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Abstract
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Article Information:
Estimating the Determinants of Poverty Depth among the Peri-Urban Farmers in Nigeria
B.C. Asogwa, J.C. Umeh and V.A. Okwoche
Corresponding Author: B.C. Asogwa
Submitted: February 02, 2012
Accepted: February 22, 2012
Published: May 10, 2012 |
Abstract:
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This study estimated the determinants of poverty depth among the peri-urban farmers in Nigeria
using farm level data from randomly sampled 389 peri-urban farmers in Benue State, Nigeria. Data collected
for the study were analysed using Tobit regression model. The study showed that 71.1% variation in poverty
depth was explained by variations in the specified explanatory variables. Furthermore, at 5% level of
significance, the factors that significantly influenced poverty depth among the respondents were farm total
economic efficiency, household income, farm size, household size, age, education, farming experience, access
to credit, gainful employment for household members, membership of farmer association, extension contact
and valuable farm asset. However, a sustained improvement in farm total economic efficiency and per capita
income (via gainful employment opportunities for household members), as well as redistribution of household
income to minimize income inequality would go a long way to reduce poverty depth among the respondents.
Furthermore, improved farmers’ access to technological information and collective farmers’ institutions that
provide opportunities for risk sharing and improved bargaining power that are not available to individual
farmers, will lead to poverty reduction. Improvement in the educational opportunities of the farmers will lead
to increased income from farming and improvement in the quality of life and hence poverty reduction.
Key words: Farmers, peri-urban area, poverty depth, poverty determinants, Tobit model, ,
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Cite this Reference:
B.C. Asogwa, J.C. Umeh and V.A. Okwoche, . Estimating the Determinants of Poverty Depth among the Peri-Urban Farmers in Nigeria. Current Research Journal of Social Sciences, (3): 201-206.
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ISSN (Online): 2041-3246
ISSN (Print): 2041-3238 |
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