We Need a More Targeted Approach to Combatting Global Inequality

A new trove of data may allow us to replace a trickle-down approach with more precise efforts.

The global economic system works very well for some people, including us. It hardly works at all for millions of others. Those for whom it doesn’t work are robbed of the opportunity to lead the life they want, and that is unjust.

We believe that every life has equal value. That’s why we believe in progressive taxes and paying our fair share to support government programs, and it’s why we are giving virtually all of our money away. We want to narrow inequality. But even though the motive for our philanthropy in the United States and around the world is the same, the way we put it into practice is not.

Most of our philanthropy in the United States is focused on public education. A great school is a key to success, but you’re less likely to go to one if you’re a student of color, low income, or both. We hope to help change those odds by improving schools. Expanding educational opportunity is not a silver-bullet solution to economic inequality—for example, it doesn’t address the fact that only one in five senior leaders at U.S. companies is a woman, and that only one in 25 is a woman of color—but it’s a start. And just last year, we launched a complementary effort to help organizations across the country attack some of the root causes of poverty.

Globally, we focus on health for the very same reason. We saw a terrible inequality, and we were moved by the injustice of it. A country can keep 99.8 percent of children alive during the first, most vulnerable years of their life. We know it’s possible, because Finland, which leads the world in child survival, does exactly that. But there are 10 countries in the world where a child is 50 times more likely to die than a child in Finland. Mere survival, of course, is not the goal. Thriving is. But most adults in these countries are trying to scratch a living out of already infertile soil as the climate changes. Many cannot read. Women are expected to marry young, bear children, and spend the majority of their life running the household. Thriving is very difficult under these circumstances.

Reducing inequality around the world poses different challenges than it does in the United States. The data we use to measure American economic mobility, for example, are relatively fine-grained, allowing us to look down to the level of individual zip codes. Not only can we compare our home of Seattle to one in Bettendorf, Iowa; we can compare South Seattle to North Seattle—and even the Rainier View neighborhood to Phinney Ridge.

Around the world, though, we have had to measure inequality at the level of regions or countries. We focus on driving child mortality in, say, sub-Saharan Africa or Yemen down to the level in western Europe or Finland.

Making big regional or national comparisons helps highlight the problem of inequality, but it can be a dangerous basis for formulating solutions. Such comparisons invite sweeping generalizations, treating foreign countries as undifferentiated units of analysis. China is four times the size of the United States, but it’s common to fall into the trap of regarding it as more unitary than the suburbs of Indianapolis.

Recently, though, we received a new trove of data from the Institute for Health Metrics and Evaluation that makes it impossible to see inequality in foreign countries as any less complex than inequality in the United States.

The data are about health and education at the district level—that is, at the equivalent of the county level in the United States—in every single low- and low-middle-income country. They show with quantitative precision that every country has its South and North Seattles, its Bettendorfs, and its Indianapolis suburbs.

Consider Nigeria, which is about the size of France, Germany, and Great Britain combined. Nigeria may be a lower-middle-income country on average, but it’s not uniform. Parts of it resemble very poor countries—and parts of it are like much richer ones.

For example, in Garki, in Jigawa state, the average person never finished elementary school. (The average woman there, by the way, has more than two years less schooling than the average man.) By comparison, in Ado Ekiti, in Ekiti state, the average person is a high-school graduate. A child born in Ado Ekiti is three times more likely to survive than one born in Garki.

When you start to understand global inequality at the local level, it changes how you think about interventions.

If the goal is for low-income countries to close the gap with high-income countries, then the average is all that matters. Many governments and development organizations have concentrated on reaching those who are easiest to reach. As a result, life typically gets better for the best-off first, and then, gradually, for everyone else. Eventually, over the course of decades or centuries, the poorest mostly catch up.

This trickle-down approach, it turns out, actually does work, to an extent. We’re optimists, but even we were surprised to discover that from 2000 to 2017, more than 99 percent of districts in developing countries—some 17,000 in all—improved their child-mortality rates and years of schooling. No matter how many times you hear the opposite, life is improving for almost everyone, almost everywhere.

But people who are unhealthy and uneducated today don’t have decades or centuries to wait. Moreover, in countries where some people are already doing well, the quickest way to raise the average is to concentrate on those who aren’t.

In short, governments—and philanthropies like ours—need to hurry up, and that means replacing the trickle-down approach with precise targeting. The key is identifying those in need, analyzing how to help, and delivering solutions directly to them. And a few governments around the world are starting to experiment with doing just that.

Government policies often exacerbate inequalities in health care. Primary-care systems are designed to provide people with the majority of the services they need, but low- and middle-income countries spend only about one-third of their health budget on primary care. In other words, many governments prioritize highly specialized health care for a minority of mostly well-off people, forcing everyone else to pay out of pocket to meet basic needs. Some countries, though, are trying a different approach. Thailand, for example, has prioritized primary care, and now there is not a single Thai village without its own health center.

The government of India, meanwhile, is using mobile technology to reinvent the relationship between poor citizens and the state. Cooking-gas subsidies used to be available to every single Indian, regardless of income. But the top 10 percent of Indian earners received seven times more in subsidies than the bottom 10 percent. Several years ago, the government started transferring money directly into people’s mobile money accounts, which reduced fraud, generating nearly $9 billion in savings since 2015. The new approach also enabled the government to deposit money directly into women’s accounts instead of giving cash to the head of household (almost invariably a man). India has now helped 75 million poor women in poor states purchase gas stoves so that they can stop spending hours gathering firewood and breathing in hazardous smoke from kitchen fires.

Ethiopia’s economy has been growing by 10 percent or more every year for a decade. With 80 percent of Ethiopians living in rural areas, agricultural growth underpins the country’s economic success, and that growth has been stimulated by a government program that pays smallholder farmers to work on agriculture-related public-works projects. The money they earn helps them manage emergencies and invest in their farms, while the work they do building dams, cisterns, and other infrastructure will keep Ethiopia resilient in the face of climate change.

All these targeted efforts rely on data, and that’s why the Bill & Melinda Gates Foundation invests so much in data—collecting more of them, analyzing them in more sophisticated ways, and sharing findings with leaders and advocates who need to understand them. That includes the people who work at our foundation, because we won’t maximize the impact of our work to reduce inequality until our grants help precisely the right people in precisely the right places.

The two of us have always been impatient optimists. This new trove of health and education data makes us both more impatient and more optimistic. We’re more optimistic because we see a clear path to eliminating inequality—and more impatient because more countries, including our own, need to follow it.