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. References Apple Inc. (2004) “iTunes Music Store Catalog Tops One Million Songs,” Apple Press Info, Available at <http://www.apple.com/pr/library/2004/08/10iTunesMusic-Store-Catalog-Tops-One-Million-Songs.html>. Associated Press (2014) “Apple Wins Class-Action Lawsuit Over iPod Prices,” The New York Times, December 16 issue. Bailey, Elizabeth E. and William J. Baumol (1984) “Deregulation and the Theory of Contestable Markets,” Yale Journal on Regulation, 1, 111– 137. Baumol, William J., John C. Panzar, and Robert D. Willig (1986) “On the Theory of Perfectly-Contestable Markets,” in Joseph E. Stiglitz and G. Frank Mathewson (eds), New Developments in the Analysis of Market Structure, Cambridge: The MIT Press. Baumol, William J., John C. Panzar, and Robert D. Willig (1988) Contestable Markets and the Theory of Industry Structure, Revised Edition, San Diego: Harcourt Brace Jovanovich Publishers. Berndt, Ernst R. and Neal J. Rappaport (2001) “Price and Quality of Desktop and Mobile Personal Computers: A Quarter-Century Historical Overview,” American Economic Review, 91(2), 268–273. 19 Chow, Gregory C. (1967), “Technological Change and the Demand for Computers”, American Economic Review, 57(5), 1117–30. Chwelos, P.D., E.R. Berndt, and I.M. Cockburn (2008) “Faster, smaller, cheaper: an hedonic price analysis of PDAs,” Applied Economics, 40(22), 2839–2856. Court, Andrew T. (1939), “Hedonic Price Indexes with Automotive Examples,” in The Dynamics of Automobile Demand, New York: General Motors Corporation, 99–117. Diewert, W. Erwin (2004) “Elementary Indices,” in Consumer Price Index Manual: Theory and Practice, Geneva: International Labour Office, Chapter 20, 355– 371. Edwards, Benj (2011) “The birth of the iPod,” Macworld, October 23 issue. Grient, Heymerik van der, and Haan Jan de (2003) “An Almost Ideal Hedonic Price Index for Televisions,” Paper presented to the International Working Group on Price Indices (Seventh Meeting), 111–122. Liegey, Paul and Nicole Shepler (1999) “Adjusting VCR Prices for Quality Change: A Study Using Hedonic Methods,” Monthly Labor Review, 122(9), 22–37. Prud’homme, Marc, Dimitri Sanga, and Kam Yu (2005) “A computer software price index using scanner data,” Canadian Journal of Economics, 38(3), 999–1017. Shepherd, William G. (1984) “ ‘Contestability’ vs. Competition,” American Economic Review, 74(4), 572–587. Stiglitz, Joseph E. (1987) “Technological Change, Sunk Costs, and Competition,” Brookings Papers on Economic Activity, 1987(3), 833–947. Triplett, Jack E. (1989) “Price and Technological Change in a Capital Good: A Survey of Research on Computers,” in Dale W. Jorgenson and Ralph Landau (eds), Technology and Capital Formation, Cambridge: The MIT Press, 127– 213. Triplett, Jack (2004) “Handbook on Hedonic Indexes and Quality Adjustments in Price Indexes: Special Application to Information Technology Products,” STI Working Paper 2004/9 Statistical Analysis of Science, Technology and Industry, OECD. Willig, Robert D. (2008) “Contestable Markets,” in Steven N. Durlauf and Lawrence E. Blume (eds), The New Palgrave Dictionary of Economics, Second Edition, Volume 2, Palgrave Macmillan, 182–187. Yangzom, Kelsang (2013) “Applying the Hedonic Quality Adjustment Method to Digital Cameras,” Unpublished study, Statistics Canada. 20 Yu, Kam and Marc Prud’homme (2010) “Econometric issues in hedonic price indices: the case of internet service providers,” Applied Economics, 42, 1973– 1994. 21
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