Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/56441
Type: Journal article
Title: Local linear M-estimators in null recurrent time series
Author: Lin, Zhengyan
Li, Degui
Chen, Jia
Citation: Statistica Sinica, 2009; 19:1683-1703
Publisher: Statistica Sinica
Issue Date: 2009
ISSN: 1017-0405
School/Discipline: School of Economics
Statement of
Responsibility: 
Zhengyan Lin, Degui Li and Jia Chen
Abstract: In this paper, we study a nonlinear cointegration type model , where and are observed nonstationary processes and is an unobserved stationary process. The process is assumed to be a null-recurrent Markov chain. We apply a robust version of local linear regression smoothers to estimate . Under mild conditions, the uniform weak consistency and asymptotic normality of the local linear M-estimators are established. Furthermore, a one-step iterated procedure is introduced to obtain the local linear M-estimator and the optimal bandwidth selection is discussed. Meanwhile, some numerical examples are given to show that the proposed theory and methods perform well in practice.
Keywords: Asymptotic normality; -null recurrent Markov chain; cointegration model; consistency; local linear M-estimator.
RMID: 0020092505
Description (link): http://www3.stat.sinica.edu.tw/statistica/j19n4/19-4.html
Appears in Collections:Economics publications

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