measuring turnout who voted in 2010
Download
Skip this Video
Download Presentation
Measuring Turnout – Who Voted in 2010?

Loading in 2 Seconds...

play fullscreen
1 / 27

Measuring Turnout Who Voted in 2010 - PowerPoint PPT Presentation


  • 61 Views
  • Uploaded on

Measuring Turnout – Who Voted in 2010?. British Election Study - 2010. Harold Clarke, David Sanders, Marianne Stewart, Paul Whiteley, University of Essex and University of Texas at Dallas [email protected] Turnout Figures in the 2005 and 2010 British Election Study Surveys for Britain.

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about 'Measuring Turnout Who Voted in 2010' - sharona


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
measuring turnout who voted in 2010
Measuring Turnout – Who Voted in 2010?

British Election Study - 2010

Harold Clarke, David Sanders, Marianne Stewart, Paul Whiteley,

University of Essex and University of Texas at Dallas

[email protected]

the measurement of turnout in various studies percentages exceeding actual turnout
The Measurement of Turnout in Various Studies – Percentages Exceeding Actual Turnout
slide5

Likelihood of Voting Scale in the Pre-Election Survey ‘Please think of a scale that runs from 0 to 10, where 0 means very unlikely and 10 means very likely, how likely is it that you will vote in the next general election that may be held soon?’

slide6
Pre-Election Probability of Voting Scale as a Predictor of Post-Election Reported Turnout in 2010 (Eta=0.44)
slide7
Pre-Election Probability of Voting Scale as a Predictor of Post-Election Reported Turnout in 2005 (eta=0.56)
slide8
Pre-Election Probability of Voting Scale as a Predictor of Post-Election Validated Turnout in 2005 (Eta=0.43)
logistic regression of turnout with demographic predictors bes panel data
Logistic Regression of Turnout with Demographic Predictors (BES panel data)
  • p<0.01=***; p<0.05=**; p<0.10=*
rational choice model of turnout
Rational Choice Model of Turnout
  • Turnout = α0 + β1 Efficacy * Collective Benefits
  • - β2Costs + β3 Individual Benefits
  • + β4Civic Duty
  • Turnout: Self-reported voting, post-election survey
  • Collective Benefits: Party Differential weighted by Efficacy, pre-election survey
  • Individual Benefits: private benefits of voting, pre-election survey
  • Civic Duty: Perceptions of Duty to Vote, pre-election survey
  • See H.Clarke, D. Sanders, M.Stewart and P. Whiteley, Political Choice in Britain (Oxford University Press, 2004) chapter 8.
collective benefits party differential
Collective Benefits – Party Differential
  • Party Differential
  • = (Con – Lab)2 + (Con – LibDem)2 + (Lab – LibDem)2
  • The greater the party differential the greater the incentive to vote
slide20

Efficacy in the Rational Choice Model‘Please use the 0 to 10 scale to tell me how likely it is that the votes of people like you will make a difference to which party wins the election in this constituency’

civic duty and voting i would be seriously neglecting my duty as a citizen if i didn t vote
Civic Duty and Voting ‘I would be seriously neglecting my duty as a citizen if I didn\'t vote’.
logistic model of turnout with rational choice and demographic predictors
Logistic Model of Turnout with Rational Choice and Demographic Predictors
  • p<0.01=***; p<0.05=**; p<0.10=*
conclusions
Conclusions
  • A theoretical model significantly improves the predictive power of a turnout model over and above demographic predictors
  • We might expect nobody with a score of less than 7 or 8 on the pre-election likelihood of voting scale to vote, but they do.
  • If we use demographics to model the discrepancy between the likelihood and actual voting they don’t help very much
  • However, the theoretical model does help to capture this discrepancy and with other theoretical models it can be used to weight the likelihood of voting measure to make it more accurate
ad