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Final Report

Utilization Rates, Win Rates, and

Disparity Ratios for Broadcast Licenses

Awarded by the FCC

Prepared for the FCC as a deliverable under the contract “Estimation of Utilization

Rates/Probabilities of Obtaining Broadcast Licenses from the Federal Communications

Commission or of Obtaining Broadcast and Wireless Licenses through Secondary Market

Transactions”

prepared by

KPMG LLP

Economic Consulting Services

For

Federal Communications Commission

November, 2000
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I. Introduction ...............................................................................................................3

II. Comparative Hearings and Minority and Female Credit...........................................5

Comparative Hearing Process .......................................................................................5

Minority and Gender Credit in Comparative Hearings.................................................6

Gender Ownership Policies...........................................................................................9

III. Data Collection....................................................................................................11

IV. Definitions of Win rates, Availability, and Disparity Ratios...................................13

V. Participation by Race and Gender in Comparative Hearings..................................18

VI. Win Rates and Participation Rates by Race, Gender in Comparative Hearings.....21

VII. Win Rates and Disparity Ratios by Race, Gender based on Definition of Control 31

VIII. Level of Competition within Hearings................................................................34

Appendix I: Information Collected from Form 301 for the Development

of Utilization Ratios ........................................................................................................38

Appendix II. Standard Deviations of Estimates Presented in Tables............................39
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I. Introduction

KPMG LLP has prepared this report for the Federal Communications Commission

(FCC). The FCC engaged KPMG to prepare a study of utilization rates and probability

of obtaining broadcast licenses from the FCC. The study will assist the FCC as part of a

series of studies to determine if there has been previous discrimination by the agency or

passive participation by the FCC in discrimination by the private sector.

This study measures license award rates by gender and race during periods of time when

the FCC’s stated policy was to provide preferences to minorities and women. During

this period, the FCC awarded licenses under two regimes. First, the FCC would award a

license to individual applicants (singletons) who were judged as qualified when only a

single application was received. Second, if more than one applicant applied for the

same license, then the FCC used Comparative Hearings, an administrative hearing

process, to allocate broadcast licenses during the period from the 1940s until 1993.1

In this report, KPMG presents its findings regarding participation rates and utilization

rates for participants who were involved in Comparative Hearings from 1978-81 and

1989-93. A comparative hearing was the administrative process that the FCC used to

allocate broadcast licenses during the period from the 1940s until 1993.2 This report

provides results developed from data collected and compiled on the participation and

success of minorities and women in the FCC’s comparative hearing award process for

radio and TV licenses.3

 

1

 After comparative hearings, the FCC used auctions to award licenses. The first auction took place in

1999.

2

 While the FCC’s Request for Proposal focused on utilization, and participation, we also measure

disparity. We define utilization differently than it is defined in the FCC’s RFP. The RFP describes

utilization as the percentage of wins for each racial group, e.g. wins for group divided by the number of

participants for group. While we make this calculation, we refer to it as a win rate rather than utilization

rate. The standard literature on utilization refers to a utilization rate as the percentage of licenses won by

each racial group. E.g. total wins for each group divided by total awards (for all groups combined).

Participation (or availability) refers to the percentage of total availability that is comprised of each racial

group. Disparity is a measure of utilization relative to availability. Typically in the literature on disparity

studies, if the disparity ratio is substantively less than 1, say .8, then it is not unreasonable to suspect the

possibility that discrimination may be present.

3 There are two companion pieces to this study that were prepared by KPMG. The first is “History of the

Broadcast License Application Process”. This report describes the license application and award process

in great detail. The second companion study prepared by KPMG, “Logistic Regression Models of the

Broadcast License Award Process for Licenses Awarded by the FCC”, presents models of the license

award process that attempt to determine how race, gender and other factors influenced the allocation of

licenses awarded by the FCC.
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The report is organized as follows.

Section II, Comparative Hearings and Minority and Female Credit provides a brief

overview of the comparative hearing process and an introduction to minority and female

credit.

Section III, Data Collection, outlines the efforts taken to collect these data.

Section IV, Definitions of Win Rates, Availability and Disparity Ratios, reviews some of

the properties of these measures.

Section V, Participation by Race and Gender in Comparative Hearings, summarizes

participation statistics by demographic group.

Section VI, Win Rates and Disparity Ratios by Race and Gender in Comparative

Hearings, contains the central results of this memo. The section includes various

formulations of win rates and disparity ratios.

Section VII Win Rates and Disparity Ratios by Race and Gender, Based on Definition

of Control, considers win rates and disparity ratios based on a variety of definitions of

which group controls an application.

Section VIII, Level of Competition within Hearings, looks at variation in the level of

competition within hearings by examining the average number of parties per application

and average number of applications per hearing across various demographic groups.

Appendix I provides the data collection form used to acquire these data.

Appendix II, Standard Deviations, discusses the impact of statistical uncertainly on

each of the estimates presented in the previous sections.
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II. Comparative Hearings and Minority and Female Credit4

Comparative Hearing Process

Comparative Hearings began soon after the FCC was created by the Communications

Act of 1934 (the “Act”).5 The Act granted the FCC the authority to regulate

“communications by wire and radio so as to make available to all the people of the

United States a rapid, efficient, nation-wide, and worldwide wire and radio

communication service.” This Act also empowers the FCC to issue broadcasting

licenses “as public convenience, interest, and necessity requires.”6

One landmark court case that was resolved in 1945 reinforced the importance of the

comparative hearing process in awarding a broadcast license when there are multiple

applicants. In Ashbacker Radio Corp. v. FCC, 326 U.S. 327 (1945), the Supreme Court

of the United States held that:

Where the Federal Communications Commission has before it two

applications for broadcasting permits which are mutually exclusive,

it may not, in view of the provisions of the Act for a hearing where

an application is not granted upon examination, exercise its statutory

authority to grant an application upon examination without a

hearing.

This decision set the legal precedent that a publicly distributed license must be assigned

through a process that does not exclude competition for the license.

A comparative hearing was necessary when more than one applicant applied for the

same broadcast license. In the event of multiple applicants, the FCC would hold a

 

4

 This section is an abbreviated discussion. More detail is provided in the KPMG report, “History of the

Broadcast License Application Process”.

5

 Communications Act of 1934, ch. 652, 48 Stat. 1064, 73rd Cong., 2d Sess. (1934) codified as amended

at 47 U.S.C. §151 et seq. (1937).

6

 Lawmakers anticipated the possibility that disputes might arise in the process of awarding broadcast

licenses. Section 309 (a) of the Act grants authority to the FCC to assign any dispute over a license to a

judicial hearing: If upon examination of any application for a station license or for the renewal or

modification of a station license the Commission shall determine that public interest, convenience, or

necessity would be served by the granting thereof, it shall authorize the issuance, renewal, or modification

thereof in accordance with said finding. In the event the Commission upon examination of any such

application does not reach such a decision with respect thereto, it shall notify the applicant thereof, shall

fix and give notice of a time and place for the hearing thereon, and shall afford such applicant an

opportunity to be heard under such rules and regulations as it may prescribe.
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comparative hearing, a proceeding that was presided over by an Administrative Law

Judge (ALJ). The purpose of the comparative hearing was to determine which applicant

for a broadcast license is best qualified to hold the license.

In the period from 1970-1993, 2,437 licenses were awarded by comparative hearing

while 6,178, or the majority of the licenses, were awarded to singleton applications

because these applications were never challenged. Factors that the FCC described as

determinative of license award were:

1. Diversification of control of the media of mass communications.

2. Full-time participation in station operation by owners.

3. Proposed program service.

4. Past broadcast record.

5. Efficient use of frequency.

6. Character of the applicants.

7. Other factors.

While the measures of success in acquiring a license that are presented in this report

were influenced by these factors, we do not control for these factors in the measures that

we present in this report. A companion report, “Logistic Regression Models of the

Broadcast License Award Process for Licenses Awarded by the FCC“ develops models

of win rates by minority and gender status that control for some of these factors.

Minority and Gender Credit in Comparative Hearings

While the criteria set forth by the FCC in 1965 included diversification of control,

initially the FCC refused to include the racial composition of an applicant group as a

relevant factor in a comparative hearing. This position was challenged in 1965 by the

Comint Corp applicant group in the comparative hearing for a TV broadcast license in

Orlando, Florida.

In 1965, the D.C. Court of Appeals vacated the decision that awarded the TV license to

Mid Florida Corp. and opened the license to competition. Eight applicants filed for

ownership and the matter went to comparative hearing. In the comparative hearing, one

of the applicants, Comint Corp., filed an application that included two black owners

with a 14% shared interest. The proposed community for the license awarded had a

25% minority population. Comint argued that minority ownership should be given

comparative credit on the basis of the 1965 statement on comparative hearings (1

F.C.C.2d 393 (1965)) which stated that the "two primary objectives toward which the

process of comparison . . . are . . . the best practicable service to the public, and . . . a

maximum diffusion of control of the media of mass communications." The FCC noted

that while it:

"is sympathetic with Comint's argument and recognizes the validity

of the goal of increased minority ownership of the media of mass
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communications .... however, the Communications Act, like the

Constitution, is color blind and therefore, in a comparative broadcast

proceeding, which is governed by the Commission's Policy

Statement . . . Black ownership cannot and should not be an

independent comparative factor . . . rather, such ownership must be

shown on the record to result in some public interest.”

Comint challenged the FCC’s refusal to explicitly consider race in the comparative

hearing process and appealed the FCC’s ruling to the DC Court of Appeals.

In the 1974 decision 495 F.2d 929 (D.C. Cir. 1974), the DC Court of Appeals

reversed the result of the Mid-Florida comparative hearing. The Court held that

comparative merit should be awarded to an applicant, two of whose stockholders,

each owning approximately seven percent of the applicant's stock, were Black and

would participate in the operation of the station. The Court pointed out that both of

the Black principals were local residents of the community being applied for who

had been active in advancing the interests of Black members of the community, and

that 25 percent of the population of the area applied for were Black. It also noted

that since the highest interest owned by any of the applicant's principals was ten

percent, the two stockholders' individual and combined ownership was substantial.

In addition, no Blacks were then participating in the ownership or management of

any of the media of mass communications in that community. In these

circumstances, the Court concluded that minority stock ownership is "a consideration

relevant to a choice among applicants of broader community representation and

practicable service to the public." (161 U.S. App. D.C. at 357, 495 F.2d at 937.) The

court went on to comment:

It is consistent with the primary objective of maximum

diversification of ownership of mass communications media

for the Commission in a comparative license proceeding to

afford favorable consideration to an applicant who, not as a

mere token but in good faith, as broadening community

representation, gives a local minority group media

entrepreneurship.... We hold only that when minority

ownership is likely to increase diversity of content, especially

on opinion and viewpoint, merit should be awarded. (TV 9

Inc. v. FCC, 495 F.2d 929 (D.C. Cir. 1973), cert. denied, 418

U.S. 986 (1974)).

Accordingly, without recommending or requiring any quota system, the Court held that

merit should be awarded for minority ownership where it is likely to increase the

diversity of program content, especially of opinion and viewpoint. In a Supplemental

Opinion, the Court emphasized that it was not holding that merit should be based on

Black ownership alone, but rather in that case upon a meaningful combination of

ownership and participation in station affairs which indicated that Black persons having
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a substantial identification with minority rights would be able to translate their positions

and their ownership stake into meaningful effect on this aspect of station programming.

The Court also explained that "merit" meant only "favorable consideration," or a plusfactor, not a "preference," and that it was to be weighed along with other relevant factors

in determining which applicant is to be awarded a preference. (161 U.S. App. D.C. at

361, 495 F.2d at 941.)

This decision set a new precedent for the incorporation of minority participation as a

factor in the comparative hearing process.

Not long after the Court of Appeals decided that minority credit for integrated minority

owners was appropriate, Administrative Law Judges began deciding cases on this basis.

Additionally, administrative law judges at the FCC expanded on the TV 9 decision. In

particular, the considerations applied to race in the TV 9 decision were applied to gender

in the Rosemore decision.

In Rosemore Broadcasting, Co., Inc., (54 F.C.C. 2d 394, 418 (1975)), the FCC reasoned

that integrated female ownership should be awarded credit in comparative hearings

because women, like minorities, are "likely to increase diversity of content." The FCC

went on to state that female participation in an application can be given credit when it

“reflects broader community representation.” Because two of the three individuals

associated with Rosemore Broadcasting Co.’s application were female and these women

planned on playing a significant role in the day-to-day operation of the broadcast

station, the Rosemore application was enhanced in the FCC’s eyes. The Rosemore

Broadcasting Company went on to win the license in the comparative hearing.

Since the DC Court of Appeals in 1974 had set in place minority ownership and

employment policies within comparative hearings the FCC and Administrative Law

Judges had started awarding minority credit to applicants for broadcast licenses.

However, in 1978 the FCC observed a "continuation of an extreme disparity between

the representation of minorities in our population and in the broadcasting industry" and

subsequently issued "further Commission action" or Statement of Policy on Minority

Ownership of Broadcasting Facilities (See 68 F.C.C.2d 979, 982). This statement

formalized the use of minority merits in the comparative hearing process.

Metro Broadcasting, Inc.

Reviewing the FCC’s policies under intermediate scrutiny, the Supreme Court held that

the FCC's policy of minority ownership and employment in comparative hearings which

gave enhancement credit for minority ownership and participation and the policy of

allowing "distress sales" to FCC-approved minority-owned firms did not violate equal

protection under the Fifth Amendment.

The Court reasoned:
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Minority preference policies adopted by the Federal Communications

Commission (FCC)-- do not violate the equal protection component

of the Federal Constitution's Fifth Amendment, where Congress has

enacted appropriations legislation (101 Stat 1329-31, 102 Stat 2216,

and 103 Stat 1020) prohibiting the FCC from spending any

appropriated funds to examine or change its minority ownership

polices, because (1) the policies in question have been mandated by

Congress; (2) the interest in enhancing broadcast diversity is, at the

very least, an important governmental objective; and (3) the policies

in question are substantially related to the achievement of the

government's interest, since (a) both the FCC and Congress--whose

joint determination must be given great weight--have concluded that

there is a relationship between expanded minority ownership and

greater broadcast diversity, (b) this judgment is based on extensive

empirical evidence rather than on impermissible stereotyping, and (c)

the policies are in other relevant respects substantially related to the

goal of promoting broadcast diversity...

Gender Ownership Policies

Gainesville Media, Inc.

Approximately one month after the Commission issued Statement of Policy on Minority

Ownership of Broadcasting Facilities, a Review Board hearing the Gainesville Media,

Inc. case reanalyzed its decision regarding female ownership credit in comparative

hearings. Initially, the board held that . . .

since there was no evidence in the record of the extent of female

ownership in the mass media in Gainesville, we had no basis on

which to conclude that such participation would achieve a public

interest benefit. Upon further reflection, we now believe the better

course is to consider female ownership and participation, despite

the absence of record evidence regarding the ownership situations

at other stations (see Gainesville Media, Inc., 70 F.C.C.2d 143,

149 (Rev. Bd. 1978)).

Soon after the Gainesville decision, a review board clarified the justification and

reasoning for female ownership policies. The Board concluded:

... merit for female ownership and participation is warranted upon

essentially the same basis as the merit given for black ownership

and participation, but that it is a merit of lesser significance. The

basic policy considerations are the same. Women are a general

population group which has suffered from a discriminatory

attitude in various fields of activity, and one which, partly as a
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consequence, has certain separate needs and interests with respect

to which the inclusion of women in broadcast ownership and

operation can be of value. On the other hand, it is equally obvious

that the need for diversity and sensitivity reflected in the structure

of a broadcast station is not so pressing with respect to women as

it is with respect to blacks--women have not been excluded from

the mainstream of society as have black people (see Mid-Florida

Television Corp., 70 F.C.C.2d 281, 326 (Rev. Bd. 1978), set aside

on other grounds, 87 F.C.C.2d 203 (1981)).

This decision demonstrated that credit is applied for female participation in a broadcast

license application, but that credit is not as significant as the credit applied for minority

participation in a broadcast license application.

In 1993’s Bechtel decision 10 F.3d 875 (D.C. Cir. 1993), the D.C. Circuit

Court found that the “continued application of the integration credit is arbitrary and

capricious, and therefore unlawful.” The court stated that the policy of extending

additional credit to applicants who intended to personally manage and operate the

broadcast stations was “without foundation.” By invalidating the integration credit

the court effectively eliminated gender and race ownership and employment policies

associated with the integration credit. In 1994 the FCC suspended all active

comparative hearings until an adequate resolution to the issues raised in Bechtel

could be formulated.

The Telecommunications Act of 1996 eliminated the role of comparative

hearings in the renewal of broadcast licenses. The 1994 suspension of the comparative

hearing process effectively became permanent in 1997 when Congress mandated that

the FCC utilize a competitive bidding process for the distribution of all future

commercial broadcast license awards.7 The first auction associated with this mandate

occurred in October of 1999 and generated (unofficially) about $58 million from the

distribution of 116 broadcast licenses and included several frozen license applications

from the Bechtel ruling.

While minority ownership policies were not included in this auction process,

first-time broadcasters and “small” broadcasters were accorded with auction credits to

assist in their bidding.

After the suspension of the comparative hearing process due to the Bechtel

decision, but before the implementation of the broadcast license auctions, two

important court cases were decided which will impact the ability of the FCC to

implement minority and female ownership and employment policies in the future.

 

7

 See Omnibus Budget Reconciliation Act of 1993. Pursuant to this Act, the FCC received the authority

to conduct auctions. Also note that competitive bidding was not required for broadcast license awards in

which only one applicant expressed interest.
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In the 1995 Adarand decision [515 U.S. 200 (1995)], the Supreme Court held

that any federal program that uses racial or ethnic criteria as a basis for decision

making must serve a compelling governmental interest such as remedying past

discrimination and must be narrowly tailored to serve that interest. Furthermore, the

court ruled that any racial distinctions employed by a local, state, or the federal

government “must be analyzed by the reviewing court under strict scrutiny,”

specifically overruling the standard of review used in Metro Broadcasting.

In United States v. Virginia, 518 U.S. 515 (1996), the Supreme Court

considered the distinctions made by local, state, and the federal government with

respect to gender. In this case the court reaffirmed that these gender distinctions

need only satisfy “intermediate scrutiny”. While the definition of intermediate

scrutiny is somewhat vague, it is clear that intermediate scrutiny is a lower standard

than strict scrutiny.

III. Data Collection

In order to develop statistics about the success of female, ethnic and minority and

majority race groups in the comparative hearing process, KPMG collected data from

FCC archives in Suitland Maryland during the period October, 1999 through March,

2000. Within the files on comparative hearing proceedings, maintained as paper files at

the National Records Center, exist data on the declared minority status of parties to

applications for broadcast licenses that were considered in the comparative hearing

process. Also available are outcomes of the comparative hearings, i.e. a record of which

applications have been awarded the licenses.

The data collection effort involved collecting information for 3063 parties involved in

775 applications in a sample of 230 comparative hearings over the periods 1978 to 1981,

and 1989-1993. These periods were selected to satisfy a number of requirements.8

First, these were both periods when financial information was collected in the license

 

8

 The FCC also requested an analysis of the period before minority preferences were in place. However,

the cost of acquiring the necessary data prior to the minority and female preference period would have

been prohibitive. KPMG examined the records in the FCC archives and determined that there was

insufficient data on race of applicant. Therefore, analysis of this period would require KPMG to locate

and survey license applicants using contact (name and address information) that was 20 or more years old.

Based on a pilot survey of secondary market participants who sold a broadcast station between 1993 and

1999, KPMG estimated that only a 3.2 percent response rate could be achieved. Based on this experience

and due to the fact that these contact information were approximately 20 years old, it was highly unlikely

that KPMG would have been able to collect sufficient data for the pre-preference period; therefore this

part of the study was terminated.
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application.9 Second, during these periods, the FCC’s stated policy was to provide

credit for minority applicants.

KPMG retrieved documents from a random sample of the hearings that occurred during

these two time periods. The universe of available hearings was made available to

KPMG in two formats. For the period prior to 1983, the Administrative Law Judge

Listing was used. This is a paper database. For the period after 1983 we relied upon the

BAPS database. The BAPS database is an electronic database containing information

on each comparative hearing that took place from the early 1980’s up to today. Both

data sources provide the following important information with regards to each hearing:

• unique hearing identifiers

• service

• ascension number.

• call sign

• start date for hearing

• end date for hearing

Tables 1 and 2 show the population of hearings and population of applications for radio

and television hearings, broken into the two time periods.

Table 1.

Number of Hearings

Years 1978-

1981

 1989-

1993

Total

All Licenses 421 142 563

 Radio 286 134 420

 AM 85 0 85

 FM 201 134 335

 TV 135 8 143

 

9 While financial information was not necessary for the construction of success ratios for groups in

attaining broadcast licenses (utilization ratios), it was necessary for developing a regression model of the

award process based on the factors and policies identified by the FCC as important to the award of a

broadcast license. Although the selection of these time periods was guided by the requirements of the

regression model, these periods are also useful for the construction of utilization ratios. Both of these

time periods encompass the period when minority preference policies were used by the FCC in the award

of broadcast licenses.
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Table 2.

Number of Applications

Years 1978-

1981

1989-

1993

Total

All Licenses 1,064 595 1,659

 Radio 716 583 1,299

 AM 177 0 177

 FM 539 583 1,122

 TV 348 12 360

A sample of 230 comparative hearings was drawn from the population of hearings using

stratified random sampling. The sample was stratified by service (AM, FM, and TV).

This sample size was selected in an effort to balance the cost of data collection with the

need to obtain a reasonable level of accuracy at various levels of disaggregation.

Once the sample was drawn, data collection personnel, who were primarily made up of

personnel with legal or paralegal backgrounds, retrieved the files from the National

Records Center in Suitland, MD. and collected the necessary data.10 The data items that

were collected for the construction of the utilization ratios come principally from the

application form 301. The items from this form are shown in appendix I.

IV. Definitions of Win Rates, Availability, and Disparity Ratios

Differing definitions for availability, utilization, and disparity ratios may offer a variety

of insights; accordingly, we have used these data to develop a variety of estimates.11

The differences in the estimates that appear in this report are mainly due to differing

measures of availability, which is defined as the pool of applicants or potential

applicants who are willing and able to compete for a broadcast license.

Before presenting results, this section describes the measures and how they are

constructed. All of the win ratios we have developed are expressed as a ratio of a

measure of success (or winning applicants) and a measure of participation (or

applicants). A number of different ratios are presented. They are generally presented

in the order of complexity of the calculation, with the simplest calculations presented

 

10 The data collected for the development of the utilization ratios was limited to a few key items. A more

comprehensive data collection was performed for a subset of these hearings for the regression model.

11 While we use the words participation and availability almost interchangeably in this document, there is

a distinction. Participation refers to the people who have actually participated in the comparative hearing

process. While we use this as a measure of availability, we should also point out that this measure could

be biased downward if discrimination was responsible for inhibiting participation. More information on

this issue is provided in section IV, “Definition of Win Rates, Availability ....”.
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first. While we present a number of measures, our preferred measure is called the

“relative award rate” and it is presented in Table 13.

A key concept to keep in mind when reviewing these results is that there are different

levels of aggregation that can be used to make calculations of success in acquiring

licenses. This is due to the nature of the comparative hearing process and the fact that

hearings are made up of multiple applications and applications can be made up of

multiple parties of different race and gender who cooperate to bid on licenses.

The party is the lowest level for which measures of success can be calculated. Next

there is the application level. Therefore, when we measure win rates, we can do it at the

party level; i.e. how many parties of a particular group were involved as participants in

winning applications. Or we can measure win rates at the application level, e.g. we can

measure how many applications won where at least 1 party of a particular group was

represented in the application or we could measure how many applications won when a

particular group controlled more than 50% of the equity in the application. We present

measures that use all of these definitions here.

There are strengths and weaknesses to all of the measures that we present. For example,

looking at the data on a party basis, as we will do in tables 7 through 12, shows how a

demographic group does overall but says nothing about the distribution of results for a

group. If many parties from one demographic group were concentrated in only a few

winning applications, it might appear as if the group were acquiring more licenses than

it was actually acquiring because success would be attributed to a lot of parties who won

few licenses. Also, accounting for equity control may be important because if that

control is lacking, then what appears to be adequate participation may in fact not be

meaningful participation. Finally, it is also important to distinguish win rates based on

the value of licenses. It is conceivable that a group could be winning a reasonable

number of licenses but if they were licenses of little value, this would not be a

reasonable result. To account for this possibility, we have weighted the win rates by

population of the area in which the licenses are awarded where population serves as a

proxy for value of the license.12

Definitions for the measures that will appear in the tables that follow are provided

below.

Relative win rate (party basis) = # winning parties in-group / # of parties in-group.

Relative win rate (equity basis) = equity of winning parties in group / equity of all

parties in group

 

12 While we have included a population weighted measure here, there are many other factors that we

should control for. KPMG’s companion report performs this more rigorous analysis.
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Absolute win rate = # winners in-group / total # of parties in all groups combined

% of winners = # of winners in group / total number of winners

(also known in literature as a utilization rate)

% participation = # of parties in group / total number of parties

Disparity ratio = % of winners / % participation

The relative award rate R is defined by the following equation:

∑ ∑ ∑ = = =

= − = −

N

i

i

N

i

i

N

i

i i m

N

z

N

z m

N

R

1 1 1

1 1

( )

1

where N is the number of hearings, i indexes hearings, zi takes a value of one if the

license in hearing i is awarded to a minority and zero if not, and mi is the percentage of

minority applicants in hearing i. The relative award rate is defined analogously for nonminorities, males, and females.

Winner take all relative win rate = #winning parties in group where equity is

controlling / #parties in group

It is informative to contrast calculated win ratios across different groups of applicants.

Nevertheless, it is important to keep in mind that win rates cannot account for

differences between groups that span multiple dimensions. For example, when

contrasting a win rate for male applicants with a win rate for female applicants it is

important to keep in mind that the ratio does not account for differences in other

applicant characteristics (asset holdings for example) across the two groups. This

suggests that it would be inappropriate to conclude that discrimination is taking place

simply on the basis of win rates. Further analysis, which is presented in a companion

study, using logistic regression models, discusses whether there are significant

differences in award rates based on race or gender, while controlling for many factors

that affect award rates.

The definition of the pool of “eligible participants” associated with various groups has

frequently been a disputed issue in the calculation of availability ratios for studies of

disparity. Typically, the broader the measure of the pool who are eligible to participate

for each group, the greater the dispute because a broader pool is less likely to contain

qualified and willing participants. At one extreme, the entire population of the group in

question can be classified as eligible participants. But the entire population is not

qualified or willing to participate in the process and therefore this is an inappropriate

measure of eligibility. The Croson decision suggests a measure that contains only those
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who are qualified, willing and able to participate.13 The measure of availability used in

this study is narrower and more conservative than that in Croson. In the contracting

context, availability is measured by counting all pre-qualified contractors, not just those

who apply for a given contract. In licensing, there is no group of pre-qualified bidders,

so the study uses those who actually applied for the given license.

Consistent with the conditions of Croson, we use a measure of the pool of eligible

participants for each group. For the purpose of the win rates, availability, and disparity

ratios presented here, the set of eligible participants associated with each group is

limited to the set of individuals in that group that we actually observed participating in a

comparative hearing.14

It is certainly conceivable that a broader measure of the pool of eligible participants

could be more relevant. A broader and theoretically more appealing measure might

include those who would have liked to apply, but failed to apply, because they may have

been frustrated by the process or did not have equal access to the resources required to

fulfill the application requirements.

We have not attempted to develop a methodology to measure the number of eligible

participants for various groups using definitions of availability that are broader than the

number who have actually participated in the hearing process. We believe that this line

of inquiry is certainly warranted since the availability measure is an extremely important

determinant of whether one can adequately measure the existence of disparity. If the

measure of availability excludes potential applicants who have not been able to apply

due to the existence of discrimination, then disparity measures that do not account for

this possibility will be biased against a finding of discrimination. On the other hand if

the measure of availability is over-inclusive so that it were to include those who are not

qualified, willing and able to participate in the process, then disparity measures using

such a measure of availability would be biased towards a finding of discrimination. The

measures of availability that we use in this study are certainly not over-inclusive and are

more likely to be under-inclusive.

Win rate and disparity measures that are based on a narrow definition of availability,

such as the one we use here, result in a conditional measure of win rates or disparity.

The disparity and availability ratios are conditional in the sense that we are testing only

the second of two dimensions of the process. The first dimension of the hearing process

relates to who is able to participate in a hearing; i.e. who is able to apply. The second

dimension relates to who wins given that they have passed the first hurdle, i.e. been able

 

13 488 U.S. 469, 109 S.Ct. 706; City of Richmond v. J.A. Croson Company (1989) U.S. Supreme Court

14 The disparity measure that we calculate is widely used by state and local governments when calculating

disparity in the award of public contracts. This measure is not necessarily the best measure for the

purpose of measuring disparity in the award of licenses, which unlike recurring public contracts, are only

awarded on a one-time basis. Our preferred measure is the relative award rate that is presented in Table

13.
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to participate and have been included in the application and hearing process. Our

analysis only considers the second of these two dimensions. If minority or female

participation has been affected by impediments such as inadequate access to capital, due

to discrimination, the disparity measures represented here would not capture this

dimension of the licensing process.

We do note, as the following data will suggest, that minority participation in

broadcasting is very low relative to minority representation in the general population.

Table 3 shows the minority participation in broadcasting and minority shares of the U.S.

population.
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Table 3.

Participation in Comparative Hearings and Percent of U.S. Population in 1990*

Percent of Parties in

Hearings (1)

Percent of U.S. Population

(2)

Total Minority 8.9% 23.8%

 Black 3.4% 12.2%

 Asian .4% 2.7%

 Hispanic 3.9% 8.7%

 American Indian, Eskimo, Aleut .4% .7%

 White 91.1% 76.2%

Male 79.3% 48.7%

Female 20.7% 51.3%

*Notes: (1) Detailed race and ethnic categories do not sum to total minority for the Percent of parties in

hearings, due to nonreporting of this level of detail for a small portion of the minority applicants (.8% fail

to report the level of detail about their minority status). (2) For the percent of U.S. population, there is

slight overlap in the figure for black and Hispanic because black includes those blacks of Hispanic origin

(about .5% of the 12.2% of blacks are of Hispanic origin).

There is certainly a large difference between the minority share of participants in

comparative hearings and the minority share of the U.S. population.

Note that during the period that we are performing this analysis, the FCC’s stated policy

was to provide credit for minority participation in applications. Therefore, when we

present win rates and disparity rates, one would expect that if the FCC’s policy has been

effective, there would be greater minority participation (and probably greater utilization)

than in the absence of this policy. We can assume then that the level of female and

minority participation, which is low relative to female and minority representation in the

population, would have been even lower still in the absence of the FCC’s stated

policy.15

V. Participation by Race and Gender in Comparative Hearings

 

15 Without collecting data from the period before preferences were in place, it is not apparent how much

additional minority and female participation has resulted from the FCC’s stated policy of providing credit

for minority and female participation in applications. However, it has been established that ownership of

broadcast licenses was as low as 10 out of 7,500 radio stations and none of the more than 1,000 television

stations held in 1971 (see TV 9 Inc. v. FCC, 161 U.S. App. D.C. 349, 347, n. 28, 495 F.2d 929, 937 n. 28

(1973)).
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Table 4 shows the number of hearings in our sample.16 Tables 5 and 6 present data on

participation, by demographic group, using alternative definitions of participation. Table

5 shows the number of parties to applications considered in hearings, broken out by race

and gender, and the percentage of each group of the total number of participants in these

230 comparative hearings. Table 6 is similar to table 5 except that it shows the number

of applications where a group has at least 1 party of a given demographic group

participating in the application.

Table 4.

Number of Comparative Hearings in Sample by Type of Hearing

Radio and Television 230

 Radio 155

 AM 25

 FM 130

Television 75

We can see from Tables 5 and 6 that there were 3082 parties in 740 applications in these

230 hearings. 91.1% of all participants were white while 8.9% were minority. Of the

minority participants, about 43.1% are Black, 48.8% are Hispanic, 4.5% are Asian, and

3.7% are American Indian.17

Men made up 79% of all parties while females made up 21%. A strict comparison of

the number of minority and female participants to the population at large would indicate

low minority and female participation in the hearing process. While we have described

earlier that this is not an appropriate comparison for the purposes of Croson, it does

demonstrate that for at least the first dimension of the comparative hearing process,

participation; minority ownership of broadcast stations is probably low because of low

participation rates. This says nothing about the issue of whether the comparative

hearing award process was fair or not.

Table 5.

Participation (number of parties in applications) by Minority Status and Gender

in Broadcast, Radio, and TV Comparative Hearings

 

16 We define a hearing as consisting of two or more applications. We define each application as

consisting of one or more parties. For our purposes the word “party” and the word “individual” are

synonymous.

17 It is assumed that the discrepancy between total minority reported and the sum of the finer reporting

level (by race) is equally distributed across the race categories.
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Broadcast

(Radio&TV)

Radio Television

Total Parties 3082 1526 1556

Headcount Percent Headcount Percent Headcount Percent

White male 2262 73.4% 1060 69.4% 1202 77.2%

White female 546 17.7% 306 20.1% 240 15.4%

Minority male 182 5.9% 105 6.9% 77 4.9%

Minority female 92 3.0% 55 3.6% 37 2.4%

White 2808 91.1% 1366 89.5% 1442 92.7%

Minority 274 8.9% 160 10.5% 114 7.3%

Black 106 3.4% 67 4.4% 39 2.5%

Hispanic 120 3.9% 70 4.6% 50 3.2%

Asian 11 0.4% 4 0.3% 7 0.4%

American Indian 12 0.4% 8 0.5% 4 0.3%

Male 2444 79.3% 1165 76.3% 1279 82.2%

Female 638 20.7% 361 23.7% 277 17.8%

* minorities do not add exactly to total because sometimes, parties only indicated minority status

and failed to specify the details of which minority group they were in.
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Table 6.

Participation (Number of applications) by Minority Status and Gender in

Comparative Hearings (with at least 1 party in this demographic group)

 Broadcast (Radio&TV) Radio Television

Total applications 740 Percent 494 Percent 246 Percent

White male 662 89.5% 439 88.9% 223 90.7%

White female 332 44.9% 213 43.1% 119 48.4%

Minority male 90 12.2% 48 9.7% 42 17.1%

Minority female 67 9.1% 41 8.3% 26 10.6%

White 705 95.3% 474 96.0% 231 93.9%

Minority 122 16.5% 72 14.6% 50 20.3%

 Black 50 6.8% 31 6.3% 19 7.7%

 Hispanic 57 7.7% 30 6.1% 27 11.0%

 Asian 8 1.1% 3 .6% 5 2.0%

 American Indian 10 1.4% 6 1.2% 4 1.6%

Male 694 93.8% 458 92.7% 236 95.9%

Female 374 50.5% 239 48.4% 135 54.9%

VI. Win Rates and Participation Rates by Race, Gender in Comparative

Hearings

In calculating win rates and disparity ratios, it is critical to determine which applicant

actually won each hearing. The data indicating which applicants won the comparative

hearings come from either the Broadcast Applications Processing System (BAPS)

database or the Administrative Law Judge Listing. This data is also confirmed in the

manual data collection operation where we retrieved information directly from archived

comparative hearing documents. On occasion, the decision of the ALJ to award a

license to a particular applicant is appealed to a higher court and there is a reversal of a

decision. We have conducted the additional data collection necessary to capture these

post comparative hearing reversals. In our sample of 230 hearings, this occurred 15

times.

Tables 7 through 12 show counts of the number of parties by race and gender who have

participated in applications that won in a comparative hearing. The tables also show

participation rates, win rates, and disparity ratios, both unadjusted and adjusted for

differences in the population of areas where the licenses were granted. Population

weighted participation and win rates are shown in tables 8, 10, and 12. These rates are
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designed to determine if there has been any difference in the win or participation rates

according to the value of the license, where the value of the license is proxied by

population of the area in which the license is awarded. Population data that are used as

weights come from U.S. Census data.18

There are two relative win rate measures in the tables. Relative win rate (party basis) is

simply the number of winning parties in the group divided by the total number of

participants of that group. Relative win rate (equity basis) is similar, except that wins

are determined based on which group has majority equity. Relative win rate (equity

basis) can differentiate between a win with minority participation but no equity, and a

win with participation and equity. Wins with substantial equity participation are

accorded higher weight than wins with little or no equity participation.

The tables also show each group’s share of winners and share of participants. To the

extent that the share of winners exceeds the participation share, the group is winning at a

higher rate than would be dictated by their participation alone. To the extent that a

participation rate exceeds winning share, then the group is winning less often than their

participation would dictate. Based on these definitions, table 7 shows that over all

hearings, non-minorities are winning at slightly lower rates (90.1% vs. 91.1%) than their

rate of participation while minorities are winning at slightly higher rates (9.9% vs.

8.9%) than their participation rate.

By type of service, as shown in tables 9 and 11, there is a slightly different story.

Because there does not appear to be any difference between participation and win rates

in radio (0% difference between win rates and participation rates for both non-minorities

and minorities) but slightly higher win rates relative to participation for minorities in TV

(9.2% win rates versus 7.3% participation rate).

Both white females (19.7% vs. 17.7%) and minority females (3.5% vs. 3%) are winning

at higher rates than their participation rate. White males are winning at slightly lower

rates (70.5% vs. 73.3%) than their participation rates, while minority males (6.3% vs.

5.9%) are winning at a slightly higher rate than their participation rate.

This story changes slightly when participation and wins are weighted by population.

Weighting by population elevates the importance of participation and wins in higher

population areas. While there is not much impact on the results for broadcast as a

whole, the population weighting affects the results for radio. For radio, after weighting

for population, minorities do a little bit worse than non-minorities and females do a little

bit worse than males. The differences between participation and win rates after

weighting by population are too small to suggest that any sort of bias is occurring in the

award process for radio licenses such that minorities would not be as likely to win in

higher population areas.

 

18 Place and County Subdivision Population Estimates,

http://www.census.gov/population/www/estimates/citypop.html
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Table 7.

Win Rates and Participation Rates (By race and gender) – Broadcast

Total parties 3082

Winning Parties # of

Wins

#

parties

Relative

win rate

(party basis)

Relative

win rate

(equity basis)

Absolute

win rate

% of

winners

% participation

Disparity

Ratio:

%winning

÷

%participation

White male 825 2262 36.5% 30.9% 26.8% 70.5% 73.4% .96

White female 229 546 41.9% 36.1% 7.4% 19.6% 17.7% 1.11

Minority male 75 182 41.2% 40.9% 2.4% 6.4% 5.9% 1.09

Minority female 41 92 44.6% 32.5% 1.3% 3.5% 3.0% 1.17

White 1054 2808 37.6% 31.8% 34.2% 90.1% 91.1% .99

Minority 116 274 42.3% 38.1% 3.8% 9.9% 8.9% 1.11

 Black 51 106 48.1% 44.1% 1.7% 4.4% 3.4% 1.29

 Hispanic 47 120 39.2% 37.5% 1.5% 4.0% 3.9% 1.03

 Asian 5 11 45.5% 69.4% 0.2% 0.4% 0.4% 1.00

 American Indian 2 12 16.7% 7.1% 0.1% 0.2% 0.4% .500

Male 900 2444 36.8% 31.7% 29.2% 76.9% 79.3% .97

Female 270 638 42.3% 35.5% 8.8% 23.1% 20.7% 1.12

Relative win rate (party basis) = # winning parties in-group / # of parties in-group.

Relative win rate (equity basis) = winning equity in group / total equity for group

Absolute win rate = # winning parties in-group / total # of parties.

% of winners = # of winners / total number of winners

% participation = # of parties / total parties

Disparity ratio = % of winners / % participation
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Table 8.

Population Weighted Win Rates (By race and gender) – Broadcast

Population Weighted

Group % of

winners

%

participation

Disparity Ratio

%winning

÷

%participation

White male 71.4% 75.3% .95

White female 17.5% 14.7% 1.19

Minority male 8.8% 7.9% 1.11

Minority female 2.3% 2.1% 1.10

White 88.9% 90.0% 1.0

Minority 11.1% 10.0% 1.11

 Black 6.1% 4.8% 1.27

 Hispanic 3.0% 4.1% .73

 Asian 0.5% 0.6% .83

 American Indian 0.2% 0.2% 1.0

Male 80.2% 83.2% .96

Female 19.8% 16.8% 1.18

% of winners = # of winners / total number of winners – weighted by population in area of license

% participation = # of parties / total parties – weighted by population in area of license

Disparity ratio = % of winners / % participation
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Table 9.

Win Rates and Participation Rates (By race and gender) – TV

Total parties 1556

Winning Parties # of Wins #

parties

Relative

win rate

(party basis)

Relative

win rate

(equity basis)

Absolute

win rate

% of

winners

% participation

Disparity:

%winning

÷

%participation

White male 440 1202 36.6% 29.4% 28.3% 72.6% 77.2% .94

White female 110 240 45.8% 39.4% 7.1% 18.2% 15.4% 1.18

Minority male 36 77 46.7% 36.7% 2.3% 5.9% 4.9% 1.20

Minority female 20 37 54.0% 22.7% 1.3% 3.3% 2.4% 1.38

White 550 1442 38.1% 30.7% 35.3% 90.8% 92.7% .98

Minority 56 114 49.1% 32.6% 3.6% 9.2% 7.3% 1.26

 Black 23 39 59.0% 39.2% 1.5% 3.8% 2.5% 1.52

 Hispanic 22 50 44.0% 32.1% 1.4% 3.6% 3.2% 1.13

 Asian 3 7 42.9% 39.8% 1.9% 0.5% 0.4% 1.25

 American Indian 1 4 25.0% 4.3% 0.1% 0.2% 0.3% .67

Male 476 1279 37.2% 30.1% 30.6% 78.5% 82.2% .95

Female 130 277 46.9% 35.6% 8.4% 21.5% 17.8% 1.21

Relative win rate (party basis) = # winning parties in-group / # of parties in-group.

Relative win rate (equity basis) = winning equity in group / total equity for group

Absolute win rate = # winning parties in-group / total # of parties.

% of winners = # of winners / total number of winners

% participation = # of parties / total parties

Disparity ratio = % of winners / % participation
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26

Table 10.

Population Weighted Win Rates (By race and gender) – TV

Population Weighted

Group % of winners %

participation

Disparity Ratio:

%winning

÷

%participation

White male 74.0% 80.1% .92

White female 18.6% 15.3% 1.22

Minority male 5.2% 3.2% 1.63

Minority female 2.1% 1.3% 1.62

White 92.6% 95.5% .97

Minority 7.4% 4.5% 1.62

 Black 1.9% 1.5% 1.27

 Hispanic 3.2% 2.0% 1.60

 Asian 0.5% 0.4% 1.25

 American Indian 0.2% 0.2% 1.00

Male 79.2% 83.3% .95

Female 20.8% 16.7% 1.25

 % of winners = # of winners / total number of winners – weighted by population in area of license

 % participation = # of parties / total parties – weighted by population in area of license

Disparity ratio = % of winners / % participation
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Table 11.

Win Rates and Participation Rates (By race and gender) – Radio

Total parties 1526

Winning Parties # of Wins #

parties

Relative

win rate

(party basis)

Relative

win rate

(equity basis)

Absolute

win rate

% of

winners

%

participation

Disparity

Ratio:

%winning

÷

%participation

White male 385 1060 36.3% 31.7% 25.2% 68.3% 69.5% .98

White female 119 306 38.9% 35.1% 7.8% 21.1% 20.1% 1.05

Minority male 39 105 37.2% 44.0% 2.6% 6.9% 6.9% 1.00

Minority female 21 55 38.2% 38.0% 1.4% 3.7% 3.6% 1.03

White 504 1366 36.9% 32.4% 33.0% 89.4% 89.5% 1.00

Minority 60 160 37.5% 41.9% 3.9% 10.6% 10.5% 1.01

 Black 28 67 41.8% 46.4% 1.8% 5.0% 4.4% 1.14

 Hispanic 25 70 35.7% 42.9% 1.6% 4.4% 4.6% .96

 Asian 2 4 50.0% 75.0% 0.1% 0.4% 0.3% 1.33

 American Indian 1 8 12.5% 8.2% 0.1% 0.2% 0.5% .40

Male 424 1165 36.3% 32.6% 27.8% 75.0% 76.3% .98

Female 140 361 38.8% 35.5% 9.2% 24.8% 23.7% 1.05

Relative win rate (party basis) = # winning parties in-group / # of parties in-group.

Relative win rate (equity basis) = winning equity in group / total equity for group

Absolute win rate = # winning parties in-group / total # of parties.

% of winners = # of winners / total number of winners

% participation = # of parties / total parties

Disparity ratio = % of winners / % participation
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28

Table 12.

Population Weighted Win Rates (By race and gender) – Radio

Population Weighted

Group % of winners %

participation

Disparity Ratio:

%winning

÷

%participation

White male 58.3% 56.0% 1.04

White female 11.8% 12.1% .98

Minority male 27.0% 26.7% 1.01

Minority female 2.9% 5.2% .56

White 70.1% 68.1% 1.03

Minority 29.9% 31.9% .94

 Black 27.4% 17.8% 1.54

 Hispanic 2.0% 12.4% .16

 Asian 0.1% 1.4% .07

 American Indian 0.1% 0.1% 1.00

Male 85.2% 82.7% 1.03

Female 14.7% 17.3% .85

 % of winners = # of winners / total number of winners – weighted by population in area of license

% participation = # of parties / total parties – weighted by population in area of license

Disparity ratio = % of winners / % participation

In addition to the relatively simple win rates defined above, we developed a relatively

more sophisticated measure of potential win rate disparity referred to as the “relative

award rate (R)”. The relative award rate for minorities is the percentage of license

awards to minorities relative to average minority participation. The relative award rate

R is defined by the following equation:

∑ ∑ ∑ = = =

= − = −

N

i

i

N

i

i

N

i

i i m

N

z

N

z m

N

R

1 1 1

1 1

( )

1

where N is the number of hearings, i indexes hearings, zi takes a value of one if the

license in hearing i is awarded to a minority and zero if not, and mi is the percentage of

minority applicants in hearing i. The relative award rate is defined analogously for nonminorities, males, and females. These calculations take place across the 230 hearings.

The determination of whether a hearing is won by a minority is dependent upon the

count of minorities in the winning application versus the number of non-minorities in

the winning application. When the number of minorities in the winning application

exceeds the number of non-minorities, the winning application is considered as
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minority. Similarly when the number of females in the winning application exceeds the

number of males, the winning application is considered as female.

The calculation of the relative award rate is also performed using equity as the

determinant of control of the application.

The value of R must lie between one and minus one. If minorities are on average

awarded licenses in proportion to their participation, R will be zero. Thus, we define

“no disparity” as R = 0. If minorities are awarded licenses less than suggested by their

percentage of applications, R will be negative. If minorities are awarded licenses more

than suggested by their percentage of applications, R will be positive.

The measure R has the statistical advantage, among the more sophisticated measures we

considered, of being defined as a population mean. For a population of hearings, we can

estimate the population mean of R by taking a sample of hearings, determining minority

status for each application and for the winning application in each sampled hearing, and

computing the sample mean corresponding to R. The sample mean is an unbiased and

consistent estimator of the population mean R . Further, if the sample is drawn

randomly the sampled hearings are independent, and the variance of the sample mean

can be derived and computed with relative ease. The sample mean and variance can be

used to perform a statistical test of the hypothesis that R = 0, i.e. the hypothesis of no

disparity.

In contrast to some other measures that are presented later, such as the “winner take all

win rates”, the relative award rate is calculated over hearings and measures success in

hearings relative to average participation in hearings.

This is our preferred measure because the calculation of R is based on the relative

minority participation within a hearing. This controls for competition within hearings

of different sizes (number of applications) and places minority participation and win rate

within the context of its particular hearing. Other measures presented in this paper do

not take advantage of hearing groups but, rather, calculates win rates for applications

and parties as if they are independent of one another.

Table 13 presents the relative award rates for All Broadcast, TV, and Radio for nonminorities, minorities, males, and females (using the count of participants in each group

as the determinant of which group controls the winning application).

Table 13.
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Relative Award Rates

(Using majority based on body counts to define winning group)

All Broadcast TV Radio

Male .09 .09 .09

Female -.09 -.09 -.09

Non-minority .014 .01 .015

Minority -.014 -.01 -.015

Table 14 presents the relative award rates for All Broadcast, TV, and Radio for nonminorities, minorities, males, and females (using the majority equity definition as the

determinant of which group controls the winning application).

Table 14

Relative Award Rates

(Using majority based on equity to define winning group)

All Broadcast TV Radio

Male .02 .03 .02

Female -.02 -.03 .-.02

Non-minority .003 .02 -.006

Minority -.003 -.02 .006

According to these two tables, the relative award rates for males are higher than those

for females. The non-minority relative award rates are slightly higher than minority

based on using a definition where the counts of the parties from each group in the

application determine the winning group of the application. Using the alternative

definition where the group with the most equity is defined as the winner of the winning

application, there is little difference between non-minorities and minority relative award

rates.

Standard errors for the estimates in Tables 13 and 14 are shown in Table II.1 in

appendix II. Calculation of the 95% confidence intervals for these estimates suggests

that there is a statistically significant difference between the male and female relative

award rates shown in Table 13 (where the count of parties in each group determines the

group who controls the winning application). This is the only instance where there is a

statistically significant difference in any of these relative award rates. There are no

statistically significant difference between the relative award rates for minorities and

non-minorities.
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It is important to note here that the period examined in this study was the period during

which the FCC awarded credit for minority or female participation.19 Thus, one might

expect that minorities and women would have similar success rates to non-minorities.

VII. Win Rates and Disparity Ratios by Race and Gender, Based on Definition

of Control

Table 15 shows the number of applications that each group controls from an equity

perspective. We refer to the number of these applications as “winner take all” since we

make an assumption that if this application wins, then it is a win for this particular

group.

We classify a particular group as controlling an application if and only if that group

owns greater than 50% of the equity associated with an application. We classify a

particular group as having won a hearing in a winner take all setting if and only if that

group owns greater than 50% of the equity in the winning application for that hearing.

According to this definition of control, non-minorities control 670 or 90.5 % of all

applications while minorities’ control 70 or 9.5 % of all applications. For radio, nonminorities control 451 or 91.3% of radio applications and minorities control 8.7%. For

television, non-minorities control 89% of TV applications and minorities control 11%.

Table 15.

Applications where Group has Majority Equity

 (by Gender and Minority Status)

All

Broadcast

Participation

Share

Radio Participation

Share

TV Participation

Share

Total 740 494 246

 Non-minority 670 90.5% 451 91.3% 219 89%

 Minority 64 8.6% 38 7.7% 26 11%

 Male 600 81.1% 385 77.9% 215 87.4%

 Female 109 14.7% 79 16.0% 30 12.2%

*Ties are excluded from these counts so shares will not sum to exactly 100%.

By gender, females have majority ownership for 109 or 14.7% of applications, which is

split between 79 (16%) for radio and 30 (12.2%) for TV. Males control 600 or 81.1% of

applications, which is split between 385 (77.9%) for radio and 215 (87.4%) for TV.

Table 16 shows the number of winning applications controlled by each group (see panel

1), and the total number of applications controlled by each group (see panel 2) where

 

19 See footnote 8
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control is defined as owning greater than 50% of equity. It also shows the total number

of applications with participation by each group, regardless of control (see panel 3).20

The number of applications (panel 1) will be used as the numerator in an alternative

measure of relative win rates and disparity ratios while number of applications in panels

(2) and (3) will be used as the alternative availability measures for the denominator of

the relative win rates and disparity ratios.

Table 16.

Winner Take All Applications

(Applications by Gender and Minority Status where Group has Majority Equity)

Winning (1) Total (2)

(Narrow Availability Measure)

All Apps Regardless of

Control (3)*

(Broad Availability Measure)

All Radio TV All Radio TV All Radio TV

 Non-minority 213 145 68 670 451 219 705 474 231

 Minority 24 17 7 64 38 26 122 72 50

 Male 191 125 66 600 385 215 694 458 236

 Female 38 28 10 109 79 30 374 239 135

* This measure has the property that applications will have no unique classification for any one group

Counts for each demographic group in (1) and (2) are based on having majority equity in an application.

Counts in (3) are based on having any participation by a demographic group in an application.

Counts in (1) and (2) exclude ties.

Table 17 presents a relative win rate based on the winner take all definition of success

and using the narrow measure of availability, i.e. only the applications for which the

demographic group has majority equity. Table 17a shows the disparity ratio using the

narrow measure of availability.

Table 17.

Winner Take all Relative Win Rate using

Narrow Availability Measure (1) / (2)

All

Broadcast

Radio TV

 Non-minority 31.8% 32.2% 31.1%

 Minority 37.5% 44.7% 26.9%

 Male 31.8% 32.5% 30.7%

 Female 34.9% 35.4% 33.3%

 These calculations are based on data from Table 16; e.g.

Minority TV 7/26=26.9%.

 

20 Participation, in this instance, is simply defined as the presence of at least 1 party of that demographic

group in an application.
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Table 17a.

Disparity Ratio Using

Narrow Availability Measure

All

Broadcast

Radio TV

 Non-minority .98 .97 1.01

 Minority 1.16 1.35 .88

 Male .99 .98 .99

 Female 1.08 1.07 1.07

Disparity ratio = % winning / % availability

e.g. .Minority Broadcast = (24/237) / (64/734) = 1.16

Table 18 shows a relative win ratio based on the winner take all definition of success

and using a broader measure of availability than the measure used in Table 17. Based

on this measure, minority and female controlled applications have a lower probability of

winning a license than non-minority and male controlled applications. Table 18a shows

the corresponding disparity ratio. The broader measure of availability is based on

including all applications with representation in the group, regardless of who controls

the application from an equity perspective. The idea behind this ratio is that availability

should include all who are ready, willing, and able to bid on a license.

Table 18.

Winner Take all Relative Win Rate using

Broader Availability Measure (1) / (3)

All

Broadcast

Radio TV

 Non-minority 30.2% 30.6% 29.4%

 Minority 19.7% 23.6% 14.0%

 Male 27.5% 27.3% 28.0%

 Female 10.2% 11.7% 7.4%

These calculations are based on data from Table 16; e.g.

Minority TV: 7/50=14%
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Table 18a.

Disparity Ratio using

Broader Availability Measure (1) / (3)

All

Broadcast

Radio TV

 Non-minority 1.05 1.03 1.10

 Minority .69 .80 .52

 Male 1.28 1.24 1.37

 Female .47 .53 .36

Disparity ratio = % winning / % availability

Based on using the broader definition of availability in the relative win rates and

disparity ratios, there is a statistically significant difference between both non-minority

and minority relative win rates and disparity ratios and between male and female

relative win rates and disparity ratios. The results from Tables 18 and 18a rely on

broader definitions of availability that includes all those who have participated in the

process, regardless of whether they have the capability of controlling the application

from an equity perspective.

VIII. Level of Competition within Hearings

While another part of the analysis, which is presented in a companion report, will

control for various differences in the characteristics of applicants, we will also provide

here some basic data on the level of competition within hearings, i.e. the number of

applications of various groups within hearings. The purpose of presenting these data is

to get an idea of how competitive each hearing is based on the number of applicants. It

will be interesting to determine if there are any differences in the number of applications

in hearings with and without minority participation.

The following tables show the average number of parties in applications and the average

number of applications in hearings by minority status and gender. Examination of these

averages may be suggestive of the odds of winning a hearing based solely on the

number of competing applications.

Table 19.
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Average number of parties in applications by Race and Gender

All

Broadcast

Radio TV

All Applications 4.2 3.1 6.3

 White 4.3 3.1 6.6

 Minority 5.9 4.5 7.9

 Male 4.4 3.2 6.5

 Female 5.5 4.2 8.0

Averages are based on using only applications with

at least one party that is in group

Based on all applications, there tend to be more parties in applications with minority or

female representation than there are for applications with white parties (5.9 for minority,

5.5 for female, and 4.3 for white). This is a sizable difference. For winning

applications, the difference is even greater; there are 8.3 parties in winning applications

with minority representation, 6.5 parties for winning applications with female

representation, and only 5 parties for winning applications with white representation.

Table 20

Average number of parties per winning application

by Race and Gender

All

Broadcast

Radio TV

All Applications 4.9 3.4 8.0

 White 5.0 3.5 8.3

 Minority 8.3 4.8 13.0

 Male 5.1 3.6 8.4

 Female 6.5 4.5 10.2

Averages are based on using only applications with

at least one party that is in group

Table 21
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Average number of minority parties per winning application

by Race and Gender

All

Broadcast

Radio TV

All Applications .5 .4 .7

 White .4 .2 .7

 Minority 2.3 2.1 2.7

 Male .5 .4 .8

 Female .7 .4 1.1

Averages are based on using only applications with

at least one party that is in group

Table 22

Average Number of white parties per winning application

by Race and Gender

All

Broadcast

Radio TV

All Applications 4.4 3.1 7.2

 White 4.6 3.3 7.6

 Minority 5.9 2.8 10.3

 Male 4.6 3.2 7.6

 Female 5.9 4.1 9.2

Averages are based on using only applications with

at least one party that is in group

Table 23 shows that there are also differences between the number of applications in

hearings with and without minority participation. For those hearings where a minority

is represented within an application, there are on average 3.7 applications per hearing.

For those hearings with female participation, there are an average of 3.4 applications per

hearing, while for those hearings without minority participation, there is an average of

3.2 applications per hearing. This suggests that the odds of winning a license may be

lower in hearings with minority or female participation.

Table 23
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Average Number of Applications per Hearing

by Race and Gender (where there is at least one party of type)

Hearing with at least

one party

All

Broadcast

Radio TV

 White 3.2 3.2 3.3

 Minority 3.7 3.8 3.5

 Male 3.2 3.2 3.3

 Female 3.4 3.4 3.4

Averages are based on using only applications with

at least one party that is in group

The corresponding average number of applications per hearing when there is at least one

application in the hearing that is controlled by a group is shown below. Recall that

control is defined as having greater than 50% equity.

Table 24

Average Number of Applications per Hearing

by Race and Gender (where group has control)

Group with at least

one application

All

Broadcast

Radio TV

 White 3.3 3.2 3.3

 Minority 4.0 4.0 4.2

 Male 3.3 3.2 3.3

 Female 3.9 3.9 4.0

These results are similar to those in the previous table. It appears that minority and

female controlled applications may face more competition in the form of a greater

number of competing applications in the comparative hearing.
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Appendix I: Information Collected from Form 301 for the Development

of Utilization Ratios

General Hearing Information

1. Docket number

2. Number of Applications

3. Community

4. Channel

5. Frequency

6. Service (select one) : ® AM ® FM ® TV

APPLICATION (form 301) INFORMATION

For each Application:

1. Name of Applying Organization:

2. Number of Parties

3. Date Application Filed

4. Winner ® Yes ® No

5. Merger ® Yes ® No

6. Dismiss: ® Yes ® No

7. Appeal: ® Yes ® No

For Each Party to an Application:

1. Party Name

2. Party number

3. Position

4. Ownership (percentage of ownership)

5. Voting (percent of control)

6. Gender (pick one) ® Male ® Female

7. Minority status: ® Yes ® No

8. Race/Ethnicity: ® Black ® Hispanic ® Asian ® American Indian/Eskimo
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Appendix II. Standard Deviations of Estimates Presented in Tables

Note that all of the ratios, averages, and other calculations presented in this memo are

not exact calculations generated from the population of comparative hearings. Instead,

all of these calculations are estimates based off of a sample of comparative hearings

drawn from the population.

For this reason, when discussing the results of this memo it is necessary to account for

the uncertainty associated with any estimate. This uncertainty is stated in terms of the

standard deviation of the estimate. Let us refer to the estimate as “p” and the standard

deviation as “s”. Then, for each of the estimates in this memo, it is appropriate to state

that we are 95% confident that the true population value lies in the range:

[ p – 1.96 * s , p + 1.96 * s]

Hence, knowing the standard deviation associated with each estimate is critical. The

standard deviations associated with several of the more central estimates are provided in

Tables II.1 and Table II.2. Table II.1 provides the standard deviations for several of the

win rates presented in the report. Table II.2 provides the standard deviations for several

of the averages presented in the report.

Note that the standard deviations of the population proportions in Table II.1 are

relatively straightforward to calculate. These population estimates are in the form of a

binomial estimate. The standard deviation of a binomial estimator is simply a function

of the sample proportion and the sample size.

The calculation of the standard deviation associated with the winning percentages in

Table II.1, on the other hand, is complicated. The winning percentages are in the form

of ratio estimates. The standard deviation of a ratio estimate is a complicated function

of the sample variances and co-variances of components of the ratio calculation and the

sample size.21

We accounted for the finite sample size correction when calculating the standard

deviations of the population proportions and the estimates of the winning percentages.

 

21 See Cochran, William G., Sampling Techniques, New York: John Wiley & Sons, Inc., 1977 page 164,

formula 6.44 for the estimate, and formula 6.45 for the variance of the estimate.
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Table II.1

Standard Errors Associated with Selected Estimated Rates

 Standard Deviations

Estimates All Broadcast TV Radio

Relative win rate for non-minority males 0.76% 0.92% 1.46%

Relative win rate for minority males 2.11% 6.09% 0.97%

Relative win rate for white females 1.96% 2.23% 3.68%

Relative win rate for minority females 5.63% 10.03% 3.59%

Relative win rate for non-minorities 0.71% 0.86% 1.37%

Relative win rate for minorities 2.05% 5.23% 1.00%

 Relative win rate for blacks 2.69% 8.92% 1.18%

 Relative win rate for Hispanics 3.28% 7.74% 1.69%

 Relative win rate for Asians 6.54% 13.43% 3.64%

 Relative win rate for American Indians 20.40% 22.64% 43.45%

Relative win rate for females 1.85% 2.20% 2.79%

Relative win rate for males 0.72% 0.92% 1.04%

Participation rate for white males 0.60% 0.70% 1.01%

Participation rate for minority males 0.37% 0.31% 0.90%

Participation rate for white females 0.49% 0.63% 0.66%

Participation rate for minority females 0.20% 0.20% 0.45%

Participation rate for whites 0.42% 0.36% 0.95%

Participation rate for minorities 0.42% 0.36% 0.95%

 Participation rate for blacks 0.30% 0.21% 0.78%

 Participation rate for Hispanics 0.27% 0.25% 0.67%

 Participation rate for Asians 0.11% 0.11% 0.24%

 Participation rate for American Indians 0.06% 0.07% 0.07%

Participation rate for females 0.52% 0.65% 0.77%

Participation rate for males 0.52% 0.65% 0.77%
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Table II.1 (cont.)

Standard Errors Associated with Selected Estimates

Standard Deviations

Estimates All Broadcast TV Radio

Party defined winning differential (table 13)

Minority 1.07% 2.00% 1.50%

Non-minority 1.07% 2.00% 1.50%

Female 1.67% 2.50% 2.20%

Male 1.67% 2.50% 2.20%

Equity defined winning differential (table 14)

Minority 1.20% 2.20% 1.30%

Non-minority 1.20% 2.20% 1.30%

Female 1.70% 2.70% 2.20%

Male 1.70% 2.70% 2.20%

Winner Take All (Narrow Measure – table 17)

Minority 2.70% 2.77% 3.94%

Non-minority 1.29% 1.69% 1.67%

Female 1.16% 1.27% 1.64%

Male 1.26% 1.65% 1.64%

Winner Take All (Broader Measure – table 18)

Minority 4.22% 4.76% 5.87%

Non-Minority 1.34% 1.76% 1.73%

Female 2.80% 4.73% 3.29%

Male 1.42% 1.77% 1.88%
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Table II.2

Standard Errors Associated with Selected Estimated Averages

Estimate Standard Deviations

All Broadcast TV Radio

Average parties per application

all apps 0.17 0.38 0.14

 When at least one party is:

 Minority 0.63 1.26 0.58

 White 0.17 0.40 0.14

 Male 0.17 0.39 0.14

 Female 0.28 0.59 0.24

Average parties per winning app

Overall 0.38 0.96 0.28

 When at least one party is:

 Minority 1.33 2.50 1.03

 White 0.40 0.99 0.30

 Male 0.41 1.01 0.30

 Female 0.60 1.32 0.47

Average apps per hearing

Overall 0.13 0.24 0.16

 When at least one party is:

 Minority 0.28 0.42 0.38

 White 0.13 0.25 0.16

 Male 0.13 0.25 0.16

 Female 0.15 0.28 0.18

Consider some examples how uncertainty impacts the interpretation of the estimates in

this report. Consider the (unweighted) relative win rate for whites, 37%, and minorities,

36.9%. The standard deviation associated with the measure for whites is .76%, a very

small standard deviation. The standard deviation associated with the corresponding

estimate of the minority win rate is a larger 2.11%. This implies that we can be 95%

sure that the true population relative win rate for whites falls in the range (35.48%,

38.52%). The corresponding range for minorities is (32.68%, 41.12%). The measure

for minorities is less precise because there are fewer minority parties in our sample.

Note that there exists significant overlap between the two 95% confidence intervals

stated in the above example. This implies that we can not reject the hypothesis that the

two true population relative win rates (the one for whites and the one for minorities) are

equal to each other. In fact, this in ability to reject the hypothesis of equality applies to

a significant percentage of all the “win rates” stated in this memo.

Consider the example of the winner take all relative win rate, for all broadcast hearings,

with the broader definition of availability. Using the statistics in Table 18, the win rate
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for whites is 30%, with a standard deviation of 1.29% (see Table II.1) and the win rate

for minorities is 21%, with a 2.8% standard deviation. This implies that we can be 95%

certain that the true population value for whites falls in the range (27.42%, 32.58%) and

the true population for minorities falls in the range (18.42%, 26.6%). Note that these

confidence intervals do not overlap. Hence, we can assert, with 95% confidence, that

the true population values for these two statistics are not equal. Using the same

methodology one can show that there is a statistically significant difference between the

win rate for men and women for the same specified win rate formula.