Upgrading the smallholder dairy value chain: A system dynamics ex-ante impact assessment in Tanzania's Kilosa district

This paper examines ex-ante impacts of two policy interventions that improve productivity of local-breed cows through artificial insemination (AI) and producers’ access to distant markets through a dairy market hub. The majority of cattle in Kilosa district in Tanzania are local low productivity breeds kept by smallholders and agro-pastoralists. Milk production is seasonal, which constrains producers’ access to distant urban markets, constrains producers’ incomes and restricts profitability in dairy processing. We developed and evaluated an integrated system dynamics (SD) simulation model that captures many relevant feedbacks between the biological dynamics of dairy cattle production, the economics of milk market access, and the impacts of rainfall as an environmental factor. Our analysis indicated that in the short (1 year) and medium (5-year) term, policy interventions have a negative effect on producers’ income due to high AI costs. However, in the long term (5+ years), producers’ income from dairy cattle activities markedly increases (by, on average, 7% per year). The results show the potential for upgrading the smallholder dairy value chain in Kilosa, but achievement of this result may require financial support to producers in the initial stages (first 5 years) of the interventions, particularly to offset AI costs, as well as additional consideration of post-farm value chain costs. Furthermore, institutional aspects of dairy market hub have substantial effects on trade-offs amongst performance measures (e.g. higher profit vs. milk consumption at producer's household) with gain in cumulative profit coming at the expense of a proportional and substantial reduction in home milk consumption.