placestats

Governance score vs. Price level

Fades after adjusting for income

Across 163 countries, Governance score and Price level rise and fall together at r = +0.70 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to +0.49, which could easily be chance (q = 0.058, 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.

Comparing countries across the middle half of price level, 0.337 to 0.646 ratio to the US, governance score is better by 0.753 typical gaps at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.532 typical gaps.

Link before adjusting (r)+0.702p = 1.8e-25 · 163 countries
After adjusting for national income+0.485p = 6.1e-11 · likely range [+0.36, +0.59]
p, allowing for regions0.015standard error 0.144 · 7 regions
Check for luck (q)0.058across 18,622 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
Price level · ratio to the US (US = 1)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

Governance score · typical gaps (standard deviations) →Price level · ratio to the US (US = 1) →-1.491.570.1661.41Angola: -0.602 typical gaps (standard deviations), 0.385 ratio to the US (US = 1)Albania: 0.259 typical gaps (standard deviations), 0.514 ratio to the US (US = 1)United Arab Emirates: -0.438 typical gaps (standard deviations), 0.68 ratio to the US (US = 1)Argentina: 0.568 typical gaps (standard deviations), 0.506 ratio to the US (US = 1)Armenia: 0.127 typical gaps (standard deviations), 0.41 ratio to the US (US = 1)Australia: 1.42 typical gaps (standard deviations), 1.01 ratio to the US (US = 1)Austria: 1.31 typical gaps (standard deviations), 0.87 ratio to the US (US = 1)Azerbaijan: -1.03 typical gaps (standard deviations), 0.319 ratio to the US (US = 1)Burundi: -1.16 typical gaps (standard deviations), 0.308 ratio to the US (US = 1)Belgium: 1.32 typical gaps (standard deviations), 0.893 ratio to the US (US = 1)Benin: 0.0936 typical gaps (standard deviations), 0.33 ratio to the US (US = 1)Burkina Faso: -0.825 typical gaps (standard deviations), 0.315 ratio to the US (US = 1)Bangladesh: -0.507 typical gaps (standard deviations), 0.289 ratio to the US (US = 1)Bulgaria: 0.537 typical gaps (standard deviations), 0.496 ratio to the US (US = 1)Bahrain: -0.69 typical gaps (standard deviations), 0.617 ratio to the US (US = 1)Bosnia and Herzegovina: -0.0604 typical gaps (standard deviations), 0.447 ratio to the US (US = 1)Belarus: -1.15 typical gaps (standard deviations), 0.271 ratio to the US (US = 1)Belize: 0.087 typical gaps (standard deviations), 0.575 ratio to the US (US = 1)Bolivia: 0.114 typical gaps (standard deviations), 0.336 ratio to the US (US = 1)Brazil: 0.502 typical gaps (standard deviations), 0.517 ratio to the US (US = 1)Barbados: 1.13 typical gaps (standard deviations), 1.41 ratio to the US (US = 1)Bhutan: 0.659 typical gaps (standard deviations), 0.283 ratio to the US (US = 1)Botswana: 0.763 typical gaps (standard deviations), 0.397 ratio to the US (US = 1)Central African Republic: -1.17 typical gaps (standard deviations), 0.482 ratio to the US (US = 1)Canada: 1.39 typical gaps (standard deviations), 0.924 ratio to the US (US = 1)Switzerland: 1.54 typical gaps (standard deviations), 1.32 ratio to the US (US = 1)Chile: 1.15 typical gaps (standard deviations), 0.63 ratio to the US (US = 1)China: -0.875 typical gaps (standard deviations), 0.526 ratio to the US (US = 1)Cote d'Ivoire: -0.208 typical gaps (standard deviations), 0.402 ratio to the US (US = 1)Cameroon: -0.934 typical gaps (standard deviations), 0.336 ratio to the US (US = 1)Congo, Dem. Rep.: -1.07 typical gaps (standard deviations), 0.499 ratio to the US (US = 1)Congo, Rep.: -0.987 typical gaps (standard deviations), 0.363 ratio to the US (US = 1)Colombia: 0.377 typical gaps (standard deviations), 0.41 ratio to the US (US = 1)Comoros: -0.604 typical gaps (standard deviations), 0.468 ratio to the US (US = 1)Cabo Verde: 0.977 typical gaps (standard deviations), 0.528 ratio to the US (US = 1)Costa Rica: 1.15 typical gaps (standard deviations), 0.691 ratio to the US (US = 1)Cyprus: 0.98 typical gaps (standard deviations), 0.701 ratio to the US (US = 1)Czechia: 1.24 typical gaps (standard deviations), 0.701 ratio to the US (US = 1)Germany: 1.35 typical gaps (standard deviations), 0.839 ratio to the US (US = 1)Djibouti: -0.803 typical gaps (standard deviations), 0.488 ratio to the US (US = 1)Denmark: 1.57 typical gaps (standard deviations), 1.05 ratio to the US (US = 1)Dominican Republic: 0.48 typical gaps (standard deviations), 0.426 ratio to the US (US = 1)Algeria: -0.674 typical gaps (standard deviations), 0.336 ratio to the US (US = 1)Ecuador: 0.126 typical gaps (standard deviations), 0.455 ratio to the US (US = 1)Egypt, Arab Rep.: -0.9 typical gaps (standard deviations), 0.166 ratio to the US (US = 1)Spain: 1.13 typical gaps (standard deviations), 0.748 ratio to the US (US = 1)Estonia: 1.4 typical gaps (standard deviations), 0.77 ratio to the US (US = 1)Ethiopia: -0.809 typical gaps (standard deviations), 0.367 ratio to the US (US = 1)Finland: 1.51 typical gaps (standard deviations), 0.968 ratio to the US (US = 1)Fiji: 0.538 typical gaps (standard deviations), 0.401 ratio to the US (US = 1)France: 1.14 typical gaps (standard deviations), 0.847 ratio to the US (US = 1)Gabon: -0.556 typical gaps (standard deviations), 0.489 ratio to the US (US = 1)United Kingdom: 1.25 typical gaps (standard deviations), 0.948 ratio to the US (US = 1)Georgia: 0.0236 typical gaps (standard deviations), 0.416 ratio to the US (US = 1)Ghana: 0.586 typical gaps (standard deviations), 0.348 ratio to the US (US = 1)Guinea: -0.779 typical gaps (standard deviations), 0.412 ratio to the US (US = 1)Gambia, The: 0.128 typical gaps (standard deviations), 0.317 ratio to the US (US = 1)Guinea-Bissau: -0.69 typical gaps (standard deviations), 0.394 ratio to the US (US = 1)Equatorial Guinea: -1.3 typical gaps (standard deviations), 0.449 ratio to the US (US = 1)Greece: 0.751 typical gaps (standard deviations), 0.68 ratio to the US (US = 1)Guatemala: 0.000403 typical gaps (standard deviations), 0.463 ratio to the US (US = 1)Guyana: 0.328 typical gaps (standard deviations), 0.422 ratio to the US (US = 1)Hong Kong SAR, China: -0.017 typical gaps (standard deviations), 0.801 ratio to the US (US = 1)Honduras: -0.154 typical gaps (standard deviations), 0.505 ratio to the US (US = 1)Croatia: 0.761 typical gaps (standard deviations), 0.621 ratio to the US (US = 1)Haiti: -0.951 typical gaps (standard deviations), 0.592 ratio to the US (US = 1)Hungary: 0.237 typical gaps (standard deviations), 0.592 ratio to the US (US = 1)Indonesia: 0.0177 typical gaps (standard deviations), 0.352 ratio to the US (US = 1)India: 0.0581 typical gaps (standard deviations), 0.238 ratio to the US (US = 1)Ireland: 1.43 typical gaps (standard deviations), 1.13 ratio to the US (US = 1)Iran, Islamic Rep.: -1.28 typical gaps (standard deviations), 0.277 ratio to the US (US = 1)Iraq: -0.727 typical gaps (standard deviations), 0.371 ratio to the US (US = 1)Iceland: 1.37 typical gaps (standard deviations), 1.22 ratio to the US (US = 1)Israel: 0.72 typical gaps (standard deviations), 1.09 ratio to the US (US = 1)Italy: 0.911 typical gaps (standard deviations), 0.774 ratio to the US (US = 1)Jamaica: 0.748 typical gaps (standard deviations), 0.623 ratio to the US (US = 1)Jordan: -0.18 typical gaps (standard deviations), 0.486 ratio to the US (US = 1)Japan: 1.34 typical gaps (standard deviations), 0.793 ratio to the US (US = 1)Kazakhstan: -0.619 typical gaps (standard deviations), 0.361 ratio to the US (US = 1)Kenya: -0.0288 typical gaps (standard deviations), 0.316 ratio to the US (US = 1)Kyrgyz Republic: -0.706 typical gaps (standard deviations), 0.294 ratio to the US (US = 1)Cambodia: -0.921 typical gaps (standard deviations), 0.42 ratio to the US (US = 1)Korea, Rep.: 1.06 typical gaps (standard deviations), 0.728 ratio to the US (US = 1)Kuwait: -0.424 typical gaps (standard deviations), 0.601 ratio to the US (US = 1)Lao PDR: -0.976 typical gaps (standard deviations), 0.224 ratio to the US (US = 1)Lebanon: -0.406 typical gaps (standard deviations), 0.403 ratio to the US (US = 1)Liberia: 0.064 typical gaps (standard deviations), 0.542 ratio to the US (US = 1)St. Lucia: 0.549 typical gaps (standard deviations), 0.579 ratio to the US (US = 1)Sri Lanka: 0.356 typical gaps (standard deviations), 0.283 ratio to the US (US = 1)Lesotho: 0.356 typical gaps (standard deviations), 0.33 ratio to the US (US = 1)Lithuania: 1.16 typical gaps (standard deviations), 0.618 ratio to the US (US = 1)Luxembourg: 1.48 typical gaps (standard deviations), 1.07 ratio to the US (US = 1)Latvia: 1.13 typical gaps (standard deviations), 0.672 ratio to the US (US = 1)Morocco: -0.333 typical gaps (standard deviations), 0.421 ratio to the US (US = 1)Moldova: 0.335 typical gaps (standard deviations), 0.416 ratio to the US (US = 1)Madagascar: -0.392 typical gaps (standard deviations), 0.269 ratio to the US (US = 1)Maldives: -0.015 typical gaps (standard deviations), 0.662 ratio to the US (US = 1)Mexico: -0.0935 typical gaps (standard deviations), 0.622 ratio to the US (US = 1)North Macedonia: 0.285 typical gaps (standard deviations), 0.386 ratio to the US (US = 1)Mali: -0.943 typical gaps (standard deviations), 0.294 ratio to the US (US = 1)Malta: 0.978 typical gaps (standard deviations), 0.713 ratio to the US (US = 1)Myanmar: -1.49 typical gaps (standard deviations), 0.177 ratio to the US (US = 1)Montenegro: 0.475 typical gaps (standard deviations), 0.496 ratio to the US (US = 1)Mongolia: 0.484 typical gaps (standard deviations), 0.325 ratio to the US (US = 1)Mozambique: -0.547 typical gaps (standard deviations), 0.413 ratio to the US (US = 1)Mauritania: -0.54 typical gaps (standard deviations), 0.345 ratio to the US (US = 1)Mauritius: 0.962 typical gaps (standard deviations), 0.449 ratio to the US (US = 1)Malawi: 0.271 typical gaps (standard deviations), 0.321 ratio to the US (US = 1)Malaysia: 0.278 typical gaps (standard deviations), 0.317 ratio to the US (US = 1)Namibia: 0.568 typical gaps (standard deviations), 0.365 ratio to the US (US = 1)Niger: -0.715 typical gaps (standard deviations), 0.292 ratio to the US (US = 1)Nigeria: -0.334 typical gaps (standard deviations), 0.34 ratio to the US (US = 1)Nicaragua: -1.19 typical gaps (standard deviations), 0.377 ratio to the US (US = 1)Netherlands: 1.38 typical gaps (standard deviations), 0.888 ratio to the US (US = 1)Norway: 1.53 typical gaps (standard deviations), 0.971 ratio to the US (US = 1)Nepal: 0.128 typical gaps (standard deviations), 0.275 ratio to the US (US = 1)New Zealand: 1.45 typical gaps (standard deviations), 0.957 ratio to the US (US = 1)Oman: -0.349 typical gaps (standard deviations), 0.51 ratio to the US (US = 1)Pakistan: -0.658 typical gaps (standard deviations), 0.188 ratio to the US (US = 1)Panama: 0.565 typical gaps (standard deviations), 0.546 ratio to the US (US = 1)Peru: 0.244 typical gaps (standard deviations), 0.546 ratio to the US (US = 1)Philippines: -0.052 typical gaps (standard deviations), 0.374 ratio to the US (US = 1)Poland: 0.922 typical gaps (standard deviations), 0.507 ratio to the US (US = 1)Portugal: 1.15 typical gaps (standard deviations), 0.702 ratio to the US (US = 1)Paraguay: 0.135 typical gaps (standard deviations), 0.398 ratio to the US (US = 1)Qatar: -0.421 typical gaps (standard deviations), 0.828 ratio to the US (US = 1)Romania: 0.595 typical gaps (standard deviations), 0.495 ratio to the US (US = 1)Russian Federation: -1.11 typical gaps (standard deviations), 0.337 ratio to the US (US = 1)Rwanda: -0.532 typical gaps (standard deviations), 0.3 ratio to the US (US = 1)Saudi Arabia: -0.712 typical gaps (standard deviations), 0.504 ratio to the US (US = 1)Sudan: -1.43 typical gaps (standard deviations), 0.265 ratio to the US (US = 1)Senegal: 0.459 typical gaps (standard deviations), 0.39 ratio to the US (US = 1)Singapore: 0.528 typical gaps (standard deviations), 0.798 ratio to the US (US = 1)Sierra Leone: -0.0448 typical gaps (standard deviations), 0.241 ratio to the US (US = 1)El Salvador: -0.354 typical gaps (standard deviations), 0.49 ratio to the US (US = 1)Somalia, Fed. Rep.: -1.29 typical gaps (standard deviations), 0.403 ratio to the US (US = 1)Serbia: -0.129 typical gaps (standard deviations), 0.527 ratio to the US (US = 1)Sao Tome and Principe: 0.469 typical gaps (standard deviations), 0.527 ratio to the US (US = 1)Suriname: 0.64 typical gaps (standard deviations), 0.316 ratio to the US (US = 1)Slovak Republic: 0.851 typical gaps (standard deviations), 0.703 ratio to the US (US = 1)Slovenia: 1.1 typical gaps (standard deviations), 0.706 ratio to the US (US = 1)Sweden: 1.49 typical gaps (standard deviations), 0.874 ratio to the US (US = 1)Eswatini: -0.976 typical gaps (standard deviations), 0.363 ratio to the US (US = 1)Seychelles: 0.921 typical gaps (standard deviations), 0.622 ratio to the US (US = 1)Syrian Arab Republic: -1.29 typical gaps (standard deviations), 0.195 ratio to the US (US = 1)Chad: -1.1 typical gaps (standard deviations), 0.363 ratio to the US (US = 1)Togo: -0.492 typical gaps (standard deviations), 0.362 ratio to the US (US = 1)Thailand: -0.321 typical gaps (standard deviations), 0.292 ratio to the US (US = 1)Tajikistan: -1.22 typical gaps (standard deviations), 0.291 ratio to the US (US = 1)Turkmenistan: -1.33 typical gaps (standard deviations), 0.561 ratio to the US (US = 1)Trinidad and Tobago: 0.718 typical gaps (standard deviations), 0.59 ratio to the US (US = 1)Tunisia: -0.317 typical gaps (standard deviations), 0.301 ratio to the US (US = 1)Turkiye: -0.647 typical gaps (standard deviations), 0.344 ratio to the US (US = 1)Tanzania: -0.365 typical gaps (standard deviations), 0.282 ratio to the US (US = 1)Uganda: -0.676 typical gaps (standard deviations), 0.343 ratio to the US (US = 1)Ukraine: -0.182 typical gaps (standard deviations), 0.302 ratio to the US (US = 1)Uruguay: 1.29 typical gaps (standard deviations), 0.777 ratio to the US (US = 1)United States: 0.906 typical gaps (standard deviations), 1 ratio to the US (US = 1)Uzbekistan: -0.864 typical gaps (standard deviations), 0.269 ratio to the US (US = 1)Viet Nam: -0.692 typical gaps (standard deviations), 0.299 ratio to the US (US = 1)South Africa: 0.602 typical gaps (standard deviations), 0.425 ratio to the US (US = 1)Zambia: 0.0286 typical gaps (standard deviations), 0.319 ratio to the US (US = 1)Zimbabwe: -0.779 typical gaps (standard deviations), 0.69 ratio to the US (US = 1)BRBBTNCHEISLMMRMUSQATSDNSURSYRTKM

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.7021.8e-25163
By rank (Spearman), not adjusted+0.6682.0e-22163
Standard (Pearson), adjusted for national income+0.4856.1e-11163
By rank (Spearman), adjusted for national income+0.3863.9e-7163

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 163 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: +0.217 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.471 (without BLR) to +0.497 (without ZWE). 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: BLR (-0.014).

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 & Pacific17+0.43
Europe & Central Asia48+0.57
Latin America & Caribbean25+0.52
Middle East, North Africa, Afghanistan & Pakistan19+0.64
Sub-Saharan Africa46+0.02

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 third55+0.15
Middle third54+0.38
Richest third54+0.72

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
Christians97+0.46
Muslims45+0.13

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+0.05
Never a European colony20+0.54
Spain19+0.29
United Kingdom48+0.34

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
Nationalist25+0.12
No strong official ideology110+0.46

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 banned25+0.49
No parties banned116+0.42

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 = +0.475 after dropping 4 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.

Loading…

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)

ratio to the US (US = 1)
Years
Denmark DNK1.571.052025, 2023
Switzerland CHE1.541.322025, 2023
Norway NOR1.530.9712025, 2023
Finland FIN1.510.9682025, 2023
Sweden SWE1.490.8742025, 2023
Luxembourg LUX1.481.072025, 2023
New Zealand NZL1.450.9572025, 2023
Ireland IRL1.431.132025, 2023
Australia AUS1.421.012025, 2023
Estonia EST1.40.772025, 2023
Canada CAN1.390.9242025, 2023
Netherlands NLD1.380.8882025, 2023
Iceland ISL1.371.222025, 2023
Germany DEU1.350.8392025, 2023
Japan JPN1.340.7932025, 2023

fh; un_sdg; vdem; wdi; wgi
Feenstra, Robert C., Robert Inklaar and Marcel P. Timmer (2015), "The Next Generation of the Penn World Table", American Economic Review, 105(10), 3150-3182, www.ggdc.net/pwt. Data: Penn World Table version 11.0, Groningen Growth and Development Centre, doi:10.34894/FABVLR.

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.

Price level

Price level of household consumption, compared with the US (Penn World Table)

Groningen Growth and Development Centre, University of Groningen · via DataverseNL · CC BY 4.0 · updated irregular (new versions every few years)

How expensive the things households buy are in a country, compared with the US in the same year, when money is changed at the market exchange rate. A value of 0.5 means a typical basket of goods and services costs about half what it would in the US. Richer countries tend to be more expensive. It comes from the same price comparisons used to adjust GDP for what money buys, so it shares a building block with GDP per capita (PPP). Years in which the Penn World Table flags the price comparison as unreliable are left out. No "better" direction is set.

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 18,622 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 Price level

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

More links with Governance score or Price level