It has often been said that the world’s aggregate poverty gap—the total monetary amount by which all poor people fall below the poverty line—is modest when one uses poverty lines typical of low-income countries. The implication is sometimes drawn that only a modest sum of money is needed to eliminate global poverty—to bring all poor people up to the international poverty line. However, eliminating poverty may well be a lot harder than the size of the aggregate poverty gap might suggest. Identifying who is poor and by how much is challenging. The poverty gap calculation could be way off the mark. The presentation will draw on the following two papers (with Caitlin Brown) that have tried to assess whether the data typically available and routinely used by policymakers in sub-Saharan Africa—the poorest region of the world by most measures—are adequate to reliably identify who is poor. It will be shown that even with a budget sufficient to eliminate poverty with full information, standard proxy-means tests do not bring the poverty rate below about three-quarters of its initial value. Nor does the optimal (poverty-minimizing) allocation of transfers based on the information typically available do much better. The prevailing methods are particularly deficient in reaching the poorest households. And even when poor households are reached, poor individuals are often missed. Indeed, roughly three-quarters of underweight women and undernourished children are not found in the poorest 20% of households, and around half are not found in the poorest 40%. Some potential improvements in current targeting methods are considered, as is a universal basic income as a policy option.
Watch and join us via Live Chat: Seminar will be live-streamed, allowing for online audience participation (only available during the seminar)