Model specification test with correlated but not cointegrated variables

Li Gan (), Cheng Hsiao and Shu Xu

Journal of Econometrics, 2014, vol. 178, issue P1, 80-85

Abstract: Many macroeconomic and financial variables show highly persistent and correlated patterns but are not necessarily cointegrated. Recently, Sun et al. (2011) 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 (search for similar items in EconPapers)
JEL-codes: C13 C14 C22 (search for similar items in EconPapers)
Date: 2014
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:econom:v:178:y:2014:i:p1:p:80-85

DOI: 10.1016/j.jeconom.2013.08.008

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