Palm Oil — 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
Palm Oil — Stock Variation is currently reported for 131 countries. The highest value is 720 1000 t in China; the lowest is -130 1000 t in Philippines.
The median across all reporting countries is 0 1000 t, and the mean is 23.21 1000 t.
The gap between the highest and lowest reporting country is a factor of about 6.
Over the past decade 43 countries rose and 36 fell. The largest increase was in Niger (up 1,900.0%), and the largest decrease in Nepal (down 1,200.0%).
Palm Oil — Stock Variation: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | China | 720 1000 t | 2023 | up 414.3% | volatile |
| 2 | China, mainland | 711 1000 t | 2023 | up 430.6% | volatile |
| 3 | Indonesia | 633 1000 t | 2023 | up 91.8% | volatile |
| 4 | Malaysia | 373 1000 t | 2023 | — | volatile |
| 5 | India | 143 1000 t | 2023 | down 49.1% | volatile |
| 6 | Vietnam | 100 1000 t | 2023 | up 23.5% | volatile |
| 6 | Viet Nam | 100 1000 t | 2023 | up 23.5% | volatile |
| 8 | Burkina Faso | 90 1000 t | 2023 | up 429.4% | volatile |
| 8 | Nigeria | 90 1000 t | 2023 | — | volatile |
| 10 | Afghanistan | 70 1000 t | 2023 | — | volatile |
| 11 | Guatemala | 64 1000 t | 2023 | up 900.0% | volatile |
| 12 | Mauritania | 45 1000 t | 2023 | — | volatile |
| 13 | Guinea | 40 1000 t | 2023 | up 566.7% | volatile |
| 13 | Niger | 40 1000 t | 2023 | up 1,900.0% | volatile |
| 15 | Senegal | 39 1000 t | 2023 | up 254.5% | volatile |
| 16 | Belgium | 29 1000 t | 2023 | — | volatile |
| 17 | Congo | 20 1000 t | 2023 | up 566.7% | volatile |
| 17 | Italy | 20 1000 t | 2023 | — | volatile |
| 17 | Thailand | 20 1000 t | 2023 | up 66.7% | volatile |
| 20 | Portugal | 18 1000 t | 2023 | up 125.0% | volatile |
| 21 | Myanmar | 17 1000 t | 2023 | up 221.4% | volatile |
| 21 | Democratic People's Republic of Korea | 17 1000 t | 2018 | — | volatile |
| 23 | Mexico | 16 1000 t | 2023 | up 6.7% | volatile |
| 24 | Oman | 15 1000 t | 2023 | up 400.0% | volatile |
| 25 | Cameroon | 13 1000 t | 2023 | up 750.0% | volatile |
| 25 | United Republic of Tanzania | 13 1000 t | 2023 | up 18.2% | volatile |
| 27 | Ghana | 12 1000 t | 2023 | up 166.7% | volatile |
| 27 | Republic of Korea | 12 1000 t | 2023 | — | volatile |
| 29 | Haiti | 11 1000 t | 2023 | up 466.7% | volatile |
| 30 | Cote d'Ivoire | 10 1000 t | 2023 | down 50.0% | volatile |
| 30 | Djibouti | 10 1000 t | 2023 | — | volatile |
| 30 | Algeria | 10 1000 t | 2023 | up 42.9% | volatile |
| 30 | Egypt | 10 1000 t | 2023 | up 111.8% | volatile |
| 30 | Gabon | 10 1000 t | 2023 | up 900.0% | volatile |
| 30 | Mozambique | 10 1000 t | 2023 | — | volatile |
| 30 | Côte d'Ivoire | 10 1000 t | 2023 | down 50.0% | volatile |
| 37 | Kenya | 9 1000 t | 2023 | up 190.0% | volatile |
| 37 | Liberia | 9 1000 t | 2023 | — | volatile |
| 37 | Caribbean | 9 1000 t | 2023 | up 1,000.0% | volatile |
| 37 | China, Taiwan Province of | 9 1000 t | 2023 | up 50.0% | volatile |
| 41 | Brazil | 8 1000 t | 2023 | down 60.0% | volatile |
| 41 | Ukraine | 8 1000 t | 2023 | down 81.4% | volatile |
| 43 | Spain | 7 1000 t | 2023 | down 97.2% | volatile |
| 43 | Nicaragua | 7 1000 t | 2023 | — | volatile |
| 45 | Jordan | 4 1000 t | 2023 | down 63.6% | volatile |
| 46 | Czechia | 3 1000 t | 2023 | up 250.0% | volatile |
| 46 | France | 3 1000 t | 2023 | — | volatile |
| 48 | Costa Rica | 2 1000 t | 2023 | down 97.3% | volatile |
| 48 | Denmark | 2 1000 t | 2023 | down 71.4% | volatile |
| 48 | Kazakhstan | 2 1000 t | 2023 | — | volatile |
| 48 | Cambodia | 2 1000 t | 2023 | up 133.3% | volatile |
| 48 | Eswatini | 2 1000 t | 2023 | — | volatile |
| 48 | Trinidad and Tobago | 2 1000 t | 2023 | — | volatile |
| 48 | Zimbabwe | 2 1000 t | 2023 | — | volatile |
| 55 | Bulgaria | 1 1000 t | 2023 | — | flat |
| 55 | Croatia | 1 1000 t | 2023 | — | volatile |
| 55 | Suriname | 1 1000 t | 2023 | — | volatile |
| 55 | Samoa | 1 1000 t | 2023 | — | volatile |
| 55 | Polynesia | 1 1000 t | 2023 | — | volatile |
| 60 | Argentina | 0 1000 t | 2023 | — | volatile |
| 60 | Australia | 0 1000 t | 2023 | down 100.0% | volatile |
| 60 | Azerbaijan | 0 1000 t | 2023 | down 100.0% | volatile |
| 60 | Bahrain | 0 1000 t | 2023 | — | flat |
| 60 | Bosnia and Herzegovina | 0 1000 t | 2023 | up 100.0% | volatile |
| 60 | Switzerland | 0 1000 t | 2023 | up 100.0% | volatile |
| 60 | Chile | 0 1000 t | 2023 | — | volatile |
| 60 | Finland | 0 1000 t | 2023 | — | flat |
| 60 | United Kingdom | 0 1000 t | 2023 | down 100.0% | volatile |
| 60 | Gambia | 0 1000 t | 2023 | up 100.0% | volatile |
| 60 | Guinea-Bissau | 0 1000 t | 2023 | down 100.0% | volatile |
| 60 | Greece | 0 1000 t | 2023 | — | volatile |
| 60 | Kuwait | 0 1000 t | 2023 | down 100.0% | volatile |
| 60 | Lebanon | 0 1000 t | 2023 | — | volatile |
| 60 | Sri Lanka | 0 1000 t | 2023 | down 100.0% | volatile |
| 60 | Morocco | 0 1000 t | 2023 | — | volatile |
| 60 | Madagascar | 0 1000 t | 2023 | — | volatile |
| 60 | Maldives | 0 1000 t | 2023 | — | volatile |
| 60 | Mauritius | 0 1000 t | 2023 | — | volatile |
| 60 | Malawi | 0 1000 t | 2023 | up 100.0% | volatile |
| 60 | Namibia | 0 1000 t | 2023 | — | volatile |
| 60 | New Zealand | 0 1000 t | 2023 | — | volatile |
| 60 | Peru | 0 1000 t | 2023 | up 100.0% | volatile |
| 60 | Poland | 0 1000 t | 2023 | down 100.0% | volatile |
| 60 | Rwanda | 0 1000 t | 2023 | — | volatile |
| 60 | Sierra Leone | 0 1000 t | 2023 | — | volatile |
| 60 | El Salvador | 0 1000 t | 2023 | up 100.0% | volatile |
| 60 | East Timor | 0 1000 t | 2023 | up 100.0% | volatile |
| 60 | Tunisia | 0 1000 t | 2023 | — | flat |
| 60 | Vanuatu | 0 1000 t | 2023 | — | volatile |
| 60 | South Africa | 0 1000 t | 2023 | up 100.0% | volatile |
| 60 | Timor-Leste | 0 1000 t | 2023 | up 100.0% | volatile |
| 60 | Democratic Republic of the Congo | 0 1000 t | 2023 | up 100.0% | volatile |
| 60 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | up 100.0% | volatile |
| 60 | Australia and New Zealand | 0 1000 t | 2023 | down 100.0% | volatile |
| 60 | United Kingdom of Great Britain and Northern Ireland | 0 1000 t | 2023 | down 100.0% | volatile |
| 154 | Ireland | -1 1000 t | 2023 | — | volatile |
| 154 | Romania | -1 1000 t | 2023 | down 125.0% | flat |
| 154 | Zambia | -1 1000 t | 2023 | down 200.0% | volatile |
| 157 | Comoros | -2 1000 t | 2023 | — | volatile |
| 157 | Mongolia | -2 1000 t | 2023 | — | volatile |
| 157 | Solomon Islands | -2 1000 t | 2023 | down 100.0% | volatile |
| 157 | Syria | -2 1000 t | 2023 | — | volatile |
| 157 | Syrian Arab Republic | -2 1000 t | 2023 | — | volatile |
| 162 | Ecuador | -3 1000 t | 2023 | — | volatile |
| 162 | Panama | -3 1000 t | 2023 | up 57.1% | volatile |
| 162 | Saudi Arabia | -3 1000 t | 2023 | — | volatile |
| 162 | Serbia | -3 1000 t | 2023 | — | volatile |
| 166 | Dominican Republic | -4 1000 t | 2023 | down 300.0% | volatile |
| 166 | Israel | -4 1000 t | 2023 | — | volatile |
| 168 | Iraq | -6 1000 t | 2023 | down 128.6% | volatile |
| 168 | Sweden | -6 1000 t | 2023 | — | volatile |
| 170 | Austria | -9 1000 t | 2023 | down 1,000.0% | volatile |
| 170 | United States | -9 1000 t | 2023 | — | volatile |
| 172 | Bangladesh | -10 1000 t | 2023 | down 158.8% | volatile |
| 172 | Russia | -10 1000 t | 2023 | down 123.8% | volatile |
| 172 | Russian Federation | -10 1000 t | 2023 | down 123.8% | volatile |
| 175 | Iran (Islamic Republic of) | -11 1000 t | 2023 | down 237.5% | volatile |
| 176 | Colombia | -12 1000 t | 2023 | down 180.0% | flat |
| 176 | Netherlands (Kingdom of the) | -12 1000 t | 2023 | — | volatile |
| 178 | Nepal | -13 1000 t | 2023 | down 1,200.0% | volatile |
| 178 | Turkey | -13 1000 t | 2023 | down 244.4% | volatile |
| 178 | Türkiye | -13 1000 t | 2023 | down 244.4% | volatile |
| 181 | Angola | -14 1000 t | 2023 | down 131.8% | volatile |
| 181 | Germany | -14 1000 t | 2023 | — | volatile |
| 183 | Honduras | -28 1000 t | 2023 | down 115.4% | volatile |
| 184 | Papua New Guinea | -33 1000 t | 2023 | up 31.2% | volatile |
| 185 | Melanesia | -35 1000 t | 2023 | up 28.6% | volatile |
| 186 | Pakistan | -40 1000 t | 2023 | down 121.6% | volatile |
| 187 | Ethiopia | -70 1000 t | 2023 | — | volatile |
| 188 | United Arab Emirates | -85 1000 t | 2023 | up 24.8% | volatile |
| 189 | Philippines | -130 1000 t | 2023 | down 381.5% | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- World 2,347 1000 t
- Asia 1,801 1000 t
- South-Eastern Asia 1,015 1000 t
- Eastern Asia 737 1000 t
- Africa 491 1000 t
- Western Africa 467 1000 t
- Low Income Food Deficit Countries (LIFDCs) 430 1000 t
- Least Developed Countries (LDCs) 379 1000 t
- Net Food Importing Developing Countries (NFIDCs) 353 1000 t
- Southern Asia 138 1000 t
- Land Locked Developing Countries (LLDCs) 121 1000 t
- Central America 58 1000 t
- Americas 53 1000 t
- European Union (27) 42 1000 t
- Southern Europe 42 1000 t
- Europe 36 1000 t
- Middle Africa 29 1000 t
- Northern Africa 20 1000 t
- Central Asia 2 1000 t
- Southern Africa 2 1000 t
- Eastern Europe 0 1000 t
- Western Europe -2 1000 t
- South America -5 1000 t
- Northern Europe -5 1000 t
- Northern America -9 1000 t
- United States of America -9 1000 t
- Small island developing States (SIDS) -26 1000 t
- Eastern Africa -27 1000 t
- Oceania -34 1000 t
- Western Asia -92 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.