Shadow pricing of carbon emissions from agriculture using spatially adaptive reference sets

Zhiyang Shen, Jean-Philippe Boussemart (), Michael Vardanyan and Yunlong Zhang
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Zhiyang Shen: LEM - Lille économie management - UMR 9221 - UA - Université d'Artois - UCL - Université catholique de Lille - ULCO - Université du Littoral Côte d'Opale - Université de Lille - CNRS - Centre National de la Recherche Scientifique
Jean-Philippe Boussemart: LEM - Lille économie management - UMR 9221 - UA - Université d'Artois - UCL - Université catholique de Lille - ULCO - Université du Littoral Côte d'Opale - Université de Lille - CNRS - Centre National de la Recherche Scientifique
Yunlong Zhang: UAB - Universitat Autònoma de Barcelona = Autonomous University of Barcelona = Universidad Autónoma de Barcelona

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Abstract: We propose a novel spatially adaptive nonparametric framework for estimating shadow prices of carbon dioxide emissions (CSP) in the agriculture sector. Our approach addresses the frequently overlooked issue of spatial heterogeneity among production units. Using a city-level panel dataset from four major agricultural provinces in China during the period 2008–2023, we define spatially adaptive reference sets based on the geographical proximity among metropolitan areas rather than assuming a single production frontier. Our study highlights the importance of considering spatial heterogeneity in environmental performance analysis and proposes a policy-relevant approach for promoting sustainable development in agriculture.

Date: 2025-10-30
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Published in European Review of Agricultural Economics, 2025, ⟨10.1093/erae/jbaf045⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-05357710

DOI: 10.1093/erae/jbaf045

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