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Modeling Inflation After the Crisis

Author

Listed:
  • James H. Stock

    (Harvard University)

  • Mark W. Watson

    (Princeton University)

Abstract

In the United States, the rate of price inflation falls in recessions. Turning this observation into a useful inflation forecasting equation is difficult because of multiple sources of time variation in the inflation process, including changes in Fed policy and credibility. We propose a tightly parameterized model in which the deviation of inflation from a stochastic trend (which we interpret as long-term expected inflation) reacts stably to a new gap measure, which we call the unemployment recession gap. The short-term response of inflation to an increase in this gap is stable, but the long-term response depends on the resilience, or anchoring, of trend inflation. Dynamic simulations (given the path of unemployment) match the paths of inflation during post-1960 downturns, including the current one.

Suggested Citation

  • James H. Stock & Mark W. Watson, 2010. "Modeling Inflation After the Crisis," Working Papers 2010-1, Princeton University. Economics Department..
  • Handle: RePEc:pri:econom:2010-1
    as

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    File URL: http://www.princeton.edu/~mwatson/papers/stock-watson_frbkc_2010.pdf
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    References listed on IDEAS

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    Cited by:

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    2. Behera, Harendra Kumar & Patra, Michael Debabrata, 2022. "Measuring trend inflation in India," Journal of Asian Economics, Elsevier, vol. 80(C).
    3. Bańbura, Marta & Bobeica, Elena, 2023. "Does the Phillips curve help to forecast euro area inflation?," International Journal of Forecasting, Elsevier, vol. 39(1), pages 364-390.
    4. Ivașcu Codruț, 2023. "Can Machine Learning Models Predict Inflation?," Proceedings of the International Conference on Business Excellence, Sciendo, vol. 17(1), pages 1748-1756, July.
    5. Urmat Dzhunkeev, 2024. "Forecasting Inflation in Russia Using Gradient Boosting and Neural Networks," Russian Journal of Money and Finance, Bank of Russia, vol. 83(1), pages 53-76, March.
    6. Barkan, Oren & Benchimol, Jonathan & Caspi, Itamar & Cohen, Eliya & Hammer, Allon & Koenigstein, Noam, 2023. "Forecasting CPI inflation components with Hierarchical Recurrent Neural Networks," International Journal of Forecasting, Elsevier, vol. 39(3), pages 1145-1162.
    7. Randal Verbrugge & Saeed Zaman, 2024. "Post‐COVID inflation dynamics: Higher for longer," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(4), pages 871-893, July.
    8. Zhu, Yinchu & Timmermann, Allan, 2022. "Conditional rotation between forecasting models," Journal of Econometrics, Elsevier, vol. 231(2), pages 329-347.
    9. Aguiar-Conraria, Luís & Martins, Manuel M.F. & Soares, Maria Joana, 2023. "The Phillips curve at 65: Time for time and frequency," Journal of Economic Dynamics and Control, Elsevier, vol. 151(C).
    10. Hany Guirguis & Vaneesha Boney Dutra & Zoe McGreevy, 2022. "The impact of global economies on US inflation: A test of the Phillips curve," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 46(3), pages 575-592, July.
    11. Tomohide Mineyama, 2023. "Downward Nominal Wage Rigidity and Inflation Dynamics during and after the Great Recession," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 55(5), pages 1213-1244, August.
    12. Timmermann, Allan & Zhu, Yinchu, 2021. "Conditional Rotation Between Forecasting Models," CEPR Discussion Papers 15917, C.E.P.R. Discussion Papers.
    13. David Stoneman & John V. Duca, 2024. "Using deep (machine) learning to forecast US inflation in the COVID‐19 era," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(4), pages 894-902, July.
    14. Antonello D'Agostino & Caterina Mendicino & Federico Puglisi, 2022. "Expectation‐Driven Cycles and the Changing Dynamics of Unemployment," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 54(7), pages 2173-2191, October.
    15. Enja Erker, 2024. "Forecasting medical inflation in the European Union using the ARIMA model," Public Sector Economics, Institute of Public Finance, vol. 48(1), pages 39-56.

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    More about this item

    Keywords

    Inflation;

    JEL classification:

    • C22 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Time-Series Models; Dynamic Quantile Regressions; Dynamic Treatment Effect Models; Diffusion Processes
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation

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