Price predictors in an extended hedonic regression framework: An application to wholesale cattle markets in Ethiopia

Abstract

Livestock markets influence income generation for producers, but also accessibility and affordability of highly nutritious animal-sourced foods for consumers. Despite their importance, the functioning of livestock markets in lower-income countries is poorly understood and rarely studied compared to more developed countries. This study analyzes wholesale cattle markets in Ethiopia using a uniquely rich large-scale dataset covering both prices and cattle characteristics in 39 markets (in both highland and lowland areas) over a 10-year period, and hedonic regression models structured to understand both cattle price formation and seasonal and secular price dynamics. We show that cattle prices are influenced by a wide range of factors, including proxies for meat quality, religious fasting practices, climate-based seasonality but also climate shocks and availability of grazing land, competition from animal traction services, and rising consumer incomes. However, the implied effects of these factors are often significantly different in highland mixed crop-livestock areas compared to agro-pastoralist lowland areas, emphasizing the dualistic nature of cattle markets in Ethiopia. The analyses help inform the systemic challenges that Ethiopia will need to overcome to meet rising demand for beef products in the face of sustained income and population growth, as well as the adverse effects of climate change.