Control variate method for stationary processes

Tomoyuki Amano, Masanobu Taniguchi*

*この研究の対応する著者

研究成果: Article査読

1 被引用数 (Scopus)

抄録

The sample mean is one of the most natural estimators of the population mean based on independent identically distributed sample. However, if some control variate is available, it is known that the control variate method reduces the variance of the sample mean. The control variate method often assumes that the variable of interest and the control variable are i.i.d. Here we assume that these variables are stationary processes with spectral density matrices, i.e. dependent. Then we propose an estimator of the mean of the stationary process of interest by using control variate method based on nonparametric spectral estimator. It is shown that this estimator improves the sample mean in the sense of mean square error. Also this analysis is extended to the case when the mean dynamics is of the form of regression. Then we propose a control variate estimator for the regression coefficients which improves the least squares estimator (LSE). Numerical studies will be given to see how our estimator improves the LSE.

本文言語English
ページ(範囲)20-29
ページ数10
ジャーナルJournal of Econometrics
165
1
DOI
出版ステータスPublished - 2011 11月 3

ASJC Scopus subject areas

  • 経済学、計量経済学

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