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Celebrity star power: Do age and gender effects influence box office performance?

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  • Julianne Treme
  • Lee A. Craig

Abstract

Celebrity media exposure is an increasingly strong source of actor popularity and is a viable star power variable that focuses on the impact of celebrity, not acting talent. Using People to calculate an actor's popularity, we analyse how the gender and age of a movie's lead actors affect box office success using quantile regression. We find that male celebrity media exposure can positively impact the success of a movie, whereas female celebrity exposure tends to decrease box office revenues. The results also suggest that although it may be harder for older actresses to land a lead role, it is actually the older male actors who lack the ability to carry a movie. The results highlight that a linear regression may not be the optimal solution to assess the relationship between star power and box office revenues.

Suggested Citation

  • Julianne Treme & Lee A. Craig, 2013. "Celebrity star power: Do age and gender effects influence box office performance?," Applied Economics Letters, Taylor & Francis Journals, vol. 20(5), pages 440-445, March.
  • Handle: RePEc:taf:apeclt:v:20:y:2013:i:5:p:440-445
    DOI: 10.1080/13504851.2012.709594
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    References listed on IDEAS

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    1. Stephanie Brewer & Jason Kelley & James Jozefowicz, 2009. "A blueprint for success in the US film industry," Applied Economics, Taylor & Francis Journals, vol. 41(5), pages 589-606.
    2. 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.
    3. Julianne Treme, 2010. "Effects of Celebrity Media Exposure on Box-Office Performance," Journal of Media Economics, Taylor & Francis Journals, vol. 23(1), pages 5-16.
    4. Chiou, Lesley & Lopez, Mary, 2010. "The reality of reality television: Does reality TV influence local crime rates?," Economics Letters, Elsevier, vol. 108(3), pages 330-333, September.
    5. Nelson, Randy A, et al, 2001. "What's an Oscar Worth?," Economic Inquiry, Western Economic Association International, vol. 39(1), pages 1-16, January.
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    Cited by:

    1. Vishal Narayan & Vrinda Kadiyali, 2016. "Repeated Interactions and Improved Outcomes: An Empirical Analysis of Movie Production in the United States," Management Science, INFORMS, vol. 62(2), pages 591-607, February.
    2. 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.
    3. 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.
    4. Sangjae Lee & Joon Yeon Choeh, 2020. "Movie Production Efficiency Moderating between Online Word-of-Mouth and Subsequent Box Office Revenue," Sustainability, MDPI, vol. 12(16), pages 1-18, August.
    5. Kyuhan Lee & Jinsoo Park & Iljoo Kim & Youngseok Choi, 2018. "Predicting movie success with machine learning techniques: ways to improve accuracy," Information Systems Frontiers, Springer, vol. 20(3), pages 577-588, June.
    6. Kang, Lili & Peng, Fei & Anwar, Sajid, 2022. "All that glitters is not gold: Do movie quality and contents influence box-office revenues in China?," Journal of Policy Modeling, Elsevier, vol. 44(2), pages 492-510.
    7. Julianne Treme & Zoe VanDerPloeg, 2014. "The Twitter Effect: Social Media Usage as a Contributor to Movie Success," Economics Bulletin, AccessEcon, vol. 34(2), pages 793-809.
    8. Fan, Liu & Zhang, Xiaoping & Rai, Laxmisha, 2021. "When should star power and eWOM be responsible for the box office performance? - An empirical study based on signaling theory," Journal of Retailing and Consumer Services, Elsevier, vol. 62(C).
    9. Kyuhan Lee & Jinsoo Park & Iljoo Kim & Youngseok Choi, 0. "Predicting movie success with machine learning techniques: ways to improve accuracy," Information Systems Frontiers, Springer, vol. 0, pages 1-12.

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