placestats

Hours worked (PWT) vs. Wellbeing score

Fades after adjusting for income

Across 96 countries, Hours worked (PWT) and Wellbeing score 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 -0.36, which could easily be chance (q = 0.14, 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: direction is not consistent across regions.

Comparing countries across the middle half of hours worked (PWT), 1,624 to 2,164 hours per year, wellbeing score is worse by 0.781 typical gaps at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.379 typical gaps.

Link before adjusting (r)-0.577p = 7.3e-10 · 96 countries
After adjusting for national income-0.358p = 0.000 · likely range [-0.52, -0.17]
p, allowing for regions0.032standard error 0.129 · 7 regions
Check for luck (q)0.138across 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
Wellbeing score · typical gaps (standard deviations)link with income +0.80 · high

“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 →Wellbeing score · typical gaps (standard deviations) →1,3352,483-1.981.89Albania: 2,152 hours per year, -0.617 typical gaps (standard deviations)Argentina: 1,612 hours per year, 0.216 typical gaps (standard deviations)Armenia: 1,976 hours per year, -0.118 typical gaps (standard deviations)Australia: 1,611 hours per year, 1.25 typical gaps (standard deviations)Austria: 1,438 hours per year, 1.26 typical gaps (standard deviations)Azerbaijan: 1,791 hours per year, -0.0603 typical gaps (standard deviations)Belgium: 1,593 hours per year, 0.818 typical gaps (standard deviations)Burkina Faso: 2,356 hours per year, -0.476 typical gaps (standard deviations)Bangladesh: 2,383 hours per year, -0.561 typical gaps (standard deviations)Bulgaria: 1,659 hours per year, -0.572 typical gaps (standard deviations)Bosnia and Herzegovina: 2,122 hours per year, -0.087 typical gaps (standard deviations)Belarus: 1,875 hours per year, 0.732 typical gaps (standard deviations)Bolivia: 1,968 hours per year, -0.361 typical gaps (standard deviations)Brazil: 1,994 hours per year, 0.123 typical gaps (standard deviations)Canada: 1,731 hours per year, 1.06 typical gaps (standard deviations)Switzerland: 1,529 hours per year, 1.55 typical gaps (standard deviations)Chile: 1,950 hours per year, 0.19 typical gaps (standard deviations)China: 2,328 hours per year, 0.913 typical gaps (standard deviations)Colombia: 2,471 hours per year, -0.125 typical gaps (standard deviations)Cyprus: 1,840 hours per year, -0.0176 typical gaps (standard deviations)Czechia: 1,774 hours per year, 0.726 typical gaps (standard deviations)Germany: 1,335 hours per year, 0.981 typical gaps (standard deviations)Denmark: 1,380 hours per year, 1.89 typical gaps (standard deviations)Algeria: 2,232 hours per year, -0.205 typical gaps (standard deviations)Ecuador: 1,594 hours per year, -0.164 typical gaps (standard deviations)Egypt, Arab Rep.: 2,369 hours per year, -1.08 typical gaps (standard deviations)Spain: 1,638 hours per year, 0.816 typical gaps (standard deviations)Estonia: 1,606 hours per year, 0.622 typical gaps (standard deviations)Ethiopia: 1,599 hours per year, -0.726 typical gaps (standard deviations)Finland: 1,497 hours per year, 1.87 typical gaps (standard deviations)France: 1,487 hours per year, 0.717 typical gaps (standard deviations)United Kingdom: 1,523 hours per year, 1.07 typical gaps (standard deviations)Georgia: 1,932 hours per year, -0.493 typical gaps (standard deviations)Ghana: 1,656 hours per year, -0.73 typical gaps (standard deviations)Greece: 1,893 hours per year, -0.284 typical gaps (standard deviations)Guatemala: 2,151 hours per year, 0.352 typical gaps (standard deviations)Hong Kong SAR, China: 2,240 hours per year, 0.0778 typical gaps (standard deviations)Croatia: 1,974 hours per year, 0.0883 typical gaps (standard deviations)Hungary: 1,668 hours per year, 0.266 typical gaps (standard deviations)Indonesia: 1,958 hours per year, -0.192 typical gaps (standard deviations)India: 2,383 hours per year, -0.736 typical gaps (standard deviations)Ireland: 1,654 hours per year, 0.894 typical gaps (standard deviations)Iran, Islamic Rep.: 2,246 hours per year, -0.684 typical gaps (standard deviations)Iraq: 1,583 hours per year, -0.726 typical gaps (standard deviations)Iceland: 1,452 hours per year, 1.78 typical gaps (standard deviations)Italy: 1,701 hours per year, 0.438 typical gaps (standard deviations)Jordan: 2,483 hours per year, -0.666 typical gaps (standard deviations)Japan: 1,654 hours per year, 0.552 typical gaps (standard deviations)Kazakhstan: 1,975 hours per year, 0.304 typical gaps (standard deviations)Kenya: 2,035 hours per year, -0.678 typical gaps (standard deviations)Kyrgyz Republic: 1,830 hours per year, 0.225 typical gaps (standard deviations)Korea, Rep.: 1,910 hours per year, 0.475 typical gaps (standard deviations)Kuwait: 2,318 hours per year, 0.607 typical gaps (standard deviations)Lebanon: 2,412 hours per year, -1.54 typical gaps (standard deviations)Lithuania: 1,640 hours per year, 0.51 typical gaps (standard deviations)Luxembourg: 1,452 hours per year, 0.652 typical gaps (standard deviations)Latvia: 1,625 hours per year, 0.212 typical gaps (standard deviations)Morocco: 2,174 hours per year, -0.382 typical gaps (standard deviations)Moldova: 1,989 hours per year, -1.29 typical gaps (standard deviations)Mexico: 1,629 hours per year, 0.335 typical gaps (standard deviations)North Macedonia: 1,949 hours per year, -0.171 typical gaps (standard deviations)Mali: 2,243 hours per year, -0.328 typical gaps (standard deviations)Malta: 1,848 hours per year, 0.15 typical gaps (standard deviations)Myanmar: 2,197 hours per year, -0.547 typical gaps (standard deviations)Malaysia: 2,308 hours per year, 0.215 typical gaps (standard deviations)Nigeria: 2,062 hours per year, -0.611 typical gaps (standard deviations)Netherlands: 1,439 hours per year, 1.54 typical gaps (standard deviations)Norway: 1,412 hours per year, 1.82 typical gaps (standard deviations)New Zealand: 1,708 hours per year, 1.46 typical gaps (standard deviations)Pakistan: 2,471 hours per year, -0.299 typical gaps (standard deviations)Peru: 2,143 hours per year, -0.348 typical gaps (standard deviations)Philippines: 2,096 hours per year, -0.119 typical gaps (standard deviations)Poland: 1,807 hours per year, 0.505 typical gaps (standard deviations)Portugal: 1,735 hours per year, 0.195 typical gaps (standard deviations)Qatar: 2,435 hours per year, 0.756 typical gaps (standard deviations)Romania: 1,826 hours per year, 0.197 typical gaps (standard deviations)Russian Federation: 2,087 hours per year, -0.00878 typical gaps (standard deviations)Rwanda: 1,584 hours per year, -0.867 typical gaps (standard deviations)Singapore: 2,283 hours per year, 0.779 typical gaps (standard deviations)Serbia: 1,995 hours per year, 0.105 typical gaps (standard deviations)Slovak Republic: 1,621 hours per year, 0.318 typical gaps (standard deviations)Slovenia: 1,588 hours per year, 0.55 typical gaps (standard deviations)Sweden: 1,432 hours per year, 1.7 typical gaps (standard deviations)Thailand: 2,177 hours per year, 0.256 typical gaps (standard deviations)Tajikistan: 2,134 hours per year, 0.104 typical gaps (standard deviations)Trinidad and Tobago: 1,610 hours per year, 0.0637 typical gaps (standard deviations)Tunisia: 2,288 hours per year, -0.73 typical gaps (standard deviations)Turkiye: 1,747 hours per year, -0.508 typical gaps (standard deviations)Ukraine: 2,045 hours per year, -0.244 typical gaps (standard deviations)Uruguay: 1,481 hours per year, 0.449 typical gaps (standard deviations)United States: 1,789 hours per year, 0.943 typical gaps (standard deviations)Uzbekistan: 2,099 hours per year, 0.617 typical gaps (standard deviations)Viet Nam: 2,160 hours per year, 0.469 typical gaps (standard deviations)South Africa: 2,181 hours per year, -0.515 typical gaps (standard deviations)Zambia: 2,200 hours per year, -1.67 typical gaps (standard deviations)Zimbabwe: 2,311 hours per year, -1.98 typical gaps (standard deviations)CHNDNKETHIRQISLLBNNORQATRWASGPZMBZWE

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.5777.3e-1096
By rank (Spearman), not adjusted-0.5525.7e-996
Standard (Pearson), adjusted for national income-0.3580.00096
By rank (Spearman), adjusted for national income-0.2390.01996

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 96 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: +0.220 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.391 (without CHN) to -0.339 (without EGY). 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: CHN (-0.033).

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 & Pacific13-0.43
Europe & Central Asia46-0.57
Middle East, North Africa, Afghanistan & Pakistan12+0.08

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 third32-0.16
Middle third32-0.04
Richest third32-0.60

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
Christians58-0.48
Muslims25-0.09

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+0.33
United Kingdom23-0.30

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
Nationalist16-0.29
No strong official ideology67-0.45

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 banned12-0.03
No parties banned74-0.39

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 = -0.354 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.

Loading…

Over time, within countries

Everything above compares countries with each other at one moment. This section compares each country only with itself over 0years. So a link here can’t come from anything about a country that stays the same, such as its history, geography, institutions or culture.

Not enough history inside each country to look at this over time. That needs countries measured for several years in a row, and at least one of these measures is measured too rarely.

The data


hours per year
typical gaps (standard deviations)		Years
Jordan JOR2,483-0.6662023, 2022
Pakistan PAK2,471-0.2992023, 2022
Colombia COL2,471-0.1252023, 2022
Qatar QAT2,4350.7562023, 2014
Lebanon LBN2,412-1.542023, 2022
Bangladesh BGD2,383-0.5612023, 2022
India IND2,383-0.7362023, 2022
Egypt, Arab Rep. EGY2,369-1.082023, 2022
Burkina Faso BFA2,356-0.4762023, 2010
China CHN2,3280.9132023, 2022
Kuwait KWT2,3180.6072023, 2014
Zimbabwe ZWE2,311-1.982023, 2022
Malaysia MYS2,3080.2152023, 2022
Tunisia TUN2,288-0.732023, 2022
Singapore SGP2,2830.7792023, 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.
ivs; whr

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.

Wellbeing score

Wellbeing score

PlaceStats · via PlaceStats · Derived work; each member keeps its own licence · updated recomputed with the panel

The average of 3 measures from 2 publishers. Each measure is first put on a common scale: 0 is the average country in an average year, and 1 is a typical gap between countries (a standard deviation). Each is turned so that higher is better. Measures are averaged within each publisher first, so a publisher with many measures does not count for more. Members: Self-reported happiness, Interpersonal trust, Life satisfaction.

How this was computed

Data used: most recent value in 2010-2025; values come from 2010–2023. 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 Wellbeing score

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

More links with Hours worked (PWT) or Wellbeing score