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Developing an underlying inflation gauge for China

Author

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  • Marlene Amstad
  • Ye Huan
  • Guonan Ma

Abstract

The headline consumer price inflation (CPI) is often considered too noisy, narrowly defined, and/or slowly available for policymaking. On the other hand, traditional core inflation measures may reduce volatility but do not address other issues and may even exclude important information. This paper develops a new underlying inflation gauge (UIG) for China which differentiates between trend and noise, is available daily and uses a broad set of variables that potentially influence inflation. Its construction follows the works at other major central banks, adopts the methodology of a dynamic factor model that extracts the lower frequency components as developed by Forni et al. (2000) and draws on the experience of the People's Bank of China in modelling inflation. The paper is the first application of this type of dynamic factor model for inflation to any large emerging market economy. Our UIG for China is less noisy but still closely tracks the headline CPI. It does not suffer from the excess volatility reduction that plagues traditional core inflation measures and instead provides additional information. Finally, when forecasting the headline CPI, our UIG for China outperforms traditional core measures over different samples.

Suggested Citation

  • Marlene Amstad & Ye Huan & Guonan Ma, 2014. "Developing an underlying inflation gauge for China," BIS Working Papers 465, Bank for International Settlements.
  • Handle: RePEc:bis:biswps:465
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    Cited by:

    1. Marlene Amstad & Ye Huan & Guonan Ma, 2014. "Developing an underlying inflation gauge for China," BIS Working Papers 465, Bank for International Settlements.
    2. Amstad, Marlene & Ye, Huan & Ma, Guonan, 2018. "Developing an underlying inflation gauge for China," BOFIT Discussion Papers 11/2018, Bank of Finland Institute for Emerging Economies (BOFIT).
    3. repec:zbw:bofitp:2018_011 is not listed on IDEAS
    4. Sukudhew (Sukhdave) Singh, 2016. "Economic changes, inflation dynamics and policy responses: the Malaysian experience," BIS Papers chapters, in: Bank for International Settlements (ed.), Inflation mechanisms, expectations and monetary policy, volume 89, pages 231-245, Bank for International Settlements.
    5. Marlene Amstad & Simon M. Potter & Robert W. Rich, 2017. "The New York Fed Staff Underlying Inflation Gauge (UIG)," Economic Policy Review, Federal Reserve Bank of New York, issue 23-2, pages 1-32.
    6. Iris Day, 2017. "Underlying Consumer Price Inflation in China," RBA Bulletin (Print copy discontinued), Reserve Bank of Australia, pages 29-36, December.
    7. Bjarni G. Einarsson, 2014. "A Dynamic Factor Model for Icelandic Core Inflation," Economics wp67, Department of Economics, Central bank of Iceland.
    8. The People's Bank of China, 2016. "An underlying inflation gauge (UIG) for China," BIS Papers chapters, in: Bank for International Settlements (ed.), Inflation mechanisms, expectations and monetary policy, volume 89, pages 117-121, Bank for International Settlements.

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    More about this item

    Keywords

    Inflation; Dynamic Factor Models; Core Inflation; Monetary Policy; Forecasting; China;
    All these keywords.

    JEL classification:

    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General
    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • 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
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • C43 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Index Numbers and Aggregation

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