Treenuts — 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
Treenuts — Residuals is currently reported for 93 countries. The highest value is 112 1000 t in Burkina Faso; the lowest is -743 1000 t in Ghana.
The median across all reporting countries is 0 1000 t, and the mean is -20.92 1000 t.
Over the past decade 20 countries rose and 8 fell. The largest increase was in Burkina Faso (up 2,900.0%), and the largest decrease in Kyrgyzstan (down 900.0%).
Treenuts — Residuals: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Burkina Faso | 112 1000 t | 2023 | up 2,900.0% | volatile |
| 2 | Uzbekistan | 8 1000 t | 2023 | up 300.0% | volatile |
| 3 | Albania | 0 1000 t | 2023 | — | volatile |
| 3 | Argentina | 0 1000 t | 2023 | — | volatile |
| 3 | Armenia | 0 1000 t | 2023 | — | volatile |
| 3 | Antigua and Barbuda | 0 1000 t | 2023 | — | volatile |
| 3 | Australia | 0 1000 t | 2023 | up 100.0% | volatile |
| 3 | Austria | 0 1000 t | 2023 | — | volatile |
| 3 | Bangladesh | 0 1000 t | 2023 | — | volatile |
| 3 | Belarus | 0 1000 t | 2023 | — | volatile |
| 3 | Chile | 0 1000 t | 2023 | up 100.0% | volatile |
| 3 | China | 0 1000 t | 2023 | — | volatile |
| 3 | Ecuador | 0 1000 t | 2023 | up 100.0% | volatile |
| 3 | Egypt | 0 1000 t | 2023 | — | volatile |
| 3 | Spain | 0 1000 t | 2023 | — | volatile |
| 3 | Ethiopia | 0 1000 t | 2023 | — | volatile |
| 3 | Guinea | 0 1000 t | 2023 | up 100.0% | volatile |
| 3 | Gambia | 0 1000 t | 2023 | up 100.0% | volatile |
| 3 | Greece | 0 1000 t | 2023 | — | volatile |
| 3 | Guatemala | 0 1000 t | 2023 | — | volatile |
| 3 | Hungary | 0 1000 t | 2023 | — | volatile |
| 3 | Jamaica | 0 1000 t | 2023 | — | volatile |
| 3 | Jordan | 0 1000 t | 2023 | — | volatile |
| 3 | Kuwait | 0 1000 t | 2023 | — | volatile |
| 3 | Laos | 0 1000 t | 2023 | — | volatile |
| 3 | Luxembourg | 0 1000 t | 2023 | up 100.0% | volatile |
| 3 | Moldova | 0 1000 t | 2023 | up 100.0% | volatile |
| 3 | Malaysia | 0 1000 t | 2023 | up 100.0% | volatile |
| 3 | Nicaragua | 0 1000 t | 2023 | — | volatile |
| 3 | Pakistan | 0 1000 t | 2023 | up 100.0% | volatile |
| 3 | Panama | 0 1000 t | 2023 | — | volatile |
| 3 | Poland | 0 1000 t | 2023 | — | volatile |
| 3 | Portugal | 0 1000 t | 2023 | — | volatile |
| 3 | Rwanda | 0 1000 t | 2023 | — | volatile |
| 3 | Sierra Leone | 0 1000 t | 2023 | — | volatile |
| 3 | Sweden | 0 1000 t | 2023 | — | volatile |
| 3 | Tajikistan | 0 1000 t | 2023 | — | volatile |
| 3 | Tunisia | 0 1000 t | 2023 | up 100.0% | volatile |
| 3 | Turkey | 0 1000 t | 2023 | — | volatile |
| 3 | Uganda | 0 1000 t | 2023 | — | volatile |
| 3 | Vietnam | 0 1000 t | 2023 | up 100.0% | volatile |
| 3 | Yemen | 0 1000 t | 2023 | — | volatile |
| 3 | China, Hong Kong SAR | 0 1000 t | 2023 | — | volatile |
| 3 | Republic of Moldova | 0 1000 t | 2023 | up 100.0% | volatile |
| 3 | Viet Nam | 0 1000 t | 2023 | up 100.0% | volatile |
| 3 | Türkiye | 0 1000 t | 2023 | — | volatile |
| 3 | Australia and New Zealand | 0 1000 t | 2023 | up 100.0% | volatile |
| 3 | Lao People's Democratic Republic | 0 1000 t | 2023 | — | volatile |
| 3 | Democratic People's Republic of Korea | 0 1000 t | 2018 | — | volatile |
| 151 | Djibouti | -1 1000 t | 2023 | — | volatile |
| 151 | Georgia | -1 1000 t | 2023 | — | volatile |
| 151 | Kazakhstan | -1 1000 t | 2023 | — | volatile |
| 151 | Qatar | -1 1000 t | 2023 | — | volatile |
| 151 | Thailand | -1 1000 t | 2023 | up 50.0% | volatile |
| 151 | East Timor | -1 1000 t | 2023 | — | volatile |
| 151 | Zambia | -1 1000 t | 2023 | — | volatile |
| 151 | Timor-Leste | -1 1000 t | 2023 | — | volatile |
| 151 | Democratic Republic of the Congo | -1 1000 t | 2023 | — | volatile |
| 151 | United Republic of Tanzania | -1 1000 t | 2023 | — | volatile |
| 161 | Bulgaria | -2 1000 t | 2023 | — | volatile |
| 162 | Belgium | -3 1000 t | 2023 | down 200.0% | volatile |
| 162 | France | -3 1000 t | 2023 | — | volatile |
| 162 | Guinea-Bissau | -3 1000 t | 2023 | — | volatile |
| 162 | Guyana | -3 1000 t | 2023 | — | volatile |
| 162 | Mozambique | -3 1000 t | 2023 | down 200.0% | volatile |
| 162 | Syria | -3 1000 t | 2023 | — | volatile |
| 162 | Syrian Arab Republic | -3 1000 t | 2023 | — | volatile |
| 169 | Afghanistan | -4 1000 t | 2023 | — | volatile |
| 169 | Myanmar | -4 1000 t | 2023 | — | volatile |
| 169 | Eswatini | -4 1000 t | 2023 | — | volatile |
| 169 | Uruguay | -4 1000 t | 2023 | up 42.9% | volatile |
| 173 | United Arab Emirates | -5 1000 t | 2023 | — | volatile |
| 174 | Mexico | -7 1000 t | 2023 | — | volatile |
| 174 | Iran (Islamic Republic of) | -7 1000 t | 2023 | down 250.0% | volatile |
| 176 | Mongolia | -8 1000 t | 2023 | — | volatile |
| 177 | Russia | -10 1000 t | 2023 | down 25.0% | volatile |
| 177 | Russian Federation | -10 1000 t | 2023 | down 25.0% | volatile |
| 179 | Bolivia (Plurinational State of) | -13 1000 t | 2023 | down 18.2% | falling |
| 180 | Cote d'Ivoire | -16 1000 t | 2023 | — | volatile |
| 180 | Cambodia | -16 1000 t | 2023 | — | volatile |
| 180 | Côte d'Ivoire | -16 1000 t | 2023 | — | volatile |
| 183 | Nigeria | -20 1000 t | 2023 | — | volatile |
| 184 | Israel | -21 1000 t | 2023 | up 53.3% | volatile |
| 185 | South Africa | -25 1000 t | 2023 | — | volatile |
| 186 | Kyrgyzstan | -40 1000 t | 2023 | down 900.0% | volatile |
| 187 | Dominican Republic | -42 1000 t | 2023 | — | volatile |
| 187 | Caribbean | -42 1000 t | 2023 | — | volatile |
| 189 | Senegal | -73 1000 t | 2023 | — | volatile |
| 190 | Sri Lanka | -92 1000 t | 2023 | — | volatile |
| 191 | Indonesia | -99 1000 t | 2023 | up 12.4% | falling |
| 192 | Netherlands (Kingdom of the) | -140 1000 t | 2023 | — | volatile |
| 193 | United States | -572 1000 t | 2023 | — | volatile |
| 194 | Ghana | -743 1000 t | 2023 | down 101.9% | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- Land Locked Developing Countries (LLDCs) 44 1000 t
- Oceania 0 1000 t
- Northern Africa 0 1000 t
- Northern Europe -1 1000 t
- Southern Europe -1 1000 t
- Middle Africa -1 1000 t
- Least Developed Countries (LDCs) -5 1000 t
- Eastern Africa -7 1000 t
- Central America -8 1000 t
- Eastern Asia -9 1000 t
- Eastern Europe -12 1000 t
- Low Income Food Deficit Countries (LIFDCs) -18 1000 t
- South America -22 1000 t
- Southern Africa -29 1000 t
- Western Asia -30 1000 t
- Central Asia -33 1000 t
- Small island developing States (SIDS) -50 1000 t
- Southern Asia -103 1000 t
- South-Eastern Asia -121 1000 t
- Western Europe -146 1000 t
- European Union (27) -148 1000 t
- Europe -159 1000 t
- Net Food Importing Developing Countries (NFIDCs) -168 1000 t
- Asia -295 1000 t
- Northern America -572 1000 t
- United States of America -572 1000 t
- Americas -644 1000 t
- Western Africa -752 1000 t
- Africa -789 1000 t
- World -1,886 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.