February 2020

Inflation at Risk

David López-Salido and Francesca Loria


We investigate how macroeconomic drivers affect the predictive inflation distribution as well as the probability that inflation will run above or below certain thresholds over the near term. This is what we refer to as Inflation-at-Risk–a measure of the tail risks to the inflation outlook. 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 conditional predictive distribution of inflation that remains even when focusing on the post-2000 period of stable and low mean inflation. We also document that in the United States and in the Euro Area tight financial conditions carry substantial downside 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.

Accessible version (.zip)

Keywords: Quantile Regression, Inflation Risks.

DOI: https://doi.org/10.17016/FEDS.2020.013

PDF: Full Paper

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Last Update: August 18, 2020