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Modeling movie success when "nobody knows anything": Conditional stable distribution analysis of film returns

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  • W David Walls

Abstract

In this paper we apply a recently-developed statistical model that explicitly accounts for the extreme uncertainty surrounding film returns. The conditional distribution of box-office returns is analyzed using the stable distribution regression model. The regression coefficients in this model represent what is known about the correlates of film success while at the same time permitting the variance of film success at the box office to be infinite. The empirical analysis shows that the conditional distribution of film returns has infinite variance, and this invalidates statistical inferences from the often-applied least-squares regression model. The estimates of the stable regression confirm some earlier results on the statistics of the movie business and the analysis demonstrates how to model box-office success in the movie business where ``nobody knows anything''

Suggested Citation

  • W David Walls, 2004. "Modeling movie success when "nobody knows anything": Conditional stable distribution analysis of film returns," Econometric Society 2004 Far Eastern Meetings 409, Econometric Society.
  • Handle: RePEc:ecm:feam04:409
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    References listed on IDEAS

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    1. Victor Ginsburgh, 2001. "Economics of arts and culture," ULB Institutional Repository 2013/1869, ULB -- Universite Libre de Bruxelles.
    2. De Vany, Arthur S. & Walls, W. David, 2004. "Motion picture profit, the stable Paretian hypothesis, and the curse of the superstar," Journal of Economic Dynamics and Control, Elsevier, vol. 28(6), pages 1035-1057, March.
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    9. Benoit Mandelbrot, 2015. "The Variation of Certain Speculative Prices," World Scientific Book Chapters,in: THE WORLD SCIENTIFIC HANDBOOK OF FUTURES MARKETS, chapter 3, pages 39-78 World Scientific Publishing Co. Pte. Ltd..
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    Cited by:

    1. Jordi McKenzie, 2010. "How do theatrical box office revenues affect DVD retail sales? Australian empirical evidence," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 34(3), pages 159-179, August.
    2. Ana Suárez-Vázquez, 2011. "Critic power or star power? The influence of hallmarks of quality of motion pictures: an experimental approach," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 35(2), pages 119-135, May.
    3. Sumiko Asai, 2011. "Demand analysis of hit music in Japan," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 35(2), pages 101-117, May.
    4. repec:spr:orspec:v:40:y:2018:i:1:d:10.1007_s00291-017-0492-0 is not listed on IDEAS
    5. Don M. Chance & Eric Hillebrand & Jimmy E. Hilliard, 2008. "Pricing an Option on Revenue from an Innovation: An Application to Movie Box Office Revenue," Management Science, INFORMS, vol. 54(5), pages 1015-1028, May.
    6. Daniel Kaimann, 2014. "Combining Qualitative Comparative Analysis and Shapley Value Decomposition: A Novel Approach for Modeling Complex Causal Structures in Dynamic Markets," Working Papers Dissertations 12, Paderborn University, Faculty of Business Administration and Economics.
    7. Sudip Bhattacharjee & Ram D. Gopal & Kaveepan Lertwachara & James R. Marsden & Rahul Telang, 2007. "The Effect of Digital Sharing Technologies on Music Markets: A Survival Analysis of Albums on Ranking Charts," Management Science, INFORMS, vol. 53(9), pages 1359-1374, September.
    8. Ana Suárez-Vázquez & José Quevedo, 2015. "Analyzing superstars’ power using support vector machines," Empirical Economics, Springer, vol. 49(4), pages 1521-1542, December.
    9. Juan Prieto-Rodriguez & Fernanda Gutierrez-Navratil & Victoria Ateca-Amestoy, 2015. "Theatre allocation as a distributor’s strategic variable over movie runs," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 39(1), pages 65-83, February.
    10. Jordi McKenzie, 2010. "Do 'African American' films perform better or worse at the box office? An empirical analysis of motion picture revenues and profits," Applied Economics Letters, Taylor & Francis Journals, vol. 17(16), pages 1559-1564.
    11. Michael Pokorny & John Sedgwick, 2010. "Profitability trends in Hollywood, 1929 to 1999: somebody must know something -super-1," Economic History Review, Economic History Society, vol. 63(1), pages 56-84, February.
    12. McKenzie, Jordi, 2013. "Predicting box office with and without markets: Do internet users know anything?," Information Economics and Policy, Elsevier, vol. 25(2), pages 70-80.
    13. Brinja Meiseberg & Thomas Ehrmann, 2013. "Diversity in teams and the success of cultural products," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 37(1), pages 61-86, February.
    14. Chien-Ping Chen, 2009. "A Puzzle or a Choice: Uniform Pricing for Motion Pictures at the Box," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 37(1), pages 73-85, March.
    15. Arthur Vany & W. Walls, 2007. "Estimating the Effects of Movie Piracy on Box-office Revenue," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 30(4), pages 291-301, June.
    16. Jordi McKenzie, 2009. "Revealed word-of-mouth demand and adaptive supply: survival of motion pictures at the Australian box office," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 33(4), pages 279-299, November.
    17. repec:eee:ijrema:v:34:y:2017:i:2:p:442-461 is not listed on IDEAS
    18. Kaimann, Daniel & Pannicke, Julia, 2015. "Movie success in a genre specific contest: Evidence from the US film industry," Ilmenau Economics Discussion Papers 98, Ilmenau University of Technology, Institute of Economics.
    19. Starling D. Hunter III & Ravi Chinta & Susan Smith & Awais Shamim & Alya Bawazir, 2016. "Moneyball for TV: A Model for Forecasting the Audience of New Dramatic Television Series," Studies in Media and Communication, Redfame publishing, vol. 4(2), pages 13-22, December.
    20. Liran Einav & S. Ravid, 2009. "Stock market response to changes in movies’ opening dates," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 33(4), pages 311-319, November.
    21. Frederick Derrick & Nancy Williams & Charles Scott, 2014. "A two-stage proxy variable approach to estimating movie box office receipts," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 38(2), pages 173-189, May.
    22. W. David Walls, 2004. "Revenues, Profitability, and Returns: Clinical Analysis of the Market for Mobster Films," International Journal of Business and Economics, College of Business and College of Finance, Feng Chia University, Taichung, Taiwan, vol. 3(2), pages 93-106, August.
    23. John Sedgwick & Michael Pokorny, 2010. "Consumers as risk takers: Evidence from the film industry during the 1930s," Business History, Taylor & Francis Journals, vol. 52(1), pages 74-99.
    24. Allègre Hadida, 2010. "Commercial success and artistic recognition of motion picture projects," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 34(1), pages 45-80, February.

    More about this item

    Keywords

    motion picture industry; economics of the movie business; film success; stable Paretian model; symmetric stable regression analysis;

    JEL classification:

    • L82 - Industrial Organization - - Industry Studies: Services - - - Entertainment; Media
    • Z1 - Other Special Topics - - Cultural Economics

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