placestats

Hours worked (PWT) vs. Redistribution

Fades after adjusting for income

Across 45 countries, Hours worked (PWT) and Redistribution rise and fall together at r = -0.66 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to -0.35, which could easily be chance (q = 0.22, 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: leave-one-out range spans 0.19 in r.

Comparing countries across the middle half of redistribution, 23.2% to 38.1% reduction in the Gini, hours worked (PWT) is 204 hours per year lower at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 96.5 hours per year.

Link before adjusting (r)-0.655p = 1.0e-6 · 45 countries
After adjusting for national income-0.347p = 0.021 · likely range [-0.58, -0.06]
p, allowing for regions0.054standard error 0.145 · 7 regions
Check for luck (q)0.223across 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
Redistribution · % reduction in the Ginilink with income +0.50 · moderate

“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 →Redistribution · % reduction in the Gini →1,3352,3832.67%48.3%Australia: 1,611 hours per year, 27.7% reduction in the GiniAustria: 1,438 hours per year, 41.4% reduction in the GiniBelgium: 1,593 hours per year, 47.7% reduction in the GiniBulgaria: 1,659 hours per year, 26% reduction in the GiniBrazil: 1,994 hours per year, 13.8% reduction in the GiniCanada: 1,731 hours per year, 29.3% reduction in the GiniSwitzerland: 1,529 hours per year, 21.2% reduction in the GiniChile: 1,950 hours per year, 8.68% reduction in the GiniChina: 2,328 hours per year, 6.22% reduction in the GiniCosta Rica: 2,177 hours per year, 12.6% reduction in the GiniCzechia: 1,774 hours per year, 43.5% reduction in the GiniGermany: 1,335 hours per year, 38.7% reduction in the GiniDenmark: 1,380 hours per year, 37.5% reduction in the GiniSpain: 1,638 hours per year, 34.4% reduction in the GiniEstonia: 1,606 hours per year, 33.5% reduction in the GiniFinland: 1,497 hours per year, 47.2% reduction in the GiniFrance: 1,487 hours per year, 42.2% reduction in the GiniUnited Kingdom: 1,523 hours per year, 29.7% reduction in the GiniGreece: 1,893 hours per year, 36.9% reduction in the GiniCroatia: 1,974 hours per year, 33.1% reduction in the GiniHungary: 1,668 hours per year, 29.4% reduction in the GiniIndia: 2,383 hours per year, 2.67% reduction in the GiniIreland: 1,654 hours per year, 41.2% reduction in the GiniIceland: 1,452 hours per year, 35.7% reduction in the GiniIsrael: 1,890 hours per year, 23.2% reduction in the GiniItaly: 1,701 hours per year, 36.2% reduction in the GiniJapan: 1,654 hours per year, 34.1% reduction in the GiniKorea, Rep.: 1,910 hours per year, 18.2% reduction in the GiniLithuania: 1,640 hours per year, 29.7% reduction in the GiniLuxembourg: 1,452 hours per year, 35.7% reduction in the GiniLatvia: 1,625 hours per year, 28.1% reduction in the GiniMexico: 1,629 hours per year, 3.77% reduction in the GiniNetherlands: 1,439 hours per year, 34.2% reduction in the GiniNorway: 1,412 hours per year, 39.5% reduction in the GiniNew Zealand: 1,708 hours per year, 28.7% reduction in the GiniPoland: 1,807 hours per year, 41.9% reduction in the GiniPortugal: 1,735 hours per year, 36.5% reduction in the GiniRomania: 1,826 hours per year, 38.1% reduction in the GiniRussian Federation: 2,087 hours per year, 27% reduction in the GiniSlovak Republic: 1,621 hours per year, 48.3% reduction in the GiniSlovenia: 1,588 hours per year, 42.4% reduction in the GiniSweden: 1,432 hours per year, 33.1% reduction in the GiniTurkiye: 1,747 hours per year, 18.6% reduction in the GiniUnited States: 1,789 hours per year, 22.1% reduction in the GiniSouth Africa: 2,181 hours per year, 12.8% reduction in the GiniAUTCHECHNCRICZEDEUFINHRVINDMEXPOLSWE

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.6551.0e-645
By rank (Spearman), not adjusted-0.5547.9e-545
Standard (Pearson), adjusted for national income-0.3470.02145
By rank (Spearman), adjusted for national income-0.3340.02745

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 45 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: +0.308 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.475 (without MEX) to -0.289 (without CHN). 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: MEX (-0.128).

Fragile: this link may not hold up.
  • leave-one-out range spans 0.19 in r
  • much weaker within regions than across them (largely a between-region difference)

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
Europe & Central Asia31-0.10

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 third15-0.18
Middle third15-0.59
Richest third15-0.40

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
Christians36-0.25

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
No strong official ideology38-0.42

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
No parties banned42-0.32

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 = -0.279 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 13years. 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 = -0.328) but mostly disappears in year-to-year changes (r = -0.111). That points to slow trends particular to each country, not the two measures moving together from year to year.

Across countries (adjusted)-0.347for comparison
Within countries-0.335each country vs itself
…and vs the same year elsewhere-0.328q = 0.016 · 39 countries
Year-on-year changes-0.111q = 0.393
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.

441 country-years (one country in one year), 39 countries, 2011–2023, about 11 years each on average. Share of the variation that happens within countries over time: 4% for Hours worked (PWT), 6% for Redistribution. 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

0.40−0.4-60+10years Redistribution trails Hours worked (PWT) →lag -6: r = 0.062 (n = 217)lag -5: r = 0.039 (n = 249)lag -4: r = -0.124 (n = 286)lag -3: r = -0.220 (n = 338)lag -2: r = -0.254 (n = 371)lag -1: r = -0.249 (n = 416)lag +0: r = -0.328 (n = 441)lag +1: r = -0.337 (n = 442)lag +2: r = -0.339 (n = 442)lag +3: r = -0.300 (n = 442)lag +4: r = -0.311 (n = 442)lag +5: r = -0.268 (n = 442)lag +6: r = -0.243 (n = 442)lag +7: r = -0.209 (n = 442)lag +8: r = -0.210 (n = 442)lag +9: r = -0.196 (n = 442)lag +10: r = -0.171 (n = 442)

Same year (lag 0): -0.328. 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
% reduction in the Gini		Years
India IND2,3832.67%2023, 2011
China CHN2,3286.22%2023, 2011
South Africa ZAF2,18112.8%2023, 2017
Costa Rica CRI2,17712.6%2023, 2024
Russian Federation RUS2,08727%2023, 2017
Brazil BRA1,99413.8%2023, 2022
Croatia HRV1,97433.1%2023
Chile CHL1,9508.68%2023, 2022
Korea, Rep. KOR1,91018.2%2023, 2022
Greece GRC1,89336.9%2023
Israel ISR1,89023.2%2023, 2022
Romania ROU1,82638.1%2023
Poland POL1,80741.9%2023
United States USA1,78922.1%2023
Czechia CZE1,77443.5%2023

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.
OECD databases as named on each indicator: PISA, Social Expenditure Database (SOCX), Income Distribution Database, Development Assistance Committee statistics, Family Database, Government at a Glance, Corporate Tax Statistics, employment and environment statistics

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.

Redistribution

Reduction in the Gini coefficient from taxes and transfers

OECD · via Our World in Data · CC BY 4.0 (OECD terms and conditions) · updated annual, except the snapshots noted per indicator · comparable from 2011 only

The Gini before taxes and payments minus the Gini after them, as a share of the first. It shows how much of the inequality produced by the market the government removes. It is built from the before-tax Gini above, so their pair is built from the same numbers and flagged. No "better" direction is set: a country may redistribute little because its market incomes are already equal.

How this was computed

Data used: most recent value in 2010-2025; values come from 2011–2024. 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 Redistribution

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

More links with Hours worked (PWT) or Redistribution