Eviction and poverty in American cities     [pdf]  [publisher's link]  [NBER working paper]  [econimate video]     Quarterly Journal of Economics (2023)
(with Rob Collinson, John Eric Humphries, Nick Mader, Davin Reed, and Daniel Tannenbaum)

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 pose 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). Media coverage: The Economist, New York Times.

Selection bias in voluntary random testing: evidence from a COVID-19 antibody study     [pdf]  [publisher's link]     AEA Papers & Proceedings (2023)
(with Deniz Dutz, Michael Greenstone, Ali Hortacsu, Santiago Lacouture, Magne Mogstad, Azeem Shaikh, and Alex Torgovitsky)

Centralized school choice with unequal outside options    [pdf]  [publisher's link]     Journal of Public Economics (2022)
(with Mohammad Akbarpour, Adam Kapor, Chris Neilson, and Seth Zimmerman) 

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.


Selection in surveys: using randomized incentives to detect and account for nonresponse bias    [pdf]  [NBER working paper]  [BFI working paper]  [BFI research brief (non-technical)]  [VoxEU column]     Revise & resubmit, Review of Economic Studies
(with Deniz Dutz, Ingrid Huitfeldt, Santiago Lacouture, Magne Mogstad, and Alex Torgovitsky)

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.

Non-representativeness in population health research: evidence from a COVID-19 antibody study    [NBER working paper]  [BFI working paper]  [BFI research brief (non-technical)]     Conditionally accepted, AER: Insights
(with Deniz Dutz, Michael Greenstone, Ali Hortacsu, Santiago Lacouture, Magne Mogstad, Azeem Shaikh, and Alex Torgovitsky) 

We analyze representativeness in a COVID-19 serological study with randomized participation incentives. We find large participation gaps by race and income when incentives are lower. High incentives increase participation rates for all groups, but increase them more among underrepresented groups. High incentives restore representativeness on race and income, and also on health variables likely to be correlated with seropositivity, such as the uninsured rate, hospitalization rates, and an aggregate COVID-19 risk index.

Media coverage: New York Times, STAT.

Conviction, incarceration, and recidivism: understanding the revolving door    [pdf]    Revise & resubmit, Quarterly Journal of Economics
(with John Eric Humphries, Aurelie Ouss, Kamelia Stavreva, and Megan Stevenson)
We study the effects of conviction and incarceration on recidivism using quasi-random judge assignment. We extend the typical binary-treatment framework to a setting with multiple treatments, and outline a set of assumptions under which standard 2SLS regressions recover causal and margin-specific treatment effects. Under these assumptions, 2SLS regressions applied to data on felony cases in Virginia imply that conviction leads to a large and long-lasting increase in recidivism relative to dismissal, consistent with a criminogenic effect of a criminal record. In contrast, incarceration reduces recidivism, but only in the short run. The assumptions we outline could be considered restrictive in the random judge framework, ruling out some reasonable models of judge decision-making. Indeed, a key assumption is empirically rejected in our data. Nevertheless, after deriving an expression for the resulting asymptotic bias, we argue that the failure of this assumption is unlikely to overturn our qualitative conclusions. Finally, we propose and implement alternative identification strategies. Consistent with our characterization of the bias, these analyses yield estimates qualitatively similar to those based on the 2SLS estimates. Taken together, our results suggest that conviction is an important and potentially overlooked driver of recidivism, while incarceration mainly has shorter-term incapacitation effects.

The socio-economic consequences of housing assistance     [pdf]     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.


Eviction and 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)

Non-payment and eviction in the rental housing market (with John Eric Humphries, Scott Nelson, Dam Linh Nguyen, and Daniel Waldinger)

Right-to-Counsel and rental housing markets: quasi-experimental evidence from New York (with Rob Collinson, John Eric Humphries, Stephanie Kestelman, Scott Nelson, and Daniel Waldinger)

The effects of emergency rental assistance during the pandemic: evidence from lotteries in four cities (with Rob Collinson, Anthony DeFusco, John Eric Humphries, Ben Keys, David Phillips, Vincent Reina, and Patrick Turner)