Estimation and test for quantile nonlinear cointegrating regression

Haiqi Li, Chaowen Zheng and Yu Guo

Economics Letters, 2016, vol. 148, issue C, 27-32

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.

Keywords: Quantile nonlinear cointegration; Nonlinearity test; Polynomial approximation; Fully modified procedure (search for similar items in EconPapers)
JEL-codes: C12 C13 C22 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecolet:v:148:y:2016:i:c:p:27-32

DOI: 10.1016/j.econlet.2016.09.014

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