placestats

Governance score vs. PISA reading

Fades after adjusting for income

Across 84 countries, Governance score and PISA reading rise and fall together at r = +0.52 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to +0.30, which could easily be chance (q = 0.51, 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 pisa reading, 385 to 479 PISA points, governance score is better by 0.711 typical gaps at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.569 typical gaps.

Link before adjusting (r)+0.522p = 3.6e-7 · 84 countries
After adjusting for national income+0.296p = 0.007 · likely range [+0.09, +0.48]
p, allowing for regions0.242standard error 0.216 · 5 regions
Check for luck (q)0.511across 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.

Governance score · typical gaps (standard deviations)link with income +0.53 · moderate
PISA reading · PISA pointslink with income +0.77 · high

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

Every country as a dot

Governance score · typical gaps (standard deviations) →PISA reading · PISA points →-1.261.47329543Albania: 0.323 typical gaps (standard deviations), 358 PISA pointsUnited Arab Emirates: -0.981 typical gaps (standard deviations), 417 PISA pointsArgentina: 0.815 typical gaps (standard deviations), 401 PISA pointsAustralia: 1.38 typical gaps (standard deviations), 498 PISA pointsAustria: 1.33 typical gaps (standard deviations), 480 PISA pointsBelgium: 1.41 typical gaps (standard deviations), 479 PISA pointsBulgaria: 0.74 typical gaps (standard deviations), 404 PISA pointsBosnia and Herzegovina: 0.0899 typical gaps (standard deviations), 403 PISA pointsBelarus: -1.26 typical gaps (standard deviations), 474 PISA pointsBrazil: 0.85 typical gaps (standard deviations), 410 PISA pointsCanada: 1.36 typical gaps (standard deviations), 507 PISA pointsSwitzerland: 1.47 typical gaps (standard deviations), 483 PISA pointsChile: 1.32 typical gaps (standard deviations), 448 PISA pointsColombia: 0.733 typical gaps (standard deviations), 409 PISA pointsCosta Rica: 1.34 typical gaps (standard deviations), 415 PISA pointsCyprus: 1.1 typical gaps (standard deviations), 381 PISA pointsCzechia: 1.31 typical gaps (standard deviations), 489 PISA pointsGermany: 1.36 typical gaps (standard deviations), 480 PISA pointsDenmark: 1.47 typical gaps (standard deviations), 489 PISA pointsDominican Republic: 0.621 typical gaps (standard deviations), 351 PISA pointsAlgeria: -0.695 typical gaps (standard deviations), 350 PISA pointsSpain: 1.32 typical gaps (standard deviations), 474 PISA pointsEstonia: 1.41 typical gaps (standard deviations), 511 PISA pointsFinland: 1.38 typical gaps (standard deviations), 490 PISA pointsFrance: 1.24 typical gaps (standard deviations), 474 PISA pointsUnited Kingdom: 1.27 typical gaps (standard deviations), 494 PISA pointsGeorgia: 0.0179 typical gaps (standard deviations), 374 PISA pointsGreece: 0.914 typical gaps (standard deviations), 438 PISA pointsGuatemala: 0.291 typical gaps (standard deviations), 374 PISA pointsHong Kong SAR, China: -0.536 typical gaps (standard deviations), 500 PISA pointsCroatia: 0.865 typical gaps (standard deviations), 475 PISA pointsHungary: 0.225 typical gaps (standard deviations), 473 PISA pointsIndonesia: 0.125 typical gaps (standard deviations), 359 PISA pointsIreland: 1.41 typical gaps (standard deviations), 516 PISA pointsIceland: 1.32 typical gaps (standard deviations), 436 PISA pointsIsrael: 0.783 typical gaps (standard deviations), 474 PISA pointsItaly: 1 typical gaps (standard deviations), 482 PISA pointsJamaica: 1.01 typical gaps (standard deviations), 410 PISA pointsJordan: -0.271 typical gaps (standard deviations), 342 PISA pointsJapan: 1.28 typical gaps (standard deviations), 516 PISA pointsKazakhstan: -0.796 typical gaps (standard deviations), 386 PISA pointsCambodia: -1.01 typical gaps (standard deviations), 329 PISA pointsKorea, Rep.: 1.05 typical gaps (standard deviations), 515 PISA pointsLebanon: -0.112 typical gaps (standard deviations), 353 PISA pointsLithuania: 1.14 typical gaps (standard deviations), 472 PISA pointsLuxembourg: 1.38 typical gaps (standard deviations), 470 PISA pointsLatvia: 1.22 typical gaps (standard deviations), 475 PISA pointsMorocco: -0.351 typical gaps (standard deviations), 339 PISA pointsMoldova: 0.5 typical gaps (standard deviations), 411 PISA pointsMexico: 0.134 typical gaps (standard deviations), 415 PISA pointsNorth Macedonia: 0.352 typical gaps (standard deviations), 359 PISA pointsMalta: 1.12 typical gaps (standard deviations), 445 PISA pointsMontenegro: 0.55 typical gaps (standard deviations), 405 PISA pointsMongolia: 0.716 typical gaps (standard deviations), 378 PISA pointsMalaysia: 0.169 typical gaps (standard deviations), 388 PISA pointsNetherlands: 1.32 typical gaps (standard deviations), 459 PISA pointsNorway: 1.43 typical gaps (standard deviations), 477 PISA pointsNew Zealand: 1.32 typical gaps (standard deviations), 501 PISA pointsPanama: 0.84 typical gaps (standard deviations), 392 PISA pointsPeru: 0.522 typical gaps (standard deviations), 408 PISA pointsPhilippines: 0.0585 typical gaps (standard deviations), 347 PISA pointsPoland: 0.996 typical gaps (standard deviations), 489 PISA pointsPortugal: 1.26 typical gaps (standard deviations), 477 PISA pointsParaguay: 0.349 typical gaps (standard deviations), 373 PISA pointsQatar: -0.908 typical gaps (standard deviations), 419 PISA pointsRomania: 0.749 typical gaps (standard deviations), 428 PISA pointsRussian Federation: -1.14 typical gaps (standard deviations), 479 PISA pointsSaudi Arabia: -1.14 typical gaps (standard deviations), 383 PISA pointsSingapore: 0.0449 typical gaps (standard deviations), 543 PISA pointsEl Salvador: -0.352 typical gaps (standard deviations), 365 PISA pointsSerbia: -0.0738 typical gaps (standard deviations), 440 PISA pointsSlovak Republic: 1.02 typical gaps (standard deviations), 447 PISA pointsSlovenia: 1.19 typical gaps (standard deviations), 469 PISA pointsSweden: 1.42 typical gaps (standard deviations), 487 PISA pointsThailand: -0.383 typical gaps (standard deviations), 379 PISA pointsTrinidad and Tobago: 1.03 typical gaps (standard deviations), 427 PISA pointsTunisia: -0.257 typical gaps (standard deviations), 361 PISA pointsTurkiye: -0.691 typical gaps (standard deviations), 456 PISA pointsUkraine: -0.0525 typical gaps (standard deviations), 428 PISA pointsUruguay: 1.39 typical gaps (standard deviations), 430 PISA pointsUnited States: 0.998 typical gaps (standard deviations), 504 PISA pointsUzbekistan: -1.04 typical gaps (standard deviations), 336 PISA pointsViet Nam: -0.933 typical gaps (standard deviations), 462 PISA pointsKosovo: 0.371 typical gaps (standard deviations), 342 PISA pointsBLRCYPDOMDZAESTIRLJPNKHMRUSSGPUZBXKX

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.5223.6e-784
By rank (Spearman), not adjusted+0.6079.0e-1084
Standard (Pearson), adjusted for national income+0.2960.00784
By rank (Spearman), adjusted for national income+0.3280.00284

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 84 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: +0.226 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.224 (without QAT) to +0.356 (without BLR). 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: QAT (-0.072).

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 & Pacific13+0.10
Europe & Central Asia44+0.05
Latin America & Caribbean15+0.59

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 third28+0.15
Middle third28+0.04
Richest third28+0.48

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
Christians55-0.01
Muslims16+0.07

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
Spain14+0.44
United Kingdom13+0.66

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 = +0.296 after dropping 0 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)
PISA points		Years
Denmark DNK1.474892025, 2022
Switzerland CHE1.474832025, 2022
Norway NOR1.434772025, 2022
Sweden SWE1.424872025, 2022
Ireland IRL1.415162025, 2022
Belgium BEL1.414792025, 2022
Estonia EST1.415112025, 2022
Uruguay URY1.394302025, 2022
Finland FIN1.384902025, 2022
Australia AUS1.384982025, 2022
Luxembourg LUX1.384702025, 2018
Germany DEU1.364802025, 2022
Canada CAN1.365072025, 2022
Costa Rica CRI1.344152025, 2022
Austria AUT1.334802025, 2022

fh; un_sdg; vdem; wdi; wgi
OECD databases as named on each indicator: PISA, Social Expenditure Database (SOCX), Income Distribution Database, Development Assistance Committee statistics, Family Database, Government at a Glance, Corporate Tax Statistics, employment and environment statistics

Sources

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.

PISA reading

PISA mean reading score

OECD · via Our World in Data · CC BY 4.0 (OECD terms and conditions) · updated annual, except the snapshots noted per indicator

How this was computed

Data used: most recent value in 2010-2025; values come from 2015–2025. 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 5 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 Governance score and PISA reading

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

More links with Governance score or PISA reading