PREDICTION OF THE LIKELIHOOD OF HOUSEHOLDS FOOD SECURITY IN THE LAKE VICTORIA REGION OF KENYA

Peter Nyamuhanga Mwita, Romanus Odhiambo Otieno, Verdiana Grace Masanja, Charles Muyanja

Abstract


This paper considers the modeling and prediction of  households food security status using a sample of households in the  Lake Victoria region of Kenya. A priori expected food security  factors and their measurements are given. A binary logistic regression model  derived was fitted to thirteen priori expected factors. Analysis of the marginal effects revealed that effecting the use of the seven significant determinants: farmland size, per capita aggregate production, household size, gender of household head, use of fertilizer, use of pesticide/herbicide and education of household head,  increase the likelihood of a household being food secure. Finally, interpretations  of   predicted conditional probabilities, following improvement of significant determinants,  are given.


Keywords


household; food; security; logistic; probability

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DOI: http://dx.doi.org/10.18187/pjsor.v7i2.241

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Title

PREDICTION OF THE LIKELIHOOD OF HOUSEHOLDS FOOD SECURITY IN THE LAKE VICTORIA REGION OF KENYA

Keywords

household; food; security; logistic; probability

Description

This paper considers the modeling and prediction of  households food security status using a sample of households in the  Lake Victoria region of Kenya. A priori expected food security  factors and their measurements are given. A binary logistic regression model  derived was fitted to thirteen priori expected factors. Analysis of the marginal effects revealed that effecting the use of the seven significant determinants: farmland size, per capita aggregate production, household size, gender of household head, use of fertilizer, use of pesticide/herbicide and education of household head,  increase the likelihood of a household being food secure. Finally, interpretations  of   predicted conditional probabilities, following improvement of significant determinants,  are given.


Date

2011-06-01

Identifier


Source

Pakistan Journal of Statistics and Operation Research; Vol 7. No. 2, July 2011



Print ISSN: 1816-2711 | Electronic ISSN: 2220-5810