Abstract This article investigates how economic, political, spatial, and linguistic factors jointly structure the political geography of Switzerland. Leveraging detailed municipal-level income tax data, we reconstruct wealth distributions and compute different inter-municipality economic distances from Swiss Federal Tax data. These, declined into simple mean and optimal transport distances (Wasserstein), are compared to political distances derived from 381 national referenda (1971--2024). Using a kernel-based approach, multidimensional scaling (MDS), spatial autocorrelation index and multiple regression, we explore the alignment between economic inequality, political behavior, and spatial-linguistic structures. Our results reveal that optimal transport income disparities explain political divides better than do the average wealth, while linguistic and urban--rural divisions remain largely dominant structuring forces of political explanation. This study highlights the potential of MDS visualization and the kernel associations in analyzing spatially embedded political behavior.
Romain Loup (Wed,) studied this question.