Mutton & Goat 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
Mutton & Goat Meat — Stock Variation is currently reported for 182 countries. The highest value is 21 1000 t in China; the lowest is -9 1000 t in United Arab Emirates.
The median across all reporting countries is 0 1000 t, and the mean is 0.4231 1000 t.
The gap between the highest and lowest reporting country is a factor of about 2.
Over the past decade 28 countries rose and 29 fell. The largest increase was in Kyrgyzstan (up 1,100.0%), and the largest decrease in Russian Federation (down 158.3%).
Mutton & Goat Meat — Stock Variation: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | China | 21 1000 t | 2023 | up 362.5% | volatile |
| 2 | China, mainland | 20 1000 t | 2023 | up 300.0% | volatile |
| 3 | Mongolia | 17 1000 t | 2023 | up 466.7% | volatile |
| 4 | Kyrgyzstan | 10 1000 t | 2023 | up 1,100.0% | volatile |
| 5 | Kuwait | 4 1000 t | 2023 | up 300.0% | volatile |
| 6 | Pakistan | 3 1000 t | 2023 | down 50.0% | volatile |
| 6 | Australia and New Zealand | 3 1000 t | 2023 | — | volatile |
| 8 | Brazil | 2 1000 t | 2023 | unchanged | volatile |
| 8 | Germany | 2 1000 t | 2023 | up 125.0% | volatile |
| 8 | Indonesia | 2 1000 t | 2023 | up 140.0% | volatile |
| 8 | New Zealand | 2 1000 t | 2023 | — | volatile |
| 8 | Sweden | 2 1000 t | 2023 | up 100.0% | rising |
| 13 | Australia | 1 1000 t | 2023 | — | volatile |
| 13 | Greece | 1 1000 t | 2023 | up 103.4% | volatile |
| 13 | Croatia | 1 1000 t | 2023 | down 50.0% | falling |
| 13 | Rwanda | 1 1000 t | 2023 | unchanged | volatile |
| 13 | Côte d'Ivoire | 1 1000 t | 2023 | down 50.0% | volatile |
| 18 | Afghanistan | 0 1000 t | 2023 | up 100.0% | volatile |
| 18 | Angola | 0 1000 t | 2023 | — | flat |
| 18 | Albania | 0 1000 t | 2023 | — | flat |
| 18 | Argentina | 0 1000 t | 2023 | down 100.0% | volatile |
| 18 | Armenia | 0 1000 t | 2023 | — | flat |
| 18 | Antigua and Barbuda | 0 1000 t | 2023 | — | flat |
| 18 | Austria | 0 1000 t | 2023 | — | volatile |
| 18 | Azerbaijan | 0 1000 t | 2023 | up 100.0% | volatile |
| 18 | Belgium | 0 1000 t | 2023 | up 100.0% | volatile |
| 18 | Burkina Faso | 0 1000 t | 2023 | — | volatile |
| 18 | Bangladesh | 0 1000 t | 2023 | up 100.0% | volatile |
| 18 | Bulgaria | 0 1000 t | 2023 | — | flat |
| 18 | Bahrain | 0 1000 t | 2023 | — | flat |
| 18 | Bahamas | 0 1000 t | 2023 | — | flat |
| 18 | Bosnia and Herzegovina | 0 1000 t | 2023 | — | flat |
| 18 | Belarus | 0 1000 t | 2023 | — | flat |
| 18 | Belize | 0 1000 t | 2023 | — | flat |
| 18 | Barbados | 0 1000 t | 2023 | — | flat |
| 18 | Bhutan | 0 1000 t | 2023 | — | flat |
| 18 | Botswana | 0 1000 t | 2023 | — | flat |
| 18 | Canada | 0 1000 t | 2023 | up 100.0% | volatile |
| 18 | Switzerland | 0 1000 t | 2023 | — | flat |
| 18 | Chile | 0 1000 t | 2023 | — | volatile |
| 18 | Cameroon | 0 1000 t | 2023 | down 100.0% | volatile |
| 18 | Congo | 0 1000 t | 2023 | — | flat |
| 18 | Colombia | 0 1000 t | 2023 | — | volatile |
| 18 | Comoros | 0 1000 t | 2023 | — | flat |
| 18 | Costa Rica | 0 1000 t | 2023 | — | flat |
| 18 | Cuba | 0 1000 t | 2019 | — | flat |
| 18 | Cyprus | 0 1000 t | 2023 | — | volatile |
| 18 | Czechia | 0 1000 t | 2023 | down 100.0% | falling |
| 18 | Djibouti | 0 1000 t | 2023 | — | flat |
| 18 | Denmark | 0 1000 t | 2023 | — | flat |
| 18 | Dominican Republic | 0 1000 t | 2023 | — | flat |
| 18 | Algeria | 0 1000 t | 2023 | down 100.0% | volatile |
| 18 | Ecuador | 0 1000 t | 2023 | — | flat |
| 18 | Egypt | 0 1000 t | 2023 | down 100.0% | volatile |
| 18 | Spain | 0 1000 t | 2023 | up 100.0% | volatile |
| 18 | Estonia | 0 1000 t | 2023 | — | flat |
| 18 | Ethiopia | 0 1000 t | 2023 | down 100.0% | volatile |
| 18 | Finland | 0 1000 t | 2023 | — | volatile |
| 18 | Fiji | 0 1000 t | 2023 | — | flat |
| 18 | France | 0 1000 t | 2023 | — | flat |
| 18 | Gabon | 0 1000 t | 2023 | — | flat |
| 18 | Georgia | 0 1000 t | 2023 | — | flat |
| 18 | Ghana | 0 1000 t | 2023 | up 100.0% | volatile |
| 18 | Guinea | 0 1000 t | 2023 | — | volatile |
| 18 | Gambia | 0 1000 t | 2023 | — | flat |
| 18 | Guinea-Bissau | 0 1000 t | 2023 | — | flat |
| 18 | Grenada | 0 1000 t | 2023 | — | flat |
| 18 | Guatemala | 0 1000 t | 2023 | — | volatile |
| 18 | Guyana | 0 1000 t | 2023 | — | flat |
| 18 | Honduras | 0 1000 t | 2023 | — | flat |
| 18 | Haiti | 0 1000 t | 2023 | — | volatile |
| 18 | Hungary | 0 1000 t | 2023 | — | flat |
| 18 | India | 0 1000 t | 2023 | down 100.0% | volatile |
| 18 | Ireland | 0 1000 t | 2023 | down 100.0% | volatile |
| 18 | Iraq | 0 1000 t | 2023 | up 100.0% | volatile |
| 18 | Iceland | 0 1000 t | 2023 | — | volatile |
| 18 | Israel | 0 1000 t | 2023 | up 100.0% | volatile |
| 18 | Italy | 0 1000 t | 2023 | up 100.0% | volatile |
| 18 | Jamaica | 0 1000 t | 2023 | — | flat |
| 18 | Jordan | 0 1000 t | 2023 | — | flat |
| 18 | Kazakhstan | 0 1000 t | 2023 | up 100.0% | flat |
| 18 | Kenya | 0 1000 t | 2023 | down 100.0% | volatile |
| 18 | Cambodia | 0 1000 t | 2023 | — | flat |
| 18 | Kiribati | 0 1000 t | 2023 | — | flat |
| 18 | Saint Kitts and Nevis | 0 1000 t | 2023 | — | flat |
| 18 | Lebanon | 0 1000 t | 2023 | — | flat |
| 18 | Liberia | 0 1000 t | 2023 | — | flat |
| 18 | Libya | 0 1000 t | 2023 | down 100.0% | volatile |
| 18 | Saint Lucia | 0 1000 t | 2023 | — | flat |
| 18 | Sri Lanka | 0 1000 t | 2023 | — | flat |
| 18 | Lesotho | 0 1000 t | 2023 | up 100.0% | volatile |
| 18 | Lithuania | 0 1000 t | 2023 | — | volatile |
| 18 | Luxembourg | 0 1000 t | 2023 | — | flat |
| 18 | Latvia | 0 1000 t | 2023 | — | flat |
| 18 | Morocco | 0 1000 t | 2023 | up 100.0% | volatile |
| 18 | Madagascar | 0 1000 t | 2023 | — | flat |
| 18 | Maldives | 0 1000 t | 2023 | — | flat |
| 18 | Mexico | 0 1000 t | 2023 | down 100.0% | volatile |
| 18 | Marshall Islands | 0 1000 t | 2023 | — | flat |
| 18 | North Macedonia | 0 1000 t | 2023 | — | flat |
| 18 | Malta | 0 1000 t | 2023 | — | flat |
| 18 | Myanmar | 0 1000 t | 2023 | — | volatile |
| 18 | Montenegro | 0 1000 t | 2023 | — | volatile |
| 18 | Mozambique | 0 1000 t | 2023 | — | flat |
| 18 | Mauritania | 0 1000 t | 2023 | down 100.0% | volatile |
| 18 | Mauritius | 0 1000 t | 2023 | — | volatile |
| 18 | Malawi | 0 1000 t | 2023 | — | flat |
| 18 | Malaysia | 0 1000 t | 2023 | — | flat |
| 18 | Namibia | 0 1000 t | 2023 | — | volatile |
| 18 | New Caledonia | 0 1000 t | 2023 | — | flat |
| 18 | Niger | 0 1000 t | 2023 | — | volatile |
| 18 | Nigeria | 0 1000 t | 2023 | up 100.0% | volatile |
| 18 | Nicaragua | 0 1000 t | 2023 | — | flat |
| 18 | Norway | 0 1000 t | 2023 | down 100.0% | flat |
| 18 | Nepal | 0 1000 t | 2023 | — | volatile |
| 18 | Nauru | 0 1000 t | 2023 | — | flat |
| 18 | Oman | 0 1000 t | 2023 | down 100.0% | volatile |
| 18 | Panama | 0 1000 t | 2023 | — | flat |
| 18 | Peru | 0 1000 t | 2023 | — | volatile |
| 18 | Philippines | 0 1000 t | 2023 | down 100.0% | volatile |
| 18 | Papua New Guinea | 0 1000 t | 2023 | down 100.0% | volatile |
| 18 | Poland | 0 1000 t | 2023 | — | volatile |
| 18 | Portugal | 0 1000 t | 2023 | down 100.0% | volatile |
| 18 | Paraguay | 0 1000 t | 2023 | — | flat |
| 18 | French Polynesia | 0 1000 t | 2023 | — | flat |
| 18 | Qatar | 0 1000 t | 2023 | — | volatile |
| 18 | Romania | 0 1000 t | 2023 | down 100.0% | volatile |
| 18 | Saudi Arabia | 0 1000 t | 2023 | up 100.0% | volatile |
| 18 | Senegal | 0 1000 t | 2023 | — | volatile |
| 18 | Solomon Islands | 0 1000 t | 2023 | — | flat |
| 18 | Sierra Leone | 0 1000 t | 2023 | up 100.0% | volatile |
| 18 | El Salvador | 0 1000 t | 2023 | — | flat |
| 18 | Serbia | 0 1000 t | 2023 | — | flat |
| 18 | Sao Tome and Principe | 0 1000 t | 2023 | — | flat |
| 18 | Suriname | 0 1000 t | 2023 | — | flat |
| 18 | Slovakia | 0 1000 t | 2023 | — | flat |
| 18 | Slovenia | 0 1000 t | 2023 | — | flat |
| 18 | Eswatini | 0 1000 t | 2023 | — | flat |
| 18 | Seychelles | 0 1000 t | 2023 | — | flat |
| 18 | Thailand | 0 1000 t | 2023 | — | flat |
| 18 | Tajikistan | 0 1000 t | 2023 | up 100.0% | volatile |
| 18 | Turkmenistan | 0 1000 t | 2023 | — | volatile |
| 18 | Tonga | 0 1000 t | 2023 | — | flat |
| 18 | Trinidad and Tobago | 0 1000 t | 2023 | — | flat |
| 18 | Tunisia | 0 1000 t | 2023 | — | volatile |
| 18 | Tuvalu | 0 1000 t | 2023 | — | flat |
| 18 | Uganda | 0 1000 t | 2023 | — | flat |
| 18 | Ukraine | 0 1000 t | 2023 | — | volatile |
| 18 | Uruguay | 0 1000 t | 2023 | down 100.0% | volatile |
| 18 | Uzbekistan | 0 1000 t | 2023 | down 100.0% | volatile |
| 18 | Saint Vincent and the Grenadines | 0 1000 t | 2023 | — | flat |
| 18 | Vanuatu | 0 1000 t | 2023 | — | flat |
| 18 | Samoa | 0 1000 t | 2023 | — | flat |
| 18 | Yemen | 0 1000 t | 2023 | — | flat |
| 18 | Zambia | 0 1000 t | 2023 | — | volatile |
| 18 | Zimbabwe | 0 1000 t | 2023 | — | flat |
| 18 | Micronesia | 0 1000 t | 2023 | — | flat |
| 18 | Timor-Leste | 0 1000 t | 2023 | — | flat |
| 18 | Cabo Verde | 0 1000 t | 2023 | — | flat |
| 18 | Melanesia | 0 1000 t | 2023 | down 100.0% | volatile |
| 18 | Polynesia | 0 1000 t | 2023 | — | flat |
| 18 | Democratic Republic of the Congo | 0 1000 t | 2023 | — | volatile |
| 18 | Caribbean | 0 1000 t | 2023 | — | volatile |
| 18 | Bolivia (Plurinational State of) | 0 1000 t | 2023 | — | flat |
| 18 | China, Hong Kong SAR | 0 1000 t | 2023 | down 100.0% | volatile |
| 18 | Iran (Islamic Republic of) | 0 1000 t | 2023 | up 100.0% | volatile |
| 18 | Republic of Korea | 0 1000 t | 2023 | — | flat |
| 18 | Republic of Moldova | 0 1000 t | 2023 | — | flat |
| 18 | Syrian Arab Republic | 0 1000 t | 2023 | down 100.0% | volatile |
| 18 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | — | volatile |
| 18 | Viet Nam | 0 1000 t | 2023 | — | flat |
| 18 | Türkiye | 0 1000 t | 2023 | down 100.0% | volatile |
| 18 | Lao People's Democratic Republic | 0 1000 t | 2023 | — | flat |
| 18 | United Republic of Tanzania | 0 1000 t | 2023 | down 100.0% | volatile |
| 18 | China, Taiwan Province of | 0 1000 t | 2023 | up 100.0% | volatile |
| 18 | Netherlands (Kingdom of the) | 0 1000 t | 2023 | — | volatile |
| 18 | United Kingdom of Great Britain and Northern Ireland | 0 1000 t | 2023 | — | volatile |
| 18 | Democratic People's Republic of Korea | 0 1000 t | 2018 | — | volatile |
| 18 | Micronesia (Federated States of) | 0 1000 t | 2023 | — | flat |
| 18 | China, Macao SAR | 0 1000 t | 2023 | — | flat |
| 181 | Russian Federation | -7 1000 t | 2023 | down 158.3% | volatile |
| 182 | United Arab Emirates | -9 1000 t | 2023 | unchanged | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- World 57 1000 t
- Asia 51 1000 t
- Eastern Asia 40 1000 t
- Land Locked Developing Countries (LLDCs) 28 1000 t
- Net Food Importing Developing Countries (NFIDCs) 21 1000 t
- Central Asia 11 1000 t
- Low Income Food Deficit Countries (LIFDCs) 11 1000 t
- European Union (27) 8 1000 t
- Oceania 3 1000 t
- Southern Asia 3 1000 t
- Africa 2 1000 t
- Western Europe 2 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.