Search and Matching for Adoption from Foster Care

To find families for the more than 100,000 children in need of adoptive placements, most United States child welfare agencies have employed a family-driven search approach in which prospective families respond to announcements made by the agency. However, some agencies have switched to a caseworker-driven search approach in which the caseworker directly contacts families recommended for a child. We introduce a novel search-and-matching model that captures the key features of the adoption process and compare family-driven with caseworker-driven search in a game-theoretical framework. Under either approach, the equilibria are generated by threshold strategies and form a lattice structure. Our main theoretical finding then shows that no family-driven equilibrium can Pareto dominate any caseworker-driven outcome, whereas it is possible that each caseworker-driven equilibrium Pareto dominates every equilibrium attainable under family-driven search. We also find that when families are sufficiently impatient, caseworker-driven search is better for all children. We illustrate numerically that most agents are better off under caseworker-driven search for a wide range of parameters. Finally, we provide empirical evidence from an agency that switched to caseworker-driven search and achieved a three-year adoption probability that outperformed a statewide benchmark by 24%, as well as a statistically significant 27% improvement in adoption hazard rates.