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Article: Threshold Regression With A Threshold Boundary
Title | Threshold Regression With A Threshold Boundary |
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Authors | |
Keywords | threshold regression threshold boundary Poisson point process compound Poisson field two-sided Brownian field |
Issue Date | 2020 |
Publisher | Taylor & Francis Inc. The Journal's web site is located at http://www.tandfonline.com/loi/ubes20 |
Citation | Journal of Business and Economic Statistics, 2020, Epub 2020-03-10 How to Cite? |
Abstract | This paper studies computation, estimation, inference and testing for linearity in threshold regression with a threshold boundary. We first put forward a new algorithm to ease the computation of the threshold boundary, and develop the asymptotics for the least squares estimator in both the fixed-threshold-effect framework and the small-threshold-effect framework. We also show that the inverting-likelihood-ratio method is not suitable to construct confidence sets for the threshold parameters, while the nonparametric posterior interval is still applicable. We then propose a new score-type test to test for the existence of threshold effects. Comparing with the usual Wald-type test, it is computationally less intensive, and its critical values are easier to obtain by the simulation method. Simulation studies corroborate the theoretical results. We finally conduct two empirical applications in labor economics to illustrate the nonconstancy of thresholds. |
Persistent Identifier | http://hdl.handle.net/10722/281852 |
ISSN | 2023 Impact Factor: 2.9 2023 SCImago Journal Rankings: 3.385 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Yu, P | - |
dc.contributor.author | Fan, X | - |
dc.date.accessioned | 2020-04-03T07:22:42Z | - |
dc.date.available | 2020-04-03T07:22:42Z | - |
dc.date.issued | 2020 | - |
dc.identifier.citation | Journal of Business and Economic Statistics, 2020, Epub 2020-03-10 | - |
dc.identifier.issn | 0735-0015 | - |
dc.identifier.uri | http://hdl.handle.net/10722/281852 | - |
dc.description.abstract | This paper studies computation, estimation, inference and testing for linearity in threshold regression with a threshold boundary. We first put forward a new algorithm to ease the computation of the threshold boundary, and develop the asymptotics for the least squares estimator in both the fixed-threshold-effect framework and the small-threshold-effect framework. We also show that the inverting-likelihood-ratio method is not suitable to construct confidence sets for the threshold parameters, while the nonparametric posterior interval is still applicable. We then propose a new score-type test to test for the existence of threshold effects. Comparing with the usual Wald-type test, it is computationally less intensive, and its critical values are easier to obtain by the simulation method. Simulation studies corroborate the theoretical results. We finally conduct two empirical applications in labor economics to illustrate the nonconstancy of thresholds. | - |
dc.language | eng | - |
dc.publisher | Taylor & Francis Inc. The Journal's web site is located at http://www.tandfonline.com/loi/ubes20 | - |
dc.relation.ispartof | Journal of Business and Economic Statistics | - |
dc.rights | Accepted Manuscript (AM) i.e. Postprint This is an Accepted Manuscript of an article published by Taylor & Francis in [Journal of Business and Economic Statistics] on [2020], available online: http://www.tandfonline.com/10.1080/07350015.2020.1740712 | - |
dc.subject | threshold regression | - |
dc.subject | threshold boundary | - |
dc.subject | Poisson point process | - |
dc.subject | compound Poisson field | - |
dc.subject | two-sided Brownian field | - |
dc.title | Threshold Regression With A Threshold Boundary | - |
dc.type | Article | - |
dc.identifier.email | Yu, P: pingyu@hku.hk | - |
dc.identifier.authority | Yu, P=rp01941 | - |
dc.description.nature | postprint | - |
dc.identifier.doi | 10.1080/07350015.2020.1740712 | - |
dc.identifier.scopus | eid_2-s2.0-85083573407 | - |
dc.identifier.hkuros | 309662 | - |
dc.identifier.volume | Epub 2020-03-10 | - |
dc.identifier.isi | WOS:000526330800001 | - |
dc.publisher.place | United States | - |
dc.identifier.issnl | 0735-0015 | - |