文章基本信息

标题：Finite Sample Improvement in Statistical Inference with I(1) Processes
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作者：D Marinucci ; Peter M Robinson
期刊名称：Japanese Studies Programme Papers
出版年度：2001
出版社：Suntory Toyota International Centres for Economics and Related Disciplines
摘要：Robinson and Marinucci (1998) investigated the asymptotic behaviour of a narrow-band semiparametric procedure termed Frequency Domain Least Squares (FDLS) in the broad context of fractional cointegration analysis. Here we restrict to the standard case when the data are I(1) and the cointegrating errors are I(0), proving that modifications of the Fully-Modified Ordinary Least Squares (FM-OLS) procedure of Phillips and Hansen (1990) which use the FDLS idea have the same asymptotically desirable properties as FM-OLS, and, on the basis of a Monte Carlo study, find evidence that they have superior finite-sample properties; the new procedures are also shown to compare satisfactorily with parametric estimates
关键词：Fully-modified ordinary least squares; finite sample ;improvements; statistical inference with I(1) processes; Monte Carlo study; ;parametric estimates