Working paper

Spatial simultaneous autoregressive models for compositional data: Application to land use

Christine Thomas-Agnan, Thibault Laurent, Anne Ruiz-Gazen, T.H.A Nguyen, Raja Chakir, and Anna Lungarska

Abstract

Econometric land use models study determinants of land-use-shares of different classes: ``agriculture'', ``forest'', ``urban'' and ``other'' for example. Land-use-shares have a compositional nature as well as an important spatial dimension. We compare two compositional regression models with a spatial autoregressive nature in the framework of land use. We study the impact of the choice of coordinate space. We discuss parameters interpretation taking into account the non linear structure as well as the spatial dimension. We compute and interpret the semi-elasticities of the shares with respect to the explanatory variables and the spatial impact summary measures.

Keywords

compositional regression model; marginal effects; simplicial derivative; elasticity; semi-elasticity.;

JEL codes

  • C10: General
  • C39: Other
  • C46: Specific Distributions • Specific Statistics
  • C65: Miscellaneous Mathematical Tools
  • M31: Marketing
  • Q15: Land Ownership and Tenure • Land Reform • Land Use • Irrigation • Agriculture and Environment

Reference

Christine Thomas-Agnan, Thibault Laurent, Anne Ruiz-Gazen, T.H.A Nguyen, Raja Chakir, and Anna Lungarska, Spatial simultaneous autoregressive models for compositional data: Application to land use, TSE Working Paper, n. 20-1098, May 2020.

See also

Published in

TSE Working Paper, n. 20-1098, May 2020