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MultiLevel Modeling of Space–Time Variations: Exploring Landslide Voting Patterns at United States Presidential Elections, 1992–2016

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MultiLevel Modeling of Space–Time Variations : Exploring Landslide Voting Patterns at United States Presidential Elections, 1992–2016. / Johnston, Ron; Jones, Kelvyn; Manley, David.

In: Geographical Analysis, Vol. 51, No. 3, 01.07.2019, p. 280-313.

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@article{bd1571686c784a3190e1c497ea381c04,
title = "MultiLevel Modeling of Space–Time Variations: Exploring Landslide Voting Patterns at United States Presidential Elections, 1992–2016",
abstract = "Much has been written about the polarization of the American electorate and its reflection in its legislatures, but less about its spatial polarization, which Bishop has argued has taken place in parallel with the ideological and behavioral polarization. The extent of that polarization can be assessed, he argues, by identifying the number of landslide counties, those won at presidential elections by margins of 20 percentage points or more. This paper uses a multilevel modeling strategy to explore changes in the number and extent of those landslide counties over the period 1992–2016, relative to both the location of the counties and their population composition. It shows that a county’s population composition was a major determinant of whether it returned a landslide for either party’s candidate at any election—with a clear change in direction over the period for counties according to their level of affluence—but this was by no means the sole determinant. Holding constant those variations there were additional geographies that were more place- than people-specific.",
keywords = "United States, presidential elections, spatial polarization, landslides",
author = "Ron Johnston and Kelvyn Jones and David Manley",
year = "2019",
month = "7",
day = "1",
doi = "10.1111/gean.12176",
language = "English",
volume = "51",
pages = "280--313",
journal = "Geographical Analysis",
issn = "0016-7363",
publisher = "Ohio State University Press",
number = "3",

}

RIS - suitable for import to EndNote

TY - JOUR

T1 - MultiLevel Modeling of Space–Time Variations

T2 - Exploring Landslide Voting Patterns at United States Presidential Elections, 1992–2016

AU - Johnston, Ron

AU - Jones, Kelvyn

AU - Manley, David

PY - 2019/7/1

Y1 - 2019/7/1

N2 - Much has been written about the polarization of the American electorate and its reflection in its legislatures, but less about its spatial polarization, which Bishop has argued has taken place in parallel with the ideological and behavioral polarization. The extent of that polarization can be assessed, he argues, by identifying the number of landslide counties, those won at presidential elections by margins of 20 percentage points or more. This paper uses a multilevel modeling strategy to explore changes in the number and extent of those landslide counties over the period 1992–2016, relative to both the location of the counties and their population composition. It shows that a county’s population composition was a major determinant of whether it returned a landslide for either party’s candidate at any election—with a clear change in direction over the period for counties according to their level of affluence—but this was by no means the sole determinant. Holding constant those variations there were additional geographies that were more place- than people-specific.

AB - Much has been written about the polarization of the American electorate and its reflection in its legislatures, but less about its spatial polarization, which Bishop has argued has taken place in parallel with the ideological and behavioral polarization. The extent of that polarization can be assessed, he argues, by identifying the number of landslide counties, those won at presidential elections by margins of 20 percentage points or more. This paper uses a multilevel modeling strategy to explore changes in the number and extent of those landslide counties over the period 1992–2016, relative to both the location of the counties and their population composition. It shows that a county’s population composition was a major determinant of whether it returned a landslide for either party’s candidate at any election—with a clear change in direction over the period for counties according to their level of affluence—but this was by no means the sole determinant. Holding constant those variations there were additional geographies that were more place- than people-specific.

KW - United States

KW - presidential elections

KW - spatial polarization

KW - landslides

UR - http://www.scopus.com/inward/record.url?scp=85055253353&partnerID=8YFLogxK

U2 - 10.1111/gean.12176

DO - 10.1111/gean.12176

M3 - Article

VL - 51

SP - 280

EP - 313

JO - Geographical Analysis

JF - Geographical Analysis

SN - 0016-7363

IS - 3

ER -