ABSTRACT
It is well known that agricultural intensification has been one of the main causes of biodiversity loss around the world. The economic concept of efficiency is closely related to this detrimental causation as it focuses the evaluation of the relative waste of resources. Moreover, a trade-off between agricultural production efficiency and environmental efficiency can be assumed. In recent decades a significant amount of literature has been produced concerned with establishing a link between production efficiency and environmental efficiency with respect to quantitative modelling. This has been mainly addressed by focusing on the incorporation of undesirable outputs (e.g. polluting emissions) or the incorporation of environmentally detrimental inputs (as e.g. nitrogen surplus). However, while the debate with respect to linear programming-based DEA modelling is already at an advanced stage (see Färe et al. 1989; Ball et al. 1994; Scheel 2001; Hailu and Veeman 2001; Kuosmanen 2005), the corresponding one with respect to stochastic frontier modelling has been initially started by Reinhard et al. 1999 and 2002 but still needs considerable efforts. Neglecting stochastic influences, the former approach seems to be less appropriate with respect to the stochastic nature of agricultural production. Existing stochastic modelling approaches nevertheless show methodical shortcomings with respect to the choice of the functional form (estimates of environmental efficiency are restricted to a certain parameter range as well as functional flexibility) as well as exclusively considering environmentally detrimental inputs.
