An omnibus test to detect time-heterogeneity in time series
AbstractThis paper focuses on a procedure to test for structural changes in the first two moments of a time series, when no information about the process driving the breaks is available. We model the series as a finite-order auto-regressive process plus an orthogonal Bernstein polynomial to capture heterogeneity. Testing for the null of time-invariance is then achieved by testing the order of the polynomial, using either an information criterion, or a restriction test. The procedure is an omnibus test in the sense that it covers both the pure discrete structural changes and some continuous changes models. To some extent, our paper can be seen as an extension of Heracleous et al. (Econom Rev 27:363–384, 2008).
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Bibliographic InfoPaper provided by Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne in its series Documents de travail du Centre d'Economie de la Sorbonne with number 10098.
Length: 24 pages
Date of creation: Dec 2010
Date of revision:
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Structural changes; Bernstein polynomial; Time-homogeneity.;
Other versions of this item:
- Dominique Guégan & Philippe Peretti, 2013. "An omnibus test to detect time-heterogeneity in time series," Computational Statistics, Springer, vol. 28(3), pages 1225-1239, June.
- 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
This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-01-03 (All new papers)
- NEP-ECM-2011-01-03 (Econometrics)
- NEP-ETS-2011-01-03 (Econometric Time Series)
- NEP-ORE-2011-01-03 (Operations Research)
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Catalin Starica & Clive Granger, 2004.
"Non-stationarities in stock returns,"
- 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.
- Bai, Jushan, 1999. "Likelihood ratio tests for multiple structural changes," Journal of Econometrics, Elsevier, vol. 91(2), pages 299-323, August.
- Perron, Pierre, 1989.
"The Great Crash, the Oil Price Shock, and the Unit Root Hypothesis,"
Econometric Society, vol. 57(6), pages 1361-1401, November.
- Perron, P, 1988. "The Great Crash, The Oil Price Shock And The Unit Root Hypothesis," Papers 338, Princeton, Department of Economics - Econometric Research Program.
- Hansen, Bruce E., 2000.
"Testing for structural change in conditional models,"
Journal of Econometrics,
Elsevier, vol. 97(1), pages 93-115, July.
- Tom Doan, . "RATS programs to replicate structural break test with Hansen's fixed regressor bootstrap," Statistical Software Components RTZ00089, Boston College Department of Economics.
- Bruce E. Hansen, 1998. "Testing for Structural Change in Conditional Models," Boston College Working Papers in Economics 310., Boston College Department of Economics.
- Tom Doan, . "REGHBREAK: RATS procedure to perform structural break test with bootstrapped p-values," Statistical Software Components RTS00176, Boston College Department of Economics.
- Altissimo, Filippo & Corradi, Valentina, 2003. "Strong rules for detecting the number of breaks in a time series," Journal of Econometrics, Elsevier, vol. 117(2), pages 207-244, December.
- BAI, Jushan & PERRON, Pierre, 1998.
"Computation and Analysis of Multiple Structural-Change Models,"
Cahiers de recherche
9807, Universite de Montreal, Departement de sciences economiques.
- 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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