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 Budget’s 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 Arbitron’s definition, rather than by using the FCC’s prior signal- contour method. Because Arbitron’s market definition was more restrictive than the signal-contour market, some ownership positions were no longer within the FCC’s 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 station’s service area completely encompasses the newspaper’s 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 station’s 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 station’s actual airplay. For example, one could measure the percentage of a station’s 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 station’s 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 Steiner’s 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 group’s 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 station’s 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 station’s 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 BIA’s 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 BIA’s 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 ? ˆ 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 ˆˆ ?? + (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 ˆ ? and 3 ˆ ? , 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 station’s nighttime power, its daytime power, and station age; ?s are the associated parameters; and ? ijk is the additive stochastic error term. As before, let? ˆ 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 ˆˆ ?? + , 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: BIA’s 101 formats (“Format 101”), BIA’s 20 major format categories (“Format 20”), and a modified version of BIA’s 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 station’s 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 station’s 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.