Statizoid

Government expenditure on pre-primary education, PPP$ (millions) by country

Total general (local, regional and central) government expenditure on pre-primary education (current, capital, and transfers), in millions PPP$ (at purchasing power parity), in nominal value. It includes expenditure funded by transfers from international sources to government. Total government expenditure for a...

Countries reporting
142
Highest
61,662 millions
United States
Lowest
0 millions
Uganda
Median
140.61 millions
Years covered
50
1970–2019
Data points
2,189

What the numbers show

Government expenditure on pre-primary education, PPP$ (millions) is currently reported for 142 countries. The highest value is 61,662 millions in United States; the lowest is 0 millions in Uganda.

The median across all reporting countries is 140.61 millions, and the mean is 2,162 millions.

Over the past decade 95 countries rose and 15 fell. The largest increase was in Eswatini (up 7,492.8%), and the largest decrease in Democratic Republic of Congo (down 100.0%).

Government expenditure on pre-primary education, PPP$: full country ranking

#Country LatestYear 10-year changeTrend
1 United States 61,662 millions 2017 — rising
2 Russia 33,343 millions 2013 up 356.4% volatile
3 Germany 21,621 millions 2017 up 97.9% rising
4 France 21,066 millions 2017 — volatile
5 Brazil 15,055 millions 2011 up 186.5% rising
6 Italy 11,962 millions 2017 up 32.9% rising
7 Mexico 10,126 millions 2011 up 135.6% volatile
8 Spain 8,191 millions 2017 down 3.4% volatile
9 South Korea 8,056 millions 2016 — volatile
10 Poland 7,655 millions 2017 up 140.3% volatile
11 United Kingdom 6,438 millions 2017 down 6.5% volatile
12 Sweden 6,414 millions 2017 up 205.1% volatile
13 Japan 5,090 millions 2017 up 37.7% rising
14 Argentina 4,980 millions 2017 up 125.4% volatile
15 Ukraine 4,768 millions 2017 up 62.5% rising
16 Vietnam 4,324 millions 2013 up 211.5% rising
17 Belgium 3,948 millions 2017 up 67.2% rising
18 Venezuela 3,799 millions 2009 up 805.4% volatile
19 India 3,767 millions 2013 up 178.0% rising
20 Chile 3,268 millions 2017 up 233.9% volatile
21 Netherlands 3,231 millions 2017 up 27.1% volatile
22 Israel 2,970 millions 2017 up 156.9% volatile
23 Australia 2,773 millions 2017 up 743.0% volatile
24 Peru 2,639 millions 2019 up 178.6% volatile
25 Denmark 2,633 millions 2017 up 92.4% volatile
26 Austria 2,428 millions 2017 up 90.4% rising
27 Norway 2,385 millions 2017 up 190.9% volatile
28 Ecuador 2,360 millions 2018 up 83.7% volatile
29 Thailand 2,345 millions 2013 down 10.5% volatile
30 Switzerland 2,342 millions 2017 up 251.5% volatile
31 Czechia 2,163 millions 2017 up 120.9% rising
32 Hungary 2,036 millions 2017 up 57.5% rising
33 Belarus 1,994 millions 2017 up 73.7% rising
34 Finland 1,865 millions 2017 up 188.9% volatile
35 Canada 1,789 millions 2000 up 33.6% rising
36 Colombia 1,767 millions 2018 up 41.5% volatile
37 Romania 1,674 millions 2017 up 54.4% rising
38 Indonesia 1,513 millions 2014 up 344.3% volatile
39 Kazakhstan 1,493 millions 2016 up 405.2% volatile
40 Bulgaria 1,417 millions 2017 up 108.7% rising
41 Portugal 1,356 millions 2017 up 43.8% volatile
42 Malaysia 1,267 millions 2019 up 235.5% volatile
44 Kuwait 1,071 millions 2014 up 41.9% volatile
45 Slovakia 896.23 millions 2017 up 119.5% volatile
46 China 887.93 millions 1999 up 167.2% rising
47 New Zealand 862.58 millions 2017 up 218.9% volatile
48 Greece 786.6 millions 2017 — volatile
49 South Africa 689.71 millions 2019 up 146.6% volatile
50 Guatemala 629.45 millions 2019 up 117.8% volatile
51 Croatia 596.9 millions 2017 up 46.4% rising
52 Lithuania 593.37 millions 2017 up 73.5% rising
53 Dominican Republic 487.77 millions 2019 up 337.2% volatile
54 Ghana 486.97 millions 2014 up 249.9% volatile
55 Latvia 454.74 millions 2017 up 70.5% volatile
56 Moldova 454.2 millions 2018 up 74.2% rising
57 Uruguay 442.92 millions 2018 up 329.4% volatile
58 Slovenia 396.98 millions 2017 up 29.4% rising
59 Mongolia 379.06 millions 2017 up 136.5% rising
60 Luxembourg 322.27 millions 2017 up 61.8% volatile
61 Azerbaijan 313.16 millions 2018 up 61.0% volatile
62 Costa Rica 297.9 millions 2019 up 57.3% volatile
63 Kyrgyzstan 249.13 millions 2017 up 352.2% volatile
64 Paraguay 243.95 millions 2016 up 177.4% rising
65 Ireland 240.54 millions 2015 up 5,099.4% volatile
66 Tanzania 210.79 millions 2014 up 87.0% rising
67 El Salvador 208.85 millions 2018 up 38.8% rising
68 Philippines 208.45 millions 2009 up 1,794.8% volatile
69 Iran 181.99 millions 2018 down 57.7% volatile
70 Iceland 172.4 millions 2017 up 111.1% volatile
71 Oman 171.21 millions 2019 — volatile
72 Cote d'Ivoire 145.56 millions 2018 up 276.5% volatile
73 Ethiopia 135.65 millions 2015 up 6,808.4% volatile
74 Kenya 132.5 millions 2015 up 143.4% volatile
75 Estonia 127.53 millions 2013 up 132.2% rising
76 Armenia 115.89 millions 2017 up 79.8% rising
77 Cyprus 102.75 millions 2017 up 36.8% volatile
78 Georgia 100.3 millions 2012 — falling
79 Singapore 91.92 millions 2017 — volatile
80 Trinidad and Tobago 91.88 millions 2009 up 190.3% volatile
81 Laos 75.08 millions 2014 up 1,162.8% volatile
82 Serbia 74.87 millions 2018 up 377.6% volatile
83 Cameroon 73.51 millions 2013 — volatile
84 Tajikistan 70.61 millions 2015 up 351.5% volatile
85 Niger 69.73 millions 2017 — volatile
86 Malta 68.27 millions 2017 up 91.0% volatile
87 Jamaica 60.53 millions 2019 down 48.7% volatile
88 Panama 59.98 millions 2011 up 91.0% rising
89 Congo 59.2 millions 2010 up 1,894.7% volatile
90 Nepal 54.62 millions 2015 — volatile
91 Maldives 45.44 millions 2019 up 42.0% rising
92 Benin 41.72 millions 2015 up 522.2% volatile
93 Nicaragua 37.12 millions 2010 up 816.9% volatile
94 Gabon 29.71 millions 2014 — rising
95 Myanmar 24.66 millions 2017 — volatile
96 Cambodia 24.46 millions 2014 up 774.6% volatile
97 Guyana 20.52 millions 2012 up 0.2% volatile
98 Mauritius 17.28 millions 2019 up 112.4% rising
99 Senegal 15.66 millions 2018 down 9.3% volatile
100 San Marino 14.18 millions 2018 up 44.6% volatile
101 Aruba 12.32 millions 2016 up 13.8% rising
102 Jordan 10.48 millions 2019 down 33.8% volatile
103 Seychelles 9.65 millions 2016 up 243.4% volatile
104 Belize 9.39 millions 2018 up 358.0% volatile
105 Namibia 9.29 millions 2017 up 114.8% volatile
106 Rwanda 9.25 millions 2018 up 137.6% volatile
107 Zambia 8.83 millions 2017 — volatile
108 Togo 8.55 millions 2016 — volatile
109 Brunei 8.48 millions 2016 — volatile
110 Burkina Faso 8.44 millions 2016 up 532.8% volatile
111 Mauritania 7.79 millions 2019 up 663.2% volatile
112 Eswatini 7.66 millions 2014 up 7,492.8% volatile
113 Mali 5.54 millions 2017 down 51.4% volatile
114 Bermuda 4.22 millions 2017 down 15.0% rising
115 Comoros 3.79 millions 2015 up 3,476.9% volatile
116 Cape Verde 1.91 millions 2017 up 333.7% volatile
117 Dominica 1.75 millions 2019 up 3,993.8% volatile
118 Madagascar 1.67 millions 2012 — volatile
119 Chad 1.61 millions 2011 — volatile
120 Fiji 1.29 millions 2011 up 88.6% volatile
121 Saint Vincent and the Grenadines 1.24 millions 2015 up 559.8% volatile
122 Central African Republic 1.07 millions 2010 — volatile
123 Guinea 0.9667 millions 2018 — volatile
124 Lesotho 0.9581 millions 2018 up 44.4% volatile
125 Barbados 0.8765 millions 2008 down 88.1% volatile
126 Burundi 0.1173 millions 2013 down 52.2% volatile
127 Vanuatu 0.0374 millions 2017 down 80.2% volatile
128 Afghanistan 0 millions 2017 — flat
128 Bangladesh 0 millions 2012 — flat
128 Bhutan 0 millions 2015 — flat
128 Democratic Republic of Congo 0 millions 2015 down 100.0% volatile
128 Gambia 0 millions 2015 — flat
128 Saint Lucia 0 millions 2018 down 100.0% volatile
128 Sri Lanka 0 millions 2018 — flat
128 Morocco 0 millions 2013 — volatile
128 North Macedonia 0 millions 1996 — flat
128 Malawi 0 millions 2016 — volatile
128 Pakistan 0 millions 1987 — flat
128 Sierra Leone 0 millions 2019 — flat
128 Syria 0 millions 2015 — flat
128 Tunisia 0 millions 2010 — volatile
128 Turkey 0 millions 2006 down 100.0% volatile
128 Uganda 0 millions 2014 — flat

About this data

Indicator
Government expenditure on pre-primary education, PPP$ (millions)
Unit
millions
Source
UNESCO Institute for Statistics
Licence
CC BY 4.0 (World Bank Open Data)
Coverage
144 places, 2,189 data points, 1970–2019
Last refreshed

Total general (local, regional and central) government expenditure on pre-primary education (current, capital, and transfers), in millions PPP$ (at purchasing power parity), in nominal value. 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$. 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/