How Bad Is Music File Sharing? – Part 10

Wendy Chi examined in a John Hopkins University working paper (Chi 2008) whether file sharing crowds out purchases of physical and digital music by using Forrester Research’s consumer mail surveys for the years 2004 to 2006, which are representative samples for the U.S. and Canada. In her study, Chi comes to the result that “illegal” downloads and physical and non-physical music purchases are positively correlated and that the sampling effect of file sharing dominates the substitution effect. Therefore filesharing does not necessarily hurt music sales. Why this should be the case can be read here.

The surveys are representative for all age groups between 18 and 99 in the U.S. and Canada and include 60,000 households. They contain 90 questions about the respondents’ adoption of technology. The surveys provide detailed information on hours spent on TV, Internet, and radio. They include variables indicating the purchases of physical and non-physical music, “illegal” music downloads, type of Internet access, and ownership of portable music players. For purchasing music online, the data also contain information on the frequency of buying (daily, a few times a week, or a few times a month). In addition, the data also provide information on technology adaption, including whether one publishes a webpage, writes audio CDs, participates in online auctions, uses instant messaging, reads computer magazines, searches for free or discounted goods and services, and purchases software, books, DVDs, and videogames.

Descriptive statistics show that the percentage of people who bought music within three months prior to the survey decreased from 26.66% to 17.36%. The percentage of people who regularly downloaded music for free slightly decreased from 8.85% in 2005 to 7.90% in 2006. However, the propability of music purchases for people who regularly download music for free is much higher than the propability of music purchases for people who do not regularly download “illegal” music. This result is consistant across all three years.

In order to test these findings statistically, the author examined the individuals’ decision to purchase music by estimating a standard probit model with Xi as vector of individual characteristics, P2Pi as a dummy variable and εi as a normally distributed random error. However, if the file sharing variable and the error term are correlated (not independent), the single-equation probit estimates will be biased. Therefore, Chi used a bivariant probit model with instrument variables. As instruments, active participation in religious activities and violations of traffic laws within last twelve months were used. This implies that individuals who violate traffic laws are less concerned about being prosecuted and are more likely to violate intellectual property laws as well. Therefore, the author found a positive correlation between file sharing and whether one received parking tickets in the last twelve months – an information that is also included in the Forrester Research’s surveys. On the other hand, active participants in religious activities are expected to be less likely to violate laws, especially IPRs. Chi, thus, found a negative correlation between illegal downloads and church attendance. In addition, instrument measures of one’s comfort with digital technology including the frequent use of CD writers, the publishing of a webpage, participation in online auction, hours spent online, one’s attitude towards technology were also included in the bivariant probit model. In measuring for peoples’ propensity to download music files for free, Chi not only used the measures of ethical behavior and technological affinity but also attended to the interaction of the two.

The results of the bivariante probit estimates indicate that “[t]he probability of making legal music purchases among illegal-downloaders greatly exceeds the probability of legal music purchases among non-illegal downloaders” (Chi 2008: 14). Since the sample mean of the treatment group (“illegal” downloaders) is greater than the sample mean of the control group, “illegal” downloads have a positive impact on physical and non-physical music purchases. All tests of instrument validity (exogeneity tests) and the robustness tests confirmed this result.

To sum up, the results suggest that “illegal” downloads and physical and non-physical music purchases are positively correlated and that the sampling effect of file sharing dominates the substitution effect.

However, Chi’s model only focuses on the difference in the participation rate of “illegal” downloaders and “non-illegal” downloaders on music purchases. It does not tell us anything about a change in music spending. Therefore, it is possible that file sharers, despite their higher prospensity for purchasing music, spend less money than non-file sharers. This could be in line with the thesis that the recent recession in the music industry is not originally caused by file sharing but by music consumers’ altered behavior. I.e. file sharers might tend to buy single tracks online instead of digital albums and CDs.

Although Chi’s study provides interesting insights into the motivation and behavior of music consumsers, it did not directly focus on the relationship between record sales and file sharing activity. In addition, the used instrument variables have to be questioned, since it is not very plausible that religious activity and violation of traffic laws really have an impact on music consumption. However, if the study’s results are reliable, the music industry’s representatives should be warned that confining music file sharing may hurt music sales, since the sampling effect of music file sharing dominates the substition effect.


Chi, Wendy, 2008, Does File Sharing Crowd Out Copyrighted Goods? Evidence from the Music Recording Industry. Working Paper, Department of Economics, Johns Hopkins University.

In part 11, Julie Holland Mortimer and Alan Sorensen paper “Supply Responses to Digital Distribution: Recorded Music and Live Performances” will be discussed.


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