Eggs — 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
Eggs — Stock Variation is currently reported for 157 countries. The highest value is 15 1000 t in China; the lowest is -1 1000 t in Iran (Islamic Republic of).
The median across all reporting countries is 0 1000 t, and the mean is 0.3885 1000 t.
The gap between the highest and lowest reporting country is a factor of about 15.
Over the past decade 12 countries rose and 14 fell. The largest increase was in Brazil (up 600.0%), and the largest decrease in United Arab Emirates (down 100.0%).
Eggs — Stock Variation: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | China | 15 1000 t | 2023 | down 79.2% | volatile |
| 1 | China, mainland | 15 1000 t | 2023 | down 79.2% | volatile |
| 3 | Brazil | 7 1000 t | 2023 | up 600.0% | volatile |
| 4 | Mauritania | 6 1000 t | 2018 | — | volatile |
| 5 | India | 4 1000 t | 2023 | up 200.0% | volatile |
| 6 | Denmark | 3 1000 t | 2023 | — | volatile |
| 6 | Spain | 3 1000 t | 2023 | up 109.1% | volatile |
| 6 | Thailand | 3 1000 t | 2023 | up 200.0% | volatile |
| 9 | Gambia | 2 1000 t | 2021 | — | volatile |
| 10 | Czechia | 1 1000 t | 2023 | — | volatile |
| 10 | Estonia | 1 1000 t | 2023 | — | volatile |
| 10 | Indonesia | 1 1000 t | 2023 | unchanged | volatile |
| 10 | Philippines | 1 1000 t | 2023 | — | volatile |
| 14 | Angola | 0 1000 t | 2023 | — | flat |
| 14 | Albania | 0 1000 t | 2023 | — | flat |
| 14 | United Arab Emirates | 0 1000 t | 2023 | down 100.0% | flat |
| 14 | Argentina | 0 1000 t | 2023 | up 100.0% | volatile |
| 14 | Armenia | 0 1000 t | 2023 | — | flat |
| 14 | Australia | 0 1000 t | 2023 | — | volatile |
| 14 | Austria | 0 1000 t | 2023 | down 100.0% | flat |
| 14 | Azerbaijan | 0 1000 t | 2023 | — | flat |
| 14 | Belgium | 0 1000 t | 2023 | up 100.0% | volatile |
| 14 | Burkina Faso | 0 1000 t | 2023 | — | flat |
| 14 | Bangladesh | 0 1000 t | 2023 | — | flat |
| 14 | Bulgaria | 0 1000 t | 2023 | — | volatile |
| 14 | Bahrain | 0 1000 t | 2023 | — | flat |
| 14 | Bahamas | 0 1000 t | 2023 | — | flat |
| 14 | Bosnia and Herzegovina | 0 1000 t | 2023 | — | flat |
| 14 | Belarus | 0 1000 t | 2023 | up 100.0% | volatile |
| 14 | Belize | 0 1000 t | 2021 | — | flat |
| 14 | Barbados | 0 1000 t | 2023 | — | flat |
| 14 | Botswana | 0 1000 t | 2023 | — | flat |
| 14 | Canada | 0 1000 t | 2023 | down 100.0% | volatile |
| 14 | Switzerland | 0 1000 t | 2023 | up 100.0% | volatile |
| 14 | Chile | 0 1000 t | 2023 | up 100.0% | volatile |
| 14 | Cameroon | 0 1000 t | 2023 | — | flat |
| 14 | Congo | 0 1000 t | 2023 | — | flat |
| 14 | Colombia | 0 1000 t | 2023 | — | flat |
| 14 | Costa Rica | 0 1000 t | 2023 | — | volatile |
| 14 | Cuba | 0 1000 t | 2019 | up 100.0% | volatile |
| 14 | Cyprus | 0 1000 t | 2023 | — | flat |
| 14 | Germany | 0 1000 t | 2023 | — | volatile |
| 14 | Algeria | 0 1000 t | 2023 | — | volatile |
| 14 | Ecuador | 0 1000 t | 2023 | — | flat |
| 14 | Egypt | 0 1000 t | 2023 | — | flat |
| 14 | Ethiopia | 0 1000 t | 2023 | — | flat |
| 14 | Finland | 0 1000 t | 2023 | — | volatile |
| 14 | Fiji | 0 1000 t | 2021 | — | flat |
| 14 | France | 0 1000 t | 2023 | — | flat |
| 14 | Gabon | 0 1000 t | 2023 | — | flat |
| 14 | Georgia | 0 1000 t | 2021 | — | flat |
| 14 | Ghana | 0 1000 t | 2023 | — | flat |
| 14 | Guinea | 0 1000 t | 2023 | — | flat |
| 14 | Greece | 0 1000 t | 2023 | — | volatile |
| 14 | Grenada | 0 1000 t | 2023 | — | flat |
| 14 | Guatemala | 0 1000 t | 2023 | — | flat |
| 14 | Guyana | 0 1000 t | 2023 | — | flat |
| 14 | Honduras | 0 1000 t | 2023 | — | flat |
| 14 | Croatia | 0 1000 t | 2023 | — | flat |
| 14 | Haiti | 0 1000 t | 2023 | — | flat |
| 14 | Hungary | 0 1000 t | 2023 | — | volatile |
| 14 | Ireland | 0 1000 t | 2023 | down 100.0% | volatile |
| 14 | Iraq | 0 1000 t | 2023 | — | flat |
| 14 | Iceland | 0 1000 t | 2023 | — | flat |
| 14 | Israel | 0 1000 t | 2023 | — | flat |
| 14 | Italy | 0 1000 t | 2023 | — | volatile |
| 14 | Jamaica | 0 1000 t | 2023 | — | flat |
| 14 | Jordan | 0 1000 t | 2023 | down 100.0% | volatile |
| 14 | Kazakhstan | 0 1000 t | 2023 | — | flat |
| 14 | Kenya | 0 1000 t | 2023 | — | flat |
| 14 | Kyrgyzstan | 0 1000 t | 2023 | — | volatile |
| 14 | Cambodia | 0 1000 t | 2023 | — | flat |
| 14 | Kuwait | 0 1000 t | 2023 | — | flat |
| 14 | Lebanon | 0 1000 t | 2023 | — | flat |
| 14 | Libya | 0 1000 t | 2023 | — | flat |
| 14 | Saint Lucia | 0 1000 t | 2023 | — | flat |
| 14 | Sri Lanka | 0 1000 t | 2023 | — | flat |
| 14 | Lesotho | 0 1000 t | 2023 | — | flat |
| 14 | Lithuania | 0 1000 t | 2023 | — | volatile |
| 14 | Luxembourg | 0 1000 t | 2023 | — | volatile |
| 14 | Latvia | 0 1000 t | 2023 | — | flat |
| 14 | Morocco | 0 1000 t | 2023 | — | volatile |
| 14 | Madagascar | 0 1000 t | 2023 | — | flat |
| 14 | Maldives | 0 1000 t | 2023 | — | flat |
| 14 | Mexico | 0 1000 t | 2023 | down 100.0% | volatile |
| 14 | Marshall Islands | 0 1000 t | 2023 | — | volatile |
| 14 | North Macedonia | 0 1000 t | 2023 | down 100.0% | volatile |
| 14 | Malta | 0 1000 t | 2023 | — | flat |
| 14 | Myanmar | 0 1000 t | 2023 | — | flat |
| 14 | Mongolia | 0 1000 t | 2023 | — | flat |
| 14 | Mozambique | 0 1000 t | 2023 | — | flat |
| 14 | Mauritius | 0 1000 t | 2023 | — | flat |
| 14 | Malawi | 0 1000 t | 2023 | — | flat |
| 14 | Malaysia | 0 1000 t | 2023 | — | flat |
| 14 | Namibia | 0 1000 t | 2023 | — | flat |
| 14 | New Caledonia | 0 1000 t | 2023 | — | flat |
| 14 | Niger | 0 1000 t | 2023 | — | flat |
| 14 | Nigeria | 0 1000 t | 2023 | — | volatile |
| 14 | Nicaragua | 0 1000 t | 2023 | — | volatile |
| 14 | Norway | 0 1000 t | 2023 | — | flat |
| 14 | Nepal | 0 1000 t | 2023 | — | flat |
| 14 | New Zealand | 0 1000 t | 2023 | — | volatile |
| 14 | Oman | 0 1000 t | 2023 | — | flat |
| 14 | Pakistan | 0 1000 t | 2023 | — | flat |
| 14 | Panama | 0 1000 t | 2023 | — | volatile |
| 14 | Peru | 0 1000 t | 2023 | — | flat |
| 14 | Poland | 0 1000 t | 2023 | down 100.0% | flat |
| 14 | Portugal | 0 1000 t | 2023 | down 100.0% | volatile |
| 14 | Paraguay | 0 1000 t | 2023 | — | flat |
| 14 | French Polynesia | 0 1000 t | 2023 | — | flat |
| 14 | Qatar | 0 1000 t | 2023 | — | volatile |
| 14 | Romania | 0 1000 t | 2023 | down 100.0% | volatile |
| 14 | Rwanda | 0 1000 t | 2023 | — | flat |
| 14 | Saudi Arabia | 0 1000 t | 2023 | — | volatile |
| 14 | Senegal | 0 1000 t | 2023 | — | volatile |
| 14 | Sierra Leone | 0 1000 t | 2023 | — | flat |
| 14 | El Salvador | 0 1000 t | 2023 | — | volatile |
| 14 | Serbia | 0 1000 t | 2023 | — | volatile |
| 14 | Slovakia | 0 1000 t | 2023 | down 100.0% | volatile |
| 14 | Slovenia | 0 1000 t | 2023 | — | flat |
| 14 | Sweden | 0 1000 t | 2023 | up 100.0% | volatile |
| 14 | Eswatini | 0 1000 t | 2023 | — | flat |
| 14 | Seychelles | 0 1000 t | 2023 | — | flat |
| 14 | Tajikistan | 0 1000 t | 2023 | — | flat |
| 14 | Trinidad and Tobago | 0 1000 t | 2023 | — | flat |
| 14 | Tunisia | 0 1000 t | 2023 | — | volatile |
| 14 | Uganda | 0 1000 t | 2023 | — | flat |
| 14 | Ukraine | 0 1000 t | 2023 | up 100.0% | volatile |
| 14 | Uruguay | 0 1000 t | 2023 | — | flat |
| 14 | Uzbekistan | 0 1000 t | 2023 | — | flat |
| 14 | Samoa | 0 1000 t | 2020 | — | flat |
| 14 | Yemen | 0 1000 t | 2023 | — | flat |
| 14 | Zambia | 0 1000 t | 2023 | — | flat |
| 14 | Zimbabwe | 0 1000 t | 2023 | — | flat |
| 14 | Micronesia | 0 1000 t | 2023 | — | volatile |
| 14 | Cabo Verde | 0 1000 t | 2023 | — | flat |
| 14 | Melanesia | 0 1000 t | 2023 | — | flat |
| 14 | Polynesia | 0 1000 t | 2023 | — | flat |
| 14 | Democratic Republic of the Congo | 0 1000 t | 2023 | — | flat |
| 14 | Caribbean | 0 1000 t | 2023 | — | volatile |
| 14 | Bolivia (Plurinational State of) | 0 1000 t | 2023 | — | flat |
| 14 | China, Hong Kong SAR | 0 1000 t | 2023 | — | flat |
| 14 | Republic of Korea | 0 1000 t | 2023 | down 100.0% | volatile |
| 14 | Republic of Moldova | 0 1000 t | 2023 | — | flat |
| 14 | Russian Federation | 0 1000 t | 2023 | — | volatile |
| 14 | Syrian Arab Republic | 0 1000 t | 2023 | — | flat |
| 14 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | — | flat |
| 14 | Viet Nam | 0 1000 t | 2023 | — | flat |
| 14 | Türkiye | 0 1000 t | 2023 | — | flat |
| 14 | Australia and New Zealand | 0 1000 t | 2023 | — | volatile |
| 14 | Côte d'Ivoire | 0 1000 t | 2023 | — | flat |
| 14 | United Republic of Tanzania | 0 1000 t | 2023 | — | flat |
| 14 | China, Taiwan Province of | 0 1000 t | 2023 | — | volatile |
| 14 | Netherlands (Kingdom of the) | 0 1000 t | 2023 | — | flat |
| 14 | United Kingdom of Great Britain and Northern Ireland | 0 1000 t | 2023 | — | volatile |
| 14 | Democratic People's Republic of Korea | 0 1000 t | 2018 | — | flat |
| 157 | Iran (Islamic Republic of) | -1 1000 t | 2023 | — | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- World 42 1000 t
- Asia 23 1000 t
- Eastern Asia 15 1000 t
- European Union (27) 10 1000 t
- Europe 10 1000 t
- Americas 9 1000 t
- South America 6 1000 t
- South-eastern Asia 5 1000 t
- Northern Europe 4 1000 t
- Southern Europe 4 1000 t
- Southern Asia 3 1000 t
- Northern America 2 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.