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Testing linearity against threshold effects: uniform inference in quantile regression

Testing linearity against threshold effects: uniform inference in quantile regression
Testing linearity against threshold effects: uniform inference in quantile regression
This paper develops a uniform test of linearity against threshold effects in the quantile regression framework. The test is based on the supremum of the Wald process over the space of quantile and threshold parameters. We establish the limiting null distribution of the test statistic for stationary weakly dependent processes, and propose a simulation method to approximate the critical values. The proposed simulation method makes the test easy to implement. Monte Carlo experiments show that the proposed test has good size and reasonable power against non-linear threshold models.
0020-3157
413-439
Galvao, A.
e0987498-19e4-4bed-b2d7-3d605ca1cbed
Kato, K.
72064545-1585-4b6e-906f-d5c8d2575ebd
Montes-Rojas, G.
d139fc6a-1f73-4db6-bb54-a38d14a7b030
Olmo, J.
706f68c8-f991-4959-8245-6657a591056e
Galvao, A.
e0987498-19e4-4bed-b2d7-3d605ca1cbed
Kato, K.
72064545-1585-4b6e-906f-d5c8d2575ebd
Montes-Rojas, G.
d139fc6a-1f73-4db6-bb54-a38d14a7b030
Olmo, J.
706f68c8-f991-4959-8245-6657a591056e

Galvao, A., Kato, K., Montes-Rojas, G. and Olmo, J. (2014) Testing linearity against threshold effects: uniform inference in quantile regression. Annals of the Institute of Statistical Mathematics, 66 (2), 413-439. (doi:10.1007/s10463-013-0418-9).

Record type: Article

Abstract

This paper develops a uniform test of linearity against threshold effects in the quantile regression framework. The test is based on the supremum of the Wald process over the space of quantile and threshold parameters. We establish the limiting null distribution of the test statistic for stationary weakly dependent processes, and propose a simulation method to approximate the critical values. The proposed simulation method makes the test easy to implement. Monte Carlo experiments show that the proposed test has good size and reasonable power against non-linear threshold models.

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Published date: April 2014
Organisations: Economics

Identifiers

Local EPrints ID: 369379
URI: http://eprints.soton.ac.uk/id/eprint/369379
ISSN: 0020-3157
PURE UUID: ac4b80d0-9770-41c7-b05e-3d73f00dee72
ORCID for J. Olmo: ORCID iD orcid.org/0000-0002-0437-7812

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Date deposited: 02 Oct 2014 11:34
Last modified: 15 Mar 2024 03:46

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Contributors

Author: A. Galvao
Author: K. Kato
Author: G. Montes-Rojas
Author: J. Olmo ORCID iD

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