Inflation at risk in advanced and emerging market economies

first published in September 2020, revised September 2023

Focus

Discussion of inflation risks, especially whether risks to future inflation are balanced or tilted to the upside or downside, often take centre stage in central bank policy meetings and communication. Policymakers often consider not only the most likely future path of inflation but also the full range of possible outcomes around that path. However, there is limited research on inflation risks and the factors that drive them, even for emerging market economies (EMEs) where inflation has generally been higher and more volatile.

Contribution

We investigate inflation risks and their drivers in a large sample of advanced and emerging market economies. The starting point of our analysis is a Phillips curve, a workhorse model that links inflation to its main determinants. To investigate inflation-at-risk, the Phillips curve is estimated as a quantile regression. We use this type of regression because it highlights when tail risks for inflation - that is, the chance of very high or low inflation - evolve differently from average outcomes.

Findings

We find that, across most economies, upside inflation risks have generally fallen over time. This reflects the adoption of inflation targeting frameworks and the success that central banks have had in controlling inflation. Relevant inflation risk drivers differ across groups of countries. In advanced economies, being at the zero lower bound raises the probability of very low inflation outcomes. In EMEs, large exchange rate depreciations raise the probability of high inflation outcomes. We also find that tightening financial conditions increase both upside and downside tail risks, especially in EMEs.

Abstract

Using quantile regression techniques, we study the drivers of inflation risks in a large panel of advanced and emerging market economies (EMEs). We document several facts regarding the inflation forecast distribution and highlight some key differences between these two groups of countries. First, the exchange rate has a quantitatively important and non-linear impact on the inflation outlook in EMEs: a depreciation is associated with larger increases in the upper quantiles than in the lower quantiles, increasing the right skewness of the distribution. By contrast, there is no evidence of such non-linearities for advanced economies. Second, tighter financial conditions in EMEs carry both downside and upside risks to inflation, while having a muted impact on the modal or mean outcome. This is in contrast to advanced economies, where only downside risks prove sensitive. Third, the zero lower bound on policy rates translates into substantial downside risks to inflation. Finally, the adoption of inflation targeting is associated not only with lower mean inflation but also with a less right-skewed distribution. Our findings underscore the importance of including non-linearities in structural models of inflation dynamics.

JEL codes: E31, E37, E52

Keywords: quantile regressions, forecast density, inflation risk, monetary policy framework, exchange rates, zero lower bound, inflation targeting