IDEAS home Printed from https://ideas.repec.org/a/inm/ormnsc/v61y2015i7p1704-1721.html
   My bibliography  Save this article

Counterfactual Decomposition of Movie Star Effects with Star Selection

Author

Listed:
  • Angela (Xia) Liu

    (School of Economics and Management, Tsinghua University, Beijing 100084, People's Republic of China)

  • Tridib Mazumdar

    (Whitman School of Management, Syracuse University, Syracuse, New York 13244)

  • Bo Li

    (School of Economics and Management, Tsinghua University, Beijing 100084, People's Republic of China)

Abstract

We investigate the effects of a movie star on the movie's opening week theater allocations and box office revenue. Because the pairing of a star and a movie involves a bilateral matching process between the studio and the star, the star (hence the nonstar) movie samples are nonrandom and the star variable is potentially endogenous. To assess the star as well as movie characteristics effects, we utilize a switching model to account for endogenous assignment of stars and nonstars into respective movie samples. In addition to controlling for selection biases, the endogenous switching model generates managerially relevant insights into the factors that influence a star's assignment to a movie. Additionally, because the star and nonstar movie characteristics (e.g., movie budget, distribution, genre, etc.) are often systematically different, we counterfactually estimate the theater allocations and revenues that nonstars (stars) would have generated had they acted in movies endowed with the same characteristics as the star (nonstar) movies. The decomposition analysis, conducted at different quantiles of theater and revenue distributions, shows that the presence of a star has a much stronger effect on theater allocations than the movie characteristics have. However, the revenue difference is entirely contributed by the differences in the characteristics of the star and nonstar movies. Thus, the star effects on revenue come indirectly through the theater allocations as well as from the characteristics of the movies in which they participate. This paper was accepted by Pradeep Chintagunta, marketing.

Suggested Citation

  • 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.
    • Handle: RePEc:inm:ormnsc:v:61:y:2015:i:7:p:1704-1721
    DOI: 10.1287/mnsc.2014.1923
    as

    Download full text from publisher

    File URL: http://dx.doi.org/10.1287/mnsc.2014.1923
    Download Restriction: no
    File URL: https://libkey.io/10.1287/mnsc.2014.1923?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Anita Elberse & Jehoshua Eliashberg, 2003. "Demand and Supply Dynamics for Sequentially Released Products in International Markets: The Case of Motion Pictures," Marketing Science, INFORMS, vol. 22(3), pages 329-354.
    2. W. D. Walls, 2005. "Modelling heavy tails and skewness in film returns," Applied Financial Economics, Taylor & Francis Journals, vol. 15(17), pages 1181-1188.
    3. Ravid, S Abraham, 1999. "Information, Blockbusters, and Stars: A Study of the Film Industry," The Journal of Business, University of Chicago Press, vol. 72(4), pages 463-492, October.
    4. Jehoshua Eliashberg & Anita Elberse & Mark A.A.M. Leenders, 2006. "The Motion Picture Industry: Critical Issues in Practice, Current Research, and New Research Directions," Marketing Science, INFORMS, vol. 25(6), pages 638-661, 11-12.
    5. Karniouchina, Ekaterina V., 2011. "Impact of star and movie buzz on motion picture distribution and box office revenue," International Journal of Research in Marketing, Elsevier, vol. 28(1), pages 62-74.
    6. Adler, Moshe, 1985. "Stardom and Talent," American Economic Review, American Economic Association, vol. 75(1), pages 208-212, March.
    7. Thorsten Hennig-Thurau & Mark Houston & Shrihari Sridhar, 2006. "Can good marketing carry a bad product? Evidence from the motion picture industry," Marketing Letters, Springer, vol. 17(3), pages 205-219, July.
    8. Ramya Neelamegham & Pradeep Chintagunta, 1999. "A Bayesian Model to Forecast New Product Performance in Domestic and International Markets," Marketing Science, INFORMS, vol. 18(2), pages 115-136.
    9. Oaxaca, Ronald, 1973. "Male-Female Wage Differentials in Urban Labor Markets," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 14(3), pages 693-709, October.
    10. Christopher Bollinger & James P. Ziliak & Kenneth R. Troske, 2011. "Down from the Mountain: Skill Upgrading and Wages in Appalachia," Journal of Labor Economics, University of Chicago Press, vol. 29(4), pages 819-857.
    11. Alan S. Blinder, 1973. "Wage Discrimination: Reduced Form and Structural Estimates," Journal of Human Resources, University of Wisconsin Press, vol. 8(4), pages 436-455.
    12. Liran Einav, 2007. "Seasonality in the U.S. motion picture industry," RAND Journal of Economics, RAND Corporation, vol. 38(1), pages 127-145, March.
    13. Steven Albert, 1998. "Movie Stars and the Distribution of Financially Successful Films in the Motion Picture Industry," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 22(4), pages 249-270, December.
    14. José Mata & José A. F. Machado, 2005. "Counterfactual decomposition of changes in wage distributions using quantile regression," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 20(4), pages 445-465.
    15. Lee, Lung-Fei, 1978. "Unionism and Wage Rates: A Simultaneous Equations Model with Qualitative and Limited Dependent Variables," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 19(2), pages 415-433, June.
    16. Moshe Buchinsky, 1998. "The dynamics of changes in the female wage distribution in the USA: a quantile regression approach," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 13(1), pages 1-30.
    17. W. D. Walls, 2009. "Robust Analysis of Movie Earnings," Journal of Media Economics, Taylor & Francis Journals, vol. 22(1), pages 20-35.
    18. Wiji Arulampalam & Alison L. Booth & Mark L. Bryan, 2007. "Is There a Glass Ceiling over Europe? Exploring the Gender Pay Gap across the Wage Distribution," ILR Review, Cornell University, ILR School, vol. 60(2), pages 163-186, January.
    19. 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.
    20. Koenker, Roger W & Bassett, Gilbert, Jr, 1978. "Regression Quantiles," Econometrica, Econometric Society, vol. 46(1), pages 33-50, January.
    21. Axel Heitmueller, 2006. "Public-private sector pay differentials in a devolved Scotland," Journal of Applied Economics, Universidad del CEMA, vol. 9, pages 295-323, November.
    22. Melly, Blaise, 2005. "Decomposition of differences in distribution using quantile regression," Labour Economics, Elsevier, vol. 12(4), pages 577-590, August.
    23. Amit M. Joshi & Dominique M. Hanssens, 2009. "Movie Advertising and the Stock Market Valuation of Studios: A Case of “Great Expectations?”," Marketing Science, INFORMS, vol. 28(2), pages 239-250, 03-04.
    24. Heckman, James, 2013. "Sample selection bias as a specification error," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 31(3), pages 129-137.
    25. Victor Chernozhukov & Christian Hansen, 2005. "An IV Model of Quantile Treatment Effects," Econometrica, Econometric Society, vol. 73(1), pages 245-261, January.
    26. James Albrecht & Anders Bjorklund & Susan Vroman, 2003. "Is There a Glass Ceiling in Sweden?," Journal of Labor Economics, University of Chicago Press, vol. 21(1), pages 145-177, January.
    27. Gyourko, Joseph & Tracy, Joseph, 1988. "An Analysis of Public- and Private-Sector Wages Allowing for Endogenous Choices of Both Government and Union Status," Journal of Labor Economics, University of Chicago Press, vol. 6(2), pages 229-253, April.
    28. Lee, Sokbae, 2007. "Endogeneity in quantile regression models: A control function approach," Journal of Econometrics, Elsevier, vol. 141(2), pages 1131-1158, December.
    29. Klein, Roger W & Spady, Richard H, 1993. "An Efficient Semiparametric Estimator for Binary Response Models," Econometrica, Econometric Society, vol. 61(2), pages 387-421, March.
    30. MacDonald, Glenn M, 1988. "The Economics of Rising Stars," American Economic Review, American Economic Association, vol. 78(1), pages 155-166, March.
    31. Arthur De Vany & W. Walls, 1999. "Uncertainty in the Movie Industry: Does Star Power Reduce the Terror of the Box Office?," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 23(4), pages 285-318, November.
    32. Wagner Kamakura & Suman Basuroy & Peter Boatwright, 2006. "Is silence golden? An inquiry into the meaning of silence in professional product evaluations," Quantitative Marketing and Economics (QME), Springer, vol. 4(2), pages 119-141, June.
    33. Rosen, Sherwin, 1981. "The Economics of Superstars," American Economic Review, American Economic Association, vol. 71(5), pages 845-858, December.
    34. Chernozhukov, Victor & Hansen, Christian, 2006. "Instrumental quantile regression inference for structural and treatment effect models," Journal of Econometrics, Elsevier, vol. 132(2), pages 491-525, June.
    35. Pradeep K. Chintagunta & Shyam Gopinath & Sriram Venkataraman, 2010. "The Effects of Online User Reviews on Movie Box Office Performance: Accounting for Sequential Rollout and Aggregation Across Local Markets," Marketing Science, INFORMS, vol. 29(5), pages 944-957, 09-10.
    36. Axel Heitmueller, 2006. "Public-Private Sector Pay Differentials in a Devolved Scotland," Journal of Applied Economics, Taylor & Francis Journals, vol. 9(2), pages 295-323, November.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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).
    2. Brianna JeeWon Paulich & V. Kumar, 2021. "Relating entertainment features in screenplays to movie performance: an empirical investigation," Journal of the Academy of Marketing Science, Springer, vol. 49(6), pages 1222-1242, November.
    3. Shijie Lu & Xin (Shane) Wang & Neil Bendle, 2020. "Does Piracy Create Online Word of Mouth? An Empirical Analysis in the Movie Industry," Management Science, INFORMS, vol. 66(5), pages 2140-2162, May.
    4. Fei Peng & Lili Kang & Sajid Anwar & Xue Li, 2019. "Star power and box office revenues: evidence from China," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 43(2), pages 247-278, June.
    5. Wei, Liyuan & Yang, Yupin, 2022. "An empirical investigation of director selection in movie preproduction: A two-sided matching approach," International Journal of Research in Marketing, Elsevier, vol. 39(3), pages 888-906.
    6. 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.
    7. Qian Li & Yuanyuan Tang & Wei Xu & Mingming Wang, 2023. "Variance does matter in affecting the box office: a multi-aspect investigation," Electronic Commerce Research, Springer, vol. 23(2), pages 659-679, June.
    8. Jun Pang & Angela Xia Liu & Peter N. Golder, 2022. "Critics’ conformity to consumers in movie evaluation," Journal of the Academy of Marketing Science, Springer, vol. 50(4), pages 864-887, July.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Hofmann, Julian & Clement, Michel & Völckner, Franziska & Hennig-Thurau, Thorsten, 2017. "Empirical generalizations on the impact of stars on the economic success of movies," International Journal of Research in Marketing, Elsevier, vol. 34(2), pages 442-461.
    2. Fei Peng & Lili Kang & Sajid Anwar & Xue Li, 2019. "Star power and box office revenues: evidence from China," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 43(2), pages 247-278, June.
    3. Jelena Lausev, 2014. "WHAT HAS 20 YEARS OF PUBLIC–PRIVATE PAY GAP LITERATURE TOLD US? EASTERN EUROPEAN TRANSITIONING vs. DEVELOPED ECONOMIES," Journal of Economic Surveys, Wiley Blackwell, vol. 28(3), pages 516-550, July.
    4. Kaya Ezgi, 2021. "Gender wage gap across the distribution: What is the role of within- and between-firm effects?," IZA Journal of Development and Migration, Sciendo & Forschungsinstitut zur Zukunft der Arbeit GmbH (IZA), vol. 12(1), pages 1-49, January.
    5. 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.
    6. 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.
    7. Martinez-Sanchis, Elena & Mora, Juan & Kandemir, Ilker, 2012. "Counterfactual distributions of wages via quantile regression with endogeneity," Computational Statistics & Data Analysis, Elsevier, vol. 56(11), pages 3212-3229.
    8. 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.
    9. Amanda S. King & John T. King & Michael Reksulak, 2017. "Signaling for access to high-demand markets: evidence from the US motion picture industry," Journal of Cultural Economics, Springer;The Association for Cultural Economics International, vol. 41(4), pages 441-465, November.
    10. Thomas Grandner & Dieter Gstach, 2012. "Decomposing wage discrimination in Germany and Austria with counterfactual densities," Department of Economics Working Papers wuwp145, Vienna University of Economics and Business, Department of Economics.
    11. 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.
    12. 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.
    13. Michael Lewis & Yeujun Yoon, 2018. "An Empirical Examination of the Development and Impact of Star Power in Major League Baseball," Journal of Sports Economics, , vol. 19(2), pages 155-187, February.
    14. Töpfer, Marina, 2017. "Detailed RIF decomposition with selection: The gender pay gap in Italy," Hohenheim Discussion Papers in Business, Economics and Social Sciences 26-2017, University of Hohenheim, Faculty of Business, Economics and Social Sciences.
    15. Gaenssle Sophia & Budzinski Oliver & Astakhova Daria, 2018. "Conquering the Box Office: Factors Influencing Success of International Movies in Russia," Review of Network Economics, De Gruyter, vol. 17(4), pages 245-266, December.
    16. Chzhen, Yekaterina & Mumford, Karen, 2011. "Gender gaps across the earnings distribution for full-time employees in Britain: Allowing for sample selection," Labour Economics, Elsevier, vol. 18(6), pages 837-844.
    17. Collischon Matthias, 2019. "Is There a Glass Ceiling over Germany?," German Economic Review, De Gruyter, vol. 20(4), pages 329-359, December.
    18. Sonja C. Kassenboehmer & Mathias G. Sinning, 2014. "Distributional Changes in the Gender Wage Gap," ILR Review, Cornell University, ILR School, vol. 67(2), pages 335-361, April.
    19. Arceo-Gómez, Eva O. & Campos-Vázquez, Raymundo M., 2014. "Evolución de la brecha salarial de género en México," El Trimestre Económico, Fondo de Cultura Económica, vol. 0(323), pages .619-653, julio-sep.
    20. Azam, Mehtabul, 2012. "Changes in Wage Structure in Urban India, 1983–2004: A Quantile Regression Decomposition," World Development, Elsevier, vol. 40(6), pages 1135-1150.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:inm:ormnsc:v:61:y:2015:i:7:p:1704-1721. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Chris Asher (email available below). General contact details of provider: https://edirc.repec.org/data/inforea.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.