Stimulants — 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
Stimulants — Residuals is currently reported for 92 countries. The highest value is 0 1000 t in Bangladesh; the lowest is -132 1000 t in Indonesia.
The median across all reporting countries is 0 1000 t, and the mean is -10.61 1000 t.
Over the past decade 17 countries rose and 23 fell. The largest increase was in Switzerland (up 100.0%), and the largest decrease in United Arab Emirates (down 2,000.0%).
Stimulants — Residuals: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Bangladesh | 0 1000 t | 2023 | — | volatile |
| 1 | Bulgaria | 0 1000 t | 2023 | — | volatile |
| 1 | Belize | 0 1000 t | 2023 | — | volatile |
| 1 | Switzerland | 0 1000 t | 2023 | up 100.0% | volatile |
| 1 | Chile | 0 1000 t | 2023 | up 100.0% | volatile |
| 1 | Cote d'Ivoire | 0 1000 t | 2023 | down 100.0% | volatile |
| 1 | Congo | 0 1000 t | 2023 | — | volatile |
| 1 | Colombia | 0 1000 t | 2023 | — | volatile |
| 1 | Costa Rica | 0 1000 t | 2023 | up 100.0% | volatile |
| 1 | Djibouti | 0 1000 t | 2023 | — | volatile |
| 1 | United Kingdom | 0 1000 t | 2023 | — | volatile |
| 1 | Georgia | 0 1000 t | 2023 | — | volatile |
| 1 | Guinea-Bissau | 0 1000 t | 2023 | down 100.0% | volatile |
| 1 | Greece | 0 1000 t | 2023 | down 100.0% | volatile |
| 1 | Croatia | 0 1000 t | 2023 | — | volatile |
| 1 | Ireland | 0 1000 t | 2023 | up 100.0% | volatile |
| 1 | Italy | 0 1000 t | 2023 | — | volatile |
| 1 | Kazakhstan | 0 1000 t | 2023 | — | volatile |
| 1 | Kuwait | 0 1000 t | 2023 | — | volatile |
| 1 | Laos | 0 1000 t | 2023 | — | volatile |
| 1 | Lesotho | 0 1000 t | 2023 | — | volatile |
| 1 | Latvia | 0 1000 t | 2023 | — | volatile |
| 1 | Madagascar | 0 1000 t | 2023 | — | volatile |
| 1 | Malawi | 0 1000 t | 2023 | — | volatile |
| 1 | Niger | 0 1000 t | 2023 | — | volatile |
| 1 | Norway | 0 1000 t | 2023 | — | volatile |
| 1 | New Zealand | 0 1000 t | 2023 | down 100.0% | volatile |
| 1 | Oman | 0 1000 t | 2023 | — | volatile |
| 1 | Panama | 0 1000 t | 2023 | — | volatile |
| 1 | Philippines | 0 1000 t | 2023 | — | volatile |
| 1 | Papua New Guinea | 0 1000 t | 2023 | up 100.0% | volatile |
| 1 | Solomon Islands | 0 1000 t | 2023 | — | volatile |
| 1 | Sierra Leone | 0 1000 t | 2023 | down 100.0% | volatile |
| 1 | El Salvador | 0 1000 t | 2023 | up 100.0% | volatile |
| 1 | Serbia | 0 1000 t | 2023 | — | volatile |
| 1 | Slovakia | 0 1000 t | 2023 | — | volatile |
| 1 | Eswatini | 0 1000 t | 2023 | up 100.0% | volatile |
| 1 | Ukraine | 0 1000 t | 2023 | — | volatile |
| 1 | Yemen | 0 1000 t | 2023 | down 100.0% | volatile |
| 1 | Zimbabwe | 0 1000 t | 2023 | — | volatile |
| 1 | Melanesia | 0 1000 t | 2023 | up 100.0% | volatile |
| 1 | China, Hong Kong SAR | 0 1000 t | 2023 | — | volatile |
| 1 | Iran (Islamic Republic of) | 0 1000 t | 2023 | — | volatile |
| 1 | Australia and New Zealand | 0 1000 t | 2023 | down 100.0% | volatile |
| 1 | Côte d'Ivoire | 0 1000 t | 2023 | down 100.0% | volatile |
| 1 | Lao People's Democratic Republic | 0 1000 t | 2023 | — | volatile |
| 1 | China, Taiwan Province of | 0 1000 t | 2023 | — | volatile |
| 1 | United Kingdom of Great Britain and Northern Ireland | 0 1000 t | 2023 | — | volatile |
| 151 | Germany | -1 1000 t | 2023 | — | volatile |
| 151 | Estonia | -1 1000 t | 2023 | — | volatile |
| 151 | Ghana | -1 1000 t | 2023 | down 100.6% | volatile |
| 151 | Gambia | -1 1000 t | 2023 | — | volatile |
| 151 | Liberia | -1 1000 t | 2023 | — | volatile |
| 151 | Myanmar | -1 1000 t | 2023 | — | volatile |
| 151 | Nicaragua | -1 1000 t | 2023 | up 94.4% | volatile |
| 151 | Paraguay | -1 1000 t | 2023 | — | volatile |
| 151 | Turkey | -1 1000 t | 2023 | — | volatile |
| 151 | Vietnam | -1 1000 t | 2023 | up 97.1% | volatile |
| 151 | Viet Nam | -1 1000 t | 2023 | up 97.1% | volatile |
| 151 | Türkiye | -1 1000 t | 2023 | — | volatile |
| 163 | Jordan | -2 1000 t | 2023 | — | volatile |
| 163 | Peru | -2 1000 t | 2023 | — | volatile |
| 165 | Argentina | -3 1000 t | 2023 | — | volatile |
| 165 | Burkina Faso | -3 1000 t | 2023 | — | volatile |
| 165 | Cambodia | -3 1000 t | 2023 | — | volatile |
| 165 | Sri Lanka | -3 1000 t | 2023 | down 50.0% | falling |
| 165 | Rwanda | -3 1000 t | 2023 | down 200.0% | volatile |
| 165 | Zambia | -3 1000 t | 2023 | — | volatile |
| 165 | Republic of Korea | -3 1000 t | 2023 | — | volatile |
| 172 | Egypt | -4 1000 t | 2023 | — | volatile |
| 172 | Poland | -4 1000 t | 2023 | up 55.6% | volatile |
| 174 | Kenya | -5 1000 t | 2023 | up 61.5% | volatile |
| 175 | Democratic Republic of the Congo | -6 1000 t | 2023 | down 125.0% | volatile |
| 176 | Mexico | -11 1000 t | 2023 | down 1,000.0% | volatile |
| 176 | Thailand | -11 1000 t | 2023 | up 87.4% | volatile |
| 178 | Czechia | -13 1000 t | 2023 | down 1,200.0% | volatile |
| 178 | Uganda | -13 1000 t | 2023 | up 58.1% | volatile |
| 180 | China | -14 1000 t | 2023 | down 75.0% | volatile |
| 180 | China, mainland | -14 1000 t | 2023 | down 55.6% | falling |
| 182 | United Republic of Tanzania | -23 1000 t | 2023 | — | volatile |
| 183 | Hungary | -32 1000 t | 2023 | down 39.1% | volatile |
| 184 | Canada | -40 1000 t | 2023 | up 20.0% | rising |
| 184 | Nigeria | -40 1000 t | 2023 | down 233.3% | volatile |
| 186 | Spain | -43 1000 t | 2023 | down 437.5% | volatile |
| 187 | Guinea | -54 1000 t | 2023 | — | volatile |
| 188 | United Arab Emirates | -63 1000 t | 2023 | down 2,000.0% | volatile |
| 189 | India | -72 1000 t | 2023 | down 928.6% | volatile |
| 190 | Cameroon | -78 1000 t | 2023 | — | volatile |
| 191 | Malaysia | -86 1000 t | 2023 | down 72.0% | volatile |
| 192 | Netherlands (Kingdom of the) | -87 1000 t | 2023 | — | volatile |
| 193 | Ecuador | -94 1000 t | 2023 | up 3.1% | flat |
| 194 | Indonesia | -132 1000 t | 2023 | down 473.9% | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- Oceania 0 1000 t
- Small island developing States (SIDS) 0 1000 t
- Central Asia 0 1000 t
- Southern Africa 0 1000 t
- Northern Europe -1 1000 t
- Northern Africa -4 1000 t
- Central America -12 1000 t
- Eastern Asia -17 1000 t
- Land Locked Developing Countries (LLDCs) -24 1000 t
- Northern America -40 1000 t
- Southern Europe -44 1000 t
- Eastern Africa -47 1000 t
- Eastern Europe -49 1000 t
- Western Asia -65 1000 t
- Southern Asia -75 1000 t
- Middle Africa -84 1000 t
- Western Europe -88 1000 t
- South America -99 1000 t
- Western Africa -101 1000 t
- Least Developed Countries (LDCs) -113 1000 t
- Net Food Importing Developing Countries (NFIDCs) -128 1000 t
- Americas -152 1000 t
- European Union (27) -181 1000 t
- Europe -182 1000 t
- Low Income Food Deficit Countries (LIFDCs) -188 1000 t
- South-Eastern Asia -234 1000 t
- Africa -236 1000 t
- Asia -392 1000 t
- World -961 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.