SIGNAL EXTRACTION FOR NON-STATIONARY MULTIVARIATE TIME SERIES WITH ILLUSTRATIONS FOR TREND INFLATION

TUCKER MCELROY; THOMAS TRIMBUR

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SIGNAL EXTRACTION FOR NON-STATIONARY MULTIVARIATE TIME SERIES WITH ILLUSTRATIONS FOR TREND INFLATION

机译：具有平稳趋势说明的非平稳多元时间序列的信号提取

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This article advances the theory and methodology of signal extraction by developing the optimal treatment of difference stationary multivariate time-series models. Using a flexible time-series structure that includes co-integrated processes, we derive and prove formulas for minimum mean square error estimation of signal vectors in multiple series, from both a finite sample and a bi-infinite sample. As an illustration, we present econometric measures of the trend in total inflation that make optimal use of the signal content in core inflation.

机译：通过开发差分平稳多元时间序列模型的最佳处理方法，本文提出了信号提取的理论和方法。使用包括协整过程的灵活时间序列结构，我们从有限样本和双无限样本中推导并证明了多个序列中信号矢量的最小均方误差估计公式。作为说明，我们介绍了总通货膨胀趋势的计量经济学指标，这些指标可以最佳利用核心通货膨胀中的信号含量。

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来源
《Journal of Time Series Analysis》 |2015年第2期|209-227|共19页
作者
TUCKER MCELROY; THOMAS TRIMBUR;
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作者单位

US Census Bureau, Washington, DC, USA;

Federal Reserve Board, Washington, DC, USA,Johns Hopkins University, Baltimore, MD, USA;

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原文格式 PDF
正文语种 eng
中图分类
关键词
co-integration; common trends; filters; multivariate models; stochastic trends; unobserved components;

机译：协整共同趋势;过滤器多元模型;随机趋势;未观察到的成分;

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SIGNAL EXTRACTION FOR NON-STATIONARY MULTIVARIATE TIME SERIES WITH ILLUSTRATIONS FOR TREND INFLATION

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