Abstract
Although most studies of file-sharing have concluded that file-sharing has decreased record sales, the extent of the decreased sales often seems uneven. This paper demonstrates that the results are more uniform than previously understood once a consistent metric is used to provide easy comparability across studies. This paper uses the percent of the decline in record sales that is due to file-sharing as a metric to translate the results of the literature into a common framework and then summarizes those results. What has not been previously noted is that the estimates from most studies imply that the impact of file-sharing was sufficient to have caused the entire decline in record sales that occurred from the advent of Napster up to about 2005. A smaller number of studies using post-2005 data indicate that the shift to digital formats may also have contributed to the sales decline that continued after 2005.
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Notes
Napster (the initial popular file-sharing site) was born in 1999, grew to prominence in 2000, and was shut down in 2001, as documented in Liebowitz (2006).
In most instances, there is no direct measure of file-sharing. Instead, a proxy, such as Internet usage, is often used. This may overstate the impact of organized file-sharing because other uses of the Internet that might reduce record sales (such as exchanging music files using email) cannot be separated from the impact of programs allowing organized and anonymous file-sharing. The results for these studies should probably be understood either to include a wider aspect of sharing files than organized file-sharing systems, or else to indicate an estimated result that is biased upward. Using the Internet, particularly for other forms of entertainment, might also usurp a user’s time that would otherwise be used listening to music, causing a different upward bias in the estimated impact of file-sharing, although Liebowitz (2008) has estimated this bias to be quite small.
The substitutability between originals and copies depends on how easy it is for unauthorized mp3 files to be played on the same audio devices and in the same locations as the legitimate purchased music that was available on CDs. In the early days of file-sharing, MP3 files could not be played on most audio systems and converting MP3 files into the WAV files found on CDs required a CD burner which many users did not yet own. Over time, CD and DVD players gained the ability to play MP3 files, CD burners became commonplace, and MP3 players, such as the iPod, became the centerpiece of home and auto audio systems although the timing differed by country. These advances in technology increasingly made illicit downloads better substitutes for purchased originals.
Oberholzer-Gee and Strumpf (2009) apply the identical term “displacement rate” to metric 3.
This statement is taken from the abstract of Rob and Waldfogel (2006).
Liebowitz (2006) discusses various estimates of the relative size of the illicit download market (FS) relative to the legitimate market (RS) and concludes that the estimates of relative size are wildly disparate and that many estimates of the illicit market indicate that it is considerably larger than the legitimate market.
One might generalize this to try to account for a decline from any trendline, not just zero. If the actual growth of sales fell below trend, then even with an increase in sales, it would be reasonable to consider the deviation from trend as lost sales and we could then examine the fraction of lost sales, measured in this way, that is due to file-sharing. However, because those lost sales are conjectural, I have not recommended that approach here. Nevertheless, as we will see below, it is not unreasonable to encounter an effect of file-sharing that exceeds 100 % of the observed decline in legitimate sales, implying that an upward trendline would have continued if not for file-sharing.
The US data on unit sales and revenues come from the RIAA Web site. Because subscriptions do not easily translate into CD sales, unit sales become less reliable after 2010 due to the growth of subscription and streaming revenue which first surpassed 5 % of total consumer revenue in 2011 and rose to 14 % of consumer revenue in 2013.
The non-US revenues come from an IFPI database that is used to produce their yearly “Recording Industry in Numbers” report. The numbers for the non-US portion of the world are only approximations because the IFPI converts all foreign currencies to US dollars at a single year’s exchange rate. This will not cause problems as long as inflation rates in the rest of the world are similar to those in the USA In fact, Japan has had considerably lower inflation, the Eurozone a slightly lower rate and developing countries a higher inflation rate. The further the average inflation rate in the rest of the world (weighted by record sales) from the US rate, the less reliable will be the inflation adjustment for non-US countries. With no adjustment for inflation, nominal non-US sales fell by 46 %.
Professor Hong, in his 2013 article, prefers a result of 20 % although he found that the overall result after trying to control for compositional changes in his data was 40 %. His preference for the 20 % value is based in large part on the fact that when he subdivides his population data into cohorts, some of the coefficients are statistically insignificant even though their values still imply an overall 40 % decline. He chooses to set these insignificant coefficients to zero, thus lowering the overall impact to 20 %. But having less than typical statistical confidence in a result does not imply that a result of zero is more appropriate than the measured coefficient. Thus, I list both numbers.
Professor Hong, in correspondence, suggested that his 2007 result not be given equal consideration to those from his 2013 paper because he did not try to control for compositional changes in his 2007 paper (although his 2007 paper appears to be written after his 2013 paper). Because he has not withdrawn or repudiated his 2007 paper, however, and because we cannot know whether he has truly been successful in controlling for compositional changes in his 2013 paper, I include the paper in Table 2. Even if his 2007 paper were removed from the Table, however, it would merely lower the share of papers finding that the entire decline was due to file-sharing from 63 % (7.5/12) to 59 % (6.5/11). Also, the average value of Metric 3 for all papers would still be over 100 %.
See page 7, “Recording Industry in Numbers,” 2014, IFPI.
Figure 1 is based on a data set from the IFPI titled “Recorded Music Sales by Territory 1997–2012”, and updated for 2013 using the IFPI “Recording Industry in Numbers,” 2014. Performing Rights and Synchronization Fees are not included since they do not represent sales of prerecorded music to consumers. In the European market the share of digital is 37 %.
The RIAA revenue figures for the USA are based on an estimate of final retail price and thus include all these costs. The IFPI values are wholesale prices and do not include the retailing costs.
News stories indicated that iTunes pressured the record companies to keep prices below those preferred by the record companies, making the possibility of inelastic demand more likely.
It is well known that only a competitive industry could be operating in an inelastic region of the demand curve because industry profit maximization (as would occur with a monopoly or cartel) requires that the industry operate in the elastic portion of demand.
ITunes insisted that companies wishing to sell albums also make available as singles all individual songs from the album. In addition, news articles indicated that Apple wanted lower prices for singles than did record companies and that Apple prevailed, at least for the first few years.
They must have concluded that allowing iTunes to sell music was profitable but they may have preferred to be able to choose if and when to unbundle the songs contained in albums.
Andersen and Frenz estimated that each illicitly downloaded song increased sales by slightly less than half a unit (.44) which would imply that would have been no sales of prerecorded music at all if file-sharing did not exist. It is difficult to take such a result seriously.
Gopal et al. (2006) find that the act of ‘sampling,’ by itself, has a positive impact on sales but they do not claim that the impact of file-sharing, although it may contain a sampling component, is positive. This judgment is directly supported by their statement “This [positive sampling result] has major implications for the music industry, in that the industry can potentially reverse the effects of online audio piracy.” This quotation makes it clear that Gopal et al. (2006) believe that piracy is likely to have an overall negative impact on the industry that might be overturned if the industry would try to encourage sampling in various venues (although one does have to read the paper fairly carefully to understand some of its conclusions).
The raw results used in these calculations can be found in the “Appendix”.
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Acknowledgments
I would like to thank Steve Margolis, Joel Waldfogel and Alejandro Zentner for their input and the Center for the Analysis of Property Rights and Innovation for financial support.
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Appendix: The creation of Metric 3 for various studies
Appendix: The creation of Metric 3 for various studies
Below is the version of Table 2 that gives more information about the exact results from calculations of Metric 3. A brief description of the calculations for each paper then follows. I tried to contact each of the authors to make sure I understood and fairly represented their papers. I heard back from all but Peitz and Waelbroeck and Blackburn.
Published/unpublished studies | Share of decline due to file-sharing (%) | Metric used | Time frame | Geography |
|---|---|---|---|---|
Hong (2007) | 110 | 1 | 1997–2002 | USA |
Hong (2013) | 20–40 | 3 | 1997–2002 | USA |
Liebowitz (2006) | 100 | 3 | 2005 | USA |
Liebowitz (2008) | 200 | 3 | 1998–2003 | USA |
Michel (2006) | 45 | 1 | 2003 | USA |
Peitz and Waelbroeck (2004) | 125 | 1 | 1998–2002 | World |
Rob and Waldfogel (2006) | 35 or 140 | 1 | 2003/4 | USA |
Waldfogel (2010) | 66 | 2 | 2008/9 | USA |
Zentner (2005) | 40–160 | 1 | 2002 | World |
Zentner (2006) | 190 | 1 | 2001 | 7 European |
Blackburn (2004) | >115 | 1 | 2003 | USA |
Zentner (2009) | 58–92 | 3 | 1997–2008 | World |
Hong (2007): He looks at the impact of the Internet on several activities, including purchases of sound recordings. Col 2 of his Table 4 directly measures the percentage change in sound recordings due to the Internet, which he finds to be 26 %. At that time (2002), US sales units had fallen by 23 %, as can be seen in Table 1 above. This leads to the ratio of 26/23.
Hong (2013): This is discussed in footnotes 10 and 11. He adjusts his initial estimates to control for the possibly changing composition of the populations used in his difference-in-difference estimates. When he makes this adjustment, he finds an overall decline of 40 % due to file-sharing. He then tries to separate these results into subcategories of users/households and although the overall results do not change, the statistical significance for some subsets of the population does change and he sets the results from the insignificant groups to zero, lowering his overall result to 20 %. As I explain in the footnotes, I do not believe that setting these values to zero is an appropriate action. He then, as an additional test, mixes two inconsistent data sets and gets results similar to 20 %.
Liebowitz (2006): The approach in this paper was to examine whether alternative hypotheses could explain any of the decline. He concluded that no alternative explanation held up very well with most being completely rejected by the data. New evidence has further confirmed this conclusion. Thus, the entire decline is attributed to file-sharing.
Liebowitz (2008): Liebowitz discusses his results in terms of Metric 3 but only to indicate that more than the entire decline is due to file-sharing (or somewhat more precisely, that Internet activities that promote piracy, which may overstate the effect of organized file-sharing narrowly defined). In Table 1, overall album sales fell by .58 units. In Table 5, line 5, file-sharing is claimed to have led to a decline of 1.19 units. This works out to almost exactly 200 % as the share of the decline that file-sharing was responsible for. Liebowitz calculated that the growth rate in sales implied by his results, in the counterfactual world without file-sharing, was 3.6 %, which seemed reasonable given the historical growth of sales in the prior three decades.
Michel (2006): He uses US data through 2003. He found a decline of 13 % that he attributes to file-sharing although the cause is likely to be somewhat broader since he does not measure file-sharing per se. Unit sales had fallen by 28 % at that time, leading to a value of 45 % for Metric 3 (13/28).
Peitz and Waelbroeck (2004): They used data for 16 large markets from 1998 through 2002. They find a 20 % decline in unit sales. Assuming that an average of the USA and non-USA (based on revenues) would mimic somewhat their sample of countries implies a decline in sales of 16 %. This leads to a value for Metric 3 of 125 % (20/16) although there is some uncertainty in this construction. Still, their estimate is almost certainly over 100 % since the USA had an early and very high drop in units the first few years after Napster, and its decline was just slightly greater than 20 %, giving slightly under 100 % as the low end estimate of Metric 3.
Rob and Waldfogel (2006): Although the text discusses their results in terms of Metric 2, they also present a result in terms of Metric 1 in which their OLS estimate translates to a 9 % decline in sales in the 2003/2004 period (this can be found on their page 53 (“downloading reduced purchases by individuals in the sample by about 9 percent”). The average sales decline in those two years is about 26 % so that Metric 3 is 35 % (9/26). Their instrumental variable approach provides an estimate that is four times as large, which thus becomes 140 %. They conservatively lead with their OLS result but always mention both, so I included both as well. Their results are based on a sample of students that is likely to overstate the impact of file-sharing.
Waldfogel 2010: He uses Metric 2 and finds that the share of each downloaded song that replaces a purchased song averages 27 %. From his Table 2, the size of the illicit market is 6.7 relative to the legitimate market’s 5.5, giving a ratio of 122 %. Multiplying 27 by 122 % indicates an overall decline due to file-sharing of 33 %. The average 2008/2009 decline in the USA was about 50 %, giving a Metric 3 value of 66 %. His results are based on a sample of students that is likely to overstate the impact of file-sharing.
Zentner (2005): He uses 2002 IFPI world unit sales across countries. The average of the 6 coefficient in his Table 2 is 15.5. In 2002, according to Table 1, the worldwide decline in real revenue was about 16 %. This gives a Metric 3 value of about 100 %.
Zentner (2006), using 2001 survey data from 7 European countries, found that without file-sharing sales would have been 8 % higher, or, in other words, that file-sharing appeared to decrease sound recording sales by roughly 7.4 %. European unit sales were down by 3.8 %, although there are more European countries than his seven. Nevertheless, the Metric 3 value is 195 % (7.4/3.8).
Blackburn (2004): In his Table 7, a 40 % reduction in file-sharing leads to a 17 % increase in sales and a 50 % reduction leads to a 26 % increase. Since US units sales had fallen by 23 % in 2003 and a 100 % decrease in file-sharing would have a larger impact than a 50 % decrease, the implication is that Metric 3 would be considerably larger than 115 %.
Zentner (2009): Since Zentner uses Metric 3 in his paper, one merely needs to read his discussion surrounding his Table 3. The range he presents is 58–92 %.
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Liebowitz, S.J. How much of the decline in sound recording sales is due to file-sharing?. J Cult Econ 40, 13–28 (2016). https://doi.org/10.1007/s10824-014-9233-2
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DOI: https://doi.org/10.1007/s10824-014-9233-2