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Spatial Autocorrelation in Econometric Land Use Models: An Overview
[Autocorrélation spatiale dans les modèles économétriques d'utilisation des sols : une vue d'ensemble]

Author

Listed:
  • Raja Chakir

    (ECO-PUB - Economie Publique - AgroParisTech - Université Paris-Saclay - INRAE - Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement)

  • Julie Le Gallo

    (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)

Abstract

This chapter provides an overview of the literature on econometric land use models including spatial autocorrelation. These models are useful to analyze the determinants of land use changes and to study their implications for the environment (carbon stocks, water quality, biodiversity, ecosystem services). Recent methodological advances in spatial econometrics have improved the quality of econometric models allowing them to identify more precisely the determinants of land use changes and make more accurate land use predictions. We review the current state of the literature on studies which account explicitly for spatial autocorrelation in econometric land use models or in the environmental impacts of land use.

Suggested Citation

  • Raja Chakir & Julie Le Gallo, 2021. "Spatial Autocorrelation in Econometric Land Use Models: An Overview [Autocorrélation spatiale dans les modèles économétriques d'utilisation des sols : une vue d'ensemble]," Post-Print hal-03350490, HAL.
    • Handle: RePEc:hal:journl:hal-03350490
    DOI: 10.1007/978-3-030-73249-3_18
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