Accessibility navigation


Estimation and test for quantile nonlinear cointegrating regression

Li, H., Zheng, C. and Guo, Y. (2016) Estimation and test for quantile nonlinear cointegrating regression. Economics Letters, 148. pp. 27-32. ISSN 0165-1765

Full text not archived in this repository.

It is advisable to refer to the publisher's version if you intend to cite from this work. See Guidance on citing.

To link to this item DOI: 10.1016/j.econlet.2016.09.014

Abstract/Summary

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.

Item Type:Article
Refereed:Yes
Divisions:No Reading authors. Back catalogue items
ID Code:107085
Publisher:Elsevier

University Staff: Request a correction | Centaur Editors: Update this record

Page navigation