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Common and Idiosyncratic Inflation

Author

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  • Hie Joo Ahn
  • Matteo Luciani

Abstract

We disentangle price changes due to economy‐wide shocks from those driven by idiosyncratic shocks by estimating a two‐regime dynamic factor model with dynamic loadings on a new large dataset of finely disaggregated monthly personal consumption expenditures price inflation indexes from 1959 through 2024. We find that up to the mid‐1990s and after the COVID‐19 pandemic, common shocks were the primary driver of US inflation dynamics and had long‐lasting effects. In contrast, in the intermediate period, idiosyncratic shocks were the main driver, and common shocks had short‐lived effects.

Suggested Citation

  • Hie Joo Ahn & Matteo Luciani, 2026. "Common and Idiosyncratic Inflation," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 41(2), pages 156-168, March.
  • Handle: RePEc:wly:japmet:v:41:y:2026:i:2:p:156-168
    DOI: 10.1002/jae.70023
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    References listed on IDEAS

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    1. repec:bla:revinw:v:48:y:2002:i:2:p:217-33 is not listed on IDEAS
    2. Michele Lenza & Giorgio E. Primiceri, 2022. "How to estimate a vector autoregression after March 2020," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 37(4), pages 688-699, June.
    3. 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.
    4. Matteo Barigozzi & Matteo Luciani, 2023. "Measuring the Output Gap using Large Datasets," The Review of Economics and Statistics, MIT Press, vol. 105(6), pages 1500-1514, November.
    5. Martín Almuzara & Argia M. Sbordone, 2022. "Inflation Persistence: How Much Is There and Where Is It Coming From?," Liberty Street Economics 20220420, Federal Reserve Bank of New York.
    6. Ricardo Reis & Mark W. Watson, 2010. "Relative Goods' Prices, Pure Inflation, and the Phillips Correlation," American Economic Journal: Macroeconomics, American Economic Association, vol. 2(3), pages 128-157, July.
    7. Alan J. Auerbach & Yuriy Gorodnichenko, 2013. "Corrigendum: Measuring the Output Responses to Fiscal Policy," American Economic Journal: Economic Policy, American Economic Association, vol. 5(3), pages 320-322, August.
    8. Yunjong Eo & Luis Uzeda & Benjamin Wong, 2023. "Understanding trend inflation through the lens of the goods and services sectors," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 38(5), pages 751-766, August.
    9. Jean Boivin & Marc P. Giannoni & Ilian Mihov, 2009. "Sticky Prices and Monetary Policy: Evidence from Disaggregated US Data," American Economic Review, American Economic Association, vol. 99(1), pages 350-384, March.
    10. Diebold, Francis X & Mariano, Roberto S, 2002. "Comparing Predictive Accuracy," Journal of Business & Economic Statistics, American Statistical Association, vol. 20(1), pages 134-144, January.
    11. Matteo Barigozzi & Matteo Luciani, 2019. "Quasi Maximum Likelihood Estimation and Inference of Large Approximate Dynamic Factor Models via the EM algorithm," Papers 1910.03821, arXiv.org, revised Sep 2024.
    12. Karl Whelan, 2002. "A Guide To U.S. Chain Aggregated Nipa Data," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 48(2), pages 217-233, June.
    13. Raffaella Giacomini & Halbert White, 2006. "Tests of Conditional Predictive Ability," Econometrica, Econometric Society, vol. 74(6), pages 1545-1578, November.
    14. Luciani, Matteo, 2014. "Forecasting with approximate dynamic factor models: The role of non-pervasive shocks," International Journal of Forecasting, Elsevier, vol. 30(1), pages 20-29.
    15. James H. Stock & Mark W. Watson, 2007. "Erratum to "Why Has U.S. Inflation Become Harder to Forecast?"," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(7), pages 1849-1849, October.
    16. Claudio Borio & Piti Disyatat & Dora Xia & Egon Zakrajšek, 2021. "Monetary policy, relative prices and inflation control: flexibility born out of success," BIS Quarterly Review, Bank for International Settlements, September.
    17. Kim, Chang-Jin & Kim, Jaeho, 2022. "Trend-Cycle Decompositions Of Real Gdp Revisited: Classical And Bayesian Perspectives On An Unsolved Puzzle," Macroeconomic Dynamics, Cambridge University Press, vol. 26(2), pages 394-418, March.
    18. Boivin, Jean & Ng, Serena, 2006. "Are more data always better for factor analysis?," Journal of Econometrics, Elsevier, vol. 132(1), pages 169-194, May.
    19. James H. Stock & Mark W. Watson, 2007. "Why Has U.S. Inflation Become Harder to Forecast?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 39(s1), pages 3-33, February.
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