Automation and efficiency: A latent class analysis of Irish dairy farms

Abstract

Abstract Automation has always played a significant role in the productivity and efficiency of agriculture. This paper explores the role of automation on farms' technical efficiency (TE) in an expanding dairy sector. We use a representative sample of Irish dairy farms that includes detailed data on automated technologies. We apply a latent class stochastic frontier model to assess technology heterogeneity amongst Irish dairy farms to obtain their TE scores. We identify two classes of farms: smaller, less intensive and larger, and more intensive farms. We find significant differences between the classes in relation to farm characteristics, input use, labour efficiency, and TE scores. Larger, more intensive farms produce closer to their stochastic frontier. Our findings also suggest that automation has a heterogeneous effect on farms' TE depending on farms' classification. Specifically, adopting automated cluster removers and scrapers is associated with higher TE on smaller, less intensive farms. In contrast, automated parlour feeders are positively associated with larger, more intensive farms' TE. Finally, the implications of adopting automated technologies on Irish farms are discussed.