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Research Article Open access CC BY 4.0

A Comparative Analysis of Poverty Dynamics in Relation to Household, Regional Characteristics and Farming Systems in Kenya

Samuel Kimote, Mutuku Muleli

Asian Journal of Agricultural Extension, Economics & Sociology · pp. 1–14 · Published 8 Nov 2018

10.9734/AJAEES/2018/18094

Abstract

This study aimed at describing poverty incidences in Kenya in relation to regional characteristics, household characteristics and farming systems, with a view to using the research findings to make recommendations for poverty alleviation and wealth creation. The study used social capital; a non-monetary indicator to gain a deeper understanding of causes of poverty in Kenya with a view to identifying the poor and what makes them poor in order to plan for them. A logistic regression mode was fitted using secondary data from the Kenya National Bureau of Statistics’ Integrated Household Budget Survey of 2005/2006. The model had household characteristics, regional characteristic and farming systems as independent variables (IVs) and socio-economic status as the Dependent Variable (DV).The results indicated that the likelihood that a household is poor is related to household income, the household head traits, household characteristics, regional (provincial) characteristics and farming systems’ characteristics. The results further proved that the use of Multiple Correspondence Analysis (MCA) approach to determine the composite poverty indicator yields the same results as when an asset index or any other technique is used. From the findings, there is need for concerted efforts, from government as well as other stakeholders, towards provision of services (seedlings, extension services and other agricultural inputs) to both large scale and small case farmers; increasing awareness on the importance of crops diversification; construction; and rehabilitation of infrastructure facilities and checking on population growth.

Composite poverty indicator determinants logistic MCAc multiple

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