Coconuts - Incl Copra — 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
Coconuts - Incl Copra — Stock Variation is currently reported for 117 countries. The highest value is 170 1000 t in Papua New Guinea; the lowest is -30 1000 t in Indonesia.
The median across all reporting countries is 0 1000 t, and the mean is 4.54 1000 t.
The gap between the highest and lowest reporting country is a factor of about 6.
Over the past decade 40 countries rose and 29 fell. The largest increase was in Melanesia (up 2,633.3%), and the largest decrease in India (down 933.3%).
Coconuts - Incl Copra — Stock Variation: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Papua New Guinea | 170 1000 t | 2023 | — | volatile |
| 2 | Melanesia | 164 1000 t | 2023 | up 2,633.3% | volatile |
| 3 | Sri Lanka | 96 1000 t | 2023 | down 17.2% | volatile |
| 4 | Bangladesh | 22 1000 t | 2023 | up 340.0% | volatile |
| 5 | Caribbean | 21 1000 t | 2023 | up 250.0% | volatile |
| 6 | Jamaica | 19 1000 t | 2023 | up 35.7% | volatile |
| 6 | Thailand | 19 1000 t | 2023 | up 218.8% | volatile |
| 8 | United States | 17 1000 t | 2023 | — | volatile |
| 9 | Mexico | 13 1000 t | 2023 | up 186.7% | volatile |
| 10 | Nigeria | 8 1000 t | 2023 | down 38.5% | volatile |
| 11 | Russia | 7 1000 t | 2023 | up 600.0% | volatile |
| 11 | Russian Federation | 7 1000 t | 2023 | up 600.0% | volatile |
| 13 | United Kingdom | 5 1000 t | 2023 | — | volatile |
| 13 | United Kingdom of Great Britain and Northern Ireland | 5 1000 t | 2023 | — | volatile |
| 15 | Belgium | 4 1000 t | 2023 | — | volatile |
| 15 | Brazil | 4 1000 t | 2023 | down 55.6% | volatile |
| 15 | Cote d'Ivoire | 4 1000 t | 2023 | down 88.6% | volatile |
| 15 | Côte d'Ivoire | 4 1000 t | 2023 | down 88.6% | volatile |
| 19 | Guinea | 3 1000 t | 2023 | — | volatile |
| 19 | United Republic of Tanzania | 3 1000 t | 2023 | up 123.1% | volatile |
| 21 | Austria | 2 1000 t | 2023 | — | volatile |
| 21 | Ghana | 2 1000 t | 2023 | up 300.0% | volatile |
| 21 | Nicaragua | 2 1000 t | 2023 | — | volatile |
| 21 | Saudi Arabia | 2 1000 t | 2023 | — | volatile |
| 21 | Trinidad and Tobago | 2 1000 t | 2023 | — | volatile |
| 26 | Switzerland | 1 1000 t | 2023 | — | rising |
| 26 | Colombia | 1 1000 t | 2023 | — | volatile |
| 26 | Czechia | 1 1000 t | 2023 | unchanged | volatile |
| 26 | Spain | 1 1000 t | 2023 | up 200.0% | volatile |
| 26 | Portugal | 1 1000 t | 2023 | up 200.0% | volatile |
| 26 | Sweden | 1 1000 t | 2023 | — | volatile |
| 26 | Ukraine | 1 1000 t | 2023 | — | volatile |
| 26 | Polynesia | 1 1000 t | 2023 | up 112.5% | volatile |
| 34 | Angola | 0 1000 t | 2023 | — | flat |
| 34 | Argentina | 0 1000 t | 2023 | up 100.0% | volatile |
| 34 | Antigua and Barbuda | 0 1000 t | 2023 | — | volatile |
| 34 | Azerbaijan | 0 1000 t | 2023 | — | volatile |
| 34 | Burkina Faso | 0 1000 t | 2023 | up 100.0% | volatile |
| 34 | Bulgaria | 0 1000 t | 2023 | down 100.0% | volatile |
| 34 | Bahrain | 0 1000 t | 2023 | — | volatile |
| 34 | Canada | 0 1000 t | 2023 | down 100.0% | volatile |
| 34 | Chile | 0 1000 t | 2023 | up 100.0% | flat |
| 34 | China | 0 1000 t | 2023 | down 100.0% | volatile |
| 34 | Germany | 0 1000 t | 2023 | — | volatile |
| 34 | Denmark | 0 1000 t | 2023 | down 100.0% | volatile |
| 34 | Dominican Republic | 0 1000 t | 2023 | up 100.0% | volatile |
| 34 | Algeria | 0 1000 t | 2023 | up 100.0% | volatile |
| 34 | Ecuador | 0 1000 t | 2023 | — | volatile |
| 34 | Egypt | 0 1000 t | 2023 | down 100.0% | volatile |
| 34 | Fiji | 0 1000 t | 2023 | down 100.0% | volatile |
| 34 | France | 0 1000 t | 2023 | up 100.0% | volatile |
| 34 | Greece | 0 1000 t | 2023 | down 100.0% | volatile |
| 34 | Guatemala | 0 1000 t | 2023 | — | volatile |
| 34 | Guyana | 0 1000 t | 2023 | up 100.0% | volatile |
| 34 | Honduras | 0 1000 t | 2023 | — | flat |
| 34 | Croatia | 0 1000 t | 2023 | — | volatile |
| 34 | Hungary | 0 1000 t | 2023 | down 100.0% | volatile |
| 34 | Ireland | 0 1000 t | 2023 | — | volatile |
| 34 | Iraq | 0 1000 t | 2023 | up 100.0% | volatile |
| 34 | Israel | 0 1000 t | 2023 | down 100.0% | volatile |
| 34 | Italy | 0 1000 t | 2023 | — | volatile |
| 34 | Jordan | 0 1000 t | 2023 | up 100.0% | flat |
| 34 | Kenya | 0 1000 t | 2023 | down 100.0% | flat |
| 34 | Cambodia | 0 1000 t | 2023 | down 100.0% | flat |
| 34 | Kiribati | 0 1000 t | 2023 | down 100.0% | volatile |
| 34 | Kuwait | 0 1000 t | 2023 | — | volatile |
| 34 | Lebanon | 0 1000 t | 2023 | up 100.0% | volatile |
| 34 | Saint Lucia | 0 1000 t | 2023 | — | volatile |
| 34 | Lithuania | 0 1000 t | 2023 | — | volatile |
| 34 | Morocco | 0 1000 t | 2023 | — | volatile |
| 34 | Madagascar | 0 1000 t | 2023 | up 100.0% | volatile |
| 34 | North Macedonia | 0 1000 t | 2023 | — | volatile |
| 34 | Mozambique | 0 1000 t | 2023 | — | volatile |
| 34 | Mauritius | 0 1000 t | 2023 | — | volatile |
| 34 | Malaysia | 0 1000 t | 2023 | up 100.0% | volatile |
| 34 | Namibia | 0 1000 t | 2023 | — | volatile |
| 34 | New Caledonia | 0 1000 t | 2023 | — | volatile |
| 34 | Niger | 0 1000 t | 2023 | down 100.0% | flat |
| 34 | Nepal | 0 1000 t | 2023 | down 100.0% | flat |
| 34 | New Zealand | 0 1000 t | 2023 | up 100.0% | volatile |
| 34 | Oman | 0 1000 t | 2023 | down 100.0% | volatile |
| 34 | Philippines | 0 1000 t | 2023 | up 100.0% | volatile |
| 34 | Poland | 0 1000 t | 2023 | up 100.0% | volatile |
| 34 | French Polynesia | 0 1000 t | 2023 | up 100.0% | volatile |
| 34 | Qatar | 0 1000 t | 2023 | — | volatile |
| 34 | Romania | 0 1000 t | 2023 | — | volatile |
| 34 | Senegal | 0 1000 t | 2023 | down 100.0% | volatile |
| 34 | Serbia | 0 1000 t | 2023 | up 100.0% | volatile |
| 34 | Sao Tome and Principe | 0 1000 t | 2023 | — | volatile |
| 34 | Slovakia | 0 1000 t | 2023 | down 100.0% | volatile |
| 34 | Syria | 0 1000 t | 2023 | up 100.0% | volatile |
| 34 | Tonga | 0 1000 t | 2023 | — | volatile |
| 34 | Turkey | 0 1000 t | 2023 | up 100.0% | volatile |
| 34 | Uzbekistan | 0 1000 t | 2023 | — | volatile |
| 34 | Vietnam | 0 1000 t | 2023 | down 100.0% | volatile |
| 34 | Vanuatu | 0 1000 t | 2023 | up 100.0% | volatile |
| 34 | Samoa | 0 1000 t | 2023 | up 100.0% | volatile |
| 34 | Yemen | 0 1000 t | 2023 | — | volatile |
| 34 | South Africa | 0 1000 t | 2023 | up 100.0% | volatile |
| 34 | Micronesia | 0 1000 t | 2023 | down 100.0% | volatile |
| 34 | China, Hong Kong SAR | 0 1000 t | 2023 | — | volatile |
| 34 | Iran (Islamic Republic of) | 0 1000 t | 2023 | up 100.0% | volatile |
| 34 | Republic of Korea | 0 1000 t | 2023 | — | volatile |
| 34 | Syrian Arab Republic | 0 1000 t | 2023 | up 100.0% | volatile |
| 34 | Viet Nam | 0 1000 t | 2023 | down 100.0% | volatile |
| 34 | Türkiye | 0 1000 t | 2023 | up 100.0% | volatile |
| 34 | China, mainland | 0 1000 t | 2023 | down 100.0% | volatile |
| 34 | China, Taiwan Province of | 0 1000 t | 2023 | — | volatile |
| 34 | Netherlands (Kingdom of the) | 0 1000 t | 2023 | — | volatile |
| 175 | United Arab Emirates | -1 1000 t | 2023 | up 75.0% | volatile |
| 176 | Australia | -2 1000 t | 2023 | — | volatile |
| 176 | Australia and New Zealand | -2 1000 t | 2023 | unchanged | volatile |
| 178 | Solomon Islands | -6 1000 t | 2023 | down 185.7% | volatile |
| 179 | Venezuela (Bolivarian Republic of) | -7 1000 t | 2023 | — | volatile |
| 180 | Pakistan | -9 1000 t | 2023 | down 156.2% | volatile |
| 181 | India | -25 1000 t | 2023 | down 933.3% | volatile |
| 182 | Indonesia | -30 1000 t | 2023 | up 97.5% | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- World 333 1000 t
- Small island developing States (SIDS) 186 1000 t
- Oceania 163 1000 t
- Net Food Importing Developing Countries (NFIDCs) 129 1000 t
- Southern Asia 84 1000 t
- Asia 75 1000 t
- Americas 51 1000 t
- Europe 24 1000 t
- Least Developed Countries (LDCs) 22 1000 t
- Africa 21 1000 t
- Western Africa 18 1000 t
- Northern America 17 1000 t
- United States of America 17 1000 t
- Central America 14 1000 t
- European Union (27) 11 1000 t
- Eastern Europe 9 1000 t
- Low Income Food Deficit Countries (LIFDCs) 8 1000 t
- Western Europe 7 1000 t
- Northern Europe 6 1000 t
- Eastern Africa 3 1000 t
- Southern Europe 3 1000 t
- Western Asia 1 1000 t
- Land Locked Developing Countries (LLDCs) 1 1000 t
- Central Asia 0 1000 t
- Northern Africa 0 1000 t
- Southern Africa 0 1000 t
- Middle Africa 0 1000 t
- Eastern Asia 0 1000 t
- South America -1 1000 t
- South-Eastern Asia -11 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.