The drivers of spatial cropping patterns in Burgundy

Valentin Bellassen (), Jean-Sauveur Ay and Mohamed Hilal ()
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Valentin Bellassen: CESAER - Centre d'Economie et de Sociologie Rurales Appliquées à l'Agriculture et aux Espaces Ruraux - AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement
Mohamed Hilal: CESAER - Centre d'Economie et de Sociologie Rurales Appliquées à l'Agriculture et aux Espaces Ruraux - AgroSup Dijon - Institut National Supérieur des Sciences Agronomiques, de l'Alimentation et de l'Environnement - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement

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Abstract: This study quantifies the relative influence of pedo-climatic conditions –natural advantage –and market proximity in the determination of crop location in Burgundy. Econometric models are designed to study the share or presence of six different crops –barley, rapeseed, soy, proteaginous pea, hemp and lentils –at municipal scale. Market proximity is found to have a significant influence on the location of four of them, namely barley, rapeseed, proteaginous pea and hemp. Market proximity increases the share of barley in arable crops by more than 10 percentage points and its influence on the share of barley is as important as pedo-climatic conditions. The influence of malt plants is highest within 80 minutes from plant location. For hemp, the inclusion of market proximity variables in the model increases the phi correlation coefficient from 0.14 to 0.18 and strongly constrains the areas predicted as suitable for hemp. We also derive from these six test cases two likely feasibility conditions for the quantification of market proximity influence on crop location: markets must be crop-specific (eg. hemp factories, which process only hemp) and they must be present in two different locations to limit the multicollinearity and endogeneity problems associated with distance variables. Low crop abundance does not seem to hamper the implementation of our method. This method could be used to refine existing downscaling procedures in economic models of agricultural supply such as AROPAj or CAPRI.

Keywords: Burgundy France; Market proximity; crop location (search for similar items in EconPapers)
Date: 2020-07-08
Note: View the original document on HAL open archive server: https://hal.inrae.fr/hal-02894116
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