Ranking EU Agricultural Sectors under the Prism of Alternative Widths on Window DEA

Abstract

Providing food security while preserving natural resources and reducing the use of production factors (land, labor, and capital), is a critical challenge for EU agricultural sectors in the 21st century. Sustainable Development goals adoption has increased the need for eliminating Greenhouse gas emissions across all EU sectors, while production should remain stable or even increase. For this purpose, Window Data Envelopment Analysis (DEA) has been selected as a benchmarking technique, in order to assess input use efficiency of agricultural sectors of EU countries for the 2005–2019 period. Moreover, three-year projections (until 2022) have been calculated in order to acquire future efficiency scores. Emphasis has been given on the selection of alternative window widths, examining their influence on calculating efficiency scores for both projected and actual dataset. From a methodological point of view, this paper aims to highlight the assumption of zero technological change within Window DEA frames and present their differences. At the same time, results indicate that Estonia (1.000), the Netherlands (0.999) and Slovenia (0.999) are the most efficient countries in terms of input use efficiency, while Finland, UK, and Hungary (0.670, 0.755 and 0.771) score the least. Countries of central Europe (Hungary, Czech Rep., Croatia, Slovakia, and Austria) should redesign their agricultural strategies, so as to achieve the nine objectives of the upcoming CAP (2021–2027).

Window data envelopment analysis approach: A review and bibliometric analysis

“…Introducing an effective and powerful approach for estimation of OWW concerning the situations and information of case study and application (for details, see Charnes et al, 1994;Cullinane & Wang, 2010;Kyrgiakos et al, 2021;Maidamisa et al, 2012;Ratner & Ratner, 2017).…”

A systematic literature review of data envelopment analysis implementation in agriculture under the prism of sustainability

“…Further assessment is needed regarding qualitative data like the quality of sowing, quality of spraying or quality characteristics of the final product. TOPSIS Model, which can handle both scale and categorical data, can be easily combined with DEA methodology in the agricultural sector, embodying a wider range of involved variables in the benchmarking process (Kyrgiakos et al 2021a , b ; Wang et al 2021 ).…”

“…Although authors are aware of the existence of a higher number of papers with DEA implementation in the agricultural sector with great potential, e.g. application of DEA in agriculture at the EU level (Kočišová 2015 ; Madau et al 2017 ), local level (Işgın et al 2020 ), comparisons of DEA results with SFA (Theodoridis and Psychoudakis 2008 ) or newer approaches like 2-stage DEA (F. Ren et al 2021 ), engagement of spatial characteristics (Z. Li et al 2021 ), DEA with Artificial Neural Networks (ANNs) (Vlontzos and Pardalos 2017 ) or Window DEA approaches (Kyrgiakos et al 2021a , b ; Shahraki et al 2019 ), thus they were excluded because they did not fulfill the previously stated limitation. Moreover, prominent journals like American Journal of Agricultural Economics or Journal of Agricultural Economics are missing from the two databases, a fact that should be seriously considered by researchers when using these search engines.…”

Agricultural Eco-Efficiency: Challenges and Progress

“…While ensuring that the quality of agricultural products meets people's needs and the economic benefits of agricultural production, we need to pay more attention to ecological and environmental protection and realize the coordination between agricultural economic development and environmental protection so as to make ecological agriculture achieve greater development space. Only by realizing the protection of ecological environment can we fundamentally improve the efficiency of agricultural production [70][71][72]. In addition, it is necessary to repair the environment that has caused serious ecological damage in a scientific way and focus on prevention when the ecological environment has not been found to be damaged so as to maintain the sustainable development of agricultural ecosystem [53].…”