placestats

Environment score vs. Inflation

Holds up after adjusting for income

Across 186 countries, Environment score and Inflation rise and fall together at r = -0.10 (on a scale from −1 to +1, where 0 means no link). There is almost no link to explain.

Comparing countries across the middle half of inflation, 1.42% to 4.59% per year, environment score is worse by 0.00804 typical gaps at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.0107 typical gaps.

Link before adjusting (r)-0.097p = 0.188 · 186 countries
After adjusting for national income-0.131p = 0.074 · likely range [-0.27, +0.01]
p, allowing for regions0.116standard error 0.072 · 7 regions
Check for luck (q)0.032across 14,952 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.

Environment score · typical gaps (standard deviations)link with income -0.20 · independent
Inflation · % per yearlink with income -0.23 · independent

Neither of these is closely tied to national income, so adjusting for income is a real test here, not a formality.

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

Every country as a dot

Environment score · typical gaps (standard deviations) →Inflation · % per year →-1.361.41-6.6%220%Aruba: -0.568 typical gaps (standard deviations), 4.26% per yearAfghanistan: -0.523 typical gaps (standard deviations), -6.6% per yearAngola: 0.161 typical gaps (standard deviations), 20.2% per yearAlbania: 0.126 typical gaps (standard deviations), 2.15% per yearUnited Arab Emirates: -0.764 typical gaps (standard deviations), 1.25% per yearArgentina: -0.619 typical gaps (standard deviations), 220% per yearArmenia: 0.171 typical gaps (standard deviations), 3.31% per yearAntigua and Barbuda: -0.4 typical gaps (standard deviations), 1.37% per yearAustralia: -0.479 typical gaps (standard deviations), 2.87% per yearAustria: 0.246 typical gaps (standard deviations), 3.53% per yearAzerbaijan: -0.3 typical gaps (standard deviations), 5.62% per yearBurundi: -0.0681 typical gaps (standard deviations), 34.1% per yearBelgium: -0.458 typical gaps (standard deviations), 2.47% per yearBenin: 0.414 typical gaps (standard deviations), 1.1% per yearBurkina Faso: -0.0452 typical gaps (standard deviations), -0.586% per yearBangladesh: -0.492 typical gaps (standard deviations), 8.77% per yearBulgaria: 0.511 typical gaps (standard deviations), 4.58% per yearBahrain: -0.998 typical gaps (standard deviations), -0.138% per yearBahamas, The: 0.515 typical gaps (standard deviations), 1.11% per yearBosnia and Herzegovina: -0.345 typical gaps (standard deviations), 3.98% per yearBelarus: -0.309 typical gaps (standard deviations), 6.6% per yearBelize: 0.901 typical gaps (standard deviations), 1.06% per yearBolivia: 0.485 typical gaps (standard deviations), 19.5% per yearBrazil: 0.586 typical gaps (standard deviations), 5.02% per yearBarbados: -0.776 typical gaps (standard deviations), 0.847% per yearBrunei Darussalam: 0.653 typical gaps (standard deviations), -0.303% per yearBhutan: 1.31 typical gaps (standard deviations), 3.56% per yearBotswana: 0.111 typical gaps (standard deviations), 2.66% per yearCentral African Republic: 0.95 typical gaps (standard deviations), 1% per yearCanada: -0.387 typical gaps (standard deviations), 2.07% per yearSwitzerland: -0.314 typical gaps (standard deviations), 0.154% per yearChile: -0.186 typical gaps (standard deviations), 4.21% per yearChina: -0.489 typical gaps (standard deviations), 0.0596% per yearCote d'Ivoire: -0.00841 typical gaps (standard deviations), 0.125% per yearCameroon: 0.149 typical gaps (standard deviations), 3.4% per yearCongo, Dem. Rep.: 0.825 typical gaps (standard deviations), 2.89% per yearCongo, Rep.: 0.909 typical gaps (standard deviations), 2.4% per yearColombia: 0.211 typical gaps (standard deviations), 5.14% per yearComoros: 0.371 typical gaps (standard deviations), 3.25% per yearCabo Verde: -0.266 typical gaps (standard deviations), 2.34% per yearCosta Rica: 0.544 typical gaps (standard deviations), -0.0737% per yearCuracao: -0.691 typical gaps (standard deviations), 2.62% per yearCayman Islands: -0.178 typical gaps (standard deviations), -0.625% per yearCyprus: 0.125 typical gaps (standard deviations), 0.127% per yearCzechia: -0.0912 typical gaps (standard deviations), 2.46% per yearGermany: 0.291 typical gaps (standard deviations), 2.17% per yearDjibouti: -0.758 typical gaps (standard deviations), -0.314% per yearDominica: 0.683 typical gaps (standard deviations), 2.53% per yearDenmark: -0.462 typical gaps (standard deviations), 1.89% per yearDominican Republic: 0.273 typical gaps (standard deviations), 3.87% per yearAlgeria: -0.942 typical gaps (standard deviations), 1.42% per yearEcuador: 0.265 typical gaps (standard deviations), 0.71% per yearEgypt, Arab Rep.: -0.655 typical gaps (standard deviations), 14.1% per yearSpain: 0.143 typical gaps (standard deviations), 2.67% per yearEstonia: 0.148 typical gaps (standard deviations), 4.83% per yearEthiopia: 0.224 typical gaps (standard deviations), 13.2% per yearFinland: 0.21 typical gaps (standard deviations), 0.333% per yearFiji: -0.00523 typical gaps (standard deviations), -1.38% per yearFrance: 0.104 typical gaps (standard deviations), 0.944% per yearMicronesia, Fed. Sts.: 1.41 typical gaps (standard deviations), 5.41% per yearGabon: 0.838 typical gaps (standard deviations), 1.77% per yearUnited Kingdom: -0.167 typical gaps (standard deviations), 3.88% per yearGeorgia: 0.13 typical gaps (standard deviations), 3.87% per yearGhana: 0.0042 typical gaps (standard deviations), 14.2% per yearGuinea: 0.564 typical gaps (standard deviations), 3.57% per yearGambia, The: -0.0847 typical gaps (standard deviations), 11.6% per yearGuinea-Bissau: 1.13 typical gaps (standard deviations), 0.875% per yearEquatorial Guinea: 0.635 typical gaps (standard deviations), 2.92% per yearGreece: 0.286 typical gaps (standard deviations), 2.48% per yearGrenada: -0.00211 typical gaps (standard deviations), 0.61% per yearGuatemala: 0.0972 typical gaps (standard deviations), 1.49% per yearGuyana: 0.279 typical gaps (standard deviations), 3.33% per yearHong Kong SAR, China: 0.654 typical gaps (standard deviations), 1.44% per yearHonduras: 0.44 typical gaps (standard deviations), 4.6% per yearCroatia: 0.352 typical gaps (standard deviations), 3.69% per yearHaiti: -0.248 typical gaps (standard deviations), 28.6% per yearHungary: -0.203 typical gaps (standard deviations), 4.41% per yearIndonesia: -0.0353 typical gaps (standard deviations), 1.91% per yearIndia: -0.45 typical gaps (standard deviations), 2.4% per yearIreland: -0.609 typical gaps (standard deviations), 2.21% per yearIran, Islamic Rep.: -0.896 typical gaps (standard deviations), 42.2% per yearIraq: -1.06 typical gaps (standard deviations), 0.303% per yearIceland: -0.648 typical gaps (standard deviations), 4.09% per yearIsrael: -0.327 typical gaps (standard deviations), 3.04% per yearItaly: -0.13 typical gaps (standard deviations), 1.53% per yearJamaica: 0.249 typical gaps (standard deviations), 4% per yearJordan: -0.817 typical gaps (standard deviations), 1.77% per yearJapan: 0.488 typical gaps (standard deviations), 3.17% per yearKazakhstan: -0.982 typical gaps (standard deviations), 11.4% per yearKenya: -0.239 typical gaps (standard deviations), 4.07% per yearKyrgyz Republic: -0.649 typical gaps (standard deviations), 8.21% per yearCambodia: 0.668 typical gaps (standard deviations), 2.35% per yearKiribati: -0.15 typical gaps (standard deviations), 6.51% per yearSt. Kitts and Nevis: -0.0225 typical gaps (standard deviations), 3.56% per yearKorea, Rep.: 0.0613 typical gaps (standard deviations), 2.12% per yearKuwait: -0.916 typical gaps (standard deviations), 2.36% per yearLao PDR: 0.194 typical gaps (standard deviations), 7.74% per yearLebanon: -0.563 typical gaps (standard deviations), 14.6% per yearLiberia: 0.44 typical gaps (standard deviations), 8.32% per yearLibya: -1.2 typical gaps (standard deviations), 1.84% per yearSt. Lucia: 0.251 typical gaps (standard deviations), 2.03% per yearSri Lanka: 0.377 typical gaps (standard deviations), -4.76% per yearLesotho: -0.0865 typical gaps (standard deviations), 4.27% per yearLithuania: -0.162 typical gaps (standard deviations), 3.79% per yearLuxembourg: 0.228 typical gaps (standard deviations), 2.26% per yearLatvia: 0.159 typical gaps (standard deviations), 3.75% per yearMorocco: -0.723 typical gaps (standard deviations), 0.702% per yearMoldova: -0.6 typical gaps (standard deviations), 7.76% per yearMadagascar: 0.0256 typical gaps (standard deviations), 8.05% per yearMaldives: -0.811 typical gaps (standard deviations), 4.01% per yearMexico: -0.208 typical gaps (standard deviations), 3.81% per yearNorth Macedonia: 0.199 typical gaps (standard deviations), 4.07% per yearMali: -0.342 typical gaps (standard deviations), 3.28% per yearMalta: -0.267 typical gaps (standard deviations), 2.36% per yearMyanmar: -0.0285 typical gaps (standard deviations), 8.83% per yearMontenegro: 0.725 typical gaps (standard deviations), 3.9% per yearMongolia: -0.55 typical gaps (standard deviations), 8.61% per yearMozambique: 0.668 typical gaps (standard deviations), 4.37% per yearMauritania: -0.813 typical gaps (standard deviations), 1.55% per yearMauritius: -0.67 typical gaps (standard deviations), 3.67% per yearMalawi: 0.29 typical gaps (standard deviations), 28.4% per yearMalaysia: -0.0832 typical gaps (standard deviations), 1.38% per yearNamibia: 0.287 typical gaps (standard deviations), 3.51% per yearNiger: -0.0158 typical gaps (standard deviations), -4.45% per yearNigeria: -0.142 typical gaps (standard deviations), 23% per yearNicaragua: 0.266 typical gaps (standard deviations), 2.08% per yearNetherlands: -0.417 typical gaps (standard deviations), 3.2% per yearNorway: -0.266 typical gaps (standard deviations), 3.04% per yearNepal: 0.446 typical gaps (standard deviations), 2.65% per yearNaoero: -1.36 typical gaps (standard deviations), -0.125% per yearNew Zealand: 0.242 typical gaps (standard deviations), 2.84% per yearOman: -0.755 typical gaps (standard deviations), 0.968% per yearPakistan: -0.261 typical gaps (standard deviations), 3.55% per yearPanama: 0.629 typical gaps (standard deviations), -0.188% per yearPeru: 0.321 typical gaps (standard deviations), 1.53% per yearPhilippines: -0.169 typical gaps (standard deviations), 1.66% per yearPalau: 0.451 typical gaps (standard deviations), -0.418% per yearPapua New Guinea: 0.355 typical gaps (standard deviations), 4.42% per yearPoland: 0.261 typical gaps (standard deviations), 3.81% per yearPortugal: 0.0342 typical gaps (standard deviations), 2.34% per yearParaguay: 0.000094 typical gaps (standard deviations), 4.04% per yearWest Bank and Gaza: -0.918 typical gaps (standard deviations), 9.81% per yearQatar: -1.07 typical gaps (standard deviations), 1.27% per yearRomania: -0.023 typical gaps (standard deviations), 7.19% per yearRussian Federation: -0.306 typical gaps (standard deviations), 8.72% per yearRwanda: 0.0329 typical gaps (standard deviations), 5.91% per yearSaudi Arabia: -0.827 typical gaps (standard deviations), 2.04% per yearSudan: -0.493 typical gaps (standard deviations), 139% per yearSenegal: 0.476 typical gaps (standard deviations), 1.46% per yearSingapore: -0.811 typical gaps (standard deviations), 0.903% per yearSolomon Islands: 0.565 typical gaps (standard deviations), 3.36% per yearSierra Leone: 0.222 typical gaps (standard deviations), 7.49% per yearEl Salvador: -0.26 typical gaps (standard deviations), 0.258% per yearSerbia: -0.0414 typical gaps (standard deviations), 3.89% per yearSao Tome and Principe: 0.815 typical gaps (standard deviations), 11% per yearSuriname: 0.523 typical gaps (standard deviations), 9.21% per yearSlovak Republic: 0.381 typical gaps (standard deviations), 4% per yearSlovenia: 0.723 typical gaps (standard deviations), 2.37% per yearSweden: 0.257 typical gaps (standard deviations), 0.679% per yearEswatini: -0.382 typical gaps (standard deviations), 2.6% per yearSint Maarten (Dutch part): -1.14 typical gaps (standard deviations), 2.19% per yearSeychelles: 1.37 typical gaps (standard deviations), 0.298% per yearSyrian Arab Republic: -0.83 typical gaps (standard deviations), 13.4% per yearChad: 0.0555 typical gaps (standard deviations), -3.91% per yearTogo: 0.37 typical gaps (standard deviations), 0.433% per yearThailand: -0.0809 typical gaps (standard deviations), -0.134% per yearTajikistan: -0.207 typical gaps (standard deviations), 3.39% per yearTimor-Leste: 0.626 typical gaps (standard deviations), 0.428% per yearTonga: -0.421 typical gaps (standard deviations), 5.59% per yearTrinidad and Tobago: 0.0462 typical gaps (standard deviations), 0.994% per yearTunisia: -0.741 typical gaps (standard deviations), 5.15% per yearTurkiye: -0.549 typical gaps (standard deviations), 34.9% per yearTuvalu: 0.231 typical gaps (standard deviations), 0.501% per yearTanzania: 1.04 typical gaps (standard deviations), 3.33% per yearUganda: 0.0236 typical gaps (standard deviations), 3.58% per yearUkraine: -0.368 typical gaps (standard deviations), 12.7% per yearUruguay: -0.769 typical gaps (standard deviations), 4.65% per yearUnited States: -0.491 typical gaps (standard deviations), 2.95% per yearUzbekistan: -0.714 typical gaps (standard deviations), 8.8% per yearSt. Vincent and the Grenadines: 0.669 typical gaps (standard deviations), 0.815% per yearViet Nam: -0.262 typical gaps (standard deviations), 3.31% per yearVanuatu: 0.276 typical gaps (standard deviations), 0.656% per yearSamoa: 0.0432 typical gaps (standard deviations), 2.21% per yearSouth Africa: -0.667 typical gaps (standard deviations), 3.21% per yearZambia: 1.13 typical gaps (standard deviations), 13.9% per yearZimbabwe: 0.403 typical gaps (standard deviations), 105% per yearARGBTNFSMLBYNRUSDNSXMSYCZWE

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.0970.188186
By rank (Spearman), not adjusted-0.0660.369186
Standard (Pearson), adjusted for national income-0.1310.074186
By rank (Spearman), adjusted for national income-0.1170.114186

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 186 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: -0.035 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.156 (without ZWE) to -0.098 (without SDN). 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: SDN (+0.033).

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 & Pacific29-0.07
Europe & Central Asia47-0.37
Latin America & Caribbean35-0.25
Middle East, North Africa, Afghanistan & Pakistan22-0.06
Sub-Saharan Africa45-0.18

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 third62-0.15
Middle third62-0.18
Richest third62-0.26

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
Christians110-0.17
Muslims47-0.18

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
France25-0.26
Never a European colony20-0.29
Spain20-0.26
United Kingdom62-0.08

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 = -0.096 after dropping 27 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)

% per year
Years
Micronesia, Fed. Sts. FSM1.415.41%2024, 2022
Seychelles SYC1.370.298%2024, 2025
Bhutan BTN1.313.56%2024, 2025
Guinea-Bissau GNB1.130.875%2024, 2025
Zambia ZMB1.1313.9%2024, 2025
Tanzania TZA1.043.33%2024, 2025
Central African Republic CAF0.951%2024, 2025
Congo, Rep. COG0.9092.4%2024, 2025
Belize BLZ0.9011.06%2024, 2025
Gabon GAB0.8381.77%2024, 2025
Congo, Dem. Rep. COD0.8252.89%2024, 2016
Sao Tome and Principe STP0.81511%2024, 2025
Montenegro MNE0.7253.9%2024, 2025
Slovenia SVN0.7232.37%2024, 2025
Dominica DMA0.6832.53%2024, 2025

wdi
World Bank, World Development Indicators

Sources

Environment score

Environment score

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

The average of 3 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: Forest area, CO2 per capita, Protected land.

Inflation

Inflation, consumer prices (annual %)

World Bank · CC BY 4.0 · updated quarterly

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 14,952 pairs at once, using the Benjamini–Hochberg method. Underlying data last updated DYB 2024. How the country data works · explore Environment score and Inflation

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

More links with Environment score or Inflation