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ResearchPaper
2017
Spatial differences in stunting and household agricultural production in South Africa : (re-)examining the links using national panel survey data
Spatial differences in stunting and household agricultural production in South Africa : (re-)examining the links using national panel survey data
Abstract (English)
One explanation for the increasing prevalence of stunting in South Africa over the past 15 years while other development indicators have improved is that Big Food retail chains have been contributing to a low quality diet across the country, particularly in poor urban households. We thus use nationally representative longitudinal data (2008–2014) to trace 6 years of stunting’s evolution among South African children, adolescents, and young adults aged 0–19, with particular attention to how the prevalence of under-nutrition differs between urban and rural areas and how the drivers of poor nutrition vary spatially. The results of our random-effects logistic regressions on the nutritional impact of household agricultural production suggest that, conditional on household income, subsistence farming is associated with a lower probability of stunting. Even more important, although under-nutrition retains a strong spatial component, once observable differences in living standards are controlled for, the higher tendency for children in deep rural households to suffer from (severe) stunting reverses.
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Publication series
Hohenheim discussion papers in business, economics and social sciences; 2017,13
Published in
Faculty
Faculty of Business, Economics and Social Sciences
Institute
Institute of Economics
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Language
English
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Classification (DDC)
330 Economics
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Standardized keywords (GND)
Sustainable Development Goals
BibTeX
@techreport{Otterbach2017,
url = {https://hohpublica.uni-hohenheim.de/handle/123456789/6168},
author = {Otterbach, Steffen and Rogan, Michael},
title = {Spatial differences in stunting and household agricultural production in South Africa : (re-)examining the links using national panel survey data},
year = {2017},
school = {Universität Hohenheim},
series = {Hohenheim discussion papers in business, economics and social sciences},
}