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: June 28, 2024
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 134 Scopus

Publication Search Results

Now showing 1 - 2 of 2
  • Publication
    Savings Facilitation or Capital Injection?: Impacts and Spillovers of Livelihood Interventions in Post-Conflict Côte d’Ivoire
    (World Bank, Washington, DC, 2023-09-12) Marguerie, Alicia; Premand, Patrick
    Policy makers grapple with the optimal design of multidimensional strategies to improve poor households’ livelihoods. To address financial constraints, are capital injections needed, or is savings mobilization sufficient This paper tests the direct effects and local spillovers of three instruments to relax financial constraints, each combined with micro-entrepreneurship training. “Cash grants” and “cash grants with repayment” directly inject capital, while “village savings and loan associations” (VSLAs) promote more efficient group saving. The randomized controlled trial took place in western regions of Côte d’Ivoire that were affected by a post-electoral crisis in 2011 and an earlier conflict. The interventions had differential effects on the dynamics of savings and productive asset accumulation. The cash grant modalities generated investments in startup capital, although nearly 30 percent of the grant was saved. In contrast, village savings and loan associations did not increase total savings but gradually induced investments, so that productive assets caught up with cash grant recipients after 15 months. Positive local spillovers on savings and independent activities were also observed. Yet, investments in independent activities were not sufficient to increase profits, possibly because they were limited due to high precautionary saving motives in the post-conflict study setting.
  • Publication
    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.