placestats

Extreme poverty rate vs. Fixed broadband

Fades after adjusting for income

Across 162 countries, Extreme poverty rate and Fixed broadband rise and fall together at r = -0.60 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to +0.14, which could easily be chance (q = 0.15, 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: correlation moves sharply once outliers are trimmed.

Comparing countries across the middle half of extreme poverty rate, 0.4% to 18% of population, fixed broadband is worse by 8.28 per 100 people at the top of that range than the bottom. Comparing only countries with similar national income, the gap reverses, to 1.5 per 100 people the other way.

Link before adjusting (r)-0.603p = 2.2e-17 · 162 countries
After adjusting for national income+0.140p = 0.077 · likely range [-0.02, +0.29]
p, allowing for regions0.034standard error 0.051 · 7 regions
Check for luck (q)0.145across 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.

Extreme poverty rate · % of populationlink with income -0.83 · proxy
Fixed broadband · per 100 peoplelink with income +0.88 · 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

Extreme poverty rate · % of population →Fixed broadband · per 100 people →0%85.3%048.9Angola: 39.3% of population, 0.363 per 100 peopleAlbania: 0.3% of population, 24.9 per 100 peopleUnited Arab Emirates: 0% of population, 40.8 per 100 peopleArgentina: 1% of population, 26.1 per 100 peopleArmenia: 0.8% of population, 20.3 per 100 peopleAustralia: 0.9% of population, 36.5 per 100 peopleAustria: 0.5% of population, 30.1 per 100 peopleBurundi: 74.2% of population, 0.0203 per 100 peopleBelgium: 0.1% of population, 44.2 per 100 peopleBenin: 27.2% of population, 0.277 per 100 peopleBurkina Faso: 42.1% of population, 0.851 per 100 peopleBangladesh: 5.9% of population, 8.09 per 100 peopleBulgaria: 1% of population, 37 per 100 peopleBosnia and Herzegovina: 0.3% of population, 29.4 per 100 peopleBelarus: 0% of population, 36.3 per 100 peopleBelize: 1% of population, 9.75 per 100 peopleBolivia: 2.1% of population, 12.1 per 100 peopleBrazil: 3% of population, 24.1 per 100 peopleBarbados: 1.7% of population, 37.5 per 100 peopleBhutan: 0% of population, 2.92 per 100 peopleBotswana: 21.4% of population, 7.44 per 100 peopleCentral African Republic: 71.6% of population, 0.0161 per 100 peopleCanada: 0.3% of population, 42.5 per 100 peopleSwitzerland: 0.2% of population, 47 per 100 peopleChile: 0.4% of population, 23.7 per 100 peopleChina: 0% of population, 47.2 per 100 peopleCote d'Ivoire: 20.8% of population, 1.6 per 100 peopleCameroon: 26.7% of population, 2.13 per 100 peopleCongo, Dem. Rep.: 85.3% of population, 0.032 per 100 peopleCongo, Rep.: 39.2% of population, 1.27 per 100 peopleColombia: 8.5% of population, 17.2 per 100 peopleComoros: 5.1% of population, 0.388 per 100 peopleCabo Verde: 14.6% of population, 8.31 per 100 peopleCosta Rica: 0.8% of population, 23.3 per 100 peopleCyprus: 0% of population, 37.6 per 100 peopleCzechia: 0% of population, 38.9 per 100 peopleGermany: 0.7% of population, 45.6 per 100 peopleDjibouti: 25.4% of population, 1.47 per 100 peopleDenmark: 0.4% of population, 43.4 per 100 peopleDominican Republic: 0.8% of population, 11.2 per 100 peopleAlgeria: 0% of population, 13.3 per 100 peopleEcuador: 3.4% of population, 17.2 per 100 peopleEgypt, Arab Rep.: 1.4% of population, 11.7 per 100 peopleSpain: 0.8% of population, 39.2 per 100 peopleEstonia: 0.3% of population, 35.4 per 100 peopleEthiopia: 38.6% of population, 0.594 per 100 peopleFinland: 0.2% of population, 36.5 per 100 peopleFiji: 4.7% of population, 1.8 per 100 peopleFrance: 0.1% of population, 48.9 per 100 peopleMicronesia, Fed. Sts.: 26.1% of population, 5.82 per 100 peopleGabon: 3.8% of population, 4.69 per 100 peopleUnited Kingdom: 0.4% of population, 42.2 per 100 peopleGeorgia: 4.2% of population, 30.4 per 100 peopleGhana: 39% of population, 0.665 per 100 peopleGuinea: 11.7% of population, 0.00628 per 100 peopleGambia, The: 22% of population, 0.519 per 100 peopleGuinea-Bissau: 39.9% of population, 0.386 per 100 peopleEquatorial Guinea: 8.8% of population, 0.101 per 100 peopleGreece: 0.6% of population, 44.7 per 100 peopleGrenada: 0.8% of population, 29.8 per 100 peopleGuatemala: 9.7% of population, 5.34 per 100 peopleHonduras: 15.7% of population, 4.58 per 100 peopleCroatia: 0.3% of population, 29.6 per 100 peopleHaiti: 40.4% of population, 0.307 per 100 peopleHungary: 0.9% of population, 37.5 per 100 peopleIndonesia: 4% of population, 4.92 per 100 peopleIndia: 5.3% of population, 3.15 per 100 peopleIreland: 0.1% of population, 32.3 per 100 peopleIran, Islamic Rep.: 2.5% of population, 12.1 per 100 peopleIraq: 0.5% of population, 17.6 per 100 peopleIceland: 0.1% of population, 37.5 per 100 peopleIsrael: 0.4% of population, 29.2 per 100 peopleItaly: 0.9% of population, 31.8 per 100 peopleJamaica: 1.4% of population, 16 per 100 peopleJordan: 0.1% of population, 7.02 per 100 peopleJapan: 1.2% of population, 38.6 per 100 peopleKazakhstan: 0% of population, 15.3 per 100 peopleKenya: 45.5% of population, 3.04 per 100 peopleKyrgyz Republic: 2.2% of population, 7.8 per 100 peopleKiribati: 0.9% of population, 0.0349 per 100 peopleKorea, Rep.: 0.1% of population, 47.8 per 100 peopleLao PDR: 7.1% of population, 2.72 per 100 peopleLebanon: 5.8% of population, 7.29 per 100 peopleLiberia: 33.6% of population, 0.275 per 100 peopleSt. Lucia: 0.1% of population, 13.6 per 100 peopleSri Lanka: 2.7% of population, 8.47 per 100 peopleLesotho: 41.9% of population, 0.379 per 100 peopleLithuania: 1.1% of population, 27.8 per 100 peopleLuxembourg: 0.1% of population, 40.3 per 100 peopleLatvia: 0.4% of population, 25.8 per 100 peopleMorocco: 3.7% of population, 7.3 per 100 peopleMoldova: 0.1% of population, 29.6 per 100 peopleMadagascar: 69.2% of population, 0.124 per 100 peopleMaldives: 0% of population, 19.6 per 100 peopleMexico: 1.6% of population, 21.7 per 100 peopleMarshall Islands: 2.1% of population, 2.35 per 100 peopleNorth Macedonia: 3.9% of population, 29.9 per 100 peopleMali: 36.1% of population, 0.774 per 100 peopleMalta: 0.4% of population, 44.5 per 100 peopleMyanmar: 10.3% of population, 2.87 per 100 peopleMontenegro: 2.5% of population, 32.3 per 100 peopleMongolia: 0.4% of population, 15.8 per 100 peopleMozambique: 81.4% of population, 0.142 per 100 peopleMauritania: 10.2% of population, 0.947 per 100 peopleMauritius: 0.5% of population, 28 per 100 peopleMalawi: 75.4% of population, 0.0864 per 100 peopleMalaysia: 0% of population, 13.5 per 100 peopleNamibia: 22.9% of population, 2.83 per 100 peopleNiger: 60.5% of population, 0.111 per 100 peopleNigeria: 41.8% of population, 0.0787 per 100 peopleNicaragua: 6.6% of population, 5.78 per 100 peopleNetherlands: 0.1% of population, 43 per 100 peopleNorway: 0.2% of population, 45.2 per 100 peopleNepal: 2.4% of population, 10.1 per 100 peopleNaoero: 9.7% of population, 9.96 per 100 peoplePakistan: 23% of population, 1.47 per 100 peoplePanama: 3.1% of population, 18.1 per 100 peoplePeru: 5.1% of population, 11.7 per 100 peoplePhilippines: 5.3% of population, 7.14 per 100 peoplePoland: 0.2% of population, 25.4 per 100 peoplePortugal: 0.4% of population, 45.2 per 100 peopleParaguay: 2.1% of population, 12.9 per 100 peopleWest Bank and Gaza: 2.1% of population, 8.16 per 100 peopleQatar: 0% of population, 11.8 per 100 peopleRomania: 0.7% of population, 35.8 per 100 peopleRussian Federation: 0.1% of population, 27.1 per 100 peopleRwanda: 38.6% of population, 0.596 per 100 peopleSudan: 10.1% of population, 0.0604 per 100 peopleSenegal: 17.9% of population, 4.04 per 100 peopleSolomon Islands: 40.3% of population, 0.107 per 100 peopleSierra Leone: 41.5% of population, 0.00227 per 100 peopleEl Salvador: 4.6% of population, 12.5 per 100 peopleSerbia: 1.1% of population, 33.4 per 100 peopleSao Tome and Principe: 13% of population, 2.99 per 100 peopleSuriname: 2.2% of population, 18.8 per 100 peopleSlovak Republic: 0.5% of population, 33.8 per 100 peopleSlovenia: 0% of population, 34.2 per 100 peopleSweden: 0.8% of population, 40.6 per 100 peopleEswatini: 44.5% of population, 2.51 per 100 peopleSeychelles: 0.7% of population, 31.6 per 100 peopleSyrian Arab Republic: 18% of population, 6.86 per 100 peopleChad: 39.5% of population, 0 per 100 peopleTogo: 34.7% of population, 1.42 per 100 peopleThailand: 0% of population, 14.9 per 100 peopleTajikistan: 6.1% of population, 0.984 per 100 peopleTimor-Leste: 44% of population, 0.006 per 100 peopleTonga: 0.4% of population, 8.17 per 100 peopleTunisia: 0.7% of population, 15 per 100 peopleTurkiye: 0.2% of population, 23.4 per 100 peopleTuvalu: 9% of population, 4.52 per 100 peopleTanzania: 51.3% of population, 0.246 per 100 peopleUganda: 59.8% of population, 0.208 per 100 peopleUkraine: 0% of population, 21.7 per 100 peopleUruguay: 0.2% of population, 33 per 100 peopleUnited States: 1.1% of population, 38.9 per 100 peopleUzbekistan: 2.3% of population, 34.7 per 100 peopleViet Nam: 1.6% of population, 23.7 per 100 peopleVanuatu: 19.5% of population, 1.16 per 100 peopleSamoa: 4.5% of population, 0.878 per 100 peopleSouth Africa: 17.4% of population, 5.35 per 100 peopleZambia: 71.7% of population, 0.79 per 100 peopleZimbabwe: 49.2% of population, 1.94 per 100 peopleBTNCHNCODFRAKIRKORMHLMOZMWI

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.6032.2e-17162
By rank (Spearman), not adjusted-0.8053.9e-38162
Standard (Pearson), adjusted for national income+0.1400.077162
By rank (Spearman), adjusted for national income-0.2080.008162

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 162 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: +0.463 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.120 (without MOZ) to +0.175 (without QAT). The bar above shows that range on a scale from −1 to +1, with the solid line at the full result. The single country that moves r most: QAT (+0.035).

Fragile: this link may not hold up.
  • correlation moves sharply once outliers are trimmed
  • sign flips once outliers are trimmed
  • 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 & Pacific23+0.22
Europe & Central Asia46-0.04
Latin America & Caribbean24+0.01
Middle East, North Africa, Afghanistan & Pakistan16-0.19
Sub-Saharan Africa45-0.00

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 third54-0.28
Middle third54-0.26
Richest third54-0.01

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
Christians103+0.19
Muslims39-0.18

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
France24+0.08
Never a European colony16+0.09
Spain20+0.02
United Kingdom48-0.05

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 = -0.019 after dropping 13 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 27years. So a link here can’t come from anything about a country that stays the same, such as its history, geography, institutions or culture.

The link also shows up within countries over time (r = +0.447). It holds even when looking only at changes from one year to the next (r = +0.151). This is the strongest kind of evidence available here: it holds when each country is compared only with itself, and it is not just a product of shared trends.

Across countries (adjusted)+0.140for comparison
Within countries-0.242each country vs itself
…and vs the same year elsewhere+0.447q = 0.001 · 89 countries
Year-on-year changes+0.151q = 1.0e-5
The direction flips. Comparing each country only with itself gives -0.24. Also taking out what happened to the whole world each year gives +0.45. So the first figure was picking up a trend both measures share with worldwide progress, not a link between them.
Read with care.
  • The association is much weaker in year-on-year changes than in levels, which points to shared country-specific trends.

1,529 country-years (one country in one year), 89 countries, 1998–2024, about 17 years each on average. Share of the variation that happens within countries over time: 22% for Extreme poverty rate, 45% for Fixed broadband. The margins of error allow for each country appearing many times, and for each year’s value being close to the year before.

Year-to-year changes are a cautious test, not a final answer. Looking only at changes from one year to the next removes each country’s own trends. But it also makes measurement mistakes louder, which pulls the results toward zero. A near-zero result here is weak evidence of no link, not proof.

With one measure years behind the other

0.60−0.6-100+10years Fixed broadband trails Extreme poverty rate →lag -10: r = 0.403 (n = 860)lag -9: r = 0.426 (n = 924)lag -8: r = 0.460 (n = 998)lag -7: r = 0.476 (n = 1,066)lag -6: r = 0.487 (n = 1,137)lag -5: r = 0.489 (n = 1,211)lag -4: r = 0.501 (n = 1,281)lag -3: r = 0.509 (n = 1,342)lag -2: r = 0.508 (n = 1,411)lag -1: r = 0.521 (n = 1,472)lag +0: r = 0.447 (n = 1,529)lag +1: r = 0.407 (n = 1,560)lag +2: r = 0.432 (n = 1,560)lag +3: r = 0.393 (n = 1,532)lag +4: r = 0.337 (n = 1,497)lag +5: r = 0.284 (n = 1,488)lag +6: r = 0.240 (n = 1,444)lag +7: r = 0.203 (n = 1,392)lag +8: r = 0.176 (n = 1,368)lag +9: r = 0.151 (n = 1,323)lag +10: r = 0.131 (n = 1,260)

Same year (lag 0): +0.447. A peak away from zero does not show which comes first. These series change slowly — this year’s value is close to last year’s. That makes the curve smooth and nearly symmetric, whatever produced the data. Even a sharp peak at one lag (a gap of some years) would not prove that one measure changes the other.

The largest value on this curve (+0.52 at lag -1) is higher than the same-year one by 0.07. That gap is not a finding. It is the largest of 21 closely related estimates, and picking the biggest of many tests always makes it look bigger. That is exactly why nothing on this site is ranked or chosen by lag.

The data


% of population
per 100 people		Years
Congo, Dem. Rep. COD85.3%0.0322020, 2024
Mozambique MOZ81.4%0.1422022, 2024
Malawi MWI75.4%0.08642019, 2024
Burundi BDI74.2%0.02032020, 2023
Zambia ZMB71.7%0.792022, 2024
Central African Republic CAF71.6%0.01612021, 2022
Madagascar MDG69.2%0.1242021, 2023
Niger NER60.5%0.1112021, 2024
Uganda UGA59.8%0.2082019, 2024
Tanzania TZA51.3%0.2462018, 2024
Zimbabwe ZWE49.2%1.942019, 2024
Kenya KEN45.5%3.042022, 2024
Eswatini SWZ44.5%2.512016, 2024
Timor-Leste TLS44%0.0062014, 2024
Burkina Faso BFA42.1%0.8512021, 2024

World Bank, World Development Indicators
World Bank, World Development Indicators

Sources

Extreme poverty rate

Poverty headcount ratio at $3.00 a day (2021 PPP) (% of population)

World Bank · CC BY 4.0 · updated quarterly

Fixed broadband

Fixed broadband subscriptions (per 100 people)

International Telecommunication Union · CC BY 4.0 · updated quarterly

Subscriptions, not people. A household line counts once, however many people use it. A country that went straight to mobile data can be well connected with few of these lines. Internet users, already on the site, is the measure of people.

How this was computed

Data used: most recent value in 2010-2025; values come from 2010–2025. To adjust for income, each measure is first predicted from GDP per person (in percentage terms, on a log scale) with a straight-line fit. Only what is left over is then compared. This is called a partial correlation. The line is drawn the standard way (ordinary least squares), which picks the line that comes closest to all the countries at once. The error margins allow for countries in the same region resembling each other, using 7 World Bank regions. The q-value corrects for testing all 12,497 pairs at once, using the Benjamini–Hochberg method. Underlying data last updated DYB 2024. How the country data works · explore Extreme poverty rate and Fixed broadband

This page shows that two measures go together. It does not show that Extreme poverty rate changes Fixed broadband, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.

More links with Extreme poverty rate or Fixed broadband