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The party leadership model : an early forecast of the 2015 British general election

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Murr, Andreas (2015) The party leadership model : an early forecast of the 2015 British general election. Research & Politics, 2 (2). pp. 1-9. doi:10.1177/2053168015583346 ISSN 2053-1680.

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Official URL: https://doi.org/10.1177/2053168015583346

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Abstract

British political parties select their leaders to win elections. The winning margin of the party leader among the selectorate reflects how likely they think she is to win the General Election. The present research compares the winning margins of party leaders in their party leadership elections and uses the results of this comparison to predict that the party leader with the larger winning margin will become the next Prime Minister. I term this process "the Party Leadership Model". The model correctly forecasts 8 out of 10 past elections, while making these forecasts 4 years in advance on average. According to a Bayesian analysis, there is a 95 per cent probability that having the larger winning margin in party leadership elections increases the chances of winning the General Election. Because David Cameron performed better among Conservative MPs in 2005 than Ed Miliband did among Labour MPs in 2010, the model predicts Cameron to become Prime Minister again in 2015. The Bayesian calculation puts his chances of re-election at 75 per cent.

Item Type: Journal Article
Subjects: J Political Science > JA Political science (General)
J Political Science > JF Political institutions (General)
J Political Science > JN Political institutions (Europe) > JN101 Great Britain
Divisions: Faculty of Social Sciences > Politics and International Studies
Library of Congress Subject Headings (LCSH): Election forecasting -- Great Britain, Public opinion polls -- Great Britain, Exit polling (Elections) -- Great Britain, Political leadership -- Great Britain -- Forecasting
Journal or Publication Title: Research & Politics
Publisher: Sage Publications, Inc.
ISSN: 2053-1680
Official Date: 1 April 2015
Dates:
DateEvent
1 April 2015Published
28 May 2015Available
19 December 2014Accepted
Volume: 2
Number: 2
Page Range: pp. 1-9
DOI: 10.1177/2053168015583346
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access (Creative Commons)
Date of first compliant deposit: 13 January 2020
Date of first compliant Open Access: 13 January 2020
Open Access Version:
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