The Oscars’ Commercial Impact: Some Evidence from International Data Fernanda Gutierrez-Navratil Universidad Pública de Navarra PRELIMINARY DRAFT PLEASE DO NOT QUOTE Abstract: This paper aims to measure the value, in terms of their impact on weekly box-office revenues, of the most important Oscar nominations and awards (best picture, best director, best actor/actress, best supporting actor/actress and best original and adapted screenplay). This impact has seldom been measured controlling for the unobserved heterogeneity of movies, which is crucial since awards and nominations are usually allocated to high quality films. Also, we distinguish between the effect of a nomination before and after the Oscars are awarded. Thus, we test whether the effects change after the Oscar ceremony, since the audience could pay more attention to nominated films after that. Besides, we check whether it really matters which film win the Oscar. Then, we focused on the most important category, the best film award. We study the decision taken by the Academy in 2009 to raise the number of nominations. We test whether this decision has affected the commercial impact of nominations, because some members of the Academy have been campaigning for a return to five best film nominations. Finally, we analysed whether the commercial impact of an Oscar or a nomination in this category differs between the domestic and foreign markets, due to the particular characteristics of each market. We use weekly data on revenues from the USA and the main European markets and exploit the differences in the release schedules of these countries to disentangle the impact of awards and quality on movies demand. The panel data structure with three dimensions: movie, week and country, allow us to control not only for the perceived “quality” of each movie in each country, but also for the temporal decay pattern of the weekly box office revenues by film and by country. Key words: Panel data, Movies Performance, Box-office revenues, Oscar nominations and awards 1 1. Introduction Producers and distributors try to take as much commercial advantage as possible from the “free” promotion implied by Oscar nominations and awards. Those films that have a chance to be nominated are intentionally released in the United States at the end of the year in order to be eligible and also to be on screen when nominations are announced and Oscars are awarded. However, when a film is no longer on screen and is nominated, it is very likely that it will be re-released in movie theatres to capitalize on the nomination. Clearly, the expected impact of a nomination or award will depend on the Oscar category (Best Picture, Best Director, Best Actor/Actress, Best Supporting Actor/Actress, and Best Screenplay). The Best Picture award is expected to have the largest effect but it is also important to know the magnitude and the relative importance of all the other categories. Additionally, the expected impact of nominations and awards could differ between the domestic market and foreign markets (due to specific characteristics of each country). This impact could also change when there is a redesign of awards rules, for instance, in 2009 when the Academy decided to raise the number of nominations in the best picture category. With this information in mind, producers would be able to take better decisions regarding budgets (allocation of resources), especially for films that are expected to compete in these nominations and awards. Distributors could decide about the release schedules of these films in domestic and foreign markets. For the Academy, this information could also be useful for an eventual redesign of the awards rules to generate higher value for the industry. 2 Accordingly, this paper attempts to measure the value of the most important Oscar nominations and awards in terms of their impact on box office revenues. This impact has seldom been measured using panel data techniques that allow controlling for differences in movies’ marketability and quality via the estimation of individual effects, which are inherent to this market. Controlling for individual effects is crucial since nominations and awards are not randomly allocated and usually go to higher quality movies. 1 Starting with Litman (1983), this topic has been the subject of a host of papers using regression models to determine what is important in explaining box office results. Most authors find that nominations and awards (which are separated by a couple of weeks) have a significant effect on revenues (see, for instance, Hirschman and Pieros 1985; Dodds and Holbrook 1988; Ravid 1999; Simonoff and Sparrow 2000). Most of these papers are, however, unable to separate the effect of the quality of a movie from the award effect since they use box office results in one country only, 2,3 which makes it difficult to control for the heterogeneity of movies. 1 See however Ginsburgh and Weyers (2014) who, focusing on the period 1929–1995, show that many nominated are of better quality than those that received the Oscar for Best Movie. Authors looked at fifteen 100 Top Movie Lists and use as a quality indicator the number of lists in which a movie appears. 2 With exception of Craig et al. (2005), who consider several countries but are not interested in the effect of awards. There are also examples of papers that do not take advantage of the panel structure of their data set. For instance, Elberse and Eliashberg (2003) “opt for a model that does not capture unobserved individual specific effects” and they run the regression separately for each country in their sample. 3 United States: Chen et al. (2013), Deuchert et al. (2005), Ginsburgh (2003), Nelson et al. (2001), East Asia: Lee (2009). 3 We use a sample that consists of the weekly box office revenues (starting with the week of release, and including the following 40 weeks if the run is long enough) of the 150 top box office films released each year in each country (the United States, the United Kingdom, France, Germany and Spain) from 2002 to 2015. We use the three dimensions of this panel structure (movie, week and country) to control not only for the perceived “quality” of each movie in each country, but also for the temporal decay pattern of the weekly box office revenues by film and by country. This makes it possible to separate the effect of the quality of a movie from the effect of awards on demand. Also, we are able to measure the effect of awards from the week in which a movie was nominated or awarded and to distinguish between the impact of nominations before and after the Oscar ceremony. Since the audience could pay more attention to nominated films after the Oscars ceremony, given its popularity. Besides, it also allows us to check whether it really matters which film win the Oscar. We also exploit the differences in the release dates of movies in these countries to better evaluate the impact of nominations and awards. This framework permits a comparison of revenues before and after the announcement of nominations and awards and an assessment of the impact at particular points in time by matching running weeks in different countries, some before and others after the nominations. The impact of nominations on box office revenues may also change over time. For instance, if the nomination is revealed at an early stage of the commercial run of the movie, one can expect the (weekly) impact to be greater. To take this into account, we estimate a weekly box- office revenue model specified in semi-log form. In the next section we describe the sample and database used. Section 3 discusses the empirical specifications and the estimation method. We present the principal results in 4 Section 4. In section 5 and 6, we check the robustness of the results and present additional results respectively. Finally, the conclusions and management implications are presented in Section 7. 2. Sample and database The sample we use for our empirical analysis comprises the 150 top box-office films released each year in each country (the United States, the United Kingdom, France, Germany and Spain) from January 1st, 2002 to December 31st, 2015. We have collected the information provided by A. C. Nielsen EDI on movies released in the United States and the four largest European motion pictures markets (United Kingdom, France, Germany and Spain). For each movie and country, our dataset includes information on titles, weekly and cumulative box-office revenue, number of theatres on each week of exhibition, distributors, official release dates and certain film characteristics (identification of sequels, MPAA rating, etc.). In the case of France we have weekly and cumulative attendance instead of box-office revenues. We use the information provided by the Box Office Mojo website (boxofficemojo.com) relating to the movies nominated and awarded with Oscars in the different categories. We also use information about the different movie titles in each country provided by the Internet Movie Database web site (imdb.com), to match movies across countries. Thus, we obtain a panel data structure with three dimensions: movie, week and country. We use the three dimensions of this dataset to better assess the impact of Oscar nominations and awards on box-office revenues. 5 We have removed from the sample, those movie-week combinations observed only in one country, in order to achieve a better identification of temporal patterns. This implies that movies released in only one country were removed from the sample. Also, we withdrew all movies with short runs (one month or shorter runs), as we are interested in the impact of nominations and awards and there is a 5-6 week gap between both announcements.