placestats

Infrastructure score vs. Rule of law

Fades after adjusting for income

Across 194 countries, Infrastructure score and Rule of law 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 +0.04, which could easily be chance (q = 0.75, 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 rule of law, -0.856 to 0.677 points, infrastructure score is better by 0.687 typical gaps at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.0251 typical gaps.

Link before adjusting (r)+0.656p = 2.9e-25 · 194 countries
After adjusting for national income+0.040p = 0.581 · likely range [-0.10, +0.18]
p, allowing for regions0.550standard error 0.063 · 7 regions
Check for luck (q)0.748across 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
Rule of law · index (approx. -2.5 to 2.5)link with income +0.72 · high

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

Infrastructure score · typical gaps (standard deviations) →Rule of law · index (approx. -2.5 to 2.5) →-1.011.78-2.212.02Aruba: 0.917 typical gaps (standard deviations), 1.22 index (approx. -2.5 to 2.5)Afghanistan: 0.116 typical gaps (standard deviations), -1.94 index (approx. -2.5 to 2.5)Angola: -0.152 typical gaps (standard deviations), -1.17 index (approx. -2.5 to 2.5)Albania: 1.14 typical gaps (standard deviations), -0.119 index (approx. -2.5 to 2.5)Andorra: 1.78 typical gaps (standard deviations), 1.41 index (approx. -2.5 to 2.5)United Arab Emirates: 1.61 typical gaps (standard deviations), 0.497 index (approx. -2.5 to 2.5)Argentina: 1.25 typical gaps (standard deviations), -0.251 index (approx. -2.5 to 2.5)Armenia: 1.09 typical gaps (standard deviations), -0.142 index (approx. -2.5 to 2.5)Antigua and Barbuda: 0.859 typical gaps (standard deviations), 0.602 index (approx. -2.5 to 2.5)Australia: 1.5 typical gaps (standard deviations), 1.47 index (approx. -2.5 to 2.5)Austria: 1.37 typical gaps (standard deviations), 1.68 index (approx. -2.5 to 2.5)Azerbaijan: 1.19 typical gaps (standard deviations), -0.485 index (approx. -2.5 to 2.5)Burundi: -0.835 typical gaps (standard deviations), -1.3 index (approx. -2.5 to 2.5)Belgium: 1.64 typical gaps (standard deviations), 1.28 index (approx. -2.5 to 2.5)Benin: 0.00537 typical gaps (standard deviations), -0.412 index (approx. -2.5 to 2.5)Burkina Faso: -0.245 typical gaps (standard deviations), -0.884 index (approx. -2.5 to 2.5)Bangladesh: 0.649 typical gaps (standard deviations), -0.96 index (approx. -2.5 to 2.5)Bulgaria: 1.25 typical gaps (standard deviations), -0.0333 index (approx. -2.5 to 2.5)Bahrain: 1.17 typical gaps (standard deviations), 0.168 index (approx. -2.5 to 2.5)Bahamas, The: 1.25 typical gaps (standard deviations), 0.251 index (approx. -2.5 to 2.5)Bosnia and Herzegovina: 1.29 typical gaps (standard deviations), -0.319 index (approx. -2.5 to 2.5)Belarus: 1.48 typical gaps (standard deviations), -1.23 index (approx. -2.5 to 2.5)Belize: 0.573 typical gaps (standard deviations), -0.397 index (approx. -2.5 to 2.5)Bermuda: 1.68 typical gaps (standard deviations), 0.8 index (approx. -2.5 to 2.5)Bolivia: 0.886 typical gaps (standard deviations), -1.27 index (approx. -2.5 to 2.5)Brazil: 1.18 typical gaps (standard deviations), -0.446 index (approx. -2.5 to 2.5)Barbados: 1.31 typical gaps (standard deviations), 0.728 index (approx. -2.5 to 2.5)Brunei Darussalam: 1.22 typical gaps (standard deviations), 0.588 index (approx. -2.5 to 2.5)Bhutan: 0.847 typical gaps (standard deviations), 0.79 index (approx. -2.5 to 2.5)Botswana: 0.5 typical gaps (standard deviations), 0.312 index (approx. -2.5 to 2.5)Central African Republic: -1.01 typical gaps (standard deviations), -1.71 index (approx. -2.5 to 2.5)Canada: 1.56 typical gaps (standard deviations), 1.46 index (approx. -2.5 to 2.5)Switzerland: 1.7 typical gaps (standard deviations), 1.76 index (approx. -2.5 to 2.5)Chile: 1.25 typical gaps (standard deviations), 0.691 index (approx. -2.5 to 2.5)China: 1.66 typical gaps (standard deviations), -0.579 index (approx. -2.5 to 2.5)Cote d'Ivoire: 0.207 typical gaps (standard deviations), -0.578 index (approx. -2.5 to 2.5)Cameroon: 0.557 typical gaps (standard deviations), -1.25 index (approx. -2.5 to 2.5)Congo, Dem. Rep.: -0.672 typical gaps (standard deviations), -1.63 index (approx. -2.5 to 2.5)Congo, Rep.: 0.312 typical gaps (standard deviations), -1.18 index (approx. -2.5 to 2.5)Colombia: 1.01 typical gaps (standard deviations), -0.56 index (approx. -2.5 to 2.5)Comoros: 0.259 typical gaps (standard deviations), -1.13 index (approx. -2.5 to 2.5)Cabo Verde: 0.806 typical gaps (standard deviations), 0.424 index (approx. -2.5 to 2.5)Costa Rica: 1.19 typical gaps (standard deviations), 0.617 index (approx. -2.5 to 2.5)Cayman Islands: 1.58 typical gaps (standard deviations), 0.83 index (approx. -2.5 to 2.5)Cyprus: 1.47 typical gaps (standard deviations), 0.689 index (approx. -2.5 to 2.5)Czechia: 1.48 typical gaps (standard deviations), 1.19 index (approx. -2.5 to 2.5)Germany: 1.65 typical gaps (standard deviations), 1.63 index (approx. -2.5 to 2.5)Djibouti: 0.0105 typical gaps (standard deviations), -1.01 index (approx. -2.5 to 2.5)Dominica: 1.01 typical gaps (standard deviations), 0.397 index (approx. -2.5 to 2.5)Denmark: 1.65 typical gaps (standard deviations), 2 index (approx. -2.5 to 2.5)Dominican Republic: 0.956 typical gaps (standard deviations), -0.182 index (approx. -2.5 to 2.5)Algeria: 0.932 typical gaps (standard deviations), -0.697 index (approx. -2.5 to 2.5)Ecuador: 0.989 typical gaps (standard deviations), -0.965 index (approx. -2.5 to 2.5)Egypt, Arab Rep.: 0.864 typical gaps (standard deviations), -0.752 index (approx. -2.5 to 2.5)Spain: 1.55 typical gaps (standard deviations), 0.932 index (approx. -2.5 to 2.5)Estonia: 1.45 typical gaps (standard deviations), 1.49 index (approx. -2.5 to 2.5)Ethiopia: -0.309 typical gaps (standard deviations), -1.05 index (approx. -2.5 to 2.5)Finland: 1.48 typical gaps (standard deviations), 2.02 index (approx. -2.5 to 2.5)Fiji: 0.665 typical gaps (standard deviations), 0.306 index (approx. -2.5 to 2.5)France: 1.7 typical gaps (standard deviations), 0.979 index (approx. -2.5 to 2.5)Micronesia, Fed. Sts.: -0.101 typical gaps (standard deviations), 0.977 index (approx. -2.5 to 2.5)Gabon: 0.665 typical gaps (standard deviations), -1.16 index (approx. -2.5 to 2.5)United Kingdom: 1.6 typical gaps (standard deviations), 1.27 index (approx. -2.5 to 2.5)Georgia: 1.29 typical gaps (standard deviations), 0.149 index (approx. -2.5 to 2.5)Ghana: 0.59 typical gaps (standard deviations), 0.054 index (approx. -2.5 to 2.5)Guinea: 0.156 typical gaps (standard deviations), -1.15 index (approx. -2.5 to 2.5)Gambia, The: 0.215 typical gaps (standard deviations), -0.394 index (approx. -2.5 to 2.5)Guinea-Bissau: -0.158 typical gaps (standard deviations), -1.23 index (approx. -2.5 to 2.5)Equatorial Guinea: -0.269 typical gaps (standard deviations), -1.54 index (approx. -2.5 to 2.5)Greece: 1.57 typical gaps (standard deviations), 0.298 index (approx. -2.5 to 2.5)Grenada: 1.09 typical gaps (standard deviations), 0.541 index (approx. -2.5 to 2.5)Greenland: 1.24 typical gaps (standard deviations), 1.57 index (approx. -2.5 to 2.5)Guatemala: 0.576 typical gaps (standard deviations), -0.962 index (approx. -2.5 to 2.5)Guyana: 0.809 typical gaps (standard deviations), -0.334 index (approx. -2.5 to 2.5)Hong Kong SAR, China: 1.57 typical gaps (standard deviations), 0.921 index (approx. -2.5 to 2.5)Honduras: 0.417 typical gaps (standard deviations), -1.18 index (approx. -2.5 to 2.5)Croatia: 1.28 typical gaps (standard deviations), 0.377 index (approx. -2.5 to 2.5)Haiti: -0.312 typical gaps (standard deviations), -1.6 index (approx. -2.5 to 2.5)Hungary: 1.5 typical gaps (standard deviations), 0.192 index (approx. -2.5 to 2.5)Indonesia: 0.742 typical gaps (standard deviations), -0.207 index (approx. -2.5 to 2.5)India: 0.527 typical gaps (standard deviations), -0.0392 index (approx. -2.5 to 2.5)Ireland: 1.43 typical gaps (standard deviations), 1.59 index (approx. -2.5 to 2.5)Iran, Islamic Rep.: 0.97 typical gaps (standard deviations), -1.23 index (approx. -2.5 to 2.5)Iraq: 1.04 typical gaps (standard deviations), -1.36 index (approx. -2.5 to 2.5)Iceland: 1.53 typical gaps (standard deviations), 1.63 index (approx. -2.5 to 2.5)Israel: 1.31 typical gaps (standard deviations), 0.6 index (approx. -2.5 to 2.5)Italy: 1.36 typical gaps (standard deviations), 0.619 index (approx. -2.5 to 2.5)Jamaica: 1.06 typical gaps (standard deviations), -0.0777 index (approx. -2.5 to 2.5)Jordan: 0.776 typical gaps (standard deviations), 0.169 index (approx. -2.5 to 2.5)Japan: 1.45 typical gaps (standard deviations), 1.51 index (approx. -2.5 to 2.5)Kazakhstan: 1.09 typical gaps (standard deviations), -0.382 index (approx. -2.5 to 2.5)Kenya: 0.22 typical gaps (standard deviations), -0.465 index (approx. -2.5 to 2.5)Kyrgyz Republic: 0.943 typical gaps (standard deviations), -0.936 index (approx. -2.5 to 2.5)Cambodia: 0.689 typical gaps (standard deviations), -1.06 index (approx. -2.5 to 2.5)Kiribati: 0.485 typical gaps (standard deviations), 0.786 index (approx. -2.5 to 2.5)St. Kitts and Nevis: 1.19 typical gaps (standard deviations), 0.59 index (approx. -2.5 to 2.5)Korea, Rep.: 1.72 typical gaps (standard deviations), 1.12 index (approx. -2.5 to 2.5)Kuwait: 0.878 typical gaps (standard deviations), 0.231 index (approx. -2.5 to 2.5)Lao PDR: 0.399 typical gaps (standard deviations), -0.742 index (approx. -2.5 to 2.5)Lebanon: 0.731 typical gaps (standard deviations), -1.09 index (approx. -2.5 to 2.5)Liberia: -0.767 typical gaps (standard deviations), -0.868 index (approx. -2.5 to 2.5)Libya: 0.512 typical gaps (standard deviations), -1.7 index (approx. -2.5 to 2.5)St. Lucia: 0.881 typical gaps (standard deviations), 0.503 index (approx. -2.5 to 2.5)Sri Lanka: 0.669 typical gaps (standard deviations), -0.258 index (approx. -2.5 to 2.5)Lesotho: -0.0187 typical gaps (standard deviations), -0.407 index (approx. -2.5 to 2.5)Lithuania: 1.29 typical gaps (standard deviations), 1.37 index (approx. -2.5 to 2.5)Luxembourg: 1.59 typical gaps (standard deviations), 1.76 index (approx. -2.5 to 2.5)Latvia: 1.28 typical gaps (standard deviations), 1.09 index (approx. -2.5 to 2.5)Macao SAR, China: 1.33 typical gaps (standard deviations), 0.852 index (approx. -2.5 to 2.5)Morocco: 0.928 typical gaps (standard deviations), -0.368 index (approx. -2.5 to 2.5)Moldova: 1.23 typical gaps (standard deviations), -0.161 index (approx. -2.5 to 2.5)Madagascar: -0.434 typical gaps (standard deviations), -0.883 index (approx. -2.5 to 2.5)Maldives: 1.11 typical gaps (standard deviations), 0.0443 index (approx. -2.5 to 2.5)Mexico: 1.13 typical gaps (standard deviations), -1.15 index (approx. -2.5 to 2.5)Marshall Islands: 0.406 typical gaps (standard deviations), 0.836 index (approx. -2.5 to 2.5)North Macedonia: 1.36 typical gaps (standard deviations), -0.225 index (approx. -2.5 to 2.5)Mali: -0.495 typical gaps (standard deviations), -1.09 index (approx. -2.5 to 2.5)Malta: 1.63 typical gaps (standard deviations), 0.727 index (approx. -2.5 to 2.5)Myanmar: 0.298 typical gaps (standard deviations), -1.81 index (approx. -2.5 to 2.5)Montenegro: 1.37 typical gaps (standard deviations), 0.181 index (approx. -2.5 to 2.5)Mongolia: 1.03 typical gaps (standard deviations), -0.0998 index (approx. -2.5 to 2.5)Mozambique: -0.592 typical gaps (standard deviations), -1.19 index (approx. -2.5 to 2.5)Mauritania: 0.0018 typical gaps (standard deviations), -0.864 index (approx. -2.5 to 2.5)Mauritius: 1.17 typical gaps (standard deviations), 0.639 index (approx. -2.5 to 2.5)Malawi: -0.672 typical gaps (standard deviations), -0.146 index (approx. -2.5 to 2.5)Malaysia: 1.09 typical gaps (standard deviations), 0.345 index (approx. -2.5 to 2.5)Namibia: 0.203 typical gaps (standard deviations), 0.328 index (approx. -2.5 to 2.5)Niger: -0.7 typical gaps (standard deviations), -0.946 index (approx. -2.5 to 2.5)Nigeria: -0.0861 typical gaps (standard deviations), -1.01 index (approx. -2.5 to 2.5)Nicaragua: 0.574 typical gaps (standard deviations), -1.62 index (approx. -2.5 to 2.5)Netherlands: 1.63 typical gaps (standard deviations), 1.71 index (approx. -2.5 to 2.5)Norway: 1.68 typical gaps (standard deviations), 1.95 index (approx. -2.5 to 2.5)Nepal: 0.616 typical gaps (standard deviations), -0.304 index (approx. -2.5 to 2.5)Naoero: 0.872 typical gaps (standard deviations), 0.252 index (approx. -2.5 to 2.5)New Zealand: 1.51 typical gaps (standard deviations), 1.67 index (approx. -2.5 to 2.5)Oman: 1.03 typical gaps (standard deviations), 0.449 index (approx. -2.5 to 2.5)Pakistan: 0.386 typical gaps (standard deviations), -1.02 index (approx. -2.5 to 2.5)Panama: 0.927 typical gaps (standard deviations), -0.263 index (approx. -2.5 to 2.5)Peru: 0.907 typical gaps (standard deviations), -0.506 index (approx. -2.5 to 2.5)Philippines: 0.696 typical gaps (standard deviations), -0.574 index (approx. -2.5 to 2.5)Palau: 0.865 typical gaps (standard deviations), 1.17 index (approx. -2.5 to 2.5)Papua New Guinea: -0.611 typical gaps (standard deviations), -0.571 index (approx. -2.5 to 2.5)Poland: 1.24 typical gaps (standard deviations), 0.577 index (approx. -2.5 to 2.5)Puerto Rico (US): 1.14 typical gaps (standard deviations), 0.546 index (approx. -2.5 to 2.5)Portugal: 1.6 typical gaps (standard deviations), 1.07 index (approx. -2.5 to 2.5)Paraguay: 0.928 typical gaps (standard deviations), -0.584 index (approx. -2.5 to 2.5)West Bank and Gaza: 0.774 typical gaps (standard deviations), -0.989 index (approx. -2.5 to 2.5)Qatar: 1.06 typical gaps (standard deviations), 0.59 index (approx. -2.5 to 2.5)Romania: 1.45 typical gaps (standard deviations), 0.371 index (approx. -2.5 to 2.5)Russian Federation: 1.32 typical gaps (standard deviations), -1.16 index (approx. -2.5 to 2.5)Rwanda: 0.0662 typical gaps (standard deviations), 0.1 index (approx. -2.5 to 2.5)Saudi Arabia: 1.67 typical gaps (standard deviations), 0.21 index (approx. -2.5 to 2.5)Sudan: -0.572 typical gaps (standard deviations), -1.77 index (approx. -2.5 to 2.5)Senegal: 0.482 typical gaps (standard deviations), -0.205 index (approx. -2.5 to 2.5)Singapore: 1.33 typical gaps (standard deviations), 1.43 index (approx. -2.5 to 2.5)Solomon Islands: 0.0941 typical gaps (standard deviations), 0.153 index (approx. -2.5 to 2.5)Sierra Leone: -0.336 typical gaps (standard deviations), -0.839 index (approx. -2.5 to 2.5)El Salvador: 0.822 typical gaps (standard deviations), -0.713 index (approx. -2.5 to 2.5)San Marino: 1.5 typical gaps (standard deviations), 1.16 index (approx. -2.5 to 2.5)Somalia, Fed. Rep.: -0.395 typical gaps (standard deviations), -2.21 index (approx. -2.5 to 2.5)Serbia: 1.38 typical gaps (standard deviations), -0.2 index (approx. -2.5 to 2.5)Sao Tome and Principe: 0.187 typical gaps (standard deviations), -0.353 index (approx. -2.5 to 2.5)Suriname: 0.901 typical gaps (standard deviations), -0.209 index (approx. -2.5 to 2.5)Slovak Republic: 1.4 typical gaps (standard deviations), 0.561 index (approx. -2.5 to 2.5)Slovenia: 1.42 typical gaps (standard deviations), 0.979 index (approx. -2.5 to 2.5)Sweden: 1.57 typical gaps (standard deviations), 1.73 index (approx. -2.5 to 2.5)Eswatini: 0.534 typical gaps (standard deviations), -0.86 index (approx. -2.5 to 2.5)Seychelles: 1.35 typical gaps (standard deviations), 0.597 index (approx. -2.5 to 2.5)Syrian Arab Republic: 0.27 typical gaps (standard deviations), -1.81 index (approx. -2.5 to 2.5)Chad: -0.72 typical gaps (standard deviations), -1.44 index (approx. -2.5 to 2.5)Togo: -0.0274 typical gaps (standard deviations), -0.633 index (approx. -2.5 to 2.5)Thailand: 1.06 typical gaps (standard deviations), -0.216 index (approx. -2.5 to 2.5)Tajikistan: 0.389 typical gaps (standard deviations), -1.18 index (approx. -2.5 to 2.5)Turkmenistan: 0.294 typical gaps (standard deviations), -1.41 index (approx. -2.5 to 2.5)Timor-Leste: 0.389 typical gaps (standard deviations), -0.626 index (approx. -2.5 to 2.5)Tonga: 0.595 typical gaps (standard deviations), 0.694 index (approx. -2.5 to 2.5)Trinidad and Tobago: 1.22 typical gaps (standard deviations), -0.372 index (approx. -2.5 to 2.5)Tunisia: 0.956 typical gaps (standard deviations), -0.364 index (approx. -2.5 to 2.5)Turkiye: 1.19 typical gaps (standard deviations), -0.843 index (approx. -2.5 to 2.5)Tuvalu: 0.208 typical gaps (standard deviations), 1.22 index (approx. -2.5 to 2.5)Tanzania: -0.0741 typical gaps (standard deviations), -0.519 index (approx. -2.5 to 2.5)Uganda: -0.319 typical gaps (standard deviations), -0.739 index (approx. -2.5 to 2.5)Ukraine: 0.97 typical gaps (standard deviations), -0.72 index (approx. -2.5 to 2.5)Uruguay: 1.41 typical gaps (standard deviations), 0.951 index (approx. -2.5 to 2.5)United States: 1.53 typical gaps (standard deviations), 0.962 index (approx. -2.5 to 2.5)Uzbekistan: 1.42 typical gaps (standard deviations), -0.656 index (approx. -2.5 to 2.5)St. Vincent and the Grenadines: 1.22 typical gaps (standard deviations), 0.502 index (approx. -2.5 to 2.5)Virgin Islands (U.S.): 0.721 typical gaps (standard deviations), 0.579 index (approx. -2.5 to 2.5)Viet Nam: 1.17 typical gaps (standard deviations), -0.314 index (approx. -2.5 to 2.5)Vanuatu: -0.0444 typical gaps (standard deviations), 0.422 index (approx. -2.5 to 2.5)Samoa: 0.0591 typical gaps (standard deviations), 1.05 index (approx. -2.5 to 2.5)South Africa: 0.709 typical gaps (standard deviations), 0.0177 index (approx. -2.5 to 2.5)Zambia: -0.161 typical gaps (standard deviations), -0.561 index (approx. -2.5 to 2.5)Zimbabwe: 0.0863 typical gaps (standard deviations), -1.21 index (approx. -2.5 to 2.5)BLRCAFCHECHNDNKFSMNORRUSSDNSOMTUVWSM

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.6562.9e-25194
By rank (Spearman), not adjusted+0.6801.2e-27194
Standard (Pearson), adjusted for national income+0.0400.581194
By rank (Spearman), adjusted for national income+0.0900.214194

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 194 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: +0.616 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.002 (without GNQ) to +0.057 (without WSM). 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: GNQ (-0.038).

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 & Pacific31-0.15
Europe & Central Asia51+0.27
Latin America & Caribbean35+0.26
Middle East, North Africa, Afghanistan & Pakistan22+0.23
Sub-Saharan Africa46+0.40

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 third65+0.01
Middle third64+0.13
Richest third65+0.46

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
Christians111+0.07
Muslims49+0.03

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+0.21
Never a European colony21+0.07
Spain20+0.16
United Kingdom63+0.24

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 = +0.040 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 (approx. -2.5 to 2.5)
Years
Andorra AND1.781.412024
Korea, Rep. KOR1.721.122024
Switzerland CHE1.71.762024
France FRA1.70.9792024
Bermuda BMU1.680.82024
Norway NOR1.681.952024
Saudi Arabia SAU1.670.212024
China CHN1.66-0.5792024
Denmark DNK1.6522024
Germany DEU1.651.632024
Belgium BEL1.641.282024
Malta MLT1.630.7272024
Netherlands NLD1.631.712024
United Arab Emirates ARE1.610.4972024
Portugal PRT1.61.072024

wdi
Kaufmann, D. and A. Kraay, Worldwide Governance Indicators, World Bank

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.

Rule of law

Rule of Law (estimate)

World Bank · CC BY 4.0 · updated annual

How this was computed

Data used: most recent value in 2010-2025; values come from 2022–2024. 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 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 Rule of law

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

More links with Infrastructure score or Rule of law