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Modeling heavy tails and skewness in film returns

Author

Listed:
  • W. D. Walls

    (University of Calgary)

Abstract

The average of box-office revenue is dominated by extreme outcomes, with most films earning little and most revenues flowing to a few blockbusters. In this paper the skewness and heavy tails of film returns are formally modelled using skew-Normal and skew-t distributions. Logarithmic skew-Normal and skew-t models of the distribution of box-office revenue are fitted conditional on star actors and directors, budget, release pattern, genre, rating, and year of release. The estimates show significantly more skewness and heavier tails than the log-Normal distribution. It is also found that a wide theatrical release has a much smaller impact on box-office revenue when heavy tails and skewness are explicitly modelled.

Suggested Citation

  • W. D. Walls, "undated". "Modeling heavy tails and skewness in film returns," Working Papers 2014-48, Department of Economics, University of Calgary, revised 23 Sep 2014.
    • Handle: RePEc:clg:wpaper:2014-48
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    Cited by:

    1. Allègre L. Hadida & Joseph Lampel & W. David Walls & Amit Joshi, 2021. "Hollywood studio filmmaking in the age of Netflix: a tale of two institutional logics," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 45(2), pages 213-238, June.
    2. Andrew M. Jones & James Lomas & Nigel Rice, 2015. "Healthcare Cost Regressions: Going Beyond the Mean to Estimate the Full Distribution," Health Economics, John Wiley & Sons, Ltd., vol. 24(9), pages 1192-1212, September.
    3. 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.
    4. Michael S. Smith & Shaun P. Vahey, 2016. "Asymmetric Forecast Densities for U.S. Macroeconomic Variables from a Gaussian Copula Model of Cross-Sectional and Serial Dependence," Journal of Business & Economic Statistics, Taylor & Francis Journals, vol. 34(3), pages 416-434, July.
    5. 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.
    6. Ivan Pitt, 2010. "Superstar effects on royalty income in a performing rights organization," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 34(3), pages 219-236, August.
    7. repec:lan:wpaper:1089 is not listed on IDEAS
    8. 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.
    9. Angela (Xia) Liu & Tridib Mazumdar & Bo Li, 2015. "Counterfactual Decomposition of Movie Star Effects with Star Selection," Management Science, INFORMS, vol. 61(7), pages 1704-1721, July.
    10. Ronny Behrens & Natasha Zhang Foutz & Michael Franklin & Jannis Funk & Fernanda Gutierrez-Navratil & Julian Hofmann & Ulrike Leibfried, 2021. "Leveraging analytics to produce compelling and profitable film content," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 45(2), pages 171-211, June.
    11. 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.
    12. 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.
    13. Caroline Elliott & Rob Simmons, 2008. "Determinants of UK Box Office Success: The Impact of Quality Signals," Review of Industrial Organization, Springer;The Industrial Organization Society, vol. 33(2), pages 93-111, September.
    14. W. Walls, 2010. "Superstars and heavy tails in recorded entertainment: empirical analysis of the market for DVDs," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 34(4), pages 261-279, November.
    15. 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.
    16. repec:lan:wpaper:1111 is not listed on IDEAS
    17. Sayantan Ghosh Dastidar & Caroline Elliott, 2020. "The Indian film industry in a changing international market," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 44(1), pages 97-116, March.
    18. Blomkvist, Katarina & Kappen, Philip & Zander, Ivo, 2014. "Superstar inventors—Towards a people-centric perspective on the geography of technological renewal in the multinational corporation," Research Policy, Elsevier, vol. 43(4), pages 669-682.
    19. Antipov, Evgeny & Pokryshevskaya, Elena, 2010. "Accounting for latent classes in movie box office modeling," MPRA Paper 27644, University Library of Munich, Germany.
    20. repec:lan:wpaper:1176 is not listed on IDEAS
    21. Moez Hababou & Nawel Amrouche & Kamel Jedidi, 2016. "Measuring Economic Efficiency in the Motion Picture Industry: a Data Envelopment Analysis Approach," Customer Needs and Solutions, Springer;Institute for Sustainable Innovation and Growth (iSIG), vol. 3(3), pages 144-158, December.
    22. repec:lan:wpaper:1090 is not listed on IDEAS
    23. Natalia Gmerek, 2015. "The determinants of Polish movies’ box office performance in Poland," Journal of Marketing and Consumer Behaviour in Emerging Markets, University of Warsaw, Faculty of Management, vol. 1(1), pages 15-35.
    24. Vlasios Voudouris & Robert Gilchrist & Robert Rigby & John Sedgwick & Dimitrios Stasinopoulos, 2012. "Modelling skewness and kurtosis with the BCPE density in GAMLSS," Journal of Applied Statistics, Taylor & Francis Journals, vol. 39(6), pages 1279-1293, November.
    25. Jordi Mckenzie, 2008. "Bayesian Information Transmission and Stable Distributions: Motion Picture Revenues at the Australian Box Office," The Economic Record, The Economic Society of Australia, vol. 84(266), pages 338-353, September.

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