The Asymptotic Behaviour of the Residual Sum of Squares in Models with Multiple Break Points

Alastair Hall, Denise Osborn, Nikolaos Sakkas

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Abstract

Models with multiple discrete breaks in parameters are usually estimated via least squares. This paper, firstly, 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. Secondly, 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 Ordinary, Nonlinear and Two Stage Least Squares. An application to US monetary policy rejects the assumption that breaks are associated with changes in the chair of the Fed.
Original languageEnglish
JournalEconometric Reviews
Volume36
Issue number6-9
Early online date5 Apr 2017
DOIs
Publication statusPublished - 2017

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