research

In many low income countries, a regulated formal sector and an unregulated informal sector coexist within the same industry and occupation. Understanding why workers choose to work at informal rather than formal jobs is critical to crafting effective labor market policy. This paper studies the importance of two determinants of worker sorting between sectors: (1) search frictions and (2) worker preferences for nonwage amenities. Focusing on the garment industry in urban Bangladesh, I collect data on workers’ job histories and elicit their preferences for specific job amenities in a choice experiment. I use the data to estimate a partial equilibrium model of job search that incorporates (1) a dual-sector labor market with sector-specific search frictions and (2) heterogeneous preferences for amenities. I find that search frictions differ by sector—workers searching for a job from unemployment are 22pp more likely to receive offers from the informal sector than the formal sector over the course of a year. Additionally, preferences for nonwage amenities are strong, with some workers willing to pay nearly 30% of their wages for amenities like good supervisors and factory formality. Finally, I use the model to understand the impact of various unemployment benefit policies, from universal cash transfers to targeted unemployment insurance. I show that targeted policies, which are hard to implement in a high-informality setting, can push workers who are more salary-motivated into the informal sector.

How do households in low-income countries (LICs) respond to changes in public health funding? This paper studies household health and expenditure decisions in Malawi before and after the country’s 2013 Cashgate scandal, which led to a large and persistent withdrawal of general budget support from international donors to the Malawian government. Leveraging data on the universe of health facilities in Malawi, I construct a measure of exposure to the funding shock, which differs by subdistrict due to variation in the funding sources of health facilities available in each area. I then estimate the causal effect of the shock on household health decisions using a differences-in-differences design with shock exposure as a continuous treatment. I find that households most affected by the funding shock are less likely to visit government-funded facilities and get less preventive care. Results are heterogeneous by income, with richer households seeking more at-home and pharmacy-based care while poorer households continue to use government funded facilities. This paper's analysis highlights the need to incorporate more distributional and behavioral considerations when informing health policy decisions in LICs.