Projects
Recent working papers
The Design and Impact of Cash Transfers: Experimental Evidence from Compton, California (with Sidhya Balakrishnan, Sewin Chan, Sara Constantino, and Johannes Haushofer). Randomly chosen low-income households in Compton, CA received unconditional cash transfers averaging roughly $500 monthly. Half received transfers twice monthly, half quarterly. Eighteen months later, twice-monthly transfers improved food security relative to quarterly transfers, but had no other differential effects on pre-specified main outcomes. Averaging across frequencies, monthly income (excluding transfers) was lower than controls by $333, and expenditures (excluding major durables) by $302, without changes in other primary outcomes, including overall labor supply. In line with this, we find suggestive evidence that households paid down debt and purchased durables. Transfers also affected part-time work, housing security, and violence.
Poverty at Higher Frequency (with Joshua Merfeld). National poverty rates are meant to track the share of populations that are poor in a given year. We show that, instead, de facto poverty rates often reflect the fraction of the year that households experience poverty. This transformation arises in low- and middle-income countries that follow expert guidelines for collecting household expenditure data. The de facto measures reflect seasonal variability and register deprivations of households not usually considered poor. With panel data from India we show how, contrary to historical definitions, global poverty depends on households’ abilities to smooth consumption within the year.
Ideas for India: India’s Poverty Rate Does Not Measure What You Think It Does
Selecting Experimental Sites for External Validity (with Michael Gechter, Keisuke Hirano, Jean Lee, Mahreen Mahmud, Orville Mondal, Saravana Ravindran, and Abu Shonchoy). Policy decisions often depend on evidence generated elsewhere. We take a decision theoretic approach to choosing where to experiment to optimize external validity. We frame external validity through a policy lens, taking a Bayesian approach and developing a prior specification for the joint distribution of site-level treatment effects using a microeconometric structural model and allowing for other sources of heterogeneity. With data from South Asia, we show that, relative to basing policies on experiments in optimal sites, large efficiency losses result from instead using evidence from randomly-selected sites or, conversely, from sites with the largest expected treatment effects.