Researchers measure poverty traps in Peru using household data nobody thought to analyze

A new statistical method lets researchers track how families move in and out of poverty using rotating household survey data that earlier methods couldn't fully use. This means governments can now measure whether poor households stay poor, escape poverty, or cycle in and out of it, using data they already collect instead of waiting for expensive new surveys.

Poverty measurement in poor countries has been stuck: long-term household surveys are expensive and rare, so policymakers have had to guess at whether their anti-poverty programs actually work. This method uses Peru's existing household survey data — collected in waves, not continuous — to track real poverty persistence and mobility without waiting years for panel data to accumulate. The practical shift: development banks and governments can now see which poverty is temporary and which is structural, using data they already have. That changes what poverty-reduction programs they build next.