Statizoid

Wool (Clean Eq.) — Import Quantity by country

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
131
Highest
345,048 t
China, mainland
Lowest
0 t
China, Macao SAR
Median
107 t
Years covered
53
1961–2013
Data points
7,582

What the numbers show

Wool (Clean Eq.) — Import Quantity is currently reported for 131 countries. The highest value is 345,048 t in China, mainland; the lowest is 0 t in China, Macao SAR.

The median across all reporting countries is 107 t, and the mean is 6,765 t.

Over the past decade 25 countries rose and 74 fell. The largest increase was in Panama (up 2,200.0%), and the largest decrease in Democratic People's Republic of Korea (down 100.0%).

Wool (Clean Eq.) — Import Quantity: full country ranking

#Country LatestYear 10-year changeTrend
1 China, mainland 345,048 t 2013 up 109.2% volatile
2 India 88,822 t 2013 up 5.0% volatile
3 USSR 79,500 t 1991 down 37.1% rising
3 Iran (Islamic Republic of) 2,189 t 2013 down 39.9% volatile
4 United Kingdom of Great Britain and Northern Ireland 37,347 t 2013 down 29.5% volatile
4 Republic of Moldova 1,077 t 2013 down 12.9% rising
5 Germany 36,695 t 2013 down 10.9% falling
5 Viet Nam 30 t 2013 down 23.1% volatile
6 Italy 35,246 t 2013 down 57.5% falling
6 Bolivia (Plurinational State of) 23 t 2013 — volatile
7 Czechia 32,116 t 2013 up 48.7% rising
8 Belgium-Luxembourg 30,493 t 1999 down 55.9% falling
8 United Republic of Tanzania 9 t 2013 down 25.0% volatile
9 Belgium 21,798 t 2013 down 38.6% falling
9 Melanesia 0 t 2013 — volatile
9 Venezuela (Bolivarian Republic of) 0 t 2013 — volatile
9 Democratic People's Republic of Korea 0 t 2013 down 100.0% volatile
10 T�rkiye 20,531 t 2013 down 27.4% volatile
11 Uruguay 17,584 t 2013 up 41.1% volatile
12 Russian Federation 9,506 t 2013 down 52.7% volatile
13 Yugoslav SFR 8,180 t 1991 down 69.6% rising
14 Republic of Korea 8,138 t 2013 down 35.7% volatile
15 Poland 8,137 t 2013 up 263.7% volatile
16 Japan 7,303 t 2013 down 55.2% volatile
17 Czechoslovakia 7,230 t 1992 down 64.3% falling
18 Lithuania 6,719 t 2013 up 215.2% volatile
19 Belarus 6,690 t 2013 up 31.6% volatile
20 Denmark 6,365 t 2013 up 0.9% rising
21 Malaysia 5,981 t 2013 up 292.5% volatile
22 Egypt 5,570 t 2013 up 907.2% volatile
23 Portugal 5,525 t 2013 down 17.2% rising
24 Ireland 4,166 t 2013 up 277.4% falling
25 China, Taiwan Province of 4,055 t 2013 down 82.6% volatile
26 Nepal 3,564 t 2013 down 69.2% volatile
27 Netherlands (Kingdom of the) 3,363 t 2013 up 296.6% volatile
28 Spain 3,194 t 2013 down 70.2% falling
28 Caribbean 0 t 2013 down 100.0% volatile
29 South Africa 3,164 t 2013 up 36.9% falling
30 France 2,781 t 2013 down 93.9% volatile
31 Bulgaria 2,496 t 2013 down 77.1% volatile
32 Slovakia 2,451 t 2013 up 107.9% volatile
33 Australia and New Zealand 2,334 t 2013 down 83.6% rising
34 Hungary 2,318 t 2013 down 68.3% volatile
35 Thailand 2,256 t 2013 down 75.6% volatile
36 Australia 1,884 t 2013 down 85.9% rising
37 Ukraine 1,718 t 2013 up 243.6% volatile
38 Pakistan 1,404 t 2013 down 81.9% volatile
39 Austria 1,322 t 2013 up 46.2% volatile
40 Mexico 833 t 2013 down 40.9% volatile
41 Mauritius 705 t 2013 down 0.3% volatile
42 Canada 665 t 2013 down 21.5% volatile
43 United Arab Emirates 585 t 2013 up 317.9% volatile
44 China, Hong Kong SAR 580 t 2013 down 57.3% volatile
45 Switzerland 533 t 2013 down 38.6% volatile
46 Serbia 529 t 2013 up 56.0% volatile
47 Kuwait 524 t 2013 — volatile
48 Latvia 503 t 2013 down 44.7% volatile
49 New Zealand 450 t 2013 down 48.9% volatile
50 Estonia 444 t 2013 down 61.6% volatile
51 Kyrgyzstan 425 t 2013 up 63.5% volatile
52 Romania 359 t 2013 up 398.6% volatile
53 Indonesia 330 t 2013 down 33.2% volatile
54 Norway 283 t 2013 down 61.4% volatile
55 Morocco 266 t 2013 down 46.0% volatile
56 Greece 230 t 2013 down 92.1% volatile
57 North Macedonia 203 t 2013 up 331.9% volatile
57 Tunisia 203 t 2013 down 57.3% volatile
59 Serbia and Montenegro 187 t 2005 — volatile
60 Argentina 179 t 2013 down 75.5% volatile
61 Brazil 155 t 2013 down 12.9% volatile
62 Sweden 135 t 2013 down 74.5% volatile
63 Ecuador 132 t 2013 down 17.0% volatile
64 Iceland 107 t 2013 up 48.6% volatile
65 Kazakhstan 104 t 2013 — volatile
66 Burkina Faso 38 t 2013 — volatile
67 Slovenia 26 t 2013 down 58.1% volatile
68 Chile 25 t 2013 up 150.0% volatile
69 Panama 23 t 2013 up 2,200.0% volatile
70 Armenia 21 t 2013 down 16.0% volatile
70 Peru 21 t 2013 down 47.5% volatile
72 Cameroon 18 t 2013 — volatile
73 Botswana 16 t 2013 up 33.3% volatile
74 Azerbaijan 14 t 2013 — volatile
74 Colombia 14 t 2013 down 80.8% volatile
76 Nigeria 8 t 2013 down 20.0% volatile
77 Sri Lanka 5 t 2013 down 37.5% volatile
78 Lesotho 4 t 2013 — volatile
79 Afghanistan 2 t 2013 down 97.7% volatile
79 Honduras 2 t 2013 down 33.3% volatile
79 Montenegro 2 t 2013 down 90.5% volatile
79 Namibia 2 t 2013 — volatile
79 Oman 2 t 2013 — volatile
79 Senegal 2 t 2013 — volatile
79 Eswatini 2 t 2013 down 33.3% volatile
86 Cyprus 1 t 2013 — volatile
86 Mauritania 1 t 2013 — volatile
86 Philippines 1 t 2013 down 99.7% volatile
86 Zambia 1 t 2013 down 87.5% volatile
90 Albania 0 t 2013 down 100.0% volatile
90 Bangladesh 0 t 2013 down 100.0% volatile
90 Bosnia and Herzegovina 0 t 2013 down 100.0% volatile
90 Djibouti 0 t 2013 — volatile
90 Algeria 0 t 2013 down 100.0% volatile
90 Ethiopia 0 t 2013 — volatile
90 Finland 0 t 2013 down 100.0% volatile
90 Georgia 0 t 2013 down 100.0% volatile
90 Guinea 0 t 2013 down 100.0% volatile
90 Guatemala 0 t 2013 — volatile
90 Croatia 0 t 2013 down 100.0% volatile
90 Iraq 0 t 2013 — volatile
90 Israel 0 t 2013 — volatile
90 Jamaica 0 t 2013 down 100.0% volatile
90 Jordan 0 t 2013 — volatile
90 Kenya 0 t 2013 — volatile
90 Lebanon 0 t 2013 — volatile
90 Mali 0 t 2013 down 100.0% volatile
90 Malta 0 t 2013 down 100.0% volatile
90 Mongolia 0 t 2013 — volatile
90 Malawi 0 t 2013 — volatile
90 Nicaragua 0 t 2013 — volatile
90 Paraguay 0 t 2013 — volatile
90 Saudi Arabia 0 t 2013 down 100.0% volatile
90 Solomon Islands 0 t 2013 — volatile
90 El Salvador 0 t 2013 down 100.0% volatile
90 Togo 0 t 2013 — volatile
90 Trinidad and Tobago 0 t 2013 — volatile
90 Uzbekistan 0 t 2013 — volatile
90 Zimbabwe 0 t 2013 down 100.0% volatile
90 Brunei Darussalam 0 t 2013 down 100.0% volatile
90 Ethiopia PDR 0 t 1992 — volatile
90 China, Macao SAR 0 t 2013 down 100.0% volatile

Regions and income groups

Aggregates are excluded from the country ranking above so that a region can never outrank a country.

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Wool (Clean Eq.) — Import Quantity by country. Statizoid, drawing on Food and Agriculture Organization of the United Nations. Retrieved 05 October 2026, from https://agriculture.statizoid.com/stat/wool-clean-eq-import-quantity/

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About this data

Indicator
Wool (Clean Eq.) — Import Quantity
Unit
t
Source
Food and Agriculture Organization of the United Nations
Licence
CC BY-NC-SA 3.0 IGO (FAO)
Coverage
161 places, 7,582 data points, 1961–2013
Last refreshed

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 caput 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.