Non-parametric transformation regression with non-stationary data

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.

MoreLess

Year of publication:	2013
Authors:	Linton, Oliver ; Wang, Qiying
Publisher:	London : Centre for Microdata Methods and Practice (cemmap)
Subject:	Dependence \| Efficiency \| Cointegration \| Non-stationarity \| Non-parametric estimation

freely available

Full text |

More access options

doi.org

Check Google Scholar

In German libraries (KVK)

I need help

More details

Series:	cemmap working paper ; CWP16/13
Type of publication:	Book / Working Paper
Type of publication (narrower categories):	Working Paper
Language:	English
Other identifiers:	10.1920/wp.cem.2013.1613 [DOI] 743640217 [GVK] hdl:10419/79547 [Handle] RePEc:ifs:cemmap:16/13 [RePEc]
Classification:	C14 - Semiparametric and Nonparametric Methods ; C22 - Time-Series Models
Source:	EconStor

Persistent link: https://www.econbiz.de/10010318720