Miscellaneous — 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...
Countries reporting
181
Highest
80 1000 t
France
Lowest
-69 1000 t
Belarus
Median
0 1000 t
Years covered
14
2010–2023
Data points
2,828
What the numbers show
Miscellaneous — Stock Variation is currently reported for 181 countries. The highest value is 80 1000 t in France; the lowest is -69 1000 t in Belarus.
The median across all reporting countries is 0 1000 t, and the mean is 1.03 1000 t.
Over the past decade 32 countries rose and 53 fell. The largest increase was in Uzbekistan (up 800.0%), and the largest decrease in Lebanon (down 1,100.0%).
Miscellaneous — Stock Variation: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | France | 80 1000 t | 2023 | up 500.0% | volatile |
| 2 | Senegal | 38 1000 t | 2023 | — | volatile |
| 3 | Romania | 27 1000 t | 2023 | — | volatile |
| 3 | Uzbekistan | 27 1000 t | 2023 | up 800.0% | volatile |
| 5 | Finland | 15 1000 t | 2023 | — | volatile |
| 6 | Jamaica | 11 1000 t | 2023 | up 266.7% | volatile |
| 6 | Sweden | 11 1000 t | 2023 | up 22.2% | rising |
| 8 | Philippines | 10 1000 t | 2023 | down 50.0% | volatile |
| 9 | Libya | 9 1000 t | 2023 | — | volatile |
| 10 | Caribbean | 8 1000 t | 2023 | — | volatile |
| 11 | Democratic Republic of the Congo | 7 1000 t | 2023 | up 800.0% | volatile |
| 12 | Croatia | 6 1000 t | 2023 | — | volatile |
| 12 | North Macedonia | 6 1000 t | 2023 | — | volatile |
| 14 | China | 5 1000 t | 2023 | up 66.7% | volatile |
| 14 | Australia and New Zealand | 5 1000 t | 2023 | down 76.2% | volatile |
| 14 | China, Macao SAR | 5 1000 t | 2023 | — | volatile |
| 17 | Antigua and Barbuda | 4 1000 t | 2023 | — | volatile |
| 17 | Grenada | 4 1000 t | 2023 | — | volatile |
| 19 | Azerbaijan | 3 1000 t | 2023 | — | volatile |
| 19 | Botswana | 3 1000 t | 2023 | down 25.0% | volatile |
| 19 | Iceland | 3 1000 t | 2023 | — | volatile |
| 19 | Kyrgyzstan | 3 1000 t | 2023 | up 50.0% | volatile |
| 19 | Liberia | 3 1000 t | 2023 | up 200.0% | volatile |
| 19 | Niger | 3 1000 t | 2023 | down 66.7% | volatile |
| 19 | New Zealand | 3 1000 t | 2023 | — | volatile |
| 19 | Slovenia | 3 1000 t | 2023 | up 200.0% | volatile |
| 19 | Polynesia | 3 1000 t | 2023 | — | volatile |
| 28 | Australia | 2 1000 t | 2023 | down 90.5% | volatile |
| 28 | Bosnia and Herzegovina | 2 1000 t | 2023 | up 200.0% | volatile |
| 28 | Ethiopia | 2 1000 t | 2023 | up 200.0% | volatile |
| 28 | French Polynesia | 2 1000 t | 2023 | — | volatile |
| 28 | Lao People's Democratic Republic | 2 1000 t | 2023 | — | flat |
| 33 | Armenia | 1 1000 t | 2023 | — | volatile |
| 33 | Kiribati | 1 1000 t | 2023 | — | volatile |
| 33 | Maldives | 1 1000 t | 2023 | up 150.0% | volatile |
| 33 | Mauritania | 1 1000 t | 2023 | down 80.0% | volatile |
| 33 | Portugal | 1 1000 t | 2023 | down 66.7% | volatile |
| 33 | Paraguay | 1 1000 t | 2023 | — | volatile |
| 33 | Rwanda | 1 1000 t | 2023 | unchanged | volatile |
| 33 | Solomon Islands | 1 1000 t | 2023 | up 200.0% | volatile |
| 33 | Uruguay | 1 1000 t | 2023 | — | volatile |
| 33 | Samoa | 1 1000 t | 2023 | — | volatile |
| 33 | Micronesia | 1 1000 t | 2023 | — | volatile |
| 33 | Cabo Verde | 1 1000 t | 2023 | up 200.0% | volatile |
| 33 | Melanesia | 1 1000 t | 2023 | unchanged | volatile |
| 33 | United Republic of Tanzania | 1 1000 t | 2023 | down 50.0% | volatile |
| 47 | Afghanistan | 0 1000 t | 2023 | down 100.0% | volatile |
| 47 | Angola | 0 1000 t | 2023 | — | volatile |
| 47 | Albania | 0 1000 t | 2023 | down 100.0% | flat |
| 47 | United Arab Emirates | 0 1000 t | 2023 | — | volatile |
| 47 | Argentina | 0 1000 t | 2023 | — | flat |
| 47 | Austria | 0 1000 t | 2023 | down 100.0% | flat |
| 47 | Belgium | 0 1000 t | 2023 | — | flat |
| 47 | Burkina Faso | 0 1000 t | 2023 | down 100.0% | volatile |
| 47 | Bangladesh | 0 1000 t | 2023 | — | volatile |
| 47 | Bulgaria | 0 1000 t | 2023 | — | volatile |
| 47 | Bahrain | 0 1000 t | 2023 | — | flat |
| 47 | Bahamas | 0 1000 t | 2023 | down 100.0% | flat |
| 47 | Belize | 0 1000 t | 2023 | down 100.0% | volatile |
| 47 | Brazil | 0 1000 t | 2023 | — | flat |
| 47 | Bhutan | 0 1000 t | 2023 | — | volatile |
| 47 | Canada | 0 1000 t | 2023 | down 100.0% | volatile |
| 47 | Switzerland | 0 1000 t | 2023 | — | volatile |
| 47 | Chile | 0 1000 t | 2023 | up 100.0% | volatile |
| 47 | Cameroon | 0 1000 t | 2023 | down 100.0% | volatile |
| 47 | Congo | 0 1000 t | 2023 | up 100.0% | volatile |
| 47 | Colombia | 0 1000 t | 2023 | — | volatile |
| 47 | Comoros | 0 1000 t | 2023 | up 100.0% | volatile |
| 47 | Costa Rica | 0 1000 t | 2023 | — | flat |
| 47 | Cuba | 0 1000 t | 2019 | — | flat |
| 47 | Cyprus | 0 1000 t | 2023 | up 100.0% | volatile |
| 47 | Czechia | 0 1000 t | 2023 | down 100.0% | volatile |
| 47 | Germany | 0 1000 t | 2023 | — | flat |
| 47 | Djibouti | 0 1000 t | 2023 | — | flat |
| 47 | Denmark | 0 1000 t | 2023 | — | flat |
| 47 | Dominican Republic | 0 1000 t | 2023 | down 100.0% | flat |
| 47 | Algeria | 0 1000 t | 2023 | — | volatile |
| 47 | Ecuador | 0 1000 t | 2023 | down 100.0% | volatile |
| 47 | Egypt | 0 1000 t | 2023 | up 100.0% | volatile |
| 47 | Spain | 0 1000 t | 2023 | — | flat |
| 47 | Estonia | 0 1000 t | 2023 | down 100.0% | volatile |
| 47 | Fiji | 0 1000 t | 2023 | — | flat |
| 47 | Gabon | 0 1000 t | 2023 | up 100.0% | volatile |
| 47 | Georgia | 0 1000 t | 2023 | down 100.0% | volatile |
| 47 | Ghana | 0 1000 t | 2023 | down 100.0% | volatile |
| 47 | Guinea | 0 1000 t | 2023 | up 100.0% | volatile |
| 47 | Gambia | 0 1000 t | 2023 | — | flat |
| 47 | Guinea-Bissau | 0 1000 t | 2023 | down 100.0% | volatile |
| 47 | Greece | 0 1000 t | 2023 | up 100.0% | volatile |
| 47 | Guatemala | 0 1000 t | 2023 | — | flat |
| 47 | Guyana | 0 1000 t | 2023 | — | volatile |
| 47 | Honduras | 0 1000 t | 2023 | up 100.0% | volatile |
| 47 | Haiti | 0 1000 t | 2023 | up 100.0% | volatile |
| 47 | Hungary | 0 1000 t | 2023 | — | flat |
| 47 | Indonesia | 0 1000 t | 2023 | — | flat |
| 47 | India | 0 1000 t | 2023 | — | flat |
| 47 | Ireland | 0 1000 t | 2023 | down 100.0% | volatile |
| 47 | Iraq | 0 1000 t | 2023 | — | volatile |
| 47 | Israel | 0 1000 t | 2023 | up 100.0% | volatile |
| 47 | Italy | 0 1000 t | 2023 | — | flat |
| 47 | Jordan | 0 1000 t | 2023 | down 100.0% | volatile |
| 47 | Kazakhstan | 0 1000 t | 2023 | down 100.0% | volatile |
| 47 | Kenya | 0 1000 t | 2023 | down 100.0% | volatile |
| 47 | Cambodia | 0 1000 t | 2023 | down 100.0% | volatile |
| 47 | Saint Kitts and Nevis | 0 1000 t | 2023 | up 100.0% | flat |
| 47 | Kuwait | 0 1000 t | 2023 | down 100.0% | volatile |
| 47 | Sri Lanka | 0 1000 t | 2023 | down 100.0% | flat |
| 47 | Lesotho | 0 1000 t | 2023 | down 100.0% | flat |
| 47 | Lithuania | 0 1000 t | 2023 | — | flat |
| 47 | Luxembourg | 0 1000 t | 2023 | — | volatile |
| 47 | Latvia | 0 1000 t | 2023 | — | volatile |
| 47 | Morocco | 0 1000 t | 2023 | — | flat |
| 47 | Madagascar | 0 1000 t | 2023 | — | volatile |
| 47 | Mexico | 0 1000 t | 2023 | up 100.0% | volatile |
| 47 | Marshall Islands | 0 1000 t | 2023 | — | flat |
| 47 | Malta | 0 1000 t | 2023 | — | flat |
| 47 | Myanmar | 0 1000 t | 2023 | — | volatile |
| 47 | Montenegro | 0 1000 t | 2023 | down 100.0% | volatile |
| 47 | Mozambique | 0 1000 t | 2023 | up 100.0% | volatile |
| 47 | Mauritius | 0 1000 t | 2023 | down 100.0% | volatile |
| 47 | Malawi | 0 1000 t | 2023 | down 100.0% | volatile |
| 47 | Malaysia | 0 1000 t | 2023 | — | flat |
| 47 | Namibia | 0 1000 t | 2023 | — | volatile |
| 47 | New Caledonia | 0 1000 t | 2023 | — | volatile |
| 47 | Nigeria | 0 1000 t | 2023 | — | volatile |
| 47 | Nicaragua | 0 1000 t | 2023 | down 100.0% | volatile |
| 47 | Nepal | 0 1000 t | 2023 | — | volatile |
| 47 | Nauru | 0 1000 t | 2023 | — | volatile |
| 47 | Pakistan | 0 1000 t | 2023 | — | volatile |
| 47 | Panama | 0 1000 t | 2023 | — | volatile |
| 47 | Peru | 0 1000 t | 2023 | — | flat |
| 47 | Papua New Guinea | 0 1000 t | 2023 | down 100.0% | volatile |
| 47 | Poland | 0 1000 t | 2023 | — | volatile |
| 47 | Saudi Arabia | 0 1000 t | 2023 | down 100.0% | volatile |
| 47 | Sierra Leone | 0 1000 t | 2023 | down 100.0% | volatile |
| 47 | El Salvador | 0 1000 t | 2023 | — | volatile |
| 47 | Serbia | 0 1000 t | 2023 | — | flat |
| 47 | Sao Tome and Principe | 0 1000 t | 2023 | — | flat |
| 47 | Suriname | 0 1000 t | 2023 | down 100.0% | flat |
| 47 | Slovakia | 0 1000 t | 2023 | down 100.0% | flat |
| 47 | Seychelles | 0 1000 t | 2023 | — | volatile |
| 47 | Thailand | 0 1000 t | 2023 | — | flat |
| 47 | Tajikistan | 0 1000 t | 2023 | — | flat |
| 47 | Turkmenistan | 0 1000 t | 2023 | — | flat |
| 47 | Tonga | 0 1000 t | 2023 | — | volatile |
| 47 | Trinidad and Tobago | 0 1000 t | 2023 | up 100.0% | volatile |
| 47 | Tunisia | 0 1000 t | 2023 | — | flat |
| 47 | Tuvalu | 0 1000 t | 2023 | — | flat |
| 47 | Uganda | 0 1000 t | 2023 | — | flat |
| 47 | Ukraine | 0 1000 t | 2023 | — | volatile |
| 47 | Vanuatu | 0 1000 t | 2023 | — | flat |
| 47 | Yemen | 0 1000 t | 2023 | down 100.0% | volatile |
| 47 | Zambia | 0 1000 t | 2023 | down 100.0% | volatile |
| 47 | Zimbabwe | 0 1000 t | 2023 | down 100.0% | volatile |
| 47 | Timor-Leste | 0 1000 t | 2023 | — | volatile |
| 47 | Bolivia (Plurinational State of) | 0 1000 t | 2023 | — | flat |
| 47 | China, Hong Kong SAR | 0 1000 t | 2023 | down 100.0% | volatile |
| 47 | Iran (Islamic Republic of) | 0 1000 t | 2023 | — | volatile |
| 47 | Republic of Korea | 0 1000 t | 2023 | — | flat |
| 47 | Republic of Moldova | 0 1000 t | 2023 | — | volatile |
| 47 | Russian Federation | 0 1000 t | 2023 | up 100.0% | volatile |
| 47 | Syrian Arab Republic | 0 1000 t | 2023 | down 100.0% | volatile |
| 47 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | down 100.0% | volatile |
| 47 | Viet Nam | 0 1000 t | 2023 | — | flat |
| 47 | Türkiye | 0 1000 t | 2023 | — | flat |
| 47 | China, mainland | 0 1000 t | 2023 | — | flat |
| 47 | Côte d'Ivoire | 0 1000 t | 2023 | — | flat |
| 47 | China, Taiwan Province of | 0 1000 t | 2023 | up 100.0% | volatile |
| 47 | Netherlands (Kingdom of the) | 0 1000 t | 2023 | — | flat |
| 47 | United Kingdom of Great Britain and Northern Ireland | 0 1000 t | 2023 | up 100.0% | volatile |
| 47 | Micronesia (Federated States of) | 0 1000 t | 2023 | — | flat |
| 172 | Saint Lucia | -1 1000 t | 2023 | down 200.0% | volatile |
| 173 | Saint Vincent and the Grenadines | -3 1000 t | 2023 | down 50.0% | volatile |
| 174 | Mongolia | -4 1000 t | 2023 | down 180.0% | volatile |
| 175 | Barbados | -6 1000 t | 2023 | down 500.0% | volatile |
| 176 | Qatar | -7 1000 t | 2023 | — | flat |
| 177 | Oman | -10 1000 t | 2023 | — | flat |
| 177 | Eswatini | -10 1000 t | 2023 | — | volatile |
| 179 | Lebanon | -12 1000 t | 2023 | down 1,100.0% | volatile |
| 180 | Norway | -20 1000 t | 2023 | down 217.6% | volatile |
| 181 | Belarus | -69 1000 t | 2023 | down 560.0% | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- World 187 1000 t
- European Union (27) 142 1000 t
- Low Income Food Deficit Countries (LIFDCs) 114 1000 t
- Africa 87 1000 t
- Least Developed Countries (LDCs) 86 1000 t
- Net Food Importing Developing Countries (NFIDCs) 85 1000 t
- Western Europe 80 1000 t
- Western Africa 69 1000 t
- Europe 63 1000 t
- Land Locked Developing Countries (LLDCs) 42 1000 t
- Central Asia 30 1000 t
- Asia 19 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.