BAI, Jushan & PERRON, Pierre, 1998. "Computation and Analysis of Multiple Structural-Change Models," Cahiers de recherche 9807, Universite de Montreal, Departement de sciences economiques.
  2. 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.
  3. Engle, Robert F & Smith, Aaron, 1998. "Stochastic Permanent Breaks," University of California at San Diego, Economics Working Paper Series qt99v0s0zx, Department of Economics, UC San Diego.
  4. Andrews, Donald W K, 1993. "Tests for Parameter Instability and Structural Change with Unknown Change Point," Econometrica, Econometric Society, vol. 61(4), pages 821-56, July.
  5. Diebold, Francis X. & Inoue, Atsushi, 2001. "Long memory and regime switching," Journal of Econometrics, Elsevier, vol. 105(1), pages 131-159, November.
  6. 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.
  7. 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.
  8. Catalin Starica & Clive Granger, 2004. "Non-stationarities in stock returns," Econometrics 0411016, EconWPA.
  9. Vinod, H. D., 2004. "Ranking mutual funds using unconventional utility theory and stochastic dominance," Journal of Empirical Finance, Elsevier, vol. 11(3), pages 353-377, June.
  10. Hamilton, James D., 1990. "Analysis of time series subject to changes in regime," Journal of Econometrics, Elsevier, vol. 45(1-2), pages 39-70.
  11. Donald W.K. Andrews & Inpyo Lee & Werner Ploberger, 1992. "Optimal Changepoint Tests for Normal Linear Regression," Cowles Foundation Discussion Papers 1016, Cowles Foundation for Research in Economics, Yale University.
  12. 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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