Olive 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
Olive Oil — Stock Variation is currently reported for 92 countries. The highest value is 23 1000 t in Greece; the lowest is -80 1000 t in Syrian Arab Republic.
The median across all reporting countries is 0 1000 t, and the mean is -2.57 1000 t.
Over the past decade 14 countries rose and 20 fell. The largest increase was in Greece (up 192.0%), and the largest decrease in United Arab Emirates (down 700.0%).
Olive Oil — Stock Variation: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Greece | 23 1000 t | 2023 | up 192.0% | volatile |
| 2 | Burkina Faso | 15 1000 t | 2023 | — | volatile |
| 3 | Portugal | 12 1000 t | 2023 | down 7.7% | volatile |
| 4 | Turkey | 3 1000 t | 2023 | up 105.6% | volatile |
| 4 | Türkiye | 3 1000 t | 2023 | up 105.6% | volatile |
| 6 | Netherlands (Kingdom of the) | 2 1000 t | 2023 | — | volatile |
| 7 | Canada | 1 1000 t | 2023 | down 50.0% | volatile |
| 7 | China | 1 1000 t | 2023 | down 75.0% | volatile |
| 7 | Ecuador | 1 1000 t | 2023 | — | volatile |
| 7 | United Kingdom | 1 1000 t | 2023 | — | volatile |
| 7 | Lebanon | 1 1000 t | 2023 | up 150.0% | volatile |
| 7 | Sweden | 1 1000 t | 2023 | — | volatile |
| 7 | Cabo Verde | 1 1000 t | 2023 | — | volatile |
| 7 | Iran (Islamic Republic of) | 1 1000 t | 2023 | unchanged | volatile |
| 7 | China, mainland | 1 1000 t | 2023 | down 66.7% | volatile |
| 7 | United Kingdom of Great Britain and Northern Ireland | 1 1000 t | 2023 | — | volatile |
| 17 | Angola | 0 1000 t | 2023 | — | volatile |
| 17 | Albania | 0 1000 t | 2023 | — | volatile |
| 17 | Austria | 0 1000 t | 2023 | up 100.0% | volatile |
| 17 | Belgium | 0 1000 t | 2023 | down 100.0% | volatile |
| 17 | Bangladesh | 0 1000 t | 2023 | — | volatile |
| 17 | Bulgaria | 0 1000 t | 2023 | down 100.0% | volatile |
| 17 | Brazil | 0 1000 t | 2023 | up 100.0% | flat |
| 17 | Chile | 0 1000 t | 2023 | up 100.0% | volatile |
| 17 | Cote d'Ivoire | 0 1000 t | 2023 | — | volatile |
| 17 | Costa Rica | 0 1000 t | 2023 | — | volatile |
| 17 | Cyprus | 0 1000 t | 2023 | — | volatile |
| 17 | Czechia | 0 1000 t | 2023 | — | volatile |
| 17 | Germany | 0 1000 t | 2023 | — | volatile |
| 17 | Denmark | 0 1000 t | 2023 | down 100.0% | flat |
| 17 | Egypt | 0 1000 t | 2023 | down 100.0% | volatile |
| 17 | Estonia | 0 1000 t | 2023 | — | volatile |
| 17 | Ethiopia | 0 1000 t | 2023 | — | volatile |
| 17 | Finland | 0 1000 t | 2023 | — | volatile |
| 17 | Fiji | 0 1000 t | 2023 | — | volatile |
| 17 | Ghana | 0 1000 t | 2023 | — | volatile |
| 17 | Guatemala | 0 1000 t | 2023 | — | volatile |
| 17 | Croatia | 0 1000 t | 2023 | — | volatile |
| 17 | Hungary | 0 1000 t | 2023 | — | volatile |
| 17 | Indonesia | 0 1000 t | 2023 | — | volatile |
| 17 | India | 0 1000 t | 2023 | down 100.0% | volatile |
| 17 | Ireland | 0 1000 t | 2023 | — | volatile |
| 17 | Iraq | 0 1000 t | 2023 | — | volatile |
| 17 | Jordan | 0 1000 t | 2023 | — | volatile |
| 17 | Kuwait | 0 1000 t | 2023 | — | flat |
| 17 | Maldives | 0 1000 t | 2023 | — | volatile |
| 17 | Mexico | 0 1000 t | 2023 | down 100.0% | volatile |
| 17 | North Macedonia | 0 1000 t | 2023 | — | volatile |
| 17 | Malta | 0 1000 t | 2023 | — | volatile |
| 17 | Namibia | 0 1000 t | 2023 | — | volatile |
| 17 | Nigeria | 0 1000 t | 2023 | — | volatile |
| 17 | Norway | 0 1000 t | 2023 | — | volatile |
| 17 | New Zealand | 0 1000 t | 2023 | up 100.0% | volatile |
| 17 | Panama | 0 1000 t | 2023 | — | volatile |
| 17 | Peru | 0 1000 t | 2023 | — | volatile |
| 17 | Philippines | 0 1000 t | 2023 | — | volatile |
| 17 | Poland | 0 1000 t | 2023 | up 100.0% | volatile |
| 17 | Romania | 0 1000 t | 2023 | — | volatile |
| 17 | Saudi Arabia | 0 1000 t | 2023 | — | volatile |
| 17 | Senegal | 0 1000 t | 2023 | — | volatile |
| 17 | El Salvador | 0 1000 t | 2023 | — | volatile |
| 17 | Slovenia | 0 1000 t | 2023 | — | volatile |
| 17 | Seychelles | 0 1000 t | 2023 | — | volatile |
| 17 | Ukraine | 0 1000 t | 2023 | down 100.0% | flat |
| 17 | Uruguay | 0 1000 t | 2023 | — | volatile |
| 17 | Yemen | 0 1000 t | 2023 | — | volatile |
| 17 | South Africa | 0 1000 t | 2023 | up 100.0% | volatile |
| 17 | Melanesia | 0 1000 t | 2023 | — | volatile |
| 17 | Democratic Republic of the Congo | 0 1000 t | 2023 | — | volatile |
| 17 | China, Hong Kong SAR | 0 1000 t | 2023 | — | flat |
| 17 | Republic of Korea | 0 1000 t | 2023 | — | volatile |
| 17 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | down 100.0% | flat |
| 17 | Côte d'Ivoire | 0 1000 t | 2023 | — | volatile |
| 17 | United Republic of Tanzania | 0 1000 t | 2023 | — | volatile |
| 17 | China, Taiwan Province of | 0 1000 t | 2023 | down 100.0% | volatile |
| 173 | Libya | -1 1000 t | 2023 | — | volatile |
| 173 | Mauritius | -1 1000 t | 2023 | — | volatile |
| 173 | Qatar | -1 1000 t | 2023 | — | volatile |
| 176 | Colombia | -2 1000 t | 2023 | — | volatile |
| 176 | Israel | -2 1000 t | 2023 | down 166.7% | volatile |
| 178 | Australia and New Zealand | -3 1000 t | 2023 | up 50.0% | volatile |
| 179 | Argentina | -4 1000 t | 2023 | up 33.3% | flat |
| 179 | Australia | -4 1000 t | 2023 | up 20.0% | volatile |
| 179 | Algeria | -4 1000 t | 2023 | unchanged | volatile |
| 182 | United Arab Emirates | -8 1000 t | 2023 | down 700.0% | volatile |
| 183 | Spain | -12 1000 t | 2023 | down 102.0% | volatile |
| 184 | United States | -14 1000 t | 2023 | — | volatile |
| 185 | Morocco | -18 1000 t | 2023 | down 205.9% | volatile |
| 186 | Tunisia | -20 1000 t | 2023 | down 281.8% | volatile |
| 187 | Italy | -50 1000 t | 2023 | up 10.7% | volatile |
| 188 | Syria | -80 1000 t | 2023 | down 433.3% | volatile |
| 188 | Syrian Arab Republic | -80 1000 t | 2023 | down 433.3% | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- Western Africa 16 1000 t
- Least Developed Countries (LDCs) 15 1000 t
- Land Locked Developing Countries (LLDCs) 15 1000 t
- Western Europe 2 1000 t
- Northern Europe 2 1000 t
- Small island developing States (SIDS) 1 1000 t
- Eastern Europe 1 1000 t
- Central America 1 1000 t
- Southern Asia 1 1000 t
- South-Eastern Asia 1 1000 t
- Southern Africa 0 1000 t
- Middle Africa 0 1000 t
- Eastern Asia 0 1000 t
- Eastern Africa -1 1000 t
- Oceania -3 1000 t
- South America -5 1000 t
- Northern America -13 1000 t
- United States of America -14 1000 t
- Americas -17 1000 t
- Europe -21 1000 t
- European Union (27) -22 1000 t
- Net Food Importing Developing Countries (NFIDCs) -23 1000 t
- Southern Europe -26 1000 t
- Africa -28 1000 t
- Northern Africa -43 1000 t
- Low Income Food Deficit Countries (LIFDCs) -65 1000 t
- Asia -83 1000 t
- Western Asia -86 1000 t
- World -153 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.