Person:
Grosh, Margaret

Social Protection and Jobs Global Practice
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Social safety nets, Poverty analysis, Labor markets, Social protection
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Social Protection and Jobs Global Practice
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Last updated: January 31, 2023
Biography
Margaret Grosh is the Senior Advisor for the World Bank’s Social Protection and Jobs Global Practice. She has written, lectured, and advised extensively on social protection programs, especially on targeting and cash transfer programs, globally and for Latin America. She has extensive experience with social protection both for responding to a crisis and for improving equality of opportunity. Earlier, she served as Lead Economist in the Latin American and Caribbean Region’s Human Development Department, led the team for Social Assistance in the World Bank’s Global Social Protection Department and, before that, the Living Standard Measurement Study in the Research Department. She holds a Ph.D. in economics from Cornell University.

Publication Search Results

Now showing 1 - 2 of 2
  • Publication
    Revisiting Targeting in Social Assistance: A New Look at Old Dilemmas
    (Washington, DC: World Bank, 2022-03-31) Grosh, Margaret; Wai-Poi, Matthew; Tesliuc, Emil
    Targeting is a commonly used, but much debated, policy within global social assistance practice. This book examines the well- known dilemmas in light of the growing body of experience, new implementation capacities, and the potential to bring new data and data science to bear. Chapter 1 presents a series of essays on the factors that shape choices around why or whether or how narrowly/broadly to target different parts of social assistance. Chapter 2 updates the global empirics around the outcomes and costs of focusing benefits on the poor or vulnerable. Chapter 3 illustrates the options and choices that must be made in moving from an abstract vision of focusing resources on the poor or vulnerable to more specific concepts and implementable definitions and procedures, and how the many choices should be informed by values, empirics and context. Chapter 4 provides a brief treatment of delivery systems and processes showing their importance to distributional outcomes and suggesting the many facets with room for improvement. Chapter 5 discusses the choice between targeting methods, how differences in purposes and contexts shape those. Chapter 6 summarizes and comprehensively updates the know-how with respect to the data and inference used by the different household-specific targeting methods. Chapter 7 contains a primer on measurement issues, going much deeper than usual and explaining how better measurement can lead to clearer understanding of targeting issues. Chapter 8 explores machine learning algorithms for household-specific mechanisms for eligibility determination.
  • Publication
    Exploring Universal Basic Income: A Guide to Navigating Concepts, Evidence, and Practices
    (Washington, DC: World Bank, 2020) Gentilini, Ugo; Grosh, Margaret; Rigolini, Jamele; Yemtsov, Ruslan; Gentilini, Ugo; Grosh, Margaret; Rigolini, Jamele; Yemtsov, Ruslan; Bastagli, Francesca; Lustig, Nora; Monsalve Montiel, Emma; Quan, Siyu; Ter-Minassian, Teresa; De Wispelaere, Jurgen; Lowe, Christina; George, Tina
    Universal basic income (UBI) is emerging as one of the most hotly debated issues in development and social protection policy. But what are the features of UBI? What is it meant to achieve? How do we know, and what don’t we know, about its performance? What does it take to implement it in practice? Drawing from global evidence, literature, and survey data, this volume provides a framework to elucidate issues and trade-offs in UBI with a view to help inform choices around its appropriateness and feasibility in different contexts. Specifically, the book examines how UBI differs from or complements other social assistance programs in terms of objectives, coverage, incidence, adequacy, incentives, effects on poverty and inequality, financing, political economy, and implementation. It also reviews past and current country experiences, surveys the full range of existing policy proposals, provides original results from micro–tax benefit simulations, and sets out a range of considerations around the analytics and practice of UBI.