Estimating floating voters: a comparison between the ecological inference and the survey methods

L. Russo*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

There are two main approaches to estimating the proportion of the electorate who are floating voters: the survey method and the ecological estimate method. Both the methods have their advantages and their problems. The main difficulties with the survey method are the coverage of the sample and the problems introduced by reliance on the quality of memory of the subjects. Ecological estimates have different problems, the principal of which is known as the ecological fallacy. The aim of this paper is to assess whether the survey and ecological estimates of voter swing between two elections are significantly different. For this purpose I will consider the 2006 and 2008 Italian Parliamentary elections. Given the short temporal gap between these two elections, both the methods should give reliable estimates, as the shorter the time between the two elections, the fewer the problems which will be encountered by subjects recalling the party they voted for in the previous one, and the fewer the changes which will have taken place in the composition of the population between the two elections. The ecological data I will employ comprise all the votes cast in both of the elections under consideration (2006 and 2008), at the polling station level. In Italy there are about 60,000 polling stations, and I will analyse the data from these using the Goodman Model. The survey data has been provided by Italian National Election Studies (ITANES), and consists of a large representative sample, obtained by interviews conducted by CATI.

Original languageEnglish
Pages (from-to)1667-1683
Number of pages17
JournalQuality & Quantity
Volume48
Issue number3
DOIs
Publication statusPublished - May 2014

Keywords

  • BEHAVIOR
  • DEMOCRACIES
  • ELECTORAL VOLATILITY
  • Ecological inference
  • Floating voters
  • Flows-of-vote
  • Goodman model
  • INDIVIDUALS
  • Italy
  • REGRESSIONS

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