The Growth of China's Domestic Film Market

Written by Weicheng Wang and Tara Deworsop under the direction of David Backus, May 2016

Abstract

Ever since Harrison Ford’s The Fugitive became the first foreign-produced film distributed in Communist China, Hollywood films have been highly in demand in the Chinese market. Even though Hollywood films are subject to a strict quota of 34 films a year, from 2008 to 2012 revenue from foreign movies in China's top 25 grossing films was able to keep up with or exceed domestic film revenues. The Chinese government has thus justified their quotas by arguing that protection is needed to support the local market. This paper will examine the growth of local Chinese films versus foreign films. It will also look at revenue growth by genre to see what types of movies the Chinese prefer to watch.

Introduction

For the Chinese government, which seeks to maintain legitimacy in the eyes of Chinese citizens, and which heavily relies on media to broadcast an image consistent with that goal, controlling the film market has always been an important task. For decades, China completely banned the import of foreign films. Owing to international pressure, it recently began letting in 34 revenue-sharing films per year.

However, these films are subject to strict regulations. All foreign films are distributed by a few state-owned companies. The government also imposes a multitude of regulations on foreign films that can change at any time. One of these is that foreign studios can only get at maximum 25% of the profit from a foreign film in China. Despite this tricky regulatory environment, foreign films have had a very successful run in the Chinese market in the past several years, taking just about 50% of the domestic market's revenue. We examine this growth over time and examine possible reasons for this growth, as well as take a closer look at 2015, where a trend of Chinese films outperforming foreign films may be emerging.

Data Set


In [6]:
import sys
import pandas as pd
import matplotlib as mpl
import matplotlib.pyplot as plt
import numpy as np
import datetime as dt
import time

%matplotlib inline

print('Python version:', sys.version)
print('Pandas version: ', pd.__version__)aaaaaaaaa
print('Matplotlib version: ', mpl.__version__)
print('Today: ', dt.date.today())

dfs = pd.ExcelFile("/Users/Wei/Downloads/Movie Data Workbook.TD2.xlsx")
dfs.sheet_names
x1 = dfs.parse('Summary')
x2 = dfs.parse('2015')
x3 = dfs.parse('2015S')
totalrev = ['Foreign Revenue','China Revenue']
genre = ['Action','Animation','Comedy','Drama','Romance','Fantasy','Science Fiction']
x1 = x1.set_index('Year')
x1[totalrev] = x1[totalrev]/1000000
x1[genre] = x1[genre]/1000000
x1['Foreign %'] = x1['Foreign %']*100
x1


Python version: 3.5.1 |Anaconda 4.0.0 (x86_64)| (default, Dec  7 2015, 11:24:55) 
[GCC 4.2.1 (Apple Inc. build 5577)]
Pandas version:  0.18.0
Matplotlib version:  1.5.1
Today:  2016-05-12
Out[6]:
Foreign Revenue China Revenue Foreign % China % Action Animation Comedy Drama Romance Fantasy Science Fiction
Year
2008 196.032457 215.709428 47.610521 0.523895 81.904173 31.612056 21.216383 29.901082 123.080371 49.769706 56.183926
2009 269.443586 332.395672 44.770025 0.552300 152.659969 58.635240 83.210201 130.462133 54.891808 23.993818 97.986090
2010 478.513138 504.811437 48.662786 0.513372 355.097372 0.000000 116.735703 0.000000 93.180835 118.826893 299.483771
2011 535.364760 548.020093 49.415936 0.505841 444.581144 133.568779 50.700155 128.687790 128.633694 71.775889 63.234930
2012 1028.434312 534.901082 65.784624 0.342154 718.468315 101.479134 155.012365 124.428130 281.584235 0.000000 182.363215
2013 797.802164 1017.324575 43.952973 0.560470 743.080371 61.009274 90.992272 0.000000 395.349304 241.542504 283.153014
2014 904.250386 1620.621329 35.813716 0.641863 967.778980 0.000000 467.355487 0.000000 400.814529 233.123648 455.799073
2015 1724.786708 2130.950541 44.732994 0.552670 1671.111283 311.123648 743.744977 108.123648 0.000000 495.455951 526.177743

This data is taken from entgroup.cn, a Chinese company that tracks the top-performing 25 film's revenue. Revenue is displayed here in millions of dollars yearly. 'Foreign' films includes any film that is not a domestically made Chinese film or a China-Hong Kong co-production. The vast majority of the 34 foreign films allowed in each year are from America, with 1 or 2 titles from other countries such France, the United Kingdom, and Australia.

Foreign vs. China Movie Revenue, 2008-2015


In [7]:
dt.datetime(2011, 1, 1)
x1.index = [dt.datetime(year, 1, 1) for year in x1.index]

In [8]:
x1[totalrev].plot()
plt.title('Foreign vs. China Movie Revenue, 2008-2015')
plt.xlabel('Year')
plt.ylabel('Revenue (millions of $)')


Out[8]:
<matplotlib.text.Text at 0x11c7a9c88>

As can be seen here, top 25 films' foreign revenue closely tracked Chinese film revenue until the year 2012, when foreign film strongly beat Chinese film revenue. 2012 was by no means a bad year for China - in fact 2 of the top 3 films of the year were Chinese. It was simply that foreign films had an excellent year by comparison. The average American film earned six times as much revenue as the average Chinese film, owing to blockbusters such as the Avengers and Mission Impossible 4, which both grossed over $100 million at the box office. Truly though, it was a year when the tide rose for everyone, with the domestic film market as a whole growing 30 percent from the previous year (Cain).

Many in the industry speculate that this led the Chinese government to a policy of 'retaliation' since 2012, whereas Foreign films have been subject to harsh blackout periods for months at a time where only Chinese films may be released. Foreign films also generally get shorter release windows than Chinese films, with some films showing for as little as 3 weeks. As another form of punishment, US films of similar genres have been forced to effectively 'compete' against one another by being released at the same time. For instance, the 2015 film Inside Out was released on the same day as 'Pixels', another animation film, reducing both of their revenues. It does appear that measures taken by the Chinese government after 2012 have affected foreign revenue, as it has dropped substantially below Chinese revenue, when it was on a path to overtake it in 2012. Of course, owing to the unpredictable nature of movie revenues, it's hard to say for certain how much of this is due to government influence.

Top 25 Foreign Films Percentage Market Share


In [19]:
fig, ax = plt.subplots()

x1['Foreign %'].plot()  
plt.title('Top 25 Films Foreign Percentage Market Share')
plt.xlabel('Year')
plt.ylabel('Percent Market Share')
ax.set_ylim(bottom = 0, top =100)


Out[19]:
(0, 100)

The Chinese government has announced that it planned to maintain foreign box office revenue below 50% of the total market (Makinin). We can see that with regards to the top 25 movies of each year, this is definitely true, with the major exception being 2012. 2013 and 2014's revenue in particular was well below the previous trend, indicating that there may have been some Chinese government intervenetion to achieve those results.

Top 100 Movies of 2015 by Release Date


In [23]:
fig, ax = plt.subplots()
g = x3['Gross']/1000000
r = x3['Release'].astype(np.int64)
color = [x3['Cateogry'].replace('Foreign','b').replace('China','r')]
col = ['b', 'r', 'r', 'r', 'b', 'b', 'r', 'r', 'r', 'r', 'r', 'b', 'r',
        'b', 'r', 'b', 'b', 'r', 'b', 'b', 'r', 'b', 'r', 'b', 'r', 'b',
        'b', 'r', 'r', 'r', 'b', 'b', 'b', 'b', 'r', 'r', 'r', 'r', 'r',
        'r', 'r', 'r', 'r', 'r', 'r', 'r', 'b', 'r', 'r', 'r', 'b', 'b',
        'r', 'b', 'r', 'r', 'r', 'r', 'b', 'r', 'b', 'r', 'r', 'r', 'r',
        'b', 'r', 'r', 'r', 'b', 'r', 'r', 'b', 'b', 'b', 'b', 'r', 'b',
        'b', 'b', 'b', 'b', 'b', 'r', 'r', 'r', 'r', 'r', 'r', 'r', 'r',
        'r', 'r', 'r', 'r', 'r', 'r', 'r', 'r', 'r']
        
plt.scatter(r,g,c=col)
ax.set_ylim(bottom = 0)

plt.title('Top 100 Movies of 2015 by Release Date')
plt.xlabel('Month')
plt.ylabel('Revenue (millions of $)')


Out[23]:
<matplotlib.text.Text at 0x11d055cc0>

As can be seen here, there is no clear difference between the revenue distributions patterns of the top 100 foreign and Chinese films of 2015. It seems that both categories have most films in the bottom 20%, with a few films breaking the 200 million USD mark and even fewer breaking the 300 million USD mark. This seems to show that Chinese audiences do not have a clear preference for domestic or foreign films simply because of their nation of origin. Nor would it appear that releasing a film in any particular time of year is more likely to result in higher revenue. It does seem that revenue is slightly higher towards the end of the year, but this is also owing to there being a few major blockbusters during this time.

In general, 2015 was a year of trend reversals. As can be seen by the red dots, seven out of ten films in the top 10 were Chinese. Domestic film revenue grew 69% year over year, while foreign imports grew only by 24%. However, foreign commentators have been unable to tell how much of this growth is organic. Some of the Chinese films in the top 10 category, such as Monster Hunt, were given signifcantly longer runs than foreign film, and summer blackout periods were in effect for foreign films as well.

Top 25 Total Revenue by Genre, 2008-2015


In [9]:
x1[genre].plot()
plt.title('Top 25 Total Revenue By Genre, 2008-2015')
plt.xlabel('Year')
plt.ylabel('Revenue (millions of $)')


Out[9]:
<matplotlib.text.Text at 0x11cac2cf8>

As a matter of interest, we plotted aggregated film revenue by genre to see which were most popular with Chinese audiences. It appears that the only genre that grows steadily year after year is action, although comedy and science fiction films also hold some sway. The reason for this is likely simple: most of the 'tentpole' Hollywood imported films (such as Iron Man and the Avengers) tend to be action films, because historically they have done the best, creating a chicken-and-egg effect. As blockbuster films make several times the amount of an average film, these add disproportionately to the action total. Also, action films tend to be more likely than other genres to translate across cultures, versus categories like comedy which can be more nuanced with languages.

Because this data aggregates foreign and domestic revenue, we also see genres that are weak exports (such as comedy) doing better because of domestic support. Several of the top 25 films of 2015 were local comedies, and several were also domestic CGI-enhanced fantasy films. Because these films had little presence at the Chinese box office in previous years, there could be pent-up demand, and these categories are likely to continue growing in the future, with producers tailoring their offerings to suit local tastes for comedy. Also, while animation films individually perform very well in China (for example Kung-Fu Panda), on the whole, there are not enough animation films released every year to make a significant dent in the market.

Conclusion

We can see from this analysis that, for many possible reasons, Chinese films are overtaking foreign films in revenue growth in their home market. This effect is probably as much economic as it is cultural. For instance, China adds more theaters per year than any other developed country, adding over 8,000 new theaters in 2015. Most of these theaters tend to concentrate in second and third-tier cities, where the audiences are less accustomed to foreign films. Thus, it is more likely for Chinese films to gain strong market share with more culturally relevant films, especially when foreign films are capped at the current rate of 34 films per year. For instance, the top film of 2012 was 'Lost in Thailand', a homegrown movie about Chinese who get into misadventures in Thailand. The film was made on a shoestring budget but was able to edge out 'Titanic: 3D' for the top spot of the year because it resonated with Chinese audiences' desire for adventure and travel abroad.

At the same time however, there has been a more dubious effect caused by Chinese government interference with foreign film releases, such as by creating film blackout periods and releasing foreign films of similar genres at almost the same time. Thus, while it is clear that Chinese films have a lot of room for organic growth, it's not as clear where foreign films would naturally fit into the picture without government interference. This is compounded by the fact that Chinese films seldom sell very well at all outside of China, indicating that much work needs to be done to tailor films for export.

We may have an opportunity to see how this plays out in 2017 or 2018. In 2017, foreign film distributors will seek to renegotiate the WTO agreement capping film imports at 34 per year. If the quota is increased and Chinese films continue to surge, this will be an indication that the Chinese market is really in an organic growth phase with demand for local content. However, if foreign films again have the sort of beat they did in 2012, it will indicate that foreign weakness in the market is mainly due to government interference. In either case, the next few years will be fascinating to watch for the Chinese domestic film market.

References