IDEAS home Printed from https://ideas.repec.org/a/taf/apeclt/v29y2022i13p1187-1192.html
   My bibliography  Save this article

Is Rotten Tomatoes killing the movie industry? A regression discontinuity approach

Author

Listed:
  • Marislei Nishijima
  • Mauro Rodrigues
  • Thaís Luiza Donega Souza

Abstract

We study the effect of expert reviews on consumer choice, focusing on the movie industry. Specifically, we estimate the impact of a popular movie review aggregator – Rotten Tomatoes (RT) – on box office revenue, using a sample of 1,239 movies widely-released in the U.S. between 1999 and 2019. RT’s rating system allows us to use regression discontinuity, thus avoiding problems associated with omitted unobservable characteristics of movies (such as quality and commercial appeal). We do not find evidence that RT ratings affect box office performance.

Suggested Citation

  • Marislei Nishijima & Mauro Rodrigues & Thaís Luiza Donega Souza, 2022. "Is Rotten Tomatoes killing the movie industry? A regression discontinuity approach," Applied Economics Letters, Taylor & Francis Journals, vol. 29(13), pages 1187-1192, July.
    • Handle: RePEc:taf:apeclt:v:29:y:2022:i:13:p:1187-1192
    DOI: 10.1080/13504851.2021.1918324
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/13504851.2021.1918324
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/13504851.2021.1918324?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to look for a different version below or search for a different version of it.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Suman Basuroy & S. Abraham Ravid & Richard T. Gretz & B. J. Allen, 2020. "Is everybody an expert? An investigation into the impact of professional versus user reviews on movie revenues," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 44(1), pages 57-96, March.
    2. Alexander L. Brown & Colin F. Camerer & Dan Lovallo, 2012. "To Review or Not to Review? Limited Strategic Thinking at the Movie Box Office," American Economic Journal: Microeconomics, American Economic Association, vol. 4(2), pages 1-26, May.
    3. David A. Reinstein & Christopher M. Snyder, 2005. "The Influence Of Expert Reviews On Consumer Demand For Experience Goods: A Case Study Of Movie Critics," Journal of Industrial Economics, Wiley Blackwell, vol. 53(1), pages 27-51, March.
    4. Victor Ginsburgh, 2003. "Awards, Success and Aesthetic Quality in the Arts," Journal of Economic Perspectives, American Economic Association, vol. 17(2), pages 99-111, Spring.
    5. Christer Thrane, 2018. "Do expert reviews affect the decision to see motion pictures in movie theatres? An experimental approach," Applied Economics, Taylor & Francis Journals, vol. 50(28), pages 3066-3075, 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. Jordi McKenzie, 2023. "The economics of movies (revisited): A survey of recent literature," Journal of Economic Surveys, Wiley Blackwell, vol. 37(2), pages 480-525, April.
    2. Michela Ponzo & Vincenzo Scoppa, 2015. "Experts’ awards and economic success: evidence from an Italian literary prize," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 39(4), pages 341-367, November.
    3. Thaís L. D. Souza & Marislei Nishijima & Ana C. P. Fava, 2019. "Do consumer and expert reviews affect the length of time a film is kept on screens in the USA?," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 43(1), pages 145-171, March.
    4. Ethan Mollick & Ramana Nanda, 2016. "Wisdom or Madness? Comparing Crowds with Expert Evaluation in Funding the Arts," Management Science, INFORMS, vol. 62(6), pages 1533-1553, June.
    5. Stefano Dellavigna & Johannes Hermle, 2017. "Does Conflict of Interest Lead to Biased Coverage? Evidence from Movie Reviews," The Review of Economic Studies, Review of Economic Studies Ltd, vol. 84(4), pages 1510-1550.
    6. Martina Dattilo & Fabio Padovano & Yvon Rocaboy, 2023. "More is worse: the evolution of quality of the UNESCO World Heritage List and its determinants," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 47(1), pages 71-96, March.
    7. John Ashworth & Bruno Heyndels & Kristien Werck, 2010. "Expert judgements and the demand for novels in Flanders," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 34(3), pages 197-218, August.
    8. Kamal Bookwala & Caleb Gallemore & Joaquín Gómez‐Miñambres, 2022. "The influence of food recommendations: Evidence from a randomized field experiment," Economic Inquiry, Western Economic Association International, vol. 60(4), pages 1898-1910, October.
    9. Dubois, Pierre & Nauges, Céline, 2010. "Identifying the effect of unobserved quality and expert reviews in the pricing of experience goods: Empirical application on Bordeaux wine," International Journal of Industrial Organization, Elsevier, vol. 28(3), pages 205-212, May.
    10. Stevenson, Regan & Allen, Jared & Wang, Tang, 2022. "Failed but validated? The effect of market validation on persistence and performance after a crowdfunding failure," Journal of Business Venturing, Elsevier, vol. 37(2).
    11. Nicolas Lagios & Pierre-Guillaume Méon, 2021. "Experts, Information, Reviews, and Coordination: Evidence on How Literary Prizes Affect Sales," Working Papers CEB 21-011, ULB -- Universite Libre de Bruxelles.
    12. Francesco Angelini & Massimiliano Castellani, 2019. "Cultural and economic value: a critical review," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 43(2), pages 173-188, June.
    13. Jun Pang & Angela Xia Liu & Peter N. Golder, 2022. "Critics’ conformity to consumers in movie evaluation," Journal of the Academy of Marketing Science, Springer, vol. 50(4), pages 864-887, July.
    14. Brown, Alexander L. & Meer, Jonathan & Williams, J. Forrest, 2017. "Social distance and quality ratings in charity choice," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 66(C), pages 9-15.
    15. Wallentin, Erik, 2016. "Demand for cinema and diverging tastes of critics and audiences," Journal of Retailing and Consumer Services, Elsevier, vol. 33(C), pages 72-81.
    16. Francesco Angelini & Massimiliano Castellani, 2018. "Private pricing in the art market," Economics Bulletin, AccessEcon, vol. 38(4), pages 2371-2378.
    17. Dieter Pennerstorfer & Christoph Weiss & Andreas Huber, 2019. "Experts, Reputation and Umbrella Effects: Empirical Evidence from Wine Prices," Economics working papers 2019-08, Department of Economics, Johannes Kepler University Linz, Austria.
    18. Villas-Boas, Sofia B, 2020. "Reduced Form Evidence on Belief Updating Under Asymmetric Information," Department of Agricultural & Resource Economics, UC Berkeley, Working Paper Series qt08c456vk, Department of Agricultural & Resource Economics, UC Berkeley.
    19. GINSBURGH, Victor & NOURY, Abdul, 2005. "Cultural voting : The Eurovision Song Contest," LIDAM Discussion Papers CORE 2005006, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    20. C F Elliott & R Simmons, 2007. "Determinants of UK box office success: the impact of quality signals," Working Papers 584026, Lancaster University Management School, Economics Department.

    More about this item

    JEL classification:

    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • D9 - Microeconomics - - Micro-Based Behavioral Economics
    • C21 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Cross-Sectional Models; Spatial Models; Treatment Effect Models
    • C39 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Other

    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:taf:apeclt:v:29:y:2022:i:13:p:1187-1192. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/RAEL20 .

    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.