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Non-parametric transformation regression with non-stationary data

Oliver Linton and Qiying Wang ()

No CWP16/13, CeMMAP working papers from Centre for Microdata Methods and Practice, Institute for Fiscal Studies

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 (search for similar items in EconPapers)
JEL-codes: C14 C22 (search for similar items in EconPapers)
Date: 2013-04-23
New Economics Papers: this item is included in nep-ecm and nep-ets
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Related works:
Journal Article: NONPARAMETRIC TRANSFORMATION REGRESSION WITH NONSTATIONARY DATA (2016) Downloads
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