Do Gender Inequality Index and Public social spending go together across countries?

Across 42 countries the link before adjusting for anything is r = -0.64, on a scale from -1 (opposite) to +1 (in step). A version that uses only each country's rank gives -0.55.

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 -0.250 (42 countries, 1,262 country-years). Using year-to-year changes, it is -0.108.

Does Gender Inequality Index cause Public social spending?

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.

Gender Inequality Index vs. Public social spending

Holds up after adjusting for income

Across 42 countries, Gender Inequality Index and Public social spending rise and fall together at r = -0.64 (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 = -0.50, q = 0.036, allowing for the many pairs tested).

Comparing countries across the middle half of public social spending, 17% to 24.5% of GDP, gender inequality index is better by 0.0799 points at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.0435 points.

Link before adjusting (r)-0.639p = 5.2e-6 · 42 countries

After adjusting for national income-0.496p = 0.001 · likely range [-0.70, -0.22]

p, allowing for regions0.052standard error 0.181 · 5 regions

Check for luck (q)0.036across 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.

Gender Inequality Index · index, 0 to 1link with income -0.89 · proxy

Public social spending · % of GDPlink 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	-0.639	5.2e-6	42
By rank (Spearman), not adjusted	-0.549	0.000	42
Standard (Pearson), adjusted for national income	-0.496	0.001	42
By rank (Spearman), adjusted for national income	-0.365	0.019	42

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 42 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: +0.144 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.547 (without CHL) to -0.409 (without IRL). 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: IRL (+0.087).

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
Europe & Central Asia	30	-0.58

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	14	-0.18
Middle third	14	-0.38
Richest third	14	-0.20

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	35	-0.53

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 = -0.388 after dropping 5 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.

The link also shows up within countries over time (r = -0.250). It holds even when looking only at changes from one year to the next (r = -0.108). 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)-0.496for comparison

Within countries-0.581each country vs itself

…and vs the same year elsewhere-0.250q = 0.035 · 42 countries

Year-on-year changes-0.108q = 0.009

Read with care.

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.

1,262 country-years (one country in one year), 42 countries, 1990–2023, about 30 years each on average. Share of the variation that happens within countries over time: 16% for Gender Inequality Index, 24% for Public social spending. 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): -0.250. 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 to 1	% of GDP	Years
Colombia COL	0.393	14.1%	2023
Mexico MEX	0.358	10%	2023
Peru PER	0.34	7.55%	2023
Turkiye TUR	0.227	10.4%	2023, 2024
Romania ROU	0.227	17.6%	2023, 2021
Costa Rica CRI	0.217	12.6%	2023, 2022
Hungary HUN	0.213	18%	2023, 2024
Bulgaria BGR	0.208	20.5%	2023, 2021
Slovak Republic SVK	0.176	19.3%	2023
United States USA	0.169	19.8%	2023, 2024
Latvia LVA	0.117	19.7%	2023
Greece GRC	0.103	23.7%	2023, 2024
Chile CHL	0.102	12.9%	2023
Czechia CZE	0.088	22.1%	2023, 2024
United Kingdom GBR	0.083	23%	2023

United Nations Development Programme, Human Development Report 2025
OECD databases as named on each indicator: PISA, Social Expenditure Database (SOCX), Income Distribution Database, Development Assistance Committee statistics, Family Database, Government at a Glance, Corporate Tax Statistics, employment and environment statistics

Sources

Gender Inequality Index

United Nations Development Programme, Human Development Report Office · via Our World in Data · CC BY 3.0 IGO · updated annual

Built from deaths in childbirth, births to teenagers, seats in parliament, secondary schooling, and the share of women and men in the workforce. Five of those inputs are on the site and flagged. It is kept out of the gender score, for the same reason the HDI is kept out of the economy score.

Public social spending

Public social expenditure

OECD · via Our World in Data · CC BY 4.0 (OECD terms and conditions) · updated annual, except the snapshots noted per indicator · comparable from 1980 only

All public social spending, as a share of GDP: pensions, health, family, unemployment, housing and the rest. The figures before 1980 are stitched together from older OECD tables and from Lindert's historical estimates, so they are left out. The OECD's social spending database (SOCX) itself starts in 1980. The four spending areas below are parts of this total and are flagged as such.

How this was computed

Data used: most recent value in 2010-2025; values come from 2021–2024. 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 5 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 Gender Inequality Index and Public social spending

This page shows that two measures go together. It does not show that Gender Inequality Index changes Public social spending, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.