placestats

Researchers vs. Vulnerable employment

Fades after adjusting for income

Across 131 countries, Researchers and Vulnerable employment rise and fall together at r = -0.58 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to +0.02, which could easily be chance (q = 0.87, 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. Caution: sign flips when a single country is removed.

Comparing countries across the middle half of researchers, 139 to 3,181 per million people, vulnerable employment is better by 18.3% of employment at the top of that range than the bottom. Comparing only countries with similar national income, the gap reverses, to 0.413% of employment the other way.

Link before adjusting (r)-0.585p = 2.2e-13 · 131 countries
After adjusting for national income+0.019p = 0.829 · likely range [-0.15, +0.19]
p, allowing for regions0.768standard error 0.062 · 7 regions
Check for luck (q)0.867across 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
Vulnerable employment · % of employmentlink with income -0.87 · 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

Researchers · per million people →Vulnerable employment · % of employment →1.459,4720.456%90.2%Angola: 18.9 per million people, 66.3% of employmentAlbania: 429 per million people, 46% of employmentUnited Arab Emirates: 2,607 per million people, 1.5% of employmentArgentina: 1,313 per million people, 22.3% of employmentArmenia: 942 per million people, 32.8% of employmentAustralia: 4,569 per million people, 9.12% of employmentAustria: 6,634 per million people, 7.85% of employmentAzerbaijan: 1,663 per million people, 53.8% of employmentBurundi: 22.5 per million people, 83.7% of employmentBelgium: 5,990 per million people, 11% of employmentBurkina Faso: 46.6 per million people, 80.6% of employmentBulgaria: 2,401 per million people, 6.92% of employmentBahrain: 849 per million people, 0.749% of employmentBosnia and Herzegovina: 705 per million people, 18.1% of employmentBelarus: 1,568 per million people, 6.33% of employmentBolivia: 63.1 per million people, 62.7% of employmentBrazil: 903 per million people, 26.1% of employmentBrunei Darussalam: 506 per million people, 4.48% of employmentBhutan: 236 per million people, 69% of employmentBotswana: 180 per million people, 25.6% of employmentCanada: 5,624 per million people, 9.56% of employmentSwitzerland: 6,108 per million people, 9.6% of employmentChile: 707 per million people, 20.9% of employmentChina: 2,107 per million people, 33.4% of employmentCongo, Dem. Rep.: 10.1 per million people, 81.5% of employmentCongo, Rep.: 127 per million people, 75.9% of employmentColombia: 90.2 per million people, 43% of employmentCabo Verde: 125 per million people, 34.3% of employmentCosta Rica: 508 per million people, 23.4% of employmentCyprus: 1,686 per million people, 8.38% of employmentCzechia: 4,505 per million people, 13.5% of employmentGermany: 5,926 per million people, 4.34% of employmentDenmark: 8,838 per million people, 5.4% of employmentDominican Republic: 20 per million people, 38% of employmentAlgeria: 1,764 per million people, 25.6% of employmentEcuador: 400 per million people, 50.1% of employmentEgypt, Arab Rep.: 1,120 per million people, 23.9% of employmentSpain: 3,654 per million people, 10.1% of employmentEstonia: 4,800 per million people, 7.09% of employmentEthiopia: 89 per million people, 84.1% of employmentFinland: 8,315 per million people, 9.46% of employmentFrance: 5,369 per million people, 8.5% of employmentUnited Kingdom: 4,473 per million people, 11.5% of employmentGeorgia: 1,896 per million people, 42.4% of employmentGhana: 87.5 per million people, 60% of employmentGambia, The: 50.9 per million people, 63.5% of employmentGreece: 5,283 per million people, 23.1% of employmentGuatemala: 1.45 per million people, 36.2% of employmentHong Kong SAR, China: 5,874 per million people, 5.76% of employmentHonduras: 188 per million people, 33.9% of employmentCroatia: 2,440 per million people, 6.35% of employmentHungary: 4,567 per million people, 7.83% of employmentIndonesia: 395 per million people, 50% of employmentIndia: 259 per million people, 71.6% of employmentIreland: 5,753 per million people, 9.64% of employmentIran, Islamic Rep.: 2,240 per million people, 39.5% of employmentIraq: 164 per million people, 27.1% of employmentIceland: 5,953 per million people, 8.4% of employmentItaly: 2,855 per million people, 14.3% of employmentJordan: 576 per million people, 7.86% of employmentJapan: 5,609 per million people, 7.49% of employmentKazakhstan: 758 per million people, 24.8% of employmentKenya: 384 per million people, 63.8% of employmentCambodia: 30.4 per million people, 52.3% of employmentKorea, Rep.: 9,472 per million people, 17.7% of employmentKuwait: 145 per million people, 2.4% of employmentSri Lanka: 94.5 per million people, 39.2% of employmentLesotho: 32.2 per million people, 32.6% of employmentLithuania: 3,704 per million people, 10.4% of employmentLuxembourg: 5,359 per million people, 6.95% of employmentLatvia: 2,191 per million people, 8.62% of employmentMacao SAR, China: 4,634 per million people, 3.33% of employmentMorocco: 1,083 per million people, 35.5% of employmentMoldova: 650 per million people, 58.6% of employmentMadagascar: 32.9 per million people, 84.4% of employmentMexico: 438 per million people, 25.3% of employmentNorth Macedonia: 888 per million people, 12.3% of employmentMali: 26 per million people, 75.8% of employmentMalta: 2,355 per million people, 10.1% of employmentMyanmar: 28 per million people, 62.9% of employmentMontenegro: 764 per million people, 14.3% of employmentMongolia: 535 per million people, 38.4% of employmentMozambique: 44.4 per million people, 83.7% of employmentMauritius: 689 per million people, 14.9% of employmentMalawi: 25.2 per million people, 59.9% of employmentMalaysia: 1,218 per million people, 21.9% of employmentNamibia: 225 per million people, 29.9% of employmentNiger: 26.9 per million people, 83.7% of employmentNigeria: 22.1 per million people, 66.5% of employmentNetherlands: 6,563 per million people, 13.4% of employmentNorway: 7,451 per million people, 4.17% of employmentNew Zealand: 5,435 per million people, 12.6% of employmentOman: 739 per million people, 3.81% of employmentPakistan: 474 per million people, 55.5% of employmentPanama: 250 per million people, 37.9% of employmentPhilippines: 320 per million people, 33.6% of employmentPapua New Guinea: 33.2 per million people, 71.2% of employmentPoland: 3,675 per million people, 15% of employmentPuerto Rico (US): 332 per million people, 10.3% of employmentPortugal: 5,983 per million people, 9.66% of employmentParaguay: 139 per million people, 36.1% of employmentWest Bank and Gaza: 584 per million people, 18.4% of employmentQatar: 948 per million people, 0.456% of employmentRomania: 1,082 per million people, 13% of employmentRussian Federation: 2,639 per million people, 4.93% of employmentRwanda: 133 per million people, 39.4% of employmentSaudi Arabia: 1,235 per million people, 1.66% of employmentSenegal: 572 per million people, 63% of employmentSingapore: 8,782 per million people, 9.3% of employmentEl Salvador: 55.5 per million people, 30.8% of employmentSerbia: 2,688 per million people, 23.9% of employmentSlovak Republic: 3,507 per million people, 11.8% of employmentSlovenia: 5,616 per million people, 10.6% of employmentSweden: 8,911 per million people, 6.87% of employmentEswatini: 138 per million people, 28.4% of employmentSyrian Arab Republic: 140 per million people, 38.9% of employmentChad: 56.7 per million people, 90.2% of employmentTogo: 57.8 per million people, 75% of employmentThailand: 1,592 per million people, 48% of employmentTrinidad and Tobago: 493 per million people, 21.2% of employmentTunisia: 1,668 per million people, 17.9% of employmentTurkiye: 2,645 per million people, 23.9% of employmentTanzania: 19.3 per million people, 83.7% of employmentUganda: 81.3 per million people, 74.4% of employmentUkraine: 586 per million people, 19% of employmentUruguay: 938 per million people, 24.4% of employmentUnited States: 4,937 per million people, 3.81% of employmentUzbekistan: 640 per million people, 33.3% of employmentViet Nam: 836 per million people, 51.4% of employmentSouth Africa: 444 per million people, 11.7% of employmentZimbabwe: 95.1 per million people, 68.2% of employmentBHRBRNDNKKORKWTMDGSGPSWETCDTZA

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.5852.2e-13131
By rank (Spearman), not adjusted-0.7607.1e-26131
Standard (Pearson), adjusted for national income+0.0190.829131
By rank (Spearman), adjusted for national income-0.0870.324131

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 131 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: +0.566 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.002 (without SGP) to +0.038 (without BTN). 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: SGP (-0.021).

Fragile: this link may not hold up.
  • sign flips when a single country is removed
  • sign flips once outliers are trimmed
  • direction is not consistent across regions

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+0.05
Europe & Central Asia45-0.04
Latin America & Caribbean17-0.35
Middle East, North Africa, Afghanistan & Pakistan17+0.30
Sub-Saharan Africa29-0.22

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 third44-0.36
Middle third43-0.01
Richest third44+0.44

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
Christians80-0.01
Muslims32-0.02

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
France13-0.47
Never a European colony15+0.19
Spain16-0.46
United Kingdom36+0.10

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 = -0.014 after dropping 5 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 = +0.045, 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 vulnerable employment move with it.

Across countries (adjusted)+0.019for comparison
Within countries-0.321each country vs itself
…and vs the same year elsewhere+0.045q = 0.746 · 103 countries
Year-on-year changes-0.023q = 0.489
Read with care.
  • Almost all of the second indicator's variation is between countries, so the within-country estimate rests on a small part of the data.
  • Much of the within-country association disappears once shared global year effects are removed, which points to a common worldwide trend rather than a country-level relationship.

1,874 country-years (one country in one year), 103 countries, 1996–2024, about 18 years each on average. Share of the variation that happens within countries over time: 14% for Researchers, 2% for Vulnerable employment. 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

0.10−0.1-100+10years Vulnerable employment trails Researchers →lag -10: r = 0.002 (n = 1,645)lag -9: r = 0.007 (n = 1,693)lag -8: r = 0.018 (n = 1,740)lag -7: r = 0.028 (n = 1,785)lag -6: r = 0.033 (n = 1,832)lag -5: r = 0.037 (n = 1,875)lag -4: r = 0.040 (n = 1,875)lag -3: r = 0.041 (n = 1,875)lag -2: r = 0.041 (n = 1,875)lag -1: r = 0.042 (n = 1,875)lag +0: r = 0.045 (n = 1,874)lag +1: r = 0.049 (n = 1,873)lag +2: r = 0.060 (n = 1,836)lag +3: r = 0.060 (n = 1,763)lag +4: r = 0.062 (n = 1,688)lag +5: r = 0.055 (n = 1,605)lag +6: r = 0.055 (n = 1,530)lag +7: r = 0.054 (n = 1,439)lag +8: r = 0.037 (n = 1,368)lag +9: r = 0.016 (n = 1,276)lag +10: r = 0.018 (n = 1,199)

Same year (lag 0): +0.045. 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
% of employment		Years
Korea, Rep. KOR9,47217.7%2023, 2025
Sweden SWE8,9116.87%2023, 2025
Denmark DNK8,8385.4%2023, 2025
Singapore SGP8,7829.3%2022, 2025
Finland FIN8,3159.46%2023, 2025
Norway NOR7,4514.17%2023, 2025
Austria AUT6,6347.85%2023, 2025
Netherlands NLD6,56313.4%2023, 2025
Switzerland CHE6,1089.6%2023, 2025
Belgium BEL5,99011%2023, 2025
Portugal PRT5,9839.66%2023, 2025
Iceland ISL5,9538.4%2023, 2025
Germany DEU5,9264.34%2023, 2025
Hong Kong SAR, China HKG5,8745.76%2024, 2025
Ireland IRL5,7539.64%2023, 2025

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.

Vulnerable employment

Vulnerable employment, total (% of total employment)

International Labour Organization · CC BY 4.0 · updated quarterly

Self-employed workers and unpaid family workers, who have no employer and usually no protection. The ILO estimates it with a model for every country and year, which is why it is complete where surveys are not.

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 Vulnerable employment

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

More links with Researchers or Vulnerable employment