Rice and products — 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
Rice and products — Residuals is currently reported for 100 countries. The highest value is 843 1000 t in Indonesia; the lowest is -556 1000 t in Belgium.
The median across all reporting countries is 0 1000 t, and the mean is 0.69 1000 t.
The gap between the highest and lowest reporting country is a factor of about 2.
Over the past decade 8 countries rose and 16 fell. The largest increase was in Djibouti (up 520.0%), and the largest decrease in Belgium (down 11,020.0%).
Rice and products — Residuals: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Indonesia | 843 1000 t | 2023 | — | volatile |
| 2 | Djibouti | 279 1000 t | 2023 | up 520.0% | volatile |
| 3 | Venezuela (Bolivarian Republic of) | 239 1000 t | 2023 | down 64.1% | volatile |
| 4 | Ghana | 107 1000 t | 2023 | — | volatile |
| 5 | United States | 94 1000 t | 2023 | — | volatile |
| 6 | United Kingdom | 70 1000 t | 2023 | down 13.6% | volatile |
| 6 | United Kingdom of Great Britain and Northern Ireland | 70 1000 t | 2023 | down 13.6% | volatile |
| 8 | Cote d'Ivoire | 27 1000 t | 2023 | down 53.4% | volatile |
| 8 | Côte d'Ivoire | 27 1000 t | 2023 | down 53.4% | volatile |
| 10 | Guinea-Bissau | 8 1000 t | 2023 | — | volatile |
| 10 | Libya | 8 1000 t | 2023 | — | volatile |
| 12 | Marshall Islands | 2 1000 t | 2023 | — | volatile |
| 12 | Micronesia | 2 1000 t | 2023 | — | volatile |
| 14 | Norway | 1 1000 t | 2023 | — | volatile |
| 14 | East Timor | 1 1000 t | 2023 | down 97.7% | volatile |
| 14 | Saint Vincent and the Grenadines | 1 1000 t | 2023 | — | volatile |
| 14 | Timor-Leste | 1 1000 t | 2023 | down 97.7% | volatile |
| 14 | Netherlands (Kingdom of the) | 1 1000 t | 2023 | down 96.3% | volatile |
| 19 | Angola | 0 1000 t | 2023 | — | volatile |
| 19 | United Arab Emirates | 0 1000 t | 2023 | — | volatile |
| 19 | Argentina | 0 1000 t | 2023 | — | volatile |
| 19 | Antigua and Barbuda | 0 1000 t | 2023 | — | volatile |
| 19 | Bangladesh | 0 1000 t | 2023 | — | volatile |
| 19 | Belize | 0 1000 t | 2023 | — | volatile |
| 19 | Bhutan | 0 1000 t | 2023 | — | volatile |
| 19 | Chile | 0 1000 t | 2023 | down 100.0% | volatile |
| 19 | China | 0 1000 t | 2023 | down 100.0% | volatile |
| 19 | Colombia | 0 1000 t | 2023 | — | volatile |
| 19 | Germany | 0 1000 t | 2023 | — | volatile |
| 19 | Egypt | 0 1000 t | 2023 | — | volatile |
| 19 | Finland | 0 1000 t | 2023 | — | volatile |
| 19 | Guinea | 0 1000 t | 2023 | — | volatile |
| 19 | Greece | 0 1000 t | 2023 | — | volatile |
| 19 | Guyana | 0 1000 t | 2023 | down 100.0% | volatile |
| 19 | India | 0 1000 t | 2023 | up 100.0% | volatile |
| 19 | Iraq | 0 1000 t | 2023 | — | volatile |
| 19 | Italy | 0 1000 t | 2023 | up 100.0% | volatile |
| 19 | Jamaica | 0 1000 t | 2023 | — | volatile |
| 19 | Jordan | 0 1000 t | 2023 | — | volatile |
| 19 | Kenya | 0 1000 t | 2023 | — | volatile |
| 19 | Kuwait | 0 1000 t | 2023 | down 100.0% | volatile |
| 19 | Laos | 0 1000 t | 2023 | — | volatile |
| 19 | Saint Lucia | 0 1000 t | 2023 | — | volatile |
| 19 | Sri Lanka | 0 1000 t | 2023 | — | volatile |
| 19 | Myanmar | 0 1000 t | 2023 | — | volatile |
| 19 | Mozambique | 0 1000 t | 2023 | — | volatile |
| 19 | New Caledonia | 0 1000 t | 2023 | down 100.0% | volatile |
| 19 | Niger | 0 1000 t | 2023 | — | volatile |
| 19 | New Zealand | 0 1000 t | 2023 | — | volatile |
| 19 | Oman | 0 1000 t | 2023 | — | volatile |
| 19 | Pakistan | 0 1000 t | 2023 | — | volatile |
| 19 | Panama | 0 1000 t | 2023 | up 100.0% | volatile |
| 19 | Peru | 0 1000 t | 2023 | — | volatile |
| 19 | Philippines | 0 1000 t | 2023 | — | volatile |
| 19 | Poland | 0 1000 t | 2023 | up 100.0% | volatile |
| 19 | Portugal | 0 1000 t | 2023 | — | volatile |
| 19 | Russia | 0 1000 t | 2023 | — | volatile |
| 19 | Sao Tome and Principe | 0 1000 t | 2023 | — | volatile |
| 19 | Slovakia | 0 1000 t | 2023 | — | volatile |
| 19 | Syria | 0 1000 t | 2023 | — | volatile |
| 19 | Tajikistan | 0 1000 t | 2023 | — | volatile |
| 19 | Ukraine | 0 1000 t | 2023 | — | volatile |
| 19 | Samoa | 0 1000 t | 2023 | — | volatile |
| 19 | Yemen | 0 1000 t | 2023 | — | volatile |
| 19 | South Africa | 0 1000 t | 2023 | up 100.0% | volatile |
| 19 | Zimbabwe | 0 1000 t | 2023 | — | volatile |
| 19 | Melanesia | 0 1000 t | 2023 | down 100.0% | volatile |
| 19 | Polynesia | 0 1000 t | 2023 | — | volatile |
| 19 | Caribbean | 0 1000 t | 2023 | — | volatile |
| 19 | Iran (Islamic Republic of) | 0 1000 t | 2023 | — | volatile |
| 19 | Russian Federation | 0 1000 t | 2023 | — | volatile |
| 19 | Syrian Arab Republic | 0 1000 t | 2023 | — | volatile |
| 19 | Australia and New Zealand | 0 1000 t | 2023 | — | volatile |
| 19 | Lao People's Democratic Republic | 0 1000 t | 2023 | — | volatile |
| 19 | United Republic of Tanzania | 0 1000 t | 2023 | up 100.0% | volatile |
| 19 | China, Macao SAR | 0 1000 t | 2023 | down 100.0% | volatile |
| 171 | France | -1 1000 t | 2023 | — | volatile |
| 171 | Honduras | -1 1000 t | 2023 | — | volatile |
| 171 | Croatia | -1 1000 t | 2023 | — | volatile |
| 171 | Lebanon | -1 1000 t | 2023 | — | volatile |
| 171 | Romania | -1 1000 t | 2023 | — | volatile |
| 171 | Slovenia | -1 1000 t | 2023 | — | volatile |
| 177 | Democratic People's Republic of Korea | -2 1000 t | 2018 | — | volatile |
| 178 | Bulgaria | -3 1000 t | 2023 | — | volatile |
| 178 | Ecuador | -3 1000 t | 2023 | — | volatile |
| 180 | Guatemala | -4 1000 t | 2023 | — | volatile |
| 180 | Republic of Korea | -4 1000 t | 2023 | up 96.5% | volatile |
| 182 | Spain | -6 1000 t | 2023 | — | volatile |
| 182 | Israel | -6 1000 t | 2023 | — | volatile |
| 184 | Madagascar | -8 1000 t | 2023 | — | volatile |
| 185 | Moldova | -15 1000 t | 2023 | — | volatile |
| 185 | Republic of Moldova | -15 1000 t | 2023 | — | volatile |
| 187 | Cambodia | -23 1000 t | 2023 | — | volatile |
| 188 | Vietnam | -48 1000 t | 2023 | — | volatile |
| 188 | Viet Nam | -48 1000 t | 2023 | — | volatile |
| 190 | Canada | -51 1000 t | 2023 | — | volatile |
| 191 | Brazil | -182 1000 t | 2023 | — | volatile |
| 192 | Paraguay | -304 1000 t | 2023 | — | volatile |
| 193 | Mexico | -428 1000 t | 2023 | — | volatile |
| 194 | Belgium | -556 1000 t | 2023 | down 11,020.0% | 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) 1,906 1000 t
- Africa 1,805 1000 t
- Least Developed Countries (LDCs) 1,641 1000 t
- Western Africa 1,526 1000 t
- World 1,410 1000 t
- Low Income Food Deficit Countries (LIFDCs) 1,384 1000 t
- South-Eastern Asia 772 1000 t
- Asia 757 1000 t
- Eastern Africa 272 1000 t
- United States of America 94 1000 t
- Northern Europe 70 1000 t
- Northern America 43 1000 t
- Small island developing States (SIDS) 12 1000 t
- Northern Africa 8 1000 t
- Oceania 2 1000 t
- Central Asia 0 1000 t
- Middle Africa 0 1000 t
- Southern Africa -1 1000 t
- Southern Asia -1 1000 t
- Eastern Asia -7 1000 t
- Western Asia -7 1000 t
- Southern Europe -8 1000 t
- Eastern Europe -20 1000 t
- South America -251 1000 t
- Land Locked Developing Countries (LLDCs) -320 1000 t
- Central America -432 1000 t
- Europe -514 1000 t
- Western Europe -556 1000 t
- European Union (27) -569 1000 t
- Americas -640 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.