Government expenditure on education not specified by level, constant US$ (millions) by country
Total general (local, regional and central) government expenditure on education (current, capital, and transfers) not specified by level in millions US$ in constant value (taking into account inflation). It includes expenditure funded by transfers from international sources to government. Total government...
What the numbers show
Government expenditure on education not specified by level, constant US$ (millions) is currently reported for 149 countries. The highest value is 22,833 millions in Italy; the lowest is 0 millions in Zimbabwe.
The median across all reporting countries is 0.2422 millions, and the mean is 368.92 millions.
Over the past decade 31 countries rose and 41 fell. The largest increase was in Ghana (up 110,469.0%), and the largest decrease in Australia (down 100.0%).
Government expenditure on education not specified by level, constant U: full country ranking
| # | Country | Latest | Year | 10-year change | Trend |
|---|---|---|---|---|---|
| 1 | Italy | 22,833 millions | 2017 | β | volatile |
| 2 | Russia | 6,317 millions | 2017 | up 1.8% | rising |
| 3 | Indonesia | 4,216 millions | 2015 | up 77.3% | volatile |
| 4 | Germany | 3,055 millions | 2017 | down 1.5% | falling |
| 5 | South Africa | 2,288 millions | 2019 | up 37.4% | volatile |
| 6 | China | 2,156 millions | 1999 | β | volatile |
| 7 | Mexico | 1,530 millions | 2017 | up 12.7% | rising |
| 8 | Thailand | 1,361 millions | 2013 | down 17.7% | volatile |
| 9 | Hong Kong | 1,150 millions | 2019 | up 77.5% | rising |
| 10 | Norway | 978.16 millions | 2017 | up 27.2% | falling |
| 11 | Macao | 901.7 millions | 2018 | β | volatile |
| 12 | Romania | 809.05 millions | 2017 | up 32.7% | rising |
| 13 | Singapore | 697.93 millions | 2018 | up 2.3% | volatile |
| 14 | Belgium | 634.16 millions | 2017 | down 10.3% | volatile |
| 15 | Hungary | 616.14 millions | 2017 | up 130.2% | volatile |
| 16 | Switzerland | 566 millions | 2017 | down 21.3% | rising |
| 17 | Democratic Republic of Congo | 560.93 millions | 2015 | up 1,701.1% | volatile |
| 18 | Pakistan | 415.48 millions | 2017 | β | rising |
| 19 | Panama | 391.33 millions | 2011 | up 304.9% | volatile |
| 20 | Ghana | 365.24 millions | 2014 | up 110,469.0% | volatile |
| 21 | Kazakhstan | 316.61 millions | 2018 | up 88.0% | volatile |
| 22 | Dominican Republic | 279.89 millions | 2019 | up 884.8% | volatile |
| 23 | Portugal | 254.23 millions | 2017 | down 17.3% | rising |
| 24 | Costa Rica | 253.87 millions | 2019 | up 481.0% | volatile |
| 25 | Algeria | 196.88 millions | 2012 | up 56.9% | volatile |
| 26 | Senegal | 195.02 millions | 2018 | up 507.9% | volatile |
| 27 | Czechia | 173.04 millions | 2017 | down 14.8% | volatile |
| 28 | Uruguay | 143.76 millions | 2018 | β | volatile |
| 29 | Belarus | 126.37 millions | 2017 | β | volatile |
| 30 | Monaco | 93.76 millions | 2017 | up 246.1% | volatile |
| 31 | Iceland | 93.06 millions | 2017 | up 24.3% | rising |
| 32 | Kyrgyzstan | 92.8 millions | 2017 | up 30.0% | volatile |
| 33 | Guatemala | 91.96 millions | 2019 | down 19.5% | rising |
| 34 | Tajikistan | 89.41 millions | 2015 | up 761.1% | volatile |
| 35 | Kuwait | 70.38 millions | 2011 | up 18.5% | volatile |
| 36 | Angola | 66.91 millions | 2006 | β | volatile |
| 37 | Kenya | 62.38 millions | 2015 | β | volatile |
| 38 | Chad | 51.99 millions | 2018 | β | volatile |
| 39 | Malta | 43.6 millions | 2017 | down 30.1% | volatile |
| 40 | Lebanon | 36.57 millions | 2013 | down 23.7% | volatile |
| 41 | Andorra | 36.03 millions | 2019 | up 22.9% | rising |
| 42 | Madagascar | 36 millions | 2012 | down 14.6% | rising |
| 43 | Bahrain | 34.2 millions | 2017 | β | rising |
| 44 | Mauritius | 28.79 millions | 2019 | up 41.6% | falling |
| 45 | Armenia | 27.35 millions | 2017 | up 144.3% | rising |
| 46 | Colombia | 26.54 millions | 2018 | down 30.2% | volatile |
| 47 | Aruba | 25.07 millions | 2016 | down 35.5% | falling |
| 48 | Serbia | 20.01 millions | 2018 | down 18.2% | falling |
| 49 | Belize | 19.62 millions | 2018 | up 1,412.7% | volatile |
| 50 | Guyana | 16.36 millions | 2012 | down 43.4% | rising |
| 51 | Israel | 15.56 millions | 2017 | down 98.1% | rising |
| 52 | Namibia | 13.93 millions | 2017 | β | volatile |
| 53 | Malawi | 9.42 millions | 2016 | up 96.9% | flat |
| 54 | Saint Lucia | 9.32 millions | 2018 | β | volatile |
| 55 | Albania | 9.31 millions | 2017 | β | rising |
| 56 | Rwanda | 8.55 millions | 2018 | up 123.4% | volatile |
| 57 | Moldova | 7.65 millions | 2018 | down 85.2% | volatile |
| 58 | Saint Vincent and the Grenadines | 7.3 millions | 2018 | β | volatile |
| 59 | Lesotho | 7.12 millions | 2018 | up 96.6% | volatile |
| 60 | Burundi | 6.64 millions | 2013 | β | volatile |
| 61 | Vanuatu | 6.4 millions | 2017 | up 73.3% | volatile |
| 62 | Peru | 4.56 millions | 2019 | β | volatile |
| 63 | Mauritania | 3.95 millions | 2019 | down 78.9% | volatile |
| 64 | Cape Verde | 3.48 millions | 2017 | β | volatile |
| 65 | Slovenia | 3.47 millions | 2017 | up 2,264.3% | volatile |
| 66 | Cote d'Ivoire | 1.69 millions | 2018 | β | volatile |
| 67 | Paraguay | 1.15 millions | 2016 | β | volatile |
| 68 | Congo | 1.13 millions | 2010 | down 92.1% | volatile |
| 69 | Eswatini | 0.9647 millions | 2014 | down 87.9% | volatile |
| 70 | Central African Republic | 0.7939 millions | 2011 | β | volatile |
| 71 | Slovakia | 0.4638 millions | 2017 | down 99.4% | volatile |
| 72 | Gabon | 0.3202 millions | 2014 | β | volatile |
| 73 | Saint Kitts and Nevis | 0.2723 millions | 2016 | β | volatile |
| 74 | Niger | 0.2593 millions | 2017 | β | volatile |
| 75 | Cameroon | 0.2422 millions | 2013 | β | volatile |
| 76 | Afghanistan | 0 millions | 2017 | β | flat |
| 76 | Argentina | 0 millions | 2017 | β | volatile |
| 76 | Australia | 0 millions | 2017 | down 100.0% | volatile |
| 76 | Austria | 0 millions | 2017 | β | volatile |
| 76 | Azerbaijan | 0 millions | 2018 | down 100.0% | volatile |
| 76 | Benin | 0 millions | 2015 | β | volatile |
| 76 | Burkina Faso | 0 millions | 2016 | down 100.0% | volatile |
| 76 | Bangladesh | 0 millions | 2019 | β | volatile |
| 76 | Bulgaria | 0 millions | 2017 | β | flat |
| 76 | Bermuda | 0 millions | 2017 | β | flat |
| 76 | Brazil | 0 millions | 2017 | β | flat |
| 76 | Barbados | 0 millions | 2017 | β | volatile |
| 76 | Canada | 0 millions | 2017 | β | flat |
| 76 | Chile | 0 millions | 2016 | β | volatile |
| 76 | Comoros | 0 millions | 2015 | β | volatile |
| 76 | Cuba | 0 millions | 2010 | β | volatile |
| 76 | Cyprus | 0 millions | 2017 | β | volatile |
| 76 | Denmark | 0 millions | 2017 | down 100.0% | flat |
| 76 | Ecuador | 0 millions | 2019 | β | volatile |
| 76 | Egypt | 0 millions | 1996 | down 100.0% | volatile |
| 76 | Spain | 0 millions | 2016 | β | volatile |
| 76 | Estonia | 0 millions | 2017 | down 100.0% | volatile |
| 76 | Ethiopia | 0 millions | 2013 | β | volatile |
| 76 | Finland | 0 millions | 2017 | β | volatile |
| 76 | Fiji | 0 millions | 2013 | down 100.0% | volatile |
| 76 | United Kingdom | 0 millions | 2017 | β | volatile |
| 76 | Georgia | 0 millions | 2018 | down 100.0% | volatile |
| 76 | Guinea | 0 millions | 2018 | down 100.0% | volatile |
| 76 | Gambia | 0 millions | 2015 | down 100.0% | volatile |
| 76 | Greece | 0 millions | 2017 | β | volatile |
| 76 | Croatia | 0 millions | 2015 | down 100.0% | volatile |
| 76 | India | 0 millions | 2013 | β | volatile |
| 76 | Ireland | 0 millions | 2017 | β | volatile |
| 76 | Iran | 0 millions | 2018 | β | volatile |
| 76 | Jamaica | 0 millions | 2019 | β | volatile |
| 76 | Jordan | 0 millions | 2019 | β | volatile |
| 76 | Japan | 0 millions | 2017 | down 100.0% | falling |
| 76 | Cambodia | 0 millions | 2014 | β | flat |
| 76 | South Korea | 0 millions | 2016 | β | volatile |
| 76 | Laos | 0 millions | 2014 | down 100.0% | volatile |
| 76 | Sri Lanka | 0 millions | 2018 | β | volatile |
| 76 | Lithuania | 0 millions | 2017 | β | volatile |
| 76 | Luxembourg | 0 millions | 2017 | β | volatile |
| 76 | Latvia | 0 millions | 2017 | β | volatile |
| 76 | Morocco | 0 millions | 2009 | β | volatile |
| 76 | Maldives | 0 millions | 2019 | β | flat |
| 76 | North Macedonia | 0 millions | 1996 | β | flat |
| 76 | Mali | 0 millions | 2017 | β | volatile |
| 76 | Mongolia | 0 millions | 2016 | β | flat |
| 76 | Malaysia | 0 millions | 2019 | β | volatile |
| 76 | Netherlands | 0 millions | 2017 | β | volatile |
| 76 | Nepal | 0 millions | 2015 | down 100.0% | volatile |
| 76 | New Zealand | 0 millions | 2017 | down 100.0% | volatile |
| 76 | Oman | 0 millions | 2019 | β | volatile |
| 76 | Philippines | 0 millions | 2009 | down 100.0% | volatile |
| 76 | Poland | 0 millions | 2017 | β | volatile |
| 76 | Saudi Arabia | 0 millions | 1998 | β | flat |
| 76 | Sierra Leone | 0 millions | 2019 | down 100.0% | volatile |
| 76 | El Salvador | 0 millions | 2018 | down 100.0% | volatile |
| 76 | South Sudan | 0 millions | 2017 | β | flat |
| 76 | Sweden | 0 millions | 2017 | β | volatile |
| 76 | Seychelles | 0 millions | 2016 | β | volatile |
| 76 | Togo | 0 millions | 2017 | down 100.0% | volatile |
| 76 | East Timor | 0 millions | 2014 | β | flat |
| 76 | Tunisia | 0 millions | 2015 | β | volatile |
| 76 | Turkey | 0 millions | 2006 | β | volatile |
| 76 | Tanzania | 0 millions | 2014 | β | flat |
| 76 | Uganda | 0 millions | 2014 | down 100.0% | volatile |
| 76 | Ukraine | 0 millions | 2017 | β | volatile |
| 76 | United States | 0 millions | 2017 | β | flat |
| 76 | British Virgin Islands | 0 millions | 2019 | β | flat |
| 76 | Vietnam | 0 millions | 2013 | β | flat |
| 76 | Zambia | 0 millions | 2017 | down 100.0% | volatile |
| 76 | Zimbabwe | 0 millions | 2014 | β | volatile |
About this data
Total general (local, regional and central) government expenditure on education (current, capital, and transfers) not specified by level in millions US$ 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 US$, and where it is expressed in constant value, uses a GDP deflator to account for inflation. The constant prices base year is normally three years before the year of the data release. For example, in the July 2017 data release, constant US$ 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/