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Inflation at Risk

Author

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  • López-Salido, J David
  • Loria, Francesca

Abstract

We find that the recent muted response of the conditional mean of inflation to economic conditions does not convey an adequate representation of the overall pattern of inflation dynamics. Analyzing data from the 1970s reveals ample variability in the entire conditional distribution of inflation. Focusing on the period from 2000 onward bolsters this evidence. Using time-series data for the United States and the Euro Area, we document that looking at the entire conditional distribution of inflation uncovers – after controlling for the state of the labor market and inflation expectations – that heightened financial conditions carry substantial and persistent low-inflation risks, a feature overlooked by much of the literature. Our paper offers a new empirical perspective to existing macroeconomic models, showing that changes in credit conditions are also key to understand the dynamics of the inflation tails.

Suggested Citation

  • López-Salido, J David & Loria, Francesca, 2019. "Inflation at Risk," CEPR Discussion Papers 14074, C.E.P.R. Discussion Papers.
    • Handle: RePEc:cpr:ceprdp:14074
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    References listed on IDEAS

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    Cited by:

    1. Andrea Carriero & Todd E. Clark & Massimiliano Marcellino, 2024. "Capturing Macro‐Economic Tail Risks with Bayesian Vector Autoregressions," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 56(5), pages 1099-1127, August.
    2. Danilo Cascaldi-Garcia & Cisil Sarisoy & Juan M. Londono & Bo Sun & Deepa D. Datta & Thiago Ferreira & Olesya Grishchenko & Mohammad R. Jahan-Parvar & Francesca Loria & Sai Ma & Marius Rodriguez & Ilk, 2023. "What Is Certain about Uncertainty?," Journal of Economic Literature, American Economic Association, vol. 61(2), pages 624-654, June.
    3. Alex Tagliabracci, 2020. "Asymmetry in the conditional distribution of euro-area inflation," Temi di discussione (Economic working papers) 1270, Bank of Italy, Economic Research and International Relations Area.
    4. Rottner, Matthias, 2022. "Financial crises and shadow banks: A quantitative analysis," Discussion Papers 15/2022, Deutsche Bundesbank.

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    More about this item

    Keywords

    Quantile regression; Inflation risk;

    JEL classification:

    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • E31 - Macroeconomics and Monetary Economics - - Prices, Business Fluctuations, and Cycles - - - Price Level; Inflation; Deflation

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