Model Specification Test with Correlated But Not Cointegrated Variables

19 Pages Posted: 27 Aug 2013

See all articles by Li Gan

Li Gan

Texas A&M University - Department of Economics; National Bureau of Economic Research (NBER)

Cheng Hsiao

University of Southern California - Department of Economics; National Taiwan University; National Bureau of Economic Research (NBER)

Shu Xu

Southwestern University of Finance and Economics (SWUFE)

Date Written: October 18, 2012

Abstract

Many macroeconomic and financial variables show highly persistent and correlated patterns but not necessarily cointegrated. Recently, Sun, Hsiao and Li (2010) propose using a semiparametric varying coefficient approach to capture correlations between integrated but non cointegrated variables. Due to the complication arising from the integrated disturbance term and the semiparametric functional form, consistent estimation of such a semiparametric model requires stronger conditions than usually needed for consistent estimation for a linear (spurious) regression model, or a semiparametric varying coefficient model with a stationary disturbance. Therefore, it is important to develop a testing procedure to examine for a given data set, whether linear relationship holds or not, while allowing for the disturbance being an integrated process. In this paper we propose two test statistics for detecting linearity against semiparametric varying coefficient alternative specification. Monte Carlo simulations are used to examine the finite sample performances of the proposed tests.

Keywords: Specification test, Spurious regression, varying coefficient, kernel estimation

JEL Classification: C13, C14, C22

Suggested Citation

Gan, Li and Hsiao, Cheng and Xu, Shu, Model Specification Test with Correlated But Not Cointegrated Variables (October 18, 2012). CAFE Research Paper No. 13.09. Available at SSRN: https://ssrn.com/abstract=2316286 or http://dx.doi.org/10.2139/ssrn.2316286

Li Gan

Texas A&M University - Department of Economics ( email )

5201 University Blvd.
College Station, TX 77843-4228
United States

National Bureau of Economic Research (NBER) ( email )

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Cheng Hsiao (Contact Author)

University of Southern California - Department of Economics ( email )

3620 South Vermont Ave. Kaprielian (KAP) Hall, 300
Los Angeles, CA 90089
United States

National Taiwan University

1 Sec. 4, Roosevelt Road
Taipei, 106
Taiwan

National Bureau of Economic Research (NBER)

1050 Massachusetts Avenue
Cambridge, MA 02138
United States

Shu Xu

Southwestern University of Finance and Economics (SWUFE) ( email )

55 Guanghuacun St,
Chengdu, Sichuan 610074
China

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