placestats

Governance score vs. Out-of-pocket health spending

Fades after adjusting for income

Across 169 countries, Governance score and Out-of-pocket health spending 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 = -0.38, which could easily be chance (q = 0.057, allowing for the many pairs tested, and allowing for countries in the same region being alike).

Comparing countries across the middle half of out-of-pocket health spending, 16.2% to 44.4% of health spending, governance score is worse by 0.668 typical gaps at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.418 typical gaps.

Link before adjusting (r)-0.524p = 2.8e-13 · 169 countries
After adjusting for national income-0.385p = 2.6e-7 · likely range [-0.51, -0.25]
p, allowing for regions0.011standard error 0.107 · 7 regions
Check for luck (q)0.057across 17,292 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
Out-of-pocket health spending · % of health spendinglink with income -0.34 · 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) →Out-of-pocket health spending · % of health spending →-1.531.573.16%80.5%Afghanistan: -1.53 typical gaps (standard deviations), 77.1% of health spendingAngola: -0.602 typical gaps (standard deviations), 32.5% of health spendingAlbania: 0.259 typical gaps (standard deviations), 48.3% of health spendingAndorra: 0.556 typical gaps (standard deviations), 11.1% of health spendingUnited Arab Emirates: -0.438 typical gaps (standard deviations), 9.67% of health spendingArgentina: 0.568 typical gaps (standard deviations), 24.5% of health spendingArmenia: 0.127 typical gaps (standard deviations), 80.5% of health spendingAustralia: 1.42 typical gaps (standard deviations), 15.8% of health spendingAustria: 1.31 typical gaps (standard deviations), 16.5% of health spendingAzerbaijan: -1.03 typical gaps (standard deviations), 64.6% of health spendingBurundi: -1.16 typical gaps (standard deviations), 24.5% of health spendingBelgium: 1.32 typical gaps (standard deviations), 21.5% of health spendingBenin: 0.0936 typical gaps (standard deviations), 42.4% of health spendingBurkina Faso: -0.825 typical gaps (standard deviations), 43.8% of health spendingBangladesh: -0.507 typical gaps (standard deviations), 79.3% of health spendingBulgaria: 0.537 typical gaps (standard deviations), 35.5% of health spendingBahrain: -0.69 typical gaps (standard deviations), 28.7% of health spendingBosnia and Herzegovina: -0.0604 typical gaps (standard deviations), 31% of health spendingBelarus: -1.15 typical gaps (standard deviations), 28.5% of health spendingBelize: 0.087 typical gaps (standard deviations), 26.8% of health spendingBolivia: 0.114 typical gaps (standard deviations), 27.3% of health spendingBrazil: 0.502 typical gaps (standard deviations), 26.2% of health spendingBarbados: 1.13 typical gaps (standard deviations), 49.5% of health spendingBhutan: 0.659 typical gaps (standard deviations), 25.5% of health spendingBotswana: 0.763 typical gaps (standard deviations), 4.26% of health spendingCentral African Republic: -1.17 typical gaps (standard deviations), 45% of health spendingCanada: 1.39 typical gaps (standard deviations), 15.3% of health spendingSwitzerland: 1.54 typical gaps (standard deviations), 22% of health spendingChile: 1.15 typical gaps (standard deviations), 39.1% of health spendingChina: -0.875 typical gaps (standard deviations), 32.2% of health spendingCote d'Ivoire: -0.208 typical gaps (standard deviations), 32% of health spendingCameroon: -0.934 typical gaps (standard deviations), 67.7% of health spendingCongo, Dem. Rep.: -1.07 typical gaps (standard deviations), 38% of health spendingCongo, Rep.: -0.987 typical gaps (standard deviations), 28% of health spendingColombia: 0.377 typical gaps (standard deviations), 14.7% of health spendingComoros: -0.604 typical gaps (standard deviations), 56.6% of health spendingCabo Verde: 0.977 typical gaps (standard deviations), 25.7% of health spendingCosta Rica: 1.15 typical gaps (standard deviations), 24.1% of health spendingCyprus: 0.98 typical gaps (standard deviations), 17.9% of health spendingCzechia: 1.24 typical gaps (standard deviations), 14.1% of health spendingGermany: 1.35 typical gaps (standard deviations), 10.7% of health spendingDjibouti: -0.803 typical gaps (standard deviations), 28.8% of health spendingDenmark: 1.57 typical gaps (standard deviations), 13.9% of health spendingDominican Republic: 0.48 typical gaps (standard deviations), 25.1% of health spendingAlgeria: -0.674 typical gaps (standard deviations), 45% of health spendingEcuador: 0.126 typical gaps (standard deviations), 30.9% of health spendingEgypt, Arab Rep.: -0.9 typical gaps (standard deviations), 57.2% of health spendingSpain: 1.13 typical gaps (standard deviations), 20.9% of health spendingEstonia: 1.4 typical gaps (standard deviations), 21.4% of health spendingEthiopia: -0.809 typical gaps (standard deviations), 46.3% of health spendingFinland: 1.51 typical gaps (standard deviations), 14.1% of health spendingFiji: 0.538 typical gaps (standard deviations), 8.31% of health spendingFrance: 1.14 typical gaps (standard deviations), 9.23% of health spendingGabon: -0.556 typical gaps (standard deviations), 17.3% of health spendingUnited Kingdom: 1.25 typical gaps (standard deviations), 14.6% of health spendingGeorgia: 0.0236 typical gaps (standard deviations), 58.8% of health spendingGhana: 0.586 typical gaps (standard deviations), 26.7% of health spendingGuinea: -0.779 typical gaps (standard deviations), 54.4% of health spendingGambia, The: 0.128 typical gaps (standard deviations), 33.8% of health spendingGuinea-Bissau: -0.69 typical gaps (standard deviations), 61.6% of health spendingEquatorial Guinea: -1.3 typical gaps (standard deviations), 66% of health spendingGreece: 0.751 typical gaps (standard deviations), 34.3% of health spendingGuatemala: 0.000403 typical gaps (standard deviations), 57.2% of health spendingGuyana: 0.328 typical gaps (standard deviations), 26.3% of health spendingHonduras: -0.154 typical gaps (standard deviations), 53.1% of health spendingCroatia: 0.761 typical gaps (standard deviations), 9.38% of health spendingHaiti: -0.951 typical gaps (standard deviations), 52.4% of health spendingHungary: 0.237 typical gaps (standard deviations), 23.1% of health spendingIndonesia: 0.0177 typical gaps (standard deviations), 31.1% of health spendingIndia: 0.0581 typical gaps (standard deviations), 43.9% of health spendingIreland: 1.43 typical gaps (standard deviations), 10.6% of health spendingIran, Islamic Rep.: -1.28 typical gaps (standard deviations), 43.1% of health spendingIraq: -0.727 typical gaps (standard deviations), 54% of health spendingIceland: 1.37 typical gaps (standard deviations), 14.9% of health spendingIsrael: 0.72 typical gaps (standard deviations), 20.5% of health spendingItaly: 0.911 typical gaps (standard deviations), 22.3% of health spendingJamaica: 0.748 typical gaps (standard deviations), 20.2% of health spendingJordan: -0.18 typical gaps (standard deviations), 34.5% of health spendingJapan: 1.34 typical gaps (standard deviations), 12.2% of health spendingKazakhstan: -0.619 typical gaps (standard deviations), 27.6% of health spendingKenya: -0.0288 typical gaps (standard deviations), 24.2% of health spendingKyrgyz Republic: -0.706 typical gaps (standard deviations), 42.3% of health spendingCambodia: -0.921 typical gaps (standard deviations), 60.6% of health spendingKorea, Rep.: 1.06 typical gaps (standard deviations), 33.7% of health spendingKuwait: -0.424 typical gaps (standard deviations), 10% of health spendingLao PDR: -0.976 typical gaps (standard deviations), 44.8% of health spendingLebanon: -0.406 typical gaps (standard deviations), 29.7% of health spendingLiberia: 0.064 typical gaps (standard deviations), 63.2% of health spendingLibya: -1.12 typical gaps (standard deviations), 19.2% of health spendingSt. Lucia: 0.549 typical gaps (standard deviations), 37.1% of health spendingSri Lanka: 0.356 typical gaps (standard deviations), 54.8% of health spendingLesotho: 0.356 typical gaps (standard deviations), 13.2% of health spendingLithuania: 1.16 typical gaps (standard deviations), 31.4% of health spendingLuxembourg: 1.48 typical gaps (standard deviations), 8.5% of health spendingLatvia: 1.13 typical gaps (standard deviations), 35.1% of health spendingMorocco: -0.333 typical gaps (standard deviations), 37.3% of health spendingMoldova: 0.335 typical gaps (standard deviations), 27.5% of health spendingMadagascar: -0.392 typical gaps (standard deviations), 27.4% of health spendingMaldives: -0.015 typical gaps (standard deviations), 18% of health spendingMexico: -0.0935 typical gaps (standard deviations), 41.2% of health spendingNorth Macedonia: 0.285 typical gaps (standard deviations), 39.6% of health spendingMali: -0.943 typical gaps (standard deviations), 47.2% of health spendingMalta: 0.978 typical gaps (standard deviations), 30.9% of health spendingMyanmar: -1.49 typical gaps (standard deviations), 71.1% of health spendingMontenegro: 0.475 typical gaps (standard deviations), 26.3% of health spendingMongolia: 0.484 typical gaps (standard deviations), 48.8% of health spendingMozambique: -0.547 typical gaps (standard deviations), 10.4% of health spendingMauritania: -0.54 typical gaps (standard deviations), 43.8% of health spendingMauritius: 0.962 typical gaps (standard deviations), 45.2% of health spendingMalawi: 0.271 typical gaps (standard deviations), 12% of health spendingMalaysia: 0.278 typical gaps (standard deviations), 37.1% of health spendingNamibia: 0.568 typical gaps (standard deviations), 7.49% of health spendingNiger: -0.715 typical gaps (standard deviations), 51.5% of health spendingNigeria: -0.334 typical gaps (standard deviations), 71.9% of health spendingNicaragua: -1.19 typical gaps (standard deviations), 37.6% of health spendingNetherlands: 1.38 typical gaps (standard deviations), 11.8% of health spendingNorway: 1.53 typical gaps (standard deviations), 13.7% of health spendingNepal: 0.128 typical gaps (standard deviations), 59.4% of health spendingNew Zealand: 1.45 typical gaps (standard deviations), 12.7% of health spendingOman: -0.349 typical gaps (standard deviations), 6.31% of health spendingPakistan: -0.658 typical gaps (standard deviations), 52.9% of health spendingPanama: 0.565 typical gaps (standard deviations), 40.5% of health spendingPeru: 0.244 typical gaps (standard deviations), 27% of health spendingPhilippines: -0.052 typical gaps (standard deviations), 44.4% of health spendingPapua New Guinea: -0.0334 typical gaps (standard deviations), 8.55% of health spendingPoland: 0.922 typical gaps (standard deviations), 16.2% of health spendingPortugal: 1.15 typical gaps (standard deviations), 28.2% of health spendingParaguay: 0.135 typical gaps (standard deviations), 36.3% of health spendingQatar: -0.421 typical gaps (standard deviations), 7.43% of health spendingRomania: 0.595 typical gaps (standard deviations), 23% of health spendingRussian Federation: -1.11 typical gaps (standard deviations), 28.4% of health spendingRwanda: -0.532 typical gaps (standard deviations), 4.1% of health spendingSaudi Arabia: -0.712 typical gaps (standard deviations), 14.1% of health spendingSudan: -1.43 typical gaps (standard deviations), 57.4% of health spendingSenegal: 0.459 typical gaps (standard deviations), 44.3% of health spendingSingapore: 0.528 typical gaps (standard deviations), 25.4% of health spendingSolomon Islands: 0.45 typical gaps (standard deviations), 3.16% of health spendingSierra Leone: -0.0448 typical gaps (standard deviations), 54.5% of health spendingEl Salvador: -0.354 typical gaps (standard deviations), 32.5% of health spendingSomalia, Fed. Rep.: -1.29 typical gaps (standard deviations), 30.8% of health spendingSerbia: -0.129 typical gaps (standard deviations), 32.1% of health spendingSao Tome and Principe: 0.469 typical gaps (standard deviations), 16.7% of health spendingSuriname: 0.64 typical gaps (standard deviations), 19.7% of health spendingSlovak Republic: 0.851 typical gaps (standard deviations), 20.2% of health spendingSlovenia: 1.1 typical gaps (standard deviations), 11.7% of health spendingSweden: 1.49 typical gaps (standard deviations), 13.4% of health spendingEswatini: -0.976 typical gaps (standard deviations), 11% of health spendingSeychelles: 0.921 typical gaps (standard deviations), 28% of health spendingSyrian Arab Republic: -1.29 typical gaps (standard deviations), 72.4% of health spendingChad: -1.1 typical gaps (standard deviations), 51.7% of health spendingTogo: -0.492 typical gaps (standard deviations), 64.3% of health spendingThailand: -0.321 typical gaps (standard deviations), 9.93% of health spendingTajikistan: -1.22 typical gaps (standard deviations), 62.4% of health spendingTurkmenistan: -1.33 typical gaps (standard deviations), 77.4% of health spendingTimor-Leste: 0.458 typical gaps (standard deviations), 6.99% of health spendingTrinidad and Tobago: 0.718 typical gaps (standard deviations), 45.3% of health spendingTunisia: -0.317 typical gaps (standard deviations), 37.9% of health spendingTurkiye: -0.647 typical gaps (standard deviations), 19% of health spendingTanzania: -0.365 typical gaps (standard deviations), 27.9% of health spendingUganda: -0.676 typical gaps (standard deviations), 32.2% of health spendingUkraine: -0.182 typical gaps (standard deviations), 45.3% of health spendingUruguay: 1.29 typical gaps (standard deviations), 17.1% of health spendingUnited States: 0.906 typical gaps (standard deviations), 10.9% of health spendingUzbekistan: -0.864 typical gaps (standard deviations), 64.1% of health spendingViet Nam: -0.692 typical gaps (standard deviations), 39.2% of health spendingVanuatu: 0.64 typical gaps (standard deviations), 8.38% of health spendingSouth Africa: 0.602 typical gaps (standard deviations), 6.69% of health spendingZambia: 0.0286 typical gaps (standard deviations), 10.3% of health spendingZimbabwe: -0.779 typical gaps (standard deviations), 10.6% of health spendingAFGARMBGDBRBDNKIRLLUXMMRRWASWZTKMZWE

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.5242.8e-13169
By rank (Spearman), not adjusted-0.5121.1e-12169
Standard (Pearson), adjusted for national income-0.3852.6e-7169
By rank (Spearman), adjusted for national income-0.3532.8e-6169

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 169 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: +0.139 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.400 (without SWZ) to -0.361 (without TKM). 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: TKM (+0.024).

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 & Pacific20-0.71
Europe & Central Asia49-0.27
Latin America & Caribbean25-0.17
Middle East, North Africa, Afghanistan & Pakistan21-0.07
Sub-Saharan Africa46-0.33

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 third57-0.52
Middle third56-0.39
Richest third56-0.04

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
Christians101-0.39
Muslims47-0.27

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
France25-0.31
Never a European colony21-0.13
Spain19-0.47
United Kingdom51-0.30

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
Nationalist24-0.50
No strong official ideology115-0.42

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
A few parties banned26-0.09
No parties banned120-0.43

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 = -0.385 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)
% of health spending		Years
Denmark DNK1.5713.9%2025, 2024
Switzerland CHE1.5422%2025, 2023
Norway NOR1.5313.7%2025, 2023
Finland FIN1.5114.1%2025, 2023
Sweden SWE1.4913.4%2025, 2024
Luxembourg LUX1.488.5%2025, 2024
New Zealand NZL1.4512.7%2025, 2024
Ireland IRL1.4310.6%2025, 2024
Australia AUS1.4215.8%2025, 2023
Estonia EST1.421.4%2025, 2024
Canada CAN1.3915.3%2025, 2024
Netherlands NLD1.3811.8%2025, 2024
Iceland ISL1.3714.9%2025, 2024
Germany DEU1.3510.7%2025, 2024
Japan JPN1.3412.2%2025, 2023

fh; un_sdg; vdem; wdi; wgi
World Bank, World Development Indicators

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.

Out-of-pocket health spending

Out-of-pocket expenditure (% of current health expenditure)

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

The share of a country's health spending paid by patients themselves when they get care. Health spending as a share of GDP is already on the site and shows how much is spent. This shows who pays.

How this was computed

Data used: most recent value in 2010-2025; values come from 2011–2025. 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 17,292 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 Out-of-pocket health spending

This page shows that two measures go together. It does not show that Governance score changes Out-of-pocket health spending, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.

More links with Governance score or Out-of-pocket health spending