Vulnerability to Global Market Shocks V.2: Price Shocks to Major Staple Foods

Overview

All 15 staple foods: All products combined, there is a concentration of the most dependent imports countries in Africa. Indeed, more than a dozen of the countries in the continent have a high index (above 50%). In the African continent, the most vulnerable countries are Djibouti (99.06%), Mauritius (94.80%).
Main 3 staple foods: Regarding wheat, maize and rice, four countries appear to be the most vulnerable because of their status as net importers (Djibouti, Oman, Bahrain and Iceland), while 22 countries are self-sufficient. Africa remains the continent with the highest number of import-vulnerable countries.
Wheat: Wheat is a widely traded commodity across 183 countries. Among them, 26 countries serve as net exporters, meeting 100% of the consumption needs for 63 other countries. The remaining countries exhibit varying degrees of dependence on wheat imports, ranging from 4% to 99.9%.
Rice: Rice is heavily imported in numerous regions, including Europe, Africa, Canada, and Australia. Among 159 countries that import rice, 45% of them are entirely dependent on imports for their rice supply.
Maize: Maize is traded in 168 countries, with notable import reliance in the Middle East, West South America, North Europe, and parts of South Africa. Of these, 18% of countries are responsible for meeting the needs of the rest of the world.
Sorghum: Sorghum is primarily imported in China, Canada, Central Asia, and parts of Europe. Seventeen countries exhibit 100% reliance on sorghum imports.
Millet: Millet is imported in 53 countries, with 33 of them being entirely dependent on imports. Seventeen countries are net exporters of millet.
Beans: The index shows that there are around twenty net exporting countries with a heterogeneous distribution across continents (e.g., Canada, the United States, Argentina, South Africa, and Australia). Conversely, around forty countries are net importers. Some countries import all of their domestic requirements, including Afghanistan, Libya, Uzbekistan, Nigeria, and Vietnam. They are therefore particularly vulnerable to potential price increases. In addition, self-sufficient countries are mainly located in Africa (e.g., Mali, Gabon, Ghana, Benin, Togo, and Zambia).
Groundnuts: Net exporters are concentrated in the Americas (e.g., the United States, Brazil, Argentina, and Bolivia) and Africa (e.g., Senegal, Sudan, Ethiopia, and Tanzania), as well as several countries in Asia. Conversely, countries with a high and very high level of dependency are mainly located in Europe, Central Asia, and southwest Asia. Finally, the countries that self-sufficient in groundnuts are mainly located in Africa.
Soybeans: Thirty-six countries import all their soybean needs, while another 40 rely on imports for over half of their requirements. Although they are distributed across all continents, we observe a concentration in Europe (e.g., Germany, Spain, and Scandinavia), Asia (e.g., China, Mongolia, and Indonesia) and in South America (e.g., Mexico, Colombia, and Peru). Most countries in Africa are self-sufficient in soybeans, meaning they have little or no imports and exports. Major exporters include the United States, Canada, Brazil, and Ukraine.
Cassava: Cassava is a key imported commodity in North America, Asia, Europe, and Australia. Forty countries entirely depend on cassava imports.
Yams: Twenty-two countries import yams, with 21 of them being 100% reliant on imports. In contrast, 10 countries are net exporters of yams.
Potatoes: Across all the countries covered in this analysis, we generally observe low import dependence, indicating that potatoes are not widely traded. Indeed, the number of self-sufficient or very weakly dependent countries dominates. The few most dependent countries with an import dependence ratio greater than 50% are located in southern Africa (Botswana, Namibia, and Eswatini), in West Africa (e.g., Benin, Togo, Senegal, Cote d’Ivoire, and Senegal), in South America (e.g., Paraguay and Suriname), and southeast Asia (e.g., Cambodia, Malaysia, and Thailand).
Sweet Potatoes: Sweet potatoes are rarely traded internationally. All or almost all of South America, Africa, and Asia are self-sufficient in sweet potatoes, meaning that they import or export less than 5% of their domestic requirements. Exporters include the United States, Mexico, Egypt, and South Africa. Although Canada, western Europe, and Russia are shown as highly dependent on imports, in fact, their consumption of sweet potatoes is very low.
Plantains: Among the 64 countries that import plantains, 59 rely on imports for 100% of their needs. Thirteen countries, including Ecuador and Myanmar, serve as notable net exporters of plantains.
Vegetable oil: Central and South Asia, the Middle East, many African countries, and parts of West South America significantly rely on vegetable oil imports. A total of 25 countries imports 100% of their vegetable oil needs.
Sugar: In Latin America, most countries are exporters, but in Africa, most are heavily dependent on sugar imports. Only six African countries are exporters (South Africa, Zimbabwe, Zambia, Zambia, Malawi, and Egypt), and a handful are self-sufficient or weakly dependent. In Asia, Russia, India, and Thailand are among the few exporters, while southwest Asia, Central Asia, and southeast Asia are heavily dependent on sugar imports. In Europe, sugar beet production allows some northern European countries to export sugar, while southern European countries are heavy importers.

The import dependency ratio is based on data on imports, exports, and domestic supply quantity from the FAO Food Balance Sheet. Domestic supply quantity is calculated by the FAO as production plus net imports plus net reductions in stocks minus losses. The data are available annually for 183 countries. We use data for 2020, the most recent available, and 15 staple foods: wheat, rice, maize, sorghum, millet, cassava, sweet potatoes, yams, plantains, beans, groundnuts, soybeans, sugar, and vegetable oil. In the FAO database, the cereals, cassava, and potatoes include products made from the staple crop such as wheat bread and maize flour. Vegetable oil is an aggregated category that includes 13 types of oil in the original FAO database.
The import dependency ratio is calculated as follows:

For net importers, the import dependency ratio is positive, while for net exporters, the import dependency ratio is negative. In a few cases, the net imports were greater than the domestic supply quantity, which appears to reflect data errors. In these cases, we set the import dependency ratio at 100 percent.

Data source for this analysis

The contribution of each commodity to the caloric intake in each country is calculated using the Food Balance Sheets calculated by the Food and Agriculture Organization . These data are available on an annual basis for 182 countries. The most recent data are for 2020. We calculate the total caloric intake and then the contribution of four commodities: wheat, maize, rice, and sorghum. In each case, the commodities include calories consumed from grain products. For example, “wheat and products” includes consumption of wheat, flour, bread, and other wheat products.

Underlying data: the full dataset used for the analysis

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Overview

This map provides a visual representation of the share of the population experiencing moderate to severe food insecurity in various countries. The data indicates that a significant number of countries in Africa exhibit a very high population share experiencing food insecurity. South Asia, Central and South America follow closely in the number of countries with high food insecurity rates.

The data on moderate and food insecurity (MFI) are obtained from the FAO Suite of Food Security Indicators. These data are based on household surveys using the Food Insecurity Experience Scale (FIES). For 2020, estimates of MFI are available for 142 countries of 183 countries, leaving 41 countries for which we have data on caloric intake and net imports but not food insecurity.
To fill this gap, we use interpolated values based on regression estimates of moderate and severe food insecurity as a function of per capita gross domestic product (purchasing power parity, 2017 international US dollars), the FAO Prevalence of Undernourishment, the Gini coefficient, and the headcount poverty rate (FAO and World Bank). To get estimates of food insecurity, we use as many of these proxy indicators as are available for the country in question, resulting in the use of seven regression models with different combinations of these indicators. All models use linear and quadratic versions of the explanatory variables. These models can explain most of the variance in the food insecurity rate, with values of R2 between 0.61 and 0.81. The 41 countries for which is was necessary to interpolate MFI values are Burundi, Bahrain, Belarus, Bolivia, Bhutan, China, Colombia, Cuba, Cyprus, Dominica, Dominican Republic, Micronesia, Gabon, Guyana, India, Iraq, Saint Lucia, Mali, New Caledonia, Niger, Nicaragua, Nauru, Oman, Panama, Papua New Guinea, North Korea, French Polynesia, Qatar, Rwanda, Saudi Arabia, Solomon Islands, Seychelles, Syrian Arab Republic, Chad, Tajikistan, Turkmenistan, Timor-Leste, Turkey, Taiwan, Venezuela, and Yemen.
More information on the data and methods, including the interpolation procedure and sensitivity analysis, is available from Minot, N. et al. (2023). How vulnerable are countries to higher food prices? A new approach. Washington, DC: International Food Policy Research Institute.

Data source for this analysis

These data are based on household surveys using the Food Insecurity Experience Scale (FIES). To fill this gap, we use interpolated values based on regression estimates of moderate and severe food insecurity as a function of per capita gross domestic product, the FAO Prevalence of Undernourishment, the Gini coefficient , and the headcount poverty rate.

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• Underlying data: the full dataset used for the analysis
• Map image file
• Map PDF
• Table PDF

Overview

All 15 staple foods: The national Food Import Vulnerability Index (FIVI) is calculated as the geometric mean of two components: the share of calories from the 15 staple foods that are imported and the share of the population experiencing food insecurity. According to the national FIVI, the countries most vulnerable to higher world prices of staple foods are Yemen (with a score of 84) and Haiti (76), followed by Eswatini, Botswana, and Comoros (all three at 71). In contrast, Argentina, Russia, and Paraguay stand out as the least vulnerable.
Wheat: Yemen remains the most vulnerable country regarding wheat, with an index value of 70, followed by Afghanistan and Djibouti with values of 54. Importance of wheat in Yemen's caloric needs (46%) and its status as a near-net importer explains this ranking.
Rice: The most vulnerable countries regarding rice are Liberia, Gambia, and Guinea-Bissau, with index values of 61, 59, and 59, respectively.
Maize: Due to a high dependence on imports (with a rate of more than 70%) Zimbabwe, Lesotho, and Eswatini are the most vulnerable countries regarding maize price hikes.
Sorghum: South Sudan, Rwanda, and Eswatini represent the most vulnerable countries to sorghum price increases.
Millet: Nineteen countries are marked as vulnerable to millet price increases, with index values ranging from 1.7 to 8.5, reflecting a low caloric share and limited trade for millet.
Beans: In general, we observe low vulnerability in all the countries covered due to the low caloric contribution of the product on the one hand and the low level of dependence on imports on the other. Only two countries qualify as having low vulnerability to higher world prices in beans: El Salvador and Venezuela. No country qualifies as having medium, high, or very high vulnerability.
Groundnuts: Vulnerability to external shocks for this product is relatively low due to low caloric intake and low dependence on imports. Numerous countries in sub-Saharan Africa are not vulnerable to higher groundnut prices because they are exporters. This includes countries in the Sahel, Horn of Africa, and southeastern Africa.
Soybeans: Due to low caloric intake and low dependence on imports, the vulnerability to higher soybean prices is relatively low. The highest FIVI scores are in Timor-Leste, Taiwan, and Thailand, though even these scores are less than 20, placing them in the category of very low vulnerability. China is the largest importer of soybeans in the world, importing more than 80% of its requirements, but its FIVI score is low because soybeans play a minor role in the diet and food insecurity is not widespread.
Yams: Sixteen countries are identified as vulnerable to yam price increases, with small index values ranging from 0.5 to 5.2.
Cassava: Given the small share of cassava in caloric intake, only Rwanda and Laos have FIVI values higher than 20, reflecting lower vulnerability to price shocks for cassava worldwide.
Potatoes: Across the countries covered by the index, there is generally a low vulnerability to higher prices of potatoes. The country most vulnerable is Barbados, for which the FIVI score is just 20. All other countries have very low or negligible vulnerability or they export potatoes.
Sweet potatoes: All countries are have negligible vulnerability in sweet potatoes or export the product. This reflects the fact that sweet potatoes are not widely traded and/or are not an important source of calories. The most vulnerable country is Mauritania, though its FIVI score is just 7.4, indicating negligible vulnerability.
Vegetable oil: Congo, Zimbabwe, and Yemen are identified as the most vulnerable countries despite the relatively small share of caloric intake from vegetable oil in their diets.
Sugar: Four countries are classified as having high vulnerability to spikes in international sugar prices: the Gambia, Yemen, Haiti, and Djibouti. Another 29 countries are considered to have medium vulnerability. African countries affected by medium vulnerability are Libya, Botswana, Namibia, Sudan, South Sudan, Guinea, and Mauritania. In South America, Venezuela and Suriname are in the medium vulnerability category. Finally, in Asia, Afghanistan, Iraq and Syria are in the same situation.
Plantains: The number of vulnerable countries to plantain price rises reaches 48, with index values ranging from 0.5 to 15.5, highlighting a low degree of vulnerability.

The Food Import Vulnerability Index (FIVI) used in this analysis has three components:

• the share of calories that the food commodity represents in the national diet,
• the share of national consumption of the commodity that comes from imports, and
• the share of the population experiencing moderate or severe food insecurity

The data for the share of calories and the import dependency ratio were downloaded from the FAO Food Balance Sheet. The data on the share of the population experiencing food insecurity were obtained from the FAO Suite of Food Security Indicators, although this variable had to be interpolated using data on per capita GDP and the prevalence of undernourishment for some countries (see the methods description for the Food Insecurity section). The coverage is 183 countries and 15 staple foods for the year 2020. The staple foods included in the FIVI are wheat, rice, maize, sorghum, millet, cassava, sweet potatoes, yams, plantains, beans, groundnuts, soybeans, sugar, and vegetable oil. In the FAO database, the cereals, cassava, and potatoes include products made from the staple crop such as wheat bread and maize flour. Vegetable oil is an aggregated category that includes 13 types of oil in the original FAO database.
The commodity-level FIVI is calculated at the country-commodity level using the following expression: :

Although index i refers to the 15 staple foods, index j refers to all 90 food commodities in the FAO database. Thus, the caloric share for each staple food is the proportion of total caloric intake. In the case of exporters, the import dependency ratio is negative. Since negative numbers cannot be raised to a fractional power, we set the value of FIVI to zero. This is consistent with the fact that an exporter of a given commodity is not vulnerable to increased world prices of the commodity.
The rational for using a multiplicative index is that the vulnerability should be zero if a) the commodity does not play a role in the local diet, b) domestic consumption is based entirely on domestic production without relying on imports, or c) there is no food insecurity in the country. The base index uses equal weights for the three components, but we carry out sensitivity analysis to determine whether the index and rankings are affected by applying different weights to the three components.
The national Food Import Vulnerability Index (FIVI) is calculated as follows:

The first term in parentheses is the weighted average of the import dependence ratio ((M_ci-X_ci)/S_ci) across the 15 staple commodities, where the weights are the caloric contribution of each commodity to total staple calories in that country (C_ic/ΣC_ic). Note that, unlike the calculation for the commodity-level FIVI, the summation in the denominator is limited to the 15 staple foods. As above, if the country exports a commodity, the import dependency ratio is set to zero for that commodity, reflecting the fact that it is not vulnerable to higher world prices of that commodity. The weighted average of the import shares for each commodity is equal to the share of the calories from the 15 staple foods that is imported. The second term is the share of the population that is moderately or severely food insecure (MFI_c)
The national FIVI will be low if imports represent a small share of the calories consumed from the 15 staple foods or the share of the population experiencing moderate or severe food insecurity is low. Conversely, the national FIVI will be high if a large share of the calories consumed of the 15 staple foods is imported and a large proportion of the population is moderately or severely food insecure.
More information on the data and methods, including the interpolation procedure and sensitivity analysis, is available from Minot, N. et al. (2023). How vulnerable are countries to higher food prices? A new approach. Washington, DC: International Food Policy Research Institute.

Data source for this analysis

The contribution of each commodity to the caloric intake in each country is calculated using the Food Balance Sheets calculated by the Food and Agriculture Organization . These data are available on an annual basis for 182 countries. The most recent data are for 2020. We calculate the total caloric intake and then the contribution of four commodities: wheat, maize, rice, and sorghum. In each case, the commodities include calories consumed from grain products. For example, “wheat and products” includes consumption of wheat, flour, bread, and other wheat products.

Download content here

• Underlying data: the full dataset used for the analysis
• Map image file
• Map PDF
• Table PDF