Milk - Excluding Butter — 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...
Countries reporting
184
Highest
5,005 1000 t
India
Lowest
-634 1000 t
United Arab Emirates
Median
0 1000 t
Years covered
14
2010–2023
Data points
3,042
What the numbers show
Milk - Excluding Butter — Stock Variation is currently reported for 184 countries. The highest value is 5,005 1000 t in India; the lowest is -634 1000 t in United Arab Emirates.
The median across all reporting countries is 0 1000 t, and the mean is 27.06 1000 t.
The gap between the highest and lowest reporting country is a factor of about 8.
Over the past decade 84 countries rose and 56 fell. The largest increase was in India (up 12,612.5%), and the largest decrease in Caribbean (down 566.7%).
Milk - Excluding Butter — Stock Variation: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | India | 5,005 1000 t | 2023 | up 12,612.5% | volatile |
| 2 | Denmark | 295 1000 t | 2023 | up 226.6% | volatile |
| 3 | China | 224 1000 t | 2023 | down 83.8% | volatile |
| 3 | China, mainland | 224 1000 t | 2023 | down 83.5% | volatile |
| 5 | Netherlands (Kingdom of the) | 189 1000 t | 2023 | down 68.8% | volatile |
| 6 | Australia and New Zealand | 163 1000 t | 2023 | up 329.6% | volatile |
| 7 | Iraq | 113 1000 t | 2023 | up 351.1% | volatile |
| 8 | Vietnam | 104 1000 t | 2023 | down 74.9% | volatile |
| 8 | Viet Nam | 104 1000 t | 2023 | down 74.9% | volatile |
| 10 | Thailand | 90 1000 t | 2023 | up 291.5% | volatile |
| 11 | New Zealand | 84 1000 t | 2023 | up 210.5% | volatile |
| 12 | Bangladesh | 80 1000 t | 2023 | up 344.4% | volatile |
| 13 | Australia | 79 1000 t | 2023 | up 1,480.0% | volatile |
| 14 | Morocco | 54 1000 t | 2023 | up 325.0% | volatile |
| 15 | Saudi Arabia | 50 1000 t | 2023 | — | volatile |
| 16 | Belarus | 38 1000 t | 2023 | up 575.0% | volatile |
| 16 | Colombia | 38 1000 t | 2023 | up 195.0% | volatile |
| 18 | Yemen | 36 1000 t | 2023 | up 620.0% | volatile |
| 19 | Ireland | 34 1000 t | 2023 | — | volatile |
| 20 | Mauritius | 29 1000 t | 2023 | up 323.1% | volatile |
| 21 | Brazil | 26 1000 t | 2023 | up 136.1% | volatile |
| 22 | Libya | 22 1000 t | 2023 | up 633.3% | volatile |
| 23 | Nigeria | 21 1000 t | 2023 | up 320.0% | volatile |
| 23 | Poland | 21 1000 t | 2023 | down 25.0% | volatile |
| 25 | United Kingdom | 19 1000 t | 2023 | — | volatile |
| 25 | United Kingdom of Great Britain and Northern Ireland | 19 1000 t | 2023 | — | volatile |
| 27 | Canada | 18 1000 t | 2023 | up 212.5% | volatile |
| 28 | Ukraine | 16 1000 t | 2023 | up 633.3% | volatile |
| 29 | Portugal | 15 1000 t | 2023 | up 600.0% | flat |
| 30 | Greece | 14 1000 t | 2023 | down 93.1% | volatile |
| 30 | Maldives | 14 1000 t | 2023 | up 800.0% | volatile |
| 32 | Spain | 13 1000 t | 2023 | — | volatile |
| 32 | Honduras | 13 1000 t | 2023 | up 750.0% | volatile |
| 34 | Hungary | 12 1000 t | 2023 | up 111.7% | volatile |
| 35 | Indonesia | 11 1000 t | 2023 | down 8.3% | volatile |
| 35 | Latvia | 11 1000 t | 2023 | down 45.0% | volatile |
| 37 | Republic of Korea | 10 1000 t | 2023 | up 176.9% | volatile |
| 38 | Germany | 9 1000 t | 2023 | — | volatile |
| 38 | Ethiopia | 9 1000 t | 2023 | up 800.0% | volatile |
| 40 | Slovakia | 7 1000 t | 2023 | up 450.0% | volatile |
| 41 | Ghana | 6 1000 t | 2023 | down 33.3% | volatile |
| 41 | Malta | 6 1000 t | 2023 | — | volatile |
| 43 | Guyana | 5 1000 t | 2023 | up 155.6% | volatile |
| 43 | Croatia | 5 1000 t | 2023 | up 350.0% | volatile |
| 43 | Lebanon | 5 1000 t | 2023 | up 25.0% | volatile |
| 43 | Uruguay | 5 1000 t | 2023 | up 106.1% | volatile |
| 43 | Democratic Republic of the Congo | 5 1000 t | 2023 | down 58.3% | volatile |
| 48 | Egypt | 4 1000 t | 2023 | down 98.0% | volatile |
| 48 | Guatemala | 4 1000 t | 2023 | up 166.7% | volatile |
| 48 | Kazakhstan | 4 1000 t | 2023 | down 90.0% | volatile |
| 48 | Malawi | 4 1000 t | 2023 | up 33.3% | volatile |
| 48 | Syria | 4 1000 t | 2023 | up 111.1% | volatile |
| 48 | Syrian Arab Republic | 4 1000 t | 2023 | up 111.1% | volatile |
| 54 | Bulgaria | 3 1000 t | 2023 | up 117.6% | volatile |
| 54 | Switzerland | 3 1000 t | 2023 | — | volatile |
| 54 | Kyrgyzstan | 3 1000 t | 2023 | down 66.7% | volatile |
| 54 | Sri Lanka | 3 1000 t | 2023 | up 103.9% | volatile |
| 54 | Zimbabwe | 3 1000 t | 2023 | down 88.0% | volatile |
| 54 | China, Taiwan Province of | 3 1000 t | 2023 | up 250.0% | volatile |
| 60 | Gambia | 2 1000 t | 2023 | up 105.1% | volatile |
| 60 | Tajikistan | 2 1000 t | 2023 | — | volatile |
| 60 | Turkey | 2 1000 t | 2023 | up 128.6% | volatile |
| 60 | Iran (Islamic Republic of) | 2 1000 t | 2023 | up 150.0% | volatile |
| 60 | Türkiye | 2 1000 t | 2023 | up 128.6% | volatile |
| 60 | United Republic of Tanzania | 2 1000 t | 2023 | unchanged | volatile |
| 66 | Armenia | 1 1000 t | 2023 | up 200.0% | volatile |
| 66 | Belgium | 1 1000 t | 2023 | up 150.0% | volatile |
| 66 | Burkina Faso | 1 1000 t | 2023 | down 92.3% | volatile |
| 66 | Belize | 1 1000 t | 2023 | — | volatile |
| 66 | Chile | 1 1000 t | 2023 | up 100.7% | volatile |
| 66 | Cameroon | 1 1000 t | 2023 | down 80.0% | volatile |
| 66 | Czechia | 1 1000 t | 2023 | down 99.4% | volatile |
| 66 | Estonia | 1 1000 t | 2023 | — | volatile |
| 66 | France | 1 1000 t | 2023 | — | volatile |
| 66 | Grenada | 1 1000 t | 2023 | — | volatile |
| 66 | Cambodia | 1 1000 t | 2023 | down 75.0% | volatile |
| 66 | Nepal | 1 1000 t | 2023 | — | volatile |
| 66 | Serbia | 1 1000 t | 2023 | — | flat |
| 66 | Suriname | 1 1000 t | 2023 | — | volatile |
| 66 | Slovenia | 1 1000 t | 2023 | — | volatile |
| 66 | Cabo Verde | 1 1000 t | 2023 | unchanged | volatile |
| 66 | Melanesia | 1 1000 t | 2023 | up 120.0% | volatile |
| 66 | Democratic People's Republic of Korea | 1 1000 t | 2018 | unchanged | volatile |
| 84 | Afghanistan | 0 1000 t | 2023 | down 100.0% | volatile |
| 84 | Angola | 0 1000 t | 2023 | — | volatile |
| 84 | Albania | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | Antigua and Barbuda | 0 1000 t | 2023 | — | volatile |
| 84 | Azerbaijan | 0 1000 t | 2023 | down 100.0% | volatile |
| 84 | Bahamas | 0 1000 t | 2023 | down 100.0% | volatile |
| 84 | Bosnia and Herzegovina | 0 1000 t | 2023 | up 100.0% | flat |
| 84 | Barbados | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | Botswana | 0 1000 t | 2023 | down 100.0% | volatile |
| 84 | Cote d'Ivoire | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | Congo | 0 1000 t | 2023 | down 100.0% | volatile |
| 84 | Comoros | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | Costa Rica | 0 1000 t | 2023 | down 100.0% | volatile |
| 84 | Cuba | 0 1000 t | 2019 | up 100.0% | volatile |
| 84 | Cyprus | 0 1000 t | 2023 | down 100.0% | volatile |
| 84 | Djibouti | 0 1000 t | 2023 | down 100.0% | volatile |
| 84 | Dominican Republic | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | Ecuador | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | Finland | 0 1000 t | 2023 | — | volatile |
| 84 | Fiji | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | Gabon | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | Guinea | 0 1000 t | 2023 | down 100.0% | volatile |
| 84 | Guinea-Bissau | 0 1000 t | 2023 | down 100.0% | volatile |
| 84 | Haiti | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | Israel | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | Jamaica | 0 1000 t | 2023 | down 100.0% | volatile |
| 84 | Jordan | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | Kiribati | 0 1000 t | 2023 | up 100.0% | flat |
| 84 | Saint Kitts and Nevis | 0 1000 t | 2023 | — | flat |
| 84 | Laos | 0 1000 t | 2023 | down 100.0% | volatile |
| 84 | Liberia | 0 1000 t | 2023 | down 100.0% | flat |
| 84 | Saint Lucia | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | Moldova | 0 1000 t | 2023 | down 100.0% | volatile |
| 84 | Madagascar | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | Mexico | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | North Macedonia | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | Montenegro | 0 1000 t | 2023 | — | volatile |
| 84 | Mongolia | 0 1000 t | 2023 | — | volatile |
| 84 | Mozambique | 0 1000 t | 2023 | — | volatile |
| 84 | Mauritania | 0 1000 t | 2023 | down 100.0% | volatile |
| 84 | Namibia | 0 1000 t | 2023 | down 100.0% | volatile |
| 84 | New Caledonia | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | Niger | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | Nicaragua | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | Norway | 0 1000 t | 2023 | down 100.0% | volatile |
| 84 | Peru | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | Papua New Guinea | 0 1000 t | 2023 | — | flat |
| 84 | Paraguay | 0 1000 t | 2023 | — | volatile |
| 84 | French Polynesia | 0 1000 t | 2023 | — | volatile |
| 84 | Qatar | 0 1000 t | 2023 | — | volatile |
| 84 | Rwanda | 0 1000 t | 2023 | down 100.0% | flat |
| 84 | Senegal | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | Solomon Islands | 0 1000 t | 2023 | down 100.0% | volatile |
| 84 | Sierra Leone | 0 1000 t | 2023 | down 100.0% | volatile |
| 84 | El Salvador | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | Sao Tome and Principe | 0 1000 t | 2023 | — | volatile |
| 84 | Sweden | 0 1000 t | 2023 | — | volatile |
| 84 | Eswatini | 0 1000 t | 2023 | down 100.0% | volatile |
| 84 | Seychelles | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | Turkmenistan | 0 1000 t | 2023 | — | volatile |
| 84 | East Timor | 0 1000 t | 2023 | — | volatile |
| 84 | Tonga | 0 1000 t | 2023 | — | volatile |
| 84 | Tunisia | 0 1000 t | 2023 | down 100.0% | volatile |
| 84 | Uzbekistan | 0 1000 t | 2023 | — | volatile |
| 84 | Vanuatu | 0 1000 t | 2023 | — | flat |
| 84 | Samoa | 0 1000 t | 2023 | down 100.0% | volatile |
| 84 | Micronesia | 0 1000 t | 2023 | up 100.0% | flat |
| 84 | Timor-Leste | 0 1000 t | 2023 | — | volatile |
| 84 | Polynesia | 0 1000 t | 2023 | down 100.0% | flat |
| 84 | Bolivia (Plurinational State of) | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | Republic of Moldova | 0 1000 t | 2023 | down 100.0% | volatile |
| 84 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | Côte d'Ivoire | 0 1000 t | 2023 | up 100.0% | volatile |
| 84 | Lao People's Democratic Republic | 0 1000 t | 2023 | down 100.0% | volatile |
| 84 | China, Macao SAR | 0 1000 t | 2023 | up 100.0% | volatile |
| 169 | Argentina | -1 1000 t | 2023 | up 99.1% | volatile |
| 169 | Luxembourg | -1 1000 t | 2023 | — | volatile |
| 169 | Myanmar | -1 1000 t | 2023 | down 125.0% | volatile |
| 169 | Trinidad and Tobago | -1 1000 t | 2023 | up 75.0% | volatile |
| 169 | Saint Vincent and the Grenadines | -1 1000 t | 2023 | — | volatile |
| 174 | Pakistan | -2 1000 t | 2023 | up 93.5% | volatile |
| 174 | Romania | -2 1000 t | 2023 | up 88.9% | volatile |
| 174 | United States | -2 1000 t | 2023 | down 100.0% | volatile |
| 174 | Zambia | -2 1000 t | 2023 | down 150.0% | volatile |
| 178 | South Africa | -3 1000 t | 2023 | up 96.2% | volatile |
| 178 | China, Hong Kong SAR | -3 1000 t | 2023 | down 112.5% | volatile |
| 180 | Kenya | -4 1000 t | 2023 | up 77.8% | flat |
| 181 | Austria | -7 1000 t | 2023 | down 118.9% | volatile |
| 182 | Panama | -8 1000 t | 2023 | down 300.0% | volatile |
| 183 | Philippines | -16 1000 t | 2023 | down 118.6% | volatile |
| 184 | Bahrain | -23 1000 t | 2023 | — | volatile |
| 185 | Algeria | -24 1000 t | 2023 | up 91.3% | volatile |
| 186 | Malaysia | -25 1000 t | 2023 | up 64.3% | volatile |
| 187 | Lithuania | -74 1000 t | 2023 | up 37.3% | volatile |
| 188 | Kuwait | -79 1000 t | 2023 | down 325.7% | volatile |
| 189 | Italy | -80 1000 t | 2023 | up 26.6% | volatile |
| 189 | Caribbean | -80 1000 t | 2023 | down 566.7% | volatile |
| 191 | Oman | -262 1000 t | 2023 | down 315.9% | volatile |
| 192 | Russia | -564 1000 t | 2023 | — | volatile |
| 192 | Russian Federation | -564 1000 t | 2023 | — | volatile |
| 194 | United Arab Emirates | -634 1000 t | 2023 | down 303.8% | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- Southern Asia 5,104 1000 t
- World 5,033 1000 t
- Asia 4,700 1000 t
- European Union (27) 476 1000 t
- Northern Europe 286 1000 t
- Eastern Asia 210 1000 t
- Net Food Importing Developing Countries (NFIDCs) 199 1000 t
- Western Europe 195 1000 t
- Least Developed Countries (LDCs) 166 1000 t
- South-Eastern Asia 165 1000 t
- Oceania 163 1000 t
- Africa 159 1000 t
- Low Income Food Deficit Countries (LIFDCs) 110 1000 t
- Northern Africa 78 1000 t
- South America 75 1000 t
- Eastern Africa 46 1000 t
- Western Africa 31 1000 t
- Land Locked Developing Countries (LLDCs) 28 1000 t
- Americas 22 1000 t
- Northern America 16 1000 t
- Central America 11 1000 t
- Central Asia 9 1000 t
- Middle Africa 7 1000 t
- Southern Africa -2 1000 t
- United States of America -2 1000 t
- Europe -11 1000 t
- Southern Europe -25 1000 t
- Small island developing States (SIDS) -28 1000 t
- Eastern Europe -467 1000 t
- Western Asia -788 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.