Stimulants — 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
Stimulants — Stock Variation is currently reported for 171 countries. The highest value is 312 1000 t in Cote d'Ivoire; the lowest is -387 1000 t in Türkiye.
The median across all reporting countries is 0 1000 t, and the mean is 2.49 1000 t.
Over the past decade 52 countries rose and 59 fell. The largest increase was in Indonesia (up 6,300.0%), and the largest decrease in United Arab Emirates (down 2,033.3%).
Stimulants — Stock Variation: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Cote d'Ivoire | 312 1000 t | 2023 | up 113.7% | volatile |
| 1 | Côte d'Ivoire | 312 1000 t | 2023 | up 113.7% | volatile |
| 3 | China | 107 1000 t | 2023 | up 374.4% | volatile |
| 4 | Netherlands (Kingdom of the) | 105 1000 t | 2023 | up 160.7% | volatile |
| 5 | China, mainland | 87 1000 t | 2023 | up 274.0% | volatile |
| 6 | Indonesia | 64 1000 t | 2023 | up 6,300.0% | volatile |
| 7 | Colombia | 54 1000 t | 2023 | up 125.0% | volatile |
| 7 | Malaysia | 54 1000 t | 2023 | up 1,700.0% | volatile |
| 9 | United Kingdom | 52 1000 t | 2023 | — | volatile |
| 9 | United Kingdom of Great Britain and Northern Ireland | 52 1000 t | 2023 | — | volatile |
| 11 | Guinea | 42 1000 t | 2023 | — | volatile |
| 12 | Thailand | 36 1000 t | 2023 | up 3,500.0% | volatile |
| 13 | India | 30 1000 t | 2023 | up 76.5% | volatile |
| 14 | Canada | 29 1000 t | 2023 | up 3,000.0% | volatile |
| 15 | Belgium | 27 1000 t | 2023 | down 49.1% | volatile |
| 16 | Algeria | 23 1000 t | 2023 | up 360.0% | volatile |
| 17 | Iraq | 22 1000 t | 2023 | up 1,200.0% | volatile |
| 18 | Kenya | 20 1000 t | 2023 | up 122.0% | volatile |
| 18 | Papua New Guinea | 20 1000 t | 2023 | up 1,900.0% | volatile |
| 18 | Melanesia | 20 1000 t | 2023 | up 900.0% | volatile |
| 21 | China, Hong Kong SAR | 14 1000 t | 2023 | up 100.0% | volatile |
| 22 | Lebanon | 12 1000 t | 2023 | up 9.1% | volatile |
| 22 | Saudi Arabia | 12 1000 t | 2023 | — | volatile |
| 24 | Czechia | 11 1000 t | 2023 | — | volatile |
| 24 | Greece | 11 1000 t | 2023 | — | volatile |
| 24 | Uzbekistan | 11 1000 t | 2023 | up 266.7% | volatile |
| 27 | Azerbaijan | 10 1000 t | 2023 | — | volatile |
| 27 | Iran (Islamic Republic of) | 10 1000 t | 2023 | down 58.3% | volatile |
| 29 | Morocco | 8 1000 t | 2023 | up 14.3% | volatile |
| 30 | Romania | 7 1000 t | 2023 | — | volatile |
| 31 | Spain | 6 1000 t | 2023 | — | volatile |
| 31 | Madagascar | 6 1000 t | 2023 | — | volatile |
| 31 | Slovenia | 6 1000 t | 2023 | — | volatile |
| 34 | Guatemala | 5 1000 t | 2023 | up 162.5% | volatile |
| 34 | Hungary | 5 1000 t | 2023 | — | volatile |
| 36 | Laos | 4 1000 t | 2023 | up 33.3% | volatile |
| 36 | Vietnam | 4 1000 t | 2023 | up 144.4% | volatile |
| 36 | Viet Nam | 4 1000 t | 2023 | up 144.4% | volatile |
| 36 | Lao People's Democratic Republic | 4 1000 t | 2023 | up 33.3% | volatile |
| 36 | China, Taiwan Province of | 4 1000 t | 2023 | unchanged | volatile |
| 41 | Ireland | 3 1000 t | 2023 | down 50.0% | volatile |
| 41 | Portugal | 3 1000 t | 2023 | down 50.0% | volatile |
| 41 | Tunisia | 3 1000 t | 2023 | up 50.0% | volatile |
| 44 | Argentina | 2 1000 t | 2023 | up 103.1% | volatile |
| 44 | Georgia | 2 1000 t | 2023 | down 33.3% | volatile |
| 44 | Italy | 2 1000 t | 2023 | — | volatile |
| 44 | Kazakhstan | 2 1000 t | 2023 | down 87.5% | volatile |
| 44 | Libya | 2 1000 t | 2023 | down 33.3% | volatile |
| 44 | Nepal | 2 1000 t | 2023 | — | volatile |
| 44 | Philippines | 2 1000 t | 2023 | down 93.3% | volatile |
| 44 | Syria | 2 1000 t | 2023 | down 81.8% | volatile |
| 44 | Zimbabwe | 2 1000 t | 2023 | up 140.0% | flat |
| 44 | Syrian Arab Republic | 2 1000 t | 2023 | down 81.8% | volatile |
| 44 | China, Macao SAR | 2 1000 t | 2023 | up 300.0% | volatile |
| 55 | Armenia | 1 1000 t | 2023 | — | volatile |
| 55 | Bulgaria | 1 1000 t | 2023 | down 92.9% | volatile |
| 55 | Bahrain | 1 1000 t | 2023 | — | volatile |
| 55 | Bosnia and Herzegovina | 1 1000 t | 2023 | up 200.0% | volatile |
| 55 | Cameroon | 1 1000 t | 2023 | down 95.5% | volatile |
| 55 | Cyprus | 1 1000 t | 2023 | up 200.0% | volatile |
| 55 | Finland | 1 1000 t | 2023 | down 80.0% | volatile |
| 55 | Honduras | 1 1000 t | 2023 | down 66.7% | volatile |
| 55 | Croatia | 1 1000 t | 2023 | — | volatile |
| 55 | Marshall Islands | 1 1000 t | 2023 | — | volatile |
| 55 | North Macedonia | 1 1000 t | 2023 | — | volatile |
| 55 | Montenegro | 1 1000 t | 2023 | down 50.0% | volatile |
| 55 | Namibia | 1 1000 t | 2023 | unchanged | volatile |
| 55 | Senegal | 1 1000 t | 2023 | unchanged | volatile |
| 55 | Tajikistan | 1 1000 t | 2023 | — | volatile |
| 55 | Ukraine | 1 1000 t | 2023 | down 75.0% | volatile |
| 55 | Yemen | 1 1000 t | 2023 | up 200.0% | volatile |
| 55 | South Africa | 1 1000 t | 2023 | up 125.0% | volatile |
| 55 | Micronesia | 1 1000 t | 2023 | — | volatile |
| 74 | Afghanistan | 0 1000 t | 2023 | down 100.0% | volatile |
| 74 | Angola | 0 1000 t | 2023 | — | volatile |
| 74 | Albania | 0 1000 t | 2023 | — | volatile |
| 74 | Antigua and Barbuda | 0 1000 t | 2023 | — | volatile |
| 74 | Burkina Faso | 0 1000 t | 2023 | down 100.0% | volatile |
| 74 | Bangladesh | 0 1000 t | 2023 | down 100.0% | volatile |
| 74 | Bahamas | 0 1000 t | 2023 | down 100.0% | volatile |
| 74 | Belize | 0 1000 t | 2023 | down 100.0% | volatile |
| 74 | Botswana | 0 1000 t | 2023 | — | volatile |
| 74 | Chile | 0 1000 t | 2023 | up 100.0% | volatile |
| 74 | Congo | 0 1000 t | 2023 | — | volatile |
| 74 | Costa Rica | 0 1000 t | 2023 | up 100.0% | volatile |
| 74 | Cuba | 0 1000 t | 2019 | — | volatile |
| 74 | Germany | 0 1000 t | 2023 | up 100.0% | volatile |
| 74 | Djibouti | 0 1000 t | 2023 | down 100.0% | volatile |
| 74 | Ecuador | 0 1000 t | 2023 | up 100.0% | volatile |
| 74 | Estonia | 0 1000 t | 2023 | up 100.0% | volatile |
| 74 | France | 0 1000 t | 2023 | up 100.0% | volatile |
| 74 | Gambia | 0 1000 t | 2023 | — | volatile |
| 74 | Grenada | 0 1000 t | 2023 | — | volatile |
| 74 | Guyana | 0 1000 t | 2023 | — | volatile |
| 74 | Jamaica | 0 1000 t | 2023 | — | volatile |
| 74 | Jordan | 0 1000 t | 2023 | down 100.0% | volatile |
| 74 | Cambodia | 0 1000 t | 2023 | down 100.0% | volatile |
| 74 | Kuwait | 0 1000 t | 2023 | down 100.0% | volatile |
| 74 | Saint Lucia | 0 1000 t | 2023 | — | volatile |
| 74 | Sri Lanka | 0 1000 t | 2023 | up 100.0% | volatile |
| 74 | Luxembourg | 0 1000 t | 2023 | — | volatile |
| 74 | Latvia | 0 1000 t | 2023 | — | volatile |
| 74 | Moldova | 0 1000 t | 2023 | down 100.0% | volatile |
| 74 | Malta | 0 1000 t | 2023 | — | volatile |
| 74 | Myanmar | 0 1000 t | 2023 | — | volatile |
| 74 | Mongolia | 0 1000 t | 2023 | up 100.0% | volatile |
| 74 | Mozambique | 0 1000 t | 2023 | up 100.0% | volatile |
| 74 | Mauritania | 0 1000 t | 2023 | down 100.0% | volatile |
| 74 | Mauritius | 0 1000 t | 2023 | — | volatile |
| 74 | Malawi | 0 1000 t | 2023 | up 100.0% | volatile |
| 74 | Niger | 0 1000 t | 2023 | down 100.0% | volatile |
| 74 | Nigeria | 0 1000 t | 2023 | down 100.0% | volatile |
| 74 | Norway | 0 1000 t | 2023 | — | volatile |
| 74 | New Zealand | 0 1000 t | 2023 | up 100.0% | volatile |
| 74 | Panama | 0 1000 t | 2023 | — | volatile |
| 74 | Peru | 0 1000 t | 2023 | down 100.0% | volatile |
| 74 | Poland | 0 1000 t | 2023 | down 100.0% | volatile |
| 74 | Paraguay | 0 1000 t | 2023 | down 100.0% | volatile |
| 74 | Qatar | 0 1000 t | 2023 | — | volatile |
| 74 | Russia | 0 1000 t | 2023 | up 100.0% | volatile |
| 74 | Rwanda | 0 1000 t | 2023 | — | volatile |
| 74 | El Salvador | 0 1000 t | 2023 | — | flat |
| 74 | Sao Tome and Principe | 0 1000 t | 2023 | — | volatile |
| 74 | Slovakia | 0 1000 t | 2023 | down 100.0% | volatile |
| 74 | Sweden | 0 1000 t | 2023 | — | volatile |
| 74 | Eswatini | 0 1000 t | 2023 | — | volatile |
| 74 | Turkmenistan | 0 1000 t | 2023 | down 100.0% | volatile |
| 74 | East Timor | 0 1000 t | 2023 | down 100.0% | volatile |
| 74 | Trinidad and Tobago | 0 1000 t | 2023 | — | volatile |
| 74 | Uruguay | 0 1000 t | 2023 | down 100.0% | volatile |
| 74 | Saint Vincent and the Grenadines | 0 1000 t | 2023 | — | volatile |
| 74 | Vanuatu | 0 1000 t | 2023 | — | volatile |
| 74 | Samoa | 0 1000 t | 2023 | up 100.0% | flat |
| 74 | Zambia | 0 1000 t | 2023 | — | flat |
| 74 | Timor-Leste | 0 1000 t | 2023 | down 100.0% | volatile |
| 74 | Polynesia | 0 1000 t | 2023 | up 100.0% | volatile |
| 74 | Democratic Republic of the Congo | 0 1000 t | 2023 | — | volatile |
| 74 | Bolivia (Plurinational State of) | 0 1000 t | 2023 | down 100.0% | volatile |
| 74 | Republic of Moldova | 0 1000 t | 2023 | down 100.0% | volatile |
| 74 | Russian Federation | 0 1000 t | 2023 | up 100.0% | volatile |
| 74 | Venezuela (Bolivarian Republic of) | 0 1000 t | 2023 | down 100.0% | volatile |
| 165 | Ethiopia | -1 1000 t | 2023 | down 200.0% | volatile |
| 165 | Maldives | -1 1000 t | 2023 | — | volatile |
| 167 | Kyrgyzstan | -2 1000 t | 2023 | — | volatile |
| 167 | Liberia | -2 1000 t | 2023 | down 300.0% | volatile |
| 167 | Lithuania | -2 1000 t | 2023 | down 166.7% | volatile |
| 167 | Pakistan | -2 1000 t | 2023 | up 60.0% | volatile |
| 167 | Republic of Korea | -2 1000 t | 2023 | unchanged | volatile |
| 172 | Austria | -3 1000 t | 2023 | down 123.1% | volatile |
| 172 | Haiti | -3 1000 t | 2023 | — | volatile |
| 174 | Belarus | -4 1000 t | 2023 | down 200.0% | volatile |
| 174 | Israel | -4 1000 t | 2023 | down 233.3% | volatile |
| 174 | Mexico | -4 1000 t | 2023 | up 87.1% | volatile |
| 174 | Nicaragua | -4 1000 t | 2023 | down 500.0% | volatile |
| 178 | Australia | -5 1000 t | 2023 | up 58.3% | volatile |
| 178 | Switzerland | -5 1000 t | 2023 | down 66.7% | volatile |
| 178 | Denmark | -5 1000 t | 2023 | down 155.6% | volatile |
| 178 | Uganda | -5 1000 t | 2023 | — | volatile |
| 178 | Australia and New Zealand | -5 1000 t | 2023 | up 84.8% | volatile |
| 183 | Oman | -7 1000 t | 2023 | down 333.3% | volatile |
| 183 | Sierra Leone | -7 1000 t | 2023 | — | volatile |
| 185 | Egypt | -8 1000 t | 2023 | down 180.0% | volatile |
| 186 | Dominican Republic | -10 1000 t | 2023 | down 400.0% | volatile |
| 187 | United Republic of Tanzania | -12 1000 t | 2023 | down 200.0% | volatile |
| 188 | Caribbean | -13 1000 t | 2023 | down 1,400.0% | volatile |
| 189 | United States | -30 1000 t | 2023 | — | volatile |
| 190 | Ghana | -52 1000 t | 2023 | down 279.3% | volatile |
| 191 | United Arab Emirates | -58 1000 t | 2023 | down 2,033.3% | volatile |
| 192 | Brazil | -217 1000 t | 2023 | down 189.3% | volatile |
| 193 | Turkey | -387 1000 t | 2023 | down 1,388.5% | volatile |
| 193 | Türkiye | -387 1000 t | 2023 | down 1,388.5% | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- Net Food Importing Developing Countries (NFIDCs) 358 1000 t
- World 350 1000 t
- Africa 342 1000 t
- Western Africa 297 1000 t
- Europe 228 1000 t
- European Union (27) 181 1000 t
- South-Eastern Asia 164 1000 t
- Western Europe 124 1000 t
- Eastern Asia 119 1000 t
- Low Income Food Deficit Countries (LIFDCs) 59 1000 t
- Northern Europe 50 1000 t
- Southern Asia 40 1000 t
- Least Developed Countries (LDCs) 33 1000 t
- Southern Europe 32 1000 t
- Land Locked Developing Countries (LLDCs) 29 1000 t
- Northern Africa 28 1000 t
- Eastern Europe 22 1000 t
- Oceania 16 1000 t
- Central Asia 13 1000 t
- Eastern Africa 12 1000 t
- Small island developing States (SIDS) 8 1000 t
- Middle Africa 3 1000 t
- Southern Africa 2 1000 t
- Northern America -1 1000 t
- Central America -3 1000 t
- United States of America -30 1000 t
- Asia -57 1000 t
- South America -162 1000 t
- Americas -179 1000 t
- Western Asia -393 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.