An Application of Random Effects Generalized Ordered Probit Model on The Drivers of Food Insecurity in Kenya

Abstract

Food insecurity is a leading health and nutrition issue for decades, especially in developing countries. Despite the good policies implemented by the national and county government to reduce food insecurity status among smallholder farming households, food insecurity is still a challenge in many parts of the country. Thus, the current paper sought to establish the drivers of food insecurity among households in Kenya. Using panel data from the Kenya Covid-19 Rapid Response Phone Survey, the Random effects Generalized ordered Probit model was employed to analyze the factors affecting food insecurity. The three variables revealed the unobserved heterogeneity in the dependent variable. A household being in the central region increased the probability of a household falling into the low dietary diversity (LDD) and medium dietary diversity (MDD) categories by 1.9% (p<0.10) and 2.9% (p<0.01) compared to households from other regions in Kenya. Also, a household living in the western region has a higher probability of being in the low dietary diversity (LDD) and medium dietary diversity (MDD) categories by 3.1% (p<0.01) and 2.1% (p<0.01). being a year older increases the probability of a household being in the high dietary diversity (HDD) level by 0.1 % (p<0.01). Internet access, mobile phone ownership, and gender had a significant effect across various levels of household dietary diversity. Policies should be tailored to capture region-specific agroecological conditions while households should be encouraged to diversify differently in the crop and livestock production activities as a risk management strategy and as an adaptation strategy against climate change.