placestats

Abortion rate (estimate) vs. Government effectiveness

Holds up after adjusting for income

Across 142 countries, Abortion rate (estimate) and Government effectiveness rise and fall together at r = -0.45 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to -0.20 (q = 0.029, allowing for the many pairs tested). Much of the first figure is that both measures rise with national income, but a very weak negative link remains. Caution: direction is not consistent across regions.

Comparing countries across the middle half of abortion rate (estimate), 15.3 to 36.4 per 1,000 women aged 15-49, government effectiveness is worse by 0.616 points at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.167 points.

Link before adjusting (r)-0.450p = 2.0e-8 · 142 countries
After adjusting for national income-0.196p = 0.020 · likely range [-0.35, -0.03]
p, allowing for regions0.002standard error 0.037 · 7 regions
Check for luck (q)0.029across 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.

Abortion rate (estimate) · per 1,000 women aged 15-49link with income -0.50 · 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

Abortion rate (estimate) · per 1,000 women aged 15-49 →Government effectiveness · index (approx. -2.5 to 2.5) →580.3-2.022.28Angola: 33.4 per 1,000 women aged 15-49, -0.785 index (approx. -2.5 to 2.5)Albania: 9.45 per 1,000 women aged 15-49, 0.312 index (approx. -2.5 to 2.5)Argentina: 33.2 per 1,000 women aged 15-49, 0.184 index (approx. -2.5 to 2.5)Armenia: 42.8 per 1,000 women aged 15-49, -0.364 index (approx. -2.5 to 2.5)Australia: 16.1 per 1,000 women aged 15-49, 1.81 index (approx. -2.5 to 2.5)Azerbaijan: 71.9 per 1,000 women aged 15-49, 0.166 index (approx. -2.5 to 2.5)Burundi: 25.6 per 1,000 women aged 15-49, -1.01 index (approx. -2.5 to 2.5)Belgium: 7.78 per 1,000 women aged 15-49, 1.19 index (approx. -2.5 to 2.5)Benin: 31.9 per 1,000 women aged 15-49, -0.185 index (approx. -2.5 to 2.5)Burkina Faso: 30.5 per 1,000 women aged 15-49, -0.875 index (approx. -2.5 to 2.5)Bangladesh: 35.3 per 1,000 women aged 15-49, -0.619 index (approx. -2.5 to 2.5)Bulgaria: 10.2 per 1,000 women aged 15-49, 0.0428 index (approx. -2.5 to 2.5)Bosnia and Herzegovina: 11 per 1,000 women aged 15-49, -0.635 index (approx. -2.5 to 2.5)Belarus: 10.5 per 1,000 women aged 15-49, -0.702 index (approx. -2.5 to 2.5)Belize: 31.8 per 1,000 women aged 15-49, -0.129 index (approx. -2.5 to 2.5)Bolivia: 37.8 per 1,000 women aged 15-49, -0.61 index (approx. -2.5 to 2.5)Brazil: 32.3 per 1,000 women aged 15-49, -0.224 index (approx. -2.5 to 2.5)Barbados: 44.6 per 1,000 women aged 15-49, 0.605 index (approx. -2.5 to 2.5)Bhutan: 32.1 per 1,000 women aged 15-49, 0.581 index (approx. -2.5 to 2.5)Botswana: 30.7 per 1,000 women aged 15-49, 0.417 index (approx. -2.5 to 2.5)Central African Republic: 26.8 per 1,000 women aged 15-49, -1.58 index (approx. -2.5 to 2.5)Canada: 11.6 per 1,000 women aged 15-49, 1.76 index (approx. -2.5 to 2.5)Switzerland: 5.18 per 1,000 women aged 15-49, 1.84 index (approx. -2.5 to 2.5)Chile: 35.9 per 1,000 women aged 15-49, 0.964 index (approx. -2.5 to 2.5)China: 49 per 1,000 women aged 15-49, 0.896 index (approx. -2.5 to 2.5)Cote d'Ivoire: 35.3 per 1,000 women aged 15-49, -0.316 index (approx. -2.5 to 2.5)Cameroon: 33.9 per 1,000 women aged 15-49, -0.801 index (approx. -2.5 to 2.5)Congo, Dem. Rep.: 32.7 per 1,000 women aged 15-49, -1.69 index (approx. -2.5 to 2.5)Congo, Rep.: 44.4 per 1,000 women aged 15-49, -1.11 index (approx. -2.5 to 2.5)Colombia: 27.1 per 1,000 women aged 15-49, -0.111 index (approx. -2.5 to 2.5)Comoros: 30.6 per 1,000 women aged 15-49, -1.21 index (approx. -2.5 to 2.5)Cabo Verde: 49.1 per 1,000 women aged 15-49, 0.415 index (approx. -2.5 to 2.5)Costa Rica: 21.1 per 1,000 women aged 15-49, 0.287 index (approx. -2.5 to 2.5)Czechia: 6.86 per 1,000 women aged 15-49, 1.18 index (approx. -2.5 to 2.5)Germany: 5.77 per 1,000 women aged 15-49, 1.55 index (approx. -2.5 to 2.5)Djibouti: 20.6 per 1,000 women aged 15-49, -0.493 index (approx. -2.5 to 2.5)Denmark: 11.6 per 1,000 women aged 15-49, 1.91 index (approx. -2.5 to 2.5)Dominican Republic: 36.6 per 1,000 women aged 15-49, 0.0746 index (approx. -2.5 to 2.5)Ecuador: 27.9 per 1,000 women aged 15-49, -0.22 index (approx. -2.5 to 2.5)Spain: 8.73 per 1,000 women aged 15-49, 1.11 index (approx. -2.5 to 2.5)Estonia: 15.9 per 1,000 women aged 15-49, 1.3 index (approx. -2.5 to 2.5)Ethiopia: 24.4 per 1,000 women aged 15-49, -0.646 index (approx. -2.5 to 2.5)Finland: 8.09 per 1,000 women aged 15-49, 1.82 index (approx. -2.5 to 2.5)France: 14.4 per 1,000 women aged 15-49, 1.2 index (approx. -2.5 to 2.5)Gabon: 40.6 per 1,000 women aged 15-49, -0.567 index (approx. -2.5 to 2.5)United Kingdom: 13.1 per 1,000 women aged 15-49, 1.18 index (approx. -2.5 to 2.5)Georgia: 80.3 per 1,000 women aged 15-49, 0.456 index (approx. -2.5 to 2.5)Ghana: 36.6 per 1,000 women aged 15-49, 0.0596 index (approx. -2.5 to 2.5)Guinea: 26.4 per 1,000 women aged 15-49, -0.888 index (approx. -2.5 to 2.5)Gambia, The: 16.4 per 1,000 women aged 15-49, -0.536 index (approx. -2.5 to 2.5)Guinea-Bissau: 58.5 per 1,000 women aged 15-49, -1.37 index (approx. -2.5 to 2.5)Greece: 15 per 1,000 women aged 15-49, 0.191 index (approx. -2.5 to 2.5)Guatemala: 18.9 per 1,000 women aged 15-49, -0.909 index (approx. -2.5 to 2.5)Guyana: 36.4 per 1,000 women aged 15-49, -0.0982 index (approx. -2.5 to 2.5)Hong Kong SAR, China: 13 per 1,000 women aged 15-49, 1.64 index (approx. -2.5 to 2.5)Honduras: 20.7 per 1,000 women aged 15-49, -0.62 index (approx. -2.5 to 2.5)Croatia: 16.5 per 1,000 women aged 15-49, 0.71 index (approx. -2.5 to 2.5)Haiti: 38.1 per 1,000 women aged 15-49, -2.02 index (approx. -2.5 to 2.5)Hungary: 13.6 per 1,000 women aged 15-49, 0.502 index (approx. -2.5 to 2.5)Indonesia: 25 per 1,000 women aged 15-49, 0.18 index (approx. -2.5 to 2.5)India: 48 per 1,000 women aged 15-49, 0.405 index (approx. -2.5 to 2.5)Iceland: 12.7 per 1,000 women aged 15-49, 1.65 index (approx. -2.5 to 2.5)Italy: 18.9 per 1,000 women aged 15-49, 0.792 index (approx. -2.5 to 2.5)Jamaica: 38.1 per 1,000 women aged 15-49, 0.171 index (approx. -2.5 to 2.5)Japan: 6 per 1,000 women aged 15-49, 2.09 index (approx. -2.5 to 2.5)Kazakhstan: 47 per 1,000 women aged 15-49, 0.147 index (approx. -2.5 to 2.5)Kenya: 42.7 per 1,000 women aged 15-49, -0.298 index (approx. -2.5 to 2.5)Kyrgyz Republic: 31.2 per 1,000 women aged 15-49, -0.889 index (approx. -2.5 to 2.5)Cambodia: 45 per 1,000 women aged 15-49, -0.294 index (approx. -2.5 to 2.5)Korea, Rep.: 21 per 1,000 women aged 15-49, 1.49 index (approx. -2.5 to 2.5)Lao PDR: 34 per 1,000 women aged 15-49, -0.582 index (approx. -2.5 to 2.5)Liberia: 42.3 per 1,000 women aged 15-49, -1.25 index (approx. -2.5 to 2.5)St. Lucia: 37.2 per 1,000 women aged 15-49, 0.268 index (approx. -2.5 to 2.5)Sri Lanka: 27.9 per 1,000 women aged 15-49, -0.275 index (approx. -2.5 to 2.5)Lesotho: 23.5 per 1,000 women aged 15-49, -0.647 index (approx. -2.5 to 2.5)Lithuania: 7.15 per 1,000 women aged 15-49, 1.2 index (approx. -2.5 to 2.5)Latvia: 10.3 per 1,000 women aged 15-49, 0.743 index (approx. -2.5 to 2.5)Moldova: 18.2 per 1,000 women aged 15-49, 0.258 index (approx. -2.5 to 2.5)Madagascar: 59.9 per 1,000 women aged 15-49, -0.863 index (approx. -2.5 to 2.5)Maldives: 42 per 1,000 women aged 15-49, -0.221 index (approx. -2.5 to 2.5)Mexico: 30.6 per 1,000 women aged 15-49, -0.22 index (approx. -2.5 to 2.5)North Macedonia: 14.3 per 1,000 women aged 15-49, -0.0323 index (approx. -2.5 to 2.5)Mali: 22.5 per 1,000 women aged 15-49, -1.29 index (approx. -2.5 to 2.5)Myanmar: 26 per 1,000 women aged 15-49, -1.56 index (approx. -2.5 to 2.5)Montenegro: 5.89 per 1,000 women aged 15-49, 0.366 index (approx. -2.5 to 2.5)Mongolia: 21 per 1,000 women aged 15-49, -0.389 index (approx. -2.5 to 2.5)Mozambique: 40.4 per 1,000 women aged 15-49, -0.716 index (approx. -2.5 to 2.5)Mauritania: 17 per 1,000 women aged 15-49, -0.741 index (approx. -2.5 to 2.5)Malawi: 31.4 per 1,000 women aged 15-49, -0.726 index (approx. -2.5 to 2.5)Namibia: 29.2 per 1,000 women aged 15-49, 0.0993 index (approx. -2.5 to 2.5)Niger: 15.2 per 1,000 women aged 15-49, -0.77 index (approx. -2.5 to 2.5)Nigeria: 32.7 per 1,000 women aged 15-49, -1.01 index (approx. -2.5 to 2.5)Nicaragua: 15.3 per 1,000 women aged 15-49, -1.05 index (approx. -2.5 to 2.5)Netherlands: 7.15 per 1,000 women aged 15-49, 1.75 index (approx. -2.5 to 2.5)Norway: 10.8 per 1,000 women aged 15-49, 1.84 index (approx. -2.5 to 2.5)Nepal: 41.3 per 1,000 women aged 15-49, -0.885 index (approx. -2.5 to 2.5)New Zealand: 12 per 1,000 women aged 15-49, 1.85 index (approx. -2.5 to 2.5)Pakistan: 43.1 per 1,000 women aged 15-49, -0.6 index (approx. -2.5 to 2.5)Panama: 29.6 per 1,000 women aged 15-49, 0.245 index (approx. -2.5 to 2.5)Peru: 42.4 per 1,000 women aged 15-49, -0.2 index (approx. -2.5 to 2.5)Philippines: 36 per 1,000 women aged 15-49, 0.145 index (approx. -2.5 to 2.5)Papua New Guinea: 36.4 per 1,000 women aged 15-49, -0.9 index (approx. -2.5 to 2.5)Poland: 10.5 per 1,000 women aged 15-49, 0.673 index (approx. -2.5 to 2.5)Puerto Rico (US): 31.5 per 1,000 women aged 15-49, -0.255 index (approx. -2.5 to 2.5)Portugal: 6.77 per 1,000 women aged 15-49, 0.947 index (approx. -2.5 to 2.5)Paraguay: 34 per 1,000 women aged 15-49, -0.355 index (approx. -2.5 to 2.5)Romania: 31 per 1,000 women aged 15-49, 0.418 index (approx. -2.5 to 2.5)Russian Federation: 45.7 per 1,000 women aged 15-49, -0.322 index (approx. -2.5 to 2.5)Rwanda: 27.8 per 1,000 women aged 15-49, 0.349 index (approx. -2.5 to 2.5)Senegal: 15.3 per 1,000 women aged 15-49, 0.234 index (approx. -2.5 to 2.5)Singapore: 5 per 1,000 women aged 15-49, 2.28 index (approx. -2.5 to 2.5)Solomon Islands: 32.1 per 1,000 women aged 15-49, -0.869 index (approx. -2.5 to 2.5)Sierra Leone: 45.4 per 1,000 women aged 15-49, -0.967 index (approx. -2.5 to 2.5)El Salvador: 24 per 1,000 women aged 15-49, -0.183 index (approx. -2.5 to 2.5)Somalia, Fed. Rep.: 28.7 per 1,000 women aged 15-49, -1.95 index (approx. -2.5 to 2.5)Serbia: 12.7 per 1,000 women aged 15-49, 0.102 index (approx. -2.5 to 2.5)Sao Tome and Principe: 38.5 per 1,000 women aged 15-49, -0.719 index (approx. -2.5 to 2.5)Suriname: 31 per 1,000 women aged 15-49, -0.454 index (approx. -2.5 to 2.5)Slovak Republic: 7.15 per 1,000 women aged 15-49, 0.658 index (approx. -2.5 to 2.5)Slovenia: 8.13 per 1,000 women aged 15-49, 1.09 index (approx. -2.5 to 2.5)Sweden: 17.3 per 1,000 women aged 15-49, 1.77 index (approx. -2.5 to 2.5)Eswatini: 29.3 per 1,000 women aged 15-49, -0.781 index (approx. -2.5 to 2.5)Chad: 17.4 per 1,000 women aged 15-49, -1.1 index (approx. -2.5 to 2.5)Togo: 32.1 per 1,000 women aged 15-49, -0.801 index (approx. -2.5 to 2.5)Thailand: 25 per 1,000 women aged 15-49, 0.254 index (approx. -2.5 to 2.5)Tajikistan: 25.8 per 1,000 women aged 15-49, -0.601 index (approx. -2.5 to 2.5)Turkmenistan: 18.9 per 1,000 women aged 15-49, -1.06 index (approx. -2.5 to 2.5)Timor-Leste: 34 per 1,000 women aged 15-49, -0.899 index (approx. -2.5 to 2.5)Tonga: 25 per 1,000 women aged 15-49, -0.0373 index (approx. -2.5 to 2.5)Trinidad and Tobago: 48.3 per 1,000 women aged 15-49, 0.111 index (approx. -2.5 to 2.5)Tanzania: 37.5 per 1,000 women aged 15-49, -0.292 index (approx. -2.5 to 2.5)Uganda: 43 per 1,000 women aged 15-49, -0.35 index (approx. -2.5 to 2.5)Ukraine: 20.5 per 1,000 women aged 15-49, -0.599 index (approx. -2.5 to 2.5)Uruguay: 11.4 per 1,000 women aged 15-49, 0.69 index (approx. -2.5 to 2.5)United States: 11.9 per 1,000 women aged 15-49, 1.36 index (approx. -2.5 to 2.5)Uzbekistan: 22.7 per 1,000 women aged 15-49, -0.144 index (approx. -2.5 to 2.5)Viet Nam: 64 per 1,000 women aged 15-49, -0.0923 index (approx. -2.5 to 2.5)Vanuatu: 39.2 per 1,000 women aged 15-49, -0.817 index (approx. -2.5 to 2.5)Samoa: 42.8 per 1,000 women aged 15-49, 0.434 index (approx. -2.5 to 2.5)South Africa: 29.7 per 1,000 women aged 15-49, -0.226 index (approx. -2.5 to 2.5)Zambia: 34.6 per 1,000 women aged 15-49, -0.533 index (approx. -2.5 to 2.5)Zimbabwe: 18.2 per 1,000 women aged 15-49, -0.988 index (approx. -2.5 to 2.5)AZEBLRCHECHNGEOGNBJPNMDGNICSGPSOM

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.4502.0e-8142
By rank (Spearman), not adjusted-0.4404.2e-8142
Standard (Pearson), adjusted for national income-0.1960.020142
By rank (Spearman), adjusted for national income-0.0540.523142

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 142 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: +0.254 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.217 (without BLR) to -0.173 (without RUS). 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: RUS (+0.023).

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 & Pacific21-0.10
Europe & Central Asia43-0.13
Latin America & Caribbean26+0.05
Sub-Saharan Africa42-0.04

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 third48-0.09
Middle third47+0.39
Richest third47-0.48

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
Christians96-0.21
Muslims27-0.11

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
France21-0.12
Never a European colony16-0.14
Spain17+0.13
United Kingdom38-0.25

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 = -0.218 after dropping 2 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


per 1,000 women aged 15-49

index (approx. -2.5 to 2.5)
Years
Georgia GEO80.30.4562019, 2024
Azerbaijan AZE71.90.1662019, 2024
Viet Nam VNM64-0.09232019, 2024
Madagascar MDG59.9-0.8632019, 2024
Guinea-Bissau GNB58.5-1.372019, 2024
Cabo Verde CPV49.10.4152019, 2024
China CHN490.8962019, 2024
Trinidad and Tobago TTO48.30.1112019, 2024
India IND480.4052019, 2024
Kazakhstan KAZ470.1472019, 2024
Russian Federation RUS45.7-0.3222019, 2024
Sierra Leone SLE45.4-0.9672019, 2024
Cambodia KHM45-0.2942019, 2024
Barbados BRB44.60.6052019, 2024
Congo, Rep. COG44.4-1.112019, 2024

Bearak, J. M., Popinchalk, A., Beavin, C. et al. (2022), 'Country-specific estimates of unintended pregnancy and abortion incidence: a global comparative analysis of levels in 2015-2019', BMJ Global Health 7(3), e007151. Guttmacher Institute. Supplementary appendix, tables A3-A5.
Kaufmann, D. and A. Kraay, Worldwide Governance Indicators, World Bank

Sources

Abortion rate (estimate)

Abortions per 1,000 women aged 15-49 (model estimate, 2015-2019)

Guttmacher Institute (Bearak et al. 2022, BMJ Global Health) · CC BY-NC 4.0 · updated one edition (2015-2019 estimates, published 2022)

The Guttmacher Institute's estimate of all abortions, legal or not, per 1,000 women aged 15 to 49 (women of childbearing age), averaged over 2015-2019. Where a country has good counts, the estimate stays close to them. Where it does not, including most countries where abortion is banned, it is worked out by a statistical model from surveys, births, birth control use and similar countries. Only 75 of the 166 countries with any data had counts reliable enough to use directly, so for many countries this is an informed estimate with a wide range: Georgia's is 80, but it could be anywhere from 46 to 133. The official count of legal abortions is shown separately. No "better" direction is set.

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 2019–2024. 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 Abortion rate (estimate) and Government effectiveness

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

More links with Abortion rate (estimate) or Government effectiveness