Quantifying rural livelihood strategies in developing countries using an activity choice approach

This article uses a quantitative activity choice approach, based on identification of activity variables and application of latent class cluster analysis, to identify five major rural livelihood strategies pursued by households (n= 576) in Bolivia, Nepal, and Mozambique. Income sources and welfare o...

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Bibliographic Details
Published in:Agricultural economics 2013-01, Vol.44 (1), p.57-71
Main Authors: Nielsen, Øystein Juul, Rayamajhi, Santosh, Uberhuaga, Patricia, Meilby, Henrik, Smith‐Hall, Carsten
Format: Article
Language:English
Subjects:
assets
Cluster analysis
Cross-country comparison
Developing countries
Economics
Education
Environmental income
farmers
Household asset endowments
Households
I31
Income
Land ownership
Latent class cluster analysis
LDCs
Livelihood
Norms
O30
Q12
Q50
R20
Regression
Rural
Small farms
Small-scale farming
Strategy
Studies
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Summary:This article uses a quantitative activity choice approach, based on identification of activity variables and application of latent class cluster analysis, to identify five major rural livelihood strategies pursued by households (n= 576) in Bolivia, Nepal, and Mozambique. Income sources and welfare outcomes are compared across strategies and household differences in asset holdings are analyzed using multinomial logit regression. Findings reveal that income diversification is the norm, that a higher degree of specialization does not characterize more remunerative livelihood strategies, that nonfarm income significantly contributes to higher income earnings, that environmental reliance does not vary across strategies, and that small‐scale farmers are the largest and poorest livelihood group. Some livelihood strategies are superior to all other strategies in terms of income earned; access to more remunerative livelihood strategies is determined by land ownership, education, and ethnic affiliation. Finally, the article also highlights that additional work is required to determine the most suitable methods for livelihood strategy identification.
ISSN:0169-5150
1574-0862
DOI:10.1111/j.1574-0862.2012.00632.x