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Accounting for Latent Cropping Management Practices Choices in Crop Production Models: a Random Parameter Hidden Markov Model Approach

Author

Listed:
  • Esther Devilliers

    (INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, BETA - Bureau d'Économie Théorique et Appliquée - AgroParisTech - UNISTRA - Université de Strasbourg - Université de Haute-Alsace (UHA) - Université de Haute-Alsace (UHA) Mulhouse - Colmar - UL - Université de Lorraine - CNRS - Centre National de la Recherche Scientifique - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

  • Obafemi Philippe Koutchade

    (INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, SMART - Structures et Marché Agricoles, Ressources et Territoires - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - Institut Agro Rennes Angers - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement)

  • A. Carpentier

    (INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement, SMART - Structures et Marché Agricoles, Ressources et Territoires - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement - Institut Agro Rennes Angers - Institut Agro - Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement)

Abstract

In this article, we account for cropping management practices (CMPs) in economists' production functions to evaluate pesticide uses responsiveness to price changes in a context of heterogeneous technology. CMPs being latent in most economists' datasets and CMP changes entailing adjustment costs, we consider a hidden Markov model to describe the dynamics of farmer's CMP choice. We also account for farmers' unobserved heterogeneity by considering a random parameter model for our production function. An illustration on French winter wheat producers of La Marne area uncovers very high-yielding, high-yielding and low-input CMPs. The characteristics of the low-input CMPs we uncover are very close to those tested by agronomists in the area covered by our data. We also show that input uses differences between low-input and more conventional CMPs are too small for taxes on chemical inputs to imply large relative profitability effects and thus to encourage farmers to adopt less intensive practices.
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Suggested Citation

  • Esther Devilliers & Obafemi Philippe Koutchade & A. Carpentier, 2022. "Accounting for Latent Cropping Management Practices Choices in Crop Production Models: a Random Parameter Hidden Markov Model Approach," Post-Print hal-04157706, HAL.
    • Handle: RePEc:hal:journl:hal-04157706
    as

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