Oh, Wallsten and Lovin (2019)

From Copyright EVIDENCE

Advertising Architectural Publishing of books, periodicals and other publishing Programming and broadcasting Computer programming Computer consultancy Creative, arts and entertainment Cultural education

Film and motion pictures Sound recording and music publishing Photographic activities PR and communication Software publishing (including video games) Specialised design Television programmes Translation and interpretation

1. Relationship between protection (subject matter/term/scope) and supply/economic development/growth/welfare 2. Relationship between creative process and protection - what motivates creators (e.g. attribution; control; remuneration; time allocation)? 3. Harmony of interest assumption between authors and publishers (creators and producers/investors) 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)

A. Nature and Scope of exclusive rights (hyperlinking/browsing; reproduction right) B. Exceptions (distinguish innovation and public policy purposes; open-ended/closed list; commercial/non-commercial distinction) C. Mass digitisation/orphan works (non-use; extended collective licensing) 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)

Source Details

Oh, Wallsten and Lovin (2019)
Title: Do Pirated Video Streams Crowd Out Non-Pirated Video Streams? Evidence from Online Activity
Author(s): Oh, S., Wallsten, S., Lovin, N.
Year: 2019
Citation: Oh, S., Wallsten, S. and Lovin, N. (2019) Do Pirated Video Streams Crowd Out Non-Pirated Video Streams? Evidence from Online Activity. Tech Policy Institute Working Paper.
Link(s): Open Access
Key Related Studies:
Discipline:
Linked by:
About the Data
Data Description: Data concerning raw internet traffic were obtained from ComScore Total Home Panel. This includes over one trillion observations of internet data from 19,764 American households and their 468,612 devices.
The Study uses various econometric techniques to measure whether pirated streams displaced time spent watching Netflix, Hulu, YouTube and Amazon video.
Data Type: Secondary data
Secondary Data Sources:
Data Collection Methods:
Data Analysis Methods:
Industry(ies):
Country(ies):
Cross Country Study?: No
Comparative Study?: No
Literature review?: No
Government or policy study?: No
Time Period(s) of Collection:
  • September 2016 - November 2017
Funder(s):

Abstract

“Does watching more pirated streaming video mean spending less time watching non-pirated streaming video? This study measures whether, and how much, time spent watching pirated video crowds out time spent on streaming video apps. While prior studies have estimated the impact of piracy on sales revenues, our study measures the impact of piracy on time spent on free and paid streaming apps. We combine big data tools with standard econometric techniques, including a two-stage least squares model, to analyze 5.25 terabytes of online activity data from 19,764 American households and their 468,612 devices from 2016 to 2017. The analysis suggests that every minute spent engaged with pirated video sites crowded out about 3.5minutes of time spent streaming video. Because pirated video files are generally more compressed than non-pirated video files and because they are frequently downloaded as entire files rather than streamed, as with non-pirate sites like Netflix and Amazon, we conclude that our results exhibit closer to a 1-to-1crowding out effect of piracy on over-the-top streaming video services.”

Main Results of the Study

The study finds that consumption of pirated streams crowds out consumption from non-pirated streaming apps: for every ten-minute time period spent on pirated streaming sites this is associated with approx 3.5 fewer minutes on a non-pirated streaming site. The study cautions that this figure may be underestimating the overall figure due to compression techniques used for pirated content and frequency of downloading pirated content (rather than streaming).

There is some variation of the crowding-out effect across the top five streaming services. For example, whilst this effect is noted for Netflix and Amazon, the effect with YouTube is slightly different. For every ten minutes of pirated streaming, this is associated with an additional 67 minutes of YouTube viewing. The study suggests this may be due to the more idiosyncratic viewing patterns on YouTube, which contains both user-generated and pirated materials, or the fact that this content is free, unlike non-pirated streaming sites.

Policy Implications as Stated By Author

The study does not offer any explicit policy conclusions.



Coverage of Study

Coverage of Fundamental Issues
Issue Included within Study
Relationship between protection (subject matter/term/scope) and supply/economic development/growth/welfare
Relationship between creative process and protection - what motivates creators (e.g. attribution; control; remuneration; time allocation)?
Harmony of interest assumption between authors and publishers (creators and producers/investors)
Effects of protection on industry structure (e.g. oligopolies; competition; economics of superstars; business models; technology adoption)
Understanding consumption/use (e.g. determinants of unlawful behaviour; user-generated content; social media)
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Coverage of Evidence Based Policies
Issue Included within Study
Nature and Scope of exclusive rights (hyperlinking/browsing; reproduction right)
Exceptions (distinguish innovation and public policy purposes; open-ended/closed list; commercial/non-commercial distinction)
Mass digitisation/orphan works (non-use; extended collective licensing)
Licensing and Business models (collecting societies; meta data; exchanges/hubs; windowing; crossborder availability)
Fair remuneration (levies; copyright contracts)
Enforcement (quantifying infringement; criminal sanctions; intermediary liability; graduated response; litigation and court data; commercial/non-commercial distinction; education and awareness)
Green-tick.png

Datasets

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