Nguyen, Thi Huong An, Thomas-Agnan, Christine, Laurent, Thibault, Ruiz-Gazen, Anne, Chakir, Raja and Lungarska, Anna (2021) A simultaneous spatial autoregressive model for compositional data. Spatial Economic Analysis, vol. 16 (n° 2). pp. 161-175.

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Identification Number : 10.1080/17421772.2020.1828613


In an election, the vote shares by party for a given subdivision of a territory form a compositional vector (positive components adding up to 1). Conventional multiple linear regression models are not adapted to explain this composition due to the constraint on the sum of the components and the potential spatial autocorrelation across territorial units. We develop a simultaneous spatial autoregressive model for compositional data that allows for both spatial correlation and correlations across equations. Using simulations and a data set from the 2015 French departmental election, we illustrate its estimation by two-stage and three-stage least squares methods.

Item Type: Article
Language: English
Date: June 2021
Refereed: Yes
Uncontrolled Keywords: Multivariate Spatial Autocorrelation, Spatial Weight Matrix, Three-stage Least Squares, Two-stage, Least, Squares, simplex, electorel data, CoDa
Divisions: TSE-R (Toulouse)
Site: UT1
Date Deposited: 11 Dec 2020 13:32
Last Modified: 04 Sep 2023 08:41
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