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Jiang, X.-Q. (Kyo, K.) and Kitagawa, G. (1993) A Time Varying Coefficient Vector AR Modeling of Nonstationary Covariance Time Series. Signal Processing, 33, 315-331. https://doi.org/10.1016/0165-1684(93)90129-X

has been cited by the following article:

• TITLE: The Dynamic Relationship between Economic Growth and Inflation in Japan

  AUTHORS: Koki Kyo

  KEYWORDS: Bayesian Modeling, Dynamic Relationship Analysis, Time-Varying Coeffi-cient, Gross Domestic Product, Consumer Price Index, Japanese Economy

  JOURNAL NAME: Open Journal of Social Sciences, Vol.6 No.3, March 13, 2018

  ABSTRACT: To develop a way to analyze the dynamic relationship between the economic growth and the level of inflation in Japan, we propose a Bayesian regression method to estimate the dynamic dependence of the stationary component of GDP on a stationary component of the CPI. First, we extract stationary components from original GDP and CPI time series using a set of state space models. Then, we construct a set of Bayesian regression models with a time-varying coefficient. We also analyze the dynamic relationship between the stationary components of GDP and the CPI using Japanese economic statistics from 1980 to 2005.