placestats

Infrastructure score vs. Regulatory quality

Fades after adjusting for income

Across 194 countries, Infrastructure score and Regulatory quality rise and fall together at r = +0.73 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to +0.01, which could easily be chance (q = 0.91, 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: sign flips when a single country is removed.

Comparing countries across the middle half of regulatory quality, -0.644 to 0.649 points, infrastructure score is better by 0.693 typical gaps at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.00488 typical gaps.

Link before adjusting (r)+0.727p = 3.3e-33 · 194 countries
After adjusting for national income+0.007p = 0.920 · likely range [-0.13, +0.15]
p, allowing for regions0.849standard error 0.037 · 7 regions
Check for luck (q)0.914across 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
Regulatory quality · index (approx. -2.5 to 2.5)link with income +0.83 · 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

Infrastructure score · typical gaps (standard deviations) →Regulatory quality · index (approx. -2.5 to 2.5) →-1.011.78-22.13Aruba: 0.917 typical gaps (standard deviations), 0.981 index (approx. -2.5 to 2.5)Afghanistan: 0.116 typical gaps (standard deviations), -1.54 index (approx. -2.5 to 2.5)Angola: -0.152 typical gaps (standard deviations), -0.773 index (approx. -2.5 to 2.5)Albania: 1.14 typical gaps (standard deviations), 0.136 index (approx. -2.5 to 2.5)Andorra: 1.78 typical gaps (standard deviations), 1.1 index (approx. -2.5 to 2.5)United Arab Emirates: 1.61 typical gaps (standard deviations), 1.13 index (approx. -2.5 to 2.5)Argentina: 1.25 typical gaps (standard deviations), -0.235 index (approx. -2.5 to 2.5)Armenia: 1.09 typical gaps (standard deviations), 0.138 index (approx. -2.5 to 2.5)Antigua and Barbuda: 0.859 typical gaps (standard deviations), 0.635 index (approx. -2.5 to 2.5)Australia: 1.5 typical gaps (standard deviations), 1.72 index (approx. -2.5 to 2.5)Austria: 1.37 typical gaps (standard deviations), 1.35 index (approx. -2.5 to 2.5)Azerbaijan: 1.19 typical gaps (standard deviations), 0.135 index (approx. -2.5 to 2.5)Burundi: -0.835 typical gaps (standard deviations), -0.814 index (approx. -2.5 to 2.5)Belgium: 1.64 typical gaps (standard deviations), 1.24 index (approx. -2.5 to 2.5)Benin: 0.00537 typical gaps (standard deviations), -0.277 index (approx. -2.5 to 2.5)Burkina Faso: -0.245 typical gaps (standard deviations), -0.526 index (approx. -2.5 to 2.5)Bangladesh: 0.649 typical gaps (standard deviations), -0.95 index (approx. -2.5 to 2.5)Bulgaria: 1.25 typical gaps (standard deviations), 0.288 index (approx. -2.5 to 2.5)Bahrain: 1.17 typical gaps (standard deviations), 0.95 index (approx. -2.5 to 2.5)Bahamas, The: 1.25 typical gaps (standard deviations), -0.107 index (approx. -2.5 to 2.5)Bosnia and Herzegovina: 1.29 typical gaps (standard deviations), -0.35 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), -0.45 index (approx. -2.5 to 2.5)Bermuda: 1.68 typical gaps (standard deviations), 0.629 index (approx. -2.5 to 2.5)Bolivia: 0.886 typical gaps (standard deviations), -1.25 index (approx. -2.5 to 2.5)Brazil: 1.18 typical gaps (standard deviations), -0.295 index (approx. -2.5 to 2.5)Barbados: 1.31 typical gaps (standard deviations), 0.441 index (approx. -2.5 to 2.5)Brunei Darussalam: 1.22 typical gaps (standard deviations), 0.887 index (approx. -2.5 to 2.5)Bhutan: 0.847 typical gaps (standard deviations), -0.0913 index (approx. -2.5 to 2.5)Botswana: 0.5 typical gaps (standard deviations), 0.402 index (approx. -2.5 to 2.5)Central African Republic: -1.01 typical gaps (standard deviations), -1.27 index (approx. -2.5 to 2.5)Canada: 1.56 typical gaps (standard deviations), 1.36 index (approx. -2.5 to 2.5)Switzerland: 1.7 typical gaps (standard deviations), 1.77 index (approx. -2.5 to 2.5)Chile: 1.25 typical gaps (standard deviations), 0.781 index (approx. -2.5 to 2.5)China: 1.66 typical gaps (standard deviations), -0.0713 index (approx. -2.5 to 2.5)Cote d'Ivoire: 0.207 typical gaps (standard deviations), -0.167 index (approx. -2.5 to 2.5)Cameroon: 0.557 typical gaps (standard deviations), -0.729 index (approx. -2.5 to 2.5)Congo, Dem. Rep.: -0.672 typical gaps (standard deviations), -1.28 index (approx. -2.5 to 2.5)Congo, Rep.: 0.312 typical gaps (standard deviations), -1.15 index (approx. -2.5 to 2.5)Colombia: 1.01 typical gaps (standard deviations), 0.0134 index (approx. -2.5 to 2.5)Comoros: 0.259 typical gaps (standard deviations), -1.25 index (approx. -2.5 to 2.5)Cabo Verde: 0.806 typical gaps (standard deviations), 0.0451 index (approx. -2.5 to 2.5)Costa Rica: 1.19 typical gaps (standard deviations), 0.582 index (approx. -2.5 to 2.5)Cayman Islands: 1.58 typical gaps (standard deviations), 1.07 index (approx. -2.5 to 2.5)Cyprus: 1.47 typical gaps (standard deviations), 0.74 index (approx. -2.5 to 2.5)Czechia: 1.48 typical gaps (standard deviations), 1.23 index (approx. -2.5 to 2.5)Germany: 1.65 typical gaps (standard deviations), 1.5 index (approx. -2.5 to 2.5)Djibouti: 0.0105 typical gaps (standard deviations), -0.853 index (approx. -2.5 to 2.5)Dominica: 1.01 typical gaps (standard deviations), 0.0598 index (approx. -2.5 to 2.5)Denmark: 1.65 typical gaps (standard deviations), 1.93 index (approx. -2.5 to 2.5)Dominican Republic: 0.956 typical gaps (standard deviations), 0.207 index (approx. -2.5 to 2.5)Algeria: 0.932 typical gaps (standard deviations), -0.753 index (approx. -2.5 to 2.5)Ecuador: 0.989 typical gaps (standard deviations), -0.646 index (approx. -2.5 to 2.5)Egypt, Arab Rep.: 0.864 typical gaps (standard deviations), -0.499 index (approx. -2.5 to 2.5)Spain: 1.55 typical gaps (standard deviations), 0.621 index (approx. -2.5 to 2.5)Estonia: 1.45 typical gaps (standard deviations), 1.4 index (approx. -2.5 to 2.5)Ethiopia: -0.309 typical gaps (standard deviations), -0.833 index (approx. -2.5 to 2.5)Finland: 1.48 typical gaps (standard deviations), 1.96 index (approx. -2.5 to 2.5)Fiji: 0.665 typical gaps (standard deviations), 0.0651 index (approx. -2.5 to 2.5)France: 1.7 typical gaps (standard deviations), 1.15 index (approx. -2.5 to 2.5)Micronesia, Fed. Sts.: -0.101 typical gaps (standard deviations), -0.763 index (approx. -2.5 to 2.5)Gabon: 0.665 typical gaps (standard deviations), -0.723 index (approx. -2.5 to 2.5)United Kingdom: 1.6 typical gaps (standard deviations), 1.51 index (approx. -2.5 to 2.5)Georgia: 1.29 typical gaps (standard deviations), 0.65 index (approx. -2.5 to 2.5)Ghana: 0.59 typical gaps (standard deviations), -0.0899 index (approx. -2.5 to 2.5)Guinea: 0.156 typical gaps (standard deviations), -0.892 index (approx. -2.5 to 2.5)Gambia, The: 0.215 typical gaps (standard deviations), -0.664 index (approx. -2.5 to 2.5)Guinea-Bissau: -0.158 typical gaps (standard deviations), -1.19 index (approx. -2.5 to 2.5)Equatorial Guinea: -0.269 typical gaps (standard deviations), -1.4 index (approx. -2.5 to 2.5)Greece: 1.57 typical gaps (standard deviations), 0.48 index (approx. -2.5 to 2.5)Grenada: 1.09 typical gaps (standard deviations), 0.0499 index (approx. -2.5 to 2.5)Greenland: 1.24 typical gaps (standard deviations), 1.5 index (approx. -2.5 to 2.5)Guatemala: 0.576 typical gaps (standard deviations), -0.309 index (approx. -2.5 to 2.5)Guyana: 0.809 typical gaps (standard deviations), -0.447 index (approx. -2.5 to 2.5)Hong Kong SAR, China: 1.57 typical gaps (standard deviations), 1.74 index (approx. -2.5 to 2.5)Honduras: 0.417 typical gaps (standard deviations), -0.628 index (approx. -2.5 to 2.5)Croatia: 1.28 typical gaps (standard deviations), 0.286 index (approx. -2.5 to 2.5)Haiti: -0.312 typical gaps (standard deviations), -1.46 index (approx. -2.5 to 2.5)Hungary: 1.5 typical gaps (standard deviations), 0.335 index (approx. -2.5 to 2.5)Indonesia: 0.742 typical gaps (standard deviations), 0.125 index (approx. -2.5 to 2.5)India: 0.527 typical gaps (standard deviations), -0.0961 index (approx. -2.5 to 2.5)Ireland: 1.43 typical gaps (standard deviations), 1.79 index (approx. -2.5 to 2.5)Iran, Islamic Rep.: 0.97 typical gaps (standard deviations), -1.51 index (approx. -2.5 to 2.5)Iraq: 1.04 typical gaps (standard deviations), -1.03 index (approx. -2.5 to 2.5)Iceland: 1.53 typical gaps (standard deviations), 1.33 index (approx. -2.5 to 2.5)Israel: 1.31 typical gaps (standard deviations), 1.11 index (approx. -2.5 to 2.5)Italy: 1.36 typical gaps (standard deviations), 0.64 index (approx. -2.5 to 2.5)Jamaica: 1.06 typical gaps (standard deviations), 0.0909 index (approx. -2.5 to 2.5)Jordan: 0.776 typical gaps (standard deviations), 0.276 index (approx. -2.5 to 2.5)Japan: 1.45 typical gaps (standard deviations), 1.33 index (approx. -2.5 to 2.5)Kazakhstan: 1.09 typical gaps (standard deviations), 0.0471 index (approx. -2.5 to 2.5)Kenya: 0.22 typical gaps (standard deviations), -0.334 index (approx. -2.5 to 2.5)Kyrgyz Republic: 0.943 typical gaps (standard deviations), -0.517 index (approx. -2.5 to 2.5)Cambodia: 0.689 typical gaps (standard deviations), -0.631 index (approx. -2.5 to 2.5)Kiribati: 0.485 typical gaps (standard deviations), -0.501 index (approx. -2.5 to 2.5)St. Kitts and Nevis: 1.19 typical gaps (standard deviations), 0.48 index (approx. -2.5 to 2.5)Korea, Rep.: 1.72 typical gaps (standard deviations), 1.01 index (approx. -2.5 to 2.5)Kuwait: 0.878 typical gaps (standard deviations), 0.404 index (approx. -2.5 to 2.5)Lao PDR: 0.399 typical gaps (standard deviations), -0.636 index (approx. -2.5 to 2.5)Lebanon: 0.731 typical gaps (standard deviations), -0.959 index (approx. -2.5 to 2.5)Liberia: -0.767 typical gaps (standard deviations), -0.842 index (approx. -2.5 to 2.5)Libya: 0.512 typical gaps (standard deviations), -1.74 index (approx. -2.5 to 2.5)St. Lucia: 0.881 typical gaps (standard deviations), 0.182 index (approx. -2.5 to 2.5)Sri Lanka: 0.669 typical gaps (standard deviations), -0.299 index (approx. -2.5 to 2.5)Lesotho: -0.0187 typical gaps (standard deviations), -0.485 index (approx. -2.5 to 2.5)Lithuania: 1.29 typical gaps (standard deviations), 1.29 index (approx. -2.5 to 2.5)Luxembourg: 1.59 typical gaps (standard deviations), 1.84 index (approx. -2.5 to 2.5)Latvia: 1.28 typical gaps (standard deviations), 1.1 index (approx. -2.5 to 2.5)Macao SAR, China: 1.33 typical gaps (standard deviations), 1.37 index (approx. -2.5 to 2.5)Morocco: 0.928 typical gaps (standard deviations), -0.0267 index (approx. -2.5 to 2.5)Moldova: 1.23 typical gaps (standard deviations), -0.0467 index (approx. -2.5 to 2.5)Madagascar: -0.434 typical gaps (standard deviations), -0.749 index (approx. -2.5 to 2.5)Maldives: 1.11 typical gaps (standard deviations), -0.235 index (approx. -2.5 to 2.5)Mexico: 1.13 typical gaps (standard deviations), -0.196 index (approx. -2.5 to 2.5)Marshall Islands: 0.406 typical gaps (standard deviations), -0.688 index (approx. -2.5 to 2.5)North Macedonia: 1.36 typical gaps (standard deviations), 0.266 index (approx. -2.5 to 2.5)Mali: -0.495 typical gaps (standard deviations), -0.762 index (approx. -2.5 to 2.5)Malta: 1.63 typical gaps (standard deviations), 0.492 index (approx. -2.5 to 2.5)Myanmar: 0.298 typical gaps (standard deviations), -1.42 index (approx. -2.5 to 2.5)Montenegro: 1.37 typical gaps (standard deviations), 0.127 index (approx. -2.5 to 2.5)Mongolia: 1.03 typical gaps (standard deviations), -0.0707 index (approx. -2.5 to 2.5)Mozambique: -0.592 typical gaps (standard deviations), -0.764 index (approx. -2.5 to 2.5)Mauritania: 0.0018 typical gaps (standard deviations), -0.778 index (approx. -2.5 to 2.5)Mauritius: 1.17 typical gaps (standard deviations), 0.94 index (approx. -2.5 to 2.5)Malawi: -0.672 typical gaps (standard deviations), -0.585 index (approx. -2.5 to 2.5)Malaysia: 1.09 typical gaps (standard deviations), 0.68 index (approx. -2.5 to 2.5)Namibia: 0.203 typical gaps (standard deviations), 0.135 index (approx. -2.5 to 2.5)Niger: -0.7 typical gaps (standard deviations), -0.762 index (approx. -2.5 to 2.5)Nigeria: -0.0861 typical gaps (standard deviations), -0.633 index (approx. -2.5 to 2.5)Nicaragua: 0.574 typical gaps (standard deviations), -0.991 index (approx. -2.5 to 2.5)Netherlands: 1.63 typical gaps (standard deviations), 1.72 index (approx. -2.5 to 2.5)Norway: 1.68 typical gaps (standard deviations), 1.67 index (approx. -2.5 to 2.5)Nepal: 0.616 typical gaps (standard deviations), -0.552 index (approx. -2.5 to 2.5)Naoero: 0.872 typical gaps (standard deviations), -0.525 index (approx. -2.5 to 2.5)New Zealand: 1.51 typical gaps (standard deviations), 1.84 index (approx. -2.5 to 2.5)Oman: 1.03 typical gaps (standard deviations), 0.688 index (approx. -2.5 to 2.5)Pakistan: 0.386 typical gaps (standard deviations), -0.793 index (approx. -2.5 to 2.5)Panama: 0.927 typical gaps (standard deviations), -0.0738 index (approx. -2.5 to 2.5)Peru: 0.907 typical gaps (standard deviations), 0.0828 index (approx. -2.5 to 2.5)Philippines: 0.696 typical gaps (standard deviations), 0.0793 index (approx. -2.5 to 2.5)Palau: 0.865 typical gaps (standard deviations), 0.481 index (approx. -2.5 to 2.5)Papua New Guinea: -0.611 typical gaps (standard deviations), -0.6 index (approx. -2.5 to 2.5)Poland: 1.24 typical gaps (standard deviations), 0.686 index (approx. -2.5 to 2.5)Puerto Rico (US): 1.14 typical gaps (standard deviations), 0.653 index (approx. -2.5 to 2.5)Portugal: 1.6 typical gaps (standard deviations), 0.74 index (approx. -2.5 to 2.5)Paraguay: 0.928 typical gaps (standard deviations), -0.141 index (approx. -2.5 to 2.5)West Bank and Gaza: 0.774 typical gaps (standard deviations), -0.468 index (approx. -2.5 to 2.5)Qatar: 1.06 typical gaps (standard deviations), 0.966 index (approx. -2.5 to 2.5)Romania: 1.45 typical gaps (standard deviations), 0.383 index (approx. -2.5 to 2.5)Russian Federation: 1.32 typical gaps (standard deviations), -1.07 index (approx. -2.5 to 2.5)Rwanda: 0.0662 typical gaps (standard deviations), 0.27 index (approx. -2.5 to 2.5)Saudi Arabia: 1.67 typical gaps (standard deviations), 0.71 index (approx. -2.5 to 2.5)Sudan: -0.572 typical gaps (standard deviations), -1.66 index (approx. -2.5 to 2.5)Senegal: 0.482 typical gaps (standard deviations), -0.242 index (approx. -2.5 to 2.5)Singapore: 1.33 typical gaps (standard deviations), 2.13 index (approx. -2.5 to 2.5)Solomon Islands: 0.0941 typical gaps (standard deviations), -0.888 index (approx. -2.5 to 2.5)Sierra Leone: -0.336 typical gaps (standard deviations), -1.06 index (approx. -2.5 to 2.5)El Salvador: 0.822 typical gaps (standard deviations), -0.176 index (approx. -2.5 to 2.5)San Marino: 1.5 typical gaps (standard deviations), 0.865 index (approx. -2.5 to 2.5)Somalia, Fed. Rep.: -0.395 typical gaps (standard deviations), -1.73 index (approx. -2.5 to 2.5)Serbia: 1.38 typical gaps (standard deviations), 0.0784 index (approx. -2.5 to 2.5)Sao Tome and Principe: 0.187 typical gaps (standard deviations), -0.891 index (approx. -2.5 to 2.5)Suriname: 0.901 typical gaps (standard deviations), -0.919 index (approx. -2.5 to 2.5)Slovak Republic: 1.4 typical gaps (standard deviations), 0.405 index (approx. -2.5 to 2.5)Slovenia: 1.42 typical gaps (standard deviations), 0.798 index (approx. -2.5 to 2.5)Sweden: 1.57 typical gaps (standard deviations), 1.67 index (approx. -2.5 to 2.5)Eswatini: 0.534 typical gaps (standard deviations), -0.638 index (approx. -2.5 to 2.5)Seychelles: 1.35 typical gaps (standard deviations), 0.39 index (approx. -2.5 to 2.5)Syrian Arab Republic: 0.27 typical gaps (standard deviations), -2 index (approx. -2.5 to 2.5)Chad: -0.72 typical gaps (standard deviations), -1.09 index (approx. -2.5 to 2.5)Togo: -0.0274 typical gaps (standard deviations), -0.408 index (approx. -2.5 to 2.5)Thailand: 1.06 typical gaps (standard deviations), 0.106 index (approx. -2.5 to 2.5)Tajikistan: 0.389 typical gaps (standard deviations), -0.759 index (approx. -2.5 to 2.5)Turkmenistan: 0.294 typical gaps (standard deviations), -1.69 index (approx. -2.5 to 2.5)Timor-Leste: 0.389 typical gaps (standard deviations), -0.734 index (approx. -2.5 to 2.5)Tonga: 0.595 typical gaps (standard deviations), -0.194 index (approx. -2.5 to 2.5)Trinidad and Tobago: 1.22 typical gaps (standard deviations), -0.207 index (approx. -2.5 to 2.5)Tunisia: 0.956 typical gaps (standard deviations), -0.39 index (approx. -2.5 to 2.5)Turkiye: 1.19 typical gaps (standard deviations), -0.211 index (approx. -2.5 to 2.5)Tuvalu: 0.208 typical gaps (standard deviations), -0.402 index (approx. -2.5 to 2.5)Tanzania: -0.0741 typical gaps (standard deviations), -0.535 index (approx. -2.5 to 2.5)Uganda: -0.319 typical gaps (standard deviations), -0.524 index (approx. -2.5 to 2.5)Ukraine: 0.97 typical gaps (standard deviations), -0.301 index (approx. -2.5 to 2.5)Uruguay: 1.41 typical gaps (standard deviations), 0.647 index (approx. -2.5 to 2.5)United States: 1.53 typical gaps (standard deviations), 1.35 index (approx. -2.5 to 2.5)Uzbekistan: 1.42 typical gaps (standard deviations), -0.527 index (approx. -2.5 to 2.5)St. Vincent and the Grenadines: 1.22 typical gaps (standard deviations), 0.106 index (approx. -2.5 to 2.5)Virgin Islands (U.S.): 0.721 typical gaps (standard deviations), 1.1 index (approx. -2.5 to 2.5)Viet Nam: 1.17 typical gaps (standard deviations), -0.267 index (approx. -2.5 to 2.5)Vanuatu: -0.0444 typical gaps (standard deviations), -0.325 index (approx. -2.5 to 2.5)Samoa: 0.0591 typical gaps (standard deviations), -0.102 index (approx. -2.5 to 2.5)South Africa: 0.709 typical gaps (standard deviations), -0.0601 index (approx. -2.5 to 2.5)Zambia: -0.161 typical gaps (standard deviations), -0.421 index (approx. -2.5 to 2.5)Zimbabwe: 0.0863 typical gaps (standard deviations), -1.18 index (approx. -2.5 to 2.5)BDIBLRCAFCHEDNKIRNLUXMWIRUSSDNSGPSOM

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.7273.3e-33194
By rank (Spearman), not adjusted+0.7832.2e-41194
Standard (Pearson), adjusted for national income+0.0070.920194
By rank (Spearman), adjusted for national income+0.1260.081194

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: +0.720 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.039 (without GNQ) to +0.028 (without BLR). 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 (-0.047).

Fragile: this link may not hold up.
  • sign flips when a single country is removed
  • 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 & Pacific31-0.13
Europe & Central Asia51+0.27
Latin America & Caribbean35+0.20
Middle East, North Africa, Afghanistan & Pakistan22+0.24
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 third65-0.01
Middle third64+0.22
Richest third65+0.35

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+0.04
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+0.06
Never a European colony21+0.19
Spain20+0.49
United Kingdom63+0.12

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 = +0.007 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 AND1.781.12024
Korea, Rep. KOR1.721.012024
Switzerland CHE1.71.772024
France FRA1.71.152024
Bermuda BMU1.680.6292024
Norway NOR1.681.672024
Saudi Arabia SAU1.670.712024
China CHN1.66-0.07132024
Denmark DNK1.651.932024
Germany DEU1.651.52024
Belgium BEL1.641.242024
Malta MLT1.630.4922024
Netherlands NLD1.631.722024
United Arab Emirates ARE1.611.132024
Portugal PRT1.60.742024

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.

Regulatory quality

Regulatory Quality (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 Regulatory quality

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

More links with Infrastructure score or Regulatory quality