Aggregation level matters: evidence from french electoral data

Aggregation level matters: evidence from french electoral data This paper, issued from the Cartelec project, raises a methodological issue regarding ecological inference. Studying abstention in two recent French elections in the Parisian agglomeration, a linear regression is launched on three different levels of aggregation: from the finest one (polling station), through cities, to electoral districts (circonscriptions). Tests on multicollinearity clearly indicate that employing the finest level of aggregation allows more variables to be significant, enhances the explanatory power of the model, and improves the collinearity amongst the dependent variables. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Quality & Quantity Springer Journals

Aggregation level matters: evidence from french electoral data

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Publisher
Springer Netherlands
Copyright
Copyright © 2012 by Springer Science+Business Media Dordrecht
Subject
Social Sciences, general; Methodology of the Social Sciences; Social Sciences, general
ISSN
0033-5177
eISSN
1573-7845
D.O.I.
10.1007/s11135-012-9814-0
Publisher site
See Article on Publisher Site

Abstract

This paper, issued from the Cartelec project, raises a methodological issue regarding ecological inference. Studying abstention in two recent French elections in the Parisian agglomeration, a linear regression is launched on three different levels of aggregation: from the finest one (polling station), through cities, to electoral districts (circonscriptions). Tests on multicollinearity clearly indicate that employing the finest level of aggregation allows more variables to be significant, enhances the explanatory power of the model, and improves the collinearity amongst the dependent variables.

Journal

Quality & QuantitySpringer Journals

Published: Dec 8, 2012

References

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