Alcohol, Non-Food — 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
Alcohol, Non-Food — Stock Variation is currently reported for 163 countries. The highest value is 56 1000 t in Spain; the lowest is -15 1000 t in Paraguay.
The median across all reporting countries is 0 1000 t, and the mean is 0.7791 1000 t.
The gap between the highest and lowest reporting country is a factor of about 4.
Over the past decade 22 countries rose and 11 fell. The largest increase was in Egypt (up 600.0%), and the largest decrease in Australia (down 100.0%).
Alcohol, Non-Food — Stock Variation: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Spain | 56 1000 t | 2023 | up 380.0% | volatile |
| 2 | Kenya | 22 1000 t | 2023 | — | volatile |
| 2 | Thailand | 22 1000 t | 2023 | up 37.5% | rising |
| 4 | Egypt | 15 1000 t | 2023 | up 600.0% | volatile |
| 5 | Costa Rica | 13 1000 t | 2023 | up 144.8% | volatile |
| 6 | Hungary | 10 1000 t | 2023 | up 133.3% | volatile |
| 7 | Bolivia (Plurinational State of) | 6 1000 t | 2023 | — | volatile |
| 8 | Ecuador | 5 1000 t | 2023 | up 350.0% | volatile |
| 9 | Argentina | 1 1000 t | 2023 | down 98.0% | volatile |
| 9 | Barbados | 1 1000 t | 2023 | — | volatile |
| 9 | Malawi | 1 1000 t | 2023 | — | volatile |
| 13 | Albania | 0 1000 t | 2023 | — | flat |
| 13 | United Arab Emirates | 0 1000 t | 2023 | — | flat |
| 13 | Armenia | 0 1000 t | 2023 | up 100.0% | volatile |
| 13 | Antigua and Barbuda | 0 1000 t | 2023 | — | flat |
| 13 | Australia | 0 1000 t | 2023 | down 100.0% | volatile |
| 13 | Austria | 0 1000 t | 2023 | — | flat |
| 13 | Azerbaijan | 0 1000 t | 2023 | — | flat |
| 13 | Belgium | 0 1000 t | 2023 | — | volatile |
| 13 | Burkina Faso | 0 1000 t | 2023 | — | flat |
| 13 | Bangladesh | 0 1000 t | 2023 | — | flat |
| 13 | Bahrain | 0 1000 t | 2023 | — | volatile |
| 13 | Bahamas | 0 1000 t | 2023 | — | flat |
| 13 | Bosnia and Herzegovina | 0 1000 t | 2023 | — | flat |
| 13 | Belarus | 0 1000 t | 2023 | down 100.0% | volatile |
| 13 | Belize | 0 1000 t | 2023 | — | flat |
| 13 | Brazil | 0 1000 t | 2023 | up 100.0% | volatile |
| 13 | Botswana | 0 1000 t | 2023 | — | flat |
| 13 | Canada | 0 1000 t | 2023 | — | volatile |
| 13 | Switzerland | 0 1000 t | 2023 | — | flat |
| 13 | Chile | 0 1000 t | 2023 | — | flat |
| 13 | China | 0 1000 t | 2023 | — | volatile |
| 13 | Cameroon | 0 1000 t | 2023 | — | flat |
| 13 | Congo | 0 1000 t | 2023 | — | flat |
| 13 | Colombia | 0 1000 t | 2023 | — | flat |
| 13 | Comoros | 0 1000 t | 2023 | — | flat |
| 13 | Cuba | 0 1000 t | 2019 | down 100.0% | flat |
| 13 | Cyprus | 0 1000 t | 2023 | — | flat |
| 13 | Czechia | 0 1000 t | 2023 | — | volatile |
| 13 | Germany | 0 1000 t | 2023 | up 100.0% | volatile |
| 13 | Djibouti | 0 1000 t | 2023 | — | flat |
| 13 | Denmark | 0 1000 t | 2023 | — | flat |
| 13 | Algeria | 0 1000 t | 2023 | — | flat |
| 13 | Estonia | 0 1000 t | 2023 | — | volatile |
| 13 | Ethiopia | 0 1000 t | 2023 | — | volatile |
| 13 | Finland | 0 1000 t | 2023 | — | flat |
| 13 | Fiji | 0 1000 t | 2023 | — | flat |
| 13 | France | 0 1000 t | 2023 | — | flat |
| 13 | Gabon | 0 1000 t | 2023 | — | flat |
| 13 | Georgia | 0 1000 t | 2023 | — | flat |
| 13 | Ghana | 0 1000 t | 2023 | — | volatile |
| 13 | Guinea | 0 1000 t | 2023 | — | flat |
| 13 | Gambia | 0 1000 t | 2023 | — | flat |
| 13 | Greece | 0 1000 t | 2023 | — | flat |
| 13 | Grenada | 0 1000 t | 2023 | — | flat |
| 13 | Guatemala | 0 1000 t | 2023 | — | flat |
| 13 | Guyana | 0 1000 t | 2023 | — | flat |
| 13 | Honduras | 0 1000 t | 2023 | — | flat |
| 13 | Croatia | 0 1000 t | 2023 | up 100.0% | flat |
| 13 | Haiti | 0 1000 t | 2023 | — | flat |
| 13 | Indonesia | 0 1000 t | 2023 | up 100.0% | volatile |
| 13 | India | 0 1000 t | 2023 | — | flat |
| 13 | Ireland | 0 1000 t | 2023 | — | flat |
| 13 | Iceland | 0 1000 t | 2023 | — | flat |
| 13 | Israel | 0 1000 t | 2023 | — | flat |
| 13 | Italy | 0 1000 t | 2023 | — | volatile |
| 13 | Jamaica | 0 1000 t | 2023 | — | flat |
| 13 | Jordan | 0 1000 t | 2023 | — | flat |
| 13 | Kazakhstan | 0 1000 t | 2023 | down 100.0% | volatile |
| 13 | Kyrgyzstan | 0 1000 t | 2023 | down 100.0% | volatile |
| 13 | Cambodia | 0 1000 t | 2023 | — | flat |
| 13 | Kiribati | 0 1000 t | 2023 | — | flat |
| 13 | Saint Kitts and Nevis | 0 1000 t | 2023 | — | flat |
| 13 | Kuwait | 0 1000 t | 2023 | — | flat |
| 13 | Lebanon | 0 1000 t | 2023 | — | flat |
| 13 | Libya | 0 1000 t | 2023 | — | flat |
| 13 | Saint Lucia | 0 1000 t | 2023 | — | flat |
| 13 | Sri Lanka | 0 1000 t | 2023 | — | flat |
| 13 | Lithuania | 0 1000 t | 2023 | — | volatile |
| 13 | Luxembourg | 0 1000 t | 2023 | — | flat |
| 13 | Latvia | 0 1000 t | 2023 | — | flat |
| 13 | Morocco | 0 1000 t | 2023 | up 100.0% | volatile |
| 13 | Madagascar | 0 1000 t | 2023 | — | flat |
| 13 | Maldives | 0 1000 t | 2023 | — | flat |
| 13 | Mexico | 0 1000 t | 2023 | down 100.0% | volatile |
| 13 | North Macedonia | 0 1000 t | 2023 | — | flat |
| 13 | Malta | 0 1000 t | 2023 | — | flat |
| 13 | Myanmar | 0 1000 t | 2023 | — | flat |
| 13 | Montenegro | 0 1000 t | 2023 | — | flat |
| 13 | Mongolia | 0 1000 t | 2023 | — | flat |
| 13 | Mozambique | 0 1000 t | 2023 | — | flat |
| 13 | Mauritania | 0 1000 t | 2023 | — | flat |
| 13 | Mauritius | 0 1000 t | 2023 | up 100.0% | volatile |
| 13 | Malaysia | 0 1000 t | 2023 | — | flat |
| 13 | Namibia | 0 1000 t | 2023 | — | flat |
| 13 | New Caledonia | 0 1000 t | 2023 | — | flat |
| 13 | Niger | 0 1000 t | 2023 | — | flat |
| 13 | Nigeria | 0 1000 t | 2023 | — | volatile |
| 13 | Nicaragua | 0 1000 t | 2023 | up 100.0% | volatile |
| 13 | Norway | 0 1000 t | 2023 | — | flat |
| 13 | Nepal | 0 1000 t | 2023 | — | flat |
| 13 | New Zealand | 0 1000 t | 2023 | — | flat |
| 13 | Oman | 0 1000 t | 2023 | — | flat |
| 13 | Pakistan | 0 1000 t | 2023 | up 100.0% | volatile |
| 13 | Panama | 0 1000 t | 2023 | — | volatile |
| 13 | Peru | 0 1000 t | 2023 | up 100.0% | volatile |
| 13 | Philippines | 0 1000 t | 2023 | — | flat |
| 13 | Papua New Guinea | 0 1000 t | 2023 | — | flat |
| 13 | Poland | 0 1000 t | 2023 | down 100.0% | volatile |
| 13 | Portugal | 0 1000 t | 2023 | — | flat |
| 13 | French Polynesia | 0 1000 t | 2023 | — | flat |
| 13 | Qatar | 0 1000 t | 2023 | — | volatile |
| 13 | Romania | 0 1000 t | 2023 | — | volatile |
| 13 | Rwanda | 0 1000 t | 2023 | — | flat |
| 13 | Saudi Arabia | 0 1000 t | 2023 | — | flat |
| 13 | Senegal | 0 1000 t | 2023 | — | volatile |
| 13 | Solomon Islands | 0 1000 t | 2023 | — | flat |
| 13 | Sierra Leone | 0 1000 t | 2023 | — | volatile |
| 13 | El Salvador | 0 1000 t | 2023 | up 100.0% | volatile |
| 13 | Serbia | 0 1000 t | 2023 | — | flat |
| 13 | Sao Tome and Principe | 0 1000 t | 2023 | — | flat |
| 13 | Suriname | 0 1000 t | 2023 | — | flat |
| 13 | Slovenia | 0 1000 t | 2023 | — | flat |
| 13 | Sweden | 0 1000 t | 2023 | — | volatile |
| 13 | Eswatini | 0 1000 t | 2023 | — | volatile |
| 13 | Seychelles | 0 1000 t | 2023 | — | flat |
| 13 | Tajikistan | 0 1000 t | 2023 | — | flat |
| 13 | Trinidad and Tobago | 0 1000 t | 2023 | up 100.0% | volatile |
| 13 | Tunisia | 0 1000 t | 2023 | — | flat |
| 13 | Uganda | 0 1000 t | 2023 | down 100.0% | volatile |
| 13 | Ukraine | 0 1000 t | 2023 | up 100.0% | volatile |
| 13 | Uruguay | 0 1000 t | 2023 | — | flat |
| 13 | Saint Vincent and the Grenadines | 0 1000 t | 2023 | — | flat |
| 13 | Vanuatu | 0 1000 t | 2023 | — | flat |
| 13 | Samoa | 0 1000 t | 2023 | — | flat |
| 13 | Yemen | 0 1000 t | 2023 | — | flat |
| 13 | Zambia | 0 1000 t | 2023 | — | flat |
| 13 | Zimbabwe | 0 1000 t | 2023 | up 100.0% | volatile |
| 13 | Micronesia | 0 1000 t | 2023 | — | flat |
| 13 | Cabo Verde | 0 1000 t | 2023 | — | flat |
| 13 | Melanesia | 0 1000 t | 2023 | — | flat |
| 13 | Polynesia | 0 1000 t | 2023 | — | flat |
| 13 | Democratic Republic of the Congo | 0 1000 t | 2023 | — | flat |
| 13 | China, Hong Kong SAR | 0 1000 t | 2023 | — | flat |
| 13 | Iran (Islamic Republic of) | 0 1000 t | 2023 | — | flat |
| 13 | Republic of Korea | 0 1000 t | 2023 | — | flat |
| 13 | Republic of Moldova | 0 1000 t | 2023 | down 100.0% | volatile |
| 13 | Russian Federation | 0 1000 t | 2023 | — | volatile |
| 13 | Syrian Arab Republic | 0 1000 t | 2023 | — | flat |
| 13 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | up 100.0% | volatile |
| 13 | Australia and New Zealand | 0 1000 t | 2023 | down 100.0% | volatile |
| 13 | China, mainland | 0 1000 t | 2023 | — | volatile |
| 13 | Côte d'Ivoire | 0 1000 t | 2023 | — | flat |
| 13 | Lao People's Democratic Republic | 0 1000 t | 2023 | — | flat |
| 13 | United Republic of Tanzania | 0 1000 t | 2023 | — | flat |
| 13 | China, Taiwan Province of | 0 1000 t | 2023 | — | flat |
| 13 | Netherlands (Kingdom of the) | 0 1000 t | 2023 | — | volatile |
| 13 | United Kingdom of Great Britain and Northern Ireland | 0 1000 t | 2023 | — | flat |
| 13 | China, Macao SAR | 0 1000 t | 2023 | — | volatile |
| 161 | Bulgaria | -1 1000 t | 2023 | up 87.5% | volatile |
| 162 | Slovakia | -2 1000 t | 2023 | — | flat |
| 163 | Türkiye | -7 1000 t | 2023 | — | flat |
| 164 | Paraguay | -15 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 306 1000 t
- Americas 196 1000 t
- Northern America 185 1000 t
- United States of America 185 1000 t
- European Union (27) 64 1000 t
- Europe 63 1000 t
- Southern Europe 56 1000 t
- Net Food Importing Developing Countries (NFIDCs) 39 1000 t
- Africa 31 1000 t
- Caribbean 1 1000 t
- Eastern Africa 23 1000 t
- Low Income Food Deficit Countries (LIFDCs) 23 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.