The spatial and temporal dynamics of voter preference determinants in four U.S. presidential elections (2008–2020)

Li, Ziqi; Fotheringham, A. Stewart

doi:10.1111/tgis.12880

Cited by 6 publications

(7 citation statements)

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“…2019, p. 14). Most of the effects of the independent variables fall in line with the expectations noted in Table 2 and the geographic patterns shown by Li and Fotheringham (2022).…”

Section: Explaining Change and Consistencysupporting

confidence: 85%

“…The average conditional index is 12.65, well below 30 which indicates an issue with multicollinearity (Oshan et al 2019, p. 14). 17 Most of the effects of the independent variables fall in line with the expectations noted in Table 2 and the geographic patterns shown by Li and Fotheringham (2022).…”

Section: Explaining Change and Consistencysupporting

confidence: 67%

“…In MGWR analyses, the intercept is meaningful (Fotheringham, Yang, and Kang 2017; Li and Fotheringham 2022). It represents the standardized level of GOP partisan voting during the Geographic Sort alignment holding all of the independent variables constant at their mean of zero.…”

Section: Explaining Change and Consistencymentioning

confidence: 99%

“…It represents the standardized level of GOP partisan voting during the Geographic Sort alignment holding all of the independent variables constant at their mean of zero. Or put another way, the intercept represents the inherent bias in each county toward each party's presidential ticket that is “due to where they live,” “independent of all the other contributing factors in the model” (Li and Fortheringham 2022, p. 16). Panel F of Figure 6 shows a strong sectionally based partisan bias.…”

Section: Explaining Change and Consistencymentioning

confidence: 99%

“…This represents people born in 1946, the beginning of the Baby Boom through 1985, which roughly coincides with the end of Gen X. There is one control variable drawn from the rural sociology literature that is not on the list of standard variables used by political geographers for predicting presidential voting patterns in counties (for standard list used by political geographers, see Li and Fotheringham 2022).…”

Section: Explaining Change and Consistencymentioning

confidence: 99%

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The 1990s party realignment of U.S. presidential elections: Geographic sorting of counties by blue or red

Aistrup

Mahato

Morris

2023

Social Science Quarterly

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Introduction: This paper addresses the issue of partisan polarization in the U.S. in presidential voting at the county level. The literature on the growing partisan sorting and/or polarization is extensive, and controversies are pervasive. This paper focuses on the timing and sequence of changes in partisan vote shares at the county level from 1952 through the 2020 election. Methods: We apply confirmatory factor analysis to identify the structures of partisan competition in counties from 1952 to 2020, and multiscale geographically weighted regression (MGWR) to uncover the social processes that influence the growing partisan polarization in the U.S. Results: We find that the growing partisan segregation coincides with the beginning of a secular change in the structure of partisan competition at the presidential level among counties that has intensified over the past quarter century. Polarization, segregation of partisans in communities, and a rise in sectionalism are the predominant characteristics of this new alignment. Conclusion:This study confirms a secular realignment in the structure of party competition among counties in presidential elections starting in 1996 and solidifying in 2008 when Obama is elected. The segregation of counties by dark shades of red or blue is the unique fingerprint of this new alignment that we call the "Geographic Sort" alignment.

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“…2019, p. 14). Most of the effects of the independent variables fall in line with the expectations noted in Table 2 and the geographic patterns shown by Li and Fotheringham (2022).…”

Section: Explaining Change and Consistencysupporting

confidence: 85%

Section: Explaining Change and Consistencysupporting

confidence: 67%