Oilcrops Oil, Other — 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
Oilcrops Oil, Other — Stock Variation is currently reported for 160 countries. The highest value is 683 1000 t in United States; the lowest is -49 1000 t in Malaysia.
The median across all reporting countries is 0 1000 t, and the mean is 7.72 1000 t.
The gap between the highest and lowest reporting country is a factor of about 14.
Over the past decade 47 countries rose and 41 fell. The largest increase was in France (up 7,600.0%), and the largest decrease in Oman (down 1,200.0%).
Oilcrops Oil, Other — Stock Variation: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | United States | 683 1000 t | 2023 | up 6,309.1% | volatile |
| 2 | Netherlands (Kingdom of the) | 206 1000 t | 2023 | up 836.4% | volatile |
| 3 | France | 150 1000 t | 2023 | up 7,600.0% | volatile |
| 4 | Kenya | 72 1000 t | 2023 | up 132.3% | volatile |
| 5 | Cote d'Ivoire | 45 1000 t | 2023 | up 1,025.0% | volatile |
| 5 | Côte d'Ivoire | 45 1000 t | 2023 | up 1,025.0% | volatile |
| 7 | Vietnam | 41 1000 t | 2023 | up 720.0% | volatile |
| 7 | Viet Nam | 41 1000 t | 2023 | up 720.0% | volatile |
| 9 | Ecuador | 14 1000 t | 2023 | up 800.0% | volatile |
| 9 | Spain | 14 1000 t | 2023 | — | volatile |
| 11 | Iran (Islamic Republic of) | 13 1000 t | 2023 | up 1,200.0% | volatile |
| 12 | Romania | 10 1000 t | 2023 | up 300.0% | volatile |
| 13 | Greece | 9 1000 t | 2023 | up 125.0% | volatile |
| 13 | India | 9 1000 t | 2023 | up 120.5% | volatile |
| 15 | Lithuania | 7 1000 t | 2023 | — | volatile |
| 16 | Poland | 6 1000 t | 2023 | up 250.0% | volatile |
| 17 | Czechia | 5 1000 t | 2023 | — | volatile |
| 18 | United Arab Emirates | 4 1000 t | 2023 | down 50.0% | volatile |
| 18 | Belgium | 4 1000 t | 2023 | down 55.6% | volatile |
| 18 | Indonesia | 4 1000 t | 2023 | up 300.0% | volatile |
| 18 | Pakistan | 4 1000 t | 2023 | up 233.3% | volatile |
| 22 | Croatia | 3 1000 t | 2023 | — | volatile |
| 22 | Slovakia | 3 1000 t | 2023 | up 200.0% | volatile |
| 22 | Sweden | 3 1000 t | 2023 | — | volatile |
| 22 | Trinidad and Tobago | 3 1000 t | 2023 | up 200.0% | volatile |
| 22 | Tunisia | 3 1000 t | 2023 | unchanged | volatile |
| 27 | Switzerland | 2 1000 t | 2023 | — | volatile |
| 27 | Honduras | 2 1000 t | 2023 | up 166.7% | volatile |
| 27 | Kazakhstan | 2 1000 t | 2023 | up 100.0% | volatile |
| 27 | Norway | 2 1000 t | 2023 | — | volatile |
| 27 | Nepal | 2 1000 t | 2023 | up 300.0% | volatile |
| 27 | Portugal | 2 1000 t | 2023 | — | volatile |
| 27 | Tajikistan | 2 1000 t | 2023 | up 100.0% | volatile |
| 34 | Chile | 1 1000 t | 2023 | down 80.0% | volatile |
| 34 | Cyprus | 1 1000 t | 2023 | — | volatile |
| 34 | Algeria | 1 1000 t | 2023 | down 75.0% | volatile |
| 34 | Jamaica | 1 1000 t | 2023 | down 66.7% | volatile |
| 34 | Lebanon | 1 1000 t | 2023 | up 200.0% | volatile |
| 34 | Myanmar | 1 1000 t | 2023 | unchanged | volatile |
| 34 | Mozambique | 1 1000 t | 2023 | up 200.0% | volatile |
| 34 | Namibia | 1 1000 t | 2023 | — | volatile |
| 34 | Nigeria | 1 1000 t | 2023 | down 80.0% | volatile |
| 34 | El Salvador | 1 1000 t | 2023 | unchanged | volatile |
| 34 | Turkey | 1 1000 t | 2023 | down 94.7% | volatile |
| 34 | South Africa | 1 1000 t | 2023 | up 125.0% | volatile |
| 34 | Türkiye | 1 1000 t | 2023 | down 94.7% | volatile |
| 34 | China, Taiwan Province of | 1 1000 t | 2023 | — | volatile |
| 48 | Afghanistan | 0 1000 t | 2023 | down 100.0% | volatile |
| 48 | Albania | 0 1000 t | 2023 | down 100.0% | volatile |
| 48 | Argentina | 0 1000 t | 2023 | up 100.0% | volatile |
| 48 | Armenia | 0 1000 t | 2023 | up 100.0% | volatile |
| 48 | Antigua and Barbuda | 0 1000 t | 2023 | — | volatile |
| 48 | Azerbaijan | 0 1000 t | 2023 | up 100.0% | volatile |
| 48 | Burkina Faso | 0 1000 t | 2023 | down 100.0% | volatile |
| 48 | Bangladesh | 0 1000 t | 2023 | — | volatile |
| 48 | Bulgaria | 0 1000 t | 2023 | — | volatile |
| 48 | Bahrain | 0 1000 t | 2023 | — | volatile |
| 48 | Bahamas | 0 1000 t | 2023 | — | flat |
| 48 | Bosnia and Herzegovina | 0 1000 t | 2023 | — | volatile |
| 48 | Belarus | 0 1000 t | 2023 | up 100.0% | volatile |
| 48 | Belize | 0 1000 t | 2023 | — | volatile |
| 48 | Barbados | 0 1000 t | 2023 | up 100.0% | volatile |
| 48 | Bhutan | 0 1000 t | 2023 | — | volatile |
| 48 | Botswana | 0 1000 t | 2023 | — | flat |
| 48 | Congo | 0 1000 t | 2023 | — | volatile |
| 48 | Costa Rica | 0 1000 t | 2023 | up 100.0% | volatile |
| 48 | Cuba | 0 1000 t | 2019 | — | volatile |
| 48 | Denmark | 0 1000 t | 2023 | — | volatile |
| 48 | Dominican Republic | 0 1000 t | 2023 | — | volatile |
| 48 | Egypt | 0 1000 t | 2023 | up 100.0% | volatile |
| 48 | Estonia | 0 1000 t | 2023 | — | volatile |
| 48 | Ethiopia | 0 1000 t | 2023 | up 100.0% | volatile |
| 48 | Finland | 0 1000 t | 2023 | up 100.0% | volatile |
| 48 | Fiji | 0 1000 t | 2023 | — | volatile |
| 48 | Gabon | 0 1000 t | 2023 | down 100.0% | volatile |
| 48 | United Kingdom | 0 1000 t | 2023 | — | volatile |
| 48 | Guinea | 0 1000 t | 2023 | down 100.0% | volatile |
| 48 | Gambia | 0 1000 t | 2023 | — | volatile |
| 48 | Guinea-Bissau | 0 1000 t | 2023 | — | volatile |
| 48 | Guyana | 0 1000 t | 2023 | — | flat |
| 48 | Haiti | 0 1000 t | 2023 | down 100.0% | volatile |
| 48 | Hungary | 0 1000 t | 2023 | — | volatile |
| 48 | Ireland | 0 1000 t | 2023 | — | flat |
| 48 | Iceland | 0 1000 t | 2023 | — | volatile |
| 48 | Israel | 0 1000 t | 2023 | down 100.0% | volatile |
| 48 | Italy | 0 1000 t | 2023 | up 100.0% | volatile |
| 48 | Jordan | 0 1000 t | 2023 | down 100.0% | volatile |
| 48 | Kyrgyzstan | 0 1000 t | 2023 | down 100.0% | volatile |
| 48 | Liberia | 0 1000 t | 2023 | — | volatile |
| 48 | Libya | 0 1000 t | 2023 | — | volatile |
| 48 | Sri Lanka | 0 1000 t | 2023 | down 100.0% | volatile |
| 48 | Lesotho | 0 1000 t | 2023 | — | volatile |
| 48 | Latvia | 0 1000 t | 2023 | — | volatile |
| 48 | Morocco | 0 1000 t | 2023 | — | volatile |
| 48 | Moldova | 0 1000 t | 2023 | up 100.0% | flat |
| 48 | Madagascar | 0 1000 t | 2023 | — | volatile |
| 48 | Maldives | 0 1000 t | 2023 | — | volatile |
| 48 | Mexico | 0 1000 t | 2023 | up 100.0% | volatile |
| 48 | Malta | 0 1000 t | 2023 | — | flat |
| 48 | Montenegro | 0 1000 t | 2023 | — | volatile |
| 48 | Mauritania | 0 1000 t | 2023 | — | volatile |
| 48 | Mauritius | 0 1000 t | 2023 | — | volatile |
| 48 | Niger | 0 1000 t | 2023 | down 100.0% | volatile |
| 48 | Nicaragua | 0 1000 t | 2023 | — | volatile |
| 48 | New Zealand | 0 1000 t | 2023 | — | volatile |
| 48 | Panama | 0 1000 t | 2023 | down 100.0% | volatile |
| 48 | Peru | 0 1000 t | 2023 | — | volatile |
| 48 | Paraguay | 0 1000 t | 2023 | — | volatile |
| 48 | Rwanda | 0 1000 t | 2023 | — | volatile |
| 48 | Sierra Leone | 0 1000 t | 2023 | — | volatile |
| 48 | Serbia | 0 1000 t | 2023 | — | flat |
| 48 | Suriname | 0 1000 t | 2023 | — | volatile |
| 48 | Syria | 0 1000 t | 2023 | down 100.0% | volatile |
| 48 | Turkmenistan | 0 1000 t | 2023 | — | volatile |
| 48 | East Timor | 0 1000 t | 2023 | — | volatile |
| 48 | Uganda | 0 1000 t | 2023 | — | volatile |
| 48 | Ukraine | 0 1000 t | 2023 | down 100.0% | volatile |
| 48 | Uruguay | 0 1000 t | 2023 | up 100.0% | volatile |
| 48 | Uzbekistan | 0 1000 t | 2023 | down 100.0% | volatile |
| 48 | Saint Vincent and the Grenadines | 0 1000 t | 2023 | — | volatile |
| 48 | Yemen | 0 1000 t | 2023 | up 100.0% | volatile |
| 48 | Zambia | 0 1000 t | 2023 | — | volatile |
| 48 | Zimbabwe | 0 1000 t | 2023 | up 100.0% | volatile |
| 48 | Timor-Leste | 0 1000 t | 2023 | — | volatile |
| 48 | Melanesia | 0 1000 t | 2023 | — | volatile |
| 48 | Democratic Republic of the Congo | 0 1000 t | 2023 | down 100.0% | volatile |
| 48 | Republic of Korea | 0 1000 t | 2023 | down 100.0% | volatile |
| 48 | Republic of Moldova | 0 1000 t | 2023 | up 100.0% | flat |
| 48 | Syrian Arab Republic | 0 1000 t | 2023 | down 100.0% | volatile |
| 48 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | up 100.0% | volatile |
| 48 | China, mainland | 0 1000 t | 2023 | up 100.0% | volatile |
| 48 | United Kingdom of Great Britain and Northern Ireland | 0 1000 t | 2023 | — | volatile |
| 167 | Djibouti | -1 1000 t | 2023 | — | flat |
| 167 | Georgia | -1 1000 t | 2023 | down 200.0% | volatile |
| 167 | Iraq | -1 1000 t | 2023 | up 94.1% | volatile |
| 167 | Qatar | -1 1000 t | 2023 | — | volatile |
| 167 | Russia | -1 1000 t | 2023 | up 85.7% | volatile |
| 167 | Senegal | -1 1000 t | 2023 | down 150.0% | volatile |
| 167 | Caribbean | -1 1000 t | 2023 | down 110.0% | volatile |
| 167 | Russian Federation | -1 1000 t | 2023 | up 85.7% | volatile |
| 175 | Austria | -2 1000 t | 2023 | down 133.3% | volatile |
| 175 | Brazil | -2 1000 t | 2023 | down 140.0% | volatile |
| 175 | Thailand | -2 1000 t | 2023 | unchanged | volatile |
| 178 | Cameroon | -3 1000 t | 2023 | down 400.0% | volatile |
| 178 | Ghana | -3 1000 t | 2023 | down 123.1% | volatile |
| 178 | Philippines | -3 1000 t | 2023 | — | volatile |
| 178 | Saudi Arabia | -3 1000 t | 2023 | — | volatile |
| 182 | Kuwait | -4 1000 t | 2023 | down 500.0% | volatile |
| 182 | United Republic of Tanzania | -4 1000 t | 2023 | down 133.3% | volatile |
| 184 | Germany | -5 1000 t | 2023 | — | volatile |
| 185 | Canada | -8 1000 t | 2023 | down 108.1% | volatile |
| 186 | Angola | -10 1000 t | 2023 | — | volatile |
| 186 | Australia | -10 1000 t | 2023 | down 300.0% | volatile |
| 186 | China | -10 1000 t | 2023 | down 25.0% | volatile |
| 186 | Australia and New Zealand | -10 1000 t | 2023 | down 300.0% | volatile |
| 190 | Guatemala | -11 1000 t | 2023 | down 22.2% | volatile |
| 190 | Oman | -11 1000 t | 2023 | down 1,200.0% | volatile |
| 190 | China, Hong Kong SAR | -11 1000 t | 2023 | — | volatile |
| 193 | Colombia | -25 1000 t | 2023 | — | volatile |
| 194 | Malaysia | -49 1000 t | 2023 | up 35.5% | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- World 1,163 1000 t
- United States of America 683 1000 t
- Northern America 674 1000 t
- Americas 654 1000 t
- Europe 419 1000 t
- European Union (27) 416 1000 t
- Western Europe 355 1000 t
- Net Food Importing Developing Countries (NFIDCs) 101 1000 t
- Africa 88 1000 t
- Eastern Africa 68 1000 t
- Low Income Food Deficit Countries (LIFDCs) 54 1000 t
- Southern Europe 29 1000 t
- Southern Asia 28 1000 t
- Western Africa 25 1000 t
- Eastern Europe 23 1000 t
- Asia 12 1000 t
- Northern Europe 12 1000 t
- Northern Africa 5 1000 t
- Central Asia 3 1000 t
- Southern Africa 2 1000 t
- Eastern Asia 1 1000 t
- Small island developing States (SIDS) -1 1000 t
- Land Locked Developing Countries (LLDCs) -6 1000 t
- Central America -8 1000 t
- South-Eastern Asia -8 1000 t
- Oceania -10 1000 t
- South America -11 1000 t
- Middle Africa -12 1000 t
- Western Asia -13 1000 t
- Least Developed Countries (LDCs) -27 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.