Bitte verwenden Sie diesen Link, um diese Publikation zu zitieren, oder auf sie als Internetquelle zu verweisen: https://hdl.handle.net/10419/320556 
Erscheinungsjahr: 
2025
Schriftenreihe/Nr.: 
GLO Discussion Paper No. 1628
Verlag: 
Global Labor Organization (GLO), Essen
Zusammenfassung: 
In sub-Saharan Africa, child fostering-a widespread practice in which a child moves out of the household of her biological parents-can have significant implications for a child's overall well-being. Using longitudinal data from South Africa that includes individual tracking, we employ double machine learning techniques to evaluate the impact of fostering on nutrition, addressing biases related to selection into treatment and endogenous attrition, two common challenges in the literature. Our findings reveal that fostering reduces the probability of being stunted by 6.8 percentage points, corresponding to a 37 percent reduction compared to the mean prevalence. This improvement appears to be driven by foster children relocating to smaller, rural households, often including retired individuals, typically grandparents, who receive a pension. Furthermore, we find that it not only enhances the nutritional status of foster children but also benefits the nutrition of other children from sending households, suggesting that fostering can be mutually beneficial for both groups.
Schlagwörter: 
Child Fostering
Nutrition
Machine Learning
South Africa
JEL: 
I15
J12
J13
O15
C14
Dokumentart: 
Working Paper

Datei(en):
Datei
Größe
937.76 kB





Publikationen in EconStor sind urheberrechtlich geschützt.