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© 2022 International Monetary Fund

WP/22/168

IMF Working Paper

MCD

Inflation-at-Risk in in the Middle East, North Africa, and Central Asia

Prepared by Maximilien Queyranne, Romain Lafarguette, and Kubi Johnson^*

Authorized for distribution by Roberto Cardarelli

September 2022

ABSTRACT: This paper investigates inflation risks for 12 Middle East and Central Asia countries, with an equal share of commodities exporters and importers. The empirical strategy leverages the recent developments in the estimation of macroeconomic risks and uses a semi-parametric approach that balances well flexibility and robustness for density projections. The paper uncovers interesting features of inflation dynamics in the region, including the role of backward versus forward-looking drivers, non-linearities, and heterogeneous and delayed exchange rate pass-through. The results have important implications for the conduct of monetary policy and central bank communication in the Middle East and Central Asia and emerging markets in general.

RECOMMENDED CITATION: Queyranne M., Lafarguette R, and Johnson K. (2022). Inflation-at-Risk in the Middle East and Central Asia, IMF Working Paper, WP/22/168

JEL Classification Numbers:	C53, D81, E31, E52
Keywords:	Emerging markets; inflation; inflation expectations; Phillips Curve; monetary policy; central bank communication; Middle East; North Africa; Central Asia
Author’s E-Mail Address:	mqueyranne@imf.org, rlafarguette@imf.org

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JEL Classification Numbers:	C53, D81, E31, E52
Keywords:	Emerging markets; inflation; inflation expectations; Phillips Curve; monetary policy; central bank communication; Middle East; North Africa; Central Asia
Author’s E-Mail Address:	mqueyranne@imf.org, rlafarguette@imf.org

Title Page

WORKING PAPERS

Inflation-at-Risk in in the Middle East, North Africa, and Central Asia

Prepared by Maximilien Queyranne, Romain Lafarguette, and Kubi Johnson ¹

Contents

• Glossary

• Executive Summary

• Literature Review

• Empirical Strategy

• Empirical Results

  • Benchmark Regressions

  • Quantile Regressions

  • Distributions of Future Inflation

• Conclusions and Policy Implications

• Appendix I. Data Sources

• Appendix II. OLS Results for Four-Quarter-Ahead Core Inflation

• Appendix III. Quantile Regressions for Two-Quarter-Ahead Core Inflation By Country

• Appendix IV. Four-Quarter-Ahead Core Inflation - Quantile Coefficients by Regressor

• Appendix V. Quantile Regressions For Four-Quarter-Ahead Core Inflation By Country

• References

• FIGURES

• 1. Derived Core Inflation, Oil Exporters

• 2. Derived Core Inflation, Oil Importers

• 3. Two-Quarter Ahead Core Inflation - Quantile Coefficients by Regressor

• 4. Oil Exporters: Two-Quarters-Ahead Core Inflation Distribution

• 5. Oil Importers: Two-Quarters-Ahead Core Inflation Distribution

Glossary

Executive Summary

Following the COVID-19 shock, price pressures have intensified in most countries as demand recovered from the pandemic, supply chain distortions persisted, and commodity prices surged (IMF, 2021). Headline inflation has spiked, while core inflation – the change in the prices of goods and services excluding food and energy - has started to rise as well. In the Middle East and Central Asia (ME&CA) region, inflation rates have also surged since mid-2020, driven mostly by external factors, particularly international food prices (IMF, 2022). The war in Ukraine has triggered a further increase in commodity prices, that has translated into higher inflation.

In this context, central banks need to assess upside risks to their baseline inflation forecasts. Since at least the 1980s, economists have recognized the important effects that uncertainty and risks can have on economic decisions. Following the pandemic, price pressures have been higher and more persistent than forecasted by most central banks, pointing to a tendency to underestimate upside tail risks. In that context, gauging the balance of risks to the baseline inflation forecasts and identifying key drivers of inflation dynamics have become critical to navigate the considerable uncertainty surrounding the outlook for price movements. While central banks in advanced economies are increasingly incorporating risks into their inflation forecasts (pioneered by the Bank of England inflation fan charts at the end of the 1990s, see for instance Britton et al. 1998), most central banks in emerging markets focus only on central inflation projections for their policy making.

Against this background, this paper addresses a few key questions: what are the main drivers of core inflation in the ME&CA countries? Has the distribution of core inflation outcomes varied across time in the region? How central banks can better deal with inflation risks, especially upside ones, when making monetary policy decisions and communicating risks to baseline forecasts? Given recent price hikes, what are the main risks for inflation outcomes in the ME&CA region?

To answer these questions, this paper first estimates the mean of future core inflation outcomes for a set of ME&CA countries, conditional on a set of contemporaneous variables, and shows the heterogeneity of inflation drivers at different horizons (two-quarter-ahead (2Q-ahead) and four-quarter-ahead (4Q-ahead)). The model relies on an augmented a Phillips Curve, which features a series of domestic and external macroeconomic variables that can affect core inflation (current core inflation, output gap, inflation expectations, commodity prices, and the exchange rate), a measure of the underlying trend in inflation that is less volatile than the consumer price index (CPI) ans is generally a better gauge of long-term inflation expectations. The Phillips Curve is estimated via panel OLS and the core inflation is regressed on the domestic and external macroeconomic variables of each country. We find that current inflation is the main explanatory variable of future 2Q-ahead core inflation across our sample, pointing to significant inertia in price setting, while inflation expectations have a stronger effect on 4Q-ahead core inflation. Commodity prices are also large determinants of future inflation, while the exchange rate is more muted given that some countries in the sample have a fixed exchange rate. We also find that the domestic output gap has limited explanatory power on future core inflation across our sample, pointing to limited short-term trade-off between employment and inflation in the regio Second, we estimate the entire distribution of future possible core inflation outcomes rather than just the point (baseline) forecast. We use the semi-parametric density estimation strategy used in the IMF Growth-at-Risk (GaR) model (Prasad and al., 2019, and Lafarguette, 2019) to project the future dynamic of core inflation. We estimate quantile regression to gauge the relative importance of current macro-financial regressors on 2Q- ahead and 4Q-ahead core inflation at different points in the sample. We focus our analysis on the right tail of the distribution to capture upside risks, i.e. high inflation. Typically, in most countries, the explanatory power of the model is maximized on the right-tail of the inflation distribution: while low and average inflation dynamics can be driven by many factors – including seasonal ones – high inflation has a limited set of clearly identified drivers, each with a substantial impact. For 2Q-ahead inflation, current core inflation has the strongest impact when inflation is high, suggesting a high-degree of persistence. This underscores the importance of keeping inflation low and stable to prevent self-reinforcing inflation dynamics. Exchange rate and commodity prices have a smaller effect than current core inflation on 2Q-ahead inflation, although their relative impact is magnified at the right tail of the inflation distribution compared to the central and lower quantiles. For 4Q-ahead core inflation, inflation expectations play a larger role in explaining inflation outcomes, and the transmission of commodity prices and exchange rate depreciation is more pronounced than in the short run (see Caselli and Roitman 2016 for a thorough analysis of exchange rate pass-through in emerging markets).

Third, to analyze the evolution of future inflation risks across time, we fit parametric distributions to the estimated inflation quantiles at three points in time: in the middle of our sample period (end-2014), at end-2019 to measure inflation dynamics prior to the COVID-19 shock, and at end-2021, to determine whether right tail risks increased recently along with higher headline inflation. We find that in most ME&CA countries, core inflation distributions shifted to the left and became centered around lower levels of inflation from 2014-2019 when considering 4Q-ahead inflation. More recently, however, the distribution of future core inflation outcomes has moved to the right in most countries, especially for 4Q-ahead core inflation. The surge in commodity prices had not yet fully passed through to core inflation at end-2021 in most countries, but future core inflation outcomes have become more volatile and more skewed to the right.

Finally, our model captures nonlinearities and provides a forward-looking approach to mitigate inflation risks and avoid a de-anchoring of inflation expectations. Central banks could leverage this Value-at-Risk (VaR) approach to better communicate risks to the outlook and the baseline.

The paper is organized as follows. Section I reviews the literature on inflation-at-risk. Section II presents some stylized facts on inflation developments in the ME&CA region discusses the data and empirical approach. Section IIII presents the results. And Section IV discusses policy implications and concludes.