Honey — 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
Honey — Stock Variation is currently reported for 86 countries. The highest value is 14 1000 t in China; the lowest is -4 1000 t in Argentina.
The median across all reporting countries is 0 1000 t, and the mean is 0.8837 1000 t.
The gap between the highest and lowest reporting country is a factor of about 4.
Over the past decade 22 countries rose and 22 fell. The largest increase was in Morocco (up 300.0%), and the largest decrease in Russia (down 150.0%).
Honey — Stock Variation: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | China | 14 1000 t | 2023 | up 216.7% | volatile |
| 2 | China, mainland | 13 1000 t | 2023 | up 218.2% | volatile |
| 3 | Brazil | 8 1000 t | 2023 | up 100.0% | volatile |
| 4 | United Kingdom | 6 1000 t | 2023 | up 50.0% | volatile |
| 4 | United Kingdom of Great Britain and Northern Ireland | 6 1000 t | 2023 | up 50.0% | volatile |
| 6 | Iran (Islamic Republic of) | 5 1000 t | 2023 | — | volatile |
| 7 | Hungary | 3 1000 t | 2023 | — | volatile |
| 8 | Chile | 2 1000 t | 2023 | — | volatile |
| 8 | Guatemala | 2 1000 t | 2023 | — | volatile |
| 8 | Ireland | 2 1000 t | 2023 | up 100.0% | rising |
| 8 | Morocco | 2 1000 t | 2023 | up 300.0% | volatile |
| 8 | Moldova | 2 1000 t | 2023 | — | volatile |
| 8 | Portugal | 2 1000 t | 2023 | up 100.0% | volatile |
| 8 | Romania | 2 1000 t | 2023 | down 33.3% | volatile |
| 8 | Uzbekistan | 2 1000 t | 2023 | up 100.0% | volatile |
| 8 | Republic of Moldova | 2 1000 t | 2023 | — | volatile |
| 17 | Azerbaijan | 1 1000 t | 2023 | — | volatile |
| 17 | Colombia | 1 1000 t | 2023 | — | volatile |
| 17 | Czechia | 1 1000 t | 2023 | up 200.0% | volatile |
| 17 | Spain | 1 1000 t | 2023 | — | volatile |
| 17 | Greece | 1 1000 t | 2023 | down 66.7% | falling |
| 17 | North Macedonia | 1 1000 t | 2023 | — | volatile |
| 17 | Sierra Leone | 1 1000 t | 2023 | — | volatile |
| 17 | Syria | 1 1000 t | 2023 | — | volatile |
| 17 | Thailand | 1 1000 t | 2023 | unchanged | volatile |
| 17 | Turkey | 1 1000 t | 2023 | up 116.7% | volatile |
| 17 | Uruguay | 1 1000 t | 2023 | up 150.0% | volatile |
| 17 | Syrian Arab Republic | 1 1000 t | 2023 | — | volatile |
| 17 | Türkiye | 1 1000 t | 2023 | up 116.7% | volatile |
| 30 | Angola | 0 1000 t | 2023 | — | flat |
| 30 | Australia | 0 1000 t | 2023 | up 100.0% | volatile |
| 30 | Austria | 0 1000 t | 2023 | down 100.0% | volatile |
| 30 | Belgium | 0 1000 t | 2023 | down 100.0% | volatile |
| 30 | Bangladesh | 0 1000 t | 2023 | — | volatile |
| 30 | Bulgaria | 0 1000 t | 2023 | up 100.0% | flat |
| 30 | Belarus | 0 1000 t | 2023 | — | volatile |
| 30 | Canada | 0 1000 t | 2023 | down 100.0% | volatile |
| 30 | Switzerland | 0 1000 t | 2023 | up 100.0% | volatile |
| 30 | Cuba | 0 1000 t | 2019 | — | volatile |
| 30 | Germany | 0 1000 t | 2023 | up 100.0% | volatile |
| 30 | Denmark | 0 1000 t | 2023 | — | volatile |
| 30 | Dominican Republic | 0 1000 t | 2023 | down 100.0% | flat |
| 30 | Algeria | 0 1000 t | 2023 | — | flat |
| 30 | Egypt | 0 1000 t | 2023 | down 100.0% | flat |
| 30 | Ethiopia | 0 1000 t | 2023 | down 100.0% | volatile |
| 30 | Finland | 0 1000 t | 2023 | — | volatile |
| 30 | Georgia | 0 1000 t | 2023 | down 100.0% | volatile |
| 30 | Croatia | 0 1000 t | 2023 | down 100.0% | volatile |
| 30 | Indonesia | 0 1000 t | 2023 | — | volatile |
| 30 | India | 0 1000 t | 2023 | down 100.0% | flat |
| 30 | Italy | 0 1000 t | 2023 | down 100.0% | volatile |
| 30 | Kazakhstan | 0 1000 t | 2023 | — | volatile |
| 30 | Kenya | 0 1000 t | 2023 | — | volatile |
| 30 | Kyrgyzstan | 0 1000 t | 2023 | — | volatile |
| 30 | Kuwait | 0 1000 t | 2023 | — | volatile |
| 30 | Lithuania | 0 1000 t | 2023 | — | volatile |
| 30 | Latvia | 0 1000 t | 2023 | — | volatile |
| 30 | Mexico | 0 1000 t | 2023 | — | volatile |
| 30 | Malaysia | 0 1000 t | 2023 | — | volatile |
| 30 | Norway | 0 1000 t | 2023 | — | volatile |
| 30 | Nepal | 0 1000 t | 2023 | — | volatile |
| 30 | New Zealand | 0 1000 t | 2023 | down 100.0% | volatile |
| 30 | Poland | 0 1000 t | 2023 | — | volatile |
| 30 | Saudi Arabia | 0 1000 t | 2023 | down 100.0% | volatile |
| 30 | Serbia | 0 1000 t | 2023 | — | volatile |
| 30 | Slovakia | 0 1000 t | 2023 | down 100.0% | volatile |
| 30 | Slovenia | 0 1000 t | 2023 | up 100.0% | volatile |
| 30 | Sweden | 0 1000 t | 2023 | — | volatile |
| 30 | Tunisia | 0 1000 t | 2023 | — | volatile |
| 30 | United States | 0 1000 t | 2023 | down 100.0% | volatile |
| 30 | Vietnam | 0 1000 t | 2023 | — | flat |
| 30 | Yemen | 0 1000 t | 2023 | — | volatile |
| 30 | South Africa | 0 1000 t | 2023 | — | volatile |
| 30 | Caribbean | 0 1000 t | 2023 | down 100.0% | flat |
| 30 | China, Hong Kong SAR | 0 1000 t | 2023 | — | volatile |
| 30 | Republic of Korea | 0 1000 t | 2023 | up 100.0% | volatile |
| 30 | Viet Nam | 0 1000 t | 2023 | — | flat |
| 30 | Australia and New Zealand | 0 1000 t | 2023 | up 100.0% | volatile |
| 30 | United Republic of Tanzania | 0 1000 t | 2023 | down 100.0% | flat |
| 30 | China, Taiwan Province of | 0 1000 t | 2023 | up 100.0% | volatile |
| 30 | Netherlands (Kingdom of the) | 0 1000 t | 2023 | down 100.0% | volatile |
| 189 | Russia | -1 1000 t | 2023 | down 150.0% | volatile |
| 189 | Russian Federation | -1 1000 t | 2023 | down 150.0% | volatile |
| 191 | United Arab Emirates | -2 1000 t | 2023 | — | volatile |
| 191 | Ukraine | -2 1000 t | 2023 | up 60.0% | volatile |
| 193 | Argentina | -4 1000 t | 2023 | down 33.3% | volatile |
Regions and income groups
Aggregates are excluded from the country ranking above so that a region can never outrank a country.
- World 60 1000 t
- Asia 28 1000 t
- Europe 19 1000 t
- Eastern Asia 19 1000 t
- European Union (27) 14 1000 t
- Americas 11 1000 t
- South America 9 1000 t
- Northern Europe 9 1000 t
- Eastern Europe 5 1000 t
- Southern Europe 5 1000 t
- Southern Asia 5 1000 t
- Land Locked Developing Countries (LLDCs) 5 1000 t
- Low Income Food Deficit Countries (LIFDCs) 4 1000 t
- Africa 3 1000 t
- Northern Africa 3 1000 t
- Net Food Importing Developing Countries (NFIDCs) 3 1000 t
- Central Asia 2 1000 t
- Central America 2 1000 t
- Least Developed Countries (LDCs) 1 1000 t
- Western Africa 1 1000 t
- South-Eastern Asia 1 1000 t
- Western Asia 1 1000 t
- Oceania 0 1000 t
- Northern America 0 1000 t
- Small island developing States (SIDS) 0 1000 t
- Western Europe 0 1000 t
- Eastern Africa 0 1000 t
- Southern Africa 0 1000 t
- Middle Africa 0 1000 t
- United States of America 0 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.