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Understanding poverty in cash-crop agro-forestry systems: evidence from Ghana and Ethiopia

Hirons, N., Robinson, E. J. Z., McDermott, C., Morel, A., Asare, R., Boyd, E., Gonfa, T., Gole, T. W., Malhi, Y., Mason, J. and Norris, K. (2018) Understanding poverty in cash-crop agro-forestry systems: evidence from Ghana and Ethiopia. Ecological Economics, 154. pp. 31-41. ISSN 0921-8009

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To link to this item DOI: 10.1016/j.ecolecon.2018.07.021

Abstract/Summary

This paper examines the linkages between cash-crop income and other dimensions of poverty to interrogate assumptions regarding the relationship between agricultural income and poverty alleviation. The analysis treats poverty as a multi-dimensional and socially disaggregated phenomenon. The paper employs a mixed methods approach to case studies of Ghana and Ethiopia to explore two critical issues. First, how income from cash crops is linked with other dimensions of poverty. Second, how income and land are socially disaggregated. The paper then draws on qualitative data to critically reflect on how poverty is understood within studied communities. The results show that some, but not all, indicators of poverty vary across income quartiles and that significant differences exist across social groups. The analysis suggests that although cash crops are essential, focusing on increasing income from cash crops will not necessarily have a predictable or progressive impact on wellbeing. Furthermore, the analysis highlights how contextual factors, such as the provision of communal services, the nature of land holdings and the quality of local governance mediate the potential poverty alleviating outcomes of income increases. Future development of sustainable intensification strategies should focus on the prevalence of trade-offs and the fundamental social relations underpinning poverty dynamics.

Item Type:Article
Refereed:Yes
Divisions:Faculty of Life Sciences > School of Agriculture, Policy and Development > Economic and Social Sciences Division > Food Economics and Marketing (FEM)
ID Code:78457
Publisher:Elsevier

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