How did the economic crisis caused by the Covid-19 pandemic impact poor households in Sub-Saharan Africa? This paper tackles this question by combining 73 High-Frequency Phone Surveys collected by national governments in 14 countries with older nationally representative surveys containing information on household consumption. In particular, it examines how outcomes differed according to predicted per capita consumption quintiles in the first wave of the survey, and in subsequent waves by households’ predicted per capita consumption. The initial shock affected households throughout the predicted welfare distribution. Households in the bottom 40 percent responded by sharply increasing farming activities between May and July of 2020 and gradually increasing ownership of non-farm enterprises starting in August. This coincided with an improvement in welfare, as measured by a decline in food insecurity and distressed asset sales among these households during the second half of 2020. With respect to education, children in the bottom quintile were 15 percentage points less likely to engage in learning activities than those in the top quintile in the immediate aftermath of the crisis, and the engagement gap between the bottom 40 and top 60 widened in the summer before narrowing in the fall due to large declines in engagement among the top 60. Poorer households were slightly more likely to report receiving public assistance immediately following the shock, and this difference changed little over the course of 2020. The results highlight the widespread impacts of the crisis both on welfare and children’s educational engagement, the importance of agriculture and household non-farm enterprises as safety nets for the poor, and the substantial recovery made by the poorest households in the year following the crisis.
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Reproducible Research Repository (World Bank) | https://reproducibility.worldbank.org |
The code was run in two computers with the following specifications:
Computer 1:
Runtime: 12 hours
All data used for this reproducibility package are restricted. See dataset information for data access.
Author | Affiliation | |
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Feraud Tchuisseu Seuyong | Université de Montréal | feraud.tchuisseu@umontreal.ca |
Ifeanyi Edochie | World Bank | iedochie@worldbank.org |
David Newhouse | World Bank | dnewhouse@worldbank.org |
Ani Rudra Silwal | U.S. Census Bureau | ani.r.silwal@census.gov |
2024-03
Location | Code |
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Sub-Saharan Africa | SSA |
The materials in the reproducibility packages are distributed as they were prepared by the staff of the International Bank for Reconstruction and Development/The World Bank. The findings, interpretations, and conclusions expressed in this event do not necessarily reflect the views of the World Bank, the Executive Directors of the World Bank, or the governments they represent. The World Bank does not guarantee the accuracy of the materials included in the reproducibility package.
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Modified BSD3 | https://opensource.org/license/bsd-3-clause/ |
Name | Affiliation | |
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David Newhouse | World Bank | dnewhouse@worldbank.org |
Reproducibility WBG | World Bank | reproducibility@worldbank.org |
Name | Abbreviation | Affiliation | Role |
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Reproducibility WBG | DIME | World Bank - Development Impact Department | Verification and preparation of metadata |
2024-03-15
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