Estimation and test for quantile nonlinear cointegrating regression
Estimation and test for quantile nonlinear cointegrating regression
In order to investigate the nonlinear relationship among economic variables at each quantile level, this paper proposes a quantile nonlinear cointegration model in which the nonlinear relationship at each quantile level is approximated by a polynomial. The parameter estimator in the proposed model is shown to follow a nonstandard distribution asymptotically due to serial correlation and endogeneity. Therefore, this paper develops a fully modified estimator which follows a mixture normal distribution asymptotically. Moreover, a test statistic for the linearity and its asymptotic distribution are also derived. Monte Carlo results show that the proposed test has good finite sample performance.
27-32
Li, Haiqi
e87d6bf1-e1a6-474f-96e8-f2b7ae0b433a
Zheng, Chaowen
4ba693c1-6dd0-45b1-acf1-45bfb393f3fc
Guo, Yu
7a99375b-caae-41c6-92ab-cc076242a421
29 September 2016
Li, Haiqi
e87d6bf1-e1a6-474f-96e8-f2b7ae0b433a
Zheng, Chaowen
4ba693c1-6dd0-45b1-acf1-45bfb393f3fc
Guo, Yu
7a99375b-caae-41c6-92ab-cc076242a421
Li, Haiqi, Zheng, Chaowen and Guo, Yu
(2016)
Estimation and test for quantile nonlinear cointegrating regression.
Economics Letters, 148, .
(doi:10.1016/j.econlet.2016.09.014).
Abstract
In order to investigate the nonlinear relationship among economic variables at each quantile level, this paper proposes a quantile nonlinear cointegration model in which the nonlinear relationship at each quantile level is approximated by a polynomial. The parameter estimator in the proposed model is shown to follow a nonstandard distribution asymptotically due to serial correlation and endogeneity. Therefore, this paper develops a fully modified estimator which follows a mixture normal distribution asymptotically. Moreover, a test statistic for the linearity and its asymptotic distribution are also derived. Monte Carlo results show that the proposed test has good finite sample performance.
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Accepted/In Press date: 18 September 2016
e-pub ahead of print date: 22 September 2016
Published date: 29 September 2016
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Local EPrints ID: 484863
URI: http://eprints.soton.ac.uk/id/eprint/484863
ISSN: 0165-1765
PURE UUID: 2a563aab-d43a-427f-a42f-4b0923e744ba
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Date deposited: 23 Nov 2023 17:54
Last modified: 18 Mar 2024 04:15
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Author:
Haiqi Li
Author:
Chaowen Zheng
Author:
Yu Guo
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