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Signal Extraction for Non-stationary Multivariate Time Series with Illustrations for Trend Inflation
Signal Extraction for Non-stationary Multivariate Time Series with Illustrations for Trend Inflation
Abstract
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.
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Page Last Revised - October 8, 2021
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