Cocoa Beans and products — 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
Cocoa Beans and products — Stock Variation is currently reported for 181 countries. The highest value is 303 1000 t in Côte d'Ivoire; the lowest is -52 1000 t in Ghana.
The median across all reporting countries is 0 1000 t, and the mean is 3.24 1000 t.
The gap between the highest and lowest reporting country is a factor of about 6.
Over the past decade 29 countries rose and 36 fell. The largest increase was in Indonesia (up 9,800.0%), and the largest decrease in United Arab Emirates (down 1,250.0%).
Cocoa Beans and products — Stock Variation: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Côte d'Ivoire | 303 1000 t | 2023 | up 107.5% | volatile |
| 2 | Netherlands (Kingdom of the) | 105 1000 t | 2023 | up 171.9% | volatile |
| 3 | Indonesia | 97 1000 t | 2023 | up 9,800.0% | volatile |
| 4 | Malaysia | 54 1000 t | 2023 | up 1,700.0% | volatile |
| 5 | India | 32 1000 t | 2023 | up 346.2% | volatile |
| 6 | Algeria | 19 1000 t | 2023 | up 171.4% | volatile |
| 7 | Belgium | 18 1000 t | 2023 | down 35.7% | volatile |
| 8 | Brazil | 14 1000 t | 2023 | up 158.3% | volatile |
| 8 | United Kingdom of Great Britain and Northern Ireland | 14 1000 t | 2023 | — | volatile |
| 10 | Iran (Islamic Republic of) | 10 1000 t | 2023 | up 433.3% | volatile |
| 11 | Colombia | 9 1000 t | 2023 | up 400.0% | volatile |
| 11 | Thailand | 9 1000 t | 2023 | up 350.0% | volatile |
| 11 | Uzbekistan | 9 1000 t | 2023 | up 800.0% | volatile |
| 14 | Czechia | 8 1000 t | 2023 | — | volatile |
| 15 | Madagascar | 6 1000 t | 2023 | up 700.0% | volatile |
| 16 | Spain | 5 1000 t | 2023 | down 83.9% | volatile |
| 16 | Hungary | 5 1000 t | 2023 | — | volatile |
| 18 | Viet Nam | 4 1000 t | 2023 | up 300.0% | volatile |
| 19 | Morocco | 3 1000 t | 2023 | up 50.0% | volatile |
| 19 | Romania | 3 1000 t | 2023 | up 200.0% | volatile |
| 21 | Argentina | 2 1000 t | 2023 | up 300.0% | volatile |
| 21 | Greece | 2 1000 t | 2023 | — | volatile |
| 21 | Iraq | 2 1000 t | 2023 | up 300.0% | volatile |
| 21 | Libya | 2 1000 t | 2023 | up 300.0% | volatile |
| 21 | Portugal | 2 1000 t | 2023 | unchanged | volatile |
| 21 | Melanesia | 2 1000 t | 2023 | — | volatile |
| 27 | Azerbaijan | 1 1000 t | 2023 | unchanged | volatile |
| 27 | Bulgaria | 1 1000 t | 2023 | unchanged | volatile |
| 27 | Bosnia and Herzegovina | 1 1000 t | 2023 | — | flat |
| 27 | Finland | 1 1000 t | 2023 | unchanged | volatile |
| 27 | Guatemala | 1 1000 t | 2023 | up 200.0% | volatile |
| 27 | Italy | 1 1000 t | 2023 | — | volatile |
| 27 | North Macedonia | 1 1000 t | 2023 | — | volatile |
| 27 | Papua New Guinea | 1 1000 t | 2023 | — | volatile |
| 27 | Senegal | 1 1000 t | 2023 | unchanged | volatile |
| 27 | Slovenia | 1 1000 t | 2023 | — | volatile |
| 27 | Ukraine | 1 1000 t | 2023 | — | volatile |
| 27 | Yemen | 1 1000 t | 2023 | unchanged | volatile |
| 27 | Syrian Arab Republic | 1 1000 t | 2023 | — | volatile |
| 40 | Afghanistan | 0 1000 t | 2023 | down 100.0% | volatile |
| 40 | Angola | 0 1000 t | 2023 | — | volatile |
| 40 | Albania | 0 1000 t | 2023 | — | flat |
| 40 | Armenia | 0 1000 t | 2023 | up 100.0% | volatile |
| 40 | Antigua and Barbuda | 0 1000 t | 2023 | — | flat |
| 40 | Burkina Faso | 0 1000 t | 2023 | — | volatile |
| 40 | Bangladesh | 0 1000 t | 2023 | — | volatile |
| 40 | Bahrain | 0 1000 t | 2023 | — | flat |
| 40 | Bahamas | 0 1000 t | 2023 | — | flat |
| 40 | Belarus | 0 1000 t | 2023 | down 100.0% | volatile |
| 40 | Belize | 0 1000 t | 2023 | — | flat |
| 40 | Barbados | 0 1000 t | 2023 | — | flat |
| 40 | Bhutan | 0 1000 t | 2023 | — | flat |
| 40 | Botswana | 0 1000 t | 2023 | — | volatile |
| 40 | Chile | 0 1000 t | 2023 | — | volatile |
| 40 | Cameroon | 0 1000 t | 2023 | down 100.0% | volatile |
| 40 | Congo | 0 1000 t | 2023 | — | volatile |
| 40 | Comoros | 0 1000 t | 2023 | — | flat |
| 40 | Costa Rica | 0 1000 t | 2023 | — | volatile |
| 40 | Cuba | 0 1000 t | 2019 | — | flat |
| 40 | Cyprus | 0 1000 t | 2023 | — | flat |
| 40 | Germany | 0 1000 t | 2023 | up 100.0% | volatile |
| 40 | Djibouti | 0 1000 t | 2023 | — | flat |
| 40 | Ecuador | 0 1000 t | 2023 | up 100.0% | volatile |
| 40 | Estonia | 0 1000 t | 2023 | up 100.0% | volatile |
| 40 | Ethiopia | 0 1000 t | 2023 | — | flat |
| 40 | Fiji | 0 1000 t | 2023 | — | flat |
| 40 | France | 0 1000 t | 2023 | — | volatile |
| 40 | Gabon | 0 1000 t | 2023 | — | flat |
| 40 | Georgia | 0 1000 t | 2023 | — | volatile |
| 40 | Guinea | 0 1000 t | 2023 | down 100.0% | volatile |
| 40 | Gambia | 0 1000 t | 2023 | — | flat |
| 40 | Guinea-Bissau | 0 1000 t | 2023 | — | flat |
| 40 | Grenada | 0 1000 t | 2023 | — | volatile |
| 40 | Guyana | 0 1000 t | 2023 | — | flat |
| 40 | Honduras | 0 1000 t | 2023 | — | volatile |
| 40 | Croatia | 0 1000 t | 2023 | down 100.0% | volatile |
| 40 | Ireland | 0 1000 t | 2023 | down 100.0% | volatile |
| 40 | Iceland | 0 1000 t | 2023 | — | flat |
| 40 | Jamaica | 0 1000 t | 2023 | — | flat |
| 40 | Jordan | 0 1000 t | 2023 | down 100.0% | volatile |
| 40 | Kazakhstan | 0 1000 t | 2023 | down 100.0% | volatile |
| 40 | Kenya | 0 1000 t | 2023 | down 100.0% | volatile |
| 40 | Kyrgyzstan | 0 1000 t | 2023 | — | volatile |
| 40 | Cambodia | 0 1000 t | 2023 | — | flat |
| 40 | Kiribati | 0 1000 t | 2023 | — | flat |
| 40 | Saint Kitts and Nevis | 0 1000 t | 2023 | — | flat |
| 40 | Kuwait | 0 1000 t | 2023 | down 100.0% | volatile |
| 40 | Saint Lucia | 0 1000 t | 2023 | — | flat |
| 40 | Sri Lanka | 0 1000 t | 2023 | down 100.0% | volatile |
| 40 | Lesotho | 0 1000 t | 2023 | — | flat |
| 40 | Luxembourg | 0 1000 t | 2023 | — | volatile |
| 40 | Latvia | 0 1000 t | 2023 | — | volatile |
| 40 | Maldives | 0 1000 t | 2023 | — | volatile |
| 40 | Marshall Islands | 0 1000 t | 2023 | — | flat |
| 40 | Malta | 0 1000 t | 2023 | — | flat |
| 40 | Myanmar | 0 1000 t | 2023 | — | volatile |
| 40 | Montenegro | 0 1000 t | 2023 | — | flat |
| 40 | Mongolia | 0 1000 t | 2023 | up 100.0% | volatile |
| 40 | Mozambique | 0 1000 t | 2023 | — | flat |
| 40 | Mauritania | 0 1000 t | 2023 | — | volatile |
| 40 | Mauritius | 0 1000 t | 2023 | — | flat |
| 40 | Malawi | 0 1000 t | 2023 | — | flat |
| 40 | Namibia | 0 1000 t | 2023 | — | volatile |
| 40 | New Caledonia | 0 1000 t | 2023 | — | flat |
| 40 | Niger | 0 1000 t | 2023 | — | volatile |
| 40 | Nigeria | 0 1000 t | 2023 | down 100.0% | volatile |
| 40 | Nicaragua | 0 1000 t | 2023 | — | volatile |
| 40 | Norway | 0 1000 t | 2023 | — | volatile |
| 40 | Nepal | 0 1000 t | 2023 | — | volatile |
| 40 | Nauru | 0 1000 t | 2023 | — | flat |
| 40 | New Zealand | 0 1000 t | 2023 | — | volatile |
| 40 | Pakistan | 0 1000 t | 2023 | — | flat |
| 40 | Panama | 0 1000 t | 2023 | — | volatile |
| 40 | Philippines | 0 1000 t | 2023 | up 100.0% | volatile |
| 40 | Poland | 0 1000 t | 2023 | up 100.0% | volatile |
| 40 | Paraguay | 0 1000 t | 2023 | — | flat |
| 40 | French Polynesia | 0 1000 t | 2023 | — | flat |
| 40 | Qatar | 0 1000 t | 2023 | — | volatile |
| 40 | Rwanda | 0 1000 t | 2023 | — | flat |
| 40 | Saudi Arabia | 0 1000 t | 2023 | down 100.0% | falling |
| 40 | Solomon Islands | 0 1000 t | 2023 | — | flat |
| 40 | El Salvador | 0 1000 t | 2023 | — | flat |
| 40 | Serbia | 0 1000 t | 2023 | — | flat |
| 40 | Sao Tome and Principe | 0 1000 t | 2023 | — | volatile |
| 40 | Suriname | 0 1000 t | 2023 | — | flat |
| 40 | Slovakia | 0 1000 t | 2023 | down 100.0% | volatile |
| 40 | Sweden | 0 1000 t | 2023 | — | flat |
| 40 | Eswatini | 0 1000 t | 2023 | — | flat |
| 40 | Seychelles | 0 1000 t | 2023 | — | flat |
| 40 | Tajikistan | 0 1000 t | 2023 | down 100.0% | volatile |
| 40 | Turkmenistan | 0 1000 t | 2023 | down 100.0% | flat |
| 40 | Tonga | 0 1000 t | 2023 | — | flat |
| 40 | Trinidad and Tobago | 0 1000 t | 2023 | — | volatile |
| 40 | Tunisia | 0 1000 t | 2023 | — | volatile |
| 40 | Tuvalu | 0 1000 t | 2023 | — | flat |
| 40 | Uganda | 0 1000 t | 2023 | — | flat |
| 40 | Uruguay | 0 1000 t | 2023 | — | volatile |
| 40 | Saint Vincent and the Grenadines | 0 1000 t | 2023 | — | flat |
| 40 | Vanuatu | 0 1000 t | 2023 | — | volatile |
| 40 | Samoa | 0 1000 t | 2023 | — | flat |
| 40 | Zambia | 0 1000 t | 2023 | — | flat |
| 40 | Zimbabwe | 0 1000 t | 2023 | — | flat |
| 40 | Micronesia | 0 1000 t | 2023 | — | flat |
| 40 | Timor-Leste | 0 1000 t | 2023 | — | flat |
| 40 | Cabo Verde | 0 1000 t | 2023 | — | flat |
| 40 | Polynesia | 0 1000 t | 2023 | — | flat |
| 40 | Democratic Republic of the Congo | 0 1000 t | 2023 | — | volatile |
| 40 | Bolivia (Plurinational State of) | 0 1000 t | 2023 | down 100.0% | volatile |
| 40 | Republic of Korea | 0 1000 t | 2023 | — | flat |
| 40 | Republic of Moldova | 0 1000 t | 2023 | — | flat |
| 40 | Russian Federation | 0 1000 t | 2023 | down 100.0% | volatile |
| 40 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | down 100.0% | volatile |
| 40 | Türkiye | 0 1000 t | 2023 | down 100.0% | volatile |
| 40 | China, mainland | 0 1000 t | 2023 | down 100.0% | volatile |
| 40 | Lao People's Democratic Republic | 0 1000 t | 2023 | — | flat |
| 40 | China, Taiwan Province of | 0 1000 t | 2023 | — | volatile |
| 40 | Democratic People's Republic of Korea | 0 1000 t | 2018 | — | flat |
| 40 | Micronesia (Federated States of) | 0 1000 t | 2023 | — | flat |
| 40 | China, Macao SAR | 0 1000 t | 2023 | — | volatile |
| 160 | China | -1 1000 t | 2023 | down 103.8% | volatile |
| 160 | Peru | -1 1000 t | 2023 | down 133.3% | volatile |
| 160 | China, Hong Kong SAR | -1 1000 t | 2023 | down 200.0% | volatile |
| 160 | United Republic of Tanzania | -1 1000 t | 2023 | up 80.0% | volatile |
| 164 | Australia | -3 1000 t | 2023 | — | volatile |
| 164 | Austria | -3 1000 t | 2023 | down 400.0% | volatile |
| 164 | Canada | -3 1000 t | 2023 | up 50.0% | volatile |
| 164 | Haiti | -3 1000 t | 2023 | — | volatile |
| 164 | Mexico | -3 1000 t | 2023 | up 85.0% | volatile |
| 164 | Australia and New Zealand | -3 1000 t | 2023 | — | volatile |
| 170 | Israel | -4 1000 t | 2023 | down 500.0% | volatile |
| 170 | Liberia | -4 1000 t | 2023 | — | volatile |
| 170 | Lithuania | -4 1000 t | 2023 | down 233.3% | volatile |
| 173 | Denmark | -5 1000 t | 2023 | down 350.0% | volatile |
| 173 | Lebanon | -5 1000 t | 2023 | down 600.0% | volatile |
| 175 | Oman | -7 1000 t | 2023 | — | volatile |
| 175 | Sierra Leone | -7 1000 t | 2023 | — | flat |
| 177 | Egypt | -8 1000 t | 2023 | down 366.7% | volatile |
| 178 | Switzerland | -10 1000 t | 2023 | down 233.3% | volatile |
| 178 | Dominican Republic | -10 1000 t | 2023 | down 1,100.0% | volatile |
| 181 | United Arab Emirates | -27 1000 t | 2023 | down 1,250.0% | volatile |
| 182 | Ghana | -52 1000 t | 2023 | down 273.3% | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- World 613 1000 t
- Net Food Importing Developing Countries (NFIDCs) 283 1000 t
- Africa 265 1000 t
- Western Africa 242 1000 t
- Asia 194 1000 t
- South-Eastern Asia 164 1000 t
- Europe 146 1000 t
- European Union (27) 140 1000 t
- Western Europe 110 1000 t
- Southern Asia 42 1000 t
- South America 24 1000 t
- Eastern Asia 18 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.