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Scaling Up Social Assistance Where Data is Scarce - Opportunities and Limits of Novel Data and AI

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  • Yuko Okamura
  • Tim Ohlenburg
  • Emil Tesliuc

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  • Yuko Okamura & Tim Ohlenburg & Emil Tesliuc, 2024. "Scaling Up Social Assistance Where Data is Scarce - Opportunities and Limits of Novel Data and AI," World Bank Publications - Reports 41553, The World Bank Group.
    • Handle: RePEc:wbk:wboper:41553
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    References listed on IDEAS

    as
    1. Elena Camilletti & UNICEF Office of Research - Innocenti, 2020. "Social Protection and Its Effects on Gender Equality: A literature review," Papers inwopa1120, Innocenti Working Papers.
    2. Isabella S. Smythe & Joshua E. Blumenstock, 2022. "Geographic microtargeting of social assistance with high-resolution poverty maps," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 119(32), pages 2120025119-, August.
    3. Emily Aiken & Suzanne Bellue & Dean Karlan & Chris Udry & Joshua E. Blumenstock, 2022. "Machine learning and phone data can improve targeting of humanitarian aid," Nature, Nature, vol. 603(7903), pages 864-870, March.
    4. Ashley Pople & Ruth Hill & Stefan Dercon & Ben Brunckhorst, 2021. "Anticipatory Cash Transfers in Climate Disaster Response," CSAE Working Paper Series 2021-07, Centre for the Study of African Economies, University of Oxford.
    5. Adrien Bouguen & Yue Huang & Michael Kremer & Edward Miguel, 2019. "Using Randomized Controlled Trials to Estimate Long-Run Impacts in Development Economics," Annual Review of Economics, Annual Reviews, vol. 11(1), pages 523-561, August.
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