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.
Highlights
The agricultural sector is the backbone of the Kenyan economy, making multifaceted contributions to the economy
The average farmland size, average per capita aggregate production, percentage of fertilizer users, percentage of pesticide users, percentage of household with female as head, percentage of educated household heads are all of food secure households and are higher than corresponding food insecure households on average
Food balance sheet has been used with the logistic regression model to predict the status of households food security
Summary
The agricultural sector is the backbone of the Kenyan economy, making multifaceted contributions to the economy. It is responsible for about 24% of Gross Domestic Product, over 50% of all domestic exports and employing about 70% of the labour force, see KNBS (2007, 2009). Over 10 million Kenyan, of whom the majority reside in rural areas, are food insecure, KARI (2009). This is despite that 85.4% of all households in the rural Kenya are engaged in crop farming activities, see KNBS (2007, 2008). According to FAO (1996), food security occurs “when all people (at the individual, household, district, national, regional and global), at all
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