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Computation and analysis of multiple structural change models

Jushan Bai () and Pierre Perron ()

Journal of Applied Econometrics, 2003, vol. 18, issue 1, 1-22

Abstract: In a recent paper, Bai and Perron (1998) considered theoretical issues related to the limiting distribution of estimators and test statistics in the linear model with multiple structural changes. In this companion paper, we consider practical issues for the empirical applications of the procedures. We first address the problem of estimation of the break dates and present an efficient algorithm to obtain global minimizers of the sum of squared residuals. This algorithm is based on the principle of dynamic programming and requires at most least-squares operations of order O(T 2 ) for any number of breaks. Our method can be applied to both pure and partial structural change models. Second, we consider the problem of forming confidence intervals for the break dates under various hypotheses about the structure of the data and the errors across segments. Third, we address the issue of testing for structural changes under very general conditions on the data and the errors. Fourth, we address the issue of estimating the number of breaks. Finally, a few empirical applications are presented to illustrate the usefulness of the procedures. All methods discussed are implemented in a GAUSS program. Copyright © 2002 John Wiley & Sons, Ltd.

Date: 2003
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http://hdl.handle.net/10.1002/jae.659 Link to full text; subscription required (text/html)
http://qed.econ.queensu.ca:80/jae/2003-v18.1/ Supporting data files and programs (text/html)

Related works:
Working Paper: Computation and Analysis of Multiple Structural-Change Models (1998) Downloads
Software Item: BAIPERRON: RATS procedure to perform Bai-Perron Test for Multiple Structural Changes Downloads
Software Item: MULTIPLEBREAKS: RATS procedure to perform multiple structural change analysis Downloads
Software Item: RATS programs to replicate examples of Bai-Perron procedure Downloads
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