Machine learning methods are increasingly applied in the development policy arena. Among many recent policy applications, machine learning has been used to predict poverty, soil properties, and conflicts.
In a recent Policy Research Working Paper by Paolo Brunori, Paul Hufe and Daniel Mahler (BHM hereafter), machine learning methods are utilized to measure a popular understanding of distributional injustice – the amount of unequal opportunities individuals face. Equality of opportunity is an influential political ideal since it combines two powerful principles: individual responsibility and equality. In a world with equal opportunities, all individuals have the same chances to attain social positions and valuable outcomes. They are free to choose how to behave and they are held responsible for the consequences of their choices.
“Tell me where you live, and I can predict how well you’ll do in life.”
Does welfare vary largely across space?
Although I don’t have a crystal ball, I do know for a fact that location is an excellent predictor of one’s welfare. Indeed, a child born in Togo today is expected to live nearly 20 years less than a child born in the United States. Moreover, this child will earn a tiny fraction—less than 3%—of what his or her American counterpart will earn.
Cities in East Asia and the Pacific can be vibrant, exciting, and filled with opportunities. Yet we are always struck by their dichotomies: there are the bright lights, modern skyscrapers, air-conditioned malls, and the hustle and bustle of people coming and going to offices and shops.
And there are also neighborhoods with no safe drinking water, sanitation, or waste collection; where houses flood every time it rains; and where families spend long hours trying to earn enough to feed themselves and keep their children in school.
With an estimated 250 million people living in slums across the East Asia and Pacific region, and much more urbanization to come, prioritizing the delivery of basic services and ensuring opportunities for the urban poor presents an urgent call for action.
: climate change, natural disasters, poverty, water scarcity, food insecurity, global displacement, conflict and violence. These are not the kinds of challenges that will go away on their own—they feed off one another and flourish. The world is responding with the Sustainable Development Goals (SDG), which lay out a road map to building a more inclusive, peaceful and prosperous world—a better world.
In Part I of our blog —based on a background note we wrote for the World Bank’s 2017–2022 Country Partnership Framework for Ethiopia—we presented our key findings on the spatial or regional distribution of poverty and child malnutrition in Ethiopia.
In Part II of our blog, we look at changes in road density over the ten years from 2006 to 2016, and in nightlights in six cities over four years from 2012 to 2016.