IDEAS home Printed from https://ideas.repec.org/p/clb/wpaper/201102.html

Media Exposure And Individual Choices: Evidence From Lotto Players

Author

Listed:
  • Maria De Paola

  • Vincenzo Scoppa

    (Dipartimento di Economia e Statistica, Università della Calabria)

Abstract

To what extent individual choices are influenced by media exposure? We try to provide evidence on this issue considering how the sales of lotto tickets are determined by the size of the top prize (the jackpot) compared to the amount of attention that media devote to the game. We use data on the Italian SuperEnalotto (2003- 2010) and estimate tickets sales in relation to the jackpot size and to several measures of lotto media coverage. To take into account that media attention may be affected by the amount of tickets sold we instrument media coverage with the availability of other newsworthy material (sport events and disasters). It emerges that media attention to the game is inversely related to the availability of other news. Two-Stage-Least Squares Estimations show that, given the jackpot size, players spend more on lotto when media attention to the game is higher.

Suggested Citation

  • Maria De Paola & Vincenzo Scoppa, 2011. "Media Exposure And Individual Choices: Evidence From Lotto Players," Working Papers 201102, Università della Calabria, Dipartimento di Economia, Statistica e Finanza "Giovanni Anania" - DESF.
    • Handle: RePEc:clb:wpaper:201102
    as

    Download full text from publisher

    File URL: http://www.ecostat.unical.it/RePEc/WorkingPapers/WP02_2011.pdf
    File Function: First version, 2011-02
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Paul C. Tetlock, 2007. "Giving Content to Investor Sentiment: The Role of Media in the Stock Market," Journal of Finance, American Finance Association, vol. 62(3), pages 1139-1168, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Müller, Karsten, 2020. "German forecasters' narratives: How informative are German business cycle forecast reports?," Working Papers 23, German Research Foundation's Priority Programme 1859 "Experience and Expectation. Historical Foundations of Economic Behaviour", Humboldt University Berlin.
    2. Gao, Xin & Xu, Weidong & Li, Donghui, 2025. "Media coverage and managerial investment learning from stock markets: International evidence," Research in International Business and Finance, Elsevier, vol. 76(C).
    3. Yan Luo & Linying Zhou, 2020. "Textual tone in corporate financial disclosures: a survey of the literature," International Journal of Disclosure and Governance, Palgrave Macmillan, vol. 17(2), pages 101-110, September.
    4. Jiao Ji & Oleksandr Talavera & Shuxing Yin, 2018. "The Hidden Information Content: Evidence from the Tone of Independent Director Reports," Working Papers 2018-28, Swansea University, School of Management.
    5. Jang, Junkyu, 2025. "Selective news selection model for explainable stock prediction via cross-attention integration," Finance Research Letters, Elsevier, vol. 85(PD).
    6. Lixiang Wang & Wendi Hou & Yupei Liu, 2023. "How do co‐shareholding networks affect negative media coverage? Evidence from China," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(4), pages 4221-4249, December.
    7. Kamaladdin Fataliyev & Aneesh Chivukula & Mukesh Prasad & Wei Liu, 2021. "Stock Market Analysis with Text Data: A Review," Papers 2106.12985, arXiv.org, revised Jul 2021.
    8. Keval Amin & Erica Harris, 2022. "The Effect of Investor Sentiment on Nonprofit Donations," Journal of Business Ethics, Springer, vol. 175(2), pages 427-450, January.
    9. King, Timothy & Srivastav, Abhishek & Williams, Jonathan, 2016. "What's in an education? Implications of CEO education for bank performance," Journal of Corporate Finance, Elsevier, vol. 37(C), pages 287-308.
    10. Kirtac, Kemal & Germano, Guido, 2024. "Sentiment trading with large language models," Finance Research Letters, Elsevier, vol. 62(PB).
    11. Yilun Zhang & Zheng Tang & Hexiang Sun & Yufeng Shi, 2026. "Deep g-Pricing for CSI 300 Index Options with Volatility Trajectories and Market Sentiment," Papers 2601.18804, arXiv.org.
    12. Sapkota, Niranjan, 2022. "News-based sentiment and bitcoin volatility," International Review of Financial Analysis, Elsevier, vol. 82(C).
    13. Eryka Probierz & Adam Galuszka & Katarzyna Klimczak & Karol Jedrasiak & Tomasz Wisniewski & Tomasz Dzida, 2021. "Financial Sentiment on Twitter's Community and it's Connection to Polish Stock Market Movements in Context of Behavior Modelling," European Research Studies Journal, European Research Studies Journal, vol. 0(4 - Part ), pages 56-65.
    14. Onur Özdemir & Selin Yalçıntaş, 2026. "Herd investing and market inefficiency in forex markets over the COVID-19 outbreak: the multifractality analysis," SN Business & Economics, Springer, vol. 6(3), pages 1-35, March.
    15. Hadhri, Sinda & Younus, Mehak & Naeem, Muhammad Abubakr & Yarovaya, Larisa, 2025. "Listening to the Market: Music sentiment and cryptocurrency returns," Journal of International Money and Finance, Elsevier, vol. 157(C).
    16. Chen, Cathy Yi-Hsuan & Fengler, Matthias R. & Härdle, Wolfgang Karl & Liu, Yanchu, 2022. "Media-expressed tone, option characteristics, and stock return predictability," Journal of Economic Dynamics and Control, Elsevier, vol. 134(C).
    17. Baur, Dirk G. & Smales, Lee A., 2020. "Hedging geopolitical risk with precious metals," Journal of Banking & Finance, Elsevier, vol. 117(C).
    18. Gric, Zuzana & Ehrenbergerova, Dominika & Hodula, Martin, 2022. "The power of sentiment: Irrational beliefs of households and consumer loan dynamics," Journal of Financial Stability, Elsevier, vol. 59(C).
    19. Goldman, Eitan & Martel, Jordan & Schneemeier, Jan, 2022. "A theory of financial media," Journal of Financial Economics, Elsevier, vol. 145(1), pages 239-258.
    20. Montone, Maurizio & Zhu, Yuhao & Zwinkels, Remco C.J., 2024. "Managerial sentiment and employment," Journal of Behavioral and Experimental Finance, Elsevier, vol. 43(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;
    ;

    JEL classification:

    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness
    • D1 - Microeconomics - - Household Behavior
    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:clb:wpaper:201102. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Giovanni Dodero (email available below). General contact details of provider: https://edirc.repec.org/data/decalit.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.