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Does Public Opinion Affect Political Speech?

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  • Hager, Anselm
  • Hilbig, Hanno

Abstract

Does public opinion affect political speech? Of particular interest is whether public opinion affects (i) what topics politicians address and (ii) what positions they endorse. We present evidence from Germany where the government was recently forced to declassify its public opinion research, allowing us to link the content of the research to subsequent speeches. Our causal identification strategy exploits the exogenous timing of the research's dissemination to cabinet members within a window of a few days. We find that exposure to public opinion research leads politicians to markedly change their speech. First, we show that linguistic similarity between political speech and public opinion research increases significantly after reports are passed on to the cabinet, suggesting that politicians change the topics they address. Second, we demonstrate that exposure to public opinion research alters politicians' substantive positions in the direction of majority opinion.

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  • Hager, Anselm & Hilbig, Hanno, 2020. "Does Public Opinion Affect Political Speech?," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 64(4), pages 921-937.
    • Handle: RePEc:zbw:espost:218852
    DOI: 10.1111/ajps.12516
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    1. Margaret E. Roberts & Brandon M. Stewart & Dustin Tingley & Christopher Lucas & Jetson Leder‐Luis & Shana Kushner Gadarian & Bethany Albertson & David G. Rand, 2014. "Structural Topic Models for Open‐Ended Survey Responses," American Journal of Political Science, John Wiley & Sons, vol. 58(4), pages 1064-1082, October.
    2. Grimmer, Justin & Stewart, Brandon M., 2013. "Text as Data: The Promise and Pitfalls of Automatic Content Analysis Methods for Political Texts," Political Analysis, Cambridge University Press, vol. 21(3), pages 267-297, July.
    3. Andrew C. Eggers & Arthur Spirling, 2014. "Ministerial Responsiveness in Westminster Systems: Institutional Choices and House of Commons Debate, 1832–1915," American Journal of Political Science, John Wiley & Sons, vol. 58(4), pages 873-887, October.
    4. Lucas, Christopher & Nielsen, Richard A. & Roberts, Margaret E. & Stewart, Brandon M. & Storer, Alex & Tingley, Dustin, 2015. "Computer-Assisted Text Analysis for Comparative Politics," Political Analysis, Cambridge University Press, vol. 23(2), pages 254-277, April.
    5. Jonathan B. Slapin & Sven‐Oliver Proksch, 2008. "A Scaling Model for Estimating Time‐Series Party Positions from Texts," American Journal of Political Science, John Wiley & Sons, vol. 52(3), pages 705-722, July.
    6. McCrary, Justin, 2008. "Manipulation of the running variable in the regression discontinuity design: A density test," Journal of Econometrics, Elsevier, vol. 142(2), pages 698-714, February.
    7. Rauh, Christian, 2015. "Communicating supranational governance? The salience of EU affairs in the German Bundestag, 1991–2013," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 16(1), pages 116-138.
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    Cited by:

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    5. Silvia Angerer & Daniela Glätzle-Rützler & Philipp Lergetporer & Thomas Rittmannsberger, 2022. "How Does the Vaccine Approval Procedure Affect Covid-19 Vaccination Intentions?," CESifo Working Paper Series 9648, CESifo.
    6. Lergetporer, Philipp & Woessmann, Ludger, 2023. "Earnings information and public preferences for university tuition: Evidence from representative experiments," Journal of Public Economics, Elsevier, vol. 226(C).
    7. Angerer, Silvia & Glätzle-Rützler, Daniela & Lergetporer, Philipp & Rittmannsberger, Thomas, 2023. "How does the vaccine approval procedure affect COVID-19 vaccination intentions?," European Economic Review, Elsevier, vol. 158(C).
    8. Kruse, Tobias & Atkinson, Giles, 2022. "Understanding public support for international climate adaptation payments: evidence from a choice experiment," LSE Research Online Documents on Economics 112963, London School of Economics and Political Science, LSE Library.
    9. Silvia Angerer & Daniela Glätzle-Rützler & Philipp Lergetporer & Thomas Rittmannsberger, 2022. "How does the vaccine approval procedure affect COVID-19 vaccination intentions?," Working Papers 2022-04, Faculty of Economics and Statistics, Universität Innsbruck.

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