Climate‐Smart Dairy Practices: The Role of Practice Clusters in Enhancing the Performance of Dairy Farms in Kenya

Climate variability is affecting the productivity, profitability, and resilience of smallholder dairy producers in developing countries. The adoption of climate‐smart (CS) dairy practices has been promoted to mitigate these negative effects. However, while interest in dairy CS practices is growing, empirical evidence on their adoption patterns and impact on key farm performance indicators, particularly cost of production and gross margin, remains limited. Moreover, the influence of adoption drivers appears to be highly context‐specific, underscoring the need for more nuanced and rigorous analysis. This study evaluates the impact of adopting seventeen CS dairy practices, grouped into four dominant clusters, on milk yield, variable production costs and gross margin. The analysis is based on a cross‐sectional survey of 665 smallholder dairy farmers across three milksheds in Kenya. Latent class analysis is employed to group the practices into dominant clusters. The multinomial endogenous treatment effects model is used to estimate the effects of those clusters on milk yield, variable production costs and gross margin, while accounting for selection bias and endogeneity stemming from both observed and unobserved heterogeneity across households. The findings reveal that belonging to any of the four clusters is influenced by access to and frequency of extension services from various providers. There is significant variability in milk yield, production costs and gross margin across the clusters. These results underscore the need for targeted policy interventions to enhance smallholder dairy productivity, profitability, and resilience amid climate variability.