Accounting for Latent Cropping Management Practices Choices in Crop Production Models: a Random Parameter Hidden Markov Model Approach
Year: 2022
Type: preprint
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.
Source: HAL
Institutions: Centre National de la Recherche Scientifique, AgroParisTech, Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement, Bureau d'Economie Théorique et Appliquée, Université de Strasbourg, Université de Lorraine, Structures et marchés agricoles, ressources et territoires
Language: English
Subfield: Economics and Econometrics
Domain: Social Sciences
SDG: Zero hunger
Open Access status: green
OpenAlex ID: W4390869580