Eggs — Export quantity 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 — Export quantity is currently reported for 146 countries. The highest value is 803 1000 t in Netherlands (Kingdom of the); the lowest is 0 1000 t in China, Macao SAR.
The median across all reporting countries is 1 1000 t, and the mean is 23.36 1000 t.
Over the past decade 35 countries rose and 25 fell. The largest increase was in Morocco (up 3,400.0%), and the largest decrease in Mexico (down 100.0%).
Eggs — Export quantity: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Netherlands (Kingdom of the) | 803 1000 t | 2023 | up 17.4% | rising |
| 2 | Poland | 318 1000 t | 2023 | up 25.2% | rising |
| 3 | Germany | 219 1000 t | 2023 | down 3.1% | flat |
| 4 | Türkiye | 208 1000 t | 2023 | down 26.0% | rising |
| 5 | China | 177 1000 t | 2023 | up 71.8% | rising |
| 6 | China, mainland | 174 1000 t | 2023 | up 77.6% | rising |
| 7 | Spain | 150 1000 t | 2023 | down 4.5% | rising |
| 8 | Belgium | 145 1000 t | 2023 | up 40.8% | rising |
| 9 | India | 124 1000 t | 2023 | up 65.3% | rising |
| 10 | Jordan | 102 1000 t | 2023 | up 537.5% | volatile |
| 11 | France | 97 1000 t | 2023 | down 11.8% | falling |
| 12 | Italy | 81 1000 t | 2023 | up 118.9% | rising |
| 13 | Malaysia | 76 1000 t | 2023 | down 20.0% | falling |
| 14 | Latvia | 61 1000 t | 2023 | up 177.3% | rising |
| 15 | Brazil | 59 1000 t | 2023 | up 195.0% | rising |
| 16 | Denmark | 41 1000 t | 2023 | up 192.9% | rising |
| 17 | Morocco | 35 1000 t | 2023 | up 3,400.0% | volatile |
| 17 | Thailand | 35 1000 t | 2023 | up 40.0% | rising |
| 19 | Czechia | 33 1000 t | 2023 | up 83.3% | rising |
| 19 | Ukraine | 33 1000 t | 2023 | down 32.7% | volatile |
| 19 | United Kingdom of Great Britain and Northern Ireland | 33 1000 t | 2023 | up 26.9% | rising |
| 22 | Oman | 30 1000 t | 2023 | up 500.0% | volatile |
| 22 | Portugal | 30 1000 t | 2023 | down 6.2% | rising |
| 22 | Romania | 30 1000 t | 2023 | up 42.9% | rising |
| 25 | Bulgaria | 29 1000 t | 2023 | up 123.1% | rising |
| 26 | Austria | 24 1000 t | 2023 | up 100.0% | rising |
| 27 | Lithuania | 22 1000 t | 2023 | up 69.2% | rising |
| 27 | Russian Federation | 22 1000 t | 2023 | up 15.8% | rising |
| 29 | Sweden | 20 1000 t | 2023 | up 81.8% | rising |
| 30 | Finland | 13 1000 t | 2023 | up 18.2% | rising |
| 30 | Hungary | 13 1000 t | 2023 | unchanged | rising |
| 32 | Ireland | 12 1000 t | 2023 | up 71.4% | rising |
| 32 | Slovakia | 12 1000 t | 2023 | unchanged | falling |
| 34 | Egypt | 11 1000 t | 2023 | up 120.0% | volatile |
| 35 | Kazakhstan | 10 1000 t | 2023 | — | volatile |
| 36 | United Arab Emirates | 8 1000 t | 2023 | down 27.3% | rising |
| 37 | Pakistan | 7 1000 t | 2023 | down 41.7% | volatile |
| 38 | Canada | 6 1000 t | 2023 | down 53.8% | falling |
| 38 | Viet Nam | 6 1000 t | 2023 | up 200.0% | rising |
| 40 | Serbia | 5 1000 t | 2023 | up 400.0% | volatile |
| 41 | Albania | 4 1000 t | 2023 | up 300.0% | volatile |
| 41 | Argentina | 4 1000 t | 2023 | down 60.0% | volatile |
| 41 | Belarus | 4 1000 t | 2023 | down 91.8% | falling |
| 41 | Dominican Republic | 4 1000 t | 2023 | — | volatile |
| 41 | Greece | 4 1000 t | 2023 | unchanged | rising |
| 41 | Kuwait | 4 1000 t | 2023 | down 63.6% | volatile |
| 41 | Saudi Arabia | 4 1000 t | 2023 | down 92.7% | volatile |
| 41 | Uzbekistan | 4 1000 t | 2023 | — | volatile |
| 41 | Caribbean | 4 1000 t | 2023 | — | volatile |
| 41 | Iran (Islamic Republic of) | 4 1000 t | 2023 | up 300.0% | volatile |
| 51 | Azerbaijan | 3 1000 t | 2023 | — | volatile |
| 51 | Guatemala | 3 1000 t | 2023 | — | volatile |
| 51 | Luxembourg | 3 1000 t | 2023 | up 200.0% | volatile |
| 51 | Australia and New Zealand | 3 1000 t | 2023 | down 40.0% | falling |
| 55 | Australia | 2 1000 t | 2023 | up 100.0% | volatile |
| 55 | Bosnia and Herzegovina | 2 1000 t | 2023 | down 50.0% | falling |
| 55 | Costa Rica | 2 1000 t | 2023 | down 33.3% | flat |
| 55 | Estonia | 2 1000 t | 2023 | down 50.0% | falling |
| 55 | Fiji | 2 1000 t | 2023 | unchanged | volatile |
| 55 | Honduras | 2 1000 t | 2023 | — | volatile |
| 55 | Croatia | 2 1000 t | 2023 | up 100.0% | rising |
| 55 | Indonesia | 2 1000 t | 2023 | — | volatile |
| 55 | Norway | 2 1000 t | 2023 | unchanged | rising |
| 55 | Peru | 2 1000 t | 2023 | down 71.4% | volatile |
| 55 | Slovenia | 2 1000 t | 2023 | up 100.0% | rising |
| 55 | Zambia | 2 1000 t | 2023 | up 100.0% | rising |
| 55 | Melanesia | 2 1000 t | 2023 | unchanged | volatile |
| 55 | Republic of Korea | 2 1000 t | 2023 | up 100.0% | volatile |
| 55 | China, Taiwan Province of | 2 1000 t | 2023 | down 33.3% | rising |
| 70 | Switzerland | 1 1000 t | 2023 | unchanged | flat |
| 70 | Cameroon | 1 1000 t | 2023 | — | volatile |
| 70 | Colombia | 1 1000 t | 2023 | unchanged | volatile |
| 70 | Georgia | 1 1000 t | 2023 | — | volatile |
| 70 | Sri Lanka | 1 1000 t | 2023 | unchanged | volatile |
| 70 | Malawi | 1 1000 t | 2023 | unchanged | volatile |
| 70 | Nicaragua | 1 1000 t | 2023 | — | volatile |
| 70 | New Zealand | 1 1000 t | 2023 | down 75.0% | falling |
| 70 | Panama | 1 1000 t | 2023 | unchanged | rising |
| 70 | Rwanda | 1 1000 t | 2022 | — | volatile |
| 70 | Tajikistan | 1 1000 t | 2022 | — | volatile |
| 70 | Tunisia | 1 1000 t | 2022 | — | volatile |
| 70 | Uganda | 1 1000 t | 2023 | unchanged | volatile |
| 70 | China, Hong Kong SAR | 1 1000 t | 2023 | down 50.0% | volatile |
| 84 | Afghanistan | 0 1000 t | 2022 | — | flat |
| 84 | Angola | 0 1000 t | 2023 | — | flat |
| 84 | Armenia | 0 1000 t | 2023 | — | flat |
| 84 | Antigua and Barbuda | 0 1000 t | 2020 | — | flat |
| 84 | Burkina Faso | 0 1000 t | 2023 | — | flat |
| 84 | Bangladesh | 0 1000 t | 2015 | — | flat |
| 84 | Bahrain | 0 1000 t | 2023 | — | flat |
| 84 | Bahamas | 0 1000 t | 2018 | — | flat |
| 84 | Belize | 0 1000 t | 2017 | — | flat |
| 84 | Barbados | 0 1000 t | 2020 | — | flat |
| 84 | Botswana | 0 1000 t | 2023 | — | flat |
| 84 | Chile | 0 1000 t | 2022 | — | flat |
| 84 | Congo | 0 1000 t | 2023 | — | volatile |
| 84 | Cyprus | 0 1000 t | 2023 | — | flat |
| 84 | Djibouti | 0 1000 t | 2023 | — | flat |
| 84 | Algeria | 0 1000 t | 2023 | — | flat |
| 84 | Ecuador | 0 1000 t | 2020 | — | flat |
| 84 | Ethiopia | 0 1000 t | 2023 | — | flat |
| 84 | Gabon | 0 1000 t | 2023 | — | flat |
| 84 | Ghana | 0 1000 t | 2023 | — | flat |
| 84 | Gambia | 0 1000 t | 2016 | — | flat |
| 84 | Guyana | 0 1000 t | 2022 | — | flat |
| 84 | Iraq | 0 1000 t | 2022 | — | volatile |
| 84 | Iceland | 0 1000 t | 2023 | — | flat |
| 84 | Israel | 0 1000 t | 2017 | — | flat |
| 84 | Jamaica | 0 1000 t | 2023 | — | flat |
| 84 | Kenya | 0 1000 t | 2023 | — | volatile |
| 84 | Kyrgyzstan | 0 1000 t | 2023 | — | flat |
| 84 | Lebanon | 0 1000 t | 2023 | — | volatile |
| 84 | Libya | 0 1000 t | 2019 | — | flat |
| 84 | Lesotho | 0 1000 t | 2023 | — | flat |
| 84 | Madagascar | 0 1000 t | 2022 | — | flat |
| 84 | Mexico | 0 1000 t | 2023 | down 100.0% | volatile |
| 84 | North Macedonia | 0 1000 t | 2022 | down 100.0% | volatile |
| 84 | Malta | 0 1000 t | 2020 | — | flat |
| 84 | Myanmar | 0 1000 t | 2018 | — | flat |
| 84 | Montenegro | 0 1000 t | 2023 | — | flat |
| 84 | Mozambique | 0 1000 t | 2023 | — | flat |
| 84 | Mauritius | 0 1000 t | 2023 | — | flat |
| 84 | Namibia | 0 1000 t | 2023 | — | volatile |
| 84 | New Caledonia | 0 1000 t | 2023 | — | flat |
| 84 | Niger | 0 1000 t | 2019 | — | flat |
| 84 | Nigeria | 0 1000 t | 2023 | — | volatile |
| 84 | Nepal | 0 1000 t | 2016 | — | flat |
| 84 | Philippines | 0 1000 t | 2023 | — | flat |
| 84 | Senegal | 0 1000 t | 2023 | — | flat |
| 84 | El Salvador | 0 1000 t | 2023 | — | volatile |
| 84 | Eswatini | 0 1000 t | 2023 | — | volatile |
| 84 | Trinidad and Tobago | 0 1000 t | 2023 | — | flat |
| 84 | Uruguay | 0 1000 t | 2022 | — | flat |
| 84 | Vanuatu | 0 1000 t | 2023 | — | flat |
| 84 | Samoa | 0 1000 t | 2021 | — | flat |
| 84 | Yemen | 0 1000 t | 2023 | — | volatile |
| 84 | Zimbabwe | 0 1000 t | 2023 | down 100.0% | volatile |
| 84 | Cabo Verde | 0 1000 t | 2023 | — | flat |
| 84 | Polynesia | 0 1000 t | 2021 | — | flat |
| 84 | Bolivia (Plurinational State of) | 0 1000 t | 2023 | — | flat |
| 84 | Republic of Moldova | 0 1000 t | 2021 | — | flat |
| 84 | Syrian Arab Republic | 0 1000 t | 2023 | — | volatile |
| 84 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2016 | — | flat |
| 84 | Côte d'Ivoire | 0 1000 t | 2023 | — | flat |
| 84 | United Republic of Tanzania | 0 1000 t | 2023 | — | flat |
| 84 | China, Macao SAR | 0 1000 t | 2018 | — | flat |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- World 3,448 1000 t
- Europe 2,273 1000 t
- European Union (27) 2,168 1000 t
- Western Europe 1,292 1000 t
- Asia 829 1000 t
- Eastern Europe 495 1000 t
- Western Asia 361 1000 t
- Americas 284 1000 t
- Southern Europe 280 1000 t
- Northern Europe 206 1000 t
- Northern America 204 1000 t
- Eastern Asia 198 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.