Person:
Premand, Patrick

Development Impact Evaluation Group, the World Bank
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Social protection, Safety nets, Employment, Skills, Early childhood development, Impact evaluation, Development economics
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Development Impact Evaluation Group, the World Bank
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Last updated September 12, 2023
Biography
Patrick Premand is a Senior Economist in the Development Impact Evaluation Group (DIME) in the research Vice-Presidency at the World Bank. He works on Social Protection and Safety Nets; Jobs, Economic Inclusion and Entrepreneurship; and Early Childhood Development. He conducts impact evaluations and policy experiments of social protection, jobs and human development programs. He often works on government-led interventions implemented at scale, in close collaboration with policymakers and researchers. He has led policy dialogue and technical assistance activities, as well as worked on the design, implementation and management of a range of World Bank operations. He previously held various positions at the World Bank, including in the Social Protection & Jobs group in Africa, the Human Development Economics Unit of the Africa region, the Office of the Chief Economist for Human Development, and the Poverty Unit of the Latin America and Caribbean region. He holds a DPhil in Economics from Oxford University.
Citations 124 Scopus

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    Do Workfare Programs Live Up to Their Promises? Experimental Evidence from Côte d’Ivoire
    (World Bank, Washington, DC, 2021-04) Bertrand, Marianne ; Crepon, Bruno ; Marguerie, Alicia ; Premand, Patrick
    Workfare programs are one of the most popular social protection and employment policy instruments in the developing world. They evoke the promise of efficient targeting, as well as immediate and lasting impacts on participants’ employment, earnings, skills and behaviors. This paper evaluates contemporaneous and post-program impacts of a public works intervention in Côte d’Ivoire. The program was randomized among urban youths who self-selected to participate and provided seven months of employment at the formal minimum wage. Randomized subsets of beneficiaries also received complementary training on basic entrepreneurship or job search skills. During the program, results show limited impacts on the likelihood of employment, but a shift toward wage jobs, higher earnings and savings, as well as changes in work habits and behaviors. Fifteen months after the program ended, savings stock remain higher, but there are no lasting impacts on employment or behaviors, and only limited impacts on earnings. Machine learning techniques are applied to assess whether program targeting can improve. Significant heterogeneity in impacts on earnings is found during the program but not post-program. Departing from self-targeting improves performance: a range of practical targeting mechanisms achieve impacts close to a machine learning benchmark by maximizing contemporaneous impacts without reducing post-program impacts. Impacts on earnings remain substantially below program costs even under improved targeting.