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

Ron Johnston*, Kelvyn Jones, David Manley

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

4 Citations (Scopus)
157 Downloads (Pure)

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.

Original languageEnglish
Pages (from-to)280-313
Number of pages34
JournalGeographical Analysis
Volume51
Issue number3
Early online date23 Oct 2018
DOIs
Publication statusPublished - 1 Jul 2019

Keywords

  • United States
  • presidential elections
  • spatial polarization
  • landslides

Fingerprint

Dive into the research topics of 'MultiLevel Modeling of Space–Time Variations: Exploring Landslide Voting Patterns at United States Presidential Elections, 1992–2016'. Together they form a unique fingerprint.

Cite this