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Household Vulnerability to Food Insecurity and the Regional Food Insecurity Gap in Kenya

Authors: Lilian Korir; Marian Rizov; Eric Ruto; Patrick Paul Walsh;

Household Vulnerability to Food Insecurity and the Regional Food Insecurity Gap in Kenya

Abstract

Food insecurity remains a vital concern in Kenya. Vulnerable members of the population, such as children, the elderly, marginalised ethnic minorities, and low-income households, are disproportionately affected by food insecurity. Following the pioneering work of Sen, which examined exposure to food insecurity at a household level using his “entitlement approach”, this paper estimates households’ vulnerability to food insecurity. In turn, the outcome variable is decomposed in order to explain the food insecurity gap between households classified as “marginalised” and “non-marginalised”. We applied the Oaxaca-Blinder decomposition method to examine vulnerability to food insecurity and, in particular, contributions of observed differences in socio-demographic characteristics (endowments) or differences in the returns to these characteristics, which, in our context, is associated with poor public services and infrastructure in the vicinity of the household. The results indicated that differences in vulnerability to food insecurity were mainly attributable to observed differences in socio-demographic characteristics such as education, age, and household income. Therefore, policies seeking to attain equity by investment into targeted household characteristics in terms of access to food and other productive resources could effectively combat food insecurity. For example, policymakers could develop programs for household inclusiveness using education and social protection programs, including insurance schemes against risk of endowment loss.

Country
United Kingdom
Keywords

inequality, 330, L112 Agricultural Economics, vulnerability, TJ807-830, 338, coping strategies, social protection, TD194-195, Renewable energy sources, L430 Public Policy, food insecurity, L110 Applied Economics, GE1-350, L430 - Public policy, Environmental effects of industries and plants, ddc:330, L110 - Applied economics, regional disparities, L112 - Agricultural economics, L140 - Econometrics, 300, Environmental sciences, L120 - Microeconomics, L140 Econometrics, L120 Microeconomics

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    15
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
15
Top 10%
Average
Top 10%
Green
gold