Specification testing for nonlinear multivariate cointegrating regressions

Chaohua Dong, Jiti Gao, Dag Tjøstheim, Jiying Yin

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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.

Original languageEnglish
Pages (from-to)104-117
Number of pages14
JournalJournal of Econometrics
Volume200
Issue number1
DOIs
Publication statusPublished - 1 Sep 2017

Keywords

  • Cointegration
  • Endogeneity
  • Nonparametric kernel estimation
  • Parametric model specification
  • Time series

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