Non-Parametric Transformation Regression with Non-Stationary Data

30 Pages Posted: 23 Apr 2013

See all articles by Oliver B. Linton

Oliver B. Linton

University of Cambridge

Qiying Wang

University of Sydney

Date Written: April 22, 2013

Abstract

We examine a kernel regression smoother for time series that takes account of the error correlation structure as proposed by Xiao et al. (2008). We show that this method continues to improve estimation in the case where the regressor is a unit root or near unit root process.

Keywords: Dependence, Efficiency, Cointegration, Non-stationarity, Non-parametric estimation

JEL Classification: C14, C22

Suggested Citation

Linton, Oliver B. and Wang, Qiying, Non-Parametric Transformation Regression with Non-Stationary Data (April 22, 2013). Available at SSRN: https://ssrn.com/abstract=2255034 or http://dx.doi.org/10.2139/ssrn.2255034

Oliver B. Linton (Contact Author)

University of Cambridge ( email )

Faculty of Economics
Cambridge, CB3 9DD
United Kingdom

Qiying Wang

University of Sydney ( email )

University of Sydney
Sydney, NSW 2006
Australia

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