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The Role of Soft and Hard The Role of Soft and Hard Information in the Pricing of Information in the Pricing of Assets and contract Design -- Assets and contract Design -- Evidence from ScreenplaysEvidence from Screenplays

SalesSalesWilliam N. Goetzmann Yale School of ManagementWilliam N. Goetzmann Yale School of Management

S. Abraham Ravid, Rutgers University and Cornell UniversityS. Abraham Ravid, Rutgers University and Cornell UniversityRon Sverdlove, Rutgers UniversityRon Sverdlove, Rutgers University

Vicente Pons-Sanz, Renaissance CapitalVicente Pons-Sanz, Renaissance Capital

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ObjectiveObjective

This one of very few papers outside the financial This one of very few papers outside the financial

intermediation industry, which shows how soft intermediation industry, which shows how soft

information affects asset pricing. information affects asset pricing.

Second, we look at empirical contract design in a Second, we look at empirical contract design in a

setting of pure risk sharing and information setting of pure risk sharing and information

asymmetries, with no effort component. asymmetries, with no effort component.

Third, we can compare ex-ante pricing of a screenplay Third, we can compare ex-ante pricing of a screenplay

to ex-post performance of resulting movies, an to ex-post performance of resulting movies, an

experiment which is difficult to perform in other experiment which is difficult to perform in other

industries. industries.

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Research DesignResearch Design

We look at sales of screenplays. We We look at sales of screenplays. We consider prices as well as contract design consider prices as well as contract design (cash upfront vs. a contingent contract). (cash upfront vs. a contingent contract). We test for “large” vs. “small” buyers.We test for “large” vs. “small” buyers.

The independent variables we use include The independent variables we use include the complexity and nature of the “pitch” the complexity and nature of the “pitch” which proxies for soft information, as well which proxies for soft information, as well as “hard information” variables on the as “hard information” variables on the screenwriter’s experience.screenwriter’s experience.

We include control variablesWe include control variables We also consider the performance of the We also consider the performance of the

resulting films.resulting films.

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Literature Review- Soft Information.Literature Review- Soft Information.There is a growing literature on the role of soft information in There is a growing literature on the role of soft information in organizations:organizations:The main theoretical focus is on how soft information affects The main theoretical focus is on how soft information affects organizational structure: See Laffont and Tirole (1997), Stein organizational structure: See Laffont and Tirole (1997), Stein (2002) Faure Grimaud et al. (2003) Baker et al. (1994);(2002) Faure Grimaud et al. (2003) Baker et al. (1994);

Important recent applications of the concept of soft information Important recent applications of the concept of soft information focus on the financial intermediation industry, where soft focus on the financial intermediation industry, where soft information is combined with hard information, inclduing information is combined with hard information, inclduing Petersen and Rajan (2002), Petersen (2004), Berger et al. Petersen and Rajan (2002), Petersen (2004), Berger et al. (2005) Liberti (2004) shows how soft information proxies in the (2005) Liberti (2004) shows how soft information proxies in the banking sector affect the price of working capital loans. Butler banking sector affect the price of working capital loans. Butler (2004) considers the pricing of municipal bond issues. Petersen (2004) considers the pricing of municipal bond issues. Petersen (2004) provides a conceptual survey.(2004) provides a conceptual survey.

Management studies include Uzzi (1999) and Uzzi and Gilespie Management studies include Uzzi (1999) and Uzzi and Gilespie (2002) who introduce related concepts, such as (2002) who introduce related concepts, such as “embeddedness” and duration and “multiplexity” of banking “embeddedness” and duration and “multiplexity” of banking relationship. relationship.

Cohen and Carruthers (2001) present an interesting historical Cohen and Carruthers (2001) present an interesting historical study. study.

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Literature Review- Contract Literature Review- Contract DesignDesign

A huge theoretical literature.A huge theoretical literature. Empirical Contract Design papers include Empirical Contract Design papers include

for example, Lerner and Merges, (1998) - for example, Lerner and Merges, (1998) - Bio-medical Industries; Gompers and Bio-medical Industries; Gompers and Lerner(1996) Kaplan and Stromberg Lerner(1996) Kaplan and Stromberg (2003), Bengtsson et al.,(2005)- Venture (2003), Bengtsson et al.,(2005)- Venture capital; Banerjee and Duflo (2000) – Indian capital; Banerjee and Duflo (2000) – Indian Software industries.Software industries.

In the movie industry- Chisholm (1997) In the movie industry- Chisholm (1997) and Eliashberg et al. (2007).and Eliashberg et al. (2007).

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Soft and Hard Information and the Film Soft and Hard Information and the Film IndustryIndustry

TheThe film industry is a mechanism for turning ideas into film industry is a mechanism for turning ideas into

profit. profit.

A major portion of the industry is devoted to the A major portion of the industry is devoted to the

solicitation, evaluation, screening and business solicitation, evaluation, screening and business

assessment of artistic projects. assessment of artistic projects.

Many of these projects begin as script concepts that Many of these projects begin as script concepts that

are read by agents, pitched to studio professionals, are read by agents, pitched to studio professionals,

reviewed within studio companies, discussed and reviewed within studio companies, discussed and

approved or rejected at meetings, optioned or approved or rejected at meetings, optioned or

purchased by studios through simple or contingent purchased by studios through simple or contingent

contracts, revised and re-written as part of the contracts, revised and re-written as part of the

production process and finallyproduction process and finally reviewed by industry reviewed by industry

participants for awards. participants for awards.

This process uses soft as well as hard information.This process uses soft as well as hard information.

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A Conceptual Model of Soft Information A Conceptual Model of Soft Information There is no universally accepted definition of soft There is no universally accepted definition of soft information.information.Some authors implicitly suggest that soft information is Some authors implicitly suggest that soft information is information that is difficult (costly) to communicate to information that is difficult (costly) to communicate to outsiders (See Stein (2002) and others).outsiders (See Stein (2002) and others).In this case, we can differentiate between soft and hard In this case, we can differentiate between soft and hard information by the cost of transmission. Also, if you “work information by the cost of transmission. Also, if you “work harder” you can make soft information “harder”.harder” you can make soft information “harder”.Soft information can also be defined as a non-numeric input Soft information can also be defined as a non-numeric input into a decision-making process, or information that is into a decision-making process, or information that is “communicated in text”(Petersen,2004).“communicated in text”(Petersen,2004).Soft Information can also be regarded as data for which Soft Information can also be regarded as data for which human cognition is required and can be interpreted human cognition is required and can be interpreted differently by different people.differently by different people.Our variables attempt to proxy for the existence of Our variables attempt to proxy for the existence of information that is hard to transmit and open to information that is hard to transmit and open to different interpretations by different people. We use different interpretations by different people. We use the number of words in the pitch and whether or not the number of words in the pitch and whether or not other films are mentioned, and the number of genres other films are mentioned, and the number of genres specified.specified.

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Examples:Examples: Short and sweet:Short and sweet: Greatest EscapesGreatest Escapes: Several 12 year old kids escape : Several 12 year old kids escape

from a camp from hell.from a camp from hell. On any given Saturday Remembering the Titans On any given Saturday Remembering the Titans

Gives me the Varsity Blues:Gives me the Varsity Blues: Spoof of football Spoof of football movies [Note that the title is longer than the logline.]movies [Note that the title is longer than the logline.]

Long and complex: Long and complex: Joe SomebodyJoe Somebody: “Corporate guy who is divorced and : “Corporate guy who is divorced and

at the end of his rope is beaten up and humiliated by at the end of his rope is beaten up and humiliated by a co-worker over a parking space. He confronts his a co-worker over a parking space. He confronts his fears and in the process comes to terms with what he fears and in the process comes to terms with what he wants out of life and ultimately falls in love again”.wants out of life and ultimately falls in love again”.

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Examples (continued):Examples (continued): Short with another Short with another

movie mentioned:movie mentioned: Act of treasonAct of treason: “In the : “In the

line of Fire” meets the line of Fire” meets the “body guard”.“body guard”.

Several GenresSeveral Genres:: Spoils of war; genre: Spoils of war; genre:

action adventure action adventure comedycomedy ; A newly ; A newly found treasure map found treasure map leads three soldiers to leads three soldiers to look for rewards just look for rewards just days before the Kuwait days before the Kuwait desert storm invasion. desert storm invasion. (a comedy???)(a comedy???)

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Large vs. SmallLarge vs. Small

Theoretical models (see Stein, 2002) Theoretical models (see Stein, 2002) suggest that large hierarcial suggest that large hierarcial organizations will shun soft information.organizations will shun soft information.

Empirical papers (Liberti, 2004, Berger Empirical papers (Liberti, 2004, Berger et al. 2005) suggest that this is indeed et al. 2005) suggest that this is indeed the case in the banking sector.the case in the banking sector.

We consider large studios vs. other We consider large studios vs. other buyers, and expect large studios to pay buyers, and expect large studios to pay more for “harder” screenplays.more for “harder” screenplays.

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Contingent contracts.Contingent contracts.

In equilibrium, a cash compensation In equilibrium, a cash compensation should be offered to a risk averse writer by should be offered to a risk averse writer by a multi-national conglomerate (no effort a multi-national conglomerate (no effort issues), approaching the “first best” a-la- issues), approaching the “first best” a-la- Holmstrom(1979).Holmstrom(1979).

However, consider the following example- However, consider the following example- Seller and buyer agree that if a screenplay Seller and buyer agree that if a screenplay

is produced it is worth 10,000 and if not, 0.is produced it is worth 10,000 and if not, 0. Seller thinks the probability is 0.5, buyer Seller thinks the probability is 0.5, buyer

0.1. 0.1. A cash contract will not work. A contract A cash contract will not work. A contract

contingent on production will. contingent on production will.

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Forward looking pricesForward looking prices

““Nobody knows anything” William Nobody knows anything” William Goldman (1983)- or efficient Goldman (1983)- or efficient markets?markets?

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DataDataThe 2003 Spec Screenplay Sales Directory, compiled The 2003 Spec Screenplay Sales Directory, compiled by Hollywoodsales.com, contains approximately six by Hollywoodsales.com, contains approximately six years of screenplays sales. The information provided years of screenplays sales. The information provided on each sale includes: title, pitch, genre, agent, on each sale includes: title, pitch, genre, agent, producer, date-of-sale, purchase price, and buyer and producer, date-of-sale, purchase price, and buyer and the type of contract; sometimes additional the type of contract; sometimes additional information,.information,.

We search IMDB for screenwriter information, in We search IMDB for screenwriter information, in particular, how many of his screenplays had been particular, how many of his screenplays had been produced; we also check IMDB and our data set for produced; we also check IMDB and our data set for first time screenwriters.first time screenwriters.

For each movie produced, we obtain its financial For each movie produced, we obtain its financial performance from Baseline services in California. performance from Baseline services in California. Specifically, we have the budget of each film, Specifically, we have the budget of each film, domestic revenues, international revenues as well as domestic revenues, international revenues as well as video and DVD revenues. video and DVD revenues.

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Data (2)Data (2)We obtain several additional control variables. We obtain several additional control variables.

MPAA ratings (in particular, family friendly ratings) were MPAA ratings (in particular, family friendly ratings) were significantly correlated with revenues and returns in a significantly correlated with revenues and returns in a number of previous papers . Our sample is somewhat number of previous papers . Our sample is somewhat skewed with no G rated films and too many PG-13 rated skewed with no G rated films and too many PG-13 rated films (see Ravid (1999), Ravid and Basuroy (2004), DeVany films (see Ravid (1999), Ravid and Basuroy (2004), DeVany and Walls (2002) Fee (2001) and Simonoff and Sparrow and Walls (2002) Fee (2001) and Simonoff and Sparrow (2000)).(2000)).

Stars can matter – we consider academy awards and Stars can matter – we consider academy awards and nominations and starmeter rankings from IMDB.pro..nominations and starmeter rankings from IMDB.pro..

Reviews- in its Crix pix column, Variety classifies reviews Reviews- in its Crix pix column, Variety classifies reviews as “pro”, “con”, and “mixed.” We use these classifications as “pro”, “con”, and “mixed.” We use these classifications to come up with measures of the quality of critical reviews. to come up with measures of the quality of critical reviews.

Finally, we look up each film’s release date (see Einav Finally, we look up each film’s release date (see Einav (2003)).(2003)).

Variables we createVariables we create::

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Variables: Soft Variables: Soft Information Information Proxies.Proxies.

The idea- to approximate The idea- to approximate complexity, difficulty of transmission complexity, difficulty of transmission

and “fuzziness”.and “fuzziness”. Soft Information – Script Complexity VariablesSoft Information – Script Complexity Variables Words LoglineWords Logline counts the number of words in the script logline (pitch).counts the number of words in the script logline (pitch).

Soft_WordSoft_Wordss equals 0 if the script logline contains less than 20 words; 1 if the equals 0 if the script logline contains less than 20 words; 1 if the script logline contains between 21 and 30 words; 2 if the script logline script logline contains between 21 and 30 words; 2 if the script logline contains between 31 and 40 words; and 3 if the script logline contains more contains between 31 and 40 words; and 3 if the script logline contains more than 40 words. (we tried several other cutoffs).than 40 words. (we tried several other cutoffs).

HighwordsHighwords equals 1 if the number of words in the logline is greater than 40. equals 1 if the number of words in the logline is greater than 40.

InfoDummyInfoDummy equals 1 if additional information about the script is available. equals 1 if additional information about the script is available. Transparent ScriptTransparent Script: We create a script complexity index, that equals 1 when : We create a script complexity index, that equals 1 when

the log line contains less than 20 words (i.e. Soft_Words equals 0), and the log line contains less than 20 words (i.e. Soft_Words equals 0), and additional information about the script is available (i.e. InfoDummy equals additional information about the script is available (i.e. InfoDummy equals 1). 1).

Soft_GenreSoft_Genre equals 1 if the qualified number of genres is 2 or greater, and 0 equals 1 if the qualified number of genres is 2 or greater, and 0 otherwise.otherwise.

Soft_LogmoviesSoft_Logmovies equals 1 if the scripts logline refers to any other movie, and equals 1 if the scripts logline refers to any other movie, and 0 otherwise.0 otherwise.

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““Hard Information” variablesHard Information” variables Number MoviesNumber Movies measures the number of scripts previously measures the number of scripts previously

sold by the script’s screenwriter. sold by the script’s screenwriter. Reputation MoviesReputation Movies takes the value 0 if the screenwriter takes the value 0 if the screenwriter

has not previously sold any script; 1 if the screenwriter has has not previously sold any script; 1 if the screenwriter has previously sold between 1 and 3 scripts; 2 if the screenwriter previously sold between 1 and 3 scripts; 2 if the screenwriter has previously sold between 4 and 10 scripts; and 3 if the has previously sold between 4 and 10 scripts; and 3 if the screenwriter has previously sold more than 10 scripts.screenwriter has previously sold more than 10 scripts.

First MovieFirst Movie takes the value one if the screenwriter has not takes the value one if the screenwriter has not previously sold any script, and 0 otherwise. previously sold any script, and 0 otherwise.

Nominated Oscar (Awarded Oscar)Nominated Oscar (Awarded Oscar) takes the value 1 if takes the value 1 if the screenwriter has been previously nominated to an Oscar. the screenwriter has been previously nominated to an Oscar.

Any Nomination (Any Award)Any Nomination (Any Award) takes the value 1 if the takes the value 1 if the screenwriter has been previously nominated to an award in screenwriter has been previously nominated to an award in the following festivals: Oscars, Golden Globes, British the following festivals: Oscars, Golden Globes, British Academy Awards, Emmy Award, European Film Award, Academy Awards, Emmy Award, European Film Award, Cannes, Sundance, Toronto, Berlin.Cannes, Sundance, Toronto, Berlin.

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Prices and soft informationPrices and soft information

N Price Cont Mean Median Mean

SoftWords 0 296 684 468 0.60141 214 645 468 0.60282 139 609 520 0.63313 102 624 298 0.7157

p-value 0.0441 ** 0.1963

InfoDummy 0 508 623 468 0.62991 269 697 484 0.5911

p-value 0.3368 0.0001 *** 0.2900

TransparentScript 0 651 622 460 0.62521 100 836 497 0.6100

p-value 0.0548 * 0.0267 ** 0.7707

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Screenwriter’s experienceScreenwriter’s experience

N Price Cont Mean Median Mean

ReputationMovies 0 460 475 303 0.62391 219 718 520 0.60732 77 1114 565 0.66233 21 2019 1100 0.3810

p-value 0.0001 *** 0.1209

FirstMovie 1 460 475 303 0.62390 317 900 550 0.6057

p-value 0.0001 *** 0.0001 *** 0.6080

NomOscar 0 764 628 468 0.61911 13 1890 878 0.4615

p-value 0.0001 *** 0.0403 ** 0.2456

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Small vs. Large OrganizationsSmall vs. Large Organizations

Panel H: Hard and Soft Information: Large and Small Buyer Values

N Mean Price Large-Small Large/Small Large Small Large Small Difference Ratio

High Hard, Low Soft 60 106 1214 771 443 ** 1.574

Low Hard, High Soft 69 168 542 471 71 1.151

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Price (table 2)Price (table 2)

NumberMovies 53.200 ***(6.7400)

ReputationMovies 341.494 ***(7.1400)

NomOscar 815.258 ***(2.8900)

AnyNom 683.390 ***(4.2100)

TransparentScript 143.939 223.033 **(1.3500) (2.1000)

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Price- contingent contract, Price- contingent contract, movie not made (table 4)movie not made (table 4)

NumberMovies 47.508 ***(9.1600)

ReputationMovies

FirstMovie * LogWords

SoftWords

InfoDummy

FirstMovie * SoftGenres

SoftLogMovies 33.431(0.5400)

HighWords -73.684 *(-1.6700)

FirstMovie * HighWords

LargeStudio 78.526 **(2.4300)

Action

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The Probability of a contingent The Probability of a contingent contract (table 5)contract (table 5)

NumberMovies -0.020 *(0.0662)

FirstMovie

TransparentScript 0.036(0.7941)

SoftLogMovies

SoftGenres -0.053(0.5856)

HighWords 0.312 **(0.0303)

LargeStudio 0.073(0.4398)

Action

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Movies by screenwriter (not Movies by screenwriter (not reported)reported)

FirstMovie = 0 (N = 76) FirstMovie =1 (N = 66)

Average St. Dev. Average St. Dev. T-test

Negative Costs 36300 25100 29400 23400 0.0942Dom. Print & Advertising Costs 25200 10600 23800 13100 0.4769Domestic Gross 41500 44700 35100 39300 0.3645Domestic Rentals 22100 23800 18500 20800 0.3423Foreign Gross 30100 47600 24200 36600 0.4277Foreign Rentals 14300 22500 11600 17700 0.4431Domestic Video Gross 22400 16200 19200 19100 0.2968Domestic DVD Gross 14000 27500 8380 13400 0.1462Total Revenues 80500 124000 65300 83700 0.2588Rate1 3.69 3.44 3.28 3.42 0.5051Rate2 1.70 1.21 1.46 1.10 0.2590

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Total RevenuesTotal Revenues

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Rate of return regressionsRate of return regressions

Price 0.0003 *** 0.0004 ***(3.0600) (3.6100)

Ln Budget 1 -0.0760(-0.3900)

Ln Budget 2 -0.1150(-0.4800)

PG 0.4613 (0.8123)(0.6200) (1.1400)

PG-13 0.6794 ** 0.5302 *(2.4200) (1.8800)

Positive Review Fraction 1.6092 **(2.0400)

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Results and conclusions:Results and conclusions:

Our analysis supports the notion that hard information as well as soft Our analysis supports the notion that hard information as well as soft

information are priced in screenplays sales. information are priced in screenplays sales.

Soft information lowers the price. In a market where distance and Soft information lowers the price. In a market where distance and

relationships cannot be applied differentially, soft information is relationships cannot be applied differentially, soft information is

viewed as a risk factor. Reputation increases prices paid.viewed as a risk factor. Reputation increases prices paid.

Large studios pay more, but seem to shun soft information, as expected.Large studios pay more, but seem to shun soft information, as expected.

Even in the absence of effort incentives, we do not observe “first best” risk Even in the absence of effort incentives, we do not observe “first best” risk

sharing. “softer” screenplays and less experienced writers are likely to sell sharing. “softer” screenplays and less experienced writers are likely to sell

as contingent contracts.as contingent contracts.

Prices paid for screenplays are correlated with the eventual success of the Prices paid for screenplays are correlated with the eventual success of the

movies produced. Somebody knows something (contrary to William movies produced. Somebody knows something (contrary to William

Goldman’s suggestion)Goldman’s suggestion)