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Testing for threshold effects in regression models

Lee, Sokbae, Seo, Myung Hwan and Shi, Youngki (2011) Testing for threshold effects in regression models. Journal of the American Statistical Association, 106 (493). pp. 220-231. ISSN 0162-1459

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Identification Number: 10.1198/jasa.2011.tm09800

Abstract

In this article, we develop a general method for testing threshold effects in regression models, using sup-likelihood-ratio (LR)-type statistics. Although the sup-LR-type test statistic has been considered in the literature, our method for establishing the asymptotic null distribution is new and nonstandard. The standard approach in the literature for obtaining the asymptotic null distribution requires that there exist a certain quadratic approximation to the objective function. The article provides an alternative, novel method that can be used to establish the asymptotic null distribution, even when the usual quadratic approximation is intractable. We illustrate the usefulness of our approach in the examples of the maximum score estimation, maximum likelihood estimation, quantile regression, and maximum rank correlation estimation. We establish consistency and local power properties of the test. We provide some simulation results and also an empirical application to tipping in racial segregation. This article has supplementary materials online.

Item Type: Article
Official URL: http://www.amstat.org/publications/jasa.cfm
Additional Information: © 2011 American Statistical Association
Divisions: Economics
Subjects: H Social Sciences > HB Economic Theory
Sets: Departments > Economics
Collections > Economists Online
Date Deposited: 05 Apr 2011 13:59
Last Modified: 20 Jun 2019 01:28
URI: http://eprints.lse.ac.uk/id/eprint/33876

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