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Structural-break models under mis-specification: Implications for forecasting

Cited 4 time in Web of Science Cited 6 time in Scopus
Authors
Koo, Bonsoo; Seo, Myung Hwan
Issue Date
2015
Publisher
Elsevier
Citation
Journal of Econometrics, vol.188, pp. 166–181
Keywords
Structural breakForecastingMis-specificationCube-root asymptotics
Abstract
This paper revisits the least squares estimator of the linear regression with a structural break. We view
the model as an approximation to the true data generating process whose exact nature is unknown
but perhaps changing over time either continuously or with some jumps. This view is widely held in
the forecasting literature and under this view, the time series dependence property of all the observed
variables is unstable as well. We establish that the rate of convergence of the estimator to a properly
defined limit is at most the cube root of T , where T is the sample size, which is much slower than the
standard super consistent rate. We also provide an asymptotic distribution of the estimator and that
of the Gaussian quasi likelihood ratio statistic for a certain class of true data generating processes. We
relate our finding to current forecast combination methods and propose a new averaging scheme. Our
method compares favourably with various contemporary forecasting methods in forecasting a number of
macroeconomic series.
Language
English
URI
https://hdl.handle.net/10371/95634
DOI
https://doi.org/10.1016/j.jeconom.2015.03.046
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Appears in Collections:
College of Social Sciences (사회과학대학)Dept. of Economics (경제학부)Journal Papers (저널논문_경제학부)
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