Optimally Testing General Breaking Processes in Linear Time Series Models

UCSD Economics Working Paper No. 2003-07

57 Pages Posted: 16 Jul 2003

See all articles by Graham Elliott

Graham Elliott

University of California, San Diego (UCSD) - Department of Economics

Ulrich K. Müller

Princeton University - Department of Economics

Date Written: April 2003

Abstract

There are a large number of tests for instability or breaks in coefficients in regression models designed for different possible departures from a stable regression. We make two contributions to this literature. First, we provide conditions under which optimal tests are asymptotically equivalent. Our conditions allow for models with many or relatively few breaks, clustered breaks, regularly occurring breaks or smooth transitions to changes in the regression coefficients. Thus we show nothing is gained asymptotically by knowing the exact breaking process. Second, we provide a statistic that is simple to compute, avoids any need for searching over high dimensions when there are many breaks, is valid for a wide range of data generating processes and has high power for many alternative models.

Keywords: Optimal Tests, Parameters Instability, Breaks Tests

JEL Classification: C12, C22

Suggested Citation

Elliott, Graham and Müller, Ulrich K., Optimally Testing General Breaking Processes in Linear Time Series Models (April 2003). UCSD Economics Working Paper No. 2003-07, Available at SSRN: https://ssrn.com/abstract=410927 or http://dx.doi.org/10.2139/ssrn.410927

Graham Elliott (Contact Author)

University of California, San Diego (UCSD) - Department of Economics ( email )

9500 Gilman Drive
La Jolla, CA 92093-0508
United States
858-534-4481 (Phone)
858-534-7040 (Fax)

Ulrich K. Müller

Princeton University - Department of Economics ( email )

Princeton, NJ 08544-1021
United States
609-258-3216 (Phone)
609-258-4026 (Fax)

HOME PAGE: http://www.princeton.edu/~umueller

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