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The International Monetary Funds intervention in education systems and its impact on childrens chances of completing school

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  • Adel Daoud

Abstract

Enabling children to acquire an education is one of the most effective means to reduce inequality, poverty, and ill-health globally. While in normal times a government controls its educational policies, during times of macroeconomic instability, that control may shift to supporting international organizations, such as the International Monetary Fund (IMF). While much research has focused on which sectors has been affected by IMF policies, scholars have devoted little attention to the policy content of IMF interventions affecting the education sector and childrens education outcomes: denoted IMF education policies. This article evaluates the extent which IMF education policies exist in all programs and how these policies and IMF programs affect childrens likelihood of completing schools. While IMF education policies have a small adverse effect yet statistically insignificant on childrens probability of completing school, these policies moderate effect heterogeneity for IMF programs. The effect of IMF programs (joint set of policies) adversely effect childrens chances of completing school by six percentage points. By analyzing how IMF-education policies but also how IMF programs affect the education sector in low and middle-income countries, scholars will gain a deeper understanding of how such policies will likely affect downstream outcomes.

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  • Adel Daoud, 2021. "The International Monetary Funds intervention in education systems and its impact on childrens chances of completing school," Papers 2201.00013, arXiv.org.
    • Handle: RePEc:arx:papers:2201.00013
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    1. Joseph STIGLITZ, 2013. "The global crisis, social protection and jobs," International Labour Review, International Labour Organization, vol. 152, pages 93-106, January.
    2. Alexander E. Kentikelenis & Thomas H. Stubbs & Lawrence P. King, 2016. "IMF conditionality and development policy space, 1985–2014," Review of International Political Economy, Taylor & Francis Journals, vol. 23(4), pages 543-582, July.
    3. Angus Deaton, 2015. "The Great Escape: Health, Wealth, and the Origins of Inequality," Economics Books, Princeton University Press, edition 1, number 10054.
    4. Daoud, Adel & Kim, Rockli & Subramanian, S.V., 2019. "Predicting women's height from their socioeconomic status: A machine learning approach," Social Science & Medicine, Elsevier, vol. 238(C), pages 1-1.
    5. Daoud, Adel, 2018. "Unifying Studies of Scarcity, Abundance, and Sufficiency," Ecological Economics, Elsevier, vol. 147(C), pages 208-217.
    6. Susan Athey & Guido W. Imbens, 2017. "The State of Applied Econometrics: Causality and Policy Evaluation," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 3-32, Spring.
    7. Adel Daoud, 2010. "Robbins and Malthus on Scarcity, Abundance, and Sufficiency," American Journal of Economics and Sociology, Wiley Blackwell, vol. 69(4), pages 1206-1229, October.
    8. International Monetary Fund, 2003. "Republic of Tajikistan: Staff Report for the 2002 Article IV Consultation and Request for a Three-Year Arrangement Under the Poverty Reduction and Growth Facility," IMF Staff Country Reports 2003/010, International Monetary Fund.
    9. Sendhil Mullainathan & Jann Spiess, 2017. "Machine Learning: An Applied Econometric Approach," Journal of Economic Perspectives, American Economic Association, vol. 31(2), pages 87-106, Spring.
    10. Christoph Moser & Jan-Egbert Sturm, 2011. "Explaining IMF lending decisions after the Cold War," The Review of International Organizations, Springer, vol. 6(3), pages 307-340, September.
    11. International Monetary Fund, 2003. "Pakistan: Fourth Review Under the Three-Year Arrangement Under the Poverty Reduction and Growth Facility and Request for Waiver of Performance Criterion," IMF Staff Country Reports 2003/054, International Monetary Fund.
    12. International Monetary Fund, 2003. "Albania: Second Review Under the Three-Year Arrangement Under the Poverty Reduction and Growth Facility," IMF Staff Country Reports 2003/218, International Monetary Fund.
    13. International Monetary Fund, 2003. "Islamic Republic of Mauritania: Staff Report for the 2003 Article IV Consultation, and Request for a Three-Year Arrangement Under the Poverty Reduction and Growth Facility," IMF Staff Country Reports 2003/314, International Monetary Fund.
    14. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    15. International Monetary Fund, 2003. "Mali: Sixth Review Under the Poverty Reduction and Growth Facility," IMF Staff Country Reports 2003/246, International Monetary Fund.
    16. Imad A. Moosa & Nisreen Moosa, 2019. "Eliminating the IMF," Springer Books, Springer, number 978-3-030-05761-9, December.
    17. Halleröd, Björn & Rothstein, Bo & Daoud, Adel & Nandy, Shailen, 2013. "Bad Governance and Poor Children: A Comparative Analysis of Government Efficiency and Severe Child Deprivation in 68 Low- and Middle-income Countries," World Development, Elsevier, vol. 48(C), pages 19-31.
    18. Victor Chernozhukov & Whitney K. Newey & James Robins, 2018. "Double/de-biased machine learning using regularized Riesz representers," CeMMAP working papers CWP15/18, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    19. International Monetary Fund, 2003. "Republic of Armenia: Fourth Review under the Poverty Reduction and Growth Facility and Request for Waiver of Performance Criterion," IMF Staff Country Reports 2003/379, International Monetary Fund.
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    1. Daoud, Adel & Herlitz, Anders & Subramanian, S.V., 2022. "IMF fairness: Calibrating the policies of the International Monetary Fund based on distributive justice," World Development, Elsevier, vol. 157(C).

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