Global Inflation, Regional Factors 
Inflation is often a global phenomenon, as a common shock—such as a drop in oil supply, a major war, or a pandemic—can cause consumer prices to surge in many countries simultaneously. This paper introduces a novel concept of regional inflation factors. Using inflation data for the 1970–2023 period from a balanced panel of 61 advanced and developing economies, it shows that in addition to responding to global factors, inflation comoves strongly within geographical regions. This regional comovement proves particularly important for developing countries.
Key Findings
- In developing countries, the regional factor explains a share of inflation variance that typically is larger than the share explained by the global factor. For example, in developing countries located in Asia, the regional factor explains 27.8 percent of the variation in inflation, while the global factor explains only 8.9 percent.
- By contrast, in advanced economies, the global factor explains a much larger share of the variation.
- The regional structure is supported by an unsupervised machine learning algorithm, which groups countries according to inflation similarity.
- In general, each region’s factor is positively correlated with the prices of that region’s import commodities and negatively correlated with the prices of its export commodities.
- Including global and regional factors in the forecast model improves the accuracy of the near-term inflation forecasts for all regions relative to the benchmark. In most cases, including the regional factor improves the model’s forecasting over that of the model with the global factor only. The results are similar but somewhat weaker at longer forecasting horizons.
Implications
The paper’s analysis provides an enhanced understanding of global inflation, especially in developing countries. Given the persistence of the regional factors, developing countries’ central banks can particularly benefit by paying attention to the inflation dynamics in their neighboring countries.
Abstract
This paper shows that global inflation dynamics have a sizable regional component. Using a balanced panel of 61 countries that starts in 1970, we document that while the global factor, defined as the dominant principal component, explains a large portion of inflation variation in advanced economies, a model with only one principal component is less successful for developing countries. By contrast, a hierarchical dynamic factor model, which includes a global (unconstrained) factor and regional (restricted) factors, performs substantially better for emerging market and developing economies. The regional factors are linked to commodity prices and help improve the accuracy of inflation forecasts at the country level. Employing an unsupervised machine-learning technique, we show that the estimated clusters of countries, grouped according to similarities in inflation dynamics, exhibit a strong regional pattern. Our findings suggest that policymakers in developing countries should pay close attention to inflation dynamics in their neighboring countries.