An article in Fast Company highlights a new collaboration between CEGA Faculty Director Josh Blumenstock and Facebook’s Data for Good to produce a “Relative Wealth Index,” which would be available to nonprofit organizations and governments to assist in more accurately targeting cash assistance to the poorest households, given the scarcity of accurate wealth metrics:
“Adding to an already overwhelming global poverty crisis, the pandemic increased the need for humanitarian aid distribution. In December, the UN appealed for $35 billion to be allotted to the 160 million in need around the world. With limited resources, and some countries cutting assistance, it’s important that the very poorest receive funds first. But need is incredibly hard to assess and usually relies on a combination of survey data that’s only sporadically collected, along with a rather limited well of geospatial data. The targeting that results is often indefinite and overly broad.
Improving that pinpointing is the goal of a collaboration between UC Berkeley’s Center for Effective Global Action and Facebook’s Data for Good, the tech giant’s policy branch. The joint effort is producing extremely granular “micro-estimates” of socioeconomic status, down to 2-kilometer-by-2-kilometer squares, for 135 low- to middle-income countries. Each grid square contains a measure of absolute wealth, or the average wealth of people in that area, in dollar terms, and of relative wealth, compared to other areas in the same country. The new model—called the Relative Wealth Index—will be freely available to nonprofits and governments as they decide how to distribute cash assistance to the developing world. “The more granular you’re targeting, the more likely it is that more benefits will go to the poorer people than wealthier people,” says Joshua Blumenstock, associate professor at UC Berkeley, who’s leading the initiative there.”
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