placestats

Hours worked (PWT) vs. Researchers

Fades after adjusting for income

Across 114 countries, Hours worked (PWT) and Researchers 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) leaves r = -0.46, which could easily be chance (q = 0.14, allowing for the many pairs tested, and allowing for countries in the same region being alike). Caution: direction is not consistent across regions.

Comparing countries across the middle half of hours worked (PWT), 1,626 to 2,170 hours per year, researchers is worse by 2,282 per million people at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 1,511 per million people.

Link before adjusting (r)-0.518p = 3.6e-9 · 114 countries
After adjusting for national income-0.461p = 2.7e-7 · likely range [-0.60, -0.30]
p, allowing for regions0.031standard error 0.165 · 7 regions
Check for luck (q)0.137across 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.

Hours worked (PWT) · hours per yearlink with income -0.40 · moderate
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

Hours worked (PWT) · hours per year →Researchers · per million people →1,3352,5341.459,472Angola: 2,115 hours per year, 18.9 per million peopleAlbania: 2,152 hours per year, 429 per million peopleUnited Arab Emirates: 2,514 hours per year, 2,607 per million peopleArgentina: 1,612 hours per year, 1,313 per million peopleArmenia: 1,976 hours per year, 942 per million peopleAustralia: 1,611 hours per year, 4,569 per million peopleAustria: 1,438 hours per year, 6,634 per million peopleAzerbaijan: 1,791 hours per year, 1,663 per million peopleBelgium: 1,593 hours per year, 5,990 per million peopleBurkina Faso: 2,356 hours per year, 46.6 per million peopleBulgaria: 1,659 hours per year, 2,401 per million peopleBahrain: 2,052 hours per year, 849 per million peopleBosnia and Herzegovina: 2,122 hours per year, 705 per million peopleBelarus: 1,875 hours per year, 1,568 per million peopleBolivia: 1,968 hours per year, 63.1 per million peopleBrazil: 1,994 hours per year, 903 per million peopleBotswana: 2,258 hours per year, 180 per million peopleCanada: 1,731 hours per year, 5,624 per million peopleSwitzerland: 1,529 hours per year, 6,108 per million peopleChile: 1,950 hours per year, 707 per million peopleChina: 2,328 hours per year, 2,107 per million peopleCongo, Dem. Rep.: 1,841 hours per year, 10.1 per million peopleCongo, Rep.: 2,534 hours per year, 127 per million peopleColombia: 2,471 hours per year, 90.2 per million peopleCosta Rica: 2,177 hours per year, 508 per million peopleCyprus: 1,840 hours per year, 1,686 per million peopleCzechia: 1,774 hours per year, 4,505 per million peopleGermany: 1,335 hours per year, 5,926 per million peopleDenmark: 1,380 hours per year, 8,838 per million peopleDominican Republic: 2,072 hours per year, 20 per million peopleAlgeria: 2,232 hours per year, 1,764 per million peopleEcuador: 1,594 hours per year, 400 per million peopleEgypt, Arab Rep.: 2,369 hours per year, 1,120 per million peopleSpain: 1,638 hours per year, 3,654 per million peopleEstonia: 1,606 hours per year, 4,800 per million peopleEthiopia: 1,599 hours per year, 89 per million peopleFinland: 1,497 hours per year, 8,315 per million peopleFrance: 1,487 hours per year, 5,369 per million peopleUnited Kingdom: 1,523 hours per year, 4,473 per million peopleGeorgia: 1,932 hours per year, 1,896 per million peopleGhana: 1,656 hours per year, 87.5 per million peopleGreece: 1,893 hours per year, 5,283 per million peopleGuatemala: 2,151 hours per year, 1.45 per million peopleHong Kong SAR, China: 2,240 hours per year, 5,874 per million peopleCroatia: 1,974 hours per year, 2,440 per million peopleHungary: 1,668 hours per year, 4,567 per million peopleIndonesia: 1,958 hours per year, 395 per million peopleIndia: 2,383 hours per year, 259 per million peopleIreland: 1,654 hours per year, 5,753 per million peopleIran, Islamic Rep.: 2,246 hours per year, 2,240 per million peopleIraq: 1,583 hours per year, 164 per million peopleIceland: 1,452 hours per year, 5,953 per million peopleItaly: 1,701 hours per year, 2,855 per million peopleJordan: 2,483 hours per year, 576 per million peopleJapan: 1,654 hours per year, 5,609 per million peopleKazakhstan: 1,975 hours per year, 758 per million peopleKenya: 2,035 hours per year, 384 per million peopleCambodia: 2,389 hours per year, 30.4 per million peopleKorea, Rep.: 1,910 hours per year, 9,472 per million peopleKuwait: 2,318 hours per year, 145 per million peopleSri Lanka: 2,053 hours per year, 94.5 per million peopleLithuania: 1,640 hours per year, 3,704 per million peopleLuxembourg: 1,452 hours per year, 5,359 per million peopleLatvia: 1,625 hours per year, 2,191 per million peopleMorocco: 2,174 hours per year, 1,083 per million peopleMoldova: 1,989 hours per year, 650 per million peopleMadagascar: 1,799 hours per year, 32.9 per million peopleMexico: 1,629 hours per year, 438 per million peopleNorth Macedonia: 1,949 hours per year, 888 per million peopleMali: 2,243 hours per year, 26 per million peopleMalta: 1,848 hours per year, 2,355 per million peopleMyanmar: 2,197 hours per year, 28 per million peopleMozambique: 1,507 hours per year, 44.4 per million peopleMauritius: 1,990 hours per year, 689 per million peopleMalawi: 1,596 hours per year, 25.2 per million peopleMalaysia: 2,308 hours per year, 1,218 per million peopleNamibia: 2,184 hours per year, 225 per million peopleNiger: 2,069 hours per year, 26.9 per million peopleNigeria: 2,062 hours per year, 22.1 per million peopleNetherlands: 1,439 hours per year, 6,563 per million peopleNorway: 1,412 hours per year, 7,451 per million peopleNew Zealand: 1,708 hours per year, 5,435 per million peopleOman: 2,266 hours per year, 739 per million peoplePakistan: 2,471 hours per year, 474 per million peoplePhilippines: 2,096 hours per year, 320 per million peoplePoland: 1,807 hours per year, 3,675 per million peoplePortugal: 1,735 hours per year, 5,983 per million peopleParaguay: 2,123 hours per year, 139 per million peopleQatar: 2,435 hours per year, 948 per million peopleRomania: 1,826 hours per year, 1,082 per million peopleRussian Federation: 2,087 hours per year, 2,639 per million peopleRwanda: 1,584 hours per year, 133 per million peopleSaudi Arabia: 2,125 hours per year, 1,235 per million peopleSenegal: 2,335 hours per year, 572 per million peopleSingapore: 2,283 hours per year, 8,782 per million peopleSerbia: 1,995 hours per year, 2,688 per million peopleSlovak Republic: 1,621 hours per year, 3,507 per million peopleSlovenia: 1,588 hours per year, 5,616 per million peopleSweden: 1,432 hours per year, 8,911 per million peopleSyrian Arab Republic: 1,621 hours per year, 140 per million peopleChad: 1,585 hours per year, 56.7 per million peopleThailand: 2,177 hours per year, 1,592 per million peopleTrinidad and Tobago: 1,610 hours per year, 493 per million peopleTunisia: 2,288 hours per year, 1,668 per million peopleTurkiye: 1,747 hours per year, 2,645 per million peopleTanzania: 2,129 hours per year, 19.3 per million peopleUganda: 2,128 hours per year, 81.3 per million peopleUkraine: 2,045 hours per year, 586 per million peopleUruguay: 1,481 hours per year, 938 per million peopleUnited States: 1,789 hours per year, 4,937 per million peopleUzbekistan: 2,099 hours per year, 640 per million peopleViet Nam: 2,160 hours per year, 836 per million peopleSouth Africa: 2,181 hours per year, 444 per million peopleZimbabwe: 2,311 hours per year, 95.1 per million peopleCOGCOLDNKFINHKGKORMOZPAKSGPSWETCDURY

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.5183.6e-9114
By rank (Spearman), not adjusted-0.4381.1e-6114
Standard (Pearson), adjusted for national income-0.4612.7e-7114
By rank (Spearman), adjusted for national income-0.2430.010114

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 114 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: +0.057 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.509 (without SGP) to -0.437 (without QAT). 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 (-0.047).

Fragile: this link may not hold up.
  • 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 & Pacific14-0.19
Europe & Central Asia44-0.60
Latin America & Caribbean13-0.52
Middle East, North Africa, Afghanistan & Pakistan16+0.18
Sub-Saharan Africa23-0.03

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 third38+0.16
Middle third38-0.13
Richest third38-0.58

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
Christians69-0.60
Muslims29+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
France12-0.16
Never a European colony14-0.39
Spain13-0.43
United Kingdom30-0.26

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
Nationalist17-0.16
No strong official ideology78-0.44

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 banned15-0.09
No parties banned84-0.38

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 = -0.491 after dropping 1 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 = -0.173, 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 hours worked (PWT) moved did not tend to see their researchers move with it.

Across countries (adjusted)-0.461for comparison
Within countries-0.550each country vs itself
…and vs the same year elsewhere-0.173q = 0.514 · 89 countries
Year-on-year changes-0.046q = 0.203
Read with care.
  • Almost all of this indicator's variation is between countries, not within them, 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.

1,676 country-years (one country in one year), 89 countries, 1996–2023, about 19 years each on average. Share of the variation that happens within countries over time: 6% for Hours worked (PWT), 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

0.20−0.2-100+10years Researchers trails Hours worked (PWT) →lag -10: r = -0.193 (n = 1,006)lag -9: r = -0.194 (n = 1,070)lag -8: r = -0.178 (n = 1,142)lag -7: r = -0.196 (n = 1,204)lag -6: r = -0.186 (n = 1,288)lag -5: r = -0.176 (n = 1,351)lag -4: r = -0.178 (n = 1,428)lag -3: r = -0.179 (n = 1,491)lag -2: r = -0.179 (n = 1,559)lag -1: r = -0.175 (n = 1,617)lag +0: r = -0.173 (n = 1,676)lag +1: r = -0.168 (n = 1,694)lag +2: r = -0.159 (n = 1,666)lag +3: r = -0.162 (n = 1,639)lag +4: r = -0.159 (n = 1,611)lag +5: r = -0.149 (n = 1,576)lag +6: r = -0.144 (n = 1,541)lag +7: r = -0.147 (n = 1,488)lag +8: r = -0.154 (n = 1,432)lag +9: r = -0.144 (n = 1,373)lag +10: r = -0.155 (n = 1,314)

Same year (lag 0): -0.173. 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


hours per year
per million people		Years
Congo, Rep. COG2,5341272023, 2022
United Arab Emirates ARE2,5142,6072023, 2021
Jordan JOR2,4835762023, 2017
Pakistan PAK2,4714742023
Colombia COL2,47190.22023, 2017
Qatar QAT2,4359482023, 2021
Cambodia KHM2,38930.42023, 2015
India IND2,3832592023, 2020
Egypt, Arab Rep. EGY2,3691,1202023, 2024
Burkina Faso BFA2,35646.62023, 2010
Senegal SEN2,3355722023, 2015
China CHN2,3282,1072023
Kuwait KWT2,3181452023, 2024
Zimbabwe ZWE2,31195.12023, 2012
Malaysia MYS2,3081,2182023, 2022

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

Hours worked (PWT)

Average annual hours worked per person engaged (Penn World Table)

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

Hours actually worked in a year, averaged over everyone with a job, including the self-employed and part-timers. It measures the same thing as the OECD hours measure, and for countries in both the two mostly agree. This one is kept because it reaches much further: about 130 countries each year from 2010 to 2023, where the OECD series has 38 countries and stops in 2016. Before 2000 it covers mainly rich countries. 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 Hours worked (PWT) and Researchers

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

More links with Hours worked (PWT) or Researchers