Title: Lost on the Web: Does Web Distribution Stimulate or Depress Television Viewing?
1Lost on the Web Does Web Distribution Stimulate
or Depress Television Viewing?
- Joel Waldfogel
- The Wharton School
- University of Pennsylvania
2Introduction
- YouTube
- Site hosting video
- User-generated
- Network content
- Appeared in Feb 2005, rapid growth
- Top 10 sites within year
- Times Innovation of the Year 06
- My question effect on television viewing (on
network controlled viewing)
3YouTube Growth
Weve been living through an experiment
4Networks huffy about unauthorized content
5Enter the Lawyers
March 07 Viacom demands 1,000,000,000
6Networks post shows online
- late 05 and early 06
- ABC, NBC sell episodes on iTunes
- CBS at Google Video Store
- Experiments in free distribution
- May 06 ABC free on web
- Fall 06 all major networks offering multiple
shows online free - Today lots of shows available free
7ComedyCentral.com
8which brings us to the question
- How do unauthorized and authorized web
distribution of network content affect television
viewing? - Study a relevant convenience sample during a
period of change - Relevant intense web users
- Convenient on campus
- during growth of web distribution
9Cf. file sharing literature
- Music
- Close substitute, quick and easy to get
- Divided attention
- Most studies some displacement, not 11
- Movies
- Web offers poor substitute, DVD copying better
- Undivided attention
- Nearly 11 displacement
- TV different?
- Episodes complements
- Demand stimulation plausible
10Theory life without YouTube
- Watch conventional television when valuation
exceeds price - price is willingness to watch commercials,
adapt lifestyle to program schedule - (Similar to TiVo)
11Life with web distribution
- Holding distribution of valuations constant,
effects depends on whether v gt p0. - If low valuation viewers watch online, then
DWL?, no reduction in TV viewing. - But free episodes online can shift out
distribution of valuations. - Even more than in music or movies, ambiguous
effects
12Data Survey of 300 Penn students
- How often do you watch video material obtained
over the web? What authorized and unauthorized
sites/sources do you use (e.g. YouTube,
BitTorrent, abc.com)? - Since Fall 2006, how many hours per week do you
spend viewing - Authorized video on the web?
- Unauthorized video on the web
- Traditional television
- list TV shows you watched during the 2006-2007
television season - Authorized web, unauthorized web, TV frequently
or sometimes. - Ditto for 2005-2006 season
13Sites used
- Unauthorized
- YouTube dominant
- tv-links.co.uk, peekvid.com, and bittorrent
- Authorized
- abc.com, nbc.com, fox.com, cbs.com, and cnn.com
14Shows watched
- TV Greys Anatomy, Entourage, and The Daily Show
- Authorized Web Anatomy, Lost, and The Daily Show
- Unauthorized web The Daily Show, South Park, and
Scrubs
15Weekly viewing 06-07
16Series Viewing Growth 05-07
- Web viewing up
- Unauthorized doubles
- Authorized triples big network response worked
- TV flat
17Empirical Approaches
- CX do people watching more series on the web
watch fewer on TV - Longitudinal
- Aggregate do people whose web viewing rises
between seasons experience bigger changes in TV
series viewing?
18Basic CX Approach
- TV number of series watched on conventional
television, - WF number of series watched frequently on the
web - WS number of series watched sometimes on the
web - X characteristics of the respondent (age,
gender, etc.), and - e unobserved determinants of the respondents
television viewing. - do people who watch more series on the web watch
more or fewer series on conventional TV?
19Disaggregated CX approach
- Break variables into auth unauth components
- WF UNF AUF, etc
- Concern unobservables correlated with WF, WS
- (people who like TV like it via all media)
20Cross section evidence -05/06
No differences between auth unaith channels
Those who watch more shows frequently on the
web watch fewer shows on TV
This operates through shows viewed freqly on TV
21Cross section evidence -06/07
Unauthd coefs more negative
Similar, but positive coefficients in sometimes
regression
22CX interpretation
- Lots of positive coefficients
- Consistent with unobserved het or complementarity
- Whats interesting?
- Some actual negative coefficients, suggesting
substitution -
23Longitudinal approach
- Attempt to get around unobserved heterogeneity
- difference across seasons
24Figure 3 Change in Frequent Viewing on Web
(Unauthorized) and Television
Rho -0.20
25Figure 4 Change in Frequent Viewing on Web
(Authorized) and Television
rho -0.20 here too
26Estimating equation
- Analogous to CX specification
27Longitudinal estimates
Small effects overall
Positive coefs on sometimes
Little sig diff auth vs unath
Negative effects on freqly, esp freq on freq
28Longitudinal bottom line
- Smaller than CX magnitudes
- Evaluating at 2006-07 web viewing
- TVF down by 0.36
- TVS up by 0.55
-
29Translating series viewing into hours
- How do numbers of series viewed frequently or
sometimes on TV map into weekly hours?
30(No Transcript)
31Results on hours of viewing
- Implied change in weekly hours
- Authorized web 1.78
- Unauthorized web 2.26
- Overall, TV down 0.24 hours, web viewing up 4.04
hours - Effect on networks depends on value of viewers on
TV vs authorized web
32Conclusion
- Substantial use of web in this sample
- Half of TV viewing
- From zero, large growth in web viewing
- with small reduction in TV viewing
- Less displacement than in movies and music
- Movies (11) music (less) TV ( none?)
- Caveats
- Convenience sample
- Would be nice to study broader population