Variable Inputs Allocation among Crops: A Time-Varying Random Parameters Approach

Allocation d'intrants variables entre les cultures: Une approche de paramètres aléatoires variant dans le temps

Obafemi Philippe Koutchade (), Alain Carpentier () and Fabienne Femenia ()
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Obafemi Philippe Koutchade: 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
Alain Carpentier: 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
Fabienne Femenia: 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 paper, we propose an approach to allocate input uses among crops produced by farmers, based on panel data that includes input use aggregated at the farm-level. Our proposed approach simultaneously allows for (i) controlling for observed and unobserved farm heterogeneity, (ii) accounting for the potential dependence of input uses on acreage decisions, and (iii) ensuring consistent values of input use estimates. These are significant issues commonly faced in the estimation of input allocation equations. The approach is based on a model of input allocation derived from accounting identities, where unobserved input uses per crop are treated as time-varying random parameters. We estimate our model on a sample of French farms' accounting data, by relying on an extension of the Stochastic Approximation of Expectation Maximization algorithm. Our results show good performance of our approach in accurately allocating input uses among crops, for the crops the most frequently produced in our data sample in particular.

Keywords: Input allocation; Crop production decisions; Random parameter models; SAEM algorithm; Allocation d’intrants; Choix de production agricole; Modèles à paramètres aléatoires; Algorithme SAEM (search for similar items in EconPapers)
Date: 2024-12-13
Note: View the original document on HAL open archive server: https://hal.inrae.fr/hal-04836702v1
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