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Entertainment and Media: Markets and Economics

Entertainment and Media: Markets and Economics. Uncertainty and the Winner's Curse. 1/35. Uncertainty and Information. RandomnessDo movies fail randomly? Chaos, complexity and movie starsModeling randomness; probabilityVariance and the winner's curse. 2/35. More Losers than Winners. Movie succ

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Entertainment and Media: Markets and Economics

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    1. Entertainment and Media: Markets and Economics Professor William Greene

    2. Entertainment and Media: Markets and Economics Uncertainty and the Winner’s Curse

    3. Uncertainty and Information Randomness Do movies fail randomly? Chaos, complexity and movie stars Modeling randomness; probability Variance and the winner’s curse

    4. More Losers than Winners Movie success for the studios The numerical majority of movies ‘lose’ money Based on Hollywood Accounting Not really when foreign box, video and TV are counted

    5. Predictable Failure - Gigli

    6. Forrest Gump “Lost Money” Forrest Gump (1994) (Paramount Pictures) US Box Office $330M Foreign Box Office $350M Total, About $830M Soundtracks, etc. $150M Net profit -$ 62M (!) A disappearing act? U.S. Box ? 50% to Exhibitors (Theaters) Paramount Receives Approx $191M Distribution “Fee” = 32% $ 62M Distribution Cost $ 67M (Advt., Prints, Screening, etc.) Advt. Overhead $ 7M (10% of Distribution Cost) Production “Negative” Cost $112M (Tom Hanks, Robert Zemekis, $20M (8% of GROSS, each) Studio Overhead $15M Interest on Negative Costs $ 6M Net Profits from the Project -$62M Winston Groom, Author 19% of NET = 0 Eric Roth, Screenwriter 19% of NET = 0 Coming to America (1988) – The Art Buchwald Case

    8. Entertainment and Media: Markets and Economics Reasons for Failure in the Movie Business

    9. Producing Flops (R.Caves) Sequence of small failures Multiple stage production, large SUNK cost at each Each stage is sensibly funded. Failure comes at the end of the chain. By then, the costs are sunk.

    10. Growing a Ten Ton Turkey In prospect, 5 stages in sequence: 1 2 3 4 5 Release Costs: 20 20 20 20 20 E[Cost] = 100 Revenue 0 0 0 0 0 100 E[Revenue] = 100 After a disappointing first stage, E[R] falls by 10% Looking forward, costs needed to complete the project. Costs: {20} 20 20 20 20 E[Cost] = 80 {sunk} E[Revenue] = 90 Ex post: Total cost 100M, Total Revenue if expectations are met, 90. Note the crucial role of SUNK, nonrecoverable costs (i.e., the output of those costs cannot be sold on any market)

    11. Art for Art’s Sake (The Alamo) Production function view of inputs – indifference to final product Creative production view – “the masterpiece” (e.g., directors) Incentives – internalized. A problem of moral hazard: Separation of decision from costs of those decisions. (Principals and agents) Noteworthy examples: Bonfire of the Vanities Heaven’s Gate Gigli (‘Production’ cost $25M(J+B) + $29M+ Marketing $20M Box Office: < 6M (J Lo/Ben star vehicle. Which problem sank this film?)

    12. Ishtar!

    13. Art for Art’s Sake

    14. Opening Week Perspective

    15. Unpredictable Failure Wisdom Audiences and box office are uncertain Stars have power to make movies succeed. [Helena (Kim Basinger) gets boxed.] Better wisdom Movies are “complex systems” Complexity mixes order and chaos Even with stars, movies are unpredictable

    16. Order and Chaos Audience behavior Pure randomness ? movies do equally well (rolls of the dice) Information cascades ? chaotic behavior and herding Actual behavior embodies both: Complex system

    17. Dynamic Movie Systems Dynamic “systems” evolve through time

    18. Stable and Chaotic Systems Stable systems Not necessarily predictable, but regularly behaved Don’t depend very much on where the process starts Chaotic systems Totally unpredictable Depend crucially on where the process starts Trivial differences in the starting point produces wild differences and oscillations in the state variables. Seems to characterize big movies.

    19. End Results of Chaos Power law distributions of rewards This is a winner take all market.

    20. Power law outcomes are unpredictable Very few movies show a positive “profit”

    21. Strategies for Dealing with the Risk of Failure in the Movies Portfolio? Not if the previous analysis is correct. Hire a really big star? Movie as brand name? (The Matrix, Harry Potter, Shrek, James Bond series …) Profit Sharing Contracts: This reallocates risk; it does nothing to reduce it.

    22. Movie Riddles (S. Ravid) Making Movies is hugely risky, and almost all of them lose money. Why do they keep making movies? Nobody knows. Why do they keep paying megabucks for big stars? Why are so few G and so many R movies made? Why do they keep making big “event” movies (like THE ALAMO)? Strategies for avoiding risk.

    23. Regression Results

    24. Risk Aversion? Movie makers are risk averse. Studios are public corporations Stock holders can be risk averse, corporations should not be. An incompatibility between “agents” (risk averse movie makers) and “principals” (risk loving stockholders).

    25. Star Power Natural response by movie makers to avoid blame for failure. Failure occurs for many reasons and no reason Conventional wisdom – stars make a movie Audiences make the movie. Current trend (somewhat) away from stars.

    26. The Star’s the Thing? DeVany and Walls, et. al. Stars do not guarantee success. On average (not always) stars do keep movies out of the bottom. The conclusion is uncertain: Kim Basinger – Boxing Helena Tom Hanks – the Da Vinci Code, The Lost Symbol

    27. Movie Star Economics “Movies made by Viacom and [Cruise’s] production company earned more than $2.5 billion at the box office.” [They] are not worth the expense. Ravid: Regressions. Returns not driven by stars … Nobody knows…

    28. Fading Star Power Star Driven Films in Share of Top 25 Grossing Films 1987 44% 1997 60% 2007 13% Other Drivers Franchise (Batman, Harry Potter, Bourne) Awards Buzz comedies/musicals Media/grassroots Special Effects Creator

    29. Car Chases? Why so much violence (and sex) R rated movies have lower average box than G and PG. Sex doesn’t sell. Violence or violence and sex do OK on average, but have LOWER VARIANCE. Risk avoidance. S&V are rarely major flops. Low variance, so AGENTS keep their jobs.

    30. Really Big Movies Titanic, Pearl Harbor, Alamo Big budgets ? lower variance (Superman Returns: $260 million) Big stars make big budgets

    31. Traditional Movie Success Model

    32. Something New: Internet Buzz

    33. Internet Buzzes John Carter

    34. Domestic Box Office Receipts: Place Your Bets

    35. Entertainment and Media: Markets and Economics The Winner’s Curse

    36. The Winner’s Curse Bidding situation (sealed bid auctions) Publishing (Jack Welch’s book) Offshore oil leases Broadcast frequencies Baseball, football, basketball, hockey players Art (The masterpiece effect) General Result: High bidder bids over the value of the property – Winner’s regret.

    37. The Winner’s Curse Common value, uncertainty in the value Bidders have private estimates Correlated because of some public information Based on some private and some public information (oil and gas leases, spectrum for cellular) Estimates may be unbiased, but still randomly distributed – bidders have different information Winner might just be the most optimistic but Expected maximum valuation > true value

    38. The Winner’s Curse

    39. Understanding The Winner’s Curse Assumptions Property has a true value: ? Bidders combine private and public information to form an estimate of ? N bids submitted, B1,…,BN Bidders do not collude Bids are randomly distributed around the true value Bids are unbiased – on average right, but some higher than ? and some lower Maximum bid wins the auction

    40. Possible Examples of the Winner’s Curse Bill Clinton: Between Hope and History: 70% returned Johnnie Cochrane: Journey to Justice: $3.5M advance, 350,000 of 650,000 unsold Whoopie Goldberg: $6M advance, total failure (?) Jack Welch $6M. Hillary Clinton, $8M Why? Trade publishers integrated into large publishing firms; organizational complexity and separation of decisions from ultimate consequences (corporate levels) Incentives of publishers. Signalling value of advances to celebrity authors and large first printings. Market characteristic – winner take all markets, most entrants fail, with or without a celebrity author.

    41. Winner’s Curse?

    42. Strategy for Avoiding the Curse Learn N, f(.), ? through experience and research Scale back bids Collude: Professional sports Does it work? What else is needed? Assumptions about how other players behave.

    43. Entertainment and Media: Markets and Economics Uncertainty in success of large multistage projects. Probable elements of failure in some bidding situations.

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