How ecoefficient is European food consumption? A frontier-based multiregional input?output analysis

Abstract

This paper presents an integrated approach combining the optimization-based frontier model with a global multiregional input?output (MRIO) analysis for food consumption in Europe. The weighted and conventional data envelopment analysis models are coupled with production and consumption-based environmental and economic footprint data obtained from the environmental footprint explorer database. Eco-efficiency assessment is carried out using multiple undesirable environmental outputs such as carbon emission, total energy consumption, land use, material use, water use, and one desirable economic output, which is the gross value-added (GVA). This assessment indicates an efficiency level of each economic activity associated with its environmental impacts and policies are made as a result of the efficiency level to propose an equilibrium between economic development and environmental impacts. Finally, a sensitivity analysis of each parameter, variability analysis between weighted and non-weighted models, and performance improvement projections are presented. Based on the results, four countries become efficient when moving from production-based accounting (PBA) to consumption-based accounting (CBA). France, United Kingdom, Italy, and Sweden are efficient countries in both findings. Denmark caused the highest carbon emission from the production point of view. Germany is the largest importer in all environmental categories such as carbon emission, energy usage, material use, land use, and water use. Additionally, the weight-restricted model indicated a noticeable difference concerning the eco-efficiency scores under the PBA and CBA approach, where land use and material footprint categories were found to be the most sensitive parameters for eco-efficiency scores. The authors believe that this integrated approach will aid in decision-making and help build a composite eco-efficiency score when comparing the performance of food consumption with multiple environmental and economic metrics.