This study investigates the spatial and political contagion dynamics influencing candidate polls for US swing states during the 2020 presidential election. By suggesting a Markov Switching Spatial-Temporal AutoRegressive model (MSSTAR), we achieve evidence of significant interdependence and regime-specific impact of spatial components, particularly in states with uncertain electoral outcomes. The model highlights the role of neighboring states during periods of greater political uncertainty.
Spatial Dependence in the Dynamics of the 2020 Presidential Election Polls Trackers
Demetrio Lacava
;Edoardo Otranto
2025-01-01
Abstract
This study investigates the spatial and political contagion dynamics influencing candidate polls for US swing states during the 2020 presidential election. By suggesting a Markov Switching Spatial-Temporal AutoRegressive model (MSSTAR), we achieve evidence of significant interdependence and regime-specific impact of spatial components, particularly in states with uncertain electoral outcomes. The model highlights the role of neighboring states during periods of greater political uncertainty.File in questo prodotto:
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