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Measuring State and District Ideology with Spatial Realignment

  • James E. Monogan and Jeff Gill

We develop a new approach for modeling public sentiment by micro-level geographic region based on Bayesian hierarchical spatial modeling. Recent production of detailed geospatial political data means that modeling and measurement lag behind available information. The output of the models gives not only nuanced regional differences and relationships between states, but more robust state-level aggregations that update past research on measuring constituency opinion. We rely here on the spatial relationships among observations and units of measurement in order to extract measurements of ideology as geographically narrow as measured covariates. We present an application in which we measure state and district ideology in the United States in 2008.

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James E. Monogan III, Assistant Professor, Department of Political Science, University of Georgia, Athens, GA 30602 ( Jeff Gill, Professor, Departments of Political Science, Biostatistics and Surgery, Washington University, One Brookings Drive, Seigle Hall, St. Louis, MO 63130-4899 ( The authors thank Robert S. Erikson, Bradley P. Carlin, Guy D. Whitten, Stephen Ansolabehere, Robert J. Franzese, Jude Hays, Paulo J. Ribeiro Jr., and the anonymous reviewers for their helpful assistance. This study was supported in part by resources and technical expertise from the Georgia Advanced Computing Resource Center, a partnership between the University of Georgia’s Office of the Vice President for Research and Office of the Vice President for Information Technology. Questions may be directed to James Monogan as corresponding author. Complete replication information and our estimates of ideology in 2008 are available at our Dataverse page: To view supplementary material for this article, please visit

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Political Science Research and Methods
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