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Movies Josh Finkelstein John Hottinger Jenny Yaillen Xiang Huang Edward Han Rory MacDonald Tyronne Martin.

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Presentation on theme: "Movies Josh Finkelstein John Hottinger Jenny Yaillen Xiang Huang Edward Han Rory MacDonald Tyronne Martin."— Presentation transcript:

1 Movies Josh Finkelstein John Hottinger Jenny Yaillen Xiang Huang Edward Han Rory MacDonald Tyronne Martin

2 Intro For an economist the study of econometrics, or the statistical analyzing of economic data, is extremely important in understanding economic phenomena. By analyzing sets of past economic data, economists hope to be able to discover trends and tendencies that can be used to predict future economic events with greater accuracy.Cinema has strongly influenced society since its inception, not only socially but economically. It is not uncommon for modern movies to be produced at the cost of tens of million dollars, and to achieve gross profits many times that. With figures as impressive as these it is clear that movies make a discernable impact on the economy. A clearer understanding of what factors influence the gross profit generated by movies is vital to predicting the impact they will have on the economy.

3 What we are studying? For this study fifty high popularity movies created within the past sixty years were selected to be analyzed. The aspects of the movies that were studied were the rating, budget, domestic gross, length, viewer score, critic score and profit. These variables were then regressed using statistical analysis to determine important relationships between variables, and their relation to the revenue generated by the movies.

4 Variables – Rating (R, PG-13, PG, G) – Production Budget – Gross (domestically only) – Length – Viewer Rating (Rotten Tomatoes) – Critic Rating (Rotten Tomatoes) – Profit (Gross-Budget)

5 Why we are studying it? Study past economic data to predict future events Better understand factors that influence economic impact of movies Understanding of past movies allow us to predict gross/budget of future movies

6 On average, what type of movie (ie R, PG-13, PG) has the highest gross and budget (in millions)???

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8 Does there seem to be a trend in what type of movies are being produced?

9 Gone with the Wind1939G Jaws1975PG Grease1978PG Halloween1978R Raiders of the Lost Ark1981PG Terminator1984R Aliens1986R Indiana Jones and the Last Crusade1989PG-13 Ghost1990PG-13 Schindler's List1993R Forrest Gump1994PG-13 Pulp Fiction1994R True Lies1994R Braveheart1995R The American President1995PG-13 Executive Decision1996R Independence Day1996PG-13 Multiplicity1996PG-13 Scream1996R As Good As It Gets1997PG-13 Chasing Amy1997R Contact1997PG Dante's Peak1997PG-13 Good Will Hunting1997R I Know What You Did Last Summer1997R Men in Black1997PG-13 Speed 2:Cruise Control1997PG-13 The Fifth Element1997PG-13 The Game1997R Titanic1997PG-13 Volcano1997PG-13 Armageddon1998PG-13 Deep Impact1998PG-13 Hard Rain1998R Saving Private ryan1998R The Man in the Iron Mask1998PG-13 Star Wars Ep. I: The Phantom Menace1999PG How the Grinch Stole Christmas2000PG Harry Potter and the Sorcerer's Stone2001PG Spider-Man2002PG-13 The Lord of the Rings: The Return of the King2003PG-13 Shrek 22004PG Star Wars Ep. III: Revenge of the Sith2005PG-13 Pirates of the Caribbean: Dead Man's Chest2006PG-13 Spider-Man 32007PG-13 The Dark Knight2008PG-13 Avatar2009PG-13 Paranormal Activity2009R Toy Story 32010G Robin Hood2010PG-13

10 Does Critic Rating Effect Gross?

11 Dependent Variable: LNGROSS Method: Least Squares Date: 11/27/10 Time: 15:02 Sample: 1 50 Included observations: 50 VariableCoefficientStd. Errort-StatisticProb. CRITICRATING C R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Akaike info criterion Sum squared resid Schwarz criterion Log likelihood F-statistic Durbin-Watson stat Prob(F-statistic) Took log

12 Is There a Relationship Between Viewer Rating and Gross? Dependent Variable: LNGROSS Method: Least Squares Date: 11/27/10 Time: 15:08 Sample: 1 50 Included observations: 50 VariableCoefficientStd. Errort-StatisticProb. VIEWERRATING C R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Akaike info criterion Sum squared resid Schwarz criterion Log likelihood F-statistic Durbin-Watson stat Prob(F-statistic)

13 Is there a relationship between the length of a movie and it’s gross??

14 Dependent Variable: LNGROSS Method: Least Squares Date: 11/27/10 Time: 15:06 Sample: 1 50 Included observations: 50 VariableCoefficientStd. Errort-StatisticProb. LENGTH C R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Akaike info criterion Sum squared resid Schwarz criterion Log likelihood F-statistic Durbin-Watson stat Prob(F-statistic)

15 Is there a relationship between critic and viewer ratings?

16 Dependent Variable: CRITICRATING Method: Least Squares Date: 11/24/10 Time: 00:05 Sample: 1 50 Included observations: 50 VariableCoefficientStd. Errort-StatisticProb. VIEWERRATING C R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Akaike info criterion Sum squared resid Schwarz criterion Log likelihood F-statistic Durbin-Watson stat Prob(F-statistic)

17 Is there a relationship between profit and viewer rating?

18 Dependent Variable: PROFIT Method: Least Squares Date: 11/24/10 Time: 00:01 Sample: 1 50 Included observations: 50 VariableCoefficientStd. Errort-StatisticProb. VIEWERRATING C R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Akaike info criterion Sum squared resid Schwarz criterion Log likelihood F-statistic Durbin-Watson stat Prob(F-statistic) PROFIT = *VIEWERRATING

19 Is there a relationship between the profit of a movie (gross-budget) and the rating received from critics?

20 Dependent Variable: PROFIT Method: Least Squares Date: 11/23/10 Time: 23:59 Sample: 1 50 Included observations: 50 VariableCoefficientStd. Errort-StatisticProb. CRITICRATING C R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Akaike info criterion Sum squared resid Schwarz criterion Log likelihood F-statistic Durbin-Watson stat Prob(F-statistic)

21 Dependent Variable: PROFIT Method: Least Squares Date: 11/27/10 Time: 15:18 Sample: 1 50 Included observations: 50 VariableCoefficientStd. Errort-StatisticProb. CRITICRATING R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Akaike info criterion Sum squared resid Schwarz criterion Log likelihood Durbin-Watson stat DROP CONSTANT

22 Is there relationship between how much a movie makes (profit=gross- budget) and it’s length?

23 Dependent Variable: PROFIT Method: Least Squares Date: 11/24/10 Time: 00:13 Sample: 1 50 Included observations: 50 VariableCoefficientStd. Errort-StatisticProb. LENGTH C R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Akaike info criterion Sum squared resid Schwarz criterion Log likelihood F-statistic Durbin-Watson stat Prob(F-statistic) PROFIT = *LENGTH

24 Dependent Variable: PROFIT Method: Least Squares Date: 11/27/10 Time: 15:21 Sample: 1 50 Included observations: 50 VariableCoefficientStd. Errort-StatisticProb. LENGTH R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Akaike info criterion Sum squared resid Schwarz criterion Log likelihood Durbin-Watson stat DROPPED THE CONSTANT

25 Making lngross regression more significant… Dependent Variable: LNGROSS Method: Least Squares Date: 11/27/10 Time: 15:09 Sample: 1 50 Included observations: 50 VariableCoefficientStd. Errort-StatisticProb. CRITICRATING VIEWERRATING LENGTH C R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Akaike info criterion Sum squared resid Schwarz criterion Log likelihood F-statistic Durbin-Watson stat Prob(F-statistic) Dependent Variable: LNGROSS Method: Least Squares Date: 11/30/10 Time: 11:46 Sample: 1 50 Included observations: 50 VariableCoefficientStd. Errort-StatisticProb. CRITICRATING LENGTH C R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Akaike info criterion Sum squared resid Schwarz criterion Log likelihood F-statistic Durbin-Watson stat Prob(F-statistic)

26 Dependent Variable: LNGROSS Method: Least Squares Date: 11/30/10 Time: 11:39 Sample: 1 50 Included observations: 50 VariableCoefficientStd. Errort-StatisticProb. R LENGTH CRITICRATING C R-squared Mean dependent var Adjusted R-squared S.D. dependent var S.E. of regression Akaike info criterion Sum squared resid Schwarz criterion Log likelihood F-statistic Durbin-Watson stat Prob(F-statistic) Final lngross regression…..

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28 Conclusion The lower the rating (R, PG-13)=higher gross Higher critic rating=higher gross/profit Higher viewer rating=higher gross/profit Critic rating and viewer rating=correlated By taking some of the most significant relationships we found we were able to create our final significant and correlated lngross regression


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