placestats

Infrastructure score vs. Liberal democracy

Fades after adjusting for income

Across 167 countries, Infrastructure score and Liberal democracy rise and fall together at r = +0.53 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to +0.13, which could easily be chance (q = 0.48, 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 liberal democracy, 0.127 to 0.617 points, infrastructure score is better by 0.682 typical gaps at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.0808 typical gaps.

Link before adjusting (r)+0.525p = 3.1e-13 · 167 countries
After adjusting for national income+0.132p = 0.089 · likely range [-0.02, +0.28]
p, allowing for regions0.233standard error 0.100 · 7 regions
Check for luck (q)0.481across 12,497 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.

Infrastructure score · typical gaps (standard deviations)link with income +0.90 · proxy
Liberal democracy · index (0-1)link with income +0.52 · moderate

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

Every country as a dot

Infrastructure score · typical gaps (standard deviations) →Liberal democracy · index (0-1) →-1.011.720.0150.884Afghanistan: 0.116 typical gaps (standard deviations), 0.018 index (0-1)Angola: -0.152 typical gaps (standard deviations), 0.163 index (0-1)Albania: 1.14 typical gaps (standard deviations), 0.382 index (0-1)United Arab Emirates: 1.61 typical gaps (standard deviations), 0.077 index (0-1)Argentina: 1.25 typical gaps (standard deviations), 0.524 index (0-1)Armenia: 1.09 typical gaps (standard deviations), 0.371 index (0-1)Australia: 1.5 typical gaps (standard deviations), 0.793 index (0-1)Austria: 1.37 typical gaps (standard deviations), 0.757 index (0-1)Azerbaijan: 1.19 typical gaps (standard deviations), 0.053 index (0-1)Burundi: -0.835 typical gaps (standard deviations), 0.06 index (0-1)Belgium: 1.64 typical gaps (standard deviations), 0.794 index (0-1)Benin: 0.00537 typical gaps (standard deviations), 0.323 index (0-1)Burkina Faso: -0.245 typical gaps (standard deviations), 0.103 index (0-1)Bangladesh: 0.649 typical gaps (standard deviations), 0.116 index (0-1)Bulgaria: 1.25 typical gaps (standard deviations), 0.499 index (0-1)Bahrain: 1.17 typical gaps (standard deviations), 0.062 index (0-1)Bosnia and Herzegovina: 1.29 typical gaps (standard deviations), 0.339 index (0-1)Belarus: 1.48 typical gaps (standard deviations), 0.038 index (0-1)Bolivia: 0.886 typical gaps (standard deviations), 0.352 index (0-1)Brazil: 1.18 typical gaps (standard deviations), 0.704 index (0-1)Barbados: 1.31 typical gaps (standard deviations), 0.679 index (0-1)Bhutan: 0.847 typical gaps (standard deviations), 0.457 index (0-1)Botswana: 0.5 typical gaps (standard deviations), 0.52 index (0-1)Central African Republic: -1.01 typical gaps (standard deviations), 0.102 index (0-1)Canada: 1.56 typical gaps (standard deviations), 0.736 index (0-1)Switzerland: 1.7 typical gaps (standard deviations), 0.843 index (0-1)Chile: 1.25 typical gaps (standard deviations), 0.781 index (0-1)China: 1.66 typical gaps (standard deviations), 0.039 index (0-1)Cote d'Ivoire: 0.207 typical gaps (standard deviations), 0.228 index (0-1)Cameroon: 0.557 typical gaps (standard deviations), 0.114 index (0-1)Congo, Dem. Rep.: -0.672 typical gaps (standard deviations), 0.115 index (0-1)Congo, Rep.: 0.312 typical gaps (standard deviations), 0.115 index (0-1)Colombia: 1.01 typical gaps (standard deviations), 0.555 index (0-1)Comoros: 0.259 typical gaps (standard deviations), 0.132 index (0-1)Cabo Verde: 0.806 typical gaps (standard deviations), 0.631 index (0-1)Costa Rica: 1.19 typical gaps (standard deviations), 0.809 index (0-1)Cyprus: 1.47 typical gaps (standard deviations), 0.664 index (0-1)Czechia: 1.48 typical gaps (standard deviations), 0.794 index (0-1)Germany: 1.65 typical gaps (standard deviations), 0.782 index (0-1)Djibouti: 0.0105 typical gaps (standard deviations), 0.118 index (0-1)Denmark: 1.65 typical gaps (standard deviations), 0.884 index (0-1)Dominican Republic: 0.956 typical gaps (standard deviations), 0.505 index (0-1)Algeria: 0.932 typical gaps (standard deviations), 0.126 index (0-1)Ecuador: 0.989 typical gaps (standard deviations), 0.386 index (0-1)Egypt, Arab Rep.: 0.864 typical gaps (standard deviations), 0.115 index (0-1)Spain: 1.55 typical gaps (standard deviations), 0.741 index (0-1)Estonia: 1.45 typical gaps (standard deviations), 0.837 index (0-1)Ethiopia: -0.309 typical gaps (standard deviations), 0.1 index (0-1)Finland: 1.48 typical gaps (standard deviations), 0.808 index (0-1)Fiji: 0.665 typical gaps (standard deviations), 0.398 index (0-1)France: 1.7 typical gaps (standard deviations), 0.8 index (0-1)Gabon: 0.665 typical gaps (standard deviations), 0.178 index (0-1)United Kingdom: 1.6 typical gaps (standard deviations), 0.689 index (0-1)Georgia: 1.29 typical gaps (standard deviations), 0.275 index (0-1)Ghana: 0.59 typical gaps (standard deviations), 0.606 index (0-1)Guinea: 0.156 typical gaps (standard deviations), 0.095 index (0-1)Gambia, The: 0.215 typical gaps (standard deviations), 0.522 index (0-1)Guinea-Bissau: -0.158 typical gaps (standard deviations), 0.095 index (0-1)Equatorial Guinea: -0.269 typical gaps (standard deviations), 0.047 index (0-1)Greece: 1.57 typical gaps (standard deviations), 0.568 index (0-1)Guatemala: 0.576 typical gaps (standard deviations), 0.523 index (0-1)Guyana: 0.809 typical gaps (standard deviations), 0.328 index (0-1)Hong Kong SAR, China: 1.57 typical gaps (standard deviations), 0.142 index (0-1)Honduras: 0.417 typical gaps (standard deviations), 0.38 index (0-1)Croatia: 1.28 typical gaps (standard deviations), 0.593 index (0-1)Haiti: -0.312 typical gaps (standard deviations), 0.098 index (0-1)Hungary: 1.5 typical gaps (standard deviations), 0.315 index (0-1)Indonesia: 0.742 typical gaps (standard deviations), 0.296 index (0-1)India: 0.527 typical gaps (standard deviations), 0.26 index (0-1)Ireland: 1.43 typical gaps (standard deviations), 0.822 index (0-1)Iran, Islamic Rep.: 0.97 typical gaps (standard deviations), 0.103 index (0-1)Iraq: 1.04 typical gaps (standard deviations), 0.22 index (0-1)Iceland: 1.53 typical gaps (standard deviations), 0.72 index (0-1)Israel: 1.31 typical gaps (standard deviations), 0.588 index (0-1)Italy: 1.36 typical gaps (standard deviations), 0.642 index (0-1)Jamaica: 1.06 typical gaps (standard deviations), 0.679 index (0-1)Jordan: 0.776 typical gaps (standard deviations), 0.274 index (0-1)Japan: 1.45 typical gaps (standard deviations), 0.734 index (0-1)Kazakhstan: 1.09 typical gaps (standard deviations), 0.131 index (0-1)Kenya: 0.22 typical gaps (standard deviations), 0.446 index (0-1)Kyrgyz Republic: 0.943 typical gaps (standard deviations), 0.178 index (0-1)Cambodia: 0.689 typical gaps (standard deviations), 0.051 index (0-1)Korea, Rep.: 1.72 typical gaps (standard deviations), 0.739 index (0-1)Kuwait: 0.878 typical gaps (standard deviations), 0.127 index (0-1)Lao PDR: 0.399 typical gaps (standard deviations), 0.11 index (0-1)Lebanon: 0.731 typical gaps (standard deviations), 0.267 index (0-1)Liberia: -0.767 typical gaps (standard deviations), 0.417 index (0-1)Libya: 0.512 typical gaps (standard deviations), 0.098 index (0-1)Sri Lanka: 0.669 typical gaps (standard deviations), 0.613 index (0-1)Lesotho: -0.0187 typical gaps (standard deviations), 0.512 index (0-1)Lithuania: 1.29 typical gaps (standard deviations), 0.712 index (0-1)Luxembourg: 1.59 typical gaps (standard deviations), 0.777 index (0-1)Latvia: 1.28 typical gaps (standard deviations), 0.751 index (0-1)Morocco: 0.928 typical gaps (standard deviations), 0.251 index (0-1)Moldova: 1.23 typical gaps (standard deviations), 0.449 index (0-1)Madagascar: -0.434 typical gaps (standard deviations), 0.187 index (0-1)Maldives: 1.11 typical gaps (standard deviations), 0.416 index (0-1)Mexico: 1.13 typical gaps (standard deviations), 0.221 index (0-1)North Macedonia: 1.36 typical gaps (standard deviations), 0.374 index (0-1)Mali: -0.495 typical gaps (standard deviations), 0.15 index (0-1)Malta: 1.63 typical gaps (standard deviations), 0.621 index (0-1)Myanmar: 0.298 typical gaps (standard deviations), 0.015 index (0-1)Montenegro: 1.37 typical gaps (standard deviations), 0.5 index (0-1)Mongolia: 1.03 typical gaps (standard deviations), 0.424 index (0-1)Mozambique: -0.592 typical gaps (standard deviations), 0.175 index (0-1)Mauritania: 0.0018 typical gaps (standard deviations), 0.127 index (0-1)Mauritius: 1.17 typical gaps (standard deviations), 0.639 index (0-1)Malawi: -0.672 typical gaps (standard deviations), 0.462 index (0-1)Malaysia: 1.09 typical gaps (standard deviations), 0.355 index (0-1)Namibia: 0.203 typical gaps (standard deviations), 0.519 index (0-1)Niger: -0.7 typical gaps (standard deviations), 0.177 index (0-1)Nigeria: -0.0861 typical gaps (standard deviations), 0.311 index (0-1)Nicaragua: 0.574 typical gaps (standard deviations), 0.019 index (0-1)Netherlands: 1.63 typical gaps (standard deviations), 0.774 index (0-1)Norway: 1.68 typical gaps (standard deviations), 0.847 index (0-1)Nepal: 0.616 typical gaps (standard deviations), 0.505 index (0-1)New Zealand: 1.51 typical gaps (standard deviations), 0.787 index (0-1)Oman: 1.03 typical gaps (standard deviations), 0.14 index (0-1)Pakistan: 0.386 typical gaps (standard deviations), 0.176 index (0-1)Panama: 0.927 typical gaps (standard deviations), 0.575 index (0-1)Peru: 0.907 typical gaps (standard deviations), 0.506 index (0-1)Philippines: 0.696 typical gaps (standard deviations), 0.291 index (0-1)Papua New Guinea: -0.611 typical gaps (standard deviations), 0.384 index (0-1)Poland: 1.24 typical gaps (standard deviations), 0.645 index (0-1)Portugal: 1.6 typical gaps (standard deviations), 0.717 index (0-1)Paraguay: 0.928 typical gaps (standard deviations), 0.376 index (0-1)Qatar: 1.06 typical gaps (standard deviations), 0.091 index (0-1)Romania: 1.45 typical gaps (standard deviations), 0.464 index (0-1)Russian Federation: 1.32 typical gaps (standard deviations), 0.056 index (0-1)Rwanda: 0.0662 typical gaps (standard deviations), 0.09 index (0-1)Saudi Arabia: 1.67 typical gaps (standard deviations), 0.047 index (0-1)Sudan: -0.572 typical gaps (standard deviations), 0.034 index (0-1)Senegal: 0.482 typical gaps (standard deviations), 0.484 index (0-1)Singapore: 1.33 typical gaps (standard deviations), 0.36 index (0-1)Solomon Islands: 0.0941 typical gaps (standard deviations), 0.539 index (0-1)Sierra Leone: -0.336 typical gaps (standard deviations), 0.348 index (0-1)El Salvador: 0.822 typical gaps (standard deviations), 0.09 index (0-1)Somalia, Fed. Rep.: -0.395 typical gaps (standard deviations), 0.128 index (0-1)Serbia: 1.38 typical gaps (standard deviations), 0.208 index (0-1)Sao Tome and Principe: 0.187 typical gaps (standard deviations), 0.519 index (0-1)Suriname: 0.901 typical gaps (standard deviations), 0.626 index (0-1)Slovak Republic: 1.4 typical gaps (standard deviations), 0.573 index (0-1)Slovenia: 1.42 typical gaps (standard deviations), 0.589 index (0-1)Sweden: 1.57 typical gaps (standard deviations), 0.853 index (0-1)Eswatini: 0.534 typical gaps (standard deviations), 0.097 index (0-1)Seychelles: 1.35 typical gaps (standard deviations), 0.68 index (0-1)Syrian Arab Republic: 0.27 typical gaps (standard deviations), 0.054 index (0-1)Chad: -0.72 typical gaps (standard deviations), 0.062 index (0-1)Togo: -0.0274 typical gaps (standard deviations), 0.157 index (0-1)Thailand: 1.06 typical gaps (standard deviations), 0.314 index (0-1)Tajikistan: 0.389 typical gaps (standard deviations), 0.043 index (0-1)Turkmenistan: 0.294 typical gaps (standard deviations), 0.034 index (0-1)Timor-Leste: 0.389 typical gaps (standard deviations), 0.549 index (0-1)Trinidad and Tobago: 1.22 typical gaps (standard deviations), 0.668 index (0-1)Tunisia: 0.956 typical gaps (standard deviations), 0.265 index (0-1)Turkiye: 1.19 typical gaps (standard deviations), 0.11 index (0-1)Tanzania: -0.0741 typical gaps (standard deviations), 0.297 index (0-1)Uganda: -0.319 typical gaps (standard deviations), 0.165 index (0-1)Ukraine: 0.97 typical gaps (standard deviations), 0.24 index (0-1)Uruguay: 1.41 typical gaps (standard deviations), 0.79 index (0-1)United States: 1.53 typical gaps (standard deviations), 0.571 index (0-1)Uzbekistan: 1.42 typical gaps (standard deviations), 0.079 index (0-1)Viet Nam: 1.17 typical gaps (standard deviations), 0.102 index (0-1)Vanuatu: -0.0444 typical gaps (standard deviations), 0.623 index (0-1)South Africa: 0.709 typical gaps (standard deviations), 0.633 index (0-1)Zambia: -0.161 typical gaps (standard deviations), 0.375 index (0-1)Zimbabwe: 0.0863 typical gaps (standard deviations), 0.147 index (0-1)AREBDICAFCHECHNDNKLBRMWINORSAUTCDVUT

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.5253.1e-13167
By rank (Spearman), not adjusted+0.5292.1e-13167
Standard (Pearson), adjusted for national income+0.1320.089167
By rank (Spearman), adjusted for national income+0.1630.035167

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 167 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: +0.393 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.095 (without QAT) to +0.161 (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: QAT (-0.037).

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 & Pacific21-0.09
Europe & Central Asia48+0.26
Latin America & Caribbean23+0.50
Middle East, North Africa, Afghanistan & Pakistan21+0.36
Sub-Saharan Africa46+0.37

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 third56+0.09
Middle third55+0.01
Richest third56+0.50

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
Christians99+0.13
Muslims47+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
France25+0.19
Never a European colony21-0.00
Spain19+0.39
United Kingdom49+0.38

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 = +0.132 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)

index (0-1)
Years
Korea, Rep. KOR1.720.7392024, 2025
Switzerland CHE1.70.8432024, 2025
France FRA1.70.82024, 2025
Norway NOR1.680.8472024, 2025
Saudi Arabia SAU1.670.0472024, 2025
China CHN1.660.0392024, 2025
Denmark DNK1.650.8842024, 2025
Germany DEU1.650.7822024, 2025
Belgium BEL1.640.7942024, 2025
Malta MLT1.630.6212024, 2025
Netherlands NLD1.630.7742024, 2025
United Arab Emirates ARE1.610.0772024, 2025
Portugal PRT1.60.7172024, 2025
United Kingdom GBR1.60.6892024, 2025
Luxembourg LUX1.590.7772024, 2025

wdi
Coppedge, M. et al., V-Dem Dataset, Varieties of Democracy (V-Dem) Project

Sources

Infrastructure score

Infrastructure score

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

The average of 5 measures from 1 publisher. 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: Electricity access, Slum share of urban population, Mobile subscriptions, Fixed broadband, Internet users.

Liberal democracy

Liberal democracy index

V-Dem Institute, University of Gothenburg · via Our World in Data · CC BY 4.0 · updated annual

Electoral democracy plus limits on the head of government, independent courts and protected personal freedoms. It contains the electoral democracy index as a part, so the two are built from the same numbers and bound to match.

How this was computed

Data used: most recent value in 2010-2025; values come from 2022–2025. 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 12,497 pairs at once, using the Benjamini–Hochberg method. Underlying data last updated DYB 2024. How the country data works · explore Infrastructure score and Liberal democracy

This page shows that two measures go together. It does not show that Infrastructure score changes Liberal democracy, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.

More links with Infrastructure score or Liberal democracy