Agenda

Matching market design traditionally wields microeconomic theory to improve efficiency and fairness in object allocation environments without money. My current research agenda extends developments in matching theory to design foster care and adoption matching mechanisms where novel elements irreducibly embed themselves in the market operation. Foster care requires additional design considerations that are relatively understudied in economic literature. Therefore, my work pushes the theoretical frontier to develop methodological tools relevant to the foster care setting while empirically evaluating these tools to demonstrate their efficacy. I also design experiments and empirically evaluate policies and organizational programs that encourage socially beneficial outcomes for vulnerable populations, especially vulnerable children in poverty and in any child welfare systems.

Working Papers

Abstract: Caseworkers in foster care systems seek to place waiting children in the most suitable homes. Furthermore, social work guidelines prioritize heterogeneous attributes of children and homes when deliberating placements. We use insights from market design and dynamic matching to characterize a class of dynamically envy-free mechanisms that incentivize expedient placements when children and homes arrive to the market over time and homes may accept or decline placements. The mechanisms have robustness against justified envy and costly patience. We analyze strategic incentives and efficiency properties of dynamic envy-freeness. Finally, we conduct empirical simulations that affirm that our mechanisms drastically increase placements and reduce waiting costs while maintaining robustness to prediction error versus a naive mechanism that always sequentially runs Deferred Acceptance. Practitioners can implement our mechanisms through assigning priority to child-home matches or through existing match recommendation systems.


Abstract: In many local foster care systems across the United States, child welfare practitioners struggle to effectively match children in need of a home to foster families. We tackle this problem while navigating a key sensitivity in this domain: in foster care systems, individual caseworkers must assent to any proposed matching. We codify this constraint in one-sided matching markets as the problem of matching design with sufficiency. We design a mechanism that guarantees outcome sufficiency, a form of welfare-maximizing Pareto efficiency ensuring that no caseworker can ex-post gain from any child-family placement reassignment and that the foster care authority's objective preferences for child-family placements are maximally satisfied. Our work subsequently evaluates this mechanism's strategic properties. Finally, we plan to conduct a lab-in-the-field experiment to elicit real-world caseworkers' preferences and estimate the child welfare gains our algorithm produces. Current simulation-based results show dramatic improvements to welfare. Designing sufficient matching systems is an example of mechanism-reform because replacing existing systems without regard for existing agents' preferences and wishes has previously resulted in failure.

Works in Progress