Contestability in the Digital Music Player Market
Wei Dai∗ and Kam Yu†
May 2015
Abstract
In this paper we test the concept of contestability in the digital music
player market. The theory of contestable markets implies that although producers in an oligopoly have market power, the threat of new entrants keeps
their behaviours in check and in some situations the market outcome can be
comparable with that of a perfect competition.
The digital player market has been dominated by one producer, Apple Inc.
with a few followers. The structure does not satisfy the conditions of a pure
contestable market such as absence of sunk cost, no product differentiation,
price taking behaviour of entrants, etc. But Baumol and others argue that pure
contestable markets rarely happen in reality. We therefore estimate a qualityadjusted price index with the hedonic method from 2002 to 2010 and compare
it with the price trends of other digital products like personal computers and
digital cameras. Results show that the quality-adjusted prices decline at a
rate of about 20 percent per year during the period, which is similar to other
IT products. This provides support for the idea that the digital music player
market is fairly contestable.
1
Introduction
Since the introduction of the first Walkman in the late 1980s, Sony had been the
leader in the design and production of portable music players. With the emergence of
personal computers the Internet in the 1990s, the portable music player market went
through a classic transformation of creative destruction. Developments of digital file
formats for music and small hard drives made digital music players possible. Apple
Computers introduced the iPod in 2001 with mixed reaction from the consumers
(Edwards, 2011). With the introduction of the iTunes Store in 2003, however, the
Apple devices became the market leader (Apple Inc., 2004). Over the years other
manufacturers have introduced competitive models of portable music players. Nevertheless, Apple has been able to maintain its near-monopoly power. Class-action
∗
†
University of Calgary, Email: [email protected].
Lakehead University, Email: [email protected].
lawsuits have been filed in the U.S. starting in 2005 on behalf of millions of consumers regarding the the abuse of market power by Apple. Finally, in December
2014, the court decided the company did not compete unfairly and rejected the case
(Associated Press, 2014).
The theory of constable markets proposes that under certain conditions, producers in a market making economic profits are under the threat of new firm entries.
The presence of these potential entries imposes a constraint on the incumbent firms
to exercise their market power. In the extreme case, even a monopoly will set the
market price at the average cost of production. Consequently, if the market is contestable, market efficiency can be achieved without any government intervention.
The theory aims to generalize the theory of competitive equilibrium.
A number of writers, however, argue that the theory of perfectly contestable
markets is theoretical inconsistent and empirically empty. They argue that the
assumptions of the model contain internal logical conflicts. Moreover, even the
assumptions are logically sound, there are very few, if any, industries that will be
qualified as perfectly contestable.
In the case of the iPod, Apple is the dominant producer which can maintain
its strong market power in spite of entries of big companies like Microsoft. We are
interested in how the company can hold its market share. Although digital music
players do not satisfy the strict definition of a pure contestable market, the idea
of using a pricing strategy to deter entries seems appealing. The first step of our
investigation is to construct a price index over time and compare it with those of other
highly competitive digital consumer goods such as computer and digital camera. Our
results show that the price trend is comparable with the other markets.
Section 2 below provides a brief description of the theory of contestable markets.
Section 3 expands the history of portable music players and the hedonic method
used to measure the price trend. Data sources and methodology are explained in
sections 4 and 5. The resulting price indices are presented in section 6. We also
compare our result with the price trends of other digital products. Finally section 7
concludes.
2
Theory of Contestable Markets
2.1
Basic Theory
The theory of contestable markets was developed in the 1970s with the aim of generalizing the theory of perfect competition.1 The key insight of the theory emphasizes
potential competition from firms not yet in the market exerts pressure on the incumbent firms to keep prices low. We present a baseline model here with a single
market of a homogeneous good with output quantity y. The multi-product case can
be extended by treating y as a vector (see Willig, 2008).
1
See Baumol et al. (1986, 1988) and Willig (2008).
2
An industry configuration consists m firms in the market with outputs y1 , y2 , . . . , ym .
Technology in production is commonly known so that each firm’s cost function is the
same and written as C(y), with C(0) = 0. The firms charge a single market price p.
Market demand is represented by the demand function D(p).
The industry configuration is said to be feasible if supply and demand are in
equilibrium and all firms at least break even. That is, at the market price p,
m
X
yi = D(p),
i=1
pyi ≥ C(yi ),
i = 1, . . . , m.
Furthermore, the configuration is said to be sustainable if any outside firm entering
the market with a price pe less than or equal to p and an output level ye will lose
money. In other words, for all pe ≤ p and ye > 0,
pe ye ≤ C(ye ).
Baumol et al. define a perfectly contestable market (PCM) to be an industry configuration that is feasible and sustainable. It follows that a PCM is in equilibrium, with
each incumbent firm earning zero economic profit. No outside firm has the incentive
to enter the market. The benchmark case of perfect competition, the authors point
out, is a special case of a PCM. The converse, however, is not true. We illustrate
this point with the extreme case of a monopoly, that is, when m = 1.
Suppose that the cost function of an industry is given by
(
F + cy, if y > 0,
C(y) =
(1)
0,
if y = 0,
where F is a fixed cost if a firm is in production, and a constant marginal cost c.
With market demand function D(p), the short-run monopoly profit is
πm = max {D(p)p − cy} .
y
Economic profit is positive if πm > F . In this case, the profit maximizing output ym ,
depicted in figure 1, is where the marginal cost curve intersects the marginal revenue
curve. The firm will charge the monopoly price pm on the demand curve (not shown
in the diagram). Since profit is positive with this price-output pair (pm , ym ), absence
any government barriers, other firms have the incentive to enter the market. An
entrant can charge a price between pm and the average cost curve and take over the
market from the incumbent. Given the threat of entry, the incumbent will instead
choose the price-output pair (pc , yc ), where the demand curve meets the average cost
curve. In this case the monopoly is breaking even, that is,
D(pc )pc − cyc = F.
3
p
MR
D
6
B
B
pc
c
J
J
B
J
B
J
B
J
B
J
B
J
B
J
B
J
Jr
B
AC
Br
J
B
J MC
B
J
- y
ym
yc
Figure 1: A Contestable Monopoly
It is easy to see that price-output pair (pc , yc ) is feasible and sustainable and therefore
contestable. Consequently the market is in a long-run equilibrium.
The results of this model have important implications. First, the threat of entry
forces the monopoly to adopt an average-cost pricing strategy. Second, the classic
monopoly profit is dissipated to the benefit of the consumers. Third, although the
socially efficient outcome of marginal-cost pricing cannot be achieved in the presence
of the fixed cost, a contestable market is the second-best solution. No government
subsidy is needed to induce the firm to produce at the marginal-cost pricing output.
This second best solution is labelled as a Ramsey optimum by the proponents of the
theory. In fact, a number of markets have been identified as contestable and therefore
deemed to be deregulated in the U.S. These markets include railroad transportation,
commercial airline, the trucking sector, and telecommunications (Bailey and Baumol,
1984).
2.2
Criticisms
The idea of the perfectly contestable markets have been criticized by many writers.
Shepherd (1894), who labels the assumptions of PCM as “ultra-free entry”, argues
that they are logically inconsistent. He points out that the model assumes that
if entry does happen, the incumbents would ignore the entrants and maintain their
existing market price. But the model also implies that entry is total, and the entrants
would take over the market. Therefore it is not logical to assume that the incumbents
would not respond to the entry.
The critical question is, how “fixed” is the fixed cost F in equation (1)? This is
the usual distinction between the short run and the long run. If F is fixed for a long
time comparing to the lifetime of the firms in the model, then we normally label it a
sunk cost. The PCM theory assumes that potential entrants can do a “hit-and-run
entry” in order to put pressure on the incumbents. This implies that production
4
is free of sunk costs. Shepherd (1984) points out that in order to enter a market,
a firm needs basic investment such as market research, product development and
design, advertising and marketing, and faces transaction costs in financial and legal
services. Most of these costs are not recoverable upon exit and therefore are sunk
costs. Empirical studies have shown that the most important factor in entry barriers
is product differentiation.
Stiglitz (1987) uses a simple game-theoretical model to show that even small sunk
costs can be barriers to enter a market. In fact, an incumbent firm can strategically
choose a technology with high sunk cost to deter entry. His description fits the
market of digital music players well, at least in the early product stage:
Because technological change inherently involves increasing returns
and sunk costs, the contestability doctrine is particularly inapplicable to
industries in which technological change is important; potential competition ensures neither economic efficiency nor zero profits. (p. 887)
Indeed, it is inconceivable that Apple makes zero economic profit from selling iPods.
We are interested instead on studying the effects of the company’s pricing strategy
on its competitors and potential entrants. Our argument is that sunk costs are low
for companies that are already producing similar digital products such as computers
and personal digital assistants. Companies such as Dell, HP, Palm, and IBM can
enter the market without much efforts. In fact, it is surprising that even Sony, which
reenters the market with its MP3 players, is unable to regain its former market share
that the Walkman achieved.
3
The Portable Music Player Market
3.1
Brief History
Portable music players have gone through a process of evolution during past decades.
Sony Corporation (Sony) released Walkman portable audio cassette players in 1980s.
From then on, listening to music was not an activity limited in homes or theatres
any more. People could listen to music outside with a handy size portable cassette or
CD player. At the end of 20th century, the revolutionary device — portable digital
audio player (also short for MP3 player) — was introduced to consumers. Finally,
it replaced the traditional portable audio cassette/CD player, and dominated the
portable audio device market.
The first mass-produced portable digital audio player was MPMan manufactured
by SeaHan Information Systems. It featured a 32 or 64 megabytes (M) flash memory
and was released in 1998 at the price of $400 ($600 for 64M model) on the Japanese
market.2 Three years later, Apple Inc. (Apple) released its first generation iPod
players. The iPods swept across the whole world after Apple released the third
2
All prices quoted in this paper are in U.S. dollar unless stated otherwise.
5
generation products in 2004. By September 2010, 270 million iPod players had been
sold. Other major electronic manufacturers including Microsoft Corporation, Dell
Inc., Sony, etc. also released their own portable digital audio players. The portable
digital audio players also changed the recording industry. Consumers began to buy
individual songs or the whole albums online (e.g. iTunes) and download them to their
devices instead of buying CDs. The price and technical specifications of a portable
digital audio player such as memory size and battery life after each recharge influence
consumers’ decisions.
For the early models, the hard-disk based versions had a maximum capacity of
10 gigabytes (G). The flash-memory based models only had about 128 megabytes
(0.125 G) capacity. They were usually equipped with a 2 inch (diagonal dimension)
monochrome display. Battery life lasted less than 15 hours. A typical model costed
about $300. The products since then have undergone a rapid technological development. In 2010, the typical players had more than 30G capacity (maximum 160G
for hard-disk based models), with up to 30 to 40 hours battery life, and a maximum
7 inches colourful, even touchable, built-in displays. Due to the continuous changes
in product characteristics, we need a quality-adjusted price index to measure the
general price trend. In this study, hedonic methods are used to estimate the shadow
prices of the product characteristics. The resulting index reflects the market price
trend net of quality changes.
3.2
Measuring the Price Trend
The hedonic method was developed by Court (1939) to construct hedonic price
indices for automobiles. Chow (1967) borrowed the technique to measure price
changes for computers over the period 1955–1965 in the U.S. Since then the hedonic techniques have received more attention and are commonly used to analyze
products with rapid technological changes. For example, Triplett (1989) finds that
the quality-adjusted prices for mainframe computers and peripheral equipments fell
10% to 30% per year for over 25 years. Berndt and Rappaport (2001) compute the
quality-adjusted price indices for desktop and laptop personal computers (PC) over
a quarter-century. They find that the average annual price decline for desktop PC
was 27%, compared with 21% for laptops. They also observe that the price declines
accelerated in the 1990s. The U.S. Bureau of Labor Statistics (BLS) first published
a price index based on hedonic method for mainframe computers in 1990 and expanded the method to other consumer electronics such as televisions, video cassette
recorders etc. (Liegey and Shepler, 1999). Triplett (2004) provides a detailed survey
of the hedonic method.
6
4
4.1
Data
Data Sources
Data are obtained from product reviews of portable digital audio players on PC
Magazine’s website (PCMag.com) and CNET.com. These two websites provide reviews, news, and other information on a wide range of consumer electronics. The
product reviews include the list prices (manufacturer’s suggested retail price, MSRP)
and sufficient technical specifications. Information on the two websites are combined
to construct our data set. For instance, the PCMag reviews provide products’ list
prices but not their first released dates, while the CNET reviews record all products’ released dates but provide little information on their list prices. So combining
these two sources makes it possible to record both list price and released date of
a model. A disadvantage of this approach is the inconsistent technical test results
for some products. For example, they provide different battery life test results for
some models. To avoid the discrepancy, we use the rated battery life claimed by the
manufacturers.
The basic unit of an observation is a portable digital audio player model on
the market in United States. If a model has different list prices in different years,
several observations are recorded according to its different prices. For example, Apple
released the sixth iPod Classic in September 2008 at $249. One year later, it reduced
the list price to $229. These are treated as two observations with different prices in
the two years. Since all models are produced by large manufacturers, it is reasonable
to assume that the data constitute a large part of the overall portable digital audio
player market sales. The data set contains 260 observations over the 2002–2010
sample period. The number of each year’s observations is shown in table 1.
Table 1: Number of Observations
Year
Number of observations
2002
2003
2004
2005
2006
2007
2008
2009
2010
13
15
23
47
37
48
41
23
13
Total
260
7
Table 2: Product Attributes and Measurement of Variables. (Expected Sign of
Coefficient Shown in Parentheses)
Attribute
Variable
Measurement
Price (dependent variable)
Capacity attributes:
size
drive type
P
List price
CAP (+)
FLASH (+)
Battery Life
Built-in Display attributes:
size
colour type
BATTERY (+)
Installed capacity, in gigabytes (G)
Dummy variable
(= 1 if flash memory)
Battery life for audio lay, in hours
control type
4.2
SCREEN (+)
COLOUR (+)
TOUCH (+)
Diagonal dimension, in inches
Dummy variable
(= 1 if colour)
Dummy variable
(= 1 if touchscreen)
Technical Characteristics
The price of a portable digital audio player is assumed to depend on several attributes
that determine its performance and portability. All technology product reviews of
PCMag and CNET focus on capacity, battery life, and built-in display (see table 2).
Digital audio players have a huge advantage in the capacity of storing songs in
comparison to other traditional players such as Sony Walkman cassette players and
portable CD players, which only can play a cassette or CD containing about 10
songs. When the first iPod was released in October 2001, it was equipped with
a 5 gigabytes (G) hard drive. Apple claimed that it was capable of storing 1,000
songs. When Apple released the sixth generation iPod Classic in September 2007,
it had a 160 G hard drive with the ability of holding up to 40,000 songs. The
capacity increase reflects the quality improvement in those players. On the other
hand, capacity is manufacturers’ basis for pricing their products. Manufacturers
usually release a series of products simultaneously with same features except their
capacities, and price them differentially according to their capacities; thus the price
differences directly reflect the values of capacities.
The capacity of a player depends on its data storage device. There are two
types storage devices, hard disk drive (HDD) and flash memory. In our data set, 95
models are equipped with HDD and 165 with flash memory. The average capacity
of HDD in our models is 39.31 G, and 9.27 G for flash memory. Models with flash
memory are more expansive then with HDD for the same storage capacity. For
example, in 2004, Creative Technology Ltd. released two models “Nomad MuVo
Slim” and “Nomad MuVo2” at same price of $199. They had almost the same
8
technical specifications except the data storage devices. The Nomad MuVo Slim
used flash memory to store data and provides 0.25 G capacity. The Nomad MuVo2
had a HDD with 4 G capacity. The later one had 16 times larger capacity than
former at the same price. Flash memory is more expensive but has advantages in
smaller size, lighter weight and lower power consumption than HDD. As technology
developed and production cost declined, the number of flash-based models increased.
In 2006, about than 60% are flash memory models. After 2006, only those models
that provided “extreme” large capacity (60 G, 80 G, 120 G etc.) used HDD. In 2009
and 2010, all newly released models were flash-based, and the maximum capacity
of flash memory increased to 64 G. Since flash memory is smaller and lighter than
HDD, we use a dummy variable in the hedonic equation not only to distinguish
the two different data storage devices, but also to reflect the differences in models’
portability. Therefore, other things being equal, the flash-based models are expected
to be more expansive than others with HDDs.
Battery life dictates playing time between recharging. Thus longer battery life
improves the portability of a music player. In the data set, the models use either
built-in rechargeable batteries or changeable dry-cells (usually AAA batteries). The
average battery life by year is shown in table 3. It increases from 10.15 hours to 32.77
hours over the sample periods. This reflects the improvement in battery technology.
Table 3: Average Battery Life (hours)
Year
Mean of Battery Life
2002
2003
2004
2005
2006
2007
2008
2009
2010
10.15
12.47
17.91
21.19
20.30
25.07
28.09
32.26
32.77
Total
23.08
Fourteen early models in our samples do not include built-in displays. Table 4
shows the diagonal dimensions (in inches) of built-in displays by year. The average
size increases steadily except the year 2004. In 2010, it was 88% larger than that
in 2002, which means that the viewable areas have been enlarged nearly 4 times.
The displays are either monochrome or colour. Monochrome displays can only show
some simple text information such as the name of a song, time, and other simple information. Colourful screens, depending on other technical specifications of models,
can show colour photos, album covers, lyrics, and even play videos. After 2007, all
9
newly released models are equipped with colour built-in displays. A dummy variable
is used to distinguish the models with the two different built-in displays. Another
dummy variable is used for the later models with touchable screens.
Table 4: Average Display Diagonal Dimensions (inches)
Year
Mean of diagonal dimensions
2002
2003
2004
2005
2006
2007
2008
2009
2010
1.35
1.73
1.62
1.82
2.06
2.28
2.39
2.40
2.54
Total
2.07
In summary, the product characteristics obtained from the two data sources
include measures of the following variables: P (price in U.S. dollars); CAP (memory
size in gigabytes); BATTERY (battery life in hours); SCREEN (diagonal dimension
of built-in display in inches). COLOUR is a dummy variable equal to one if the
model has a colour display; TOUCH is a dummy variable equal to one if the model
has a touchscreen; and FLASH is a dummy variable equal to one if the model is a
flash-based digital player (see table 2).
5
Methodology
5.1
Functional Forms
Issues in functional form used in hedonic studies are addressed in Yu and Prud’homme
(2010). We follow their methods and recommendations and start with the model selection. Let Pit be the list price of portable digital audio player model i in period t,
Xijt be the value for the jth characteristic for the model i in period t or a dummy
variable. εit is assumed to be a disturbance term which is normally distributed with
mean 0 and constant variance. Three functional forms are used in this study:
1. Linear
Pit = α0 +
n
X
j=1
10
βj Xijt + εit
2. Semilog
log Pit = α0 +
n
X
βj Xijt + εit
j=1
3. Log-Log
log Pit = α0 +
n
X
βj log Xijt + εit
j=1
These three functional forms are widely used in constructing quality-adjusted
price indexes. Their performance is evaluated through the procedures suggested by
Yu and Prud’homme (2010) in the following sections. Models which do not have a
built-in display are assigned the value of zero for the variable SCREEN. In the log-log
model, all values for this variable are modified by addition of 1 before transforming
into log values.
5.2
Heteroskedasticity and Structural Changes
The quality-adjusted price indices can be constructed from the results of separate
yearly regressions, adjacent-year regressions and all-year pooled regressions. In the
presence of structural changes over the sample period, pooled regressions will not be
appropriate. Therefore, Chow tests are performed to detect any structural changes
with adjacent-year regressions. Since the test requires constant variance between
different periods, the first step is to test for the presence of heteroskedasticity. Results of the White tests (p-values) are shown in table 5. At 1% significance level,
homoskedasticity is rejected for only one adjacent-year regression in period 2005–06
in linear functional form among all 24 regressions.
Table 5: White Test on Adjacent-Year Regressions (p-values)
Year
Linear
Semilog
Log-Log
2002–03
2003–04
2004–05
2005–06
2006–07
2007–08
2008–09
2009–10
0.3952
0.2333
0.2928
0.0000*
0.0875
0.0612
0.2590
0.4093
0.6423
0.3547
0.5188
0.5659
0.7075
0.6579
0.0346
0.0960
0.4045
0.4088
0.7767
0.4775
0.0056
0.5123
0.0158
0.1307
Note: *null hypothesis of homoskedasticity
is rejected at 1% significance level
11
In the absence of heteroskedasticity, we can continue the tests for structural
changes. The Chow test results are reported in table 6. For all three functional
forms, structural changes are detected in periods 2004–2005, 2005–2006, 2006–2007
and 2008–2009 at 5% significance level. Since structural changes exist in nearly half
of the sample periods for all functional forms, a pooled regression may be biased.
Consequently, we proceed with the adjacent-year regressions and separate yearly
regressions. The price index based on a pooled regression is also computed for the
purpose of comparison.
Table 6: Chow Test on Adjacent-Year Regressions (F -statistics)
Year
Linear
Semilog
Log-Log
2002–03
2003–04
2004–05
2005–06
2006–07
2007–08
2008–09
2009–10
1.65
2.02
11.82*
21.46*
9.08*
0.90
2.58
1.54
1.15
1.38
3.45*
5.77*
5.33*
1.45
3.15*
0.73
3.31
1.84
3.43*
8.84*
9.57*
1.97
5.57*
1.09
Note: *null hypothesis of no structural change
is rejected at 5% significance level
5.3
Model Selection
The linear form is simple and the estimated coefficients directly reflect the shadow
prices of the product characteristic. The estimated coefficients in the log-log form can
be interpreted as the partial elasticities of price with respect to the characteristics.
¯ 2 ),
We use three indicators to evaluate the functional forms, namely, adjusted R2 (R
Akaike’s Information Criterion (AIC), and Schwarz’s Bayesian Information Criterion
(BIC). The results for the yearly regressions are shown in table 7. The log-log form
¯ 2 for most years. In comparison to other two functional forms, the
has better R
¯ 2 for all yearly regressions. The AIC and SC
semilog form gives relatively inferior R
indicate that the log-log form performs relatively well after 2005. Based on these
results, the log-log functional form is selected to run the regressions in constructing
the quality-adjusted price indices.
5.4
Multicollinearity
In general, when manufacturers release new models, some technical attributes are upgraded concurrently. For instance, colour screens usually come with larger diagonal
12
Table 7: Model Selection Statistics
Year
Criterion
Linear
Semilog
Log-Log
2002
2006
¯2
R
AIC
BIC
¯2
R
AIC
BIC
¯2
R
AIC
BIC
¯2
R
AIC
BIC
¯2
R
2007
AIC
BIC
¯2
R
2008
AIC
BIC
¯2
R
2009
AIC
BIC
¯2
R
0.7382
149.68
153.07
0.4435
180.37
183.91
0.8382
250.94
257.76
0.9503
480.95
493.90
0.9097
371.26
382.54
0.7817
512.28
525.38
0.7118
454.39
466.38
0.8270
246.01
253.96
0.9493
124.88
128.27
0.6842
5.91
9.30
0.4760
7.63
11.17
0.7600
0.79
7.60
0.8872
−18.70
−5.75
0.8550
−10.46
0.81
0.6758
29.61
42.71
0.7368
19.69
31.68
0.7755
18.78
26.73
0.9031
−0.30
3.09
0.7624
2.21
5.60
0.6112
3.16
6.70
0.7283
3.64
10.46
0.9246
−37.68
−24.73
0.9211
−32.98
−21.71
0.8315
−1.81
11.28
0.8653
−7.77
4.23
0.8778
4.79
12.74
0.9562
−10.61
−7.23
2003
2004
2005
2010
AIC
BIC
¯2
R
AIC
BIC
dimensions. The Pearson product-moment correlation coefficient (Pearson’s r) between the variables log SCREEN and COLOUR is 0.6290, which is not small. Also,
the Pearson’s r for log SCREEN and log CAP is 0.6934, and appear not to be uncorrelated. Nevertheless, the values of another key indicator to detect multicollinearity,
the variance inflation factors (VIF), are relatively small for these variables. The
maximum value is 3.24 and the mean is 2.39 (see table 8). No variables’ VIFs exceed
the “rule of thumb” value of 10. It means that the multicollinearity is not a serious
problem.
13
Table 8: Variance Inflation Factors
6
6.1
Variable
VIF
1/VIF
log SCREEN
log CAP
FLASH
COLOUR
TOUCH
log BATTERY
3.24
2.98
2.70
2.50
1.50
1.38
0.3084
0.3360
0.3708
0.3973
0.6688
0.7227
Mean VIF
2.39
Regression and Price Trends
All-year Pooled Regression
Results of all-year pooled regression in the log-log functional form are shown in
table 9. This model explains 85.16% of the variation in natural logarithm of list
prices.
Table 9: All-year Pooled Regression
Variable
log CAP
FLASH
log BATTERY
log SCREEN
COLOUR
TOUCH
D2003
D2004
D2005
D2006
D2007
D2008
D2009
D2010
constant
Coefficient
t-statistic
0.2356
0.2313
0.1739
0.2769
0.1251
0.4363
−0.2987
−0.4181
−0.5834
−0.9038
−1.2603
−1.3783
−1.7371
−1.8713
4.7424
14.05
4.10
4.91
3.93
2.34
8.08
−3.37
−5.18
−7.53
−10.83
−14.78
−14.94
−16.78
−16.13
44.63
Note: all coefficients are significant at 5% level
14
Table 10: All-Year Pooled Quality-Adjusted Price Index
Year
Price Index
Percentage Change
2002
2003
2004
2005
2006
2007
2008
2009
2010
1
0.7418
0.6583
0.5580
0.4050
0.2836
0.2520
0.1760
0.1539
–
−25.82%
−11.25%
−15.23%
−27.42%
−29.99%
−11.13%
−30.15%
−12.55%
The estimated coefficients of CAP and FLASH are positive and significant as
expected. Prices of models with larger capacity are higher, other things being equal.
The price of a flash-based model is estimated to be 23.13% higher than that of using
HDD. Regarding built-in display attributes, as expected, SCREEN, COLOUR and
TOUCH are positively signed, and significant at 5% level. A 1% increase in battery
life leads to 0.17% increase of model’s estimated price. Finally, the coefficients of
time dummy variables (D2003 to D2010 ) are significantly negative, meaning continuous
price decline over the sample periods.
For this all-year pooled regression in log-log form, the quality-adjusted price index
can be obtained by taking the antilog value of each year’s dummy variable coefficient
(the base year’s price index is assumed to be 1). The quality-adjusted price index
and percentage changes from previous year are shown in table 10.
The annual decrease rate of price index is between about −10% and −30%. The
average annual growth rate (AAGR) based on this method is −20.9%.
6.2
Adjacent-Year Regressions
In the context of structural changes the quality-adjusted price index based on the
all-year pooled regression result may be biased. In this section, the quality-adjusted
price index based on adjacent-year regressions in log-log form is constructed. The
quality-adjusted price index for year t is the antilog of the sum of the coefficients
of year dummy variables from the base year 2002 to year t. Starting from the
consecutive year 2002–03, eight regressions in log-log form are estimated. Results
are reported in table 11.
The average adjacent-year quality-adjusted price index declines at 21.5% per year,
which is slightly higher than that of all-year pooled price index. The maximum
decline rate is 33.6% in 2009, and the minimum is 10.7% in 2004. However, the
coefficients of time dummy variable D2004 and D2010 are not significant at 5% level
15
Table 11: Adjacent-Year Quality-adjusted Price Index
Year
Price Index
Percentage Change
2002
2003
2004
2005
2006
2007
2008
2009
2010
1
0.7077
0.6319
0.5293
0.3912
0.2776
0.2458
0.1632
0.1436
–
−29.23%
−10.70%
−16.25%
−26.09%
−29.03%
−11.47%
−33.60%
−11.97%
in adjacent-year regressions. If the coefficients of these two years are assumed to be
zero, the AAGR becomes −19.14%, which is slightly less than that of the all-year
pooled index.
6.3
Separate Yearly Regressions
With the separate yearly regressions, fitted prices are calculated based on each year’s
estimated coefficients of variables. Three commonly used of elementary price formulae, the Jevons, Carli and Dutot indices, are calculated. Since the coefficients are
estimated from the regressions in log-log form, the three indices are formulated as
follows:
• Jevons price index
1
\
\
exp(log
Pt − log
P0 ) n
Pj =
Y
Pc =
1X
\
\
exp(log
Pt − log
P0 )
n
• Carli price index
• Dutot price index
P
Pd = P
\
exp(log
Pt )
\
exp(log
P0 )
\
\
where log
P0 and log
Pt are fitted logarithmic values of list prices for the base year 0
and the comparison year t. The three elementary indices are listed in table 12. The
yearly rates of change are shown in parentheses. Figure 2 plots their price trends.
The Carli price index has higher values than other two for all years and thus
declines with the slowest rate per year (−17.4%). This conforms with the wellknown theoretical result that the Carli index is upward biased relative to the Jevons
16
Table 12: Elementary Price Indices of Digital Music Players
Year
Jevons
Carli
Dutot
2002
1
(–)
0.6472
(−35.28%)
0.6789
(4.89%)
0.5657
(−16.67%)
0.4239
(−25.08%)
0.3248
(−23.37%)
0.2856
(−12.07%)
0.1984
(−30.55%)
0.1747
(−11.94%)
1
(–)
0.6534
(−34.66%)
0.7199
(10.17%)
0.6644
(−7.70%)
0.5004
(−24.68%)
0.3852
(−23.02%)
0.3425
(−11.10%)
0.2424
(−29.23%)
0.2171
(−10.42%)
1
(–)
0.6305
(−36.95%)
0.6313
(0.13%)
0.5763
(−8.72%)
0.4291
(−25.54%)
0.3287
(−23.39%)
0.2969
(−9.69%)
0.2157
(−27.34%)
0.1826
(−15.37%)
−19.60%
−17.38%
−19.15%
2003
2004
2005
2006
2007
2008
2009
2010
AAGR
Figure 2: Elementary Price Indices
(see Diewert, 2004). The Dutot price index is relatively unstable in comparison to
the Jevons price index. The fluctuation, however, is not very significant, and their
AAGRs are close (Jevons −19.6%, Dutot −19.2%). Yu and Prud’homme (2010)
17
Table 13: Price Comparison of Digital Consumer Products
Product
Camera
PDA∗
Desktop computer
Laptop computer
Software
TV
Music player
∗
Study
Yangzom (2013)
Chwelos et al. (2008)
Berndt and Rappaport (2001)
Berndt and Rappaport (2001)
Prud’homme et al. (2005)
Grient and Haan (2003)
This study
Years
2012–2013
1999–2004
1976–1999
1983–1999
1996–2000
1999–2001
2002–2010
Price AAGR∗∗ (%)
−18
−20
−27
−21
−6
−7
−20
Personal digital assistant
Average annual growth rate
∗∗
suggest that because the estimated quality-adjusted prices are far from homogeneous, the Dutot price index is unstable if the homogeneity assumption cannot be
upheld. Therefore, the Jevons price index is the most appropriate among the three
elementary price formulae. The Jevons price index declines somewhat slower than
the price indices constructed from all-year pooled and adjacent-year regressions, but
the differences are not very significant.
6.4
Comparison to Other IT Products
Table 13 compares the average annual price changes of some selected digital consumer
products. The average annual price declines range from 6% for computer software
to 27% for desktop computers. It is interesting to observe that the average price
decline for digital music players we find in this study is comparable to those of
digital cameras, personal digital assistants, and laptop computers. These markets
are considered to be highly competitive with no dominant producers. Our results
suggest that the market price for digital music players behaves closely with other
similar digital consumer products.
7
Conclusion
The objective of this paper is to investigate the likelihood of contestability in the
digital music player market. Since the introduction of the iPod series, the market
has been dominated by one company, namely Apple Inc. Theoretically, the characteristics of the market do not satisfy the concept of a perfect contestable market.
The presence of sunk costs in product design and development, marketing and advertising, and product differentiation implies that the competition is imperfectly
contestable at best. Consequently, the incumbents, in particular the market leader,
do not earn zero economic profit.
We estimate the price trend of portable digital music players in United States
for the period 2002–2010. Quality-adjusted price indices are constructed by hedonic
18
methods. The results indicate that the average market price declines at about 20%
per year. Since the estimates are based on list prices, not actual “street” prices, the
decline rates should be viewed as the lower-bounds of the true quality-adjusted price
declines.
We find that the average price decline is comparable to other similar digital
consumer products such as camera, personal digital assistant, and laptop computers.
There are no dominant producers in these other markets so that price competitions
are quite intensive. This suggests that although the digital music player market in
highly concentrated, price competition is nonetheless strong. We do not know the
exact pricing strategy of the leading firm, but it seem fair to suggest that the market
is somewhat contestable.
As smart phones have developed rapidly after 2007, the demand for portable digital audio players falls because smart phones can perform what portable digital audio
players do. As a result, the sales of portable digital audio players decline. Major
manufacturers have changed their focus to the smart phone market and slowed down
the portable digital audio player development, or even terminated the production.
Therefore, this study can also be extended to study the market behaviours of smart
phones in the future.
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