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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.

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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)

iiii

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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