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It's (Change in) the (Future) Economy, Stupid: Economic Indicators, the Media, and Public Opinion

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  • Stuart N. Soroka
  • Dominik A. Stecula
  • Christopher Wlezien

Abstract

Economic perceptions affect policy preferences and government support. It thus matters that these perceptions are driven by factors other than the economy, including media coverage. We nevertheless know little about how media reflect economic trends, and whether they influence (or are influenced by) public economic perceptions. This article explores the economy, media, and public opinion, focusing in particular on whether media coverage and the public react to changes in or levels of economic activity, and the past, present, or future economy. Analyses rely on content‐analytic data drawn from 30,000 news stories over 30 years in the United States. Results indicate that coverage reflects change in the future economy, and that this both influences and is influenced by public evaluations. These patterns make more understandable the somewhat surprising finding of positive coverage and public assessments in the midst of the Great Recession. They also may help explain previous findings in political behavior.

Suggested Citation

  • Stuart N. Soroka & Dominik A. Stecula & Christopher Wlezien, 2015. "It's (Change in) the (Future) Economy, Stupid: Economic Indicators, the Media, and Public Opinion," American Journal of Political Science, John Wiley & Sons, vol. 59(2), pages 457-474, February.
    • Handle: RePEc:wly:amposc:v:59:y:2015:i:2:p:457-474
    DOI: 10.1111/ajps.12145
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    Cited by:

    1. Bennani, Hamza, 2018. "Media coverage and ECB policy-making: Evidence from an augmented Taylor rule," Journal of Macroeconomics, Elsevier, vol. 57(C), pages 26-38.
    2. Nimark, Kristoffer P. & Pitschner, Stefan, 2019. "News media and delegated information choice," Journal of Economic Theory, Elsevier, vol. 181(C), pages 160-196.
    3. Călin Vâlsan & Elena Druică & Zizi Goschin & Rodica Ianole-Călin, 2024. "The Perception of Economic Growth and the Romanian “Mioritic Syndrome”," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(1), pages 3718-3739, March.
    4. Hannah L. Paul & Andrew Q. Philips, 2022. "What goes up must come down: Theory and model specification of threshold dynamics," Social Science Quarterly, Southwestern Social Science Association, vol. 103(5), pages 1273-1289, September.
    5. Marcos Bujosa & Antonio García‐Ferrer & Aránzazu de Juan & Antonio Martín‐Arroyo, 2020. "Evaluating early warning and coincident indicators of business cycles using smooth trends," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(1), pages 1-17, January.
    6. Cahan, Dodge, 2019. "Electoral cycles in government employment: Evidence from US gubernatorial elections," European Economic Review, Elsevier, vol. 111(C), pages 122-138.
    7. Allison, Thomas H. & Grimes, Matthew & McKenny, Aaron F. & Short, Jeremy C., 2021. "Occupy Wall Street ten years on: How its disruptive institutional entrepreneurship spread and why it fizzled," Journal of Business Venturing Insights, Elsevier, vol. 16(C).
    8. Hampson, Daniel P. & Gong, Shiyang & Xie, Yi, 2021. "How consumer confidence affects price conscious behavior: The roles of financial vulnerability and locus of control," Journal of Business Research, Elsevier, vol. 132(C), pages 693-704.
    9. Miklos Sebők & Zoltán Kacsuk & Ákos Máté, 2022. "The (real) need for a human touch: testing a human–machine hybrid topic classification workflow on a New York Times corpus," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(5), pages 3621-3643, October.
    10. Riatu Mariatul Qibthiyyah & Ummi Salamah, 2018. "Are (More) Economic News Good for the Economy ? Case on Indonesian Sub-nationals," LPEM FEBUI Working Papers 201826, LPEM, Faculty of Economics and Business, University of Indonesia, revised 2018.
    11. Raffaele Guetto & Maria Francesca Morabito & Daniele Vignoli & Matthias Vollbracht, 2021. "Media Coverage of the Economy and Fertility," Econometrics Working Papers Archive 2021_12, Universita' degli Studi di Firenze, Dipartimento di Statistica, Informatica, Applicazioni "G. Parenti".
    12. Hanjo Odendaal, 2021. "A machine learning approach to domain specific dictionary generation. An economic time series framework," Working Papers 06/2021, Stellenbosch University, Department of Economics.
    13. Benito Umaña-Hermosilla & Hanns de la Fuente-Mella & Claudio Elórtegui-Gómez & Marisela Fonseca-Fuentes, 2020. "Multinomial Logistic Regression to Estimate and Predict the Perceptions of Individuals and Companies in the Face of the COVID-19 Pandemic in the Ñuble Region, Chile," Sustainability, MDPI, vol. 12(22), pages 1-20, November.

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