Centralized school choice with unequal outside options (with Mohammad Akbarpour, Adam Kapor, Chris Neilson, and Seth Zimmerman) [paper] Journal of Public Economics (2022)
We study how market design choices exacerbate or mitigate pre-existing inequalities among participants. We introduce outside options in a well-known school choice model, and show that students always prefer manipulable over strategy-proof mechanisms if and only if they have an outside option. We test for the proposed relationship between outside options and manipulability in a setting where we can identify students' outside options and observe applications under two mechanisms. Consistent with theory, students with an outside option are more likely to list popular, highly-rated schools under the Boston mechanism, and this gap disappears after switching to a Deferred Acceptance mechanism.
Eviction and poverty in American cities (with Rob Collinson, John Eric Humphries, Nick Mader, Davin Reed, and Daniel Tannenbaum) [draft] Accepted, Quarterly Journal of Economics
More than two million U.S. households have an eviction case filed against them each year. Policymakers at the federal, state, and local levels are increasingly pursuing policies to reduce the number of evictions, citing harm to tenants and high public expenditures related to homelessness. We study the consequences of eviction for tenants using newly linked administrative data from two large cities. We document that prior to housing court, tenants experience declines in earnings and employment and increases in financial distress and hospital visits. These pre-trends are more pronounced for tenants who are evicted, which poses a challenge for disentangling correlation and causation. To address this problem, we use an instrumental variables approach based on cases randomly assigned to judges of varying leniency. We find that an eviction order increases homelessness, and reduces earnings, durable consumption, and access to credit. Effects on housing and labor market outcomes are driven by impacts for female and Black tenants.
This paper replaces "Does eviction cause poverty? Quasi-experimental evidence from Cook County, IL" (2019).
This project is supported by the National Science Foundation, the Laura and John Arnold Foundation, the Spencer Foundation, the Kreisman Initiative on Housing Law and Policy, the Horowitz Foundation for Social Policy, the Robert Wood Johnson Foundation, the Becker Friedman Institute, and the Tobin Center for Economic Policy. It is part of the "Using Linked Data to Advance Evidence-Based Policymaking" initiative, a collaboration between Chapin Hall and the Census Bureau. The project was referenced in the Economist and in the New York Times.
Selection in surveys: using randomized incentives to detect and account for nonresponse bias (with Deniz Dutz, Ingrid Huitfeldt, Santiago Lacouture, Magne Mogstad, and Alex Torgovitsky) [draft] [VoxEU] Under review
We show how to use randomized participation incentives to test and account for nonresponse bias in surveys. We first use data from a survey about labor market conditions, linked to full-population administrative data, to provide evidence of large differences in labor market outcomes between participants and nonparticipants, differences which would not be observable to an analyst who only has access to the survey data. These differences persist even after correcting for observable characteristics, raising concerns about nonresponse bias in survey responses. We then use the randomized incentives in our survey to directly test for nonresponse bias, and find strong evidence that the bias is substantial. Next, we apply a range of existing methods that account for nonresponse bias and find they produce bounds (or point estimates) that are either wide or far from the ground truth. We investigate the failure of these methods by taking a closer look at the determinants of participation, finding that the composition of participants changes in opposite directions in response to incentives and reminder emails. We develop a model of participation that allows for two dimensions of unobserved heterogeneity in the participation decision. Applying the model to our data produces bounds (or point estimates) that are narrower and closer to the ground truth than the other methods. Our results highlight the benefits of including randomized participation incentives in surveys. Both the testing procedure and the methods for bias adjustment may be attractive tools for researchers who are able to embed randomized incentives into their survey.
The socio-economic consequences of housing assistance [draft] Revision in progress
This paper analyzes the effect of Europe’s largest public housing program on socio-economic outcomes for low-income households. Using lotteries for housing units in the Netherlands and data linking national registers to application choices, I show that the average move into public housing negatively affects labor market outcomes and proxies for neighborhood quality, and increases public assistance receipt. However, consistent with a model of labor supply responses to conditional in-kind transfers, average impacts miss substantial heterogeneity both across neighborhoods and, within neighborhood, across recipients. Moves into high-income neighborhoods generate positive effects, which are driven by ‘upward’ moves made by individuals previously living in low- or middle-income neighborhoods. Lateral and ‘downward’ moves have the opposite effect. To evaluate whether these results generalize to non-recipients, I develop a model of application behavior that utilizes panel data on application choices and exploits variation induced by the housing allocation mechanism. Using the model, I recover the distribution of heterogeneity that drives selection into and returns from lotteries, and estimate that selection on gains is limited. This suggests that targeting public housing in high-income neighborhoods based on observable characteristics can increase economic self-sufficiency.
Representation and hesitancy in population health research: evidence from a COVID-19 antibody study (with Deniz Dutz, Michael Greenstone, Ali Hortacsu, Santiago Lacouture, Magne Mogstad, Azeem Shaikh, and Alex Torgovitsky) [draft] [non-technical summary] Under review
We examine why minority and poor households are often underrepresented in studies that require active participation. Using data from a serological study with randomized participation incentives, we find large participation gaps by race and income when incentives are low, but not when incentives are high. We develop a framework for using randomized incentives to disentangle the roles of hesitancy and non-contact in driving the participation gaps, and find that hesitancy is the predominant factor. Hesitancy rates strongly correlate with hospitalization rates and COVID-19 risk, suggesting that individuals facing higher health risks may be underrepresented in studies with low incentives.
Selection bias in voluntary random testing: evidence from a COVID-19 antibody study (with Deniz Dutz, Michael Greenstone, Ali Hortacsu, Santiago Lacouture, Magne Mogstad, Azeem Shaikh, and Alex Torgovitsky) [draft] Forthcoming in the American Economic Review Papers and Proceedings
WORK IN PROGRESS
Conviction, incarceration, and recidivism: understanding the revolving door (with John Eric Humphries, Aurelie Ouss, Kamelia Stavreva, and Megan Stevenson)
This paper examines the effects of conviction without incarceration -- a common outcome of criminal court proceedings -- and of incarceration on recidivism. We study felony cases in Virginia that are quasi-randomly assigned to judges, and make three contributions. First, we present estimates of the impact of conviction on recidivism based on a 2SLS regression with judge stringency instruments. If given a causal interpretation, our estimates would imply large and sustained increases in recidivism from receiving a conviction relative to dismissal. Using a similar research design, we find that incarceration reduces recidivism in the first year, likely due to incapacitation, with no longer-term effects. These conclusions about incarceration are further supported by analysis based on discontinuities in sentencing guidelines. Second, we discuss how, in multiple-treatment settings, some models of judge decision making facilitate the interpretation of 2SLS estimands as well-defined treatment effects, while others do not. In particular, we consider which models of the judge decision process imply that 2SLS estimates interpretable treatment effects for a particular margin, such as conviction vs dismissal, or incarceration vs conviction. Third, we discuss and implement several methods which allow us to recover margin-specific treatment effects under sets of assumptions where 2SLS estimates do not. Most of these yield conclusions similar in sign and magnitude to those drawn based on the 2SLS estimates, although they are sometimes less precise. We conclude that conviction may be an important and potentially overlooked driver of recidivism, while incarceration mainly has shorter-term incapacitation effects.
The effects of eviction on children’s wellbeing and educational attainment (with Rob Collinson, Deniz Dutz, John Eric Humphries, Nick Mader, and Daniel Tannenbaum)
Waiting time as a screening device: evidence from an affordable housing lottery (with Rob Collinson and Daniel Waldinger)
Screening, default, and eviction in the rental housing market (with John Eric Humphries, Scott Nelson and Daniel Waldinger)
Emergency assistance grants and household stability during the pandemic: evidence based on lotteries in five cities (with Rob Collinson, Anthony DeFusco, John Eric Humphries, Ben Keys, David Phillips, Vincent Reina, and Patrick Turner)