Alcohol, Non-Food — 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
Alcohol, Non-Food — Export quantity is currently reported for 141 countries. The highest value is 2,013 1000 t in Brazil; the lowest is 0 1000 t in China, Taiwan Province of.
The median across all reporting countries is 1 1000 t, and the mean is 63.74 1000 t.
Over the past decade 29 countries rose and 42 fell. The largest increase was in Ukraine (up 3,850.0%), and the largest decrease in Armenia (down 100.0%).
Alcohol, Non-Food — Export quantity: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Brazil | 2,013 1000 t | 2023 | down 13.3% | flat |
| 2 | Netherlands (Kingdom of the) | 1,589 1000 t | 2023 | up 223.0% | rising |
| 3 | Pakistan | 660 1000 t | 2023 | up 15.4% | rising |
| 4 | Belgium | 503 1000 t | 2023 | up 7.9% | rising |
| 5 | France | 493 1000 t | 2023 | down 28.9% | falling |
| 6 | Hungary | 480 1000 t | 2023 | up 51.9% | rising |
| 7 | Germany | 332 1000 t | 2023 | up 101.2% | rising |
| 8 | Spain | 326 1000 t | 2023 | up 74.3% | rising |
| 9 | United Kingdom of Great Britain and Northern Ireland | 228 1000 t | 2023 | up 130.3% | volatile |
| 10 | Paraguay | 187 1000 t | 2023 | up 1,600.0% | volatile |
| 11 | Poland | 169 1000 t | 2023 | up 322.5% | volatile |
| 12 | Sweden | 164 1000 t | 2023 | up 45.1% | rising |
| 13 | Canada | 161 1000 t | 2023 | up 177.6% | rising |
| 14 | Slovakia | 148 1000 t | 2023 | up 131.2% | rising |
| 15 | Guatemala | 144 1000 t | 2023 | down 23.4% | rising |
| 16 | Austria | 141 1000 t | 2022 | up 56.7% | rising |
| 17 | India | 132 1000 t | 2023 | down 46.8% | falling |
| 18 | Peru | 114 1000 t | 2023 | down 4.2% | rising |
| 19 | Bulgaria | 82 1000 t | 2023 | up 192.9% | rising |
| 20 | Ukraine | 79 1000 t | 2023 | up 3,850.0% | volatile |
| 21 | Lithuania | 65 1000 t | 2023 | up 261.1% | volatile |
| 22 | Eswatini | 64 1000 t | 2023 | up 300.0% | rising |
| 23 | Australia | 63 1000 t | 2023 | up 96.9% | volatile |
| 23 | Australia and New Zealand | 63 1000 t | 2023 | up 96.9% | volatile |
| 25 | Italy | 60 1000 t | 2023 | up 39.5% | rising |
| 26 | Russian Federation | 53 1000 t | 2023 | down 27.4% | rising |
| 27 | Bolivia (Plurinational State of) | 50 1000 t | 2023 | down 60.9% | rising |
| 28 | Indonesia | 47 1000 t | 2023 | down 30.9% | rising |
| 29 | Republic of Korea | 36 1000 t | 2023 | — | volatile |
| 30 | Czechia | 28 1000 t | 2023 | down 15.2% | flat |
| 31 | China | 27 1000 t | 2023 | down 41.3% | volatile |
| 31 | Uganda | 27 1000 t | 2023 | up 2,600.0% | volatile |
| 31 | China, mainland | 27 1000 t | 2023 | down 41.3% | volatile |
| 34 | Republic of Moldova | 25 1000 t | 2023 | — | volatile |
| 35 | United Arab Emirates | 23 1000 t | 2023 | up 2,200.0% | volatile |
| 36 | Costa Rica | 18 1000 t | 2023 | down 75.3% | volatile |
| 37 | Argentina | 14 1000 t | 2023 | up 100.0% | rising |
| 38 | Kazakhstan | 13 1000 t | 2023 | — | volatile |
| 39 | Nicaragua | 11 1000 t | 2023 | up 57.1% | rising |
| 39 | Türkiye | 11 1000 t | 2023 | up 120.0% | volatile |
| 41 | Egypt | 10 1000 t | 2023 | down 44.4% | volatile |
| 42 | Belarus | 9 1000 t | 2023 | down 18.2% | rising |
| 43 | Mauritius | 8 1000 t | 2023 | up 60.0% | volatile |
| 43 | Viet Nam | 8 1000 t | 2023 | down 75.0% | volatile |
| 45 | Colombia | 7 1000 t | 2023 | — | volatile |
| 45 | Cuba | 7 1000 t | 2019 | down 30.0% | flat |
| 47 | Bhutan | 5 1000 t | 2023 | — | rising |
| 47 | Thailand | 5 1000 t | 2023 | down 95.5% | volatile |
| 47 | Iran (Islamic Republic of) | 5 1000 t | 2023 | down 44.4% | volatile |
| 50 | Switzerland | 4 1000 t | 2023 | up 300.0% | volatile |
| 50 | Ecuador | 4 1000 t | 2023 | down 81.0% | falling |
| 50 | Latvia | 4 1000 t | 2023 | down 33.3% | falling |
| 50 | Nigeria | 4 1000 t | 2023 | — | volatile |
| 50 | Portugal | 4 1000 t | 2023 | up 300.0% | volatile |
| 50 | Caribbean | 4 1000 t | 2023 | down 97.0% | volatile |
| 56 | Chile | 3 1000 t | 2023 | — | volatile |
| 56 | Dominican Republic | 3 1000 t | 2023 | down 40.0% | falling |
| 56 | Cambodia | 3 1000 t | 2020 | down 78.6% | volatile |
| 56 | Romania | 3 1000 t | 2023 | down 88.5% | volatile |
| 60 | Kenya | 2 1000 t | 2023 | down 88.2% | volatile |
| 60 | Morocco | 2 1000 t | 2022 | up 100.0% | volatile |
| 60 | Philippines | 2 1000 t | 2023 | down 33.3% | volatile |
| 60 | Zambia | 2 1000 t | 2023 | — | volatile |
| 64 | Barbados | 1 1000 t | 2023 | — | volatile |
| 64 | Denmark | 1 1000 t | 2023 | down 83.3% | volatile |
| 64 | Ghana | 1 1000 t | 2023 | — | volatile |
| 64 | Ireland | 1 1000 t | 2023 | down 75.0% | volatile |
| 64 | Myanmar | 1 1000 t | 2023 | — | volatile |
| 64 | Malawi | 1 1000 t | 2023 | unchanged | volatile |
| 64 | Rwanda | 1 1000 t | 2022 | — | volatile |
| 64 | Sierra Leone | 1 1000 t | 2023 | down 80.0% | falling |
| 64 | Venezuela (Bolivarian Republic of) | 1 1000 t | 2019 | unchanged | volatile |
| 64 | United Republic of Tanzania | 1 1000 t | 2023 | down 66.7% | volatile |
| 74 | Afghanistan | 0 1000 t | 2019 | — | flat |
| 74 | Angola | 0 1000 t | 2023 | — | flat |
| 74 | Armenia | 0 1000 t | 2023 | down 100.0% | volatile |
| 74 | Antigua and Barbuda | 0 1000 t | 2023 | — | flat |
| 74 | Azerbaijan | 0 1000 t | 2023 | — | volatile |
| 74 | Burkina Faso | 0 1000 t | 2022 | — | volatile |
| 74 | Bangladesh | 0 1000 t | 2014 | — | flat |
| 74 | Bahrain | 0 1000 t | 2023 | — | flat |
| 74 | Bosnia and Herzegovina | 0 1000 t | 2023 | — | flat |
| 74 | Botswana | 0 1000 t | 2023 | — | flat |
| 74 | Cameroon | 0 1000 t | 2023 | — | flat |
| 74 | Cyprus | 0 1000 t | 2021 | — | flat |
| 74 | Djibouti | 0 1000 t | 2023 | — | flat |
| 74 | Algeria | 0 1000 t | 2020 | — | flat |
| 74 | Estonia | 0 1000 t | 2023 | — | volatile |
| 74 | Ethiopia | 0 1000 t | 2022 | — | flat |
| 74 | Finland | 0 1000 t | 2023 | — | flat |
| 74 | Fiji | 0 1000 t | 2020 | — | flat |
| 74 | Georgia | 0 1000 t | 2023 | — | volatile |
| 74 | Gambia | 0 1000 t | 2023 | — | flat |
| 74 | Greece | 0 1000 t | 2023 | — | volatile |
| 74 | Grenada | 0 1000 t | 2023 | — | flat |
| 74 | Guyana | 0 1000 t | 2023 | — | flat |
| 74 | Honduras | 0 1000 t | 2023 | — | flat |
| 74 | Croatia | 0 1000 t | 2023 | down 100.0% | volatile |
| 74 | Haiti | 0 1000 t | 2023 | — | flat |
| 74 | Israel | 0 1000 t | 2023 | — | flat |
| 74 | Jamaica | 0 1000 t | 2021 | down 100.0% | volatile |
| 74 | Jordan | 0 1000 t | 2023 | — | flat |
| 74 | Kyrgyzstan | 0 1000 t | 2022 | — | volatile |
| 74 | Kuwait | 0 1000 t | 2023 | — | flat |
| 74 | Lebanon | 0 1000 t | 2023 | — | volatile |
| 74 | Saint Lucia | 0 1000 t | 2020 | — | volatile |
| 74 | Sri Lanka | 0 1000 t | 2023 | — | flat |
| 74 | Luxembourg | 0 1000 t | 2023 | — | flat |
| 74 | Madagascar | 0 1000 t | 2023 | down 100.0% | volatile |
| 74 | Mexico | 0 1000 t | 2023 | down 100.0% | volatile |
| 74 | North Macedonia | 0 1000 t | 2023 | — | flat |
| 74 | Malta | 0 1000 t | 2022 | — | flat |
| 74 | Montenegro | 0 1000 t | 2020 | — | flat |
| 74 | Malaysia | 0 1000 t | 2023 | — | volatile |
| 74 | Namibia | 0 1000 t | 2023 | — | flat |
| 74 | New Caledonia | 0 1000 t | 2022 | — | flat |
| 74 | Norway | 0 1000 t | 2023 | — | volatile |
| 74 | New Zealand | 0 1000 t | 2023 | — | flat |
| 74 | Oman | 0 1000 t | 2022 | — | volatile |
| 74 | Panama | 0 1000 t | 2023 | down 100.0% | volatile |
| 74 | Papua New Guinea | 0 1000 t | 2021 | — | volatile |
| 74 | French Polynesia | 0 1000 t | 2023 | — | flat |
| 74 | Saudi Arabia | 0 1000 t | 2023 | — | volatile |
| 74 | Senegal | 0 1000 t | 2023 | down 100.0% | volatile |
| 74 | El Salvador | 0 1000 t | 2023 | down 100.0% | volatile |
| 74 | Serbia | 0 1000 t | 2023 | — | volatile |
| 74 | Suriname | 0 1000 t | 2022 | — | flat |
| 74 | Slovenia | 0 1000 t | 2023 | — | volatile |
| 74 | Trinidad and Tobago | 0 1000 t | 2023 | down 100.0% | volatile |
| 74 | Tunisia | 0 1000 t | 2020 | — | flat |
| 74 | Uruguay | 0 1000 t | 2023 | — | volatile |
| 74 | Saint Vincent and the Grenadines | 0 1000 t | 2023 | — | flat |
| 74 | Samoa | 0 1000 t | 2019 | — | flat |
| 74 | Zimbabwe | 0 1000 t | 2023 | down 100.0% | volatile |
| 74 | Melanesia | 0 1000 t | 2022 | down 100.0% | volatile |
| 74 | Polynesia | 0 1000 t | 2023 | — | flat |
| 74 | China, Hong Kong SAR | 0 1000 t | 2023 | — | flat |
| 74 | Syrian Arab Republic | 0 1000 t | 2023 | — | flat |
| 74 | Côte d'Ivoire | 0 1000 t | 2023 | down 100.0% | volatile |
| 74 | Lao People's Democratic Republic | 0 1000 t | 2019 | — | volatile |
| 74 | China, Taiwan Province of | 0 1000 t | 2023 | — | flat |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- World 14,631 1000 t
- Americas 8,355 1000 t
- Northern America 5,784 1000 t
- United States of America 5,623 1000 t
- Europe 4,849 1000 t
- European Union (27) 4,451 1000 t
- Western Europe 2,920 1000 t
- South America 2,392 1000 t
- Eastern Europe 1,076 1000 t
- Asia 976 1000 t
- Net Food Importing Developing Countries (NFIDCs) 905 1000 t
- Southern Asia 803 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.