placestats

Health spending vs. Hours worked (PWT)

Holds up after adjusting for income

Across 126 countries, Health spending and Hours worked (PWT) rise and fall together at r = -0.54 (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 = -0.44, q = 0.031, allowing for the many pairs tested).

Comparing countries across the middle half of hours worked (PWT), 1,644 to 2,177 hours per year, health spending is 2.48% of GDP lower at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 1.85% of GDP.

Link before adjusting (r)-0.538p = 8.6e-11 · 126 countries
After adjusting for national income-0.440p = 2.8e-7 · likely range [-0.57, -0.29]
p, allowing for regions0.002standard error 0.087 · 7 regions
Check for luck (q)0.031across 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.

Health spending · % of GDPlink with income +0.29 · independent
Hours worked (PWT) · hours per yearlink with income -0.40 · moderate

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

Every country as a dot

Health spending · % of GDP →Hours worked (PWT) · hours per year →2.17%16.7%1,3352,658Angola: 2.55% of GDP, 2,115 hours per yearAlbania: 7.05% of GDP, 2,152 hours per yearUnited Arab Emirates: 4.97% of GDP, 2,514 hours per yearArgentina: 10.3% of GDP, 1,612 hours per yearArmenia: 9.32% of GDP, 1,976 hours per yearAustralia: 10.4% of GDP, 1,611 hours per yearAustria: 11.8% of GDP, 1,438 hours per yearAzerbaijan: 4.27% of GDP, 1,791 hours per yearBelgium: 10.8% of GDP, 1,593 hours per yearBurkina Faso: 7.8% of GDP, 2,356 hours per yearBangladesh: 2.17% of GDP, 2,383 hours per yearBulgaria: 7.92% of GDP, 1,659 hours per yearBahrain: 4% of GDP, 2,052 hours per yearBosnia and Herzegovina: 8.92% of GDP, 2,122 hours per yearBelarus: 7.08% of GDP, 1,875 hours per yearBolivia: 6.92% of GDP, 1,968 hours per yearBrazil: 9.73% of GDP, 1,994 hours per yearBotswana: 6.26% of GDP, 2,258 hours per yearCanada: 11.3% of GDP, 1,731 hours per yearSwitzerland: 11.7% of GDP, 1,529 hours per yearChile: 10.5% of GDP, 1,950 hours per yearChina: 5.94% of GDP, 2,328 hours per yearCote d'Ivoire: 3.43% of GDP, 2,103 hours per yearCameroon: 4.55% of GDP, 2,181 hours per yearCongo, Dem. Rep.: 3.68% of GDP, 1,841 hours per yearCongo, Rep.: 3.3% of GDP, 2,534 hours per yearColombia: 8.14% of GDP, 2,471 hours per yearCosta Rica: 6.87% of GDP, 2,177 hours per yearCyprus: 8.12% of GDP, 1,840 hours per yearCzechia: 8.51% of GDP, 1,774 hours per yearGermany: 12.3% of GDP, 1,335 hours per yearDenmark: 9.39% of GDP, 1,380 hours per yearDominican Republic: 4.6% of GDP, 2,072 hours per yearAlgeria: 4.35% of GDP, 2,232 hours per yearEcuador: 7.56% of GDP, 1,594 hours per yearEgypt, Arab Rep.: 4.88% of GDP, 2,369 hours per yearSpain: 9.22% of GDP, 1,638 hours per yearEstonia: 7.84% of GDP, 1,606 hours per yearEthiopia: 2.8% of GDP, 1,599 hours per yearFinland: 10.5% of GDP, 1,497 hours per yearFrance: 11.5% of GDP, 1,487 hours per yearGabon: 3.13% of GDP, 2,174 hours per yearUnited Kingdom: 11.1% of GDP, 1,523 hours per yearGeorgia: 6.86% of GDP, 1,932 hours per yearGhana: 2.95% of GDP, 1,656 hours per yearGreece: 8.39% of GDP, 1,893 hours per yearGuatemala: 6.8% of GDP, 2,151 hours per yearCroatia: 7.15% of GDP, 1,974 hours per yearHungary: 6.37% of GDP, 1,668 hours per yearIndonesia: 2.7% of GDP, 1,958 hours per yearIndia: 3.34% of GDP, 2,383 hours per yearIreland: 6.85% of GDP, 1,654 hours per yearIran, Islamic Rep.: 6.03% of GDP, 2,246 hours per yearIraq: 5.53% of GDP, 1,583 hours per yearIceland: 8.98% of GDP, 1,452 hours per yearIsrael: 7.1% of GDP, 1,890 hours per yearItaly: 8.44% of GDP, 1,701 hours per yearJamaica: 7.6% of GDP, 1,963 hours per yearJordan: 7.66% of GDP, 2,483 hours per yearJapan: 10.7% of GDP, 1,654 hours per yearKazakhstan: 3.77% of GDP, 1,975 hours per yearKenya: 4.35% of GDP, 2,035 hours per yearKyrgyz Republic: 4.5% of GDP, 1,830 hours per yearCambodia: 4.62% of GDP, 2,389 hours per yearKorea, Rep.: 8.68% of GDP, 1,910 hours per yearKuwait: 4.96% of GDP, 2,318 hours per yearLebanon: 5.57% of GDP, 2,412 hours per yearSri Lanka: 3.68% of GDP, 2,053 hours per yearLithuania: 7.6% of GDP, 1,640 hours per yearLuxembourg: 5.89% of GDP, 1,452 hours per yearLatvia: 7.28% of GDP, 1,625 hours per yearMorocco: 6.06% of GDP, 2,174 hours per yearMoldova: 6.74% of GDP, 1,989 hours per yearMadagascar: 3.43% of GDP, 1,799 hours per yearMexico: 5.5% of GDP, 1,629 hours per yearNorth Macedonia: 7.43% of GDP, 1,949 hours per yearMali: 3.81% of GDP, 2,243 hours per yearMalta: 8.84% of GDP, 1,848 hours per yearMyanmar: 4.46% of GDP, 2,197 hours per yearMozambique: 8.5% of GDP, 1,507 hours per yearMauritius: 5.57% of GDP, 1,990 hours per yearMalawi: 6.53% of GDP, 1,596 hours per yearMalaysia: 3.96% of GDP, 2,308 hours per yearNamibia: 9.48% of GDP, 2,184 hours per yearNiger: 4.05% of GDP, 2,069 hours per yearNigeria: 4.19% of GDP, 2,062 hours per yearNetherlands: 10% of GDP, 1,439 hours per yearNorway: 9.43% of GDP, 1,412 hours per yearNew Zealand: 10.1% of GDP, 1,708 hours per yearOman: 3.49% of GDP, 2,266 hours per yearPakistan: 2.52% of GDP, 2,471 hours per yearPeru: 5.64% of GDP, 2,143 hours per yearPhilippines: 5.1% of GDP, 2,096 hours per yearPoland: 8.06% of GDP, 1,807 hours per yearPortugal: 10.2% of GDP, 1,735 hours per yearParaguay: 8.36% of GDP, 2,123 hours per yearQatar: 2.52% of GDP, 2,435 hours per yearRomania: 5.71% of GDP, 1,826 hours per yearRussian Federation: 7.04% of GDP, 2,087 hours per yearRwanda: 5.13% of GDP, 1,584 hours per yearSaudi Arabia: 5.69% of GDP, 2,125 hours per yearSudan: 2.85% of GDP, 2,658 hours per yearSenegal: 4.32% of GDP, 2,335 hours per yearSingapore: 4.49% of GDP, 2,283 hours per yearSerbia: 8.03% of GDP, 1,995 hours per yearSlovak Republic: 7.35% of GDP, 1,621 hours per yearSlovenia: 9.88% of GDP, 1,588 hours per yearSweden: 11.2% of GDP, 1,432 hours per yearSyrian Arab Republic: 2.71% of GDP, 1,621 hours per yearChad: 5% of GDP, 1,585 hours per yearThailand: 4.54% of GDP, 2,177 hours per yearTajikistan: 7.44% of GDP, 2,134 hours per yearTurkmenistan: 5.5% of GDP, 2,179 hours per yearTrinidad and Tobago: 7.53% of GDP, 1,610 hours per yearTunisia: 7.99% of GDP, 2,288 hours per yearTurkiye: 4.28% of GDP, 1,747 hours per yearTanzania: 3.05% of GDP, 2,129 hours per yearUganda: 4.24% of GDP, 2,128 hours per yearUkraine: 8.2% of GDP, 2,045 hours per yearUruguay: 9.02% of GDP, 1,481 hours per yearUnited States: 16.7% of GDP, 1,789 hours per yearUzbekistan: 6.74% of GDP, 2,099 hours per yearViet Nam: 4.56% of GDP, 2,160 hours per yearSouth Africa: 8.91% of GDP, 2,181 hours per yearZambia: 5.98% of GDP, 2,200 hours per yearZimbabwe: 2.93% of GDP, 2,311 hours per yearAUTCOGCOLDEUETHGHAJORPAKSDNSYRUSA

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.5388.6e-11126
By rank (Spearman), not adjusted-0.5272.3e-10126
Standard (Pearson), adjusted for national income-0.4402.8e-7126
By rank (Spearman), adjusted for national income-0.3878.4e-6126

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 126 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: +0.097 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.464 (without USA) to -0.410 (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: QAT (+0.030).

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 & Pacific13-0.78
Europe & Central Asia47-0.39
Latin America & Caribbean15-0.11
Middle East, North Africa, Afghanistan & Pakistan18-0.13
Sub-Saharan Africa28-0.14

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 third42-0.14
Middle third42-0.29
Richest third42-0.67

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
Christians74-0.27
Muslims36+0.04

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
France16+0.33
Never a European colony17-0.10
Spain14-0.16
United Kingdom35-0.51

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
Nationalist20-0.44
No strong official ideology85-0.41

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 banned18-0.18
No parties banned93-0.34

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 = -0.464 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 24years. So a link here can’t come from anything about a country that stays the same, such as its history, geography, institutions or culture.

The link shows up within countries over time (r = -0.274) but mostly disappears in year-to-year changes (r = -0.062). That points to slow trends particular to each country, not the two measures moving together from year to year.

Across countries (adjusted)-0.440for comparison
Within countries-0.422each country vs itself
…and vs the same year elsewhere-0.274q = 0.000 · 128 countries
Year-on-year changes-0.062q = 0.079
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.
  • The association is much weaker in year-on-year changes than in levels, which points to shared country-specific trends.

2,740 country-years (one country in one year), 128 countries, 2000–2023, about 21 years each on average. Share of the variation that happens within countries over time: 6% for Health spending, 12% for Hours worked (PWT). 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

0.30−0.3-100+10years Hours worked (PWT) trails Health spending →lag -10: r = -0.123 (n = 2,088)lag -9: r = -0.100 (n = 2,164)lag -8: r = -0.100 (n = 2,238)lag -7: r = -0.114 (n = 2,312)lag -6: r = -0.143 (n = 2,385)lag -5: r = -0.181 (n = 2,457)lag -4: r = -0.199 (n = 2,518)lag -3: r = -0.210 (n = 2,579)lag -2: r = -0.230 (n = 2,640)lag -1: r = -0.261 (n = 2,701)lag +0: r = -0.274 (n = 2,740)lag +1: r = -0.260 (n = 2,674)lag +2: r = -0.242 (n = 2,603)lag +3: r = -0.221 (n = 2,535)lag +4: r = -0.180 (n = 2,467)lag +5: r = -0.125 (n = 2,399)lag +6: r = -0.090 (n = 2,272)lag +7: r = -0.062 (n = 2,145)lag +8: r = -0.024 (n = 2,018)lag +9: r = 0.011 (n = 1,891)lag +10: r = 0.055 (n = 1,760)

Same year (lag 0): -0.274. 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


% of GDP
hours per year		Years
United States USA16.7%1,7892023
Germany DEU12.3%1,3352024, 2023
Austria AUT11.8%1,4382024, 2023
Switzerland CHE11.7%1,5292023
France FRA11.5%1,4872024, 2023
Canada CAN11.3%1,7312024, 2023
Sweden SWE11.2%1,4322024, 2023
United Kingdom GBR11.1%1,5232024, 2023
Belgium BEL10.8%1,5932023
Japan JPN10.7%1,6542023
Chile CHL10.5%1,9502024, 2023
Finland FIN10.5%1,4972023
Australia AUS10.4%1,6112023
Argentina ARG10.3%1,6122023
Portugal PRT10.2%1,7352024, 2023

World Bank, World Development Indicators
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.

Sources

Health spending

Current health expenditure (% of GDP)

World Health Organization Global Health Expenditure Database · CC BY 4.0 · updated quarterly

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.

How this was computed

Data used: most recent value in 2010-2025; values come from 2021–2024. 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 Health spending and Hours worked (PWT)

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

More links with Health spending or Hours worked (PWT)