placestats

Contraceptive use (any method) vs. Government effectiveness

Fades after adjusting for income

Across 147 countries, Contraceptive use (any method) and Government effectiveness rise and fall together at r = +0.56 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to +0.21, which could easily be chance (q = 0.28, 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 contraceptive use (any method), 30% to 66.6%, government effectiveness is better by 0.867 points at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.241 points.

Link before adjusting (r)+0.564p = 1.0e-13 · 147 countries
After adjusting for national income+0.212p = 0.010 · likely range [+0.05, +0.36]
p, allowing for regions0.111standard error 0.114 · 7 regions
Check for luck (q)0.282across 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.

Contraceptive use (any method) · %link with income +0.56 · moderate
Government effectiveness · index (approx. -2.5 to 2.5)link with income +0.85 · proxy

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

Every country as a dot

Contraceptive use (any method) · % →Government effectiveness · index (approx. -2.5 to 2.5) →6.9%85.5%-2.022.09Afghanistan: 22.5%, -1.93 index (approx. -2.5 to 2.5)Angola: 13.7%, -0.785 index (approx. -2.5 to 2.5)Albania: 46%, 0.312 index (approx. -2.5 to 2.5)Argentina: 70.1%, 0.184 index (approx. -2.5 to 2.5)Armenia: 57.1%, -0.364 index (approx. -2.5 to 2.5)Australia: 66.9%, 1.81 index (approx. -2.5 to 2.5)Austria: 65.7%, 1.51 index (approx. -2.5 to 2.5)Azerbaijan: 54.9%, 0.166 index (approx. -2.5 to 2.5)Burundi: 28.5%, -1.01 index (approx. -2.5 to 2.5)Belgium: 66.7%, 1.19 index (approx. -2.5 to 2.5)Benin: 22.4%, -0.185 index (approx. -2.5 to 2.5)Burkina Faso: 34%, -0.875 index (approx. -2.5 to 2.5)Bangladesh: 64%, -0.619 index (approx. -2.5 to 2.5)Bosnia and Herzegovina: 46%, -0.635 index (approx. -2.5 to 2.5)Belarus: 52.6%, -0.702 index (approx. -2.5 to 2.5)Belize: 51.4%, -0.129 index (approx. -2.5 to 2.5)Bolivia: 66.5%, -0.61 index (approx. -2.5 to 2.5)Brazil: 80.2%, -0.224 index (approx. -2.5 to 2.5)Barbados: 59.2%, 0.605 index (approx. -2.5 to 2.5)Bhutan: 65.6%, 0.581 index (approx. -2.5 to 2.5)Botswana: 67.4%, 0.417 index (approx. -2.5 to 2.5)Central African Republic: 17.8%, -1.58 index (approx. -2.5 to 2.5)Switzerland: 71.6%, 1.84 index (approx. -2.5 to 2.5)Chile: 76.3%, 0.964 index (approx. -2.5 to 2.5)China: 84.5%, 0.896 index (approx. -2.5 to 2.5)Cote d'Ivoire: 32%, -0.316 index (approx. -2.5 to 2.5)Cameroon: 19.3%, -0.801 index (approx. -2.5 to 2.5)Congo, Dem. Rep.: 28.1%, -1.69 index (approx. -2.5 to 2.5)Congo, Rep.: 30.1%, -1.11 index (approx. -2.5 to 2.5)Colombia: 81%, -0.111 index (approx. -2.5 to 2.5)Comoros: 11.6%, -1.21 index (approx. -2.5 to 2.5)Cabo Verde: 55.8%, 0.415 index (approx. -2.5 to 2.5)Costa Rica: 70.9%, 0.287 index (approx. -2.5 to 2.5)Germany: 80.3%, 1.55 index (approx. -2.5 to 2.5)Djibouti: 19%, -0.493 index (approx. -2.5 to 2.5)Dominican Republic: 62.8%, 0.0746 index (approx. -2.5 to 2.5)Algeria: 53.6%, -0.251 index (approx. -2.5 to 2.5)Ecuador: 77.9%, -0.22 index (approx. -2.5 to 2.5)Egypt, Arab Rep.: 58.5%, -0.0971 index (approx. -2.5 to 2.5)Spain: 62.1%, 1.11 index (approx. -2.5 to 2.5)Estonia: 75.1%, 1.3 index (approx. -2.5 to 2.5)Ethiopia: 36.1%, -0.646 index (approx. -2.5 to 2.5)Finland: 85.5%, 1.82 index (approx. -2.5 to 2.5)Fiji: 35.4%, 0.609 index (approx. -2.5 to 2.5)France: 78.4%, 1.2 index (approx. -2.5 to 2.5)Gabon: 24.8%, -0.567 index (approx. -2.5 to 2.5)United Kingdom: 76.1%, 1.18 index (approx. -2.5 to 2.5)Georgia: 39.3%, 0.456 index (approx. -2.5 to 2.5)Ghana: 36.3%, 0.0596 index (approx. -2.5 to 2.5)Guinea: 10.9%, -0.888 index (approx. -2.5 to 2.5)Gambia, The: 18.9%, -0.536 index (approx. -2.5 to 2.5)Guinea-Bissau: 21.2%, -1.37 index (approx. -2.5 to 2.5)Equatorial Guinea: 12.6%, -1.18 index (approx. -2.5 to 2.5)Guatemala: 60.6%, -0.909 index (approx. -2.5 to 2.5)Guyana: 29.9%, -0.0982 index (approx. -2.5 to 2.5)Hong Kong SAR, China: 66.7%, 1.64 index (approx. -2.5 to 2.5)Honduras: 69.4%, -0.62 index (approx. -2.5 to 2.5)Haiti: 34.3%, -2.02 index (approx. -2.5 to 2.5)Indonesia: 52.6%, 0.18 index (approx. -2.5 to 2.5)India: 66.7%, 0.405 index (approx. -2.5 to 2.5)Ireland: 73.3%, 1.61 index (approx. -2.5 to 2.5)Iran, Islamic Rep.: 77.4%, -0.706 index (approx. -2.5 to 2.5)Iraq: 52.8%, -1.1 index (approx. -2.5 to 2.5)Italy: 65.1%, 0.792 index (approx. -2.5 to 2.5)Jamaica: 60.6%, 0.171 index (approx. -2.5 to 2.5)Jordan: 60.1%, 0.216 index (approx. -2.5 to 2.5)Japan: 58.3%, 2.09 index (approx. -2.5 to 2.5)Kazakhstan: 53%, 0.147 index (approx. -2.5 to 2.5)Kenya: 62.5%, -0.298 index (approx. -2.5 to 2.5)Kyrgyz Republic: 39.4%, -0.889 index (approx. -2.5 to 2.5)Cambodia: 61.9%, -0.294 index (approx. -2.5 to 2.5)Kiribati: 33.6%, -0.434 index (approx. -2.5 to 2.5)Korea, Rep.: 84.2%, 1.49 index (approx. -2.5 to 2.5)Lao PDR: 56.3%, -0.582 index (approx. -2.5 to 2.5)Liberia: 24.9%, -1.25 index (approx. -2.5 to 2.5)Libya: 27.7%, -1.42 index (approx. -2.5 to 2.5)St. Lucia: 55.5%, 0.268 index (approx. -2.5 to 2.5)Sri Lanka: 64.6%, -0.275 index (approx. -2.5 to 2.5)Lesotho: 67.4%, -0.647 index (approx. -2.5 to 2.5)Morocco: 70.8%, 0.176 index (approx. -2.5 to 2.5)Moldova: 56%, 0.258 index (approx. -2.5 to 2.5)Madagascar: 49.7%, -0.863 index (approx. -2.5 to 2.5)Maldives: 18.8%, -0.221 index (approx. -2.5 to 2.5)Mexico: 71.8%, -0.22 index (approx. -2.5 to 2.5)North Macedonia: 59.9%, -0.0323 index (approx. -2.5 to 2.5)Mali: 17.2%, -1.29 index (approx. -2.5 to 2.5)Myanmar: 52.2%, -1.56 index (approx. -2.5 to 2.5)Montenegro: 20.7%, 0.366 index (approx. -2.5 to 2.5)Mongolia: 48.1%, -0.389 index (approx. -2.5 to 2.5)Mozambique: 26.4%, -0.716 index (approx. -2.5 to 2.5)Mauritania: 14.3%, -0.741 index (approx. -2.5 to 2.5)Mauritius: 63.8%, 0.765 index (approx. -2.5 to 2.5)Malawi: 65.6%, -0.726 index (approx. -2.5 to 2.5)Malaysia: 42.8%, 0.915 index (approx. -2.5 to 2.5)Namibia: 56.1%, 0.0993 index (approx. -2.5 to 2.5)Niger: 15.3%, -0.77 index (approx. -2.5 to 2.5)Nigeria: 21.6%, -1.01 index (approx. -2.5 to 2.5)Nicaragua: 80.4%, -1.05 index (approx. -2.5 to 2.5)Netherlands: 73%, 1.75 index (approx. -2.5 to 2.5)Nepal: 57.2%, -0.885 index (approx. -2.5 to 2.5)Oman: 29.7%, 0.568 index (approx. -2.5 to 2.5)Pakistan: 34%, -0.6 index (approx. -2.5 to 2.5)Panama: 50.8%, 0.245 index (approx. -2.5 to 2.5)Peru: 77.3%, -0.2 index (approx. -2.5 to 2.5)Philippines: 58.3%, 0.145 index (approx. -2.5 to 2.5)Papua New Guinea: 36.7%, -0.9 index (approx. -2.5 to 2.5)Poland: 63.2%, 0.673 index (approx. -2.5 to 2.5)Portugal: 73.9%, 0.947 index (approx. -2.5 to 2.5)Paraguay: 68.4%, -0.355 index (approx. -2.5 to 2.5)West Bank and Gaza: 57.3%, -1.1 index (approx. -2.5 to 2.5)Qatar: 37.5%, 1.13 index (approx. -2.5 to 2.5)Russian Federation: 68%, -0.322 index (approx. -2.5 to 2.5)Rwanda: 64.1%, 0.349 index (approx. -2.5 to 2.5)Saudi Arabia: 40%, 0.783 index (approx. -2.5 to 2.5)Sudan: 12.8%, -1.79 index (approx. -2.5 to 2.5)Senegal: 26.5%, 0.234 index (approx. -2.5 to 2.5)Solomon Islands: 29.3%, -0.869 index (approx. -2.5 to 2.5)Sierra Leone: 21.2%, -0.967 index (approx. -2.5 to 2.5)El Salvador: 53.6%, -0.183 index (approx. -2.5 to 2.5)Somalia, Fed. Rep.: 6.9%, -1.95 index (approx. -2.5 to 2.5)Serbia: 62.3%, 0.102 index (approx. -2.5 to 2.5)Sao Tome and Principe: 49.7%, -0.719 index (approx. -2.5 to 2.5)Suriname: 39.1%, -0.454 index (approx. -2.5 to 2.5)Eswatini: 57.7%, -0.781 index (approx. -2.5 to 2.5)Chad: 8.1%, -1.1 index (approx. -2.5 to 2.5)Togo: 23.8%, -0.801 index (approx. -2.5 to 2.5)Thailand: 72.8%, 0.254 index (approx. -2.5 to 2.5)Tajikistan: 29.3%, -0.601 index (approx. -2.5 to 2.5)Turkmenistan: 49.7%, -1.06 index (approx. -2.5 to 2.5)Timor-Leste: 26%, -0.899 index (approx. -2.5 to 2.5)Tonga: 29.3%, -0.0373 index (approx. -2.5 to 2.5)Trinidad and Tobago: 36.5%, 0.111 index (approx. -2.5 to 2.5)Tunisia: 54%, -0.239 index (approx. -2.5 to 2.5)Turkiye: 69.8%, -0.0707 index (approx. -2.5 to 2.5)Tuvalu: 23.7%, -0.691 index (approx. -2.5 to 2.5)Tanzania: 37.6%, -0.292 index (approx. -2.5 to 2.5)Uganda: 43%, -0.35 index (approx. -2.5 to 2.5)Ukraine: 65.5%, -0.599 index (approx. -2.5 to 2.5)United States: 73.9%, 1.36 index (approx. -2.5 to 2.5)Uzbekistan: 58.8%, -0.144 index (approx. -2.5 to 2.5)Viet Nam: 72.8%, -0.0923 index (approx. -2.5 to 2.5)Vanuatu: 49%, -0.817 index (approx. -2.5 to 2.5)Samoa: 16.6%, 0.434 index (approx. -2.5 to 2.5)Kosovo: 66.7%, -0.0613 index (approx. -2.5 to 2.5)South Africa: 54.6%, -0.226 index (approx. -2.5 to 2.5)Zambia: 49.6%, -0.533 index (approx. -2.5 to 2.5)Zimbabwe: 66.8%, -0.988 index (approx. -2.5 to 2.5)AFGDEUFINIRNJPNKORNICQATSDNSOMWSMZWE

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted+0.5641.0e-13147
By rank (Spearman), not adjusted+0.5582.1e-13147
Standard (Pearson), adjusted for national income+0.2120.010147
By rank (Spearman), adjusted for national income+0.2180.008147

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 147 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: +0.352 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from +0.182 (without GUY) to +0.235 (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: GUY (-0.031).

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 & Pacific23-0.36
Europe & Central Asia33+0.19
Latin America & Caribbean24+0.40
Middle East, North Africa, Afghanistan & Pakistan15+0.17
Sub-Saharan Africa45+0.54

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 third49+0.25
Middle third49+0.22
Richest third49+0.44

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
Christians86+0.20
Muslims44+0.02

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
France23+0.17
Never a European colony21+0.07
Spain18+0.45
United Kingdom46+0.32

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 = +0.225 after dropping 1 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 29years. So a link here can’t come from anything about a country that stays the same, such as its history, geography, institutions or culture.

Within countries over time, there is no link that is clearly more than chance (r = -0.040, comparing each country only with itself over the years, and each year only with the same year elsewhere). Whatever the cross-country picture shows, countries whose contraceptive use (any method) moved did not tend to see their government effectiveness move with it.

Across countries (adjusted)+0.212for comparison
Within countries+0.244each country vs itself
…and vs the same year elsewhere-0.040q = 0.830 · 65 countries
Year-on-year changes—q = —
Read with care.
  • Almost all of this indicator's variation is between countries, not within them, so the within-country estimate rests on a small part of the data.
  • Much of the within-country association disappears once shared global year effects are removed, which points to a common worldwide trend rather than a country-level relationship.

499 country-years (one country in one year), 65 countries, 1996–2024, about 8 years each on average. Share of the variation that happens within countries over time: 9% for Contraceptive use (any method), 13% for Government effectiveness. 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

0.20−0.2-80+10years Government effectiveness trails Contraceptive use (any method) →lag -8: r = -0.006 (n = 237)lag -7: r = -0.071 (n = 217)lag -6: r = -0.131 (n = 273)lag -5: r = 0.063 (n = 281)lag -4: r = 0.017 (n = 374)lag -3: r = 0.043 (n = 364)lag -2: r = 0.000 (n = 435)lag -1: r = -0.038 (n = 431)lag +0: r = -0.040 (n = 499)lag +1: r = -0.056 (n = 499)lag +2: r = -0.079 (n = 549)lag +3: r = -0.053 (n = 604)lag +4: r = -0.092 (n = 553)lag +5: r = -0.014 (n = 622)lag +6: r = -0.043 (n = 567)lag +7: r = -0.052 (n = 537)lag +8: r = -0.107 (n = 511)lag +9: r = -0.060 (n = 483)lag +10: r = 0.023 (n = 473)

Same year (lag 0): -0.040. 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 (-0.13 at lag -6) is higher than the same-year one by 0.09. That gap is not a finding. It is the largest of 19 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


%

index (approx. -2.5 to 2.5)
Years
Finland FIN85.5%1.822015, 2024
China CHN84.5%0.8962017, 2024
Korea, Rep. KOR84.2%1.492021, 2024
Colombia COL81%-0.1112015, 2024
Nicaragua NIC80.4%-1.052012, 2024
Germany DEU80.3%1.552011, 2024
Brazil BRA80.2%-0.2242013, 2024
France FRA78.4%1.22010, 2024
Ecuador ECU77.9%-0.222018, 2024
Iran, Islamic Rep. IRN77.4%-0.7062010, 2024
Peru PER77.3%-0.22023, 2024
Chile CHL76.3%0.9642016, 2024
United Kingdom GBR76.1%1.182012, 2024
Estonia EST75.1%1.32014, 2024
United States USA73.9%1.362019, 2024

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

Sources

Contraceptive use (any method)

Contraceptive prevalence, any method (% of married women ages 15-49)

World Bank · CC BY 4.0 · updated quarterly

The share of married women aged 15 to 49 who use any form of birth control, including traditional ones such as withdrawal, from national surveys. Only married women (and women living with a partner) are counted. Most countries have a survey only every few years.

Government effectiveness

Government Effectiveness (estimate)

World Bank · CC BY 4.0 · updated annual

How this was computed

Data used: most recent value in 2010-2025; values come from 2010–2024. 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 14,952 pairs at once, using the Benjamini–Hochberg method. Underlying data last updated DYB 2024. How the country data works · explore Contraceptive use (any method) and Government effectiveness

This page shows that two measures go together. It does not show that Contraceptive use (any method) changes Government effectiveness, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.

More links with Contraceptive use (any method) or Government effectiveness