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The value of and demand for diverse news sources

Author

Listed:
  • Anujit Chakraborty
  • Evan Calford

    (Department of Economics, University of California Davis)

Abstract

We study the value of and the demand for instrumentally-valuable information in a simple decision environment where signals are transparently polarized. We find that in both information aggregation and acquisition, subjects use sophisticated heuristics to counter the polarization in signals. Even though the number of precise Bayesian reports are small, most subjects (64%) generate unpolarized reports even when faced with polarized signals. Subjects placed in a market place of information rarely end up buying polarized signals and instead overwhelmingly opt for diverse information. The demand for diverse information increases as diverse information becomes more valuable and decreases as it becomes more expensive.

Suggested Citation

  • Anujit Chakraborty & Evan Calford, 2023. "The value of and demand for diverse news sources," Working Papers 355, University of California, Davis, Department of Economics.
    • Handle: RePEc:cda:wpaper:355
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    1. Benjamin Enke, 2020. "What You See Is All There Is," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 135(3), pages 1363-1398.
    2. Heiner Mikosch & Christopher Roth & Samad Sarferaz & Johannes Wohlfart, 2024. "Uncertainty and Information Acquisition: Evidence from Firms and Households," American Economic Journal: Macroeconomics, American Economic Association, vol. 16(2), pages 375-405, April.
    3. Andreas Fuster & Ricardo Perez-Truglia & Mirko Wiederholt & Basit Zafar, 2022. "Expectations with Endogenous Information Acquisition: An Experimental Investigation," The Review of Economics and Statistics, MIT Press, vol. 104(5), pages 1059-1078, December.
    4. Mary A. Burke & Michael Manz, 2014. "Economic Literacy and Inflation Expectations: Evidence from a Laboratory Experiment," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 46(7), pages 1421-1456, October.
    5. Ben Greiner, 2015. "Subject pool recruitment procedures: organizing experiments with ORSEE," Journal of the Economic Science Association, Springer;Economic Science Association, vol. 1(1), pages 114-125, July.
    6. Ambuehl, Sandro & Li, Shengwu, 2018. "Belief updating and the demand for information," Games and Economic Behavior, Elsevier, vol. 109(C), pages 21-39.
    7. Felipe A. Araujo & Stephanie W. Wang & Alistair J. Wilson, 2021. "The Times They Are A-Changing: Experimenting with Dynamic Adverse Selection," American Economic Journal: Microeconomics, American Economic Association, vol. 13(4), pages 1-22, November.
    8. Francesco Capozza & Ingar Haaland & Christopher Roth & Johannes Wohlfart, 2021. "Studying Information Acquisition in the Field: A Practical Guide and Review," ECONtribute Discussion Papers Series 124, University of Bonn and University of Cologne, Germany.
    9. Duffy, John & Hopkins, Ed & Kornienko, Tatiana & Ma, Mingye, 2019. "Information choice in a social learning experiment," Games and Economic Behavior, Elsevier, vol. 118(C), pages 295-315.
    10. Christopher Roth & Sonja Settele & Johannes Wohlfart, 2022. "Risk Exposure and Acquisition of Macroeconomic Information," American Economic Review: Insights, American Economic Association, vol. 4(1), pages 34-53, March.
    11. Pëllumb Reshidi & Alessandro Lizzeri & Leeat Yariv & Jimmy Chan & Wing Suen, 2021. "Individual and Collective Information Acquisition: An Experimental Study," CESifo Working Paper Series 9468, CESifo.
    12. Salvatore Nunnari & Giovanni Montari, 2019. "Audi Alteram Partem: An Experiment on Selective Exposure to Information," Working Papers 650, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.
    13. Romain Gauriot & Lionel Page & John Wooders, 2016. "Nash at Wimbledon: Evidence from Half a Million Serves," QuBE Working Papers 046, QUT Business School.
    14. Daniel Chen & Tobias J. Moskowitz & Kelly Shue, 2016. "Decision-Making under the Gambler's Fallacy: Evidence from Asylum Judges, Loan Officers, and Baseball Umpires," NBER Working Papers 22026, National Bureau of Economic Research, Inc.
    15. Matthew Gentzkow & Jesse M. Shapiro, 2006. "Media Bias and Reputation," Journal of Political Economy, University of Chicago Press, vol. 114(2), pages 280-316, April.
    16. Gary Charness & Ryan Oprea & Sevgi Yuksel, 2021. "How do People Choose Between Biased Information Sources? Evidence from a Laboratory Experiment," Journal of the European Economic Association, European Economic Association, vol. 19(3), pages 1656-1691.
    17. Duffy, John & Hopkins, Ed & Kornienko, Tatiana, 2021. "Lone wolf or herd animal? Information choice and learning from others," European Economic Review, Elsevier, vol. 134(C).
    18. Ananda Ganguly & Joshua Tasoff, 2017. "Fantasy and Dread: The Demand for Information and the Consumption Utility of the Future," Management Science, INFORMS, vol. 63(12), pages 4037-4060, December.
    19. Nielsen, Kirby, 2020. "Preferences for the resolution of uncertainty and the timing of information," Journal of Economic Theory, Elsevier, vol. 189(C).
    20. Matthew Rabin, 2002. "Inference by Believers in the Law of Small Numbers," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 117(3), pages 775-816.
    21. Daniel L. Chen & Tobias J. Moskowitz & Kelly Shue, 2016. "Decision Making Under the Gambler’s Fallacy: Evidence from Asylum Judges, Loan Officers, and Baseball Umpires," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 131(3), pages 1181-1242.
    22. Ignacio Esponda & Emanuel Vespa, 2024. "Contingent Thinking and the Sure-Thing Principle: Revisiting Classic Anomalies in the Laboratory," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 91(5), pages 2806-2831.
    23. Florian Zimmermann, 2015. "Clumped or Piecewise? Evidence on Preferences for Information," Management Science, INFORMS, vol. 61(4), pages 740-753, April.
    24. Yusufcan Masatlioglu & Yeşim Orhun & Collin Raymond, 2023. "Intrinsic Information Preferences and Skewness," American Economic Review, American Economic Association, vol. 113(10), pages 2615-2644, October.
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    More about this item

    JEL classification:

    • D90 - Microeconomics - - Micro-Based Behavioral Economics - - - General
    • D91 - Microeconomics - - Micro-Based Behavioral Economics - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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