Specification testing for nonlinear multivariate cointegrating regressions

Chaohua Dong, Jiti Gao, Dag Tjøstheim and Jiying Yin

Journal of Econometrics, 2017, vol. 200, issue 1, 104-117

Abstract: This paper considers a general model specification test for nonlinear multivariate cointegrating regressions where the regressor consists of a univariate integrated time series and a vector of stationary time series. The regressors and the errors are generated from the same innovations, so that the model accommodates endogeneity. A new and simple test is proposed, and the resulting asymptotic theory is established. The test statistic is constructed based on a natural distance function between a nonparametric estimate and a smoothed parametric counterpart. The asymptotic distribution of the test statistic under the parametric specification is proportional to that of a local-time random variable with a known distribution. In addition, the finite sample performance of the proposed test is evaluated using both simulated and real data examples.

Keywords: Cointegration; Endogeneity; Nonparametric kernel estimation; Parametric model specification; Time series (search for similar items in EconPapers)
JEL-codes: C12 C14 C22 (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (11)

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0304407617300787
Full text for ScienceDirect subscribers only

Related works:
Working Paper: Specification Testing for Nonlinear Multivariate Cointegrating Regressions (2016)
Working Paper: Specification Testing for Nonlinear Multivariate Cointegrating Regressions (2014)
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:200:y:2017:i:1:p:104-117

DOI: 10.1016/j.jeconom.2017.05.016

Access Statistics for this article

Journal of Econometrics is currently edited by T. Amemiya, A. R. Gallant, J. F. Geweke, C. Hsiao and P. M. Robinson

More articles in Journal of Econometrics from Elsevier
Bibliographic data for series maintained by Catherine Liu ().