Modelling farm behaviour on soil fertility with the policy variable: a case from Africa

Abstract

This paper describes a new approach to make predictions on the behaviour of farms in Africa related to soil fertility management. Not only sectorial factors, but also the larger socio-economic context including policies influence the behaviour of small-scale farms. Science does not yet understand this context due to its vast heterogeneity, contingencies and complexity. We collected and processed qualitative data and sociological parameters to transform them into numbers. The model we constructed is based on probabilistic estimates of behaviour of farm classes under two scenarios in Mali (Mafeya) and Zambia (Chipata). We propose seven distinct farm classes to simulate the likeliness for a change from one class to another under defined policy regimes and other social conditions. In real life, network of actors, institutions and other social formations couple and decouple farmer’s identities and farms in highly dynamic social and ecological processes. We constructed a simplified model based on selected social theories, interpretative sociological inquiry and Markov chains in order to allow simulations under the two policy scenarios “as-is” and “to-be”. Our simulations result in significantly different outcomes per locality and scenario. This approach allows practical simulations of farm, food and agriculture systems and comparative research. We expect a better understanding of the dynamics of farms, faster adoption of innovations and a better base for a research-led dialogue of practitioners and policy makers. The paper demonstrates the primordial role of policies, influencing directly farmers’ behaviour, rural and labour markets as well as food systems and rural development.