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Published online by Cambridge University Press: 04 January 2017
Measures of constituency preferences are of vital importance for the study of political representation and other research areas. Yet, such measures are often difficult to obtain. Previous survey-based estimates frequently lack precision and coverage due to small samples, rely on questionable assumptions or require detailed auxiliary information about the constituencies' population characteristics. We propose an alternative Bayesian hierarchical approach that exploits minimal geographic information readily available from digitalized constituency maps. If at hand, social background data are easily integrated. To validate the method, we use national polls and district-level results from the 2009 German Bundestag election, an empirical case for which detailed structural information is missing.
Authors' note: We are grateful to Michael Herrmann, Thomas Hinz, Winfried Pohlmeier, Susumu Shikano, Marco Steenbergen as well as the editors and reviewers of this journal for helpful comments and support. Supplementary materials for this article are available on the Political Analysis Web site. Appendix is available from the Political Analysis Dataverse at http://hdl.handle.net/1902.1/16363.
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