Together, Russia and Ukraine supply about 30% of the world’s wheat and barley exports. Ukraine is also a major cooking fuel, accounting for 14% of globally traded corn and 75% of globally traded sunflower oil. The supply of these products is being severely disrupted due to the ongoing conflict. In the case of Ukraine, this is due to disruption of the Black Sea shipping route. In the case of Russia, this is due to the effects of sanctions on the agricultural supply chain. With extreme global weather patterns (such as heat in parts of India, the United States and France; historic droughts in East Africa; and floods in China) and increasing protectionism, this has led to sharp rise in staple food prices that have led to significant welfare losses. On poor families in developing countries (Arezki 2022, Artuc et al. 2022, Porto and Rijkers 2022).
To put these recent changes in a historical context, in Figure 1 we plot the FAO food price index between 1961 and 2022. The current figure of 145.5 is a record high, easily surpassing the previous spikes of the 1970s and early 2010s. Recent growth has been driven mainly by cereals and vegetable oils.
Figure 1 FAO Real Food Price Index, 1961-2022
From the conflict in Europe to the conflict in Africa
Understanding the underlying effects of these food price shocks on the African conflict is essential. State fragility and repeated civil wars are costly impediments to economic development in many African countries. Identifying how and why economic fluctuations affect civil conflict can help to articulate policies that promote peace.
A process predicts that the price of the product will be higher Reduce Conflict in the area that produces the given product. This is due to increasing productivity wages in the affected sector and thus increasing the cost of opportunities for marginal workers to participate in illegal or risky economic activities, such as joining armed groups (Dal Bo and Dal Bo 2011). This prediction is therefore particularly relevant for labor-intensive sectors, such as coffee production in Colombia and cereal farming in Africa in general (Dubbe & Vargas 2013, Burman & Kautenier 2015, McGuirk & Burke 2020).
However, as we documented in McGuirk and Burke (2020), there are also countervailing mechanisms through which staple food prices can rise. Increase Conflict Since food occupies a large part of Africa’s household spending (on average about 40%), the net impact of food price shocks for a given person will critically depend on whether one is a net producer or a net consumer of a relevant product. Adequately high food prices can force a net consumer to resort to risky economic coping strategies in order to maintain a required calorie intake, especially in the absence of conventional financially smooth processes. Thus, just as rising prices could induce marginal workers To avoid Participating in armed groups in areas where crops are grown, they can also persuade marginal workers. Join Armed groups in areas where crops are eaten.
We find evidence of this countervailing effect in our paper. We examine the effects of rising food prices on the incidence of intergroup conflicts at the 0.5-degree grid cell level (55km x 55km in the equator) in Africa. To differentiate between channels we create two shift-share instruments: a ‘producer price index’ (PPI) that combines with a temporary change in world food prices with a cross-sectional change in crop production across cells; And a ‘Consumer Price Index’ (CPI) which instead uses cross-sectional changes in crop use across the country. We assume that a standard deviation in PPI has increased Reduces Conflicts within a cell increase by an average of 17.2%, while a typical deviation in CPI increases Increases Conflict in a cell is 8.6%. Our estimates indicate that the countries most at risk of conflict through CPI influence are Rwanda, Gambia, Sierra Leone, Somalia, Swaziland / Swatini, Central African Republic, Djibouti, Mozambique, South Africa, Zimbabwe, Ghana, Niger and Mali.
We can use these estimates to predict the specific effects of rising wheat and corn prices from January to April 2022, which we assumed were primarily due to the war in Ukraine. Through the PPI effect, the conflict is reduced by 1.7%. Through the CPI effect, the conflict increased by 6.17%. Since the PPI effect is only relevant in areas where crops are grown, we estimate that the weighted average effect of the Russian invasion is 5.3% increase in inter-group conflict in Africa.
We illustrate these relationships graphically using the updated raw data in Figure 2. For simplicity, we use the FAO Food Price Index (again in the real sense), which is universally available and easy to track over time. We simply plot the relationship between the food price index of the x-axis and the natural log of death in the event of a cell-year inter-group conflict on the y-axis.1 We call these incidents ‘factor conflicts’ because they usually capture conflicts between organized armed groups competing for control of the region.
To distinguish between reciprocal effects, we split the sample into two chambers. ‘Agricultural cell’ is defined as the area at the top of a crop field, which means that at least 22% of a cell’s land is used for crop production (Monfreda et al. 2008). These cells make up about 42% of the African population. The rest of the ‘other cells’. The plots in Figure 2 indicate that the 50-point price spike – a level of change between 2019 and 2022 – is associated with a 5.8% decline in agricultural cells and a 1.8% increase in deaths in other cells.
Figure 2 The relationship between the FAO real food price index and the loss of life in agriculture versus other cells from the intergroup ‘factor conflict’
A second countervailing effect is related to what is commonly called ‘food riots’. Throughout history, scholars have documented the role of rapidly rising staple food prices in the outbreak of riots, protests, looting, and even peasant revolts (Bellemere 2015, Ubilava 2022). These actions differ from inter-group factor conflicts in that they are usually aimed at influencing policy (through demonstrations), output (through looting), or otherwise make more atomic and uncoordinated decisions aimed at exposing inequality. Often with food price spikes. These phenomena may occur due to the presence of net consumers in both agricultural and non-agricultural cells. We label these as ‘output conflict’ events, measured on ACLED datasets as riots, demonstrations, or other violence against civilians.2
We estimate that a typical deviation increase in PPI and CPI increases the probability of output conflict by 18.9% and 14.4%, respectively. Unlike in the case of factor conflicts, the price push here leads to further conflicts in both agricultural and non-agricultural sectors.
We re-illustrate this relationship graphically using updated data from the FAO Food Price Index in Figure 3. We show that in both types of cells, higher output results in more output collision deaths. The overall effect is thus unambiguous.
Figure 3 The relationship between FAO real food price index and loss of life from ‘output conflict’ in agriculture vs. other cells
In short, Russia’s invasion of Ukraine has led to a historically sharp rise in staple food items. These in turn could affect the spatial distribution of conflict events in Africa next year. We predict that intergroup ‘factor conflict’ events will move from the most productive agricultural areas and to areas with low crop production. Our estimates suggest that rising prices will also contribute to a higher probability of ‘output conflict’ – small-scale riots, protests and / or civil violence in both food-producing and food-consuming areas. Policies to improve agricultural productivity in Africa can protect both producers and consumers from the detrimental effects of future international price volatility.
Arezki, R. (2022), “War in Ukraine, Impact in Africa. Impact of Rising Energy and Food Prices”, VoxEU.org.
Artuc, E, G Falcone, G Porto and B Rijker (2022), “War-induced food inflation hurts the poor”, VoxEU.org, 1 April.
Bellemare, MF (2015), “Food Rise, Food Price Instability, and Social Instability”, American Journal of Agricultural Economics 97 (1): 1-21.
Berman, N and M Couttenier (2015), “External Shocks, Internal Shots: The Geography of Civil Conflicts”, Economics and Statistics Review 97 (4): 758-776.
Dubey, O. and JF Vargas (2013), “Commodity Prices and Civil Conflict: Evidence from Colombia”, Review of Economic Studies 80 (4): 1384-1421.
McGuirk, E. and M. Burke (2020), “The Economic Source of Conflict in Africa”, Journal of Political Economy 128 (10): 3940-3997.
Monfreda, C. N. Ramankutty and J. A. Foley (2008), “Planetary Cultivation: 2. Crop Area, Yield, Physiological Types and Geographical Distribution of Net Early Production in 2000”, Global biochemical cycle 22 (1).
Porto, G and B Rijker (2022), “Food Crisis No Respect for Borders”, VoxEU.org, 20 May.
Ubilava, D. J. Hastings and K. Atale (2022), “Agriculture Windfalls and the Seasonality of Political Violence in Africa”, preprint.
1 Conflict data came from the Upsala Conflict Data Program (UCDP) (https://ucdp.uu.se/).
2 See https://acleddata.com/#/dashboard