Paper Info
Title
The spatial and temporal dynamics of voter preference determinants in four US presidential elections (2008-2020)
Abstract
Political and social processes that shape people's voting preferences might be linked to geographical location, varying from place to place, and operating at local, regional, and national scales. Here, we use a local modeling technique, multiscale geographically weighted regression (MGWR), to examine spatial and temporal variations in the influences of county-level socio-economic factors on voter preference during the 2008-2020 U.S. presidential elections. We argue that the local intercept in the MGWR model is an indicator of the effect of spatial context on voter preference and not only can this be separated from the effect of other socio-economic factors, but it needs to be in order to prevent misspecification bias in the indicators of these other factors. We also identify strong and consistent divisions across the country in how context shapes election results.
Year
DOI
Venue
2022
10.1111/tgis.12880
TRANSACTIONS IN GIS
DocType
Volume
Issue
Journal
26
3
ISSN
Citations 
PageRank 
1361-1682
0
0.34
References 
Authors
0
2
Name
Order
Citations
PageRank
Ziqi Li100.34
A. Stewart Fotheringham214333.77