Do Gini index and Women in a union go together across countries?

Across 159 countries the link before adjusting for anything is r = -0.34, on a scale from -1 (opposite) to +1 (in step). A version that uses only each country's rank gives -0.23.

Does the link hold within countries over time, not just across countries?

Comparing each country only with itself across 1990-2023, and setting aside what happened worldwide in each year, the link is -0.089 (113 countries, 1,895 country-years). Using year-to-year changes, it is +0.010.

Does Gini index cause Women in a union?

This analysis cannot answer that. It shows only that the two go together. A link between two country measures, adjusted or not, does not show that either one changes the other. Country figures also say nothing about individual people.

Gini index vs. Women in a union

Holds up after adjusting for income

Across 159 countries, Gini index and Women in a union rise and fall together at r = -0.34 (on a scale from −1 to +1, where 0 means no link). It holds up almost unchanged when only countries with similar income (GDP per person) are compared (r = -0.51, q = 0.038, allowing for the many pairs tested). Caution: direction is not consistent across regions.

Comparing countries across the middle half of women in a union, 52.2% to 63% of women aged 15-49, gini index is better by 3.1 points at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 4.68 points.

Link before adjusting (r)-0.344p = 8.8e-6 · 159 countries

After adjusting for national income-0.508p = 1.0e-11 · likely range [-0.61, -0.38]

p, allowing for regions0.006standard error 0.124 · 7 regions

Check for luck (q)0.038across 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.

Gini index · index (0-100)link with income -0.34 · moderate

Women in a union · % of women aged 15-49link with income -0.44 · moderate

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

Every country as a dot

best-fit line line after adjusting

Four ways to measure the link

Method	r	p	Countries
Standard (Pearson), not adjusted	-0.344	8.8e-6	159
By rank (Spearman), not adjusted	-0.234	0.003	159
Standard (Pearson), adjusted for national income	-0.508	1.0e-11	159
By rank (Spearman), adjusted for national income	-0.443	5.6e-9	159

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 159 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: -0.163 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.524 (without TON) to -0.473 (without NAM). 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: NAM (+0.035).

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.

	n	r
East Asia & Pacific	21	+0.30
Europe & Central Asia	47	+0.03
Latin America & Caribbean	23	+0.01
Middle East, North Africa, Afghanistan & Pakistan	15	-0.44
Sub-Saharan Africa	45	-0.60

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.

	n	r
Poorest third	53	-0.40
Middle third	53	-0.69
Richest third	53	-0.15

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.

	n	r
Christians	101	-0.51
Muslims	39	-0.27

By last european coloniser

	n	r
France	23	-0.48
Never a European colony	16	+0.02
Spain	19	-0.27
United Kingdom	47	-0.68

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 = -0.364 after dropping 8 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 34years. 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 = -0.089, 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 gini index moved did not tend to see their women in a union move with it.

Across countries (adjusted)-0.508for comparison

Within countries+0.120each country vs itself

…and vs the same year elsewhere-0.089q = 0.394 · 113 countries

Year-on-year changes+0.010q = 0.855

1,895 country-years (one country in one year), 113 countries, 1990–2023, about 17 years each on average. Share of the variation that happens within countries over time: 14% for Gini index, 13% for Women in a union. 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

Same year (lag 0): -0.089. 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 data

	index (0-100)	% of women aged 15-49	Years
Namibia NAM	59.1	33.7%	2015, 2018
Botswana BWA	54.9	41.5%	2015, 2017
Eswatini SWZ	54.6	36.4%	2016, 2022
Colombia COL	54.4	50.9%	2024, 2018
South Africa ZAF	54.1	33.6%	2022, 2020
Zambia ZMB	51.5	55.7%	2022, 2018
Angola AGO	51.3	57.2%	2018, 2016
Zimbabwe ZWE	50.3	62.2%	2019, 2022
Brazil BRA	50.3	56.9%	2024, 2019
Panama PAN	49.7	53.2%	2024, 2023
Mozambique MOZ	49.6	64.8%	2022, 2023
Congo, Rep. COG	48.9	55.3%	2011, 2015
Nicaragua NIC	46.2	56%	2014, 2012
Ecuador ECU	45.9	45.3%	2025, 2022
Honduras HND	45.7	54.4%	2024, 2019

World Bank, World Development Indicators
United Nations, Department of Economic and Social Affairs, Population Division: World Population Prospects 2024 and Estimates and Projections of Women of Reproductive Age Who Are Married or in a Union

Sources

Gini index

World Bank · CC BY 4.0 · updated quarterly

Sparse and uneven: most countries report only every few years, and coverage is thinnest where inequality is highest. Be wary of comparisons that match Gini with other measures year by year.

Women in a union

Share of women aged 15 to 49 who are married or in a union

United Nations Department of Economic and Social Affairs, Population Division · via Our World in Data · CC BY 3.0 IGO · updated biennial

A snapshot of how many women are in a union at one time, not a count of new unions each year. It counts couples living together as a union, which the OECD marriage rate does not. So the two can disagree without either being wrong, and their pair is worth reading for exactly that. The UN estimates it with a statistical model from survey and census data, for over two hundred countries. No "better" direction is set.

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 Gini index and Women in a union

This page shows that two measures go together. It does not show that Gini index changes Women in a union, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.