Spatial Autocorrelation in Econometric Land Use Models: An Overview

Raja Chakir and Julie Le Gallo

A chapter in Advances in Contemporary Statistics and Econometrics, 2021, pp 339-362 from Springer

Abstract: 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.

Date: 2021
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Working Paper: Spatial Autocorrelation in Econometric Land Use Models: An Overview (2021)
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DOI: 10.1007/978-3-030-73249-3_18

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