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Spatial Autocorrelation in Econometric Land Use Models: An Overview

In: Advances in Contemporary Statistics and Econometrics

Author

Listed:
  • Raja Chakir

    (Université Paris-Saclay, INRAE, AgroParisTech, Economie Publique)

  • Julie Le Gallo

    (CESAER UMR1041, Agrosup Dijon, INRAE, Université de Bourgogne Franche-Comté)

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," Springer Books, in: Abdelaati Daouia & Anne Ruiz-Gazen (ed.), Advances in Contemporary Statistics and Econometrics, pages 339-362, Springer.
    • Handle: RePEc:spr:sprchp:978-3-030-73249-3_18
    DOI: 10.1007/978-3-030-73249-3_18
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