I am an economist on a 5-year research fellowship at Stanford University's Hoover Institution. I work on topics across public and labor economics, often partnering with government agencies to improve public services and gain insight into social behavior.
I received a PhD in Economics from Harvard University and a BA in Economics and International Relations from Stanford University.
Office: Herbert Hoover Memorial Building (HHMB) 107
434 Galvez Mall
Stanford, CA 94305
Female workers earn $0.89 for each male-worker dollar even in a unionized workplace where tasks, wages, and promotion schedules are identical for men and women by design. Using administrative time-card data on bus and train operators, we show that this earnings gap can be explained by female operators taking fewer hours of overtime and more hours of unpaid time-off than male operators. Female operators, especially those with dependents, pursue schedule conventionality, predictability, and controllability more than male operators. We demonstrate that while reducing schedule controllability can limit the earnings gap, it can also hurt female workers and their productivity.
We study the mental health of graduate students at 8 top-ranked economics PhD programs in the U.S. Using clinically validated surveys, we find that 24.8% experience moderate or severe symptoms of depression or anxiety - more than two times the population average. Though sample selection concerns exist, alternative estimates nonetheless suggest higher prevalence rates of such symptoms than in the general population. Mental health issues are especially prevalent at the end of the PhD program: 36.7% of students in years 6+ of their program experience moderate or severe symptoms of depression or anxiety, versus 21.2% of first-year students. 25.2% of economics students with these symptoms are in treatment, compared to 41.4% of graduate students in other programs. A similar percentage of economics students (40-50%) say they cannot honestly discuss mental health with advisers as say they cannot honestly discuss research progress or non-academic career options. Only 26% find their work to be useful always or most of the time, compared to 70% of economics faculty and 63% of the working age population. We provide recommendations for students, faculty, and administrators on ways to improve graduate student mental health.
Using a network approach, we show how the federal funds market was transformed during the financial crisis through the collapse of the ABCP market in 2007, changes in monetary policy implementation, and an increase in counterparty credit risk. For both aggregate and bank-level network metrics, we find that increases in counterparty and liquidity risk are associated with reduced lending activity within the network. We also provide evidence that network peer effects are strong and influence banks’ holdings of reserve balances and rates paid in the federal funds market. Finally, we document how these changes to the network structure dampened the transmission of monetary policy.
Most U.S. government spending on highways and bridges is done through “scaling” procurement auctions, in which private construction firms submit unit price bids for each piece of material required to complete a project. Using data on bridge maintenance projects undertaken by the Massachusetts Department of Transportation (MassDOT), we present evidence that firm bidding behavior in this context is consistent with optimal skewing under risk aversion: firms limit their risk exposure by placing lower unit bids on items with greater uncertainty. We estimate bidders’ risk aversion, the risk in each auction, and the distribution of bidders’ private costs. Simulating equilibrium item-level bids under counterfactual settings, we estimate the fraction of project spending that is due to risk and evaluate auction mechanisms under consideration by policymakers. We find that scaling auctions provide substantial savings relative to lump sum auctions and show how our framework can be used to evaluate alternative auction designs.
I use regression discontinuity analysis to measure the effect of one of the Affordable Housing Goals, the Underserved Areas Goal (UAG), on the number of whole single‐family mortgages purchased by Fannie Mae and Freddie Mac (GSEs) in undeserved census tracts for 1996–2002. Focusing additionally on tracts that became UAG‐eligible in 2005–2006, I measure the effect of the UAG during peak years for the subprime market. The results suggest a small UAG effect and challenge the view that the goals caused the GSEs to supply substantially more credit to high‐risk borrowers than they otherwise would have supplied during the subprime boom.