Papers In Progress:
The Effects of Floodplain Regulation on Housing Markets (Job Market Paper, with Anna Russo)
We investigate the effects of housing regulations designed to correct a wedge between privately- and socially-optimal construction in areas at risk of flooding in Florida. Using a spatial regression discontinuity around regulatory boundaries and an event study around the policy's introduction, we document that floodplain regulation reduces new construction in high-risk areas and increases the share of newly-built houses that are elevated. Embedding these effects in a model of residential choices with elastic housing supply, we find that the policy reduces expected flood damages by 60%. One-quarter of this reduction is driven by relocation of new construction to lower-risk areas, and three-quarters is driven by elevation of houses remaining in risky areas. However, this second-best policy achieves at best about 10% of possible welfare gains because of poor targeting. It overcorrects in many areas, inducing more consumers to elevate and relocate than is socially-optimal, while still allowing inefficiently-high construction in the riskiest places. By contrast, a flexible corrective tax on flood risk would achieve substantial welfare gains of more than $2,700 per newly-developed house.
Ex-Ante Moral Hazard in Wildfire Insurance (with Anna Russo)
- We study whether home insurance coverage increases wildfire risk in California. We have leveraged quasi-random variation in insurance premiums to provide an instrument for insurance coverage. In ongoing work, we are exploring the impact of insurance on wildfire risk. Thinning vegetation reduces wildfire risk, but until recently, insurers have been unable to contract on this behavior, potentially leading to moral hazard. We will use computer vision algorithms to extract vegetation extent from high-resolution satellite data, and we will combine this with building footprint data to measure risk mitigation activity.
Weathering Shocks: The Case of Energy Bills
- I study the income risk imposed on low-income households by extreme weather events which trigger spikes in energy bills. With aggregated grocery store spending data, I find that cold snaps induce low-income households to disproportionately substitute towards home cooking. Using proprietary, anonymized administrative financial transactions data, I will be able to isolate the causal effect of larger energy bills by interacting extreme weather events with quasi-random spatial, temporal, and technological variation in energy costs. I will also be able to measure the impact of changes in energy bills on outcomes such as restaurant spending, appliance purchases, prescription drug spending, and hospital visits.
Selection and Screening: The Case of Mammograms (with Liran Einav, Amy Finkelstein, Tamar Oostrom and Heidi Williams) American Economic Review, December 2020
- We analyze selection into screening in the context of recommendations that breast cancer screening start at age 40. Combining medical claims with a clinical oncology model, we document that compliers with the recommendation are less likely to have cancer than younger women who select into screening or women who never screen. We show this selection is quantitatively important: shifting the recommendation from age 40 to 45 results in three times as many deaths if compliers were randomly selected than under the estimated patterns of selection. The results highlight the importance of considering characteristics of compliers when making and designing recommendations.