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Econometrics 2017, 5(1), 2; doi:10.3390/econometrics5010002

Fixed-b Inference for Testing Structural Change in a Time Series Regression

1
Korea Energy Economics Institute, Ulsan 44543, Korea
2
Michigan State University, East Lansing, MI 48824, USA
*
Author to whom correspondence should be addressed.
Academic Editor: Pierre Perron
Received: 19 August 2016 / Revised: 13 December 2016 / Accepted: 14 December 2016 / Published: 30 December 2016
(This article belongs to the Special Issue Unit Roots and Structural Breaks)
View Full-Text   |   Download PDF [397 KB, uploaded 30 December 2016]   |  

Abstract

This paper addresses tests for structural change in a weakly dependent time series regression. The cases of full structural change and partial structural change are considered. Heteroskedasticity-autocorrelation (HAC) robust Wald tests based on nonparametric covariance matrix estimators are explored. Fixed-b theory is developed for the HAC estimators which allows fixed-b approximations for the test statistics. For the case of the break date being known, the fixed-b limits of the statistics depend on the break fraction and the bandwidth tuning parameter as well as on the kernel. When the break date is unknown, supremum, mean and exponential Wald statistics are commonly used for testing the presence of the structural break. Fixed-b limits of these statistics are obtained and critical values are tabulated. A simulation study compares the finite sample properties of existing tests and proposed tests. View Full-Text
Keywords: HAC estimator; kernel; bandwidth; partial structural change; break point HAC estimator; kernel; bandwidth; partial structural change; break point
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

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Cho, C.-K.; Vogelsang, T.J. Fixed-b Inference for Testing Structural Change in a Time Series Regression. Econometrics 2017, 5, 2.

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