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

Author

Listed:
  • Zhiyang Shen

    (LEM - Lille économie management - UMR 9221 - UA - Université d'Artois - UCL - Université catholique de Lille - 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 - Université de Lille - CNRS - Centre National de la Recherche Scientifique)

  • Michael Vardanyan

    (LEM - Lille économie management - UMR 9221 - UA - Université d'Artois - UCL - Université catholique de Lille - 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)

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.

Suggested Citation

  • Zhiyang Shen & Jean-Philippe Boussemart & Michael Vardanyan & Yunlong Zhang, 2025. "Shadow pricing of carbon emissions from agriculture using spatially adaptive reference sets," Post-Print hal-05357710, HAL.
    • Handle: RePEc:hal:journl:hal-05357710
    DOI: 10.1093/erae/jbaf045
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