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. Usingpanel data fromrural India,we show how conventional poverty measures can distort understandings of poverty: exposure to poverty is wider andmore common than typicallymeasured, 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.