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A Method of Scaling with Applications to the 1968 and 1972 Presidential Elections
Abstract
A method of scaling is proposed to estimate the positions of candidates and voters on a common issue dimension. The scaling model assumes that candidates occupy true positions in an issue space and that individual level perceptual data arise from this in a two step process. The first step consists of a stochastic component, satisfying the standard Gauss Markov assumptions, which reflects true misperception. The second step consists of a linear distortion which is introduced in the survey situation. Estimates of the parameters of the model are developed by applying the least squares criterion, and distributions of the estimates are investigated by Monte Carlo methods. The scaling technique is applied to the seven-point issue scales asked in the 1968 and 1972 SRC survey. The resulting ideal point estimates are related to candidate positions in 1968 to test a simple Downsian voting model.
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Citations
Cited by
The Microfoundations of Mass Polarization
Levendusky, M. S. (2009) · Political Analysis · doi:10.1093/pan/mpp003 · Cited by 125
A Common Left-Right Scale for Voters and Parties in Europe
Lo, J., Proksch, S.-O., & Gschwend, T. (2014) · Political Analysis · doi:10.1093/pan/mpt028 · Cited by 78
Park, B. (2018) · Social Forces · doi:10.1093/sf/sox093 · Cited by 67
Metadata
- Authors
- Aldrich, J. H., & McKelvey, R. D.
- Venue
- American Political Science Review
- Publisher
- Cambridge University Press
- Published
- 1977-03-01
- Volume
- 71
- Issue
- 1
- Pages
- 111-130
- ISSN
- 0003-0554 (ISSN-L)
- OpenAlex
- W2133394367
- Cited by
- 301
- References
- 0
- FWCI
- 14.83
- Type
- journal article
- Language
- en
- Open access
- closed
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Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
