Specification Testing for Nonlinear Multivariate Cointegrating Regressions
Chaohua Dong (),
Jiti Gao (),
Dag Tjøstheim () and
Jiying Yin ()
No 8/14, Monash Econometrics and Business Statistics Working Papers from Monash University, Department of Econometrics and Business Statistics
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 endogeniety. 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 through using both simulated and real data examples.
Keywords: ointegration; endogeneity; nonparametric kernel estimation; parametric model speci-fication; time series. (search for similar items in EconPapers)
JEL-codes: C12 C14 C22 (search for similar items in EconPapers)
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Journal Article: Specification testing for nonlinear multivariate cointegrating regressions (2017)
Working Paper: Specification Testing for Nonlinear Multivariate Cointegrating Regressions (2016)
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