The poverty impacts of improved cowpea varieties in Nigeria: A counterfactual analysis
Julius Manda,
Arega D. Alene,
Adane H. Tufa,
Tahirou Abdoulaye,
Tesfamicheal Wossen,
David Chikoye and
Victor Manyong
World Development, 2019, vol. 122, issue C, 261-271
Abstract:
Adoption of improved agricultural technologies has long been recognized as critical for reducing poverty through increased productivity, incomes, and asset accumulation. Using a nationally representative survey data from a sample of over 1500 households in Nigeria, this paper evaluates the impacts of adoption of improved cowpea varieties on income and asset poverty reduction using an endogenous switching regression model. The results showed that adoption of improved cowpea varieties increased per capita household income and asset ownership by 17 and 24 percentage points, respectively. The results based on the observed and counterfactual income and asset distributions further showed that adoption reduced both income poverty and asset poverty by 5 percentage points. The paper concludes with a discussion of the policy options for increasing adoption and impacts of improved cowpea varieties in Nigeria.
Keywords: Endogenous switching regression; Counterfactual; Improved cowpea varieties; Nigeria; Poverty reduction (search for similar items in EconPapers)
Date: 2019
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (26)
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0305750X19301494
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:wdevel:v:122:y:2019:i:c:p:261-271
DOI: 10.1016/j.worlddev.2019.05.027
Access Statistics for this article
World Development is currently edited by O. T. Coomes
More articles in World Development from Elsevier
Bibliographic data for series maintained by Catherine Liu ().