Milk - Excluding Butter — Residuals 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
Milk - Excluding Butter — Residuals is currently reported for 152 countries. The highest value is 2,804 1000 t in Belarus; the lowest is -4,413 1000 t in France.
The median across all reporting countries is -1 1000 t, and the mean is -71.78 1000 t.
Over the past decade 40 countries rose and 55 fell. The largest increase was in India (up 8,600.0%), and the largest decrease in Cyprus (down 16,700.0%).
Milk - Excluding Butter — Residuals: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Belarus | 2,804 1000 t | 2023 | up 2,696.3% | volatile |
| 2 | Malaysia | 788 1000 t | 2023 | up 34.7% | rising |
| 3 | Lithuania | 470 1000 t | 2023 | up 28.8% | volatile |
| 4 | Venezuela (Bolivarian Republic of) | 469 1000 t | 2023 | — | volatile |
| 5 | Kyrgyzstan | 125 1000 t | 2023 | — | volatile |
| 6 | India | 85 1000 t | 2023 | up 8,600.0% | volatile |
| 7 | Portugal | 35 1000 t | 2023 | down 65.3% | volatile |
| 8 | Bulgaria | 3 1000 t | 2023 | up 400.0% | volatile |
| 9 | Estonia | 1 1000 t | 2023 | down 98.1% | volatile |
| 9 | Eswatini | 1 1000 t | 2023 | — | volatile |
| 11 | Afghanistan | 0 1000 t | 2023 | — | volatile |
| 11 | Antigua and Barbuda | 0 1000 t | 2023 | — | volatile |
| 11 | Australia | 0 1000 t | 2023 | up 100.0% | volatile |
| 11 | Azerbaijan | 0 1000 t | 2023 | up 100.0% | volatile |
| 11 | Burkina Faso | 0 1000 t | 2023 | — | volatile |
| 11 | Belize | 0 1000 t | 2023 | — | volatile |
| 11 | Switzerland | 0 1000 t | 2023 | down 100.0% | volatile |
| 11 | Cameroon | 0 1000 t | 2023 | up 100.0% | volatile |
| 11 | Congo | 0 1000 t | 2023 | up 100.0% | volatile |
| 11 | Colombia | 0 1000 t | 2023 | — | volatile |
| 11 | Djibouti | 0 1000 t | 2023 | — | volatile |
| 11 | Dominican Republic | 0 1000 t | 2023 | — | volatile |
| 11 | Algeria | 0 1000 t | 2023 | — | volatile |
| 11 | Gabon | 0 1000 t | 2023 | down 100.0% | volatile |
| 11 | United Kingdom | 0 1000 t | 2023 | up 100.0% | volatile |
| 11 | Guinea | 0 1000 t | 2023 | — | volatile |
| 11 | Gambia | 0 1000 t | 2023 | up 100.0% | volatile |
| 11 | Guyana | 0 1000 t | 2023 | — | volatile |
| 11 | Iceland | 0 1000 t | 2023 | up 100.0% | volatile |
| 11 | Israel | 0 1000 t | 2023 | up 100.0% | volatile |
| 11 | Kazakhstan | 0 1000 t | 2023 | down 100.0% | volatile |
| 11 | Cambodia | 0 1000 t | 2023 | — | volatile |
| 11 | Kuwait | 0 1000 t | 2023 | up 100.0% | volatile |
| 11 | Laos | 0 1000 t | 2023 | — | volatile |
| 11 | Lebanon | 0 1000 t | 2023 | up 100.0% | volatile |
| 11 | Libya | 0 1000 t | 2023 | down 100.0% | volatile |
| 11 | Moldova | 0 1000 t | 2023 | — | volatile |
| 11 | Maldives | 0 1000 t | 2023 | up 100.0% | volatile |
| 11 | Mexico | 0 1000 t | 2023 | — | volatile |
| 11 | Marshall Islands | 0 1000 t | 2023 | — | volatile |
| 11 | Malta | 0 1000 t | 2023 | down 100.0% | volatile |
| 11 | Myanmar | 0 1000 t | 2023 | — | volatile |
| 11 | Mauritius | 0 1000 t | 2023 | — | volatile |
| 11 | Namibia | 0 1000 t | 2023 | — | volatile |
| 11 | New Caledonia | 0 1000 t | 2023 | — | volatile |
| 11 | Norway | 0 1000 t | 2023 | down 100.0% | volatile |
| 11 | Oman | 0 1000 t | 2023 | down 100.0% | volatile |
| 11 | Panama | 0 1000 t | 2023 | — | volatile |
| 11 | French Polynesia | 0 1000 t | 2023 | — | flat |
| 11 | Romania | 0 1000 t | 2023 | up 100.0% | volatile |
| 11 | Rwanda | 0 1000 t | 2023 | — | volatile |
| 11 | Saudi Arabia | 0 1000 t | 2023 | up 100.0% | volatile |
| 11 | Solomon Islands | 0 1000 t | 2023 | — | volatile |
| 11 | Sierra Leone | 0 1000 t | 2023 | — | volatile |
| 11 | El Salvador | 0 1000 t | 2023 | — | volatile |
| 11 | Sao Tome and Principe | 0 1000 t | 2023 | — | volatile |
| 11 | Suriname | 0 1000 t | 2023 | down 100.0% | volatile |
| 11 | Seychelles | 0 1000 t | 2023 | down 100.0% | volatile |
| 11 | Syria | 0 1000 t | 2023 | — | volatile |
| 11 | Turkmenistan | 0 1000 t | 2023 | — | volatile |
| 11 | Trinidad and Tobago | 0 1000 t | 2023 | down 100.0% | flat |
| 11 | Tunisia | 0 1000 t | 2023 | down 100.0% | volatile |
| 11 | Micronesia | 0 1000 t | 2023 | — | volatile |
| 11 | Polynesia | 0 1000 t | 2023 | — | flat |
| 11 | Caribbean | 0 1000 t | 2023 | down 100.0% | volatile |
| 11 | China, Hong Kong SAR | 0 1000 t | 2023 | — | volatile |
| 11 | Republic of Moldova | 0 1000 t | 2023 | — | volatile |
| 11 | Syrian Arab Republic | 0 1000 t | 2023 | — | volatile |
| 11 | Lao People's Democratic Republic | 0 1000 t | 2023 | — | volatile |
| 11 | China, Taiwan Province of | 0 1000 t | 2023 | — | volatile |
| 11 | United Kingdom of Great Britain and Northern Ireland | 0 1000 t | 2023 | up 100.0% | volatile |
| 11 | Democratic People's Republic of Korea | 0 1000 t | 2018 | — | volatile |
| 11 | China, Macao SAR | 0 1000 t | 2023 | — | volatile |
| 116 | Bangladesh | -1 1000 t | 2023 | — | volatile |
| 116 | Egypt | -1 1000 t | 2023 | unchanged | volatile |
| 116 | Croatia | -1 1000 t | 2023 | — | volatile |
| 116 | Kenya | -1 1000 t | 2023 | — | volatile |
| 116 | Sri Lanka | -1 1000 t | 2023 | — | volatile |
| 116 | Mozambique | -1 1000 t | 2023 | — | volatile |
| 116 | Malawi | -1 1000 t | 2023 | up 75.0% | volatile |
| 116 | Pakistan | -1 1000 t | 2023 | up 99.9% | volatile |
| 116 | Peru | -1 1000 t | 2023 | — | volatile |
| 116 | Senegal | -1 1000 t | 2023 | up 50.0% | volatile |
| 116 | Vietnam | -1 1000 t | 2023 | up 99.9% | volatile |
| 116 | Viet Nam | -1 1000 t | 2023 | up 99.9% | volatile |
| 128 | Ethiopia | -2 1000 t | 2023 | up 66.7% | volatile |
| 128 | Zimbabwe | -2 1000 t | 2023 | down 150.0% | volatile |
| 130 | Honduras | -4 1000 t | 2023 | down 33.3% | falling |
| 130 | Uruguay | -4 1000 t | 2023 | — | volatile |
| 130 | Iran (Islamic Republic of) | -4 1000 t | 2023 | up 91.7% | volatile |
| 133 | Chile | -5 1000 t | 2023 | down 200.0% | volatile |
| 133 | Jordan | -5 1000 t | 2023 | up 50.0% | volatile |
| 133 | Nigeria | -5 1000 t | 2023 | — | volatile |
| 136 | Yemen | -6 1000 t | 2023 | up 85.0% | volatile |
| 137 | Iraq | -7 1000 t | 2023 | — | volatile |
| 137 | Republic of Korea | -7 1000 t | 2023 | down 153.8% | volatile |
| 139 | Argentina | -8 1000 t | 2023 | down 33.3% | volatile |
| 139 | Canada | -8 1000 t | 2023 | up 95.7% | volatile |
| 139 | Madagascar | -8 1000 t | 2023 | down 33.3% | volatile |
| 142 | Brazil | -9 1000 t | 2023 | down 800.0% | volatile |
| 142 | Uganda | -9 1000 t | 2023 | down 550.0% | volatile |
| 142 | Ukraine | -9 1000 t | 2023 | unchanged | volatile |
| 145 | Ghana | -10 1000 t | 2023 | — | volatile |
| 145 | Paraguay | -10 1000 t | 2023 | — | volatile |
| 147 | Botswana | -11 1000 t | 2023 | up 8.3% | volatile |
| 148 | Ireland | -12 1000 t | 2023 | down 108.8% | volatile |
| 148 | Nicaragua | -12 1000 t | 2023 | down 200.0% | volatile |
| 150 | Bahrain | -13 1000 t | 2023 | — | volatile |
| 150 | Latvia | -13 1000 t | 2023 | down 262.5% | volatile |
| 152 | Fiji | -14 1000 t | 2023 | up 54.8% | volatile |
| 152 | United States | -14 1000 t | 2023 | down 108.9% | volatile |
| 152 | Melanesia | -14 1000 t | 2023 | up 54.8% | volatile |
| 155 | Bosnia and Herzegovina | -16 1000 t | 2023 | — | volatile |
| 156 | Costa Rica | -17 1000 t | 2023 | down 41.7% | falling |
| 156 | South Africa | -17 1000 t | 2023 | down 142.9% | volatile |
| 158 | Serbia | -18 1000 t | 2023 | down 200.0% | volatile |
| 159 | Turkey | -21 1000 t | 2023 | down 23.5% | falling |
| 159 | Türkiye | -21 1000 t | 2023 | down 23.5% | falling |
| 161 | Slovenia | -25 1000 t | 2023 | down 525.0% | volatile |
| 162 | Guatemala | -28 1000 t | 2023 | down 460.0% | volatile |
| 163 | Finland | -29 1000 t | 2023 | up 96.2% | volatile |
| 164 | Sweden | -31 1000 t | 2023 | up 73.7% | volatile |
| 165 | Denmark | -34 1000 t | 2023 | down 277.8% | flat |
| 166 | Hungary | -40 1000 t | 2023 | down 266.7% | volatile |
| 167 | Cote d'Ivoire | -41 1000 t | 2023 | down 46.4% | falling |
| 167 | Côte d'Ivoire | -41 1000 t | 2023 | down 46.4% | falling |
| 169 | Slovakia | -49 1000 t | 2023 | down 40.0% | volatile |
| 170 | Italy | -51 1000 t | 2023 | up 96.6% | volatile |
| 171 | Czechia | -53 1000 t | 2023 | up 49.5% | volatile |
| 172 | Mauritania | -76 1000 t | 2023 | down 52.0% | falling |
| 173 | New Zealand | -82 1000 t | 2023 | down 162.1% | volatile |
| 173 | Australia and New Zealand | -82 1000 t | 2023 | down 170.7% | volatile |
| 175 | Morocco | -87 1000 t | 2023 | up 13.0% | flat |
| 176 | United Arab Emirates | -91 1000 t | 2023 | down 600.0% | volatile |
| 177 | Luxembourg | -97 1000 t | 2023 | down 4,750.0% | volatile |
| 178 | Poland | -123 1000 t | 2023 | up 86.6% | volatile |
| 179 | Cyprus | -166 1000 t | 2023 | down 16,700.0% | volatile |
| 180 | Austria | -176 1000 t | 2023 | down 1,253.8% | volatile |
| 181 | Indonesia | -181 1000 t | 2023 | down 61.6% | volatile |
| 182 | Germany | -215 1000 t | 2023 | down 189.2% | volatile |
| 183 | Thailand | -243 1000 t | 2023 | down 133.7% | volatile |
| 184 | Spain | -375 1000 t | 2023 | down 49.4% | volatile |
| 185 | China | -416 1000 t | 2023 | down 227.6% | volatile |
| 185 | China, mainland | -416 1000 t | 2023 | down 227.6% | volatile |
| 187 | Belgium | -532 1000 t | 2023 | up 0.2% | rising |
| 188 | Russia | -963 1000 t | 2023 | down 15,950.0% | volatile |
| 188 | Russian Federation | -963 1000 t | 2023 | down 15,950.0% | volatile |
| 190 | Netherlands (Kingdom of the) | -1,062 1000 t | 2023 | down 7.7% | volatile |
| 191 | Philippines | -1,216 1000 t | 2023 | — | volatile |
| 192 | Greece | -1,283 1000 t | 2023 | down 1,524.0% | volatile |
| 193 | Zambia | -1,665 1000 t | 2023 | — | volatile |
| 194 | France | -4,413 1000 t | 2023 | up 28.5% | rising |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- Eastern Europe 1,570 1000 t
- South America 432 1000 t
- Northern Europe 353 1000 t
- Americas 350 1000 t
- Central Asia 125 1000 t
- Southern Asia 78 1000 t
- Middle Africa 0 1000 t
- Small island developing States (SIDS) -14 1000 t
- United States of America -14 1000 t
- Northern America -22 1000 t
- Southern Africa -27 1000 t
- Low Income Food Deficit Countries (LIFDCs) -30 1000 t
- Central America -60 1000 t
- Northern Africa -88 1000 t
- Oceania -96 1000 t
- Western Africa -169 1000 t
- Western Asia -309 1000 t
- Eastern Asia -735 1000 t
- South-Eastern Asia -853 1000 t
- Net Food Importing Developing Countries (NFIDCs) -1,489 1000 t
- Land Locked Developing Countries (LLDCs) -1,574 1000 t
- Eastern Africa -1,689 1000 t
- Asia -1,695 1000 t
- Southern Europe -1,734 1000 t
- Least Developed Countries (LDCs) -1,806 1000 t
- Africa -1,973 1000 t
- Europe -6,305 1000 t
- Western Europe -6,494 1000 t
- European Union (27) -8,269 1000 t
- World -9,719 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.