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|Title:||Local linear M-estimators in null recurrent time series|
|Citation:||Statistica Sinica, 2009; 19:1683-1703|
|School/Discipline:||School of Economics|
|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.|
|Appears in Collections:||Economics publications|
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