placestats

Labor share of income vs. Researchers

Holds up after adjusting for income

Across 109 countries, Labor share of income and Researchers rise and fall together at r = +0.32 (on a scale from −1 to +1, where 0 means no link). It holds up almost unchanged when only countries with similar income (GDP per person) are compared (r = +0.49, q = 0.038, allowing for the many pairs tested).

Comparing countries across the middle half of labor share of income, 43.8% to 57.1% of GDP, researchers is better by 982 per million people at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 1,072 per million people.

Link before adjusting (r)+0.321p = 0.001 · 109 countries
After adjusting for national income+0.486p = 9.8e-8 · likely range [+0.33, +0.62]
p, allowing for regions0.003standard error 0.103 · 7 regions
Check for luck (q)0.038across 18,622 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.

Labor share of income · % of GDPlink with income +0.08 · independent
Researchers · per million peoplelink with income +0.85 · proxy

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

Every country as a dot

Labor share of income · % of GDP →Researchers · per million people →17.7%74.1%1.459,472Angola: 22.3% of GDP, 18.9 per million peopleAlbania: 70.5% of GDP, 429 per million peopleArgentina: 52.8% of GDP, 1,313 per million peopleArmenia: 50.9% of GDP, 942 per million peopleAustralia: 54.6% of GDP, 4,569 per million peopleAustria: 60.8% of GDP, 6,634 per million peopleAzerbaijan: 39.2% of GDP, 1,663 per million peopleBurundi: 60.6% of GDP, 22.5 per million peopleBelgium: 58.6% of GDP, 5,990 per million peopleBurkina Faso: 42.6% of GDP, 46.6 per million peopleBulgaria: 51.7% of GDP, 2,401 per million peopleBahrain: 29.4% of GDP, 849 per million peopleBosnia and Herzegovina: 67.1% of GDP, 705 per million peopleBelarus: 57% of GDP, 1,568 per million peopleBolivia: 49.8% of GDP, 63.1 per million peopleBrazil: 51.1% of GDP, 903 per million peopleBotswana: 27.8% of GDP, 180 per million peopleCanada: 65.9% of GDP, 5,624 per million peopleSwitzerland: 65.3% of GDP, 6,108 per million peopleChile: 44% of GDP, 707 per million peopleChina: 56.1% of GDP, 2,107 per million peopleColombia: 47.8% of GDP, 90.2 per million peopleCabo Verde: 62.6% of GDP, 125 per million peopleCosta Rica: 53.1% of GDP, 508 per million peopleCyprus: 53.7% of GDP, 1,686 per million peopleCzechia: 51.2% of GDP, 4,505 per million peopleGermany: 63.7% of GDP, 5,926 per million peopleDenmark: 60.1% of GDP, 8,838 per million peopleDominican Republic: 42.7% of GDP, 20 per million peopleEcuador: 53% of GDP, 400 per million peopleEgypt, Arab Rep.: 36.2% of GDP, 1,120 per million peopleSpain: 59.4% of GDP, 3,654 per million peopleEstonia: 60.7% of GDP, 4,800 per million peopleFinland: 58.3% of GDP, 8,315 per million peopleFrance: 63.1% of GDP, 5,369 per million peopleUnited Kingdom: 59.5% of GDP, 4,473 per million peopleGeorgia: 46.7% of GDP, 1,896 per million peopleGreece: 54% of GDP, 5,283 per million peopleGuatemala: 46.9% of GDP, 1.45 per million peopleHong Kong SAR, China: 52.7% of GDP, 5,874 per million peopleHonduras: 54.7% of GDP, 188 per million peopleCroatia: 61.3% of GDP, 2,440 per million peopleHungary: 53.7% of GDP, 4,567 per million peopleIndonesia: 50.9% of GDP, 395 per million peopleIndia: 53.3% of GDP, 259 per million peopleIreland: 30.9% of GDP, 5,753 per million peopleIran, Islamic Rep.: 39.3% of GDP, 2,240 per million peopleIraq: 29.6% of GDP, 164 per million peopleIceland: 61.7% of GDP, 5,953 per million peopleItaly: 51.2% of GDP, 2,855 per million peopleJordan: 49.3% of GDP, 576 per million peopleJapan: 58.7% of GDP, 5,609 per million peopleKazakhstan: 37.3% of GDP, 758 per million peopleKenya: 54% of GDP, 384 per million peopleKorea, Rep.: 54.6% of GDP, 9,472 per million peopleKuwait: 24.9% of GDP, 145 per million peopleSri Lanka: 38.1% of GDP, 94.5 per million peopleLesotho: 66.1% of GDP, 32.2 per million peopleLithuania: 57.1% of GDP, 3,704 per million peopleLuxembourg: 49.8% of GDP, 5,359 per million peopleLatvia: 62.2% of GDP, 2,191 per million peopleMacao SAR, China: 32.2% of GDP, 4,634 per million peopleMorocco: 46.5% of GDP, 1,083 per million peopleMoldova: 51.3% of GDP, 650 per million peopleMexico: 38.1% of GDP, 438 per million peopleNorth Macedonia: 52.5% of GDP, 888 per million peopleMalta: 45.9% of GDP, 2,355 per million peopleMongolia: 40.6% of GDP, 535 per million peopleMozambique: 54% of GDP, 44.4 per million peopleMauritius: 45.6% of GDP, 689 per million peopleMalaysia: 39.7% of GDP, 1,218 per million peopleNamibia: 52.9% of GDP, 225 per million peopleNiger: 39.1% of GDP, 26.9 per million peopleNigeria: 31.2% of GDP, 22.1 per million peopleNetherlands: 55.9% of GDP, 6,563 per million peopleNorway: 38.4% of GDP, 7,451 per million peopleNew Zealand: 55.4% of GDP, 5,435 per million peopleOman: 30.3% of GDP, 739 per million peoplePanama: 32.8% of GDP, 250 per million peoplePhilippines: 44.9% of GDP, 320 per million peoplePoland: 54.8% of GDP, 3,675 per million peoplePortugal: 61.7% of GDP, 5,983 per million peopleParaguay: 44.5% of GDP, 139 per million peopleQatar: 17.7% of GDP, 948 per million peopleRomania: 50% of GDP, 1,082 per million peopleRussian Federation: 52.9% of GDP, 2,639 per million peopleRwanda: 74.1% of GDP, 133 per million peopleSaudi Arabia: 28% of GDP, 1,235 per million peopleSenegal: 52.3% of GDP, 572 per million peopleSingapore: 43.9% of GDP, 8,782 per million peopleEl Salvador: 52.1% of GDP, 55.5 per million peopleSerbia: 63.7% of GDP, 2,688 per million peopleSlovak Republic: 53.2% of GDP, 3,507 per million peopleSlovenia: 63.3% of GDP, 5,616 per million peopleSweden: 61% of GDP, 8,911 per million peopleEswatini: 61.2% of GDP, 138 per million peopleChad: 48.5% of GDP, 56.7 per million peopleTogo: 50.1% of GDP, 57.8 per million peopleThailand: 43.8% of GDP, 1,592 per million peopleTrinidad and Tobago: 33.8% of GDP, 493 per million peopleTunisia: 56.1% of GDP, 1,668 per million peopleTurkiye: 42.6% of GDP, 2,645 per million peopleTanzania: 58.3% of GDP, 19.3 per million peopleUkraine: 55.8% of GDP, 586 per million peopleUruguay: 51.9% of GDP, 938 per million peopleUnited States: 56.8% of GDP, 4,937 per million peopleUzbekistan: 37.9% of GDP, 640 per million peopleSouth Africa: 54.3% of GDP, 444 per million peopleZimbabwe: 53.3% of GDP, 95.1 per million peopleAGOALBDNKIRLKORKWTLSONORQATRWASGPSWE

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.3210.001109
By rank (Spearman), not adjusted+0.3360.000109
Standard (Pearson), adjusted for national income+0.4869.8e-8109
By rank (Spearman), adjusted for national income+0.4654.0e-7109

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 109 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: -0.165 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.455 (without QAT) to +0.513 (without ALB). 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 (-0.031).

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+0.62
Europe & Central Asia44+0.29
Latin America & Caribbean16+0.64
Middle East, North Africa, Afghanistan & Pakistan12+0.70
Sub-Saharan Africa20+0.28

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 third37+0.00
Middle third36+0.46
Richest third36+0.70

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
Christians70+0.50
Muslims24+0.21

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
Never a European colony14+0.69
Spain16+0.35
United Kingdom26+0.68

By official ideology

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
Nationalist14+0.36
No strong official ideology78+0.45

By party system

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
A few parties banned12+0.42
No parties banned85+0.39

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 = +0.463 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 28years. 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 = -0.024, 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 labor share of income moved did not tend to see their researchers move with it.

Across countries (adjusted)+0.486for comparison
Within countries-0.133each country vs itself
…and vs the same year elsewhere-0.024q = 0.875 · 89 countries
Year-on-year changes-0.011q = 0.796

1,749 country-years (one country in one year), 89 countries, 1996–2023, about 20 years each on average. Share of the variation that happens within countries over time: 11% for Labor share of income, 15% for Researchers. 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 Researchers trails Labor share of income →lag -10: r = -0.054 (n = 1,020)lag -9: r = -0.057 (n = 1,087)lag -8: r = -0.066 (n = 1,172)lag -7: r = -0.072 (n = 1,238)lag -6: r = -0.088 (n = 1,321)lag -5: r = -0.090 (n = 1,389)lag -4: r = -0.085 (n = 1,467)lag -3: r = -0.074 (n = 1,536)lag -2: r = -0.052 (n = 1,614)lag -1: r = -0.030 (n = 1,682)lag +0: r = -0.024 (n = 1,749)lag +1: r = -0.018 (n = 1,784)lag +2: r = -0.014 (n = 1,784)lag +3: r = -0.017 (n = 1,784)lag +4: r = -0.029 (n = 1,784)lag +5: r = -0.042 (n = 1,784)lag +6: r = -0.033 (n = 1,784)lag +7: r = -0.034 (n = 1,742)lag +8: r = -0.034 (n = 1,702)lag +9: r = -0.036 (n = 1,659)lag +10: r = -0.036 (n = 1,614)

Same year (lag 0): -0.024. 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 largest value on this curve (-0.09 at lag -5) is higher than the same-year one by 0.07. That gap is not a finding. It is the largest of 21 closely related estimates, and picking the biggest of many tests always makes it look bigger. That is exactly why nothing on this site is ranked or chosen by lag.

The data


% of GDP
per million people		Years
Rwanda RWA74.1%1332023
Albania ALB70.5%4292023, 2022
Bosnia and Herzegovina BIH67.1%7052023, 2024
Lesotho LSO66.1%32.22023
Canada CAN65.9%5,6242023, 2022
Switzerland CHE65.3%6,1082023
Germany DEU63.7%5,9262023
Serbia SRB63.7%2,6882023, 2024
Slovenia SVN63.3%5,6162023
France FRA63.1%5,3692023
Cabo Verde CPV62.6%1252023, 2014
Latvia LVA62.2%2,1912023
Iceland ISL61.7%5,9532023
Portugal PRT61.7%5,9832023
Croatia HRV61.3%2,4402023

Feenstra, Robert C., Robert Inklaar and Marcel P. Timmer (2015), "The Next Generation of the Penn World Table", American Economic Review, 105(10), 3150-3182, www.ggdc.net/pwt. Data: Penn World Table version 11.0, Groningen Growth and Development Centre, doi:10.34894/FABVLR.
World Bank, World Development Indicators

Sources

Labor share of income

Labor share of GDP (Penn World Table)

Groningen Growth and Development Centre, University of Groningen · via DataverseNL · CC BY 4.0 · updated irregular (new versions every few years)

The share of a country's income (GDP) that is paid to people for their work: wages, salaries and benefits, plus an estimate of what the self-employed, such as farmers and shopkeepers, earn for their work. The rest goes to the owners of land, buildings and machines as profit, rent and interest. Where there is little data on the self-employed, the Penn World Table fills in a value by a fixed rule, so figures for poorer countries are rougher, and a few countries show the same value every year. No "better" direction is set.

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.

How this was computed

Data used: most recent value in 2010-2025; values come from 2010–2024. 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 18,622 pairs at once, using the Benjamini–Hochberg method. Underlying data last updated V-Dem v16; V-Party v2. How the country data works · explore Labor share of income and Researchers

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

More links with Labor share of income or Researchers