Notes
Quoted from http://www.imax.com.au/visitor_info/.
Henceforth, we use screen size and screen width interchangeably.
This ignores costs associated with provision of higher quality and higher variety.
One critique of this approach is that the predicted number of showings is the same for all movies within a chain-location, such that a fixed effect at the chain-location level would remove all variation in this instrument. In the presence of such a fixed effect, an interaction between the instrument and movie characteristics indexed by jt would remove such a concern and predict different numbers of showings across movies within a chain-location.
We do not include the nesting parameter in the before estimation as without instrumenting for the nest, this parameter - which is highly correlated with the dependant variable - explains most of the variation in the data.
References
Ainslie, A., Xavier, D., & Zufryden, F. (2005). Modeling movie life cycles and market share. Marketing Science, 24(3), 508–517.
Berry, S., Levinsohn, J., & Pakes, A. (1995). Automobile prices in market equilibrium. Econometrica, 63, 841–890.
Bohlmann, J.D., Golder, P. N., & Mitra, D. (2002). Deconstructing the pioneer’s advantage: Examining vintage effects and consumer valuations of quality and variety. Management Science, 48(9), 1175–1195.
Davis, P. (2006). Spatial competition in retail markets: movie theaters. RAND Journal of Economics, 37(4), 964–982.
Draganska, M., Mazzeo, M., & Seim, K. (2009). Beyond plain vanilla: modeling joint pricing and product assortment choices. Quantitative Marketing and Economics, 7(2), 105–146.
Einav, L. (2007). Seasonality in the U.S. motion picture industry. RAND Journal of Economics, 38(1), 127–145.
Elberse, A., & Eliashberg, J. (2003). Demand and supply dynamics for sequentially released products in international markets: The case of motion pictures. Marketing Science, 22(3), 329–354.
Eliashberg, J., Elberse, A., & Leenders, M. (2006). The motion picture industry: critical issues in practice, current research, and new research directions. Marketing Science, 25(6), 638–661.
Gil, R. (2013). The interplay of formal and relational contracts: evidence from movies. The Journal of Law, Economics and Organization, 29(3), 681–710.
Gil, R., & Hartmann, W.R. (2009). Empirical analysis of metering price discrimination: evidence from concession sales at movie theaters. Marketing Science, 28(6), 1046–1062.
Goettler, R.L., & Leslie, P. (2005). Cofinancing to manage risk in the motion picture industry. Journal of Economics and Management Strategy, 14(2), 231–26.
Mazzeo, M. (2003). Competition and service quality in the u.s. airline industry. Review of Industrial Organization, 22(4), 275–296.
Mortimer, J. (2007). Price discrimiation, copyright law, and technological innovation: evidence from the introduction of DVDs. The Quarterly Journal of Economics, 122(3), 1307–1350.
Mortimer, J. (2008). Vertical contracts in the video rental industry. The Review of Economic Studies, 75(1), 165–199.
Nevo, A. (2000). A practitioner’s guide to estimation of random-coef cients logit models of demand. Journal of Economics & Management Strategy, 9(4), 513–548.
Orhun, Y., Chintagunta, P., & Venkataraman, S. (2014). Impact of competition on product decisions: Movie choices of exhibitors, working paper, ross school of business.
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Appendix A: first-stage regression
Appendix A: first-stage regression
Table 6 presents the first-stage regression results for the main variables of interest - price, ln(Shows), ln(Screen Width) and the nesting parameter - specific to Specification S3. The number of screens in a chain was the instrument for shows. The significant coefficients on screensXhhi indicates that screens and shows are correlated. The overall effect at the average demographic is positive indicating that a chain with more screens (and a higher hhi) has more shows. The instrument for screen size - hhi - is such that it takes on large values when a chain has more variation in screen sizes across its auditoria and also when there are more screens. The overall coefficient on hhi and hhi 2 at the average demographic is significantly negative, indicating that such chains are more likely to screen movies in auditoria with smaller screens. The instrument for the nesting parameter - 1/(No. competing movies) - takes on larger values when there are fewer competing movies playing in the market. A positive coefficient indicates that the inside-nest share of the movie is higher when there are fewer competing movies playing. The average price of other movies playing in a chain that week is positively correlated with the price of the focal movie.
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Rao, A., Hartmann, W.R. Quality vs. variety: Trading larger screens for more shows in the era of digital cinema. Quant Mark Econ 13, 117–134 (2015). https://doi.org/10.1007/s11129-015-9156-z
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DOI: https://doi.org/10.1007/s11129-015-9156-z