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.

中文翻译：

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评估挪威奶牛场采用自动挤奶系统的环境影响

我们提出了一种基于生态效率的新颖程序，用于评估技术采用对农场的影响，同时考虑次级影响。次要影响被定义为可能影响环境、社会或经济结果的技术结构和行为适应。我们将该程序应用于挪威的自动挤奶系统 (AMS)，发现 AMS 会产生二次效应，最强烈的是减少每头奶牛的劳动力和增加牛群规模。为了估计 AMS 的效果，我们采用了一种新颖的因果机器学习方法。 AMS 对生态效率产生异质效应，与牛群扩张和每头牛的劳动力呈负相关。