An Adaptive Targeted Field Experiment: Job Search Assistance for Refugees in Jordan

Simon Quinn, Stefano Caria, Grant Gordon, Maximilian Kasy, Soha Shami and Alexander Teytelboym

No 15359, CEPR Discussion Papers from C.E.P.R. Discussion Papers

Abstract: We introduce a novel adaptive targeted treatment assignment methodology for field experiments. Our Tempered Thompson Algorithm balances the goals of maximizing the precision of treatment effect estimates and maximizing the welfare of experimental participants. A hierarchical Bayesian model allows us to adaptively target treatments. We implement our methodology in Jordan, testing policies to help Syrian refugees and local jobseekers to find work. The immediate employment impacts of a small cash grant, information and psychological support are close to zero, but targeting raises employment by 1 percentage-point (20%). After four months, cash has a sizable effect on employment and earnings of Syrians.

Date: 2020-10
New Economics Papers: this item is included in nep-ara and nep-exp
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Citations: View citations in EconPapers (15)

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Related works:
Journal Article: An Adaptive Targeted Field Experiment: Job Search Assistance for Refugees in Jordan (2024)
Working Paper: An Adaptive Targeted Field Experiment: Job Search Assistance for Refugees in Jordan (2021)
Working Paper: An Adaptive Targeted Field Experiment: Job Search Assistance for Refugees in Jordan (2020)
Working Paper: An Adaptive Targeted Field Experiment: Job Search Assistance for Refugees in Jordan (2020)
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