View source for Mortimer, Nosko and Sorensen (2012)

{{MainSource
|Source={{Source
|Name of Study=Mortimer, Nosko and Sorensen (2012)
|Author=Mortimer, J. H.;Nosko, C.;Sorensen, A.
|Title=Supply responses to digital distribution: Recorded music and live performances
|Year=2012
|Full Citation=Mortimer, J. H., Nosko, C., & Sorensen, A. (2012). Supply responses to digital distribution: Recorded music and live performances. Information Economics and Policy, 24(1), 3-14.
|Abstract=Technologies that enable free redistribution of digital goods (e.g., music, movies, software, books) can undermine sellers’ ability to profitably sell such goods, which raises concerns about the future development of socially valuable digital products. In this paper we explore the possibility that broad, illegitimate distribution of a digital good might have offsetting effects on the demand for complementary non-digital goods. We examine the impact of file-sharing on sales of recorded music and on the demand for live concert performances. We provide evidence suggesting that while file-sharing reduced album sales, it simultaneously increased demand for concerts. This effect is most pronounced for small artists, perhaps because file-sharing boosts awareness of such artists. The impact of file-sharing on large, well-known artists’ live performances is negligible.
|Authentic Link=http://www.sciencedirect.com/science/article/pii/S016762451200008X
|Reference=Teece (1986); Blackburn (2004); Zentner (2006); Rob and Waldfogel (2007); Hong(2007);
|Plain Text Proposition=The main results of this study are:

* As with the earlier literature, the study finds that sales of recorded music declined precipitously with the entry of Napster and large-scale file-sharing. 

* The evidence is consistent with illegitimate redistribution of digital goods increasing revenue from non-digital complementary products. While file-sharing may have substantially displaced album sales, it also facilitated a broader distribution of music, which appears to have expanded awareness of smaller artists and increased demand for their live concert performances. 

* Concert revenues for large artists, however, appear to have been largely unaffected by file-sharing. Music for large artists was likely widely available prior to file-sharing, and as a result it is not surprising that demand for those artists’ concerts would have been largely unaffected by file-sharing. 

* The decline in album sales is much more pronounced for large artists than for small artists. Large artists’ music may have been more readily available on file-sharing sites, in which case file-sharing would naturally have a bigger impact on large artists. But for small artists, file-sharing may have increased awareness of their music and encouraged some additional album sales from a larger fan base even as it displaced album sales to others. 

* While the market for live music appears to expand after Napster, and the market for recorded music contracts, the results imply that large artists lose market share in both markets.

* Given the sharp changes observed over a very short period of time around the entry of Napster, along with the differences in the effects for large vs. small artists, the findings in this paper are more easily explained by file-sharing than by other contemporaneous factors.
|FundamentalIssue=4. Effects of protection on industry structure (e.g. oligopolies; competition; economics of superstars; business models; technology adoption), 5. Understanding consumption/use (e.g. determinants of unlawful behaviour; user-generated content; social media),
|EvidenceBasedPolicy=D. Licensing and Business models (collecting societies; meta data; exchanges/hubs; windowing; crossborder availability), E. Fair remuneration (levies; copyright contracts), F. Enforcement (quantifying infringement; criminal sanctions; intermediary liability; graduated response; litigation and court data; commercial/non-commercial distinction; education and awareness),
|Discipline=L10: General, L82: Entertainment • Media, L86: Information and Internet Services • Computer Software
|Intervention-Response=The authors state that, "The implication, as argued by Teece (1986), is that public policy aimed at promoting innovation should not ignore the impact of an innovation on goods or assets that are complementary to it." 

Further, it is strongly implied throughout this article that rather than simply measuring the damage caused by unauthorised file-sharing in one sector of the industries, the broader costs ''and'' benefits of innovation should be carefully considered when policy is devised.
|Description of Data=The data used in this study come from several sources.  

* The data on concerts come from Pollstar. These data describe 227,230 concert events performed by 12,356 artists in the period 1993–2004. For concerts performed between 1993–2002, the data provide detailed box office information, including tickets sold, total ticket revenues, and high and low ticket prices. For 2003 and 2004, the study observes the dates, locations (city and venue name), and identities of all performing bands, but does not have data on box office receipts.

* Data on album sales come from Nielsen SoundScan, a company that tracks music sales at the point of sale. Some of the results reported are based on aggregate sales by designated market area (DMA), covering the years 1993–2002. The study observes data for a subsample of 1,806 artists matched to the concert data from Pollstar. These artists are referred to as a  “matched sample”.

* Additional data on recorded music for individual albums from MusicBrainz, an online database that tracks detailed album information for official album releases for the purpose of documenting or “tagging” downloaded music tracks.

* In addition to the detailed data on concerts and recorded music, a number of characteristics about artists and recorded releases are collected from several other sources. These include: artist characteristics from allmusic.com’s online database of artists, and data from Recorded Industry Association of America (RIAA) to measure cumulative album sales prior to 1993 for artists that were established before that date. The study also uses data from BigChampagne (collected during 2007) to measure a cross-section of downloading activity across artists and cities.
|Data Year=1993-2004; 2007
|Data Type=Secondary data
|Data Source=Pollstar; Nielsen SoundScan; RIAA; MusicBrainz; BigChampagne;
|Method of Collection=Survey Research (quantitative; e.g. sales/income reporting), Quantitative data/text mining, Longitudinal Study
|Method of Analysis=Correlation and Association, Regression Analysis
|Industry=Sound recording and music publishing;
|Country=United States;
|Cross-country=No
|Comparative=No
|Government or policy=No
|Literature review=No
|Funded By=None;
}}
|Dataset={{Dataset
|Sample Size=227230
|Level of Aggregation=Concerts,
|Data Material Year=1993-2004
}}{{Dataset
|Sample Size=1806
|Level of Aggregation=Recording Artists,
|Data Material Year=1993-2004
}}
}}