Television Station Ownership Structure and the
Quantity and Quality of TV Programming?
Federal Communications Commission
Media Ownership Study #3
Gregory S. Crawford
Department of Economics
University of Arizona
July 23, 2007
?I would like to thank Jim Castler at Tribune Media Services, Enid Maran at Nielsen Media Research, and
Henry Laura at TNS for working with me and the FCC in providing the data used in this study. I would also
like to thank Michelle Connolly, Chief Economist at the FCC, for her un agging support in obtaining this
data. I would particularly like to thank Joseph Cullen for his outstanding research assistance in getting the
many very large datasets used in this study to talk to each other. Correspondence may be sent to Gregory
S. Crawford, Department of Economics, University of Arizona, Tucson, AZ 85721-0108, phone 520-621-5247,
email crawford@eller.arizona.edu.
1
1 Executive Summary
In this study we analyze the relationship between the ownership structure of television stations and
the quantity and quality of television programming in the United States between 2003 and 2006.
Television programming comes in many kinds and even deflning programming of difierent kinds
can be di–cult. We report patterns of overall television availability and viewing as well as focus on
several types of programming of particular interest to the FCC that were included in the mandate
for this report.1
Regarding the quantity and quality of television programming, our focus is decidedly economic.
For each type of programming, we have three concentric quantity measures. First we consider
the programming available on each major and most minor broadcast and cable television program
networks ofiered (roughly) anywhere in the United States.2 This represents either an idealized view
ofwhat someone mighthaveavailableto them ifthey wereable to costlessly access anyprogramming
ofiered through any distribution channel anywhere in the U.S. or (perhaps more realistically) a
statement about the scope of programming being produced for consumption somewhere in the
country. Second, we weight our programming measures by network availability (i.e. is a particular
network or program "on the shelf"). This gives a sense of what share of U.S. households could
choose to view programming of a given type if they wished to do so. Finally, we examine what
households actually watch. We feel these three measures { what is produced, what is available, and
what is watched { provide a robust picture of the quantity of television programming in the United
States. Interesting patterns arise from considering each of these difierent measures.
We similarly focus on economic measures of programming quality. We have two measures. First,
we measure quality by the number of households who choose to watch a program (as measured
by the Nielsen television rating) as a share of households that have access to that programming.
This captures the idea that for programming that is free to households (i.e. broadcast television
programming or cable television programming after purchasing access to a bundle of networks),
higher quality programs will garner higher ratings. Second, we measure program quality by the
number and length (in minutes and seconds) of advertisements included on that program. This
captures the idea that the more advertisements included in a program, the less enjoyable it is to
viewers to watch that program.3
1In particular, (1) Local News and Public Afiairs Programming, (2) Minority Programming, (3) Children’s Pro-
gramming, (4) Family Programming, (5) Indecent Programming, (6) Violent Programming, and (7) Religious Pro-
gramming. See Section 4 below for the alternative deflnitions used for each of these programming types.
2In our flnal analysis, we analyze programming on 1,583 broadcast stations and 192 cable networks.
3As discussed further below, there are many other ways to interpret "quantity" and (especially) "quality" in
television markets. We chose these deflnitions for two reasons. The flrst was data complementarity and availability:
economic measures of program quality flt best with economic measures of program quantity and aesthetic measures of
program quality are both subjective and di–cult to obtain on a broad scale. The second were idiosyncratic preferences
and training: a non-economist, or an economist with a less empirical perspective, might well have selected alternative
2
While we examine what we feel is a broad range of outcomes in television markets, we limit our
ownership analysis to the relationship between the ownership structure of television stations and
the quantity and quality of television programming. While we had hopes for studying a much wider
range of ownership issues, data limitations prevented them from being realized. In particular, the
ownershipvariablesinourstudycometousfromtheFederalCommunicationCommission’s(FCC’s)
Study 2 (Diwadi, Roberts, and Wise (2007)). The focus in that study is on ownership structure
at the distribution level. For television markets, that means the ownership structure of television
stations and cable television and satellite systems. We use the data provided on television station
ownership in our study. We were unable, however, to use the data provided on ownership of cable
television and satellite systems due to limitations in our cable television data.4
Conducting the study proved to be a challenging organizational task. As noted above, we obtained
television station ownership information for every full-power broadcast television station between
2002 and 2005 from Diwadi, Roberts, and Wise (2007). We then matched this with information
about the quantity and quality of television programming from four major industry data providers.
From each provider, we obtained information on various aspects of television programming for each
of two weeks per year (in May and November) for 4 years (from 2003-2006). We obtained program
schedule data, including detailed information about individual programs, for each broadcast tele-
vision station and almost 200 cable networks from Tribune Media Services (hereafter TMS). We
obtained partial-day program ratings for each of the programs shown on broadcast television sta-
tions from Nielsen Media Research (hereafter Nielsen). We obtained average national prime-time
cable network television ratings by year from Kagan Media Research (hereafter, Kagan). Finally,
we obtained information about the quantity of and revenue from advertising on each of the pro-
grams on broadcast television stations in most of the top 108 DMAs from TNS.5 We then merged
them together and conducted the study.
With respect to our measures of the quantity of television programming, we flnd there are im-
portant difierences between the programming provided on broadcast versus cable networks for
News, Religious, and Violent programming (more on broadcast), and Public Afiairs, Children’s,
and Adult programming (more on cable). We flnd that "niche", or special-interest, programming
measures. Our hope is that the measures we chose, and in particular the links between them, will contribute something
new to the ongoing discussion of the impact of changes in media ownership on television markets.
4In particular, while Diwadi, Roberts, and Wise (2007) provides information on cable and satellite television
penetration by DMA, it does not provide information about the networks carried by those cable and satellite providers.
We explored building this information ourselves using both TMS data and data from various editions of Warren
Publishing’sCableandTelevisionFactbook(e.g. Warren(2005)), butwereunabletolinkinformationaboutownership
from the FCC’s cable system database to the either of these datasets in time for this report. Further complicating
matters was an unrelated inability to get most of our quantity and quality measures for cable programming. We
discuss the difierences in our broadcast and cable television data in Section 3 below.
5The exact time frames addressed difiered across data providers. In the flnal analysis, we used information about
the quantity and quality of television programming across 4 years, 2003-2006, and correlated that with changes in
ownership across 3 years, 2003-2005.
3
(Minority Adult, and Religious programming) is less widely available than general-interest pro-
gramming (News, Children’s, and Family programming). Examining patterns across time, we flnd
that program production and/or availability is falling across time for Network News (though not
Local News), Public Afiairs, Family, and Religious programming and rising across time for Latino,
Children’s, Adult, and the more violent of Violent programming. Also rising across time is the
average Television Content rating across all rated programs.
With respect to our measures of the quality of television programming, we flnd that in general, pro-
gramming is more highly rated on broadcast than cable networks. Of the programming types, News
and Violent programming are the most highly rated (i.e. highest quality), with Latino/Spanish-
language, Children’s and Family programming substantially lower, and non-Latino Minority and
Religious programming lower still. Examining patterns over time, we flnd that the relative quality
of News programming is declining with some measures of Children’s programming and the more
violent Violent programming gaining ground. With respect to advertising market outcomes, we flnd
that a–liates of the Big-4 broadcast networks (ABC, CBS, NBC, and Fox) provide more advertising
minutes at higher prices than do other broadcast television stations and that this advantage ap-
pears to be increasing over time. From the perspective of a viewer (households), rising advertising
minutes suggest the quality of television programming is falling over time.
We relate these measures to the ownership structure of broadcast television stations. Our strongest
flndings are for Local News: television stations owned by a parent that also owns a newspaper in the
area ofier more local news programming. By some methods, television stations owned by corporate
parents with larger annual revenue also ofier more Local News, but by other methods they ofier
less. This is an important area for further inquiry. We flnd that local ownership is correlated
with more Public Afiairs and Family programming. While we flnd important and interesting
difierences in the amount of Violent programming across network a–liates, it does not appear to
be correlated in an economically and statistically signiflcant way with ownership structure. Efiects
of ownership structure on other programming types or on outcomes in the advertising market
are either economically insigniflcant, statistically insigniflcant, or difier in their predicted efiects
according to the method of analysis.
Therestofthisreportproceedsasfollows. InSection2webrie ydescribetheeconomicorganization
of television markets. In Section 3 we describe our sources of data and in Section 4 describe the
deflnition of the programming types that form the basis of the study and the aggregation we do
to analyze the data. Section 5 describes patterns of the quantity and quality of programming in
the television industry and Section 6 relates these to the ownership structure of local television
markets. Section 7 concludes.
4
2 The Television Industry: A Study of Two-Sided Markets
Measuring the relationship between ownership structure and the quantity and quality of television
programming flrst requires an understanding of the economic environment in which that program-
ming is provided. I brie y describe the economic organization of the television industry in this
section.
The television market is an example of what economists call two-sided markets. Like any product,
consumers of television programming value it and (in some way) are willing to pay for it.6 Call
the market in which this happens the Content Market. Unlike most products, however, their
consumption creates another product, audiences, which the television provider can then sell to
advertisers. Call the market in which this happens the Advertising Market.
There has been considerable research in the last several years on the unusual economics of two-sided
markets like that in the television industry (e.g. Anderson and Gabszewicz (2005)).7 For example,
if one side of the market (e.g. advertisers) values highly the number of consumers on the other
side of the market (e.g. viewers), prices to the second (viewer) side can be decreased below cost.8
Furthermore, a merger on one side of a two-sided market can increases competition on the other
side, increasing total welfare (Rochet and Tirole (2006)). While I will not address such issues in
this report, they highlight a common theme in the analysis of two-sided markets: flrms that want to
maximize proflts or policy-makers that want to maximize social welfare must analyze the outcomes
in and the links between both markets. And so in this study I will examine the relationship between
ownership structure and features of both the Content and Advertising markets.
But which content market(s)? Which advertising market(s)? For each of these markets, there is a
vertical "supply chain", i.e. a sequence of markets through which content (audiences) must pass
before it is made available to viewers (advertisers). This is most clearly seen in the Content Market,
so I focus the subsequent discussion there.
Before a typical consumer can watch a typical program, it must make it to the screen of the
television that she turns on. Figure 1 provides a graphical representation of this process in the tele-
vision programming industry. Downward arrows represent the  ow of programming from Content
Providers to Consumers. The distribution rights to most content (e.g. a television program like
"Crocodile Hunter") is purchased by a Television Network (e.g. CBS or The Discovery Channel)
and placed in its programming lineup (see, e.g., Owen and Wildman (1992)). These networks are
6This payment may be in terms of actual money paid to a television provider or in terms of attention given to the
advertisements on a freely-available program.
7Much of this research was sparked by prominent antitrust cases involving flrms in two-sided markets (e.g. United
States v. VISA U.S.A, United States v. Microsoft). See Rochet and Tirole (2006) for a recent survey with an
economic focus and Evans (2003) for a recent survey with an antitrust focus.
8Such is free (to consumers, not to advertisers) broadcast television born.
5
then distributed to consumers in one of two ways. Broadcast Networks like ABC, CBS, and NBC
distribute their programming over the air via local broadcast television stations at no cost to house-
holds. Cable Television Networks like The Discovery Channel, MTV, and ESPN instead distribute
their programming via cable or satellite television systems that charge fees to consumers.9
Upward arrows represent the creation and sale of audiences to advertisers as a consequence of
television viewing by consumers. Some audiences, represented by the dashed line at the right
of the flgure, are sold directly to advertisers by distributors of television networks, particularly
those created by local or regional programming. Most audiences, however, are aggregated across
distribution channels (e.g. the total viewers to ESPN across all cable and satellite systems) and
sold to advertisers by program networks.10
The various sub-markets that characterize the purchase and sale of content or audiences are in-
dicated at each step in the chain. For example, Content Providers sell their content to television
networks in what I call the Program (Production) Market, Networks sell access to all their con-
tent to broadcast and cable television systems in the Program (Network) Market, and Consumers
purchase access to programming in the (Program) Distribution Market.
Ownership structure at any point in the chain of either market can in uence outcomes like the
quantity and quality of television programming provided to households.11 As noted above, for
reasons of data availability we focus in this study on the relationship between the ownership struc-
ture of broadcast television stations and the quantity and quality of television programming. This
will necessarily give only part of the picture about the full relationship between media ownership
structure and television programming. We raise this issue not to belittle the insights we provide
here, but to highlight the value of extending what we have done here not only to other distribution
channels (e.g. cable and satellite systems, eventually to Internet distribution), but also to the Pro-
gram Network, Program Production, and Audience (Advertising) markets and to the ownership
links between them.
3 Data
In this section, we describe the sources of data used in the study.
9The dashed arrow between content providers and consumers represents the small but growing trend to distribute
some content directly to consumer via the Internet (e.g. the television programs "Lost" and "Desperate Housewives").
10Even this is an incomplete picture. For example, some programming, particularly syndicated programming, is
sold directly from content providers to broadcast television stations.
11For example, Wilbur (2005) flnds that more programming is provided that matches advertiser preferences (e.g.
targeting adult males) than that matches viewer preferences.
6
3.1 Television Station Ownership Data
Our ownership data on broadcast television stations comes from Diwadi, Roberts, and Wise (2007).
The interested reader is referred there for more details. We describe the key variables we use in
our study in Section 6 below.
3.2 Programming Data
Overview The FCC agreed to purchase data on our behalf in order to address the issues in
this study. We would ideally have obtained information on every program on every channel (or
network) on every broadcast television and cable system in the U.S. over a fairly long time horizon.
Ofcourse, this provedboth tooexpensiveand toomuchdatato tractably analyze. As acompromise,
we obtained information on every program on every major broadcast television station and cable
network for two weeks of every year between 2003 and 2006. The weeks chosen were selected
during two of the Nielsen "sweeps Months" to facilitate obtaining Nielsen’s DMA-level television
ratings data for each program. The Nielsen TV year runs roughly September through May,12 so
we selected weeks near the beginning and end of the Nielsen year. We tried to consistently select
the same week each year to control for seasonal factors that might otherwise bias our year-to-year
comparisons. In the end, we chose the second "Nielsen week" in each of the November and May
sweeps periods. The speciflc weeks chosen are presented below in table 1.
Table 1: Data Dates
Year Week 1 Week 2
2003 May 8-14 Nov 6-12
2004 May 13-19 Nov 11-17
2005 May 12-18 Nov 10-16
2006 May 11-17 Nov 9-15
Television Schedule Data (TMS) Our basic unit of observation is a television program (e.g
"Friends") shown on a particular "station" (broadcast station or cable television network, e.g.
WNBC in New York City or the USA cable network) at a particular time (e.g. Monday, May
8th, 2003, at 8:00 EST). While in principle this information is publicly available (e.g. published
daily in local newspapers or provided by programming distributors), there are so many broadcast
networks and cable systems that flrms have arisen to organize it, ensure its accuracy, add additional
12With "sweeps" in November, February, May, and July.
7
information, and sell it to interested parties. Tribune Media Services (TMS) is one such flrm,
primarily selling access to their data to a variety of industry participants (e.g. print programming
guides, cable systems, websites, etc.).
TMS measures the universe of television programming provided on any broadcast television station
or cable system in the U.S., Canada, and Mexico, over 20,000 unique "channels".13 Many of these
aren’t practically relevant (e.g. an audio channel on the local cable system in Kansas), so we limited
the analysis to every full-power broadcast television station and cable and premium television
network in the United States. We obtained a list of the former from the ownership data described
above. We obtained a list of the latter from TMS, Kagan World Media (2006), and NCTA (2007).14
There are 1,583 full-power broadcast television stations and 192 cable and premium programming
networks included in our flnal dataset.
Table 2 describes the flelds we used from the TMS Program Schedule data. Following the structure
of a relational database, the top panel of Table 2 describes the information provided for each
channel-date-starting time-program (our unit of observation).15 Information common to a channel
and program are then presented in the second and third panels of the table. The Channel ID and
Program ID link the data in each of the panels for each date and starting time.
Of particular relevance for our analysis are the "Program Type" and "Category" flelds as these
are the primary source data we use by which we allocate programming into categories for later,
separate analysis. TMS identifles a Program Type and Category for every program ofiered on
television.16 There are 33 Program Types and over 300 Categories in the TMS data. As there was
signiflcant overlap in some of the Program Types, we combined a number of them. The 33 TMS
Program Types and our smaller set of 23 "Estimation" Program Types are presented in Table 3.
We performed a similar exercise reducing the number of Categories from 309 to 37; the speciflc
allocation we used is provided in Tables 29-31. The proportions of programming in each Program
Type and Category in our flnal dataset is given in Table 4.
Television Ratings Data (Nielsen, Kagan) While the TMS data tell us each of the programs
ofiered on every major broadcast television station and cable network in the United States, they do
not tell us how many people were exposed to that programming nor how many watched them. For
that, the FCC purchased data from Nielsen Media Research (Nielsen) and Kagan Media Services
(Kagan) for the same weeks and years for which we obtained the TMS data.
13TMS organizes their data flrst according to "channels". These range from full- and low-power broadcast television
stations to cable, premium, and pay-per-view networks to local origination, split broadcast, and split cable channels.
14The NCTA website cited above was the most comprehensive resource. Obtaining programming information for
some of the smaller cable networks in particular required an extensive iterative process with TMS.
15As noted in the table, we normalized starting times to the quarter-hour.
16For convenience, when I refer to Program Type and Category flelds in the TMS data, I will capitalize each word.
This will identify when I refer to the speciflc TMS data versus the general issue of program types or categories.
8
There were several idiosyncracies to the Nielsen data. First, we were only able to obtain ratings
data for certain parts of the day: from 7:00-11:00 a.m. and from 6:00 p.m.-12:00 a.m. We focus
exclusively on the latter period in our results. Second, the broadcast and cable network ratings
came from difierent sources within the company. Broadcast ratings data are available for each of
the 210 DMAs and are used in the study. Due to di–culties in the delivery and formatting of the
cable ratings data, we were not able to use them in this study. Instead, we obtained annual average
prime-time ratings data from Kagan World Media (2006). While not ideal { the broadcast ratings
data are for the speciflc programs shown on the speciflc days of our study while the cable ratings
data are annual averages - they are useful for permitting us to conduct an integrated analysis of
programming on both broadcast and cable networks.
Advertising Minutes Data (TNS) As noted in Section 2, it is important to understand the
impact of ownership structure on both the content and advertising markets. To do so, the FCC
purchased data from TNS, Inc. (TNS) for the same weeks for which we obtained the TMS and
Nielsen data.
There were also several idiosyncracies to the TNS data. First, the FCC contracted with TNS for
only broadcast advertising minutes. These were available in most of the top 108 DMAs.17 Second,
TNS provided us with information about the number and length of advertisements in each program,
but only information about the number of promotions in each program.18 This impacted slightly
our estimates of the total non-programming time on a given program.19
4 Data Aggregation and Program Types
As described earlier, we have three measures of the quantity of television: the amount of television
programming produced (and available somewhere) in the United States, the amount of television
programming available to the typical U.S. household, and the amount of television actually watched
by U.S. households. We will discuss programming of difierent types in what follows; for now assume
17Missing were DMAs 10-11, 66-68, and 76-78.
18Promotions are advertisements for other television programs. Typically these are for other programs on the same
channel or other programs on a–liated channels.
19The data were given to us at the level of the network-program-timeperiod-advertisement. Each ad (or promotion)
was associated with a "pod", a collection of ads and/or promotions associated with each commercial break within
a program. To aggregate the data to the level of the program, we flrst aggregated the information within each pod
and then aggregated information across pods within a program. We only ran into trouble when a promotion was
either flrst or last within a pod. In that case, we didn’t know exactly how long the pod was (and therefore how long
the promotion was). To estimate total non-programming (i.e. ad plus promotion) time, we substituted the average
promotion length (which we can calculate by comparing pod length to total advertising length for pods that begin
and end with ads) for those promotions at the beginning and end of the pod. This is unlikely to dramatically impact
our results.
9
we are discussing a "generic television program".
How do we measure what is produced? As described above, the TMS data provides an exhaustive
inventory of the television "channels" (broadcast television stations and cable television networks)
on ofier across the United States. Indeed, they provide too much - almost 8,000 such "channels".
We trim this down in two ways. First, for broadcast networks, we focus on the set of full-power
broadcast television stations that are the focus of the FCC Media Ownership study #2. We further
reduce this number by removing from our study (where feasible) the second (weaker) broadcast
television station a–liated with a broadcast network within each Nielsen DMA.20 Second, for cable
networks, we had to decide how many cable networks to include in the analysis. NCTA (2007) lists
over 500 cable networks (planned or active). This very large number no doubt re ects the growth
in available capacity across cable and satellite systems brought on by the digital distribution of
programming. But how many of these are truly available? An early version of our results using the
TMS data included 362 cable networks. In the results we present here, however, we focus on the
set of basic cable networks for which we had information about their nationwide availability from
Kagan World Media (2006) as well as any premium and pay-per-view networks.21 This left 192
cable networks. While not exhaustive - and perhaps not representative of the future of program
availability - it does re ect the population of at-least-reasonably-available cable networks as of late
2006.
What do we miss by limiting ourselves in this way? In the broadcast area, these rules mean we will
not analyze the rise of low-power broadcast television stations.22 In the cable area, it means we do
not analyze two types of networks: new and/or very narrowly distributed basic cable networks and
various types of local origination (public access, etc.).23
4.1 Aggregating Broadcast Programming
Before we describe the patterns in the data under these assumptions, we must address a fun-
damental difierence in the reporting of broadcast and cable television programming in the data.
20For example, there are two ABC a–liates in the 7th-largest DMA: WCVB (Boston, MA) and WMUR (Manch-
ester, NH). Of these, WCVB has the (much) higher average rating across the programs in our data: 4.82 versus 0.96.
We therefore dropped from the analysis WMUR, along with all 234 other network a–liates for which there was a
second a–liate with the same network within the same DMA that had higher ratings. There were 7 instances of
multiple network a–liates for which neither had any ratings information in the data. In these cases, we assumed they
could each reach 50% of the households in the DMA.
21The least widely distributed basic cable network (HTV Musica) was available in just 2.0 million households.
22A brief look at the full TMS data shows that they are on the rise: from 776 in May 2003 to 1,235 in November
2006.
23This may seem an important omission given the FCC’s current and historic focus on localism (cf. FCC (2003)),
but we concluded a detailed analysis of the many varieties of local origination was beyond the scope of this study.
The data exist, however, for a detailed analysis of locally available cable programming. As for LPTV stations, we
can say that their number has grown in the sample, from 484 in May 2003 to 697 in November 2006.
10
In our estimation dataset, there are 1,583 broadcast a–liates and 192 cable networks. Much of
the programming on the broadcast networks, however, is similar, particularly during prime time
(8:00-11:00 EST).24 Even if not, it is provided within a DMA while each of the cable networks can
(at least in principle) be distributed nationally. In order to compare programming, at least on a
national basis, we had to somehow aggregate the information about the programming provided on
broadcast a–liates into something like a "national" broadcast network.
This problem was conceptually easy for television stations a–liated with a broadcast network:
simply "add up" (with appropriate weights) the programming provided on each a–liate. We
describe in detail how we did this in the next paragraph. But how should one "add up" the many
independent and public television stations? While many assumptions are possible, we chose to
make several "virtual networks" of these stations.25 Take independent stations for clarity (public
stations were treated similarly). We examined all the independent television stations within each
DMA in the U.S. and ranked them according to their channel number (with low channel numbers
at the top of the list).26 We then made a "network" of all of the "flrst" independent stations. Call
this "network" "Independent 1". We made similar "networks" out of each of the second, third,
etc. stations until we ran out of stations. This yielded 9 independent television "networks" and 6
public television "networks". Table 5 reports the number of a–liates for each of our networks in
the estimation data. Tables 27 and 28 report the identities of the cable networks in the data.27
Having identifled each broadcast network (real or virtual), we next faced the task of aggregating
these across the various DMAs into a single national network. But what does it mean to "add
up" "Wheel of Fortune" in San Diego with "Entertainment Tonight" in Tampa?28 While we can’t
aggregate program names, we can aggregate the characteristics of those programs. Consider the
TV Content Rating for clarity.29 "Wheel of Fortune" in San Diego has a TV Content Rating of
TV-G (give it a value of 3) while "Entertainment Tonight" isn’t rated (give it a value of 0). Adding
up the tv ratings of these two programs (and across all the programs on a given network for a given
day and time period) gives both an "average" TV rating as well as the share of a–liates that have
each rating.30 We do this not only for TV Content Ratings, but for all the characteristics of the
24After standardizing for difierences in time zones, it was typical for every a–liate of the four big broadcast networks
(ABC, CBS, NBC, and FOX) in the United States to carry the same program.
25This had the advantage of capturing the fact that households in some (larger) DMAs have access to more
independent and public television stations than households in other DMAs.
26Channel number is historically important as signal quality via over-the-air broadcast was generally higher the
lower the channel number.
27There appear to be a few idiosyncracies in the networks reported to us by the data providers. For example, we
received a number of the premium "multiplexes" (e.g. Showtime, Starz) but not others (e.g. HBO, Cinemax). This
is unlikely to dramatically afiect our conclusions.
28Note this isn’t nearly as much a problem for the major broadcast networks in prime time. There, the uniformity
of programming across a–liates means we can simply report the program being shown on all the a–liates.
29Thetelevisioncontentratingisamethodofdescribingthesuitabilityofparticularcontentforparticularaudiences.
They are similar to MPAA ratings for movies. We describe them in further detail below.
30For example, the average TV content rating of programs on NBC a–liates at 7:00 p.m. (more generally, one
11
programming provided to us by TMS (or deflned by us using TMS data). This yields a picture
of what the "average" television station a–liated with each network is broadcasting for a given
quarter-hour of a given day.
4.2 Programming Types
We are now prepared to describe patterns of television programming in the United States, both in
general and with respect to the programming types articulated by the FCC when commissioning this
study. They asked after 7 programming types: (1) Local News and Public Afiairs Programming,
(2) Minority Programming, (3) Children’s Programming, (4) Family Programming, (5) Indecent
Programming, (6) Violent Programming, and (7) Religious Programming. This section describe
how we deflned each of these types of programming.
We used two primary pieces of information in deflning programming types. The most useful and
accurate was to exploit information in the Program Type and Category flelds in the data provided
to us by TMS.31 For example, we deflned a program to be a "News" program if either the Program
Type or Category was "News". While very useful for some program types, however, the TMS
data proved less useful for others (e.g. Minority Programming). Our second way of deflning
program types was therefore to identify the target audience (if one existed) for broadcast and cable
television networks and assume that all programming provided on that network was that type
of programming. For example, we deflned all the programming shown on Black Entertainment
Television to be minority-targeted programming. The speciflc rules for each type of programming
are described below.
1. News and Public Afiairs Programming.
As noted above, we deflned programming to be news programming if either the Program
Type or Category was "News". Similarly, we deflned programming to be Public Afiairs
Programming if the Program Type was "Public Afiairs". We further distinguished between
Network News and Local News on broadcast television networks by examining how often a
particular program title appeared across all television stations. If it had over 1,000 quarter-
hours in the data, we deflned that to be a network news program.32 All other news programs
were deflned as local news programs.
hour before prime time) on November 15, 2006 among programs that give ratings is 3.4 (about halfway between
TV-G and TV-PG). Or if more detail is wanted, of the 187 NBC a–liates in our estimation dataset, 65.2% didn’t
rate their program, 21.4% showed programming rated TV-G, 12.8% showed programming rated TV-PG, and 0.5%
showed programming rated TV-14.
31Table 4 lists our (shortened) versions of these flelds. Appendix 7 describes the rules TMS uses to allocate
programming to their 33 program types. According to discussions with senior TMS personnel, programming is
allocated to "Categories" flrst according to any information provided by the program provider in press kits, program
schedules, etc. If the Category is still unclear, the Editorial Department stafi queries them for this information.
32A one-hour local news program shown once per day for every day in our data would show up for 224 quarter-
12
2. Minority Programming.
We distinguished between programming targeting three types of audiences: Black audiences,
Latino/Spanish-speaking audiences, and other minority audiences (e.g. International, East
Asian, South Asian, Gay & Lesbian, etc.) We ofier two kinds of deflnitions. First, we
went through the list of 192 cable networks and decided if any of these networks targeted
any of these minority groups. The networks we chose for each of our three audiences is
detailed in Appendix B. This is unfortunately crude, however, as some programming ofiered
on other (including broadcast) networks clearly targets minority audiences. While TMS
didn’t provide information about the other minority audiences, we deflned any programming
with a "Spanish" or "Pelicula" Program Type or Category to target Latino/Spanish-speaking
audiences.
3. Children’s Programming.
We had two deflnitions for children’s programming. First, we deflned a program as a children’s
program if it’s Program Type or Category was "Children". Second, we deflned a program as
a children’s program if it was a movie with an MPAA rating of "G" or a television program
with a Television Content rating of TV-Y or TV-Y7.33
4. Family Programming.
We have three deflnitions of family programming. First, we articulated the set of cable
networks that provide family programming.34 Second, we deflned a program as a family
program if it had a Television Content rating of TV-G. Third, we deflned a program as a
family program if it had an Arts, Educational, or Documentary theme.35
5. Indecent Programming.
We deflned indecent programming as Adult Programming.36 We have two measures. First,
we deflned all programming on a network showing programming with strong sexual content
as adult programming. Second, we deflned as adult programming any movie with an MPAA
rating of NC-17 or any television program with a Television Content rating of TV-MA-S
("explicit sexual situations") or TV-MA-L ("strong coarse language").
hours. Programs with more than 1,000 quarter-hours were obvious network news programs like "The CBS Evening
News".
33MPAA ratings are ratings provided by the Motion Picture Association of America to rate a movie’s suitability
for certain audiences (see, e.g., Wikipedia (2007a)). The Television Content rating system is a similar mechanism for
television programming (see, e.g., Wikipedia (2007b)).
34This is not without controversy as reasonable people can come to very difierent conclusions about what consti-
tutes a network providing family programming. In part, we deflned family networks subjectively, although we did
incorporate information provided from news reports of the networks included on recently-introduced family-friendly
tiers by major cable television providers.
35In particular, if it had a Program Type or Category of "ArtsSci", a Program Type of "Instructional" (but not
"Business"), a Category of "Educational" or a Category of "Documentary".
36As above, others may have other deflnitions.
13
6. Violent Programming.
We had many possible deflnitions of violent programming. First we allocated several of TMS’s
Categories into a "Violent" Category.37 Second through fourth, we deflned violent program-
ming as any program with a television content rating of TV-PG-V ("Moderate violence"),
TV-14-V ("Intense violence"), and TV-MV-V ("Extreme graphic violence").
7. Religions Programming
We had two deflnitions of religious programming. First, we deflned all programming on a net-
work showing primarily religious programming as religious. Second, we deflned programming
to be religious programming if it had a Program Type or Category of "Religious".
8. Overall targeting.
Finally, we simply calculated the average rating of all movies and television programs that
were rated.38
5 The Quantity and Quality of Television Programming
5.1 The Quantity of Television Programming
We are now ready to describe patterns in our three measures of the quantity of television pro-
gramming in the United States. Table 6 examines (a measure of) the quantity of programming
that is produced for distribution anywhere in the United States. Reported is the average amount
of programming of various types ofiered on any of the 27 Broadcast networks listed in Table 539
or on any of the 192 Cable networks listed in Table 27 and Table 28 over the 8 weeks in 4 years
listed in Table 1. For reasons of comparability with the data we later report, all the tables in this
section report patterns of programming between 6:00 p.m. and 12:00 a.m. (or the equivalent).40
We restrict attention to this period as (a) it includes prime time (8:00-11:00 EST), the period that
most people watch the most television and (b) it includes the early and late evening news, one of
the programming types of particular interest in this study.
37These were "Horror", "Extreme", "Pro Wrestling", and "Terror". Note again our caveat that reasonable people
could deflne things difierently.
38For the MPAA ratings, we assigned a value of 1 for "G" to 5 for "TV-MA". For the Television Content ratings,
we assigned a value of 1 for "TV-Y" to 6 for "TV-MA".
39Where note we have created 9 "Independent" and 6 "Public" broadcast networks for the purposes of these tables.
40Prime time programming is generally held to be between 8:00 p.m. and 11:00 p.m. Eastern Standard Time
(EST) and Paciflc Standard Time (PST), and between 7:00 p.m. and 10:00 p.m. Central Standard Time (CST) and
Mountain Standard Time (MST). We verifled that these patterns held in the data and then time shifted all of the
CST and MST programming to synchronize prime time across time zones.
14
Program Production An entry in Table 6 is read as follows. For the 27 broadcast and 192
cable networks between 6:00 p.m. and 12:00 a.m. EST (or the equivalent) for the 8 weeks over
4 years between 2003 and 2006, 4.14 % of the quarter-hours are devoted to some kind of News
programming, 1.98% is devoted to Public Afiairs programming, etc. The second and third columns
in Table 6 break out the average percentage of quarter-hours for each program type across broadcast
and cable networks.
Before describing the data, we must note a few caveats. First, note that programming within the
broadcast networks are weighted equally for every a–liate in the U.S., regardless of the number
of households in the DMA. Second, programming is also equally weighted across networks both
within and across types (i.e. programming on MNT counts equally with programming on ABC and
programming on Hallmark TV counts equally with programming on TNT). We correct for both of
these features in the next table.
That being said, there are interesting patterns both across programming types and across dis-
tribution channel within type. The most popular programming type (as deflned here) is Family
programming, with up to 19.2% of quarter hours, while the other programming types are relatively
equal in size with viewing shares between 1 and 8%, depending on the measure used. There are
important difierences between the programming provided on broadcast versus cable networks for
News, Religious, and Violent programming (more on broadcast), and Public Afiairs, Children’s,
and Adult programming (more on cable). The average MPAA rating for movies (for movies that
provide ratings) is similar across the two distribution platforms, while the average television content
rating (for television program that provide ratings) is higher on cable.
Program Availability Table 7 reports our second measure of television programming quantity,
that related to availability. We calculate the availability of programming in difierent ways for
broadcast and cable networks. For broadcast networks, we calculate availability by weighting the
programming within each DMA by the number of households within that DMA. For the purposes
of this calculation, we assume that every household within a DMA can view the programming
broadcast by any station within that DMA. As a consequence, programming that is provided more
widely (across more DMAs) or is provided more frequently in large versus small DMAs, will be more
widely available.41 The sample statistics in Table 7 re ect these difierences. For cable networks,
we calculate availability by the national average number of households that can access the network
via cable or satellite according to Kagan World Media (2006). This varies across years by network,
with the Discovery Network, CNN, and ESPN the three most widely available networks across the
41For example, programming provided on ABC will have greater weight than programming provided on CW as
ABC has more a–liates in more and larger DMAs than does CW (cf. Table 5).
15
sample period.42 For the purposes of this table, we assume that premium and pay-per-view cable
networks have zero availability.43
An entry in Table 7 is read as follows. The typical quarter-hour of news programming is available
to almost half (48.0%) of U.S. television households. Broadcast news programming is more widely
available (to 66.4% of U.S. TV households) than is cable news programming (36.7%). Several pat-
terns emerge when comparing the patterns of availability to the patterns of program production
from Table 6. First, as might be expected, "niche", or special-interest, programming (Minor-
ity Adult, and Religious programming) is much less widely available than more general-interest
programming (News, Children’s, and Family programming). Second, there are only moderate dif-
ferences in availability of programming between broadcast and cable, with News, Latino/Spanish-
language Minority, Violent, and Religious programming more widely available on broadcast sta-
tions44 and Black and Other Minority programming more widely available on cable.
Programs Watched Table 8 reports our third and flnal measure of television programming
quantity, that related to what is actually watched. As for availability, these are calculated difierently
forbroadcastandcableprogrammingnetworks. Broadcastratingsarethemoreaccurate: theycome
from Nielsen and report the rating for the speciflc program collected in the TMS database. As for
availability, we then aggregated these weighted by the households in each DMA. For cable networks,
we did not have ratings matched to the program. Instead we have average yearly (through 2005)
prime-time ratings by cable network, also from Kagan World Media (2006). These are non-zero for
62 cable networks in 2005.
An entry in Table 8 is read as follows. The average rating for an quarter-hour of news programming
carried between 6:00 p.m. and 12:00 a.m. on a broadcast television network is 2.01, or roughly
2.22 million 2005 U.S. television households.45 There are substantial difierences in ratings across
program types and between broadcast and cable ofierings. First, News and Violent programming
are the most highly rated, with Children’s and Family programming substantially lower, and Mi-
nority and Religious programming lower still. In general, programming is more highly rated on
broadcast than cable networks, although cable does relatively well on Children’s and Public Afiairs
42For example, Discovery was available to 90.3 million of the estimated 110.2 million U.S. television households in
2005.
43This is obviously strong. We do this as we weren’t able to conveniently flnd premium and pay-per-view availability
information. This assumption will impact most our calculations for adult programming, underestimating its overall
availability.
44Note that all of the "other" broadcast television stations not a–liated with one of the major broadcast networks
provide either Spanish-language or religious programming. Note also the more widely available adult programming
on broadcast is a sure consequence of our assumptions on adult-oriented cable networks.
45For convenience, we use an entry for a broadcast network as our example as we have more confldence in those
values.
16
programming.46
Of course, ratings can be low either because people have access to a program and don’t choose to
watch or because they don’t have access to it in the flrst place. To get a sense of the importance of
the latter efiect, Table 9 reports the ratings as a share of households with access. An entry in this
table reads as follows. On average across the prime-time quarter-hours in our data, 0.45% of the
people with access to Spanish-language programming choose to watch it. That the entries in this
table moderate the stark difierences in ratings from Table 8 suggests (as might be expected) that
the low numbers of people that watch particular (esp. niche) programming do so both because of
limited availability and a limited wish to do so.
Patterns in Production, Availability, and Viewing Over Time Tables 10-12 duplicate the
all-network averages in tables 6-8, but report it for each of the years in our data. Several interesting
patterns emerge.
First, regarding program production and availability in Tables 10 and 11, it is clear that program-
ming of difierent types are becoming more or less popular over time. Program types whose pro-
duction and/or availability is falling across time include Network News (though not Local News),
Public Afiairs, Family, and Religious programming.47 Program types whose production and/or
availability is rising across time include Latino, Children’s, Adult, and the higher categories of
Violent programming. Note also the average Television Content rating across all rated programs
is rising over time. Glancing at Table 12 suggests a reason. While only a 3-year horizon due to
our lack of cable ratings for 2006, aggregate ratings across time are falling for News and Religious
programming, but rising (sharply) for Children’s and Violent programming.
5.2 The Quality of Television Programming
Ratings as Program Quality We now turn to our two (economic) measures of television pro-
gram quality. One we have seen already: television ratings. In particular, we flrst measure quality
by the Nielsen television rating obtained for the program (where available). This captures the idea
that for programming that is free to households (i.e. broadcast television programming or cable
television programming after purchasing access to a bundle of networks), higher quality programs
will garner higher ratings.
46Note while total ratings for cable television viewing recently passed total ratings for broadcast television viewing,
cable viewing is shared over a much larger number of networks, depressing their average.
47Note that what is reported is the share of quarter hours that are devoted to programming of a given type. The
total number of quarter-hours of programming is increasing over time due to the introduction of new cable networks.
Thus it is possible that while the share of programming of a given type is falling, it’s total quantity (in quarter-hours)
is rising.
17
Table 9, introduced above in our discussion of viewing pattern, describes patterns in viewing choices
among households with access to broadcast and cable programming. If one accepts the premise that
more households watch what they perceive to be higher quality programming, then News and Vio-
lent programming is perceived to be, on average across quarter hours, the highest quality television
programming, followed (depending on the measure) by Latino/Spanish-language, Children’s, and
Family programming. These patterns come predominantly from viewership patterns in broadcast
television.48
Table 13 duplicates this table for all networks across time. The data here suggest the relative
quality of News programming is declining with a mixture of (relative) winners.49 The strongest
results appear to be for some measures of Children’s programming and the more violent Violent
programming.
Advertising Minutes as Program Quality Our other measure of program quality is the
number and length (in minutes and seconds) of advertisements included on that program. This
captures the idea that the more advertisements included in a program, the less enjoyable it is to
viewers to watch that program.
Table 14 reports patterns in the broadcast television advertising market by a–liate type and year.50
Here we split outcomes in the advertising market for the a–liates of the "Big 4" broadcast television
networks (ABC, CBS, NBC, and Fox) and for other a–liates (MNT, CW, Independents, PBS, and
others).
There are strong difierences in all features of advertising outcomes between the Big 4 and the rest.
Big 4 a–liates have, on average, more ads per program, more ad minutes, and a higher share of
time devoted to advertising. Similar conclusions apply to promotions. With prices per 30-second
ad more than twice as high, revenue per ad is almost triple that of independents and the other
network a–liates.
Patterns across time suggest this dominance is if anything only growing stronger. Despite a general
upward trend in program length for Big 4 a–liates over time, ad minutes that grow even faster
show that the share of total time devoted to ads has increased, from 22.1% (about 13.25 minutes
in a 60 minute program) to 22.9% (about 13.75 minutes), or an additional 30-second ad.51 From
this perspective, the quality of broadcast television programming is falling over time.
48Despite the fact that there are over 6 times as many minutes of cable programming, higher average ratings for
broadcast programming give them relatively more weight in determining overall viewership patterns.
49Note that overall ratings for television are also declining in this period.
50Recall from section 3 that we only have access to advertising market data for the broadcast television market.
51Note this is just ad time. The additional time for promotions shows that total non-programming time for a 60
minute program shown on a Big-4 a–liate is 19.75 minutes by the end our sample .
18
6 Ownership Structure and Program Quantity and Quality
Section 5 described the overall patterns of television programming quantity and quality that form
the background for an analysis of the impact of television station ownership structure on those
outcomes. I brie y describe the data used in this part of the paper and then present our results.
6.1 Data Preliminaries
As described in Section 3 above, our data on television station ownership comes from Diwadi,
Roberts, and Wise (2007). The ownership information for television systems in that study comes
from the BIA Financial Network. It provided year-end snapshots of ownership of each of the
over 1,800 full-power broadcast television stations operating in the United States. We will use
information on the following features of television station ownership in this study:
1. Local ownership. A television network was deflned to be locally owned if the zip-code of the
physical location of the parent corporation matched any of the zip codes within the DMA
served by the television station.
2. Parent corporation ownership. Various features of parent corporation ownership are provided
in the data. We describe these in more detail when we present our results.
3. Cross-ownership information. Noted in the data are whether the parent corporation of the
television station also owns a radio station or newspaper within the same DMA.
4. Minority and female ownership. Noted in the data are whether the owner is a minority or a
woman.
Linking the Data As our ownership information pertains only to television stations, all of our
subsequent analysis will look at programming and advertising outcomes in broadcast television
markets.
An observation in the ownership data is a television station-year, i.e. WCVB-Boston in 2005.
By contrast an observation (on a broadcast television station) in our quantity and quality data is
a station-day-quarterhour-program. To link the data, we therefore aggregated our quantity and
quality data across all the quarter-hours between 6:00 p.m. and 12:00 a.m.52 and across all the
days within a year53 to get a matching dataset on station-years. The link between the two datasets
was not perfect - we lost some observations on the match and some more by choosing to balance
52We continue to focus on this "prime time extended" period.
53For us, 14, as we have two weeks of data per year.
19
the ownership data such that we had an observation in the data for each station for all three years
in the sample.54 The results was a sample of 4,437 station years, or 1,479 stations for each of 3
years.
Tables 15 and 16 present sample statistics for this composite database. Table 15 presents infor-
mation about the market in which the station operates (DMA rank, DMA households), whether
it is a commercial or non-commercial station, and the ownership variables described above. It also
includes information about advertising market outcomes (ad minutes, ad revenue, and ad prices)
and splits the data between the same Big 4 network a–liates (ABC, NBC, CBS, and Fox) and
others as was done above.
As for ad markets, Big 4 network a–liates difier substantially from other a–liates in their market
and ownership characteristics. Big-4 a–liates are more likely to be in smaller markets (one needs
a big market to support and independent television station) and are exclusively commercial. They
are less likely to be locally owned, with similar (tiny) patterns of minority and female ownership.55
Parent corporations (owners) of big-4 a–liates have roughly double the revenue of other a–liate
owners, although similar patterns in the number of stations owned and percent of households
reached. As might be expected given the revenue flgures, big-4 a–liate owners are more likely to
have holdings in print and radio.
Table 16 provides programming information for the same data. Note flrst that the quantity measure
we use here (and in the subsequent analysis) is the production of television programming. While
analyzing also availability and ratings would have been interesting, time and space constraints
prevented it. Second, note that the across-network averages for broadcast stations here look slightly
difierent from those in Table 6. In part, this re ects the slightly difierent samples (here 1,479
broadcast stations; there 1,583) and in part the difierent number of stations that are being averaged
over.56
While the patterns across program types are familiar from our earlier analysis, there are substantial
difierences in the programming of the Big-4 and other a–liates. Big-4 a–liates ofier much more
News and Violent programming and less Children’s, Family, and Religious programming. Relatedly,
the average TV Content rating is substantially higher for Big-4 stations.
54While not strictly necessary, we didn’t want to bias our results by comparing outcomes of existing stations with
outcomes of stations that were newly entering or exiting the industry. In practice, it is likely inconsequential as the
stations dropped due on these criteria were only 1.5% of all stations.
55Note the flgures for minority and female ownership read as, e.g, 0.85% of Big-4 network a–liates being owned
by a minority.
56In particular, as we are not aggregating stations to national averages, we’ve elected to pool the Independent and
Public television stations instead of splitting them out into "virtual" networks. As such, we have are averaging across
all programming equally rather than (as there) averaging up to the level of the network and then averaging across
networks.
20
6.2 Empirical Framework
The framework we will use to analyze the relationship between television ownership structure and
the quantity is that of simple linear regression (Ordinary Least Squares). We have a number of
outcome variables of interest (the quantity produced of various types of programming, advertising
minutes and prices), a number of ownership variables of interest (local ownership, cross-ownership,
etc.), a number of control variables (DMA size, commercial status, and broadcast network af-
flliation), and a number of econometric approaches (cross-section regression, various flxed-efiects
regressions).
Tables 17-26 present the results from regressions combining each of the elements described above.
Before we describe them, however, we would like to describe the common structure of the tables
and discuss some of the underlying econometric issues that motivates that structure. We can then
safely refer to these issues when analyzing each of the individual speciflcations.
Table 17 is representative of the results that we will momentarily present. It presents difierent
speciflcations of a regression of the share of quarter hours of programming that is local news on
a variety of measures of television station ownership structure and other controls. There are 9
speciflcations that we brie y describe here:
1. Speciflcation (1): Regression of the Local News Share on market controls:
† DMA households and it’s square
† Commercial station dummy, and
† A–liation dummies
{ ABC, CBS, NBC, Fox,
{ CW, Independents, PBS,
{ Spanish-Language, Others,
{ Excluded category is MNT
2. Speciflcation (2): (1) + DMA and Year flxed efiects. Those parameters not reported.
3. Speciflcation (3): (2) + Locally Owned Dummy
4. Speciflcation (4): (2) + Minority Owned Dummy
5. Speciflcation (5): (2) + Female Owned Dummy
6. Speciflcation (6): (2) + Newspaper-TV Cross-Ownership Dummy
7. Speciflcation (7): (2) + Radio-TV Cross-Ownership Dummy
21
8. Speciflcation (8): (2) + Parent Company revenue (in $billions)
9. Speciflcation (9): (2) + All ownership controls
We run these 9 speciflcations for each of 9 dependent variables: (1) Local News programming, (2)
Public Afiairs programming, (3) Spanish-language programming, (4) Children’s programming57,
(5) Family programming58, (6) Violent programming59, (7) Religious programming, (8) Advertising
time (in minutes), and (9) Advertising prices (for a 30-second ad).
In addition, Table 26 runs Speciflcation (9) for each of these dependent variables including all the
ownership controls and DMA, year, and channel flxed efiects. Those parameters are not reported.
Econometric Caveats 60
It is well known that Ordinary Least Squares provides the best linear unbiased estimation of the
relationship between one (dependent) variable and other (explanatory) variables. In this role, it
merely reports the (conditional) correlation between the dependent variable (e.g. share of minutes
that are local news) and any one explanatory variable (e.g. local ownership) controlling for the
other explanatory variables.
In particular, it does not guarantee any kind of causal relationship between the explanatory variable
and the dependent variable, i.e. a statistically signiflcant (positive) relationship between local
ownership and local news minutes does not mean local ownership is the cause of higher local news
minutes. Why not? Among other reasons, because there could be other factors that are correlated
with both local ownership and local news provision (e.g. a strong local community).
In general, we try to use econometric strategies that will control for all unobserved factors such that
it is di–cult to think of anything not in the regression that could cause bias a causal interpretation.
It is notoriously di–cult to claim causation in cross-section regressions like speciflcation (1) because
of a host of factors across markets that might in uence outcomes but not be observed to the
econometrician. One such factor is the strength of the local television markets. This motivates the
use of DMA flxed efiects in the balance of the speciflcations. It is still possible, however, that there
are unobserved factors across television stations within a market that can in uence both ownership
variables and programming quantity or quality.
This motivates the use of channel flxed efiects in Table 26. In this case, no cross-sectional variation
is used at all to identify the efiects of interest. Instead, all the variation in the data identifying
57Either of "Children’s Programming" and G Movies or TV-Y / TV-Y7 TV.
58Either of TV-G programming or Arts, Educational, or Documentary programming.
59Any of TV-PG-V, TV-14-V, or TV-MA-V programming.
60The reader uninterested in details of econometric analysis can skip this section.
22
the results is from changes across time in the ownership of a given station. In our case, however,
this means a regression with almost 1,700 parameters.61 It is likely the case that including channel
flxed efiects eliminates much of the variation in the data. This often has econometric consequences
- imprecise statistical efiects - but even in the presence of statistically signiflcant efiects suggests
caution to understand how much variation in the data is driving a particular result (and the likely
generality of that variation). This is a common tradeofi in empirical economic analysis. We will
further address these issues as the need arises when discussing our results.
6.3 Ownership Structure and Program Quantity
We brie y summarize the flndings of the results from the regressions of various ownership variables
on each of our programming quantity variables described above. The table and the column in the
table providing the support for each conclusion is included in parenthesis after each conclusion.
1. Local News programming (Table 17). Larger markets tend to devote a greater share of
minutes to local news (1). A–liates of ABC, CBS, and NBC provide substantially more
and a–liates of Fox and PBS provide slightly more local news than other broadcast stations
(1-9).62 Locally owned stations ofier less local news (3), although this result disappears when
controlling for other features of the ownership structure (9). Television stations owned by a
parent that also owns a newspaper in the area ofier (~3.0 percentage points) more local news
programming (6, 9). The results in Table 17 with DMA dummies suggest television stations
owned by corporate parents with larger annual revenue ofier more local news (8, 9).63 By
contrast, using channel flxed efiects, an increase in the size of a corporate parent’s annual
revenue is correlated with a decrease in the amount of local news (Table 26, (1)).64
2. Public Afiairs programming (Table 18). Smaller markets have more public afiairs program-
ming (1). PBS and Independent stations have more (1-9). Locally owned and female owned
stations have more public afiairs programming (3, 5, 9).
3. Spanish-Language programming (Table19). Spanish-language stationshaveaverylargeefiect
on the amount of Spanish-language programming.65 Using channel flxed efiects, becoming
611,479 channel flxed efiects plus 200+ DMA flxed efiects.
62The coe–cient on ABC, for example, says that controlling for all the other explanatory variables in the regression,
a television station a–liated with ABC provides an estimated 16 percentage points more news programming than a
television station a–liated with the MNT network.
63A $500 million (1 standard deviation) increase in the corporate parent’s annual revenue is correlated with an
estimated 0.033*0.5 = 1.65 percentage point increase in the amount of local news programming.
64With the same $500 million increase now correlated with an estimated 0.5 percentage point decrease in the
amount of local news programming.
65Becoming a Spanish-language station is associated with an estimated 32-percentage point increase in the amount
of Spanish-language programming.
23
owned by a parent with newspaper ownership is correlated with an increase in the amount of
Spanish-language programming (Table 26, (3)).66
4. Children’s programming (Table 20). PBS stations ofier more children’s programming than
other stations (1-9). Locally owned stations ofier more children’s programming (3, 9) and
stations that also own a radio station in the DMA ofier less. Using channel flxed efiects,
becoming owned by a parent with newspaper ownership and minority ownership are both
correlated with a decrease in the amount of children’s programming (Table 26, (3)).67
5. Family programming (Table 21). Larger market provide less family programming (1). PBS,
Independent TV stations, and other TV stations (mostly religious) provide more family pro-
gramming (1-9). Interestingly, CBS provides slightly more (1-9). Locally owned stations
provide slightly more as well (3, 9). Television stations owned by corporate parents with
larger annual revenue ofier less family programming (8, 9).68
6. Violent programming (Table 22). Larger markets provide less violent programming (1). There
are important difierences across broadcast a–liates in the amount of violent programming
they provide: relative to MNT, Fox and CBS provide slightly more and all other a–liates
(save CW) provides quite a bit less (1-9). None of the other statistically signiflcant efiects
are economically signiflcant.
7. Religious programming (Table 23). Smaller markets provide more religious programming (1).
PBS stations provide substantially less and Independent and Other (mostly religious) stations
provide substantially more religious programming (1-9). Female owned stations provide more
religious programming (5, 9).
8. Advertising time (Table 24). Recall advertising time is one of our measures of the quality
of television programming. Independent and other stations provide slightly more advertising
time (1-9).69 Using channel flxed efiects, there are a number of statistically signiflcants
efiects of changes in ownership: Becoming minority-owned, co-owned with a radio station, or
becoming owned by a larger parent are all associated with increased advertising time, while
becoming co-owned with a newspaper is associated with decreased advertising time.70
66One should be careful extrapolating this result as it is likely based on a very small number of observations.
67One should be careful over-interpreting our results on children’s programming. This is children’s programming
in prime time. As seen in Table 16, this is quite rare, accounting for only 1.7% of programming minutes across the
sample.
68A $500 million (1 standard deviation) increase in the corporate parent’s annual revenue is correlated with an esti-
mated 0.010*.5 = 0.5 percentage point decrease in the amount of family programming. While statistically signiflcant,
this is economically small (relative to a mean 19.75% share of minutes for family programming).
69A 0.30 increase on a mean of 11.95 is less than 3 %.
70The economic efiects here are large, so care must be taken before extrapolating these flndings to investigate the
number of changes in ownership on which they are based.
24
9. Advertising prices (Table 25).71 Larger markets have statistically and economically signif-
icantly higher advertising prices (1).72 A–liates of the Big-4 broadcast networks charge
substantially higher prices than other broadcast stations with a–liates of ABC, CBS, and
NBC charging slightly more than Fox (1-9). Locally owned stations charge higher prices (3,
9). Television stations owned by a parent that also owns a radio station in the area charge
slightly higher prices.
7 Conclusion
In this study we analyze the impact of the ownership structure in local television markets on the
quantity and quality of television programming. We have obtained information from a variety of
major data providers in the television industry and linked them together to form a unique dataset
to address these questions. This dataset includes information on almost 1,600 broadcast television
stations and almost 200 cable television networks across every DMA in the country over 4 years.
Our results are based on over 9,000,000 quarter-hours of programming.
We measure the quantity of television programming not only by about the amount and type of
programming provided (anywhere) on television, but also by it’s availability to households, and
by what people actually watch. We measure the quality of programming (again) by what people
watch (among the programming that is available to them) and also by the number of advertising
minutes on that programming.
The commission for this study mandated we examine the quantity and quality of seven types
of programming: (1) Local News and Public Afiairs Programming, (2) Minority Programming,
(3) Children’s Programming, (4) Family Programming, (5) Indecent Programming, (6) Violent
Programming, and (7) Religious Programming. We found it di–cult to flnd a single satisfactory
deflnition for each of these. What we suspect we will lack in unanimity, we hope to compensate
with clarity - we describe in great detail our various measures and note here that our conclusions
are based on those particular choices. Assessing the robustness of these conclusions to alternative
choices would be welcome.
What do we flnd? With regard to general patterns of quantity and quality, we flnd there are
important difierences between the programming provided on broadcast versus cable networks for
News, Religious, and Violent programming (more on broadcast), and Public Afiairs, Children’s,
71While not the mandate of this study, economists often worry about the impact of ownership changes on prices.
As such, I include this paragraph as well.
72The linear term in the pair dominates, so the efiect is particularly strong at low DMA households. For example a
1 million increase in DMA household size at very low household size is associated with a $1.04 increase in the average
advertising price.
25
and Adult programming (more on cable). We flnd that "niche", or special-interest, programming
(Minority Adult, and Religious programming) is much less widely available than general-interest
programming (News, Children’s, and Family programming). Examining patterns across time, we
flnd that program production and/or availability is falling across time for Network News (though
not Local News), Public Afiairs, Family, and Religious programming and rising across time for
Latino, Children’s, Adult, and the more violent of Violent programming. Also rising across time is
the average Television Content rating across all rated programs.
We flnd that in general, programming is more highly rated on broadcast than cable networks. Of
the programming types, News and Violent programming are the most highly rated (i.e. highest
quality), with Latino/Spanish-language, Children’s and Family programming substantially lower,
and non-Latino Minority and Religious programming lower still. Examining patterns over time, we
flnd that the relative quality of News programming is declining with some measures of Children’s
programming and the more violent Violent programming gaining ground. With respect to adver-
tising minutes and prices, we flnd a–liates of the Big-4 broadcast networks (ABC, CBS, NBC, and
Fox) are strong and growing stronger. From the perspective of advertising minutes in particular,
the quality of television programming is falling over time.
We relate these measures to the ownership structure of broadcast television stations. Our strongest
flndings are for Local News: television stations owned by a parent that also owns a newspaper in the
area ofier more local news programming. By some methods, television stations owned by corporate
parents with larger annual revenue also ofier more Local News, but by other methods they ofier
less. This is an important area for further inquiry. We flnd that local ownership is correlated
with more Public Afiairs and Family programming. While we flnd important and interesting
difierences in the amount of Violent programming across network a–liates, it does not appear to
be correlated in an economically and statistically signiflcant way with ownership structure. Efiects
of ownership structure on other programming types or on outcomes in the advertising market
are either economically insigniflcant, statistically insigniflcant, or difier in their predicted efiects
according to the method of analysis.
Our hope was that the data we created here might be used to address some of the wide-ranging
issues regarding media ownership structure and outcomes in television markets. While we are
content with the insights we have gained regarding ownership structure among broadcast television
stations, we feel it important to point out this is just one link in the chain of markets that govern
the production and sale of television programming. Extending the analysis here to consider other
distribution channels (cable, satellite, and Internet) and other parts of the vertical chain (notably
the market for programming at the production and network levels) would do more to flll out the
picture of the impacts of media ownership on the quantity and quality of television programming.
26
A TMS Program Types
The following describes the rules used by TMS to allocate programming to program types.73
ARTS Fine arts series such as ballet, opera, theatrical productions, museum exhibits.
CARTOON An animated program such as Flintstones, Smurfs. Note: animated specials
such as Garfleld and Peanuts would go under Childrens Special and adult-oriented
animated shows should be aggressively pursued in an attempt for a more
appropriate program type like Network Series.
CHILDREN’S Includes series designed speciflcally for children 12 years and under.
SHOW Note: childrens specials and cartoons are not included here. Examples:
Sesame Street, Captain Kangaroo, Fraggle Rock.
CHILDREN’S Specials speciflcally designed for children 12 years and under.
SPECIAL
CINEMA Includes movies in French on French services and stations. Movies dubbed
in French or with French subtitles should carry Cinema as the program type.
DAYTIME SOAP Continuing daily drama.
FILLER Programs aired to flll time between featured programs. Use when titles
are not available.
FINANCE All money related, investment oriented or business series. Examples: Wall
Street Week, Wall Street Journal Report, Smart Money, Nations Business Today.
FIRST-RUN Never-seen-before series or episodes, distributed via syndication.
SYNDICATED These are new programs that arent aired exclusively on any network or cable.
GAME SHOW Includes all game shows and lotteries. Examples: Wheel of Fortune,
Jeopardy, Price is Right. Also, high-school or college quiz shows (with teams
in the subtitle).
HEALTH Includes health and fltness-type series like Weight Watcher Magazine,
Medicine Today, Your Baby and You, aerobics and exercise shows.
HOBBIES & How-to series. Examples: Car Owners Maintenance Guide, Sewing With Nancy,
CRAFTS Home Again, Wok With Yan.
INSTRUCTIONAL Any program seeking to teach academic or theoretical lessons.
MINISERIES A miniseries is deflned as a program longer than 4 hours/2 parts; any limited
series (flctional or non-flctional) with fewer than 13 parts or episodes.
73Obtained in an email from Robin Perkins, Senior Electronic Accounts Representative, Tribune Media Services,
July 13, 2007.
27
MOVIE This includes all fllms with a theatrical release or intended for a theatrical
release or made for video. Spanish (Pelicula), French (Cinema) and made-for-TV
movies (TV Movie) have their own types. An animated movie is still a movie,
not a cartoon.
MUSIC Includes all music-related series except music specials. Examples: Lawrence
Welk, Soul Train, Evening at Pops.
MUSIC SPECIAL Generally, one-time-only musical programs. Examples: concerts,
recitals, performances.
NETWORK These are any open-ended series running on the networks (NBC, ABC,
SERIES CBS, PBS, CTV, CBC, FOX) or major cables, such as USA, HBO, LIFETIME,
etc., that can be continued due to audience demand.
NEWS Includes local and network news.
OTHER For any program that doesnt flt into any of the other types.
PELICULA This includes movies in Spanish on Spanish services and stations. Movies dubbed
in Spanish or with Spanish subtitles should carry Pelicula as the program type.
PLAYOFF This includes the Super Bowl, World Series, NCAA Playofis, Stanley
SPORT Cup Playofis, NBA Playofis.
PSEUDO SPORT Any sporting type program where the outcome is predetermined. Example:
professional wrestling.
PUBLIC Includes current events programs like Meet the Press, Firing Line,
AFFAIRS Washington Week in Review, Nightline. Also, if any local news program has public
afiairs aspects, its typed Public Afiairs.
RELIGIOUS Includes religious shows like 700 Club.
SPECIAL Generally a one-time-only program that deviates from the normal lineup.
A special is a program truly out of the ordinary and NOT a single episode of a past
or present series being shown in a difierent time slot. When creating a special
with seasonal content, place a Y in the SEASONAL fleld of the program record.
SPORTS This is for sports programs that feature more than one sport.
ANTHOLOGY Examples: Wide World of Sports, Eye on Sports, Sportsworld, etc.
SPORTING This is a sporting event that is not a team vs. team contest.
EVENT Examples: a golf tournament, a horse race, bowling tournaments, a boxing match.
SPORTS This is for shows dealing with sports including interviews, highlights,
RELATED results and analysis. Examples: NFL Today, Super Bowl Highlights, SportsCenter,
coaches shows, flshing shows, skiing tips, etc.
SYNDICATED All series airing on a channel except programming produced exclusively
SERIES for them or obtained through a network relationship. Older episodes of a
current network series can be in syndication. Examples: Cheers, Star
Trek: The Next Generation, A Difierent World, The Brady Bunch.
28
TALK SHOW Includes shows in which a host or hostess introduces and chats with show
business personalities, national or international celebrities, and other persons
currently in the news, sometimes before a studio audience. Examples:
Oprah, Jerry Springer, etc.
TEAM VS. TEAM This is a sporting event with two teams. Examples: NFL Football,
Major League Baseball, all-star games, bowl games.
TV MOVIE Includes movies that premiere on TV, not in theaters. This includes made
for pay movies on premium channels such as HBO, SHOWTIME, etc.
29
B Cable Network Program Types
The following describes the rules we used to allocate programming from entire cable networks
to program types. These decisions were based on information provided at NCTA (2007) unless
otherwise noted.
Networks targeting Black Entertainment Television (BET), BET Gospel, BET Jazz,
Black audiences Black Family Channel, Starz in Black, TV One, and VH1 Soul.
Networks targeting Azteca, Dicovery en Espanol, Dicovery Kids en Espanol, EcuaTV,
Latino or Spanish- ESPN Deportes, Galavision, GolTV, History Channel en Espanol,
speaking audiences HITN, HTV 10, La Familia, Mun2, SITV, Telefutura, Telemundo,
Travel and Living en Espanol, and Univision.
Networks targeting AZN TV, CNBC World, CNN International, History Channel International,
other minority Logo
audiences
Children’s networks ABC Family Channel, Discovery Kids, Discovery Kids en Espanol,
The Disney Channel, Nickelodeon, Nicktoons, Noggin, Toon Disney
Family networks ABC Family Channel, Animal Planet, Biography Channel, Boomerang,
Discovery, Discovery en Espanol, Discovery Kids, Discovery Kids en Espanol,
Disney, The DIY Network, Fit TV, The Food Network, The History Channel,
Home & Garden, La Familia, The Learning Channel, National Geographic,
Nickelodeon, Nicktoons, Noggin, The Science Channel, Toon Disney,
and The Weather Channel.
Adult networks Club Jenna, Hustler TV, Playboy, Playboy HD, Playboy en Espanol,
Spice, Spice2, Ten, Tenbox, Tenblue, Ten Clips, Ten Max, Ten Xtsy
Religious networks Inspirational Net, ION, Trinity Broadcasting Network
30
Table 2: TMS Data
Full Data
Full Dataset Estimation Dataset
Variable Description Unique Values Unique Values
Channel ID TMS channel reference number 7,966 1,775
Program ID TMS program reference number 248,384 148,724
Start Date Date (day) 56 56
Start Time Program Start Timea 96 96
Duration Scheduled Program Duration (in minutes) 242 230
Total Observationsb 11,567,399 9,296,389
Channel Data
Full Dataset Estimation Dataset
Variable Description Unique Values Unique Values
Channel ID TMS channel reference number 8,634 1,775
A–liation Channel A–liation 26 27
Chan. Descrip. Full-Power B/C, Cable, etc. 8 4
Number Channel Number (B/C) 74 67
Time Zone Channel Time Zone 19 5
City City Name 1,077 511
State State Name 62 49
DMA DMA Name 211 208
DMA Rank DMA Rank 211 208
Program Data
Full Dataset Estimation Dataset
Variable Description Unique Values Unique Values
Program ID TMS program reference number 379,552 148,724
Program Type Program Type (like Genre) 33 23
Category Program Category 374 36
MPAA Rating MPAA Rating 9 9
Parental Rating Parental TV Rating 6 6
Expanded Rating Expanded Parental TV Rating 16 16
Source: TMS.
aRounded to the quarter hour.
bTotal observations in the full dataset are for start times only. For the estimation dataset, total observations are
for all quarter-hours a program is running.
31
Table 3: TMS and Estimation Program Types
TMS TMS Estimation Estimation
Type ID Program Type Type ID Program Type
1 Arts 1 ArtsSci
2 Cartoon 3 Cartoon
3 Children’s Show 4 Children
4 Children’s Special 4 Children
5 Cinema 11 Movie
6 Daytime Soap 5 DaytimeSoap
7 Filler 15 Other
8 Finance 2 Business
9 First-run syndicated 21 Syndicated
10 Game Show 6 GameShow
11 Health 7 Health
12 Hobbies & Craft 8 Hobbies
13 Instructional 9 Instructional
14 Miniseries 10 Miniseries
15 Movie 11 Movie
16 Music 12 Music
17 Music Special 12 Music
18 Network Series 13 NetworkSeries
19 News 14 News
20 Other 15 Other
21 Pelicula 16 Pelicula
22 Playofi Sports 20 Sports
23 Pseudo-sports 20 Sports
24 Public Afiairs 17 PublicAfiairs
25 Religious 18 Religious
26 Special 19 Special
27 Sporting Event 20 Sports
28 Sports Anthology 20 Sports
29 Sports-related 20 Sports
30 Syndicated 21 Syndicated
31 Talk Show 22 TalkShow
32 Team vs. Team 20 Sports
33 TV Movie 23 TVMovie
Source: TMS and author decisions. See Appendix A for deflnitions of TMS Program Types.
32
Table 4: Distribution of Program Types and Categories in the Estimation Dataset
Program Type Number Share Category Number Share
ArtsSci 273 0.18 ActionAdv 5,397 3.63
Business 786 0.53 Adult 3,898 2.62
Cartoon 5,091 3.42 Animated 6,498 4.37
Children 6,356 4.27 Anthol 534 0.36
DaytimeSoap 961 0.65 ArtsSci 2,857 1.92
GameShow 1,441 0.97 Business 1,453 0.98
Health 2,370 1.59 Children 920 0.62
Hobbies 10,237 6.88 Comedy 4,764 3.20
Infomercial 6,042 4.06 Community 1,231 0.83
Instructional 3,811 2.56 Documentary 2,235 1.50
Miniseries 352 0.24 Drama 13,622 9.16
Movie 11,078 7.45 Educational 13,090 8.80
Music 2,999 2.02 Entertainment 2,800 1.88
NetworkSeries 20,919 14.07 Fantasy 952 0.64
News 1,610 1.08 French 159 0.11
Other 8,333 5.60 GameShow 501 0.34
Pelicula 941 0.63 Health 2,181 1.47
PublicAfiairs 3,240 2.18 History 170 0.11
Religious 5,704 3.84 Hobbies 1,011 0.68
Special 7,308 4.91 HomeGarden 12,994 8.74
Sports 11,701 7.87 Infomercial 6,042 4.06
Syndicated 31,942 21.48 Missing 18,586 12.50
TVMovie 1,456 0.98 Movie 158 0.11
TalkShow 3,773 2.54 Music 2,960 1.99
News 1,218 0.82
Other 629 0.42
Outdoor 5,877 3.95
PublicAfiairs 2,230 1.50
Reality 5,236 3.52
Religious 1,750 1.18
Shopping 1,388 0.93
Sitcom 13,668 9.19
Spanish 1,817 1.22
Sports 8,468 5.69
Violent 1,298 0.87
Weather 132 0.09
Total 148,724 100.00 Total 148,724 100.00
Source: TMS and author calculations. See Table 3 for allocation of TMS Program Types to Estimation Program
Types (i.e. the Program Types used in this study). See Tables 29-31 for allocation of TMS Categories to Estimation
Categories (i.e. the Categories used in this study).
33
Table 5: Broadcast Networks in the Estimation Dataset
Program Type Number Share
Major Broadcast Networks
ABC 183 11.56
CBS 185 11.69
NBC 187 11.81
FOX 168 10.61
CW 93 5.87
MNT 74 4.67
Independent and Public "Networks"
IND1 86 5.43
IND2 40 2.53
IND3 20 1.26
IND4 12 0.76
IND5 9 0.57
IND6 5 0.32
IND7 3 0.19
IND8 1 0.06
IND9 1 0.06
PBS1 181 11.43
PBS2 91 5.75
PBS3 40 2.53
PBS4 22 1.39
PBS5 6 0.38
PBS6 4 0.25
Other Broadcast Networks
AZA 5 0.32
ION 52 3.28
TBN 37 2.34
TEL 22 1.39
TLF 19 1.20
UNI 37 2.34
Total 1,583 100.00
Source: Author calculations. Note: IND1-IND9 (PBS1-PBS6) are "virtual networks" consisting of the flrst, second,
etc. Independent (Public) television station ofiered in each Nielsen DMA. See Section 4.1 for more details. AZA
= Azteca America, ION = The "i" network, TBN = Trinity Broadcasting Network, TEL = Telemundo, TLF =
Telefutura, and UNI = Univision
34
Table 6: Program Production by Programming Type
6:00 p.m. - 12:00 a.m. EST (or equivalent), 2 weeks/year, 2003-2006
All Broadcast Cable
Variable Networks Networks Networks
News Programming
Any News 4.14 11.79 2.96
Network News 0.51 2.63 0.18
Local News 3.63 9.16 2.78
Public Afiairs Programming 1.98 3.40 1.76
Minority Programming
Networks Targeting Black Audiences 3.39 0.00 3.91
Targeting Latino Audiences
On Networks Targeting Latino Audiences 8.13 15.17 7.05
Spanish-Language Programming 3.39 5.54 3.05
Networks Targeting Other Diverse Audiences 2.65 0.00 3.06
Children’s Programming
"Children’s Programming" 1.93 0.84 2.10
G Movies or TV-Y / TV-Y7 TV 3.11 1.06 3.42
Either of the above 5.03 1.90 5.52
Family Programming
Networks Targeting Families 10.93 0.00 12.61
TY-G Programming 11.59 17.05 10.75
Arts, Educational, or Documentary Programming 7.60 6.46 7.77
Either of the two above 19.18 23.50 18.52
Adult Programming
Networks Showing Adult Programming 4.98 0.00 5.75
NC-17 Movies or TV-MA-S / TV-MA-L TV 0.67 0.39 0.72
Violent Programming
"Violent Programming" 1.70 0.53 1.88
TV-PG-V Television 1.46 2.31 1.33
TV-14-V Television 1.47 2.07 1.37
TV-MA-V Television 0.19 0.12 0.20
Any of the three above 3.11 4.50 2.90
Any of the last two above 1.65 2.18 1.57
Religious Programming
Networks Showing Primarily Religious Programming 1.52 7.58 0.58
"Religious Programming" 3.03 11.76 1.69
Overall Targeting
Average TV Content Rating (where noted for TV) 3.81 3.66 3.86
Average MPAA Rating (where noted for movies) 3.96 4.00 3.95
Observations 265,388 35,448 229,940
Notes: Reported in the table is the percentage of quarter-hours of programming on one of 27 broadcast
television networks (cf. Table 5) or 192 cable television networks (cf. Table 27-28) between 6:00 p.m. and
12:00 a.m. EST (or the equivalent) during each of the two weeks per year for 4 years (cf. Table 1) devoted
to programming of the listed types. See Section 4.2 for further detail about the deflnition of program types.
Source: Author calculations.
35
Table 7: Program Availability by Program Type
6:00 p.m. - 12:00 a.m. EST (or equivalent), 2 weeks/year, 2003-2006
All Broadcast Cable
Variable Networks Networks Networks
News Programming
Any News 48.00 66.38 36.74
Network News 52.81 76.26 1.23
Local News 47.33 63.54 39.09
Public Afiairs Programming 56.64 40.49 61.47
Minority Programming
Networks Targeting Black Audiences 20.99 | 20.99
Targeting Latino Audiences
On Networks Targeting Latino Audiences 13.47 31.39 7.53
Spanish-Language Programming 12.52 31.93 7.09
Networks Targeting Other Diverse Audiences 16.23 | 16.23
Children’s Programming
"Children’s Programming" 38.59 37.36 38.66
G Movies or TV-Y / TV-Y7 TV 41.39 39.47 41.48
Either of the above 40.31 38.54 40.41
Family Programming
Networks Targeting Families 53.38 | 53.38
TY-G Programming 40.44 37.89 41.07
Arts, Educational, or Documentary Programming 40.98 43.54 40.66
Either of the two above 40.66 39.44 40.89
Adult Programming
Networks Showing Adult Programming | | |
NC-17 Movies or TV-MA-S / TV-MA-L TV 10.31 34.97 8.26
Violent Programming
"Violent Programming" 19.85 54.20 18.37
TV-PG-V Television 50.13 70.63 44.62
TV-14-V Television 47.35 73.62 41.25
TV-MA-V Television 10.52 35.63 8.30
Any of the three above 46.41 71.11 40.51
Any of the last two above 43.13 71.61 37.04
Religious Programming
Networks Showing Primarily Religious Programming 40.94 51.92 18.99
"Religious Programming" 21.99 26.50 17.14
Overall Targeting
Average TV Content Rating (where noted for TV)
Average MPAA Rating (where noted for movies)
Observations 265,388 35,448 229,940
Notes: Reported in the table is the average estimated share of U.S. households with access to programming
of each type. Average is over the same networks and time periods described in the notes to Table 6. It is
calculated by weighting programming of each type by availability and dividing by the average amount of
programming of that type (from Table 6). See Section 5.1 for more details. Source: Author calculations.
36
Table 8: Program Ratings by Program Type
6:00 p.m. - 12:00 a.m. EST (or equivalent), 2 weeks/year, 2003-2005
All Broadcast Cable
Variable Networks Networks Networks
News Programming
Any News 0.83 2.01 0.11
Network News 1.88 2.73 0.00
Local News 0.68 1.81 0.11
Public Afiairs Programming 0.27 0.07 0.33
Minority Programming
Networks Targeting Black Audiences 0.05 | 0.05
Targeting Latino Audiences
On Networks Targeting Latino Audiences 0.09 0.34 0.00
Spanish-Language Programming 0.06 0.25 0.00
Networks Targeting Other Diverse Audiences 0.00 | 0.00
Children’s Programming
"Children’s Programming" 0.16 0.01 0.17
G Movies or TV-Y / TV-Y7 TV 0.25 0.12 0.26
Either of the above 0.22 0.07 0.22
Family Programming
Networks Targeting Families 0.28 | 0.28
TY-G Programming 0.20 0.31 0.17
Arts, Educational, or Documentary Programming 0.13 0.02 0.14
Either of the two above 0.17 0.23 0.16
Adult Programming
Networks Showing Adult Programming 0.00 | 0.00
NC-17 Movies or TV-MA-S / TV-MA-L TV 0.04 0.02 0.04
Violent Programming
"Violent Programming" 0.14 0.97 0.11
TV-PG-V Television 0.75 2.29 0.34
TV-14-V Television 0.91 3.70 0.26
TV-MA-V Television 0.04 0.00 0.04
Any of the three above 0.78 2.88 0.28
Any of the last two above 0.81 3.51 0.23
Religious Programming
Networks Showing Primarily Religious Programming 0.09 0.14 0.00
"Religious Programming" 0.02 0.01 0.04
Overall Targeting
Average TV Content Rating (where noted for TV)
Average MPAA Rating (where noted for movies)
Observations 265,388 35,448 229,940
Notes: Reported in the table is the average rating (i.e. share of U.S. households that watch a program)
across program types. Average is over the same networks and time periods described in the notes to Table
6. It is calculated by weighting programming of each type by the number of households that viewed the
program. See Section 5.1 for more details. Source: Author calculations.
37
Table 9: Program Ratings as a Share of Households with Access (Program Quality)
6:00 p.m. - 12:00 a.m. EST (or equivalent), 2 weeks/year, 2003-2005
All Broadcast Cable
Variable Networks Networks Networks
News Programming
Any News 1.73 3.03 0.29
Network News 3.56 3.59 0.00
Local News 1.44 2.84 0.29
Public Afiairs Programming 0.48 0.17 0.54
Minority Programming
Networks Targeting Black Audiences 0.23 | 0.23
Targeting Latino Audiences
On Networks Targeting Latino Audiences 0.64 1.08 0.02
Spanish-Language Programming 0.45 0.79 0.03
Networks Targeting Other Diverse Audiences 0.01 | 0.01
Children’s Programming
"Children’s Programming" 0.41 0.04 0.43
G Movies or TV-Y / TV-Y7 TV 0.61 0.31 0.63
Either of the above 0.54 0.19 0.55
Family Programming
Networks Targeting Families 0.52 | 0.52
TY-G Programming 0.50 0.81 0.42
Arts, Educational, or Documentary Programming 0.31 0.04 0.35
Either of the two above 0.42 0.58 0.39
Adult Programming
Networks Showing Adult Programming | | |
NC-17 Movies or TV-MA-S / TV-MA-L TV 0.38 0.05 0.50
Violent Programming
"Violent Programming" 0.72 1.78 0.58
TV-PG-V Television 1.50 3.24 0.77
TV-14-V Television 1.92 5.03 0.63
TV-MA-V Television 0.38 0.00 0.52
Any of the three above 1.69 4.05 0.70
Any of the last two above 1.87 4.89 0.63
Religious Programming
Networks Showing Primarily Religious Programming 0.22 0.26 0.00
"Religious Programming" 0.11 0.05 0.22
Overall Targeting
Average TV Content Rating (where noted for TV)
Average MPAA Rating (where noted for movies)
Observations 265,388 35,448 229,940
Notes: Reported in the table is the average rating among households with access to a program. This is
also used as one of our measures of Program Quality. Average is over the same networks and time periods
described in the notes to Table 6. It is calculated by taking the average rating in Table 8 and dividing by
the average availability in Table 7. See Section 5.1 for more details. Source: Author calculations.
38
Table 10: Program Production by Programming Type and Time
6:00 p.m. - 12:00 a.m. EST (or equivalent), 2 weeks/year, 2003-2006
Variable 2003 2004 2005 2006
News Programming
Any News 4.29 3.99 4.07 4.22
Network News 0.60 0.51 0.49 0.46
Local News 3.69 3.47 3.58 3.76
Public Afiairs Programming 2.37 2.13 1.88 1.59
Minority Programming
Networks Targeting Black Audiences 3.26 3.61 3.45 3.23
Targeting Latino Audiences
On Networks Targeting Latino Audiences 7.11 8.07 8.35 8.87
Spanish-Language Programming 2.94 3.01 3.41 4.09
Networks Targeting Other Diverse Audiences 2.65 2.55 2.67 2.72
Children’s Programming
"Children’s Programming" 1.70 1.91 2.15 1.94
G Movies or TV-Y / TV-Y7 TV 3.18 3.28 3.04 2.94
Either of the above 4.88 5.19 5.19 4.88
Family Programming
Networks Targeting Families 11.46 10.89 10.69 10.74
TY-G Programming 11.35 12.18 11.93 10.94
Arts, Educational, or Documentary Programming 8.32 7.46 7.05 7.62
Either of the two above 19.67 19.64 18.98 18.56
Adult Programming
Networks Showing Adult Programming 4.84 4.60 4.89 5.52
NC-17 Movies or TV-MA-S / TV-MA-L TV 0.75 0.48 0.63 0.83
Violent Programming
"Violent Programming" 1.52 1.71 1.94 1.63
TV-PG-V Television 1.43 1.45 1.54 1.41
TV-14-V Television 1.37 1.40 1.56 1.51
TV-MA-V Television 0.15 0.16 0.23 0.22
Any of the three above 2.95 3.01 3.33 3.14
Any of the last two above 1.52 1.56 1.79 1.73
Religious Programming
Networks Showing Primarily Religious Programming 1.64 1.56 1.49 1.40
"Religious Programming" 3.31 3.15 2.92 2.79
Overall Targeting
Average TV Content Rating (where noted for TV) 3.71 3.75 3.84 3.93
Average MPAA Rating (where noted for movies) 3.99 3.93 3.98 3.95
Observations 61,314 64,560 67,530 71,984
Notes: Reported in the table is the percentage of quarter-hours of programming by program type and year.
It is the analog of Table 6 split out by year. Average is over the same networks and time periods described
in the notes to Table 6. Source: Author calculations.
39
Table 11: Program Availability by Program Type and Time
6:00 p.m. - 12:00 a.m. EST (or equivalent), 2 weeks/year, 2003-2006
Variable 2003 2004 2005 2006
News Programming
Any News 47.79 46.11 48.59 51.07
Network News 55.60 52.73 52.15 47.71
Local News 46.52 45.14 48.11 51.53
Public Afiairs Programming 57.48 57.79 54.52 48.05
Minority Programming
Networks Targeting Black Audiences 17.91 19.00 21.41 23.61
Targeting Latino Audiences
On Networks Targeting Latino Audiences 14.14 13.43 13.50 13.81
Spanish-Language Programming 13.57 12.97 12.24 14.14
Networks Targeting Other Diverse Audiences 13.29 14.97 16.92 19.47
Children’s Programming
"Children’s Programming" 28.78 34.62 41.07 42.20
G Movies or TV-Y / TV-Y7 TV 35.89 39.80 44.39 43.65
Either of the above 33.42 37.89 43.02 43.05
Family Programming
Networks Targeting Families 51.40 53.93 54.73 53.65
TY-G Programming 41.66 39.66 40.46 36.79
Arts, Educational, or Documentary Programming 42.24 42.40 40.80 41.86
Either of the two above 41.91 40.70 40.59 38.67
Adult Programming
Networks Showing Adult Programming | | | |
NC-17 Movies or TV-MA-S / TV-MA-L TV 12.53 15.53 7.10 10.82
Violent Programming
"Violent Programming" 26.29 16.48 15.81 18.87
TV-PG-V Television 44.85 52.90 50.60 47.33
TV-14-V Television 48.35 37.62 44.57 55.39
TV-MA-V Television 0.64 23.71 12.06 5.96
Any of the three above 44.23 44.27 45.14 48.29
Any of the last two above 43.66 36.22 40.45 49.12
Religious Programming
Networks Showing Primarily Religious Programming 40.98 41.09 40.72 38.44
"Religious Programming" 20.43 22.09 22.66 21.79
Overall Targeting
Average TV Content Rating (where noted for TV)
Average MPAA Rating (where noted for movies)
Observations 61,314 64,560 67,530 71,984
Notes: Reported in the table is the average estimated share of U.S. households with access to programming
of each type, by year. It is the analog of Table 7 split out by year. Average is over the same networks and
time periods described in the notes to Table 6. Source: Author calculations.
40
Table 12: Program Ratings by Program Type and Time
6:00 p.m. - 12:00 a.m. EST (or equivalent), 2 weeks/year, 2003-2006
Variable 2003 2004 2005
News Programming
Any News 1.03 0.89 0.85
Network News 2.34 1.76 1.82
Local News 0.81 0.77 0.71
Public Afiairs Programming 0.34 0.32 0.34
Minority Programming
Networks Targeting Black Audiences 0.07 0.06 0.07
Targeting Latino Audiences
On Networks Targeting Latino Audiences 0.11 0.09 0.08
Spanish-Language Programming 0.06 0.06 0.06
Networks Targeting Other Diverse Audiences 0.00 0.00 0.01
Children’s Programming
"Children’s Programming" 0.16 0.20 0.27
G Movies or TV-Y / TV-Y7 TV 0.31 0.34 0.36
Either of the above 0.26 0.29 0.33
Family Programming
Networks Targeting Families 0.37 0.37 0.38
TY-G Programming 0.27 0.23 0.25
Arts, Educational, or Documentary Programming 0.19 0.17 0.17
Either of the two above 0.23 0.21 0.22
Adult Programming
Networks Showing Adult Programming 0.00 0.00 0.00
NC-17 Movies or TV-MA-S / TV-MA-L TV 0.05 0.09 0.04
Violent Programming
"Violent Programming" 0.28 0.15 0.15
TV-PG-V Television 0.85 0.90 0.75
TV-14-V Television 0.93 0.79 1.22
TV-MA-V Television 0.00 0.09 0.07
Any of the three above 0.85 0.81 0.93
Any of the last two above 0.84 0.72 1.08
Religious Programming
Networks Showing Primarily Religious Programming 0.13 0.11 0.08
"Religious Programming" 0.03 0.03 0.04
Overall Targeting
Average TV Content Rating (where noted for TV)
Average MPAA Rating (where noted for movies)
Observations 61,314 64,560 67,530
Notes: Reported in the table is the average rating across program types and years. This table covers 2003-
2005 as we did not have cable ratings data for 2006. It is the analog of Table 8 split out by year. Average
is over the same networks and time periods described in the notes to Table 6. Source: Author calculations.
41
Table 13: Program Ratings as a Share of Households with Access (Program Quality)
6:00 p.m. - 12:00 a.m. EST (or equivalent), 2 weeks/year, 2003-2006
Variable 2003 2004 2005
News Programming
Any News 2.15 1.94 1.74
Network News 4.21 3.33 3.49
Local News 1.75 1.70 1.49
Public Afiairs Programming 0.60 0.56 0.62
Minority Programming
Networks Targeting Black Audiences 0.41 0.11 0.31
Targeting Latino Audiences
On Networks Targeting Latino Audiences 0.75 0.69 0.62
Spanish-Language Programming 0.47 0.47 0.49
Networks Targeting Other Diverse Audiences 0.00 0.00 0.03
Children’s Programming
"Children’s Programming" 0.55 0.59 0.66
G Movies or TV-Y / TV-Y7 TV 0.87 0.85 0.82
Either of the above 0.78 0.76 0.76
Family Programming
Networks Targeting Families 0.73 0.98 0.69
TY-G Programming 0.64 0.59 0.62
Arts, Educational, or Documentary Programming 0.44 0.39 0.41
Either of the two above 0.56 0.51 0.54
Adult Programming
Networks Showing Adult Programming | | |
NC-17 Movies or TV-MA-S / TV-MA-L TV 0.42 0.57 0.53
Violent Programming
"Violent Programming" 1.06 0.89 0.92
TV-PG-V Television 1.90 1.71 1.48
TV-14-V Television 1.93 2.11 2.74
TV-MA-V Television 0.00 0.38 0.59
Any of the three above 1.91 1.83 2.05
Any of the last two above 1.93 2.00 2.66
Religious Programming
Networks Showing Primarily Religious Programming 0.31 0.27 0.19
"Religious Programming" 0.13 0.14 0.16
Overall Targeting
Average TV Content Rating (where noted for TV)
Average MPAA Rating (where noted for movies)
Observations 61,314 64,560 67,530
Notes: Reported in the table is the average rating among households with access to a program across program
types and years. This is also used as one of our measures of Program Quality. This table covers 2003-2005
as we did not have cable ratings data for 2006. It is the analog of Table 9 split out by year. Average is over
the same networks and time periods described in the notes to Table 6. Source: Author calculations.42
Table 14: Outcomes in the Broadcast Advertising Market, By A–liate Type and Year
6:00 - 12:00 p.m. (or equivalent), Top 100 DMAs
Big 4 Network A–liates
Variable All Years 2003 2004 2005 2006
Scheduled Duration (minutes) 57.98 55.47 60.10 58.08 58.29
Ads
Number of Ads 27.90 26.72 27.95 28.22 28.77
Total Ad Time (minutes) 12.4 11.7 12.5 12.5 12.8
Ad Share (percent) 22.5 22.1 22.3 22.6 22.9
Promotions
Number of Promotions 6.91 6.99 7.22 6.75 6.68
Total Promo Time (minutes) 5.8 5.9 6.1 5.7 5.6
Promo Share (percent) 10.0 10.5 9.9 9.8 10.0
Ads + Promos
Number of Ads + Promos 34.82 33.71 35.17 34.97 35.45
Total Ad + Promo Time (minutes) 18.2 17.6 18.6 18.2 18.4
Total Ad + Promo Share (percent) 32.5 32.6 32.2 32.4 32.9
Revenue and Price
Total Revenue from All Ads (000s) $28.59 $24.91 $27.28 $30.03 $32.44
Average Price per 30-second spot (000s) $1.12 $1.06 $1.09 $1.14 $1.19
Observations 5,280 1,344 1,344 1,344 1,248
Other Broadcast Station A–liates
Variable All Years 2003 2004 2005 2006
Scheduled Duration (minutes) 66.39 68.87 67.41 64.84 64.24
Ads
Number of Ads 22.48 22.73 22.93 22.59 21.61
Total Ad Time (minutes) 11.1 11.5 11.2 10.9 10.6
Ad Share (percent) 17.6 17.6 17.7 17.7 17.4
Promotions
Number of Promotions 7.23 7.78 7.60 6.91 6.57
Total Promo Time (minutes) 6.1 6.6 6.4 5.8 5.5
Promo Share (percent) 9.2 9.6 9.5 8.9 8.7
Ads + Promos
Number of Ads + Promos 29.70 30.51 30.53 29.50 28.18
Total Ad + Promo Time (minutes) 17.2 18.1 17.6 16.7 16.1
Total Ad + Promo Share (percent) 26.8 27.1 27.3 26.6 26.1
Revenue and Price
Total Revenue from All Ads $10.99 $11.57 $11.20 $10.17 $10.98
Average Price per 30-second spot (000s) $0.53 $0.55 $0.54 $0.50 $0.54
Observations 15,400 4,025 3,842 3,813 3,720
Notes: Reported in the table is average outcomes from the advertising market, by a–liate type and year.
The average is over commercial (i.e. non-PBS) broadcast television stations in most of the top 108 DMAs for
the same hours (6:00-12:00) and weeks of data described in the notes to Table 6. Big-4 a–liates are television
stations a–liated with ABC, CBS, NBC, or FOX. Other a–liates are the other a–liate types listed in Table
5, except that Independent television stations are pooled together and not split out into a "virtual network"
as reported in that table. Source: TMS, TNS, and author calculations.
43
Table 15: Sample Statistics for Ownership Analysis, Page 1
Market, Ownership, and Advertising Variables
All "Big-4" Other
Variable Stations Stations Stations
DMA Information
DMA Rank 76.22 93.35 60.45
DMA Households (000s) 905.9 607.9 1,180.3
Commercial Station 0.76 1.00 0.53
Ownership Information
Local Ownership Information
Locally Owned (percent) 25.17 11.80 37.49
Minority Owned (percent) 0.74 0.85 0.65
Female Owned (percent) 1.42 1.27 1.56
Parent Ownership Information
Number of stations owned by parent 21.34 22.94 19.87
Parent revenue (millions) $302.13 $405.27 $207.16
Percent of U.S. households covered by parent 7.61 8.08 7.17
Cross-Ownership Information
Newspaper-TV cross-ownership (percent) 1.89 3.39 0.52
Radio-TV cross-ownership (percent) 18.35 9.83 26.19
Ad Market Information
Scheduled Duration (minutes) 58.06 58.12 57.95
Ads
Total Ad Time (minutes) 11.95 12.28 11.24
Ad Share (percent) 0.21 0.21 0.20
Promotions
Total Promo Time (minutes) 5.79 5.91 5.53
Promo Share (percent) 0.10 0.10 0.09
Ads + Promos
Total Ad + Promo Time (minutes) 17.75 18.19 16.77
Total Ad + Promo Share (percent) 0.31 0.31 0.29
Revenue and Price
Total Revenue from All Ads (000s) $22.83 $27.80 $11.99
Average Price per 30-second spot (000s) $31.31 $37.34 $18.17
Observations 4,437 2,127 2,310
Notes: Reported in the table are sample statistics for the data used in our analysis of television station
ownership structure on the quantity and quality of television programming. An observation is a broadcast-
television-station-year, thus the (e.g.) news programming is the percentage of quarter hours ofiering news
programming across all the programs ofiered by that station between 6:00 p.m. and 12:00 a.m. EST (or
the equivalent) during each of the two weeks per year for 4 years (cf. Table 1) for which we have data. See
Section ?? for more details. Source: Diwadi, Roberts, and Wise (2007), TMS, and author calculations.
44
Table 16: Sample Statistics for Ownership Analysis, Page 2
Programming Variables
All "Big-4" Other
Variable Stations Stations Stations
News Programming
Any News 18.95 28.43 10.22
Network News 6.00 11.47 0.96
Local News 12.95 16.96 9.26
Public Afiairs Programming 2.82 0.14 5.28
Minority Programming
Spanish-Language Programming 1.69 0.00 3.24
Children’s Programming
"Children’s Programming" 0.79 0.00 1.52
G Movies or TV-Y / TV-Y7 TV 1.01 0.21 1.74
Either of the above 1.80 0.21 3.26
Family Programming
TY-G Programming 13.11 4.55 20.98
Arts, Educational, or Documentary Programming 6.64 1.06 11.79
Either of the two above 19.75 5.61 32.77
Adult Programming
NC-17 Movies or TV-MA-S / TV-MA-L TV 0.47 0.00 0.90
Violent Programming
"Violent Programming" 0.50 0.12 0.85
TV-PG-V Television 3.94 5.06 2.91
TV-14-V Television 4.08 6.13 2.20
TV-MA-V Television 0.16 0.00 0.30
Any of the three above 8.18 11.18 5.41
Any of the last two above 4.24 6.13 2.50
Religious Programming
"Religious Programming" 5.69 0.03 10.91
Overall Targeting
Average TV Content Rating (where noted for TV) 3.94 4.28 3.61
Average MPAA Rating (where noted for movies) 3.73 3.62 3.88
Observations 4,437 2,127 2,310
Notes: Reported in the table are sample statistics for the data used in our analysis of television station
ownership structure on the quantity and quality of television programming. An observation is a broadcast-
television-station-year, thus the (e.g.) advertising time is the average advertising time for all the programs
ofiered by that station between 6:00 p.m. and 12:00 a.m. EST (or the equivalent) during each of the two
weeks per year for 4 years (cf. Table 1) for which we have data. See Section ?? for more details. Source:
TMS, Nielsen, and author calculations.
45
Table 17: The Impact of Ownership Structure on Local News Programming
Speciflcation (1) (2) (3) (4) (5) (6) (7) (8) (9)
Estimate Estimate Estimate Estimate Estimate Estimate Estimate Estimate Estimate
Variable Std. Err. Std. Err. Std. Err. Std. Err. Std. Err. Std. Err. Std. Err. Std. Err. Std. Err.
DMA Information
DMA Households 0.026 | | | | | | | |
(0.00)
DMA HH Squared -0.003 | | | | | | | |
(0.00)
Commercial Station -0.01 0.00 0.00 0.00 0.00 0.00 0.00 -0.01 -0.01
-(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01)
A–liate Information
ABC 0.16 0.16 0.16 0.16 0.16 0.16 0.16 0.18 0.17
-(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01)
CBS 0.16 0.17 0.17 0.17 0.17 0.16 0.16 0.17 0.17
-(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01)
NBC 0.17 0.18 0.18 0.18 0.18 0.17 0.18 0.18 0.18
-(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01)
FOX 0.09 0.10 0.10 0.10 0.10 0.10 0.10 0.10 0.10
-(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01)
CW 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.02 0.01
-(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01)
PBS 0.11 0.12 0.13 0.12 0.12 0.12 0.12 0.14 0.14
-(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01)
Independent 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.05 0.05
-(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01)
Spanish Language 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.05 0.05
-(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01)
Other A–liation 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.02 0.02
-(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01)
Ownership Information
Locally Owned | | -0.006 | | | | | 0.000
-(0.003) -(0.003)
Minority Owned | | | -0.005 | | | | -0.002
-(0.012) -(0.012)
Female Owned | | | | 0.012 | | | 0.016
-(0.009) -(0.008)
Newspaper-TV | | | | | 0.029 | | 0.030
-(0.007) -(0.007)
Radio-TV | | | | | | 0.004 | 0.001
-(0.003) -(0.003)
Parent revenue | | | | | | | 0.033 0.033
-(0.002) -(0.002)
Constant 0.02 0.00 0.00 0.00 0.00 0.00 0.00 -0.01 -0.01
-(0.01) -(0.02) -(0.02) -(0.02) -(0.02) -(0.02) -(0.02) -(0.02) -(0.02)
Year Dummies No Yes Yes Yes Yes Yes Yes Yes Yes
DMA Fixed Efiects No Yes Yes Yes Yes Yes Yes Yes Yes
Observations 4,437 4,437 4,437 4,437 4,437 4,437 4,437 4,437 4,437
R-squared 0.44 0.51 0.51 0.51 0.51 0.51 0.51 0.53 0.53
Notes: Reported are the results of 9 regressions of the percentage of minutes of local news coverage on
various measures of television station ownership structure and control variables. Section 4.2 describes the
deflnition of the dependent variable. Section 6.2 describes the various speciflcations in more detail. Standard
errors in parentheses. Bold face indicates statistical signiflcance at the 5% level.
46
Table 18: The Impact of Ownership Structure on Public Afiairs Programming
Speciflcation (1) (2) (3) (4) (5) (6) (7) (8) (9)
Estimate Estimate Estimate Estimate Estimate Estimate Estimate Estimate Estimate
Variable Std. Err. Std. Err. Std. Err. Std. Err. Std. Err. Std. Err. Std. Err. Std. Err. Std. Err.
DMA Information
DMA Households -0.002 | | | | | | | |
(0.00)
DMA HH Squared 0.001 | | | | | | | |
(0.00)
Commercial Station -0.05 -0.05 -0.05 -0.05 -0.05 -0.05 -0.05 -0.05 -0.05
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
A–liate Information
ABC 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
CBS 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
NBC 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
FOX 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
CW 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
PBS 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
Independent 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
Spanish Language 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
Other A–liation 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
Ownership Information
Locally Owned | | 0.004 | | | | | 0.004
-(0.001) -(0.001)
Minority Owned | | | 0.002 | | | | -0.002
-(0.006) -(0.006)
Female Owned | | | | 0.017 | | | 0.016
-(0.004) -(0.004)
Newspaper-TV | | | | | -0.005 | | -0.007
-(0.004) -(0.004)
Radio-TV | | | | | | 0.001 | 0.001
-(0.001) -(0.001)
Parent revenue | | | | | | | 0.000 0.001
-(0.001) -(0.001)
Constant 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05 0.05
(0.00) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01)
Year Dummies No Yes Yes Yes Yes Yes Yes Yes Yes
DMA Fixed Efiects No Yes Yes Yes Yes Yes Yes Yes Yes
Observations 4,437 4,437 4,437 4,437 4,437 4,437 4,437 4,437 4,437
R-squared 0.66 0.7 0.7 0.7 0.7 0.7 0.7 0.7 0.7
Notes: Reported are the results of 9 regressions of the percentage of minutes of public afiairs programming
on various measures of television station ownership structure and control variables. Section 4.2 describes the
deflnition of the dependent variable. Section 6.2 describes the various speciflcations in more detail. Standard
errors in parentheses. Bold face indicates statistical signiflcance at the 5% level.
47
Table 19: The Impact of Ownership Structure on Spanish-Language Programming
Speciflcation (1) (2) (3) (4) (5) (6) (7) (8) (9)
Estimate Estimate Estimate Estimate Estimate Estimate Estimate Estimate Estimate
Variable Std. Err. Std. Err. Std. Err. Std. Err. Std. Err. Std. Err. Std. Err. Std. Err. Std. Err.
DMA Information
DMA Households 0.001 | | | | | | | |
(0.00)
DMA HH Squared 0.000 | | | | | | | |
(0.00)
Commercial Station 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
A–liate Information
ABC 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
CBS 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
NBC 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
FOX 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
CW 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
PBS 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
Independent 0.01 0.01 0.02 0.01 0.01 0.01 0.01 0.01 0.01
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
Spanish Language 0.32 0.32 0.32 0.32 0.32 0.32 0.32 0.32 0.32
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
Other A–liation 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
Ownership Information
Locally Owned | | -0.007 | | | | | -0.008
-(0.001) -(0.001)
Minority Owned | | | 0.005 | | | | 0.005
-(0.006) -(0.006)
Female Owned | | | | -0.003 | | | -0.001
-(0.004) -(0.004)
Newspaper-TV | | | | | -0.001 | | 0.002
-(0.004) -(0.004)
Radio-TV | | | | | | 0.004 | 0.005
-(0.001) -(0.001)
Parent revenue | | | | | | | -0.001 -0.003
-(0.001) -(0.001)
Constant -0.01 -0.01 -0.01 -0.01 -0.01 -0.01 -0.01 -0.01 -0.01
(0.00) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01)
Year Dummies No Yes Yes Yes Yes Yes Yes Yes Yes
DMA Fixed Efiects No Yes Yes Yes Yes Yes Yes Yes Yes
Observations 4,437 4,437 4,437 4,437 4,437 4,437 4,437 4,437 4,437
R-squared 0.82 0.83 0.83 0.83 0.83 0.83 0.83 0.83 0.83
Notes: Reported are the results of 9 regressions of the percentage of minutes of spanish-language pro-
gramming on various measures of television station ownership structure and control variables. Section 4.2
describes the deflnition of the dependent variable. Section 6.2 describes the various speciflcations in more
detail. Standard errors in parentheses. Bold face indicates statistical signiflcance at the 5% level.
48
Table 20: The Impact of Ownership Structure on Children’s Programming
Speciflcation (1) (2) (3) (4) (5) (6) (7) (8) (9)
Estimate Estimate Estimate Estimate Estimate Estimate Estimate Estimate Estimate
Variable Std. Err. Std. Err. Std. Err. Std. Err. Std. Err. Std. Err. Std. Err. Std. Err. Std. Err.
DMA Information
DMA Households 0.001 | | | | | | | |
(0.00)
DMA HH Squared 0.000 | | | | | | | |
(0.00)
Commercial Station 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
-(0.01) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
A–liate Information
ABC 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
CBS 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
NBC 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
FOX 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
CW 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
PBS 0.07 0.07 0.07 0.07 0.07 0.07 0.07 0.07 0.07
-(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01)
Independent 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
Spanish Language 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.02
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
Other A–liation 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
Ownership Information
Locally Owned | | 0.007 | | | | | 0.007
-(0.002) -(0.002)
Minority Owned | | | -0.006 | | | | -0.007
-(0.008) -(0.008)
Female Owned | | | | 0.005 | | | 0.004
-(0.006) -(0.006)
Newspaper-TV | | | | | 0.001 | | -0.002
-(0.005) -(0.005)
Radio-TV | | | | | | -0.004 | -0.005
-(0.002) -(0.002)
Parent revenue | | | | | | | -0.001 0.000
-(0.002) -(0.002)
Constant 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
-(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01)
Year Dummies No Yes Yes Yes Yes Yes Yes Yes Yes
DMA Fixed Efiects No Yes Yes Yes Yes Yes Yes Yes Yes
Observations 4,437 4,437 4,437 4,437 4,437 4,437 4,437 4,437 4,437
R-squared 0.26 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4
Notes: Reported are the results of 9 regressions of the percentage of minutes of children’s programming
on various measures of television station ownership structure and control variables. The speciflc children’s
programming variable chosen is ’Either "Children’s Programming", G Movies, or TV-Y or TV-Y7 Program-
ming". Section 4.2 describes the deflnition of the dependent variable in more detail. Section 6.2 describes
the various speciflcations in more detail. Standard errors in parentheses. Bold face indicates statistical
signiflcance at the 5% level.
49
Table 21: The Impact of Ownership Structure on Family Programming
Speciflcation (1) (2) (3) (4) (5) (6) (7) (8) (9)
Estimate Estimate Estimate Estimate Estimate Estimate Estimate Estimate Estimate
Variable Std. Err. Std. Err. Std. Err. Std. Err. Std. Err. Std. Err. Std. Err. Std. Err. Std. Err.
DMA Information
DMA Households -0.006 | | | | | | | |
(0.00)
DMA HH Squared 0.000 | | | | | | | |
(0.00)
Commercial Station -0.17 -0.17 -0.16 -0.17 -0.17 -0.17 -0.17 -0.16 -0.16
-(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01)
A–liate Information
ABC 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
-(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01)
CBS 0.02 0.03 0.03 0.03 0.03 0.03 0.03 0.02 0.03
-(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01)
NBC 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
-(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01)
FOX 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
-(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01)
CW 0.01 0.00 0.00 0.01 0.01 0.00 0.01 0.00 0.01
-(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01)
PBS 0.34 0.34 0.34 0.34 0.34 0.34 0.34 0.34 0.34
-(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01)
Independent 0.16 0.16 0.15 0.16 0.16 0.16 0.16 0.15 0.15
-(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01)
Spanish Language -0.04 -0.03 -0.03 -0.03 -0.03 -0.03 -0.03 -0.04 -0.03
-(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01)
Other A–liation 0.23 0.23 0.23 0.23 0.23 0.23 0.23 0.22 0.23
-(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01)
Ownership Information
Locally Owned | | 0.013 | | | | | 0.011
-(0.004) -(0.004)
Minority Owned | | | -0.017 | | | | -0.015
-(0.017) -(0.017)
Female Owned | | | | -0.019 | | | -0.022
-(0.012) -(0.012)
Newspaper-TV | | | | | 0.011 | | 0.006
-(0.011) -(0.011)
Radio-TV | | | | | | -0.006 | -0.006
-(0.004) -(0.004)
Parent revenue | | | | | | | -0.010 -0.008
-(0.003) -(0.003)
Constant 0.22 0.21 0.21 0.21 0.21 0.21 0.21 0.21 0.21
-(0.01) -(0.03) -(0.03) -(0.03) -(0.03) -(0.03) -(0.03) -(0.03) -(0.03)
Year Dummies No Yes Yes Yes Yes Yes Yes Yes Yes
DMA Fixed Efiects No Yes Yes Yes Yes Yes Yes Yes Yes
Observations 4,437 4,437 4,437 4,437 4,437 4,437 4,437 4,437 4,437
R-squared 0.84 0.85 0.85 0.85 0.85 0.85 0.85 0.85 0.85
Notes: Reported are the results of 9 regressions of the percentage of minutes of family programming on
various measures of television station ownership structure and control variables. The speciflc family pro-
gramming variable chosen is ’Either TV-G television programming or Arts, Educational or Documentary
programming’. Section 4.2 describes the deflnition of the dependent variable in more detail. Section 6.2
describes the various speciflcations in more detail. Standard errors in parentheses. Bold face indicates
statistical signiflcance at the 5% level.
50
Table 22: The Impact of Ownership Structure on Violent Programming
Speciflcation (1) (2) (3) (4) (5) (6) (7) (8) (9)
Estimate Estimate Estimate Estimate Estimate Estimate Estimate Estimate Estimate
Variable Std. Err. Std. Err. Std. Err. Std. Err. Std. Err. Std. Err. Std. Err. Std. Err. Std. Err.
DMA Information
DMA Households -0.004 | | | | | | | |
(0.00)
DMA HH Squared 0.000 | | | | | | | |
(0.00)
Commercial Station 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
A–liate Information
ABC -0.08 -0.08 -0.08 -0.08 -0.08 -0.08 -0.08 -0.08 -0.08
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
CBS 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02 0.02
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
NBC -0.14 -0.14 -0.14 -0.14 -0.14 -0.14 -0.14 -0.14 -0.14
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
FOX 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.04 0.04
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
CW 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
PBS -0.08 -0.08 -0.07 -0.08 -0.08 -0.08 -0.08 -0.07 -0.07
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
Independent -0.13 -0.13 -0.13 -0.13 -0.13 -0.13 -0.13 -0.13 -0.13
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
Spanish Language -0.15 -0.15 -0.15 -0.15 -0.15 -0.15 -0.15 -0.15 -0.15
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
Other A–liation -0.14 -0.14 -0.14 -0.14 -0.14 -0.14 -0.14 -0.14 -0.14
(0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00) (0.00)
Ownership Information
Locally Owned | | -0.004 | | | | | -0.003
-(0.001) -(0.001)
Minority Owned | | | -0.003 | | | | -0.002
-(0.006) -(0.006)
Female Owned | | | | 0.001 | | | 0.003
-(0.004) -(0.004)
Newspaper-TV | | | | | -0.006 | | -0.005
-(0.004) -(0.004)
Radio-TV | | | | | | 0.003 | 0.003
-(0.001) -(0.001)
Parent revenue | | | | | | | 0.003 0.003
-(0.001) -(0.001)
Constant 0.14 0.12 0.12 0.12 0.12 0.12 0.12 0.12 0.12
(0.00) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01)
Year Dummies No Yes Yes Yes Yes Yes Yes Yes Yes
DMA Fixed Efiects No Yes Yes Yes Yes Yes Yes Yes Yes
Observations 4,437 4,437 4,437 4,437 4,437 4,437 4,437 4,437 4,437
R-squared 0.81 0.85 0.85 0.85 0.85 0.85 0.85 0.85 0.85
Notes: Reported are the results of 9 regressions of the percentage of minutes of violent programming on
various measures of television station ownership structure and control variables. The speciflc violent pro-
gramming variable chosen is ’Either TV-PG-V, TV-14-V, or TV-MA-V television programming. Section 4.2
describes the deflnition of the dependent variable in more detail. Section 6.2 describes the various speciflca-
tions in more detail. Standard errors in parentheses. Bold face indicates statistical signiflcance at the 5%
level.
51
Table 23: The Impact of Ownership Structure on Religious Programming
Speciflcation (1) (2) (3) (4) (5) (6) (7) (8) (9)
Estimate Estimate Estimate Estimate Estimate Estimate Estimate Estimate Estimate
Variable Std. Err. Std. Err. Std. Err. Std. Err. Std. Err. Std. Err. Std. Err. Std. Err. Std. Err.
DMA Information
DMA Households -0.034 | | | | | | | |
-(0.01)
DMA HH Squared 0.003 | | | | | | | |
(0.00)
Commercial Station -0.21 -0.22 -0.22 -0.22 -0.22 -0.22 -0.22 -0.22 -0.22
-(0.02) -(0.02) -(0.02) -(0.02) -(0.02) -(0.02) -(0.02) -(0.02) -(0.02)
A–liate Information
ABC -0.02 -0.02 -0.02 -0.02 -0.02 -0.02 -0.02 -0.02 -0.02
-(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01)
CBS -0.02 -0.01 -0.02 -0.01 -0.01 -0.01 -0.01 -0.02 -0.01
-(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01)
NBC -0.02 -0.01 -0.01 -0.01 -0.02 -0.01 -0.01 -0.02 -0.02
-(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01)
FOX -0.01 -0.01 -0.01 -0.01 -0.01 -0.01 -0.01 -0.01 -0.01
-(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01)
CW 0.01 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00
-(0.02) -(0.02) -(0.02) -(0.02) -(0.02) -(0.02) -(0.02) -(0.02) -(0.02)
PBS -0.22 -0.23 -0.23 -0.23 -0.23 -0.23 -0.22 -0.23 -0.23
-(0.02) -(0.02) -(0.02) -(0.02) -(0.02) -(0.02) -(0.02) -(0.02) -(0.02)
Independent 0.30 0.29 0.29 0.29 0.29 0.29 0.30 0.29 0.29
-(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01)
Spanish Language 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01
-(0.02) -(0.02) -(0.02) -(0.02) -(0.02) -(0.02) -(0.02) -(0.02) -(0.02)
Other A–liation 0.34 0.33 0.33 0.33 0.33 0.33 0.33 0.32 0.32
-(0.01) -(0.02) -(0.02) -(0.02) -(0.02) -(0.02) -(0.02) -(0.02) -(0.02)
Ownership Information
Locally Owned | | 0.011 | | | | | 0.008
-(0.006) -(0.007)
Minority Owned | | | -0.012 | | | | -0.029
-(0.028) -(0.028)
Female Owned | | | | 0.081 | | | 0.081
-(0.020) -(0.020)
Newspaper-TV | | | | | 0.016 | | 0.011
-(0.018) -(0.018)
Radio-TV | | | | | | -0.007 | -0.007
-(0.007) -(0.007)
Parent revenue | | | | | | | -0.006 -0.003
-(0.006) -(0.006)
Constant 0.24 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37
-(0.02) -(0.04) -(0.04) -(0.04) -(0.04) -(0.04) -(0.04) -(0.04) -(0.04)
Year Dummies No Yes Yes Yes Yes Yes Yes Yes Yes
DMA Fixed Efiects No Yes Yes Yes Yes Yes Yes Yes Yes
Observations 4,437 4,437 4,437 4,437 4,437 4,437 4,437 4,437 4,437
R-squared 0.42 0.47 0.47 0.47 0.47 0.47 0.47 0.47 0.47
Notes: Reported are the results of 9 regressions of the percentage of minutes of religious programming on
various measures of television station ownership structure and control variables. Section 4.2 describes the
deflnition of the dependent variable in more detail. Section 6.2 describes the various speciflcations in more
detail. Standard errors in parentheses. Bold face indicates statistical signiflcance at the 5% level.
52
Table 24: The Impact of Ownership Structure on Advertising Time
Speciflcation (1) (2) (3) (4) (5) (6) (7) (8) (9)
Estimate Estimate Estimate Estimate Estimate Estimate Estimate Estimate Estimate
Variable Std. Err. Std. Err. Std. Err. Std. Err. Std. Err. Std. Err. Std. Err. Std. Err. Std. Err.
DMA Information
DMA Households -0.034 | | | | | | | |
-(0.01)
DMA HH Squared 0.003 | | | | | | | |
(0.00)
Commercial Station | | | | | | | | |
A–liate Information
ABC -0.02 -0.02 -0.02 -0.02 -0.02 -0.02 -0.02 -0.02 -0.02
-(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01)
CBS -0.02 -0.01 -0.02 -0.01 -0.01 -0.01 -0.01 -0.02 -0.01
-(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01)
NBC -0.02 -0.01 -0.01 -0.01 -0.02 -0.01 -0.01 -0.02 -0.02
-(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01)
FOX -0.01 -0.01 -0.01 -0.01 -0.01 -0.01 -0.01 -0.01 -0.01
-(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01)
CW 0.01 0.00 0.00 0.00 0.00 0.00 0.01 0.00 0.00
-(0.02) -(0.02) -(0.02) -(0.02) -(0.02) -(0.02) -(0.02) -(0.02) -(0.02)
PBS | | | | | | | | |
Independent 0.30 0.29 0.29 0.29 0.29 0.29 0.30 0.29 0.29
-(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01) -(0.01)
Spanish Language 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01 0.01
-(0.02) -(0.02) -(0.02) -(0.02) -(0.02) -(0.02) -(0.02) -(0.02) -(0.02)
Other A–liation 0.34 0.33 0.33 0.33 0.33 0.33 0.33 0.32 0.32
-(0.01) -(0.02) -(0.02) -(0.02) -(0.02) -(0.02) -(0.02) -(0.02) -(0.02)
Ownership Information
Locally Owned | | 0.011 | | | | | 0.008
-(0.006) -(0.007)
Minority Owned | | | -0.012 | | | | -0.029
-(0.028) -(0.028)
Female Owned | | | | 0.081 | | | 0.081
-(0.020) -(0.020)
Newspaper-TV | | | | | 0.016 | | 0.011
-(0.018) -(0.018)
Radio-TV | | | | | | -0.007 | -0.007
-(0.007) -(0.007)
Parent revenue | | | | | | | -0.006 -0.003
-(0.006) -(0.006)
Constant 0.24 0.37 0.37 0.37 0.37 0.37 0.37 0.37 0.37
-(0.02) -(0.04) -(0.04) -(0.04) -(0.04) -(0.04) -(0.04) -(0.04) -(0.04)
Year Dummies No Yes Yes Yes Yes Yes Yes Yes Yes
DMA Fixed Efiects No Yes Yes Yes Yes Yes Yes Yes Yes
Observations 4,437 4,437 4,437 4,437 4,437 4,437 4,437 4,437 4,437
R-squared 0.42 0.47 0.47 0.47 0.47 0.47 0.47 0.47 0.47
Notes: Reported are the results of 9 regressions of the average minutes of television advertising on various
measures of television station ownership structure and control variables. Section 6.2 describes the various
speciflcations in more detail. Standard errors in parentheses. Bold face indicates statistical signiflcance at
the 5% level.
53
Table 25: The Impact of Ownership Structure on Advertising Prices
Price is for 30-second advertisement.
Speciflcation (1) (2) (3) (4) (5) (6) (7) (8) (9)
Estimate Estimate Estimate Estimate Estimate Estimate Estimate Estimate Estimate
Variable Std. Err. Std. Err. Std. Err. Std. Err. Std. Err. Std. Err. Std. Err. Std. Err. Std. Err.
DMA Information
DMA Households 1.040 | | | | | | | |
-(0.04)
DMA HH Squared -0.039 | | | | | | | |
-(0.01)
Commercial Station | | | | | | | | |
A–liate Information
ABC 1.19 1.27 1.26 1.28 1.27 1.28 1.20 1.28 1.22
-(0.07) -(0.07) -(0.07) -(0.07) -(0.07) -(0.07) -(0.07) -(0.07) -(0.07)
CBS 1.18 1.27 1.26 1.27 1.27 1.27 1.16 1.27 1.18
-(0.07) -(0.07) -(0.07) -(0.07) -(0.07) -(0.07) -(0.07) -(0.07) -(0.07)
NBC 1.14 1.22 1.21 1.22 1.22 1.23 1.19 1.22 1.22
-(0.07) -(0.07) -(0.07) -(0.07) -(0.07) -(0.07) -(0.07) -(0.07) -(0.07)
FOX 0.82 0.88 0.88 0.88 0.88 0.88 0.84 0.88 0.85
-(0.07) -(0.07) -(0.07) -(0.07) -(0.07) -(0.07) -(0.07) -(0.07) -(0.07)
CW 0.25 0.29 0.29 0.29 0.30 0.30 0.20 0.29 0.24
-(0.08) -(0.08) -(0.08) -(0.08) -(0.08) -(0.08) -(0.08) -(0.08) -(0.08)
PBS | | | | | | | | |
Independent -0.41 -0.35 -0.39 -0.35 -0.35 -0.36 -0.43 -0.34 -0.44
-(0.09) -(0.09) -(0.09) -(0.09) -(0.09) -(0.09) -(0.09) -(0.10) -(0.09)
Spanish Language -0.44 -0.45 -0.44 -0.45 -0.45 -0.46 -0.63 -0.44 -0.61
-(0.08) -(0.09) -(0.09) -(0.09) -(0.09) -(0.09) -(0.09) -(0.09) -(0.09)
Other A–liation -0.34 -0.35 -0.34 -0.34 -0.35 -0.35 -0.34 -0.34 -0.30
-(0.09) -(0.10) -(0.09) -(0.10) -(0.10) -(0.10) -(0.09) -(0.10) -(0.10)
Ownership Information
Locally Owned | | 0.196 | | | | | 0.241
-(0.053) -(0.058)
Minority Owned | | | -0.397 | | | | -0.353
-(0.219) -(0.214)
Female Owned | | | | -0.162 | | | -0.123
-(0.157) -(0.155)
Newspaper-TV | | | | | -0.145 | | -0.307
-(0.084) -(0.087)
Radio-TV | | | | | | 0.370 | 0.354
-(0.046) -(0.047)
Parent revenue | | | | | | | 0.015 0.044
-(0.030) -(0.031)
Constant -0.91 -0.87 -0.87 -0.88 -0.87 -0.88 -0.80 -0.88 -0.83
-(0.06) -(0.26) -(0.26) -(0.26) -(0.26) -(0.26) -(0.25) -(0.26) -(0.25)
Year Dummies No Yes Yes Yes Yes Yes Yes Yes Yes
DMA Fixed Efiects No Yes Yes Yes Yes Yes Yes Yes Yes
Observations 1,676 1,676 1,676 1,676 1,676 1,676 1,676 1,676 1,676
R-squared 0.73 0.75 0.75 0.75 0.75 0.75 0.76 0.75 0.76
Notes: Reported are the results of 9 regressions of the average price of television advertising on various
measures of television station ownership structure and control variables. Price is the average price for a
30-second advertisement. Section 6.2 describes the various speciflcations in more detail. Standard errors in
parentheses. Bold face indicates statistical signiflcance at the 5% level.
54
Table 26: The Impact of Ownership Structure on Each Outcome Variable
Channel Fixed Efiects
Spanish
Dependent Local Public Language Children’s Family Violent Religious Ad Ad
Variable News Afiairs Prog. Prog. Prog. Prog. Prog. Time Prices
Estimate Estimate Estimate Estimate Estimate Estimate Estimate Estimate Estimate
Variable Std. Err. Std. Err. Std. Err. Std. Err. Std. Err. Std. Err. Std. Err. Std. Err. Std. Err.
Commercial Station 0.00 0.00 0.10 0.00 -0.84 -0.11 0.01 | |
-(0.01) -(0.01) -(0.01) -(0.01) -(0.02) -(0.03) -(0.01)
A–liate Information
ABC 0.26 0.35 0.06 -0.09 -0.91 0.11 -0.05 -1.89 1.40
-(0.03) -(0.03) -(0.02) -(0.03) -(0.06) -(0.08) -(0.04) -(1.69) -(0.39)
CBS 0.28 0.35 0.10 -0.14 -1.02 0.02 0.05 -3.38 0.60
-(0.04) -(0.03) -(0.03) -(0.03) -(0.08) -(0.10) -(0.05) -(2.16) -(0.50)
NBC 0.22 0.36 0.03 -0.07 -0.73 0.20 -0.13 -1.53 0.23
-(0.03) -(0.02) -(0.02) -(0.02) -(0.06) -(0.07) -(0.04) -(1.62) -(0.37)
FOX 0.17 0.37 0.00 -0.03 -0.62 0.30 0.06 -3.70 0.41
-(0.03) -(0.02) -(0.02) -(0.02) -(0.06) -(0.07) -(0.04) -(2.36) -(0.54)
CW 0.01 0.35 0.10 -0.07 -0.89 0.17 0.04 0.26 0.64
-(0.03) -(0.02) -(0.02) -(0.02) -(0.05) -(0.07) -(0.04) -(1.31) -(0.30)
PBS 0.26 0.44 0.24 -0.17 -1.97 0.30 -0.02 | |
-(0.06) -(0.04) -(0.04) -(0.04) -(0.11) -(0.14) -(0.07)
Independent -0.15 0.35 0.14 -0.03 -0.68 0.28 -0.10 -2.68 0.79
-(0.03) -(0.02) -(0.02) -(0.02) -(0.05) -(0.06) -(0.03) -(1.58) -(0.36)
Spanish Language -0.07 0.35 0.22 -0.02 -0.63 0.27 -0.10 -3.74 -0.27
-(0.03) -(0.02) -(0.02) -(0.02) -(0.05) -(0.06) -(0.03) -(1.57) -(0.36)
Other A–liation -0.15 0.35 0.05 -0.02 -0.70 0.40 -0.09 2.47 -0.05
-(0.03) -(0.02) -(0.02) -(0.02) -(0.05) -(0.06) -(0.03) -(0.99) -(0.23)
Ownership Information
Locally Owned -0.002 -0.002 -0.003 0.001 -0.010 0.003 0.000 0.215 0.139
-(0.004) -(0.003) -(0.003) -(0.003) -(0.007) -(0.009) -(0.005) -(0.275) -(0.063)
Minority Owned 0.034 -0.001 -0.003 -0.073 -0.079 -0.049 0.032 2.950 -0.360
-(0.012) -(0.009) -(0.009) -(0.009) -(0.023) -(0.029) -(0.015) -(1.380) -(0.318)
Female Owned 0.005 -0.002 0.001 0.005 -0.054 -0.006 0.012 -0.799 0.206
-(0.007) -(0.006) -(0.005) -(0.006) -(0.014) -(0.017) -(0.009) -(0.608) -(0.140)
Newspaper-TV 0.023 -0.007 0.035 -0.037 -0.109 -0.039 0.004 -2.620 0.799
-(0.013) -(0.010) -(0.009) -(0.010) -(0.023) -(0.029) -(0.015) -(0.563) -(0.130)
Radio-TV -0.003 -0.004 0.001 -0.001 -0.015 -0.015 -0.001 0.789 0.028
-(0.003) -(0.002) -(0.002) -(0.002) -(0.005) -(0.007) -(0.003) -(0.318) -(0.073)
Parent revenue -0.010 0.000 0.005 0.003 -0.001 0.008 0.008 0.970 0.091
-(0.004) -(0.003) -(0.003) -(0.003) -(0.007) -(0.009) -(0.004) -(0.213) -(0.049)
Constant -0.07 -0.35 -0.13 0.08 1.60 -0.01 0.12 15.90 -0.20
-(0.04) -(0.03) -(0.03) -(0.03) -(0.07) -(0.09) -(0.04) -(2.21) -(0.51)
Year Dummies Yes Yes Yes Yes Yes Yes Yes Yes Yes
DMA Fixed Efiects Yes Yes Yes Yes Yes Yes Yes Yes Yes
Channel Fixed Efiects Yes Yes Yes Yes Yes Yes Yes Yes Yes
Observations 4,437 4,437 4,437 4,437 4,437 4,437 4,437 1,676 1,676
R-squared 0.42 0.47 0.47 0.47 0.47 0.47 0.47 0.47 0.47
Notes: Reported are the results of 9 regressions of each of the dependent variables considered in the 9
previous tables on the full set of television station ownership structure and control variables. See the notes
to those tables for the speciflc deflnitions of the dependent variables. Section 6.2 describes the various
speciflcations in more detail. Standard errors in parentheses. Bold face indicates statistical signiflcance at
the 5% level.
55
Table 27: Cable Networks in the Estimation Dataset, Page 1
Basic Cable Networks
A&E DISNEY EAST KWBM CABLE
ABCFAMILY CHAN DIY NETWORK KWWT CABLE
AMC E! ENTERTAINMENT LA FAMILIA COSMOVISION
AMERICANLIFE TV ESPN LEARNING CHANNEL
ANIMAL PLANET ESPN CLASSIC LIFETIME
ANIME NETWORK ESPN DEPORTES LIFETIME MOVIE NET
AZNTV ESPN UNIVERSITY LIFETIME REAL WOMEN
B MOVIE CHANNEL ESPN2 LIME
BBC AMERICA ESPNEWS LOGO
BEAUTY & FASHION FINE LIVING MENS CHANNEL
BET GOSPEL FIT TV MILITARY CHANNEL
BET J FOOD NETWORK MILITARY HISTORY CHANNEL
BIOGRAPHY CHANNEL FOX COLLEGE SPORTS - ATL MSNBC
BLACK ENTERTAIN FOX MOVIE CHANNEL MTV
BLACK FAMILY CHANNEL FOX NEWS CHANNEL MTV HITS
BLACKBELT TV FOX REALITY CHANNEL MTV JAMS
BLOOMBERG TV FOX SOCCER CHANNEL MTV2
BOOMERANG FOX SPORTS EN ESPANOL MUN2
BRAVO FUEL TV NATIONAL GEOGRAPHIC USA
CARTOON NET FUSE NBA TV
CMT PURE COUNTRY FX EASTERN NFL NETWORK
CNBC G4 VIDEO GAME TELEVISION NICK EAST
CNBC WORLD GALAVISION PACIFIC NICKTOONS NETWOR
CNN GAMES & SPORTS NOGGIN & THE N
CNN INTL DOMESTIC GOLF CHANNEL OUTDOOR CHNL
COLLEGE SPORTS TV GOLTV INTERNATIONAL OVATION ARTS NET
COMEDY CENTRAL GREAT AM COUNTRY OXYGEN CHANNEL
COUNTRY MUSICTV US GSN SCI FI
COURT TV HALLMARK MOVIE CHANNEL SCIENCE CHANNEL
CRIME & INVESTIGATION HALLMARK USA SITV
CSPAN HISTORY CHANNEL SLEUTH
CURRENT TV HISTORY CHANNEL EN ESP SOAP NET
DISCOVERY HISTORY CHANNEL INTL SPEED CHANNEL
DISCOVERY EN ESPANOL HITN SPIKE TV
DISCOVERY HEALTH HOME & GARDEN SPORTSMAN CHANNEL
DISCOVERY HOME IDRIVETV STYLE
DISCOVERY KIDS IFC TEMPO
DISCOVERY KIDS EN ESP INSPIRATIONAL NET TENNIS CHANNEL
DISCOVERY TIMES KBCA CABLE TNT
Source: TMS, Author decisions.
56
Table 28: Cable Networks in the Estimation Dataset, Page 2
Basic Cable Networks, cont.
TOON DISNEY TV ONE WBMM CABLE
TRAVEL USA EASTERN WE WOMENS ENTMNT
TRAVEL AND LIVING EN ESP VERSUS WEALTH TV
TURNER CLASSIC MOVIES VH1 WEATHER CHANNEL
TV GUIDE CHANNEL VH1 CLASSIC WTBS SATELLITE
TV LAND VH1 SOUL
Master Television Networks
NBC WEATHER PLUS TELEMUNDO MASTER UNIVISION MASTER
TELEFUTURA EAST
Premium Cable Networks
CINEMAX MOVIE PLEX STARZ COMEDY
ENCORE RETROPLEX STARZ EDGE
ENCORE ACTION SHOWTIME BEYOND STARZ
ENCORE DRAMA SHOWTIME EAST STARZ 5 CINEMA
ENCORE LOVE SHOWTIME EXTREME STARZ HD
ENCORE MYSTERY SHOWTIME FAMILYZONE STARZ IN BLACK
ENCORE WAM SHOWTIME HDTV EAST STARZ KIDS & FAMILY
ENCORE WESTERNS SHOWTIME NEXT EAST SUNDANCE FILM
FLIX SHOWTIME SHOWCASE TMC EAST
HBO EAST SHOWTIME TOO TMC HD EAST
INDIEPLEX SHOWTIME WOMEN EAST TMC XTRA EAST
Pay-Per-View Networks
CLUB JENNA PLAYBOY TV TENBLOX
FRESH PLZ TENBLUE
HUSTLER TV US SHORTEEZ TENCLIPS
IN DEMAND 01 SPICE XCESS TENMAX
PLAYBOY EN ESPANOL SPICE2 TENXTSY
PLAYBOY HD TEN THE EROTIC NET
Source: TMS, Author decisions.
57
Table 29: TMS and Estimation Categories, Page 1
TMS Estimation TMS Estimation TMS Estimation
Category Category Category Category Category Category
AHL Hockey Sports Baile Spanish Coll Wrestle Sports
ATP Tennis Sports Ballet ArtsSci Collectibles Hobbies
Accin Spanish Base Sports Com. dramatique French
Action ActionAdv Basket Sports Comedia Spanish
Actividades Spanish Beach Volleyball Sports Comedia Musical Spanish
Activits French Beaux-arts French Comedia Romntica Spanish
Adult Adult Bicycle Sports Comedia-Drama Spanish
Adulto Adult Bicycle Racing Sports Comedy Comedy
Adventure ActionAdv Billiards GameShow Comedy-Drama Comedy
Afiaires French Biografa Spanish Community Community
Afiaires publiques French Biographie French Compras Spanish
Agricultura Spanish Biography Educational Computadoras Spanish
Agriculture Outdoor Blackjack GameShow Computers Hobbies
Amat Box Other Boat Outdoor Comunidad Spanish
Animales French Boat Racing Sports Comdie French
Animals Educational Bodybuild Sports Concursos Spanish
Animated Cartoon Bowl Sports Consumer Shopping
Animaux French Box Sports Consumidor Spanish
Anime Cartoon Bullflghting Sports Cooking HomeGarden
Anthol Anthol Business Business Cricket Sports
Antologa Spanish CFL Foot Sports Crime ActionAdv
Archery Sports Card games GameShow Crime Drama ActionAdv
Arena Foot Sports Casa&Jardinera Spanish Crimen Spanish
Art ArtsSci Cheer Other Cuisine HomeGarden
Arte French Children’s Children Culinria Spanish
Artes Escnicas Spanish Christmas Other Dance ArtsSci
Arts & Crafts HomeGarden Ciencia Spanish Darts Sports
Assunto Pblico Spanish Ciencia Ficcin Spanish Debate French
Asuntos Pblicos Spanish Clima Spanish Deportes Acuticos Spanish
Auction Shopping Cocina Spanish Dibujos Animados Spanish
Aussie Foot Sports Coleccin Spanish Dive Other
Auto Sports Coll Base Sports Divertissement French
Auto Ayuda Spanish Coll Basket Sports Docudrama Educational
Auto Racing Sports Coll Foot Sports Documentaire French
Aventura French Coll Golf Sports Documental Spanish
Aviation Hobbies Coll Hockey Sports Documentary Documentary
Award GameShow Coll Soccer Sports Documentrio Spanish
Badminton Sports Coll Volley Sports Dog Racing Sports
Source: TMS, Author decisions.
58
Table 30: TMS and Estimation Categories, Page 2
TMS Estimation TMS Estimation TMS Estimation
Category Category Category Category Category Category
Drag Other Gym Sports Motorsports Sports
Drama Drama HS Base Sports Mountain Biking Sports
Drama Documental Spanish HS Basket Sports Music Music
Drama Histrico Spanish HS Foot Sports Musical Movie
Drama de Crimen Spanish HS Hockey Sports Musical Comedy Comedy
Drame French Halloween Other Musique French
Drame Historique French Health Health Mystery Drama
Drame policier French Histoire French Mdico Spanish
Drame sentimental French Historia Spanish Msica Spanish
ECHL Hockey Sports Historical Drama Educational NBA Basket Sports
Educacional Spanish History Educational NFL Euro Sports
Educational Educational Hockey Sports NFL Foot Sports
Ejercicio Spanish Home Improvement HomeGarden NHL Hockey Sports
Entertainment Entertainment Horror Violent NLL Lacrosse Sports
Entretien French Horse Sports Naturaleza Spanish
Entrevista Spanish House&Garden HomeGarden Nature Educational
Environment Educational How-to HomeGarden Negocios Spanish
Equestrian Sports Hunt Outdoor New Year’s Other
Espectculo Spanish Infantil French News News
Espetculo Spanish Information PublicAfiairs Newsmagazine News
Event Other Int Soccer Sports Noticias Spanish
Evento Spanish Interview News Nouvelles French
Exercise Sports Juridique French OHL Hockey Sports
Extreme Violent LPGA Golf Sports Olympic Sports
Fantastique French Lacrosse Sports Opera ArtsSci
Fantasy Fantasy Latina Spanish Outdoor Outdoor
Fantasa Spanish Law PublicAfiairs PBA Bowl Sports
Fashion Entertainment Ley Other PGA Golf Sports
Field Hockey Sports MLS Soccer Sports Parade Other
Fig Skate Sports Major Base Sports Paranormal Drama
Film musical Entertainment Martial Sports Parenting Educational
Fish Outdoor Medical Health Paternidad Spanish
Foot Sports Medicina Spanish Performing Arts ArtsSci
Fundraiser Other Medio Ambiente Spanish Poker GameShow
Game Show GameShow Minor Base Music Policier French
Gay&Lesbian Other Misterio Spanish Politics PublicAfiairs
Golf Sports Moda Spanish Politique French
Gospel Religious Motorcycle Sports Polo Sports
Guerra Spanish Motorcycle Racing Sports Poltica Spanish
Source: TMS, Author decisions.
59
Table 31: TMS and Estimation Categories, Page 3
TMS Estimation TMS Estimation
Category Category Category Category
Premio Spanish Sports Related Sports
Prix French Sports Talk Sports
Pro Wrestle Violent Squash Sports
Public Afiair PublicAfiairs Standup Comedy
Pquer Spanish Sumo Wrestle Sports
Racquet Sports Surf Sports
Real Estate Business Suspense Drama
Realidad Spanish Suspenso Spanish
Reality Reality Swim Sports
Religioso Spanish Table Tennis Sports
Religious Religious Teatro Spanish
Remodelacin Spanish Tennis Sports
Revista Noticiosa Spanish Terror Violent
Rodeo Sports Thanksgiving Other
Romance Drama Theater ArtsSci
Romance-Comedy Comedy Track Sports
Rowing Sports Travel Outdoor
Rugby Sports Triathlon Sports
Running Sports Valentine’s Day Other
Rnovation&Jardin Spanish Variedad Spanish
Sailing Sports Variedades Spanish
Salud French Variety Drama
Science ArtsSci Varits Spanish
Science Fiction Drama Viaje Spanish
Science-flction Drama Volley Sports
Self-Improvement Other Voyage French
Shooting Sports WTA Tennis Sports
Shopping Shopping War History
Sit. Cmica Spanish Water Polo Sports
Sitcom Sitcom Water Ski Sports
Skateboarding Sports Watersports Sports
Ski Sports Weather Weather
Snowboard Sports Weight Sports
Snowmobile Sports Western Drama
Sobrenatural Spanish Wm. Coll. Basket Sports
Soccer Sports Wrestle Sports
Softball Sports Yacht Sports
Speed Sports ducatif Spanish
Sport Sports
hline
Source: TMS, Author decisions.
60
Figure 1: Television Programming Industry
61
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