Statizoid

Government expenditure on education not specified by level, constant PPP$ (millions) by country

Total general (local, regional and central) government expenditure on education (current, capital, and transfers) not specified by level, in millions PPP$ (at purchasing power parity) in constant value (taking into account inflation). It includes expenditure funded by transfers from international sources to...

Countries reporting
144
Highest
29,440 millions
Italy
Lowest
0 millions
Zimbabwe
Median
0 millions
Years covered
49
1971–2019
Data points
2,028

What the numbers show

Government expenditure on education not specified by level, constant PPP$ (millions) is currently reported for 144 countries. The highest value is 29,440 millions in Italy; the lowest is 0 millions in Zimbabwe.

The median across all reporting countries is 0 millions, and the mean is 664.34 millions.

Over the past decade 28 countries rose and 39 fell. The largest increase was in Ghana (up 177,100.0%), and the largest decrease in Australia (down 100.0%).

Government expenditure on education not specified by level, constant P: full country ranking

#Country LatestYear 10-year changeTrend
1 Italy 29,440 millions 2017 — volatile
2 Russia 15,324 millions 2017 up 1.8% rising
3 Indonesia 12,013 millions 2015 up 77.3% volatile
4 South Africa 5,464 millions 2019 up 37.4% volatile
5 Germany 3,651 millions 2017 down 1.5% falling
6 Thailand 3,597 millions 2013 down 17.7% rising
7 China 3,483 millions 1999 — volatile
8 Mexico 3,265 millions 2017 up 12.7% rising
9 Romania 2,036 millions 2017 up 32.7% rising
10 Hong Kong 1,505 millions 2019 up 77.5% rising
11 Macao 1,404 millions 2018 — volatile
12 Pakistan 1,339 millions 2017 — rising
13 Hungary 1,258 millions 2017 up 130.2% volatile
14 Democratic Republic of Congo 1,147 millions 2015 up 1,523.0% volatile
15 Singapore 1,098 millions 2018 up 2.3% rising
16 Ghana 900.81 millions 2014 up 177,100.0% volatile
17 Kazakhstan 851.23 millions 2018 up 88.0% volatile
18 Norway 815.48 millions 2017 up 27.2% falling
19 Panama 786.64 millions 2011 up 304.9% volatile
20 Belgium 726.32 millions 2017 down 10.3% falling
21 Dominican Republic 615.56 millions 2019 up 884.8% volatile
22 Switzerland 472.35 millions 2017 down 21.3% rising
23 Senegal 458.85 millions 2018 up 507.9% volatile
24 Costa Rica 410.69 millions 2019 up 481.0% volatile
25 Belarus 400.92 millions 2017 — volatile
26 Portugal 391.41 millions 2017 down 17.3% falling
27 Kyrgyzstan 376.84 millions 2017 up 30.0% volatile
28 Tajikistan 342.69 millions 2015 up 761.1% volatile
29 Czechia 326.8 millions 2017 down 14.8% volatile
30 Uruguay 176.98 millions 2018 — volatile
31 Guatemala 171.83 millions 2019 down 19.5% rising
32 Kenya 160.76 millions 2015 — volatile
33 Chad 123.9 millions 2018 — volatile
34 Kuwait 113.74 millions 2011 up 18.5% volatile
35 Madagascar 110.69 millions 2012 down 14.6% rising
36 Armenia 84.66 millions 2017 up 144.3% rising
37 Lebanon 75.02 millions 2013 down 23.7% volatile
38 Iceland 72.51 millions 2017 up 24.3% rising
39 Bahrain 68.73 millions 2017 — rising
40 Malta 66.51 millions 2017 down 30.1% volatile
41 Mauritius 61.56 millions 2019 up 41.6% falling
42 Colombia 59.57 millions 2018 down 30.2% volatile
43 Serbia 52.65 millions 2018 down 18.2% falling
44 Aruba 33.22 millions 2016 down 35.5% falling
45 Guyana 32.06 millions 2012 down 9.8% rising
46 Namibia 31.93 millions 2017 — volatile
47 Malawi 30.57 millions 2016 up 96.9% rising
48 Belize 29.23 millions 2018 up 1,412.7% volatile
49 Albania 26.79 millions 2017 — rising
50 Moldova 25.39 millions 2018 down 85.2% volatile
51 Rwanda 21.61 millions 2018 up 120.8% volatile
52 Lesotho 20.89 millions 2018 up 96.6% volatile
53 Burundi 17.52 millions 2013 — volatile
54 Israel 14.95 millions 2017 down 98.1% falling
55 Saint Lucia 12.86 millions 2018 — volatile
56 Mauritania 12.71 millions 2019 down 79.5% volatile
57 Saint Vincent and the Grenadines 12.39 millions 2018 — volatile
58 Peru 8.49 millions 2019 — volatile
59 Cape Verde 7.01 millions 2017 — volatile
60 Vanuatu 6.48 millions 2017 up 73.3% volatile
61 Slovenia 5.41 millions 2017 up 2,264.2% volatile
62 Cote d'Ivoire 3.87 millions 2018 — volatile
63 Paraguay 2.56 millions 2016 — volatile
64 Eswatini 2.45 millions 2014 down 87.9% volatile
65 Congo 2.2 millions 2010 down 92.1% volatile
66 Central African Republic 1.61 millions 2011 — volatile
67 Slovakia 0.8167 millions 2017 down 99.4% volatile
68 Gabon 0.6645 millions 2014 — volatile
69 Cameroon 0.6041 millions 2013 — volatile
70 Niger 0.5828 millions 2017 — volatile
71 Saint Kitts and Nevis 0.3604 millions 2016 — volatile
72 Afghanistan 0 millions 2017 — flat
72 Argentina 0 millions 2017 — volatile
72 Australia 0 millions 2017 down 100.0% volatile
72 Austria 0 millions 2017 — volatile
72 Azerbaijan 0 millions 2018 down 100.0% volatile
72 Benin 0 millions 2015 — volatile
72 Burkina Faso 0 millions 2016 down 100.0% volatile
72 Bangladesh 0 millions 2019 — volatile
72 Bulgaria 0 millions 2017 — flat
72 Bermuda 0 millions 2017 — flat
72 Brazil 0 millions 2017 — flat
72 Barbados 0 millions 2017 — volatile
72 Canada 0 millions 2017 — flat
72 Chile 0 millions 2016 — volatile
72 Comoros 0 millions 2015 — volatile
72 Cuba 0 millions 2010 — flat
72 Cyprus 0 millions 2017 — volatile
72 Denmark 0 millions 2017 down 100.0% falling
72 Ecuador 0 millions 2019 — volatile
72 Egypt 0 millions 1996 — flat
72 Spain 0 millions 2016 — volatile
72 Estonia 0 millions 2017 down 100.0% volatile
72 Ethiopia 0 millions 2013 — volatile
72 Finland 0 millions 2017 — volatile
72 United Kingdom 0 millions 2017 — volatile
72 Georgia 0 millions 2018 down 100.0% volatile
72 Guinea 0 millions 2018 down 100.0% volatile
72 Gambia 0 millions 2015 down 100.0% volatile
72 Greece 0 millions 2017 — volatile
72 Croatia 0 millions 2015 down 100.0% volatile
72 India 0 millions 2013 — volatile
72 Ireland 0 millions 2017 — volatile
72 Iran 0 millions 2018 — volatile
72 Jamaica 0 millions 2019 — volatile
72 Jordan 0 millions 2019 — volatile
72 Japan 0 millions 2017 down 100.0% falling
72 Cambodia 0 millions 2014 — flat
72 South Korea 0 millions 2016 — volatile
72 Laos 0 millions 2014 down 100.0% volatile
72 Sri Lanka 0 millions 2018 — volatile
72 Lithuania 0 millions 2017 — volatile
72 Luxembourg 0 millions 2017 — volatile
72 Latvia 0 millions 2017 — volatile
72 Morocco 0 millions 2009 — volatile
72 Maldives 0 millions 2019 — flat
72 North Macedonia 0 millions 1996 — flat
72 Mali 0 millions 2017 — flat
72 Mongolia 0 millions 2016 — flat
72 Malaysia 0 millions 2019 — volatile
72 Netherlands 0 millions 2017 — volatile
72 Nepal 0 millions 2015 down 100.0% volatile
72 New Zealand 0 millions 2017 down 100.0% volatile
72 Oman 0 millions 2019 — volatile
72 Philippines 0 millions 2009 down 100.0% volatile
72 Poland 0 millions 2017 — volatile
72 Saudi Arabia 0 millions 1998 — flat
72 Sierra Leone 0 millions 2019 down 100.0% volatile
72 El Salvador 0 millions 2018 down 100.0% volatile
72 South Sudan 0 millions 2017 — flat
72 Sweden 0 millions 2017 — volatile
72 Seychelles 0 millions 2016 — volatile
72 Togo 0 millions 2017 down 100.0% volatile
72 East Timor 0 millions 2014 — flat
72 Tunisia 0 millions 2015 — volatile
72 Turkey 0 millions 2006 — volatile
72 Tanzania 0 millions 2014 — flat
72 Uganda 0 millions 2014 down 100.0% volatile
72 Ukraine 0 millions 2017 — volatile
72 United States 0 millions 2017 — flat
72 British Virgin Islands 0 millions 2019 — flat
72 Vietnam 0 millions 2013 — flat
72 Zambia 0 millions 2017 down 100.0% volatile
72 Zimbabwe 0 millions 2014 — volatile

About this data

Indicator
Government expenditure on education not specified by level, constant PPP$ (millions)
Unit
millions
Source
UNESCO Institute for Statistics
Licence
CC BY 4.0 (World Bank Open Data)
Coverage
144 places, 2,028 data points, 1971–2019
Last refreshed

Total general (local, regional and central) government expenditure on education (current, capital, and transfers) not specified by level, in millions PPP$ (at purchasing power parity) in constant value (taking into account inflation). It includes expenditure funded by transfers from international sources to government. Total government expenditure for a given level of education (e.g. primary, secondary, or all levels combined) in national currency is converted to PPP$, and where it is expressed in constant value, uses a GDP deflator to account for inflation. The constant prices base year is normally three years before the year of the data release. For example, in the July 2017 data release, constant PPP$ values are expressed in 2014 prices. Limitations: In some instances data on total government expenditure on education refers only to the Ministry of Education, excluding other ministries which may also spend a part of their budget on educational activities. For more information, consult the UNESCO Institute of Statistics website: http://www.uis.unesco.org/Education/