Small-sample improvements in the statistical analysis of seasonally cointegrated systems

被引：13
|
作者：
Cubadda, G
Omtzigt, P
机构：
[1] Univ Molise, Dipartimento Sci Econ Gest & Sociali, I-86100 Campobasso, Italy
[2] Univ Amsterdam, Dept Quantitat Econ, NL-1018 WB Amsterdam, Netherlands
来源：
COMPUTATIONAL STATISTICS & DATA ANALYSIS | 2005年 / 49卷 / 02期
关键词：
seasonal cointegration; reduced rank regression;
D O I：
10.1016/j.csda.2004.05.016
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
New iterative reduced-rank regression procedures for seasonal cointegration analysis were proposed. The suggested methods are motivated by the idea that modelling the cointegration restrictions jointly at different frequencies may increase efficiency in finite samples. Monte Carlo simulations indicate that the new tests and estimators perform well with respect to already existing statistical procedures. (c) 2004 Elsevier B.V. All rights reserved.
引用
收藏
页码：333 / 348
页数：16
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