placestats

Abortion rate (estimate) vs. Capital per worker

Holds up after adjusting for income

Across 133 countries, Abortion rate (estimate) and Capital per worker rise and fall together at r = -0.51 (on a scale from −1 to +1, where 0 means no link). Comparing only countries with similar income (GDP per person) shrinks it to -0.29 (q = 0.010, allowing for the many pairs tested). Much of the first figure is that both measures rise with national income, but a weak negative link remains. Caution: direction is not consistent across regions.

Comparing countries across the middle half of abortion rate (estimate), 15 to 36 per 1,000 women aged 15-49, capital per worker is $157,077 lower at the top of that range than the bottom. Comparing only countries with similar national income, the gap is $53,356.

Link before adjusting (r)-0.506p = 5.1e-10 · 133 countries
After adjusting for national income-0.287p = 0.001 · likely range [-0.44, -0.12]
p, allowing for regions0.000standard error 0.039 · 7 regions
Check for luck (q)0.010across 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.

Abortion rate (estimate) · per 1,000 women aged 15-49link with income -0.50 · moderate
Capital per worker · 2021 international $ per workerlink with income +0.93 · 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 →Capital per worker · 2021 international $ per worker →580.3$4,669$788,016Angola: 33.4 per 1,000 women aged 15-49, $40,771Albania: 9.45 per 1,000 women aged 15-49, $224,756Argentina: 33.2 per 1,000 women aged 15-49, $217,740Armenia: 42.8 per 1,000 women aged 15-49, $215,201Australia: 16.1 per 1,000 women aged 15-49, $588,436Azerbaijan: 71.9 per 1,000 women aged 15-49, $103,789Burundi: 25.6 per 1,000 women aged 15-49, $5,029Belgium: 7.78 per 1,000 women aged 15-49, $788,016Benin: 31.9 per 1,000 women aged 15-49, $35,283Burkina Faso: 30.5 per 1,000 women aged 15-49, $14,647Bangladesh: 35.3 per 1,000 women aged 15-49, $75,955Bulgaria: 10.2 per 1,000 women aged 15-49, $174,610Bosnia and Herzegovina: 11 per 1,000 women aged 15-49, $261,176Belarus: 10.5 per 1,000 women aged 15-49, $354,810Belize: 31.8 per 1,000 women aged 15-49, $78,567Bolivia: 37.8 per 1,000 women aged 15-49, $53,381Brazil: 32.3 per 1,000 women aged 15-49, $172,608Barbados: 44.6 per 1,000 women aged 15-49, $213,881Bhutan: 32.1 per 1,000 women aged 15-49, $236,135Botswana: 30.7 per 1,000 women aged 15-49, $179,626Central African Republic: 26.8 per 1,000 women aged 15-49, $26,131Canada: 11.6 per 1,000 women aged 15-49, $524,837Switzerland: 5.18 per 1,000 women aged 15-49, $713,606Chile: 35.9 per 1,000 women aged 15-49, $243,644China: 49 per 1,000 women aged 15-49, $228,804Cote d'Ivoire: 35.3 per 1,000 women aged 15-49, $40,246Cameroon: 33.9 per 1,000 women aged 15-49, $32,971Congo, Dem. Rep.: 32.7 per 1,000 women aged 15-49, $10,352Congo, Rep.: 44.4 per 1,000 women aged 15-49, $142,120Colombia: 27.1 per 1,000 women aged 15-49, $133,012Comoros: 30.6 per 1,000 women aged 15-49, $61,490Cabo Verde: 49.1 per 1,000 women aged 15-49, $108,256Costa Rica: 21.1 per 1,000 women aged 15-49, $199,425Czechia: 6.86 per 1,000 women aged 15-49, $532,563Germany: 5.77 per 1,000 women aged 15-49, $456,143Djibouti: 20.6 per 1,000 women aged 15-49, $140,439Denmark: 11.6 per 1,000 women aged 15-49, $624,134Dominican Republic: 36.6 per 1,000 women aged 15-49, $248,222Ecuador: 27.9 per 1,000 women aged 15-49, $173,936Spain: 8.73 per 1,000 women aged 15-49, $645,774Estonia: 15.9 per 1,000 women aged 15-49, $440,113Ethiopia: 24.4 per 1,000 women aged 15-49, $15,427Finland: 8.09 per 1,000 women aged 15-49, $666,233France: 14.4 per 1,000 women aged 15-49, $697,343Gabon: 40.6 per 1,000 women aged 15-49, $159,764United Kingdom: 13.1 per 1,000 women aged 15-49, $512,292Georgia: 80.3 per 1,000 women aged 15-49, $431,753Ghana: 36.6 per 1,000 women aged 15-49, $46,135Guinea: 26.4 per 1,000 women aged 15-49, $22,150Gambia, The: 16.4 per 1,000 women aged 15-49, $21,269Guinea-Bissau: 58.5 per 1,000 women aged 15-49, $12,239Greece: 15 per 1,000 women aged 15-49, $528,005Guatemala: 18.9 per 1,000 women aged 15-49, $111,294Hong Kong SAR, China: 13 per 1,000 women aged 15-49, $667,472Honduras: 20.7 per 1,000 women aged 15-49, $82,123Croatia: 16.5 per 1,000 women aged 15-49, $436,860Haiti: 38.1 per 1,000 women aged 15-49, $98,654Hungary: 13.6 per 1,000 women aged 15-49, $425,172Indonesia: 25 per 1,000 women aged 15-49, $183,833India: 48 per 1,000 women aged 15-49, $77,306Iceland: 12.7 per 1,000 women aged 15-49, $663,692Italy: 18.9 per 1,000 women aged 15-49, $772,186Jamaica: 38.1 per 1,000 women aged 15-49, $127,828Japan: 6 per 1,000 women aged 15-49, $443,290Kazakhstan: 47 per 1,000 women aged 15-49, $240,251Kenya: 42.7 per 1,000 women aged 15-49, $36,351Kyrgyz Republic: 31.2 per 1,000 women aged 15-49, $75,165Cambodia: 45 per 1,000 women aged 15-49, $57,014Korea, Rep.: 21 per 1,000 women aged 15-49, $524,597Lao PDR: 34 per 1,000 women aged 15-49, $60,622Liberia: 42.3 per 1,000 women aged 15-49, $18,430St. Lucia: 37.2 per 1,000 women aged 15-49, $227,662Sri Lanka: 27.9 per 1,000 women aged 15-49, $135,884Lesotho: 23.5 per 1,000 women aged 15-49, $51,675Lithuania: 7.15 per 1,000 women aged 15-49, $351,583Latvia: 10.3 per 1,000 women aged 15-49, $567,433Moldova: 18.2 per 1,000 women aged 15-49, $150,878Madagascar: 59.9 per 1,000 women aged 15-49, $9,126Maldives: 42 per 1,000 women aged 15-49, $272,395Mexico: 30.6 per 1,000 women aged 15-49, $182,229North Macedonia: 14.3 per 1,000 women aged 15-49, $246,047Mali: 22.5 per 1,000 women aged 15-49, $13,542Myanmar: 26 per 1,000 women aged 15-49, $69,944Montenegro: 5.89 per 1,000 women aged 15-49, $230,861Mongolia: 21 per 1,000 women aged 15-49, $161,137Mozambique: 40.4 per 1,000 women aged 15-49, $20,903Mauritania: 17 per 1,000 women aged 15-49, $103,000Malawi: 31.4 per 1,000 women aged 15-49, $4,669Namibia: 29.2 per 1,000 women aged 15-49, $151,136Niger: 15.2 per 1,000 women aged 15-49, $16,530Nigeria: 32.7 per 1,000 women aged 15-49, $124,033Nicaragua: 15.3 per 1,000 women aged 15-49, $83,527Netherlands: 7.15 per 1,000 women aged 15-49, $552,270Norway: 10.8 per 1,000 women aged 15-49, $771,357Nepal: 41.3 per 1,000 women aged 15-49, $31,796New Zealand: 12 per 1,000 women aged 15-49, $260,787Pakistan: 43.1 per 1,000 women aged 15-49, $31,616Panama: 29.6 per 1,000 women aged 15-49, $444,149Peru: 42.4 per 1,000 women aged 15-49, $123,770Philippines: 36 per 1,000 women aged 15-49, $96,960Poland: 10.5 per 1,000 women aged 15-49, $217,393Portugal: 6.77 per 1,000 women aged 15-49, $546,974Paraguay: 34 per 1,000 women aged 15-49, $162,503Romania: 31 per 1,000 women aged 15-49, $306,456Russian Federation: 45.7 per 1,000 women aged 15-49, $535,814Rwanda: 27.8 per 1,000 women aged 15-49, $14,359Senegal: 15.3 per 1,000 women aged 15-49, $39,760Singapore: 5 per 1,000 women aged 15-49, $659,201Sierra Leone: 45.4 per 1,000 women aged 15-49, $11,451El Salvador: 24 per 1,000 women aged 15-49, $118,273Serbia: 12.7 per 1,000 women aged 15-49, $242,243Sao Tome and Principe: 38.5 per 1,000 women aged 15-49, $56,209Suriname: 31 per 1,000 women aged 15-49, $257,115Slovak Republic: 7.15 per 1,000 women aged 15-49, $356,502Slovenia: 8.13 per 1,000 women aged 15-49, $534,480Sweden: 17.3 per 1,000 women aged 15-49, $568,885Eswatini: 29.3 per 1,000 women aged 15-49, $109,028Chad: 17.4 per 1,000 women aged 15-49, $14,253Togo: 32.1 per 1,000 women aged 15-49, $23,596Thailand: 25 per 1,000 women aged 15-49, $154,578Tajikistan: 25.8 per 1,000 women aged 15-49, $275,734Turkmenistan: 18.9 per 1,000 women aged 15-49, $247,867Trinidad and Tobago: 48.3 per 1,000 women aged 15-49, $428,237Tanzania: 37.5 per 1,000 women aged 15-49, $33,612Uganda: 43 per 1,000 women aged 15-49, $21,690Ukraine: 20.5 per 1,000 women aged 15-49, $640,898Uruguay: 11.4 per 1,000 women aged 15-49, $250,173United States: 11.9 per 1,000 women aged 15-49, $482,411Uzbekistan: 22.7 per 1,000 women aged 15-49, $153,548Viet Nam: 64 per 1,000 women aged 15-49, $88,517South Africa: 29.7 per 1,000 women aged 15-49, $161,442Zambia: 34.6 per 1,000 women aged 15-49, $48,746Zimbabwe: 18.2 per 1,000 women aged 15-49, $21,641AZEBELCHEGEOGMBMDGNERNORRUSSENVNM

best-fit line line after adjusting

Four ways to measure the link

MethodrpCountries
Standard (Pearson), not adjusted-0.5065.1e-10133
By rank (Spearman), not adjusted-0.5333.9e-11133
Standard (Pearson), adjusted for national income-0.2870.001133
By rank (Spearman), adjusted for national income-0.1260.152133

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 133 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: +0.219 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.343 (without GEO) to -0.255 (without AZE). 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: GEO (-0.056).

Fragile: this link may not hold up.
  • direction is not consistent across regions
  • much weaker within income groups than across them (mostly a gap between richer and poorer countries)

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 & Pacific15-0.30
Europe & Central Asia43-0.10
Latin America & Caribbean24+0.28
Sub-Saharan Africa41+0.03

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 third45-0.12
Middle third44-0.10
Richest third44+0.03

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
Christians88-0.20
Muslims26-0.44

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
France21-0.01
Never a European colony16-0.14
Spain17-0.13
United Kingdom32-0.30

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
Nationalist21-0.43
No strong official ideology95-0.18

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 banned21-0.26
No parties banned99-0.23

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 = -0.313 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

2021 international $ per worker
Years
Georgia GEO80.3$431,7532019, 2023
Azerbaijan AZE71.9$103,7892019, 2023
Viet Nam VNM64$88,5172019, 2023
Madagascar MDG59.9$9,1262019, 2023
Guinea-Bissau GNB58.5$12,2392019, 2023
Cabo Verde CPV49.1$108,2562019, 2023
China CHN49$228,8042019, 2023
Trinidad and Tobago TTO48.3$428,2372019, 2023
India IND48$77,3062019, 2023
Kazakhstan KAZ47$240,2512019, 2023
Russian Federation RUS45.7$535,8142019, 2023
Sierra Leone SLE45.4$11,4512019, 2023
Cambodia KHM45$57,0142019, 2023
Barbados BRB44.6$213,8812019, 2023
Congo, Rep. COG44.4$142,1202019, 2023

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.
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

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.

Capital per worker

Capital stock per person engaged, at current PPPs (Penn World Table)

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

The value of a country's buildings, machines, roads and other equipment, divided by the number of people working. It is in dollars adjusted for what money buys in each country, and it is best for comparing countries in the same year. The Penn World Table builds it by adding up past investment and taking off wear and tear, so it is linked to the investment share by construction. Where it is used for adjusting, it is measured in percentage terms (on a log scale), like income. No "better" direction is set.

How this was computed

Data used: most recent value in 2010-2025; values come from 2019–2023. 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 Abortion rate (estimate) and Capital per worker

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

More links with Abortion rate (estimate) or Capital per worker