Description/Abstract
This paper develops new statistical inference methods for the parameters in threshold regression models. In particular, we develop a test for homogeneity of the threshold parameter and a test for linear restrictions on the regression coefficients. The tests are built upon a transformed partial-sum process after re-ordering the observations based on the rank of the threshold variable, which recasts the crosssectional threshold problem into the time-series structural break analogue. The asymptotic distributions of the test statistics are derived using this novel approach, and the finite sample properties are studied in Monte Carlo simulations. We apply the new tests to the tipping point problem studied by Card, Mas, and Rothstein (2008), and statistically justify that the location of the tipping point varies acrosstracts..
Document Type
Working Paper
Date
1-2020
Keywords
Threshold Regression, Test, Homogeneous Threshold, Linear Restriction, Tipping Point
Language
English
Series
Working Papers Series
Acknowledgements
The authors thank Ulrich Müller, Bo Honoré, Mark Watson, Kirill Evidokimov, Simon Lee, Myung Seo, Zhijie Xiao, and particpants 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.
Disciplines
Economic Policy | Economics | Public Affairs, Public Policy and Public Administration
ISSN
1525-3066
Recommended Citation
Lee, Yoonseok and Wang, Yulong, "Inference in Threshold Models" (2020). Center for Policy Research. 255.
https://surface.syr.edu/cpr/255
Source
Local input
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Additional Information
Working paper no. 223