Webinar: Poverty Estimation in Small Urban Areas

A high-resolution spatial understanding of poverty can help policymakers design effective interventions that target marginalized and vulnerable groups. Often data from detailed household surveys (e.g., LSMS, DHS) provide estimates of poverty at the national level, but these are spatially patchy. On the other hand, national census data fully represents the population but lacks detail needed to understand income or consumption. Combining these two types of data through statistical small area estimation methods we can produce high-resolution poverty maps. Such poverty mapping efforts are used by World Bank, National governments, and other Development Partners to understand poverty and inequality in data-scarce environments.

As part of the CHORUS webinar series,  Brian Robinson and Alicia Cavanaugh (McGill University) discussed the use of high-resolution spatial data on poverty, and how this can help policymakers design effective interventions targeted to marginalized and vulnerable populations. The session was chaired and moderated by Prof. Zahidul Quayyum (BRAC University).