Semiparametric generalized least squares estimation in partially linear regression models with correlated errors

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• 作者：Jinhong You and Gemai Chen
• 刊名：Journal of Statistical Planning and Inference
• 出版年：2007
• 期刊代码：36_03783758
• 类别：mt
• 出版时间：1 January 2007
• 卷：137
• 期：1
• 页码：117-132
• 文件大小：270 K

摘要

This paper is concerned with the estimation problem in partially linear regression models with serially correlated errors. The authors propose a semiparametric generalized least squares estimator (SGLSE) for the parametric component and show that it is asymptotically more efficient than the semiparametric ordinary least squares estimator (SOLSE) in terms of asymptotic covariance matrix. Other properties of this SGLSE including the asymptotic normality and the law of the iterated logarithm are established as well. A simulation study is conducted to examine the finite-sample properties of the proposed estimator and an empirical example is discussed.