what makes a blockbuster? peculiarities of ukraine
DESCRIPTION
This study is first economic research applied to Post-Soviet countries` motion picture industry. Time-series and cross-sectional analysis were applied to weekend box office of Ukraine, Commonwealth of Independent States and Poland for 2007 – 2010 years. Results support blockbuster theory and show good economic potential for locally produced moviesTRANSCRIPT
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What makes a blockbuster?
Peculiarities of Ukraine
Yevgen Nasadyuk
June 17, 2011
Kyiv School of Economics
Content
Motivation
Literature review
Methodology
Data
Results
Conclusions
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Motivation
Specific market structure of motion pictures industry in
Ukraine;
Absence of previous research of Post-Soviet movie
markets.
4
Literature review
One of the earliest theory (Litman, 1983) maintains that
motion picture success is dependent on three decision-
making areas:
the creative sphere;
the scheduling and release pattern;
the marketing effort.
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Literature review
Blockbuster hypothesis (DeVany 2004, “Hollywood Economics”): big budget leads to higher box office.
Also positive effect of: a presence of star-actors, sequel, animated and action genres on movie revenue.
Bagella and Becchetti (1999): Italian comedies are most successful among locally produced movies.
Wall (2009): high return to information for Thailand motion picture market. Dependent variables: opening weekend box office shares and movie life-time.
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My contribution
This study extend existing literature in few ways:
for the first time provides economic approach of motion pictures success for Post-Communist countries examining dependence of total movie box office on its budget, release date, genre and country of production.
applies time series dynamics for weekend box offices
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The methodology
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Null-hypothesis: higher budget higher box offices.
Model: modified DeVany (2004)
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ii
GenreSequelCountry
orStarDirectStarActorBudgetvenue
][
logRelog
65
4321
For autoregression model we use movie weekend’s
box office shares:
AR model:
Model to check date effect:
iitit SaaS 110
iiit Datevenue ][Relog 0
K
k
kt
itit
BO
BOS
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The methodology
Data
Input data contains 11062 records of weekend box office for 1413 released
movies from 2007 to 2010 year in Ukraine, Poland and CIS. Sources of data
are public available movies’ databases http://boxofficemojo.com,
http://kinopoisk.ru, http://pisf.pl
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Table 1. Aggregated statistics of weekend records
Poland CIS Ukraine Total
Total records 2,247 6,460 2,355 11,062
Movies 587 1,239 566 1,413
Average duration 3.81 4.87 3.91 4.45
Weekend average box office 190,054 351,691 76,919 260362
Average box office share 0.08 0.031 0.086 0.053
Average screens 74.7 107.4 35.4 85.9
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Data
Sample for OLS regression:
247 motion pictures (more than 50% of total box office)
114 actors / actresses in 144 (58%) movies
101 directors in 115 (46%) movies.
a) Box office revenue b) Budget
Figure 1. Total revenue and budget distribution across motion pictures
0
10000000
20000000
30000000
40000000
50000000
60000000
70000000
80000000
0 50 100 150 200 250 300
Total box ofice
Rank 0
50000000
100000000
150000000
200000000
250000000
300000000
350000000
0 50 100 150 200 250 300
Budget
Rank
Data
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Table 2. Genre statistics
Data
Poland CIS Ukraine
Action 17 23 21
Adventure 3 5 3
Crime 0 3 1
Thriller 9 12 10
War 3 3 4
Western 0 1 1
Horror 12 14 9
Action 44 61 49
Animation 18 23 20
Documentary 0 1 0
Sci-Fi 7 9 6
Period 4 3 3
Sci-Fi 11 13 9
Drama 13 24 13
Family 8 7 7
Fantasy 13 16 14
Melodrama 1 6 4
Music 3 3 3
Romantic 10 9 11
Drama 48 65 52
Comedy 15 30 20
Total 136 192 150
Data
Figure 2. Distribution of box offices across movies producers
Results
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Poland CIS Ukraine
VARIABLES Share of
box office
Share of box
office
Share of
box office
Lag of BO share 0.69*** 0.48*** 0.46***
(0.007) (0.003) (0.01)
Constant -0.001 -0.001*** 0.004**
(0.001) (0.0004) (0.002)
Observations 1,510 4,456 1,461
R-squared 0.84 0.78 0.55
Table 4. Result of autoregression model
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Table 5. Month effect estimation
Results
Poland CIS Ukraine
VARIABLES LogRevenue LogRevenue LogRevenue
January 0.78*** 0.96*** 0.67***
February 1.01*** 0.93*** 0.19
March 0.41*** 0.76*** 0.23
April 0.18 0.58*** 0.12
May 0.38*** 0.20 -0.04
June 0.09 0.35** 0.30
July -0.22* 0.17 0.22
August 0.30** 0.36** -0.04
September 0.43*** 0.57*** -0.04
October 0.44*** 0.32** 0.12
November 0.49*** 0.18 0.11
Constant 10.98*** 9.53*** 9.66***
Observations 2,247 6,460 2,354
R-squared 0.04 0.01 0.01
Results
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Table 6. Regression with aggregated genres and country of production
Poland CIS Ukraine
VARIABLES Logarithm of
total revenue
Logarithm of
total revenue
Logarithm of total
revenue
Log of budget 0.48*** 1.03*** 0.94***
(0.12) (0.09) (0.1)
Sequel 0.72** 0.68** 0.66***
(0.29) (0.27) (0.21)
Star director 0.22 -0.01 -0.03
(0.29) (0.28) (0.24)
Star actor / actress 0.32 0.24 0.3
(0.38) (0.36) (0.32)
Animation 1.38*** 0.04 0.09
(0.38) (0.35) (0.29)
Sci-Fi 0.6 0.11 0.32
(0.44) (0.43) (0.37)
Drama 0.41 -0.29 0.02
(0.27) (0.24) (0.2)
Comedy 0.1 0.02 0.62**
(0.39) (0.31) (0.27)
Poland CIS Ukraine
VARIABLES Logarithm of
total revenue
Logarithm of
total revenue
Logarithm of
total revenue
US 2.35* 2.52*** 0.14
(1.33) (0.81) (1.02)
Russia 0 5.03*** 2.58**
(0) (0.87) (1.0)
Poland 4.89*** 0 -2.67*
(1.43) (0) (1.46)
Europe 1.06 1.7* -0.63
(1.38) (0.88) (1.08)
Ukraine 0 0 0.18
(0) (0) (1.47)
Constant 1.48 -6.44*** -4.92**
(2.58) (1.79) (2.11)
Observations 136 192 150
R-squared 0.44 0.58 0.57
Results Table 6. Regression with aggregated genres and country of production - Continued
Conclusions
Blockbuster hypothesis that bigger budget increases revenue, is not rejected for all countries (similar to DeVany, McKenzie)
Weekend box office strongly depend on success of previous weekend (DeVany, Litman, Collins et al.)
Positive effect of local produced movies (similar to Wall, Bagella and Becchetti, Zarin-Nejadan and Criado)
Effect of sequel motion picture is positive and significant for all sample countries. “Animation” genre is significant for Poland. And “Comedy” is significant for Ukraine.
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Conclusions
Main peculiarities of Ukrainian movie market:
i. faster decreasing of weekend box office revenue
ii. small seasonal effect.
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Thank you for attention!
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