Rice and products — 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...
Countries reporting
181
Highest
10,495 1000 t
India
Lowest
-5,530 1000 t
China
Median
0 1000 t
Years covered
14
2010–2023
Data points
3,042
What the numbers show
Rice and products — Stock Variation is currently reported for 181 countries. The highest value is 10,495 1000 t in India; the lowest is -5,530 1000 t in China.
The median across all reporting countries is 0 1000 t, and the mean is 49.23 1000 t.
The gap between the highest and lowest reporting country is a factor of about 2.
Over the past decade 69 countries rose and 67 fell. The largest increase was in Democratic Republic of the Congo (up 5,600.0%), and the largest decrease in Angola (down 1,225.0%).
Rice and products — Stock Variation: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | India | 10,495 1000 t | 2023 | up 359.3% | volatile |
| 2 | Pakistan | 5,146 1000 t | 2023 | up 295.7% | volatile |
| 3 | Vietnam | 1,907 1000 t | 2023 | up 317.7% | volatile |
| 3 | Viet Nam | 1,907 1000 t | 2023 | up 317.7% | volatile |
| 5 | United States | 1,627 1000 t | 2023 | up 3,967.5% | volatile |
| 6 | Myanmar | 1,356 1000 t | 2023 | up 700.0% | volatile |
| 7 | Indonesia | 883 1000 t | 2023 | down 73.1% | volatile |
| 8 | Bangladesh | 475 1000 t | 2023 | up 17.9% | volatile |
| 9 | Iran (Islamic Republic of) | 371 1000 t | 2023 | down 75.1% | volatile |
| 10 | Philippines | 344 1000 t | 2023 | up 291.1% | volatile |
| 11 | Senegal | 320 1000 t | 2023 | up 44.8% | volatile |
| 12 | Liberia | 299 1000 t | 2023 | up 3,090.0% | volatile |
| 13 | Burkina Faso | 256 1000 t | 2023 | up 24.9% | volatile |
| 14 | Guinea | 252 1000 t | 2023 | up 863.6% | volatile |
| 15 | Turkey | 246 1000 t | 2023 | up 192.9% | volatile |
| 15 | Türkiye | 246 1000 t | 2023 | up 192.9% | volatile |
| 17 | Brazil | 171 1000 t | 2023 | up 2,542.9% | volatile |
| 18 | Ecuador | 127 1000 t | 2023 | up 214.4% | volatile |
| 19 | Democratic Republic of the Congo | 114 1000 t | 2023 | up 5,600.0% | volatile |
| 20 | Mauritania | 109 1000 t | 2023 | up 202.8% | volatile |
| 21 | Sierra Leone | 101 1000 t | 2023 | down 57.6% | volatile |
| 22 | Gambia | 97 1000 t | 2023 | up 306.4% | volatile |
| 23 | Cambodia | 82 1000 t | 2023 | down 58.2% | volatile |
| 23 | Netherlands (Kingdom of the) | 82 1000 t | 2023 | — | volatile |
| 25 | United Republic of Tanzania | 74 1000 t | 2023 | down 86.4% | volatile |
| 26 | Portugal | 67 1000 t | 2023 | up 1,440.0% | volatile |
| 27 | Panama | 66 1000 t | 2023 | up 273.7% | volatile |
| 28 | Saudi Arabia | 65 1000 t | 2023 | down 72.0% | volatile |
| 29 | Zimbabwe | 60 1000 t | 2023 | up 850.0% | volatile |
| 30 | Cote d'Ivoire | 50 1000 t | 2023 | up 114.0% | volatile |
| 30 | Côte d'Ivoire | 50 1000 t | 2023 | up 114.0% | volatile |
| 32 | Guyana | 46 1000 t | 2023 | up 100.0% | volatile |
| 33 | Uzbekistan | 41 1000 t | 2023 | up 17.1% | volatile |
| 34 | Oman | 40 1000 t | 2023 | up 42.9% | volatile |
| 35 | Morocco | 26 1000 t | 2023 | — | volatile |
| 36 | Italy | 22 1000 t | 2023 | up 117.7% | volatile |
| 37 | Bhutan | 21 1000 t | 2023 | — | volatile |
| 38 | Costa Rica | 17 1000 t | 2023 | up 666.7% | volatile |
| 38 | Eswatini | 17 1000 t | 2023 | up 1,600.0% | volatile |
| 40 | France | 16 1000 t | 2023 | down 59.0% | volatile |
| 41 | Afghanistan | 15 1000 t | 2023 | up 400.0% | volatile |
| 41 | Algeria | 15 1000 t | 2023 | down 51.6% | volatile |
| 41 | Trinidad and Tobago | 15 1000 t | 2023 | up 1,400.0% | volatile |
| 44 | United Kingdom | 12 1000 t | 2023 | — | volatile |
| 44 | United Kingdom of Great Britain and Northern Ireland | 12 1000 t | 2023 | — | volatile |
| 46 | Kuwait | 11 1000 t | 2023 | — | volatile |
| 46 | Tajikistan | 11 1000 t | 2023 | down 8.3% | volatile |
| 48 | Zambia | 10 1000 t | 2023 | unchanged | volatile |
| 49 | Fiji | 9 1000 t | 2023 | up 800.0% | volatile |
| 50 | Ireland | 8 1000 t | 2023 | — | volatile |
| 50 | Sweden | 8 1000 t | 2023 | — | volatile |
| 50 | South Africa | 8 1000 t | 2023 | down 97.9% | volatile |
| 53 | Azerbaijan | 7 1000 t | 2023 | up 800.0% | volatile |
| 53 | Czechia | 7 1000 t | 2023 | — | volatile |
| 55 | Botswana | 6 1000 t | 2023 | up 175.0% | volatile |
| 55 | Jamaica | 6 1000 t | 2023 | up 131.6% | volatile |
| 55 | East Timor | 6 1000 t | 2023 | down 78.6% | volatile |
| 55 | Timor-Leste | 6 1000 t | 2023 | down 78.6% | volatile |
| 55 | Cabo Verde | 6 1000 t | 2023 | — | volatile |
| 60 | Austria | 5 1000 t | 2023 | up 350.0% | volatile |
| 61 | Guatemala | 4 1000 t | 2023 | up 233.3% | volatile |
| 61 | Kiribati | 4 1000 t | 2023 | up 500.0% | volatile |
| 63 | Norway | 3 1000 t | 2023 | up 400.0% | volatile |
| 63 | Slovenia | 3 1000 t | 2023 | up 400.0% | volatile |
| 63 | Turkmenistan | 3 1000 t | 2023 | down 50.0% | volatile |
| 66 | Belize | 2 1000 t | 2023 | down 50.0% | volatile |
| 66 | Chile | 2 1000 t | 2023 | down 50.0% | volatile |
| 66 | Spain | 2 1000 t | 2023 | up 103.8% | volatile |
| 66 | Croatia | 2 1000 t | 2023 | — | volatile |
| 66 | Lithuania | 2 1000 t | 2023 | — | volatile |
| 66 | Mongolia | 2 1000 t | 2023 | down 71.4% | volatile |
| 66 | Micronesia | 2 1000 t | 2023 | up 300.0% | volatile |
| 73 | Switzerland | 1 1000 t | 2023 | — | volatile |
| 73 | Cyprus | 1 1000 t | 2023 | — | volatile |
| 73 | Finland | 1 1000 t | 2023 | — | volatile |
| 73 | Kyrgyzstan | 1 1000 t | 2023 | down 90.9% | volatile |
| 73 | Namibia | 1 1000 t | 2023 | — | volatile |
| 73 | Venezuela (Bolivarian Republic of) | 1 1000 t | 2023 | — | volatile |
| 79 | Albania | 0 1000 t | 2023 | — | volatile |
| 79 | Argentina | 0 1000 t | 2023 | down 100.0% | volatile |
| 79 | Armenia | 0 1000 t | 2023 | down 100.0% | volatile |
| 79 | Antigua and Barbuda | 0 1000 t | 2023 | down 100.0% | volatile |
| 79 | Bulgaria | 0 1000 t | 2023 | — | volatile |
| 79 | Bahamas | 0 1000 t | 2023 | — | volatile |
| 79 | Bosnia and Herzegovina | 0 1000 t | 2023 | — | volatile |
| 79 | Belarus | 0 1000 t | 2023 | down 100.0% | volatile |
| 79 | Canada | 0 1000 t | 2023 | down 100.0% | volatile |
| 79 | Comoros | 0 1000 t | 2023 | up 100.0% | volatile |
| 79 | Cuba | 0 1000 t | 2019 | up 100.0% | volatile |
| 79 | Germany | 0 1000 t | 2023 | down 100.0% | volatile |
| 79 | Djibouti | 0 1000 t | 2023 | — | volatile |
| 79 | Denmark | 0 1000 t | 2023 | down 100.0% | volatile |
| 79 | Estonia | 0 1000 t | 2023 | — | volatile |
| 79 | Gabon | 0 1000 t | 2023 | down 100.0% | volatile |
| 79 | Georgia | 0 1000 t | 2023 | down 100.0% | volatile |
| 79 | Guinea-Bissau | 0 1000 t | 2023 | down 100.0% | volatile |
| 79 | Greece | 0 1000 t | 2023 | down 100.0% | volatile |
| 79 | Honduras | 0 1000 t | 2023 | up 100.0% | volatile |
| 79 | Hungary | 0 1000 t | 2023 | up 100.0% | volatile |
| 79 | Kenya | 0 1000 t | 2023 | down 100.0% | volatile |
| 79 | Lebanon | 0 1000 t | 2023 | up 100.0% | volatile |
| 79 | Saint Lucia | 0 1000 t | 2023 | up 100.0% | flat |
| 79 | Lesotho | 0 1000 t | 2023 | up 100.0% | volatile |
| 79 | Latvia | 0 1000 t | 2023 | — | volatile |
| 79 | North Macedonia | 0 1000 t | 2023 | — | volatile |
| 79 | Montenegro | 0 1000 t | 2023 | — | volatile |
| 79 | New Caledonia | 0 1000 t | 2023 | — | volatile |
| 79 | Nicaragua | 0 1000 t | 2023 | up 100.0% | volatile |
| 79 | Nepal | 0 1000 t | 2023 | up 100.0% | volatile |
| 79 | New Zealand | 0 1000 t | 2023 | — | volatile |
| 79 | Poland | 0 1000 t | 2023 | up 100.0% | volatile |
| 79 | Romania | 0 1000 t | 2023 | up 100.0% | volatile |
| 79 | Rwanda | 0 1000 t | 2023 | down 100.0% | volatile |
| 79 | Slovakia | 0 1000 t | 2023 | down 100.0% | volatile |
| 79 | Seychelles | 0 1000 t | 2023 | — | volatile |
| 79 | Tonga | 0 1000 t | 2023 | — | volatile |
| 79 | Tunisia | 0 1000 t | 2023 | up 100.0% | volatile |
| 79 | Ukraine | 0 1000 t | 2023 | down 100.0% | volatile |
| 79 | Saint Vincent and the Grenadines | 0 1000 t | 2023 | down 100.0% | volatile |
| 79 | Vanuatu | 0 1000 t | 2023 | — | volatile |
| 79 | Yemen | 0 1000 t | 2023 | down 100.0% | volatile |
| 79 | Bolivia (Plurinational State of) | 0 1000 t | 2023 | down 100.0% | volatile |
| 79 | China, Hong Kong SAR | 0 1000 t | 2023 | — | flat |
| 79 | China, Macao SAR | 0 1000 t | 2023 | down 100.0% | volatile |
| 138 | Mauritius | -1 1000 t | 2023 | up 66.7% | volatile |
| 138 | Nigeria | -1 1000 t | 2023 | — | volatile |
| 138 | French Polynesia | -1 1000 t | 2023 | — | volatile |
| 138 | Sao Tome and Principe | -1 1000 t | 2023 | — | volatile |
| 138 | Micronesia (Federated States of) | -1 1000 t | 2023 | — | volatile |
| 143 | Maldives | -2 1000 t | 2023 | down 100.0% | volatile |
| 144 | Barbados | -3 1000 t | 2023 | — | volatile |
| 144 | Samoa | -3 1000 t | 2023 | down 250.0% | volatile |
| 146 | Polynesia | -4 1000 t | 2023 | down 300.0% | volatile |
| 147 | Belgium | -5 1000 t | 2023 | up 82.1% | volatile |
| 147 | El Salvador | -5 1000 t | 2023 | — | volatile |
| 149 | Suriname | -6 1000 t | 2023 | down 142.9% | volatile |
| 150 | Bahrain | -11 1000 t | 2023 | — | volatile |
| 150 | Solomon Islands | -11 1000 t | 2023 | down 222.2% | volatile |
| 152 | Dominican Republic | -15 1000 t | 2023 | up 79.2% | volatile |
| 153 | Malawi | -17 1000 t | 2023 | down 221.4% | volatile |
| 154 | Jordan | -25 1000 t | 2023 | — | flat |
| 154 | Libya | -25 1000 t | 2023 | down 125.3% | volatile |
| 156 | Kazakhstan | -27 1000 t | 2023 | down 280.0% | volatile |
| 156 | Niger | -27 1000 t | 2023 | down 121.8% | volatile |
| 158 | Haiti | -30 1000 t | 2023 | up 9.1% | volatile |
| 159 | Congo | -32 1000 t | 2023 | up 59.0% | volatile |
| 160 | Laos | -46 1000 t | 2023 | down 155.4% | volatile |
| 160 | Mexico | -46 1000 t | 2023 | down 21.1% | volatile |
| 160 | Lao People's Democratic Republic | -46 1000 t | 2023 | down 155.4% | volatile |
| 163 | Paraguay | -47 1000 t | 2023 | down 571.4% | volatile |
| 164 | Papua New Guinea | -48 1000 t | 2023 | up 47.8% | volatile |
| 165 | Melanesia | -50 1000 t | 2023 | up 39.0% | volatile |
| 166 | Russia | -54 1000 t | 2023 | — | volatile |
| 166 | Russian Federation | -54 1000 t | 2023 | — | volatile |
| 168 | Peru | -57 1000 t | 2023 | down 58.3% | volatile |
| 168 | Qatar | -57 1000 t | 2023 | — | volatile |
| 170 | Israel | -58 1000 t | 2023 | down 163.0% | volatile |
| 171 | Colombia | -64 1000 t | 2023 | up 9.9% | volatile |
| 172 | Ghana | -69 1000 t | 2023 | down 134.0% | volatile |
| 173 | Australia | -71 1000 t | 2023 | down 244.9% | volatile |
| 173 | Syria | -71 1000 t | 2023 | down 187.7% | volatile |
| 173 | Syrian Arab Republic | -71 1000 t | 2023 | down 187.7% | volatile |
| 173 | Australia and New Zealand | -71 1000 t | 2023 | down 244.9% | volatile |
| 177 | Madagascar | -73 1000 t | 2023 | up 23.2% | volatile |
| 178 | Malaysia | -81 1000 t | 2023 | up 33.6% | volatile |
| 179 | Angola | -90 1000 t | 2023 | down 1,225.0% | volatile |
| 180 | Cameroon | -92 1000 t | 2023 | down 134.6% | volatile |
| 181 | Iraq | -93 1000 t | 2023 | down 113.0% | volatile |
| 182 | Egypt | -133 1000 t | 2023 | up 50.2% | volatile |
| 183 | Uruguay | -146 1000 t | 2023 | down 117.9% | volatile |
| 184 | Sri Lanka | -149 1000 t | 2023 | down 144.7% | volatile |
| 185 | China, Taiwan Province of | -157 1000 t | 2023 | down 170.7% | volatile |
| 186 | Mozambique | -213 1000 t | 2023 | down 301.9% | volatile |
| 187 | Caribbean | -225 1000 t | 2023 | up 0.9% | volatile |
| 188 | Republic of Korea | -246 1000 t | 2023 | up 60.8% | volatile |
| 189 | Ethiopia | -248 1000 t | 2023 | down 427.7% | volatile |
| 190 | United Arab Emirates | -254 1000 t | 2023 | — | volatile |
| 191 | Democratic People's Republic of Korea | -522 1000 t | 2018 | up 10.8% | falling |
| 192 | Thailand | -4,143 1000 t | 2023 | down 193.0% | volatile |
| 193 | China, mainland | -5,373 1000 t | 2023 | down 145.4% | volatile |
| 194 | China | -5,530 1000 t | 2023 | down 146.9% | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- Southern Asia 16,372 1000 t
- World 13,538 1000 t
- Asia 11,103 1000 t
- Net Food Importing Developing Countries (NFIDCs) 7,623 1000 t
- Least Developed Countries (LDCs) 2,922 1000 t
- Western Africa 1,647 1000 t
- Northern America 1,627 1000 t
- United States of America 1,627 1000 t
- Americas 1,467 1000 t
- Low Income Food Deficit Countries (LIFDCs) 1,062 1000 t
- Africa 909 1000 t
- Land Locked Developing Countries (LLDCs) 606 1000 t
- South-Eastern Asia 308 1000 t
- European Union (27) 218 1000 t
- Europe 181 1000 t
- Western Europe 99 1000 t
- Southern Europe 96 1000 t
- Central America 38 1000 t
- Southern Africa 33 1000 t
- Northern Europe 33 1000 t
- Central Asia 29 1000 t
- South America 27 1000 t
- Eastern Europe -47 1000 t
- Northern Africa -116 1000 t
- Oceania -123 1000 t
- Middle Africa -153 1000 t
- Western Asia -209 1000 t
- Small island developing States (SIDS) -227 1000 t
- Eastern Africa -502 1000 t
- Eastern Asia -5,398 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.