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TESTING FOR HOMOGENEOUS THRESHOLDS IN THRESHOLD REGRESSION MODELS

Published online by Cambridge University Press:  28 October 2022

Yoonseok Lee Open the ORCID record for Yoonseok Lee [Opens in a new window]  and
Yulong Wang Open the ORCID record for Yulong Wang [Opens in a new window]
Yoonseok Lee
Affiliation:
Syracuse University
Yulong Wang*
Affiliation:
Syracuse University
*
Address correspondence to Yulong Wang, Department of Economics and Center for Policy Research, Syracuse University, 127 Eggers Hall, Syracuse, NY 13244, USA; e-mail: ywang402@syr.edu.
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Abstract

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This paper develops a test for homogeneity of the threshold parameter in threshold regression models. The test has a natural interpretation from time series perspectives and can also be applied to test for additional change points in the structural break models. The limiting distribution of the test statistic is derived, and the finite sample properties are studied in Monte Carlo simulations. We apply the new test to the tipping point problem studied by Card, Mas, and Rothstein (2008, Quarterly Journal of Economics 123, 177–218) and statistically justify that the location of the tipping point varies across tracts.

Information

Type
ARTICLES
Information
Econometric Theory , Volume 40 , Issue 3 , June 2024 , pp. 608 - 651
Creative Commons
Creative Common License - CCCreative Common License - BY
This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited.
Copyright
© The Author(s), 2022. Published by Cambridge University Press

Footnotes

We thank the editor (Peter Phillips), the Co-Editor (Simon Lee), and three anonymous referees for very constructive comments and suggestions. We also thank Ulrich Müller, Bo Honoré, Mark Watson, Kirill Evidokimov, Myung Hwan Seo, Zhijie Xiao, and participants at numerous seminar/conference presentations for very helpful discussions. Lee acknowledges financial support from the CUSE grant. Wang acknowledges financial support from the Appleby-Mosher grant.

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