The asymptotic behaviour of the residual sum of squares in models with multiple break points |
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Authors: | Alastair R. Hall Denise R. Osborn Nikolaos Sakkas |
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Affiliation: | 1. Economics, School of Social Sciences, University of Manchester, Manchester, UKalastair.hall@manchester.ac.uk;3. Economics, School of Social Sciences, University of Manchester, Manchester, UK;4. Tasmanian School of Business and Economics, University of Tasmania, Hobart, Australia;5. Department of Economics, University of Bath, Bath, England |
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Abstract: | ABSTRACTModels 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. |
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Keywords: | Linear models nonlinear models ordinary least squares parameter change two-stage least squares US monetary policy |
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