SlideShare a Scribd company logo
1 of 19
Download to read offline
Friends or foes?
Friends or foes?
A meta-analysis of the link between online piracy and the sales
of cultural goods
Wojciech Hardy - Michal Krawczyk - Joanna Tyrowicz
MAER-Net, Prague
September, 2015
Friends or foes?
Introduction
Motivation
Depending on who you ask
‘’Online piracy” is good for sales (activists opposing copyright)
‘’Online piracy” is bad for sales (copyright owners)
The debate is hot, but where is actually science?
Friends or foes?
Introduction
Motivation
Most known scientific result? App. 1000 citations on
ScholarGoogle
‘’The effect of file sharing on record sales: An empirical analysis”, F.
Oberholzer-Gee, K. Strumpf, JPE, 2007 – for foes
Not a single paper for friends that would exceed 100 citations, including
the critique by Liebowitz (2010, could not publish, conflict with J. List,
etc).
Original idea
Maybe the problem is in developing good causal analysis?
Spoilers
This is not a story about good economics vs. bad economics
Friends or foes?
Introduction
Theoretical underpinnings
Friends
“Pirated” copy is not a perfect substitute
Consumers are heterogenous in terms of preferences.
Consumers have “morals”, but they also have uncertainty about
“quality”.
Network effects.
Foes
“Pirated” copy is a perfect substitute for the original good.
BUT: Consumption at price = 0 cannot be compared to consumption with a
downward sloping demand curve at any price > 0.
Friends or foes?
Methods and data
Surveying the field
Starting point: grab everything we can, evaluate, run regressions
The process of data collection
1 EconLit with keywords (digital/online/music/film/-)”piracy” and
”displacement/sales/revenue/box office”.
2 Same on GoogleScholar (first 300 hits)
3 Inspect their bibliography + Smith and Telang (2012) + Dejean
(2009) + Grassmuck (2010)
4 Restricted papers in English : 72 papers.
5 Restricted to empirical: 44 papers
426 estimates
26 published papers and 18 WPs
Friends or foes?
Methods and data
Overview of the literature
Year of No. of No. of No. of Conclusions
publication published articles working papers estimates Film Music
2004 0 3 40 0 7
2005 2 0 2 0 2
2006 5 1 36 3 7
2007 5 0 85 5 3
2008 2 1 29 0 3
2009 4 1 41 2 4
2010 4 0 29 2 4
2011 0 3 16 4 2
2012 3 2 60 6 4
2013 1 7 88 6 7
Total 26 18 426 28 43
Friends or foes?
Methods and data
The literature is far from conclusive
Year of Film industry Music industry
publication Neg. Inconc. Pos. Neg. Inconc. Pos.
2004 - - - 2 2 3
2005 - - - 2 0 0
2006 2 1 0 5 0 2
2007 5 0 0 1 2 0
2008 - - - 2 0 1
2009 1 1 0 2 1 1
2010 1 1 0 3 1 0
2011 1 3 0 2 0 0
2012 2 3 1 2 0 2
2013 3 1 2 5 1 1
Total 15 10 3 26 7 10
Friends or foes?
Methods and data
Caveat 1 - how to measure sales
Table: Measures and proxies for sales (as dependent variable)
Proxy No. of papers No. of estimates
Consumer side Viewings 6 107
Purchases 11 98
Clicks on authorized websites 1 36
Expenditure 3 7
Producer side Sales 8 118
Revenues 7 57
Rank 1 3
Friends or foes?
Methods and data
Caveat 2 - how to measure piracy
Table: Measures and proxies for “piracy” (as independent variables)
Proxy No. of papers No. of estimates
Downloads 18 267
Spread of piracy 4 39
Clicks on unauthorized websites 1 36
Tech/Law change 5 32
Internet/tech proficiency 1 29
Supply 5 23
Friends or foes?
Methods and data
Caveat 3 - how can we tell if results are not spurious
Follow the author(s)
Best set
Worst set
Friends or foes?
Results
Results
Highlights
1 Little support for either of the camps, conclusions do not
depend on (how robust is the) method
2 There seems to be a negative time trend for films and
somewhat positive for music → the role of technology? or
cohorts?
Friends or foes?
Results
Putting evidence together: “meta-regression” for film
Friends or foes?
Results
Putting evidence together: “meta-regression” for music
Friends or foes?
Results
Forest plot for film studies, best set coefficients
Friends or foes?
Results
Forest plot for music studies, best set coefficients
Friends or foes?
Results
Funnel plot for film studies, best set coefficients
Friends or foes?
Results
Funnel plot for music studies, best set coefficients
Friends or foes?
Conclusions
Conclusions
1 The field is growing
Except for RIAA reports, now nearly everybody takes the effort
to actually have an identification strategy, which drives the
significance down
Literature is very far away from consensus
Data (un)availability an important constraint for growth
Conceptualization of consumer and consumer choice may be
the problem behind the null result in a meta-analysis
2 Music seems to behave differently from film
Technology development affected them at different rates
Methods of consumption (and thus preferences) differ
substantially
Friends or foes?
Conclusions
Comments or suggestions?

More Related Content

Similar to Friends or foes. A Meta Analysis of the Link Between Online Piracy and Sales of Cultural Goods

File sharing and copyright
File sharing and copyrightFile sharing and copyright
File sharing and copyrightGustavo Viegas
 
Rank all the things!
Rank all the things!Rank all the things!
Rank all the things!Jano Suchal
 
Rank all the (geo) things!
Rank all the (geo) things!Rank all the (geo) things!
Rank all the (geo) things!Jano Suchal
 
The Dark Art: Is Music Recommendation Science a Science
The Dark Art: Is Music Recommendation Science a ScienceThe Dark Art: Is Music Recommendation Science a Science
The Dark Art: Is Music Recommendation Science a Sciencempapish
 
Ján Suchal - Rank all the things!
Ján Suchal - Rank all the things!Ján Suchal - Rank all the things!
Ján Suchal - Rank all the things!ConversionMeetup
 
Collective Intelligence Meets the Political Agenda
Collective Intelligence Meets the Political AgendaCollective Intelligence Meets the Political Agenda
Collective Intelligence Meets the Political AgendaEDV Project
 
Music Recommendation Tutorial
Music Recommendation TutorialMusic Recommendation Tutorial
Music Recommendation TutorialOscar Celma
 
Artist And Repertoire Goes Online Evidence From Poland
Artist And Repertoire Goes Online  Evidence From PolandArtist And Repertoire Goes Online  Evidence From Poland
Artist And Repertoire Goes Online Evidence From PolandJoaquin Hamad
 
Easily Identify Sources of Supply Chain Gridlock
Easily Identify Sources of Supply Chain GridlockEasily Identify Sources of Supply Chain Gridlock
Easily Identify Sources of Supply Chain GridlockNeo4j
 
Statistics in Journalism
Statistics in JournalismStatistics in Journalism
Statistics in JournalismRegina Nuzzo
 
Tutorial: Context-awareness In Information Retrieval and Recommender Systems
Tutorial: Context-awareness In Information Retrieval and Recommender SystemsTutorial: Context-awareness In Information Retrieval and Recommender Systems
Tutorial: Context-awareness In Information Retrieval and Recommender SystemsYONG ZHENG
 
Eswc2013 audience short
Eswc2013 audience shortEswc2013 audience short
Eswc2013 audience shortClaudia Wagner
 
Social Media Boot Camp at PACOM 3
Social Media Boot Camp at PACOM 3Social Media Boot Camp at PACOM 3
Social Media Boot Camp at PACOM 3Eric Schwartzman
 
focusgroupdiscussionfor qualitative.pptx
focusgroupdiscussionfor qualitative.pptxfocusgroupdiscussionfor qualitative.pptx
focusgroupdiscussionfor qualitative.pptxsuruchi
 

Similar to Friends or foes. A Meta Analysis of the Link Between Online Piracy and Sales of Cultural Goods (20)

File sharing and copyright
File sharing and copyrightFile sharing and copyright
File sharing and copyright
 
BitTorrent and Bootlegs
BitTorrent and BootlegsBitTorrent and Bootlegs
BitTorrent and Bootlegs
 
Digital Musik
Digital MusikDigital Musik
Digital Musik
 
Rank all the things!
Rank all the things!Rank all the things!
Rank all the things!
 
Rank all the (geo) things!
Rank all the (geo) things!Rank all the (geo) things!
Rank all the (geo) things!
 
The Dark Art: Is Music Recommendation Science a Science
The Dark Art: Is Music Recommendation Science a ScienceThe Dark Art: Is Music Recommendation Science a Science
The Dark Art: Is Music Recommendation Science a Science
 
Ján Suchal - Rank all the things!
Ján Suchal - Rank all the things!Ján Suchal - Rank all the things!
Ján Suchal - Rank all the things!
 
Collective Intelligence Meets the Political Agenda
Collective Intelligence Meets the Political AgendaCollective Intelligence Meets the Political Agenda
Collective Intelligence Meets the Political Agenda
 
Music Recommendation Tutorial
Music Recommendation TutorialMusic Recommendation Tutorial
Music Recommendation Tutorial
 
Artist And Repertoire Goes Online Evidence From Poland
Artist And Repertoire Goes Online  Evidence From PolandArtist And Repertoire Goes Online  Evidence From Poland
Artist And Repertoire Goes Online Evidence From Poland
 
Easily Identify Sources of Supply Chain Gridlock
Easily Identify Sources of Supply Chain GridlockEasily Identify Sources of Supply Chain Gridlock
Easily Identify Sources of Supply Chain Gridlock
 
Statistics in Journalism
Statistics in JournalismStatistics in Journalism
Statistics in Journalism
 
Tutorial: Context-awareness In Information Retrieval and Recommender Systems
Tutorial: Context-awareness In Information Retrieval and Recommender SystemsTutorial: Context-awareness In Information Retrieval and Recommender Systems
Tutorial: Context-awareness In Information Retrieval and Recommender Systems
 
Eswc2013 audience short
Eswc2013 audience shortEswc2013 audience short
Eswc2013 audience short
 
Social Media Boot Camp at PACOM 3
Social Media Boot Camp at PACOM 3Social Media Boot Camp at PACOM 3
Social Media Boot Camp at PACOM 3
 
Smbc pacom-2
Smbc pacom-2Smbc pacom-2
Smbc pacom-2
 
Fys iii
Fys iiiFys iii
Fys iii
 
Mvctc
MvctcMvctc
Mvctc
 
Jessica clark ppt
Jessica clark pptJessica clark ppt
Jessica clark ppt
 
focusgroupdiscussionfor qualitative.pptx
focusgroupdiscussionfor qualitative.pptxfocusgroupdiscussionfor qualitative.pptx
focusgroupdiscussionfor qualitative.pptx
 

More from GRAPE

Gender board diversity and firm performance: evidence from European data
Gender board diversity and firm performance: evidence from European dataGender board diversity and firm performance: evidence from European data
Gender board diversity and firm performance: evidence from European dataGRAPE
 
Demographic transition and the rise of wealth inequality
Demographic transition and the rise of wealth inequalityDemographic transition and the rise of wealth inequality
Demographic transition and the rise of wealth inequalityGRAPE
 
(Gender) tone at the top: the effect of board diversity on gender inequality
(Gender) tone at the top: the effect of board diversity on gender inequality(Gender) tone at the top: the effect of board diversity on gender inequality
(Gender) tone at the top: the effect of board diversity on gender inequalityGRAPE
 
Gender board diversity spillovers and the public eye
Gender board diversity spillovers and the public eyeGender board diversity spillovers and the public eye
Gender board diversity spillovers and the public eyeGRAPE
 
Wage Inequality and women's self-employment
Wage Inequality and women's self-employmentWage Inequality and women's self-employment
Wage Inequality and women's self-employmentGRAPE
 
Contracts with Interdependent Preferences (2)
Contracts with Interdependent Preferences (2)Contracts with Interdependent Preferences (2)
Contracts with Interdependent Preferences (2)GRAPE
 
Empathy in risky choices on behalf of others
Empathy in risky choices on behalf of othersEmpathy in risky choices on behalf of others
Empathy in risky choices on behalf of othersGRAPE
 
Contracts with Interdependent Preferences
Contracts with Interdependent PreferencesContracts with Interdependent Preferences
Contracts with Interdependent PreferencesGRAPE
 
Tone at the top: the effects of gender board diversity on gender wage inequal...
Tone at the top: the effects of gender board diversity on gender wage inequal...Tone at the top: the effects of gender board diversity on gender wage inequal...
Tone at the top: the effects of gender board diversity on gender wage inequal...GRAPE
 
Gender board diversity spillovers and the public eye
Gender board diversity spillovers and the public eyeGender board diversity spillovers and the public eye
Gender board diversity spillovers and the public eyeGRAPE
 
The European Unemployment Puzzle: implications from population aging
The European Unemployment Puzzle: implications from population agingThe European Unemployment Puzzle: implications from population aging
The European Unemployment Puzzle: implications from population agingGRAPE
 
ENTIME_GEM___GAP.pdf
ENTIME_GEM___GAP.pdfENTIME_GEM___GAP.pdf
ENTIME_GEM___GAP.pdfGRAPE
 
POSTER_EARHART.pdf
POSTER_EARHART.pdfPOSTER_EARHART.pdf
POSTER_EARHART.pdfGRAPE
 
Boston_College Slides.pdf
Boston_College Slides.pdfBoston_College Slides.pdf
Boston_College Slides.pdfGRAPE
 
Presentation_Yale.pdf
Presentation_Yale.pdfPresentation_Yale.pdf
Presentation_Yale.pdfGRAPE
 
Presentation_Columbia.pdf
Presentation_Columbia.pdfPresentation_Columbia.pdf
Presentation_Columbia.pdfGRAPE
 
Presentation.pdf
Presentation.pdfPresentation.pdf
Presentation.pdfGRAPE
 
Presentation.pdf
Presentation.pdfPresentation.pdf
Presentation.pdfGRAPE
 
Presentation.pdf
Presentation.pdfPresentation.pdf
Presentation.pdfGRAPE
 
Slides.pdf
Slides.pdfSlides.pdf
Slides.pdfGRAPE
 

More from GRAPE (20)

Gender board diversity and firm performance: evidence from European data
Gender board diversity and firm performance: evidence from European dataGender board diversity and firm performance: evidence from European data
Gender board diversity and firm performance: evidence from European data
 
Demographic transition and the rise of wealth inequality
Demographic transition and the rise of wealth inequalityDemographic transition and the rise of wealth inequality
Demographic transition and the rise of wealth inequality
 
(Gender) tone at the top: the effect of board diversity on gender inequality
(Gender) tone at the top: the effect of board diversity on gender inequality(Gender) tone at the top: the effect of board diversity on gender inequality
(Gender) tone at the top: the effect of board diversity on gender inequality
 
Gender board diversity spillovers and the public eye
Gender board diversity spillovers and the public eyeGender board diversity spillovers and the public eye
Gender board diversity spillovers and the public eye
 
Wage Inequality and women's self-employment
Wage Inequality and women's self-employmentWage Inequality and women's self-employment
Wage Inequality and women's self-employment
 
Contracts with Interdependent Preferences (2)
Contracts with Interdependent Preferences (2)Contracts with Interdependent Preferences (2)
Contracts with Interdependent Preferences (2)
 
Empathy in risky choices on behalf of others
Empathy in risky choices on behalf of othersEmpathy in risky choices on behalf of others
Empathy in risky choices on behalf of others
 
Contracts with Interdependent Preferences
Contracts with Interdependent PreferencesContracts with Interdependent Preferences
Contracts with Interdependent Preferences
 
Tone at the top: the effects of gender board diversity on gender wage inequal...
Tone at the top: the effects of gender board diversity on gender wage inequal...Tone at the top: the effects of gender board diversity on gender wage inequal...
Tone at the top: the effects of gender board diversity on gender wage inequal...
 
Gender board diversity spillovers and the public eye
Gender board diversity spillovers and the public eyeGender board diversity spillovers and the public eye
Gender board diversity spillovers and the public eye
 
The European Unemployment Puzzle: implications from population aging
The European Unemployment Puzzle: implications from population agingThe European Unemployment Puzzle: implications from population aging
The European Unemployment Puzzle: implications from population aging
 
ENTIME_GEM___GAP.pdf
ENTIME_GEM___GAP.pdfENTIME_GEM___GAP.pdf
ENTIME_GEM___GAP.pdf
 
POSTER_EARHART.pdf
POSTER_EARHART.pdfPOSTER_EARHART.pdf
POSTER_EARHART.pdf
 
Boston_College Slides.pdf
Boston_College Slides.pdfBoston_College Slides.pdf
Boston_College Slides.pdf
 
Presentation_Yale.pdf
Presentation_Yale.pdfPresentation_Yale.pdf
Presentation_Yale.pdf
 
Presentation_Columbia.pdf
Presentation_Columbia.pdfPresentation_Columbia.pdf
Presentation_Columbia.pdf
 
Presentation.pdf
Presentation.pdfPresentation.pdf
Presentation.pdf
 
Presentation.pdf
Presentation.pdfPresentation.pdf
Presentation.pdf
 
Presentation.pdf
Presentation.pdfPresentation.pdf
Presentation.pdf
 
Slides.pdf
Slides.pdfSlides.pdf
Slides.pdf
 

Recently uploaded

VIP Kolkata Call Girl Serampore 👉 8250192130 Available With Room
VIP Kolkata Call Girl Serampore 👉 8250192130  Available With RoomVIP Kolkata Call Girl Serampore 👉 8250192130  Available With Room
VIP Kolkata Call Girl Serampore 👉 8250192130 Available With Roomdivyansh0kumar0
 
BPPG response - Options for Defined Benefit schemes - 19Apr24.pdf
BPPG response - Options for Defined Benefit schemes - 19Apr24.pdfBPPG response - Options for Defined Benefit schemes - 19Apr24.pdf
BPPG response - Options for Defined Benefit schemes - 19Apr24.pdfHenry Tapper
 
letter-from-the-chair-to-the-fca-relating-to-british-steel-pensions-scheme-15...
letter-from-the-chair-to-the-fca-relating-to-british-steel-pensions-scheme-15...letter-from-the-chair-to-the-fca-relating-to-british-steel-pensions-scheme-15...
letter-from-the-chair-to-the-fca-relating-to-british-steel-pensions-scheme-15...Henry Tapper
 
Financial institutions facilitate financing, economic transactions, issue fun...
Financial institutions facilitate financing, economic transactions, issue fun...Financial institutions facilitate financing, economic transactions, issue fun...
Financial institutions facilitate financing, economic transactions, issue fun...Avanish Goel
 
Interimreport1 January–31 March2024 Elo Mutual Pension Insurance Company
Interimreport1 January–31 March2024 Elo Mutual Pension Insurance CompanyInterimreport1 January–31 March2024 Elo Mutual Pension Insurance Company
Interimreport1 January–31 March2024 Elo Mutual Pension Insurance CompanyTyöeläkeyhtiö Elo
 
Vp Girls near me Delhi Call Now or WhatsApp
Vp Girls near me Delhi Call Now or WhatsAppVp Girls near me Delhi Call Now or WhatsApp
Vp Girls near me Delhi Call Now or WhatsAppmiss dipika
 
VIP Kolkata Call Girl Jodhpur Park 👉 8250192130 Available With Room
VIP Kolkata Call Girl Jodhpur Park 👉 8250192130  Available With RoomVIP Kolkata Call Girl Jodhpur Park 👉 8250192130  Available With Room
VIP Kolkata Call Girl Jodhpur Park 👉 8250192130 Available With Roomdivyansh0kumar0
 
VIP High Class Call Girls Saharanpur Anushka 8250192130 Independent Escort Se...
VIP High Class Call Girls Saharanpur Anushka 8250192130 Independent Escort Se...VIP High Class Call Girls Saharanpur Anushka 8250192130 Independent Escort Se...
VIP High Class Call Girls Saharanpur Anushka 8250192130 Independent Escort Se...Suhani Kapoor
 
Russian Call Girls In Gtb Nagar (Delhi) 9711199012 💋✔💕😘 Naughty Call Girls Se...
Russian Call Girls In Gtb Nagar (Delhi) 9711199012 💋✔💕😘 Naughty Call Girls Se...Russian Call Girls In Gtb Nagar (Delhi) 9711199012 💋✔💕😘 Naughty Call Girls Se...
Russian Call Girls In Gtb Nagar (Delhi) 9711199012 💋✔💕😘 Naughty Call Girls Se...shivangimorya083
 
Vip B Aizawl Call Girls #9907093804 Contact Number Escorts Service Aizawl
Vip B Aizawl Call Girls #9907093804 Contact Number Escorts Service AizawlVip B Aizawl Call Girls #9907093804 Contact Number Escorts Service Aizawl
Vip B Aizawl Call Girls #9907093804 Contact Number Escorts Service Aizawlmakika9823
 
Q3 2024 Earnings Conference Call and Webcast Slides
Q3 2024 Earnings Conference Call and Webcast SlidesQ3 2024 Earnings Conference Call and Webcast Slides
Q3 2024 Earnings Conference Call and Webcast SlidesMarketing847413
 
Stock Market Brief Deck for 4/24/24 .pdf
Stock Market Brief Deck for 4/24/24 .pdfStock Market Brief Deck for 4/24/24 .pdf
Stock Market Brief Deck for 4/24/24 .pdfMichael Silva
 
Monthly Market Risk Update: April 2024 [SlideShare]
Monthly Market Risk Update: April 2024 [SlideShare]Monthly Market Risk Update: April 2024 [SlideShare]
Monthly Market Risk Update: April 2024 [SlideShare]Commonwealth
 
原版1:1复刻堪萨斯大学毕业证KU毕业证留信学历认证
原版1:1复刻堪萨斯大学毕业证KU毕业证留信学历认证原版1:1复刻堪萨斯大学毕业证KU毕业证留信学历认证
原版1:1复刻堪萨斯大学毕业证KU毕业证留信学历认证jdkhjh
 
原版1:1复刻温哥华岛大学毕业证Vancouver毕业证留信学历认证
原版1:1复刻温哥华岛大学毕业证Vancouver毕业证留信学历认证原版1:1复刻温哥华岛大学毕业证Vancouver毕业证留信学历认证
原版1:1复刻温哥华岛大学毕业证Vancouver毕业证留信学历认证rjrjkk
 
Independent Lucknow Call Girls 8923113531WhatsApp Lucknow Call Girls make you...
Independent Lucknow Call Girls 8923113531WhatsApp Lucknow Call Girls make you...Independent Lucknow Call Girls 8923113531WhatsApp Lucknow Call Girls make you...
Independent Lucknow Call Girls 8923113531WhatsApp Lucknow Call Girls make you...makika9823
 
Mulki Call Girls 7001305949 WhatsApp Number 24x7 Best Services
Mulki Call Girls 7001305949 WhatsApp Number 24x7 Best ServicesMulki Call Girls 7001305949 WhatsApp Number 24x7 Best Services
Mulki Call Girls 7001305949 WhatsApp Number 24x7 Best Servicesnajka9823
 
Call Girls In Yusuf Sarai Women Seeking Men 9654467111
Call Girls In Yusuf Sarai Women Seeking Men 9654467111Call Girls In Yusuf Sarai Women Seeking Men 9654467111
Call Girls In Yusuf Sarai Women Seeking Men 9654467111Sapana Sha
 
Andheri Call Girls In 9825968104 Mumbai Hot Models
Andheri Call Girls In 9825968104 Mumbai Hot ModelsAndheri Call Girls In 9825968104 Mumbai Hot Models
Andheri Call Girls In 9825968104 Mumbai Hot Modelshematsharma006
 

Recently uploaded (20)

VIP Kolkata Call Girl Serampore 👉 8250192130 Available With Room
VIP Kolkata Call Girl Serampore 👉 8250192130  Available With RoomVIP Kolkata Call Girl Serampore 👉 8250192130  Available With Room
VIP Kolkata Call Girl Serampore 👉 8250192130 Available With Room
 
BPPG response - Options for Defined Benefit schemes - 19Apr24.pdf
BPPG response - Options for Defined Benefit schemes - 19Apr24.pdfBPPG response - Options for Defined Benefit schemes - 19Apr24.pdf
BPPG response - Options for Defined Benefit schemes - 19Apr24.pdf
 
letter-from-the-chair-to-the-fca-relating-to-british-steel-pensions-scheme-15...
letter-from-the-chair-to-the-fca-relating-to-british-steel-pensions-scheme-15...letter-from-the-chair-to-the-fca-relating-to-british-steel-pensions-scheme-15...
letter-from-the-chair-to-the-fca-relating-to-british-steel-pensions-scheme-15...
 
Financial institutions facilitate financing, economic transactions, issue fun...
Financial institutions facilitate financing, economic transactions, issue fun...Financial institutions facilitate financing, economic transactions, issue fun...
Financial institutions facilitate financing, economic transactions, issue fun...
 
Interimreport1 January–31 March2024 Elo Mutual Pension Insurance Company
Interimreport1 January–31 March2024 Elo Mutual Pension Insurance CompanyInterimreport1 January–31 March2024 Elo Mutual Pension Insurance Company
Interimreport1 January–31 March2024 Elo Mutual Pension Insurance Company
 
Vp Girls near me Delhi Call Now or WhatsApp
Vp Girls near me Delhi Call Now or WhatsAppVp Girls near me Delhi Call Now or WhatsApp
Vp Girls near me Delhi Call Now or WhatsApp
 
VIP Kolkata Call Girl Jodhpur Park 👉 8250192130 Available With Room
VIP Kolkata Call Girl Jodhpur Park 👉 8250192130  Available With RoomVIP Kolkata Call Girl Jodhpur Park 👉 8250192130  Available With Room
VIP Kolkata Call Girl Jodhpur Park 👉 8250192130 Available With Room
 
VIP High Class Call Girls Saharanpur Anushka 8250192130 Independent Escort Se...
VIP High Class Call Girls Saharanpur Anushka 8250192130 Independent Escort Se...VIP High Class Call Girls Saharanpur Anushka 8250192130 Independent Escort Se...
VIP High Class Call Girls Saharanpur Anushka 8250192130 Independent Escort Se...
 
Russian Call Girls In Gtb Nagar (Delhi) 9711199012 💋✔💕😘 Naughty Call Girls Se...
Russian Call Girls In Gtb Nagar (Delhi) 9711199012 💋✔💕😘 Naughty Call Girls Se...Russian Call Girls In Gtb Nagar (Delhi) 9711199012 💋✔💕😘 Naughty Call Girls Se...
Russian Call Girls In Gtb Nagar (Delhi) 9711199012 💋✔💕😘 Naughty Call Girls Se...
 
🔝+919953056974 🔝young Delhi Escort service Pusa Road
🔝+919953056974 🔝young Delhi Escort service Pusa Road🔝+919953056974 🔝young Delhi Escort service Pusa Road
🔝+919953056974 🔝young Delhi Escort service Pusa Road
 
Vip B Aizawl Call Girls #9907093804 Contact Number Escorts Service Aizawl
Vip B Aizawl Call Girls #9907093804 Contact Number Escorts Service AizawlVip B Aizawl Call Girls #9907093804 Contact Number Escorts Service Aizawl
Vip B Aizawl Call Girls #9907093804 Contact Number Escorts Service Aizawl
 
Q3 2024 Earnings Conference Call and Webcast Slides
Q3 2024 Earnings Conference Call and Webcast SlidesQ3 2024 Earnings Conference Call and Webcast Slides
Q3 2024 Earnings Conference Call and Webcast Slides
 
Stock Market Brief Deck for 4/24/24 .pdf
Stock Market Brief Deck for 4/24/24 .pdfStock Market Brief Deck for 4/24/24 .pdf
Stock Market Brief Deck for 4/24/24 .pdf
 
Monthly Market Risk Update: April 2024 [SlideShare]
Monthly Market Risk Update: April 2024 [SlideShare]Monthly Market Risk Update: April 2024 [SlideShare]
Monthly Market Risk Update: April 2024 [SlideShare]
 
原版1:1复刻堪萨斯大学毕业证KU毕业证留信学历认证
原版1:1复刻堪萨斯大学毕业证KU毕业证留信学历认证原版1:1复刻堪萨斯大学毕业证KU毕业证留信学历认证
原版1:1复刻堪萨斯大学毕业证KU毕业证留信学历认证
 
原版1:1复刻温哥华岛大学毕业证Vancouver毕业证留信学历认证
原版1:1复刻温哥华岛大学毕业证Vancouver毕业证留信学历认证原版1:1复刻温哥华岛大学毕业证Vancouver毕业证留信学历认证
原版1:1复刻温哥华岛大学毕业证Vancouver毕业证留信学历认证
 
Independent Lucknow Call Girls 8923113531WhatsApp Lucknow Call Girls make you...
Independent Lucknow Call Girls 8923113531WhatsApp Lucknow Call Girls make you...Independent Lucknow Call Girls 8923113531WhatsApp Lucknow Call Girls make you...
Independent Lucknow Call Girls 8923113531WhatsApp Lucknow Call Girls make you...
 
Mulki Call Girls 7001305949 WhatsApp Number 24x7 Best Services
Mulki Call Girls 7001305949 WhatsApp Number 24x7 Best ServicesMulki Call Girls 7001305949 WhatsApp Number 24x7 Best Services
Mulki Call Girls 7001305949 WhatsApp Number 24x7 Best Services
 
Call Girls In Yusuf Sarai Women Seeking Men 9654467111
Call Girls In Yusuf Sarai Women Seeking Men 9654467111Call Girls In Yusuf Sarai Women Seeking Men 9654467111
Call Girls In Yusuf Sarai Women Seeking Men 9654467111
 
Andheri Call Girls In 9825968104 Mumbai Hot Models
Andheri Call Girls In 9825968104 Mumbai Hot ModelsAndheri Call Girls In 9825968104 Mumbai Hot Models
Andheri Call Girls In 9825968104 Mumbai Hot Models
 

Friends or foes. A Meta Analysis of the Link Between Online Piracy and Sales of Cultural Goods

  • 1. Friends or foes? Friends or foes? A meta-analysis of the link between online piracy and the sales of cultural goods Wojciech Hardy - Michal Krawczyk - Joanna Tyrowicz MAER-Net, Prague September, 2015
  • 2. Friends or foes? Introduction Motivation Depending on who you ask ‘’Online piracy” is good for sales (activists opposing copyright) ‘’Online piracy” is bad for sales (copyright owners) The debate is hot, but where is actually science?
  • 3. Friends or foes? Introduction Motivation Most known scientific result? App. 1000 citations on ScholarGoogle ‘’The effect of file sharing on record sales: An empirical analysis”, F. Oberholzer-Gee, K. Strumpf, JPE, 2007 – for foes Not a single paper for friends that would exceed 100 citations, including the critique by Liebowitz (2010, could not publish, conflict with J. List, etc). Original idea Maybe the problem is in developing good causal analysis? Spoilers This is not a story about good economics vs. bad economics
  • 4. Friends or foes? Introduction Theoretical underpinnings Friends “Pirated” copy is not a perfect substitute Consumers are heterogenous in terms of preferences. Consumers have “morals”, but they also have uncertainty about “quality”. Network effects. Foes “Pirated” copy is a perfect substitute for the original good. BUT: Consumption at price = 0 cannot be compared to consumption with a downward sloping demand curve at any price > 0.
  • 5. Friends or foes? Methods and data Surveying the field Starting point: grab everything we can, evaluate, run regressions The process of data collection 1 EconLit with keywords (digital/online/music/film/-)”piracy” and ”displacement/sales/revenue/box office”. 2 Same on GoogleScholar (first 300 hits) 3 Inspect their bibliography + Smith and Telang (2012) + Dejean (2009) + Grassmuck (2010) 4 Restricted papers in English : 72 papers. 5 Restricted to empirical: 44 papers 426 estimates 26 published papers and 18 WPs
  • 6. Friends or foes? Methods and data Overview of the literature Year of No. of No. of No. of Conclusions publication published articles working papers estimates Film Music 2004 0 3 40 0 7 2005 2 0 2 0 2 2006 5 1 36 3 7 2007 5 0 85 5 3 2008 2 1 29 0 3 2009 4 1 41 2 4 2010 4 0 29 2 4 2011 0 3 16 4 2 2012 3 2 60 6 4 2013 1 7 88 6 7 Total 26 18 426 28 43
  • 7. Friends or foes? Methods and data The literature is far from conclusive Year of Film industry Music industry publication Neg. Inconc. Pos. Neg. Inconc. Pos. 2004 - - - 2 2 3 2005 - - - 2 0 0 2006 2 1 0 5 0 2 2007 5 0 0 1 2 0 2008 - - - 2 0 1 2009 1 1 0 2 1 1 2010 1 1 0 3 1 0 2011 1 3 0 2 0 0 2012 2 3 1 2 0 2 2013 3 1 2 5 1 1 Total 15 10 3 26 7 10
  • 8. Friends or foes? Methods and data Caveat 1 - how to measure sales Table: Measures and proxies for sales (as dependent variable) Proxy No. of papers No. of estimates Consumer side Viewings 6 107 Purchases 11 98 Clicks on authorized websites 1 36 Expenditure 3 7 Producer side Sales 8 118 Revenues 7 57 Rank 1 3
  • 9. Friends or foes? Methods and data Caveat 2 - how to measure piracy Table: Measures and proxies for “piracy” (as independent variables) Proxy No. of papers No. of estimates Downloads 18 267 Spread of piracy 4 39 Clicks on unauthorized websites 1 36 Tech/Law change 5 32 Internet/tech proficiency 1 29 Supply 5 23
  • 10. Friends or foes? Methods and data Caveat 3 - how can we tell if results are not spurious Follow the author(s) Best set Worst set
  • 11. Friends or foes? Results Results Highlights 1 Little support for either of the camps, conclusions do not depend on (how robust is the) method 2 There seems to be a negative time trend for films and somewhat positive for music → the role of technology? or cohorts?
  • 12. Friends or foes? Results Putting evidence together: “meta-regression” for film
  • 13. Friends or foes? Results Putting evidence together: “meta-regression” for music
  • 14. Friends or foes? Results Forest plot for film studies, best set coefficients
  • 15. Friends or foes? Results Forest plot for music studies, best set coefficients
  • 16. Friends or foes? Results Funnel plot for film studies, best set coefficients
  • 17. Friends or foes? Results Funnel plot for music studies, best set coefficients
  • 18. Friends or foes? Conclusions Conclusions 1 The field is growing Except for RIAA reports, now nearly everybody takes the effort to actually have an identification strategy, which drives the significance down Literature is very far away from consensus Data (un)availability an important constraint for growth Conceptualization of consumer and consumer choice may be the problem behind the null result in a meta-analysis 2 Music seems to behave differently from film Technology development affected them at different rates Methods of consumption (and thus preferences) differ substantially