Model Specification between Parametric and Nonparametric Cointegration

37 Pages Posted: 6 Sep 2012

See all articles by Jiti Gao

Jiti Gao

Monash University - Department of Econometrics & Business Statistics

Date Written: September 3, 2012

Abstract

This paper considers a general model specification between a parametric co-integrating model and a nonparametric co-integrating model in a multivariate regression model, which involves a univariate integrated time series regressor and a vector of stationary time series regressors. 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: Cointegration, nonparametric kernel estimation, nonstationary time series, parametric model specification

JEL Classification: C12, C14, C22

Suggested Citation

Gao, Jiti, Model Specification between Parametric and Nonparametric Cointegration (September 3, 2012). Available at SSRN: https://ssrn.com/abstract=2140996 or http://dx.doi.org/10.2139/ssrn.2140996

Jiti Gao (Contact Author)

Monash University - Department of Econometrics & Business Statistics ( email )

900 Dandenong Road
Caulfield East, Victoria 3145
Australia
61399031675 (Phone)
61399032007 (Fax)

HOME PAGE: http://www.jitigao.com

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
87
Abstract Views
648
Rank
524,237
PlumX Metrics