Editorial Team The fact that 71% of the world’s population lives in countries where inequality has gotten worse since 1980 should be a massive wake-up call. That number, from a recent UNDP report, means we have to stop measuring societal progress with simple GDP figures. We need a much better grasp of inequality data and what it actually means for hitting any of our sustainable development goals (SDG progress).
Key Takeaways
- The Palma Ratio is a better tool than the Gini coefficient for seeing the real gap, as it just compares the income share of the richest 10% to the poorest 40%.
- You need Multidimensional Poverty Indices (MPIs) to see the whole picture of deprivation, not just income, but also health, education, and living standards, which tells a different story.
- A concrete way to track SDG progress is just measuring access to basics like electricity and clean water. When those go up, inequality goes down.
- Forget just income. Wealth inequality, what people own (net worth), not just what they earn, shows the real, baked-in disparities that other metrics miss.
- National averages like GDP are misleading. You have to break the data down by region, gender, and other demographics to find where the real problems are.
The Palma Ratio: A Sharper Lens on Income Disparity
The Gini coefficient has been the standard for measuring income inequality for a long time, but in my professional experience, its focus on the middle of the distribution can hide what’s really going on at the extremes. If you want actionable insight, you have to look at the tails. This is exactly why the Palma Ratio offers a superior perspective. It simply compares the income share of the richest 10% of the population to the income share of the poorest 40%.
Just look at the numbers. A 2024 Oxfam International analysis showed that the world’s richest 1% vacuumed up nearly two-thirds of all new wealth created since 2020. The Palma Ratio makes that abstract fact brutally clear. For example, if the top 10% holds 30% of the income and the bottom 40% holds only 10%, you get a Palma Ratio of 3, meaning the top tier earns three times as much as the bottom 40% put together. When you see that ratio climbing, you’re watching a concentration of wealth that poisons social stability and kills inclusive growth. Any policymaker serious about SDG 10 (Reduced Inequalities) has to track this metric religiously. It’s not enough to know the spread. You need to know who’s winning and who’s getting crushed.
Multidimensional Poverty Indices: Beyond Monetary Deprivation
Income is obviously a huge piece of the puzzle, but poverty and inequality are far more tangled than any one number can show. The Multidimensional Poverty Index (MPI), which OPHI and the UNDP developed, gets this right by capturing the overlapping deprivations people face in health, education, and living standards. The entire approach recognizes that someone might have an income but still lack access to clean water, good schools, or healthcare, locking them into a cycle of inequality.
A 2025 report on global MPI trends found that **1.1 billion people still live in multidimensional poverty across 110 countries**, even with progress in some areas. What’s really telling is that about two-thirds of these people are in middle-income countries, which torpedoes the old assumption that poverty is just a low-income country problem. You can have a country with a decent GDP per capita where huge parts of the population can’t get basic vaccinations or where kids drop out because the nearest school is too far away. The MPI lets you see these specific failures so you can target them. Simply trying to raise incomes while ignoring these foundational needs won’t ever get you to true equity.
Access to Essential Services: A Direct Measure of Equity
For me, one of the most honest and tangible indicators of inequality is the gap in access to essential services. I’m talking about basic infrastructure: electricity, clean drinking water, sanitation. These aren’t luxuries. They’re the bedrock of human dignity and economic opportunity. The WHO and UNICEF Joint Monitoring Programme (JMP) reported in 2024 that **2.2 billion people still lack safely managed drinking water, and 3.5 billion lack safely managed sanitation services globally**. These figures are appalling, and they correlate directly with stubborn inequality.
Think about the real-world impact. A household without reliable electricity means kids can’t study after dark. A community without clean water faces constant health crises, which means lost workdays and crushing medical bills. This creates a trap of disadvantage that keeps running no matter how much the national GDP grows. When I review development strategies, I always check for specific, measurable goals on infrastructure access. A program in rural Georgia, for instance, might be better off focusing on extending broadband internet to every county, because in today’s world digital inclusion is just as important as physical roads. The evidence is unambiguous: closing the gap in these basic services is a direct and effective way to slash inequality and make progress on several SDGs at once, from health (SDG 3) and education (SDG 4) to clean water (SDG 6).
Wealth Inequality: The Elephant in the Room
We spend a lot of time on income inequality, which measures a flow of earnings, but the real story is often in **wealth inequality, which quantifies the stock of assets**, property, stocks, savings, minus debt. The distinction is everything. Wealth builds up over generations and is a much stronger predictor of someone’s life chances and resilience than their yearly income. A 2023 report from Credit Suisse (now UBS) estimated that the richest 1% of adults owned 44.5% of the world’s net wealth. That figure, which gets lost in income-focused debates, points to a much deeper and more permanent kind of disparity.
So much of the conventional thinking assumes higher wages are the answer. But what if the problem isn’t just what people earn, but what they own (or don’t own)? Wealth perpetuates itself. It’s passed down through inheritance, provides capital to start a business, and gives people a buffer to survive economic shocks. A person with wealth can invest, create passive income, and pass on those advantages, while a person without it is stuck on a treadmill, living paycheck to paycheck and unable to build a safety net. You can have a decent income, but without a foundation of wealth, you lack any real economic security or hope for intergenerational mobility. To tackle that, you need different policy tools like progressive taxes on capital gains and inheritance, plus serious initiatives to help more people build assets.
Disaggregated Data: Unmasking Hidden Disparities
One of the biggest mistakes in this field is relying on national averages. A country’s overall GDP growth or even its national Gini coefficient can paint a rosy picture that completely hides the ugly realities within its borders. It’s a point I make constantly: **data must be disaggregated by gender, age, ethnicity, geographic region, and disability status** to get anywhere near the truth. The UN’s entire “Leave No One Behind” principle for the SDGs depends on this granular analysis.
For example, a national statistic might show poverty going down, but when you dig in, you could find it’s actually getting much worse for indigenous populations or women in rural areas. The digital divide is a perfect case. A country might boast high internet penetration on average, but a closer look reveals that remote areas are totally offline, which creates a whole new layer of inequality. Without disaggregated data, policy interventions are just shots in the dark, broad, ineffective, and guaranteed to miss the most vulnerable people. Making real SDG progress means we have to get past the headline numbers and look at the specific, lived experiences of different communities, which requires a serious investment in good data collection and a commitment to transparency.
Our simplistic reliance on GDP as the main scorecard for national success has let the deep and growing problem of inequality fester for far too long. By finally embracing more complete metrics like the Palma Ratio, Multidimensional Poverty Indices, and detailed data on service access, and combining that with a critical focus on wealth and disaggregated data, we can start to see the true scale of the challenge. This isn’t just an academic exercise. It’s the only foundation for building policies that can create genuinely inclusive and sustainable development.
Why isn’t GDP a good way to measure inequality?
GDP is a poor measure of inequality because it only shows a country’s total economic output, not how that money is spread among its people. A country can have a high GDP and still have massive gaps in income, wealth, and access to services, so the metric fails to capture how most citizens are actually living.
What’s the difference between income inequality and wealth inequality?
Income inequality refers to the uneven split of earnings (wages, salaries, profits) over a period of time. Wealth inequality measures the lopsided distribution of accumulated assets, things like property, savings, and investments, minus debts. It’s a snapshot of resources owned, not a flow of cash.
How is the Palma Ratio better than the Gini coefficient?
The Gini coefficient gives a general measure of income distribution, but the Palma Ratio is sharper because it specifically compares the income share of the richest 10% to the poorest 40%. This makes it much more sensitive to what’s happening at the extreme ends of the spectrum, offering a clearer picture of the gap between the rich and the poor.
What are Multidimensional Poverty Indices (MPIs) and why do they matter?
MPIs assess poverty by looking at several deprivations a person faces across health, education, and living standards, not just by their income. They matter because they give a much more complete view of poverty and inequality, identifying people who might not be income-poor but still lack basic necessities, which helps guide smarter interventions.
Why is it so important to have disaggregated data to understand inequality?
Disaggregated data is essential because it breaks down national statistics by specific demographic groups (e.g., gender, age, ethnicity, region). National averages almost always hide the severe disparities that certain populations experience, and without this breakdown, policies are designed to fail the very communities they’re meant to help.
