Bovine Meat — 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
Bovine Meat — Stock Variation is currently reported for 182 countries. The highest value is 38 1000 t in Canada; the lowest is -73 1000 t in Argentina.
The median across all reporting countries is 0 1000 t, and the mean is 0.1923 1000 t.
Over the past decade 28 countries rose and 34 fell. The largest increase was in Azerbaijan (up 1,800.0%), and the largest decrease in Argentina (down 1,725.0%).
Bovine Meat — Stock Variation: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Canada | 38 1000 t | 2023 | up 1,366.7% | volatile |
| 2 | China | 37 1000 t | 2023 | down 7.5% | volatile |
| 3 | China, mainland | 32 1000 t | 2023 | down 25.6% | volatile |
| 4 | Belgium | 22 1000 t | 2023 | — | volatile |
| 5 | Austria | 18 1000 t | 2023 | — | volatile |
| 5 | United Republic of Tanzania | 18 1000 t | 2023 | up 260.0% | volatile |
| 7 | Azerbaijan | 17 1000 t | 2023 | up 1,800.0% | volatile |
| 8 | Kyrgyzstan | 14 1000 t | 2023 | up 800.0% | volatile |
| 9 | Portugal | 12 1000 t | 2023 | up 400.0% | volatile |
| 10 | Denmark | 10 1000 t | 2023 | — | volatile |
| 11 | Czechia | 9 1000 t | 2023 | — | volatile |
| 11 | Greece | 9 1000 t | 2023 | — | volatile |
| 13 | Croatia | 6 1000 t | 2023 | — | volatile |
| 13 | Italy | 6 1000 t | 2023 | — | volatile |
| 13 | Namibia | 6 1000 t | 2023 | — | volatile |
| 13 | Viet Nam | 6 1000 t | 2023 | — | volatile |
| 17 | Guatemala | 5 1000 t | 2023 | up 118.5% | volatile |
| 17 | Netherlands (Kingdom of the) | 5 1000 t | 2023 | — | volatile |
| 19 | Brazil | 4 1000 t | 2023 | up 300.0% | volatile |
| 19 | Cambodia | 4 1000 t | 2023 | down 63.6% | volatile |
| 19 | Ukraine | 4 1000 t | 2023 | — | volatile |
| 19 | China, Hong Kong SAR | 4 1000 t | 2023 | up 233.3% | volatile |
| 23 | Lithuania | 3 1000 t | 2023 | — | volatile |
| 24 | Colombia | 2 1000 t | 2023 | up 100.0% | volatile |
| 24 | Rwanda | 2 1000 t | 2023 | up 100.0% | volatile |
| 24 | Slovenia | 2 1000 t | 2023 | unchanged | falling |
| 27 | Hungary | 1 1000 t | 2023 | up 114.3% | volatile |
| 27 | Iraq | 1 1000 t | 2023 | down 66.7% | volatile |
| 27 | Niger | 1 1000 t | 2023 | up 105.3% | volatile |
| 27 | Pakistan | 1 1000 t | 2023 | down 50.0% | volatile |
| 27 | Philippines | 1 1000 t | 2023 | down 83.3% | volatile |
| 27 | Thailand | 1 1000 t | 2023 | up 133.3% | volatile |
| 27 | China, Taiwan Province of | 1 1000 t | 2023 | — | volatile |
| 27 | China, Macao SAR | 1 1000 t | 2023 | — | volatile |
| 35 | Afghanistan | 0 1000 t | 2023 | down 100.0% | flat |
| 35 | Angola | 0 1000 t | 2023 | down 100.0% | volatile |
| 35 | Albania | 0 1000 t | 2023 | — | flat |
| 35 | United Arab Emirates | 0 1000 t | 2023 | up 100.0% | volatile |
| 35 | Armenia | 0 1000 t | 2023 | — | volatile |
| 35 | Antigua and Barbuda | 0 1000 t | 2023 | — | flat |
| 35 | Australia | 0 1000 t | 2023 | — | flat |
| 35 | Burkina Faso | 0 1000 t | 2023 | down 100.0% | flat |
| 35 | Bangladesh | 0 1000 t | 2023 | down 100.0% | volatile |
| 35 | Bulgaria | 0 1000 t | 2023 | — | volatile |
| 35 | Bahrain | 0 1000 t | 2023 | — | flat |
| 35 | Bahamas | 0 1000 t | 2023 | — | flat |
| 35 | Bosnia and Herzegovina | 0 1000 t | 2023 | — | flat |
| 35 | Belarus | 0 1000 t | 2023 | down 100.0% | volatile |
| 35 | Belize | 0 1000 t | 2023 | — | flat |
| 35 | Barbados | 0 1000 t | 2023 | — | flat |
| 35 | Bhutan | 0 1000 t | 2023 | — | volatile |
| 35 | Botswana | 0 1000 t | 2023 | — | volatile |
| 35 | Switzerland | 0 1000 t | 2023 | down 100.0% | volatile |
| 35 | Chile | 0 1000 t | 2023 | up 100.0% | volatile |
| 35 | Cameroon | 0 1000 t | 2023 | — | volatile |
| 35 | Congo | 0 1000 t | 2023 | down 100.0% | volatile |
| 35 | Comoros | 0 1000 t | 2023 | — | volatile |
| 35 | Costa Rica | 0 1000 t | 2023 | — | volatile |
| 35 | Cuba | 0 1000 t | 2019 | — | flat |
| 35 | Cyprus | 0 1000 t | 2023 | up 100.0% | volatile |
| 35 | Djibouti | 0 1000 t | 2023 | — | flat |
| 35 | Dominican Republic | 0 1000 t | 2023 | — | volatile |
| 35 | Algeria | 0 1000 t | 2023 | down 100.0% | volatile |
| 35 | Ecuador | 0 1000 t | 2023 | — | flat |
| 35 | Spain | 0 1000 t | 2023 | — | volatile |
| 35 | Estonia | 0 1000 t | 2023 | — | volatile |
| 35 | Ethiopia | 0 1000 t | 2023 | down 100.0% | volatile |
| 35 | Fiji | 0 1000 t | 2023 | — | flat |
| 35 | France | 0 1000 t | 2023 | — | flat |
| 35 | Gabon | 0 1000 t | 2023 | — | flat |
| 35 | Georgia | 0 1000 t | 2023 | down 100.0% | volatile |
| 35 | Ghana | 0 1000 t | 2023 | — | volatile |
| 35 | Guinea | 0 1000 t | 2023 | — | volatile |
| 35 | Gambia | 0 1000 t | 2023 | up 100.0% | flat |
| 35 | Guinea-Bissau | 0 1000 t | 2023 | — | flat |
| 35 | Grenada | 0 1000 t | 2023 | — | flat |
| 35 | Guyana | 0 1000 t | 2023 | — | flat |
| 35 | Honduras | 0 1000 t | 2023 | — | volatile |
| 35 | Haiti | 0 1000 t | 2023 | — | flat |
| 35 | India | 0 1000 t | 2023 | up 100.0% | volatile |
| 35 | Iceland | 0 1000 t | 2023 | — | flat |
| 35 | Israel | 0 1000 t | 2023 | down 100.0% | volatile |
| 35 | Jamaica | 0 1000 t | 2023 | — | volatile |
| 35 | Jordan | 0 1000 t | 2023 | up 100.0% | volatile |
| 35 | Kazakhstan | 0 1000 t | 2023 | — | volatile |
| 35 | Kenya | 0 1000 t | 2023 | — | volatile |
| 35 | Kiribati | 0 1000 t | 2023 | — | flat |
| 35 | Saint Kitts and Nevis | 0 1000 t | 2023 | — | flat |
| 35 | Kuwait | 0 1000 t | 2023 | down 100.0% | volatile |
| 35 | Lebanon | 0 1000 t | 2023 | — | volatile |
| 35 | Liberia | 0 1000 t | 2023 | — | flat |
| 35 | Libya | 0 1000 t | 2023 | — | flat |
| 35 | Saint Lucia | 0 1000 t | 2023 | — | flat |
| 35 | Sri Lanka | 0 1000 t | 2023 | down 100.0% | volatile |
| 35 | Lesotho | 0 1000 t | 2023 | — | volatile |
| 35 | Luxembourg | 0 1000 t | 2023 | — | volatile |
| 35 | Morocco | 0 1000 t | 2023 | down 100.0% | volatile |
| 35 | Madagascar | 0 1000 t | 2023 | up 100.0% | volatile |
| 35 | Maldives | 0 1000 t | 2023 | — | flat |
| 35 | Mexico | 0 1000 t | 2023 | — | volatile |
| 35 | Marshall Islands | 0 1000 t | 2023 | — | flat |
| 35 | North Macedonia | 0 1000 t | 2023 | — | flat |
| 35 | Malta | 0 1000 t | 2023 | — | flat |
| 35 | Myanmar | 0 1000 t | 2023 | — | volatile |
| 35 | Montenegro | 0 1000 t | 2023 | — | volatile |
| 35 | Mozambique | 0 1000 t | 2023 | — | flat |
| 35 | Mauritania | 0 1000 t | 2023 | down 100.0% | volatile |
| 35 | Mauritius | 0 1000 t | 2023 | — | volatile |
| 35 | Malawi | 0 1000 t | 2023 | down 100.0% | volatile |
| 35 | Malaysia | 0 1000 t | 2023 | — | flat |
| 35 | New Caledonia | 0 1000 t | 2023 | down 100.0% | volatile |
| 35 | Nigeria | 0 1000 t | 2023 | — | volatile |
| 35 | Nicaragua | 0 1000 t | 2023 | — | volatile |
| 35 | Norway | 0 1000 t | 2023 | — | volatile |
| 35 | Nepal | 0 1000 t | 2023 | — | volatile |
| 35 | Nauru | 0 1000 t | 2023 | — | flat |
| 35 | New Zealand | 0 1000 t | 2023 | — | volatile |
| 35 | Oman | 0 1000 t | 2023 | — | volatile |
| 35 | Panama | 0 1000 t | 2023 | — | volatile |
| 35 | Peru | 0 1000 t | 2023 | — | flat |
| 35 | Papua New Guinea | 0 1000 t | 2023 | down 100.0% | volatile |
| 35 | Paraguay | 0 1000 t | 2023 | — | flat |
| 35 | French Polynesia | 0 1000 t | 2023 | — | flat |
| 35 | Qatar | 0 1000 t | 2023 | — | flat |
| 35 | Romania | 0 1000 t | 2023 | up 100.0% | volatile |
| 35 | Saudi Arabia | 0 1000 t | 2023 | up 100.0% | volatile |
| 35 | Senegal | 0 1000 t | 2023 | down 100.0% | volatile |
| 35 | Solomon Islands | 0 1000 t | 2023 | down 100.0% | flat |
| 35 | Sierra Leone | 0 1000 t | 2023 | up 100.0% | volatile |
| 35 | El Salvador | 0 1000 t | 2023 | — | flat |
| 35 | Serbia | 0 1000 t | 2023 | — | flat |
| 35 | Sao Tome and Principe | 0 1000 t | 2023 | — | flat |
| 35 | Suriname | 0 1000 t | 2023 | — | flat |
| 35 | Slovakia | 0 1000 t | 2023 | — | volatile |
| 35 | Sweden | 0 1000 t | 2023 | — | volatile |
| 35 | Eswatini | 0 1000 t | 2023 | down 100.0% | volatile |
| 35 | Seychelles | 0 1000 t | 2023 | — | flat |
| 35 | Tajikistan | 0 1000 t | 2023 | up 100.0% | volatile |
| 35 | Turkmenistan | 0 1000 t | 2023 | — | volatile |
| 35 | Tonga | 0 1000 t | 2023 | — | flat |
| 35 | Trinidad and Tobago | 0 1000 t | 2023 | — | flat |
| 35 | Tunisia | 0 1000 t | 2023 | — | volatile |
| 35 | Tuvalu | 0 1000 t | 2023 | — | flat |
| 35 | Uganda | 0 1000 t | 2023 | — | flat |
| 35 | Uruguay | 0 1000 t | 2023 | — | flat |
| 35 | Uzbekistan | 0 1000 t | 2023 | up 100.0% | volatile |
| 35 | Saint Vincent and the Grenadines | 0 1000 t | 2023 | — | flat |
| 35 | Vanuatu | 0 1000 t | 2023 | — | flat |
| 35 | Samoa | 0 1000 t | 2023 | — | flat |
| 35 | Yemen | 0 1000 t | 2023 | — | flat |
| 35 | Zambia | 0 1000 t | 2023 | down 100.0% | volatile |
| 35 | Zimbabwe | 0 1000 t | 2023 | up 100.0% | volatile |
| 35 | Micronesia | 0 1000 t | 2023 | — | flat |
| 35 | Timor-Leste | 0 1000 t | 2023 | — | flat |
| 35 | Cabo Verde | 0 1000 t | 2023 | — | flat |
| 35 | Melanesia | 0 1000 t | 2023 | down 100.0% | volatile |
| 35 | Polynesia | 0 1000 t | 2023 | — | flat |
| 35 | Democratic Republic of the Congo | 0 1000 t | 2023 | — | volatile |
| 35 | Caribbean | 0 1000 t | 2023 | — | volatile |
| 35 | Bolivia (Plurinational State of) | 0 1000 t | 2023 | — | volatile |
| 35 | Iran (Islamic Republic of) | 0 1000 t | 2023 | — | volatile |
| 35 | Republic of Korea | 0 1000 t | 2023 | — | volatile |
| 35 | Republic of Moldova | 0 1000 t | 2023 | — | flat |
| 35 | Russian Federation | 0 1000 t | 2023 | — | volatile |
| 35 | Syrian Arab Republic | 0 1000 t | 2023 | — | volatile |
| 35 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | — | flat |
| 35 | Türkiye | 0 1000 t | 2023 | down 100.0% | volatile |
| 35 | Australia and New Zealand | 0 1000 t | 2023 | — | volatile |
| 35 | Côte d'Ivoire | 0 1000 t | 2023 | down 100.0% | volatile |
| 35 | Lao People's Democratic Republic | 0 1000 t | 2023 | — | flat |
| 35 | United Kingdom of Great Britain and Northern Ireland | 0 1000 t | 2023 | — | volatile |
| 35 | Democratic People's Republic of Korea | 0 1000 t | 2018 | — | volatile |
| 35 | Micronesia (Federated States of) | 0 1000 t | 2023 | — | flat |
| 174 | Indonesia | -1 1000 t | 2023 | up 85.7% | volatile |
| 175 | Finland | -3 1000 t | 2023 | — | volatile |
| 176 | Latvia | -5 1000 t | 2023 | — | volatile |
| 177 | Mongolia | -7 1000 t | 2023 | down 600.0% | volatile |
| 178 | Egypt | -11 1000 t | 2023 | down 650.0% | volatile |
| 179 | Poland | -41 1000 t | 2023 | up 8.9% | volatile |
| 180 | Germany | -61 1000 t | 2023 | — | volatile |
| 181 | Ireland | -66 1000 t | 2023 | — | volatile |
| 182 | Argentina | -73 1000 t | 2023 | down 1,725.0% | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- Asia 75 1000 t
- Low Income Food Deficit Countries (LIFDCs) 37 1000 t
- Southern Europe 35 1000 t
- Eastern Asia 30 1000 t
- Land Locked Developing Countries (LLDCs) 29 1000 t
- Least Developed Countries (LDCs) 27 1000 t
- Eastern Africa 20 1000 t
- Western Asia 19 1000 t
- Africa 18 1000 t
- Central Asia 15 1000 t
- Net Food Importing Developing Countries (NFIDCs) 15 1000 t
- South-eastern Asia 11 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.