| Abstract [eng] |
Sustainable agricultural development is one of the most important policy goals in the European Union. Agricultural production and its intensification cause a negative impact on the environment, including climate change. The main goal of sustainable agricultural development is to increase agricultural productivity, reducing the negative impact of this production on the environment. As climate change is one of the most important environmental challenges for sustainable agricultural development, productivity growth should be assessed by introducing greenhouse gas (GHG) emission restrictions. Thus, when evaluating agricultural productivity, it is imperative to simultaneously assess and restrict undesirable production outputs, such as GHG emissions, thus ensuring sustainable agricultural productivity growth. Extensive scientific research has been done on agricultural productivity and sustainable agricultural development; however, scientists lack consensus regarding undesirable outputs, such as GHG emissions assessments, when studying the efficiency and productivity of agricultural production. Assessing agricultural productivity in sustainable agricultural development requires identifying and assessing environmental constraints, especially related to integrating climate change mitigation into the production function, which is a complex task. This work aimed to develop methods for evaluating agricultural productivity in the context of sustainable agricultural development. The goal of the dissertation is to develop a model for assessing productivity with undesirable outputs and to apply it for sustainable productivity assessment in agriculture in the EU. The dissertation reviews productivity evaluation methods and discusses various models, emphasising evaluations of undesirable production outputs in the production function. A new model for evaluating agricultural production with undesirable results was developed based on an expanded production function that includes the main factors of agricultural production (energy consumption in agriculture, capital, labour and land costs in agriculture) and GHG emissions related to energy consumption in agriculture. The new model allows for a new expansion and use of DEA capabilities in the production function, supplementing it with the global slacks-based method (SBM) for efficiency measurement, the Luenberger productivity index, the index of contribution to structural efficiency with the help of which all production factors and GHG emissions can be analysed and studied in detail and the contribution of GHG emissions to overall changes in efficiency and productivity can be evaluated. |
