A Bilevel Linear Programming Model for Developing a Subsidy Policy to Minimize the Environmental Impact of the Agricultural Sector

Konstantinos Ziliaskopoulos and Konstantinos Papalamprou
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Konstantinos Ziliaskopoulos: Department of Environmental Sciences, University of Thessaly, 41500 Larissa, Greece
Konstantinos Papalamprou: Department of Electrical and Computer Engineering, Aristotle University of Thessaloniki, 54124 Thessaloniki, Greece

Sustainability, 2022, vol. 14, issue 13, 1-10

Abstract: The agro-food industry, while critical for establishing food security, is the most environmentally impactful industry since it causes biodiversity loss and the conversion of natural land to farms and pastures, requires pesticide and fertilizer use as well as high water consumption, and leads to greenhouse gas emissions as well as soil and environmental degradation. This impact can be mitigated through proper policy design. Environmental policy in agriculture, however, is inherently complex, due to the conflict between actors in the system, namely policy makers and farmers. This article introduces a bilevel linear programming (BLP) approach for the development of subsidy policies with the upper-level objective being the minimization of the environmental impact of the agricultural sector. Both levels of the model are formulated as linear programs and by considering the Water-Energy-Food-Climate Nexus, a general-purpose model is introduced. The methodology of the model formulation is spelled out. Finally, different approaches for fine tuning the BLP model are discussed in order to adjust it to each case study’s needs, and the model is applied to the case study of the region of Thessaly, Greece.

Keywords: water-energy-food nexus; bilevel linear programming; agricultural sector; subsidy policy; environmental impact (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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