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2018 | OriginalPaper | Chapter

Structural Change in (Economic) Time Series

Author : Christian Kleiber

Published in: Complexity and Synergetics

Publisher: Springer International Publishing

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Abstract

Methods for detecting structural changes, or change points, in time series data are widely used in many fields of science and engineering. This chapter sketches some basic methods for the analysis of structural changes in time series data. The exposition is confined to retrospective methods for univariate time series. Several recent methods for dating structural changes are compared using a time series of oil prices spanning more than 60 years. The methods broadly agree for the first part of the series up to the mid-1980s, for which changes are associated with major historical events, but provide somewhat different solutions thereafter, reflecting a gradual increase in oil prices that is not well described by a step function. As a further illustration, 1990s data on the volatility of the Hang Seng stock market index are reanalyzed.

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Literature
1.
go back to reference M. Kelly, C. O’Grada, Change points and temporal dependence in reconstructions of annual temperature: did Europe experience a little Ice Age? Ann. Appl. Stat. 8, 1372–1394 (2014) M. Kelly, C. O’Grada, Change points and temporal dependence in reconstructions of annual temperature: did Europe experience a little Ice Age? Ann. Appl. Stat. 8, 1372–1394 (2014)
2.
go back to reference P. Hackl, A. Westlund, Statistical analysis of “structural change”: an annotated bibliography. Empir. Econ. 14, 167–192 (1989)CrossRef P. Hackl, A. Westlund, Statistical analysis of “structural change”: an annotated bibliography. Empir. Econ. 14, 167–192 (1989)CrossRef
3.
go back to reference A. Zeileis, F. Leisch, K. Hornik, C. Kleiber, strucchange: An R package for testing for structural change in linear regression models. J. Stat. Softw. 7, 1–38 (2002) A. Zeileis, F. Leisch, K. Hornik, C. Kleiber, strucchange: An R package for testing for structural change in linear regression models. J. Stat. Softw. 7, 1–38 (2002)
4.
go back to reference P. Perron, Dealing with structural breaks, in Palgrave Handbook of Econometrics: Volume 1: Econometric Theory, ed. by K. Patterson, T.C. Mills (Palgrave Macmillan, London, 2006), pp. 278–352 P. Perron, Dealing with structural breaks, in Palgrave Handbook of Econometrics: Volume 1: Econometric Theory, ed. by K. Patterson, T.C. Mills (Palgrave Macmillan, London, 2006), pp. 278–352
7.
go back to reference M. Csörgő, L. Horváth, Limit Theorems in Change-Point Analysis (Wiley, Hoboken, NJ, 1997) M. Csörgő, L. Horváth, Limit Theorems in Change-Point Analysis (Wiley, Hoboken, NJ, 1997)
8.
go back to reference E. Andreou, E. Ghysels, Detecting multiple breaks in financial market volatility dynamics. J. Appl. Econ. 17, 579–600 (2002)CrossRef E. Andreou, E. Ghysels, Detecting multiple breaks in financial market volatility dynamics. J. Appl. Econ. 17, 579–600 (2002)CrossRef
9.
go back to reference R.L. Brown, J. Durbin, J.M. Evans, Techniques for testing the constancy of regression relationships over time. J. R. Stat. Soc. Ser. B 37, 149–163 (1975) R.L. Brown, J. Durbin, J.M. Evans, Techniques for testing the constancy of regression relationships over time. J. R. Stat. Soc. Ser. B 37, 149–163 (1975)
11.
go back to reference R Core Team, R : A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, Vienna, 2016) R Core Team, R : A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, Vienna, 2016)
13.
go back to reference A. Zeileis, A unified approach to structural change tests based on ML scores, \(F\) statistics, and OLS residuals. Economet. Rev. 24, 445–466 (2005)CrossRefMATHMathSciNet A. Zeileis, A unified approach to structural change tests based on ML scores, \(F\) statistics, and OLS residuals. Economet. Rev. 24, 445–466 (2005)CrossRefMATHMathSciNet
14.
15.
go back to reference J. Bai, P. Perron, Computation and analysis of multiple structural change models. J. Appl. Econ. 18, 1–22 (2003)CrossRef J. Bai, P. Perron, Computation and analysis of multiple structural change models. J. Appl. Econ. 18, 1–22 (2003)CrossRef
17.
go back to reference A. Zeileis, C. Kleiber, W. Krämer, K. Hornik, Testing and dating of structural changes in practice. Comput. Stat. Data An. 44, 109–123 (2003)CrossRefMATHMathSciNet A. Zeileis, C. Kleiber, W. Krämer, K. Hornik, Testing and dating of structural changes in practice. Comput. Stat. Data An. 44, 109–123 (2003)CrossRefMATHMathSciNet
18.
go back to reference D.S. Matteson, N.A. James, A nonparametric approach for multiple change point analysis of multivariate data. J. Am. Stat. Assoc. 109, 334–345 (2014)CrossRefMATHMathSciNet D.S. Matteson, N.A. James, A nonparametric approach for multiple change point analysis of multivariate data. J. Am. Stat. Assoc. 109, 334–345 (2014)CrossRefMATHMathSciNet
19.
go back to reference M.L. Rizzo, G.J. Székely, DISCO analysis: a nonparametric extension of analysis of variance. Ann. Appl. Stat. 4, 1034–1055 (2010)CrossRefMATHMathSciNet M.L. Rizzo, G.J. Székely, DISCO analysis: a nonparametric extension of analysis of variance. Ann. Appl. Stat. 4, 1034–1055 (2010)CrossRefMATHMathSciNet
20.
go back to reference N.A. James, D.S. Matteson, ecp: An R package for nonparametric multiple change point analysis of multivariate data. J. Stat. Softw. 62, 1–25 (2014) N.A. James, D.S. Matteson, ecp: An R package for nonparametric multiple change point analysis of multivariate data. J. Stat. Softw. 62, 1–25 (2014)
22.
23.
go back to reference A.N. Shiryaev, Quickest detection problems in the technical analysis of financial data, in Mathematical Finance—Bachelier Congress 2000, Paris, June 29–July 1, 2000, ed. by H. Geman, D. Madan, S. Pliska, T. Vorst (Springer, Heidelberg, 2002), pp. 487–521 A.N. Shiryaev, Quickest detection problems in the technical analysis of financial data, in Mathematical Finance—Bachelier Congress 2000, Paris, June 29–July 1, 2000, ed. by H. Geman, D. Madan, S. Pliska, T. Vorst (Springer, Heidelberg, 2002), pp. 487–521
24.
Metadata
Title
Structural Change in (Economic) Time Series
Author
Christian Kleiber
Copyright Year
2018
DOI
https://doi.org/10.1007/978-3-319-64334-2_21