Evaluating environmental effects of adopting automatic milking systems on Norwegian dairy farms

We present a novel procedure based on eco-efficiency for assessing farm-level effects of technology adoption while considering secondary effects. Secondary effects are defined as structural and behavioural adaptations to technology that may impact environmental, social or economic outcomes. We apply the procedure to automatic milking systems (AMS) in Norway and find that AMS induces secondary effects, most strongly by decreasing labour per cow and increasing herd sizes. For estimating effects of AMS we employ a novel causal machine learning approach. AMS induce heterogenous effects on eco-efficiency, negatively associated with herd expansion and labour per cow.

Automated summary

This study presents a novel procedure based on eco-efficiency to assess the farm-level effects of technology adoption, considering secondary effects. Secondary effects refer to the structural and behavioral adaptations to technology that may impact environmental, social, or economic outcomes. The procedure is applied to automatic milking systems in Norway, revealing that the adoption of such systems induces secondary effects, predominantly through reducing labor per cow and increasing herd sizes. A novel causal machine learning approach is employed to estimate the effects of automatic milking systems, resulting in heterogenous effects on eco-efficiency, negatively associated with herd expansion and labor per cow.