Greenhouse Gas Emissions and Eco-Performance at Farm Level: A Parametric Approach
通过随机前沿分析构建分析框架，引入排放效率概念，区分持久和时变效率，研究巴伐利亚农场2005-2014年温室气体排放绩效，发现不同农场类型排放差异大，整体绩效随时间改善，为农业减排政策提供微观依据。
Abstract Agriculture is an important source of greenhouse gas (GHG) emissions and thus contributes considerably to global warming. However, farms can vary substantially in terms of their climatic impact. So far, most policies aiming at reducing GHG emissions from farming have largely been based on findings at the aggregate level, without taking farm heterogeneity properly into account. This study seeks to provide a better understanding of the GHG mitigation potential at the micro-level. We develop a comprehensible analytical framework for analyzing economic-ecological performance by way of stochastic frontier analysis. We introduce the concept of emission efficiency, where we distinguish between persistent and time-varying efficiency. We further analyze farms with respect to their emission-performance dynamics. Results from our (2005–2014) empirical application from Bavaria—an important region for the EU – show considerable differences in farm-level GHG emissions across different farm types. The same applies to emission efficiencies. Overall, emission performance improved over time. The results have important climate-policy implications as they help to provide better target measures for mitigating GHG emissions from agriculture, without compromising economic performance levels.