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Disaggregated Approach to Measuring Core Inflation

Author

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  • Young Se Kim

    (Sungkyunkwan University)

  • Hyok Jung Kim

    (Sungkyunkwan University)

Abstract

To distinguish inflation signal from transient noise, monetary policymakers have long used core inflation measures. Using disaggregate CPI data for Korea, this paper reviews extant measures of core inflation and documents several important empirical features of the measures. Our theoretical analysis demonstrates that the stylized facts on the extant measures are not compatible with a single stochastic trend, and our empirical findings strongly support this view. Motivated by price divergence, we model disaggregate prices in multiple-component structure and find there are four persistent components together with a group of diverging items. Having identified distinct common components, we employ a new core inflation measure based on a limited influence estimator for each convergence club. The new core inflation dominates the extant measures in its ability to account for central tendency of price distribution and for generating low variance of price changes. In addition, it forecasts the underlying trend of headline CPI inflation more accurately than the extant core inflation indicators do.

Suggested Citation

  • Young Se Kim & Hyok Jung Kim, 2015. "Disaggregated Approach to Measuring Core Inflation," Korean Economic Review, Korean Economic Association, vol. 31, pages 145-176.
    • Handle: RePEc:kea:keappr:ker-20150630-31-1-06
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    References listed on IDEAS

    as
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    Cited by:

    1. Byeongdeuk Jang & Young Se Kim, 2017. "Driving Forces of Inflation Expectations," Korean Economic Review, Korean Economic Association, vol. 33, pages 207-237.

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    More about this item

    Keywords

    Core Inflation; Time-varying Common Factor Model; Clustering Analysis; Divergence;
    All these keywords.

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation
    • E37 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Forecasting and Simulation: Models and Applications
    • E50 - Macroeconomics and Monetary Economics - - Monetary Policy, Central Banking, and the Supply of Money and Credit - - - General

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