FCC Media Ownership Study #5: 
Station Ownership and Programming in Radio 
 
 
 
 
By Tasneem Chipty 
CRA International, Inc. 
 
 
 
 
June 24, 2007 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
* CRA International, Inc., 200 Clarendon Street, T-33, Boston, MA 02116.  I would like 
to thank Rashmi Melgiri, Matt List, and Caterina Nelson for helpful discussions and 
valuable assistance.  The opinions expressed here are my own and do not necessarily 
reflect those of CRA International, Inc., or any of its other employees. 
   1
Station Ownership and Programming in Radio 
 by Tasneem Chipty, CRA International, June, 2007 
 
I. Introduction 
Out of concern that common ownership of media may stifle diversity of voices 
and viewpoints, the Federal Communications Commission (FCC) has historically 
placed limits on the degree of common ownership of local radio stations, as well as on 
cross-ownership among radio stations, television stations, and newspapers serving the 
same local area.   The 1996 Telecommunications Act loosened local radio station 
ownership restrictions, to different degrees across markets of different sizes, and it lifted 
all limits on radio station ownership at the national level.  Subsequent FCC rule changes 
permitted common ownership of television and radio stations in the same market and also 
permitted a certain degree of cross-ownership between radio stations and newspapers.   
These changes have resulted in a wave of radio station mergers as well as a 
number of cross-media acquisitions, shifting control over programming content to fewer 
hands.  For example, the number of radio stations owned or operated by Clear Channel 
Communications increased from about 196 stations in 1997 to 1,183 stations in 2005; the 
number of stations owned or operated by CBS (formerly known as Infinity) increased 
from 160 in 1997 to 178 in 2005; and the number of stations owned or operated by ABC 
increased from 29 in 1997 to 71 in 2005.  Over this same period, Cumulus Broadcasting 
has become the second largest radio station owner in the country, with 297 commercial 
radio stations in 2005. 
In the face of this consolidation, there has been a great deal of debate and concern 
over the effects of ownership structure on the availability of programming content.  
Critics of consolidation worry, for example, that consolidation is associated with fewer 
niche programming formats, too much voice-tracked (and not enough live) programming, 
and too little local content.  Questions of whether and how common ownership affects 
radio station programming and listenership are the subject of on-going FCC review of the 
ownership rules.  Economic theory suggests that common ownership can have both 
anti-competitive and pro-competitive effects.  On the one hand, consolidation in 
ownership may lead to the classic monopoly-like results of quality deterioration and 
   2
output reduction, with less desirable programming, reduced listening, and higher 
advertising prices.  On the other hand, consolidation may allow firms to exploit 
economies of scale and scope in programming specific genres, attracting and promoting 
talent, obtaining desirable non-music programming, and selling advertising.  
Consolidation may also allow firms to internalize the benefits of offering a wider array of 
station formats, including some niche formats, without fear of losing listeners to 
mainstream formats.  These pro-competitive benefits of consolidation may result in 
quality enhancements and greater listening.  Ultimately, whether and how common 
ownership affects radio station programming and listenership are empirical questions, 
and the answers depend on the relative importance of the different effects, including the 
degree to which terrestrial radio faces competition from other media  such as audio 
programming on cable and satellite television, satellite radio, and internet radio. 
The existing literature, which is described in more detail below, has focused on 
the effects of consolidation on the availability of program formats, including overlap in 
actual song lists across various music formats.  While there is some mixed evidence, the 
general consensus  at least from the academic literature  appears to be that 
consolidation is associated with more program formats and that there is substantial 
overlap in the actual song lists across different formats of music.  As far as I am aware, 
there is little systematic evidence on the effects of consolidation on non-music 
programming or many of the other dimensions of programming, such as live versus taped 
programming or local versus network/syndicated programming.  In addition, much of 
literature has focused on the effects of local ownership of radio and has not addressed the 
impact of national ownership or local cross-ownership across different media.  
This paper empirically studies the effects of radio ownership structure on content 
diversity, using a rich, cross-sectional dataset reflecting information from the third 
quarter of 2005.  These data include format information for each of the stations in the 
United States as well as more detailed content information from a new airplay database 
commissioned by the FCC (referred to as the Edison Database).  The Edison Database 
provides a unique opportunity to study the effects of ownership structure on non-music 
content, particularly news and sports programming.  It also provides an opportunity to 
study station programming decisions, such as percentage of time devoted to advertising, 
   3
talk entertainment, sports, and news.  Using these data, I assess the effects of ownership 
structure on various measures of program content for commercial, in-market stations, 
which are described in more detail below.  I also study the effects of ownership structure 
on advertising prices and listenership using data from SQAD and Arbitron.  Where 
possible, this analysis is conducted at the Arbitron market level, the station level, as well 
as at the station-pair level.  In addition, where possible, the analysis is conducted 
separately for FM only stations and for big and small markets.  
Some of the main findings, which are discussed in the remainder of this report, 
are summarized as follows.  Consolidation of radio ownership does not diminish the 
diversity of local format offerings.  If anything, the market level analysis suggests that 
more concentrated markets have less pile-up of stations on individual format categories, 
and large national radio owners offer more formats and less pile-up.  Consolidation of 
local radio ownership has a statistically significant and economically meaningful effect 
on the composition of non-music programming content.  In particular, owners with 
several local stations offer longer, uninterrupted blocks of sports programming in the 
evening.  This shift towards sports programming is accompanied by reductions in other 
types of programming.  The analysis also suggests that common ownership results in 
more diversity in actual programs aired.  Based on an analysis of news and sports 
formatted stations, I find there is some overlap in actual programs aired across the two 
formats generally, but not within commonly owned station-pairs within the same market. 
Further, there are no significant differences in the effects of consolidation in radio on 
programming content, across big and small markets. 
I also find that consolidation in local radio has no statistically significant effect on 
advertising prices.  National radio ownership has a negative effect on prices and cross-
ownership with local television has a positive effect on advertising prices in big markets.   
I find that stations operating in markets with other commonly owned stations achieve 
higher ratings, than do independent stations.  In addition, cross-ownership with local 
newspapers has a statistically significant, positive effect on listenership.   
The remainder of this report is organized as follows.  The next section provides a 
description of terrestrial radio, including an overview of ownership structure and 
programming content.  Section III reviews relevant literature.  Section IV describes the 
   4
various data sources used in my analysis.  Section V provides some summary statistics of 
ownership structure, programming content, advertising prices, listenership, and 
demographics based upon my analysis database.  Section VI provides an overview of the 
empirical models.  Section VII presents evidence on the effects of ownership structure on 
diversity of formats.  Section VIII presents evidence on the effects of ownership structure 
on other measures of content.  Section IX presents evidence specifically for non-music 
programming on sports and news format stations.  Section X presents evidence on the 
effects of ownership structure on advertising prices.  Section XI presents evidence on the 
effects of ownership structure on listenership.  Section XII concludes. 
II. Description of Terrestrial Radio 
Radio station owners make programming decisions and provide audio content, 
including music, talk, news, sports, and advertisements, to listeners in their local markets.  
Radio stations make money by selling advertising time to companies seeking to reach 
specific demographic segments, and the rates they obtain for advertising time depends on 
their ability to attract listeners within the companies target demographic segment.  
Listeners, or consumers of broadcast radio, choose whether and to which radio stations to 
listen.   
The last decade has brought a number of significant technological advances in the 
provision of audio content, and many new services compete with terrestrial radio by 
offering potential listeners an increasing number of choices for audio entertainment.   
New media technologies and services include audio programming by digital audio 
satellite radio services, Music Choice on cable television, XM and Sirius satellite radio 
on the direct broadcast satellite services DirecTV and EchoStar, internet-based audio 
services,
1
 high-definition radio,
2
 and low-power FM radio,
3
 as well as MP3 players, such 
                                                 
1
 According to Tom Taylor, who edits Inside Radio, approximately one-third of radio stations now stream 
their broadcasts online.  (See Journalism.org, The State of the News Media 2007: An Annual Report on 
American Journalism, Radio, p. 7, available at 
http://stateofthemedia.org/2007/printable_radio_chapter.asp?media=1&cat=1 
2
 HD Radio can provide multi-channel, multi-format digital radio services in the same bandwidth currently 
occupied by traditional AM and FM radio services. 
3
 Low-power FM (LPFM) stations broadcast with a power of 100 watts or less (yielding a service range 
of approximately 5.5 miles), and LPFM  FM licenses are limited to nonprofit educational organizations and 
   5
as the popular iPods.  According to statistics from Arbitron, the percentage of Americans 
over the age of 12 who listen to radio each week fell from 95.3 percent in fall 1998 to 
92.8 percent in 2006, a drop of 2.5 percentage points.
4
  Thus, while terrestrial radio 
listening is falling, it is still a very effective medium for reaching the American audience.  
In 2006, the highest radio listenership was for women between the ages of 25 and 34 
(95.8 percent), and the lowest was for women over the age of 65 (85.4 percent).
5
   
  
In 2005, there were 13,514 radio stations in the United States, of which 10,833 
were classified as commercial radio stations.  Commercial radio stations rely on revenues 
from selling air-time to advertisers, as opposed to non-commercial radio stations, which 
obtain funding primarily from listeners.  Of the 10,833 commercial radio stations, 6,223 
are FM stations, and 4,610 are AM stations.  Of the 2,681 non-commercial radio stations, 
2,557 are FM stations
6
 and 124 are AM stations.   
Radio stations are typically described as being in-market or out-of-market 
stations, where the term market refers to Arbitron-defined radio markets.  Today, there 
are 298 Arbitron-defined radio markets in the United States, which largely align with the 
Office of Management and Budgets Metropolitan Statistical Area (MSA) definitions.  
Generally speaking, rural areas of the United States do not fall into MSAs (or radio 
markets), and 4,260 of the U.S. commercial radio stations did not have listeners residing 
in any Arbitron market in 2005.
7
  The remaining 6,573 U.S. commercial radio stations 
have listeners residing in at least one Arbitron market.  While a station may reach 
                                                                                                                                                 
state and local government entities.  As of March 2005, there were approximately 590 LPFM stations 
operating.  (See http://www.fcc.gov/mb/audio/lpfm/.)   
4
 Sources: 1998 datum from Journalism.org, The State of the News Media 2007: An Annual Report on 
American Journalism, Radio, p. 2, available at 
http://stateofthemedia.org/2007/printable_radio_chapter.asp?media=1&cat=1, and 2007 datum from 
Arbitron, Radio Today, 2007 Edition, p. 90, available at 
http://www.arbitron.com/downloads/radiotoday07.pdf.   
5
 Source: Arbitron, Radio Today, 2007 Edition, p. 90, available at 
http://www.arbitron.com/downloads/radiotoday07.pdf. 
6
 This total does not include LPFM stations. 
7
 Of the 2,681 non-commercial U.S. radio stations, 1,000 stations were not part of an Arbitron-defined 
market. 
   6
listeners residing in more than one Arbitron market, the majority of these stations reach 
listeners in a single home market.
8
   
1. Ownership 
The 1996 Act substantially loosened local radio ownership restrictions and lifted 
all limits on national radio ownership.  Subsequent regulatory changes have modified the 
methods used by the FCC to define local station ownership caps,
 9
 permitted common 
ownership television and radio stations in the same market
10
 and also permitted some 
cross-ownership between radio stations and newspapers.
11
 
On the national level, ownership of radio stations has become substantially more 
concentrated over the nine years from 1996 to 2005.  For example, in 1997, Capstar 
Broadcasting Partners
12
 was the largest owner of radio stations nationally (in terms of 
station counts), owning a total of 299 stations, and collectively, the top 10 owners owned 
                                                 
8
 Fewer than 300 stations have listeners residing in multiple markets. 
9
 Currently, a party may own, operate, or control up to: (1) 8 commercial radio stations, not more than 5 of 
which are in the same service (AM or FM), in a radio market with 45 or more radio stations; (2) 7 
commercial radio stations, not more than 4 of which are in the same service, in a radio market with between 
30 and 44 radio stations; (3) 6 commercial radio stations, not more than 4 of which are in the same service, 
in a radio market with between 15 and 29 radio stations; and (4) 5 commercial radio stations, not more than 
3 of which are in the same service, in a radio market with 14 or fewer radio stations.  In addition, a party 
may not own, operate, or control more than 50 percent of the stations in any local radio market.  Markets 
are now being defined on the basis of Arbitrons definition, rather than by using the FCCs prior signal-
contour method.  Because Arbitrons market definition was more restrictive than the signal-contour market, 
some ownership positions were no longer within the FCCs rules.  In these cases, owners have been 
allowed to maintain their historical ownership positions, but their ability to sell their holdings is restricted. 
10
 In larger markets, a single entity may own additional radio stations depending on the number of other 
independently-owned media outlets in the market. 
11
 The current rule prohibits common ownership of a full-service broadcast station (television or radio) and 
a daily newspaper if the stations service area completely encompasses the newspapers city of publication. 
In June 2003, the Commission relaxed this rule and the separate radio/television cross-ownership restriction 
by replacing both regulations with a set of cross-media limits.   The new limits were tiered according to 
the size of the local market: (a) in those with three or fewer TV stations, all newspaper/broadcast and 
radio/television combinations were prohibited; (b) in markets with between four and eight stations, an 
entity could own a combination that includes a newspaper and either (i) one television station and up to 50 
percent of the radio stations that may be commonly owned under the applicable radio cap, or (ii) up to 100 
percent of the radio stations allowed under the applicable radio cap; and (c) in markets with nine or more 
television stations, cross-media combinations would be permitted without limit as long as they complied 
with the applicable local television and local radio caps.  These rules have not been implemented due to a 
judicial stay ordered by the Court of Appeals for the Third Circuit in June 2004.  (See United States Court 
of Appeals for the Third Circuit, Prometheus Radio Project vs. Federal Communications Commission; 
United States of America, June 24, 2004.) 
12
 Capstar Broadcasting Partners is now part of Clear Channel Communications. 
   7
a total of 1,128 radio stations.  (See Table 1.)  In 2005, Clear Channel Communications 
was (and still is) the largest national owner, owning 1,183 stations  821 FM radio 
stations and 362 AM radio stations   and operating in a total of 207 Arbitron markets.  
Cumulus Broadcasting, Inc. was the second largest owner of radio stations, with 297 
stations (217 FM and 80 AM stations), operating in 61 markets.  Collectively, the top ten 
owners owned a total of 2,400 radio stations or over 22 percent of all U.S. commercial 
radio stations.  (See Table 2.)  The top five owners based on all commercial stations are 
also the top five owners based on commercial FM stations. 
2. Programming Content 
Radio programming can be described in a number of different ways.  One 
widely-used approach is based on the stations reported format.  For example, BIAfn 
surveys radio station owners and asks them to identify their primary, secondary, and 
tertiary radio formats, recognizing that stations may vary their format based on time of 
day or day of week.
13
  BIAfn identifies 101 specific radio formats, which are fairly 
narrowly defined,
14
 and groups these 101 specific formats into 20 general groups.
15
  The 
20 general groups are titled Adult Contemporary, Album-Oriented Rock/Classic Rock, 
Classical, Contemporary Hit Radio/Top 40, Country, Easy Listening/Beautiful Music, 
Ethnic, Jazz/New Age, Middle of the Road, Miscellaneous, News, Nostalgia/Big Band, 
Oldies, Public/Educational, Religion, Rock, Spanish, Sports, Talk, and Urban.
16
  (See 
Table 3 for a 2005 breakdown of formats for commercial stations, by band and by 
format.)  Based on a review of detailed music airplay logs for 1,095 contemporary music 
                                                 
13
 In other words, a station might be classified as talk radio during the morning commute, but play 
beautiful music during the afternoon commute.   
14
 For example, 70s & 80s, 70s Hits, 70s Oldies, and 80s Hits are all considered to be different formats. 
15
 According to a BIA Financial Network Study, While acknowledging that there are differences between 
the programming of similarly classified stations, BIAfn tries to provide some framework for analysis by 
characterizing the many different programming formats.  (See Over-The-Air Radio Service to Diverse 
Audiences, BIA Financial Network, October 23, 2006, p. 4, available at 
http://www.nab.org/xert/corpcomm/pressrel/102306_Local_Diversity_Report.pdf.)  This report left out a 
few BIA-reported format groups, such as public/educational, no reported format, and dark. (See Exhibit B 
to Reply Comments by Clear Channel Communications, Inc., 2006 Quadrennial Regulatory Review, FCC 
MB Docket No. 06-121, January 16, 2007.) 
16
 For example, 70s & 80s, 70s Hits, 70s Oldies, and 80s Hits, along with 80s & 90s, Adult Hits, Beach, 
Dance Oldies, and Oldies are grouped together in the grouping Oldies. 
   8
stations, Andrew Sweeting further consolidates the BIAfn categories into eleven broader 
categories due to substantial overlaps in playlists across a number of BIAfn format 
categories.
17
  My analysis of the effects of ownership structure on the availability of 
formats considers three different levels of format categorization, which I refer to as 
Format 101, Format 20, and Format 11.  (See Appendix 1 for a description of the 
individual format categories, under these different classification schemes.) 
Other approaches to describing radio programming may be based on stations 
actual airplay.  For example, one could measure the percentage of a stations airtime 
devoted to program categories such as music, news, sports, or talk.  One could also 
measure the percentage of time spent on live versus taped programming, and percentage 
of time spent on local, versus syndicated or network programming or voice tracked.  
Syndicated programming refers to rented programming, whereby the radio station 
purchases the rights to broadcast programming created by someone else.  The 
syndicator or distributor typically attempts to sell its show to at least one station in each 
media market, in order to increase circulation.  Voice tracking refers to pre-recording 
of disc jockey talk that can then be combined with songs, advertisements, and other 
programming to create an appearance of live programming.  Finally, as with music, one 
could study overlap across formats and across stations within formats, in programs or 
personalities that comprise the non-music programming.  My analysis of the effects of 
ownership structure on programming evaluates each of these alternative measures. 
III. Relevant Literature 
Economists have been thinking (and writing) about the effects of competition and 
ownership concentration on program diversity in radio for more than half a century.  In 
his seminal paper, Steiner (1952) develops a stylized model of spatial competition that 
shows that two stations owned by different owners would tend to be programmed more 
                                                 
17
 Sweeting includes Album-Oriented Rock/Classic Rock and Rock in the category Rock, groups 
News/Sports and Talk into News/Talk, groups Classical, Jazz/New Age, Easy Listening, Middle of the 
Road, Nostalgia/Big Band, Miscellaneous, and Ethnic into Other Music, and retains the BIAfn groups 
Adult Contemporary, Contemporary Hit Radio/Top 40, Country, Oldies, Religion, Spanish, and Urban.    
(See Sweeting, Andrew, The Costs of Product Repositioning: The Case of Format Switching in the 
Commercial Radio Industry, Northwestern University Working Paper, November 2006, pp. 6-7 and Table 
1.)  At points in his paper, Sweeting groups Adult Contemporary, Contemporary Hit Radio/Top 40, 
Country, Oldies, Rock, and Urban into a new category called Contemporary Music.  (See ibid., p. 7.) 
   9
similarly than two stations owned by the same owner.  In his most simplistic two-station 
model, Steiner looks at two stations that choose formats in succession.  The first station 
will choose the most popular format, thus obtaining the largest possible audience 
(denoted L
1
).  When the second station chooses its format, it compares the number of 
listeners it would get if it also offered that format (namely L
1/2
) to the number of listeners 
in the next most popular format (L
2
), and will choose to duplicate the first stations 
format if L
1/2
 exceeds L
2
.  On the other hand, if the stations are commonly owned, the 
first station will offer the most popular format and the second station will offer the next-
most popular format, thus achieving total listenership of L
1
 plus L
2.
  In theory, however, 
consolidation of ownership in spatial models can result in minimal or maximal 
differentiation (and anything in between), depending on the assumptions underlying the 
model.
18
  Ultimately, whether and how ownership structure affects program diversity is 
an empirical question. 
Indeed, there has been a growing empirical literature studying the effects of 
ownership structure on program variety in terrestrial radio.  These studies include Rogers 
and Woodbury (1996); Berry and Waldfogel (2001); William, Brown, and Alexander 
(2002); Romeo and Dick (2005); William and Brown (2005); and Sweeting (2006).  The 
common themes are that consolidation in ownership is associated (at least weakly) with 
greater number of formats and greater listening, although there are some mixed results 
regarding the similarity (or diversity) of song playlists on music stations.  I describe each 
of the studies in turn. 
Using data from Spring 1987, Rogers and Woodbury (1996) examine the 
relationships among the number of advertiser-supported radio stations, the number of 
programming formats offered by those stations, and radio listenership.  The authors find 
that increasing the number of stations increases the number of programming formats 
offered, although a 10 percent increase in the number of stations leads to less-than a 2 
percent increase in the number of formats, and that a 10 percent increase in the number of 
formats leads, on average, to a 2.25 percent increase in radio listenership.  Based on these 
results, the authors find that doubling the number of stations would lead to a 4.24 percent 
                                                 
18
 For example, Beebe (1977) shows that Steiners conclusion that common ownership leads to increased 
program diversity depends on his assumption that potential listeners will listen only to one program (and 
choose not to listen if that program is not offered).    
   10
increase in radio listenership.  The authors also investigate the relationship between the 
number of stations within a format and radio listenership and reject the hypothesis that 
listenership is evenly spread amongst stations within a given format.  
Using data from 1993 and 1997, Berry and Waldfogel (2001) assess the impact of 
mergers among radio stations on program variety, using program formats as a measure of 
variety.  They find that concentration (measured by the reduction in the number of 
owners per market) increases the number of formats relative to the number of stations 
operating in a market.  They also find some evidence for an increase in variety overall as 
a result of increasing concentration.  
Williams, Brown, and Alexander (2002) also assess the impact of consolidation of 
radio station ownership on diversity in broadcast radio, where diversity is measured by 
the songs played by radio stations.  For stations in top-tier markets, the authors obtained 
lists of the top songs played by stations covered by R&R Magazine.  Using this 
information, they created what they term a distance measure of diversity among stations, 
based on the top ten songs played by each station, and they conducted a pair-wise 
analysis of the effects of consolidation on their sample of 174 stations, between March 
1996 and March 2001.  The authors conclude that recent consolidation has played very 
little role in playlist diversity, although this might not be the case in smaller markets[.]
19
 
Romeo and Dick (2005) investigate the relationship between ownership and 
format changes by radio stations and station listenership in ten MSAs, ranging in size 
from New York to Kalamazoo, MI, over the period from 1988 to 1998.
20
  The authors 
find that major format changes made upon station acquisition were made for stations with 
ratings that were significantly below average, while minor format changes were made for 
stations with above-average ratings. They find that major format changes were associated 
with a 23 percent increase in listenership shares.  However, minor format changes were 
not associated with increasing listenership shares, although they were a useful tool for 
differentiating a station in a crowded format space.
21
  The authors find no additional 
                                                 
19
 Williams, Brown, and Alexander, p. 18. 
20
 The authors report 153 major format changes and 104 minor format changes in their data set of 924 
station-years.   
21
 Romeo and Dick, p. 24. 
   11
impact of changes in ownership on listener shares, although nearly half of major format 
changes were made close to the date of an ownership change.  The authors did find that 
being part of a large local radio group generates economies of scale in the listening 
performance of individual stations within the group and found evidence that having a 
large local presence improves a radio groups prospects for success when making format 
changes.
22
 
Williams and Brown (2005) use playlists obtained from the R&R Magazine, for 
March 1996 and March 2004, to address changes in diversity following the 1996 
Telecommunications Act.  Employing the same methodology used by Williams, Brown, 
and Alexander (2002), these authors find that when two stations in the same market went 
from separate to common ownership, the stations grew more different, while station-pairs 
in the same format that went from separate to common ownership grew more similar, and 
that this relationship continued to hold when the station-pairs were in the same market.  
They conclude that [commonly owned stations within the same format and market play 
more similar music than separately-owned stations within the same format and market, 
because common ownership within format generates greater play list similarity.
23
  
Using a panel dataset from 1998 to 2001, Sweeting (2006) investigates the impact 
of common ownership (both of stations in the same local market and stations in different 
local markets) on programming and listenership for 1,095 contemporary music radio 
stations, using a dataset created from station airplay logs.  He finds that 
commonly-owned station-pairs in the same local market and format category are more 
highly differentiated than their separately-owned station-pairs counterparts, with the 
percentage of songs played by one station but not the other increasing from 55 percent 
when the stations are not commonly owned to 67 percent when the stations are under 
common ownership. 
To my knowledge, none of the previous studies examines programming content in 
conjunction with listenership and advertising prices. By contrast, this study examines the 
effect of ownership structure on all three - programming, listenership, and advertising 
prices.   In addition, none of the previous studies has examined programming content 
                                                 
22
 Romeo and Dick, pp. 17-18. 
23
 Williams and Brown, p. 19. 
   12
beyond formats and music playlists.  In addition to a more conventional analysis of 
formats, the data I use permit me to study the effects of ownership structure on numerous 
other measures of programming, including variety in non-music programming, the choice 
between live and taped programming, and the choice between local and 
network/syndicated programming.  Finally, the previous studies focus on the effects of 
local radio ownership on program offerings.  In addition to local radio ownership, I 
examine the effects of national radio ownership as well as the effects of cross-ownership 
between radio and local newspapers and local television. 
IV. Data 
This study relies on data from a number of different sources, including the Edison 
Database, station characteristic and demographic data from BIA Financial Network 
(BIAfn), ratings data from Arbitron, advertising cost data from SQAD, and additional 
demographic data from the U.S. Census Bureau.  I next describe each of these data 
sources in turn. 
1.  Edison Database 
In the summer of 2005, the FCC commissioned Edison Media Research to collect 
information on radio station programming.  Edison researchers collected detailed airplay 
content information for a random sample of 1,014 U.S. radio stations, including 790 
commercial stations and 222 non-commercial stations.  For each station, Edison 
researchers recorded what was broadcast during each of six 20-minute periods in a given 
day, primarily in the summer of 2005.
24
  For each such period, they recorded the 
broadcast content in 5-second increments and categorized the content along several 
dimensions, including the content type (e.g., Music, Commercials, Sports), the broadcast 
mode (local, network-syndicated, or voice-tracked), and the live type (live or taped).
25
   
I restructure these data into what I call content segments, which are consecutive 
observations that differ only by the 5-second period in which they were captured.  For 
                                                 
24
 Eighty-two percent of stations were listened to between June 1, 2005 and August 31, 2005.  Twelve 
percent of stations were listened to between August 31, 2005 and December 31, 2005.  The remaining five 
percent were listened to at some point in 2006. 
25 
This dataset contains roughly 1.4 million observations (1,014 stations x 6 survey periods per station x 20 
minutes per survey period x 12 five-second increments per minute = 1,460,160 observations). 
   13
example, if Station ABCD played the Celine Dion song, My Heart Will Go On, 
beginning at 2:00 pm, the Edison database would display 72 identical observations (one 
for each 5 second-increment of the 5 minute, 30 second-long song).  I collapse these 72 
5-second observations down to a single content-segment observation with a Start Time 
of 2:00:00 pm and an End Time of 2:05:30 pm.  Similarly, the 6 identical observations 
comprising a 30-second commercial would collapse to one, 30-second content-segment. 
Using these data, I describe programming content in a number of different ways.
26
  
First, I calculate the percentage of airplay dedicated to each content type;
27
 the percentage 
of airplay by broadcast mode (local, network/syndicated, and other), and the percentage 
of airplay devoted to live programming.  In addition, I determine the average length of 
uninterrupted blocks of music and other content types, including commercial breaks.  
Because airplay on a given station can vary substantially within a day, I calculate all of 
these statistics by day part.    I assign the 20-minute survey periods occurring on 
weekdays (Monday through Friday) to one of 5 Arbitron-defined weekday day parts: (1) 
The AM Drive (6 AM-10 AM), (2) Daytime (10 AM-3 PM), (3) The PM Drive (3 PM-7 
PM), (4) Evening (7 PM-Midnight), and (5) Overnight (Midnight-6AM).  Twenty minute 
slots occurring between 12AM Saturday morning and 12AM Monday morning are 
grouped into a sixth day part called Weekend.
 28
  Survey periods that overlap two day 
parts are excluded from my day part-specific analysis.
29
  In addition, not all stations were 
surveyed during each of the six day parts.   
Finally, I identify the number of personalities hosted by a station as well as the 
actual sports and news programs on stations that are classified as having sports or news 
                                                 
26
 My analysis relies primarily on the Edison database, as audited by the FCC.  In some of my earlier 
analysis, I used both the audited and unaudited Edison data and found the results to be stable across the 
two.   
27
 Edison categorized content as falling into one of twelve mutually-exclusive types: (1) Advertising, (2) 
Announcements, (3) Dead air/Unknown, (4) Entertainment, Leisure or DJ Banter, (5) Fundraising & 
Charity, (6) Music, (7) News, (8) Other, (9) Public Affairs, (10) Religious (Non-Music), (11) Sports, and 
(12) Static/Interference.  
28 
My understanding that these are the most listened-to day parts is based on the fact that SQAD, the 
exclusive source reporting radio advertising prices paid, reports rates for only these four day parts. 
29
 There are two stations surveyed by Edison whose 20-minute survey segments overlapped different day 
parts. 
   14
formats, in order to study the effect of national and local consolidation on non-music 
programming in more detail.
30
  
2.  Station Characteristics 
The FCC provided me with a database on radio station ownership in the United 
States, which reflected ownership as of year-end 2005.
31
  My understanding is that the 
FCC database is a modified version of the BIAfn database for the same year.  For each of 
13,514 U.S. radio stations, the database lists the stations call letters, band (AM or FM), 
owner, commercial status (commercial or non-commercial), station age, format category, 
and radio market(s) served.
32
  Of the 13,514 stations, 262 have listeners residing in two 
Arbitron radio markets, 19 have listeners residing in three Arbitron markets, and 1 station 
has listeners residing in four Arbitron markets.
33
  As a result, the ownership database 
yields 13,818 station-market specific observations.  Merging these data to the Edison 
database of surveyed stations yields an analysis database of 1,037 station-market specific 
observations.
34
   
  In addition, I use the 2005 MEDIA Access Pro database from BIAfn, which 
includes information on all U.S. radio stations, to obtain information on station 
characteristics, such as its daytime and nighttime power levels as well as its age (years 
since it first began operating).  I also obtained listenership (or ratings) data from Arbitron 
for each commercial, in-market station in my sample.  Arbitron estimates each 
commercial stations share of listening by asking a sample of listeners in each of its 
                                                 
30
 In principle, the Edison Database also contains information on song titles and artists.  My study does not 
currently make use of this aspect of the database. 
31
 Because most stations were surveyed by Edison during mid-year 2005, the time frame captured by the 
Ownership database is roughly six months later than that captured by the content database.  I am only 
aware of one radio merger that could potentially result in a mismatch between the ownership and content 
information.  Cumulus Broadcasting announced its purchase of Susquehanna Radio at the end of October 
2005, and the acquisition became effective in May of 2006.  The ownership database for 2005 describes the 
formerly Susquehanna stations distinctly as Cumulus Media Partners, not Cumulus Broadcasting, Inc. 
Thus, these stations are appropriately treated as separate from the Cumulus radio group. 
32
 Many other data are also listed, including station class, station format (a sub-categorization of format 
category), licensee, and owner parent. 
33
 For example, a radio station physically located in Washington, DC, may have listeners residing in the 
Baltimore, MD Arbitron market. 
34
 There are exactly 25 of the stations surveyed by Edison that serve two Arbitron markets and are, 
accordingly, represented twice in the station-market counts. 
   15
markets to record what they listen to and for how long in a seven-day diary.
35
  Based on 
these diaries, Arbitron calculates an Average Quarter-Hour (AQH) Rating by 
demographic group for each day part.
36
  Because stations listeners may reside in more 
than one radio market (due to some overlap), a station may be rated in as many as four 
Arbitron-defined markets.  To date, I have only included ratings information for 
commercial stations that are part of an Arbitron-defined radio market.
37
  My listenership 
analysis is based on AQH ratings for Adults 18-years and older from the spring 2005.
38
   
3.  Owner Characteristics 
Based on information in the FCC ownership database, I have calculated the 
number of stations each radio-station owner owns by band, by commercial status, and by 
format category, both nationally and by market.  In addition, the FCC ownership database 
provides information on whether a local radio station owner owns a local newspaper and 
whether the owner owns a local television station.  These data are merged onto the 1,037 
observation analysis dataset for each of the 531 owners (of which 381 are owners of in-
market stations), by owner or by owner and market.   
4.  Market Characteristics 
Finally, I add market level data to the analysis database.  Market level data are 
primarily of three forms: (1) demographic information about the listener population, (2) 
market-average radio advertising rates, and (3) radio competition and listenership 
information. 
A.  Demographic Information 
I obtain market level demographic information for each of the Arbitron radio 
markets from the BIAfn MEDIA Access Pro database.  The demographics include 
                                                 
35
 See Arbitron Radio Report Reference Guide, p. 9.1. 
36
 According to Arbitron, AQH persons is the average number of persons estimated to have listened to a 
station for a minimum of five minutes during any quarter-hour in a time period (or day part).  The AQH 
Rating is calculated by dividing the number of AQH Persons by the survey area population within the 
same sex/age group. (See Arbitron Guide, p. 2.1.) 
37
 Arbitron does not provide ratings data for non-commercial stations, and it provides listener data (but not 
ratings) for stations outside of Arbitron markets. 
38
 I do not have station-specific ratings data for 152 of 569 commercial, in-market stations in my database. 
   16
market population, the market effective buying income (EBI) per capita, and a 
breakdown of population along race and age.
39
  Additionally, I obtain information on the 
breakdown of population by highest education level attained and the market average car-
commuting time
40
 for 2005 from the U.S. Census Bureau, which I merge on to my 
database by MSA. 
B. Advertising Prices 
SQAD (formerly known as Spot Quotations And Data, Inc.) publishes prices for 
radio spots (airtime).  For each radio market,
41
 SQAD reports the average cost per point 
(CPP) and cost per thousand (CPM) paid to advertise during a given day part, to 
reach an audience with given demographic characteristics on a quarterly basis.  I use the 
market-average CPP by day part for Adults 18-years and older for the spring 2005 quarter 
in my analysis.  The time period for the SQAD data (Spring 2005) corresponds to the 
time period of the Arbitron data (also Spring 2005), while the majority of radio stations in 
the Edison Database were sampled in the summer of 2005.   
C. Radio Competition and Listenership 
My analysis of the effects of consolidation focuses on in-market, commercial 
stations only.  To the extent that some out-of-market market stations compete with 
certain-in-market stations for listenership, my focus on in-market only stations will 
overstate concentration and understate the number of stations and owners offering radio 
programming to listeners in local markets.   
For each commercial, in-market station in the Edison sample, I summarize 
competition in the markets in which it is rated.  Based on the FCC ownership database, I 
calculate, for each radio market, the number of all radio stations by band, by commercial 
status, and by format category.  In addition, I calculate the number of owners of 
                                                 
39
 The population and EBI data are from 2005, whereas the population breakdown data are from 2006. 
40
 My base specification excludes average commuting time, because it is missing for most of the markets in 
the sample.  I have however, included the variable as an additional regressor in extensions of the base 
specification, the results of which suggest that commuting time is a statistically significant determinant of 
listenership and advertising prices.  However, inclusion (or exclusion) of the variable does not affect the 
coefficients on the ownership variables, which measure the effect of consolidation and cross ownership on 
various outcome measures. 
41
 SQAD has data for only 241 of the 251 markets in my analysis database. 
   17
commercial stations that have stations in the market and the number of stations owned 
nationwide by those owners, and I calculate ownership- and format-based Herfindahl-
Hirschman indices (HHI).
42
  Finally, I calculate the level of average radio listenership 
within a market as the average of the individual station-level AQH rating for adults 18-
years and older from station-specific Arbitron data. 
V. Descriptive statistics  
The Edison Database includes information for 569 commercial, in-market 
stations, across 251 (of the 298) Arbitron markets in the United States, excluding Alaska, 
Hawaii, and Puerto Rico.  Of these 569 stations, 255 were surveyed at least once during 
the AM drive and 281 were surveyed at least once in the evening.  To examine whether 
the effects of ownership structure vary by market size, I define markets with strictly 
fewer than 30 stations as small markets and those with 30 or more stations as big 
markets.
43
  By this definition, 104 of the 251 markets are big markets and the remaining 
147 are small markets.  Table 4 provides descriptive statistics at the market level, across 
all 251 Arbitron markets, and Table 5 shows the same descriptive statistics broken out for 
big and small markets.  Table 6 provides descriptive statistics at the station level.   
Overall, the median Arbitron market has 20 radio stations and 8 owners, offering 
a total of 11 of BIAs major 20 major format categories.
44
  The largest number of 
commercial stations in any given market is 88 (Chicago, IL), while the smallest is 4 
(Sussex, NJ).  The largest number of formats in any market is 37 (based on BIAs 101 
format categories) or 18 (based on the 20 major format categories).  By comparison, the 
minimum number of formats in any market is either 3 (Sussex, NJ and Ann Arbor, MI) or 
4 (Sussex, NJ), depending on format classification.  The median small Arbitron market 
                                                 
42
 The HHI is a widely used measure of concentration.  It is calculated as the sum of squared market shares.  
Depending on whether the shares are expressed as a fraction or a percentage, the HHI can range from 0 to 1 
or 0 to 10,000.  The bigger the HHI, the more concentrated the market.  For example, a monopoly market 
would have a single firm, with share of 100 percent and an associated HHI of 10,000. 
43
 This big/small distinction is appealing in that it is broadly consistent with how markets are grouped for 
determining ownership caps.  Indeed, pre-1996, markets with fewer than 30 stations were subject to the 
same caps.  There are, of course, other divisions (e.g. based on population) that are equally reasonable, at 
least for the purpose of examining differential effects across markets of different sizes.   
44
 The average number of FM stations is 14, the average number of station owners is 6 (who collectively 
own 1088 FM stations nationally), and the average number of formats based on BIA categories is 7.   
   18
has 16 commercial stations and 7 owners, offering 9 of the 20 major format categories, 
whereas the median big Arbitron market has 34 commercial stations and 14 owners, 
offering 13 of the 20 major format categories. 
1.  Radio Ownership and Cross Media-Ownership 
There are a total of 262 unique radio station owners across the 569 commercial, 
in-market stations, spanning a total of 251 Arbitron markets included in my analysis data 
base.  The number of commercial station owners in any given market ranges from 1 to 
36.
45
  The total number of stations owned nationally by all of the owners in any market 
ranges from 6 to 2,241 stations, and the median is 1,315.
46
  The percentage of stations 
cross-owned with local television stations ranges from zero to 39 percent, and the median 
is 4 percent.  Local television cross-ownership is somewhat greater in larger markets, 
relative to small markets.  (The median percentage of stations with cross-owned 
television stations in large markets is 7 percent, while the median percentage in small 
markets is zero.)  The percentage of stations cross-owned with local newspapers ranges 
from zero to 13 percent.  Local newspaper cross-ownership is somewhat greater in small 
markets, relative to larger markets.   
2.  Programming Content 
Table 7 shows the distribution of stations by format (for each of the 20 BIA major 
format categories) for all commercial stations.  As seen in this table, Country is the most 
common format for radio stations in the United States, both for in-market stations (12.1 
percent) as well as for out-of-market stations (29.9 percent). Adult Contemporary is the 
second most common format for both groups (11.4 percent for in-market stations and 
17.1 percent for out-of-market stations).  Religion is the third most common format for 
in-market stations (10.8 percent), followed by News (9.2 percent), Spanish (8.7 percent), 
                                                 
45
 The market with one owner is Sussex, NJ.  Under the current definitions used by the FCC, no single 
owner can own all commercial stations in a market; however, some owners have been allowed to maintain 
their historical ownership positions, because their acquisitions pre-dated the operational changes.  See 
Footnote 9 above. 
46
 The vast majority of stations are listened to by listeners in a single Arbitron market.  However, a handful 
of stations are listened to by listeners in up to 4 Arbitron markets.  In my station level analyses, presented 
below, stations that are listened to by listeners in multiple markets are double counted in the national 
ownership measure.  
   19
Rock (7.0 percent), Oldies (6.1 percent), and Album-Oriented Rock (5.7 percent).  On the 
other hand, for out-of-market stations, Oldies (9.8 percent) is the third most common 
format, followed by Religion (9.2 percent), News (9.5 percent), Album-Oriented Rock 
(4.4 percent), Rock (3.8 percent), and Nostalgia/Big Band (3.6 percent). 
Table 7 also shows the distribution of formats for stations in the Edison Database.  
This distribution of formats for in-market stations includes Country (13.9 percent), News 
(12.5 percent), Adult Contemporary (9.9 percent), Sports (7.6 percent), Spanish (7.4 
percent), Nostalgia/Big Band (7.0 percent), Rock (6.9 percent), and Oldies (6.5 percent).  
These data show that Edison commercial, in-market surveyed stations are more skewed 
towards news and sports formats, relative to the population as a whole. 
Table 4 summarizes other measures of programming content, for different day 
parts.  For example, during the morning commute  across all formats for both AM and 
FM bands in the Edison  surveyed stations, 23 percent of airtime is allocated to 
advertising, 23 percent to talk entertainment,
47
 31 percent to music, 9 percent to news, 
and 6 percent to sports.  In addition, 61 percent of content is local, while 30 percent is 
network/syndicated.  61 percent of content is live, while the remainder is taped.  The 
average length of a block of uninterrupted music during the morning commute is 2 
minutes, the average advertising block just over 1 minute, the average talk entertainment 
block close to 2 minutes, the average news block about 1 minute, and the average sports 
block 30 seconds. (See Table 4 for a similar breakdown for FM only stations and Table 5 
for a breakdown for big and small markets.) 
In the evening, 18 percent of radio station airtime is allocated to advertisements, 8 
percent to talk entertainment, 52 percent to music, 3 percent to news, and 12 percent to 
sports.  In the evening, 71 percent of content is local and 65 percent of content is live.  
The average length of a block of uninterrupted music during the evening is nearly just 
over 2 minutes and 30 seconds, the average advertising block about 1 minute, the average 
talk entertainment block close to 1 minute, the average news block 30 seconds, and the 
average sports block 1 minute. 
                                                 
47
 Throughout this paper, I use the term talk entertainment as a short-hand for the Edison category 
Entertainment, Leisure or DJ Banter. 
   20
3. Advertising Prices and Listenership  
Tables 8 and 9 provide descriptive statistics on advertising prices and listenership, 
at the market and station levels, respectively.  As expected, advertising prices and 
listenership in the morning drive (which is prime-time for terrestrial radio) are higher 
than in the evening.  In addition, median advertising prices as measured by CPP are 
higher in big markets, relative to small markets.  This pattern likely reflects that fact that 
in absolute terms, a percentage of the population in a big market is larger than a 
percentage of the population in small markets.  By contrast, the median advertising prices 
as measured by CPM are higher in small markets, relative to big markets.  Listenership, 
as measured by the share of the listening population that tuned in for an average quarter 
hour, is approximately equal across big and small markets.  
4. Demographics 
The median market population is 355,000, with populations ranging from 69,000 
to 18,230,000, and the median percentage of the population that is white is 81 percent, 
with the percentage white ranging from 46 percent to 98 percent.  College graduates 
represent 24 percent of the population of the median market, with their percentage 
ranging from 12 to 47 percent.  The median age distributions are 35 percent under 24, 13 
percent between 24 and 34, 14 percent between 35 and 44, 25 percent between 45 and 64, 
and 13 percent 65 and over.  The effective buying income per capita in the median 
market is $17,895, with market-average EBIs ranging from $9,926 to $34,326. In 
addition, smaller markets have lower effective buying income, relative to bigger markets.  
They also have a greater percentage white and a somewhat older population.  (See 
Table 8.) 
VI. Empirical Models 
I study the effects of ownership structure of terrestrial radio stations on various 
measures of programming content, listenership, and advertising prices, using both 
descriptive and regressive analyses.  The descriptive analyses focus primarily on 
differences in means across subgroups that are defined to reflect varying degrees of 
common ownership.  The regression analyses include a series of reduced form models 
   21
that capture the net effect of ownership structure on the outcome variables of interest.  
These analyses are presented separately for all commercial radio stations, for FM 
commercial stations only, and for big and small Arbitron markets. 
When possible, I evaluate the effects of ownership structure using three different 
levels of aggregation:  (1) market level analyses, which focus on Arbitron-defined market 
level outcomes; (2) station level analyses, which focus on station-specific outcomes; and 
(3) station-pair analyses, which focus on station-pair level outcomes both for station-pairs 
in the same market and for station-pairs across different markets.  Each of these 
approaches has its advantages and disadvantages, as I describe below, and consideration 
of all three provides a more complete understanding of the causal link between ownership 
structure on the various outcome measures. 
1. Market Level Analyses 
The market level analyses aggregate across stations in the same market.  The base 
specifications take the following form: 
iiii
iiiioi
RadioNationalTelevisionLocalNewspaperLocal
StationsStationsHHIStationsHHIOutcome
????
?????
++++
++++=
    
 x 
765
2
4321
(1) 
where Outcome
i
 is the outcome measure (such as number of formats, format 
concentration, or average listenership  for all stations in the market) for Arbitron market 
i; HHI is the ownership HHI, which measures the concentration of ownership across all 
commercial stations in market i; STATIONS is the number of commercial radio stations in 
market i, and STATIONS 
2
 is the number of commercial stations in the market squared;
48
 
HHI x Stations is an interaction term that allows the effect of concentration to vary in 
different sized markets; Local Newspaper measures the fraction of commercial stations in 
the market that are commonly owned with a local newspaper; Local Television measures 
the fraction of commercial stations in the market that are commonly owned with a local 
television station; National Radio is are the total number of in-market commercial radio 
                                                 
48
 Specification testing supports the inclusion of the STATION squared term, suggesting that the 
relationship between market-wide station outcomes and the number of commercial stations in the market is 
nonlinear. 
   22
stations owned nationally by the radio station owners in market i; the ?s are the 
associated parameters; and ?
i
 is the additive stochastic error term.   
The parameters are estimated using the method of Ordinary Least Squares 
(OLS).  For some models where the outcome variable is binary (e.g. an indicator 
variable that equals 1 if two stations are the same format, zero otherwise), the parameter 
are estimated using Maximum Likelihood (Probit).  Let ?

 denote the estimated 
parameter values.  The estimated model can then be used to determine the marginal effect 
associated with increased concentration in ownership (as measured by the ownership 
HHI).  In the base model, the marginal effect is calculated as:  Stations
31

?? + (evaluated 
at the average number of Stations in the sample), and the standard error of the marginal 
effect is calculated using the Delta Method, a widely-used technique in the field of 
econometrics that accounts for combinations of estimated parameters (
1

? and
3

? , in this 
case).  
The base specification likely omits other relevant variables that may also be 
determinants of station outcomes.  These variables include listener demographics and 
advertiser characteristics (referred to collectively as demographics).  Accordingly, I 
extend my base specification to include: total population, effective buying income per 
capita; a set of region indicator variables;
49
 the number of retail establishments; the 
percentage of the population that is white (to measure racial diversity); the percentage of 
the population between ages 25 to 34, between ages 35 to 44, between ages 45 to 64, and 
over 65 (to measure age diversity); and the percentage of the population that has 
graduated from college, all variables that have been found to be important predictors of 
station outcomes in the previous literature.
50
  Effective buying income and the number of 
retail establishments are expected to affect equilibrium station level outcomes through the 
                                                 
49
 The region variables include MIDWEST, SOUTH, and WEST, and NORTHEAST is the 
excluded indicator variable. 
50
 For a subset of the markets, I also have information on the percent of the population that commutes to 
work, a measure that is thought to be predictive of terrestrial radio listening.  Accordingly, I have evaluated 
an alternative specification that also includes this measure.  My results are consistent with the expectation 
that the presence of commuters raises the demand for radio programming, overall listening, as well as 
advertising prices.  However, inclusion of this variable does not affect the general pattern of results 
associated with the ownership variables.  Accordingly, because the measure is not available for a 
substantial number of the analysis sample, I exclude the variable in the specifications presented here. 
   23
demand for advertising, while the remaining variables may affect equilibrium station 
level outcomes through the demand for listening and tastes for certain types of 
programming.  This extended specification is written as follows: 
iii
iiiiioi
ucsDemographiRadioNationalTelevisionLocal
NewspaperLocalStationsStationsHHIStationsHHIOutcome
++++
+++++=
876
5
2
4321
  
   x 
???
??????
 (2) 
Finally, I consider the possibility that certain markets are likely to be more 
concentrated than others, and that ownership concentration may itself be an outcome 
that is influenced by a combination of observable and unobservable market 
characteristics.  Under such circumstances, the explanatory variable included in the 
regression model (ownership HHI, in this case) would be correlated with the error term 
(?
i
 or u
i
).  It is a well-known result in econometrics that inclusion of such explanatory 
variable can bias OLS estimates of the underlying parameters, rendering the estimates 
uninterpretable.  One way to resolve this correlation problem, in theory, is to use 
instrumental variables estimation, which requires a valid instrumental variable  
something that is correlated with ownership concentration, but does not itself belong in 
the specification of the outcome regression model.  As a practical matter, it is often 
difficult to find appropriate instrumental variables, though there are categories of valid 
variables, such as lagged endogenous variables that one might try.   I have estimated 
the market level models using lagged ownership variables from 2002 (using ownership 
data from BIAfn from 2002).  The results from the instrumental variables estimation 
(which are not reported here) are very similar to those from the OLS estimation.  
Accordingly, OLS is the primary estimation method employed in this paper. 
2. Station Level Analyses 
The station level analyses are less aggregated than the market level analyses and 
exploit the station-level variation in the Edison Database. The specifications take the 
following form: 
ijiij
jkijk
ijk
ijk
ijkoijk
sticsCharacteriStationsticsCharacteriMarktet
csDemographiRadioNationalTelevisionLocal
NewspaperLocalSistersSistersOutcome
???
???
????
+++
+++
+++=
  
  
  
87
654
3
2
21
 (3) 
   24
where i indexes the station, j indexes the market, and k indexes the owner.  Outcome
ijk
 is 
the station-specific outcome measure (such as programming content or listenership); 
Sisters
ijk
 is number of commonly owned local stations in the same market as station i; 
Sisters
2
ijk
 is Sisters
ijk
 squared;
51
 Local Newspaper
ijk
 is an indicator variable that equals 1 
if the station owner also owns a local newspaper; Local Television
ijk
 is an indicator 
variable that equals 1 if the station owner also owns a local television station; National 
Radio
k
 is a count of the total number of commercial radio stations owned nationally by 
the owner of the local radio station; Demographics
j
 include the same set of listener 
demographics and advertiser characteristics described above; Market Characteristics
j
 
include owner HHI, the number of stations in the market, and an interaction term between 
HHI and stations in the market; Station Characteristics
i
 include an indicator variable that 
equals 1 if the station is an FM station, the stations nighttime power, its daytime power, 
and station age; ?s are the associated parameters; and ?
ijk
 is the additive stochastic error 
term.   
As before, let?

 denote the estimated parameter values from OLS.  The estimated 
model can then be used to determine the marginal effect associated with greater 
ownership.  In the base model, the marginal effect of local radio ownership is calculated 
as: Sisters
21

?? + , evaluated at the average number of sister stations in the sample, and 
the standard error of the marginal effect is calculated using the Delta Method. 
When possible, I replace the market level demographics and other market 
characteristics with market fixed effects.  I also replace the national owner variable with 
owner fixed effects.  These fixed-effects specifications are superior to the extent they 
capture other relevant variables about market-specific and owner-specific characteristics 
that may be omitted from the specification described above.  For example, an owner-
specific characteristic that may be relevant is whether the station-owner is vertically 
integrated into network programming, information which is not reflected in my 
specification.  In addition, the results, as I describe below, provide estimates separately 
for all stations and for FM only stations.  
                                                 
51
 Specification testing supports the inclusion of this squared term, suggesting that the relationship between 
station outcomes and local radio ownership is nonlinear. 
   25
3. Station-Pair Level Analyses 
The station-pair level analysis provides a closer look at the similarities and 
differences in programming content by ownership structure.  For this analysis, I 
characterize the multi-faceted programming decisions of stations in three different ways.  
First, I characterize each station with a vector that measures percentage of airplay time on 
different types of programming: percentage advertising, percentage announcement, 
percentage talk entertainment, percentage fundraising/charity, percentage music, 
percentage news, percentage public affairs, percentage religious, and percentage sports.
52
  
Second, I characterize each station with a vector that measures percentage of airplay time 
by program origination:  percentage local, percentage network/syndicated, and 
percentage voice tracked.  Third, I characterize each station with a vector that measures 
percentage of airplay time that is devoted to live content and the percentage devoted to 
taped content. 
I then measure the similarity between two stations by the distance between their 
two vectors (as measured by the angle between the vectors).
53
   Two stations that are 
identical in the way in which they allocate their airtime across the different categories of 
play would have a distance measure of zero degrees.  Two stations that are diametrically 
opposite (for example, one plays only live content and the other only taped content) 
would have a distance measure of 90 degrees.  More generally, the smaller is the angle 
between the vectors, the more similar are the stations programming content.   
The base station-pair specifications take the following form: 
iijoij
OwnerCommonAngle ??? ++=   
1
      (4) 
where i and j index the two stations being compared, Common Owner
ij
 is an indicator 
variable that equals 1 if the two stations are commonly owned;  ? are the associated 
parameters; and ?
ij
 is the additive stochastic error term.  A negative coefficient on the 
                                                 
52
 The analysis also controls for the small percentage of airplay time that is dead, statistic/interference, and 
uncategorized.   
53 
Specifically, I measure the distance as the arc cosine of the inner product of the two vectors, divided by 
the product of their norms.  This is a conventional measure of distance between two vectors, from linear 
algebra.  (See for example, Gilbert Strang. "Introduction to Linear Algebra". Wellesley-Cambridge Press, 
2nd ed., 1998.) 
   26
Common Owner variable would suggest that common ownership results in less variety or 
more similar programming.  
The base specification compares all commercially owned, in-market stations in 
the Edison Database.  In the results I present below, I extend the analysis by restricting 
the sample to comparisons of same-market stations only.  I further extend the analysis by 
controlling for market fixed effects.  In addition, I estimate these models without Clear 
Channel stations to determine whether the estimated effects are simply a Clear Channel 
effect. 
Finally, I refine the analysis by focusing on stations with sports and news formats 
only.  For each of these two formats, I redo the angle analysis described above.  I also 
study the overlap in actual programs played, using three different measures of program 
overlap.  To understand these different measures, consider the following example.  
Suppose there are two news stations, A and B. A plays a total of 5 unique programs 
over the course of the Edison sample period, and B plays a total of 10 unique programs 
over the course of the Edison sample period.  Further suppose that 2 of the 5 programs 
played by station A are also played on station B.  The first measure of program overlap 
simply counts the number of common programs (2 in this example).  The second measure 
of program overlap is the percentage of unique programs across the two stations that are 
common to both (2 divided by 13, or 15 percent, in this example).  The third measure of 
overlap is the average overlap across the two stations (the average of 2 divided by 5 and 2 
divided by 10, or 30 percent, in this example).  For each of these outcome measures, I 
estimate the same base specifications as well as the extensions described above. 
VII. Effects of Ownership Structure on Diversity of Formats 
In this section, I discuss the effects of ownership structure on format diversity.  As 
explained before, my analysis includes three different descriptions of format:  BIAs 101 
formats (Format 101), BIAs 20 major format categories (Format 20), and a modified 
version of BIAs 20 major format categories (Format 11).  I describe my market level 
and station-pair level analysis, in turn. 
   27
Market Level Analysis 
For each market, I construct measures of the number of available formats as well 
as a format HHI, which measures concentration in formats.  To see the distinction 
between formats and the format HHI, consider the following example.  Suppose there are 
two markets, each with 10 stations and 5 formats.  The first market has 2 stations per 
format, and the second market has 1 station for each of 4 formats and 6 stations for the 
fifth format.  Looking at format counts, the two markets appear to be identical.  However, 
looking at format HHI, market two appears to be more concentrated, in that it has more 
pile-up on a particular format.  In this example, market one has a format HHI (defined as 
the sum of squared market shares) of 0.2, and market two has a format HHI of 0.4.  
Table 10 presents a comparison of means across markets with differing levels of 
radio ownership concentration.  As seen is this table, more concentrated markets offer 
fewer formats and have more pile-up.  As a general matter, however, it is important to 
recognize that smaller markets have (by definition) fewer stations and are more 
concentrated. This greater concentration is a result of the current ownership rules that 
permit owners to own a larger fraction of stations in smaller markets, relative to bigger 
markets.  Simply observing that smaller markets have fewer formats is not by itself 
evidence that concentration results in less program diversity.  Indeed, one must 
investigate whether concentration (or other measures of ownership structure) is 
associated with a larger or smaller number of formats, controlling for market size.   
Table 11 presents a summary of the corresponding regression results.  Within the 
All Stations analysis, the top panel presents results corresponding to model (1) above, 
and the bottom panel presents results corresponding to the extended model including 
demographics (i.e., model (2) above).  Excluding demographics, there are 251 
observations in regression sample and the adjusted R-squared, measuring the goodness of 
fit of the model, ranges from 0.36 to 0.88.   
Controlling for the number of stations and the interaction effects between stations 
and concentration (via the ownership rules), concentration has no statistically significant 
effect on the number of available formats.  However, the results suggest that stations are 
more spread out across existing formats in more concentrated markets.  That is, 
concentrated markets have significantly less pile-up, as measured by less format 
   28
concentration. These results are robust to the inclusion of additional covariates, as seen in 
the With Demographics panel of Table 11.  In addition, I find that markets with more 
stations have more formats and less pile-up, as seen by the marginal effect of an increase 
in the number of stations.  Cross-ownership with local radio and/or local television 
stations does not appear to have a noticeable effect on the number of formats or on format 
pile-up.  Finally, markets with large national radio owners appear to have more formats 
and less pile-up. (See Appendix 2, Column 1 for the full set of regression results 
corresponding to the Format 101 HHI specification.  I find, for example, that there is 
more pile-up in markets with larger populations and greater effective buying income per 
capita and less pile-up in more educated markets.)   
Table 11 also presents the results for the same models based on the FM only 
stations sample.  As with all stations, the results suggest that concentration does not affect 
the number of formats, but it is associated with less format pile-up.  Table 12 presents the 
results separately for big and small markets.  Consistent with all markets, consolidation in 
big markets has no statistically significant effect on the number of formats, and it is 
associated with less-pileup.  In addition, national radio ownership (as measured by the 
number of commercial stations owned nationally the owners in the market) is also 
associated with more formats and less pile-up.  In small markets, consolidation is 
associated with fewer formats as measured by Formats 11.  However, this effect 
disappears (at least statistically) upon moving to more finely defined format categories. 
Station-Pair Level Analysis 
There are 163,853 station-pairs across all commercial, in-market stations in the 
Edison sample.  Of these, 42,175 are FM only pairs and 739 are same market pairs.  For 
each station-pair, I construct an indicator variable that equals 1 if the two stations have 
the same format and zero otherwise.  Table 13 presents a descriptive comparison of the 
likelihood that two stations have the same format, across same owner and different owner 
pairs.  These data suggest that commonly owned stations in the same market are more 
likely to have the same format than are stations owned by different owners.  However, 
this pattern is reversed when I look only at pairs of FM stations.  In addition, commonly 
owned stations in different markets are also more likely to have the same format. 
   29
Table 14 presents a summary of the corresponding regression results.  Panel [1] 
presents a comparison of all station-pairs, and panels [2] and [3] present a comparison of 
station-pairs in the same market.  Panels [1] and [2] correspond to model (4) above, and 
panel [3] extends panel [2] by controlling for market fixed effects.  The regression 
sample includes 163,853 station-pairs across all markets, 739 same-market pairs, and 
anywhere from 335 to 493 same-market station pairs that have variation in the dependent 
variable.  The pseudo R-squared (a measure of goodness of fit for Probit models) is very 
small for models without market fixed effects.  The pseudo R-squared, including market 
fixed effects, ranges from 0.08 to 0.13.   
The point estimates shown in the table are marginal effects which measure change 
in the basis points associated with common ownership.  For example, a marginal effect of 
0.05 indicates that commonly owned stations are 5 percentage points more likely to be 
the same format than stations owned by different owners.  In any case, the results using 
the sample of same-market pairs with and without market fixed effects show no 
statistically significant effect of ownership structure on the likelihood that two stations 
would be the same format.  Instead, the market demographics (as captured in the market 
fixed effects) appear to be better predictors of same format, as evidenced by the 
improvement in the pseudo R-squared. 
Table 15 presents the results of the station-pairs in the same market, with market 
fixed effects, analyzed separately for big and small markets.  Of the 493 same-market 
commercial station-pairs in the regression sample with Format 11, 452 are in big markets 
(defined to be markets with greater than 30 radio stations) and the remaining 47 are in 
small markets.  Consolidation of ownership has no statistically significant effect on any 
of the format measures in big markets.  In small markets, consolidation is associated with 
fewer formats, as measured by Format 11 and 101; however the Format 101 effect is 
highly unstable due to the small sample size (16 observations, spanning 5 markets).    
Conclusions 
Taken together, both the market level and the station-pair level analysis suggest 
that consolidation of radio ownership does not diminish the diversity of local format 
offerings.  If anything, the market level analysis suggests that more concentrated markets 
   30
have less pile-up of stations on individual format categories, and large national radio 
owners offer more formats and less pile-up. 
VIII. Effects of Ownership Structure on Other Measures of Content 
In this section, I discuss the effects of ownership structure on other measures of 
programming content.  As explained before, my analysis includes a number of new 
measures of programming content that characterize airplay time beyond simply radio 
format.  One set of measures describe the percent of airplay time devoted to different 
types of programming content:   
 Percentage local content in the AM drive; 
 Percentage network/syndicated in the AM drive; 
 Percentage live programming in the AM drive; 
 Percentage advertising in the AM drive; 
 Percentage talk entertainment in the AM drive; 
 Percentage music in the AM drive; and 
 Percentage news in the AM drive. 
These same measures are also constructed for the evening day part.  Another set of 
measures describe the length of uninterrupted minutes of different types of programming: 
 Average length of block of advertising in the AM drive; 
 Average length of block of talk entertainment in the AM drive; 
 Average length of block of music in the AM drive; and 
 Average length of block of news in the AM drive. 
These same measures are also constructed for the evening day part.  For the station level 
analysis, I also evaluate the effects of ownership structure on the number of syndicated 
programs offered as well as the number of on-air personalities.  For the station-pair level 
analysis, I also evaluate the effects of ownership structure on the overlap of specific news 
and sports programming.  I describe my market, station, and station-pair level analyses of 
the effects of consolidation on these outcome measures, in turn. 
   31
Market Level Analysis 
Table 16 presents a comparison of means across markets with differing levels of 
radio ownership concentration.  The means in the top panel are calculated across all 
station formats, across both bands.  The means in the bottom panel are calculated across 
all station formats in the FM band only.  (A format-specific discussion, for news and 
sports stations, is provided in a later section of the report.)   
Across all stations, more concentrated markets offer more local programming, 
more news, and more advertising in the AM drive and less local programming, less news, 
and less advertising in the evening, relative to less concentrated markets.  They offer less 
network/syndicated programming and sports in the AM drive and more 
network/syndicated programming and sports in the evening, relative to less concentrated 
markets.  They offer more live programming and music in both day parts and less talk 
entertainment in both day parts, relative to less concentrated markets.   Across FM 
stations, the patterns are a little different.  For example, more concentrated markets offer 
less local and less live programming in both day parts, relative to less concentrated 
markets.  
In addition, across all stations, more concentrated markets offer shorter blocks of 
advertising and talk entertainment and longer blocks of music in both day parts, relative 
to less concentrated markets.  They offer longer blocks of news in the AM drive and 
shorter blocks of news in the evening and offer shorter blocks of sports in the AM drive 
and longer blocks of sports in the evening drive, relative to less concentrated markets.  
The only noticeable difference for FM stations is the pattern for average block of sports 
programming.  FM stations in more concentrated markets appear to offer shorter blocks 
of sports programming both in the AM drive and evening, relative to less concentrated 
markets. 
Tables 17 and 17a present a summary of the corresponding regression results 
based on all stations.  (Table 17 presents only a subset of those results that are 
significantly different from zero, while Table 17a presents the full set of coefficients 
associated with ownership structure.)  The top panel presents results corresponding to 
model (1) above, and the bottom panel presents results corresponding to the extended 
model including demographics (i.e., model (2) above).  Excluding demographics, there 
   32
are either 165 or 169 observations in the regression sample.  This difference stems from 
the fact that not all stations were surveyed during the same day parts.  Similarly, Tables 
18 and 18a present a summary of the regression results based on FM only stations.  The 
measures of model fit (adjusted R-squareds) are very small in all cases (and this lack of 
explanatory power persists even at the station level).   
Nonetheless, the available evidence suggests that consolidation as measured by 
local radio station owner HHI has virtually no statistically significant effect on these 
measures of programming content.  The exceptions are for the average length of 
uninterrupted blocks of talk entertainment, music and sports in the evening  based on all 
stations.  Here, the results, controlling for demographics, suggest that consolidation is 
associated with shorter blocks of uninterrupted talk entertainment in the AM drive and 
shorter blocks of music in the evening.  In addition, consolidation is associated with 
longer blocks of sports programming in the evening.  For FM only stations, the only 
statistically significant effect of consolidation appears for news programming.  In 
particular, consolidation is associated with a lower percentage of airplay time for news 
programming in the evening.   
Finally, the results on cross-ownership suggest that local newspaper 
cross-ownership is associated with more talk entertainment and longer blocks of 
uninterrupted talk entertainment in the AM drive.  For FM only stations, it is associated 
with more news in the AM drive.  Local television ownership is associated with more 
advertising in the AM drive and less news and shorter blocks of news in the evening.  For 
FM only stations, local television ownership is associated with more news in the AM 
drive and shorter blocks of music in the evening.  Increasing radio ownership at the 
national level is associated with more talk entertainment and less sports programming in 
the AM drive.  For FM only stations, increasing radio ownership at the national level is 
associated with less news and shorter blocks of news in the evening. 
Station Level Analysis 
Table 19 presents a comparison of means across stations based on whether or not 
the station operates in a market with other commonly owned stations.  As explained 
before, Sisters is a count of the number of stations commonly owned in the market, so 
that Stations with At Least One Sister are those of an owner that owns at least two 
   33
stations in the market.  The means in the left panel are calculated across all station 
formats, across both bands.  The means in the right panel are calculated across all station 
formats in the FM band.  Tables 20 and 21 present a summary of the corresponding 
regression results based on all stations and FM only stations, respectively.  The 
regression models correspond to model (3) above.
54
  There are either 250 or 276 
observations in regression sample, depending on whether programming is measured in 
the AM drive or evening, respectively.  This difference stems from the fact that not all 
stations were surveyed during the same day parts.   In addition, there are 561 
observations in the sample for the number of syndicated programs and personalities.   As 
with the market level regressions, the measures of model fit (adjusted R-squared) are 
generally very small, though they can get as high as 0.36. 
In the all stations sample, the results suggest operating in a market with other 
commonly owned stations has no statistically significant effect on how a station is 
programmed.  In the FM only stations sample, the only effect of owning multiple radio 
station is to reduce the percent live programming in the AM drive, the percent news 
program in the AM drive, and reduce the average length of an uninterrupted block of 
news in the AM drive.  Controlling for the number of commonly owned stations, stations 
that operate in more concentrated markets offer less local, live, and music programming 
and more network/syndicated programming in the evening.  All else equal, concentration 
is also associated with longer blocks of uninterrupted sports in the evening.  In addition, 
there is no statistically significant effect of concentration on any of these program 
outcome measures for the sample of FM only stations. 
Finally, the results on cross-ownership suggest that newspaper cross-ownership is 
associated with longer blocks of uninterrupted talk in the AM drive and longer blocks of 
uninterrupted news in the evening.  Stations that have large national owners offer more 
syndicated programs and spend a statistically significantly greater percentage of airtime 
on network/syndicated programming.  In addition, national ownership is associated with 
a statistically significant, negative effect on length of an uninterrupted block of music in 
the evening.   
                                                 
54
  Because not all stations were surveyed during the AM drive and the evening, there are insufficient 
observations to estimate the model with either market fixed effects or owner fixed effects. 
   34
Station-Pair Level Analysis 
In the station-pair analysis, I evaluate whether the combinations of programming 
offered by common stations is more or less similar than the combinations offered by 
separately owned stations.  As explained before, each station is characterized by three 
different vectors of programming.   The first is what I call a content vector that 
measures percent of time on advertisements, announcements, talk entertainment, 
fundraising/charity, music, news, other, public affairs, religious, and sports.  The second 
is an origination vector that measures percent of time on local, network/syndicated, and 
voice tracked programming. The third is a live vector that measures the percent of time 
on live and taped programming.   I then measure distance in programming between any 
two station-pairs by the angle between their two vectors.  This angle will range between 
zero and 90 degrees, where a value closer to zero can be interpreted as more similar and a 
value closer to 90 as more disparate. 
Table 22 presents a description of the effect of common ownership on the 
measured angles.  The top panel compares all station-pairs (across all formats), and the 
bottom panel compares FM only station-pairs (across all formats).  Commonly owned 
stations in the same market appear to be programmed more similarly by these measures 
in the daytime, evening, and midnight to 6AM day parts.  They appear to be programmed 
less similarly in the AM drive, the PM drive, and the weekend day parts.  FM only 
station-pairs exhibit a similar pattern. 
Table 23 presents a summary of the corresponding regression results, for all 
stations.  (There are insufficient FM only station-pairs that are commonly owned and in 
the same market, in the Edison sample.  Thus, I do not present regression results for FM 
only station-pairs.)  Panel [1] corresponds to model (4) above.  Panel [2] is the same as 
Panel [1], except that the sample is restricted to same-market pairs only.  Finally, Panel 
[3] extends the model from Panel [2] by including market fixed effects.  There are 14,524 
to 43,332 station-pairs, depending on day part.  The adjusted R-squareds for the models 
without fixed effects are very low.  The adjusted R-squared for the models with fixed 
effects range between 0.02 and 0.95.  The results suggest that the differences seen in the 
descriptive table are statistically insignificant.  That is, the common ownership does not 
have any statistically significant effect on any of these measures of program content. 
   35
Table 24 provides a descriptive look at a pairwise comparison of news and sports 
format stations.  In Edison sample, there are 69 sports and 42 news commercial, in-
market stations in the Edison Database.  The top panel of Table 24 presents a summary of 
the vector comparisons for the available news pairs, by day part, and the bottom panel 
presents the same summary for the available sports pairs.  This characterization suggests 
that commonly owned news stations are programmed more similarly during the daytime 
and midnight to 6 AM day parts, and less similarly during the AM drive and evening day 
parts.  Further, commonly owned stations in different markets are programmed more 
similarly than separately owned stations in different markets.  The pattern for sports is 
less sparse  as there are insufficient observations to do this pairwise analysis by day 
part.
55
 
Conclusions 
The available evidence based on the market level, station level, and the station-
pair level analyses suggest that consolidation of radio ownership has, for the most part, 
no statistically significant effect on these measures of program outcome.   For each of the 
handful of instances in the market and station level analyses where ownership structure 
has a statistically significant effect on programming content, I have evaluated the 
magnitude of the estimated effect.  In the case of HHI, I estimate the implied change in 
the outcome measure associated with a 100 point change in the mean HHI.  For all other 
measures of ownership structure (e.g. percent of stations that cross-own local newspapers 
or number of radio stations owned nationally by the owners in the market), I calculate the 
implied change in the outcome measure associated with a 10 percent increase in 
ownership.
56
  Table 25 presents a summary of these calculations.  This pattern of results 
suggests that: 
 Cross-ownership of local newspaper and television rarely has a statistically 
significant effect on programming content, and when it does, the effect is small in 
                                                 
55
 See Appendix 2, Columns 2 and 3 for a full set of market level results for the programming outcome 
variables Percent Local, Evening and Average Block, Entertainment/Leisure/DJ Banter, AM Drive 
which encompasses talk radio.  See Appendix 3, Columns 1 and 2 for a full set of two different station level 
specifications.   
56
 The estimated effect is calculated as the 10 times the elasticity of the program content measure with 
respect to the measure of ownership evaluated at the sample means. 
   36
magnitude.  For example, a 10 percent increase in newspaper cross-ownership in 
the average market is associated with a 0.53 percent increase in airplay of talk 
programming and an increase of 0.77 minutes in the average uninterrupted block 
of talk entertainment in the AM drive. 
 Local radio consolidation is associated with less music (4 percent), less local (3 
percent), less live programming (3 percent), and less news programming (18 
percent) in the evening, though this last effect is estimated from an FM only 
stations sample.   
 All else equal, stations in more concentrated markets offer substantially longer 
segments of uninterrupted sports programming.  A 100 point increase in the HHI 
would increase the average length of an uninterrupted sports program in the 
evening by 15 minutes, across all stations.  The pattern of results suggests that this 
expanded offering is offset with the shorter segments of news programming in the 
evening.  
IX. Effect of Ownership Structure on the Variety of Actual, Non-Music 
Programs Aired 
In this section, I evaluate the effects of ownership structure on the choice of 
programs offered by sports and news radio stations.  As explained before, the Edison 
Database identifies the name of the program actually aired.  However, a preliminary 
investigation of the data suggests that there may be a substantial missing data problem.  
In fact, only 53 percent of the 66,720 minutes sampled by Edison have an identified 
program name.  A closer look at missing patterns by format suggests that sports, news, 
and talk have substantially more names identified than do other station formats.  
However, there are no two talk stations in the Edison Database that are commonly owned 
and operate in the same market, which would be required to study the effects of 
consolidation in local radio.  Thus, I focus here only on news and sports stations.  
There are 358 commercial, in-market sports stations and 602 commercial, 
in-market news stations in the United States.  By comparison, there are 69 sports and 42 
news commercial, in-market stations in the Edison Database, so little more than 10 
percent of either type is represented in the sample.  In the sample, all sports stations have 
program information available, and the median station has the program name identified 
   37
98 percent of the time.  Similarly, all but one news station has program information 
available, and the median news station has the program name identified 83 percent of the 
time. 
The top four news station programs in the Edison Database are Coast to Coast 
AM, The Rush Limbaugh Show, Sean Hannity, and Savage nation with Michael 
Savage.   These programs are carried on multiple radio stations across the country and 
possibly within the same market.  Other shows, which are not as widely distributed 
include The Ed Schultz Show, a progressive radio talk show that is carried on radio 
stations across the country (and in 9 of the top 10 Arbitron markets) and The Bob Rose 
Show, a local talk show covering a range of topics including politics, sports, and current 
events  airing on 97.3 FM, in Gainesville, Fl.   See Table 26 for the names of the top 50 
programs identified on news stations, along with the frequency with which each appears 
on the Edison sampled stations.   
The top six sports programs are ESPN and Fox Sports programs:  Gamenight on 
ESPN Radio, Allnight on ESPN Radio, The Jim Rome Show on Fox Sports Radio,  
ESPN Radio, The Dan Patrick Show on ESPN Radio,  Mike & Mike in the 
Morning, and Fox Gametime React with JT the Brick.  Other shows, which are not as 
widely distributed include The Tim Brando Show and The Dr. Bob Martin Show.  
The Tim Brando Show broadcasts sports, news, talk, scores, and sports highlights and 
is part of Sporting News Radio, which  is carried on AM and FM stations around the 
country with select programming also available on XM Satellite radio (on XM Sports 
Nation).  The Dr. Bob Martin Show is a syndicated alternative health show with call-in 
programs carried by various radio stations across the country.  See Table 27 for the 
names of the top 50 program names identified on sports stations, along with the 
frequency with which each appears on the stations in the Edison Database.   
There are a total of 111 unique sports programs and a total of 139 unique news 
programs identified across the 69 sports and 42 news stations in the Edison Database.  
Some of the programming across the two formats is common.  For example, some news 
stations carry talk shows that focus on sports.  Across all of the news and sports 
formatted stations generally, there are 17 programs in the Edison data that are available 
on both news and sports format stations.  These 17 represent 7.3 percent of all the 233 
   38
unique news and sports programming.  Alternatively, 15.3 percent of the identical sports 
station programs are available on news stations, and 12.2 percent of the identical news 
station programs are available on sports stations  for an average overlap of 13.75 
percent. 
I estimate the effects of ownership structure on measures of program duplication, 
within format, separately for sports and news stations.  As explained earlier, I measure 
variety, or rather program duplication, in three different ways:  Common Programs, % 
Overlap, and Avg. % Overlap.  The first is a count of the number of common 
programs across two station-pairs of the same format.  The second measures the 
percentage of unique programs offered across two station-pairs that are common to both.  
The third measures the average duplication across two station-pairs.   
Table 28 presents a description of the effect of common ownership on program 
overlap.  Stations owned by different owners appear to have no overlap in programming, 
for either news or sports.  Commonly-owned news stations in the same market overlap in 
14 to 22 percent of their programming and commonly-owned news stations in different 
markets overlap in 8 to 14 percent of their programming, depending on the measure of 
overlap.  By contrast, commonly-owned sports stations in the same market have no 
overlap in their programming, and commonly-owned sports stations in different markets 
have overlap in 5 to 9 percent of their programming.   
Table 29 presents a summary of the corresponding regression results.  The top 
half of the table is for news stations, and the bottom half is for sports stations.  Within 
each, panel [1] corresponds to model (4) above, and panel [2] extends model (4) by 
including two additional regressors:  an indicator variable that equals 1 if the two stations 
are in the same market (Same Market) and an interaction term between Same Owner 
and Same Market.  The coefficient on the interaction term measures the extent to 
common ownership within a market affects programming decisions differently from 
common ownership across markets.  
There are 2,211 news station-pairs and 820 sports station-pairs.  The adjusted 
R-squareds for the news models range between 0.03 and 0.04.  The adjusted R-squareds 
for the sports models are even smaller, driven by the fact that there is virtually no 
variation in the dependent variables.  The results suggest that the differences in news 
   39
station-pairs seen in the descriptive tables are statistically significant.  That is, the overlap 
in programming across commonly owned news stations is statistically significant, and 
there may be more overlap within markets rather than across markets.  The estimated 
results suggest that commonly owned stations-pairs have about one third more programs 
in common or program overlap that is 5 to 8 percent more, relative to independently 
owned station-pairs.  However, the differences in the sports station-pairs are not 
statistically significant; not only is the same owner coefficient in the bottom panel of 
Table 29 never statistically significant, but the magnitude of the point estimates 
themselves are very close to zero.  Thus, there is no overlap in sports programming for 
commonly-owned stations either within or across markets.  This result likely reflects 
practices in the underlying sports broadcast rights market, where a live (often local) 
sporting event is typically broadcast by a single radio station within a radio market. 
X. Effects of Ownership Structure on Advertising Prices 
In this section, I discuss the effects of ownership structure on advertising prices.  
As explained before, terrestrial radio stations sell advertising to businesses interested in 
reaching the stations listening audience.   Consolidation in local radio may result in 
higher advertising prices, if advertisers have no reasonable substitutes to advertising on 
radio.  To the extent that local radio groups are more efficient at selling advertising, 
consolidation in radio may actually result in lower prices.  Absent one of these 
mechanisms, consolidation should have no effect on advertising prices. 
I study this effect of consolidation with two measures of advertising prices at the 
market level  cost per point (CPP) and cost per thousand (CPM).  These measures 
are computed by SQAD, based on proprietary data collected from advertising agencies 
and media buyers.  CPP is the cost of reaching one percentage point of the listening 
audience, and the average CPP in my analysis sample is $61.29.  By contrast, CPM is the 
cost of reaching 1,000 listeners, and the average CPM in my analysis sample is $11.78, 
equivalent to 1.2 cents per listener reached.  I study the effects of consolidation on CPP 
   40
and CPM in the AM drive, in the evening, and on average across all day parts, using a 
market level model.
57
   
Table 30 presents a comparison of means across markets with differing levels of 
radio ownership concentration.  The means in the top panel are calculated across all 
station formats, across both bands.  The means in the bottom panel are calculated across 
all station formats in the FM band.  In both panels, concentration is associated with lower 
CPPs and higher CPMs.  The lower CPP in more concentrated markets may simply 
reflect the fact that more concentrated markets are by construction smaller markets, due 
to ownership rules that permit owners to own a larger fraction of stations in smaller 
markets.  In smaller markets, one percent of listeners is a smaller total number of 
listeners; hence it should follow (all else equal) that CPP is lower in smaller markets. The 
CPM measure is an absolute measure (cost per thousand listeners) and is not confounded 
by market size.   
Table 31 presents a summary of the corresponding market level regression results 
based on all stations.  The top panel presents results corresponding to model (1) above, 
and the bottom panel presents results corresponding to the extended model including 
demographics (i.e., model (2) above).  Excluding demographics, there are 241 
observations in regression sample.  The measures of model fit (adjusted R-squareds) 
range from 0.33 to 0.94.  I find that consolidation in local radio has no statistically-
significant effect on advertising prices.  As the number of stations in the market 
increases, prices decrease  a result that is consistent with competition among radio 
stations for advertising dollars.  There is some evidence that cross ownership with 
television results in higher prices in the AM drive (top panel of Table 31); however, this 
results disappears when I control for demographics (bottom panel of Table 31).   
Table 31 also presents an analogous summary of the market level regression 
results based on FM only stations.   The measures of model fit (adjusted R-squareds) 
range from 0.32 to 0.93.  As before, the results show that consolidation in local radio has 
no statistically-significant effect on market prices and that prices decrease as the number 
of stations in the market increases.  In addition, television cross-ownership is associated 
                                                 
57
 Because CPP and CPM are only available at the market, not station level, there is no additional 
information to be exploited in moving to a station or station-pair level regression model. 
   41
with statistically significantly higher CPPs, for both all stations and FM only stations.  
There is also some evidence that national ownership of FM radio stations results in lower 
advertising prices.     
Table 32 presents the results of the advertising price analysis separately for big 
and small markets.  Of the 236 markets in the regression sample with demographic 
controls, 103 are in big markets (defined to be markets with greater than 30 radio 
stations) and the remaining 133 are in small markets.  There are no differential effects of 
local radio consolidation of ownership across big and small markets.  National ownership 
has a statistically significant, negative effect on advertising prices and cross ownership 
with television has a statistically significant, positive effect on advertising prices in big 
markets across a number of the specifications  but not in small markets.  Not only is 
there no statistical significance associated these estimates in the small markets, but the 
magnitude of the corresponding coefficients are noticeably smaller. 
See Appendix 2, Column 4 for the full set of regression results corresponding to 
the CPP, AM drive specification.  In addition to the results reported above, I also find 
CPP is higher in markets with more people; it is higher in the western region of the U.S. 
(relative to the northeast); and among the different age categories, it is highest for the 35 
to 44 age category.   
XI. Effects of Ownership Structure on Listenership 
In this section, I discuss the effects of ownership structure on radio station 
listenership.  From the perspective of an economist, listenership is a useful measure in 
evaluating the effects of consolidation on public welfare.  It provides a summary measure 
of listeners valuations of a stations performance.  If consolidation in local radio 
ownership results in inferior programming, as critics of consolidation claim, one should 
observe listeners reducing their time spent listening to radio.  Alternatively, if 
consolidation results in improved programming, one should observe increased time spent 
listening.   
I study this effect of consolidation with a measure of listening called AQH 
listening (Rating).  This measure is computed by Arbitron, based on proprietary survey 
data collected from listener diaries.  Ratings are available by station, and market level 
   42
ratings are calculated as the average ratings across the available stations in the market.  
Accordingly, I estimate the effect of ownership structure on listenership using both my 
market level and station level analysis, in turn. 
Market Level Analysis 
Table 33 presents a comparison of means across markets with differing levels of 
radio ownership concentration.  The means in the top panel are calculated across all 
station formats, across both bands.  The means in the bottom panel are calculated across 
all station formats in the FM band.  In both panels, concentration is associated with 
greater listenership, even though there are fewer radio stations available in more 
concentrated markets.   
Table 34 presents a summary of the corresponding market level regression results 
based on all stations.  The top panel presents results corresponding to model (1) above, 
and the bottom panel presents results corresponding to the extended model including 
demographics (i.e., model (2) above).  Excluding demographics, there are 249 
observations in regression sample.  The measures of model fit (adjusted R-squared) range 
from 0.33 to 0.62.  The results are that consolidation in local radio has no statistically 
significant effect on average listening.  As the number of stations in the market increases, 
average listening to any one station decreases.  Listeners served by large radio groups, as 
measured by the number of commercial stations owned nationally by in-market owners, 
listen more.  In addition, there is some evidence that local newspaper cross ownership 
increases overall and AM drive listening, as measured by average quarter hour or 
(AQH), and that national ownership of radio stations is associated with increased AM 
drive listening. 
See Appendix 2, Column 5 for the full set of regression results corresponding to 
the average ratings, AM drive specification.  In addition to the results reported above, I 
also find average ratings are higher in the Midwest (relative to the Northeast); people 
ages 45 to 64 are most likely to listen to terrestrial radio, and people over 65 are least 
likely to listen to terrestrial radio (relative to others in the age distribution). 
Table 34 also presents a summary of the market level regression results based on 
FM only stations.   The measures of model fit (adjusted R-squared) range from 0.26 to 
0.54.  As with all stations, the results are that consolidation in local radio has no 
   43
statistically significant effect on listenership.  As with the all stations result, markets with 
more stations have less listening to any one station relative to markets with fewer 
stations. Finally, there are no statistically significant effects of cross-ownership on 
listening in the FM only sample. 
Table 35 presents a summary of the market level regression results broken out by 
big and small markets.  The most interesting result here is that all else equal, 
concentration in big markets is associated with lower average station AQH ratings, 
suggesting that listeners in big markets are not tuning in by as much as listeners in small 
markets.   The natural question is why are listeners in big markets are not tuning in?  Is it 
because the programming quality of concentrated station owners in big markets is below 
standard?  Or is it a fact that consumers in big, concentrated markets are more likely to 
switch to new media technologies like satellite radio and internet radio.  My study of this 
finding is on-going. 
Station Level Analysis 
Table 36 presents a comparison of means across stations with differing levels of 
radio ownership concentration.  The means in the left panel are calculated across all 
station formats, across both bands.  The means in the right panel are calculated across all 
station formats in the FM band.  In both panels, concentration is associated with greater 
listenership, even though there are fewer radio stations available in more concentrated 
markets.   
Table 37 presents a summary of the comparable regression results and is based on 
model (3) above.  There are 410 or 420 observations in the regression samples.  The 
measures of model fit (adjusted R-squareds) range from 0.143 to 0.195.  I find that 
stations operating in markets with other commonly owned stations achieve higher ratings 
(as measured by the coefficient on Sisters) than independent stations. In addition, 
cross-ownership with local newspapers has a statistically-significant positive effect on 
listenership.  There are no other statistically significant effects of ownership structure on 
listenership.
58
   
                                                 
58
 Tables 38 and 39 presents results for the same model re-estimated by replacing the market-specific 
variables with market fixed effects and the owner-specific variables with owner-fixed effects.   Table 38 
uses the sample of all commercial, in-market stations surveyed by Edison, while Table 39 uses the FM 
   44
XII. Conclusions  
This study evaluates the effects of ownership structure on programming, 
advertising prices, and listenership for terrestrial radio.  The paper catalogues the effects 
of ownership structure across numerous different measures of programming content, 
including: format counts; format concentration; percent of station airplay on music; news; 
sports, talk entertainment; advertisements, by day part; percent of station programming 
that is live; percent of station programming that is network/syndicated and voice-tracked; 
number of syndicated programs, and the number of on-air personalities.  The paper also 
offers an examination of overlap in programming for sports and news format stations.  
Finally, it assesses the effects of ownership structure on two different measures of 
advertising prices and listenership. 
Using a combination of descriptive and econometric analyses, I find that 
consolidation of radio ownership does not diminish the diversity of local format 
offerings.  If anything, more concentrated markets have less pile-up of stations on 
individual format categories, and large national radio owners offer more formats and less 
pile-up.  Consolidation of local radio ownership also has a statistically significant and 
economically meaningful effect the composition of non-music programming.  In 
particular, I find that owners with several local stations offer longer, uninterrupted blocks 
of sports programming in the evening.  This shift towards sports programming is 
accompanied by reductions in other types of programming.  Beyond this effect, 
ownership structure generally does not have much of an effect, either statistically or in 
terms of practical magnitude, on programming content.  In addition, there are no 
significant differences in the effects of consolidation in radio across big and small 
markets. 
The analysis also suggests that common ownership results in more diversity in 
actual non-music programs aired.  Based on an analysis of news and sports formatted 
stations, I find there is some overlap in actual programs aired across the two formats 
generally, but not within commonly owned station-pairs within the same market.  In 
particular, I estimate that there is about a 15 percent overlap in the programs aired across 
                                                                                                                                                 
only, in-market stations.  In both sets of tables, the results are that consolidation in local radio (as measured 
by the marginal effect of Sisters) has no statistically-significant effect on listenership.   
 
   45
the two types of stations.    However, there is only a 5 to 7 percent overlap in the actual 
news programs aired on commonly owned news station-pairs within the same market.  In 
addition, there is virtually no overlap in the actual sports programs aired on commonly 
owned sports station-pairs within the same market.    
From the point of view of audiences, I find that stations operating in markets with 
other commonly owned stations achieve higher ratings, than do independent stations.  In 
addition, cross-ownership with local newspapers has a statistically significant, positive 
effect on listenership.  However, there is some evidence that listenership is lower in more 
concentrated big markets, relative to small markets.  Finally, I find that consolidation in 
local radio has no statistically significant effect on advertising prices.  National radio 
ownership has a negative effect on prices.  In addition, cross-ownership with local 
television has a positive effect on advertising prices in big markets. 
These results are broadly consistent with the previous literature that finds more 
concentrated markets are associated with more, not less, program variety.  Some of the 
new contributions of this study, enabled in part by the Edison Database, include 
consideration of a host of other measures of programming content, examination of non-
music programming, and comparison of big and small markets.  Consideration of these 
new findings sheds some light on the questions of whether and how ownership affects 
radio station programming and listenership.   
   46
Bibliography 
 
Arbitron (2007).  Radio Today, How America Listens to Radio, 2007 Edition. 
Beebe, Jack H., Institutional Structure and Program Choices in Television Markets, 
The Quarterly Journal of Economics, February 1977, 15-37.) 
Berry, Steven and Joel Waldfogel (2001). Do Mergers Increase Product Variety? 
Evidence from Radio Broadcasting, The Quarterly Journal of Economics, August 2001, 
1009-1025. 
BIA Financial Network (2006). Over-the-Air Radio Service to Diverse Audiences. 
Goldfarb, Charles B. (2003). FCC Media Ownership Rules: Issues for Congress, CRS 
Report for Congress, September 17, 2003. 
DiCola, Peter (2006).  False Premises, False Promises: A Quantitative History of 
Ownership Consolidation in the Radio Industry, Working Paper, Future of Music 
Coalition. 
Gilbert Strang. "Introduction to Linear Algebra". Wellesley-Cambridge Press, 2nd ed., 
1998.) 
Hausman, Jerry (2006), Statement of Professor Jerry A. Hausman, submitted as Exhibit 
B to Comments by Clear Channel Communications, Inc., 2006 Quadrennial Regulatory 
Review, FCC MB Docket No. 06-121, October 23, 2006. 
Owen, Beebe, and Manning, Television Economics, (Lexington, MA:  Lexington Books, 
1974), Chapter 4 on Theories of Program Choice. 
Project for Excellence in Journalism (2007).  The State of the News Media 2007, An 
Annual Report on American Journalism, Chapter on Radio. 
Rogers, Robert P. and John R. Woodbury (1996). Market Structure, Program Diversity, 
and Radio Audience Size, Contemporary Economic Policy, Vol. XIV, 81-91. 
Romeo, Charles J. and Andrew Dick (2005). The Effect of Format Changes and 
Ownership Consolidation on Radio Station Outcomes, Mimeo, U.S. Department of 
Justice. 
Steiner, Peter O. (1952). Program Patterns and Preferences, and the Workability of 
Competition in Radio Broadcasting, The Quarterly Journal of Economics, May 1952, 
194-223. 
Sweeting, Andrew (2006). Too Much Rock and Roll? Station Ownership, Programming 
and Listenership in the Music Radio Industry, Working Paper, Department of 
Economics, Northwestern University. 
   47
Tyler Mooney, Catherine (2007).  The Determinants and Effects of Market Structure in 
the Broadcasting Industry, Working Paper, Department of Economics, University of 
Virginia. 
Williams, George, Keith Brown, and Peter Alexander (2002). Radio Market Structure 
and Music Diversity, Working Paper, Media Bureau, Federal Communications 
Commission. 
Williams, George, and Keith Brown (2005), FCC Radio Market Structure and Music 
Diversity Paper, Working Paper, Media Bureau, Federal Communications Commission.  
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
  
Table 1 - 1997 Top Owners in 2005
Station Revenues Station Revenues
CBS (Name Change to Infinity in 2005) 160 1,529.40$      178                not reported
CHANCELOR MEDIA CORPORATION 108 996.00$         
JACOR COMMUNICATIONS 204 602.20$         
CAPSTAR BROADCASTING PARTNERS 299 537.70$         
CLEAR CHANNEL COMMUNICATIONS 196 452.30$         1,183             3,632$          
ABC RADIO 29 310.40$         71                  469.85$        
COX RADIO 59 not reported 78                  494.90$        
EMMIS BROADCASTING (Name Change to Emmis Communications in 1998) 13 156.70$         24                  315.53$        
HEFTEL BROADCASTING 39 155.50$         
SUSQUEHANNA RADIO 21 141.40$         
Notes:
Source: BIA 1997 and BIA 2006
1997 2005
 1. Became AMFM Inc. after series of mergers; Acquired by Clear Channel in 2000; http://www.fcc.gov/Bureaus/Mass_Media/ 
News_Releases/2000/nrmm0034.html. 
 2. Acquired by Clear Channel in August 2000; http://www.clearchannel.com/Radio/PressRelease.aspx?PressReleaseID=1599&p=hidden. 
Owner Name
Note 1
Note 2
Note 3
Note 4
Note 5
 3. Acquired by Chancellor Media Corporation in 1999. 
 4. Acquired by Clear Channel in 1996. 
 5. Acquired by Cumulus Media Partners LLC in 2005. 
 6. Revenues in 000,000. 
Table 2:  Largest Radio Station Owners in the U.S., 2005
1
# % Cumul. % #%
1 50152 Clear Channel Communications 1,183    10.9% 10.9% 0 0.0%
2 58079 Cumulus Broadcasting Inc 297       2.7% 13.7% 0 0.0%
3 50926 Citadel Broadcasting Corp 223       2.1% 15.7% 0 0.0%
4 58707 CBS Radio 178       1.6% 17.4% 0 0.0%
5 50975 Salem Communications Corporation 105       1.0% 18.3% 0 0.0%
6 50914 Entercom 103       1.0% 19.3% 0 0.0%
7 50295 Saga Communications Inc 86         0.8% 20.1% 0 0.0%
8 58103 Cox Radio Inc 78         0.7% 20.8% 0 0.0%
9 57059 Regent Communications, Inc 74         0.7% 21.5% 0 0.0%
10 50232 Univision Communications Inc 73         0.7% 22.2% 0 0.0%
11 50312 ABC/Disney 71         0.7% 22.8% 0 0.0%
12 61094 Radio One Inc 69         0.6% 23.4% 0 0.0%
13 67894 NRG Media LLC 59         0.5% 24.0% 0 0.0%
14 59062 NextMedia Group 58         0.5% 24.5% 0 0.0%
15 50308 Entravision Holdings LLC 52         0.5% 25.0% 0 0.0%
16 56751 Three Eagles Communications Incorporated 45         0.4% 25.4% 0 0.0%
17 52621 Nassau Broadcasting Partners LP 45         0.4% 25.8% 0 0.0%
18 52170 Multicultural Radio Broadcasting Inc 45         0.4% 26.3% 0 0.0%
19 58942 Triad Broadcasting Company 44         0.4% 26.7% 0 0.0%
20 62155 Cherry Creek Radio LLC 42         0.4% 27.0% 0 0.0%
21 50870 Beasley Broadcast Group 42         0.4% 27.4% 0 0.0%
22 51175 Midwest Communications Incorporated 39         0.4% 27.8% 0 0.0%
23 50180 Max Media LLC 37         0.3% 28.1% 0 0.0%
24 50115 Journal Communications Inc 37         0.3% 28.5% 0 0.0%
25 50010 Bonneville International Corp 37         0.3% 28.8% 0 0.0%
26 63288 Davidson Media Group LLC 37         0.3% 29.2% 0 0.0%
27 58728 New Northwest Broadcasters, LLC 36         0.3% 29.5% 0 0.0%
28 68144 Cumulus Media Partners LLC
2
36         0.3% 29.8% 0 0.0%
29 52283 MCC Radio LLC 33         0.3% 30.1% 0 0.0%
30 51427 Forever Broadcasting Incorporated 33         0.3% 30.4% 0 0.0%
31 61815 Qantum Communications Corp 31         0.3% 30.7% 0 0.0%
32 61657 Border Media Partners LLC 29         0.3% 31.0% 0 0.0%
33 50902 Crawford Broadcasting Company 29         0.3% 31.3% 0 0.0%
34 58729 Bicoastal Media LLC 27         0.2% 31.5% 0 0.0%
35 52290 Black Crow Media Group 27         0.2% 31.8% 0 0.0%
36 61484 Backyard Broadcasting 27         0.2% 32.0% 0 0.0%
37 51196 Access.1 Communications 27         0.2% 32.3% 1 0.0%
38 61279 Mapleton Communications LLC 26         0.2% 32.5% 0 0.0%
39 51907 Pamal Broadcasting Ltd 26         0.2% 32.7% 0 0.0%
40 61542 Bustos Media Enterprises LLC 26         0.2% 33.0% 0 0.0%
41 50955 Lotus Communications Corp 24         0.2% 33.2% 0 0.0%
42 67864 Double O Radio LLC 24         0.2% 33.4% 0 0.0%
43 51154 Fisher Radio Regional Group 24         0.2% 33.6% 0 0.0%
44 51037 Renda Broadcasting Corporation 24         0.2% 33.9% 0 0.0%
45 58400 Emmis Communications 24         0.2% 34.1% 0 0.0%
46 52121 Simmons Media Group Inc 24         0.2% 34.3% 0 0.0%
47 50864 American General Media 23         0.2% 34.5% 0 0.0%
48 59072 First Media 23         0.2% 34.7% 0 0.0%
49 57011 Commonwealth Broadcasting Corporation 23         0.2% 34.9% 0 0.0%
50 51176 Northeast Broadcasting Company 23         0.2% 35.2% 0 0.0%
51 50113 Withers Broadcasting Co 23         0.2% 35.4% 0 0.0%
52 50905 Cromwell Group Inc, The 22         0.2% 35.6% 0 0.0%
53 50163 Flinn Broadcasting Corporation 22         0.2% 35.8% 0 0.0%
54 50957 Mid-West Family Broadcast Group 22         0.2% 36.0% 16 0.6%
55 50885 Baker Family Stations 22         0.2% 36.2% 0 0.0%
Notes:
1. Numbers reflect all U.S. commercial and non-commercial radio stations.
Source: Ownership database (from FCC)
2. In October 2005, Cumulus Media Inc. (which ranks as the 943rd largest commercial radio owner) announced the purchase of 
Susquehana Radio.  The newly acquired stations would be owned and operated under the new Cumulus identity, Cumulus Media 
Partners LLC.  Cumulus Media Partners' count of commercial stations, reported here at 36, reflects the acquisition of 32 Susquehana 
stations and 4 Cumulus Broadcasting stations.
No. OwnerCode
Non-CommercialCommercial
Owner
Table 3 - Stations by Band and Format
Total AMFMAMFM
Religion 2,084           833 1251 767 335
Country 2,081           605 1476 603 1468
Adult Contemporary 1,514           172 1342 172 1302
News 1,147           883 264 861 60
Rock 836              38 798 34 589
Oldies 831              301 530 301 519
Spanish 739              381 358 374 314
Miscellaneous 640              121 519 116 51
Album Oriented Rock/Classic Rock 602              11 591 11 552
Contemporary Hit Radio/Top 40 488              11 477 10 428
Sports 465              432 33 432 33
Urban 421              86 335 86 316
Talk 419              346 73 343 57
Nostalgia/Big Band 373              314 59 312 45
Classical 302              8 294 6 27
Public/Educational 165              10 155 3 0
Jazz/New Age 151              8 143 6 70
Ethnic 116              86 30 86 18
Middle of the Road 75                60 15 60 12
Easy Listening/Beautiful Music 65                28 37 27 27
Total 13,514         4,734           8,780           4,610        6,223        
Source: Ownership Database (from FCC), Edison Airplay Database
Commercial & Non-Commercial Commercial
Format 20
Table 4: Market Level Descriptives
Commercial, In-Market, Edison Surveyed Stations
Mean Median Min Max N Mean Median Min Max N
Number of Commercial Stations 24.20 20 4 88 251 14.36 13 2 44 251
Number of Commercial Owners 10.15 8 1 36 251 6.29 6 1 18 251
Number of Stations Owned Nationally by Owners in Market 1,087.9       1,315            6                 2,241            251         731             895               2                 1,424            251
Percentage of Stations with Cross-Owned Newspaper in Market 0% 0% 0% 13% 251 0% 0% 0% 13% 251
Percentage of Stations with Cross-Owned TV Station in Market 7% 4% 0% 39% 251 8% 5% 0% 38% 251
Format 101 Count
1
14.94 14 4 37 251 10.35 10 2 25 251
Format 20 Count
2
10.70 11 3 18 251 7.44 7 2 14 251
Format 11 Count
3
8.04 8 3 11 251 6.47 7 2 10 251
Percent Local, AM Drive 68% 76% 0% 100% 165 78% 89% 0% 100% 100
Percent Network/Syndicated, AM Drive 30% 21% 0% 100% 165 20% 11% 0% 90% 100
Percent Live, AM Drive 61% 70% 0% 100% 165 67% 74% 0% 99% 100
Percent Advertisements, AM Drive 23% 23% 0% 59% 165 24% 24% 0% 56% 100
Percent Entertainment/Leisure/DJ Banter, AM Drive 23% 16% 0% 88% 165 24% 16% 0% 78% 100
Percent Music, AM Drive 31% 32% 0% 98% 165 41% 45% 0% 98% 100
Percent News, AM Drive 9% 5% 0% 43% 165 6% 4% 0% 39% 100
Percent Sports, AM Drive 6% 0% 0% 83% 165 1% 0% 0% 9% 100
Percent Local, Evening 71% 85% 0% 100% 169 84% 95% 0% 100% 114
Percent Network/Syndicated, Evening 26% 12% 0% 100% 169 13% 4% 0% 100% 114
Percent Live, Evening 65% 75% 0% 100% 169 74% 82% 0% 100% 114
Percent Advertisements, Evening 18% 18% 0% 48% 169 16% 16% 0% 45% 114
Percent Entertainment/Leisure/DJ Banter, Evening 8% 3% 0% 84% 169 6% 2% 0% 84% 114
Percent Music, Evening 52% 61% 0% 99% 169 70% 77% 0% 99% 114
Percent News, Evening 3% 0% 0% 45% 169 1% 0% 0% 19% 114
Percent Sports, Evening 12% 0% 0% 93% 169 4% 0% 0% 93% 114
Average Block, Advertisements, AM Drive 1.36 1.09 0 5.58 165 1.33 1.00 0 5.58 100
Average Block, Entertainment/Leisure/DJ Banter, AM Drive 2.18 1.31 0 17.63 165 2.04 1.34 0 15.17 100
Average Block, Music, AM Drive 1.91 2.05 0 8.44 165 2.49 2.69 0 8.44 100
Average Block, News, AM Drive 0.73 0.58 0 3.10 165 0.62 0.50 0 3.67 100
Average Block, Sports, AM Drive 0.64 0.00 0 7.29 165 0.16 0.00 0 2.00 100
Average Block, Advertisements, Evening 1.18 1.04 0 7.50 169 1.07 0.77 0 7.50 114
Average Block, Entertainment/Leisure/DJ Banter, Evening 0.82 0.25 0 7.39 169 0.62 0.28 0 6.25 114
Average Block, Music, Evening 2.57 2.90 0 11.53 169 3.23 3.25 0 11.53 114
Average Block, News, Evening 0.37 0.00 0 2.83 169 0.12 0.00 0 2.15 114
Average Block, Sports, Evening 0.99 0.00 0 13.08 169 0.34 0.00 0 8.23 114
Midwest Census Region 25% 251 25% 251
South Census Region 40% 251 40% 251
West Census Region 17% 251 17% 251
Notes:
1.  "Format 101 Count" counts the number of formats out of BIA's 101 format categories.  
2.  "Format 20 Count" counts the number of formats out of BIA's 20 format categories.  
3.  "Format 11 Count" collapses the 20 BIA format categories into 11 based on Andrew Sweeting's analysis of BIA's music formats.
4.  "Average Block" is measured in minutes.
Source : BIAfn, Ownership database (from FCC), SQAD, Arbitron, Census, Edison Airplay Database, Sweeting (2006)
Variable
All Stations FM Only Stations
Table 5:  Market Level Descriptives, Big versus Small Markets
All Commercial, In-Market, Edison Surveyed Stations
Big Markets, 30+ Stations Small Markets, 1-29 Stations
Mean Median Min Max N Mean Median Min Max N
Number of Commercial Stations 36 34 20 88 104 16 16 4 27 147
Number of Commercial Owners 15 14 5 36 104 6 7 1 14 147
Number of Stations Owned Nationally by Owners in Market 1,401         1,525         46 2,241    104 866 1,212         6 1,721    147
Percent of Stations with Cross-Owned Newspaper in Market 0.3% 0% 0% 5% 104 0.5% 0% 0% 13% 147
Percent of Stations with Cross-Owned TV Station in Market 9.0% 7% 0% 30% 104 5.0% 0% 0% 39% 147
Format 101 Count
1
20 20 12 37 104 11 11 4 17 147
Format 20 Count
2
13 13 9 18 104 9 9 3 13 147
Format 11 Count
3
9 9 6 11 104 7 7 3 10 147
Percent Local, AM Drive 71% 77% 0% 100% 82 65% 76% 0% 100% 83
Percent Network/Syndicated, AM Drive 26% 19% 0% 100% 82 33% 21% 0% 98% 83
Percent Live, AM Drive 63% 69% 0% 98% 82 60% 71% 0% 100% 83
Percent Advertisements, AM Drive 23% 23% 0% 56% 82 23% 24% 0% 59% 83
Percent Entertainment/Leisure/DJ Banter, AM Drive 23% 20% 0% 78% 82 22% 15% 0% 88% 83
Percent Music, AM Drive 32% 33% 0% 98% 82 30% 26% 0% 95% 83
Percent News, AM Drive 9% 5% 0% 43% 82 8% 5% 0% 41% 83
Percent Sports, AM Drive 7% 0% 0% 83% 82 6% 0% 0% 72% 83
Percent Local, Evening 72% 84% 1% 100% 83 70% 85% 0% 100% 86
Percent Network/Syndicated, Evening 24% 12% 0% 99% 83 27% 11% 0% 100% 86
Percent Live, Evening 65% 76% 0% 99% 83 64% 74% 0% 100% 86
Percent Advertisements, Evening 18% 19% 1% 48% 83 17% 18% 0% 45% 86
Percent Entertainment/Leisure/DJ Banter, Evening 9% 3% 0% 84% 83 7% 2% 0% 65% 86
Percent Music, Evening 52% 56% 0% 97% 83 52% 65% 0% 99% 86
Percent News, Evening 3% 0% 0% 45% 83 3% 0% 0% 21% 86
Percent Sports, Evening 11% 0% 0% 93% 83 12% 0% 0% 81% 86
Average Block, Advertisements, AM Drive 1.41 1.16 0.00 5.58 82 1.30 1.02 0.00 5.58 83
Average Block, Entertainment/Leisure/DJ Banter, AM Drive 2.22 1.64 0.00 15.50 82 2.14 1.12 0.00 17.63 83
Average Block, Music, AM Drive 1.97 2.05 0.00 8.44 82 1.85 2.00 0.00 4.97 83
Average Block, News, AM Drive 0.72 0.57 0.00 3.10 82 0.75 0.63 0.00 2.90 83
Average Block, Sports, AM Drive 0.63 0.00 0.00 7.29 82 0.65 0.00 0.00 7.00 83
Average Block, Advertisements, Evening 1.14 1.06 0.06 3.60 83 1.21 1.03 0.00 7.50 86
Average Block, Entertainment/Leisure/DJ Banter, Evening 0.84 0.31 0.00 7.39 83 0.79 0.22 0.00 6.49 86
Average Block, Music, Evening 2.46 2.71 0.00 11.53 83 2.66 3.13 0.00 7.04 86
Average Block, News, Evening 0.28 0.00 0.00 2.71 83 0.45 0.10 0.00 2.83 86
Average Block, Sports, Evening 0.93 0.00 0.00 7.47 83 1.04 0.00 0.00 13.08 86
Notes:
1.  "Format 101 Count" counts the number of formats out of BIA's 101 format categories.  
2.  "Format 20 Count" counts the number of formats out of BIA's 20 format categories.  
3.  "Format 11 Count" collapses the 20 BIA format categories into 11 based on Andrew Sweeting's analysis of BIA's music formats.
4.  "Average Block" is measured in minutes.
Source : BIAfn, Ownership database (from FCC), SQAD, Arbitron, Census, Edison Airplay Database, Sweeting (2006)
Variable
Table 6:  Station Level Descriptives
All Commercial, In-Market, Edison Surveyed Stations
Variable Mean Median Min Max N
Percent Local, AM Drive 0.70 0.85 0.00 1.00 255
Percent Network/Syndicated, AM Drive 0.28 0.14 0.00 1.00 255
Percent Live, AM Drive 0.61 0.72 0.00 1.00 255
Percent Advertisements, AM Drive 0.23 0.23 0.00 0.59 255
Percent Entertainment/Leisure/DJ Banter, AM Drive 0.22 0.11 0.00 0.99 255
Percent Music, AM Drive 0.30 0.23 0.00 0.98 255
Percent News, AM Drive 0.09 0.05 0.00 0.61 255
Percent Sports, AM Drive 0.06 0.00 0.00 0.83 255
Percent Local, Evening 0.71 0.90 0.00 1.00 281
Percent Network/Syndicated, Evening 0.26 0.09 0.00 1.00 281
Percent Live, Evening 0.65 0.78 0.00 1.00 281
Percent Advertisements, Evening 0.18 0.18 0.00 0.48 281
Percent Entertainment/Leisure/DJ Banter, Evening 0.08 0.01 0.00 0.93 281
Percent Music, Evening 0.51 0.69 0.00 1.00 281
Percent News, Evening 0.03 0.00 0.00 0.61 281
Percent Sports, Evening 0.11 0.00 0.00 0.93 281
Average Block, Advertisements, AM Drive 1.42 1.10 0.00 10.75 255
Average Block, Entertainment/Leisure/DJ Banter, AM Drive 2.11 1.00 0.00 17.63 255
Average Block, Music, AM Drive 1.89 2.22 0.00 8.44 255
Average Block, News, AM Drive 0.76 0.58 0.00 7.42 255
Average Block, Sports, AM Drive 0.59 0.00 0.00 7.29 255
Average Block, Advertisements, Evening 1.20 1.00 0.00 7.50 281
Average Block, Entertainment/Leisure/DJ Banter, Evening 0.82 0.18 0.00 11.25 281
Average Block, Music, Evening 2.55 2.97 0.00 20.00 281
Average Block, News, Evening 0.35 0.00 0.00 5.42 281
Average Block, Sports, Evening 0.95 0.00 0.00 13.08 281
Number of Syndicated Programs 1.34 0.00 0.00 19.00 569
Number of Personalities 2.93 2.00 0.00 21.00 569
Note :  "Average Block" is measured in minutes.
Source : Ownership database (from FCC), Edison Airplay Database
Table 7:  Distribution of Commercial, In-Market Stations Across Formats
No. Format 20
Edison Surveyed 
Stations All U.S. Stations
1 Country 13.9% 12.1%
2 News 12.5% 9.2%
3 Adult Contemporary 9.9% 11.4%
4 Sports 7.6% 5.4%
5 Spanish 7.4% 8.7%
6 Nostalgia/Big Band 7.0% 3.1%
7 Rock 6.9% 7.0%
8 Oldies 6.5% 6.1%
9 Talk 6.0% 4.3%
10 Album Oriented Rock/Classic Rock 5.6% 5.7%
11 Contemporary Hit Radio/Top 40 5.1% 5.6%
12 Religion 4.7% 10.8%
13 Urban 4.0% 5.3%
14 Ethnic 0.9% 1.3%
15 Middle of the Road 0.7% 0.5%
16 Miscellaneous 0.5% 1.6%
17 Classical 0.4% 0.4%
18 Easy Listening/Beautiful Music 0.4% 0.4%
19 Jazz/New Age 0.2% 1.0%
20 Public/Educational 0.0% 0.02%
Source: Ownership Database (from FCC), Edison Airplay Database
Table 8: Market Level Descriptives
Commercial, In-Market, Edison Surveyed Stations
Mean Median Min Max N Mean Median Min Max N
CPP, AM Drive 67 33 7 979 241 67 33 7 979 241
CPP, Evening 43 26 3 550 241 43 26 3 550 241
CPP, Average 61 31 7 859 241 61 31 7 859 241
CPM, AM Drive 12 10 4 44 241 12 10 4 44 241
CPM, Evening 10 7 3 52 241 10 7 3 52 241
CPM, Average 12 10 5 43 241 12 10 5 43 241
Average Rating 1% 1% 0% 3% 249 1% 1% 0% 3% 248
Average Rating, AM Drive 1% 1% 0% 5% 249 1% 1% 0% 5% 248
Average Rating, Evening 0% 0% 0% 1% 249 0% 0% 0% 1% 248
Population (000s) 910 355 69 18,230 250 910 355 69 18,230 250
EBI Per Capita ($) 18,279         17,895         9,926         34,326         250            18,279         17,895         9,926         34,326         250            
Percentage of Population White 79% 81% 46% 98% 250 79% 81% 46% 98% 250
Percentage of Population 25-34 13% 13% 9% 20% 250 13% 13% 9% 20% 250
Percentage of Population 35-44 14% 14% 10% 17% 250 14% 14% 10% 17% 250
Percentage of Population 45-64 24% 25% 15% 36% 250 24% 25% 15% 36% 250
Percentage of Population 65 and Over 13% 13% 7% 32% 250 13% 13% 7% 32% 250
Percentage of Population, College Graduates 25% 24% 12% 47% 244 25% 24% 12% 47% 244
Big Markets, 30+ Stations Small Markets, 1-29 Stations
Mean Median Min Max N Mean Median Min Max N
CPP, AM Drive 120 63 16 979 103 28 20 7 155 138
CPP, Evening 70 39 9 550 103 23 18 3 158 138
CPP, Average 107 56 15 859 103 27 20 7 159 138
CPM, AM Drive 10 9 6 27 103 14 13 4 44 138
CPM, Evening 6 6 3 21 103 13 10 3 52 138
CPM, Average 9 8 5 24 103 14 12 5 43 138
Average Rating 1% 1% 0% 1% 104 1% 1% 0% 3% 145
Average Rating, AM Drive 1% 1% 0% 2% 104 1% 1% 1% 5% 145
Average Rating, Evening 0% 0% 0% 0% 104 0% 0% 0% 1% 145
Population (000s) 1,805 1,005 226 18,230 104 273 213 69 1,201 146
EBI Per Capita ($) 19,414 19,095 13,203 27,819 104 17,471 16,965 9,926 34,326 146
Percentage of Population White 75% 77% 50% 97% 104 82% 85% 46% 98% 146
Percentage of Population 25-34 14% 14% 11% 18% 104 13% 13% 9% 20% 146
Percentage of Population 35-44 15% 15% 12% 17% 104 14% 14% 10% 17% 146
Percentage of Population 45-65 24% 25% 18% 29% 104 24% 25% 15% 36% 146
Percentage of Population Over 65 12% 12% 7% 24% 104 14% 13% 7% 32% 146
Percentege of Population, College Graduates 26% 26% 13% 44% 104 23% 22% 12% 47% 140
Source : BIAfn, Ownership database (from FCC), SQAD, Arbitron, Census, Edison Airplay Database
Variable
Variable
All Stations FM Only Stations
Table 9:  Station Level Descriptives
All Commercial, In-Market, Edison Surveyed Stations
Variable Mean Median Min Max N
CPP, AM Drive 106.73 44.00 8.00 979.00 555
CPP, Evening 63.06 30.00 3.00 550.00 555
CPP, Average 95.85 41.00 7.00 859.00 555
CPM, AM Drive 11.08 9.58 4.25 38.33 555
CPM, Evening 8.54 6.18 3.04 51.58 555
CPM, Average 10.55 8.99 4.86 34.84 555
Adult AQH Rating, AM Drive 1.13 0.78 0.00 11.57 427
Adult AQH Rating, Evening 0.28 0.21 0.00 2.54 417
Adult AQH Rating, Average 0.87 0.65 0.00 6.18 417
Number of Sisters in Market 3.05 3.00 0.00 10.00 569
Number of Commercial Stations in Market 30.07 27.00 4.00 88.00 569
Market HHI 0.16 0.15 0.04 1.00 569
Percentage of Stations with Cross-Owned Newspaper in Market 0.01 0.00 0.00 1.00 569
Percentage of Stations with Cross-Owned TV Station in Market 0.10 0.00 0.00 1.00 569
Number of Stations Owned Nationally by Owners in Market 272.68 37.00 1.00 1,243.00 569
Number of Markets in which Owner is Present 48.75 8.00 1.00 207.00 569
Population 2005 (000s) 1,571.67 558.50 69.20 18,230.20 567
EBI Per Capita 2005 ($) 18,808.38 18,624.01 9,926.10 27,819.23 567
Midwest Census Region 0.23 0.00 0.00 1.00 569
South Census Region 0.40 0.00 0.00 1.00 569
West Census Region 0.21 0.00 0.00 1.00 569
Northeast Census Region 0.17 0.00 0.00 1.00 569
Percentage of Population White 78% 80% 46% 98% 567
Percentage of Population 25-34 13% 13% 9% 20% 567
Percentage of Population 35-44 15% 15% 10% 17% 567
Percentage of Population 45-64 24% 25% 15% 36% 567
Percentage of Population 65 and Over 13% 12% 7% 32% 567
Percentage of Population, College Graduates 26% 25% 12% 47% 561
Source : Ownership database (from FCC), SQAD, Arbitron, Census, Edison Airplay Database
Table 10:  Market Level Summary of Formats, Stratified by HHIs
All Commercial, In-Market, Edison Surveyed Stations
Means for Stations in Markets with HHI in Range
Variable
Mean for 
All 
Stations
0 ? HHI < 1,000
[1]
1,000 ? HHI < 2,000
[2]
2,000 ? HHI < 3,000
[3]
3,000 ? HHI < 4,000
[4]
4,000 ? HHI
[5]
All
Format 101 Count 14.94 23.94 16.23 11.80 9.93 6.29 -17.66 -
Format 101 HHI 0.10 0.07 0.09 0.11 0.12 0.20 0.13 +
Format 20 Count 10.70 14.53 11.44 9.36 8.17 5.86 -8.67 -
Format 20 HHI 0.14 0.11 0.13 0.14 0.16 0.22 0.11 +
Format 11 Count 8.04 9.56 8.54 7.50 6.63 5.00 -4.56 -
Format 11 HHI 0.17 0.16 0.16 0.18 0.19 0.25 0.10 +
Number of Stations 24.20 47.68 26.00 16.85 13.00 8.57 -39.11 -
FM Only
Format 101 Count 10.35 15.50 11.24 8.64 7.03 4.29 -11.21 -
Format 101 HHI 0.14 0.09 0.12 0.14 0.18 0.30 0.21 +
Format 20 Count 7.44 9.97 7.87 6.66 5.80 3.86 -6.11 -
Format 20 HHI 0.19 0.15 0.17 0.19 0.22 0.34 0.19 +
Format 11 Count 6.47 8.24 6.84 5.93 5.20 3.43 -4.81 -
Format 11 HHI 0.21 0.17 0.20 0.22 0.24 0.36 0.19 +
Number of Stations 14.36 23.47 15.80 11.20 8.77 5.57 -17.90 -
Source: Ownership Database (from FCC), Edison Airplay Database
Effect of 
Consolidation?
[6] = [5]-[1]
Table 11: Market Level Regressions Estimating the Effect of Ownership Structure on Format
Commercial, In-Market, Edison Surveyed Stations
HHI Stations
Percent of Stations with 
Cross-Owned Newspaper
Percent of Stations with 
Cross-Owned TV Station
Number of Commercial 
Stations Owned Nationally by 
In-Market Owners
Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Adj R-Squared N
Format 101 Count -0.600 (0.18) 0.426 * (14.76) 3.682 (0.50) 2.235 (1.34) 0.000747 * (3.13) 0.878 251
Format 101 HHI -0.101 * (2.38) -0.003 * (8.16) -0.082 (-0.88) 0.012 (0.55) -0.000007 * (-2.38) 0.531 251
Format 20 Count 2.091 (0.86) 0.230 * (10.94) 3.411 (0.64) 0.761 (0.63) 0.000357 * (2.05) 0.740 251
Format 20 HHI -0.200 * (3.64) -0.004 * (7.54) -0.217 (-1.79) 0.031 (1.14) -0.000007 (-1.69) 0.404 251
Format 11 Count -0.354 (0.23) 0.103 * (7.60) 1.026 (0.30) -0.008 (-0.01) 0.000201 (1.80) 0.607 251
Format 11 HHI -0.173 * (3.09) -0.003 * (6.90) -0.221 (-1.79) 0.003 (0.09) -0.000003 (-0.73) 0.361 251
With Demographics:
Format 101 Count 3.399 (1.00) 0.405 * (13.68) 0.920 (0.13) 1.526 (0.93) 0.000426 (1.73) 0.892 244
Format 101 HHI -0.109 * (2.51) -0.003 * (7.03) -0.037 (-0.40) 0.002 (0.11) -0.000006 (-1.91) 0.582 244
Format 20 Count 4.374 (1.70) 0.208 * (9.31) 1.894 (0.35) 0.369 (0.30) 0.000159 (0.85) 0.751 244
Format 20 HHI -0.200 * (3.61) -0.003 * (6.61) -0.129 (-1.10) 0.022 (0.81) -0.000007 (-1.62) 0.491 244
Format 11 Count -0.212 (0.13) 0.090 * (6.34) 0.089 (0.03) 0.070 (0.09) 0.000105 (0.89) 0.638 244
Format 11 HHI -0.148 * (2.56) -0.003 * (5.75) -0.186 (-1.51) -0.005 (-0.18) -0.000003 (-0.68) 0.426 244
HHI Stations
Percent of Stations with 
Cross-Owned Newspaper
Percent of Stations with 
Cross-Owned TV Station
Number of Commercial 
Stations Owned Nationally by 
In-Market Owners
Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Adj R-Squared N
Format 101 Count 0.282 (0.14) 0.555 * (16.84) 0.4504 (0.06) 1.272 (1.15) 0.000812 * (3.21) 0.850 251
Format 101 HHI -0.087 * (1.96) -0.007 * (9.60) 0.0762 (0.49) -0.032 (-1.29) -0.000015 * (-2.73) 0.706 251
Format 20 Count -0.133 (0.08) 0.281 * (10.74) 1.9880 (0.36) 0.355 (0.40) 0.000307 (1.53) 0.687 251
Format 20 HHI -0.110 * (2.00) -0.007 * (8.09) -0.1562 (-0.81) -0.008 (-0.28) -0.000005 (-0.64) 0.592 251
Format 11 Count -0.926 (0.68) 0.202 * (8.99) -1.6748 (-0.35) 0.742 (0.99) 0.000269 (1.56) 0.629 251
Format 11 HHI -0.028 (0.49) -0.006 * (6.32) 0.0083 (0.04) -0.039 (-1.19) -0.000006 (-0.82) 0.537 251
With Demographics:
Format 101 Count 1.603 (0.81) 0.512 * (15.16) -3.8074 (-0.55) 0.751 (0.68) 0.000276 (1.02) 0.865 244
Format 101 HHI -0.105 * (2.43) -0.006 * (8.14) 0.1564 (1.03) -0.034 (-1.40) -0.000003 (-0.57) 0.742 244
Format 20 Count 0.038 (0.02) 0.237 * (8.95) -1.0067 (-0.19) 0.181 (0.21) -0.000123 (-0.58) 0.725 244
Format 20 HHI -0.117 * (2.14) -0.006 * (6.56) -0.0650 (-0.34) -0.016 (-0.51) 0.000006 (0.83) 0.634 244
Format 11 Count -0.554 (0.42) 0.170 * (7.55) -4.6768 (-1.02) 0.824 (1.12) -0.000092 (-0.51) 0.683 244
Format 11 HHI -0.039 (0.70) -0.005 * (5.09) 0.0882 (0.45) -0.047 (-1.50) 0.000006 (0.74) 0.624 244
Note :  Asterisk denotes statistical significance at least at the 5 percent level.  Each row summarizes the results of a single regression model.
Source : BIA, Ownership Database (from FCC), Edison Airplay Database, Sweeting (2006)
All Stations
Dependent Variable
FM Only Stations
Dependent Variable
Table 12: Market Level Regressions Estimating the Effect of Ownership Structure on Format, Big versus Small Markets
Commercial,  In-Market, Edison Surveyed Stations
HHI Stations
Percent of Stations with 
Cross-Owned Newspaper
Percent of Stations with 
Cross-Owned TV Station
Number of Commercial 
Stations Owned Nationally by 
In-Market Owners
Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Adj R-Squared N
Format 101 Count 2.867 (0.27) 0.296 * (5.96) 10.3716 (0.44) 1.871 (0.58) 0.001932 * (3.45) 0.726 104
Format 101 HHI -0.098 (1.17) -0.001 (1.45) -0.1761 (-0.95) 0.013 (0.51) -0.000011 * (-2.52) 0.072 104
Format 20 Count 1.226 (0.17) 0.116 * (3.55) 11.1151 (0.72) 0.578 (0.27) 0.000810 * (2.20) 0.426 104
Format 20 HHI -0.203 (1.94) -0.001 (1.79) -0.3479 (-1.52) 0.025 (0.80) -0.000008 (-1.42) 0.074 104
Format 11 Count -0.441 (0.13) 0.040 * (2.47) -4.0090 (-0.53) -1.588 (-1.53) 0.000417 * (2.31) 0.209 104
Format 11 HHI -0.219 * (2.23) -0.001 (1.55) -0.4659 * (-2.17) 0.020 (0.67) -0.000009 (-1.67) 0.035 104
With Demographics:
Format 101 Count 11.711 (1.10) 0.268 * (4.96) 11.8832 (0.50) 2.130 (0.64) 0.001146 (1.93) 0.763 104
Format 101 HHI -0.154 (1.76) -0.001 (1.39) -0.1049 (-0.54) 0.006 (0.22) -0.000007 (-1.37) 0.132 104
Format 20 Count 6.131 (0.83) 0.086 * (2.30) 12.1382 (0.74) -0.831 (-0.36) 0.000475 (1.16) 0.452 104
Format 20 HHI -0.245 * (2.36) -0.001 (1.54) -0.1909 (-0.82) 0.033 (1.03) -0.000008 (-1.37) 0.204 104
Format 11 Count -0.003 (0.00) 0.025 (1.42) -4.0104 (-0.51) -1.296 (-1.19) 0.000246 (1.27) 0.294 104
Format 11 HHI -0.221 * (2.13) -0.001 (1.46) -0.4641 * (-2.00) 0.014 (0.44) -0.000008 (-1.46) 0.056 104
HHI Stations
Percent of Stations with 
Cross-Owned Newspaper
Percent of Stations with 
Cross-Owned TV Station
Number of Commercial 
Stations Owned Nationally by 
In-Market Owners
Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Adj R-Squared N
Format 101 Count -3.743 (1.70) 0.454 * (11.64) 0.7515 (0.13) 1.269 (0.75) 0.000204 (0.98) 0.692 147
Format 101 HHI 0.022 (0.53) -0.005 * (6.22) -0.0513 (-0.45) 0.016 (0.48) -0.000005 (-1.18) 0.438 147
Format 20 Count -1.847 (0.95) 0.300 * (8.68) 1.2134 (0.23) 0.380 (0.25) 0.000119 (0.65) 0.548 147
Format 20 HHI -0.036 (0.63) -0.005 * (5.39) -0.1836 (-1.21) 0.033 (0.76) -0.000005 (-0.94) 0.345 147
Format 11 Count -3.079 * (2.09) 0.171 * (6.53) 0.8787 (0.22) 0.638 (0.57) 0.000109 (0.78) 0.488 147
Format 11 HHI -0.001 (0.02) -0.006 * (5.50) -0.1456 (-0.94) -0.006 (-0.13) 0.000000 (-0.01) 0.349 147
With Demographics:
Format 101 Count -2.902 (1.28) 0.421 * (9.84) 0.9066 (0.15) 0.822 (0.48) 0.000037 (0.16) 0.720 140
Format 101 HHI 0.018 (0.43) -0.004 * (4.96) -0.0530 (-0.46) 0.005 (0.15) -0.000005 (-1.18) 0.495 140
Format 20 Count -1.282 (0.62) 0.274 * (7.02) 0.4563 (0.08) 0.948 (0.60) -0.000069 (-0.33) 0.568 140
Format 20 HHI -0.029 (0.50) -0.005 * (4.85) -0.1312 (-0.86) 0.017 (0.39) -0.000005 (-0.92) 0.431 140
Format 11 Count -3.547 * (2.30) 0.137 * (4.71) 0.1767 (0.04) 0.652 (0.56) -0.000015 (-0.10) 0.530 140
Format 11 HHI 0.038 (0.65) -0.005 * (4.27) -0.1334 (-0.86) 0.001 (0.02) 0.000001 (0.09) 0.439 140
Note :  Asterisk denotes statistical significance at least at the 5 percent level.  Each row summarizes the results of a single regression model.
Source : BIA, Ownership Database (from FCC), Edison Airplay Database, Sweeting (2006)
Big Markets, 30+ Stations
Small Markets, 1-29 Stations
Dependent Variable
Dependent Variable
Table 13: Station Pair Summary of Formats, Stratified by Common Ownership and Market
All Commercial, In-Market, Edison Surveyed Stations
Same Market
[1]
Different Market
[2]
Same Market
[3]
Different Market
[4]
Same Format 11 5.8% 14.6% 18.2% 13.5% 13.4% 1.1% + 4.8% +
Same Format 20 0.0% 7.9% 11.5% 7.4% 7.9% 0.5% + 3.6% +
Same Format 101 0.0% 6.7% 8.7% 4.9% 5.7% 1.8% + 3.0% +
Same Format 11 15.4% 8.7% 20.9% 15.0% 15.1% -6.3% - 5.8% +
Same Format 20 11.9% 4.3% 18.3% 10.5% 11.5% -6.2% - 6.8% +
Same Format 101 7.0% 0.0% 10.7% 5.3% 6.8% -5.3% - 3.9% +
Source: BIA, Ownership Database (from FCC), Edison Airplay Database
Effect of Common Ownership?
Same Market
[5] = [1]-[3]
Different Market
[6] = [2]-[4]
FM Only Pairs
All Station PairsVariable
Different OwnersSame Owners
All 
Station 
Pairs
Table 14: Station Pair Probit Regressions Estimating the Effect of Ownership Structure on Format
Summary of the Marginal Effect of Same Owner Indicator
Marginal
Effect Z-Stat
Pseudo
R-Squared N
Marginal
Effect Z-Stat
Pseudo
R-Squared N
Marginal
Effect Z-Stat
Pseudo
R-Squared N # Mkts
Same Format 11 0.05 * (9.79) 0.0009 163,853 0.01 (0.27) 0.0001 739 0.12 (1.56) 0.0788 493 47
Same Format 20 0.04 * (8.77) 0.0010 163,853 0.005 (0.16) 0.0001 739 0.06 (0.91) 0.0934 425 34
Same Format 101 0.03 * (8.44) 0.0012 163,853 0.02 (0.65) 0.0016 739 0.13 (1.55) 0.1345 335 25
Marginal
Effect Z-Stat
Pseudo
R-Squared N
Marginal
Effect Z-Stat
Pseudo
R-Squared N
Marginal
Effect Z-Stat
Pseudo
R-Squared N # Mkts
Same Format 11 0.06 * (6.13) 0.0012 42,175   -0.06  (-0.95) 0.0057 156 -0.01  (-0.06) 0.1055 50 11
Same Format 20 0.07 * (7.59) 0.0023 42,175   -0.06  (-1.23) 0.0104 156 -0.01  (-0.06) 0.0903 50 11
Same Format 101 0.04 * (5.36) 0.0017 42,175   --------
Source: BIA, Ownership Database (from FCC), Edison Airplay Database, Sweeting (2006)
Note:  Asterisk denotes statistical significance at least at the 5 percent level.  Each row summarizes the results of a single regression model.  The effect of ownership 
structure on the likelihood of two stations being of the same Format 101 in the same market cannot be estimated due to insufficient sample size.
Dependent Variable
Dependent Variable
FM Only, In-Market, Edison Surveyed Stations
All Commercial, In-Market, Edison Surveyed Stations
Same Markets
[2]
All  Markets
[1]
Same Markets, 
With Market Fixed Effects
[3]
Table 15: Station Pair Probit Regressions Estimating the Effect of Ownership Structure on Format, Big versus Small Markets
All Commercial, In-Market, Edison Surveyed Stations
Summary of the Marginal Effect of Same Owner Indicator
With Market Fixed Effects
Marginal
Effect Z-Stat
Pseudo
R-Squared N # Mkts
Marginal
Effect Z-Stat
Pseudo
R-Squared N # Mkts
Marginal
Effect Z-Stat
Pseudo
R-Squared N # Mkts
Same Format 11 0.12 (1.56) 0.0788 493 47 0.06 (0.91) 0.077 452 36 0.69 * (3.07) 0.194 47 11
Same Format 20 0.06 (0.91) 0.0934 425 34 0.05 (0.80) 0.090 403 28 0.22 (0.53) 0.062 28 8
Same Format 101 0.13 (1.55) 0.1345 335 25 0.09 (1.28) 0.128 325 21 1.00 * (315.96) 0.275 16 5
Source:  BIA, Ownership Database (from FCC), Edison Airplay Database, Sweeting (2006)
Dependent Variable
Notes :  Asterisk denotes statistical significance at least at the 5 percent level.  FM Only results for big versus small excluded due to insufficient sample size.  
Small Markets, 1-29 StationsBig Markets, 30+ StationsSame Markets
Table 16:  Market Level Summary of Other Program Content Measures, Stratified by HHIs
Commercial, In-Market, Edison Surveyed Stations
Means for Stations in Markets with HHI in Range
Variable
Mean for 
All 
Stations
0 ? HHI < 1,000
[1]
1,000 ? HHI < 2,000
[2]
2,000 ? HHI < 3,000
[3]
3,000 ? HHI < 4,000
[4]
4,000 ? HHI
[5]
All Stations
Percent Local, AM Drive 0.68 0.65 0.72 0.65 0.63 0.68 0.03 +
Percent Network/Syndicated, AM Drive 0.30 0.34 0.25 0.34 0.34 0.32 -0.02 -
Percent Live, AM Drive 0.61 0.59 0.64 0.59 0.59 0.60 0.01 +
Percent Advertisements, AM Drive 0.23 0.23 0.22 0.24 0.21 0.27 0.04 +
Percent Entertainment/Leisure/DJ Banter, AM Drive 0.23 0.29 0.23 0.20 0.20 0.14 -0.15 -
Percent Music, AM Drive 0.31 0.28 0.32 0.30 0.30 0.42 0.14 +
Percent News, AM Drive 0.09 0.08 0.09 0.07 0.09 0.12 0.04 +
Percent Sports, AM Drive 0.06 0.06 0.07 0.06 0.03 0.03 -0.03 -
Percent Local, Evening 0.71 0.75 0.72 0.68 0.69 0.68 -0.07 -
Percent Network/Syndicated, Evening 0.26 0.22 0.23 0.29 0.31 0.32 0.10 +
Percent Live, Evening 0.65 0.68 0.64 0.64 0.60 0.77 0.09 +
Percent Advertisements, Evening 0.18 0.21 0.18 0.16 0.18 0.11 -0.10 -
Percent Entertainment/Leisure/DJ Banter, Evening 0.08 0.09 0.08 0.08 0.07 0.02 -0.07 -
Percent Music, Evening 0.52 0.50 0.55 0.49 0.44 0.60 0.10 +
Percent News, Evening 0.03 0.04 0.02 0.03 0.03 0.02 -0.01 -
Percent Sports, Evening 0.12 0.12 0.09 0.14 0.19 0.14 0.02 +
Average Block, Advertisements, AM Drive 1.36 1.71 1.27 1.37 1.01 1.63 -0.07 -
Average Block, Entertainment/Leisure/DJ Banter, AM Drive 2.18 2.73 2.36 1.54 2.64 0.63 -2.11 -
Average Block, Music, AM Drive 1.91 1.95 1.94 1.84 1.65 3.06 1.11 +
Average Block, News, AM Drive 0.73 0.57 0.84 0.63 0.74 0.88 0.30 +
Average Block, Sports, AM Drive 0.64 0.64 0.65 0.61 0.75 0.61 -0.02 -
Average Block, Advertisements, Evening 1.18 1.27 1.10 1.15 1.55 1.06 -0.22 -
Average Block, Entertainment/Leisure/DJ Banter, Evening 0.82 0.73 0.87 0.81 0.90 0.13 -0.60 -
Average Block, Music, Evening 2.57 2.77 2.60 2.40 2.44 2.95 0.18 +
Average Block, News, Evening 0.37 0.31 0.33 0.43 0.59 0.24 -0.07 -
Average Block, Sports, Evening 0.99 0.81 0.77 1.26 1.69 1.13 0.32 +
Number of Stations 24.20 47.68 26.00 16.85 13.00 8.57 -39.11 -
FM Only Stations
Percent Local, AM Drive 0.78 0.87 0.76 0.79 0.83 0.68 -0.18 -
Percent Network/Syndicated, AM Drive 0.20 0.13 0.21 0.21 0.17 0.32 0.18 +
Percent Live, AM Drive 0.67 0.74 0.66 0.66 0.64 0.60 -0.13 -
Percent Advertisements, AM Drive 0.24 0.25 0.23 0.23 0.26 0.27 0.01 +
Percent Entertainment/Leisure/DJ Banter, AM Drive 0.24 0.21 0.25 0.23 0.29 0.14 -0.07 -
Percent Music, AM Drive 0.41 0.50 0.37 0.42 0.38 0.42 -0.08 -
Percent News, AM Drive 0.06 0.03 0.07 0.06 0.07 0.12 0.09 +
Percent Sports, AM Drive 0.01 0.00 0.01 0.005 0.00 0.03 0.03 +
Percent Local, Evening 0.84 0.85 0.80 0.91 0.76 1.00 0.15 +
Percent Network/Syndicated, Evening 0.13 0.13 0.14 0.09 0.24 0.00 -0.13 -
Percent Live, Evening 0.74 0.73 0.71 0.79 0.65 0.93 0.20 +
Percent Advertisements, Evening 0.16 0.20 0.15 0.15 0.20 0.06 -0.14 -
Percent Entertainment/Leisure/DJ Banter, Evening 0.06 0.09 0.04 0.07 0.19 0.03 -0.06 -
Percent Music, Evening 0.70 0.67 0.67 0.75 0.61 0.89 0.22 +
Percent News, Evening 0.01 0.00 0.01 0.005 0.01 0.00 -0.002 -
Percent Sports, Evening 0.04 0.02 0.06 0.01 0.00 0.00 -0.02 -
Average Block, Advertisements, AM Drive 1.33 1.84 1.23 1.31 1.03 1.63 -0.21 -
Average Block, Entertainment/Leisure/DJ Banter, AM Drive 2.04 1.44 2.48 1.65 2.04 0.63 -0.82 -
Average Block, Music, AM Drive 2.49 3.18 2.33 2.51 2.00 3.06 -0.11 -
Average Block, News, AM Drive 0.62 0.39 0.70 0.56 0.59 0.88 0.48 +
Average Block, Sports, AM Drive 0.16 0.06 0.20 0.07 0.11 0.61 0.55 +
Average Block, Advertisements, Evening 1.07 1.19 0.91 1.17 2.28 0.63 -0.56 -
Average Block, Entertainment/Leisure/DJ Banter, Evening 0.62 0.84 0.42 0.69 1.97 0.20 -0.65 -
Average Block, Music, Evening 3.23 3.41 3.09 3.36 2.68 4.42 1.01 +
Average Block, News, Evening 0.12 0.03 0.17 0.09 0.27 0.00 -0.03 -
Average Block, Sports, Evening 0.34 0.18 0.54 0.11 0.00 0.00 -0.18 -
Number of Stations 14.36 23.47 15.80 11.20 8.77 5.57 -17.90 -
Source: Ownership Database (from FCC), Edison Airplay Database
Effect of 
Consolidation?
[6] = [5]-[1]
Table 17:  Market Level Regressions Estimating the Effect of Ownership Structure on Other Program Content Measures
All Commercial, In-Market, Edison Surveyed Stations
Statistically Signficant Results
HHI Stations
Percent of Stations with 
Cross-Owned Newspaper
Percent of Stations with 
Cross-Owned TV Station
Number of Commercial 
Stations Owned Nationally 
by In-Market Owners
Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Adj R-Squared N
Percent Local, AM Drive 0.5537 (0.73) 0.0032 (0.62) -0.3853 (-0.31) 0.7700 * (2.44) 0.000024 (0.53) 0.0126 165
Percent Network/Syndicated, AM Drive -0.4505 (0.61) -0.0031 (0.61) 0.6219 (0.51) -0.7086 * (-2.31) -0.000009 (-0.21) 0.0086 165
Percent Advertisements, AM Drive 0.0985 (0.38) 0.0002 (0.13) 0.0273 (0.06) 0.2759 * (2.52) -0.000007 (-0.47) 0.0108 165
Percent Entertainment/Leisure/DJ Banter, AM Drive -0.4551 (0.83) -0.0026 (0.70) 2.6298 * (2.90) -0.0113 (-0.05) 0.000090 * (2.73) 0.0580 165
Percent Sports, AM Drive -0.2897 (0.75) 0.0007 (0.26) -0.8431 (-1.32) -0.1345 (-0.83) -0.000064 * (-2.76) 0.0207 165
Percent Local, Evening -1.6863 * (2.17) -0.0085 (1.55) -0.7657 (-0.54) 0.2292 (0.77) -0.000038 (-0.81) -0.0020 169
Percent Network/Syndicated, Evening 1.6671 * (2.31) 0.0081 (1.60) 0.8858 (0.67) -0.1363 (-0.49) 0.000006 (0.14) 0.0034 169
Average Block, Music, Evening -8.9919 * (2.08) -0.0594 (1.95) -8.0426 (-1.01) 0.1339 (0.08) -0.000068 (-0.26) -0.0053 169
Average Block, Sports, Evening 12.1597 * (2.45) 0.0954 * (2.73) -2.7839 (-0.31) -2.6692 (-1.40) -0.000388 (-1.30) 0.0244 169
With Demographics:
Percent Advertisements, AM Drive 0.1565 (0.56) -0.0002 (0.10) -0.0097 (-0.02) 0.2625 * (2.23) -0.000008 (-0.47) -0.0381 161
Percent Entertainment/Leisure/DJ Banter, AM Drive -0.8221 (1.37) -0.0057 (1.35) 2.4257 * (2.53) -0.0354 (-0.14) 0.000096 * (2.64) 0.0589 161
Percent Sports, AM Drive -0.1603 (0.39) 0.0017 (0.58) -0.8116 (-1.23) 0.0064 (0.04) -0.000064 * (-2.56) 0.0673 161
Percent News, Evening 0.1985 (1.44) 0.0008 (0.83) 0.2831 (1.18) -0.1233 * (-2.42) 0.000000 (-0.05) 0.0883 164
Average Block, Entertainment/Leisure/DJ Banter, AM Drive -15.6691 * (2.06) -0.0675 (1.25) 34.1562 * (2.80) -3.8290 (-1.20) 0.000841 (1.82) 0.0474 161
Average Block, Music, Evening -9.6674 * (1.99) -0.0551 (1.59) -8.9634 (-1.06) -0.7137 (-0.40) -0.000015 (-0.05) -0.0375 164
Average Block, News, Evening 2.7455 (1.70) 0.0054 (0.47) 5.4568 (1.94) -1.2399 * (-2.08) -0.000011 (-0.11) 0.0409 164
Average Block, Sports, Evening 13.6651 * (2.50) 0.0743 (1.91) 0.6487 (0.07) -2.4003 (-1.19) -0.000611 (-1.80) 0.0366 164
Note :  Asterisk denotes statistical significance at least at the 5 percent level.  Each row summarizes the results of a single regression model.  See Table 17a for the full set of coefficients.
Source: Ownership Database (from FCC), Edison Airplay Database
Dependent Variable
Table 17a:  Market Level Regressions Estimating the Effect of Ownership Structure on Other Program Content Measures
All Commercial, In-Market, Edison Surveyed Stations
HHI Stations
Percent of Stations with 
Cross-Owned Newspaper
Percent of Stations with 
Cross-Owned TV Station
Number of Commercial 
Stations Owned Nationally by 
In-Market Owners
Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Adj R-Squared N
Percent Local, AM Drive 0.5537 (0.73) 0.0032 (0.62) -0.3853 (-0.31) 0.7700 * (2.44) 0.000024 (0.53) 0.0126 165
Percent Network/Syndicated, AM Drive -0.4505 (0.61) -0.0031 (0.61) 0.6219 (0.51) -0.7086 * (-2.31) -0.000009 (-0.21) 0.0086 165
Percent Live, AM Drive 0.2581 (0.39) 0.0020 (0.43) -1.4351 (-1.31) 0.3552 (1.28) -0.000022 (-0.56) -0.0161 165
Percent Advertisements, AM Drive 0.0985 (0.38) 0.0002 (0.13) 0.0273 (0.06) 0.2759 * (2.52) -0.000007 (-0.47) 0.0108 165
Percent Entertainment/Leisure/DJ Banter, AM Drive -0.4551 (0.83) -0.0026 (0.70) 2.6298 * (2.90) -0.0113 (-0.05) 0.000090 * (2.73) 0.0580 165
Percent Music, AM Drive 0.2264 (0.34) 0.0004 (0.08) -1.6975 (-1.53) 0.0622 (0.22) -0.000003 (-0.07) -0.0237 165
Percent News, AM Drive 0.1305 (0.56) 0.0011 (0.66) 0.6358 (1.64) 0.0643 (0.66) 0.000003 (0.25) -0.0134 165
Percent Sports, AM Drive -0.2897 (0.75) 0.0007 (0.26) -0.8431 (-1.32) -0.1345 (-0.83) -0.000064 * (-2.76) 0.0207 165
Percent Local, Evening -1.6863 * (2.17) -0.0085 (1.55) -0.7657 (-0.54) 0.2292 (0.77) -0.000038 (-0.81) -0.0020 169
Percent Network/Syndicated, Evening 1.6671 * (2.31) 0.0081 (1.60) 0.8858 (0.67) -0.1363 (-0.49) 0.000006 (0.14) 0.0034 169
Percent Live, Evening -0.8940 (1.30) -0.0053 (1.09) -0.1246 (-0.10) -0.1266 (-0.48) 0.000030 (0.71) -0.0163 169
Percent Advertisements, Evening -0.2276 (0.95) -0.0009 (0.53) 0.1473 (0.34) 0.0822 (0.90) 0.000001 (0.04) -0.0185 169
Percent Entertainment/Leisure/DJ Banter, Evening 0.4102 (1.15) 0.0023 (0.93) -0.8489 (-1.30) 0.0749 (0.55) -0.000012 (-0.56) 0.0340 169
Percent Music, Evening -1.5286 (1.89) -0.0093 (1.64) -0.9096 (-0.61) 0.1878 (0.60) -0.000028 (-0.57) -0.0115 169
Percent News, Evening 0.1167 (0.88) 0.0009 (1.01) 0.2722 (1.13) -0.0935 (-1.85) 0.000005 (0.60) -0.0074 169
Percent Sports, Evening 0.8596 (1.55) 0.0064 (1.63) -0.3343 (-0.33) -0.3462 (-1.62) -0.000004 (-0.11) -0.0054 169
Average Block, Advertisements, AM Drive -2.2022 (0.97) -0.0162 (1.04) -2.4554 (-0.65) 0.8560 (0.90) 0.000122 (0.89) 0.0206 165
Average Block, Entertainment/Leisure/DJ Banter, AM Drive -11.5482 (1.69) -0.0591 (1.25) 36.1875 * (3.20) -3.2451 (-1.13) 0.000728 (1.77) 0.0621 165
Average Block, Music, AM Drive -1.0256 (0.26) -0.0159 (0.58) -7.5466 (-1.14) 1.2490 (0.74) 0.000179 (0.74) -0.0204 165
Average Block, News, AM Drive 1.0363 (0.59) 0.0070 (0.58) 3.9749 (1.38) 0.1461 (0.20) -0.000091 (-0.87) -0.0205 165
Average Block, Sports, AM Drive -1.6682 (0.50) 0.0004 (0.02) -3.9202 (-0.71) -1.7066 (-1.22) -0.000275 (-1.36) -0.0171 165
Average Block, Advertisements, Evening 0.3211 (0.13) -0.0002 (0.01) -2.0275 (-0.44) 1.6795 (1.75) -0.000020 (-0.14) -0.0221 169
Average Block, Entertainment/Leisure/DJ Banter, Evening 2.2775 (0.64) 0.0096 (0.38) -8.0704 (-1.23) -0.0114 (-0.01) -0.000050 (-0.23) -0.0090 169
Average Block, Music, Evening -8.9919 * (2.08) -0.0594 (1.95) -8.0426 (-1.01) 0.1339 (0.08) -0.000068 (-0.26) -0.0053 169
Average Block, News, Evening 2.0215 (1.35) 0.0087 (0.83) 4.2657 (1.56) -0.8622 (-1.50) 0.000069 (0.77) -0.0016 169
Average Block, Sports, Evening 12.1597 * (2.45) 0.0954 * (2.73) -2.7839 (-0.31) -2.6692 (-1.40) -0.000388 (-1.30) 0.0244 169
With Demographics:
Percent Local, AM Drive 0.8570 (1.03) 0.0066 (1.12) -0.7900 (-0.59) 0.5229 (1.50) 0.000025 (0.50) -0.0302 161
Percent Network/Syndicated, AM Drive -0.7680 (0.96) -0.0070 (1.23) 1.1732 (0.91) -0.4603 (-1.37) -0.000010 (-0.20) -0.0094 161
Percent Live, AM Drive 0.5842 (0.80) 0.0053 (1.03) -1.9433 (-1.66) 0.2815 (0.92) -0.000037 (-0.83) -0.0364 161
Percent Advertisements, AM Drive 0.1565 (0.56) -0.0002 (0.10) -0.0097 (-0.02) 0.2625 * (2.23) -0.000008 (-0.47) -0.0381 161
Percent Entertainment/Leisure/DJ Banter, AM Drive -0.8221 (1.37) -0.0057 (1.35) 2.4257 * (2.53) -0.0354 (-0.14) 0.000096 * (2.64) 0.0589 161
Percent Music, AM Drive 0.4767 (0.64) 0.0035 (0.67) -1.4839 (-1.25) -0.1520 (-0.49) 0.000003 (0.07) -0.0657 161
Percent News, AM Drive 0.0993 (0.39) 0.0012 (0.67) 0.6661 (1.61) 0.0908 (0.84) 0.000004 (0.26) -0.0137 161
Percent Sports, AM Drive -0.1603 (0.39) 0.0017 (0.58) -0.8116 (-1.23) 0.0064 (0.04) -0.000064 * (-2.56) 0.0673 161
Percent Local, Evening -1.4686 (1.71) -0.0055 (0.89) -1.0313 (-0.69) 0.0698 (0.22) -0.000033 (-0.62) -0.0138 164
Percent Network/Syndicated, Evening 1.3656 (1.77) 0.0044 (0.81) 1.2251 (0.92) 0.0149 (0.05) -0.000002 (-0.04) 0.0582 164
Percent Live, Evening -1.4112 (1.90) -0.0064 (1.22) -0.0005 (-0.00) -0.1572 (-0.58) 0.000032 (0.69) 0.0107 164
Percent Advertisements, Evening -0.1253 (0.47) -0.0015 (0.79) -0.0585 (-0.13) 0.0660 (0.68) -0.000010 (-0.63) -0.0483 164
Percent Entertainment/Leisure/DJ Banter, Evening 0.0723 (0.19) 0.0025 (0.91) -0.8255 (-1.23) 0.1290 (0.90) -0.000008 (-0.34) 0.0127 164
Percent Music, Evening -1.6500 (1.81) -0.0058 (0.89) -1.2161 (-0.77) 0.1298 (0.39) 0.000002 (0.03) -0.0592 164
Percent News, Evening 0.1985 (1.44) 0.0008 (0.83) 0.2831 (1.18) -0.1233 * (-2.42) 0.000000 (-0.05) 0.0883 164
Percent Sports, Evening 0.9383 (1.55) 0.0046 (1.07) 0.0268 (0.03) -0.2838 (-1.27) -0.000013 (-0.34) -0.0004 164
Average Block, Advertisements, AM Drive -0.5314 (0.21) -0.0203 (1.13) -2.0355 (-0.50) 0.4556 (0.43) 0.000083 (0.54) -0.0257 161
Average Block, Entertainment/Leisure/DJ Banter, AM Drive -15.6691 * (2.06) -0.0675 (1.25) 34.1562 * (2.80) -3.8290 (-1.20) 0.000841 (1.82) 0.0474 161
Average Block, Music, AM Drive 1.9068 (0.43) -0.0034 (0.11) -4.9048 (-0.69) -0.1302 (-0.07) 0.000144 (0.53) -0.0689 161
Average Block, News, AM Drive 0.9254 (0.50) 0.0076 (0.57) 4.7581 (1.59) 0.2985 (0.38) -0.000085 (-0.75) 0.0212 161
Average Block, Sports, AM Drive -1.0400 (0.29) 0.0146 (0.58) -2.9481 (-0.52) -0.3340 (-0.23) -0.000205 (-0.96) 0.0751 161
Average Block, Advertisements, Evening -0.2326 (0.09) -0.0116 (0.66) -2.4954 (-0.58) 1.6611 (1.83) -0.000219 (-1.43) -0.0480 164
Average Block, Entertainment/Leisure/DJ Banter, Evening -0.8028 (0.20) 0.0090 (0.32) -8.3112 (-1.22) 0.2358 (0.16) -0.000040 (-0.16) -0.0623 164
Average Block, Music, Evening -9.6674 * (1.99) -0.0551 (1.59) -8.9634 (-1.06) -0.7137 (-0.40) -0.000015 (-0.05) -0.0375 164
Average Block, News, Evening 2.7455 (1.70) 0.0054 (0.47) 5.4568 (1.94) -1.2399 * (-2.08) -0.000011 (-0.11) 0.0409 164
Average Block, Sports, Evening 13.6651 * (2.50) 0.0743 (1.91) 0.6487 (0.07) -2.4003 (-1.19) -0.000611 (-1.80) 0.0366 164
Note :  Asterisk denotes statistical significance at least at the 5 percent level.  Each row summarizes the results of a single regression model.
Source: Ownership Database (from FCC), Edison Airplay Database
Dependent Variable
Table 18:  Market Level Regressions Estimating the Effect of Ownership Structure on Other Program Content Measures
FM Only, In-Market, Edison Surveyed Stations
Statistically Signficant Results
HHI Stations
Percent of Stations with 
Cross-Owned Newspaper
Percent of Stations with 
Cross-Owned TV Station
Number of Commercial 
Stations Owned 
Nationally by In-Market 
Owners
Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Adj R-Squared N
Percent Sports, AM Drive 0.0119 (0.31) 0.0006 (1.23) -0.0127 (-0.11) -0.0427 * (-2.31) 0.000002 (0.53) 0.1027 100
Percent News, Evening -0.1273 * (2.11) -0.0005 (0.69) -0.2752 (-1.31) -0.0276 (-1.13) -0.000020 * (-3.22) 0.0903 114
Average Block, Sports, AM Drive -0.5721 (0.63) 0.0027 (0.24) 0.1326 (0.05) -0.8613 * (-1.99) -0.000030 (-0.28) 0.0537 100
Average Block, Music, Evening -6.3285 (1.67) -0.0988 * (2.14) -0.8090 (-0.06) -2.0792 (-1.35) 0.000183 (0.47) 0.0389 114
Average Block, News, Evening -1.3116 (1.71) -0.0055 (0.58) -4.2009 (-1.58) -0.3169 (-1.02) -0.000295 * (-3.75) 0.1094 114
With Demographics:
Percent News, AM Drive -0.0253 (0.15) 0.0026 (1.19) 1.3032 * (2.35) 0.2431 * (2.75) -0.000030 (-1.39) 0.2061 98
Percent News, Evening -0.1357 * (2.20) -0.0005 (0.66) -0.1654 (-0.78) -0.0140 (-0.56) -0.000020 * (-2.93) 0.2206 112
Average Block, Music, Evening -4.3478 (1.06) -0.1492 * (2.82) -3.8024 (-0.27) -3.7502 * (-2.23) -0.000001 (-0.00) 0.0301 112
Average Block, News, Evening -1.2998 (1.72) -0.0034 (0.35) -3.2743 (-1.26) -0.1307 (-0.42) -0.000283 * (-3.38) 0.2903 112
Source: Ownership Database (from FCC), Edison Airplay Database
Note:  Asterisk denotes statistical significance at least at the 5 percent level.  Each row summarizes the results of a single regression model. See Table 18a for the full set of coefficients.
Dependent Variable
Table 18a:  Market Level Regressions Estimating the Effect of Ownership Structure on Other Program Content Measures
FM Only, In-Market, Edison Surveyed Stations
HHI Stations
Percent of Stations with 
Cross-Owned Newspaper
Percent of Stations with 
Cross-Owned TV Station
Number of Commercial 
Stations Owned Nationally by 
In-Market Owners
Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Adj R-Squared N
Percent Local, AM Drive 0.8007 (1.32) 0.0106 (1.39) 0.2772 (0.15) 0.3590 (1.25) -0.000038 (-0.53) -0.0209 100
Percent Network/Syndicated, AM Drive -0.5003 (0.91) -0.0101 (1.45) 0.0628 (0.04) -0.2747 (-1.05) 0.000090 (1.40) -0.0080 100
Percent Live, AM Drive 0.7511 (1.24) 0.0091 (1.19) -0.1219 (-0.07) 0.1619 (0.56) -0.000011 (-0.15) -0.0440 100
Percent Advertisements, AM Drive 0.0730 (0.27) -0.0009 (0.27) 0.4078 (0.49) 0.1527 (1.17) -0.000027 (-0.84) 0.0432 100
Percent Entertainment/Leisure/DJ Banter, AM Drive 0.4580 (0.85) 0.0018 (0.26) -0.3997 (-0.25) 0.1144 (0.45) 0.000099 (1.58) -0.0153 100
Percent Music, AM Drive -0.4469 (0.67) -0.0004 (0.04) -0.0049 (-0.00) -0.2926 (-0.92) -0.000004 (-0.06) -0.0534 100
Percent News, AM Drive 0.2950 (1.75) 0.0020 (0.96) 0.8740 (1.71) 0.0461 (0.57) -0.000009 (-0.46) 0.0353 100
Percent Sports, AM Drive 0.0119 (0.31) 0.0006 (1.23) -0.0127 (-0.11) -0.0427 * (-2.31) 0.000002 (0.53) 0.1027 100
Percent Local, Evening 0.0924 (0.12) -0.0018 (0.19) 3.0242 (1.18) 0.2102 (0.70) -0.000034 (-0.45) -0.0119 114
Percent Network/Syndicated, Evening -0.4731 (0.78) -0.0028 (0.38) -2.7553 (-1.31) -0.0157 (-0.06) -0.000031 (-0.51) 0.0120 114
Percent Live, Evening 0.3515 (0.50) 0.0034 (0.40) 1.8213 (0.75) 0.1103 (0.39) 0.000006 (0.08) -0.0232 114
Percent Advertisements, Evening -0.4042 (1.50) -0.0044 (1.34) 0.4965 (0.53) 0.1556 (1.43) -0.000013 (-0.47) -0.0072 114
Percent Entertainment/Leisure/DJ Banter, Evening 0.3985 (1.19) 0.0007 (0.18) -1.0350 (-0.89) 0.0295 (0.22) 0.000022 (0.63) 0.1007 114
Percent Music, Evening -0.0055 (0.01) -0.0039 (0.45) 1.9243 (0.79) -0.0725 (-0.25) 0.000020 (0.28) -0.0147 114
Percent News, Evening -0.1273 * (2.11) -0.0005 (0.69) -0.2752 (-1.31) -0.0276 (-1.13) -0.000020 * (-3.22) 0.0903 114
Percent Sports, Evening -0.1516 (0.36) 0.0034 (0.66) -0.7527 (-0.52) 0.0067 (0.04) -0.000004 (-0.10) -0.0344 114
Average Block, Advertisements, AM Drive -2.1269 (0.87) -0.0274 (0.89) 0.9645 (0.13) -0.4389 (-0.38) 0.000291 (1.02) 0.0604 100
Average Block, Entertainment/Leisure/DJ Banter, AM Drive -1.6632 (0.29) 0.0128 (0.17) 3.0252 (0.17) -0.2785 (-0.10) 0.000677 (0.99) -0.0265 100
Average Block, Music, AM Drive -2.9007 (0.74) -0.0269 (0.55) 3.7116 (0.31) -1.7483 (-0.94) 0.000468 (1.02) -0.0439 100
Average Block, News, AM Drive 1.2358 (0.75) 0.0127 (0.61) 4.3084 (0.86) 0.3669 (0.47) -0.000215 (-1.11) -0.0393 100
Average Block, Sports, AM Drive -0.5721 (0.63) 0.0027 (0.24) 0.1326 (0.05) -0.8613 * (-1.99) -0.000030 (-0.28) 0.0537 100
Average Block, Advertisements, Evening -0.4363 (0.14) -0.0304 (0.81) -3.9987 (-0.37) 1.8923 (1.51) 0.000005 (0.02) -0.0279 114
Average Block, Entertainment/Leisure/DJ Banter, Evening 2.5794 (0.85) -0.0124 (0.33) -8.1034 (-0.77) 0.3907 (0.32) 0.000402 (1.29) 0.0451 114
Average Block, Music, Evening -6.3285 (1.67) -0.0988 * (2.14) -0.8090 (-0.06) -2.0792 (-1.35) 0.000183 (0.47) 0.0389 114
Average Block, News, Evening -1.3116 (1.71) -0.0055 (0.58) -4.2009 (-1.58) -0.3169 (-1.02) -0.000295 * (-3.75) 0.1094 114
Average Block, Sports, Evening -3.6979 (1.04) 0.0114 (0.26) -8.8459 (-0.72) -0.3708 (-0.26) -0.000337 (-0.93) -0.0191 114
With Demographics:
Percent Local, AM Drive 1.1783 (1.76) 0.0101 (1.15) 0.8603 (0.39) 0.1060 (0.30) -0.000046 (-0.54) -0.0435 98
Percent Network/Syndicated, AM Drive -0.8749 (1.44) -0.0105 (1.32) -0.2946 (-0.15) -0.0155 (-0.05) 0.000094 (1.21) -0.0318 98
Percent Live, AM Drive 0.9344 (1.39) 0.0056 (0.63) -0.6076 (-0.27) 0.0287 (0.08) -0.000048 (-0.56) -0.1003 98
Percent Advertisements, AM Drive 0.0665 (0.21) -0.0006 (0.14) -0.2077 (-0.20) 0.0752 (0.46) -0.000030 (-0.77) 0.0017 98
Percent Entertainment/Leisure/DJ Banter, AM Drive 0.2976 (0.52) -0.0047 (0.63) -0.9686 (-0.52) 0.2286 (0.76) 0.000076 (1.04) 0.0383 98
Percent Music, AM Drive 0.2951 (0.41) 0.0026 (0.28) 1.1780 (0.50) -0.6583 (-1.76) 0.000055 (0.60) -0.0089 98
Percent News, AM Drive -0.0253 (0.15) 0.0026 (1.19) 1.3032 * (2.35) 0.2431 * (2.75) -0.000030 (-1.39) 0.2061 98
Percent Sports, AM Drive -0.0151 (0.35) 0.0010 (1.68) 0.0642 (0.45) -0.0327 (-1.44) 0.000006 (1.08) 0.0932 98
Percent Local, Evening 0.7840 (1.00) -0.0109 (1.07) 2.3377 (0.87) -0.2373 (-0.74) -0.000074 (-0.85) 0.0222 112
Percent Network/Syndicated, Evening -0.9349 (1.57) 0.0052 (0.68) -1.2364 (-0.60) 0.2828 (1.16) -0.000018 (-0.27) 0.1509 112
Percent Live, Evening 0.4082 (0.60) -0.0054 (0.61) 2.4932 (1.06) -0.1888 (-0.67) -0.000004 (-0.05) 0.1272 112
Percent Advertisements, Evening -0.4107 (1.42) -0.0060 (1.60) -0.1071 (-0.11) 0.1326 (1.12) -0.000053 (-1.65) -0.0159 112
Percent Entertainment/Leisure/DJ Banter, Evening 0.2117 (0.62) 0.0043 (0.98) -0.7187 (-0.62) 0.1299 (0.93) 0.000011 (0.30) 0.1015 112
Percent Music, Evening 0.5559 (0.74) -0.0114 (1.18) 1.4900 (0.58) -0.4118 (-1.34) 0.000027 (0.32) -0.0090 112
Percent News, Evening -0.1357 * (2.20) -0.0005 (0.66) -0.1654 (-0.78) -0.0140 (-0.56) -0.000020 * (-2.93) 0.2206 112
Percent Sports, Evening -0.5656 (1.22) 0.0056 (0.93) -0.0054 (-0.00) 0.1860 (0.98) 0.000009 (0.18) -0.0536 112
Average Block, Advertisements, AM Drive -1.1853 (0.44) -0.0332 (0.94) -6.9594 (-0.79) -0.9389 (-0.67) 0.000211 (0.61) 0.0695 98
Average Block, Entertainment/Leisure/DJ Banter, AM Drive -2.7306 (0.42) -0.0181 (0.21) -5.1063 (-0.24) 0.8782 (0.26) 0.000836 (1.01) -0.0319 98
Average Block, Music, AM Drive -1.2510 (0.28) -0.0269 (0.47) 8.6750 (0.60) -3.1237 (-1.35) 0.000491 (0.87) -0.1021 98
Average Block, News, AM Drive -0.7098 (0.40) 0.0185 (0.80) 7.1809 (1.23) 1.5244 (1.64) -0.000299 (-1.32) 0.0220 98
Average Block, Sports, AM Drive -1.0466 (1.02) 0.0093 (0.68) 1.6708 (0.49) -0.7564 (-1.40) 0.000024 (0.18) 0.0166 98
Average Block, Advertisements, Evening -1.4973 (0.51) -0.0331 (0.86) -9.8844 (-0.97) 2.1885 (1.80) -0.000442 (-1.35) -0.0828 112
Average Block, Entertainment/Leisure/DJ Banter, Evening 1.5856 (0.51) 0.0073 (0.18) -7.7822 (-0.73) 0.8944 (0.70) 0.000258 (0.75) -0.0312 112
Average Block, Music, Evening -4.3478 (1.06) -0.1492 * (2.82) -3.8024 (-0.27) -3.7502 * (-2.23) -0.000001 (-0.00) 0.0301 112
Average Block, News, Evening -1.2998 (1.72) -0.0034 (0.35) -3.2743 (-1.26) -0.1307 (-0.42) -0.000283 * (-3.38) 0.2903 112
Average Block, Sports, Evening -7.5710 (1.95) 0.0250 (0.50) -0.4381 (-0.03) 1.3327 (0.83) -0.000221 (-0.51) -0.0108 112
Source:  Ownership Database (from FCC), Edison Airplay Database
Note :  Asterisk denotes statistical significance at least at the 5 percent level.  Each row summarizes the results of a single regression model.
Dependent Variable
Table 19:  Station Level Descriptives for Other Measures of Programming Content, Stratified by Common Ownership
Commercial, In-Market, Edison Surveyed Stations
All
[1]
Stations with
No Sisters
[2]
Stations with At 
Least One Sister
[3]
All
[5]
Stations with 
No Sisters
[6]
Stations with at 
least One Sister
[7]
Percent Local, AM Drive 0.70 0.72 0.69 -0.02 - 0.79 0.79 0.79 -0.003 -
Percent Network/Syndicated, AM Drive 0.28 0.26 0.29 0.04 + 0.20 0.15 0.21 0.06 +
Percent Live, AM Drive 0.61 0.65 0.61 -0.04 - 0.67 0.69 0.67 -0.02 -
Percent Advertisements, AM Drive 0.23 0.21 0.24 0.03 + 0.23 0.20 0.24 0.04 +
Percent Entertainment/Leisure/DJ Banter, AM Drive 0.22 0.20 0.23 0.03 + 0.24 0.17 0.25 0.08 +
Percent Music, AM Drive 0.30 0.31 0.30 -0.01 - 0.41 0.39 0.41 0.02 +
Percent News, AM Drive 0.09 0.08 0.09 0.02 + 0.06 0.08 0.06 -0.02 -
Percent Sports, AM Drive 0.06 0.06 0.06 -0.01 - 0.01 0.01 0.01 0.00 -
Percent Local, Evening 0.71 0.71 0.71 0.00 + 0.86 0.84 0.86 0.02 +
Percent Network/Syndicated, Evening 0.26 0.23 0.26 0.03 + 0.11 0.11 0.12 0.01 +
Percent Live, Evening 0.65 0.62 0.66 0.03 + 0.76 0.68 0.77 0.09 +
Percent Advertisements, Evening 0.18 0.17 0.18 0.01 + 0.16 0.15 0.16 0.02 +
Percent Entertainment/Leisure/DJ Banter, Evening 0.08 0.10 0.07 -0.03 - 0.06 0.05 0.06 0.01 +
Percent Music, Evening 0.51 0.50 0.52 0.01 + 0.71 0.72 0.71 -0.01 -
Percent News, Evening 0.03 0.03 0.03 0.00 - 0.01 0.02 0.01 -0.01 -
Percent Sports, Evening 0.11 0.08 0.12 0.04 + 0.03 0.00 0.04 0.03 +
Average Block, Advertisements, AM Drive 1.42 1.52 1.40 -0.12 - 1.36 1.22 1.38 0.16 +
Average Block, Entertainment/Leisure/DJ Banter, AM Drive 2.11 1.63 2.21 0.58 + 2.11 1.46 2.20 0.74 +
Average Block, Music, AM Drive 1.89 1.87 1.90 0.03 + 2.50 2.26 2.54 0.28 +
Average Block, News, AM Drive 0.76 0.67 0.78 0.11 + 0.63 0.72 0.61 -0.11 -
Average Block, Sports, AM Drive 0.59 0.61 0.58 -0.03 - 0.16 0.25 0.14 -0.11 -
Average Block, Advertisements, Evening 1.20 1.20 1.20 0.00 - 1.02 1.04 1.02 -0.02 -
Average Block, Entertainment/Leisure/DJ Banter, Evening 0.82 1.10 0.77 -0.33 - 0.57 0.79 0.54 -0.24 -
Average Block, Music, Evening 2.55 2.79 2.51 -0.28 - 3.29 3.58 3.25 -0.33 -
Average Block, News, Evening 0.35 0.44 0.33 -0.10 - 0.12 0.27 0.10 -0.17 -
Average Block, Sports, Evening 0.95 0.50 1.03 0.53 + 0.29 0.14 0.31 0.17 +
Number of Syndicated Programs 1.34 0.98 1.41 0.43 + 0.64 0.67 0.64 -0.03 -
Number of Personalities 2.93 2.45 3.03 0.58 + 3.60 2.93 3.71 0.78 +
Note:  Asterisk denotes statistical significance at least at the 5 percent level.  Each row summarizes the results of a single regression model.
Source: Ownership Database (from FCC), Edison Airplay Database
Variable
Effect of Common 
Ownership?
[4] = [3]-[2]
All Stations FM Only Stations
Effect of Common 
Ownership?
[8] = [7]-[6]
Table 20:  Station Level Regressions Estimating the Effect of Ownership Structure on Other Program Content Measures
All Commercial, In-Market, Edison Surveyed Stations
Includes Demographics and Station Characteristics
HHI Sisters
Newspaper Cross-
Ownership
Television Cross-
Ownership
Number of Stations Owned 
Nationally by Owner
Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Adj R-Squared N
Percent Local, AM Drive 0.0464 (0.06) -0.0191 (1.48) -0.1720 (-0.72) 0.0731 (1.11) 0.0000 (0.65) 0.0532 250
Percent Network/Syndicated, AM Drive -0.2566 (0.32) 0.0202 (1.63) 0.1906 (0.83) -0.0637 (-1.00) 0.0000 (-0.61) 0.0652 250
Percent Live, AM Drive 0.0122 (0.02) -0.0155 (1.34) -0.1974 (-0.92) 0.0563 (0.95) 0.0000 (-0.18) 0.0237 250
Percent Advertisements, AM Drive -0.1182 (0.38) 0.0073 (1.53) -0.0399 (-0.45) 0.0240 (0.98) 0.0000 (0.02) 0.0034 250
Percent Entertainment/Leisure/DJ Banter, AM Drive -0.2546 (0.39) -0.0011 (0.11) 0.2487 (1.32) -0.0219 (-0.42) 0.0000 (0.74) -0.0053 250
Percent Music, AM Drive -0.1036 (0.14) -0.0072 (0.62) -0.1191 (-0.55) 0.0034 (0.06) 0.0000 (0.55) 0.0969 250
Percent News, AM Drive -0.1415 (0.47) -0.0009 (0.18) -0.0017 (-0.02) -0.0024 (-0.10) 0.0000 (-0.73) 0.0958 250
Percent Sports, AM Drive -0.3178 (0.79) 0.0040 (0.64) -0.0224 (-0.19) 0.0297 (0.93) 0.0000 (-0.09) 0.1134 250
Percent Local, Evening -2.2108 * (2.70) 0.0133 (1.08) -0.2488 (-1.06) 0.0801 (1.25) -0.0001 (-1.79) 0.2144 276
Percent Network/Syndicated, Evening 1.9245 * (2.51) -0.0085 (0.73) 0.2294 (1.05) -0.0549 (-0.92) 0.0001 * (2.33) 0.2540 276
Percent Live, Evening -1.7999 * (2.38) 0.0004 (0.03) -0.1748 (-0.81) 0.0821 (1.39) 0.0000 (0.44) 0.1667 276
Percent Advertisements, Evening -0.3518 (1.27) 0.0076 (1.80) 0.0253 (0.32) -0.0212 (-0.98) 0.0000 (-0.55) 0.0401 276
Percent Entertainment/Leisure/DJ Banter, Evening 0.0471 (0.10) 0.0000 (0.00) -0.0724 (-0.55) -0.0030 (-0.08) 0.0000 (0.06) -0.0315 276
Percent Music, Evening -1.8120 * (2.34) 0.0120 (1.02) -0.0628 (-0.28) -0.0138 (-0.23) -0.0001 (-1.51) 0.3553 276
Percent News, Evening 0.0460 (0.30) 0.0010 (0.45) 0.0406 (0.92) -0.0030 (-0.25) 0.0000 (-0.37) 0.1381 276
Percent Sports, Evening 1.1875 (1.92) -0.0139 (1.49) -0.1275 (-0.72) 0.0867 (1.80) 0.0001 (1.76) 0.1494 276
Average Block, Advertisements, AM Drive -0.3488 (0.11) 0.0394 (0.77) -0.9434 (-1.00) 0.1923 (0.74) -0.0003 (-1.63) 0.0093 250
Average Block, Entertainment/Leisure/DJ Banter, AM Drive -4.2684 (0.56) 0.0226 (0.19) 6.0971 * (2.79) -0.3916 (-0.65) 0.0003 (0.60) 0.0232 250
Average Block, Music, AM Drive -0.4603 (0.10) -0.0554 (0.80) -0.7444 (-0.58) -0.3532 (-0.99) 0.0001 (0.50) 0.1028 250
Average Block, News, AM Drive 0.5016 (0.21) -0.0354 (0.98) 0.4232 (0.63) -0.2843 (-1.54) 0.0000 (-0.13) 0.0614 250
Average Block, Sports, AM Drive -1.5018 (0.45) -0.0109 (0.21) 0.2139 (0.22) 0.1651 (0.62) 0.0001 (0.28) 0.1356 250
Average Block, Advertisements, Evening -0.5371 (0.21) 0.0377 (0.96) 0.1696 (0.23) -0.1865 (-0.92) -0.0001 (-0.86) 0.0337 276
Average Block, Entertainment/Leisure/DJ Banter, Evening -1.3518 (0.28) 0.0102 (0.14) -0.7022 (-0.52) -0.2472 (-0.66) 0.0001 (0.36) -0.0307 276
Average Block, Music, Evening -7.5304 (1.49) -0.0310 (0.41) -0.7064 (-0.49) -0.2580 (-0.65) -0.0007 * (-2.22) 0.1788 276
Average Block, News, Evening 2.8603 (1.67) -0.0276 (1.06) 1.0977 * (2.23) -0.0870 (-0.65) 0.0001 (1.06) 0.1372 276
Average Block, Sports, Evening 14.3771 * (2.63) -0.0751 (0.91) -0.8603 (-0.55) 0.5272 (1.24) 0.0002 (0.74) 0.1124 276
Number of Syndicated Programs 5.4206 (1.43) 0.0010 (0.02) 0.4993 (0.38) -0.2558 (-0.78) 0.0006 * (2.37) 0.1367 561
Number of Personalities -3.0812 (0.57) -0.0097 (0.13) 1.3210 (0.71) 0.6883 (1.47) 0.0001 (0.26) 0.1177 561
Note :  Asterisk denotes statistical significance at least at the 5 percent level.
Source:  Ownership Database (from FCC), Edison Airplay Database
Dependent Variable
Table 21:  Station Level Regressions Estimating the Effect of Ownership Structure on Other Program Content Measures
FM Only, In-Market, Edison Surveyed Stations
Includes Demographics and Station Characteristics
HHI Sisters
Television Cross-
Ownership
Number of Stations Owned 
Nationally by Owner
Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Adj R-Squared N
Percent Local, AM Drive 0.8983 (1.23) -0.0233 (1.11) 0.0411 (0.49) 0.0001 (0.63) -0.0224 120
Percent Network/Syndicated, AM Drive -0.7446 (1.09) 0.0307 (1.57) -0.0517 (-0.66) -0.0001 (-0.79) -0.0100 120
Percent Live, AM Drive 1.0278 (1.38) -0.0450 * (2.09) 0.0250 (0.29) 0.0001 (0.66) -0.0544 120
Percent Advertisements, AM Drive -0.0969 (0.28) 0.0119 (1.19) -0.0152 (-0.38) 0.0000 (-0.39) -0.0413 120
Percent Entertainment/Leisure/DJ Banter, AM Drive 0.0043 (0.01) 0.0324 (1.72) 0.0974 (1.30) 0.0000 (-0.53) 0.0760 120
Percent Music, AM Drive -0.1942 (0.24) -0.0003 (0.01) -0.0953 (-1.01) 0.0001 (0.66) -0.0073 120
Percent News, AM Drive 0.2084 (1.13) -0.0187 * (3.53) 0.0096 (0.46) 0.0000 (-0.23) 0.2289 120
Percent Sports, AM Drive 0.0217 (0.41) -0.0029 (1.85) -0.0049 (-0.79) 0.0000 (-0.51) 0.0594 120
Percent Local, Evening 0.3284 (0.43) 0.0191 (1.09) 0.0378 (0.53) -0.0001 (-1.35) 0.0132 149
Percent Network/Syndicated, Evening -0.7391 (1.24) 0.0049 (0.36) -0.0544 (-0.96) 0.0001 (1.59) 0.1203 149
Percent Live, Evening 0.3398 (0.47) 0.0052 (0.31) 0.0873 (1.26) 0.0000 (0.29) 0.0553 149
Percent Advertisements, Evening -0.5500 (1.70) 0.0120 (1.61) -0.0237 (-0.77) 0.0000 (-1.29) 0.0096 149
Percent Entertainment/Leisure/DJ Banter, Evening -0.1381 (0.36) 0.0073 (0.81) -0.0353 (-0.96) 0.0000 (1.12) -0.0140 149
Percent Music, Evening 0.3855 (0.50) 0.0048 (0.27) 0.0463 (0.63) 0.0000 (-0.44) -0.0108 149
Percent News, Evening -0.0653 (1.07) 0.0005 (0.35) -0.0089 (-1.54) 0.0000 (-1.47) 0.1747 149
Percent Sports, Evening -0.2734 (0.63) -0.0025 (0.25) 0.0291 (0.71) 0.0000 (0.86) -0.0333 149
Average Block, Advertisements, AM Drive -2.8683 (0.81) 0.0821 (0.80) 0.2961 (0.73) -0.0008 (-1.87) 0.0454 120
Average Block, Entertainment/Leisure/DJ Banter, AM Drive -1.4015 (0.19) 0.2356 (1.12) 0.9776 (1.17) -0.0006 (-0.62) 0.0273 120
Average Block, Music, AM Drive -4.5568 (0.97) -0.0809 (0.60) -0.6546 (-1.21) 0.0002 (0.34) -0.0449 120
Average Block, News, AM Drive 0.9583 (0.44) -0.1953 * (3.12) 0.0567 (0.23) 0.0000 (0.03) 0.1134 120
Average Block, Sports, AM Drive 0.1035 (0.09) -0.0351 (1.04) -0.1342 (-1.00) -0.0001 (-0.92) -0.0070 120
Average Block, Advertisements, Evening -2.0351 (0.66) 0.0581 (0.82) -0.0498 (-0.17) -0.0003 (-0.89) -0.0952 149
Average Block, Entertainment/Leisure/DJ Banter, Evening 0.3571 (0.11) -0.0237 (0.32) -0.1937 (-0.63) 0.0005 (1.49) -0.0709 149
Average Block, Music, Evening -3.6695 (0.68) -0.0631 (0.51) -0.0588 (-0.12) -0.0009 (-1.64) 0.0408 149
Average Block, News, Evening -0.3352 (0.42) 0.0043 (0.23) -0.1513 * (-1.99) -0.0001 (-1.67) 0.2134 149
Average Block, Sports, Evening -4.9202 (1.32) 0.0264 (0.31) 0.0561 (0.16) 0.0000 (-0.05) -0.0053 149
Number of Syndicated Programs 1.0548 (0.54) 0.0286 (0.57) 0.0336 (0.16) 0.0004 (1.53) 0.0595 284
Number of Personalities 6.8053 (1.16) -0.0603 (0.40) 1.0496 (1.62) -0.0004 (-0.57) 0.0690 284
Note :  Asterisk denotes statistical significance at least at the 5 percent level.
Source:  Ownership Database (from FCC), Edison Airplay Database
Dependent Variable
Table 22:  Station Pair Descriptives for Other Content Program Measures, Stratified by Common Ownership and Market
All Commercial, In-Market, Edison Surveyed Stations
Same Market
[1]
Different Market
[2]
Same Market
[3]
Different 
Market
[4]
Content Angle 57.1 50.8 53.2 58.1 57.3 -7.3 - -4.1 -
Origination Angle 33.2 33.8 31.0 30.5 33.4 3.3 + -2.3 -
Live Angle 30.8 31.6 30.7 27.8 30.8 3.9 + -0.1 -
Content Angle 49.8 43.6 51.8 49.7 49.7 -6.1 - 2.1 +
Origination Angle 31.8 24.6 35.9 28.2 31.6 -3.6 - 4.3 +
Live Angle 31.1 29.6 35.0 30.5 31.0 -0.9 - 4.0 +
Content Angle 51.1 56.2 46.2 50.3 51.3 5.9 + -5.1 -
Origination Angle 30.6 31.8 29.3 30.4 30.7 1.4 + -1.4 -
Live Angle 30.6 32.3 30.8 30.9 30.6 1.5 + 0.2 +
Content Angle 51.2 41.9 55.6 51.8 51.0 -9.9 - 4.5 +
Origination Angle 34.9 28.5 37.1 31.3 34.8 -2.7 - 2.3 +
Live Angle 32.9 29.7 29.9 34.1 33.1 -4.3 - -3.2 -
Content Angle 50.5 52.4 49.5 53.5 50.5 -1.2 - -1.0 -
Origination Angle 37.2 35.3 38.6 36.0 37.1 -0.7 - 1.5 +
Live Angle 36.8 32.2 36.7 38.6 36.8 -6.4 - -0.1 -
Content Angle 45.7 53.7 50.0 40.6 45.6 13.1 + 4.4 +
Origination Angle 30.5 34.3 30.5 26.6 30.5 7.6 + 0.0 -
Live Angle 28.2 36.3 29.7 24.0 28.1 12.4 + 1.6 +
Content Angle 0.1 45.1 40.9 54.7 46.9 -9.6 - -6.0 -
Origination Angle 0.1 35.7 21.7 25.8 24.6 10.0 + -2.9 -
Live Angle 0.0 35.8 24.0 30.0 27.0 5.8 + -3.0 -
Content Angle 0.0 23.3 15.5 30.6 26.5 -7.4 - -10.9 -
Origination Angle 0.0 10.2 10.1 12.9 12.7 -2.8 - -2.6 -
Live Angle 0.7 15.8 13.7 20.9 19.9 -5.1 - -6.2 -
Content Angle 0.1 27.0 21.0 28.3 27.7 -1.2 - -6.7 -
Origination Angle 0.1 13.1 15.0 7.8 11.3 5.3 + 3.7 +
Live Angle 0.1 19.9 16.4 12.7 17.7 7.2 + -1.3 -
Content Angle 0.1 13.1 30.8 20.4 26.2 -7.2 - 4.6 +
Origination Angle 0.0 3.7 25.5 11.1 18.7 -7.3 - 6.9 +
Live Angle 0.0 11.2 21.7 17.4 22.9 -6.2 - -1.2 -
Content Angle 0.0 23.7 18.1 28.0 24.3 -4.3 - -6.2 -
Origination Angle 0.0 16.6 14.6 23.1 18.6 -6.5 - -4.0 -
Live Angle 0.0 17.7 18.2 25.2 23.0 -7.6 - -4.9 -
Content Angle 0.0 15.5 15.5 21.2 -5.7 -
Origination Angle 0.0 14.7 8.5 17.1 -2.4 -
Live Angle 0.0 14.8 9.5 16.5 -1.7 -
Notes:
Source: Ownership Database (from FCC), Edison Airplay Database
All
All Stations
Effect of Common 
Ownership?
Weekend
PM Drive
Evening
Different OwnersSame Owners
Variable
Evening
AM Drive
Daytime
PM Drive
Same Market
[5] = [1]-[3]
Different Market
[6] = [2]-[4]
Daytime
2. "Angle" measures the distance (in degrees) between the program description vectors of any two station pairs.  The angle or distance between two stations with 
identical programming would be zero degrees, while the angle between two diametrically opposite stations would be 90 degrees.
1. "Content" is a vector that includes % of time advertising, annoucnements, talk, fundraising/charity, music, news, public arffairs, religious, and sports. "Origination" is a 
vector that includes % of time local, network/syndicated, and voice tracked.  "Live" is a vector that includes % of time live and taped. 
Midnight-6AM
Midnight-6AM
AM Drive
Weekend
FM Only Stations
Table 23: Station Pair Regressions Estimaing the Effect of Ownership Structure on Other Program Measures
All Commercial, In-Market, Edison Surveyed Stations
Summary of the Marginal Effect of Same Owner Indicator
Marginal
Effect T-Stat
Adj. R-
Squared N
Marginal
Effect T-Stat
Adj. R-
Squared N
Marginal
Effect T-Stat
Adj. R-
Squared N # Mkts
Content Angle -4.11 *  (-6.25) 0.0012 32,628      -7.28  (-1.25) 0.00 144 -1.92  (-0.23) 0.02 144 56
Origination Angle -2.29 *  (-3.04) 0.0003 32,597      3.33 (0.52) -0.01 144 5.16 (0.63) 0.25 144 56
Live Angle -0.05  (-0.08) 0.0000 32,604      3.87 (0.65) 0.00 144 1.92 (0.25) 0.25 144 56
Content Angle 2.02 * (2.53) 0.0001 43,353      -6.11  (-0.78) 0.00 194 1.86 (0.17) 0.10 194 82
Origination Angle 4.22 * (5.53) 0.0007 43,314      -3.63  (-0.50) 0.00 193 14.07 (1.45) 0.17 193 82
Live Angle 3.95 * (5.62) 0.0007 43,332      -0.92  (-0.14) -0.01 194 12.58 (1.50) 0.25 194 82
Content Angle -4.93 *  (-5.03) 0.0007 34,970      5.95 (0.67) 0.00 145 2.13 (0.19) 0.42 145 75
Origination Angle -1.36  (-1.51) 0.0000 34,946      1.39 (0.17) -0.01 145 10.26 (0.85) 0.23 145 75
Live Angle 0.25 (0.29) 0.0000 34,950      1.48 (0.20) -0.01 145 -9.25  (-0.92) 0.34 145 75
Content Angle 4.38 * (5.34) 0.0007 39,894      -9.89  (-1.20) 0.00 164 -5.54  (-0.50) 0.22 164 78
Origination Angle 2.17 * (2.71) 0.0002 39,872      -2.73  (-0.36) -0.01 164 -6.55  (-0.68) 0.29 164 78
Live Angle -3.24 *  (-4.50) 0.0005 39,878      -4.33  (-0.63) 0.00 164 -4.17  (-0.47) 0.24 164 78
Content Angle -0.99  (-1.17) 0.0000 42,760      -1.17  (-0.16) -0.01 171 6.12 (0.61) 0.31 171 76
Origination Angle 1.47 (1.77) 0.0001 42,742      -0.73  (-0.10) -0.01 171 -1.73  (-0.17) 0.20 171 76
Live Angle -0.20  (-0.25) 0.0000 42,744      -6.45  (-0.95) 0.00 171 -2.28  (-0.22) 0.12 171 76
Content Angle 4.51 * (2.88) 0.0005 14,525      13.09 (0.84) 0.00 65 27.93 (1.26) 0.34 65 35
Origination Angle 0.03 (0.02) -0.0001 14,525      7.61 (0.63) -0.01 65 24.52 (1.48) 0.38 65 35
Live Angle 1.64 (1.36) 0.0001 14,524      12.39 (1.04) 0.00 65 17.14 (0.95) 0.95 65 35
Source : Ownership Database (from FCC), Edison Airplay Database
2. "Content" is a vector that includes % of time advertising, annoucnements, talk, fundraising/charity, music, news, public arffairs, religious, and sports. "Origination" is a vector that includes % of time local, 
network/syndicated, and voice tracked.  "Live" is a vector that includes % of time live and taped. 
3. "Angle" measures the distance (in degrees) between the program description vectors of any two station pairs.  The angle or distance between two stations with identical programming would be zero degrees, while the 
angle between two diametrically opposite stations would be 90 degrees.
PM Drive
Dependent Variable
Notes : 
Weekend
Midnight-6AM
Evening
Only Same-Market Stations
Daytime
1. Asterisk denotes statistical significance at least at the 5 percent level.
Same-Market Stations with Market Fixed EffectsAll Stations
AM Drive
Same Market
[1]
Diff Market
[2]
Same Market
[3]
Diff Market
[4]
Content Angle 51.6 7.2 33.6 56.7 52.8 -49.5 - -19.1 -
Origination Angle 40.8 53.0 36.5 48.6 41.0 4.3 + -4.4 -
Live Angle 39.3 41.0 38.6 33.1 39.3 7.9 + -0.7 -
Content Angle 50.2 46.8 40.7 50.2 51.1 -3.4 - -10.4 -
Origination Angle 33.4 12.1 30.3 25.9 33.8 -13.8 - -3.5 -
Live Angle 38.3 40.6 31.2 39.0 38.9 1.5 + -7.7 -
Content Angle 52.0 . 48.9 76.8 52.2 -3.3 -
Origination Angle 41.2 . 38.5 69.2 41.3 -2.8 -
Live Angle 42.7 . 39.1 56.4 42.9 -3.8 -
Content Angle 64.0 86.2 61.3 57.9 64.1 28.3 + -2.9 -
Origination Angle 40.3 5.4 24.9 2.5 41.5 2.9 + -16.5 -
Live Angle 41.4 5.9 38.9 24.8 41.7 -18.9 - -2.9 -
Content Angle 55.5 86.4 49.6 58.1 55.9 28.3 + -6.4 -
Origination Angle 26.6 12.3 12.4 17.0 27.9 -4.7 - -15.5 -
Live Angle 29.7 1.2 21.4 32.5 30.5 -31.3 - -9.1 -
Content Angle 45.2 . 43.5 45.3 -1.8 -
Origination Angle 26.0 . 18.7 . 26.6 -7.9 -
Live Angle 21.7 . 15.2 . 22.3 -7.1 -
Content Angle 38.6 9.9 36.8 . 39.2 -2.4 -
Origination Angle 40.9 1.6 48.8 . 40.2 8.6 +
Live Angle 28.7 11.0 38.7 . 27.4 11.3 +
Content Angle 25.8 . 34.2 . 25.1 9.1 +
Origination Angle 34.7 . 9.3 . 36.9 -27.6 -
Live Angle 44.3 . 51.0 . 43.7 7.3 +
Content Angle 39.6 74.2 39.5 . 39.4 0.1 +
Origination Angle 39.9 69.2 38.3 . 39.7 -1.4 -
Live Angle 26.4 6.1 39.4 . 26.0 13.4 +
Content Angle 31.8 . 41.2 . 31.0 10.1 +
Origination Angle 40.9 . 42.4 . 40.8 1.6 +
Live Angle 40.7 . 45.2 . 40.3 4.9 +
Content Angle 31.4 . 40.3 . 30.7 9.6 +
Origination Angle 21.7 . 13.9 . 22.3 -8.4 -
Live Angle 37.9 . 53.1 . 36.7 16.4 +
Content Angle 23.3 . 37.2 10.8 22.7 14.5 +
Origination Angle 23.8 . 14.2 35.4 24.1 -9.8 -
Live Angle 37.3 . 40.5 38.7 37.1 3.4 +
Notes:
Source: Ownership Database (from FCC), Edison Airplay Database
Midnight-6AM
Daytime
PM Drive
All Commercial, In-Market, Edison Surveyed News Station Pairs
Evening
Midnight-6AM
AM Drive
Weekend
Table 24:  News and Sports Station Pair Descriptives, Stratified by Common Ownership and Market
Variable
All Commercial, In-Market, Edison Surveyed Sports Station Pairs
All
Same Owners
AM Drive
2. "Angle" measures the distance (in degrees) between the program description vectors of any two station pairs.  The angle or distance between two stations with identical 
programming would be zero degrees, while the angle between two diametrically opposite stations would be 90 degrees.
1. "Content" is a vector that includes % of time advertising, annoucnements, talk, fundraising/charity, music, news, public arffairs, religious, and sports. "Origination" is a vector 
that includes % of time local, network/syndicated, and voice tracked.  "Live" is a vector that includes % of time live and taped. 
Weekend
Effect of Common 
Ownership?
Same Market
[5] = [1]-[3]
Different Market
[6] = [2]-[4]
Daytime
PM Drive
Evening
Different Owners
AM EVE AM EVE AM EVE AM EVE AM EVE AM EVE AM EVE AM EVE AM EVE
Talk -7 min 5%
0.53%
0.77 min
0.23 min
News
-4%
-2.5 min
0.23 min
Sports 14 min -12% 15 min
Music -5 min -4% -0.76 min
Local -3%
Live -3%
Syndicated 8% 1%
Syndicated 
Programs
Advertising 0.83%
News -18%
-31%
- 27 min
0.5% 3%
-6.5%
-6.6 min
-1.65 min
Music -0.9 min
Live -1.4%
Notes:
Source :  Tables 17, 18, 20, and 21.
1 program
Table 25:  Summary of the Market and Station Level Results of the Effects of Ownership Structure on Measures of Programming Content
National
Radio Ownership
Local 
Radio HHI
Newspaper
Cross Ownership
TV
Cross Ownership
All Stations, Market Level
Newspaper
Cross Ownership
TV
Cross Ownership
3.  The effects of changes in ownership are calculated based on the elasticity of programming content with respect to the measure of ownership structure (evaluated at the sample means).  The local radio HHI effect 
represents a change in programming content associated with a 100 point increase in the HHI.  The other chagnes represent a change in programming content associated with a 10 percent increase in ownership.
1. Red shading indicates a statistically significant, negative effect of ownership on the measure of programming content.  Green shading indicates a statisitically significant, positive effect of ownership on the measure 
of programming content.  
All Stations, Station Level
FM Only Stations, Station Level
2. Numbers shown in shaded box indicate the effect of a change in ownership structure on either the percentage of airplay time by programming content (expressed in % units) or the change in the length of an 
uninterrupted block of a particular type of programming content (expressed in minute units).
FM Only Stations, Market Level
Sisters Local Radio HHI
National
Radio Ownership Category
Table 26:  Top 50 Most Commonly Shared Programs on News Stations
No. Program Name # Stations
% Stations 
Sampled
1 COAST TO COAST AM 26 38%
2 THE RUSH LIMBAUGH SHOW 17 25%
3 SEAN HANNITY 16 23%
4 SAVAGE NATION WITH MICHAEL SAVAGE 7 10%
5 THE LAURA INGRAHAM SHOW 6 9%
6 THE CLARK HOWARD SHOW 6 9%
7 ABC NEWS 6 9%
8 STATION NEWS 5 7%
9 RADIO FACTOR WITH BILL O' REILLY 5 7%
10 THE JIM BOHANNON SHOW 5 7%
11 GLENN BECK PROGRAM 5 7%
12 MICHAEL MEDVED SHOW 4 6%
13 TRAVEL WITH STEPHANIE ABRAMS 4 6%
14 CBS NEWS 4 6%
15 THE TONY SNOW SHOW 3 4%
16 DR. JOY BROWNE 3 4%
17 PAUL HARVEY 3 4%
18 BASEBALL GAME BROADCAST 3 4%
19 FOX NEWS RADIO NETWORK 3 4%
20 THE DAVE RAMSEY SHOW 3 4%
21 THE OSGOOD FILE 3 4%
22 THE PHIL HENDRIE SHOW 3 4%
23 THE LARS LARSON SHOW 2 3%
24 THE JOEY REYNOLDS SHOW 2 3%
25 THE MAJORITY REPORT 2 3%
26 FIRST LIGHT 2 3%
27 HANDEL ON THE LAW 2 3%
28 MIKE GALLAGHER SHOW 2 3%
29 FOX GAMETIME REACT WITH JT THE BRICK 2 3%
30 NEAL BOORTZ SHOW 2 3%
31 DOUG STEPHAN'S GOOD DAY 2 3%
32 ARNIE SPANIER SHOW ON SPORTING NEWS RADIO 2 3%
33 WALLSTREET JOURNAL THIS MORNING 2 3%
34 BASEBALL POST-GAME SHOW 2 3%
35 ADVICE LINE WITH ROY MASTERS 2 3%
36 AMERICA AT NIGHT WITH ERNIE BROWN 2 3%
37 AP NEWS 2 3%
38 USA RADIO NETWORK SPORTS NEWS 2 3%
39 CNN RADIO NEWS 2 3%
40 STEVE CROWLEY'S AMERICAN SCENE 2 3%
41 THE WEEKEND SHOW 2 3%
42 THE ALAN COLMES SHOW 2 3%
43 THE ED SCHULTZ SHOW 2 3%
44 THE BULLPEN 1 1%
45 THE BOB ROSE SHOW 1 1%
46 THE BILL CUNNINGHAM SHOW 1 1%
47 THE BARRIE SINGER SHOW 1 1%
48 THE BOB CHRISTOPHER SHOW 1 1%
49 RUSS & DEE 1 1%
50 SATURDAY OPEN PHONES 1 1%
Source:  Ownership Database (from FCC), Edison Airplay Database, BIA
All Commercial, In-Market New Stations with Programming Information 
Surveyed by Edison
Table 27:  Top 50 Most Commonly Shared Programs on Sports Stations
No. Program Name # Stations
% Stations 
Sampled
1 GAMENIGHT ON ESPN RADIO 9 21%
2 ALLNIGHT ON ESPN RADIO 8 19%
3 THE JIM ROME SHOW ON FOX SPORTS RADIO 8 19%
4 ESPN RADIO 7 17%
5 THE DAN PATRICK SHOW ON ESPN RADIO 7 17%
6 MIKE & MIKE IN THE MORNING 6 14%
7 FOX GAMETIME REACT WITH JT THE BRICK 6 14%
8 THE HERD WITH COLIN COWHERD ON ESPN RADIO 5 12%
9 THE THIRD SHIFT ON FOX 5 12%
10 SPORTSCENTER ON ESPN RADIO 4 10%
11 AM GAMEDAY ON ESPN RADIO 4 10%
12 FOX SPORTS RADIO 4 10%
13 SPORTSBASH ON ESPN RADIO 3 7%
14 FANTASY FOCUS ON ESPN RADIO 3 7%
15 THE HUDDLE ON ESPN RADIO 37
16 THE V SHOW WITH BOB VALVANO ON ESPN RADIO 3 7%
17 BASEBALL GAME BROADCAST 37
18 FOX MORNING EXTRAVAGANZA WITH VAN EARL WRIGHT AND ANDREW SICILIANO 3 7%
19 THE BASEBALL SHOW ON ESPN RADIO 3 7%
20 FOX GAMETIME SUNDAY 25
21 FOX NATIONAL SPORTS REPORT 2 5%
22 THE FIRST TEAM ON FOX WITH STEVE CZABAN 2 5%
23 ABC NEWS 25
24 THE DRIVE ON FOX WITH CHRIS MYERS & BRYAN COX 2 5%
25 FOX GAMETIME LIVE 25
26 CBS NEWS %
27 FOX GAMETIME REWIND 25
28 WEEKEND GAMEDAY ON ESPN RADIO 2 5%
29 CNN RADIO NEWS 25
30 THE ED SCHULTZ SHOW 12%
31 THE DRIVETIME PLAYERS WITH RICH LORD & MARC VANDERMEER 1 2%
32 THE BUDWEISER BOBCAT MINUTE 1 2%
33 THE BOTTOM LINE 12
34 THE CHRIS RUSSELL SHOW ON SPORTING NEWS RADIO 1 2%
35 THE EDGE 12
36 THE DRIVE WITH CHRIS MEYERS ON FOX SPORTS RADIO 1 2%
37 THE DAN SILEO SHOW 12
38 THE DAVID STEIN SHOW ON SPORTING NEWS RADIO 1 2%
39 THE BEST DAMN SPORTS SHOW PERIOD ON FOX SPORTS 1 2%
40 THE DA SHOW 12
41 THE DOUG KARSCH SHOW ON ESPN RADIO 1 2%
42 THE DR. BOB MARTIN SHOW 12
43 THE BIG MO SHOW %
44 THE BEAR FACTS WITH BARRY MILLIGAN 1 2%
45 THE TIM BRANDO SHOW 12
46 THE TIM GRUNHARD SHOW %
47 THE SPORTS RADIO 610 OUTDOOR SHOW 1 2%
48 THE SANDLOT 12
49 THE SPEED ZONE %
50 XM COLLEGE FOOTBALL MINUTE 1 2%
Source: Ownership Database (from FCC), Edison Airplay Database, BIA
All Commercial, In-Market Sports Stations with Programming Information Surveyed by Edison
Table 28:  News and Sports Program Overlap Descriptives
All Commercial, In-Market Edison Surveyed Stations
Same Market
[1]
Different 
Market
[2]
Same Market
[3]
Different 
Market
[4]
Common Programs 0.272 1.000 0.577 0.000 0.247 1.000 + 0.331 +
% Overlap 3.3% 14.3% 7.5% 0.0% 3.0% 0.143 + 0.046 +
Avg % Overlap 6.0% 22.5% 13.4% 0.0% 5.4% 0.225 + 0.080 +
Common Programs 0.223 0.000 0.375 0.000 0.215 0.000 0 0.160 +
% Overlap 2.7% 0.0% 5.3% 0.0% 2.6% 0.000 0 0.028 +
Avg % Overlap 4.9% 0.0% 8.6% 0.0% 4.7% 0.000 0 0.039 +
Source:  Ownership Database (from FCC), Edison Airplay Database
Sports Stations
VariableFormat
News Stations
All
Effect of Common 
Ownership?
Same Market
[5] = [1]-[3]
Different Market
[6] = [2]-[4]
Different OwnersSame Owners
Table 29: Station Pair Regressions Estimating the Effect of Ownership Structure on Program Overlap For Sports and News Stations
Summary of the Marginal Effects of Same Owner and Same Market Indicators
Marg Eff T-Stat Marg Eff T-Stat Marg Eff T-Stat Marg Eff T-Stat
Common Programs 0.284 (8.40) * 0.0305 2,211   0.33 (8.89) * -0.247  (-1.38) 0.669 (1.76) 0.0304 2,211    
% Overlap 0.040 (9.25) * 0.0369 2,211   0.05 (9.85) * -0.030  (-1.33) 0.097 (2.04) * 0.0367 2,211    
Avg % Overlap 0.072 (9.12) * 0.0358 2,211   0.08 (9.67) * -0.054  (-1.36) 0.145 (1.71) 0.0357 2,211    
Marg Eff T-Stat Marg Eff T-Stat Marg Eff T-Stat Marg Eff T-Stat
Common Programs 0.073 (1.25) 0.0007 820      0.08 (1.32) -0.192  (-0.68) -0.078  (-0.16) -0.0006 820       
% Overlap 0.012 (1.56) 0.0018 820      0.01  (-1.63) -0.024  (-0.07) -0.012  (-0.20) 0.0004 820       
Avg % Overlap 0.020 (1.41) 0.0012 820      0.02 (1.48) -0.045  (-0.66) -0.021  (-0.18) -0.0002 820       
Source: Ownership Database (from FCC), Edison Airplay Database
N
Same Owner Same Market Same Owner x Same Market
Adj R2
Note :  Askterisk denotes statistical significance at least at the 5 percent level.
Same Owner Same Market
Specification 1 Specification 2
N Adj R2 NAdj R2
Same Owner
All Commercial, In-Market News Station Pairs
All Commercial, In-Market Sports Station Pairs
Variable
Variable
Specification 1
Same Owner x Same Market
Specification 2
Same Owner
Adj R2 N
Table 30:  Market Level Summary of Advertising Prices, Stratified by HHIs
All Commercial, In-Market Edison Surveyed Stations
Means for Stations in Markets with HHI in Range
Variable
Mean for 
All 
Stations
0 ? HHI < 1,000
[1]
1,000 ? HHI < 2,000
[2]
2,000 ? HHI < 3,000
[3]
3,000 ? HHI < 4,000
[4]
4,000 ? HHI
[5]
All Stations
CPP, AM Drive 67.1 227.5 54.5 25.8 31.3 31.4 -196.0 -
CPP, Evening 43.1 126.8 35.5 20.9 28.6 27.4 -99.3 -
CPP, Average 61.3 200.3 50.6 24.9 30.5 31.0 -169.3 -
CPM, AM Drive 12.2 8.4 10.6 13.3 17.5 21.5 13.1 +
CPM, Evening 9.9 5.0 7.8 11.4 17.0 19.6 14.6 +
CPM, Average 11.8 7.5 10.1 13.0 17.4 21.0 13.5 +
Number of Stations 24.2 47.7 26.0 16.9 13.0 8.6 -39.1 -
FM Only Stations
CPP, AM Drive 67.1 227.5 54.5 25.8 31.3 31.4 -196.0 -
CPP, Evening 43.1 126.8 35.5 20.9 28.6 27.4 -99.3 -
CPP, Average 61.3 200.3 50.6 24.9 30.5 31.0 -169.3 -
CPM,AM Drive 12.2 8.4 10.6 13.3 17.5 21.5 13.1 +
CPM,Evening 9.9 5.0 7.8 11.4 17.0 19.6 14.6 +
CPM,Average 11.8 7.5 10.1 13.0 17.4 21.0 13.5 +
Number of Stations 14.4 23.5 15.8 11.2 8.8 5.6 -17.9 -
Source:  Ownership Database (from FCC), Edison Airplay Database, SQAD
Effect of 
Consolidation?
[6] = [5]-[1]
Table 31:  Market Level Regressions Estimating the Effect of Ownership Structure on Advertising Prices
Commercial, In-Market, Edison Surveyed Stations
HHI Stations
Percent of Stations with 
Cross-Owned Newspaper
Percent of Stations with 
Cross-Owned TV Station
Number of Commercial 
Stations Owned Nationally by 
In-Market Owners
Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Adj R-Squared N
CPP, AM Drive -150.96 (1.42) 1.35 (1.47) -59.43 (-0.25) 109.01 * (2.12) 0.0117 (1.56) 0.70 241
CPP, Evening -91.33 (1.47) 0.60 (1.11) 29.59 (0.21) 57.01 (1.90) 0.0061 (1.38) 0.64 241
CPP, Average -129.84 (1.39) 1.15 (1.43) -44.72 (-0.21) 104.83 * (2.33) 0.0105 (1.59) 0.70 241
CPM, AM Drive -1.97 (0.24) -0.30 * (4.24) 3.44 (0.19) 0.95 (0.24) -0.0006 (-1.08) 0.33 241
CPM, Evening -3.72 (0.40) -0.39 * (4.81) 24.20 (1.14) 0.85 (0.19) -0.0005 (-0.70) 0.41 241
CPM, Average -2.44 (0.31) -0.33 * (4.83) 8.25 (0.46) 2.53 (0.66) -0.0004 (-0.70) 0.38 241
With Demographics:
CPP, AM Drive 49.87 (0.94) -1.02 * (2.17) 6.30 (0.05) 38.64 (1.53) -0.0069 (-1.79) 0.94 236
CPP, Evening 26.55 (0.77) -0.60 * (1.98) 41.45 (0.53) 14.51 (0.88) -0.0041 (-1.64) 0.90 236
CPP, Average 48.54 (1.06) -0.85 * (2.11) 9.58 (0.09) 40.89 (1.87) -0.0057 (-1.73) 0.94 236
CPM, AM Drive 1.96 (0.25) -0.24 * (3.54) 8.99 (0.52) -1.30 (-0.36) -0.0011 (-1.91) 0.47 236
CPM, Evening -7.14 (0.75) -0.33 * (3.96) 16.53 (0.77) 1.58 (0.35) -0.0008 (-1.18) 0.44 236
CPM, Average -1.38 (0.18) -0.26 * (4.00) 12.02 (0.71) 1.01 (0.28) -0.0008 (-1.49) 0.50 236
HHI Stations
Percent of Stations with 
Cross-Owned Newspaper
Percent of Stations with 
Cross-Owned TV Station
Number of Commercial 
Stations Owned Nationally by 
In-Market Owners
Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Adj R-Squared N
CPP, AM Drive -148.15 (1.63) 2.83 (1.89) 311.00 (0.95) 117.15 * (2.36) 0.0298 * (2.57) 0.65 241
CPP, Evening -82.50 (1.59) 1.40 (1.64) 270.03 (1.45) 62.32 * (2.20) 0.0157 * (2.38) 0.59 241
CPP, Average -126.77 (1.61) 2.39 (1.85) 270.37 (0.96) 109.36 * (2.54) 0.0259 * (2.58) 0.65 241
CPM, AM Drive 3.60 (0.56) -0.36 * (3.42) 27.49 (1.20) -0.69 (-0.20) -0.0014 (-1.76) 0.32 241
CPM, Evening 1.64 (0.21) -0.50 * (3.91) 55.57 * (1.98) -1.02 (-0.24) -0.0015 (-1.50) 0.33 241
CPM, Average 1.89 (0.29) -0.44 * (4.11) 29.81 (1.29) 0.48 (0.14) -0.0013 (-1.53) 0.34 241
With Demographics:
CPP, AM Drive 2.18 (0.05) -1.40 * (2.00) 58.73 (0.39) 31.08 (1.35) -0.0099 (-1.74) 0.93 236
CPP, Evening -0.55 (0.02) -0.76 (1.68) 97.46 (1.01) 13.17 (0.89) -0.0052 (-1.44) 0.90 236
CPP, Average 4.56 (0.13) -1.20 * (1.98) 45.68 (0.35) 32.90 (1.67) -0.0082 (-1.68) 0.93 236
CPM, AM Drive 1.88 (0.32) -0.28 * (2.76) 25.27 (1.18) -2.48 (-0.76) -0.0017 * (-2.12) 0.46 236
CPM, Evening -1.67 (0.22) -0.35 * (2.73) 43.69 (1.61) 0.83 (0.20) -0.0014 (-1.33) 0.41 236
CPM, Average -0.37 (0.06) -0.31 * (3.16) 26.59 (1.25) -0.38 (-0.12) -0.0014 (-1.74) 0.48 236
Note:  Asterisk denotes statistical significance at least at the 5 percent level.  Each row summarizes the results of a single regression model.
Source: Ownership Database (from FCC), Edison Airplay Database, SQAD
Dependent Variable
All Stations
FM Only Stations
Dependent Variable
Table 32:  Market Level Regressions Estimating the Effect of Ownership Structure on Advertising Prices, Big versus Small Markets
All Commercial, In-Market, Edison Surveyed Stations
HHI Stations
Percent of Stations with 
Cross-Owned Newspaper
Percent of Stations with 
Cross-Owned TV Station
Number of Commercial 
Stations Owned Nationally by 
In-Market Owners
Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Adj R-Squared N
CPP, AM Drive -635.19 (1.56) 3.02 (1.64) 2.75 (0.00) 255.20 * (2.17) 0.0314 (1.56) 0.6659 103
CPP, Evening -312.93 (1.38) 1.84 (1.79) 61.65 (0.13) 123.23 (1.88) 0.0178 (1.59) 0.6235 103
CPP, Average -521.59 (1.48) 2.63 (1.64) -1.75 (-0.00) 234.92 * (2.30) 0.0281 (1.60) 0.6649 103
CPM, AM Drive 7.08 (0.48) -0.04 (0.64) -24.85 (-0.81) 5.09 (1.20) -0.0014 (-1.89) 0.0566 103
CPM, Evening 5.78 (0.50) -0.05 (0.91) -11.05 (-0.46) -0.20 (-0.06) -0.0017 * (-2.88) 0.1426 103
CPM, Average 4.76 (0.36) -0.06 (1.07) -21.16 (-0.76) 5.84 (1.52) -0.0013 * (-2.02) 0.0831 103
With Demographics:
CPP, AM Drive 20.39 (0.11) -1.12 (1.20) 210.53 (0.53) 48.39 (0.86) -0.0180 (-1.80) 0.9373 103
CPP, Evening 39.39 (0.35) -0.55 (0.99) 76.29 (0.32) 9.56 (0.28) -0.0080 (-1.33) 0.9170 103
CPP, Average 49.07 (0.31) -0.93 (1.17) 118.38 (0.35) 49.90 (1.04) -0.0149 (-1.74) 0.9389 103
CPM, AM Drive 15.44 (1.15) -0.02 (0.23) 8.98 (0.31) -0.83 (-0.20) -0.0021 * (-2.92) 0.2909 103
CPM, Evening 5.23 (0.42) -0.03 (0.44) -0.90 (-0.03) -3.08 (-0.81) -0.0014 * (-2.02) 0.1077 103
CPM, Average 9.24 (0.75) -0.03 (0.45) 3.68 (0.14) 0.30 (0.08) -0.0018 * (-2.66) 0.2916 103
HHI Stations
Percent of Stations with 
Cross-Owned Newspaper
Percent of Stations with 
Cross-Owned TV Station
Number of Commercial 
Stations Owned Nationally by 
In-Market Owners
Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Adj R-Squared N
CPP, AM Drive -11.36 (0.34) -0.61 (1.02) -10.24 (-0.11) 8.69 (0.35) 0.0002 (0.06) 0.0032 138
CPP, Evening 0.41 (0.01) -0.64 (1.20) 45.03 (0.54) 11.58 (0.53) -0.0002 (-0.07) 0.0080 138
CPP, Average -8.77 (0.28) -0.56 (0.99) 1.34 (0.01) 13.27 (0.56) 0.0004 (0.13) -0.0023 138
CPM, AM Drive 3.79 (0.45) -0.57 * (3.74) 11.21 (0.47) -2.98 (-0.47) -0.0003 (-0.40) 0.2400 138
CPM, Evening 2.60 (0.25) -0.66 * (3.50) 30.12 (1.01) -0.53 (-0.07) 0.0002 (0.17) 0.2688 138
CPM, Average 3.27 (0.39) -0.58 * (3.79) 15.82 (0.66) -1.07 (-0.17) 0.0000 (0.03) 0.2544 138
With Demographics:
CPP, AM Drive 6.26 (0.39) -0.64 * (2.01) -0.73 (-0.02) -17.13 (-1.41) 0.0001 (0.05) 0.7997 133
CPP, Evening 6.16 (0.35) -0.37 (1.08) 6.31 (0.12) -5.54 (-0.42) -0.0002 (-0.11) 0.6959 133
CPP, Average 4.69 (0.32) -0.44 (1.49) 0.30 (0.01) -10.95 (-0.99) 0.0005 (0.30) 0.8153 133
CPM, AM Drive 0.87 (0.11) -0.38 * (2.46) 8.03 (0.35) -3.06 (-0.51) -0.0004 (-0.50) 0.4279 133
CPM, Evening -5.00 (0.48) -0.46 * (2.25) 6.86 (0.23) 0.73 (0.09) -0.0003 (-0.27) 0.3657 133
CPM, Average -1.75 (0.23) -0.36 * (2.36) 7.93 (0.36) -0.54 (-0.09) -0.0001 (-0.17) 0.4556 133
Source : Ownership Database (from FCC), Edison Airplay Database, SQAD
Note:  Asterisk denotes statistical significance at least at the 5 percent level.  Each row summarizes the results of a single regression model.
Big Markets, 30+ Stations
Dependent Variable
Small Markets, 1-29 Stations
Dependent Variable
Table 33:  Market Level Summary of Listenership, Stratified by HHIs
Commercial, In-Market, Edison Surveyed Stations
Means for Stations in Markets with HHI in Range
Mean for 
All 
Stations
0 ? HHI < 1,000
[1]
1,000 ? HHI < 2,000
[2]
2,000 ? HHI < 3,000
[3]
3,000 ? HHI < 4,000
[4]
4,000 ? HHI
[5]
All Stations
Average Rating 0.009 0.006 0.008 0.010 0.012 0.018 0.012 +
Average Rating, AM Drive 0.012 0.008 0.010 0.014 0.016 0.025 0.017 +
Average Rating, Evening 0.003 0.002 0.003 0.003 0.004 0.006 0.004 +
Number of Stations 24.199 47.677 26.000 16.851 13.000 8.571 -39.105 -
FM Only Stations
Average Rating 0.009 0.006 0.008 0.010 0.012 0.020 0.014 +
Average Rating, AM Drive 0.012 0.008 0.011 0.013 0.015 0.028 0.020 +
Average Rating, Evening 0.003 0.002 0.003 0.003 0.004 0.007 0.004 +
Number of Stations 14.359 23.471 15.802 11.203 8.767 5.571 -17.899 -
Effect of 
Consolidation?
[6] = [5]-[1]
Source : Ownership Database (from FCC), Edison Airplay Database, SQAD
Variable
Table 34:  Market Level Regressions Estimating the Effect of Ownership Structure on Listenership
Commercial, In-Market, Edison Stations
HHI Stations
Percent of Stations with 
Cross-Owned Newspaper
Percent of Stations with 
Cross-Owned TV Station
Number of Commercial 
Stations Owned Nationally by 
In-Market Owners
Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Adj R-Squared N
Average Rating 0.0023 (0.54) -0.0002 * (5.28) 0.0202 * (2.13) -0.0028 (-1.31) 0.0000005 (1.53) 0.5141 249
Average Rating, AM Drive -0.0019 (0.30) -0.0003 * (6.07) 0.0318 * (2.26) -0.0036 (-1.13) 0.0000010 * (2.22) 0.5154 249
Average Rating, Evening 0.0002 (0.11) -0.0001 * (3.76) 0.0061 (1.48) -0.0015 (-1.57) 0.0000002 (1.63) 0.3308 249
With Demographics:
Average Rating -0.0035 (0.83) -0.0002 * (5.75) 0.0125 (1.42) 0.0009 (0.47) 0.0000006 * (1.99) 0.6190 242
Average Rating, AM Drive -0.0106 (1.75) -0.0003 * (6.41) 0.0202 (1.58) 0.0016 (0.56) 0.0000012 * (2.70) 0.6235 242
Average Rating, Evening -0.0016 (0.89) -0.0001 * (4.47) 0.0024 (0.64) -0.0002 (-0.28) 0.0000002 (1.41) 0.4830 242
HHI Stations
Percent of Stations with 
Cross-Owned Newspaper
Percent of Stations with 
Cross-Owned TV Station
Number of Commercial 
Stations Owned Nationally by 
In-Market Owners
Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Adj R-Squared N
Average Rating 0.0005 (0.13) -0.0004 * (6.91) 0.0061 (0.47) -0.0022 (-1.05) -0.00000023 (-0.48) 0.4689 248
Average Rating, AM Drive -0.0009 (0.17) -0.0006 * (6.79) 0.0130 (0.72) -0.0016 (-0.56) 0.00000004 (0.06) 0.4606 248
Average Rating, Evening 0.0001 (0.07) -0.0001 * (4.51) 0.0008 (0.14) -0.0013 (-1.40) 0.000000009 (0.04) 0.2646 248
With Demographics:
Average Rating -0.0011 (0.29) -0.0004 * (6.23) 0.0081 (0.65) 0.0007 (0.33) -0.00000005 (-0.10) 0.5386 241
Average Rating, AM Drive -0.0038 (0.77) -0.0005 * (6.14) 0.0143 (0.83) 0.0026 (0.94) 0.00000019 (0.27) 0.5309 241
Average Rating, Evening 0.0003 (0.20) -0.0001 * (4.49) 0.0007 (0.12) -0.0003 (-0.29) -0.00000010 (-0.47) 0.4122 241
Source: Ownership Database (from FCC), Edison Airplay Database, SQAD
Note:  Asterisk denotes statistical significance at least at the 5 percent level.
Dependent Variable
All Stations
Dependent Variable
FM Only Stations
Table 35:  Market Level Regressions Estimating the Effect of Ownership Structure on Listenership, Big versus Small Markets
All Commercial, In-Market, Edison Stations
HHI Stations
Percent of Stations with 
Cross-Owned Newspaper
Percent of Stations with 
Cross-Owned TV Station
Number of Commercial 
Stations Owned Nationally by 
In-Market Owners
Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Adj R-Squared N
Average Rating -0.0087 (1.39) -0.0001 * (3.26) 0.0180 (1.31) -0.0042 * (-2.22) -0.00000062 (-1.90) 0.2964 104
Average Rating, AM Drive -0.0103 (1.18) -0.0001 * (3.10) 0.0153 (0.80) -0.0063 * (-2.38) -0.00000040 (-0.88) 0.2425 104
Average Rating, Evening -0.0043 (1.49) 0.0000 * (2.16) 0.0093 (1.47) -0.0021 * (-2.43) -0.000000172 (-1.14) 0.1498 104
With Demographics:
Average Rating -0.0154 * (2.76) -0.0001 * (4.68) 0.0015 (0.12) 0.0005 (0.31) -0.00000039 (-1.25) 0.5142 104
Average Rating, AM Drive -0.0200 * (2.52) -0.0002 * (4.47) -0.0067 (-0.38) -0.0004 (-0.14) -0.00000020 (-0.45) 0.4574 104
Average Rating, Evening -0.0065 * (2.55) -0.0001 * (3.94) 0.0028 (0.49) -0.0002 (-0.22) -0.00000020 (-1.44) 0.4209 104
HHI Stations
Percent of Stations with 
Cross-Owned Newspaper
Percent of Stations with 
Cross-Owned TV Station
Number of Commercial 
Stations Owned Nationally by 
In-Market Owners
Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Adj R-Squared N
Average Rating 0.0077 (1.62) -0.0002 * (2.72) 0.0208 (1.65) -0.0017 (-0.46) 0.00000096 * (2.15) 0.3471 145
Average Rating, AM Drive 0.0057 (0.80) -0.0005 * (3.71) 0.0340 (1.80) -0.0027 (-0.50) 0.00000166 * (2.49) 0.3868 145
Average Rating, Evening 0.0029 (1.39) -0.0001 (1.80) 0.0058 (1.07) -0.0007 (-0.45) 0.000000390 * (2.02) 0.2072 145
With Demographics:
Average Rating 0.0041 (0.92) -0.0002 * (2.01) 0.0109 (0.95) 0.0017 (0.50) 0.00000107 * (2.46) 0.5164 138
Average Rating, AM Drive -0.0002 (0.03) -0.0003 * (2.75) 0.0195 (1.18) 0.0025 (0.51) 0.00000196 * (3.13) 0.5736 138
Average Rating, Evening 0.0019 (0.97) -0.0001 (1.60) 0.0015 (0.29) 0.0000 (0.00) 0.00000034 (1.73) 0.3750 138
Note:  Asterisk denotes statistical significance at least at the 5 percent level.
Source: Ownership Database (from FCC), Edison Airplay Database, SQAD
Dependent Variable
Big Markets, 30+ Stations
Dependent Variable
Small Markets, 1-29 Stations
Table 36:  Station Level Summary of Listenership, Statified by Ownership Structure
Commercial, In-Market, Edison Surveyed Stations
All
[1]
Stations with No 
Sisters
[2]
Stations with At 
Least One Sister
[3]
All 
[5]
Stations with 
No Sisters
[6]
Stations with at 
least One Sister
[7]
Adult AQH Rating, AM Drive 1.13 0.61 1.20 0.59 + 1.13 0.69 1.19 0.50 +
Adult AQH Rating, Evening 0.28 0.14 0.30 0.16 + 0.28 0.18 0.30 0.12 +
Adult AQH Rating, Average 0.87 0.47 0.92 0.45 + 0.85 0.51 0.90 0.39 +
Source:  Ownership Database (from FCC), Edison Airplay Database, Arbitron
Variable
Effect of Common 
Ownership?
[4] = [3]-[2]
All Stations FM Only Stations
Effect of Common 
Ownership?
[8] = [7]-[6]
Table 37:  Station Level Regressions Estimating the Effect of Ownership Structure on Listenership
Commercial, In-Market, Edison Surveyed Stations
Includes Demographics and Station Characteristics
HHI Sisters
Newspaper Cross-
Ownership
Television Cross-
Ownership
Number of Stations Owned 
Nationally by Owner
Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Adj R-Squared N
Average Rating -2.4190 (1.64) 0.0498 * (2.37) 0.9908 * (2.31) -0.0354 (-0.29) 0.0001 (1.08) 0.1950 410
Average Rating, AM Drive -3.5803 (1.61) 0.0477 (1.53) 1.5715 * (2.42) 0.0529 (0.29) 0.0001 (0.89) 0.1712 420
Average Rating, Evening -1.2767 * (2.20) 0.0208 * (2.51) 0.2981 (1.76) 0.0042 (0.09) 0.0000 (1.24) 0.1427 410
HHI Sisters
Newspaper Cross-
Ownership
Television Cross-
Ownership
Number of Stations Owned 
Nationally by Owner
Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Adj R-Squared N
Average Rating -1.4175 (1.15) 0.0748 * (2.44) - - -0.0949 (-0.72) 0.0000 (0.14) 0.1827 243
Average Rating, AM Drive -1.4072 (0.77) 0.0984 * (2.17) - - -0.0161 (-0.08) 0.0000 (-0.10) 0.1675 243
Average Rating, Evening -0.8809 (1.86) 0.0265 * (2.27) - - -0.0571 (-1.14) 0.0000 (0.25) 0.1196 243
Sources: Ownership Database (from FCC), Edison Airplay Database, Arbitron
Note:  Asterisk denotes statistical significance at least at the 5 percent level.  Each row summarizes the results of a single regression model. The effect of newspaper cross-ownership cannot be estimated
because there is only one FM commercial, in-market station in the sample that is cross-owned with a local newspaper.
Dependent Variable
All Stations
Dependent Variable
FM Only Stations
Table 38:  Station Level Regressions Estimating the Effect of Ownership Structure on Listenership
All Commercial, In-Market, Edison Surveyed Stations
HHI Sisters
Newspaper Cross-
Ownership
Television Cross-
Ownership
Number of Stations Owned 
Nationally by Owner
Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat
Adj R-
Squared N
Adult AQH Rating, AM Drive - - 0.00 (0.03) 0.64 (0.76) 0.2607 (1.06) 0.0001 (0.59) 0.11 427
Adult AQH Rating, Evening - - 0.02 (1.69) 0.29 (1.33) 0.0034 (0.05) 0.0000 (-0.31) 0.08 417
Adult AQH Rating, Average - - 0.02 (0.74) 0.37 (0.64) 0.0708 (0.41) 0.0001 (0.80) 0.10 417
HHI Sisters
Newspaper Cross-
Ownership
Television Cross-
Ownership
Number of Stations Owned 
Nationally by Owner
Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat
Adj R-
Squared N
Adult AQH Rating, AM Drive -3.9054 (1.20) 0.0027 (0.04) 1.4134 (0.92) 0.0072 (0.03) - - -0.0544 427
Adult AQH Rating, Evening -1.1913 (1.43) -0.0062 (0.38) 0.2524 (0.64) 0.1055 (1.52) - - -0.0576 417
Adult AQH Rating, Average -2.2134 (1.04) 0.0053 (0.13) 0.7915 (0.79) 0.0353 (0.20) - - 0.0037 417
With Demographics:
Adult AQH Rating, AM Drive -6.0057 (1.75) -0.0287 (0.45) -0.0399 (-0.03) 0.0220 (0.08) - - 0.0128 420
Adult AQH Rating, Evening -1.3835 (1.57) -0.0158 (0.96) -0.0729 (-0.18) 0.1430 * (2.02) - - -0.0079 410
Adult AQH Rating, Average -3.6829 (1.66) -0.0238 (0.57) -0.3192 (-0.31) 0.0664 (0.37) - - 0.0637 410
Note:  Askterisk denotes statistical significance at least at the 5 percent level.
Source: Ownership Database (from FCC), Edison Airplay Database, SQAD
Dependent Variable
With Market Fixed Effects
Dependent Variable
With Owner Fixed Effects
Table 39:  Station Level Regressions Estimating the Effect of Ownership Structure on Listenership
FM Only Commercial, In-Market, Edison Surveyed Stations
With Owner Fixed Effects
HHI Sisters
Newspaper Cross-
Ownership
Television Cross-
Ownership
Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Marg. Effect T-Stat Adj R-Squared N
Adult AQH Rating, AM Drive -1.29 (0.45) 0.03 (0.36) -0.93 (-0.70) -0.23 (-0.83) -0.10 246
Adult AQH Rating, Evening -1.19 (1.84) -0.01 (0.32) -0.23 (-0.77) -0.01 (-0.19) 0.10 246
Adult AQH Rating, Average -1.75 (0.93) 0.02 (0.32) -0.58 (-0.67) -0.15 (-0.81) 0.00 246
With Demographics:
Adult AQH Rating, AM Drive -1.54 (0.50) -0.03 (0.33) -1.66 (-1.22) -0.19 (-0.66) 0.01 243
Adult AQH Rating, Evening -0.55 (0.76) -0.02 (0.73) -0.23 (-0.73) -0.03 (-0.38) 0.14 243
Adult AQH Rating, Average -1.43 (0.70) -0.02 (0.30) -0.93 (-1.02) -0.16 (-0.82) 0.05 243
Note:  Askterisk denotes statistical significance at least at the 5 percent level.
Source: Ownership Database (from FCC), Edison Airplay Database, SQAD
Dependent Variable
Appendix 1: Format Categorization Schemes
Format 11 Format 20 Format 101
AC
Adult Hits
Bright AC
Charlie
Hot AC
Jack
Lite AC
Lite Rock
Mix AC
Modern AC
Soft AC
Soft Hits
Soft Rock
Adult CHR
CHR
Dance
Rhythmic
Top 40
Americana
Blue Grass
Country
Business News
News
Sports Sports
Motivational
Talk
70s & 80s
70s Hits
70s Oldies
80s & 90s
80s Hits
Oldies
Classical Classical
Beautiful Music
Easy
Asian
Ethnic
Greek
Hawaiian
International
Japanese
Korean
Polish
Portuguese
Jazz
NAC
New Age
Smooth Jazz
Full Service
MOR
Children
Comedy
Diverse
Eclectic
Folk
Information
Polka
Variety
Variety Hits
Adult Standards
Big Band
Nostalgia
Educational
NPR
Public
Black Gospel
Christian
Christian Contemporary
Gospel
Inspiration
Religion
Religious Music
Southern Gospe
AOR
Classic Rock
AAA
Adult Rock
Alternative
Classic Hits
Modern Rock
New Rock
Progressive
Rock
Rock & Roll
Rock AC
Hurban
Mexican
Ranchera
Reggaeton
Spanish
Spanish AC
Tejano
Tropical
Black
Hip Hop
R&B Oldies
Rhythm & Blues
Urban
Urban AC
Urban CHR
Urban Contemporary
Jazz/New Age
Miscellaneous
Religion
Album Oriented Rock/Classic Rock
Rock
Talk
Oldies
Public/Educational
Easy Listening/Beautiful Music
Ethnic
Nostalgia/Big Band
Middle of the Road
Adult Contemporary
Contemporary Hit Radio/Top 40
Country
News
Urban
Spanish
Urban
Rock
Spanish
Public/Educational
Religion
News/Talk/Sports
Oldies
Adult Contemporary
Contemporary Hit Radio/Top 40
Country
Other Music
Appendix 2:  Market Level Regressions Estimating the Effects of Ownership Structure
Select Results, with Demographics
All Commercial, In-Market, Edison Surveyed Stations
Dependent Variable Format 101 HHI Percent Local, Evening
Average Block, 
Entertainment/Leisure/
DJ Banter, AM Drive CPP, AM Drive
Average Rating, 
AM Drive
Constant -2.8910 1.3334 2.4041 -130.1452 0.0036
(-0.55) (1.13) (0.44) (-1.61) (0.39)
Marginal Effect of HHI 3.3992 -1.4686 -0.8028 49.8700 -0.0106
(1.00) (1.71) (0.20) (0.94) (1.75)
Marginal Effect of Number of Stations 0.4048 * -0.0055 0.0090 -1.0161 * -0.0003 *
(13.68) (0.89) (0.32) (2.17) (6.41)
0.9200 -1.0313 -8.3112 6.3044 0.0202
(0.13) (-0.69) (-1.22) (0.05) (1.58)
1.5265 0.0698 0.2358 38.6374 0.0016
(0.93) (0.22) (0.16) (1.53) (0.56)
0.0004 0.0000 0.0000 -0.0069 0.0000 *
(1.73) (-0.62) (-0.16) (-1.79) (2.70)
0.0008 * 0.0000 -0.0002 0.0743 * 0.0000
(2.65) (0.75) (0.73) (15.21) (0.75)
0.0003 * 0.0000 -0.0001 -0.0020 0.0000
(3.05) (0.77) (1.32) (1.45) (1.94)
Midwest 0.4822 0.0611 0.5200 1.4759 0.0016 *
(1.06) (0.60) (1.12) (0.21) (2.01)
South 0.0672 0.0248 0.4219 5.4628 0.0002
(0.14) (0.24) (0.90) (0.75) (0.29)
West 0.0697 0.1009 0.6713 20.6726 * -0.0007
(0.13) (0.88) (1.29) (2.61) (-0.71)
Number of  Retail Establishments 0.0000 0.0000 0.0000 0.0000 0.0000 *
(0.56) (1.00) (-0.03) (-0.06) (-2.58)
Percent White -1.7963 -0.0763 1.1382 -57.7412 * 0.0039
(-1.14) (-0.24) (0.80) (-2.34) (1.38)
Percent Age 25 to 34 4.2783 -2.4046 -0.3078 701.3419 * -0.0329
(0.24) (-0.66) (-0.02) (2.56) (-1.05)
Percent Age 35 to 44 -13.1220 2.7932 8.6657 1005.1606 * -0.0037
(-0.64) (0.63) (0.43) (3.17) (-0.10)
Percent Age 45 to 64 -0.5134 -4.5585 * 1.9899 393.5398 * 0.0491 *
(-0.05) (-2.01) (0.19) (2.21) (2.37)
Percent 65 and Over -7.1823 0.6899 2.8181 337.2469 * -0.0300 *
(-0.85) (0.36) (0.32) (2.57) (-2.01)
Percent College Grad -7.4387 * -0.4474 2.3033 81.2947 0.0051
(-2.32) (-0.63) (0.71) (1.64) (0.90)
Adjusted R2 0.8921 -0.0138 -0.0623 0.9352 0.6235
Observations 244 164 164 236 242
Effective Buying Income Per Capita 2005 
Marginal Effect (Level and Square)
Percentage of Commercial Stations with 
Cross-Owned Newspaper
Percentage of Commercial Stations with 
Cross-Owned TV Station
Number of Commercial Stations Owned 
Nationally by In-Market Owners
Total 2005 Population (000)
Marginal Effect (Level and Square)
Appendix 3:  Station Level Regressions Estimating the Effects of Ownership Structure
Select Results, with Demographics
All Commercial, In-Market, Edison Surveyed Stations
Dependent Variable
Percent 
Network/Syndicated, 
Evening Percent Music, Evening Average Rating, Evening
Constant -0.4428 1.0615 -0.5090
(-0.49) (1.17) (-0.72)
Marginal Effect of HHI 1.9245 * -1.8120 * -1.2767 *
(2.51) (2.34) (2.20)
Marginal Effect of Number of Sister Stations -0.0085 0.0120 0.0208 *
(0.73) (1.02) (2.51)
Marginal Effect of Number of Stations 0.0133 * -0.0140 * -0.0122 *
(2.63) (2.76) (3.19)
Cross-Owned Newspaper Dummy 0.2294 -0.0628 0.2981
(1.05) (-0.28) (1.76)
Cross-Owned TV Station Dummy -0.0549 -0.0138 0.0042
(-0.92) (-0.23) (0.09)
0.0001 * -0.0001 0.0000
(2.33) (-1.51) (1.24)
Station Day Power 0.0000 0.0000 0.0000
(-0.62) (-0.48) (1.70)
Station Night Power 0.0000 0.0000 0.0000
(0.25) (0.77) (-1.00)
Station Age 0.0000 -0.0033 * 0.0035 *
(-0.04) (-2.77) (3.57)
FM Dummy -0.2889 * 0.3207 * 0.0727
(-4.50) (4.95) (1.49)
0.0000 0.0000 0.0000
(0.09) (0.80) (0.60)
0.0000 0.0000 0.0000 *
(0.67) (0.10) (2.10)
Midwest -0.0134 -0.0524 0.0692
(-0.18) (-0.69) (1.22)
South 0.0146 -0.0735 -0.0481
(0.18) (-0.90) (-0.80)
West -0.0985 -0.0071 -0.0281
(-1.08) (-0.08) (-0.44)
Number of  Retail Establishments 0.0000 0.0000 0.0000
(0.18) (-0.63) (-0.62)
Percent White 0.4371 -0.2390 -0.1637
(1.78) (-0.97) (-0.82)
Percent Age 25 to 34 -0.1926 0.2471 2.1662
(-0.07) (0.09) (1.04)
Percent Age 35 to 44 -2.6825 0.7704 2.1990
(-0.78) (0.22) (0.85)
Percent Age 45 to 64 1.6232 0.0004 1.5086
(0.94) (0.00) (1.06)
Percent 65 and Over -1.4645 0.9383 1.6821
(-1.00) (0.64) (1.58)
Percent College Grad 0.4321 -0.3375 0.2543
(0.77) (-0.60) (0.64)
Adjusted R2 0.2540 0.3553 0.1427
Observations 276 276 410
Source: Ownership Database (from FCC), Edison Airplay Database, SQAD
Total 2005 Population (000)
Marginal Effect (Level and Square)
Effective Buying Income Per Capita 2005 
Marginal Effect (Level and Square)
Number of Stations Owned Nationally by 
Owner
Note:  Asterisk denotes statistical significance at least at the 5 percent level.