No. 1004: Risky Inflation: A Cross Country Analysis
Jongrim Ha World Bank Haroon Mumtaz School of Economics and Finance, Queen Mary University of London Franz Ruch World Bank
July 10, 2026
Abstract
We develop a new dynamic factor model with stochastic volatility to quantify inflation tail risk across a large cross section of countries. The framework accommodates unbalanced panels and mixed-frequency data, allowing estimation of the full predictive distribution of inflation for over 200 economies over 1971–2023. Inflation risk—defined as the probability that inflation exceeds 5 percent over a twelve-month horizon—declined during the Great Moderation but rose sharply following the COVID-19 pandemic, with the global probability surpassing 50 percent from early 2021 through 2023. Exploiting the joint predictive distri-bution of inflation and real activity, we document a brief surge in global stagflation risk in late 2021. While inflation risk responds to both structural demand and supply shocks, it tends to decline during monetary policy tightening cycles. Cross-country evidence further shows that economies with greater trade and financial openness, stronger monetary policy frameworks, and fixed exchange rate regimes face systematically lower inflation risk, while commodity-exporting countries exhibit higher tail exposures. Overall, the results under-score the importance of monitoring inflation risks alongside inflation forecasts and highlight the role of institutions in mitigating macroeconomic tail vulnerabilities.
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Keywords: Monetary Policy; Risk; FAVAR; Stochastic Volatility.