Open Access
Translator Disclaimer
December 2010 Exit polling and racial bloc voting: Combining individual-level and R×C ecological data
D. James Greiner, Kevin M. Quinn
Ann. Appl. Stat. 4(4): 1774-1796 (December 2010). DOI: 10.1214/10-AOAS353

Abstract

Despite its shortcomings, cross-level or ecological inference remains a necessary part of some areas of quantitative inference, including in United States voting rights litigation. Ecological inference suffers from a lack of identification that, most agree, is best addressed by incorporating individual-level data into the model. In this paper we test the limits of such an incorporation by attempting it in the context of drawing inferences about racial voting patterns using a combination of an exit poll and precinct-level ecological data; accurate information about racial voting patterns is needed to assess triggers in voting rights laws that can determine the composition of United States legislative bodies. Specifically, we extend and study a hybrid model that addresses two-way tables of arbitrary dimension. We apply the hybrid model to an exit poll we administered in the City of Boston in 2008. Using the resulting data as well as simulation, we compare the performance of a pure ecological estimator, pure survey estimators using various sampling schemes and our hybrid. We conclude that the hybrid estimator offers substantial benefits by enabling substantive inferences about voting patterns not practicably available without its use.

Citation

Download Citation

D. James Greiner. Kevin M. Quinn. "Exit polling and racial bloc voting: Combining individual-level and R×C ecological data." Ann. Appl. Stat. 4 (4) 1774 - 1796, December 2010. https://doi.org/10.1214/10-AOAS353

Information

Published: December 2010
First available in Project Euclid: 4 January 2011

zbMATH: 1220.62159
MathSciNet: MR2829936
Digital Object Identifier: 10.1214/10-AOAS353

Keywords: Bayesian inference , Ecological inference , exit polls , survey sampling , voting rights litigation

Rights: Copyright © 2010 Institute of Mathematical Statistics

JOURNAL ARTICLE
23 PAGES


SHARE
Vol.4 • No. 4 • December 2010
Back to Top