placestats

Infrastructure score vs. Primary completion

Holds up after adjusting for income

Across 161 countries, Infrastructure score and Primary completion rise and fall together at r = +0.81 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to +0.44 (q = 0.037, allowing for the many pairs tested). Much of the first figure is that both measures rise with national income, but a moderate positive link remains.

Comparing countries across the middle half of primary completion, 82.1% to 99.5% of children, infrastructure score is better by 0.56 typical gaps at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.188 typical gaps.

Link before adjusting (r)+0.806p = 5.5e-38 · 161 countries
After adjusting for national income+0.438p = 6.7e-9 · likely range [+0.30, +0.56]
p, allowing for regions0.000standard error 0.051 · 7 regions
Check for luck (q)0.037across 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.

Infrastructure score · typical gaps (standard deviations)link with income +0.90 · proxy
Primary completion · % of childrenlink with income +0.83 · proxy

Both of these rise and fall closely with national income, so a strong link between them before adjusting was close to certain. Read the adjusted figure, not the first one.

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

Every country as a dot

Infrastructure score · typical gaps (standard deviations) →Primary completion · % of children →-1.011.7228.8%100%Afghanistan: 0.116 typical gaps (standard deviations), 55.4% of childrenAngola: -0.152 typical gaps (standard deviations), 65.2% of childrenAlbania: 1.14 typical gaps (standard deviations), 97.4% of childrenArgentina: 1.25 typical gaps (standard deviations), 96.7% of childrenArmenia: 1.09 typical gaps (standard deviations), 99.5% of childrenAustralia: 1.5 typical gaps (standard deviations), 99.5% of childrenAustria: 1.37 typical gaps (standard deviations), 100% of childrenAzerbaijan: 1.19 typical gaps (standard deviations), 98.4% of childrenBurundi: -0.835 typical gaps (standard deviations), 60.5% of childrenBelgium: 1.64 typical gaps (standard deviations), 98.9% of childrenBenin: 0.00537 typical gaps (standard deviations), 70.1% of childrenBurkina Faso: -0.245 typical gaps (standard deviations), 72.2% of childrenBangladesh: 0.649 typical gaps (standard deviations), 90.8% of childrenBulgaria: 1.25 typical gaps (standard deviations), 99.1% of childrenBosnia and Herzegovina: 1.29 typical gaps (standard deviations), 99.8% of childrenBelarus: 1.48 typical gaps (standard deviations), 99.8% of childrenBelize: 0.573 typical gaps (standard deviations), 90.2% of childrenBolivia: 0.886 typical gaps (standard deviations), 98.5% of childrenBrazil: 1.18 typical gaps (standard deviations), 93% of childrenBarbados: 1.31 typical gaps (standard deviations), 99.5% of childrenBhutan: 0.847 typical gaps (standard deviations), 93.6% of childrenBotswana: 0.5 typical gaps (standard deviations), 99% of childrenCentral African Republic: -1.01 typical gaps (standard deviations), 30.8% of childrenCanada: 1.56 typical gaps (standard deviations), 99.9% of childrenSwitzerland: 1.7 typical gaps (standard deviations), 99.8% of childrenChile: 1.25 typical gaps (standard deviations), 97.4% of childrenChina: 1.66 typical gaps (standard deviations), 99% of childrenCote d'Ivoire: 0.207 typical gaps (standard deviations), 78.8% of childrenCameroon: 0.557 typical gaps (standard deviations), 77.8% of childrenCongo, Dem. Rep.: -0.672 typical gaps (standard deviations), 68.4% of childrenCongo, Rep.: 0.312 typical gaps (standard deviations), 93.9% of childrenColombia: 1.01 typical gaps (standard deviations), 95.5% of childrenComoros: 0.259 typical gaps (standard deviations), 86.1% of childrenCosta Rica: 1.19 typical gaps (standard deviations), 98.9% of childrenCyprus: 1.47 typical gaps (standard deviations), 99% of childrenCzechia: 1.48 typical gaps (standard deviations), 99.9% of childrenGermany: 1.65 typical gaps (standard deviations), 100% of childrenDjibouti: 0.0105 typical gaps (standard deviations), 89.4% of childrenDenmark: 1.65 typical gaps (standard deviations), 99.9% of childrenDominican Republic: 0.956 typical gaps (standard deviations), 96.1% of childrenAlgeria: 0.932 typical gaps (standard deviations), 96.5% of childrenEcuador: 0.989 typical gaps (standard deviations), 99.5% of childrenEgypt, Arab Rep.: 0.864 typical gaps (standard deviations), 96.3% of childrenSpain: 1.55 typical gaps (standard deviations), 98.6% of childrenEstonia: 1.45 typical gaps (standard deviations), 99.5% of childrenEthiopia: -0.309 typical gaps (standard deviations), 64.6% of childrenFinland: 1.48 typical gaps (standard deviations), 99.7% of childrenFiji: 0.665 typical gaps (standard deviations), 98.9% of childrenFrance: 1.7 typical gaps (standard deviations), 99.6% of childrenGabon: 0.665 typical gaps (standard deviations), 74.3% of childrenUnited Kingdom: 1.6 typical gaps (standard deviations), 99.9% of childrenGeorgia: 1.29 typical gaps (standard deviations), 99.8% of childrenGhana: 0.59 typical gaps (standard deviations), 79.1% of childrenGuinea: 0.156 typical gaps (standard deviations), 61% of childrenGambia, The: 0.215 typical gaps (standard deviations), 74.8% of childrenGuinea-Bissau: -0.158 typical gaps (standard deviations), 30.5% of childrenEquatorial Guinea: -0.269 typical gaps (standard deviations), 73.6% of childrenGreece: 1.57 typical gaps (standard deviations), 99.3% of childrenGuatemala: 0.576 typical gaps (standard deviations), 87% of childrenGuyana: 0.809 typical gaps (standard deviations), 99.2% of childrenHonduras: 0.417 typical gaps (standard deviations), 89.6% of childrenCroatia: 1.28 typical gaps (standard deviations), 99.8% of childrenHaiti: -0.312 typical gaps (standard deviations), 50.5% of childrenHungary: 1.5 typical gaps (standard deviations), 99.2% of childrenIndonesia: 0.742 typical gaps (standard deviations), 98.9% of childrenIndia: 0.527 typical gaps (standard deviations), 96.5% of childrenIreland: 1.43 typical gaps (standard deviations), 99.8% of childrenIran, Islamic Rep.: 0.97 typical gaps (standard deviations), 96.7% of childrenIraq: 1.04 typical gaps (standard deviations), 83.3% of childrenIceland: 1.53 typical gaps (standard deviations), 97.4% of childrenIsrael: 1.31 typical gaps (standard deviations), 100% of childrenItaly: 1.36 typical gaps (standard deviations), 99.9% of childrenJamaica: 1.06 typical gaps (standard deviations), 99.4% of childrenJordan: 0.776 typical gaps (standard deviations), 98.5% of childrenJapan: 1.45 typical gaps (standard deviations), 100% of childrenKazakhstan: 1.09 typical gaps (standard deviations), 99.7% of childrenKenya: 0.22 typical gaps (standard deviations), 88.4% of childrenKyrgyz Republic: 0.943 typical gaps (standard deviations), 99.4% of childrenCambodia: 0.689 typical gaps (standard deviations), 82.7% of childrenKiribati: 0.485 typical gaps (standard deviations), 94.4% of childrenKorea, Rep.: 1.72 typical gaps (standard deviations), 100% of childrenLao PDR: 0.399 typical gaps (standard deviations), 70.1% of childrenLiberia: -0.767 typical gaps (standard deviations), 29.8% of childrenSt. Lucia: 0.881 typical gaps (standard deviations), 99.6% of childrenLesotho: -0.0187 typical gaps (standard deviations), 79.8% of childrenLithuania: 1.29 typical gaps (standard deviations), 99.7% of childrenLuxembourg: 1.59 typical gaps (standard deviations), 98.6% of childrenLatvia: 1.28 typical gaps (standard deviations), 99.6% of childrenMorocco: 0.928 typical gaps (standard deviations), 84.6% of childrenMoldova: 1.23 typical gaps (standard deviations), 98.8% of childrenMadagascar: -0.434 typical gaps (standard deviations), 54% of childrenMaldives: 1.11 typical gaps (standard deviations), 99.4% of childrenMexico: 1.13 typical gaps (standard deviations), 98.2% of childrenNorth Macedonia: 1.36 typical gaps (standard deviations), 99.5% of childrenMali: -0.495 typical gaps (standard deviations), 50% of childrenMalta: 1.63 typical gaps (standard deviations), 98.1% of childrenMyanmar: 0.298 typical gaps (standard deviations), 89.8% of childrenMontenegro: 1.37 typical gaps (standard deviations), 98.9% of childrenMongolia: 1.03 typical gaps (standard deviations), 99.7% of childrenMozambique: -0.592 typical gaps (standard deviations), 53.5% of childrenMauritania: 0.0018 typical gaps (standard deviations), 51.8% of childrenMauritius: 1.17 typical gaps (standard deviations), 99.9% of childrenMalawi: -0.672 typical gaps (standard deviations), 57.7% of childrenMalaysia: 1.09 typical gaps (standard deviations), 99.8% of childrenNamibia: 0.203 typical gaps (standard deviations), 86.3% of childrenNiger: -0.7 typical gaps (standard deviations), 77.5% of childrenNigeria: -0.0861 typical gaps (standard deviations), 76.8% of childrenNicaragua: 0.574 typical gaps (standard deviations), 77.7% of childrenNetherlands: 1.63 typical gaps (standard deviations), 99.8% of childrenNorway: 1.68 typical gaps (standard deviations), 99.8% of childrenNepal: 0.616 typical gaps (standard deviations), 90.8% of childrenNaoero: 0.872 typical gaps (standard deviations), 89.2% of childrenPakistan: 0.386 typical gaps (standard deviations), 59.5% of childrenPanama: 0.927 typical gaps (standard deviations), 95.1% of childrenPeru: 0.907 typical gaps (standard deviations), 98.1% of childrenPhilippines: 0.696 typical gaps (standard deviations), 96.2% of childrenPapua New Guinea: -0.611 typical gaps (standard deviations), 66% of childrenPoland: 1.24 typical gaps (standard deviations), 99.7% of childrenPortugal: 1.6 typical gaps (standard deviations), 99.5% of childrenParaguay: 0.928 typical gaps (standard deviations), 94.9% of childrenWest Bank and Gaza: 0.774 typical gaps (standard deviations), 99.6% of childrenQatar: 1.06 typical gaps (standard deviations), 100% of childrenRomania: 1.45 typical gaps (standard deviations), 99.1% of childrenRussian Federation: 1.32 typical gaps (standard deviations), 99.7% of childrenRwanda: 0.0662 typical gaps (standard deviations), 71.9% of childrenSudan: -0.572 typical gaps (standard deviations), 75.6% of childrenSenegal: 0.482 typical gaps (standard deviations), 65.7% of childrenSierra Leone: -0.336 typical gaps (standard deviations), 68.8% of childrenEl Salvador: 0.822 typical gaps (standard deviations), 93.7% of childrenSomalia, Fed. Rep.: -0.395 typical gaps (standard deviations), 28.8% of childrenSerbia: 1.38 typical gaps (standard deviations), 99.7% of childrenSao Tome and Principe: 0.187 typical gaps (standard deviations), 93.7% of childrenSuriname: 0.901 typical gaps (standard deviations), 91.3% of childrenSlovak Republic: 1.4 typical gaps (standard deviations), 99.8% of childrenSlovenia: 1.42 typical gaps (standard deviations), 99.5% of childrenSweden: 1.57 typical gaps (standard deviations), 100% of childrenEswatini: 0.534 typical gaps (standard deviations), 82.5% of childrenSyrian Arab Republic: 0.27 typical gaps (standard deviations), 98.1% of childrenChad: -0.72 typical gaps (standard deviations), 37.8% of childrenTogo: -0.0274 typical gaps (standard deviations), 87.8% of childrenThailand: 1.06 typical gaps (standard deviations), 99.2% of childrenTajikistan: 0.389 typical gaps (standard deviations), 98.8% of childrenTurkmenistan: 0.294 typical gaps (standard deviations), 99.8% of childrenTimor-Leste: 0.389 typical gaps (standard deviations), 82.1% of childrenTonga: 0.595 typical gaps (standard deviations), 98.4% of childrenTrinidad and Tobago: 1.22 typical gaps (standard deviations), 98% of childrenTunisia: 0.956 typical gaps (standard deviations), 96.9% of childrenTurkiye: 1.19 typical gaps (standard deviations), 98% of childrenTuvalu: 0.208 typical gaps (standard deviations), 98.8% of childrenTanzania: -0.0741 typical gaps (standard deviations), 75.7% of childrenUganda: -0.319 typical gaps (standard deviations), 30.4% of childrenUkraine: 0.97 typical gaps (standard deviations), 99.6% of childrenUruguay: 1.41 typical gaps (standard deviations), 97.9% of childrenUnited States: 1.53 typical gaps (standard deviations), 100% of childrenUzbekistan: 1.42 typical gaps (standard deviations), 99.8% of childrenViet Nam: 1.17 typical gaps (standard deviations), 98.6% of childrenVanuatu: -0.0444 typical gaps (standard deviations), 79.8% of childrenSamoa: 0.0591 typical gaps (standard deviations), 98.5% of childrenSouth Africa: 0.709 typical gaps (standard deviations), 97.1% of childrenZambia: -0.161 typical gaps (standard deviations), 67.4% of childrenZimbabwe: 0.0863 typical gaps (standard deviations), 86.9% of childrenCAFCHEFRAGNBKORLBRNERSOMTUVUGAWSM

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.8065.5e-38161
By rank (Spearman), not adjusted+0.8321.3e-42161
Standard (Pearson), adjusted for national income+0.4386.7e-9161
By rank (Spearman), adjusted for national income+0.3203.6e-5161

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 161 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: +0.367 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.419 (without PSE) to +0.459 (without SOM). 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: SOM (+0.021).

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 & Pacific22+0.38
Europe & Central Asia48+0.03
Latin America & Caribbean25+0.67
Middle East, North Africa, Afghanistan & Pakistan15+0.15
Sub-Saharan Africa44+0.35

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 third54+0.37
Middle third53+0.49
Richest third54+0.22

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
Christians101+0.51
Muslims41+0.40

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+0.50
Never a European colony19+0.47
Spain19+0.71
United Kingdom47+0.32

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 = +0.451 after dropping 12 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)
% of children		Years
Korea, Rep. KOR1.72100%2024, 2025
Switzerland CHE1.799.8%2024, 2025
France FRA1.799.6%2024, 2025
Norway NOR1.6899.8%2024, 2025
China CHN1.6699%2024, 2025
Denmark DNK1.6599.9%2024, 2025
Germany DEU1.65100%2024, 2025
Belgium BEL1.6498.9%2024, 2025
Malta MLT1.6398.1%2024, 2025
Netherlands NLD1.6399.8%2024, 2025
Portugal PRT1.699.5%2024, 2025
United Kingdom GBR1.699.9%2024, 2025
Luxembourg LUX1.5998.6%2024, 2025
Greece GRC1.5799.3%2024, 2025
Sweden SWE1.57100%2024, 2025

wdi
UNESCO Institute for Statistics, SDG indicator 4.1.2 modelled estimates

Sources

Infrastructure score

Infrastructure score

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

The average of 5 measures from 1 publisher. 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: Electricity access, Slum share of urban population, Mobile subscriptions, Fixed broadband, Internet users.

Primary completion

Primary completion rate, modelled estimate

UNESCO Institute for Statistics · via Our World in Data · CC BY 3.0 IGO · updated annual

The share of children who finish primary school. UNESCO estimates it from household surveys and uses a statistical model to fill in across years. It is not the World Bank's primary completion rate, which is a ratio built from school enrolment counts of children entering the last grade. This one asks whether the child actually finished.

How this was computed

Data used: most recent value in 2010-2025; values come from 2022–2025. 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 Infrastructure score and Primary completion

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

More links with Infrastructure score or Primary completion