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The pricing of soft and hard information: economic lessons from screenplay sales

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  • William Goetzmann
  • S. Ravid
  • Ronald Sverdlove

Abstract

This paper uses a unique data set on screenplay sales to learn how the information content of a sales pitch affects sale prices. This is one of the few studies that analyze “soft information” outside the banking industry. We find that “soft information” proxies, such as the descriptive complexity of a pitch, depress prices, in particular for less experienced writers, supporting the common industry view that high concept (short and simple) screenplays sell better. “Hard information” (measurable experience) variables are priced as well. We also find that large studios shun “soft information”, whereas small companies handle it better, as predicted by most theories. In the last part of the paper, we find that, surprisingly, buyers seem to be able to forecast the eventual success of a project based upon the purchased script, paying more for screenplays which will eventually culminate in more successful movies. In other words, perhaps “somebody knows something”. Copyright Springer Science+Business Media New York 2013

Suggested Citation

  • William Goetzmann & S. Ravid & Ronald Sverdlove, 2013. "The pricing of soft and hard information: economic lessons from screenplay sales," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 37(2), pages 271-307, May.
    • Handle: RePEc:kap:jculte:v:37:y:2013:i:2:p:271-307
    DOI: 10.1007/s10824-012-9183-5
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    Cited by:

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    2. Pamela Adams & Roberto Fontana & Astrid Marinoni, 2018. "More “team” than “fame”: spin-off success in the US television sitcom industry," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 27(6), pages 957-974.
    3. José María Liberti & Mitchell A. Petersen, 2018. "Information: Hard and Soft," NBER Working Papers 25075, National Bureau of Economic Research, Inc.
    4. Lee Yoong Hon & Ruth Lim Sheau Yen, 2018. "At the Movies: Some Stylized Facts on Investment Returns and Consumption Patterns," International Journal of Business and Economics, School of Management Development, Feng Chia University, Taichung, Taiwan, vol. 17(2), pages 123-142, September.
    5. 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.
    6. Hong Luo & Jeffrey Macher & Michael Wahlen, 2021. "Judgment Aggregation in Creative Production: Evidence from the Movie Industry," Management Science, INFORMS, vol. 67(10), pages 6358-6377, October.
    7. Darlene Chisholm & Víctor Fernández-Blanco & S. Abraham Ravid & W. David Walls, 2015. "Economics of motion pictures: the state of the art," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 39(1), pages 1-13, February.
    8. José María Liberti & Mitchell A Petersen, 2019. "Information: Hard and Soft," The Review of Corporate Finance Studies, Society for Financial Studies, vol. 8(1), pages 1-41.
    9. Lily Shen & Stephen L. Ross, 2019. "Information Value of Property Description: A Machine Learning Approach," Working papers 2019-20, University of Connecticut, Department of Economics, revised Sep 2020.
    10. Mun, Mak Kit & Chong, Choo Wei, 2018. "Forecasting Movie Demand Using Total and Split Exponential Smoothing," Jurnal Ekonomi Malaysia, Faculty of Economics and Business, Universiti Kebangsaan Malaysia, vol. 52(2), pages 81-94.

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