Model-Based Valuation of Ecosystem Services Using Bio-Economic Farm Models: Insights for Designing Green Tax Policies and Payment for Ecosystem Services

Seyed-Ali Hosseini-Yekani, Stefan Tomaczewski and Peter Zander
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Stefan Tomaczewski: Leibniz Centre for Agricultural Landscape Research (ZALF), 15374 Müncheberg, Germany
Peter Zander: Leibniz Centre for Agricultural Landscape Research (ZALF), 15374 Müncheberg, Germany

Agriculture, 2024, vol. 15, issue 1, 1-18

Abstract: The integration of ecosystem services (ESs) valuation into agricultural policy frameworks is critical for fostering sustainable land management practices. This study leverages the redesigned version of the bio-economic farm model MODAM (Multi-Objective Decision Support Tool for Agro-Ecosystem Management) to estimate the shadow prices of ESs, enabling the derivation of demand and supply curves for nitrate leaching and soil erosion control, respectively. Two hypothetical farms in Brandenburg, Germany—a smaller, arable farm in Märkisch-Oderland and a larger, diversified farm with livestock in Oder-Spree—are analyzed to explore the heterogeneity in shadow prices and corresponding cropping patterns. The results reveal that larger farms exhibit greater elasticity in response to green taxes on nitrate use and lower costs for supplying erosion control compared to smaller farms. This study highlights the utility of shadow prices as proxies for setting green taxes and payments for ecosystem services (PESs), while emphasizing the need for differentiated policy designs to address disparities between farm types. This research underscores the potential of model-based ESs valuation to provide robust economic measures for policy design, fostering sustainable agricultural practices and ecosystem conservation.

Keywords: ecosystem services valuation; bio-economic farm models; MODAM; shadow prices; green tax policy; payment for ecosystem services; nitrate leaching; soil erosion control (search for similar items in EconPapers)
JEL-codes: Q1 Q10 Q11 Q12 Q13 Q14 Q15 Q16 Q17 Q18 (search for similar items in EconPapers)
Date: 2024
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