placestats

Researchers vs. Secondary enrollment

Fades after adjusting for income

Across 129 countries, Researchers and Secondary enrollment rise and fall together at r = +0.62 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to +0.14, which could easily be chance (q = 0.57, 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 secondary enrollment, 79.6% to 104% gross, researchers is better by 1,423 per million people at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 401 per million people.

Link before adjusting (r)+0.618p = 6.3e-15 · 129 countries
After adjusting for national income+0.136p = 0.125 · likely range [-0.04, +0.30]
p, allowing for regions0.257standard error 0.109 · 7 regions
Check for luck (q)0.574across 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.

Researchers · per million peoplelink with income +0.85 · proxy
Secondary enrollment · % grosslink with income +0.71 · high

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

Researchers · per million people →Secondary enrollment · % gross →1.459,47219.9%143%Angola: 18.9 per million people, 51.5% grossAlbania: 429 per million people, 108% grossUnited Arab Emirates: 2,607 per million people, 102% grossArgentina: 1,313 per million people, 106% grossArmenia: 942 per million people, 90.9% grossAustralia: 4,569 per million people, 132% grossAustria: 6,634 per million people, 101% grossAzerbaijan: 1,663 per million people, 91.1% grossBurundi: 22.5 per million people, 23.1% grossBelgium: 5,990 per million people, 143% grossBurkina Faso: 46.6 per million people, 30% grossBulgaria: 2,401 per million people, 94.8% grossBahrain: 849 per million people, 98.8% grossBosnia and Herzegovina: 705 per million people, 87.9% grossBelarus: 1,568 per million people, 94.8% grossBolivia: 63.1 per million people, 90.5% grossBrazil: 903 per million people, 104% grossBrunei Darussalam: 506 per million people, 91.8% grossBhutan: 236 per million people, 86.2% grossBotswana: 180 per million people, 70.6% grossCanada: 5,624 per million people, 104% grossSwitzerland: 6,108 per million people, 101% grossChile: 707 per million people, 106% grossChina: 2,107 per million people, 92.3% grossCongo, Dem. Rep.: 10.1 per million people, 55.5% grossCongo, Rep.: 127 per million people, 50.5% grossColombia: 90.2 per million people, 102% grossCabo Verde: 125 per million people, 96.4% grossCosta Rica: 508 per million people, 122% grossCyprus: 1,686 per million people, 107% grossCzechia: 4,505 per million people, 97.6% grossGermany: 5,926 per million people, 100% grossDenmark: 8,838 per million people, 126% grossDominican Republic: 20 per million people, 76.4% grossAlgeria: 1,764 per million people, 105% grossEcuador: 400 per million people, 92.8% grossEgypt, Arab Rep.: 1,120 per million people, 84.8% grossSpain: 3,654 per million people, 119% grossEstonia: 4,800 per million people, 109% grossEthiopia: 89 per million people, 33.9% grossFinland: 8,315 per million people, 142% grossFrance: 5,369 per million people, 104% grossUnited Kingdom: 4,473 per million people, 112% grossGeorgia: 1,896 per million people, 101% grossGhana: 87.5 per million people, 75.7% grossGambia, The: 50.9 per million people, 107% grossGreece: 5,283 per million people, 105% grossGuatemala: 1.45 per million people, 49.6% grossHong Kong SAR, China: 5,874 per million people, 107% grossHonduras: 188 per million people, 51.8% grossCroatia: 2,440 per million people, 105% grossHungary: 4,567 per million people, 107% grossIndonesia: 395 per million people, 97.2% grossIndia: 259 per million people, 79.6% grossIreland: 5,753 per million people, 131% grossIran, Islamic Rep.: 2,240 per million people, 85.1% grossIceland: 5,953 per million people, 109% grossItaly: 2,855 per million people, 101% grossJordan: 576 per million people, 91.8% grossJapan: 5,609 per million people, 102% grossKazakhstan: 758 per million people, 97.6% grossKenya: 384 per million people, 84.3% grossCambodia: 30.4 per million people, 58.8% grossKorea, Rep.: 9,472 per million people, 96.3% grossKuwait: 145 per million people, 95.4% grossSri Lanka: 94.5 per million people, 88% grossLesotho: 32.2 per million people, 59.4% grossLithuania: 3,704 per million people, 105% grossLuxembourg: 5,359 per million people, 109% grossLatvia: 2,191 per million people, 101% grossMacao SAR, China: 4,634 per million people, 94.7% grossMorocco: 1,083 per million people, 90% grossMoldova: 650 per million people, 99.3% grossMadagascar: 32.9 per million people, 34.1% grossMexico: 438 per million people, 103% grossNorth Macedonia: 888 per million people, 90.1% grossMali: 26 per million people, 38.9% grossMalta: 2,355 per million people, 103% grossMyanmar: 28 per million people, 77% grossMontenegro: 764 per million people, 93.9% grossMongolia: 535 per million people, 96.8% grossMozambique: 44.4 per million people, 37.2% grossMauritius: 689 per million people, 90.7% grossMalawi: 25.2 per million people, 36.6% grossMalaysia: 1,218 per million people, 80.3% grossNamibia: 225 per million people, 82% grossNiger: 26.9 per million people, 19.9% grossNigeria: 22.1 per million people, 46.9% grossNetherlands: 6,563 per million people, 138% grossNorway: 7,451 per million people, 116% grossNew Zealand: 5,435 per million people, 114% grossOman: 739 per million people, 95.1% grossPakistan: 474 per million people, 48.3% grossPanama: 250 per million people, 76.6% grossPhilippines: 320 per million people, 85.3% grossPapua New Guinea: 33.2 per million people, 52.1% grossPoland: 3,675 per million people, 108% grossPuerto Rico (US): 332 per million people, 81.5% grossPortugal: 5,983 per million people, 120% grossParaguay: 139 per million people, 79.1% grossWest Bank and Gaza: 584 per million people, 89.1% grossQatar: 948 per million people, 99.6% grossRomania: 1,082 per million people, 81.6% grossRussian Federation: 2,639 per million people, 92.5% grossRwanda: 133 per million people, 48.8% grossSaudi Arabia: 1,235 per million people, 111% grossSenegal: 572 per million people, 44.1% grossSingapore: 8,782 per million people, 103% grossEl Salvador: 55.5 per million people, 62.1% grossSerbia: 2,688 per million people, 89.8% grossSlovak Republic: 3,507 per million people, 93.2% grossSlovenia: 5,616 per million people, 108% grossSweden: 8,911 per million people, 132% grossEswatini: 138 per million people, 82% grossSyrian Arab Republic: 140 per million people, 38.7% grossChad: 56.7 per million people, 23.5% grossTogo: 57.8 per million people, 63.4% grossThailand: 1,592 per million people, 92.1% grossTrinidad and Tobago: 493 per million people, 95.7% grossTunisia: 1,668 per million people, 90.3% grossTurkiye: 2,645 per million people, 118% grossTanzania: 19.3 per million people, 28.2% grossUkraine: 586 per million people, 86.2% grossUruguay: 938 per million people, 119% grossUnited States: 4,937 per million people, 97.5% grossUzbekistan: 640 per million people, 98.1% grossViet Nam: 836 per million people, 93.4% grossSouth Africa: 444 per million people, 104% grossZimbabwe: 95.1 per million people, 52.4% grossBDICRIDNKFINGMBKORNERSGPSWETCDURY

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.6186.3e-15129
By rank (Spearman), not adjusted+0.7773.0e-27129
Standard (Pearson), adjusted for national income+0.1360.125129
By rank (Spearman), adjusted for national income+0.3672.0e-5129

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 129 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: +0.481 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.093 (without FIN) to +0.167 (without SGP). 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: FIN (-0.043).

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 & Pacific18+0.09
Europe & Central Asia45+0.54
Latin America & Caribbean17+0.57
Middle East, North Africa, Afghanistan & Pakistan16+0.33
Sub-Saharan Africa28+0.11

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 third43+0.29
Middle third43+0.16
Richest third43+0.50

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
Christians79+0.23
Muslims31+0.29

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
France13+0.45
Never a European colony15-0.39
Spain16+0.55
United Kingdom34+0.12

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 = +0.200 after dropping 17 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 29years. So a link here can’t come from anything about a country that stays the same, such as its history, geography, institutions or culture.

Within countries over time, there is no link that is clearly more than chance (r = -0.134, comparing each country only with itself over the years, and each year only with the same year elsewhere). Whatever the cross-country picture shows, countries whose researchers moved did not tend to see their secondary enrollment move with it.

Across countries (adjusted)+0.136for comparison
Within countries+0.266each country vs itself
…and vs the same year elsewhere-0.134q = 0.315 · 91 countries
Year-on-year changes-0.015q = 0.910
The direction flips. Comparing each country only with itself gives +0.27. Also taking out what happened to the whole world each year gives -0.13. So the first figure was picking up a trend both measures share with worldwide progress, not a link between them.

1,454 country-years (one country in one year), 91 countries, 1996–2024, about 16 years each on average. Share of the variation that happens within countries over time: 13% for Researchers, 11% for Secondary enrollment. The margins of error allow for each country appearing many times, and for each year’s value being close to the year before.

Year-to-year changes are a cautious test, not a final answer. Looking only at changes from one year to the next removes each country’s own trends. But it also makes measurement mistakes louder, which pulls the results toward zero. A near-zero result here is weak evidence of no link, not proof.

With one measure years behind the other

0.20−0.2-100+10years Secondary enrollment trails Researchers →lag -10: r = 0.027 (n = 1,015)lag -9: r = 0.033 (n = 1,063)lag -8: r = 0.020 (n = 1,118)lag -7: r = 0.025 (n = 1,184)lag -6: r = 0.010 (n = 1,239)lag -5: r = -0.004 (n = 1,274)lag -4: r = -0.033 (n = 1,316)lag -3: r = -0.052 (n = 1,348)lag -2: r = -0.085 (n = 1,400)lag -1: r = -0.116 (n = 1,428)lag +0: r = -0.134 (n = 1,454)lag +1: r = -0.148 (n = 1,440)lag +2: r = -0.155 (n = 1,417)lag +3: r = -0.151 (n = 1,384)lag +4: r = -0.147 (n = 1,347)lag +5: r = -0.114 (n = 1,301)lag +6: r = -0.085 (n = 1,219)lag +7: r = -0.052 (n = 1,160)lag +8: r = -0.024 (n = 1,095)lag +9: r = 0.001 (n = 1,016)lag +10: r = 0.029 (n = 953)

Same year (lag 0): -0.134. A peak away from zero does not show which comes first. These series change slowly — this year’s value is close to last year’s. That makes the curve smooth and nearly symmetric, whatever produced the data. Even a sharp peak at one lag (a gap of some years) would not prove that one measure changes the other.

The data


per million people
% gross		Years
Korea, Rep. KOR9,47296.3%2023, 2024
Sweden SWE8,911132%2023, 2024
Denmark DNK8,838126%2023, 2024
Singapore SGP8,782103%2022, 2023
Finland FIN8,315142%2023, 2024
Norway NOR7,451116%2023, 2024
Austria AUT6,634101%2023, 2024
Netherlands NLD6,563138%2023
Switzerland CHE6,108101%2023, 2024
Belgium BEL5,990143%2023
Portugal PRT5,983120%2023
Iceland ISL5,953109%2023
Germany DEU5,926100%2023, 2024
Hong Kong SAR, China HKG5,874107%2024
Ireland IRL5,753131%2023, 2022

World Bank, World Development Indicators
World Bank, World Development Indicators

Sources

Researchers

Researchers in R&D (per million people)

UNESCO Institute for Statistics · CC BY 4.0 · updated quarterly

Researchers counted as full-time equivalents (two half-time researchers count as one), from national research surveys that many countries run only now and then. So coverage is thin outside the OECD.

Secondary enrollment

School enrollment, secondary (% gross)

UNESCO Institute for Statistics · CC BY 4.0 · updated quarterly

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 Researchers and Secondary enrollment

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

More links with Researchers or Secondary enrollment