Do Slum share of urban population and Voice and accountability go together across countries?

Across 182 countries the link before adjusting for anything is r = -0.54, on a scale from -1 (opposite) to +1 (in step). A version that uses only each country's rank gives -0.58.

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

Comparing each country only with itself across 2000-2022, and setting aside what happened worldwide in each year, the link is +0.084 (173 countries, 1,966 country-years). Using year-to-year changes, it is —.

Does Slum share of urban population cause Voice and accountability?

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.

Slum share of urban population vs. Voice and accountability

Fades after adjusting for income

Across 182 countries, Slum share of urban population and Voice and accountability rise and fall together at r = -0.54 (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 = 0.46, 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.

Comparing countries across the middle half of slum share of urban population, 0.561% to 44.5% of urban population, voice and accountability is worse by 0.983 points at the top of that range than the bottom. Comparing only countries with similar national income, the gap is 0.461 points.

Link before adjusting (r)-0.541p = 3.3e-15 · 182 countries

After adjusting for national income-0.209p = 0.005 · likely range [-0.34, -0.07]

p, allowing for regions0.257standard error 0.167 · 7 regions

Check for luck (q)0.462across 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.

Slum share of urban population · % of urban populationlink with income -0.78 · high

Voice and accountability · index (approx. -2.5 to 2.5)link with income +0.58 · 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	-0.541	3.3e-15	182
By rank (Spearman), not adjusted	-0.580	1.0e-17	182
Standard (Pearson), adjusted for national income	-0.209	0.005	182
By rank (Spearman), adjusted for national income	-0.247	0.001	182

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 182 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: +0.332 (a minus sign means it grew).

How solid is it?

Leaving out one country at a time, r ranges from -0.229 (without TJK) to -0.184 (without KIR). 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: KIR (+0.025).

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	28	-0.62
Europe & Central Asia	49	-0.45
Latin America & Caribbean	29	-0.23
Middle East, North Africa, Afghanistan & Pakistan	21	-0.24
Sub-Saharan Africa	46	-0.24

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	61	-0.37
Middle third	60	-0.12
Richest third	61	-0.16

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	106	-0.27
Muslims	49	-0.09

By last european coloniser

	n	r
France	25	-0.13
Never a European colony	21	-0.11
Spain	19	-0.22
United Kingdom	57	-0.33

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 = -0.209 after dropping 0 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 23years. 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 = +0.084, 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 slum share of urban population moved did not tend to see their voice and accountability move with it.

Across countries (adjusted)-0.209for comparison

Within countries+0.017each country vs itself

…and vs the same year elsewhere+0.084q = 0.309 · 173 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.

1,966 country-years (one country in one year), 173 countries, 2000–2022, about 11 years each on average. Share of the variation that happens within countries over time: 9% for Slum share of urban population, 4% for Voice and accountability. 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): +0.084. 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 (+0.17 at lag +4) is higher than the same-year one by 0.09. That gap is not a finding. It is the largest of 21 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

	% of urban population	index (approx. -2.5 to 2.5)	Years
Mali MLI	92.5%	-1.22	2022, 2024
Burkina Faso BFA	87.9%	-0.964	2022, 2024
Sao Tome and Principe STP	82.4%	0.165	2022, 2024
Chad TCD	82%	-1.52	2022, 2024
Congo, Dem. Rep. COD	78.4%	-1.21	2022, 2024
Congo, Rep. COG	75.3%	-1.31	2022, 2024
Sudan SDN	73.7%	-1.88	2022, 2024
Afghanistan AFG	71.6%	-2.15	2022, 2024
Niger NER	70.4%	-0.971	2022, 2024
Tanzania TZA	70.1%	-0.645	2022, 2024
Central African Republic CAF	68.9%	-1.31	2022, 2024
Madagascar MDG	65.7%	-0.725	2022, 2024
Equatorial Guinea GNQ	64.7%	-1.73	2022, 2024
Ethiopia ETH	64.3%	-1.24	2022, 2024
Benin BEN	64%	-0.38	2022, 2024

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

Sources

Slum share of urban population

Population living in slums (% of urban population)

UN-Habitat · CC BY 4.0 · updated quarterly

Voice and accountability

Voice and Accountability (estimate)

World Bank · CC BY 4.0 · updated annual

How this was computed

Data used: most recent value in 2010-2025; values come from 2012–2024. 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 12,497 pairs at once, using the Benjamini–Hochberg method. Underlying data last updated DYB 2024. How the country data works · explore Slum share of urban population and Voice and accountability

This page shows that two measures go together. It does not show that Slum share of urban population changes Voice and accountability, or the reverse. These figures also describe countries, not individual people. See the ecological fallacy.