Spatial Simultaneous Autoregressive Models for Compositional Data: Application to Land Use

02.12.2022 11:15 – 12:15

RESEARCH CENTER FOR STATISTICS SEMINAR / 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. After recalling some classical facts about compositional data analysis, we recall the spatial simultaneous autoregressive models. We then 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 and prove that a choice of coordinate representation does not have any impact on the parameters in the simplex as long as we do not impose further restrictions. We discuss parameter interpretation taking into account the nonlinear structure as well as the spatial dimension. To assess the impact of the explanatory variables, we compute and interpret the semi-elasticities of the shares with respect to the explanatory variables and the spatial impact summary measures.

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