National inequality figures are useful, but they can obscure the cities where economic difference is actually lived. Housing, transport, employment, public space and access to services all land in particular metropolitan areas?not in a national average.
City-level evidence can bring that local reality into view. It can also reveal a less comfortable fact: the places best measured are not necessarily the places where inequality matters most.
Coverage is part of the evidence
The first chart is not about inequality itself. It is about the data available to study it. Some countries have many city-year observations; others have very few. That shapes what researchers, policy-makers and citizens can see.
A data gap is not merely a technical inconvenience. It can become a policy gap when urban change is not measured consistently enough to recognise it.
Cities need their own evidence base
Figure 1. City-level monitoring is uneven: some metropolitan areas have repeated observations, while many are represented only once or twice.
The monitoring pattern tells us where comparison is strongest. Cities with repeated observations can show whether inequality is changing; one-off observations can only provide a snapshot. Both are useful, but they answer different questions.
This matters for the policies that shape city life. Housing affordability, public transport, labour markets and access to green space all interact with inequality at metropolitan scale.
National stability can hide local difference
Figure 2. Median metropolitan Gini values and city-level ranges reveal different inequality patterns within the countries covered by the source data.
The trend view is deliberately cautious. It does not claim that a handful of cities represent an entire country. Instead, it shows why national figures should be read alongside metropolitan evidence: cities within the same country can experience very different levels and trajectories of inequality.
That is the city inequality question. Where is prosperity shared, where is it concentrated, and which local systems are making the difference?
Better city data makes better policy possible
Urban inequality is not an abstract social indicator. It affects whether people can reach jobs, heat and cool their homes, participate in public life and benefit from economic growth. Better, more consistent metropolitan data will not solve those problems by itself. It does make them harder to ignore and easier to target.
Method and limitations
This article uses the urban Gini data available in the original analysis to compare coverage, monitoring intensity and median inequality patterns over time. City samples are uneven across countries and years, and the data should not be treated as a complete national inequality measure. The results are best read as evidence about the value?and limitations?of metropolitan monitoring.