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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
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Related works:
Working Paper: Specification Testing for Nonlinear Multivariate Cointegrating Regressions (2016) Downloads
Working Paper: Specification Testing for Nonlinear Multivariate Cointegrating Regressions (2014) Downloads
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