This paper examines the relationship between star power and box office revenues using box office data from nine countries and a continuous measure of star power based on the number of visits to a star’s web page on IMDB, the most popular web site for movie-related information. The degree of star power is computed for the top star, top three stars, and the director for the films in our sample. The results indicate that replacing an average star with a top star would increase revenues by an average of $16,618,570, while replacing three average stars with three top stars would increase revenues by an average of $64,410,381.
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Prag and Casavant (1994, p. 220) is an exception. They “use their knowledge of films and movie stars” to construct a list of actors/actresses with star power. In addition to a dummy variable indicating the presence of at least one established star, they employ an alternative variable that equals 0 in the absence of a star, .5 for a rising or falling star, 1 for a single established star, and 2 for more than one established star.
Cieply (2010) documents the growing role on ensemble casts in recent films.
Schuker (2010) discusses the growing importance of foreign box office revenues in determining casting decisions, what types of films are made, etc.
These data were no longer available on Variety.com after 2005.
Variey reports the box office revenues in terms of U.S. Dollars; all box office receipts were converted to constant dollars using the U.S. Consumer Price Index.
Film budgets are reported in U.S. dollars; we convert into constant dollars by dividing by the U.S. Consumer price Index.
Eliashberg and Shugan (1997) provide a summary of the role of critics in the motion picture industry and find that critics have their greatest impact on box office reviews several weeks after the film has been released.
For example, see The Economist (2000).
Orlando Bloom’s score is for the period 2002–2005. Prior to appearing in The Lord of the Rings and Black Hawk Down in December of 2001, his average STARmeter rankings for 45,719, 1,535, and 1,176 for 1999, 2000, and 2001, respectively.
Income is measured as GDP PPP (Purchasing Power Parity) dollars (in 1,000s) per capita, and then converted to real terms using the U.S. CPI. The population variable is also normalized to a value of 100 in the first year.
Although the model employs a panel data set it is not possible to include a time trend with the INCOME and POPULATION variables because of perfect multicollinearity.
The model was estimated using the suest routine in Stata, release 11. The standard errors were derived using the Huber/White/sandwich approach that adjusts for within-cluster correlation. See Rogers (1993) for a discussion of the estimation of the standard errors.
See Holson (2005) for a discussion of the impact of DVDs and DVRs on movie attendance.
Ackman, D. (2003). Hollywood’s star power failure, Forbes June 19.
Ainslie, A., Dreze, X., & Zufryden, F. (2005). Modeling movie lifecycles and market share. Marketing Science, 24(Summer), 508–517.
Albert, S. (1998). Movie stars and the distribution of financially successful films in the motion picture industry. Journal of Cultural Economics, 22(December), 249–270.
Austin, B. (1989). Immediate seating: A look at movie audiences. Belmont, CA: Wadsworth.
Bagella, M., & Becchetti, L. (1999). The Determinants of motion picture box office performance: Evidence from movies produced in Italy. Journal of Cultural Economics, 23(November), 237–256.
Bart, P. (2007). Does star power equal box office power? Variety, October 19.
Basuroy, S., Chatterjee, S., & Ravid, A. (2003). How critical are critical reviews? The box office effects of film critics, star power, and budgets. Journal of Marketing, 67(October), 103–117.
Bing, J. (2002). Actors savor star bucks. Variety, April 1.
Cieply, M. (2010). Hollywood’s new formula: Films crammed with stars. The New York Times, August 11, 2010, p. c1.
Collins, A., Hand, C., & Snell, M. (2002). What makes a blockbuster? Economic analysis of film success in the United Kingdom. Managerial and Decision Economics, 23(September), 343–354.
Desai, K., & Basuroy, S. (2005). Interactive influence of genre familiarity, star power, and critics’ reviews in the cultural goods industry: The case of motion pictures. Psychology and Marketing, 22(March), 203–223.
DeVany, A., & Walls, D. (1999). Uncertainty in the movie industry: Does star power reduce the terror of the box office? Journal of Cultural Economics, 23(November), 285–318.
Eliashberg, E., & Shugan, S. (1997). Film critics: Influencers or predictors? Journal of Marketing, 61(April), 68–78.
Entertainment Weekly (2006). http://www.ew.com/ew/article/0.1191047.00.html. Accessed 09 March 2009.
Faulkner, R., & Anderson, A. (1987). Short-term projects and emergent careers: Evidence from hollywood. American Journal of Sociology, 92(January), 879–909.
Holbrook, M. B. (1999). Popular appeal versus expert judgments of motion pictures. Journal of Consumer Research, 26(September), 144–155.
Holson, L. M. (2003). Summer movies: why hollywood loves to repeat itself. The New York Times, May 11.
Holson, L. M. (2005). With popcorn, DVDs, and TiVo, moviegoers are staying home. The New York Times, May 27, 2005.
Litman, B. (1983). Predicting success of theatrical movies: An empirical study. Journal of Popular Culture, 16(Spring), 159–175.
Litman, B., & Ahn, H. (1998). Predicting financial success of motion pictures. In B. Litman (Ed.), The motion picture mega-industry. Needham Heights, MA: Allyn & Bacon.
Litman, B., & Kohl, L. (1989). Predicting financial success of motion pictures: The 80’s experience. Journal of Media Economics, 2(Fall), 35–50.
McNary, D. (2007). Sequels dominate international box offices, Variety, July 6.
Mervish, D. (2011). The Hathaway effect: How Anne gives warren buffet a rise. Huffington Post, http://www.huffingtonpost.com/dan-mirvish/the-hathaway-effect-how-a_b_830041.html. Accessed March 1, 2011.
Neelamegham, R., & Chintagunta, P. (1999). A Bayesian model to forecast new product performance in domestic and international markets. Marketing Science, 18(2), 115–136.
Pomerantz, D. (2007). Ultimate star payback. http://www.forbes.com/2007/08/03/celebrities-hollywood-movies-biz-cz_dp_0806starpayback.html. Accessed 09 March 2009.
Prag, J., & Casavant, J. (1994). An empirical study of the determinants of revenues and marketing expenditures in the motion picture industry. Journal of Cultural Economics, 18(September), 217–235.
Ravid, A. (1999). Information, blockbusters, and stars: A study of the film industry. Journal of Business, 72(October), 463–492.
Rogers, W. H. (1993). Regression standard errors in clustered samples. Stata Technical Bulletin, 13, 19–23.
Sawhney, M., & Eliashberg, J. (1996). A parsimonious model for forecasting gross box-office revenues of motion pictures. Marketing Science, 15(Spring), 113–131.
Schuker, L. E. (2010). Plot change: Foreign forces transform hollywood films. The Wall Street Journal B1.
Simmons, J. (1994). A “thumbs up” pulls in the audience. Wall Street Journal B1.
Sochay, S. (1994). Predicting the performance of motion pictures. Journal of Media Economics, 7(4), 1–20.
The Economist (2000). Sneak preview: Nothing excites the movie industry more than the annual Oscar awards. February 10.
Wallace, T., Seigerman, A., & Holbrook, M. (1993). The role of actors and actresses in the success of films: How much is a movie star worth? Journal of Cultural Economics, 17(1), 1–27.
We are indebted to an anonymous referee and Andreas Waldkirch for very helpful comments that substantially improved the paper and to the Douglas Chair Fund for financial assistance.
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Nelson, R.A., Glotfelty, R. Movie stars and box office revenues: an empirical analysis. J Cult Econ 36, 141–166 (2012). https://doi.org/10.1007/s10824-012-9159-5
- Motion picture industry
- Box office revenue
- Movie stars