Bootstrapping time series models
Bootstrapping time series models
复制标题
自举时间序列模型
DOI：
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发表时间：
1996
期刊：
影响因子：
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通讯作者：
Maddala
中科院分区：
文献类型：
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作者：
G. Li;Maddala
本文综述了自举方法的最新发展，以及为使其适用于时间序列模型而需要进行的修改。本文讨论了时间序列计量经济分析中实证研究人员应注意的一些问题。讨论了自举数据生成的不同抽样方案和自举检验统计量的不同形式。本文还讨论了数据直接自举在动态模型和协整回归模型中的适用性。认为自举残差是较好的方法。所涉及的引导过程包括递归引导、移动块引导和静止引导。
This paper surveys recent development in bootstrap methods and the modifications needed for their applicability in time series models. The paper discusses some guidelines for empirical researchers in econometric analysis of time series. Different sampling schemes for bootstrap data generation and different forms of bootstrap test statistics are discussed. The paper also discusses the applicability of direct bootstrapping of data in dynamic models and cointegrating regression models. It is argued that bootstrapping residuals is the preferable approach. The bootstrap procedures covered include the recursive bootstrap, the moving block bootstrap and the stationary bootstrap.