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Combining Outcome-Based and Preference-Based Matching: A Constrained Priority Mechanism
11 Aug 2020
Stanford UniversityResearchers at Stanford and UC San Diego developed a constrained priority mechanism that balances individual preferences with aggregate social welfare objectives in allocation problems. Applied to refugee resettlement and student assignment, the mechanism demonstrated the capacity to increase predicted employment rates by up to 53% for refugees and improve mean test scores by about a third of a standard deviation for students, while managing preference satisfaction.
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Optimal multi-action treatment allocation: A two-phase field experiment to boost immigrant naturalization
22 Feb 2024
Research underscores the role of naturalization in enhancing immigrants'
socio-economic integration, yet application rates remain low. We estimate a
policy rule for a letter-based information campaign encouraging newly eligible
immigrants in Zurich, Switzerland, to naturalize. The policy rule assigns one
out of three treatment letters to each individual, based on their observed
characteristics. We field the policy rule to one-half of 1,717 immigrants,
while sending random treatment letters to the other half. Despite only moderate
treatment effect heterogeneity, the policy tree yields a larger, albeit
insignificant, increase in application rates compared to assigning the same
letter to everyone.
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