The Orphan Impact: HIV-AIDS and Student Test Scores from Sub-Saharan Africa

Autor/inn/en	Blevins, Benjamin K.; Kawata, Keisuke
Titel	The Orphan Impact: HIV-AIDS and Student Test Scores from Sub-Saharan Africa
Quelle	In: Educational Review, 73 (2021) 6, S.690-713 (24 Seiten)Infoseite zur Zeitschrift PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Blevins, Benjamin K.) ORCID (Kawata, Keisuke)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0013-1911
DOI	10.1080/00131911.2019.1689100
Schlagwörter	Acquired Immunodeficiency Syndrome (AIDS); Scores; Academic Achievement; Foreign Countries; Child Welfare; Communicable Diseases; Outcomes of Education; Regression (Statistics); Botswana; Kenya; Lesotho; Malawi; Mauritius; Mozambique; Namibia; Seychelles; South Africa; Swaziland; Tanzania; Uganda; Zambia; Zimbabwe + Suchen Sie Ihr Suchwort? Schulleistung; Ausland; Kindeswohl; Contagious disease; Contagious diseases; Communicable disease; Infektionskrankheit; Lernleistung; Schulerfolg; Regression; Regressionsanalyse; Kenia; Mosambik; Seychellen; Südafrika; Süd-Afrika; Republik Südafrika; Südafrikanische Republik; Tansania; Sambia; Simbabwe
Abstract	In sub-Saharan Africa over 52 million children are living with the death of one or both parents. Drivers of this parental mortality include afflictions at levels endemic to the region, including: HIV; malaria and other parasites; lower respiratory infections; diarrhoeal illnesses; and road accidents, among others. This paper examines the impact of orphanhood on learning outcomes among girls and boys in sub-Saharan Africa, conditional on school enrolment. By analysing test scores for approximately 60,000 pupils in 12 countries, we estimate the effect on student test scores by comparing paternal, maternal, and double orphans to non-orphans in the sample, specifically for the subjects of reading, mathematics, and HIV-AIDS knowledge. No previous study has analysed how orphanhood might influence learning by using student test score data, making this paper's approach unique in the literature. This study employs two estimation techniques: Coarsened exact matching calculates the sample average treatment effect on the treated, while matching on students' family structure, household wealth, school resources, and geographic location; and double lasso (DL) regression applies applying machine-learning for variable selection with high-dimensional controls for regional and school identifiers, school location, and student age. Our results show both CEM and DL consistently report a significant negative impact of orphanhood on test scores among specific countries, especially those which faltered in addressing the HIV-AIDS crisis. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01