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We introduce the SIML filtering methodSIML filtering of hidden random variables of trend-cycle, seasonal, and measurement errors components and propose a method to handle macroeconomic time series. We develop the asymptotic theory based on the frequency domain analysis for non-stationary time series. We illustrate some applications and analyses of macro consumption data in Japan. We also discuss the relation of our method to the one by Muller and Watson (Econometrica 86–3:775–804, 2018) in econometrics.

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The SIML Filtering Method

  • 章节

  • 发表日期：

    2025年

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  • Naoto Kunitomo,
  • Seisho Sato

摘要

We introduce the SIML filtering methodSIML filtering of hidden random variables of trend-cycle, seasonal, and measurement errors components and propose a method to handle macroeconomic time series. We develop the asymptotic theory based on the frequency domain analysis for non-stationary time series. We illustrate some applications and analyses of macro consumption data in Japan. We also discuss the relation of our method to the one by Muller and Watson (Econometrica 86–3:775–804, 2018) in econometrics.