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Two information aggregation mechanisms for predicting the opening weekend box office revenues of films: Boxoffice Prophecy and Guess of Guesses

Author

Listed:
  • David Court

    (AFTRS)

  • Benjamin Gillen

    (Caltech)

  • Jordi McKenzie

    (Macquarie University)

  • Charles R. Plott

    (Caltech)

Abstract

Field tests were conducted on two new information aggregation mechanism designs. The mechanisms were designed to collect information held as intuitions about opening weekend box office revenues for movies in Australia. The principles on which the mechanisms operate and their capacity to collect information are explored. A pari-mutuel mechanism produces a predicted probability distribution over box office amounts that is, with the exception of very small films, indistinguishable from the actual revenues. The second mechanism is based on guessing the guesses of others and when applied under conditions where incentives for accuracy are unavailable still performs well against data.

Suggested Citation

  • David Court & Benjamin Gillen & Jordi McKenzie & Charles R. Plott, 2018. "Two information aggregation mechanisms for predicting the opening weekend box office revenues of films: Boxoffice Prophecy and Guess of Guesses," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 65(1), pages 25-54, January.
    • Handle: RePEc:spr:joecth:v:65:y:2018:i:1:d:10.1007_s00199-017-1036-1
    DOI: 10.1007/s00199-017-1036-1
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    Cited by:

    1. Bronwyn Coate & Robert Hoffmann, 2022. "The behavioural economics of culture," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 46(1), pages 3-26, March.
    2. Tom Wilkening & Marcellin Martinie & Piers D. L. Howe, 2022. "Hidden Experts in the Crowd: Using Meta-Predictions to Leverage Expertise in Single-Question Prediction Problems," Management Science, INFORMS, vol. 68(1), pages 487-508, January.
    3. 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.
    4. Sonja Radas & Dražen Prelec, 2021. "Predicted preference conjoint analysis," PLOS ONE, Public Library of Science, vol. 16(8), pages 1-16, August.
    5. Sonja Radas & Drazen Prelec, 2019. "Whose data can we trust: How meta-predictions can be used to uncover credible respondents in survey data," PLOS ONE, Public Library of Science, vol. 14(12), pages 1-16, December.

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    More about this item

    Keywords

    Information aggregation; Mechanism design; Experiment; Prediction market; Field test; Box office;
    All these keywords.

    JEL classification:

    • D01 - Microeconomics - - General - - - Microeconomic Behavior: Underlying Principles
    • D02 - Microeconomics - - General - - - Institutions: Design, Formation, Operations, and Impact
    • D03 - Microeconomics - - General - - - Behavioral Microeconomics: Underlying Principles
    • D47 - Microeconomics - - Market Structure, Pricing, and Design - - - Market Design
    • C9 - Mathematical and Quantitative Methods - - Design of Experiments
    • C53 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Forecasting and Prediction Models; Simulation Methods
    • C70 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - General
    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G17 - Financial Economics - - General Financial Markets - - - Financial Forecasting and Simulation

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