Seppo Suominen Essays on cultural economics


Essay 1: Consumption of Motion Picture Art - Critics´ reviews and ticket price in explaining movie admissions



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1.1Essay 1: Consumption of Motion Picture Art - Critics´ reviews and ticket price in explaining movie admissions



The first essay considers movie attendance in Finland in 2003 explaining the number of spectators of the 20 most popular films in each week. The total number of films on distribution was 225 but with only 177 premieres. The aggregate attendance in 2003 was roughly 7.7 million and the top 10 got roughly 42 % of the spectators. Since both the weekly (time series) and movie specific (cross-section) variation is substantial, conventional regression methods are unsuitable. A panel data analysis enables regression analysis with both time-series and cross-sectional dimension.
In 2003 the average duration of movie runs in Finland was four months for the top 10 films and roughly one month for the median film in respect of the spectator number. Hence, spectators have had enough time to reveal the necessary information on the quality of the film from various sources. The essay studies the role of word-of-mouth and critical reviews in explaining movie attendance. Critical reviews are published in the weekly magazine supplement ‘Nyt’ for the newspaper that has the largest circulation in Finland, Helsingin Sanomat. World-of-mouth is measured by the previous week’s attendance figure at the cinemas in Helsinki. Since more than a fourth of young audience (age-group: 15-24) are heavy users and since they read less newspapers than older citizens in Finland, the role of critics review is probably lower than the role of word-of-mouth. Consumers in general rely more on the word-of-mouth than on other forms of information (Viljakainen, Bäck and Lindqvist 2008, 25). The first essay verifies that when the world-of-mouth is taken into account, the critics review is a significant variable to explain movie attendance. Several experiments with different explanatory variables are presented and they all reveal that the critical reviews do explain movie attendance. Since admission figures are typically the highest during the first weeks, a variable “weeks since released” is used to control this peak. The analysis shows that it is significant, as well as the price variable. The price elasticity of weekly movie admission is roughly -1 if only critically reviewed films are considered which shows some monopoly pricing potential. Panel data analysis also indicates that the fixed effects model is the most suitable for explaining weekly movie admissions in Finland in 2003.

An earlier version of the essay is published in The Finnish Journal of Business Economics 3/2011.



1.2Essay 2: Demand for ice hockey, the factors explaining attendance of ice hockey games in Finland

The second essay studies the ice hockey match attendance during the regular season 2007 – 2008 in Finland. The ice hockey league, ‘SM-liiga’ is the most important live cultural event or series of cultural events in terms of attendance per event. Yearly movies attendance is three times bigger compared with the ice hockey matches but ice hockey is by far the most popular live event. The total attendance was 1,964,626 i.e. 5,012 per match excluding play-off matches in March and April as done in this research. Ice hockey match has big uncertain component also compared with the opera and theatre where there is a manuscript to follow. The home team might win or lose the match depending on the quality of the team and the visitor. Potentially the attendence to ice hockey game could be sensitive to the ticket prices and to the seasonal variation and team performance. The Finnish data on the recent International Social Survey Programme (ISSP 2007) reveals that almost 40 % of the population never goes to see a sports activity (ice hockey, football, athletics, motor racing etc.), less than 8 % attends several times a month and the rest (i.e. more than 50 %) occasionally. The same survey also shows that physical exercise (active sport consumption) is more common than passive sport consumption (table 1: Sports consumption in Finland 2007).



Table 1: Sports consumption in Finland 2007




Daily

Several times a week

Several times a month

Occasionally

Never

Total, n

Passive sports

How often do you attend a sports activity?

4 (0.3%)

17 (1.3%)

82 (6.2%)

691 (52.3%)

526 (39.8%)

1320 (100%)

How often do you attend a sports activity? (Female)

1 (0.1%)

5 (0.7%)

38 (5.1%)

327 (44.2%)

369 (49.9%)

740 100%)

How often do you attend a sports activity? (Male)

3 (0.5%)

12 (2.1%)

43 (7.6%)

358 (63.3%)

150 (26.5%)

566 100%)

Active sports

How often do you exercise sports?

301 (22.6%)

546 (41.0%)

272 (20.5%)

183 (13.8%)

28 (2.1%)

1330 100%)

How often do you exercise sports? (Female)

189 (25.5%)

308 (41.5%)

144 (19.4%)

92 (12.4%)

9 (1.2%)

742 100%)

How often do you exercise sports? (Male)

106 (18.5%)

230 (40.1%)

127 (22.2%)

91 (15.9%)

19 (3.3%)

573 100%)

Source: ISSP 2007. Observations n = 1354. Own calculations.

Active and passive (attendance) sports consumption are slightly positively correlated (Kendall’s τ = 0,054, n = 1314, sig. = 0,028). There is also a negative relationship between age and passive sports consumption (Spearman’s ρ = -0,182, n = 1265, sig. = 0,000). For female the negative relationship is somewhat stronger (Spearman’s ρ = -0,193, n = 724, sig. = 0,000) than for male (Spearman’s ρ = -0,179, n = 540, sig. = 0,000)4.



Another survey (Liikuntatutkimus 2005-2006, Sport Survey: Adult Population) on adult population sport consumption – both active and passive – in Finland was carried out a few years ago5. The sample size was 5510. Here, 44% of surveyed responded that they had not attended any sports event between February 2005 and January 2006. Roughly, the results are in line with the ISSP 2007 survey. The most popular sports in terms of attendance were ice hockey (25.5%), football (16.9%), athletics (10.6%), skiing (6.5%) and Finnish rule baseball (5%). The largest positive correlation is between ice hockey and football attendance. Attendance and income level (8 categories from the lowest to the highest) are not correlated (not reported here).

Table 1 Attendance popularity and correlation among adult population in Finland. 2005-2006.




Popularity

Ice Hockey

Football

Athletics

Skiing

F Rule Baseball

Ice Hockey

25.5%

F: 14.6%

M: 36.4%

1













Football

16.9%

F: 11.0%

M: 22.8%

0.323 (0.000)

F: 0.353 (0.000)

M:0.193(0.000)

1










Athletics

10.6%

F: 9.9%

M: 11.3%

0.093 (0.000)

F: 0.133 (0.000)

M: 0.031 (0.108)

0.123 (0.000)

F: 0.156 (0.000)

M:0.074 (0.000)

1







Skiing

6.5%

F: 6.3%

M: 6.6%

0.009 (0.517)

F: 0.002 (0.909)

M: 0.015 (0.431)

0.022 (0.110)

F:0.019 (0.315)

M: 0.024 (0.216)

0.147 (0.000)

F:0.150 (0.000)

M: 0.143 (0.000)

1




F Rule Baseball

5.0%

F: 3.9%

M: 6.1%

0.098 (0.000)

F: 0.085 (0.000)

M: 0.096 (0.000)

0.056 (0.000)

F: 0.050 (0.009)

M: 0.049 (0.010)

0.056 (0.000)

F: 0.053 (0.006)

M: 0.058 (0.002)

0.014 (0.295)

F: 0.024 (0.212)

M: 0.001 (0.942)

1

Source: Liikuntatutkimus 2005-2006, observations 5510. Significance in parenthesis. Legend: F = female n = 2754, M = male n = 2756

The second essay (”Demand for ice hockey, the factors explaining the attendance of ice hockey games in Finland”) has particularly focus on the effects of public information on the ice hockey attendance. Since men typically read the sport pages of newspapers, the home team’s performance is well known. The performance is operationalized as the points per game measure (success). The role of distance between the home and visitor teams is also studied? We assume that the geographical distance between the home town and the visitor’s tome is a part of admittance cost. If the distance measure is ignored the price variable is incorrect.

The results indicate that both the size of the population in the town of the home team and in the town of the visitor have a statistically significant effect on attendance. The distance between home team’s town and visiting team’s town is also significant, i.e. local games have a bigger attendance than other games. Public information is also important because the demand is not elastic with respect to the ticket price. The price variable is not the actual average price since this data was not available. The price variable used in the estimations is the ticket price to the best seats, where we expect real variation the number of available seats. As the season goes on and more games have been played, attendance seems to diminish but the estimated coefficient is low even though significant. Team’s success seems to attract a bigger attendance, while visitor’s success has the opposite effect. Spectators are willing to see live game in the stadium if they expect that home team will win the game. Our results show that team could optimize their revenues by setting higher ticket prices on matches where local teams play and also when the likelihood of winning the game increase. This is further supported by the fact that loyal supporters have a season ticket, but the share of season ticket holders in the audience is not known. Success of both the home team and the visitor has an effect: home team’s success with a positive and visitor’s with a negative coefficient. The number of plays already played has a negative effect. Weekday effect is important: the attendance is bigger during Saturdays. Also the day temperature has an effect: the colder, the bigger attendance. That effect is small but still statistically significant. The local unemployment rate has no effect. In the interpretation of ice hockey as consumption good it is also important to find that the success factor of the last three games (the form guide) does not seem to explain the attendance as well as the success factor of all games played. Ice hockey attendance has a negative income elasticity. The third essay shows that a typical sport spectator is a young man with rather low educational level. Older consumers who have a higher education typically choose performing arts, like going to theatre or opera. Therefore the income elasticity of sport events is negative.


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