Kyo, K. and Noda, H. (2011) A New Algorithm for Estimating the Parameters in Seasonal Adjustment Models with a Cyclical Component. ICIC Express Letters: An International Journal of Research and Surveys, 5, 1731-1737.

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.