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Analysing Party Preferences Using Google Trends

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  • Calahorrano, Lena
  • Seithe, Mirko

Abstract

The formation of party preferences is a complex and not yet fully understood process based on a number of factors. This process, which is of great interest for both social and political science, is usually studied using questionnaire data which has proven to be a very reliable yet often costly and limited approach. Advances in technology and the rise of the internet as a primary information source for many people have created a new approach to keep track of people s interests. The major gateways to the internet s information are the so-called search engines, and Google, arguably the most commonly used search engine, allows scientists to tap the vast source of information generated by its users search queries. In this paper we describe how this data source can be used to estimate the effect of different issues on party preferences using German voters and the German party system as an example. We find that using data provided by Google Trends can lead to a variety of interesting and occasionally counterintuitive insights into peoples party preferences.

Suggested Citation

  • Calahorrano, Lena & Seithe, Mirko, 2014. "Analysing Party Preferences Using Google Trends," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100294, Verein für Socialpolitik / German Economic Association.
    • Handle: RePEc:zbw:vfsc14:100294
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    References listed on IDEAS

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    1. Logan Dancey & Paul Goren, 2010. "Party Identification, Issue Attitudes, and the Dynamics of Political Debate," American Journal of Political Science, John Wiley & Sons, vol. 54(3), pages 686-699, July.
    2. Nikolaos Askitas & Klaus F. Zimmermann, 2009. "Google Econometrics and Unemployment Forecasting," Applied Economics Quarterly (formerly: Konjunkturpolitik), Duncker & Humblot, Berlin, vol. 55(2), pages 107-120.
    3. Zeileis, Achim & Grothendieck, Gabor, 2005. "zoo: S3 Infrastructure for Regular and Irregular Time Series," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 14(i06).
    4. Zeileis, Achim, 2004. "Econometric Computing with HC and HAC Covariance Matrix Estimators," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 11(i10).
    5. Rabinowitz, George & Macdonald, Stuart Elaine, 1989. "A Directional Theory of Issue Voting," American Political Science Review, Cambridge University Press, vol. 83(1), pages 93-121, March.
    6. Henningsen, Arne & Hamann, Jeff D., 2007. "systemfit: A Package for Estimating Systems of Simultaneous Equations in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 23(i04).
    7. Thomas M. Carsey & Geoffrey C. Layman, 2006. "Changing Sides or Changing Minds? Party Identification and Policy Preferences in the American Electorate," American Journal of Political Science, John Wiley & Sons, vol. 50(2), pages 464-477, April.
    8. Geys, Benny & Vermeir, Jan, 2008. "The political cost of taxation: new evidence from German popularity ratings [Besteuerung und Popularität von Politikern: Neue Ergebnisse für die Deutsche Bundesregierung 1978-2003]," Discussion Papers, Research Unit: Market Processes and Governance SP II 2008-06, WZB Berlin Social Science Center.
    9. Ingo Geishecker & Thomas Siedler, 2012. "Job Loss Fears and (Extremist) Party Identification: First Evidence from Panel Data," SOEPpapers on Multidisciplinary Panel Data Research 511, DIW Berlin, The German Socio-Economic Panel (SOEP).
    10. Hyunyoung Choi & Hal Varian, 2012. "Predicting the Present with Google Trends," The Economic Record, The Economic Society of Australia, vol. 88(s1), pages 2-9, June.
    11. Anthony Downs, 1957. "An Economic Theory of Political Action in a Democracy," Journal of Political Economy, University of Chicago Press, vol. 65(2), pages 135-135.
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    More about this item

    JEL classification:

    • D72 - Microeconomics - - Analysis of Collective Decision-Making - - - Political Processes: Rent-seeking, Lobbying, Elections, Legislatures, and Voting Behavior
    • H00 - Public Economics - - General - - - General
    • C80 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - General

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