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The asymptotic behaviour of the residual sum of squares in models with multiple break points


Hall, AR and Osborn, DR and Sakkas, N, The asymptotic behaviour of the residual sum of squares in models with multiple break points, Econometric Reviews, 36, (6-9) pp. 667-698. ISSN 0747-4938 (2017) [Refereed Article]


Copyright Statement

Copyright 2017 Alastair R. Hall, Denise R. Osborn, and Nikolaos Sakkas. Licensed under Creative Commons Attribution 4.0 International (CC BY 4.0)

DOI: doi:10.1080/07474938.2017.1307523


Models with multiple discrete breaks in parameters are usually estimated via least squares. This paper, first, derives the asymptotic expectation of the residual sum of squares and shows that the number of estimated break points and the number of regression parameters affect the expectation differently. Second, we propose a statistic for testing the joint hypothesis that the breaks occur at specified points in the sample. Our analytical results cover models estimated by the ordinary, nonlinear, and two-stage least squares. An application to U.S. monetary policy rejects the assumption that breaks are associated with changes in the chair of the Fed.

Item Details

Item Type:Refereed Article
Keywords:linear models, nonlinear models, ordinary least squares, parameter change, two-stage least squares, US monetary policy
Research Division:Economics
Research Group:Applied economics
Research Field:Macroeconomics (incl. monetary and fiscal theory)
Objective Division:Economic Framework
Objective Group:Other economic framework
Objective Field:Other economic framework not elsewhere classified
UTAS Author:Osborn, DR (Professor Denise Osborn)
ID Code:122326
Year Published:2017
Web of Science® Times Cited:1
Deposited By:TSBE
Deposited On:2017-11-09
Last Modified:2018-05-24
Downloads:110 View Download Statistics

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