Accounting for latent classes in movie box office modeling
This paper addresses the issue of unobserved heterogeneity in film characteristics influence on box-office. We argue that the analysis of pooled samples, most common among researchers, does not shed light on underlying segmentations and leads to significantly different estimates obtained by researchers running similar regressions for movie success modeling. For instance, it may be expected that a restrictive MPAA rating is a box office poison for a family comedy, while it insignificantly influences an action movie‟s revenues. Using a finite mixture model we extract two latent groups, the differences between which can be explained in part by the movie genre, the source, the creative type and the production method. Based on this result, the authors recommend developing separate movie success models for different segments, rather than adopting an approach, that was commonly used in previous research, when one explanatory or predictive model is developed for the whole sample of movies.
|Date of creation:||10 Dec 2010|
|Contact details of provider:|| Postal: Ludwigstraße 33, D-80539 Munich, Germany|
Web page: https://mpra.ub.uni-muenchen.de
More information through EDIRC
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- W. D. Walls & A. DeVany, "undated". "Big budgets, big openings, and legs: Analysis of the blockbuster strategy," Working Papers 2014-57, Department of Economics, University of Calgary, revised 23 Sep 2014.
- Jonathan J. Morduch & Hall S. Stern, 1995.
"Using Mixture Models to Detect Sex Bias in Health Outcomes in Bangladesh,"
Harvard Institute of Economic Research Working Papers
1728, Harvard - Institute of Economic Research.
- Morduch, Jonathan J. & Stern, Hal S., 1997. "Using mixture models to detect sex bias in health outcomes in Bangladesh," Journal of Econometrics, Elsevier, vol. 77(1), pages 259-276, March.
- Morduch, J. & Stern, H.S., 1995. "Using Mixture Models to Detect Sex Bias in Health Outcomes in Bangladesh," Papers 513, Harvard - Institute for International Development.
- W. D. Walls, 2005.
"Modelling heavy tails and skewness in film returns,"
Applied Financial Economics,
Taylor & Francis Journals, vol. 15(17), pages 1181-1188.
- Mohanbir S. Sawhney & Jehoshua Eliashberg, 1996. "A Parsimonious Model for Forecasting Gross Box-Office Revenues of Motion Pictures," Marketing Science, INFORMS, vol. 15(2), pages 113-131.
When requesting a correction, please mention this item's handle: RePEc:pra:mprapa:27644. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Joachim Winter)
If references are entirely missing, you can add them using this form.