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© 2022 International Monetary Fund
WP/22/135
IMF Working Paper
Research Department
Staple Food Prices in Sub-Saharan Africa: An Empirical Assessment
Prepared by Cedric Okou, John Spray, D. Filiz Unsal
Authorized for distribution by Chris Papageorgiou
July 2022
IMF Working Papers describe research in progress by the author(s) and are published to elicit comments and to encourage debate. This paper is part of a research project on macroeconomic policy in low-income countries (IATI Identifier: GB-1–202960) supported by the U.K.’s Foreign, Commonwealth and Development Office (FCDO) and the partners in the IMF’s COVID-19 Crisis Capacity Development Initiative (CCCDI)—Belgium, Canada, China, Germany, Japan, Korea, Spain, Singapore, and Switzerland. The views expressed in IMF Working Papers are those of the author(s) and do not necessarily represent the views of the IMF, its Executive Board, IMF management, the FCDO, or the partners in the CCCDI.
ABSTRACT: This paper analyzes the domestic and external drivers of local staple food prices in Sub-Saharan Africa. Using data on domestic market prices of the five most consumed staple foods from 15 countries, this paper finds that external factors drive food price inflation, but domestic factors can mitigate these vulnerabilities. On the external side, our estimations show that Sub-Saharan African countries are highly vulnerable to global food prices, with the pass-through from global to local food prices estimated close to unity for highly imported staples. On the domestic side, staple food price inflation is lower in countries with greater local production and among products with lower consumption shares. Additionally, adverse shocks such as natural disasters and wars bring 1.8 and 4 percent staple food price surges respectively beyond generalized price increases. Economic policy can lower food price inflation, as the strength of monetary policy and fiscal frameworks, the overall economic environment, and transport constraints in geographically challenged areas account for substantial cross-country differences in staple food prices.
RECOMMENDED CITATION: Okou, C., Spray, J., and Unsal, D. F. 2022. Staple Food Prices in Sub-Saharan Africa: An Empirical Assessment, IMF Working Papers, WP/22/135.
| JEL Classification Numbers: | E31; O11; O55; Q02; Q18 |
| Keywords: | Food prices; inflation; food insecurity; disasters; wars; monetary policy framework |
| Author’s E-Mail Address: | cokou@imf.org; jspray@imf.org; dunsal@imf.org |
| JEL Classification Numbers: | E31; O11; O55; Q02; Q18 |
| Keywords: | Food prices; inflation; food insecurity; disasters; wars; monetary policy framework |
| Author’s E-Mail Address: | cokou@imf.org; jspray@imf.org; dunsal@imf.org |
Title page
WORKING PAPERS
Staple Food Prices in Sub-Saharan Africa
An Empirical Assessment
Prepared by Cedric Okou, John Spray, and D. Filiz Unsal1
Contents
I. Introduction
II. Data and Context
III. A Primer on the Drivers of Staple Food Prices
IV. Empirical Strategy and Specification
V. Econometric Results
VI. Robustness
VII. Discussions and Conclusion
Tables
Appendix
References
FIGURES
Figure 1. Daily caloric contribution and net import dependence of top 5 staples
Figure 2. Evolution of Staples Food Prices
Figure 3. Estimated effects
TABLES
Table 1. Sample of countries included in empirical exercises
Table 2. Consumption share and net import dependence of the top 5 staples
Table 3. Top 5 import trading partners of SSA
Table 4. Drivers of relative staple food prices
Table 5. Effects of high net import dependence
Table 6. Prices in largest cities
Table 7. Effects of natural disasters and wars
Table 8. Persistence of the effects of natural disasters and wars
Table 9. Effects of COVID
Table 10. Deviations of relative food price change from SSA country group average
Table 11. Robustness: price effects, γhigh>75%
Table 12. Robustness: deviations of relative food price change from SSA country group average, γhigh>75%
Table 13. Robustness: price effects, NIDhigh>50%
Table A1. Data definitions, sources, and descriptive statistics
Table A2. Fixed effects versus random effects estimations
We thank Montfort Mlachila, Chris Papageorgiou, Alain Kabundi, Christian Ebeke, Tewodaj Mogues, Mariarosaria Comunale, Evrin Prifti, Christian Bogmans, Souvik Gupta, Samuel Mann, Xin Tang and the participants of the IMF Africa and Research Departments seminar for detailed comments that significantly improved the paper. We are grateful for excellent research assistance from Katrien Smuts. This paper benefited from the Research Department COVID-19 note 22 on “Food (in)security in SSA under COVID-19: a macro perspective” and the October 2021 World Economic Outlook Box 2.1. on “Food Insecurity and Prices during COVID-19”. Authors have no competing interests to declare.