Signal Extraction for Non‐Stationary Multivariate Time Series with Illustrations for Trend Inflation
本文提出了处理差分平稳多元时间序列模型的最优信号提取方法，推导了有限样本和双无限样本下信号向量的最小均方误差估计公式，并应用于从核心通胀中提取总通胀趋势。
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.