Non-parametric transformation regression with non-stationary data

Oliver Linton and Qiying Wang

No 16/13, CeMMAP working papers from 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.

Date: 2013-04-23
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Related works:
Journal Article: NONPARAMETRIC TRANSFORMATION REGRESSION WITH NONSTATIONARY DATA (2016)
Working Paper: Non-parametric transformation regression with non-stationary data (2013)
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Persistent link: https://EconPapers.repec.org/RePEc:azt:cemmap:16/13

DOI: 10.1920/wp.cem.2013.1613

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