Beans — Stock Variation by country
A food balance sheet presents a comprehensive picture of the pattern of a country's food supply during a specified reference period. The food balance sheet shows for each food item - i.e. each primary commodity and a number of processed commodities potentially available for human consumption - the sources of supply...
What the numbers show
Beans — Stock Variation is currently reported for 139 countries. The highest value is 312 1000 t in India; the lowest is -63 1000 t in Kenya.
The median across all reporting countries is 0 1000 t, and the mean is 5.87 1000 t.
The gap between the highest and lowest reporting country is a factor of about 5.
Over the past decade 42 countries rose and 39 fell. The largest increase was in Kazakhstan (up 2,850.0%), and the largest decrease in Egypt (down 475.0%).
Beans — Stock Variation: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | India | 312 1000 t | 2023 | up 82.5% | volatile |
| 2 | China | 201 1000 t | 2023 | up 446.6% | volatile |
| 2 | China, mainland | 201 1000 t | 2023 | up 440.7% | volatile |
| 4 | United Republic of Tanzania | 132 1000 t | 2023 | down 55.9% | volatile |
| 5 | Kazakhstan | 59 1000 t | 2023 | up 2,850.0% | volatile |
| 6 | Zambia | 40 1000 t | 2023 | — | volatile |
| 7 | Argentina | 34 1000 t | 2023 | up 780.0% | volatile |
| 8 | Australia | 25 1000 t | 2023 | — | volatile |
| 8 | Australia and New Zealand | 25 1000 t | 2023 | — | volatile |
| 10 | Dominican Republic | 24 1000 t | 2023 | up 41.2% | volatile |
| 11 | Pakistan | 21 1000 t | 2023 | — | volatile |
| 12 | Mozambique | 20 1000 t | 2023 | down 66.7% | volatile |
| 13 | Vietnam | 15 1000 t | 2023 | up 236.4% | volatile |
| 13 | Viet Nam | 15 1000 t | 2023 | up 236.4% | volatile |
| 15 | Brazil | 12 1000 t | 2023 | up 104.8% | volatile |
| 15 | Iraq | 12 1000 t | 2023 | — | volatile |
| 17 | Democratic Republic of the Congo | 10 1000 t | 2023 | down 61.5% | volatile |
| 18 | Tajikistan | 9 1000 t | 2023 | — | volatile |
| 19 | Kyrgyzstan | 6 1000 t | 2023 | — | volatile |
| 20 | Djibouti | 5 1000 t | 2023 | — | volatile |
| 21 | Bangladesh | 4 1000 t | 2023 | up 150.0% | volatile |
| 22 | Ghana | 3 1000 t | 2023 | up 130.0% | volatile |
| 22 | Philippines | 3 1000 t | 2023 | unchanged | volatile |
| 24 | Albania | 2 1000 t | 2023 | unchanged | volatile |
| 24 | United Kingdom | 2 1000 t | 2023 | down 85.7% | volatile |
| 24 | Guatemala | 2 1000 t | 2023 | up 115.4% | volatile |
| 24 | Zimbabwe | 2 1000 t | 2023 | — | volatile |
| 24 | United Kingdom of Great Britain and Northern Ireland | 2 1000 t | 2023 | down 85.7% | volatile |
| 29 | Bosnia and Herzegovina | 1 1000 t | 2023 | down 66.7% | volatile |
| 29 | Chile | 1 1000 t | 2023 | down 83.3% | volatile |
| 29 | France | 1 1000 t | 2023 | up 133.3% | volatile |
| 29 | Guinea | 1 1000 t | 2023 | — | volatile |
| 29 | Croatia | 1 1000 t | 2023 | — | volatile |
| 29 | Hungary | 1 1000 t | 2023 | — | volatile |
| 29 | Cambodia | 1 1000 t | 2023 | — | volatile |
| 29 | Lebanon | 1 1000 t | 2023 | — | volatile |
| 29 | Libya | 1 1000 t | 2023 | down 50.0% | volatile |
| 29 | Senegal | 1 1000 t | 2023 | — | volatile |
| 29 | Republic of Korea | 1 1000 t | 2023 | unchanged | volatile |
| 29 | Netherlands (Kingdom of the) | 1 1000 t | 2023 | up 150.0% | volatile |
| 41 | Armenia | 0 1000 t | 2023 | — | volatile |
| 41 | Azerbaijan | 0 1000 t | 2023 | — | volatile |
| 41 | Belgium | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Bulgaria | 0 1000 t | 2023 | down 100.0% | flat |
| 41 | Belarus | 0 1000 t | 2023 | — | volatile |
| 41 | Belize | 0 1000 t | 2023 | — | volatile |
| 41 | Botswana | 0 1000 t | 2023 | down 100.0% | flat |
| 41 | Cote d'Ivoire | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Congo | 0 1000 t | 2023 | — | volatile |
| 41 | Costa Rica | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Cuba | 0 1000 t | 2019 | — | volatile |
| 41 | Germany | 0 1000 t | 2023 | — | volatile |
| 41 | Algeria | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Ecuador | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Spain | 0 1000 t | 2023 | — | volatile |
| 41 | Estonia | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Ethiopia | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Georgia | 0 1000 t | 2023 | — | volatile |
| 41 | Guinea-Bissau | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Greece | 0 1000 t | 2023 | — | volatile |
| 41 | Honduras | 0 1000 t | 2023 | — | volatile |
| 41 | Haiti | 0 1000 t | 2023 | down 100.0% | flat |
| 41 | Indonesia | 0 1000 t | 2023 | up 100.0% | flat |
| 41 | Ireland | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Israel | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Italy | 0 1000 t | 2023 | — | volatile |
| 41 | Jamaica | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Jordan | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Kuwait | 0 1000 t | 2023 | — | volatile |
| 41 | Laos | 0 1000 t | 2023 | — | volatile |
| 41 | Sri Lanka | 0 1000 t | 2023 | up 100.0% | flat |
| 41 | Lithuania | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Latvia | 0 1000 t | 2023 | — | volatile |
| 41 | Morocco | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Moldova | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Madagascar | 0 1000 t | 2023 | — | volatile |
| 41 | Marshall Islands | 0 1000 t | 2023 | — | volatile |
| 41 | North Macedonia | 0 1000 t | 2023 | — | volatile |
| 41 | Montenegro | 0 1000 t | 2023 | — | flat |
| 41 | Mauritania | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Malawi | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Malaysia | 0 1000 t | 2023 | — | volatile |
| 41 | Namibia | 0 1000 t | 2023 | — | volatile |
| 41 | Niger | 0 1000 t | 2023 | down 100.0% | flat |
| 41 | Nigeria | 0 1000 t | 2023 | — | flat |
| 41 | Nepal | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | New Zealand | 0 1000 t | 2023 | — | volatile |
| 41 | Oman | 0 1000 t | 2023 | — | volatile |
| 41 | Panama | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Peru | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Poland | 0 1000 t | 2023 | up 100.0% | flat |
| 41 | Portugal | 0 1000 t | 2023 | — | volatile |
| 41 | Qatar | 0 1000 t | 2023 | — | volatile |
| 41 | Romania | 0 1000 t | 2023 | — | volatile |
| 41 | Rwanda | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Saudi Arabia | 0 1000 t | 2023 | — | volatile |
| 41 | Sierra Leone | 0 1000 t | 2023 | — | volatile |
| 41 | El Salvador | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Serbia | 0 1000 t | 2023 | — | flat |
| 41 | Slovakia | 0 1000 t | 2023 | — | volatile |
| 41 | Slovenia | 0 1000 t | 2023 | — | volatile |
| 41 | Eswatini | 0 1000 t | 2023 | — | volatile |
| 41 | Syria | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Thailand | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Trinidad and Tobago | 0 1000 t | 2023 | — | volatile |
| 41 | Tunisia | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | United States | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Yemen | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | South Africa | 0 1000 t | 2023 | down 100.0% | flat |
| 41 | Micronesia | 0 1000 t | 2023 | — | volatile |
| 41 | Cabo Verde | 0 1000 t | 2023 | — | volatile |
| 41 | Bolivia (Plurinational State of) | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | China, Hong Kong SAR | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Iran (Islamic Republic of) | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Republic of Moldova | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Syrian Arab Republic | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Côte d'Ivoire | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Lao People's Democratic Republic | 0 1000 t | 2023 | — | volatile |
| 41 | China, Taiwan Province of | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Democratic People's Republic of Korea | 0 1000 t | 2018 | down 100.0% | volatile |
| 171 | Lesotho | -1 1000 t | 2023 | down 133.3% | flat |
| 172 | Russia | -2 1000 t | 2023 | down 112.5% | volatile |
| 172 | Russian Federation | -2 1000 t | 2023 | down 112.5% | volatile |
| 174 | Colombia | -8 1000 t | 2023 | up 60.0% | volatile |
| 174 | Paraguay | -8 1000 t | 2023 | down 366.7% | volatile |
| 176 | Turkey | -9 1000 t | 2023 | up 43.8% | volatile |
| 176 | Caribbean | -9 1000 t | 2023 | down 147.4% | volatile |
| 176 | Türkiye | -9 1000 t | 2023 | up 43.8% | volatile |
| 179 | Canada | -11 1000 t | 2023 | up 80.0% | volatile |
| 180 | United Arab Emirates | -13 1000 t | 2023 | up 18.8% | volatile |
| 181 | Nicaragua | -15 1000 t | 2023 | up 42.3% | volatile |
| 182 | Cameroon | -17 1000 t | 2023 | down 185.0% | volatile |
| 183 | Mexico | -19 1000 t | 2023 | — | volatile |
| 184 | Egypt | -45 1000 t | 2023 | down 475.0% | volatile |
| 185 | Angola | -52 1000 t | 2023 | down 165.0% | volatile |
| 185 | Myanmar | -52 1000 t | 2023 | down 132.5% | volatile |
| 187 | Ukraine | -59 1000 t | 2023 | — | volatile |
| 188 | Kenya | -63 1000 t | 2023 | — | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- Asia 574 1000 t
- World 555 1000 t
- Southern Asia 338 1000 t
- Eastern Asia 204 1000 t
- Eastern Africa 134 1000 t
- Least Developed Countries (LDCs) 101 1000 t
- Land Locked Developing Countries (LLDCs) 92 1000 t
- Low Income Food Deficit Countries (LIFDCs) 85 1000 t
- Central Asia 74 1000 t
- South America 31 1000 t
- Africa 28 1000 t
- Oceania 25 1000 t
- Western Africa 12 1000 t
- European Union (27) 5 1000 t
- Southern Europe 5 1000 t
- Net Food Importing Developing Countries (NFIDCs) 4 1000 t
- Western Europe 2 1000 t
- Northern Europe 2 1000 t
- United States of America 0 1000 t
- Southern Africa -1 1000 t
- Small island developing States (SIDS) -9 1000 t
- Western Asia -9 1000 t
- Northern America -11 1000 t
- Americas -22 1000 t
- South-Eastern Asia -32 1000 t
- Central America -33 1000 t
- Northern Africa -44 1000 t
- Europe -51 1000 t
- Eastern Europe -60 1000 t
- Middle Africa -73 1000 t
About this data
A food balance sheet presents a comprehensive picture of the pattern of a country's food supply during a specified reference period. The food balance sheet shows for each food item - i.e. each primary commodity and a number of processed commodities potentially available for human consumption - the sources of supply and its utilization. The total quantity of foodstuffs produced in a country added to the total quantity imported and adjusted to any change in stocks that may have occurred since the beginning of the reference period gives the supply available during that period. On the utilization side a distinction is made between the quantities exported, fed to livestock, used for seed, put to manufacture for food use and non-food uses, losses during storage and transportation, and food supplies available for human consumption. The per caput supply of each such food item available for human consumption is then obtained by dividing the respective quantity by the related data on the population actually partaking of it. Data on per capita food supplies are expressed in terms of quantity and - by applying appropriate food composition factors for all primary and processed products - also in terms of caloric value and protein and fat content.