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

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

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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.

Item Type: Monograph (Working Paper)
Language: English
Date: May 2020
Place of Publication: Toulouse
Uncontrolled Keywords: compositional regression model, marginal effects, simplicial derivative, elasticity, semi-elasticity.
JEL Classification: 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
Subjects: B- ECONOMIE ET FINANCE
Divisions: TSE-R (Toulouse)
Institution: Université Toulouse 1 Capitole
Site: UT1
Date Deposited: 06 May 2020 12:17
Last Modified: 29 Jul 2020 12:31
OAI Identifier: oai:tse-fr.eu:124242
URI: http://publications.ut-capitole.fr/id/eprint/34918

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