placestats

Governance score vs. Hours worked (PWT)

Fades after adjusting for income

Across 127 countries, Governance score and Hours worked (PWT) rise and fall together at r = -0.59 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) leaves r = -0.51, which could easily be chance (q = 0.052, 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), 1,647 to 2,178 hours per year, governance score is worse by 0.865 typical gaps at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.61 typical gaps.

Link before adjusting (r)-0.591p = 2.7e-13 · 127 countries
After adjusting for national income-0.514p = 7.6e-10 · likely range [-0.63, -0.37]
p, allowing for regions0.000standard error 0.062 · 7 regions
Check for luck (q)0.052across 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.

Governance score · typical gaps (standard deviations)link with income +0.63 · high
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

Governance score · typical gaps (standard deviations) →Hours worked (PWT) · hours per year →-1.491.571,3352,658Angola: -0.602 typical gaps (standard deviations), 2,115 hours per yearAlbania: 0.259 typical gaps (standard deviations), 2,152 hours per yearUnited Arab Emirates: -0.438 typical gaps (standard deviations), 2,514 hours per yearArgentina: 0.568 typical gaps (standard deviations), 1,612 hours per yearArmenia: 0.127 typical gaps (standard deviations), 1,976 hours per yearAustralia: 1.42 typical gaps (standard deviations), 1,611 hours per yearAustria: 1.31 typical gaps (standard deviations), 1,438 hours per yearAzerbaijan: -1.03 typical gaps (standard deviations), 1,791 hours per yearBelgium: 1.32 typical gaps (standard deviations), 1,593 hours per yearBurkina Faso: -0.825 typical gaps (standard deviations), 2,356 hours per yearBangladesh: -0.507 typical gaps (standard deviations), 2,383 hours per yearBulgaria: 0.537 typical gaps (standard deviations), 1,659 hours per yearBahrain: -0.69 typical gaps (standard deviations), 2,052 hours per yearBosnia and Herzegovina: -0.0604 typical gaps (standard deviations), 2,122 hours per yearBelarus: -1.15 typical gaps (standard deviations), 1,875 hours per yearBolivia: 0.114 typical gaps (standard deviations), 1,968 hours per yearBrazil: 0.502 typical gaps (standard deviations), 1,994 hours per yearBotswana: 0.763 typical gaps (standard deviations), 2,258 hours per yearCanada: 1.39 typical gaps (standard deviations), 1,731 hours per yearSwitzerland: 1.54 typical gaps (standard deviations), 1,529 hours per yearChile: 1.15 typical gaps (standard deviations), 1,950 hours per yearChina: -0.875 typical gaps (standard deviations), 2,328 hours per yearCote d'Ivoire: -0.208 typical gaps (standard deviations), 2,103 hours per yearCameroon: -0.934 typical gaps (standard deviations), 2,181 hours per yearCongo, Dem. Rep.: -1.07 typical gaps (standard deviations), 1,841 hours per yearCongo, Rep.: -0.987 typical gaps (standard deviations), 2,534 hours per yearColombia: 0.377 typical gaps (standard deviations), 2,471 hours per yearCosta Rica: 1.15 typical gaps (standard deviations), 2,177 hours per yearCyprus: 0.98 typical gaps (standard deviations), 1,840 hours per yearCzechia: 1.24 typical gaps (standard deviations), 1,774 hours per yearGermany: 1.35 typical gaps (standard deviations), 1,335 hours per yearDenmark: 1.57 typical gaps (standard deviations), 1,380 hours per yearDominican Republic: 0.48 typical gaps (standard deviations), 2,072 hours per yearAlgeria: -0.674 typical gaps (standard deviations), 2,232 hours per yearEcuador: 0.126 typical gaps (standard deviations), 1,594 hours per yearEgypt, Arab Rep.: -0.9 typical gaps (standard deviations), 2,369 hours per yearSpain: 1.13 typical gaps (standard deviations), 1,638 hours per yearEstonia: 1.4 typical gaps (standard deviations), 1,606 hours per yearEthiopia: -0.809 typical gaps (standard deviations), 1,599 hours per yearFinland: 1.51 typical gaps (standard deviations), 1,497 hours per yearFrance: 1.14 typical gaps (standard deviations), 1,487 hours per yearGabon: -0.556 typical gaps (standard deviations), 2,174 hours per yearUnited Kingdom: 1.25 typical gaps (standard deviations), 1,523 hours per yearGeorgia: 0.0236 typical gaps (standard deviations), 1,932 hours per yearGhana: 0.586 typical gaps (standard deviations), 1,656 hours per yearGreece: 0.751 typical gaps (standard deviations), 1,893 hours per yearGuatemala: 0.000403 typical gaps (standard deviations), 2,151 hours per yearHong Kong SAR, China: -0.017 typical gaps (standard deviations), 2,240 hours per yearCroatia: 0.761 typical gaps (standard deviations), 1,974 hours per yearHungary: 0.237 typical gaps (standard deviations), 1,668 hours per yearIndonesia: 0.0177 typical gaps (standard deviations), 1,958 hours per yearIndia: 0.0581 typical gaps (standard deviations), 2,383 hours per yearIreland: 1.43 typical gaps (standard deviations), 1,654 hours per yearIran, Islamic Rep.: -1.28 typical gaps (standard deviations), 2,246 hours per yearIraq: -0.727 typical gaps (standard deviations), 1,583 hours per yearIceland: 1.37 typical gaps (standard deviations), 1,452 hours per yearIsrael: 0.72 typical gaps (standard deviations), 1,890 hours per yearItaly: 0.911 typical gaps (standard deviations), 1,701 hours per yearJamaica: 0.748 typical gaps (standard deviations), 1,963 hours per yearJordan: -0.18 typical gaps (standard deviations), 2,483 hours per yearJapan: 1.34 typical gaps (standard deviations), 1,654 hours per yearKazakhstan: -0.619 typical gaps (standard deviations), 1,975 hours per yearKenya: -0.0288 typical gaps (standard deviations), 2,035 hours per yearKyrgyz Republic: -0.706 typical gaps (standard deviations), 1,830 hours per yearCambodia: -0.921 typical gaps (standard deviations), 2,389 hours per yearKorea, Rep.: 1.06 typical gaps (standard deviations), 1,910 hours per yearKuwait: -0.424 typical gaps (standard deviations), 2,318 hours per yearLebanon: -0.406 typical gaps (standard deviations), 2,412 hours per yearSri Lanka: 0.356 typical gaps (standard deviations), 2,053 hours per yearLithuania: 1.16 typical gaps (standard deviations), 1,640 hours per yearLuxembourg: 1.48 typical gaps (standard deviations), 1,452 hours per yearLatvia: 1.13 typical gaps (standard deviations), 1,625 hours per yearMorocco: -0.333 typical gaps (standard deviations), 2,174 hours per yearMoldova: 0.335 typical gaps (standard deviations), 1,989 hours per yearMadagascar: -0.392 typical gaps (standard deviations), 1,799 hours per yearMexico: -0.0935 typical gaps (standard deviations), 1,629 hours per yearNorth Macedonia: 0.285 typical gaps (standard deviations), 1,949 hours per yearMali: -0.943 typical gaps (standard deviations), 2,243 hours per yearMalta: 0.978 typical gaps (standard deviations), 1,848 hours per yearMyanmar: -1.49 typical gaps (standard deviations), 2,197 hours per yearMozambique: -0.547 typical gaps (standard deviations), 1,507 hours per yearMauritius: 0.962 typical gaps (standard deviations), 1,990 hours per yearMalawi: 0.271 typical gaps (standard deviations), 1,596 hours per yearMalaysia: 0.278 typical gaps (standard deviations), 2,308 hours per yearNamibia: 0.568 typical gaps (standard deviations), 2,184 hours per yearNiger: -0.715 typical gaps (standard deviations), 2,069 hours per yearNigeria: -0.334 typical gaps (standard deviations), 2,062 hours per yearNetherlands: 1.38 typical gaps (standard deviations), 1,439 hours per yearNorway: 1.53 typical gaps (standard deviations), 1,412 hours per yearNew Zealand: 1.45 typical gaps (standard deviations), 1,708 hours per yearOman: -0.349 typical gaps (standard deviations), 2,266 hours per yearPakistan: -0.658 typical gaps (standard deviations), 2,471 hours per yearPeru: 0.244 typical gaps (standard deviations), 2,143 hours per yearPhilippines: -0.052 typical gaps (standard deviations), 2,096 hours per yearPoland: 0.922 typical gaps (standard deviations), 1,807 hours per yearPortugal: 1.15 typical gaps (standard deviations), 1,735 hours per yearParaguay: 0.135 typical gaps (standard deviations), 2,123 hours per yearQatar: -0.421 typical gaps (standard deviations), 2,435 hours per yearRomania: 0.595 typical gaps (standard deviations), 1,826 hours per yearRussian Federation: -1.11 typical gaps (standard deviations), 2,087 hours per yearRwanda: -0.532 typical gaps (standard deviations), 1,584 hours per yearSaudi Arabia: -0.712 typical gaps (standard deviations), 2,125 hours per yearSudan: -1.43 typical gaps (standard deviations), 2,658 hours per yearSenegal: 0.459 typical gaps (standard deviations), 2,335 hours per yearSingapore: 0.528 typical gaps (standard deviations), 2,283 hours per yearSerbia: -0.129 typical gaps (standard deviations), 1,995 hours per yearSlovak Republic: 0.851 typical gaps (standard deviations), 1,621 hours per yearSlovenia: 1.1 typical gaps (standard deviations), 1,588 hours per yearSweden: 1.49 typical gaps (standard deviations), 1,432 hours per yearSyrian Arab Republic: -1.29 typical gaps (standard deviations), 1,621 hours per yearChad: -1.1 typical gaps (standard deviations), 1,585 hours per yearThailand: -0.321 typical gaps (standard deviations), 2,177 hours per yearTajikistan: -1.22 typical gaps (standard deviations), 2,134 hours per yearTurkmenistan: -1.33 typical gaps (standard deviations), 2,179 hours per yearTrinidad and Tobago: 0.718 typical gaps (standard deviations), 1,610 hours per yearTunisia: -0.317 typical gaps (standard deviations), 2,288 hours per yearTurkiye: -0.647 typical gaps (standard deviations), 1,747 hours per yearTanzania: -0.365 typical gaps (standard deviations), 2,129 hours per yearUganda: -0.676 typical gaps (standard deviations), 2,128 hours per yearUkraine: -0.182 typical gaps (standard deviations), 2,045 hours per yearUruguay: 1.29 typical gaps (standard deviations), 1,481 hours per yearUnited States: 0.906 typical gaps (standard deviations), 1,789 hours per yearUzbekistan: -0.864 typical gaps (standard deviations), 2,099 hours per yearViet Nam: -0.692 typical gaps (standard deviations), 2,160 hours per yearSouth Africa: 0.602 typical gaps (standard deviations), 2,181 hours per yearZambia: 0.0286 typical gaps (standard deviations), 2,200 hours per yearZimbabwe: -0.779 typical gaps (standard deviations), 2,311 hours per yearBWACOGCOLCRIDEUDNKETHMMRNORSDNSYRTCD

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.5912.7e-13127
By rank (Spearman), not adjusted-0.5693.0e-12127
Standard (Pearson), adjusted for national income-0.5147.6e-10127
By rank (Spearman), adjusted for national income-0.4402.5e-7127

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 127 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: +0.077 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.536 (without SYR) to -0.493 (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: SYR (-0.022).

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 & Pacific14-0.88
Europe & Central Asia47-0.49
Latin America & Caribbean15+0.09
Middle East, North Africa, Afghanistan & Pakistan18-0.14
Sub-Saharan Africa28-0.36

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 third43-0.20
Middle third42-0.28
Richest third42-0.84

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
Christians74-0.41
Muslims36+0.20

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+0.27
Never a European colony17-0.55
Spain14+0.18
United Kingdom35-0.62

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
Nationalist21-0.15
No strong official ideology85-0.59

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 banned18-0.32
No parties banned93-0.41

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 = -0.514 after dropping 0 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 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


typical gaps (standard deviations)
hours per year		Years
Denmark DNK1.571,3802025, 2023
Switzerland CHE1.541,5292025, 2023
Norway NOR1.531,4122025, 2023
Finland FIN1.511,4972025, 2023
Sweden SWE1.491,4322025, 2023
Luxembourg LUX1.481,4522025, 2023
New Zealand NZL1.451,7082025, 2023
Ireland IRL1.431,6542025, 2023
Australia AUS1.421,6112025, 2023
Estonia EST1.41,6062025, 2023
Canada CAN1.391,7312025, 2023
Netherlands NLD1.381,4392025, 2023
Iceland ISL1.371,4522025, 2023
Germany DEU1.351,3352025, 2023
Japan JPN1.341,6542025, 2023

fh; un_sdg; vdem; wdi; wgi
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

Governance score

Governance score

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

The average of 19 measures from 5 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: Civil liberties (FH), Political rights (FH), Pre-trial detainee share, Civil society participation, Political corruption, Electoral democracy, Freedom of association, Freedom of expression, Free and fair elections, Liberal democracy, Participatory democracy, Political civil liberties, Birth registration, Control of corruption, Government effectiveness, Political stability, Rule of law, Regulatory quality, Voice and accountability.

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 2023–2025. 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 Governance score and Hours worked (PWT)

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

More links with Governance score or Hours worked (PWT)