placestats

Education score vs. Governance score

Fades after adjusting for income

Across 168 countries, Education score and Governance score rise and fall together at r = +0.50 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to +0.18, which could easily be chance (q = 0.39, allowing for the many pairs tested, and allowing for countries in the same region being alike). So the first figure mostly shows richer countries differing from poorer ones, not a link between these two things.

Comparing countries across the middle half of education score, -0.0128 to 0.859 typical gaps, governance score is better by 0.577 typical gaps at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.337 typical gaps.

Link before adjusting (r)+0.503p = 3.7e-12 · 168 countries
After adjusting for national income+0.179p = 0.021 · likely range [+0.03, +0.32]
p, allowing for regions0.185standard error 0.119 · 7 regions
Check for luck (q)0.386across 12,497 pairs

How to read these.r runs from −1 (one goes up as the other goes down) to +1 (they rise together), and 0 means no link. Adjusting for national income means comparing countries with the same GDP per person, so differences in wealth can’t explain the link. Income is used in percentage terms, since an extra $1,000 means more to a poor country than to a rich one. p is how likely a link this strong would be if there were really none. Below 0.05 means it is unlikely to be chance. Very small values are written in short form: 1.1e-32 means a decimal point followed by 31 zeros and then 11, so very close to zero. The likely range is where the true figure probably lies, and a range that crosses zero means the link could easily be chance. Countries in the same region tend to resemble each other, so the third figure allows for that, which gives a fairer p. The standard error is the typical size of the error in r. Finally, testing this many pairs means some will look strong by luck alone. A q below 0.05 means this link is unlikely to be one of those.

Education score · typical gaps (standard deviations)link with income +0.81 · proxy
Governance score · typical gaps (standard deviations)link with income +0.53 · moderate

“Link with income” is how closely each measure tracks GDP per person across countries, from −1 to +1.

Every country as a dot

Education score · typical gaps (standard deviations) →Governance score · typical gaps (standard deviations) →-2.11.44-1.41.47Afghanistan: -0.557 typical gaps (standard deviations), -1.4 typical gaps (standard deviations)Angola: -0.482 typical gaps (standard deviations), -0.522 typical gaps (standard deviations)Albania: 0.923 typical gaps (standard deviations), 0.323 typical gaps (standard deviations)Andorra: 0.892 typical gaps (standard deviations), 0.558 typical gaps (standard deviations)United Arab Emirates: 0.911 typical gaps (standard deviations), -0.981 typical gaps (standard deviations)Argentina: 1.03 typical gaps (standard deviations), 0.815 typical gaps (standard deviations)Armenia: 0.65 typical gaps (standard deviations), 0.22 typical gaps (standard deviations)Australia: 1.03 typical gaps (standard deviations), 1.38 typical gaps (standard deviations)Austria: 1 typical gaps (standard deviations), 1.33 typical gaps (standard deviations)Azerbaijan: 0.629 typical gaps (standard deviations), -1.33 typical gaps (standard deviations)Burundi: -0.587 typical gaps (standard deviations), -1.09 typical gaps (standard deviations)Belgium: 1.25 typical gaps (standard deviations), 1.41 typical gaps (standard deviations)Benin: -0.586 typical gaps (standard deviations), 0.285 typical gaps (standard deviations)Burkina Faso: -0.582 typical gaps (standard deviations), -0.784 typical gaps (standard deviations)Bangladesh: 0.335 typical gaps (standard deviations), -0.359 typical gaps (standard deviations)Bulgaria: 0.794 typical gaps (standard deviations), 0.74 typical gaps (standard deviations)Bahrain: 0.537 typical gaps (standard deviations), -1.05 typical gaps (standard deviations)Bosnia and Herzegovina: 0.607 typical gaps (standard deviations), 0.0899 typical gaps (standard deviations)Belarus: 0.722 typical gaps (standard deviations), -1.26 typical gaps (standard deviations)Belize: 0.166 typical gaps (standard deviations), 0.0883 typical gaps (standard deviations)Bolivia: 0.634 typical gaps (standard deviations), 0.552 typical gaps (standard deviations)Brazil: 0.731 typical gaps (standard deviations), 0.85 typical gaps (standard deviations)Barbados: 0.581 typical gaps (standard deviations), 1.24 typical gaps (standard deviations)Bhutan: 0.277 typical gaps (standard deviations), 0.61 typical gaps (standard deviations)Botswana: 0.469 typical gaps (standard deviations), 0.872 typical gaps (standard deviations)Central African Republic: -1.65 typical gaps (standard deviations), -1.02 typical gaps (standard deviations)Canada: 1.06 typical gaps (standard deviations), 1.36 typical gaps (standard deviations)Switzerland: 0.92 typical gaps (standard deviations), 1.47 typical gaps (standard deviations)Chile: 0.979 typical gaps (standard deviations), 1.32 typical gaps (standard deviations)China: 0.674 typical gaps (standard deviations), -1.2 typical gaps (standard deviations)Cote d'Ivoire: -0.0434 typical gaps (standard deviations), -0.116 typical gaps (standard deviations)Cameroon: -0.125 typical gaps (standard deviations), -0.834 typical gaps (standard deviations)Congo, Dem. Rep.: -0.251 typical gaps (standard deviations), -0.824 typical gaps (standard deviations)Congo, Rep.: 0.119 typical gaps (standard deviations), -0.925 typical gaps (standard deviations)Colombia: 0.63 typical gaps (standard deviations), 0.733 typical gaps (standard deviations)Comoros: 0.00771 typical gaps (standard deviations), -0.464 typical gaps (standard deviations)Cabo Verde: -0.216 typical gaps (standard deviations), 1.15 typical gaps (standard deviations)Costa Rica: 0.629 typical gaps (standard deviations), 1.34 typical gaps (standard deviations)Cyprus: 1.02 typical gaps (standard deviations), 1.1 typical gaps (standard deviations)Czechia: 1.08 typical gaps (standard deviations), 1.31 typical gaps (standard deviations)Germany: 0.938 typical gaps (standard deviations), 1.36 typical gaps (standard deviations)Djibouti: -0.825 typical gaps (standard deviations), -0.784 typical gaps (standard deviations)Denmark: 0.941 typical gaps (standard deviations), 1.47 typical gaps (standard deviations)Dominican Republic: 0.651 typical gaps (standard deviations), 0.621 typical gaps (standard deviations)Algeria: 0.663 typical gaps (standard deviations), -0.695 typical gaps (standard deviations)Ecuador: 0.722 typical gaps (standard deviations), 0.447 typical gaps (standard deviations)Egypt, Arab Rep.: 0.489 typical gaps (standard deviations), -0.987 typical gaps (standard deviations)Spain: 0.983 typical gaps (standard deviations), 1.32 typical gaps (standard deviations)Estonia: 0.841 typical gaps (standard deviations), 1.41 typical gaps (standard deviations)Ethiopia: -0.777 typical gaps (standard deviations), -0.741 typical gaps (standard deviations)Finland: 1.02 typical gaps (standard deviations), 1.38 typical gaps (standard deviations)Fiji: 0.887 typical gaps (standard deviations), 0.57 typical gaps (standard deviations)France: 0.907 typical gaps (standard deviations), 1.24 typical gaps (standard deviations)Gabon: -0.00264 typical gaps (standard deviations), -0.529 typical gaps (standard deviations)United Kingdom: 1.19 typical gaps (standard deviations), 1.27 typical gaps (standard deviations)Georgia: 0.697 typical gaps (standard deviations), 0.0179 typical gaps (standard deviations)Ghana: 0.168 typical gaps (standard deviations), 0.845 typical gaps (standard deviations)Guinea: -0.598 typical gaps (standard deviations), -0.676 typical gaps (standard deviations)Gambia, The: -0.345 typical gaps (standard deviations), 0.362 typical gaps (standard deviations)Guinea-Bissau: -1.3 typical gaps (standard deviations), -0.465 typical gaps (standard deviations)Equatorial Guinea: -0.759 typical gaps (standard deviations), -1.32 typical gaps (standard deviations)Greece: 1.31 typical gaps (standard deviations), 0.914 typical gaps (standard deviations)Guatemala: 0.22 typical gaps (standard deviations), 0.291 typical gaps (standard deviations)Guyana: 0.39 typical gaps (standard deviations), 0.538 typical gaps (standard deviations)Hong Kong SAR, China: 1.34 typical gaps (standard deviations), -0.536 typical gaps (standard deviations)Honduras: 0.0516 typical gaps (standard deviations), 0.146 typical gaps (standard deviations)Croatia: 0.985 typical gaps (standard deviations), 0.865 typical gaps (standard deviations)Hungary: 0.83 typical gaps (standard deviations), 0.225 typical gaps (standard deviations)Indonesia: 0.591 typical gaps (standard deviations), 0.125 typical gaps (standard deviations)India: 0.605 typical gaps (standard deviations), 0.146 typical gaps (standard deviations)Ireland: 1.18 typical gaps (standard deviations), 1.41 typical gaps (standard deviations)Iran, Islamic Rep.: 0.667 typical gaps (standard deviations), -1.26 typical gaps (standard deviations)Iraq: -0.133 typical gaps (standard deviations), -0.488 typical gaps (standard deviations)Iceland: 1.26 typical gaps (standard deviations), 1.32 typical gaps (standard deviations)Israel: 0.804 typical gaps (standard deviations), 0.783 typical gaps (standard deviations)Italy: 0.94 typical gaps (standard deviations), 1 typical gaps (standard deviations)Jamaica: 0.446 typical gaps (standard deviations), 1.01 typical gaps (standard deviations)Jordan: 0.68 typical gaps (standard deviations), -0.271 typical gaps (standard deviations)Japan: 1.04 typical gaps (standard deviations), 1.28 typical gaps (standard deviations)Kazakhstan: 0.74 typical gaps (standard deviations), -0.796 typical gaps (standard deviations)Kenya: 0.0734 typical gaps (standard deviations), 0.217 typical gaps (standard deviations)Kyrgyz Republic: 0.764 typical gaps (standard deviations), -0.725 typical gaps (standard deviations)Cambodia: 0.174 typical gaps (standard deviations), -1.01 typical gaps (standard deviations)Korea, Rep.: 1.03 typical gaps (standard deviations), 1.05 typical gaps (standard deviations)Kuwait: 0.25 typical gaps (standard deviations), -0.696 typical gaps (standard deviations)Lao PDR: -0.35 typical gaps (standard deviations), -1.14 typical gaps (standard deviations)Lebanon: 0.088 typical gaps (standard deviations), -0.112 typical gaps (standard deviations)Liberia: -1.22 typical gaps (standard deviations), 0.416 typical gaps (standard deviations)St. Lucia: 0.462 typical gaps (standard deviations), 0.552 typical gaps (standard deviations)Sri Lanka: 0.421 typical gaps (standard deviations), 0.602 typical gaps (standard deviations)Lesotho: -0.337 typical gaps (standard deviations), 0.671 typical gaps (standard deviations)Lithuania: 0.928 typical gaps (standard deviations), 1.14 typical gaps (standard deviations)Luxembourg: 0.66 typical gaps (standard deviations), 1.38 typical gaps (standard deviations)Latvia: 0.923 typical gaps (standard deviations), 1.22 typical gaps (standard deviations)Morocco: 0.345 typical gaps (standard deviations), -0.351 typical gaps (standard deviations)Moldova: 0.734 typical gaps (standard deviations), 0.5 typical gaps (standard deviations)Madagascar: -0.569 typical gaps (standard deviations), -0.193 typical gaps (standard deviations)Maldives: 0.427 typical gaps (standard deviations), 0.0802 typical gaps (standard deviations)Mexico: 0.636 typical gaps (standard deviations), 0.134 typical gaps (standard deviations)North Macedonia: 0.658 typical gaps (standard deviations), 0.352 typical gaps (standard deviations)Mali: -1.24 typical gaps (standard deviations), -0.753 typical gaps (standard deviations)Malta: 0.945 typical gaps (standard deviations), 1.12 typical gaps (standard deviations)Myanmar: -0.0676 typical gaps (standard deviations), -1.39 typical gaps (standard deviations)Montenegro: 0.943 typical gaps (standard deviations), 0.55 typical gaps (standard deviations)Mongolia: 0.749 typical gaps (standard deviations), 0.716 typical gaps (standard deviations)Mozambique: -0.56 typical gaps (standard deviations), -0.298 typical gaps (standard deviations)Mauritania: -0.911 typical gaps (standard deviations), -0.421 typical gaps (standard deviations)Mauritius: 0.621 typical gaps (standard deviations), 1.07 typical gaps (standard deviations)Malawi: -0.546 typical gaps (standard deviations), 0.576 typical gaps (standard deviations)Malaysia: 0.529 typical gaps (standard deviations), 0.169 typical gaps (standard deviations)Namibia: 0.228 typical gaps (standard deviations), 0.69 typical gaps (standard deviations)Niger: -1.04 typical gaps (standard deviations), -0.548 typical gaps (standard deviations)Nigeria: -0.241 typical gaps (standard deviations), -0.0132 typical gaps (standard deviations)Nicaragua: 0.168 typical gaps (standard deviations), -1.24 typical gaps (standard deviations)Netherlands: 1.27 typical gaps (standard deviations), 1.32 typical gaps (standard deviations)Norway: 1 typical gaps (standard deviations), 1.43 typical gaps (standard deviations)Nepal: 0.452 typical gaps (standard deviations), 0.441 typical gaps (standard deviations)New Zealand: 1.44 typical gaps (standard deviations), 1.32 typical gaps (standard deviations)Oman: 0.293 typical gaps (standard deviations), -0.665 typical gaps (standard deviations)Pakistan: -0.556 typical gaps (standard deviations), -0.437 typical gaps (standard deviations)Panama: 0.393 typical gaps (standard deviations), 0.84 typical gaps (standard deviations)Peru: 0.773 typical gaps (standard deviations), 0.522 typical gaps (standard deviations)Philippines: 0.548 typical gaps (standard deviations), 0.0585 typical gaps (standard deviations)Papua New Guinea: -0.297 typical gaps (standard deviations), 0.227 typical gaps (standard deviations)Poland: 0.952 typical gaps (standard deviations), 0.996 typical gaps (standard deviations)Portugal: 1.02 typical gaps (standard deviations), 1.26 typical gaps (standard deviations)Paraguay: 0.452 typical gaps (standard deviations), 0.349 typical gaps (standard deviations)Qatar: 0.734 typical gaps (standard deviations), -0.908 typical gaps (standard deviations)Romania: 0.584 typical gaps (standard deviations), 0.749 typical gaps (standard deviations)Russian Federation: 0.85 typical gaps (standard deviations), -1.14 typical gaps (standard deviations)Rwanda: -0.127 typical gaps (standard deviations), -0.868 typical gaps (standard deviations)Saudi Arabia: 0.8 typical gaps (standard deviations), -1.14 typical gaps (standard deviations)Sudan: -0.831 typical gaps (standard deviations), -1.22 typical gaps (standard deviations)Senegal: -0.815 typical gaps (standard deviations), 0.683 typical gaps (standard deviations)Singapore: 1.26 typical gaps (standard deviations), 0.0449 typical gaps (standard deviations)Solomon Islands: -0.0603 typical gaps (standard deviations), 0.697 typical gaps (standard deviations)Sierra Leone: -0.279 typical gaps (standard deviations), 0.299 typical gaps (standard deviations)El Salvador: 0.37 typical gaps (standard deviations), -0.352 typical gaps (standard deviations)Somalia, Fed. Rep.: -2.1 typical gaps (standard deviations), -1.01 typical gaps (standard deviations)Serbia: 0.761 typical gaps (standard deviations), -0.0738 typical gaps (standard deviations)Sao Tome and Principe: 0.172 typical gaps (standard deviations), 0.8 typical gaps (standard deviations)Suriname: -0.157 typical gaps (standard deviations), 0.996 typical gaps (standard deviations)Slovak Republic: 0.801 typical gaps (standard deviations), 1.02 typical gaps (standard deviations)Slovenia: 1.18 typical gaps (standard deviations), 1.19 typical gaps (standard deviations)Sweden: 0.968 typical gaps (standard deviations), 1.42 typical gaps (standard deviations)Eswatini: 0.404 typical gaps (standard deviations), -1.05 typical gaps (standard deviations)Seychelles: 0.782 typical gaps (standard deviations), 0.975 typical gaps (standard deviations)Syrian Arab Republic: -0.332 typical gaps (standard deviations), -1.05 typical gaps (standard deviations)Chad: -1.2 typical gaps (standard deviations), -0.999 typical gaps (standard deviations)Togo: 0.075 typical gaps (standard deviations), -0.371 typical gaps (standard deviations)Thailand: 0.764 typical gaps (standard deviations), -0.383 typical gaps (standard deviations)Tajikistan: 0.525 typical gaps (standard deviations), -1.34 typical gaps (standard deviations)Turkmenistan: 0.598 typical gaps (standard deviations), -1.39 typical gaps (standard deviations)Timor-Leste: 0.12 typical gaps (standard deviations), 0.779 typical gaps (standard deviations)Trinidad and Tobago: 0.581 typical gaps (standard deviations), 1.03 typical gaps (standard deviations)Tunisia: 0.496 typical gaps (standard deviations), -0.257 typical gaps (standard deviations)Turkiye: 1.03 typical gaps (standard deviations), -0.691 typical gaps (standard deviations)Tanzania: -0.351 typical gaps (standard deviations), -0.315 typical gaps (standard deviations)Uganda: -0.832 typical gaps (standard deviations), -0.646 typical gaps (standard deviations)Ukraine: 0.784 typical gaps (standard deviations), -0.0525 typical gaps (standard deviations)Uruguay: 0.9 typical gaps (standard deviations), 1.39 typical gaps (standard deviations)United States: 1.11 typical gaps (standard deviations), 0.998 typical gaps (standard deviations)Uzbekistan: 0.848 typical gaps (standard deviations), -1.04 typical gaps (standard deviations)Viet Nam: 0.537 typical gaps (standard deviations), -0.933 typical gaps (standard deviations)Vanuatu: 0.198 typical gaps (standard deviations), 0.885 typical gaps (standard deviations)South Africa: 0.665 typical gaps (standard deviations), 0.883 typical gaps (standard deviations)Zambia: -0.123 typical gaps (standard deviations), 0.212 typical gaps (standard deviations)Zimbabwe: 0.181 typical gaps (standard deviations), -0.609 typical gaps (standard deviations)BELBLRCAFHKGLBRNLDNZLRUSSENSOMTCD

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.5033.7e-12168
By rank (Spearman), not adjusted+0.5564.8e-15168
Standard (Pearson), adjusted for national income+0.1790.021168
By rank (Spearman), adjusted for national income+0.2320.003168

The rank version uses only each country’s place in line, from lowest to highest, so a few extreme countries count for less. The adjusted and unadjusted versions use the same 168 countries: those that report both measures and GDP per person. So the gap between them comes from the adjustment, not from a change in which countries are counted. Drop in the size of r after adjusting: +0.324 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.150 (without GNQ) to +0.200 (without TJK). The bar above shows that range on a scale from −1 to +1, with the solid line at the full result. The single country that moves r most: GNQ (-0.029).

Within each region

Countries are not separate, unrelated cases, and neighbors share a lot. A link that holds inside each region is far more believable than one that shows up only when comparing regions.

nr
East Asia & Pacific21+0.47
Europe & Central Asia49+0.33
Latin America & Caribbean24+0.32
Middle East, North Africa, Afghanistan & Pakistan20+0.19
Sub-Saharan Africa46+0.29

By income third

If the link shows up only in the richest third of countries, it is a feature of rich countries, not a general pattern.

nr
Poorest third56+0.22
Middle third56+0.07
Richest third56+0.41

By largest religious group

Countries grouped by a label they share, such as main religion, rather than by a number. Groups of fewer than twelve countries are not shown. These groups differ in income, region and history all at once. So a gap between them is a place to start asking questions, not an answer.

nr
Christians100+0.21
Muslims46+0.03

By last european coloniser

Countries grouped by a label they share, such as main religion, rather than by a number. Groups of fewer than twelve countries are not shown. These groups differ in income, region and history all at once. So a gap between them is a place to start asking questions, not an answer.

nr
France24+0.01
Never a European colony21-0.06
Spain19+0.69
United Kingdom50+0.45

Without outliers (countries far outside the middle half of countries on either measure, by more than one and a half times the width of that middle half): r = +0.177 after dropping 2 countries.

Two series, one country

Both measures over the years for one country you pick. The two charts are stacked so they share only the years along the bottom.

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Over time, within countries

Everything above compares countries with each other at one moment. This section compares each country only with itself over 0years. So a link here can’t come from anything about a country that stays the same, such as its history, geography, institutions or culture.

Not enough history inside each country to look at this over time. That needs countries measured for several years in a row, and at least one of these measures is measured too rarely.

The data


typical gaps (standard deviations)

typical gaps (standard deviations)
Years
New Zealand NZL1.441.322023, 2025
Hong Kong SAR, China HKG1.34-0.5362024, 2025
Greece GRC1.310.9142023, 2025
Netherlands NLD1.271.322023, 2025
Iceland ISL1.261.322023, 2025
Singapore SGP1.260.04492023, 2025
Belgium BEL1.251.412023, 2025
United Kingdom GBR1.191.272023, 2025
Ireland IRL1.181.412022, 2025
Slovenia SVN1.181.192023, 2025
United States USA1.110.9982022, 2025
Czechia CZE1.081.312023, 2025
Canada CAN1.061.362023, 2025
Japan JPN1.041.282023, 2025
Argentina ARG1.030.8152023, 2025

uis; undp_hdr; wdi
fh; un_sdg; vdem; wdi; wgi

Sources

Education score

Education score

PlaceStats · via PlaceStats · Derived work; each member keeps its own licence · updated recomputed with the panel

The average of 10 measures from 3 publishers. Each measure is first put on a common scale: 0 is the average country in an average year, and 1 is a typical gap between countries (a standard deviation). Each is turned so that higher is better. Measures are averaged within each publisher first, so a publisher with many measures does not count for more. Members: Primary completion, Expected schooling, Mean years of schooling, Adult literacy, Pupil-teacher ratio, Primary enrollment, Out of school, primary, Secondary enrollment, Tertiary enrollment, Researchers.

Governance score

Governance score

PlaceStats · via PlaceStats · Derived work; each member keeps its own licence · updated recomputed with the panel

The average of 19 measures from 5 publishers. Each measure is first put on a common scale: 0 is the average country in an average year, and 1 is a typical gap between countries (a standard deviation). Each is turned so that higher is better. Measures are averaged within each publisher first, so a publisher with many measures does not count for more. Members: Civil liberties (FH), Political rights (FH), Pre-trial detainee share, Civil society participation, Political corruption, Electoral democracy, Freedom of association, Freedom of expression, Free and fair elections, Liberal democracy, Participatory democracy, Political civil liberties, Birth registration, Control of corruption, Government effectiveness, Political stability, Rule of law, Regulatory quality, Voice and accountability.

How this was computed

Data used: most recent value in 2010-2025; values come from 2010–2025. To adjust for income, each measure is first predicted from GDP per person (in percentage terms, on a log scale) with a straight-line fit. Only what is left over is then compared. This is called a partial correlation. The line is drawn the standard way (ordinary least squares), which picks the line that comes closest to all the countries at once. The error margins allow for countries in the same region resembling each other, using 7 World Bank regions. The q-value corrects for testing all 12,497 pairs at once, using the Benjamini–Hochberg method. Underlying data last updated DYB 2024. How the country data works · explore Education score and Governance score

This page shows that two measures go together. It does not show that Education score changes Governance score, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.

More links with Education score or Governance score