creativity and project value in the film industry

8/12/2019 Creativity and Project Value in the Film Industry

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Creativity and project value in the film

industry

Jialan WangMassachusetts Institute of [email protected]

January 15, 2007

Abstract

As creative workers become an increasingly important part of theeconomy, the need to understand their impact on the behavior and

organization of firms grows ever more urgent. In particular, manag-ing creative human capital requires a balance between giving workerscreative freedom and channelling their creativity toward work ger-mane to the firms goals. This project aims to explore this trade-off by examining the relationship between art and commerce in thefilm industry. Using data for films released between 1980 and 2005,I provide evidence that artistic films are more likely to have charac-teristics negatively correlated with financial performance; in addition,they perform worse than commercial films even after controlling forthese characteristics. Yet, artistic films continue to be produced, andall of the major studios have specialty-film divisions devoted to pro-

ducing them. Although this behavior may ostensibly seem inefficient,I find that artistic films benefit studios by attracting valuable starswho derive utility from working on artistic films and by increasingtheir productivity. Stars are more likely to work with a studio in fu-ture films after working on an artistic film, and these subsequent filmstend to perform better than other films with similar characteristics.Thus, while artistic projects may not seem profitable when consideredin isolation, they may enhance the value of a studios film portfolio byincreasing the productivity of stars and by increasing the likelihood of

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retaining them for future films. These results suggest that in human-capital-intensive firms, project value must be evaluated with consid-eration for human-capital-driven interactions, and they also suggest apossible role for using projects as perks for creative workers.

1 Introduction

In recent years, many commentators have noted a paradigm shift in thelabor market of developed economies of from the manufacturing sector towardservice and professional occupations. As a result, the competitive advantageof countries like the U.S. increasingly relies on the the ingenuity of humancapital to drive productivity and innovation. As Luigi Zingales asserted inhis 2000 article In Search of New Foundations, this dramatic shift in thenature of firms and the workforce necessitates new approaches to corporatefinance. In this paper, I focus on a few key aspects of the new type of firm -the creativity of human capital and costs and benefits creative freedom.

Creative workers are distinguished both by the nature of their work andby the characteristics of the people who are drawn to and succeed at creative

work. Whereas workers in a manufacturing-based economy perform mainlystandardized, repetitive tasks which required little creative input, the mostvaluable employees in the new economy - whom economist Richard Floridadeemed the creative class 1 - are both highly skilled and highly specialized,and their output reflects their unique combination of skills. As Florida putsit,

... the key difference between creative workers and other work-ers lies in what they are primarily paid to do. Those in theWorking Class and the Service Class are primarily paid to ex-

ecute according to plan, while those in the Creative Class areprimarily paid to create.[Florida, 2002, p. 8]

By Floridas estimation, creative workers make about 30% of the work-force. They include core creative workers such as scientists, artists, andwriters as well as professionals such as lawyers, doctors, and executives.While creative workers are defined by the open-ended nature of their work,they also differ from other workers in the economy in other ways. In particu-lar, creative workers seem to have very different motivations than the workers

1See Florida [2002]

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of our standard economic models. One key difference is that creative workerstend to place priority on the creative satisfaction they derive from their workand are only secondarily concerned with monetary compensation 2.

Florida and others present convincing evidence that creative workers arewilling to give up substantial monetary rewards to pursue their creative in-terests 3. In a deeper sense, the drive to pursue the ideas which most inspirethem (as opposed to those which are most popular or most lucrative) is whatmakes creative workers effective at coming up with good ideas in the first

place 4.Thus, while the standard principal-agent problem of motivating workers

to exert effort may be relevant for workers who perform routine tasks, creativeworkers generally do not need incentives to contribute effort. Instead, firmswith creative workers face the challenge of chanelling their efforts towardideas which serve the firms goals, which may not correspond to their owncreative visions. However, a key distinction between creative satisfactionand other private costs and benefits 5 from which employees may deriveutility is the intrinsic link between a persons creative satisfaction and herability to generate ideas. Thus, creative freedom is related to perks which

improve a workers productivity 6

. Furthermore, while routine tasks mainlyrequire effort, creative tasks require inspiration. Although effort can often beinduced through monetary incentives, the work of generating ideas is largelybeyond the control of workers, so even if they wanted to, they may not beable to respond to these incentives. Thus, firms face many sources of conflictbetween their financial goals and the creative goals of employees.

In particular, the payoffs to granting creative freedom are unclear. Iftoo little freedom is granted, then the innovativeness of employees may suf-fer. If too much freedom is granted, employees may pursue projects withpoor financial returns. The right amount of creative freedom depends on the

correlation between employees creative objectives and the financial objec-2See Drucker [1998] and Drucker [1999] and Florida [2002, p. 86-88]3See Chapter 5 of Florida [2002] and sources cited within4See Dubner and Levitt [May 7, 2006] and Ericsson [2006], who show that the most

productive workers are not necessarily those who are most talented, but those who aremost passionate about what they do.

5These include the cost of effort, perquisites, and other non-pecuniary aspects of aworkers utility function.

6Examples from Rajan and Wulf [2006] include corporate jets that save travel timefor executives and complementary food and beverages which cut down on employee timespent away from the office.

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tives of the firm and on how much their creative ability depends on freedom.Intuitively, the optimal amount of freedom should be greater if employeestend to pursue profitable projects when given more freedom or if employeeability depends more on having creative freedom. One example of a firmwhich gives a large amount of creative freedom is Google, which has a pol-icy of allowing workers to spend 20% of their time on projects unrelated totheir primary assignments, and reportedly, some of the companys successfulcommercial ventures were developed in employees free time. This type of

policy may also provide indirect benefits by increasing the productivity ofcreative workers, and helping to recruit and retain talent.

To that workers enjoy creative freedom, projects for which they are givencontrol may act as perks for creative employees. While previous studies suchas Rajan and Wulf [2006] have explored the potentially value-enhancing roleof perks, this paper aims to go further by examining creativity as a channelthrough which perks may boost employee productivity. By nature, firms maybe better-positioned to provide employees with the chance to exercise theircreativity than employees themselves 7. Thus, the value of projects whichallow employees creative freedom must be evaluated with consideration their

role as perquisites and their impact on the value of human capital.

2 The Film Industry

The film industry presents many advantages for studying the role of creativehuman capital. Creativity is clearly central to the film production process,since each film is a unique product which has no general blueprint and re-quires the daily creative input of the cast and crew in order to be completed.The industry serves as a model of an economy in which much of firms valuedepends on human capital, but human capital is also extremely mobile, so

firms must continuously compete to attract talented workers. As ThomasMalone wrote [Malone, 2004, p. 154],

The business of making movies provides a prototype of thekind of knowledge- and creativity-intensive work that is likely tocharacterize many industries in the future

7A scientist working at a pharmaceutical firm for example, would have a hard timeexercising his bio-chemical creativity in his garage, whereas the firm he works for has allof the necessary equipment and resources to engage his creativity.

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Employee turnover is increasing especially quickly in human-capital-intensiveindustries, so studying the film industry may provide valuable insights forthe emerging economic landscape in which firms must compete to attract themost talented workers. Lastly, since all completed film projects are publiclyreleased, the film industry allows us to examine the interactions betweenfirms and creative human capital in detail .

Films are inherently risky projects, so stars are generally regarded asvaluable assets which reduce the risk and increase the expected profits of film

projects. De Vany and Walls [2002b] present evidence of the risky nature ofthe film industry: most films make very little profit and a few films each yearmake huge profits. To cope with these risks, the industry is organized intoseveral large studios 8 which generate the bulk of industry profits as well asa multitude of much smaller studios, many of which only make a few filmsbefore petering out. The highly unpredictable nature of film revenues putslarge studios at an advantage over smaller ones, as they can use their greatercapital base to reduce the risk of individual films. De Vany and Walls [1999]show that studios can also use bigger budgets, bigger openings, and otherinvestments to reduce downside revenue risk. With between 10-20 films per

year, the large studios can also mitigate the risks of individual films throughdiversification 9.

In this study, I focus on the economic role of stars. The broad consensusamong previous studies 10 is that only a handful of actors and directors (whomI will collectively term stars) have the ability to consistently improve filmperformance. Moreover, while stars do seem to improve the revenues andrisk characteristics of films, they do not seem to improve returns or addvalue beyond the rents that they capture11. In a series of papers, De Vanyand Walls examine stars with respect to the distributions of film outcomes12. They show that although stars are no guarantee of success, a few top

stars are able to increase the probability that a film will become a hit, thusreducing risk. Moreover, De Vany and Walls [1999] identify about 20 top

8There were seven major studios until the merger of MGM with Sony in 2005 reducedthe number to six.

9See Gertner [November 12, 2006]10See John et al. [2002], Ravid [1999], De Vany and Walls [1999, 2002b] and Elseberse

[2006], among others11A notable exception is John et al. [2002], who find that star directors have a positive

and significant impact on film returns.12See De Vany and Walls [2002b, 1999, 2002a]

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stars who have positive and significant impact on the probability of filmsuccess and on film profitability. Elseberse [2006] uses data from onlinemarket simulations to show that announcements of star involvement in filmsincreases expected theatrical revenues. However, she finds that stars do notincrease the valuation of movie studios, suggesting that stars capture therents that they generate.

While most of these studies have focused on relatively recent films, it wasnot always the case that stars were able to capture their full value-added.

Under the so-called star system which was in place during the early daysof Hollywood, stars were essentially long-term employees for the studios andwere obliged to work exclusively with one studio 13. However, with the demiseof the star system in the 1940s and the rise in the power of talent agencies andthe stars they represent, studios must now compete to attract these valuablestars for their projects. Nowadays, stars are essentially free agents who workfor the studios on a project-by-project basis, although longer-term contractsare also employed. Thus, the superior bargaining position of stars in thecurrent industry environment lends credence to the rent capture hypothesis.

Another salient characteristic of the film industry which makes it a good

subject for this study is that the creative workers involved in filmmakingclearly care about the artistic merit of their work as a dimension indepen-dent of their compensation and the profitability of their films. In fact, starsmay even eschew films which are too commercial and lack strong creativeimpetus, and their reluctance to star in commercial films may be one reasonfor their extraordinarily high salaries. As legendary Hollywood screenwriterWilliam Goldman puts it, movie stars, by and large, do not want to appearin commercial films (Goldman [2000, p. 193]). Stars appetite for artisticsatisfaction can be verified in several ways. To begin with, actors and direc-tors receive very little compensation on average. As reported by the Bureau

of Labor Statistics, the average member of the guilde makes less than $ 5000per year in acting fees. Many stars work for years as unknowns before theybreak into high-paying films, so unless they grossly overestimate the prob-ability of attaining stardom, we may presume that they gain some intrinsicutility from their creative work. Moreover, many stars choose to work onartistic films for much less than their market salary even when theyre ableto command multi-million dollar salaries for commercial films. A recent ex-ample is George Clooney. While he reportedly earns up to $20 million per

13Although studios sometimes leased to each other the right to use stars.

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film 14, in recent years hes done two artistic films for a fraction of his normalsalary (Oh, Brother Where Art Thou and Syriana for $500,000 each) andtwo for no pay at all (Confessions of a Dangerous Mind and Good Night,and Good Luck). The star himself sees his commercial work as a way to gainopportunities to do work he really believes in: I succeed in both worlds.I hope that selling out on Oceans Eleven is not such a bad deal. Thetrade-off is, I get to go make something uncommercial that will probablylose money15.

In an ideal world, the films which are most artistically satisfying wouldalso generate the most profits, satisfying the talent as well as studio execu-tives and shareholders. However, many commentators have noted a profoundtension between art and commerce in Hollywood, and the dichotomy is oftenframed as a choice between studio and independent films 16. While studiofilms are characterized as big-budget movies made by one of the seven ma-jor studios to earn as much profit as possible, independent films are thosemade outside the studio system. According to director Sydney Pollack, In-dependent usually meant anything that was an alternative to recipe films ormainstream films made by studios [Biskind, 2004, p. 19]). In addition to the

content they produced, independent film studios are also identified withthe creative freedom afforded to directors by studio executives; according toa former executive of United Arists Classics (one of the artistic film divisionsused in my analysis), Once the script and the director were set and it wasclear the movie could be made for the budget they wanted, then we steppedaside and let the artists do their work Biskind [2004, p. 18]). While commen-tators draw a strong conceptual distinction between studio and independentfilms, the labels as such are misnomers. Many so-called independent filmsare actually financed, produced or distributed by the large studios, often-times through subsidiaries devoted to artistic filmmaking. These specialty

divisions are explicitly targeted toward artistic films and clearly distinguishthemselves from their studio parents, often employing labels such as inde-pendent, classic to signal their specialization.

The tension between commercial and artistic films arises because of ageneral perception that independent or artistic films seldom make a profit.

14According to the Internet Movie DataBase (IMDB), he reportedly earned $20 Millioneach for Oceans Eleven and Oceans Twelve

15Thompson [July 1, 2005]16See [Goldman, 2000, p. 206-207] or McCabe [August 20, 2004]

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According to industry expert Edward Jay Epstein17, Just as Exxon, RoyalDutch Shell, and British Petroleum do not make their living from oil paint ...Hollywood studios do not make money from producing (or distributing) theoccasional art or social-commentary movie. In fact, film studios themselvessometimes represent their films as vehicles for artistic excellence with littleprofit potential. In a recent lawsuit against the makers of oscar-winning filmBrokeback Mountain, actor Randy Quaid alleged that the films producersfalsely represented it as a low-budget, art house film, with no prospect of

making any money in order to secure his participation at a reduced salary.If we view creative satisfaction as a private benefit for stars in a standardprincipal-agent framework 18, then studios would want to give control to starsonly if artistic quality were positively correlated with project value. How-ever, since artistic measures are broadly negatively correlated with financialvalue, it seems counter-intuitive that studios have set up specialized artisticsubsidiaries which cultivate reputations for giving stars creative control offilms.

The continued production of artistic films by large studios is all the morepuzzling in light of recent work by Fee [2002], who shows that due to the

agency problem between filmmakers with artistic aspirations and studio ex-ecutives with profit motives, film producers with high artistic stakes are morelikely to finance films independently. Moreover, he finds that artistic filmswhich are financed by studios perform worse than those financed indepen-dently, possibly because filmmakers exert less effort due to their reducedcontrol in studio-financed projects. The industry has long been patronizedby wealthy investors who seem more interested in the glamour and culturalimpact of artistic films 19, and the presence of these relatively financially-insensitive investors would be expected to further drive value-maximizingstudios away from artistic filmmaking 20. Thus, the presence of investors

and firms which derive private benefits from making artistic films providesfurther disencentive for profit-motivated firms to enter this market.The question of why studios make so many artistic films is closely related

to the R-rating puzzle - the tendency of studios to make too many R-ratedfilms - which has been studied by several researchers in the past. De Vany and

17Epstein [February 22, 2006]18As in Aghion and Bolton [1992], for example19A recent example is former eBay President Jeff Skoll, whose film company has recently

financed such socially pertinent films as An Inconvenient Truth and Syriana20Morton and Podolny [1998] have noted similar dynamics in the wine industry

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Walls [2002b] present some of the most prominent evidence on this puzzle,showing that film budgets, revenues, and profits display a non-Gaussian, fat-tailed distribution, and that R-rated, counterculture films have both lowerreturns and higher risk than films rated G, PG, or PG-13 films. In contrast,Ravid and Basuroy [2004] show that movies which are very violent or whichfeature sex and violence may be less risky than average films, which providessome motivation for studios to produce them despite their lower revenues.While ratings are an imperfect proxy for artistic merit, casual inspection

shows that artistic films are disproportionately rated R, so an explanationfor why studios produce artistic films would go some ways toward explainingthe R-rating puzzle.

While some may explain the preponderance of artistic films as misman-agement or irrationality on the party of Hollywood studios, it is difficult tobelieve that such irrationality can long persist in a business as lucrative andrisky as filmmaking. Indeed, the multi-national media conglomerates whichown all of the major studios are paragons of big business - not the type offirms one would imagine to engage in art for arts sake without gaining anyeconomic benefit. Thus, given that the major studios continue to play a vi-

tal role in producing artistic films, we are obliged to consider the economicjustification for these investments.

To understand why studios make artistic films, I compare film projectsalong commercial and artistic criteria. My analysis shows a clear tensionbetween artistic and commercial quality in the film industry; while commer-cially successful films tend to have low artistic quality, films with high artisticquality tend to have low commercial value. The films which are recognized forartistic merit are likely to be smaller films with small audiences and modestprofits, the most profitable films tend to be broad comedies, action adven-tures, and childrens films. In recent years, the divide between commercial

and artistic films has widened as blockbuster films have tapped into mer-chandizing opportunities, cross-promotion deals, and alternative financingschemes to which most artistic films do not have access. Thus, the differencein profitability between commercial and artistic films is even greater than itappears from examining film revenues alone.

Thus, although artistic films do not seem to generate enough profit tojustify the frequency of their production, studios seem to find it favorable toinclude them in their film portfolios. While this behavior could be interpretedas an inefficient allocation of investment, I present evidence that artistic filmscan in fact be valuable to studios who need to attract talent from a very

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small pool of top stars. Of course, the sacrifice is wasted unless stars arecompelled to continue working with a studio after it grants the star accessto an artistic film. There are two main channels through which a star maybe induced to work with a studio again after working on an artistic film.The most direct channel is through explicit multi-film contracts betweenstudios and stars. While contracts for multiple specific films are rare owingto the uncertainty of filmmaking and the difficulties of scheduling, optionsare often used whereby studios retain the right to use a star in a future

film of its choosing. However, the main channel through which stars may beinduced to repay studios for the chance to work on artistic films is throughthe relationships and social connections formed through the process of filmingthe initial artistic film. Because relationships and informal contracts areso critical in the film industry, artistic films give studios a valuable accessto stars which allows them to nurture these social connections. Artisticprojects may allow studios to form more favorable relationships with starsthan commercial projects because stars are given creative freedom and thusmay feel more goodwill to a studio than when working on a blockbuster whichsuffers creative interference from managers. While these channels generally

do not bind a star to work for a studio in the future, they may significantincrease the probability that she will. Thus, while artistic projects maynot be profit-maximizing when evaluated individually, they may enhance theoverall value of a studios film portfolio by increasing the likelihood thatpopular stars will work with the studio in the future.

3 Data

3.1 Data sources

A wealth of data exists in the public domain on many different film char-acteristics. My primary source of data is boxofficemojo.com, a popular in-ternet resource for data on film revenues which has been cited by the WallStreet Journal and the Los Angeles Times21. The database includes over6500 films released from January 1980 to June 2005, with data on domesticand international revenues, film run times, MPAA ratings, and film distri-bution companies. In addition, the database includes production budgetsestimated from news reports and trade publications. While domestic rev-

21See Lippman [June 24, 2005] and Friedman [June 6, 2006]

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enues are included for all films my sample, less than half of them have dataon production budgets. The films with production budget data are typicallylarger and more likely to be distributed by large studios, leading to potentialsampling bias. However, since I focus on the difference between artistic andcommercial films distributed large studios, this bias is mitigated. Moreover,since artistic films tend to be smaller and are less likely to have budget data,this bias works against my hypothesis that artistic films are less profitable.I obtained a monthly CPI series from Global Financial Database to adjust

all dollar values in the dataset to December 2004 dollars. For the few filmswith budget data in foreign currency, costs were converted to USD using theaverage exchange rate for the year of release before adjusting for inflation.

Revenue and budget data are merged with data from the Internet MovieDatabase (IMDB), the worlds largest film database. From the IMDB, I havegathered data on film genres, star filmographies, and Oscar nominations.While all films in my data set are released with a unique MPAA rating (orclassified as unrated), the IMDB utilizes up to eight genre categories for asingle film. Because I use Oscar nominations as a way to identify artisticallyoriented films, I focus on the eight award categories which most reflect artistic

quality: best picture, best director, best actor, best supporting actor, bestactress, best supporting actress, best original screenplay, and best adaptedscreenplay.

I use the Premier 100, an annual list compiled by Premiere magazineof the most powerful players in Hollywood, to identify the stars who havesignificant bargaining power. This list has been used to similar effect inprevious studies such as De Vany and Walls [2002b]. Because many of themost powerful players in Hollywood are not stars but agents, executives, andproducers, stars represent only a fraction of the Premier 100, leaving us witha small but focused universe of stars who are likely to convey substantial

economic value to studios. According to my hypothesis, studios are likely touse artistic films as perks mainly for the top stars, so I restrict considerationto them. Not only might less well-known talent have little leverage with thestudios, but in their quest for fame and success, they may also be more willingto put aside their artistic ambitions for the chance to star in films which reachwide audiences. The biggest stars in the industry may have enough clout tonegotiate deals with studios which allow them to pursue artistic ambitionsin addition garnering high salaries.

As one way of identifying artistic films, I used a list of all films which

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have been shown at the Sundance Film Festival22, which was founded by filmstar Robert Redford in 1985 and is the most prominent festival for artisticand independent films in the United States. By merging these data, I havebeen able to create a unique data set with which to examine the pattern ofprojects stars take on and to determine whether artistic films benefit studiosby attracting stars.

3.2 Definitions of artistic filmsI use three different definitions of artistic films: 1) films produced by artisticdivisions of large studios 2)films nominated for oscars in one of the eight ma-jor categories 3) films exhibited at the Sundance Film Festival. Commercialfilms are defined as those made by one of the seven major studios, excludingthose made by artistic subsidiaries.

Definition 1) is a somewhat parsimonious classification of artistic filmsand has the advantage of identifying filmmakers ex anteintention of makingartistically-oriented films. Within the seven major studios 23 are numerousdivisions which specialize in different types of films or represent which la-

bels carried over from previous acquisitions. In particular, some divisionsspecialize in the production and / or distribution of artistic films. Althoughthe classification of artistic subsidiaries is subjective and based on my ownjudgement, these subsidiaries have been widely acknowledged in the press tofocus on the development artistic films 24, and they employ identifying ad-jectives such as classics and independent in their names to signal theirdistinction from their studio parents. While most films falling under defini-tion 1) would be considered artistic based on casual inspection, many filmsdistributed by large studios 25 may also be considered artistic and would bemisclassified.

Using Oscar nominations to define artistic films overcomes the issue ofoverlooking artistic films made in non-artistic divisions of studios; films dis-tributed independently, through artistic subsidiaries, and through commer-cial studio divisions are all represented under this definition. Furthermore,stars derive direct benefit from Oscar nominations in addition to films artis-

22The list was obtained from the Sundance Institute via email23See Appendix A for a list of the studios and subsidiaries24See Biskind [2004] for a detailed account of the rise of artistic subsidiaries, which

confirms the artistic orientation of all of the subisidiaries I identify.25Recent examples include Adaptation and Syriana

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tic merit since nominations enhance their personas; thus, Oscar nominationsmeasure an additional dimension of private benefits which may influence stardecisions not captured by the other measures. However, this definition alsocomes with a few empirical problems. First of all, Oscar nominations identifyonly a few films per year which have ex post achieved artistic success; thechoices are highly idiosyncratic, so the probability of nomination may notcorrespond with stars expected utility from making a film. Secondly, it isdifficult to disentangle the effect of artistic merit from the promotional boost

films receive after being nominated for Oscars. One way around this is toproxy for a films artistic merit by considering previous Oscar nominationsreceived by the cast, writers, and director. A third disadvantage is that onlya few films per year are nominated for Oscars, so this method underesti-mates the number of artistic films. Because of these shortcomings, I focuson whether Oscar nominations influence studio choice by stars rather thanusing this as a way to determine whether artistic films are profitable.

The final definition of artistic films includes all films which have beenshown at the Sundance Film Festival, which is the largest independent filmfestival in the United States and has been running since 1985 26. Using this

definition has the advantage of identifying films which are intended to beartistically oriented. While admission to the festival is competitive, only thebest films at Sundance are picked up by distributors for theatrical release, sofilms submitted and rejected from the festival are unlikely to appear in mydataset. Thus, this definition recognizes more than just ex post successfulartistic films as does definition 2). The biggest disadvantage of this definitionis that not all artistic films are submitted to the festival, so there may besignificant misclassification of non-Sundance artistic films as commercial.

All three definitions of artistic films are somewhat parsimonious defini-tions of artistic films, so they are likely to misidentify some films as commer-

cial films when in fact they were intended as artistic films. Moreover, thereis spectrum of films with both artistic and commercial characteristics, so anydefinition is bound to impinge on this gray area. The three definitions arefairly uncorrelated (see Table 1), as they identify different types of artisticfilms. While each of them has weaknesses, we can get a fairly comprehensiveview of artistic films by examining all three of them in turn.

26The festival was known as the Utah/US Film Festival starting in 1978, and in 1985Robert Redfords Sundance Institute took over management of the festival. The festivalsname was changed to the Sundance Film Festival in 1991

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Table 1: Correlations between definitions of artistic films. The followingtable shows correlations between indicator variables denoting films includedunder the four definitions of artistic films.

Variables Studio Art Oscar SundanceStudio Art 1.000Oscar 0.063 1.000Sundance 0.142 -0.010 1.000

3.3 Definition of stars

Intuitively, I define stars as actors and directors who have unique talentswhich enhance the value of the films they are a part of. One function of thisdefinition is to narrow down the list of actors and directors in my analysis, asdata on each actor and directors films must be hand-collected. Since starsare the actors and directors most likely to provide value to the studio andtherefore the ones studios are most likely to compete for, they are also theones most relevent for analysis.

In order to identify the stars who fit this intuitive definition, I use Pre-miere magazines annual list of the 100 most powerful people in Hollywood.The list includes executives, agents, as well as actors and directors, so thestars which appear on the list may be presumed to wield substantial bargain-ing power. My universe of stars consists of the 94 actors and 100 directorswho have appeared on the list between 1990 and 2005. The Premiere 100 listhas also been used to identify stars in previous work such as De Vany andWalls [2002b] and De Vany and Walls [1999]. Using this external definitionof stardom allows me to test the hypothesis of whether stars add value tofilms. While the Premiere list identifies those players regarded by industryinsiders as wielding power, this does not necessarily imply that these stars

add value to films. In particular, I examine whether stars have significantpositive fixed effects on film success, and it is not obvious ex ante that theindustry would be able to distinguish between people who choose films withfavorable characteristics and people who truly add value to films beyond itsother characteristics. Thus, using the Premiere 100 list provides a way totest whether commonly held notions of stardom correspond with economicmeasures of value and verify one of the assumptions of my hypothesis.

Using the Premiere 100 list, I construct two different definitions of starsbased on whether someone is currently on the list, was on the list in the

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past, or will be on the list in the future. While major stars such as TomCruise and Stephen Spielberg remain on the list for many years, new starsare also added to the list as their popularity increases, and others drop offthe list. The first definition I use includes any actor or director who appearson the list in any year. This definition assumes that stars have an intrinsicability which is present even before they are widely recognized and persistseven if they fade from popularity, and this ability is gradually discoveredthrough time. Under the second definition, an actor or director is only a star

in a given year if he or she appears on the Premiere list in the same year.This definition assumes that a stars ability varies through time and that thePremiere list captures these variations. Which of these definitions is morerelevant depends on their economic significance, and I report results usingboth.

3.4 Descriptive Statistics

Table 2 shows descriptive statistics for my full sample of 6505 films, whichcontains nearly all films released in the U.S. between January 1, 1980 and

June 30, 2005 excluding films which were still in theatres as of June 30,2005. Revenues are pooled for re-releases, directors cuts, and other specialshowings. The Sundance variable is 1 for films which have been shown atthe Sundance Film Festival (which has been in existence since 1985) and 0otherwise. The Powerful director variable indicates films whose directorsare ranked in the Premiere 100 in the year that the film is released, andthe Powerful director all films variable indicates films whose directors areranked in the Premiere 100 in any year. Similarly defined are Powerfulactor and Powerful actor all films. In the entire sample, about 3% offilms are made by directors contemporaneously on the Premiere list, andabout 10% are made by directors who have been on the list at some point.Reflecting the longer duration of a directors commitment to a film comparedto an actors (and hence the greater number of films an actor may make inher career), 9% and 25% of films contain actors who are contemporaneouslyon the Premiere list or have at any time been on the list, respectively. Sincethe Premiere 100 list starts only in 1990, Table 3 presents summary statisticsfor the 1990-2005 sample. As expected the means of the Powerful directorand Powerful actor variables are higher, and there are also more Sundancefilms in this sample. Other variables are not significantly different betweenthe two sample periods.

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Both revenues and production budgets have highly skewed distributionswith long right tails and very small medians compared to their means. ArthurDe Vany and co-authors 27 have examined these distributions in depth andestablished that films are unique and extremely risky projects with revenuesdriven by extreme right-tail events that are difficult to forecast ex ante. Whilemost film projects make very little if any profits, a few projects a year breakthrough and make tremendous profits. Since artistic projects are very un-likely to become attain revenues in the positive extreme, the skewed nature of

revenue distributions deepens the puzzle of why studios make artistic films.Tables 4 and 5 show breakdowns of films by the column heading by rating

and genre. The left panels show breakdowns by studio, and the right panelsshow breakdowns for all films, large studio films, artistic subsidiary films,independent films, oscar-nominated films, Sundance festival films, and filmscontaining powerful actors or powerful directors. In Table 4, entries in eachcolumn show the percentage of films of row type, and in Table 5, entries ineach column show the percentage of total (inflation-adjusted) budget allo-cated to films of row type. As noted in previous work such as Ravid andBasuroy [2004] and De Vany and Walls [2002b], very few G-rated films are

made, whereas nearly half of all films are rated R. However, previous stud-ies have not considered the amount of budget allocated to different ratingscategories. While there are more than twice as many R-rated films as PG-13-rated films as seen in Table 4, when considering the budget allocationsin Table 5, R-rated films receive only slightly more investment dollars thanPG-13 films. With the exception of greater investment in G-rated films byDisney, budget and film allocations do not differ substantially between themajor studios. However, there are key differences between commercial andartistic films, identified by the comparison between large-studio and sub-sidiary, Oscar-nominated, and Sundance festival filmes (corresponding to the

three definitions of artistic film described above). While 31% of films and62% of the budgets of large studios have ratings suitable for children (G, PG,or PG-13), only between 20-41% of the films and 37-46% of the budgets ofartistic films are suitable for children. In addition, artistic films are muchmore likely to be dramas and romances and less likely to be thrillers or actionmovies than commercial films. Ratings and genre data are from the IMDB.

27See De Vany [2004] for a compendium of his work

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Variable Mean Std. Dev. Min. Max. N

Domestic gross($M) 23.58 47.48 0 708.80 4859Runtime 1.74 0.35 0.03 6.67 4694Prod. budget($M) 34.36 34.63 0 235.96 2205

Worldwide gross($M) 43.03 113.4 0 2399.13 4857Studio Com 0.43 0.5 0 1 4909Subsidiary 0.12 0.32 0 1 4909Indie 0.45 0.5 0 1 4909# Oscar noms 0.12 0.62 0 7 4909Sundance 0.12 0.32 0 1 4909Powerful director 0.04 0.2 0 1 4909Powerful director all films 0.1 0.3 0 1 4909Powerful actor 0.12 0.32 0 1 4909Powerful actor all films 0.25 0.43 0 1 4909

Films with production budget dataDomestic gross($M) 42.46 62.61 0 708.80 2192Runtime 1.79 0.34 1.05 4.35 2184Prod. budget($M) 34.36 34.63 0 235.96 2205Worldwide gross($M) 82.43 156.33 0 2399.13 2191Studio Com 0.59 0.49 0 1 2205Subsidiary 0.13 0.34 0 1 2205Indie 0.28 0.45 0 1 2205# Oscar noms 0.22 0.85 0 7 2205Sundance 0.1 0.3 0 1 2205

Powerful director 0.08 0.27 0 1 2205Powerful director all films 0.19 0.4 0 1 2205Powerful actor 0.21 0.41 0 1 2205Powerful actor all films 0.39 0.49 0 1 2205

Table 3: Summary statistics for 1990-2005 .

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WB Para Sony MGM Fox Uni Dis All Large Sub Indep Osc noG 2 1 1 0 1 1 13 3 3 2 3 2

PG 16 17 13 21 16 22 26 18 19 6 15 14PG-13 36 39 42 45 47 44 30 38 40 29 25 29

R 45 43 44 33 36 32 31 40 37 61 50 54Unrated 0 0 0 0 0 0 0 1 0 2 6 0Sequel 18 14 10 20 14 11 6 12 13 5 6 5 Action 44 40 37 44 51 37 30 37 41 17 21 24

Comedy 36 33 42 28 34 43 49 39 39 40 38 28Drama 44 50 45 44 44 44 49 46 44 68 50 86

Romance 15 19 18 19 21 16 22 18 17 33 13 23

Thriller 38 83 32 112 45 30 23 36 39 21 26 17

Table 5: Genre and Ratings budget allocations by type of studio. The table presents the budfor films of type indicated by each column with the characteristics in each row as a perctotal budget for each film type for the entire period from 1980-2005. The left portion of thbreakdowns by studio conglomerate, which includes films by both commercial and artistic dLarge category includes films released by the seven large studios excluding those from artiand the Sub category includes films released by all artistic subsidiaries of large studios. category includes all films not released by major studios or artistic subsidiaries, but includes by artistic firms which were later acquired by large studios. The Osc nom category incl

which were nominated for at least one Oscar in the following categories: best film, best directbest supporting actor, best actress, best supporting actress, best original screenplay, and screenplay. The Sun category includes all films which were exhibited at the Sundance Film

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4 Results

4.1 Determinants of film profitability

As in previous studies such as Litman and Kohl [1989], De Vany and Walls[1999], and Ravid [1999], I consider the factors which influence film revenuesby running regressions of log revenue on film characteristics. My setup con-strasts with previous studies both in size and comprehensiveness of the sam-

ple, as well as the set of control variables used. While most previous studieshave included MPAA rating as a control, I aim to control for a broad setof film characteristics which mainly reflect variables which can be controlledby a studio before a film is released. Thus, while critical reviews have beenshown to impact film revenues, I do not include them since studios cannotcontrol critical response. On the other hand, studios can control film bud-get, film length, and director and casting choices in hopes of impacting filmquality. The only ex-post characteristic I use is a variable indicating whetherthe film had been nominated for an Oscar in a major category, and the in-clusion of this variable is mainly used as a distinguishing characteristic ofartistic films as opposed to a determinant of revenue. Estimated productionbudgets are available for over 2500 films, so at least some adjustment can bemade for cost. However, a major weakness to the data set is that project re-turns are unobservable, and in addition, some components of both cost (e.g.advertising, overhead, film duplication) and revenue (e.g. television, DVD,merchandizing) are missing. One reason for looking at revenues is that de-spite the greater financial importance of returns, film revenues continue tobe the standard benchmark for success among industry insiders 28.

Much of the analysis in the following sections is based on a basic regres-sion with log inflation-adjusted worldwide revenues on (in December 2004dollars) and independent variables including film length (in hours), produc-

tion budget (estimated in millions $), IMDB genres (films may have morethan one genre), a dummy variable for whether or not the film is part ofa series or franchise, dummies for MPAA rating (omitted category is un-rated), a dummy for whether the film was distributed by one of the majorstudios, a dummy for whether the film was distributed by one of the artisticdivisions (this variable can only equal 1 if the previous is also 1), a dummyfor inclusion in the Sundance Film Festival, a count of the number of Oscar

28Film revenues are the primary metric for film success in the industry press, and profitmaximization has been documented in studies such as Ravid and Basuroy [2004]

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nominations in eight major categories, a dummy for whether the film wasdirected by a powerful directors, a dummy for whether the film includes apowerful actor, and year and month dummies. Table 6 shows the results ofthese regressions. In this analysis, powerful directors and actors are definedas stars which appear on the Premiere list in any year, but results are similarusing stars which appear on the list in the same year a film is released.

According to Table 6, many factors influence film revenues. In particular,the regressions highlight characteristics which the studio can easily control

ahead of time, such as film length, genre, and ratings. In the absense ofunobserved constraints, studio executives should be able to allocate invest-ment according to films with the desired characteristics, and in a revenue-maximization framework, we would expect to see more investment in filmcategories which achieve higher revenues.

Film length has a positive and significant coefficient with respect to filmrevenue. Films in the sample have an average length of about 1 hour and45 minutes, and naively, one might suppose that films with shorter runningtimes would earn more money because exhibitors are able to turn the theatresaround faster. However, the positive relationship between runtimes and rev-

enues suggests that there is a countervailing effect, this effect becomes evenstronger after removing very short and very long films. One explanation isthat audiences prefer longer movies to get more value for the price of a ticket.

Consistent with previous studies, ratings are also highly significant de-terminants of revenue. However, in contrast to studies such as Ravid andBasuroy [2004], Ravid [1999] and De Vany and Walls [2002b] which find rev-enue effects to decrease as ratings become more restrictive, in my resultsPG-13 films have the highest coefficient relative to unrated films, followed byG, R and PG. All ratings categories have positive and significant coefficientsrelative to unrated films, and an F-test rejects the hypothesis that all of the

ratings coefficients are equal.As would be expected, films distributed by large studios have much higherrevenues than films distributed independently. Studio films perform bettereven after controlling for budget and film characteristics, possibly owing tostudios superior experience and marketing expertise over smaller film com-panies. However, the benefit of large studio distribution is mitigated for filmsdistributed by artistic subsidiaries. This lends support to the contention thatthe films produced by artistically-oriented subsidiaries are less profitable thanthose produced by the studio at large, raising the question of why studiosfund such subsidiaries. Similarly, as shown in the third column of Table 6

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(1) (2) (3) (4) (5)Runtime 0.733 0.733 0.741 0.476 0.734

(5.68)*** (5.65)*** (5.74)*** (3.69)*** (5.69)***Log budget 0.529 0.536 0.552 0.528 0.523

(14.27)*** (15.21)*** (15.76)*** (14.27)*** (13.83)***Sequel 0.875 0.876 0.865 0.871 0.869

(10.27)*** (10.31)*** (10.16)*** (10.23)*** (10.04)***G 1.568 1.560 1.539 1.468 1.583

(5.91)*** (5.93)*** (5.89)*** (5.68)*** (6.00)***PG 1.434 1.425 1.400 1.381 1.443

(7.21)*** (7.28)*** (7.26)*** (7.02)*** (7.26)***PG-13 1.893 1.880 1.855 1.841 1.888

(9.70)*** (9.96)*** (9.94)*** (9.42)*** (9.75)***R 1.469 1.454 1.404 1.402 1.466

(8.39)*** (8.40)*** (8.28)*** (7.99)*** (8.44)***Powerful director all films 0.576 0.576 0.581 0.427

(8.06)*** (8.10)*** (8.11)*** (6.34)***Powerful director pre 0.580

(6.75)***Powerful director 0.520

(5.10)***Powerful actor all films 0.728 0.729 0.729 0.694

(9.91)*** (9.89)*** (9.87)*** (9.68)***Powerful actor pre 0.636

(8.07)***Powerful actor 0.864

(8.26)***Studio 1.064 1.062 1.046 1.095 1.064

(10.00)*** (9.78)*** (9.23)*** (10.94)*** (9.94)***Subsidiary -0.360 -0.385 -0.459 -0.357(2.55)** (2.77)*** (3.35)*** (2.54)**

Sundance 0.077 0.397(0.43) (1.73)*

Subsidiary*Sundance 0.094(0.32)

Studio*Sundance -0.618(2.13)**

# Oscar noms 0.236(13.49)***

Genre FE yes yes yes yes yesYear FE yes yes yes yes yesMonth FE no no no no noObservations 2596 2596 2596 2596 2596R-squared 0.59 0.59 0.59 0.61 0.59Robust t statistics in parentheses* significant at 10%; ** significant at 5%; *** significant at 1%

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while films shown at the Sundance film festival perform better than otherindependent films with similar characteristics, studio-distributed Sundancefilms fare worse than other studio films. Moreover, coefficient on the stu-dio*Sundance interaction term is similar in magnitude to the coefficient onSubsidiary.

While I use Oscar nominations as a way to proxy for a films artisticmerit, it is not appropriate to use Oscar nominations to judge a films exanteprofitability since Oscar nominations are normally awarded to relatively

successful films and nominations are highly unpredictable. Moreover, manyfilms remain in theatres after nominations are announced, and the nomi-nations themselves are a large source of publicity for these films. Thus, incontrast to the other proxies for artistic merit, Oscar nominations increasefilm revenues.

Many previous studies have demonstrated the economic value of stars.John et al. [2002] show that star directors seem to have a positive fixed effectson returns. In contrast, Ravid [1999] and Ravid and Basuroy [2004] suggestthat star actors have no significant effect on revenues after controlling forbudget. In my sample, the Powerful Director and Powerful Actorvariables

are both positive and highly significant, indicating that stars have conveya positive economic benefit to studios even after controlling for budget andother film characteristics. Including a count of the number of star actorsinstead of using a dummy variable is also positive and significant, and thecoefficient drops to between 0.4 and 0.5, suggesting that additional star actorsadd value beyond the first star actor. In unreported regressions, the effectof actors and directors is higher for stars ranked higher on the Premiere 100list, suggesting that the list identifies stars with high individual ability asopposed to stars which selectively choose films in higher-revenue categories.

Table 7 presents results similar to those in Table 6 using the return on

investment as the dependent variable. The return is defined as the totalworldwide revenue divided by the production budget minus 1. This variablemay not capture the true return on film projects because it fails to take intoaccount costs of marketing, overhead costs, and contingent compensation,and it also neglicts revenues from DVD, television, and other ancilliary mar-kets. However, as argued in Ravid [1999], it may be a reasonable proxy forreturns if real revenues are a constant multiple of worldwide film revenuesand real costs are a constant multiple of production costs. Although thepredictive power of film characteristics is much lower than for revenues, thesigns and significance are generally consistent with those for revenues. As in

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the revenue regressions, longer runtime, sequels, and stars are positively cor-related with returns. Moreover, as with revenues, R-rated films have lowerreturns than films with other ratings. In addition, studio films exhibit higherreturns, while subsidiary films have lower returns than other studio films.Sundance films made by large studios also perform worse than other studiofilms, although this effect is not significant. The major difference between re-sults using returns and those for revenues is that budget is negatively relatedto film performance. The contrast between these results suggests that while

higher budgets increase revenues, they do not increase them proportionallyto the increase in costs, so they negatively affect returns.

4.1.1 Ratings Effects

Previous studies have identified film ratings as a characteristic which poten-tially identifies inefficient investment by studios. De Vany and Walls [2002b]find that when fitting the distribution of film revenues with a stable paretianstatistical model, R-rated films are stochastically dominated by all other rat-ings categories. Ravid and Basuroy [2004] and Ravid [1999] also conclude

the R is the least profitable ratings category, but Ravid and Basuroy [2004]suggest that studio managers may find R-rated films with sex or violencefavorable because they are less risky. Thus the preponderance of investmentin R-rated films (see also Tables 4 and 5) seems inconsistent with measuresof their value to studios.

In my sample, I find qualitatively similar results. The left panel of Ta-ble 8 shows the ratings fixed effects in regressions similar to those shownin Table 6 with log worldwide revenue as the dependent variable and con-trolling for film length, log production budget, ratings dummies, dummiesfor the presence of powerful actors and directors, and dummies for studioand subsidiary films (where appropriate). Each column represents coeffi-

cient estimates for the above regression restricted to different commercialand artistic film categories. In the estimates using all films, G-rated filmshave the largest fixed-effect, followed by PG-13- and PG-rated films, withR-rated films having the smallest fixed effect. These results are very similarwhen the regression is restricted to either large-studio films (excluding thoseby artistic subsidiaries) or Oscar-nominated films.

However, when the sample is restricted to subsidiary or Sundance films,the results change dramatically, as shown in the third column of Table 8.While the correlation between the fixed effects for large studio and Oscar-

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Regression Coefficient Total BudgetAll films Large stud Subsid Oscar nom Sun All films Large stud Subs

G 2.556 2.605 0.029 2.152 2775 2480 81PG 1.728 1.697 0.404 1.658 -0.112 15865 13938 265PG-13 1.823 1.621 1.358 1.393 1.043 32802 28565 1257

R 1.449 1.39 0.825 1.124 0.603 35576 27015 2637

Table 8: Ratings Effects and Allocations. Left panel: coefficients on dummies for MPAA ratingof the log of worldwide revenue on film length, log production budget, ratings dummies, dumpresence of powerful actors and directors, and dummies for studio and subsidiary films (where All ratings dummies are significant at the 1% level. Right panel: Aggregate budget (in millioto each ratings catgory by film type adjusted for inflation to December 2004 dollars.

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Allocation category(1) (2) (3) (4) (5)

Regression population All films Large stud Subsidiary Oscar nom Sundance(1) All films -0.851 -0.828 -0.742 -0.840 -0.973(2) Large stud -0.907 -0.900 -0.740 -0.836 -0.968(3) Subsidiary 0.892 0.939 0.608 0.646 -0.082(4) Oscar nom -0.975 -0.949 -0.895 -0.950 -0.861(5) Sundance 0.869 0.958 0.536 0.487 0.122

Table 9: Correlations between ratings effects and allocations. Correlationsbetween vectors of ratings fixed effects and budget allocations to the fourratings G, PG, PG-13, and R for five film categories: all films, large-studiofilms (excluding artistic subsidiary films), subsidiary films, Oscar-nominatedfilms, and Sundance films. The entry in row i, column j represents thecorrelation between the vector of fixed effects for films of category i and thevector of budget allocations for films of category j.

In contrast to these expectations, Table 11 shows a general negative cor-

relation between revenue fixed effects and investment. In addition, a strikingpattern emerges when comparing the correlation between investment andthe fixed effects for commercial films (row 2) with the correlation betweeninvestment and the fixed effects for artistic films (rows 3-5). From row 2,the correlation between investment and large-studio fixed effects are nega-tive for all types of films. In contrast, when using fixed effects for subsidiaryor Sundance film (rows 3 and 5), these correlations become positive. Thatis, studios seem to investment in both commercial and artistic films is al-located to categories which make artistic films successful. Thus, althoughthe determinantes of revenue are very different for commercial and artistic

films, investment follows the film types which make for successful artistic

films. This result is all the more suprising since artistic films make up onlya fraction of films released. In this analysis, the determinants of revenuefor Oscar-nominated films much more closely resemble those for large-studiofilms than for subsidiary or Sundance films, suggesting that the audience forOscar-nominated films is different than that for subsidiary or Sundance films.

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4.1.2 Genre Effects

Genre also plays an important role in film revenue, and the coefficients fordummy variables based on IMDB genre categories are explored in the leftpanel of Table 10. The entries represent the genre fixed effects in regressionsof log revenue controlling for film length, log production budget, ratingsdummies, dummies for the presence of powerful actors and directors, anddummies for studio and subsidiary films (where appropriate). Each column

represents coefficient estimates for the above regression restricted to differentcommercial and artistic film categories. While the impact of genre has notbeen explored extensively in the literature, I find that film genre is highlypredictive of film revenue. Indeed, it seems intuitive that potential audiencesize is highly related to genre - perhaps some moviegoers prefer to watchcomedies while some prefer dramas, and some may specialize in genres suchas horror or science fiction.

Overall, while action, animation, comedy, horror, mystery, and romancefilms receive significantly higher revenues, dramatic and war films receivesignificantly lower revenues. However, similarly to the impact of genre maydiffers among the different categories of films, especially between large-studioand subsidiary films. While the coefficient for documentaries is positive andsignificant for large-studio films, it is negative and insignificant for subsidiaryfilms. Mystery is also positive for large-studio films and negative for sub-sidiary films. While Family is positive and significant for large-studio andSundance films, it is negative and significant for subsidiary films. Mysteryfilms show a similar pattern. The results are unchanged when controllingfor studio and subsidiary fixed effects instead of using dummy variables forstudio and subsidiary films.

As with investment by rating, the right panel of Table 10) shows pattern ofinvestment which is similar among genres for all types of films; all pairwise

correlations between budget allocations exceed 0.68. Table ?? shows thecorrelations between investment and genre fixed effects for all films, large-studio films, and artistic films using the three definitions discussed previously.The entry in row i and columnj of the table represents the correlation

Corrij =Corr(F Ei,Budj) i, j {All, LargeStud, Sub, OscNom, Sun}

where F Ei and Budj are vectors of fixed effects and budget allocationscorresponding to the columns of Table 10. As in the previous section, we

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Regression Coefficient All films Large stud Subsid Oscar nom Sund All films Lar

Action 0.474 *** 0.386 *** 1.027 * 0.211 0.878 32460 293Adventure 0.123 0.072 -0.106 0.442 -0.151 22728 204Animation 0.692 *** 0.646 *** 0.817 0.066 0.000 4332 394Biography -0.033 -0.474 *** -0.170 -0.308 0.784 4303 246Comedy 0.230 *** 0.123 0.684 *** -0.160 0.172 33362 283Crime -0.136 -0.224 *** -0.332 -0.107 -0.096 14485 115Documentary 0.512 1.142 ** -0.340 0.000 0.891 74 32 Drama -0.218 *** -0.204 *** -0.177 -0.650 ** -0.388 44074 320Family 0.784 *** 0.754 *** -1.932 ** 0.662 1.280 ** 9712 905Fantasy 0.016 -0.026 0.003 -0.182 -0.540 14292 128

Horror 0.630 *** 0.379 *** 1.311 ** -0.258 *** 1.293 ** 6988 649Music -0.181 -0.253 * -0.581 -0.137 -1.232 4144 316Mystery 0.321 * 0.229 * -1.285 * 0.019 0.055 5817 510Romance 0.312 *** 0.212 ** 0.124 0.185 * 0.570 16378 124Scifi -0.061 -0.082 -0.029 0.309 -0.742 13444 126Thriller 0.147 0.214 ** 0.103 0.022 0.430 30915 278War -0.479 ** -0.319 * -0.846 -0.309 -1.435 ** 4871 347* significant at 10%; ** significant at 5%; *** significant at 1%

Table 10: Genre Effects and Allocations. Left panel: coefficients on dummies for IMDB genres

of the log of worldwide revenue on film length, log production budget, ratings dummies, dumpresence of powerful actors and directors, and dummies for studio and subsidiary films (where Right panel: Aggregate budget (in millions) allocated to each genre by film type adjusted foDecember 2004 dollars.

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Allocation category(1) (2) (3) (4) (5)

Regression population All films Large stud Subsidiary Oscar nom Sundance(1) All films -0.155 -0.094 -0.269 -0.339 -0.257(2) Large stud -0.179 -0.128 -0.271 -0.292 -0.234(3) Subsid 0.311 0.340 0.210 0.084 0.208(4) Oscar nom -0.135 -0.037 -0.451 -0.487 -0.398(5) Sund 0.019 0.052 -0.047 -0.081 -0.129

Table 11: Correlations between genre effects and allocations. Correlationsbetween vectors of genre fixed effects and budget allocations to the genresand for film categories in Table ??. The entry in row i, column j representsthe correlation between the vector of fixed effects for films of category iandthe vector of budget allocations for films of category j.

expect the investment dollars to be positively correlated with revenue fixedeffects.

Once again, Table ?? shows a general negative correlation between rev-

enue fixed effects and investment. That is, there appears to be investment ingenres which have less expected revenue, and vice versa. Instead, as shown inrow (2), film producers overall invest more in genres correlated with successfor subsidiary films, and a similar but less pronounced effect is shown forSundance films in row (5).

4.1.3 Seasonality in revenues

There is clear seasonality in film revenues, and results using month dummiesare shown in table 12. The two major season for film releases are the summermonths in June and July when children are on summer break and the holiday

season in November and December, when people take holidays and whenmost Oscar contenders are released. While the fixed effects during bothpeak seasons are comparable, films released during the summer months haveslightly greater advantage.

Moreover, the release date is an endogenous decision made by studioswhich is expected to be correlated with unobserved film quality. Althoughrelease schedules for major films may be decided well in advance, studioscommonly adjust release schedules to position the films with the highestexpectations during weekends with the largest potential audience, and they

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frequently change scheduled release dates based on their observations as thefilm is produced. Ideally, I would like to instrument for the release date witha variable which is independent of unobservable film quality, but the datado not provide such a variable. Thus, while the coefficients discussed in theprevious sections remain qualitatively unaffected by the inclusion of monthdummies, I will not focus on these results because due to the endogeneityproblem.

4.1.4 Star fixed effects

To determine the economic value of stars, I examine the coefficients of vari-ables indicating star participation in films, a similar technique to that ofDe Vany and Walls [1999] and John et al. [2002]. Consistent with their re-sults, I find that stars generally have a positive and significant effect on bothfilm revenues and returns in the multinomial setting. I calculate star fixedeffects using regressions of log revenues on film characteristics with studioand subsidiary fixed effects. Of the star directors, 82 out of 100 coefficientsare positive, and 39 of those are significant. Among the 100 star actors, 73

are positive, and 31 have positive and significant coefficients. See AppendixC for the actors and directors who have positive and significant fixed effects.

4.1.5 Star career paths

The main paper in the literature which explores the career paths of starshas been John et al. [2002], who examine firing and rehiring decisions fordirectors. While they examine the short-term contracts common in the filmindustry as a way for studios to discover talented directors and weed outuntalented ones, in this study I focus on the subset of high-ability stars.Once stars have been identified on the Premiere 100 list, presumably there

is no longer a question as to their ability. Then, the employment contractbecomes less a question of whether the star will be rehired by a studio, butrather which studio the star chooses to work with.

Among the 100 star directors in my sample, the average career length is7 films, with a standard deviation of about 5. Among the 94 star actors,the average career length is 22 films with a standard deviation of 10. Table14 shows the percentage of films with star actors or directors made by largestudios and which fall into the three artistic film categories. The left panelshows the percentage of stars with anyfilm in the given categories, and the

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(1) (2) (3) (4)Runtime 0.672 0.672 0.684 0.445

(5.22)*** (5.17)*** (5.27)*** (3.49)***Log budget 0.526 0.530 0.547 0.527

(14.19)*** (14.94)*** (15.59)*** (14.21)***Sequel 0.823 0.824 0.814 0.827

(9.50)*** (9.53)*** (9.40)*** (9.62)***G 1.583 1.579 1.556 1.477

(5.88)*** (5.89)*** (5.85)*** (5.65)***PG 1.482 1.476 1.450 1.427

(7.22)*** (7.27)*** (7.25)*** (7.01)***PG-13 1.938 1.931 1.906 1.887

(9.63)*** (9.85)*** (9.84)*** (9.33)***R 1.535 1.526 1.473 1.465

(8.43)*** (8.42)*** (8.31)*** (8.02)***Powerful director 0.551 0.552 0.558 0.404

(7.71)*** (7.76)*** (7.78)*** (6.01)***Powerful Actor 0.697 0.698 0.698 0.668

(9.46)*** (9.45)*** (9.42)*** (9.35)***Studio 1.049 1.046 1.023 1.082

(9.71)*** (9.49)*** (8.92)*** (10.50)***Subsidiary -0.388 -0.414 -0.476

(2.69)*** (2.94)*** (3.40)***Sundance 0.034 0.350

(0.19) (1.51)Studio*Sundance -0.609

(2.08)**Subsidiary*Sundance 0.111

(0.38)# Oscar noms 0.454(13.55)***

Observations 2598 2598 2598 2598R-squared 0.59 0.59 0.59 0.62Robust t statistics in parentheses* significant at 10%; ** significant at 5%; *** significant at 1%

Table 12: Determinants of film revenue including month fixed effects. Thistable presents results of OLS regressions of log revenue (in December 2004dollars) on explanatory characteristics. Robust standard errors are reported

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% with any film Avg # of filmsActors Directors Actors Directors

Studio 99 94 83 81Subsidiary 65 25 9 11Sundance 52 23 5 7Oscar nominated 80 59 14 21

Table 13: Career statistics. The left shows the percentage of all stars who

have made each type of film at some point in their careers. The right panelshows the average number of films of each type made by stars.

right panel shows the average percentage of films in each category. Whilenearly all stars have at least one film distributed by a major studio and manyof them have at least one artistic film, the average percentages of artistic filmsare much lower.

Tables 4.1.5 and 4.1.5 show the average career paths of actors and direc-tors in terms of the types of films that they make over the course of theircareers. If it were the case that stars have typical career paths whereby they

make artistic films early in their careers and commercial films later, then Imay spuriously find that artistic films increase star value by capturing thesecareer cycle effects. However, there appears to be no systematic patternin the types of films made by stars throughout their careers. As shown inFigure 4.1.5, actors tend to make slightly more studio films and subsidiaryfilms as their careers progress, but the trend is not strong. Directors seem toexhibit a stronger tendency to make subsidiary films later in their careers, soconsidering past subsidiary films may positively bias estimates of the produc-tivity impact of artistic films. However, controlling for career length shouldmitigate this problem.

In order to explore whether artistic films improve the productivity ofstars, I examine whether doing artistic films enhances the value of a starslater films. Table 14 shows the results of regressions similar to those in Table6 when actor career characteristics are added. Consistent with the intuitionof John et al. [2002], who posit that stars who are able to make more filmsare more likely to have high ability, the number of films that the star haspreviously done is positive and significant in determining revenues for filmswhich contain star actors. Although the number of artistic films a star hasdone previously does not add significantly to revenues above the number of

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(1) (2) (3) (4)Film count actor 0.044 0.040 0.038 0.040

(6.42)*** (4.78)*** (5.67)*** (5.43)***

Sub count actor 0.069(1.14)

Sun count actor 0.111(1.38)

Cum Oscar noms actor 0.011(0.75)

Actor FE yes yes yes yesDirector FE yes yes yes yesStudio FE yes yes yes yesSubsidiary FE yes yes yes yes

Genre FE yes yes yes yesYear FE yes yes yes yesMonth FE no no no noObservations 6271 6271 6271R-squared 0.58 0.58 0.58Robust t statistics in parentheses* significant at 10%; ** significant at 5%; *** significant at 1%

Table 14: Revenue regressions on actor career variables. This table presentsresults of regressions similar to those in Table 6 of log worldwide revenue onfilm characteristics. In addition, if the film contains star actors (those who

were on the Premiere list in any year), variables are included which indicatethe number of films the star has done previous to the current film and thenumber of subsidiary and Sundance films the star has previously done. Inthe event that a film contains more than one star, the average values for thetwo stars is used.

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(1) (2) (3) (4)Film count director 0.066 0.097 0.062 0.069

(3.41)*** (4.43)*** (2.80)*** (3.40)***Sub count director 0.063

(0.67)Sun count director -0.105

(0.51)Cum Oscar noms director -0.336

(2.50)**Observations 6268 6268 6268 6268R-squared 0.57 0.57 0.57 0.57Actor FE yes yes yes yesDirector FE yes yes yes yesStudio FE yes yes yes yes

Subsidiary FE yes yes yes yesGenre FE yes yes yes yesYear FE yes yes yes yesMonth FE no no no noObservations 2598 2598 2598 2598R-squared 0.04 0.04 0.04 0.04Robust t statistics in parentheses* significant at 10%; ** significant at 5%; *** significant at 1%

Table 15: Revenue regressions on actor career variables. This table presentsresults of regressions similar to those in Table 6 of log worldwide revenue on

film characteristics. In addition, if the film contains star actors (those whowere on the Premiere list in any year), variables are included which indicatethe number of films the star has done previous to the current film and thenumber of subsidiary and Sundance films the star has previously done. Inthe event that a film contains more than one star, the average values for thetwo stars is used.

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Figure 2: Average career path of directors. The figure shows the percent-age of studio films, subsidiary films, and Sundance films made by directorsaccording to chronological film sequence.

between the seven major studios based on studio characteristics and on thepast relationship between the star and studio. Since this study mainly con-cerns the production of artistic films by major studios, I do not model the

choice of independent distribution. Assuming the independence of irrelevantalternatives, this modelling choice is valid.

Given that my definition of stars consists of people whom Hollywood in-siders identify as wielding considerable power in the industry. As previousstudies have indicated, stars with real economic value are scarce, so all of thestudios must clamor for the attention of these talented few. Thus, I assumethat the stars identified in my sample are sufficiently in-demand that theywould at any given time have outstanding opportunities to work with any ofthe seven major studios; and moreover, that the studios compete for starsand not vice versa 29. This assumption is supported by industry accounts

which portray film selection as a process in which studios and independentproducers have myriad projects in development at any given time and rolesare continuously being offered to star actors and directors; as casting anddirectorial decisions are constantly in flux, stars typically negotiate with sev-eral studios at once 30. Furthermore, studio choice is examined at points intime conditionalon the fact that at least one studio made an offer.

29These opportunities might be films which the studio is developing and offers to thestar, or projects that the star or a third party controls for which studio support is sought.

30See, for instance, Goldman [2000], or Bart [2000]

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Based on the above assumptions, I model studio choice using the randomutility framework of McFadden [1974] framework, which conditions on thefact that only one studio is chosen out of the seven possibilities for each film.The utility of star t from choosing studio s {1, . . . , 7} is yts =

xts+ ts,wherextsconsists of observable studio and star characteristics andtsconsistsof unobservable factors which affect the stars utility.

Let yt = argmax(y

t1, . . . , y

t7). Then McFadden [1974] shows that if theerrorstsare independent and distributed with Weibull distributionF(ts) =

exp(ets), then the probability of star t choosing studio sis

Prob(yt = s|xt) = e

Xts

7

r=1eXtr

(1)

I estimate the conditional logit model in equation 1 using a data setconstructed using all films made by star directors or including star actors(stars are defined as any actor or director who have appeared on the Premiere100 list in any year) with seven observations for each film representing thepossible star-studio pairs. For star t, each film observation represents a

time when the star is available and interested in taking on a new film project.Naturally, only one finished film is actually observed, and the potential filmsoffered by other studios at the same time would differ from the one observed.The characteristics of the potential films offered by studios are likely to be themain drivers of the stars choice, but as these characteristics are unobservable,I can only control for characteristics of the studios and characteristics of pastfilms involving the studio and star. Since films are highly individual projectsinvolving unique combinations of cast, crew, and plotlines, the assumptionthat the unobserved film characteristics are independent is plausible.

The dependent variable corresponding to film f, star t, and studio s is0 or 1, indicating whether studio s was selected for star t in film f. Foreach film f, Xts contains characteristics of studio s in year as well ascharacteristics of the studio-star relationship in year , where is the yearthe film was released. The studio-specific independent variables in X aremeant to control mainly for the amount of resources a studio has in a givenyear as well as possibly, the ability of the studios managers. The studio-specific variables inXinclude studio revenues, number of films, and averagebudgets for films released in years and 1.

In addition to studio-specific characteristics,Xcontains controls for sim-ilarities between the types of films the studio and star make, using as proxies

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the correlations in ratings and genres of the films made by the star and stu-dio throughout the entire sample. To measure the impact of the star-studiorelationship on studio choice, I use indicator variables for whether the starhas worked for the studio in the past on any film and whether the star hasworked for the studio in the past on an artistic film. For these variables, thetemporal relationship between films is determined by release date. Alternatespecifications include using variables counting the number of past films orthe percentage of past films instead of an indicator variable. Other specifica-

tions use films released immediately before or after a given film to determinethe studio-star relationship. The results are robust to using these alternatespecifications instead.

Although I believe this simple model captures the essential aspects ofstudio choice by stars, the empirical setup is not without flaws. One com-plication is that in this data set, only the release date of the film is known,whereas the date of the deal between the star and studio is what mattersfor determining the factors which influence studio choice. The difference be-tween the contract date and the film release can range from one year to overa decade, as films are written, filmed, and edited. However, if films released

at the same time were produced at the same time, then contemporaneousmeasures of number of films released and average film budget would accu-rately reflect studio resources. While uncertainty in contract date introducesnoise in the explanatory variables, I do not believe that the variance of theerror is likely to be correlated with unobserved characteristics affecting studiochoice. As a partial remedy to this issue, I add lagged values of the studiocharacteristics. Another potential issue with this setup is that while manyfilms are proposed and enter various stages of production, only a few end upas finished films. If unobserved factors which relate to the probability that afilm successfully completes production are correlated withX, then estimates

ofXcould be biased. In addition, the empirical framework does not allowfor the possibility that not all studios compete for all of the stars for everyfilm. However, if a stronger studio-star relationship makes, then this alsoprovides a channel through which the star brings value to the studio. Thus,my hypothesis may be extended to include the impact of studio-star rela-tionships on film completion while retaining the fundamental idea of artisticfilms creating value by attracting human capital.

Table 16 presents the results of the conditional logit model for studiochoice by directors. As would be expected, much of studio choice is drivenby unobservable variables, and the R2 values are only about 0.09. Directors

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are more likely to choose studios with more films released contempaneously,where I interpret the number of films released as a proxy for studio resources.However, the odds ratio for lagged number of films released is not significantand very close to 1, indicating that measurement error in contract date be-tween the director and studio may not be a substantial issue. Average studiobudget is negatively correlated with the probability of studio choice, whichis somewhat puzzling. The revenues and number of Oscar awards a studioattains are not significant in determining studio choice, indicating they may

not be good proxies for the amount of resources a studio is able to offer to adirector. The variablesDir-stud genre corrandDir-stud rating corr indicatethe correlations between the types of genres and ratings of directors and stu-dios in the entire sample, and as would be expected, greater correlations leadto higher probability of a director choosing a studio. While the estimatesare rather large, the coefficients on the director-studio correlations are nothighly significant. The lack of significance may be due to the fact that thesecorrelations are rather coarse measures of the similarity between the types offilms favored by directors and studios, and also on the relatively films madeby each director in his career.

The Dir-stud pastvariable indicates that the director has worked withthe studio in the past, and the variable is highly significant with a coefficientaround 2. This means that ceteris parabis, the odds of choosing a studio aretwice as high if the director has worked with the studio in the past than ifhe hasnt. While the variablesDir-stud sub past and Dir-stud Osc past arenot significant, they are greater than one, indicating that on average, theyincrease the probability of choosing a studio, which is consistent with myhypothesis. However, the coefficient of Dir-stud Sun past is below one, incontrast to my prediction.

Results on the studio-star variables are similar when considering studio

choice by actors. Again, having worked previously with a studio in the pastmakes a star more likely to work with the studio again, as indicated by theAct-stud past variable. For actors, all three variables indicating previousartistic films with the same studio are above one, and both Dir-stud sub pastandDir-stud Osc pastare highly significant. In order to utilize as much dataas possible, the results in Tables 17 and 17 use all films which includes starswhich appear on the Premiere 100 list in any year. While the significancedecreases, the results are qualitatively unchanged when restricting the sam-ples to films by stars which appear on the Premiere 100 list in the year ofrelease.

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(1) (2) (3) (4)# films made by studio this year 1.235 1.234 1.233 1.234

(7.40)*** (7.43)*** (7.39)*** (7.24)***# films made by studio last year 0.991 0.991 0.988 0.990

(0.32) (0.34) (0.43) (0.35)Total studio revenue this year 1.003 1.003 1.002 1.004

(0.31) (0.30) (0.23) (0.34)Total studio revenue last year 0.991 0.991 0.991 0.991

(0.83) (0.87) (0.84) (0.84)Total Oscars studio this year 1.003 1.003 1.003 1.003

(0.17) (0.19) (0.20) (0.15)Total Oscars studio last year 1.004 1.003 1.005 1.004

(0.21) (0.19) (0.27) (0.22)Avg budget studio this year 0.995 0.995 0.995 0.995

(2.32)** (2.26)** (2.26)** (2.32)**Avg budget studio last year 0.995 0.994 0.995 0.995

(2.04)** (2.09)** (2.01)** (2.03)**Dir-stud genre corr 16.355 17.788 20.451 15.145

(1.90)* (1.98)** (2.27)** (1.83)*Dir-stud rating corr 18.487 15.414 17.587 20.141

(1.70)* (1.58) (1.67)* (1.74)*Dir-stud past 2.401 2.287 2.378 2.484

(5.69)*** (5.60)*** (5.71)*** (5.77)***Dir-stud Osc past 1.451

(1.38)Dir-stud sub past 1.894

(1.04)Dir-stud Sun past 0.527

(1.47)Observations 3147 3147 3147 3147Pseudo R-squared 0.09 0.09 0.09 0.09Robust t statistics in parentheses* significant at 10%; ** significant at 5%; *** significant at 1%

Table 16: Studio choice by directors. This table presents results of es

creativity and project value in the film industry

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