Coffee 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
Coffee and products — Stock Variation is currently reported for 178 countries. The highest value is 45 1000 t in Colombia; the lowest is -231 1000 t in Brazil.
The median across all reporting countries is 0 1000 t, and the mean is 0.5787 1000 t.
Over the past decade 42 countries rose and 35 fell. The largest increase was in Guinea (up 4,300.0%), and the largest decrease in Brazil (down 477.5%).
Coffee and products — Stock Variation: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Colombia | 45 1000 t | 2023 | up 60.7% | volatile |
| 2 | Guinea | 42 1000 t | 2023 | up 4,300.0% | volatile |
| 3 | United Kingdom of Great Britain and Northern Ireland | 38 1000 t | 2023 | — | volatile |
| 4 | Canada | 32 1000 t | 2023 | up 433.3% | volatile |
| 5 | China | 30 1000 t | 2023 | up 275.0% | volatile |
| 6 | China, Hong Kong SAR | 22 1000 t | 2023 | up 266.7% | volatile |
| 7 | Iraq | 19 1000 t | 2023 | up 1,800.0% | volatile |
| 8 | Papua New Guinea | 18 1000 t | 2023 | up 1,700.0% | volatile |
| 8 | Melanesia | 18 1000 t | 2023 | up 1,700.0% | volatile |
| 10 | Lebanon | 17 1000 t | 2023 | up 88.9% | volatile |
| 11 | Saudi Arabia | 11 1000 t | 2023 | down 8.3% | volatile |
| 12 | Azerbaijan | 10 1000 t | 2023 | up 1,100.0% | volatile |
| 13 | Belgium | 9 1000 t | 2023 | down 64.0% | volatile |
| 13 | Greece | 9 1000 t | 2023 | — | volatile |
| 13 | Côte d'Ivoire | 9 1000 t | 2023 | — | volatile |
| 16 | Switzerland | 5 1000 t | 2023 | down 28.6% | volatile |
| 16 | Morocco | 5 1000 t | 2023 | down 16.7% | volatile |
| 18 | Czechia | 4 1000 t | 2023 | — | volatile |
| 18 | Guatemala | 4 1000 t | 2023 | up 150.0% | volatile |
| 18 | Romania | 4 1000 t | 2023 | up 300.0% | volatile |
| 18 | Slovenia | 4 1000 t | 2023 | up 100.0% | rising |
| 18 | Türkiye | 4 1000 t | 2023 | up 140.0% | volatile |
| 18 | China, Taiwan Province of | 4 1000 t | 2023 | up 300.0% | volatile |
| 24 | Algeria | 3 1000 t | 2023 | up 400.0% | volatile |
| 24 | Georgia | 3 1000 t | 2023 | up 50.0% | volatile |
| 24 | Tunisia | 3 1000 t | 2023 | up 200.0% | volatile |
| 27 | Ireland | 2 1000 t | 2023 | — | volatile |
| 27 | Kazakhstan | 2 1000 t | 2023 | down 77.8% | volatile |
| 27 | Liberia | 2 1000 t | 2023 | — | volatile |
| 27 | Lithuania | 2 1000 t | 2023 | — | volatile |
| 27 | Senegal | 2 1000 t | 2023 | — | volatile |
| 27 | China, Macao SAR | 2 1000 t | 2023 | up 300.0% | volatile |
| 33 | Armenia | 1 1000 t | 2023 | unchanged | volatile |
| 33 | Cameroon | 1 1000 t | 2023 | — | volatile |
| 33 | Cyprus | 1 1000 t | 2023 | up 200.0% | volatile |
| 33 | Finland | 1 1000 t | 2023 | down 66.7% | volatile |
| 33 | Croatia | 1 1000 t | 2023 | up 125.0% | volatile |
| 33 | Marshall Islands | 1 1000 t | 2023 | — | volatile |
| 33 | Montenegro | 1 1000 t | 2023 | unchanged | volatile |
| 33 | Namibia | 1 1000 t | 2023 | unchanged | volatile |
| 33 | Portugal | 1 1000 t | 2023 | down 75.0% | volatile |
| 33 | Thailand | 1 1000 t | 2023 | — | volatile |
| 33 | Tajikistan | 1 1000 t | 2023 | — | volatile |
| 33 | Micronesia | 1 1000 t | 2023 | — | volatile |
| 33 | China, mainland | 1 1000 t | 2023 | down 50.0% | volatile |
| 46 | Afghanistan | 0 1000 t | 2023 | — | flat |
| 46 | Angola | 0 1000 t | 2023 | — | volatile |
| 46 | Albania | 0 1000 t | 2023 | — | volatile |
| 46 | United Arab Emirates | 0 1000 t | 2023 | up 100.0% | volatile |
| 46 | Argentina | 0 1000 t | 2023 | up 100.0% | volatile |
| 46 | Antigua and Barbuda | 0 1000 t | 2023 | — | volatile |
| 46 | Austria | 0 1000 t | 2023 | down 100.0% | volatile |
| 46 | Burkina Faso | 0 1000 t | 2023 | — | volatile |
| 46 | Bangladesh | 0 1000 t | 2023 | — | volatile |
| 46 | Bulgaria | 0 1000 t | 2023 | down 100.0% | volatile |
| 46 | Bahrain | 0 1000 t | 2023 | — | volatile |
| 46 | Bahamas | 0 1000 t | 2023 | down 100.0% | volatile |
| 46 | Bosnia and Herzegovina | 0 1000 t | 2023 | up 100.0% | volatile |
| 46 | Belarus | 0 1000 t | 2023 | down 100.0% | volatile |
| 46 | Belize | 0 1000 t | 2023 | down 100.0% | volatile |
| 46 | Barbados | 0 1000 t | 2023 | — | flat |
| 46 | Bhutan | 0 1000 t | 2023 | — | flat |
| 46 | Botswana | 0 1000 t | 2023 | — | flat |
| 46 | Chile | 0 1000 t | 2023 | up 100.0% | volatile |
| 46 | Congo | 0 1000 t | 2023 | — | volatile |
| 46 | Comoros | 0 1000 t | 2023 | — | flat |
| 46 | Costa Rica | 0 1000 t | 2023 | up 100.0% | volatile |
| 46 | Cuba | 0 1000 t | 2019 | — | flat |
| 46 | Germany | 0 1000 t | 2023 | up 100.0% | volatile |
| 46 | Djibouti | 0 1000 t | 2023 | down 100.0% | volatile |
| 46 | Denmark | 0 1000 t | 2023 | down 100.0% | flat |
| 46 | Dominican Republic | 0 1000 t | 2023 | up 100.0% | volatile |
| 46 | Ecuador | 0 1000 t | 2023 | — | volatile |
| 46 | Egypt | 0 1000 t | 2023 | — | volatile |
| 46 | Spain | 0 1000 t | 2023 | — | volatile |
| 46 | Estonia | 0 1000 t | 2023 | — | volatile |
| 46 | Ethiopia | 0 1000 t | 2023 | — | volatile |
| 46 | Fiji | 0 1000 t | 2023 | — | flat |
| 46 | France | 0 1000 t | 2023 | up 100.0% | volatile |
| 46 | Gabon | 0 1000 t | 2023 | — | flat |
| 46 | Ghana | 0 1000 t | 2023 | — | flat |
| 46 | Gambia | 0 1000 t | 2023 | — | flat |
| 46 | Guinea-Bissau | 0 1000 t | 2023 | — | flat |
| 46 | Grenada | 0 1000 t | 2023 | — | flat |
| 46 | Guyana | 0 1000 t | 2023 | — | volatile |
| 46 | Honduras | 0 1000 t | 2023 | down 100.0% | volatile |
| 46 | Haiti | 0 1000 t | 2023 | — | flat |
| 46 | Hungary | 0 1000 t | 2023 | — | volatile |
| 46 | Iceland | 0 1000 t | 2023 | — | flat |
| 46 | Israel | 0 1000 t | 2023 | down 100.0% | volatile |
| 46 | Italy | 0 1000 t | 2023 | down 100.0% | volatile |
| 46 | Jamaica | 0 1000 t | 2023 | — | flat |
| 46 | Jordan | 0 1000 t | 2023 | down 100.0% | volatile |
| 46 | Kyrgyzstan | 0 1000 t | 2023 | — | volatile |
| 46 | Cambodia | 0 1000 t | 2023 | down 100.0% | volatile |
| 46 | Kiribati | 0 1000 t | 2023 | — | flat |
| 46 | Saint Kitts and Nevis | 0 1000 t | 2023 | — | flat |
| 46 | Kuwait | 0 1000 t | 2023 | down 100.0% | volatile |
| 46 | Libya | 0 1000 t | 2023 | down 100.0% | volatile |
| 46 | Saint Lucia | 0 1000 t | 2023 | — | volatile |
| 46 | Sri Lanka | 0 1000 t | 2023 | — | flat |
| 46 | Luxembourg | 0 1000 t | 2023 | — | volatile |
| 46 | Latvia | 0 1000 t | 2023 | — | volatile |
| 46 | Madagascar | 0 1000 t | 2023 | — | flat |
| 46 | North Macedonia | 0 1000 t | 2023 | down 100.0% | volatile |
| 46 | Malta | 0 1000 t | 2023 | — | volatile |
| 46 | Myanmar | 0 1000 t | 2023 | — | volatile |
| 46 | Mongolia | 0 1000 t | 2023 | up 100.0% | volatile |
| 46 | Mozambique | 0 1000 t | 2023 | — | flat |
| 46 | Mauritania | 0 1000 t | 2023 | — | volatile |
| 46 | Mauritius | 0 1000 t | 2023 | — | volatile |
| 46 | Malawi | 0 1000 t | 2023 | — | flat |
| 46 | Malaysia | 0 1000 t | 2023 | — | flat |
| 46 | New Caledonia | 0 1000 t | 2023 | — | flat |
| 46 | Niger | 0 1000 t | 2023 | — | volatile |
| 46 | Nigeria | 0 1000 t | 2023 | — | volatile |
| 46 | Norway | 0 1000 t | 2023 | up 100.0% | volatile |
| 46 | Nepal | 0 1000 t | 2023 | — | flat |
| 46 | Nauru | 0 1000 t | 2023 | — | flat |
| 46 | New Zealand | 0 1000 t | 2023 | up 100.0% | volatile |
| 46 | Oman | 0 1000 t | 2023 | down 100.0% | volatile |
| 46 | Pakistan | 0 1000 t | 2023 | — | flat |
| 46 | Panama | 0 1000 t | 2023 | — | volatile |
| 46 | Peru | 0 1000 t | 2023 | down 100.0% | volatile |
| 46 | Philippines | 0 1000 t | 2023 | down 100.0% | volatile |
| 46 | Poland | 0 1000 t | 2023 | down 100.0% | volatile |
| 46 | Paraguay | 0 1000 t | 2023 | — | flat |
| 46 | French Polynesia | 0 1000 t | 2023 | — | flat |
| 46 | Qatar | 0 1000 t | 2023 | — | volatile |
| 46 | Rwanda | 0 1000 t | 2023 | — | flat |
| 46 | Solomon Islands | 0 1000 t | 2023 | — | flat |
| 46 | Sierra Leone | 0 1000 t | 2023 | — | flat |
| 46 | El Salvador | 0 1000 t | 2023 | — | volatile |
| 46 | Serbia | 0 1000 t | 2023 | — | flat |
| 46 | Sao Tome and Principe | 0 1000 t | 2023 | — | flat |
| 46 | Suriname | 0 1000 t | 2023 | — | flat |
| 46 | Slovakia | 0 1000 t | 2023 | down 100.0% | volatile |
| 46 | Sweden | 0 1000 t | 2023 | — | volatile |
| 46 | Eswatini | 0 1000 t | 2023 | — | volatile |
| 46 | Seychelles | 0 1000 t | 2023 | — | flat |
| 46 | Tonga | 0 1000 t | 2023 | — | flat |
| 46 | Trinidad and Tobago | 0 1000 t | 2023 | — | flat |
| 46 | Tuvalu | 0 1000 t | 2023 | — | flat |
| 46 | Ukraine | 0 1000 t | 2023 | — | volatile |
| 46 | Uruguay | 0 1000 t | 2023 | — | volatile |
| 46 | Uzbekistan | 0 1000 t | 2023 | — | flat |
| 46 | Saint Vincent and the Grenadines | 0 1000 t | 2023 | — | flat |
| 46 | Vanuatu | 0 1000 t | 2023 | — | flat |
| 46 | Samoa | 0 1000 t | 2023 | up 100.0% | flat |
| 46 | Yemen | 0 1000 t | 2023 | up 100.0% | volatile |
| 46 | Zambia | 0 1000 t | 2023 | — | flat |
| 46 | Zimbabwe | 0 1000 t | 2023 | — | flat |
| 46 | Timor-Leste | 0 1000 t | 2023 | down 100.0% | volatile |
| 46 | Cabo Verde | 0 1000 t | 2023 | — | flat |
| 46 | Polynesia | 0 1000 t | 2023 | up 100.0% | flat |
| 46 | Democratic Republic of the Congo | 0 1000 t | 2023 | — | volatile |
| 46 | Bolivia (Plurinational State of) | 0 1000 t | 2023 | down 100.0% | volatile |
| 46 | Iran (Islamic Republic of) | 0 1000 t | 2023 | down 100.0% | volatile |
| 46 | Republic of Moldova | 0 1000 t | 2023 | — | flat |
| 46 | Russian Federation | 0 1000 t | 2023 | up 100.0% | volatile |
| 46 | Syrian Arab Republic | 0 1000 t | 2023 | down 100.0% | volatile |
| 46 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | down 100.0% | volatile |
| 46 | Viet Nam | 0 1000 t | 2023 | up 100.0% | volatile |
| 46 | Lao People's Democratic Republic | 0 1000 t | 2023 | down 100.0% | volatile |
| 46 | Netherlands (Kingdom of the) | 0 1000 t | 2023 | up 100.0% | volatile |
| 46 | Micronesia (Federated States of) | 0 1000 t | 2023 | — | flat |
| 168 | Maldives | -1 1000 t | 2023 | — | volatile |
| 168 | Mexico | -1 1000 t | 2023 | up 90.9% | volatile |
| 168 | Republic of Korea | -1 1000 t | 2023 | unchanged | volatile |
| 171 | Australia | -2 1000 t | 2023 | up 83.3% | volatile |
| 171 | India | -2 1000 t | 2023 | up 86.7% | volatile |
| 171 | Australia and New Zealand | -2 1000 t | 2023 | up 93.8% | volatile |
| 171 | United Republic of Tanzania | -2 1000 t | 2023 | — | volatile |
| 175 | Nicaragua | -5 1000 t | 2023 | — | volatile |
| 175 | Uganda | -5 1000 t | 2023 | — | volatile |
| 177 | Kenya | -9 1000 t | 2023 | — | volatile |
| 178 | Indonesia | -33 1000 t | 2023 | — | volatile |
| 179 | Brazil | -231 1000 t | 2023 | down 477.5% | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- Europe 83 1000 t
- Western Asia 67 1000 t
- Asia 61 1000 t
- Western Africa 57 1000 t
- Africa 55 1000 t
- World 53 1000 t
- Net Food Importing Developing Countries (NFIDCs) 52 1000 t
- Northern Europe 43 1000 t
- Least Developed Countries (LDCs) 42 1000 t
- European Union (27) 39 1000 t
- Low Income Food Deficit Countries (LIFDCs) 30 1000 t
- Northern America 24 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.