Research
Research
Time Costs and Take-up of Free HIV Care (Job Market Paper)
Abstract: Even if healthcare is free, patients may still pay for treatment in the form of lost income. Despite the wide availability and free provision of antiretroviral therapy (ART), a life-saving treatment for HIV, AIDS-related mortality remains a leading cause of death for adults in Sub-Saharan Africa. In this paper, I provide evidence from Malawi that time costs are a key barrier to adherence to ART. My staggered difference-in-differences empirical strategy exploits the random timing of appointments relative to floods, which generate exogenous variation in labour productivity and reduce agricultural by 45% in subsequent weeks. I show that this negative shock to the value of time is a significant determinant of demand for ART. Floods cause a 50% reduction in the number of patients who miss appointments to refill their medication, and lead to better long-term adherence and lower mortality. Having an appointment in the weeks following a flood when the value of time is low, compared to just before, causes a 2 percentage points lower likelihood of stopping ART for three months or longer and a 20% lower risk of death within a year. Floods can both increase and decrease staple crop yields depending on when in the maize life cycle they occur, but always decrease labour supply and increase adherence to ART, suggesting that the variation in time costs is a more important mechanism than direct shocks to future consumption. My estimates imply that reducing the likelihood of three-month treatment interruptions from its peak in the busy rainy season to its low in the dry season could decrease mortality rates by 15%.
Temporary Unemployment and Labor Market Dynamics During the COVID-19 Recession (Brookings Papers on Economic Activity, 2020)
with Kory Kroft, Fabian Lange and Matthew J. Notowidigdo
PDF | Brookings | Online Appendix | NBER | Executive Summary | Replication Kit
Abstract: This paper develops a search-and-matching model that incorporates temporary unemployment and applies the model to study the labor market dynamics of the COVID-19 recession in the US. We calibrate the model using panel data from the Current Population Survey for 2001-2019, and we find that the model-based job finding rates match observed job finding rates during the entire sample period and out-of-sample up through July 2020. We also find that the Beveridge curve is well-behaved and displays little change in market tightness in 2020 once we use the calibrated model to adjust for changes in the composition of the unemployed. We then use the model to project the path of unemployment over the next 18 months. Under a range of assumptions about job losses and labor demand, our model predicts a more rapid recovery compared to a model that does not distinguish between temporary and permanent unemployment and compared to professional and academic forecasts. We find that in order to rationalize the professional forecasts of the unemployment rate, some combination of the vacancy rate, job separation rate, and recall rate of workers on temporary layoff must deteriorate substantially from current levels in the next several months.
Peer Effects in Adherence to HIV Treatment: Evidence from Malawi's Teen Clubs