What does it mean to live in a country that is 0.517 poor?

According to the UNDP’s Global Multidimensional Poverty Index (MPI), the Republic of Chad has a poverty score of 0.517. But what does this number mean? Is it a good score or a bad one? If you have no clue, you aren’t alone. While the concept of poverty is easy to grasp, quantifying it is actually pretty hard. The MPI is one of the latest in a long line of metrics to try and address this challenge. It is also one of the most confusing, which I think is a problem for anyone concerned with eradicating poverty who is trying to use it. While the MPI and metrics like it have certainly improved our ability to measure poverty accurately, these gains have come at the expense of simplicity. And in a world of shrinking attention spans, I would say it is simplicity and understandability that matter most when it comes to making policymakers and the public take poverty seriously.

How did we get here? 

We didn’t end up with the Multidimensional Poverty Index and other complex metrics by accident. They exist because more rudimentary measures of poverty have serious shortcomings. For example, I think the most widely used poverty metric, the headcount ratio, leaves a lot to be desired. This ratio, which reports the percentage of the population living below the poverty line, says nothing about the depth of poverty. If the poor get poorer, the headcount ratio remains the same as long as nobody crosses the poverty line. If that wasn’t bad enough, it also fails to acknowledge access to healthcare, education, and infrastructure. While these factors undoubtedly shape the lives of the poor, the headcount ratio remains silent on anything money can’t buy.

The MPI solves these problems. First, in contrast to the headcount ratio’s narrow focus on money, the MPI accounts for health, education, and living standards by incorporating data from ten distinct indicators including child mortality, school attendance, and access to electricity. The MPI also accounts for the depth of poverty. While the headcount ratio simply reports the percentage of the population below the poverty line, each country’s MPI score also accounts for the percentage of those experiencing multidimensional poverty and the average level of deprivation among the poor. The MPI and metrics like it provide us with an objectively more accurate picture of poverty than their predecessors.

What makes a good metric, anyhow?

The MPI describes poverty more accurately than the headcount ratio. But I consider it to be an inferior measure of poverty in today’s policy environment—full stop. While these statements seem contradictory, they aren’t. The value of any metric depends on our reasons for measurement. And when it comes to measuring poverty, our objective is to eliminate it. This means convincing policymakers and the public to act. While accuracy reigns supreme in academia, policymakers live in a world of competing priorities and shrinking attention spans. In 2015, Microsoft estimated the human attention span at eight seconds. For anyone keeping score, that’s one second less than your average goldfish. So, what does an MPI score of 0.517 mean? Eight seconds isn’t going to be enough.

What the headcount ratio lacks in accuracy, it makes up for with simplicity. The World Bank’s global headcount ratio, calculated against a $1 per day poverty line (since updated to $2.15), has proved to be an invaluable rallying cry in the fight against global poverty for a reason: it is easy to understand in both practical and moral terms. When it made its debut in 1990, the global headcount ratio revealed that almost 40% of the world’s population was living on less than one dollar a day. Even for those allergic to math, eight seconds is more than enough to understand this metric and the human suffering it represents. And in our dynamic world, it is this power to command attention and compel action that matters most.

So, have we made any progress?

While I believe our most rudimentary poverty metrics remain the most valuable ones, this doesn’t mean we haven’t made progress on poverty measurement. Metrics like the Multidimensional Poverty Index represent valuable innovations that address the very real shortcomings of earlier approaches. The issue here is not a lack of progress on poverty measurement but our ever-deepening aversion to nuance.

Understanding the lives of the poor is worth much more than eight seconds, and when policymakers are ready to pay attention, the data is there. Until then, the question remains: what does it mean to live in a country that is 0.517 poor? What about a country where 31% of the population lives on less than $2.15 per day? I’ll let you decide which metric will do more for the citizens of Chad.