Beverages, Alcoholic — 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
Beverages, Alcoholic — Stock Variation is currently reported for 155 countries. The highest value is 277 1000 t in India; the lowest is -121 1000 t in South Africa.
The median across all reporting countries is 0 1000 t, and the mean is 2.49 1000 t.
The gap between the highest and lowest reporting country is a factor of about 2.
Over the past decade 30 countries rose and 49 fell. The largest increase was in Netherlands (Kingdom of the) (up 766.7%), and the largest decrease in Uganda (down 800.0%).
Beverages, Alcoholic — Stock Variation: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | India | 277 1000 t | 2023 | up 56.5% | volatile |
| 2 | Democratic People's Republic of Korea | 86 1000 t | 2018 | up 345.7% | volatile |
| 3 | China | 66 1000 t | 2023 | down 96.6% | volatile |
| 3 | China, mainland | 66 1000 t | 2023 | down 96.5% | volatile |
| 5 | Netherlands (Kingdom of the) | 60 1000 t | 2023 | up 766.7% | volatile |
| 6 | Belarus | 25 1000 t | 2023 | — | volatile |
| 7 | Bosnia and Herzegovina | 20 1000 t | 2023 | up 233.3% | volatile |
| 8 | France | 11 1000 t | 2023 | — | volatile |
| 9 | Luxembourg | 10 1000 t | 2023 | — | volatile |
| 10 | Romania | 9 1000 t | 2023 | down 25.0% | volatile |
| 10 | Caribbean | 9 1000 t | 2023 | down 18.2% | volatile |
| 12 | Nigeria | 8 1000 t | 2023 | — | volatile |
| 13 | Dominican Republic | 7 1000 t | 2023 | unchanged | volatile |
| 14 | United Kingdom | 5 1000 t | 2023 | — | volatile |
| 14 | Eswatini | 5 1000 t | 2023 | — | volatile |
| 14 | Vietnam | 5 1000 t | 2023 | down 80.8% | volatile |
| 14 | Viet Nam | 5 1000 t | 2023 | down 80.8% | volatile |
| 14 | United Kingdom of Great Britain and Northern Ireland | 5 1000 t | 2023 | — | volatile |
| 19 | Guatemala | 4 1000 t | 2023 | down 50.0% | volatile |
| 19 | Latvia | 4 1000 t | 2023 | — | volatile |
| 21 | Lithuania | 3 1000 t | 2023 | — | volatile |
| 21 | New Zealand | 3 1000 t | 2023 | down 57.1% | volatile |
| 21 | Australia and New Zealand | 3 1000 t | 2023 | down 92.3% | volatile |
| 24 | Estonia | 2 1000 t | 2023 | up 133.3% | volatile |
| 24 | Hungary | 2 1000 t | 2023 | — | volatile |
| 24 | Liberia | 2 1000 t | 2023 | up 100.0% | volatile |
| 24 | Morocco | 2 1000 t | 2023 | unchanged | volatile |
| 24 | Serbia | 2 1000 t | 2023 | — | volatile |
| 24 | Trinidad and Tobago | 2 1000 t | 2023 | up 100.0% | volatile |
| 24 | Ukraine | 2 1000 t | 2023 | — | volatile |
| 31 | Belgium | 1 1000 t | 2023 | — | volatile |
| 31 | Bulgaria | 1 1000 t | 2023 | down 88.9% | volatile |
| 31 | Brazil | 1 1000 t | 2023 | down 99.3% | volatile |
| 31 | Ireland | 1 1000 t | 2023 | — | volatile |
| 31 | North Macedonia | 1 1000 t | 2023 | — | volatile |
| 31 | Nicaragua | 1 1000 t | 2023 | up 200.0% | volatile |
| 31 | Paraguay | 1 1000 t | 2023 | — | volatile |
| 31 | Syria | 1 1000 t | 2023 | — | volatile |
| 31 | Tunisia | 1 1000 t | 2023 | — | volatile |
| 31 | Syrian Arab Republic | 1 1000 t | 2023 | — | volatile |
| 41 | Angola | 0 1000 t | 2023 | — | volatile |
| 41 | Albania | 0 1000 t | 2023 | — | volatile |
| 41 | United Arab Emirates | 0 1000 t | 2023 | — | volatile |
| 41 | Argentina | 0 1000 t | 2023 | up 100.0% | flat |
| 41 | Antigua and Barbuda | 0 1000 t | 2023 | — | volatile |
| 41 | Australia | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Burkina Faso | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Bangladesh | 0 1000 t | 2023 | — | volatile |
| 41 | Bahrain | 0 1000 t | 2023 | — | volatile |
| 41 | Belize | 0 1000 t | 2023 | — | volatile |
| 41 | Barbados | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Canada | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Switzerland | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Chile | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Cote d'Ivoire | 0 1000 t | 2023 | — | volatile |
| 41 | Cameroon | 0 1000 t | 2023 | — | volatile |
| 41 | Congo | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Colombia | 0 1000 t | 2023 | — | volatile |
| 41 | Costa Rica | 0 1000 t | 2023 | — | volatile |
| 41 | Cyprus | 0 1000 t | 2023 | — | volatile |
| 41 | Djibouti | 0 1000 t | 2023 | — | volatile |
| 41 | Denmark | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Algeria | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Egypt | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Spain | 0 1000 t | 2023 | — | volatile |
| 41 | Ethiopia | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Finland | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Fiji | 0 1000 t | 2023 | — | volatile |
| 41 | Gabon | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Ghana | 0 1000 t | 2023 | — | volatile |
| 41 | Guinea | 0 1000 t | 2023 | — | volatile |
| 41 | Greece | 0 1000 t | 2023 | — | volatile |
| 41 | Guyana | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Honduras | 0 1000 t | 2023 | — | volatile |
| 41 | Croatia | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Haiti | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Indonesia | 0 1000 t | 2023 | down 100.0% | flat |
| 41 | Iraq | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Iceland | 0 1000 t | 2023 | — | volatile |
| 41 | Israel | 0 1000 t | 2023 | — | flat |
| 41 | Italy | 0 1000 t | 2023 | — | volatile |
| 41 | Jamaica | 0 1000 t | 2023 | up 100.0% | flat |
| 41 | Jordan | 0 1000 t | 2023 | — | volatile |
| 41 | Kazakhstan | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Kenya | 0 1000 t | 2023 | down 100.0% | flat |
| 41 | Kyrgyzstan | 0 1000 t | 2023 | — | volatile |
| 41 | Cambodia | 0 1000 t | 2023 | — | volatile |
| 41 | Laos | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Lebanon | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Saint Lucia | 0 1000 t | 2023 | — | volatile |
| 41 | Sri Lanka | 0 1000 t | 2023 | — | volatile |
| 41 | Lesotho | 0 1000 t | 2023 | — | volatile |
| 41 | Madagascar | 0 1000 t | 2023 | — | volatile |
| 41 | Maldives | 0 1000 t | 2023 | — | volatile |
| 41 | Mexico | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Malta | 0 1000 t | 2023 | — | volatile |
| 41 | Myanmar | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Mozambique | 0 1000 t | 2023 | — | volatile |
| 41 | Mauritius | 0 1000 t | 2023 | — | flat |
| 41 | Malawi | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Malaysia | 0 1000 t | 2023 | — | volatile |
| 41 | Namibia | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Norway | 0 1000 t | 2023 | — | volatile |
| 41 | Nepal | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Oman | 0 1000 t | 2023 | — | volatile |
| 41 | Panama | 0 1000 t | 2023 | — | volatile |
| 41 | Philippines | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Papua New Guinea | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Poland | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Portugal | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Russia | 0 1000 t | 2023 | — | volatile |
| 41 | Rwanda | 0 1000 t | 2023 | down 100.0% | flat |
| 41 | Sierra Leone | 0 1000 t | 2023 | — | volatile |
| 41 | El Salvador | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Slovakia | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Slovenia | 0 1000 t | 2023 | — | volatile |
| 41 | Sweden | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Seychelles | 0 1000 t | 2023 | — | volatile |
| 41 | Thailand | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Tajikistan | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Turkey | 0 1000 t | 2023 | down 100.0% | flat |
| 41 | Uruguay | 0 1000 t | 2023 | — | volatile |
| 41 | United States | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Uzbekistan | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Saint Vincent and the Grenadines | 0 1000 t | 2023 | — | volatile |
| 41 | Zambia | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Zimbabwe | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Melanesia | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Democratic Republic of the Congo | 0 1000 t | 2023 | — | volatile |
| 41 | Bolivia (Plurinational State of) | 0 1000 t | 2023 | — | volatile |
| 41 | China, Hong Kong SAR | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | Republic of Korea | 0 1000 t | 2023 | up 100.0% | volatile |
| 41 | Russian Federation | 0 1000 t | 2023 | — | volatile |
| 41 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | — | volatile |
| 41 | Türkiye | 0 1000 t | 2023 | down 100.0% | flat |
| 41 | Côte d'Ivoire | 0 1000 t | 2023 | — | volatile |
| 41 | Lao People's Democratic Republic | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | United Republic of Tanzania | 0 1000 t | 2023 | down 100.0% | flat |
| 41 | China, Taiwan Province of | 0 1000 t | 2023 | down 100.0% | volatile |
| 41 | China, Macao SAR | 0 1000 t | 2023 | — | flat |
| 180 | Bahamas | -1 1000 t | 2023 | — | volatile |
| 180 | Montenegro | -1 1000 t | 2023 | — | flat |
| 182 | Ecuador | -2 1000 t | 2023 | down 300.0% | volatile |
| 183 | Suriname | -3 1000 t | 2023 | down 200.0% | volatile |
| 184 | Armenia | -4 1000 t | 2023 | up 20.0% | volatile |
| 185 | Mongolia | -5 1000 t | 2023 | — | volatile |
| 186 | Azerbaijan | -10 1000 t | 2023 | down 350.0% | volatile |
| 186 | Czechia | -10 1000 t | 2023 | down 110.1% | volatile |
| 188 | Moldova | -14 1000 t | 2023 | — | volatile |
| 188 | Uganda | -14 1000 t | 2023 | down 800.0% | volatile |
| 188 | Republic of Moldova | -14 1000 t | 2023 | — | volatile |
| 191 | Georgia | -16 1000 t | 2023 | down 260.0% | volatile |
| 192 | Austria | -19 1000 t | 2023 | — | flat |
| 193 | Germany | -100 1000 t | 2023 | up 27.5% | volatile |
| 194 | South Africa | -121 1000 t | 2023 | down 626.1% | flat |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- Asia 314 1000 t
- Southern Asia 277 1000 t
- World 231 1000 t
- Eastern Asia 61 1000 t
- Southern Europe 21 1000 t
- Europe 16 1000 t
- Eastern Europe 16 1000 t
- Northern Europe 16 1000 t
- Americas 12 1000 t
- Western Africa 11 1000 t
- Small island developing States (SIDS) 6 1000 t
- Central America 6 1000 t
- South-Eastern Asia 5 1000 t
- Oceania 3 1000 t
- Northern Africa 3 1000 t
- Net Food Importing Developing Countries (NFIDCs) 3 1000 t
- Northern America 0 1000 t
- Central Asia 0 1000 t
- Middle Africa 0 1000 t
- United States of America 0 1000 t
- South America -3 1000 t
- Low Income Food Deficit Countries (LIFDCs) -10 1000 t
- Least Developed Countries (LDCs) -12 1000 t
- Eastern Africa -14 1000 t
- European Union (27) -24 1000 t
- Western Asia -29 1000 t
- Western Europe -37 1000 t
- Land Locked Developing Countries (LLDCs) -39 1000 t
- Africa -115 1000 t
- Southern Africa -115 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.