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To vote, or not to vote? Understanding voter turnout patterns: Constructing, interpreting and comparing logistic regression models measuring voter turnout in German federal elections
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Social Sciences, Department of Statistics.
2019 (English)Independent thesis Basic level (degree of Bachelor), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

The core of any democracy is constituted on the very principle of entrusting citizens to elect their leaders. Yet, no country has ever achieved total voter turnout. This paper aims to better understand the differences between people who vote and those who choose not to. We have chosen to look closer at the case of Germany, a country that on paper seem to have the right conditions for high voter turnout whilst instead only acquiring a mediocre turnout in recent elections. To do so, we make use of cross-sectional data collected by the World Value Survey in 2013. We construct, interpret and compare 10 different models based on both previous research on the topic of voter turnout as well as our own intuition. Through the usage of logistic regression, we aim to further the understanding on how a range of different variables affect the likelihood of one voting in German federal elections. Furthermore, some of the presented models are used to predict whether or not individuals voted as a way of comparing the models as well as a mean of evaluating their applicability. The paper presents a benchmark model constituted of two variables that are used as control variables in some of the other models as well – age and education. By extensively analysing these two variables we were able to find that they seem to improve the predictive power in terms of increasing a model’s ability to effectively detect nonvoters. Most models saw great difficulty in finding nonvoters within the dataset, furthering our perception that voter turnout is a complex phenomenon to understand on a micro-level. Despite this, we were able to distinguish what variables and models that appear to be more appropriate, convenient and suitable to understand voter turnout in the case of German federal elections based on 2013 data and hopefully by extension unveiling implications for the general case of voter turnout in industrialized, well-developed western democracies.

Place, publisher, year, edition, pages
2019. , p. 49
Keywords [en]
Voter turnout, Logistic regression, Confusion matrix, Receiver operating characteristic (ROC), World value survey (WVS), R applications
National Category
Probability Theory and Statistics
Identifiers
URN: urn:nbn:se:uu:diva-403523OAI: oai:DiVA.org:uu-403523DiVA, id: diva2:1389411
Subject / course
Statistics
Educational program
Bachelor Programme in Political Science
Presentation
2020-01-17, Ekonomikum, Kyrkogårdsgatan 10, Uppsala, 09:00 (Swedish)
Supervisors
Examiners
Available from: 2020-02-03 Created: 2020-01-29 Last updated: 2020-02-03Bibliographically approved

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CiteExportLink to record
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Citation style
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