The poverty rate is an important focus of economic policy. We show, however, that in low- and middle-income countries, the poverty rate is often not what it seems. Poverty, as conventionally measured, is thought to be the proportion of households that are poor for the year, but we show that, under common data collection practices, the measure instead captures the average share of the year that households are poor. The resulting poverty rates are sensitive to the timing of household consumption, not just its total value. For policy, this means that, contrary to common assumptions, the de facto concept of national poverty in many countries is sensitive to households’ exposure to shocks and their ability to smooth consumption within the year. While created inadvertently, this de facto concept of poverty has appealing properties as a measure of well-being, and it raises new philosophical questions about the nature of deprivation. This transformation has happened without a change in the form of the poverty measures and without longitudinal data. Instead, the transformation follows from three common practices used when collecting household data: asking survey questions with short-term recall (often covering only the past week’s or month’s spending), stratifying on sub-periods (usually quarters), and surveying households only once during the year. We illustrate the implications with monthly panel data from rural India, showing that time-sensitivity in poverty measurement has quantitatively large impacts on measured poverty, improves predictions of health outcomes, and expands the scope of strategies to reduce global poverty.
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What Win-Win Lost: Rethinking Microfinance Subsidy in the Past and Designing for the Future
The modern microfinance industry was built on the idea that lenders could (and should) profit while serving poor and excluded customers. This idea—that lenders could “win” while customers would also “win” —inspired the broader field of social enterprise and opened possibilities for business-driven responses to social problems. However, in hindsight it is possible to see that not only was the idea flawed—important claims underpinning the core idea have failed to find empirical support—but the lingering belief that “win-win” was right continues to handicap not only financial inclusion and consumer protection policies, but the social investment and finance industry as a whole. The win-win formulation was driven by the assertion that customers would be indifferent to the level of interest rates on loans and that it was simply access to finance that mattered most to customers. The argument was used to justify charging the highest interest rates to the most operationally expensive customers, who turned out to not coincidentally be the poorest customers. However, studies show that customers are indeed sensitive to interest rates and that high interest rates discourage borrowers. Moreover, despite charging high rates, financial data show that most lenders failed to earn profit after fully accounting for the subsidies received from donors and social investors. Microfinance and the social investment industry it helped spawn remain important tools for addressing poverty and inequality, but both sectors are overdue for a transparent reckoning of the roles of subsidy (including its benefits) and greater recognition of the potential for exclusion caused by high prices and the drive for profitability or “sustainability”. Muddled thinking on subsidy and prices handicapped the past but does not need to handicap the future.
Poverty at Higher Frequency
Poverty is typically measured as insufficient yearly income or consumption. In practice, however, poverty is marked by seasonality, economic instability, and illiquidity across months. To capture within-year variability, we extend traditional poverty measures to include a temporal dimension. Using panel data from rural India, we show how conventional poverty measures can distort understandings of poverty: exposure to poverty is wider and more common than typically measured, and poverty entry and exit are not sharp transitions. Accounting for within-year variability improves predictions of anthropometrics, and targeting transfers to challenging periods can reduce poverty most effectively by compensating for imperfect consumption smoothing.