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

Esther Devilliers (), Obafemi Philippe Koutchade () and Alain Carpentier
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Esther Devilliers: 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, 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

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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.

Keywords: Production Function; Heterogenous Technology; Hidden Markov model; Pesticide use (search for similar items in EconPapers)
Date: 2023-07-10
Note: View the original document on HAL open archive server: https://hal.science/hal-04157564v1
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Related works:
Working Paper: Accounting for Latent Cropping Management Practices Choices in Crop Production Models: a Random Parameter Hidden Markov Model Approach (2023)
Working Paper: Accounting for Latent Cropping Management Practices Choices in Crop Production Models: a Random Parameter Hidden Markov Model Approach (2022)
Working Paper: Accounting for Latent Cropping Management Practices Choices in Crop Production Models: a Random Parameter Hidden Markov Model Approach (2022)
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