Local Constant Kernel Estimation of a Partially Linear Varying Coefficient Cointegration Model

Luya Wang, Zhongwen Liang (), Juan Lin and Qi Li ()
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Luya Wang: School of Banking and Finance, University of International Business and Economics
Juan Lin: Department of Finance, School of Economics, and Wang Yanan Institute for Studies in Economics, Xiamen University
Qi Li: Department of Economics, Texas A&M University

Annals of Economics and Finance, 2015, vol. 16, issue 2, 353-369

Abstract: In this paper, we consider a partially linear varying coefficient cointegration model. We focus on the estimation of constant coefficients. We derive the asymptotic result for the local constant kernel estimator, which complements the results in Li, Li, Liang and Hsiao (2013) where the local polynomial estimation methods are studied. However, Li et al. (2013) impose stronger conditions to rule out the local constant estimation due to technical difficulties. We give the full treatment of the local constant method in this paper based on a novel proof. From the simulation results reported in the paper, we show that the local constant and local linear estimators perform similarly, but the local constant method requires less data. Also, in fnite sample applications the local linear estimation could suffer from the matrix singularity problem.

Keywords: Varying coefficient model; Partially linear model; Nonstationary; Cointegration (search for similar items in EconPapers)
JEL-codes: C14 C32 (search for similar items in EconPapers)
Date: 2015
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