Research

Working Papers

Algorithm tools have the potential to improve public service efficiency, but our understanding of how experts use algorithms is limited, and concerns about resulting bias are widespread. We randomize access to algorithm support for workers allocating Child Protective Services (CPS) investigations. Access to the algorithm reduced maltreatment-related hospitalizations, especially for disadvantaged groups, while reducing CPS surveillance of Black children. Child injuries fell by 29 percent. Workers improved their scrutiny of complementary information emphasized by the algorithm, and targeted investigations to children at greater risk of harm irrespective of algorithm-predicted risk. Algorithm-only counterfactuals confirm human-algorithm complementarity for both efficiency and equity.


AEA RCT Registry: AEARCTR-0006311

NeurIPS 2021 Workshop on Human and Machine Decisions Top-Three Finalist

More than 20 percent of young adult prison inmates in the United States have spent time in foster care, among whom a majority have lived in a congregate care (group-based) setting. Using three decades of administrative data from Wisconsin, we leverage exogenous variation in the relative delinquency status and imprisonment risk of foster care peers to study how peer composition affects youth's future criminal justice system contact, educational attainment, and short-term risky behavior. A one standard deviation increase in peer risk is associated with a modest 2.5 percent increase in a youth's likelihood of dropping out of high school. However, peer risk has no effect on a child's likelihood of entering prison by age 20, nor on a number of other indicators of deviant behavior. Our findings have policy implications for the recent Family First Prevention Services Act, which incentivizes the reallocation of children away from congregate care.

Presented at: AEA Annual Conference, APPAM

Payments to foster parents are among the largest per capita support payments targeted toward disadvantaged children in the United States. These payments vary considerably by state and have been the subject of longstanding policy debates, but the overall effect of payments on children's quality of care is theoretically ambiguous. We study the effect of foster care payments on caregiver labor supply, children’s foster care experiences, and children’s health using two sources of variation: natural variation in increases to state statutory payment rates and age-specific payment discontinuities that vary by state. To measure short-term outcomes, we assemble an extensive 13-year, 39-state panel of payment rates combined with microdata from Medicaid enrollment, claims, the Adoption and Foster Care Analysis and Reporting System (AFCARS), and the American Community Survey. In contrast to the prior literature, we find that increasing foster care payments has only a modest effect on whether a child is placed with a family versus in group-based care: less than a one percent increase in family home placement per $1,000 increase in a state’s annual payment rate. Further, we find little evidence of benefits along multiple dimensions of child well-being. Our findings highlight the limitations of payments to caregivers as a cost-effective strategy for improving children’s quality of care.

Presented at: APPAM, ASHEcon Emerging Scholars, University of Sydney

Work in Progress

Fostering Independence: Can Incentivized Case Management and Savings Accounts Improve Early-life Outcomes for Youth Aging out of Foster Care?

with Jonathan Tebes

Racial Disparities and Decision Tools in Child Protection 

with Emily Putnam-Hornstein


Additional projects unlisted due to ongoing data agreements!