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Core Inflation and Trend Inflation

Author

Listed:
  • James H. Stock

    (Harvard University and NBER)

  • Mark W. Watson

    (Princeton University and NBER)

Abstract

This paper examines empirically whether the measurement of trend inflation can be improved by using disaggregated data on sectoral inflation to construct indexes akin to core inflation but with a time-varying distributed lags of weights, where the sectoral weight depends on the timevarying volatility and persistence of the sectoral inflation series and on the comovement among sectors. The modeling framework is a dynamic factor model with time-varying coefficients and stochastic volatility as in Del Negro and Otrok (2008), and is estimated using U.S. data on seventeen components of the personal consumption expenditure inflation index.

Suggested Citation

  • James H. Stock & Mark W. Watson, 2016. "Core Inflation and Trend Inflation," The Review of Economics and Statistics, MIT Press, vol. 98(4), pages 770-784, October.
  • Handle: RePEc:tpr:restat:v:98:y:2016:i:4:p:770-784
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    References listed on IDEAS

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    1. Cristadoro, Riccardo & Forni, Mario & Reichlin, Lucrezia & Veronese, Giovanni, 2005. "A Core Inflation Indicator for the Euro Area," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 37(3), pages 539-560, June.
    2. Todd E. Clark & Stephen J. Terry, 2010. "Time Variation in the Inflation Passthrough of Energy Prices," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 42(7), pages 1419-1433, October.
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    Citations

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    Cited by:

    1. Mazumder, Sandeep, 2017. "Output gains from accelerating core inflation," Journal of Macroeconomics, Elsevier, vol. 51(C), pages 63-74.
    2. Cobb, Marcus P A, 2018. "Improving Underlying Scenarios for Aggregate Forecasts: A Multi-level Combination Approach," MPRA Paper 88593, University Library of Munich, Germany.
    3. Cobb, Marcus P A, 2017. "Joint Forecast Combination of Macroeconomic Aggregates and Their Components," MPRA Paper 76556, University Library of Munich, Germany.
    4. Jose Luis Nolazco & Pablo Pincheira & Jorge Selaive, 2016. "The evasive predictive ability of core inflation," Working Papers 15/34, BBVA Bank, Economic Research Department.
    5. Tallman, Ellis W. & Zaman, Saeed, 2017. "Forecasting inflation: Phillips curve effects on services price measures," International Journal of Forecasting, Elsevier, vol. 33(2), pages 442-457.
    6. Aleksandra Hałka & Grzegorz Szafrański, 2018. "What core inflation indicators measure?," NBP Working Papers 294, Narodowy Bank Polski, Economic Research Department.
    7. Egorov D.A. (Егоров, Д.А.) & Perevyshina E.A. (Перевышина, Е.А.), 2016. "Modelling of Inflationary Processes in Russia
      [Моделирование Инфляционных Процессов В России]
      ," Working Papers 2138, Russian Presidential Academy of National Economy and Public Administration.
    8. Manopimoke, Pym & Limjaroenrat, Vorada, 2017. "Trend inflation estimates for Thailand from disaggregated data," Economic Modelling, Elsevier, vol. 65(C), pages 75-94.
    9. Forbes, Kristin & Kirkham, Lewis & Theodoridis, Konstantinos, 2017. "A trendy approach to UK inflation dynamics," Discussion Papers 49, Monetary Policy Committee Unit, Bank of England.
    10. Luis Uzeda, 2016. "State Correlation and Forecasting: A Bayesian Approach Using Unobserved Components Models," ANU Working Papers in Economics and Econometrics 2016-632, Australian National University, College of Business and Economics, School of Economics.
    11. repec:eee:macchp:v2-415 is not listed on IDEAS
    12. repec:bpj:bejmac:v:17:y:2017:i:1:p:42:n:3 is not listed on IDEAS

    More about this item

    Keywords

    inflation forecasts; non-Gaussian state space; time-varying parameters; dissagregated prices;

    JEL classification:

    • 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

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