Econometrics [Econ 426]
Econometrics Project
Do critic’s ratings have significant impact on the sales of video games?
Christopher A. Robinson
4/27/2012
Hypothesis:
The video game industry is a segment of the economy that is becoming
extremely important to the United States. Every year there are hundreds of games that
are released on various platforms in various genres. The way these releases are
structured, I believe, has a profound effect on the games success or failure in the
market. Once a game is developed, it is then given to critic before it hits the
marketplace so that they may review the game and give it a numerical score. This
numerical score is a signal given to consumers that can alter their economic behavior.
The question I seek to answer with this project is: If critics give positive reviews to a
video game, is that video game more successful in the market?
Motivation:
The Video games industry is a significant industry that is often overlooked in
everyday business conversation. Statistics show that 67% of households in the United
States play video games and on average spend 13 hours per week playing video
games. With $18 billion in revenue per year and growing, video games are quickly
becoming the fastest growing export in the U.S. according to researchandmarkets.com.
A video game, if received well by consumers, can make a company millions of dollars.
For example, the game Call of Duty: Modern Warfare 3 grossed over $775 million in its
first 5 day on the market. That is a record for any movie, book, or video game in a 5 day
period. The industry consists of many large publishers and well over 1000 developers.
From 2003 to 2006 the industry’s annual growth rate exceeded 17%, compared to the
U.S. economy growth rate of 2% over the same period of years.
Literature Review:
There is a paper written by Feng Zhu and Xiaoquan (Michael) Zhang called
“Impact of Online Consumer Reviews on Sales: The Moderating Role of Product and
Consumer Characteristics.” The authors look at the influence that online consumer
reviews have on video game sales. Zhu and Zhang concluded that there was a potential
positive relationship; however, they felt that data sets with different types of media
(books, magazines, movies, etc.) could yield different results than what they concluded
with the video game industry.
A paper by David Bounie, Marc Bourreau, Michel Gensollen, and Patrick
Waelbroeck entitled “The Effect of Online Consumer Reviews on Purchasing Decision:
the Case of Video Games.” This paper investigates the relationship between online
consumer reviews on the consumers buying behaviors. In their model they included a
variable of whether a game had a demo or not. This could contribute to the success or
failure of a video game significantly they found.
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With this project I intend to go in a slightly different direction than Bounie,
Bourreau, Gensollen, and Wealbroeck did with their paper. I will investigate the effects
of online critic reviews on the sales of video game software.
Model:
The Theory that my model is empirically attempting to investigate is the theory of
information cascading. An information cascade is when people observe signals from
others and make the same choice, regardless of their own personal information. I
hypothesize that when consumers receive a positive signal from video game critics, it
inspires those who may have previously had no intentions to purchase a particular video
game to purchase the game. It is possible to have a general idea of how many units a
game will sell and that is through pre order data. So I can compare the pre order data to
the actual sales figures and perhaps be able to tell if the critics rating of the video game
affected the games sales. In other words, I am attempting to see if critics rating of
games contribute to the demand of games.
Sales:
Sales are defined as the amount of units a video game sells. In the model, sales
are the dependent variable. The sales data that I will use will be from 2011, US sales
only.
Multiplatform (+ effect on sales):
The variable multiplatform is a category that is defined on whether a video game
was released on multiple platforms (Xbox360, PlayStation 3, and Wii). I expect that this
variable will have a positive effect on sales because if a game is released on multiple
platforms, it has a broader consumer base that could potentially purchase that game.
Surveys show that 72% of U.S. households own at least one game console [ESRB,
2010].
ESRB Rating (- effect on sales):
The Entertainment Software Rating Board (ESRB) rating, which is similar to the
way the Motion Picture Association of America (MPAA) ratings are given to movies, is a
categorical variable that can have an effect on who may purchase certain games. ESRB
ratings should have a negative effect on the sales of games because it should limit the
sale of certain games to certain individuals.
Multiplayer (+ effect on sales):
Multiplayer is a component of a video game that allows other many players to
share in a video gaming experience. Multiplayer is designed to both retard the used
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games market and to increase sales of that product. If a game has multiplayer I believe
that it will have a positive effect on the sales of that game.
Critic Score (+ effect on game sales):
There are many magazines, internet websites, and even newspapers that publish
reviews of video games. There are plenty of places where you can read an “experts”
opinion on if a video game is good or not. I believe that the higher a score that a game
receives increases its sales figures and bad reviews cause the inverse effect.
Demonstration Available:
Some video game developers believe that their game’s sale will be improved if
consumers have a chance to try the game for free. This allows consumers to play some
games that they may not have otherwise considered purchasing risk free. This does
work both ways, however. Consumers that were going to make the purchase could play
the demonstration and decide that the product is not worth their money. A
demonstration, I believe, does more good than harm because it gives people a chance
to interact with a product and form their own opinions. Therefore I believe that having a
demonstration increases sales of video games.
Price:
Prices of video games are very standard throughout the industry, however, there
are some games that decide to release with lower price tags perhaps to encourage
sales to those who believe that $59.99 is too much for a particular game. The fact that
prices are standard for a generation of consoles led me to believe that price will have a
very minimal negative effect on games sales.
Analysis
The first linear model run included all of the variables outlined and defined above.
What I find are that most of the variables have low T-values and are insignificant in
determining higher video game sales. The only variable that is significant to a 95%
confidence interval was critics score. The critical T value is 1.96, and critics score has a
T value of 3.5. This is a positive outcome for my hypothesis because it shows that
critic’s scores of video games do have an impact on the sales of video games.
The second linear model removes all of the insignificant variables. This leaves a
model with the intercept term and critics score. With this model I am checking for
dramatic changes to the R squared and standard error terms. Significant changes in
these could indicate omitted variable bias. With the changes from model one to model
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two, there is only a 2% drop in what the variation that the model explains and the
standard error is lower. Both are positive results.
The third linear model is testing to see if there is a variable that could help
explain more of the variation that is occurring in video game sales. I created a dummy
variable called adult. Adult is defined as any games that are rated teen or above; games
that are geared to a more mature audience. I found that this variable was almost
significant to the 95% level and that it had a negative effect on sales. The negative
effect on sales was expected because there are less potential customers for that
product. If this variable were significant in the model it would be equal to the loss of
approximately a half a million in sales. That is surprising.
All three of the models above were linear models. I had high hopes that my
variables would be able to explain much more that 9-11% of the variation of sales from
the mean. In a n effort to be able to build better models I decided to run nonlinear
regressions of the data and see if there is more explanatory power within the regressors
of my model.
Nonlinear model one was run with a semi log model. The logged variable was the
sales variable. This model indicated that critic’s scores are still significant and they
better explain what happens to sales when sales are expressed as a percentage. The
model also has a lower mean squared error and a higher R squared.
Nonlinear model two was a double log model. The variable added was the
logarithmic critic score regressor. This model was supposed to build on the success that
the first nonlinear model had started. What I found is that the RMSE increased slightly
and the R squared decreased slightly leading me to the conclusion that nonlinear model
one was a better model for testing my hypothesis.
Nonlinear model three returned to the semi log model however I added in the
other variables that were regarded as insignificant in linear regressions to see if they
could add any explanatory power and be significant in a nonlinear model setting. While I
had no more success in having more significant variables at the 95% confidence
interval I am pleased with the lower RMSE and higher R squared. There are several
variables that would be very promising at the 90% percent confidence interval and that
is another positive thing about this model. This is the strongest model that I have
available and I will use it to test my hypotheses.
Interpretation
The question that this research first set out to answer is whether critic’s scores
have a significant impact on video games sales in the marketplace. What my model
found was that critic’s scores are significant and can alter that games sales in the
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market. The model shows that for every point given by a critic increases video games
sales by 0.05%. That may not seem like much but for example the lowest score given
by a critic in the data set was 28.33 and the highest was 95.22. The lowest game
received a measly 1.42% increase to sales while this highest game enjoyed a 4.76%
boost to sales. To put these numbers in perspective of units, the lowest game sold
14,200 more units than without a critic’s score and the highest games sold 47,600 more
copies. More interpretive data is available in table c in the appendix section.
From and economics perspective, you could say that critics can send signals to
consumers and that consumers can take that information and make an economic
decision: do I buy a particular game or not? According to the data and my model critics
can only affect sales of a game by a maximum on 5% from the mean. The mean in this
case is almost one million units; therefore they only sell about 50,000 extra copies of a
game if critics rate a game favorable. That is not a significant impact to most games but
in terms of money it is as much as 3 million dollars (50,000 copies of a game time the
$60 purchase price). That is a significant number.
Limitations
The limitations of my findings are born because of how little information is
available for viewing. I have a strong belief that the marketing budgets of these
companies have very significant impacts on the success or failure of their games. There
is also the variable of the intangible assets – what a developers name means to the sale
of the game. Well know developers games tend to sell better than developers who have
just entered the market with their first game. There are studies that show that
information cascades from experts are infrequent [Konovalov, 2011] and the presence
of highly informed individuals marketing a product increases the probability that there
will be a cascade.
Conclusion
In conclusion, my model attempts to investigate the effects of critic’s scores on
video games sales. What it finds is that critic’s ratings on video games are significant
however they impact those sales by a maximum of 5% from the mean. Not many would
call that information cascade. The signals sent by critics encourages few to run out an
buy a game that they have little to no interest in anyway. What may hold the answer to
just what video game sales hinge on could be marketing or it could be the merits of the
product itself.
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Appendix
Tables, Data Sources, and References
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Table A
Results of regressions of video games sales in 2011 based on if the game is on
multiple platforms, contains multiplayer modes, critics scores, there is a
demonstration available, the price and if it is a gear designed for adults.
Dependent Variable: Video games sales (in Millions)
Regressor
Intercept
Multiplatform
Multiplayer
Critic Score
Demonstration Available
Price
Linear Model 1
Linear Model
2
Linear Model
3
-2.52
(5.03)
0.41
(0.37)
0.29
(0.33)
0.042
(0.012)
-0.074
(0.33)
-0.003
(0.082)
-2.07
(0.91)
-1.9
(0.91)
0.04
(0.01)
0.04
(0.01)
Adult game (Rated Teen or
Mature)
-0.56
(0.32)
Summary Statistics
SER
R squared
n
1.6
0.11
119
1.59
0.09
119
1.57
0.11
119
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Variable
Description
Sales
Sales are defined
as the amount of
units a video game
sells. 2011 Sales
data used.
Released on
multiple platforms
(Xbox360,
PlayStation 3, and
Wii)
Entertainment
Software Rating
Board (ESRB)
rating – Everyone,
Everyone 10+,
Teen, Mature,
Adult Only, Rating
pending
Multiplayer is a
component of a
video game that
allows other many
players to share in
a video gaming
experience
An “experts”
rating of a games
on a scale of 0 –
100.
Ability to preview
a video game
before release
Price of a single
unit
Games rated Teen
or above
Log(Sales)
Log(Critic’s Score)
Multiplatform
ESRB Rating
Multiplayer
Critics Score
Demonstration
Available
Price
Adult
LGsales
LGCS
Data sources
Source
http://www.vgchartz.com/gamedb/
Various Developer and Publisher sources, dataset built
manually
http://www.esrb.org/ratings/ratings_guide.jsp#rating_symbols
Various Developer and Publisher sources, dataset built
manually
http://www.gamerankings.com/
Various Developer and Publisher sources, dataset built
manually
Standard prices for Video games $60
Dummy variable
Logarithmic Sales
Logarithmic Critic’s scores
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Table B
Dependent Variable: Logarithmic Video games sales
Regressor
Intercept
Nonlinear Model
1
Nonlinear
Model 2
Nonlinear
Model 3
-4.36
(0.64)
-13.77
(2.39)
-2.27
(3.44)
0.39
(0.26)
0.22
(.23)
0.05
(0.008)
Multiplatform
Multiplayer
Critic Score
0.05
(0.008)
LGCS(Logarithmic Critic
Scores)
Demonstration Available
3.04
(0.55)
-.46
(0.23)
0.34
(.23)
-0.04
(0.06)
0.42
(0.22)
1.12
0.23
119
1.09
.29
119
Price
Adult game (Rated Teen or
Mature)
-0.44
(0.23)
Summary Statistics
SER
R squared
n
1.1
0.25
119
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Table C
Impact of Critics on games sales
Scores
Lowest - 28.33
Mean – 76.05
Highest - 95.22
Percentage boost
Dollar amount
from mean (approx. 1 (number of units
million)
times $60 per unit
price)
1.42% - 14,200 units
3.65% - 36,500 units
4.76% - 47,600 units
$852,000
$2,190,000
$2,856,000
References:




Activision Investor press release
Activision Publishing, Inc – November 17, 2011
http://investor.activision.com/releasedetail.cfm?ReleaseID=624766
The Effect of Online Customer Reviews on Purchasing - Decisions: the Case of
Video Games
David Bounie, Marc Bourrea, Michel Gensollen, Patrick Waelbroeck - 2005
http://perso.univrennes1.fr/eric.darmon/workcommed/papers/bounie_bourreau_gensollen_waldbr
oeck_2_nice.pdf
Impact of Online Consumer Reviews on Sales: The Moderating Role of Product
and Consumer Characteristics
Feng Zhu and Xiaoquan (Michael) Zhang – 2009
http://blog.mikezhang.com/files/gamereviews.pdf
Video game Database
2012
www.VGchartz.com
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