Environmentally adjusted analysis of agricultural efficiency: a systematic literature review of frontier approaches
ZAGADNIENIA EKONOMIKI ROLNEJ(2023)
Abstract
The paper reviews 200 papers regarding environmentally adjusted analysis of agricultural efficiency found in the Scopus database. Based on the PRISMA method the scope of the review was limited to papers where efficiency is assessed with data envelopment analysis (DEA) or stochastic frontier analysis (SFA). The aim of this paper is to identify how efficiency analysis can be enhanced to take into account environmental aspects of agricultural production and indicate the research trends and gaps. Regarding the trends, most of the studies refer to agriculture in Europe, with a noticeable increasing trend in Asia. The production directions under research mainly include crops or milk production, usually in the farm scale. It can also be observed that a typical economic efficiency model is developed to include new environmentally detrimental inputs or undesirable outputs, such as fertilizing, climate impact, crop protection, water footprint, and energy usage. The most common determinants were farmers features, scale of production, intensification, agricultural practices, quality of the production environment, macroeconomic environment, specialization, environmental practices, and farm features. The following research gaps were identified. The case studies of Africa and North America are limited, like those at the field and local levels as well as those related to horticultural and animal production other than milk production. The SFA approaches are underdeveloped in comparison with DEA, like approaches other than additional inputs/outputs. In particular, the by-production approach seems promising. Limited attention has been paid to soil condition, biodiversity, waste generation in agriculture, and positive externalities provided by the agriculture. An interesting and less investigated area in terms of performance determinants remain farmers' behavioral features.
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Key words
stochastic frontier analysis, data envelopment analysis, eco-efficiency, sustainable intensification.
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