Preference heterogeneity, neighbourhood effects and basic services: logit kernel models for farmers’ climate adaptation in Ethiopia

Abstract

Climate change adaptations by farmers are usually analysed with multinomial choice models, which ignore heterogeneity and ‘mixing’ across alternatives and individuals. Moreover, not enough attention is devoted to basic utilities other than extension services. Aimed at a reassessment that accounts for these issues, this paper formulates conditional and mixed logit (logit kernel) models with/without neighbourhood effects. In particular, a spatial logit kernel allows capturing behavioural differences and interdependence between neighbours. The analysis was based on a survey covering 162 villages of the Ethiopian Nile basin, with 50 farm households—multistage stratified randomly sampled—in each of 20 districts (woredas). Supplementary information concerned linear programming solutions on adaptation choice attributes in smallholder farming areas, under two scenarios. Lastly, cross-district aid emergency allocation priorities for food security and agriculture, among others, served as yardsticks for comparison with prevailing adjustment decisions and location characteristics. Closeness to farms with more educated farmers and larger plot sizes turned out to increase the likelihood of a household opting to sell livestock and land along with combined measures of farmland enhancement. Logit kernel outperformed conditional logit in explanatory power, and random parameters highlighted individual and group heterogeneity in preferences. Access to electricity, healthcare, and reliable and safe water supply strengthen farmers’ ability to respond to climate change. Specific adaptation measures can contribute in turn to improve the capacity of rural communities to mitigate the severity of health and nutrition crises. By contrast, in woredas hit by recurrent epidemics and droughts, many farmers appear to be unable to resort even to basic adaptation measures, such as planting of new trees. This prompts an additional need for institutional support and infrastructure development.