Working papers

Where to Build Affordable Housing? Evaluating the Tradeoffs of Location

with Pearl Z. Li and Ariel J. Binder. June 2024
[abstract] [pdf]
How does the location of affordable housing affect household welfare, the distribution of assistance, and broader societal objectives such as racial integration? Using administrative data on tenants of units funded by the Low-Income Housing Tax Credit (LIHTC), we first show that tenant characteristics such as race and proxies for need vary widely across neighborhoods. Despite fixed eligibility requirements, tenants of LIHTC developments in higher-opportunity neighborhoods are higher income, more educated, and far less likely to be Black. To quantify the welfare implications, we build a residential choice model in which households choose from both market-rate and affordable housing options, where the latter must be rationed. While providing affordable housing in higher-opportunity neighborhoods costs more, it also increases household welfare and reduces city-wide segregation. The gains in household welfare, however, accrue to more moderate-need and white (non-Hispanic) households at the expense of high-need and Black or Hispanic households. This change in the distribution of assistance is primarily due to a `crowding out' effect: households that only apply for assistance in higher-opportunity neighborhoods crowd out those willing to apply regardless of location. Other policy levers—such as lowering the income limits used for means-testing—have only limited effects relative to the initial choice of location.

Value Pricing or Lexus Lanes? The Distributional Effects of Dynamic Tolling

with Pearl Z. Li. December 2023
[abstract] [pdf]
This paper studies the welfare and distributional effects of dynamically priced highway toll lanes. To quantify the equilibrium effects of tolling, we develop and estimate a model of driver demand, the road technology, and the pricing algorithm. The demand model features heterogeneous drivers choosing both where and when to drive, as well as uncertainty about prices and travel times. A key welfare channel is the option value of tolling: even drivers who infrequently take the priced lanes can benefit from having the option but not the obligation to pay for speed. The model is estimated using data on toll transactions, historical traffic conditions, and driver characteristics from the I-405 Express Toll Lanes in Washington State. Relative to a world in which the same number of highway lanes are all free, status-quo tolling increases aggregate welfare and benefits drivers in all income quartiles, driven in large part by the option value. Moreover, we find that drivers in the bottom income quartile gain the most under status-quo tolling. Low-income drivers have the longest I-405 commutes and they face low prices relative to their time savings from the priced lanes. They also have high option values of tolling because they are more price-sensitive, so they are more likely to be marginal when deciding between the priced and unpriced lanes. Finally, we show how simple revisions to the pricing algorithm can increase aggregate welfare and achieve redistributive goals.
Media: Marginal Revolution

Heterogeneous Preferences for Neighborhood Amenities: Evidence from GPS Data

Revise and resubmit, Review of Economics and Statistics. May 2023
[abstract] [pdf] [download NAQI data]
I study how preferences for neighborhood amenities vary by income. Using data on over 150 million visits to restaurants, shops, personal services, and entertainment places, I estimate a model of demand for amenities. I find that higher and lower-income urban residents have heterogeneous preferences for individual establishments, which often vary systematically along observable dimensions such as category, brand, and price level. Using the location and estimated quality of each establishment, I construct an aggregate Neighborhood Amenity Quality Index (NAQI) that measures the value of each neighborhood's overall access to amenities. Despite the heterogeneity in establishment-level preferences, neighborhood-level preferences exhibit a strong positive correlation; higher and lower-income residents generally agree on the quality of a neighborhood's overall access to amenities. Densely populated neighborhoods close to the urban core have especially high-quality access to amenities. Conditional on population density, neighborhoods with better amenity access tend to be richer, more educated, and have more expensive rents.

Socioeconomic Network Heterogeneity and Pandemic Policy Response

with Mohammad Akbarpour, Aude Marzuoli, Simon Mongey, Abhishek Nagaraj, Matteo Saccarola, Pietro Tebaldi, and Shoshana Vasserman. June 2020
[abstract] [pdf] [website]
We develop and implement a heterogeneous-agents network-based empirical model to analyze alternative policies during a pandemic outbreak. We combine several data sources, including information on individuals' mobility and encounters across metropolitan areas, information on health records for millions of individuals, and information on the possibility to be productive while working from home. This rich combination of data sources allows us to build a framework in which the severity of a disease outbreak varies across locations and industries, and across individuals who differ by age, occupation, and preexisting health conditions. We use this framework to analyze the impact of different social distancing policies in the context of the COVID-19 outbreaks across US metropolitan areas. Our results highlight how outcomes vary across areas in relation to the underlying heterogeneity in population density, social network structures, population health, and employment characteristics. We find that policies by which individuals who can work from home continue to do so, or in which schools and firms alternate schedules across different groups of students and employees, can be effective in limiting the health and healthcare costs of the pandemic outbreak while also reducing employment losses.
Media: Stanford News, Plugging the Gap, Berkeley Haas

Published papers

Urban Mobility and the Experienced Isolation of Students

with Lindsey Currier and Edward Glaeser
Nature Cities, Volume 1, Issue 1: 73–82, January 2024
[abstract] [pdf]
Cities provide access to stores, public amenities and other people, but that access may provide less benefit for lower-income and younger urbanites who lack money and means of easy mobility. Using detailed GPS location data, we measure the urban mobility and experienced racial and economic isolation of the young and the disadvantaged. We find that students in major metropolitan areas experience more racial and income isolation, spend more time at home, stay closer to home when they do leave, and visit fewer restaurants and retail establishments than adults. Looking across levels of income, students from higher-income families visit more amenities, spend more time outside of the home, and explore more unique locations than low-income students. Combining a number of measures into an index of urban mobility, we find that, conditional on income, urban mobility is positively correlated with home neighborhood characteristics such as distance from the urban core, car ownership, and social capital.

The Gender Pay Gap in the Gig Economy: Evidence from over a Million Uber Drivers

with Rebecca Diamond, Jonathan Hall, John List, and Paul Oyer
Review of Economic Studies, Volume 88, Issue 5: 2210–2238, October 2021
[abstract] [pdf] [published version] [slides] [twitter thread]
The growth of the gig economy generates worker flexibility that, some have speculated, will favor women. We explore this by examining labor supply choices and earnings among more than a million rideshare drivers on Uber in the U.S. We document a roughly 7% gender earnings gap amongst drivers. We show that this gap can be entirely attributed to three factors: experience on the platform (learning-by-doing), preferences over where to work (driven largely by where drivers live and, to a lesser extent, safety), and preferences for driving speed. We do not find that men and women are differentially affected by a taste for specific hours, a return to within-week work intensity, or customer discrimination. Our results suggest that there is no reason to expect the gig economy to close gender differences. Even in the absence of discrimination and in flexible labor markets, women's relatively high opportunity cost of non-paid-work time and gender-based differences in preferences and constraints can sustain a gender pay gap.
Media: Freakonomics, Marginal Revolution, Washington Post, Financial Times, The Verge, Quartz, Brookings, Telegraph, Fortune, Bloomberg, The Economist

Older Workers and the Gig Economy

with Rebecca Diamond and Paul Oyer
AEA Papers and Proceedings, 109: 372-376. 2019
[abstract] [pdf] [published version]
One way for older workers to ease into retirement is to move to the gig economy where they can freely choose hours and intensity of work. We look at age/wage profiles of workers in the traditional labor market and of Uber drivers. While the move to the gig economy generates flexibility, it also moves pay closer to a spot market where individuals earn (presumably) their marginal product. Earnings for workers in traditional jobs increase steeply with age, while Uber earnings are steadily declining after age forty. This highlights the tradeoff between flexible work arrangements and earnings.
Media: LAist, GSB Insights