placestats

Free and fair elections vs. Infrastructure score

Fades after adjusting for income

Across 167 countries, Free and fair elections and Infrastructure score rise and fall together at r = +0.60 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to +0.22, which could easily be chance (q = 0.18, 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 free and fair elections, 0.231 to 0.873 points, infrastructure score is better by 0.788 typical gaps at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.142 typical gaps.

Link before adjusting (r)+0.598p = 1.4e-17 · 167 countries
After adjusting for national income+0.221p = 0.004 · likely range [+0.07, +0.36]
p, allowing for regions0.050standard error 0.090 · 7 regions
Check for luck (q)0.181across 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.

Free and fair elections · index (0-1)link with income +0.61 · high
Infrastructure score · typical gaps (standard deviations)link with income +0.90 · proxy

Both of these rise and fall closely with national income, so a strong link between them before adjusting was close to certain. Read the adjusted figure, not the first one.

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

Every country as a dot

Free and fair elections · index (0-1) →Infrastructure score · typical gaps (standard deviations) →00.968-1.011.72Afghanistan: 0 index (0-1), 0.116 typical gaps (standard deviations)Angola: 0.293 index (0-1), -0.152 typical gaps (standard deviations)Albania: 0.467 index (0-1), 1.14 typical gaps (standard deviations)United Arab Emirates: 0.543 index (0-1), 1.61 typical gaps (standard deviations)Argentina: 0.878 index (0-1), 1.25 typical gaps (standard deviations)Armenia: 0.673 index (0-1), 1.09 typical gaps (standard deviations)Australia: 0.962 index (0-1), 1.5 typical gaps (standard deviations)Austria: 0.938 index (0-1), 1.37 typical gaps (standard deviations)Azerbaijan: 0.111 index (0-1), 1.19 typical gaps (standard deviations)Burundi: 0.107 index (0-1), -0.835 typical gaps (standard deviations)Belgium: 0.968 index (0-1), 1.64 typical gaps (standard deviations)Benin: 0.638 index (0-1), 0.00537 typical gaps (standard deviations)Burkina Faso: 0 index (0-1), -0.245 typical gaps (standard deviations)Bangladesh: 0 index (0-1), 0.649 typical gaps (standard deviations)Bulgaria: 0.64 index (0-1), 1.25 typical gaps (standard deviations)Bahrain: 0.274 index (0-1), 1.17 typical gaps (standard deviations)Bosnia and Herzegovina: 0.511 index (0-1), 1.29 typical gaps (standard deviations)Belarus: 0.194 index (0-1), 1.48 typical gaps (standard deviations)Bolivia: 0.765 index (0-1), 0.886 typical gaps (standard deviations)Brazil: 0.838 index (0-1), 1.18 typical gaps (standard deviations)Barbados: 0.875 index (0-1), 1.31 typical gaps (standard deviations)Bhutan: 0.865 index (0-1), 0.847 typical gaps (standard deviations)Botswana: 0.803 index (0-1), 0.5 typical gaps (standard deviations)Central African Republic: 0.123 index (0-1), -1.01 typical gaps (standard deviations)Canada: 0.944 index (0-1), 1.56 typical gaps (standard deviations)Switzerland: 0.942 index (0-1), 1.7 typical gaps (standard deviations)Chile: 0.956 index (0-1), 1.25 typical gaps (standard deviations)China: 0 index (0-1), 1.66 typical gaps (standard deviations)Cote d'Ivoire: 0.333 index (0-1), 0.207 typical gaps (standard deviations)Cameroon: 0.12 index (0-1), 0.557 typical gaps (standard deviations)Congo, Dem. Rep.: 0.18 index (0-1), -0.672 typical gaps (standard deviations)Congo, Rep.: 0.076 index (0-1), 0.312 typical gaps (standard deviations)Colombia: 0.756 index (0-1), 1.01 typical gaps (standard deviations)Comoros: 0.183 index (0-1), 0.259 typical gaps (standard deviations)Cabo Verde: 0.836 index (0-1), 0.806 typical gaps (standard deviations)Costa Rica: 0.944 index (0-1), 1.19 typical gaps (standard deviations)Cyprus: 0.909 index (0-1), 1.47 typical gaps (standard deviations)Czechia: 0.94 index (0-1), 1.48 typical gaps (standard deviations)Germany: 0.957 index (0-1), 1.65 typical gaps (standard deviations)Djibouti: 0.167 index (0-1), 0.0105 typical gaps (standard deviations)Denmark: 0.961 index (0-1), 1.65 typical gaps (standard deviations)Dominican Republic: 0.768 index (0-1), 0.956 typical gaps (standard deviations)Algeria: 0.307 index (0-1), 0.932 typical gaps (standard deviations)Ecuador: 0.827 index (0-1), 0.989 typical gaps (standard deviations)Egypt, Arab Rep.: 0.137 index (0-1), 0.864 typical gaps (standard deviations)Spain: 0.956 index (0-1), 1.55 typical gaps (standard deviations)Estonia: 0.952 index (0-1), 1.45 typical gaps (standard deviations)Ethiopia: 0.324 index (0-1), -0.309 typical gaps (standard deviations)Finland: 0.961 index (0-1), 1.48 typical gaps (standard deviations)Fiji: 0.54 index (0-1), 0.665 typical gaps (standard deviations)France: 0.941 index (0-1), 1.7 typical gaps (standard deviations)Gabon: 0.186 index (0-1), 0.665 typical gaps (standard deviations)United Kingdom: 0.924 index (0-1), 1.6 typical gaps (standard deviations)Georgia: 0.32 index (0-1), 1.29 typical gaps (standard deviations)Ghana: 0.709 index (0-1), 0.59 typical gaps (standard deviations)Guinea: 0.002 index (0-1), 0.156 typical gaps (standard deviations)Gambia, The: 0.777 index (0-1), 0.215 typical gaps (standard deviations)Guinea-Bissau: 0 index (0-1), -0.158 typical gaps (standard deviations)Equatorial Guinea: 0.078 index (0-1), -0.269 typical gaps (standard deviations)Greece: 0.944 index (0-1), 1.57 typical gaps (standard deviations)Guatemala: 0.666 index (0-1), 0.576 typical gaps (standard deviations)Guyana: 0.489 index (0-1), 0.809 typical gaps (standard deviations)Hong Kong SAR, China: 0.286 index (0-1), 1.57 typical gaps (standard deviations)Honduras: 0.351 index (0-1), 0.417 typical gaps (standard deviations)Croatia: 0.875 index (0-1), 1.28 typical gaps (standard deviations)Haiti: 0 index (0-1), -0.312 typical gaps (standard deviations)Hungary: 0.597 index (0-1), 1.5 typical gaps (standard deviations)Indonesia: 0.518 index (0-1), 0.742 typical gaps (standard deviations)India: 0.495 index (0-1), 0.527 typical gaps (standard deviations)Ireland: 0.945 index (0-1), 1.43 typical gaps (standard deviations)Iran, Islamic Rep.: 0.235 index (0-1), 0.97 typical gaps (standard deviations)Iraq: 0.372 index (0-1), 1.04 typical gaps (standard deviations)Iceland: 0.929 index (0-1), 1.53 typical gaps (standard deviations)Israel: 0.873 index (0-1), 1.31 typical gaps (standard deviations)Italy: 0.945 index (0-1), 1.36 typical gaps (standard deviations)Jamaica: 0.884 index (0-1), 1.06 typical gaps (standard deviations)Jordan: 0.592 index (0-1), 0.776 typical gaps (standard deviations)Japan: 0.937 index (0-1), 1.45 typical gaps (standard deviations)Kazakhstan: 0.339 index (0-1), 1.09 typical gaps (standard deviations)Kenya: 0.493 index (0-1), 0.22 typical gaps (standard deviations)Kyrgyz Republic: 0.426 index (0-1), 0.943 typical gaps (standard deviations)Cambodia: 0.092 index (0-1), 0.689 typical gaps (standard deviations)Korea, Rep.: 0.935 index (0-1), 1.72 typical gaps (standard deviations)Kuwait: 0 index (0-1), 0.878 typical gaps (standard deviations)Lao PDR: 0.236 index (0-1), 0.399 typical gaps (standard deviations)Lebanon: 0.307 index (0-1), 0.731 typical gaps (standard deviations)Liberia: 0.592 index (0-1), -0.767 typical gaps (standard deviations)Libya: 0 index (0-1), 0.512 typical gaps (standard deviations)Sri Lanka: 0.914 index (0-1), 0.669 typical gaps (standard deviations)Lesotho: 0.785 index (0-1), -0.0187 typical gaps (standard deviations)Lithuania: 0.882 index (0-1), 1.29 typical gaps (standard deviations)Luxembourg: 0.944 index (0-1), 1.59 typical gaps (standard deviations)Latvia: 0.92 index (0-1), 1.28 typical gaps (standard deviations)Morocco: 0.455 index (0-1), 0.928 typical gaps (standard deviations)Moldova: 0.662 index (0-1), 1.23 typical gaps (standard deviations)Madagascar: 0.183 index (0-1), -0.434 typical gaps (standard deviations)Maldives: 0.643 index (0-1), 1.11 typical gaps (standard deviations)Mexico: 0.545 index (0-1), 1.13 typical gaps (standard deviations)North Macedonia: 0.701 index (0-1), 1.36 typical gaps (standard deviations)Mali: 0 index (0-1), -0.495 typical gaps (standard deviations)Malta: 0.903 index (0-1), 1.63 typical gaps (standard deviations)Myanmar: 0 index (0-1), 0.298 typical gaps (standard deviations)Montenegro: 0.608 index (0-1), 1.37 typical gaps (standard deviations)Mongolia: 0.586 index (0-1), 1.03 typical gaps (standard deviations)Mozambique: 0.089 index (0-1), -0.592 typical gaps (standard deviations)Mauritania: 0.288 index (0-1), 0.0018 typical gaps (standard deviations)Mauritius: 0.865 index (0-1), 1.17 typical gaps (standard deviations)Malawi: 0.596 index (0-1), -0.672 typical gaps (standard deviations)Malaysia: 0.598 index (0-1), 1.09 typical gaps (standard deviations)Namibia: 0.604 index (0-1), 0.203 typical gaps (standard deviations)Niger: 0 index (0-1), -0.7 typical gaps (standard deviations)Nigeria: 0.355 index (0-1), -0.0861 typical gaps (standard deviations)Nicaragua: 0.137 index (0-1), 0.574 typical gaps (standard deviations)Netherlands: 0.954 index (0-1), 1.63 typical gaps (standard deviations)Norway: 0.966 index (0-1), 1.68 typical gaps (standard deviations)Nepal: 0.693 index (0-1), 0.616 typical gaps (standard deviations)New Zealand: 0.954 index (0-1), 1.51 typical gaps (standard deviations)Oman: 0.689 index (0-1), 1.03 typical gaps (standard deviations)Pakistan: 0.174 index (0-1), 0.386 typical gaps (standard deviations)Panama: 0.84 index (0-1), 0.927 typical gaps (standard deviations)Peru: 0.861 index (0-1), 0.907 typical gaps (standard deviations)Philippines: 0.271 index (0-1), 0.696 typical gaps (standard deviations)Papua New Guinea: 0.27 index (0-1), -0.611 typical gaps (standard deviations)Poland: 0.825 index (0-1), 1.24 typical gaps (standard deviations)Portugal: 0.94 index (0-1), 1.6 typical gaps (standard deviations)Paraguay: 0.633 index (0-1), 0.928 typical gaps (standard deviations)Qatar: 0 index (0-1), 1.06 typical gaps (standard deviations)Romania: 0.658 index (0-1), 1.45 typical gaps (standard deviations)Russian Federation: 0.135 index (0-1), 1.32 typical gaps (standard deviations)Rwanda: 0.227 index (0-1), 0.0662 typical gaps (standard deviations)Saudi Arabia: 0 index (0-1), 1.67 typical gaps (standard deviations)Sudan: 0 index (0-1), -0.572 typical gaps (standard deviations)Senegal: 0.701 index (0-1), 0.482 typical gaps (standard deviations)Singapore: 0.782 index (0-1), 1.33 typical gaps (standard deviations)Solomon Islands: 0.748 index (0-1), 0.0941 typical gaps (standard deviations)Sierra Leone: 0.319 index (0-1), -0.336 typical gaps (standard deviations)El Salvador: 0.307 index (0-1), 0.822 typical gaps (standard deviations)Somalia, Fed. Rep.: 0 index (0-1), -0.395 typical gaps (standard deviations)Serbia: 0.212 index (0-1), 1.38 typical gaps (standard deviations)Sao Tome and Principe: 0.753 index (0-1), 0.187 typical gaps (standard deviations)Suriname: 0.864 index (0-1), 0.901 typical gaps (standard deviations)Slovak Republic: 0.938 index (0-1), 1.4 typical gaps (standard deviations)Slovenia: 0.916 index (0-1), 1.42 typical gaps (standard deviations)Sweden: 0.945 index (0-1), 1.57 typical gaps (standard deviations)Eswatini: 0.376 index (0-1), 0.534 typical gaps (standard deviations)Seychelles: 0.884 index (0-1), 1.35 typical gaps (standard deviations)Syrian Arab Republic: 0 index (0-1), 0.27 typical gaps (standard deviations)Chad: 0.079 index (0-1), -0.72 typical gaps (standard deviations)Togo: 0.309 index (0-1), -0.0274 typical gaps (standard deviations)Thailand: 0.457 index (0-1), 1.06 typical gaps (standard deviations)Tajikistan: 0.094 index (0-1), 0.389 typical gaps (standard deviations)Turkmenistan: 0.071 index (0-1), 0.294 typical gaps (standard deviations)Timor-Leste: 0.857 index (0-1), 0.389 typical gaps (standard deviations)Trinidad and Tobago: 0.872 index (0-1), 1.22 typical gaps (standard deviations)Tunisia: 0.445 index (0-1), 0.956 typical gaps (standard deviations)Turkiye: 0.417 index (0-1), 1.19 typical gaps (standard deviations)Tanzania: 0.364 index (0-1), -0.0741 typical gaps (standard deviations)Uganda: 0.129 index (0-1), -0.319 typical gaps (standard deviations)Ukraine: 0.604 index (0-1), 0.97 typical gaps (standard deviations)Uruguay: 0.947 index (0-1), 1.41 typical gaps (standard deviations)United States: 0.902 index (0-1), 1.53 typical gaps (standard deviations)Uzbekistan: 0.304 index (0-1), 1.42 typical gaps (standard deviations)Viet Nam: 0.527 index (0-1), 1.17 typical gaps (standard deviations)Vanuatu: 0.853 index (0-1), -0.0444 typical gaps (standard deviations)South Africa: 0.849 index (0-1), 0.709 typical gaps (standard deviations)Zambia: 0.461 index (0-1), -0.161 typical gaps (standard deviations)Zimbabwe: 0.171 index (0-1), 0.0863 typical gaps (standard deviations)BDIBLRCAFCHECHNKORLBRMWINERNORSAUVUT

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.5981.4e-17167
By rank (Spearman), not adjusted+0.6401.3e-20167
Standard (Pearson), adjusted for national income+0.2210.004167
By rank (Spearman), adjusted for national income+0.2530.001167

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: +0.377 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.176 (without QAT) to +0.259 (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 (-0.045).

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 & Pacific21-0.06
Europe & Central Asia48+0.31
Latin America & Caribbean23+0.70
Middle East, North Africa, Afghanistan & Pakistan21+0.50
Sub-Saharan Africa46+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 third56+0.18
Middle third55+0.11
Richest third56+0.49

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+0.25
Muslims47+0.38

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+0.27
Never a European colony21-0.11
Spain19+0.62
United Kingdom49+0.46

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 = +0.221 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


index (0-1)

typical gaps (standard deviations)
Years
Belgium BEL0.9681.642025, 2024
Norway NOR0.9661.682025, 2024
Australia AUS0.9621.52025, 2024
Finland FIN0.9611.482025, 2024
Denmark DNK0.9611.652025, 2024
Germany DEU0.9571.652025, 2024
Spain ESP0.9561.552025, 2024
Chile CHL0.9561.252025, 2024
New Zealand NZL0.9541.512025, 2024
Netherlands NLD0.9541.632025, 2024
Estonia EST0.9521.452025, 2024
Uruguay URY0.9471.412025, 2024
Sweden SWE0.9451.572025, 2024
Italy ITA0.9451.362025, 2024
Ireland IRL0.9451.432025, 2024

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

Sources

Free and fair elections

Free and fair elections index

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

Whether elections are run without voter-registration fraud, widespread irregularities, government threats against the opposition, vote buying or election violence. This asks a narrower question than whether a country is a democracy, and one that is easier to answer. A state can run clean elections while barring the opposition from standing. It can also run dirty elections and still change government. It is the clean-elections part of the electoral democracy index. So its pair with that index, and with liberal and participatory democracy, is built from the same numbers and flagged as such.

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.

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 Free and fair elections and Infrastructure score

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

More links with Free and fair elections or Infrastructure score