[House Hearing, 116 Congress]
[From the U.S. Government Publishing Office]
DRIVING EQUITY: THE U.S. DEPARTMENT OF TRANSPORTATION'S DISADVANTAGED
BUSINESS ENTERPRISE PROGRAM
=======================================================================
(116-64)
REMOTE HEARING
BEFORE THE
COMMITTEE ON
TRANSPORTATION AND INFRASTRUCTURE
HOUSE OF REPRESENTATIVES
ONE HUNDRED SIXTEENTH CONGRESS
SECOND SESSION
__________
SEPTEMBER 23, 2020
__________
Printed for the use of the
Committee on Transportation and Infrastructure
[GRAPHIC NOT AVAILABLE IN TIFF FORMAT]
Available online at: https://www.govinfo.gov/committee/house-
transportation?path=/browsecommittee/chamber/house/committee/
transportation
__________
U.S. GOVERNMENT PUBLISHING OFFICE
43-313 PDF WASHINGTON : 2021
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COMMITTEE ON TRANSPORTATION AND INFRASTRUCTURE
PETER A. DeFAZIO, Oregon, Chair
SAM GRAVES, Missouri ELEANOR HOLMES NORTON,
DON YOUNG, Alaska District of Columbia
ERIC A. ``RICK'' CRAWFORD, Arkansas EDDIE BERNICE JOHNSON, Texas
BOB GIBBS, Ohio RICK LARSEN, Washington
DANIEL WEBSTER, Florida GRACE F. NAPOLITANO, California
THOMAS MASSIE, Kentucky DANIEL LIPINSKI, Illinois
SCOTT PERRY, Pennsylvania STEVE COHEN, Tennessee
RODNEY DAVIS, Illinois ALBIO SIRES, New Jersey
ROB WOODALL, Georgia JOHN GARAMENDI, California
JOHN KATKO, New York HENRY C. ``HANK'' JOHNSON, Jr.,
BRIAN BABIN, Texas Georgia
GARRET GRAVES, Louisiana ANDRE CARSON, Indiana
DAVID ROUZER, North Carolina DINA TITUS, Nevada
MIKE BOST, Illinois SEAN PATRICK MALONEY, New York
RANDY K. WEBER, Sr., Texas JARED HUFFMAN, California
DOUG LaMALFA, California JULIA BROWNLEY, California
BRUCE WESTERMAN, Arkansas FREDERICA S. WILSON, Florida
LLOYD SMUCKER, Pennsylvania DONALD M. PAYNE, Jr., New Jersey
PAUL MITCHELL, Michigan ALAN S. LOWENTHAL, California
BRIAN J. MAST, Florida MARK DeSAULNIER, California
MIKE GALLAGHER, Wisconsin STACEY E. PLASKETT, Virgin Islands
GARY J. PALMER, Alabama STEPHEN F. LYNCH, Massachusetts
BRIAN K. FITZPATRICK, Pennsylvania SALUD O. CARBAJAL, California,
JENNIFFER GONZALEZ-COLON, Vice Chair
Puerto Rico ANTHONY G. BROWN, Maryland
TROY BALDERSON, Ohio ADRIANO ESPAILLAT, New York
ROSS SPANO, Florida TOM MALINOWSKI, New Jersey
PETE STAUBER, Minnesota GREG STANTON, Arizona
CAROL D. MILLER, West Virginia DEBBIE MUCARSEL-POWELL, Florida
GREG PENCE, Indiana LIZZIE FLETCHER, Texas
MIKE GARCIA, California COLIN Z. ALLRED, Texas
SHARICE DAVIDS, Kansas
ABBY FINKENAUER, Iowa
JESUS G. ``CHUY'' GARCIA, Illinois
ANTONIO DELGADO, New York
CHRIS PAPPAS, New Hampshire
ANGIE CRAIG, Minnesota
HARLEY ROUDA, California
CONOR LAMB, Pennsylvania
CONTENTS
Page
Summary of Subject Matter........................................ v
STATEMENTS OF MEMBERS OF THE COMMITTEE
Hon. Peter A. DeFazio, a Representative in Congress from the
State of Oregon, and Chairman, Committee on Transportation and
Infrastructure:
Opening statement............................................ 1
Prepared statement........................................... 4
Hon. Sam Graves, a Representative in Congress from the State of
Missouri, and Ranking Member, Committee on Transportation and
Infrastructure:
Opening statement............................................ 4
Prepared statement........................................... 5
Hon. Eleanor Holmes Norton, a Delegate in Congress from the
District of Columbia, and Chairwoman, Subcommittee on Highways
and Transit:
Opening statement............................................ 5
Prepared statement........................................... 6
Hon. Rodney Davis, a Representative in Congress from the State of
Illinois, and Ranking Member, Subcommittee on Highways and
Transit:
Opening statement............................................ 7
Prepared statement........................................... 8
Hon. Eddie Bernice Johnson, a Representative in Congress from the
State of Texas, prepared statement............................. 133
Hon. Rick Larsen, a Representative in Congress from the State of
Washington, and Chairman, Subcommittee on Aviation, prepared
statement...................................................... 133
WITNESSES
Evalynn Williams, President and Chief Executive Officer, Dikita
Enterprises, Inc., on behalf of the Conference of Minority
Transportation Officials:
Oral statement............................................... 10
Prepared statement........................................... 11
Geri E. Boyer, P.E., President, Kaskaskia Engineering Group, LLC,
on behalf of the American Council of Engineering Companies:
Oral statement............................................... 14
Prepared statement........................................... 16
Mary T. Lerdahl, President, Emerald Consulting Services, LLC:
Oral statement............................................... 22
Prepared statement........................................... 24
Farad Ali, Chairman, Government Affairs Committee, Airport
Minority Advisory Council:
Oral statement............................................... 27
Prepared statement........................................... 29
Sandy-Michael E. McDonald, Director, Office of Economic and Small
Business Development, Broward County, Florida:
Oral statement............................................... 32
Prepared statement........................................... 33
Sandra D. Norman, Division Administrator, Civil Rights, Virginia
Department of Transportation:
Oral statement............................................... 36
Prepared statement........................................... 37
Jon S. Wainwright, Ph.D., Affiliated Consultant, NERA Economic
Consulting:
Oral statement............................................... 38
Prepared statement........................................... 40
SUBMISSIONS FOR THE RECORD
Submissions for the Record by Hon. Peter A. DeFazio:
Ten Disparity Studies........................................ 3
Letter of June 25, 2020, from Geri E. Boyer, P.E., President,
Kaskaskia Engineering Group, LLC........................... 95
Letter of July 13, 2020, from Lawrence T. Green, President,
Divine Cement, Inc......................................... 134
Letter of July 15, 2020, from Linda Moen, P.E., LEED BD+C,
President and Managing Member, EFK Moen.................... 136
Letter of July 1, 2020, from Carla M. Williams, DBELO,
Director of Community and Business Engagement, Hillsborough
Area Regional Transit Authority, and President, COMTO
Central Florida Chapter.................................... 137
Letter of September 19, 2020, from Colette Holt, Colette Holt
& Associates............................................... 138
Letter of June 16, 2020, from Katherine M. Cloonen,
President, JK Steel Erectors, Inc.......................... 142
Letter of June 24, 2020, from Carol L. Kwan, Carol Kwan
Consulting LLC............................................. 143
Letter of May 26, 2020, from Sarah Imberman, S. Levy Foods... 144
Letter of June 17, 2020, from Constance Macolino, President,
Puget Sound Steel Co., Inc................................. 144
Letter of September 9, 2020, from Robert S. Bright, Founder
and President, Talson Solutions, LLC....................... 145
Letter of September 8, 2020, from Lorenzo Thompson,
Principal, Thompson Civil, LLC............................. 146
Letter of July 1, 2020, from Katey Doman, President, TyE Bar
LLC........................................................ 147
Statement of Joann Payne, President, Women First National
Legislative Committee...................................... 147
Submissions for the Record by Hon. Sam Graves of Missouri:
Statement of the American Road & Transportation Builders
Association................................................ 151
Letter of October 7, 2020, from James V. Christianson, Vice
President, Government Relations, Associated General
Contractors of America..................................... 155
Statement of the Airport Restaurant and Retail Association,
Submitted for the Record by Hon. Rick Larsen................... 159
APPENDIX
Question from Hon. Troy Balderson to Sandy-Michael E. McDonald,
Director, Office of Economic and Small Business Development,
Broward County, Florida........................................ 163
Questions from Hon. Peter A. DeFazio to Jon S. Wainwright, Ph.D.,
Affiliated Consultant, NERA Economic Consulting................ 164
[GRAPHIC(S) NOT AVAILABLE IN TIFF FORMAT]
September 18, 2020
SUMMARY OF SUBJECT MATTER
TO: LMembers, Committee on Transportation and
Infrastructure
FROM: LStaff, Committee on Transportation and
Infrastructure
SUBJECT: LHearing on ``Driving Equity: The U.S. Department
of Transportation's Disadvantaged Business Enterprise Program''
_______________________________________________________________________
PURPOSE OF HEARING
The Committee on Transportation and Infrastructure will
meet on Wednesday, September 23, 2020, at 10:00 am, in room
2167 Rayburn House Office Building and remotely via Cisco
WebEx, to receive testimony regarding ``Driving Equity: The
U.S. Department of Transportation's Disadvantaged Business
Enterprise Program.'' The Committee will hear from
representatives of the Virginia Department of Transportation;
Broward County, Florida, Office of Small Business and Economic
Development; the Airport Minority Advisory Council (AMAC); the
Conference of Minority Transportation Officials (COMTO);
Emerald Consulting Services; NERA Economic Consulting; and the
American Council of Engineering Companies (ACEC).
BACKGROUND
The U.S. Department of Transportation's (DOT) Disadvantaged
Business Enterprise (DBE) Program was established to remedy
discrimination against minority and women-owned businesses.\1\
The DBE program seeks to ensure those businesses are provided
equal opportunities to compete for contracts assisted by
certain DOT funds administered by the Federal Highway
Administration (FHWA), the Federal Aviation Administration
(FAA), the Federal Transit Administration (FTA), and the
National Highway Traffic Safety Administration (NHTSA).\2\
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\1\ DOT Office of Civil Rights. Disadvantaged Business Enterprise
(DBE) Program. US Department of Transportation. Retrieved September 18,
2020, from https://www.transportation.gov/civil-rights/disadvantaged-
business-enterprise
\2\ 49 CFR 26.3.
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First established by Federal regulation in 1980 as a
minority and women's business enterprise program, the DBE
program was later statutorily authorized for surface
transportation programs in 1983 by the Surface Transportation
Assistance Act of 1982 (P.L. 97-424) to aid small businesses
owned and controlled by minorities facing historic and
continuing discriminatory barriers to participation in the
highways and transit programs.\3\
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\3\ DOT Office of Civil Rights. Disadvantaged Business Enterprise
(DBE) Program.
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DBE programs for women-owned businesses and the FAA's
airport DBE program were primarily implemented by regulation
until Congress passed the Surface Transportation and Uniform
Relocation Assistance Act of 1987 (P.L. 100-17) and the Airport
and Airway Safety and Capacity Expansion Act of 1987 (P.L. 100-
223), which expanded statutory authorization for surface and
airport transportation construction DBE programs to include
women-controlled small businesses and codified the airport DBE
program, respectively. The Airport and Airway Safety and
Capacity Expansion Act also established a separate Airport
Concession Disadvantaged Business Enterprise (ACDBE) Program
administered by the FAA for airport concessions and related
contracts.\4\ Since P.L. 100-223 codified the airport
construction DBE program and the ACBDE program, these programs
do not require statutory reauthorization in the same manner as
surface transportation DBE programs.
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\4\ Id.
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Though not codified like the airport programs, Congress has
regularly reauthorized the DBE program for highways and transit
in successive surface transportation bills, most recently with
the enactment of the Fixing America's Surface Transportation
(FAST) Act (P.L. 114-94). In addition, the U.S. House of
Representatives passed H.R. 2, the Moving Forward Act, which
aims to reauthorize the surface DBE program with some
amendments.
Both the surface DBE program and the aviation construction
DBE program are implemented pursuant to regulations established
under 49 CFR part 26. The ACDBE program is implemented pursuant
to regulations established under 49 CFR part 23.
I. WHAT IS A DBE?
For eligibility purposes, a DBE is defined as a small, for-
profit business where socially and economically disadvantaged
individuals (1) own at least 51 percent of the economic
interests of the entity, and (2) control and manage the
business operations of the firm.\5\ A firm and its minority
and/or women owners seeking certification as a DBE must meet:
(1) an ownership and control test, (2) a personal net worth
test, and (3) a size standard test, requirements for which are
described in regulation.\6\
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\5\ 49 CFR 26.5.
\6\ 49 CFR 26; 49 CFR 23.
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To be regarded as socially disadvantaged means to face
historic and ongoing discrimination, such as racial or ethnic
prejudice or cultural bias due to membership in a particular
group.\7\ Consistent with DOT implementing regulations,
minorities and women are presumed to be socially disadvantaged
(although that presumption is rebuttable).\8\ Others may
qualify as socially disadvantaged on a case-by-case basis.\9\
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\7\ 13 CFR 124.103.
\8\ 49 CFR 26.67(a) and (b).
\9\ 49 CFR 26.67(d).
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To be regarded as economically disadvantaged, an individual
must, among other things, have a personal net worth that does
not exceed $1.32 million, excluding the equity in the
individual's primary residence and the value of their ownership
interest in the firm seeking certification.\10\
To meet size standards for DBE eligibility and be regarded
as a small business in the surface transportation sector, a
business must meet the qualifications of a small business
defined by the Small Business Administration (SBA) in
accordance with the North American Industry Classification
System (NAICS) codes relevant to the business and as defined by
the annual gross receipts or employee number caps outlined for
each industry code.\11\ In addition, the small business must
not have average annual gross receipts over the firm's previous
three fiscal years in excess of $23.98 million, regardless of
the relevant NAICS code qualification.\12\
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\10\ 49 CFR 26.67(a).
\11\ 49 CFR 26.65(a).
\12\ 49 CFR 26.65(b).
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Until the FAA Reauthorization Act of 2018 (P.L. 115-254),
size standards for DBE eligibility in the aviation construction
sector reflected the same requirements as the surface DBE
program. With that Act, however, Congress removed the separate
$23.98 million gross receipts cap requirement for businesses in
the aviation construction sector, tying eligibility
requirements directly to the SBA's definitions of small
businesses.\13\
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\13\ 49 USC Sec. 47113(a)(1).
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In addition, H.R. 2, the Moving Forward Act, proposes to
remove the $23.98 million gross receipts cap from the surface
transportation DBE program as well, so the SBA would determine
business size standards for DBEs. This proposed change would
result in a uniform standard for determining small business
size for both the surface and aviation construction DBE
programs, set by the SBA.
To be certified under the FAA's ACDBE program, a business
must meet different size standards reflective of the diversity
of industries present in airport concessions.\14\
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\14\ 49 CFR 23.33.
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II. HOW ARE FIRMS CERTIFIED?
Recipients of DOT financial assistance (such as state
departments of transportation, local governments, transit
agencies, and port authorities) are required to establish a
Unified Certification Program (UCP) in their state.\15\ The
purpose of a UCP is to ensure DBEs and applicants (including
airport concessionaires) will have ``one-stop shopping'' on all
certification matters with respect to these recipients. If a
business wants to be certified as a DBE, it must submit an
application to the state UCP for approval.\16\ Determinations
as to whether a firm meets the DBE criteria are made by the UCP
using various means, including on-site visits, personal
interviews, reviews of licenses, stock ownership, equipment,
bonding capacity, work completed, resume of principal owners,
financial capacity, and type of work preferred.\17\ Once a DBE
is certified through the UCP, that certification must be
honored by all recipients of DOT funds within the state.\18\
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\15\ 49 CFR 26.81.
\16\ Id.
\17\ 49 CFR 26.83(c).
\18\ 49 CFR 26.81(b).
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While some state UCPs maintain certification reciprocity
agreements with other state UCPs, each state exercises its own
discretion as to whether it will accept certification from
other states.\19\ DBEs wishing to do business in multiple
states must generally recertify with all applicable UCPs.\20\
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\19\ 49 CFR 26.81(e) and (f).
\20\ 49 CFR 26.85.
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III. HOW DOES THE DBE PROGRAM WORK?
Under the authorizing statues for the various DBE programs,
Congress set a national 10 percent participation goal for firms
certified as DBEs in surface transportation programs, in
airport federally assisted contracting (i.e., procurement,
construction, or professional services contracts), and in
airport concessions.\21\
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\21\ See P.L. 114-94 Sec. 1101(b)(3) for surface, and 49 USC
Sec. 47113(b) for aviation.
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DOT regulations require recipients of federal financial
assistance that anticipate awarding prime contracts of more
than $250,000 to establish an annual aspirational DBE
participation goal that reflects what DBE participation in
federally-assisted projects would look like in the absence of
discrimination.\22\ Recipients must base their goals on how to
achieve a level playing field in their individual programs,
regardless of the 10 percent national goal.\23\ These goals
must be based on demonstrable evidence of the availability of
ready, willing, and able DBEs relative to the DOT-assisted
contracts that will be available that fiscal year (FY).\24\
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\22\ 49 CFR 26.21(a)(1) requires all FHWA ``primary recipients'' of
Federal financial assistance to establish a DBE program, regardless of
contract size. Subrecipients are governed by the prime recipient's DBE
program.
\23\ 49 CFR 26.45(b).
\24\ 49 CFR 26.45.
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The two-step process for goal-setting in accordance with
this demonstrable evidence is laid out in 49 CFR 26.45.
Demonstrable evidence may come from several sources, including,
but not limited to: census data, established DBE directories,
past bidder lists, determinations by other DOT recipients with
substantially similar market areas, and statistical DBE
availability and disparity studies covering recipients' market
areas.\25\ The recipient of DOT funds must establish its goal
for a three-year period and submit that goal with the
determining methodology to the FAA, FHWA, or FTA for review and
approval.\26\
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\25\ 49 CFR 26.45.
\26\ Id.
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It is important to note that a recipient's goal is
aspirational only; quotas and set-asides are generally not
permitted. In addition, DOT does not assess penalties for not
meeting DBE goals as long as good faith efforts are
demonstrably made.\27\ Furthermore, recipients are required to
use race-neutral means to meet as much of their overall goal as
possible (in this context, ``race-neutral'' refers to both race
and gender, i.e., without application of any criteria favoring
DBEs over non-DBEs).\28\ Examples of ``race-neutral means''
include: providing assistance to small businesses in overcoming
issues such as the inability to obtain bonding or financing;
unbundling large contracts to make them more accessible to
small businesses; informational and communication programs on
contracting procedures and specific contract opportunities; and
other business support services.\29\
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\27\ 49 CFR 26.47.
\28\ See 49 CFR 26.5 and 49 CFR 26.51.
\29\ 49 CFR 26.51(b).
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If a recipient is unable to meet its overall DBE
participation goal through race-neutral means, then a recipient
must establish contract goals (which are deemed race-conscious)
for DBE participation.\30\ This means the recipient has
determined that, without the use of race-conscious measures, a
level playing field for DBE businesses could not be achieved.
Contract goals require that prime contractors employed by DOT
recipients make good-faith efforts to award a certain
percentage of their total contract work to certified DBEs in
order to meet the race-conscious portion of their overall DBE
participation goal.\31\ There are no Federally-mandated
penalties for failing to meet these goals as long as good-faith
efforts are made.
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\30\ 49 CFR 26.51(d).
\31\ 49 CFR 26.51(e)(2).
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Importantly, as discussed further in section VI below,
states under the jurisdiction of the Ninth Circuit Court of
Appeals must use evidence from statistical disparity studies
during their goal-setting process before DOT recipients in
those states are allowed to set race-conscious goals for DBE
participation.\32\
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\32\ Case No. C00-5204 RBL (W.D. Wash. June 23, 2006)
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V. WHAT MUST RECIPIENTS REPORT TO DOT MODAL ADMINISTRATIONS?
Recipients of DOT funds must maintain accurate records of
data related to the participation of DBEs on projects and
report these records regularly to DOT modal
administrations.\33\ FHWA and FTA recipients must submit a
uniform report of DBE contract awards, commitments, and
payments twice per FY, and FAA recipients must submit such a
report once per FY.\34\
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\33\ 49 CFR 26.11.
\34\ Id.
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These uniform reports break down awards, commitments, and
payments of federal financial assistance in terms of, among
other things: (1) number of contracts awarded to DBEs as a
percentage of total contracts, (2) dollar amount of contracts
awarded to DBEs as a percentage of total contract dollars, (3)
a breakdown of number of contracts awarded to DBEs
disaggregated by race, gender, or other applicable categories,
and (4) a breakdown of contract dollar amounts awarded to DBEs
disaggregated by race, gender, or other applicable
categories.\35\
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\35\ 49 CFR 26, Appendix B.
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VI. HOW HAS THE DBE PROGRAM BEEN REVIEWED BY THE COURTS?
Numerous court cases dealing with the DOT's DBE program or
questions of race or gender-based discrimination have affected
the implementation of the program over time. Some have involved
the program directly and others indirectly. Below is a brief
overview of a few of the most relevant cases.
A. CITY OF RICHMOND V. J.A. CROSON CO., 488 U.S. 469 (1989)
In 1989, the United States Supreme Court held in City of
Richmond v. J.A. Croson Co. (Croson) that a Richmond, Virginia,
set-aside program giving preference to minority businesses in
the awarding of municipal contracts was unconstitutional on the
grounds that the city had failed to adequately demonstrate its
compelling interest in establishing such a program on the basis
of relevant, measurable evidence.\36\ With this holding, the
Court established an outline of what would constitute a
permissible program for race-based awarding of public contracts
by requiring that such programs be subject to a ``strict
scrutiny'' standard (the most stringent standard) of judicial
review.\37\ Under the strict scrutiny standard, a public entity
must prove: (1) that it has a ``compelling interest'' in
remedying discrimination based on ``a strong basis in
evidence,'' and (2) that the measures employed to remedy such
discrimination are ``narrowly tailored'' to the scope of the
evidence presented.\38\
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\36\ 488 U.S. 469 (1989).
\37\ Id.
\38\ Id.
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B. ADARAND V. PENA, 515 U.S. 200 (1995)
In 1995, in Adarand v. Pena (Adarand), a case dealing with
DOT funds expended in the state of Colorado, the United States
Supreme Court held that the strict scrutiny standard previously
applied in Croson applies to the Federal government in the
establishment of race-based programs.\39\ While the Court did
not specifically determine the constitutionality of DOT's DBE
program in Adarand, the Administration undertook a review of
Federal programs, including the DBE program, that used race or
gender as a basis for decision-making to ensure compliance with
the strict scrutiny standard.\40\ In 1998, Congress
reauthorized the surface DBE programs with the Transportation
Equity Act for the 21st Century (TEA-21, P.L. 105-178). In
1999, the DOT finalized new rules for both the surface and
aviation DBE programs to ensure compliance with Adarand, and
new rules for the ACDBE program were issued in 2005.\41\ Since
the new rules were adopted, courts considering the
constitutionality of the DBE program have consistently upheld
the program against facial challenges.\42\
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\39\ 515 U.S. 200 (1995).
\40\ See Affirmative Action Review Report to the President.
Retrieved September 18, 2020, from https://
clintonwhitehouse2.archives.gov/WH/EOP/OP/html/aa/aa-index.html
\41\ See 54 Fed. Reg. 5,096 (February 2, 1999), and 70 Fed. Reg.
14,496 (March 22, 2005)
\42\ See Adarand Constructors, Inc. v. Slater, 228 F.3d 1147 (10th
Cir. 2000), cert. granted, 532 U.S. 941, then dismissed as
improvidently granted, 534 U.S. 103 (2001) (Adarand VII); Sherbrooke
Turf, Inc. v. Minnesota Department of Transportation, and Gross Seed
Co. v. Nebraska Department of Roads, 345 F.3d. 964 (8th Cir. 2003),
cert. denied, 541 U.S. 1041 (2004); Western States Paving Co., Inc. v.
Washington Department of Transportation, 407 F.3d 983 (9th Cir. 2005),
cert. denied, 546 U.S. 1170 (2006); Northern Contracting, Inc. v.
Illinois Department of Transportation, 473 F.3d 715 (7th Cir. 2007)
(Northern Contracting III); Orion Insurance Group v. Washington OMWBE,
U.S. DOT, 2018 WL 6695345 (9th Cir. 2018), cert. denied, June 24, 2019.
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C. WESTERN STATES PAVING CO, INC. V. WASHINGTON STATE DEPARTMENT OF
TRANSPORTATION, CASE NO. C00-5204 RBL (W.D. WASH.
JUNE 23, 2006)
In 2005, the U.S. Court of Appeals for the Ninth Circuit
decided in Western States Paving Co, Inc. v. Washington State
Department of Transportation (Western States) that DOT's DBE
program was facially constitutional, however was
unconstitutional ``as applied'' by Washington State's DOT
(WashDOT), because WashDOT had failed to meet the strict
scrutiny requirement that the program be narrowly tailored.\43\
The court held WashDOT had not established with sufficient
statistical evidence that it needed race-conscious measures to
meet WashDOT's DBE participation goals.\44\ In response to this
ruling, the DOT advised all states within the jurisdiction of
the Ninth Circuit Court to implement only race-neutral program
goals until statistical disparity studies could be completed to
meet strict scrutiny standards for race-conscious contracting
goals.\45\
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\43\ Case No. C00-5204 RBL (W.D. Wash. June 23, 2006).
\44\ Id.
\45\ DOT Office of Civil Rights. Western States Paving Company Case
Q&A. US Department of Transportation. Retrieved September 18, 2020 from
https://www.transportation.gov/osdbu/disadvantaged-business-enterprise/
western-states-paving-company-case-q-and-a
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VII. WHAT ARE DISPARITY STUDIES AND HOW DO THEY IDENTIFY DISCRIMINATION
IN MARKETS?
Disparity studies are complex statistical analyses of
relevant marketplaces for Federal contracts. Study methodology
can vary, but studies generally aim to present policymakers
with a ``disparity ratio,'' the relative percentage of Federal
contract dollars awarded to minority groups and women in
comparison with the percentage such groups would be expected to
receive in a marketplace where discrimination is not
present.\46\ Disparity studies conducted for DOT funding
recipients may include, among other factors, analysis such as:
(1) an empirical determination of the appropriate market area
and appropriate product markets relevant to the recipients
contracting activity; (2) an estimate of the fraction of DBEs
compared with non-DBEs in the relevant market area and product
markets (DBE availability); (3) an estimate of the percentage
of the recipient's contract dollars earned by DBEs (DBE
utilization); (4) a statistical comparison of DBE availability
and utilization; (5) econometric analysis of the relative
success of DBEs in the recipients public sector market as well
as the corresponding private sector market; and (6) econometric
analysis of DBE access to capital in the relevant marketplace.
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\46\ National Academies of Sciences, Engineering, and Medicine,
Transportation Research Board, & National Cooperative Highway Research
Program. (2010). Guidelines for Conducting a Disparity and Availability
Study for the Federal DBE Program. The National Academies Press.
Retrieved September 18, 2020, from https://www.nap.edu/catalog/14346/
guidelines-for-conducting-a-disparity-and-availability-study-for-the-
federal-dbe-program
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As noted, recipients of DOT funds may use, and recipients
under the jurisdiction of the Ninth Circuit Court generally
must use pursuant to Western States, statistical disparity
studies to aid in the establishment of goals for DBE
participation on Federal-aid contracts. Since the Croson
decision, many public agencies across the country, including
DOT funding recipients, have relied upon disparity studies to
establish accurate, empirically-based goals for minority
participation in public contracting programs, including the
DOT's DBE program.
WITNESSES
LMr. Farad Ali, Airport Minority Advisory Council
LMs. Geri E. Boyer, P.E., American Council of
Engineering Companies
LMs. Mary Lerdahl, Emerald Consulting Services
LMr. Sandy-Michael McDonald, Broward County,
Florida, Office of Economic and Small Business Development
LMs. Sandra Norman, Virginia Department of
Transportation
LMr. Jon Wainwright, Ph.D., NERA Economic
Consulting
LMs. Evalynn Williams, Conference of Minority
Transportation Officials
DRIVING EQUITY: THE U.S. DEPARTMENT OF TRANSPORTATION'S DISADVANTAGED
BUSINESS ENTERPRISE PROGRAM
----------
WEDNESDAY, SEPTEMBER 23, 2020
House of Representatives,
Committee on Transportation and Infrastructure,
Washington, DC.
The committee met, pursuant to call, at 10:01 a.m., in room
2167 Rayburn House Office Building and via Cisco Webex, Hon.
Peter A. DeFazio (Chairman of the committee) presiding.
Mr. DeFazio. The committee will come to order.
I ask unanimous consent that the chair be authorized to
declare recess at any time during today's hearing.
Without objection, so ordered.
Before proceeding further, I would first like to make a few
comments about how we intend to proceed today. We had
previously covered these issues, but I want to briefly remind
Members for this hearing; it has been a while.
Today's hearing is being held in the committee's hearing
room, as well as remotely by Cisco Webex. For Members and staff
in the hearing room, I do have an announcement based on
guidance from the Attending Physician, dated June 16, 2020.
Members, staff, and all those physically present are informed
that, in accordance with recent guidance from the Office of the
Attending Physician, masks must be worn at all times during
today's proceeding, except when a Member is speaking at a
microphone.
The chair views this as a safety issue and, therefore, an
important matter of order and decorum, and will assert his
responsibility to preserve order and decorum with respect to
the wearing of masks. The chair's authority to enforce the
preservation of order and decorum during committee proceedings
derives from the Speaker's enforcement authority under clause 2
of rule I. Pursuant to clause 1 of rule XI, the rules of the
House are the rules of its committees and subcommittees, as far
as applicable.
The committee chair has long been responsible for the
enforcement of general decorum in their respective committees.
The chair would greatly prefer that all present simply uphold
the decorum of the committee by complying with reasonable
safety standards that are recommended by the Attending
Physician and are respectful of all the occupants in the room.
However, failing that, enforcement would include denial of
recognition toward Members who refuse to uphold standards of
decorum.
As this is a hybrid hearing, I also want to remind Members
of key regulations from the House Committee on Rules to ensure
the hearing goes smoothly. Members must be visible--hello--on
screen for purposes of identification when joining this
hearing. Members must also continue to use the video function
software platform, Cisco Webex, as lame as it is, for the
remainder of the time they are attending this hearing, unless
experiencing connectivity issues or other technical problems.
If a Member is experiencing any connectivity issues or
other technical problems, please inform committee staff as soon
as possible so you can receive assistance. The chat function is
available for Members on the Webex site platform for this
purpose. Members can also call the committee's main phone line,
202-225-4472, for technical assistance by phone.
Members may not participate remotely in any other
proceeding that may be occurring simultaneously.
It is the responsibility of each Member seeking recognition
to unmute their microphone prior to speaking. To avoid any
inadvertent background noise, I request every Member to keep
their microphone muted when not seeking recognition to speak.
Should I hear any inadvertent background noise, I will request
the Member to please mute their microphone.
Finally, despite this being a hybrid hearing, I want to
emphasize that all the standard rules of decorum apply.
As the chair of today's hearing, I will make a good faith
effort to provide every Member experiencing connectivity issues
an opportunity to participate fully.
Members will have the standard 5 minutes to ask questions.
To insert a document into the record, please have your
staff email it to the committee's clerk, Mike Twinchek.
This hearing is also being livestreamed for the public to
view.
And I would now recognize myself for my opening statement.
Today's hearing is focused on the United States Department
of Transportation's Disadvantaged Business Enterprise program,
DBE program, for short. It is an essential program that seeks
to remedy discrimination and its effects on women- and
minority-owned businesses as they compete for federally
assisted transportation contracts. It seeks to ensure all
businesses can compete for Federal transportation dollars on a
level playing field.
I am proud to follow in the footsteps of my friend, the
former chairman of this committee, Jim Oberstar--there is Jim,
right there [indicating portrait]--who was the last chairman to
convene a hearing on this subject, 11 years ago, in 2009.
I am also disturbed that, in the 11 years since that
hearing, discrimination has continued to plague women and
minorities in this country in the transportation sector.
Discrimination is still terribly real in America. And if the
events of 2020 have not proven that convincingly enough, I am
confident the overwhelming evidence we have examined for this
hearing will at least shut the door on the question, as it
relates to federally assisted transportation projects.
Our committee planned to hold this hearing more than 5
months ago, but our plans were delayed by the rapid spread of
the COVID-19 pandemic. Sadly, the continuing pandemic only
underscores the need for this hearing and for the DBE program.
It is increasingly clear minority communities and minority-
owned businesses have been disproportionately devastated by the
virus.
Almost 2 months ago, during debate before the passage of
H.R. 2 on the House floor, I submitted 30 high-quality
disparity studies into the Congressional Record, including many
hundreds of pages of rigorous empirical evidence testifying to
the reality of discrimination and its effects on the
transportation sector.
Today I ask unanimous consent to insert into this
committee's record an additional 10 studies, for a total of 40
studies, only a sampling of the mountain of evidence this
committee has seen over the years testifying to the reality of
discrimination in the transportation sector.
Without objection, so ordered.
[The information follows:]
Ten Disparity Studies, Submitted for the Record by Hon. Peter A.
DeFazio
The full text of each report is held on file electronically with
the Committee on Transportation and Infrastructure.
Dallas Fort Worth International Airport Disparity Study 2019, Colette
Holt & Associates, 2019
Washington State Airports Disparity Study 2019, Conducted for the
Washington State Department of Transportation, Colette Holt &
Associates, 2019
City of South Bend Disparity Study 2019, Colette Holt & Associates,
2019
2017 Minnesota Joint Disparity Study, Metropolitan Airports Commission,
Draft Report, Keen Independent Research, January 2018
2015 Disadvantaged Business Enterprise Disparity Study, John Wayne
Airport, County of Orange, California, MGT of America, Inc., December
2016
2015 Procurement Disparity Study, City of Portsmouth, Virginia, MGT of
America, Inc., 2015
Tampa International Airport 2015 Disparity Study Update, MGT of
America, Inc., August 2015
The State of Minority- and Women-Owned Business Enterprise: Evidence
from Memphis, Prepared for the Memphis-Shelby County Airport Authority,
NERA Economic Consulting, December 2013
The State of Minority- and Women-Owned Business Enterprise: Evidence
from Mississippi, Prepared for the Jackson Municipal Airport Authority,
NERA Economic Consulting, December 2012
The State of Minority- and Women-Owned Business Enterprise: Evidence
from Missouri, Prepared for the Missouri Department of Transportation,
NERA Economic Consulting, August 2012
Mr. DeFazio. I repeatedly pointed to these disparity
studies to demonstrate the reality of discrimination and its
effects. But it is equally important to note that our committee
has received qualitative evidence of discrimination, as well.
Letters from DBE-certified business owners and other
stakeholders from across the country have come to this
committee in the last few months, testifying to the importance
of the program and to the reality of discrimination faced by
women and minority business owners. Some of those business
owners and stakeholders are before us, virtually, today to
share their stories, and I thank them for their testimony.
The DBE program has been narrowly constructed to combat the
discrimination laid out in the evidence from across this
country. It is not a perfect program; I am sure we will hear
more about that today. But I believe it is an essential
program, if we want to ensure a level playing field for all
American businesses wishing to compete for Federal
transportation dollars.
Once again, I want to thank all the witnesses for taking
the time to be with us today, particularly in this rather
awkward virtual format. This is a profoundly important topic,
and I look forward to hearing your testimony.
[Mr. DeFazio's prepared statement follows:]
Prepared Statement of Hon. Peter A. DeFazio, a Representative in
Congress from the State of Oregon, and Chairman, Committee on
Transportation and Infrastructure
Today's hearing is focused on the U.S. Department of
Transportation's Disadvantaged Business Enterprise, or DBE, Program.
This essential program seeks to remedy discrimination and its effects
on women- and minority-owned businesses as they compete for Federally-
assisted transportation contracts. It seeks to ensure all businesses
can compete for Federal transportation dollars on a level playing
field.
I am very proud to follow in the footsteps of my friend, the former
Chairman of this Committee, Jim Oberstar, who was the last Chairman to
convene a hearing on this subject eleven years ago in 2009. But I am
also disturbed that in the eleven years since that hearing
discrimination has continued to plague women and minorities in this
country and in the transportation sector.
Discrimination is still terribly real in America, and if the events
of 2020 have not proven that convincingly enough, I'm confident the
overwhelming evidence we have examined for this hearing will at least
shut the door on the question as it relates to Federally-assisted
transportation contracts.
Our Committee planned to hold this hearing over five months ago,
but our plans were delayed by the rapid spread of the COVID-19
pandemic. Sadly, the continuing pandemic only underscores the need for
this hearing and for the DBE program. It is increasingly clear minority
communities and minority-owned businesses have been disproportionately
devastated by the virus.
Almost two months ago, during debate before the passage of HR 2 on
the House floor, I submitted thirty, high-quality disparity studies
into the Congressional Record including many hundreds of pages of
rigorous empirical evidence testifying to the reality of discrimination
and its effects in the transportation sector. Today, I ask unanimous
consent to insert into this Committee's Record an additional ten
studies, for a total of forty studies--only a sampling of the mountain
of evidence this Committee has seen over the years--testifying to the
reality of discrimination in the transportation sector.
I have repeatedly pointed to these disparity studies to demonstrate
the reality of discrimination and its effects, but it is equally
important to note that our Committee has received qualitative evidence
of discrimination as well. Letters from DBE-certified business owners
and other stakeholders from across the country have come to this
committee in the last few months testifying to the importance of the
program, and to the reality of discrimination faced by women and
minority business owners. Some of those business owners and
stakeholders are before us today to share their stories, and I thank
them for being here.
The DBE program has been narrowly constructed to combat the
discrimination laid out in the evidence from across this country. It is
not a perfect program, and I'm sure we will hear more about that today.
But I believe it is an essential program if we want to ensure a level
playing field for all American businesses wishing to compete for
Federal transportation dollars.
Once again, I want to thank all the witnesses for taking the time
to be with us today, particularly in this virtual format. This is a
profoundly important topic, and I look forward to hearing your
testimony.
Mr. DeFazio. With that, I would recognize the ranking
member, Sam Graves, for an opening statement.
Mr. Graves of Missouri. Thank you, Chairman DeFazio, and I
want to thank you for calling today's hearing to review the
Department of Transportation's Disadvantaged Business
Enterprise, or DBE, program.
We are all here today to examine the DBE program and
determine what, if anything, can be done to improve the
program, moving forward.
It has been 37 years since Congress first created the DBE
program, which was intended to help small businesses owned and
controlled by those facing discriminatory barriers in the
transportation, construction, and airport concessions industry.
Congress has recognized the success of the DBE program by
continuing to keep it in place, and making adjustments as
needed.
I look forward to hearing from today's witnesses as to the
progress that we have made towards realizing the goals of the
DBE program, and what recommendations they have.
And with that, I yield back.
[Mr. Graves of Missouri's prepared statement follows:]
Prepared Statement of Hon. Sam Graves, a Representative in Congress
from the State of Missouri, and Ranking Member, Committee on
Transportation and Infrastructure
We are here today to examine the DBE program and determine what, if
anything, can be done to improve the program going forward.
It has been 37 years since Congress first created the DBE program,
which was intended to help small businesses owned and controlled by
those facing discriminatory barriers in the transportation construction
and airport concession industries.
Congress has recognized the success of the DBE program by
continuing it and making adjustments as needed.
I look forward to hearing from today's witnesses as to the progress
that we have made toward realizing the goals of the DBE program, and
what recommendations they have.
Mr. DeFazio. I thank the gentleman. I now recognize the
chair of the Subcommittee on Highways and Transit,
Congresswoman Norton, for a statement.
Ms. Norton. Thank you, Mr. Chairman. I very much appreciate
your holding this important hearing, especially this year.
We are at a pivotal moment in our Nation's history, we are
shining a long-overdue light on the lived realities of people
of color in this country, despite our pledge of liberty and
justice for all. Over the last few months, the vulnerability of
African Americans, Latinos, Native American, and other Black
and Brown people has been unmistakably demonstrated as we ride
wave after wave of crisis, a global pandemic, a tanking
economy, and systemic racism repeatedly manifesting itself.
The way in which our Nation has failed and marginalized
large populations of our citizens, while unbearable to watch
over and over again, comes as no surprise to those of us who
feel the prevalence of racism in our experience.
I have spent my entire career--in Congress, and as chair of
the U.S. Equal Opportunity Commission before that--fighting for
equality and seeking to break down barriers so that all
citizens have the same opportunities to participate and thrive
in our economy and our society.
One of the most powerful tools in the field of
transportation and construction to assist people who have been
routinely left out is the Disadvantaged Business Enterprise
program. This program, when properly administered and enforced,
ensures that businesses owned by women and minorities have a
fair chance to compete for federally assisted transportation
contracts. The need for this program is ongoing, and stronger
than ever, as income inequality in this country, with a
pandemic helping it to grow, continues.
Today's panel will provide mountains of statistical
evidence that show discrimination in transportation and
construction projects. Mr. Wainwright's testimony documents,
through rigorous statistical analysis and survey data collected
by various agencies, the continued need for the DBE program. We
are also joined today by individual business owners who have
participated in the DBE program to provide some context for why
these surveys and statistical studies matter.
But let me point to a 2018 study conducted for the Maryland
Department of Transportation, whose geographic market includes
Washington, DC. The study looked at, among other things,
whether prime contractors who work with minority- and women-
owned firms as subcontractors on contracts with DBE-type goals
ever solicit or hire those same firms to work on contracts
without such goals.
The answers were stark and stunning: 69 percent of African-
American-owned firms responded that they were seldom or never
solicited to work on contracts without goals in place, and 74
percent of African-American-owned firms were seldom or never
hired to work on contracts without goals. For Hispanic
Americans, the results were 47 percent and 52 percent. For
Asian Americans, the results were 56 percent and 61 percent.
For Native Americans, the results were 82 percent and 70
percent. And for nonminority women, the results were 54 percent
and 53 percent. This is just one regional example, but this
pattern repeats itself across the country.
In closing, I remind my colleagues that this hearing
presents a welcome opportunity to elevate the realities of
minority- and women-owned business owners. By holding this
hearing today, we ensure that the DBE program and the business
owners it lifts up will receive thorough consideration by our
committee.
We also have the opportunity to learn what policy changes
Congress should consider for the continued success of the DBE
program.
And I look forward to hearing from today's witnesses, as
well as from my fellow members of this committee.
Thank you very much, Mr. Chairman.
[Ms. Norton's prepared statement follows:]
Prepared Statement of Hon. Eleanor Holmes Norton, a Delegate in
Congress from the District of Columbia, and Chairwoman, Subcommittee on
Highways and Transit
Thank you, Mr. Chairman. I cannot overstate the importance of this
hearing on the U.S. Department of Transportation's Disadvantaged
Business Enterprise program. I thank Chairman DeFazio, Ranking Member
Graves, and all the Members participating today for your time and
attention to this critical topic.
We are at a pivotal moment in our Nation's history. We are shining
a long overdue light on the lived realities for people of color in this
country, despite our pledge of ``liberty and justice for all''. Over
the last few months, the vulnerability of African American, Latinx,
Native American, and other black and brown people has been unmistakably
demonstrated as we ride wave after wave of crisis--a global pandemic, a
tanking economy, and systemic racism repeatedly manifesting as physical
violence.
The ways in which our Nation has failed and marginalized large
populations of our citizens--while unbearable to watch over and over
again--comes as no surprise to those of us who can feel the prevalence
of racism in our bones. I have spent my entire career--in Congress, and
as Chair of the U.S. Equal Opportunity Commission before that--fighting
for equality and seeking to break down barriers so that truly all
citizens have the same opportunities to participate and thrive in our
economy and our society.
One of the most powerful tools in the field of transportation and
construction to assist people who have routinely been left out or left
behind is the U.S. Department of Transportation's Disadvantaged
Business Enterprise (DBE) Program. This program, when properly
administered and enforced, ensures that businesses owned by women and
minorities have a fair chance to compete for federally assisted
transportation contracts.
The need for this program is ongoing, and stronger than ever, as
income inequality in this country with the pandemic helping it to grow.
Today's panel will provide mountains of statistical evidence that shows
discrimination on transportation construction projects is,
unfortunately, alive and well.
Mr. Wainwright's testimony documents, through rigorous statistical
analysis and survey data collected by various public agencies, the
continued need for the DBE program.
We are also joined today by individual business owners who have
participated in the DBE program and will share their personal stories
of how this program affirmatively created opportunities that did not
exist in its absence. I would like in particular to thank Ms. Lerdahl,
Ms. Williams, and Ms. Boyer for sharing your experiences with the
Committee.
To provide some context for why these surveys and statistical
studies matter, let me point to a 2018 study conducted for the Maryland
Department of Transportation, whose geographic market area includes
Washington, D.C. The study looked at, among other things, whether prime
contractors who work with minority- and women-owned firms as
subcontractors on contracts with DBE-type goals ever solicit or hire
those same firms to work on contracts without such goals. The answers
were stark and stunning--69 percent of African American owned firms
responded that they were seldom or never solicited to work on contracts
without goals in place, and 74 percent of African American owned firms
were seldom or never hired to work on contracts without goals. For
Hispanic Americans the results were 47 percent and 52 percent; for
Asian Americans the results were 56 percent and 61 percent; for Native
Americans the results were 82 percent and 70 percent; and for non-
minority women, the results were 54 percent and 53 percent. This is
just one regional example but this pattern repeats itself across the
country.
In closing, I remind my colleagues that this hearing presents a
welcome opportunity to elevate the realities of minority and women-
owned business owners. By holding this hearing today, we ensure that
the DBE program and the business owners it lifts up receive thorough
consideration by this Committee. We also have the opportunity to learn
what policy changes Congress should consider for the continued success
of the DBE program in the future.
I look forward to hearing from today's witnesses, as well as my
fellow Members, on the DBE program.
Mr. DeFazio. Thank you, Ms. Norton. I now call on the
ranking member of the Subcommittee on Highways and Transit, Mr.
Davis.
Mr. Davis. Thank you, Chairman DeFazio. I want to thank the
witnesses for participating in this important hearing. I want
to give a special welcome to my friend, Ms. Geri Boyer, who is
in southern Illinois right now.
I understand Congressman Bost is going to be providing us
with your full introduction today, so I won't steal his
thunder, unless he screws it up.
So I am watching you right now, Mike.
But it is great to see you. I appreciate the work you do
for Illinois and across the Midwest.
The Disadvantaged Business Enterprise program, administered
by the Department of Transportation, applies to airport
construction, airport concessions, and surface transportation
construction programs. The program addresses discrimination
against minority- and women-owned businesses, and provides
those businesses within the transportation industry an equal
opportunity to participate in billions of dollars of DOT-
assisted highway, transit, and airport contracts each year.
The DBE program has been successful, and this committee has
demonstrated a bipartisan commitment to this program and to
promoting full and fair access to transportation contracting
opportunities.
I commend the chairman and the ranking member for holding
this hearing today. This is an important discussion, important
to all of us in the room, and those connecting remotely, and to
the Nation, as a whole.
Mr. Chair, I yield back the balance of my time.
[Mr. Davis' prepared statement follows:]
Prepared Statement of Hon. Rodney Davis, a Representative in Congress
from the State of Illinois, and Ranking Member, Subcommittee on
Highways and Transit
I want to thank the witnesses for participating in this important
hearing, and I want to give a special welcome to Ms. Geri Boyer. It is
great to see you and I appreciate the work you do for Illinois and
across the Midwest.
The Disadvantaged Business Enterprise program, administered by the
Department of Transportation, applies to airport construction, airport
concessions, and surface transportation construction programs. The
program addresses discrimination against minority and women-owned
businesses and provides those businesses within the transportation
industry an equal opportunity to participate in billions of dollars of
DOT-assisted highway, transit, and airport contracts each year.
The DBE program has been successful, and this Committee has
demonstrated a bipartisan commitment to this program and to promoting
fair and full access to transportation contracting opportunities.
I commend you for holding this hearing today. This is an important
discussion--important to all of us in the room and those connecting
remotely, and to the Nation as a whole.
Mr. DeFazio. I thank the gentleman.
I would now like to welcome the witnesses on our panel: Ms.
Evalynn Williams, president, Dikita Enterprises, on behalf of
the Conference of Minority Transportation Officials; Ms. Geri
Boyer, president, Kaskaskia Engineering Group, on behalf of the
American Council of Engineering Companies; Ms. Mary Lerdahl,
owner, Emerald Consulting Services; Mr. Farad Ali, at-large
board director, Airport Minority Advisory Council; Mr. Sandy-
Michael McDonald, director, Office of Economic and Small
Business Development, Broward County, Florida; and Ms. Sandra
Norman, administrator, civil rights division, Virginia
Department of Transportation; and Mr. Jon Wainwright, Ph.D.,
affiliated consultant, NERA Economic Consulting.
Thank you all for participating today. We are looking
forward to your testimony.
Without objection, our witnesses' full statements will be
included in the record.
Hearing none.
Since your written testimony has been made part of the
record, the committee requests you limit your oral testimony to
5 minutes. Summarize as best as possible.
Before we hear from our panel of witnesses, I recognize
Representative Johnson to introduce Ms. Evalynn Williams.
Representative Johnson?
Ms. Johnson of Texas. Yes, thank you very much. And I want
to thank all of the witnesses for being present.
I want to say that I am pleased to introduce Ms. Evalynn
Williams, who is a constituent in Dallas, Texas. She has served
as the chief financial officer for Dikita for 26 years, prior
to transitioning to the president and CEO in 2010. Following
and guided by her father, the company has grown to
unprecedented heights. Under her leadership, the company has
continued to thrive in new markets and obtain large and notable
projects. Dikita's largest client is Dallas Area Rapid Transit,
where the company has managed transit and NTD data for the last
28 consecutive years. Recently, Dikita completed a prime role
as a 49-percent JV partner designing and managing the
construction of DART's last 3 miles of light rail, and I look
forward to her testimony.
And thank you very much for being here.
Mr. DeFazio. Thanks, Representative Johnson. I now
recognize Representative Bost to introduce Ms. Geri Boyer,
under threat by Rodney Davis.
Mr. Bost. Thank you, Mr. Chairman. You know, I am happy to
have the opportunity to introduce our constituent, Geri Boyer
from Belleville, Illinois, as a witness for today's hearing.
Ms. Boyer is a founder, owner, and president of Kaskaskia
Engineering Group. Kaskaskia Engineering Group is a civil
engineering and contracting firm that has been recognized on
the list of St. Louis Business Journal's largest women-owned
businesses over the past decade. Ms. Boyer has also won
multiple awards for her leadership. She is an active member of
the American Council of Engineering Companies, Associated
General Contractors of Illinois, Illinois Association of County
Engineers, and the Illinois Association of Highway Engineers.
Ms. Boyer is also an active member within our community,
working with the Belleville CEO Program and is the civil
chairperson for the Belle-Scott Committee of the Greater
Belleville Chamber of Commerce.
I am excited to have her give her testimony on the
Department's Disadvantaged Business Enterprise program, and
look forward to the insight that she can offer, given her years
of success in business. She is one of the most qualified
witnesses, I believe, that is on the panel today, and I
appreciate her being here, and I appreciate the opportunity to
introduce her.
And Rodney, I hope that was good enough for you, because I
think Geri is going to do a great job.
And with that, I yield back.
Mr. DeFazio. Rodney stepped out, but I am sure he is in
accordance. I think that was very well done. So thank you.
We will now move to witness testimonies.
Ms. Williams, you may proceed. You are recognized for 5
minutes.
TESTIMONY OF EVALYNN WILLIAMS, PRESIDENT AND CHIEF EXECUTIVE
OFFICER, DIKITA ENTERPRISES, INC., ON BEHALF OF THE CONFERENCE
OF MINORITY TRANSPORTATION OFFICIALS; GERI E. BOYER, P.E.,
PRESIDENT, KASKASKIA ENGINEERING GROUP, LLC, ON BEHALF OF THE
AMERICAN COUNCIL OF ENGINEERING COMPANIES; MARY T. LERDAHL,
PRESIDENT, EMERALD CONSULTING SERVICES, LLC; FARAD ALI,
CHAIRMAN, GOVERNMENT AFFAIRS COMMITTEE, AIRPORT MINORITY
ADVISORY COUNCIL; SANDY-MICHAEL E. McDONALD, DIRECTOR, OFFICE
OF ECONOMIC AND SMALL BUSINESS DEVELOPMENT, BROWARD COUNTY,
FLORIDA; SANDRA D. NORMAN, DIVISION ADMINISTRATOR, CIVIL
RIGHTS, VIRGINIA DEPARTMENT OF TRANSPORTATION; AND JON S.
WAINWRIGHT, Ph.D., AFFILIATED CONSULTANT, NERA ECONOMIC
CONSULTING
Ms. Williams. Good morning, and I want to thank you for
allowing me the opportunity to testify in support of the DBE
program. My name is Eve Williams, president of Dikita
Enterprises, a 40-year-old African-American engineering firm
located in Dallas, Texas. And today I speak on behalf of COMTO,
as well as all the DBEs across the Nation.
I also sit on the APTA board of directors, where next month
I will become the first African-American female to chair its
distinguished Business Members Board of Governors.
My company has been a part of the DBE program since its
beginning, and is the oldest black engineering firm in north
Texas.
Being a female, Black, and a small business in the
construction industry has many challenges. Programs such as the
DBE program provide us a chance to participate in lead roles,
which affords us the opportunity to create majority-minority
teams. One success story I would like to share.
Dikita was a 49-percent partner in a team where we designed
the last 3 miles of the rail system for Dallas Area Rapid
Transit. We saved the agency over $4 million, and began revenue
service 2 months ahead of schedule. The icing on the cake is
that 60 percent of the project was designed by DBE firms.
Being called disadvantaged is not a privilege, nor does it
sound like a company's goal. And quite frankly, it was
embarrassing, explaining that to my 25-year-old millennial.
What an engaging conversation that followed.
The public sector is where firms like Dikita has its
greatest opportunity. But please note, if majority companies
and public agencies are not incentivized to include firms like
mine, they won't. Let me give you a case in point.
We were going after a project in a small suburban community
near Dallas. I knew about the proposal because of my strong
relationships in the community. The project was much in our
wheelhouse, but since there were parts of the work that others
could do better, we reached out to a nationally known, local
firm that we had worked with in the past. They were not aware
of the opportunity. What happened next was shocking, but not
surprising.
In an email thread that was inadvertently sent to me, I
read a discussion that went something like this. Of course, I
changed the names here. So I called John to ask if they'd be
interested in teaming with us. John informed his boss, Ted.
John explained the services, and thought Dikita and their
company could do well, since we had a relationship.
Ted asked about the minority participation goal. John told
him there was no minority goal. Ted asked John, ``Then why
would we sub to Dikita?'' John reminded Ted that Dikita was the
best at what they were doing.
Ted told him that, since there was no minority
participation goal, ``Dig into the opportunity, and we will
just do it ourselves.''
When John questioned Ted again, Ted told them, ``Hey, we're
bigger, just reject the offer.''
This is when John sent me an email rejecting our offer, and
inadvertently included the entire thread. The email was so
painful and disappointing.
There are so many sad storybook episodes regarding blatant
discriminatory practices, especially against Black firms. In
fact, if you look closer at the minority goals being met today,
you more than likely will find that African Americans who the
DBE program was first written for will have the smallest
percentages, while other groups have benefitted more. Black
professional firms are starting to be an endangered species,
like the bald eagle was.
I do want to bring one barrier that you have the power to
change. That is the formula in determining personal net worth.
It took 22 years before an inflationary adjustment was made to
the personal net worth statement in 2011. It is now almost
another 10 years and counting. The lack of regular inflationary
adjustments could prematurely remove small businesses from the
program.
One idea I have is to exclude retirement savings from the
net worth calculation. Currently, it includes restricted funds
such as 401(k), which disincentivizes a business owner to save
for retirement. So here I am, respectfully asking for your
consideration to remove retirement savings from the personal
net worth calculation.
In conclusion, this program is not a handout. It is a leg
up. It forces big companies and public agencies to play fair.
And, quite frankly, without the DBE program, we would be out of
business at the end date of the last contract in our pipeline.
We should be protected like----
[Microphone unmuted.]
Mr. DeFazio. Somebody is transmitting. Just conclude, then,
Ms. Williams. Thank you, sorry about that.
[No response.]
Mr. DeFazio. OK?
Ms. Williams. Yes, thank you.
[Ms. Williams' prepared statement follows:]
Prepared Statement of Evalynn Williams, President and Chief Executive
Officer, Dikita Enterprises, Inc., on behalf of the Conference of
Minority Transportation Officials
My name is Evalynn Williams. I am the President and CEO of Dikita
Enterprises, Inc., a family-owned minority consulting engineering and
architectural firm headquartered in Dallas, Texas. We celebrated our
40th year in business last November. We provide civil design, program
and construction management, and transit market research as it relates
to public transit planning. We have 40-50 people typically and employ
all nationalities of which many are skilled professionals who are
either woman or are of a minority group. My father, Lucious Williams,
founded the firm in 1979 in Milwaukee Wisconsin and branched to Dallas,
where I was attending college in 1983. I promised him 2 years as his
CFO in exchange for paying off my college loans, which was only $5,000
at the time. That was 36 years ago. We've been partners ever since.
Over the years, especially in the 80 and 90's we have many times been
the first African American firm to be awarded . . . and you can fill in
the blank. Even today, I'm amazed that we continue to be the first
African American engineering firm to prime a contract with public
entities. Many of the firms we began with in the early 80s no longer
exist for various reasons, but mostly because of the lack of
opportunities and resources. We are the oldest African American
professional engineering firm in North Texas.
We offer our services to mainly the governmental sectors, that are
federally, state or locally funded. Our industries include public
transit, highways, aviation, public educational institutions, including
K-12 and higher education, municipalities for roadway and
infrastructure projects. We have worked on multi-billion dollar
projects as well as those under $100,000. We have worked across the
nation providing a variety of services, typically transit planning. We
are certified in 19 locations across the nation. Being certified in
these many areas allow us to participate with transit properties and
provide transit market research. We typically are precluded from
offering engineering services as a DBE in other states because of
certain state laws. Neither my father nor I have a professional
engineering license. We excel in management, marketing and financial
expertise.
I have a BBA degree in information systems and an MBA in
accounting. I serve on several civic boards and have won my share of
awards. I am currently a member of COMTO and the American Public
Transportation Association (APTA), where, in October, I will become the
first African American female to chair APTA's distinguished Business
Members Board of Governors. APTA membership includes at least 90% of
all public transit organizations in North America and practically every
large national commercial firm that does business with public transit
authorities. COMTO, which is the Conference of Minority Transportation
Officials, is the leading national advocate for employment diversity,
inclusion and contracting opportunities in the multi-modal, multi-
billion-dollar transportation industry. Their mission is to eliminate
barriers to maximum participation for minority individuals, veterans,
people with disabilities and certified MWDBE businesses.
In 2010, I became President and CEO of Dikita and my father has
remained active as the Chairman of the Board and Director of Government
Affairs. He owns 51% of the firm and I own 47%, while my oldest
daughter owns 2%. Being trained in accounting and finance, running an
engineering firm has its challenges in of itself. Being a female, an
African American, and a small business in the construction industry has
had many challenges. There are certain systemic stereotypes that are
associated with all the classes of categories I've mentioned, but
typically they all have one thing in common. The idea that women,
African Americans, small businesses, engineering companies ran by non-
engineers--produce an inferior work product. These certainly create
barriers for successfully contracting and being relevant in the
industry. Of all these labels, I think being African American, however,
presents the biggest challenge when competing for work.
Being a disadvantaged business has certainly helped level the
playing field. As the CEO of a 2nd generation African American
engineering and architectural firm, we would never have sustained had
it not been for disparity programs such as the Federal DBE Program.
Competition for prime contracts with the Department of Transportation,
Federal Aviation and Federal Transit is difficult at best, and out of
reach for most minority and women owned businesses (M/WBE).
It is almost impossible for DBE firms to compete with large
national and international firms. They have the capacity and depth
within their workforce and can pull from global office locations. And
over the last 15 years, they have gotten even larger; which makes the
reauthorization of the DBE Program is so extremely critical to firms
such as Dikita Enterprises, Inc. It provides us with opportunities to
join a team as a subcontractor, a prime or joint venture partner, which
in turn helps to build financial capacity and workforce resources. It's
because of this program, Dikita led a joint-venture team with a huge
majority firm to design and build the last 3 miles of rail line for the
Dallas Area Rapid Transit system (DART), saving the agency over $4
million. DART was able to open for revenue service 2 months ahead of
schedule. Sixty-one percent of the team were DBE firms.
The truth is . . . if not for the DBE Program, large corporations
would not share the work and would self-perform 100% of contract-work.
Being called ``disadvantaged'' is not a privilege nor does it sound
like a goal that a company would strive to be. The reality is, without
the program we would not have a chance at fair competition. Quite
frankly, it was embarrassing explaining to my 21-year-old millennial, a
few years ago, why we were considered a disadvantaged business. I can
tell you that an engaging conversation and history lesson spun from
this revelation. Nevertheless, the DBE program is necessary for the
continuing survival of firms such as mine--to feed our families,
educate our youth, and build our communities.
I know for a fact that if it wasn't for the federal and local
equity programs, we would not be able to compete or obtain contracts.
That is evident when you look at private vs. public work. In the public
sector, the large firms that are considered primes, contract with us
only to the extent that it will help them win the project. If the goal
is 25%, then they will typically subcontract only that minimum amount,
even though we are a proven entity. Case in point. We were going after
a project in a small suburban community near Dallas. I found out about
the request for proposal because I had very strong relationships in
that community. Much of the project was within our wheelhouse and we
felt certain we could successfully propose and win. Since there were
parts of the work that others could do better, we reached out to a
nationally known local firm that we had worked with in the past. They
were not aware of the opportunity. What happened later was shocking but
not surprising. In an email thread that was inadvertently sent to me, I
read a discussion that went something like this (all names are
fictitious and are here to make the conversation easier to understand):
John informed his boss Ted that Dikita had inquired about
XYZ company providing service on an upcoming proposal.
Ted asked about the services to be performed and John
explained the services and thought Dikita and XYZ could do well since
they have worked together in the past.
Ted asked about the minority participation goal.
John told him that there was no minority goal.
Ted asked John why they would sub to Dikita.
John reminded Ted that Dikita was very good at providing
these type of specialty services
Ted told John that XYZ was bigger and to dig into the
opportunity.
When John asked about participating with Dikita, Ted told
him that since there was no minority participation, they would just do
the project themselves.
When John questioned Ted again, Ted told him that XYZ was
bigger and to reject our offer.
This is when John sent us an email rejecting our offer
and inadvertently included the entire thread.
This kind of conversation among large majority firms is not unusual
and is a matter of practice. And often we only suspect or hear about
why we were rejected from a third party. However, this was played out
in an email and was so painful and disappointing.
There are many story-book episodes regarding blatant discriminatory
practices that occur to either keep minority firms small or run them
out of business, especially African American firms. Everyone knows that
DBE businesses often live month to month unless we have been successful
in backfilling our pipelines with future projects. One of the most
disheartening feelings is to know that you are only as good as the
current project. We have had many relationships with larger firms and
have provided excellent service, but it's never quite the excellent
services in which you are remembered. We are the token DBE checkbox
that fulfilled the requirement. This I say because I have witnessed the
less than genuine relationships we have forged. We can perform
exceptionally well for many years on a 5-year large project. However, I
notice that when that same large firm is going for the exact project-
type in another state, they will not invite us to the team. When I've
asked about being on the team, the reply is the same, ``we needed you
in Dallas, we will `use' someone else in Houston''. When I question
why, the answer is always ``because you are only useful in Dallas and
taking you to other cities or states doesn't help us to win'', even if
we are the best in providing the services required. It's political.
Well that mentality keeps firms like mine small and confines us to our
own neighborhoods. For us to grow, we need not only to be able to work
in other states, but to work in the private industry. Working for
private developers is typically not an option, hence the need for DBE
program for government projects.
I'd like to talk about another challenge I see with the DBE
Program. While I appreciate the nature of the DBE program, there seems
to be a lack of attention to some of the challenges we face. Still in
existence are discriminatory and other related barriers that pose
significant obstacles for minority and women-owned businesses competing
for federally funded contracts. One such barrier is the lack of regular
inflation-adjustments to the Personal Net Worth requirement for DBE
certification. Unlike the Business Revenue Cap, (which is reviewed and
adjusted periodically by the Secretary of Transportation) it was 22
years before an inflation-adjustment was made to the Personal Net
Worth, increasing the 1989 cap of $750K to $1.3M in 2011. It is
important to note that much like the economy, the personal net worth of
DBE owners and their companies are fluid. The lack of regular
inflation-adjustments stops DBE businesses from growing and could
prematurely remove businesses such as mine from the program. Some folks
think that this $1.3M net worth is vast. If you are a successful
business, you must accumulate a net worth that will allow banks to loan
you money in order to continue upward growth and mobility. But more
importantly, you must save money for retirement. While the formula for
calculating personal net worth excludes our homestead, it does include
your retirement savings. By including restricted retirement savings
into the calculation, it acts to disincentivize a business owner from
saving adequately for retirement. At the end of the day, we all should
have a transition plan and be able to retire comfortably. However, if
most of the dollars I save become retirement assets and those assets
count against me in the certification process, then I'm likely not
encouraged to save but to spend. So, I am asking that the program
exclude retirement savings from the Personal Net Worth calculation.
In conclusion, the disparity and the inequities of our capitalistic
society, coupled with the injustices from America's history of
discriminatory practices against African Americans specifically, are
reasons that DBE program must continue to exist and expand. My dad, my
daughters and I depend on the program to stay in business. This program
is not a handout, it's a leg up. It forces the big companies to play
fair, and quite frankly, if we graduated from the program (and its
sister M/WBE local programs) or the program is dissolved, we would be
out of business at the expiration date of the last contracts in our
pipeline.
Mr. DeFazio. OK, thank you for your testimony and your
suggestion.
Ms. Boyer, you may proceed.
Ms. Boyer. Chairman DeFazio and Ranking Member Graves,
thank you for the opportunity to testify before the committee
today. It is an honor to represent my firm and my colleagues in
the Nation's engineering industry.
And thank you, Representative Davis and Representative
Bost, for that kind introduction.
As you heard, my name is Geri Boyer. I am president and
sole owner of Kaskaskia Engineering Group, headquartered in
Belleville, Illinois. We have DBE certifications in Illinois,
Iowa, Indiana, Kentucky, Missouri, Minnesota, and Wisconsin.
I am testifying today on behalf of the American Council of
Engineering Companies, the business association of the Nation's
engineering industry. ACEC represents nearly 5,500 engineering
companies, nationwide. Our members include very large firms
with tens of thousands of employees as well as hundreds of
small businesses like mine.
I want to communicate three main points to you today: first
of all, DBE programs are essential for helping businesses like
mine compete for work; second, securing certifications in
different States and different jurisdictions can be burdensome;
and three, for professional engineering and design-related
services, it is important to balance DBE considerations with
qualification-based selection procedures.
DBE programs have provided me the opportunity to diversify
and grow my company within the engineering and construction
industry throughout the Midwest. I still encounter
discrimination and the historic effects of discrimination, and
DBE certification gives me the opportunity to compete for
contracts and expand my business opportunities.
If we are going to be able to sustain our profession and
continue to support the transportation clients we serve, it is
imperative that we continue these efforts. Diversification
makes our companies and our industry stronger, and it makes us
more appealing to the next generation of professionals which we
desperately need to recruit. Federal DBE programs are one tool
to bring these goals forward.
However, one challenge for DBE firms like mine that work in
multiple jurisdictions is the lack of a unified approach to DBE
certification. The changes made in MAP-21 to implement a
uniform certification application and reporting forms have been
helpful. All the States I mentioned before use the uniform
application, but they require the entire application again at
different times of the year. The application must be current to
equipment, purchases, loans, and anything else a business uses
to run their day-to-day operation. This creates unnecessary
work for the DBE firm and the public agency, who both have
limited time and budget pressures.
I submitted for the hearing record a white paper I helped
develop with the ACEC Illinois Business Practices Committee. It
goes into greater detail on certification challenges and
potential solutions to streamline and simplify the process.
Lastly, I want to note the intersection of DBE
certification with Federal and State procurement requirements
for contracting for engineering services. Current laws require
agencies using Federal funds to follow QBS, qualification-based
selection procedures, for procuring engineering and design-
related services. Under QBS, agencies select firms based on
their experience, expertise, and demonstrated competence. These
rules apply to federal-aid highway, transit, and airport
improvement programs through various pieces of legislation
approved by this committee over many years, which ACEC strongly
supported.
Current regulations strike an effective balance between the
QBS framework and DBE program goals. Contracting agencies are
required to give consideration to DBEs, but without set-aside
contracts or quotas. State and local agencies set their own DBE
program participation goals and the method for achieving them,
subject to DOT approval, of course. Agencies may use an
evaluation criterion for DBE participation limited to 10
percent of the overall qualifications-based selection criteria,
or they can establish DBE participation goals, which can be
satisfied through good-faith efforts.
ACEC supports this approach. It helps to achieve DBE
program goals, while still emphasizing qualifications as the
preeminent factor in selecting engineering firms. Increasing
the weight of DBE as a selection criterion, or adding specific
set-asides, quotas, or mandates will diminish QBS and the
successful project delivery that it promotes.
Thank you again for the opportunity to testify today. I
will be happy to answer any questions later.
[Ms. Boyer's prepared statement follows:]
Prepared Statement of Geri E. Boyer, P.E., President, Kaskaskia
Engineering Group, LLC, on behalf of the American Council of
Engineering Companies
Chairman DeFazio and Ranking Member Graves:
Thank you for the opportunity to testify before the committee
today. It's an honor to represent my firm and my colleagues in the
nation's engineering industry to you and the members of the committee.
My name is Geri Boyer. I am the President and sole owner of
Kaskaskia Engineering Group, a civil engineering, environmental, and
contracting firm headquartered in Belleville, Illinois.
I am testifying today on behalf of the American Council of
Engineering Companies (ACEC)--the business association of the nation's
engineering industry. ACEC member firms drive the design of America's
infrastructure and built environment. Founded in 1906, ACEC is a
national federation of 52 state and regional organizations representing
nearly 5,500 engineering firms and 600,000+ engineers, surveyors,
architects, and other specialists nationwide.
Firm Profile
I founded Kaskaskia Engineering Group, LLC (KEG) in 2006 with the
mission of making the world a better place through the practice of
engineering. Through partnerships with our clients and regulatory
agencies, we plan, design, and build projects that enhance communities,
spur economic development, and respect the environment. From the
beginning, we have recruited highly skilled employees from a variety of
public and private sector backgrounds. Armed with good experience, a
great reputation and the Disadvantaged Business Enterprise Program, I
have built an impressive portfolio of federal, state, local, and
private project experience. Since 2006, KEG has earned over $100
million in revenue and provides engineering services in Illinois, Iowa,
Indiana, Kentucky, Michigan, Minnesota, Missouri, North Dakota, Ohio,
Oklahoma, and Wisconsin.
KEG specializes in transportation engineering, traffic engineering,
geotechnical engineering, structural engineering, environmental
science, infrastructure analysis and planning, water resource
management, right-of-way acquisition, and general highway construction.
DBE Certifications and DOT Experiences
KEG is a certified DBE through the Illinois Unified Certification
Program, Iowa Department of Transportation, Indiana Department of
Transportation, Kentucky Transportation Cabinet, Missouri Regional
Certification Committee, Minnesota Unified Certification Program, and
Wisconsin Unified Certification Program.
KEG is a certified Women Business Enterprise (WBE) through the
Illinois Central Management Services, Indiana Department of
Administration, Minnesota Central CERT Certification Program, Missouri
Office of Equal Opportunity, Metropolitan Water Reclamation District of
Greater Chicago, and the Women Business Enterprise National Council.
KEG is a certified Small Business Enterprise (SBE) through the
Kentucky Transportation Cabinet and Minnesota Central CERT
Certification Program.
KEG is a self-certified Women Owned Small Business (WOSB) and
Economically Disadvantaged Women Owned Small Business (EDWOSB) through
the Small Business Administration.
In an ever changing and volatile business market, corporate growth
and stability rely on diversification strategies, which often include
providing services to multiple federal, state, and local agencies, as
well as private corporations across regional, national, and
international markets. Diversification has long been a successful
strategy for large businesses, and it is just as important for the
survival and development of small firms.
Using the opportunities that the DBE program has provided, I have
diversified my company within the engineering and construction industry
throughout the Midwest. It's this diversification that has helped me
grow and weather economic storms. But it takes all these certification
programs in multiple states in order for me to have the same
opportunities as non-DBE firms.
One challenge for DBE firms like mine that work in multiple
jurisdictions is the lack of a unified approach to DBE certification.
The amended 49 CFR Part 26 which was included in MAP-21 implemented a
revised uniform certification application and reporting forms. However,
even though there is a uniform process, there is not a uniform
certification. All the agencies I mentioned before use the uniform
application but require the entire application again at different times
of the year. The application must be current to equipment purchases,
loans, and anything else a business uses to run their day-to-day
operation. This creates unnecessary work for the DBE firm and the
public agency who both have limited time and budget pressures. And with
the rising problem of identity theft, it's stressful to be sending all
your personal information to multiple agencies in multiple states.
I encourage the committee to consider additional reforms to
streamline and simplify the DBE certification process, creating a
program that is more efficient and effective for women and minority
firms working for multiple agencies across multiple states.
Qualifications-Based Selection
It's important to note the intersection of DBE program goals with
federal and state procurement requirements for the contracting of
engineering and design-related services. Current laws require agencies
using federal funds to follow Brooks Act qualifications-based selection
(QBS) procedures for procuring engineering and design services. These
rules apply to federal-aid highway, transit, and airport improvement
programs through various pieces of legislation approved by this
committee dating back to 1987. ACEC applauds this committee's
consistent and historic leadership in protecting and expanding QBS
requirements on federal infrastructure programs. Most states have a
``Mini Brooks Act'' that apply the same selection procedures to state
programs.
Under QBS, agencies select firms based on their experience,
expertise, and demonstrated competence for the types of professional
services required. They first evaluate and rank submitting firms'
statements of qualifications, performance data, and information
regarding the proposed project or services. The contracting agency then
selects and ranks firms based on those qualifications in accordance
with the established/advertised criteria for the project and negotiates
with the most highly qualified firm to arrive at a fair and reasonable
price for the solicited services.
QBS is the gold standard for procurement of professional
engineering and design services. It helps small and DBE firms compete
for work by providing us a forum to demonstrate the advantages we often
have, including niche market expertise, ability to be nimble to meet
deadlines, local knowledge, and involvement of senior level management.
Quantitative studies have shown that QBS lowers total project costs and
results in more satisfactory outcomes for owners.
Current Federal Highway Administration (FHWA) regulations strike an
effective balance between the QBS procurement framework and DBE program
goals. Contracting agencies are required to give consideration to DBE
consultants in the procurement of engineering and design related
services contracts using federal-aid funds, but without set-aside
contracts or quotas for DBE participation. State and local agencies set
their own DBE program participation goals, as well as the method for
achieving them, subject to FHWA approval. To the extent practical, a
contracting agency must achieve DBE program participation goals through
race and gender-neutral measures. DBE participation on all contracts
funded with federal funds, whether for professional or construction
services, may be counted toward overall DBE program participation
goals.
FHWA regulations provide that when overall DBE program
participation goals cannot be met through race-neutral measures,
additional DBE participation on engineering and design-related services
contracts may be achieved through either (1) the use of an evaluation
criterion for DBE participation in the qualifications-based selection
of firms, or (2) establishment of a contract DBE participation goal.
Prime contractors can satisfy these measures through good-faith efforts
to engage DBE participation.
In its policy guidance, FHWA states that in order to ``harmonize''
QBS rules and DBE program implementation, a contracting agency may
establish the use/participation of certified and qualified DBE firms as
an evaluation criterion of no more than ten (10) percent of the total
evaluation criteria in assessing the qualifications of firms/teams to
perform the solicited services.
ACEC supports this current approach. It helps to achieve DBE
program goals while still respecting the importance of emphasizing
qualifications as the preeminent factor in selecting engineering firms.
Increasing the weight of DBE as a selection criterion or adding
specific set-asides, quotas, or mandates will diminish QBS and the
successful project delivery that it promotes.
ACEC Diversity and Inclusion Initiatives
Lastly, I want to draw the committee's attention to the new
Strategic Plan that ACEC approved in October 2019. Embodying inclusion
and diversity is one of the five pillars of the new plan. Our express
goal is that the Council is recognized as a welcoming organization
where all members are included, involved and can achieve their full
potential. The objectives include improving the diversity of ACEC
leadership, enhancing the diversity of our membership, and increasing
engagement of diverse individuals from member firms.
If we're going to be able to sustain our profession and continue to
support the transportation clients we serve, it's imperative that we
deliver on these goals. Diversity makes our companies and our industry
stronger, and it makes us more appealing to the next generation of
professionals who we need to recruit. Federal DBE programs, as explored
by this hearing today, are one tool to help firms like mine bring those
goals forward.
I want to close by inserting here the statement that the Council
made earlier this year, which encapsulates how I personally feel and
what I strongly support about the engineering industry.
``ACEC is committed to an inclusive and diverse engineering
industry.
The engineering profession has always been grounded in
integrity, fairness, and service to community. Engineers build
communities. We create space and by extension, we create social
experience. We support equality and respect for all humankind.
We believe in providing equitable opportunities within our
profession to support untapped potential both within our
workforce and within the communities we serve. And we have the
power to foster progress by breaking down the physical barriers
that can inhibit economic and social equity.
Those are the principles that have guided our community
through this difficult time. Through ACEC we will embrace
inclusion and diversity and continue to focus our members on
ways to lift people up to become their best selves and to make
our companies models of the values we embrace.''
Thank you again for the opportunity to testify.
attachment
National Unified DBE Certification Program
a white paper by ACEC Illinois
Business Practices--DBE/WBE/MBE Committee
Authored by: Geri E. Boyer, P.E., Kaskaskia Engineering Group, LLC
June 2016
Last update: 6/25/2020
Introduction
In an ever changing and volatile business market, corporate growth
and stability rely on diversification strategies, which often include
providing services to multiple federal, state, and local agencies, as
well as private corporations across regional, national, and
international markets. Diversification has long been a successful
strategy for large businesses, but it is just as important for the
survival and development of small firms.
Firms owned by women and minority group members that want to employ
diversification strategies are encumbered by the current DBE
Certification process. Public agencies and small business owners have
limited time and continued budget pressures. Time and budget
constraints have significantly affected DBE certification in Illinois
and its surrounding states. This white paper discusses how a national
unified program could strengthen, streamline, and simplify the DBE
certification program, creating a program that is more efficient and
effective for women and minority firms working for multiple agencies
across multiple states.
Background
History of DBE Program
A policy of helping small businesses owned and controlled by
socially and economically disadvantaged individuals, including
minorities and women, participating in contracting opportunities
created by Department of Transportation (DOT) financial assistance
programs, has been in effect for more than 20 years. The Department,
through its Operating Administrations, distributes billions of dollars
annually to help finance thousands of projects across the country.
Approximately 85 percent of the assistance dollars is for construction.
The major portion of construction funds are allocated to state highway
and transportation agencies for highway construction. The balance is
provided to local public transit and airport authorities for mass
transit and airport facilities.
In 1983, Congress enacted the first Disadvantaged Business
Enterprise (DBE) statutory provision, which applied primarily to small
minority-owned firms. This provision required the Department to ensure
that at least 10% of the funds authorized for the highway and transit
Federal financial assistance programs be expended with DBE's. In 1987,
Congress re-authorized and amended the statutory DBE program to, among
other changes, add women to the groups presumed to be disadvantaged.
Since 1987, the DOT has established a single DBE goal, encompassing
both firms owned by women and minority group members.
Primarily three major DOT Operating Administrations (OA's) are
involved in the DBE program. They are the Federal Highway
Administration, the Federal Aviation Administration, and the Federal
Transit Administration. The DOT DBE program is carried out by state and
local transportation agencies under the rules and guidelines in the
Code of Federal Regulations (Title 49, Part 26). The FAA also maintains
a separate DBE program for concessions in airports (Title 49, Part 23).
Title 49, Part 26 of the Code of Federal Regulation (49 CRF part
26) required all agencies in each state receiving DOT funds to
participate in a state Unified Certification Program (UCP). Within
three years of March 4, 1999, recipients of DOT funding had to sign an
agreement establishing the UCP for that state and submit the agreement
to the Secretary for approval. The agreement provided for the
establishment of a UCP, which met all the requirements. The agreement
had to specify that the UCP would follow all certification procedures
and standards; that the UCP would cooperate fully with oversight,
review, and monitoring activities of DOT and its operating
administrations; and that the UCP would implement DOT directives and
guidance concerning certification matters. The agreement also committed
recipients to ensuring that the UCP has sufficient resources and
expertise to carry out the requirements.
DBE Unified Certification Program (UCP)
The purpose of the UCP is to provide ``one-stop shopping'' to
applicants for certification. The program was designed so that if a
firm was certified using a UCP agency in a state, they would only have
to apply to one federally-funded agency within that state to work with
all UCP member agencies. In Illinois, the UCP is made up of five US
DOT-funded agencies, the Illinois Department of Transportation (IDOT),
City of Chicago, Chicago Transit Authority (CTA), Metra, and Pace. The
Regional Transportation Authority (RTA) is also part of the IL UCP, but
is a non-certifying agency. Other states have very similar programs
made up of all agencies that receive federal funds.
Non-DOT-funded Certifying Agencies
Within every state, there are also non-DOT-funded agencies. Some
will accept the DOT's state implemented DBE Certification Program, and
some have their own certification process. Several non-DOT-funded
agencies have chosen to certify women business enterprises (WBE),
minority business enterprises (MBE), and Business Enterprise owned by
People with Disabilities (BEPD). In Illinois, the non-DOT-funded
certifying agencies are Central Management Services (CMS), City of
Chicago, and Cook County.
Interstate Certification Rule
While the DBE program was always a national program, state specific
administrative requirements tended to impair a DBE firm's ability to
fully compete for business opportunities in other states. In response
to longstanding concerns from the DBE community, the USDOT issued a
proposed rule aimed at breaking down these barriers. On January 1,
2012, the interstate certification provision (49 CRF 26.85) went into
effect. Its intent was to clear up administrative obstacles to
certification that were undermining important program objectives. The
rule furthered the following fundamental objectives of the DBE program.
(1) Facilitated the ability of DBE firms to compete for DOT-
assisted contracting.
(2) Reduced administrative burdens and costs on small businesses
that sought to pursue contracting opportunities in other states.
(3) Fostered greater consistency and uniformity in the application
of certification requirements, while maintaining program integrity.
The ultimate purpose of the interstate certification rule was to
facilitate certification of currently certified firms in other
jurisdictions. Interstate certification was not meant to be an
automatic reciprocity in the sense that each state must honor the other
states' certification decisions without review. Rather, the rule
created a rebuttable presumption, such that a firm certified in its
home state is eligible to be certified in other states to which it
applies.
The Department once again amended 49 CFR Part 26, which went into
effect on November 3, 2014. The final rule improved DBE program
implementation in the following three major areas.
(1) Revised the uniform certification application and reporting
forms and created a uniform personal net worth form for use by
applicant owners, which collect the data required by the Department's
Surface Transportation Reauthorization, Moving Ahead for Progress in
the 21st Century Act (MAP-21).
(2) The rule strengthened the certification-related program
provisions, which includes adding a new section authorizing summary
suspensions under specified circumstances.
(3) The rule modified several other program provisions concerning
such subjects as overall goal setting, good faith efforts, transit
vehicle manufacturers, and counting for trucking companies.
Problems
Over the last several years, the DOT has made a concerted effort to
improve the DBE program. Many hurdles have already been overcome, but
there are still problems to be solved to make this program even more
useful to small businesses owned and controlled by socially and
economically disadvantaged individuals. Problems that are burdensome
and limit the success of a DBE company are 1) Confusion between DBE
Certification and Prequalification, 2) Duplication of Applications for
DBE Certification, and 3) Slow Responsiveness of Reviewing Agencies.
The following are a few examples to support the need for additional
changes to the DBE program.
1) Confusion between DBE Certification and Prequalification
The Bureau of Small Business Enterprises administers IDOT's DBE
program. IDOT, like all other state DOT's, is tasked with the
certification of DBE firms and the prequalification of firms wanting to
bid on contracts and/or offer their services to the department. DBE
certification and DOT prequalification are performed by two different
units within IDOT. While there is some overlap in the certification and
prequalification processes for DBE firms, the certification process is
generally concerned with establishing if a business qualifies as
``disadvantaged,'' and the prequalification process confirms if an
applicant has resources and experience to self-perform each specific
service. If you are a DBE engineering/architectural consultant, you are
certified as a DBE through the Bureau of Small Business Enterprises and
prequalified through the Bureau of Design and Environment. The Bureau
of Design and Environment prequalifies firms in multiple categories of
service.
If you are a DBE contractor, you are certified as a DBE through the
Bureau of Small Business Enterprises and prequalified through the
Bureau of Construction. The prequalification process of a contractor is
governed by Title 44 Illinois Administrative Code Section 650. The
prequalification process does not apply to subcontractors. However, DBE
subcontractors are required to be certified through the Bureau of Small
Business Enterprises but only need to be registered through the Bureau
of Construction to perform work for IDOT.
Currently, the Bureau of Small Business Enterprises utilizes the
uniform certification application and forms required in the final rule.
These forms require the applicant to fill out a listing of NAICS codes
for which they are able to self-perform. The NAICS codes are used on
the UCP online directory and generally correlate with the
prequalification categories. However, the Bureau of Small Business
Enterprises has taken on the responsibility of prequalifying
subcontractors through the certification process. Instead of verifying
NAICS codes, they are verifying the resources and experience of a DBE
subcontractor to complete an IDOT specific contract pay item. They are
also certifying DBE subcontractors/contractors in work classifications
that are not in alignment with the Bureau of Construction. These
additional requirements are limiting the expansion of DBE
subcontractors/contractors.
2) Duplication of Applications for DBE Certification
The Illinois Department of Central Management Services (CMS)
Business Enterprise Program (BEP) is now certifying businesses owned by
women, minorities, and persons with disabilities. They claim that with
their certification a company will have the opportunity to participate
in the State's 20% minority, female, and persons with disabilities
goal. Also, a company would be listed in their BEP directory that is
used by state agencies, universities, and other large firms when they
are looking for businesses owned by females, minorities, and persons
with disabilities. This program's eligibility is available to companies
whose gross annual sales are less than $75 million, which far exceeds
the limit of $23.98 million in gross annual receipts required by the
new federal form and exceeds the Small Business Administration size
standard for all transportation-related industries.
CMS states that if a firm is currently certified with the City of
Chicago, Cook County, Chicago Transit Authority, METRA, PACE, IDOT,
Women Business Development Council, or Chicago Minority Business
Development Council, you can complete the Recognition Certification
Application to qualify for the ``limited'' Business Enterprise
Certification. CMS also offers the BEP Full Certification Application,
which effectively requires the same information as the UCP, but with
different forms. Both of these application processes certify businesses
as MBE, FBE, Female and Minority Business Enterprise (FMB), and/or
Persons with Disability Business Enterprise (PBE). Although a firm may
choose to be certified by CMS using the recognition certification, this
certification is not considered a valid certification by agencies in
other states.
For example, the Indiana Department of Administration only
recognizes CMS as the official M/WBE certifying agency for the State of
Illinois. As part of their application, the Illinois firm must provide
a copy of the Illinois certification conducted by CMS. If the firm was
initially awarded certification by IDOT and the firm used the CMS
Recognition Certification, the firm cannot apply for M/WBE
certification with the State of Indiana through the Indiana Department
of Administration. Also, the Indiana Minority & Women's Business
Enterprise Division does not accept onsite reports from the City of
Chicago, PACE, Metra, the Chicago Transit Authority, or the Chicago
Minority Business Development Council, making the ability for an
Illinois DBE firm to work in Indiana as an M/WBE firm very difficult.
The City of Chicago is a member of the IL UCP, which certifies DBE
firms.
The City also has the following certifications:
MBE
WBE
Business Enterprise owned by People with Disabilities
(BEPD)
Airport Concession Disadvantaged Business Enterprise
(ACDBE)
The MBE/WBE/BEPD certification is needed to work on city-funded
contracts and the DBE/ACDBE certification is needed to work on state
and federally funded contracts. If a woman-owned DBE firm that is
already certified through the IL UCP and CMS wants to work on a city-
funded project, the firm must also apply to the City of Chicago's WBE
program.
3) Slow Responsiveness of Reviewing Agencies
The goal of the DBE program is to give individuals who own
disadvantaged businesses the opportunity to grow their business. DBE
firms are taking advantage of the goals of the DBE program and looking
for opportunities to expand their businesses outside of their home-
based state. A single firm could apply to as many as 50 DBE offices,
which places additional burden on certifying offices. Additionally, as
state DOTs replace and/or reduce staff the burden increases.
State personnel are struggling to review the applications for home-
based firms in a timely manner. Adding a maximum 60 day determination
period for non-home-based firms set forth in 49 CRF 26.85 is creating
an impossible situation for reviewing agencies. There have been cases
in which it has taken over a year to issue a DBE certification.
Solution
A proposed solution is to create a National Unified DBE
Certification Program (National UCP) to serve as a ``one-stop
shopping'' to applicants for certification. Any state agency using the
unified certification application could be a coordinating member of the
National UCP, and its certification would be recognized as a National
UCP. Under a National UCP, the firm applies one time for certification
as DBE with their participating cognizant agency or a national
organization. If approved, that certification would be honored by all
recipients of federally funded and non-federally funded projects in all
states. The National UCP would only certify firms using the unified
certification application. Prequalification, determination if an
applicant has the requisite resources and experience to complete the
service/category as required, would remain with the contracting agency.
The certification and record would be held by a national agency/
organization, such as the Small Business Administration (SBA). The SBA
already have systems in place to review a standard application,
evaluate its compliance with federal regulations, and certify its
credibility. It currently is certifying Women Owned Small Business
(WOSB), 8(A), and HUBZone. It has the capacity for the upload of
documents necessary for annual renewal (Affidavit of Continued DBE
Certification). This process would significantly reduce the time and
effort necessary to become licensed in multiple states.
B2GNow, a cloud-based software system for real-time collection,
tracking and analysis of compliance data, currently maintains
compliance of DBE firms with federal, state, and local diversity
programs. It is a tool that could serve as a DBE certification record
holder for federal and state agencies to utilize.
Certifying agencies that do not use unified certification
application or do not choose to be a coordinating member of the
National UCP could continue to certify DBE. If a firm does not intend
to work with multiple agencies in multiple states, it might not be
advantageous to certify with a national organization. A certified firm
that had been certified by a non-coordinating local certifying agency
could still apply to have their record held by the national
organization.
Although this White Paper is focused on DBE firms certified to do
engineering and contracting, any type of DBE business could benefit
from a National UCP.
Sources
``Disadvantaged Business Enterprise (DBE) Program.'' United States
Department of Transportation, n.d. Web. 08 March 2015.
``Final Rule Changes Effective as of November 3, 2014.'' United States
Department of Transportation--Departmental Office of Civil Rights, n.d.
Web. 8 March 2015.
Indiana Department of Administration Division of Supplier Diversity,
Application for Certification, n.d. Web. 1 March, 2015
``Small Business Size Standards'' US Small Business Administration,
n.d. Web. 1 March, 2015
Mr. DeFazio. Thank you, Ms. Boyer.
Ms. Lerdahl, you may proceed.
Ms. Lerdahl. Good morning, Chairman DeFazio and committee
members. My name is Mary Lerdahl, currently the owner of
Emerald Consulting Services in the Seattle area.
Prior to starting my firm to help DBEs navigate the
challenges of the construction industry, I was an electrical
contractor for 22 years. I started my firm, DBE Electric, in
2009 during the Great Recession, after losing my share of
another company as the result of a marital dissolution. The
firm DBE Electric performed 122 projects valued at over $80
million over the course of 9 years, until I was forced out of
business as a result of WSDOT, Washington State Department of
Transportation's, waiver to exclude White women from the DBE
program.
The waiver was approved by U.S. DOT in 2016 after, in my
opinion, a faulty disparity study that included projected
revenue from the two largest mega-projects in Washington State
history.
From the time the waiver was enacted in June 2017 to mid-
2018, my firm's revenues went from $9 million a year to zero.
Without the designation of a DBE, I couldn't win a single
project, even with my successful track record. I was the only
female contractor in the State that performed complex, heavy
highway electrical projects, traffic signals, illumination,
intelligent transportation, and tolling systems.
By September of 2017, a new disparity study showed that
White women were not over-represented, and WSDOT asked U.S. DOT
to rescind the waiver on September 11, 2017.
I personally made two trips to Washington, DC, to meet with
U.S. DOT, the Federal Highway Admnistration, and Terence
Coleman of the Department of Assistant General Counsel, all to
no avail. When U.S. DOT finally denied WSDOT's request to
rescind the waiver on December 13, 2019, it was far too late to
save my business and the businesses of other White women in our
State.
Because of the DBE program, I participated in building the
SR 520 floating bridge, the longest floating bridge in the
world, with Kiewit. The contract was a design-build project,
and my contract value was $14 million. It was a great example
of how a small DBE firm like mine could work together with a
large prime contractor to grow, learn, and build a project that
all contractors could be proud of.
At the same time as I was building the bridge project, I
was also working on the SR 99 Bored Tunnel project, valued at
$1.6 billion, with Seattle Tunnel Partners, the joint venture
with Dragados and Tutor-Perini. I have experienced many
incidents, overt and subtle, of discrimination in many years,
but this one was the worst. Shortly after winning the tunnel
project, Tutor-Perini purchased Fisk Electric, a large firm out
of Houston.
At an initial DBE outreach meeting, a Fisk representative
blatantly stated that they were only interested in receiving
labor-only bids from DBE firms, thus exposing the DBE firms to
more risk and less profit from the less risky material
purchases portion of the work. A local subcontractor, JH
Kelley, was brought in to sub out to the two electrical firms
owned by the joint venture--Fisk being owned by Tutor-Perini,
and SICE, being owned by Dragados in Spain--to minimize the
appearance of self-dealing.
While my firm ultimately performed $977,246 of work on the
project, public records show that SICE performed $34,315,556,
and Fisk performed $106,057,656. STP solicited bids from DBE
firms like mine in order to show good faith efforts, only to
self-perform much of the work.
I experienced sexual advances while on the project site,
while supervising my crews.
Getting paid was slow and difficult, and begging was
necessary, as they always had some excuse. They needed two
signers, who were rarely both there, for example.
Finally, while my firm was working on a change order to
convert temporary generator power to permanent power feeding
refrigerated shipping containers, I experienced discrimination
at the hands of Mike Kerschner, a project manager for Tutor-
Perini. He was pressuring me to proceed with ordering expensive
Siemens electrical gear, but my change order hadn't yet been
signed for that work, and STP owed me over $80,000. It was very
past due.
I put in a call to the local electrical union for an
electrician to do the power cutover, but the union wouldn't
fill my call for labor. I met with Mike Kerschner face to face
to discuss the ongoing failure of the union to respond to my
call. And after looking me up and down in a sexually suggestive
manner, he informed me that if I didn't have labor on the job
the next day, he would take over my work.
The next day my crews were shut out of the job, and my
equipment was taken over. I also received a letter from the
union that day, pulling manpower from all of my jobs, including
the bridge project. Fortunately, Kiewit intervened, and didn't
allow that to happen, so my company lived to see another day. I
later learned that Fisk took over my work, and that Tutor-
Perini had colluded with the union to make this happen.
My firm finally got paid the $80,000 owed by STP, only
because of a Federal Highway Administration investigation into
WSDOT's mishandling of the DBE program and the project.
Tutor-Perini has been found guilty of DBE fraud on several
occasions across the country, and has paid millions of dollars
in fines. In my opinion, the only reason Tutor-Perini hasn't
been disbarred from Federal contracting is because of the
powerful connection between this company and a certain U.S.
Senator.
In closing, the DBE program is essential to allow small
firms owned by women and minorities to compete for a few
pennies of the highway dollar. However, it must be administered
with strict compliance, starting with the Federal Highway
Administration's enforcement of CFR part 26.
State and local programs' field compliance need to start
from the bottom up, listening to the DBE firms and the field
inspectors from each agency, instead of from the top down, so
the issues can be resolved as soon as possible to avoid
business failure due to nonpayment and discrimination during
disputes.
Waivers should never again destroy a DBE firm, separating
the DBE communities.
Unfortunately, due to human nature, discrimination will
probably always be with us. But this program is effective, and
the committee has an opportunity to strengthen it and make it
more accountable and transparent to participating firms and
taxpayers. Thank you for the opportunity to share my story, and
I would be happy to share any other information you would like.
Thank you.
[Ms. Lerdahl's prepared statement follows:]
Prepared Statement of Mary T. Lerdahl, President, Emerald Consulting
Services, LLC
Good morning Chairman DeFazio and members of the Committee:
My name is Mary Lerdahl and I formerly owned an electrical
contracting firm in the Seattle area named DBE Electric. I started the
firm in November 2009 during the ``Great Recession'' after losing my
share of a similar firm as a result of a marital dissolution.
Altogether I had been an electrical contractor since 1996, for a total
of 22 years before I was driven out of business as a result of WSDOT's
(Washington State Department of Transportation) decision to waive white
women out of the federal DBE program. My company focused exclusively on
highway electrical projects; traffic signal systems, illumination,
Intelligent Transportation Systems. From 2009 to 2018 (the year the
company closed) my firm successfully completed 122 projects valued at
nearly $80 million. My firm never failed to complete a project on time
and finished all contracted projects with the exception of two, which
were the result of blatant discrimination, which I will explain later
in greater detail. The typical size of projects performed were
$500,000-$2,000,000.
The highlight of my career was building the SR 520 Floating Bridge
project, a design build project with Kiewit, the longest floating
bridge in the world. The overall project was about five years long;
about 2 years in design and 3 years in actual construction. The initial
contract was $8.9 million with the final contract value being $14
million. This project had an 8% mandatory DBE goal, which is why my
firm had a ``place at the table'', along with my company's proven track
record of projects with Kiewit and other firms. I learned so much from
that project, both technically as well as what it was like to ``work
with the big boys''. As doors opened to me because of my certification
as a DBE firm, I could see a bright future ahead for my company after
the successful completion of the project.
Kiewit treated me fairly and with respect and was a good example of
how a mega firm and a small, DBE firm could work together to build a
great project that all parties could be proud of.
At the same time I was working on the design portion of the bridge
project, I was working on the SR 99 Bored Tunnel project with Seattle
Tunnel Partners, (STP) a joint venture between Tutor-Perini and
Dragados.
The project had a value of $1.6 Billion and a 8% DBE Condition of
Award goal.
Initially my firm worked as a second tier subcontractor to one of
the larger local general contractors, and then directly for STP. The
contrast between Kiewit and STP couldn't be more stark. My firm faced
discrimination in many ways throughout my 2 year experience on the
tunnel project, finally culminating in a meeting required by WSDOT as a
result of the Conciliatory Change Order required by FHWA after an
investigation by FHWA showed widespread discrimination by STP against
DBE firms. Some of the specific instances of discrimination that I
personally suffered and my firm experienced are as follows:
1. Initial DBE ``outreach'' meetings in which Fisk Electric, a
large electrical contracting firm purchased by Tutor-Perini shortly
after winning the project, stated outright that they were only
interested in ``labor only'' bids from DBE firms, thereby denying DBE
firms the opportunity for profit on the less risky material purchases
portion of the project.
2. Sexual advances made directly to me by STP supervisors while I
was in the field supervising operations.
3. Slow payment processing and a feeling of ``begging'' to get
paid during the direct visits to STP's offices because of intentionally
slow payment processing; for example, two check signers who were hard
to track down, no option for ACH payments, delayed processing of change
orders while being demanded to perform work by STP supervisors prior to
the change orders being executed.
4. Invitations to bid electrical systems inside the tunnel that
were virtually identical to the work I was performing on the bridge
project just to provide ``good faith efforts'' and allow SICE, an
electrical firm owned by Dragados, to self-perform the work. My firm
wasted countless hours bidding this design-build work when STP knew all
along that they would never use my firm to build the work.
5. The final incident occurred when my firm was working to convert
electrical power from temporary diesel generators to provide power to
the refrigerated containers being unloaded at the Seattle waterfront to
permanent power. Since my crews primarily worked on signal systems, I
put in a call to the local IBEW (electrical workers) union for a call
for a journey level electrician with experience with such work; the
union failed to fill my call for labor and after a week without getting
my call for labor filled I had a meeting with the project
superintendent, Mike Kerschner to discuss the situation. At this time
there was a pending change order for $200,000 with specialized Siemens
equipment that I wasn't going to order the equipment until the change
order was approved. Mike Kerschner had been pressuring me to order it
anyway without a change order but I refused. When I met with him
regarding the power conversion issue due to the union's continued
failure to supply the requested labor, he was openly hostile to me
while at the same time giving me unwanted top to bottom looks that were
sexual in nature. He informed me that if I didn't get the needed labor
that he would take over my work. The next day I received a letter from
the IBEW stating that they were pulling all manpower off ALL of my jobs
because I had failed to make a trust payment, which was only two weeks
late due to STP's failure to pay my company. The union was colluding
with STP and Fisk Electric to drive my firm off the tunnel job, and
there were other large electrical contractors who were hoping to take
over my SR 520 Floating Bridge Project. Fortunately Kiewit didn't allow
that to happen, so the outright destruction of my business didn't
happen at that time. In retrospect I realize that my firm was a threat
to the assertion that DBE firms didn't have the technical expertise to
perform on such a large, technically challenging projects because I was
doing just that across the water. By the time I was locked out of the
job STP owed my firm over $80,000 and I am certain that the only reason
I eventually got paid was because of the focus of FHWA's investigation
into STP and WSDOT's administering of the DBE program. Public records
show that SICE, Inc. did $34,315.556.53 on the project and Fisk
Electric did $106,057,656.02, while my firm, DBE Electric did
$977,246.59. Both SICE and Fisk were hired by a local company, JH
Kelley, in order to minimize the appearance of the self-dealing by
STP's ownership of Fisk and SICE. It is widely known that Tutor-Perini
has been found guilty of DBE fraud in other areas of the country and
has paid millions of dollars in fines; our state simply wasn't prepared
to handle the assortment of dirty tricks that Tutor-Perini pulled in
order to line their own pockets while appearing to be employing ``good
faith efforts'' among the DBE firms who were hoping for a piece of the
pie.
While the SR 99 Bored Tunnel was one of the worst examples of
discrimination I experienced, it certainly wasn't the only one. I could
spend hours citing examples, but since my time for testimony before the
committee is limited, I will share just one more in detail. My firm was
working on a city project that had federal funds administered through
WSDOT Local Programs. The contract value was approximately $1.2
million. The general contractor was falling behind the critical path
schedule as originally submitted and approved by the city, and changed
the schedule to place the blame for the delays on my firm. When I
challenged the project manager and eventually the company president
regarding the disputed schedule and delays, they didn't want to meet
with me, only with my male project superintendent. The dispute few
uglier by the day, and resulted in the general contractor failing to
pay my firm nearly $300,000 at one point. The general contractor sought
to have my contract terminated, and WSDOT became involved in their
request in accordance with CFR Part 26 rules. In the interim, the
general contractor contacted my main pole supplier and threatened not
to pay for the $500,000 pole order if they placed it with my firm. Due
to the on-going hostilities WSDOT allowed the contract to be
terminated, but only for convenience, not for cause. I then brought
suit again the contractor and eventually was awarded the $300,000 owed
and attorney's fees after 3 years of legal battles. I know that the
only reason this situation wasn't able to be resolved without
litigation was because I am female and stood up for my company. I had
done business with this company before when I was in business with my
ex-husband, and when issues came up as they do in construction, they
were able to be resolved, ``man to man''. Not so when I was the
principal. The general contractor even stated in front of WSDOT
attorney's during meetings to resolve the issues that ``the only reason
he hired me was because he had to make the goal''. I'd also like to
mention that this man himself was a minority and had been in the DBE
program before graduating from the program. He was openly hostile to
women in the construction industry, unless they worked in the office,
not in the field and certainly not being an owner herself.
There are many other instances of outright and subtle
discrimination that I could cite, but unfortunately the worst was when
the agency that was supposed to help firms like mine actually caused
the destruction of my business by enacting the waiver to exclude white
women from the federal DBE program in Washington State. When the waiver
was enacted in June 2017 after being approved by Secretary Foxx on
December 16, 2016, my firm was doing approximately $8,000,000 in
revenue. After June 2017 when my firm was no longer considered eligible
for ``Condition of Award'' projects with DBE goals, I did not win one
single bid, including several that I knew I was the low bidder for.
This is when the full knowledge of the level of discrimination in the
highway construction industry really sunk in. I had fought battle after
battle for years, but surely I thought that my company's proven track
record of successful projects would see me through this unfortunate and
unfair period, but I was dead wrong. I did everything I could to get
work, begging contractors to use me on their projects. I had been the
only female electrical contractor doing major highway electrical
projects, and now the ``good ole boys'' were making up for lost time
getting on projects that I formerly might have won. When WSDOT excluded
my firm from participation, those project dollars didn't go to another
DBE firm; they went to larger firms in our region doing $50-600 million
in annual revenues! In the space of 18 awful months, my company died a
death of a thousand cuts as I watched my firm die, month after month. I
had to lay off my daughter, whom I had hoped to pass the company on to,
along with other family members and employees. Word spread at the IBEW
union that my company was going to go under, so getting quality labor
dispatches to finish my jobs was extremely difficult. I could have
easily filed for bankruptcy but I wanted to finish my projects and
cause as least amount of collateral damage as possible for my
employees, general contractors with which I had project backlog with,
and the public agencies who were counting on the projects to be
finished. By the fall of 2018 it was finished and there was nothing
left to show for my years of hard work except exposure to creditors due
to the personal guarantees typically required by DBE firms due to
credit discrimination. During the period of the demise of my business I
made two trips to Washington DC to meet with FHWA and USDOT to plead
for WSDOT's request to rescind the waiver dated September 13, 2017. I
met with Terence Coleman of the Department of Assistant General Counsel
to share how this delay in responding affirmatively to WSDOT's request
to rescind the waiver was causing my business failure, along with many
other women in the region, all to no avail.
Finally on December 13, 2019 USDOT denied WSDOT's request to
rescind the waiver; while the reasons cited speak for themselves, there
is no mention whatsoever of the skewing of the 2009-2011 data included
in the flawed study, which included both the DBE awarded dollars of the
two largest projects in Washington state history (SR 99 Bored Tunnel
and SR 520 Floating Bridge) as well as documented DBE fraud purported
by a white woman trucking firm that was eventually decertified as a DBE
firm by WSDOT.
In summary, while I am a positive person, I am also a realist. I
had hoped to see discrimination end during my lifetime, unfortunately
it seems to be getting worse in our society. While one can only change
oneself to be a fair and just person, we can't change human nature.
This committee through the federal DBE program has an opportunity to
make a big difference in small DBE firms. I don't think it's realistic
to expect to ``level the playing field'', but it is realistic to make a
significant impact and hold to account the large general contractors
who complain about the DBE contracting community getting a few pennies
of the federal contracting dollar. While it is too late for my firm to
benefit from the return of white women as Condition of Award as of
October 1, 2020, I am determined to do all that I can to coach and
mentor DBE firms as they navigate the difficult construction industry
and avoid being used and abused by some of the unethical prime
contractors who seek to abuse ``good faith efforts'' for their own
gain.
I had hoped to participate in building the Interstate Bridge
Replacement program, replacing the aging bridge connecting Washington
and Oregon after my successful completion of the SR 520 Floating
Bridge. When I left Oregon as a young girl in 1968 to move to
Washington with my mother and younger siblings she related that I said
``Seattle is my town'' when I saw the Space Needle. Now instead of
helping to build a physical bridge, I hope that I can use my experience
to build a bridge between DBE firms and the good general contractors
like Kiewit that do believe in this program to help empower DBE firms
to grow in the way that the DBE program was intended for.
Thank you for your time.
Mr. DeFazio. Thank you, Ms. Lerdahl.
Mr. Ali, you may proceed for 5 minutes.
[Pause.]
Mr. DeFazio. You have to unmute.
Mr. Ali. Oh, sorry. Oh, am I unmuted?
Mr. DeFazio. You are unmuted now.
Mr. Ali. I apologize for that, Chairman. I have my own
feelings about Cisco.
Chairman DeFazio, thank you, and members of the committee.
My name is Farad Ali, chairman of the advisory Government
Affairs Committee for the Airport Minority Advisory Council. I
am also the immediate past chairman of the Raleigh Durham
International Airport Authority. Thank you for providing AMAC
the opportunity to participate in the committee's hearing
today.
AMAC was founded 36 years ago to combat discrimination in
the airport industry. Since its founding, AMAC has been in the
forefront of every national policy discussion concerning this
ubiquitous nature of discrimination in the transportation
industry, and in particular, concerning airport contracting
opportunities for small and disadvantaged business enterprises.
AMAC's members include DBEs and airport concessionaire
DBEs, non-DBEs, airports, and airport officials, and all others
who are committed to promoting diversity and inclusion in the
airport industry.
The DBE authorization by Congress is vitally needed to
combat conscious and unconscious bias and institutional
discrimination that, regrettably, minority and women
entrepreneurs too often face. To be sure, steady progress has
been made. However, our DBEs and ACDBE members regularly attest
that, without the DBE program, they would be locked out of
contracting opportunities.
Having served in many capacities with AMAC, as board chair,
and committee chair, and as an airport commissioner, I too have
had my own direct observation about the additional work to be
done.
In addition, anecdotal accounts, like academic papers and
data from recent disparity studies, further document the
continuing challenge of racial and/or gender bias barriers to
full participation. They also point to the ongoing need for a
DOT DBE program.
AMAC works consistently with Congress, the U.S. DOT,
Federal Aviation Administration, aviation trade organizations,
and others, as a resource to provide education and guidance
concerning these public policies and best practices to redress
discrimination and further diversity and inclusion issues.
Often we are unwilling to, really, have candid
conversations and discussion about discrimination. But its
ongoing present-day manifestations are real.
With regard to the Government's interest in battling
discrimination, equality is a core value of our Constitution,
and fairness also yields great societal benefits.
Although there has been growth in a number of minority- and
women-owned firms in the United States, they continue to
experience both direct and indirect discrimination. Examples of
this is clear when you look at prime contractors and suppliers,
unequal access to capital, bias in bonding decisions, how
contracts are structured, and RFP experience requirements. The
Government has a powerful fundamental interest in addressing
these forms of discrimination.
The DBE program allows minority- and women-owned firms to
participate in federally assisted contracts worth millions of
dollars and, as you have heard earlier, these businesses are
only receiving pennies. But we really do appreciate all the
work that has been going on so far, and I would like to make a
few comments on the disparity studies that have been presented
for a fact of evidence.
While it was clear progress has been made, and many policy
battles have been won, it is also clear there is a continuing
and compelling need for the DBE program. There are far too many
instances when women and minorities are denied equal access to
opportunities in the transportation space. As noted, we
continue to see extreme, compelling statistical evidence of
discrimination, and its effect in disparity studies are really
clear, and we will present other ideas.
For a number of years, this committee has worked in a
bipartisan manner to shore up this program by monitoring
current discrimination and present-day effects on the past
discriminations, as well as legislation modifications for the
current program. These efforts have been really important, and
I want to let Members know that these policy gains have been
great.
But the COVID-19 epidemic has really created even more
problems for our diverse businesses. Although in response to
the pandemic Congress has provided a lot of assistance to small
business, they are hindered by these discrimination policies.
As I said earlier, these businesses have unique challenges that
can't be solved by short-term programs like the Paycheck
Protection Program, and other funding decisions.
ACDBEs will find themselves ill-equipped to participate in
programs like the Main Street Lending Program, and the airport
concessionaires, unlike passenger air carriers, air cargo
carriers, and associated contractors, received no explicit
assistance in phase 3 of the CARES Act. So I would like to ask
you to look at issues surrounding the DBE program, that you
look at what could be done in the short term to protect and
sustain these businesses that are under this current economic
crisis.
I thank you for the opportunity to testify before the House
Committee on Transportation and Infrastructure, and on behalf
of our group and the thousands of airport concessionaires, I
would like to say thank you. And if there are any other
questions, I will be happy to answer those at the appropriate
time.
[Mr. Ali's prepared statement follows:]
Prepared Statement of Farad Ali, Chairman, Government Affairs
Committee, Airport Minority Advisory Council
Chairman DeFazio, Ranking Member Graves, and members of the
Committee, my name is Farad Ali, and I am the Chairman of the
Government Affairs Committee for the Airport Minority Advisory Council
(AMAC). I am also the immediate past Chairman of the Raleigh Durham
International Airport Authority. Thank you for providing AMAC with the
opportunity to participate in the Committee's hearing today.
AMAC was founded thirty-six (36) years ago to combat discrimination
in the airport industry. Since its founding AMAC has been at the
forefront of nearly every national policy discussion concerning the
ubiquitous nature of discrimination in the transportation industry and,
in particular, concerning airport contracting opportunities for small
and disadvantaged businesses enterprises (DBEs). AMAC's members include
DBEs--and airport concessions DBEs (ACDBEs), non-DBEs, airports and
airport officials and others who are committed to promoting diversity
and inclusion in the airport industry. As a result, AMAC occupies a
unique vantage point concerning the purpose of this hearing.
The DBE program authorized by Congress is vitally needed to combat
conscious and unconscious bias and institutional discrimination that
regrettably minority and woman entrepreneurs too often experience. Too
be sure, steady progress has been made; however, our DBE and ACDBE
members regularly attest that without the DBE program they would be
locked out of contracting opportunities. Having served in many
capacities with AMAC (as a board chair and committee chair) and as an
airport commissioner I too have my own direct observations about the
additional work to be done. In addition, anecdotal accounts, academic
papers, and data from recent disparity studies--many of them undertaken
by AMAC members who are consultants and researchers--further document
the continuing challenge of racial and/or gender based barriers to full
participation. They also point to the ongoing need for the DOT DBE
program.
AMAC works consistently with Congress, the US Department of
Transportation, the Federal Aviation Administration, aviation trade
associations, and others as a resource for information, education and
guidance concerning public policies and best practices to redress
discrimination and further diversity and inclusion. On a bi-partisan
basis this Committee and the Congress has shown great leadership in
affirming the government's continuing interest in remedying
discrimination and its effects. As we are aware, Congressional efforts
to monitor ongoing evidence of discrimination undergird the statutory
and regulatory framework of the DBE program--and give airports a
targeted, narrowly tailored, evidence based ``tool'' to promote equity,
fairness, participation. Again, Mr. Chairman, AMAC thanks you and the
Committee for your ongoing leadership and collaborative approach with
industry stakeholders.
Often we are unwilling to have candid discussions about
discrimination and its ongoing present day manifestations. With regard
to the government's interest in combatting discrimination, equity is a
core value of our Constitution and fairness also yields other important
societal benefits. Although there has been growth in the number of
minority businesses in the United States, they continue to experience
both direct and indirect discrimination. Examples of indirect
discrimination include: direct discrimination by prime contractors or
suppliers, unequal access to capital, bias in bonding decisions, how
contracts are structured, RFP experience requirements in RFPs, and the
like. The government has a powerful and fundamental interest in
addressing these forms of discrimination and the DBE program is part of
that effort.
Minority-owned businesses remain underrepresented as a share of the
total U.S. business ownership. Moreover, these businesses when compared
to their non-minority counterparts typically have fewer employees and
lower revenues. This underrepresentation in large measure has its basis
in racial discrimination and addressing it is a critical reason why
Congress must continue to support initiatives like the DBE program.
The program allows women and minority-owned companies to
participate in federally-assisted transportation contracts worth
billions of dollars a year. The program is an essential entry point for
many DBE firms into the transportation space and there is a large and
growing body of evidence that shows that the DBE program enables women
and minority owned firms the opportunity to play in a space that would
otherwise be off limits to them. Simply put, this program works and as
noted previously, it is narrowly tailored to meet the constitutional
standard set out by the U.S. Supreme Court. A fact that has been
affirmed by many federal District and Courts of Appeal.
I'd like to offer a few more comments on disparity studies and
other fact based evidence that discrimination continues to a problem in
the transportation sector. While it's clear that progress has been made
and many policy battles have been won, it is also clear that there is
still a continuing and compelling need for the DBE program. In far too
many instances women and minorities are being denied equal access to
opportunities in the transportation space. As noted previously, we
continue to see extremely compelling statistical evidence of
discrimination and its effects from a variety of disparity studies that
are produced by state and local governments. These studies are backed
up by countless accounts from women and minority owned firms that show
that they continue to operate on an uneven playing field. AMAC
continuously works with its members to monitor ongoing discrimination,
and we will submit some examples to the Committee. AMAC believes that
these accounts show that this problem is not specific to any one
county, state, or group. Rather, it exists throughout the country and
effects countless individual businesses.
In the aggregate, these studies show us that women and minority
owned firms continue to face discrimination and that without
initiatives like the DBE program, these firms would receive far fewer
opportunities to successfully compete for contracts in the
transportation sector. AMAC commends the work that the Committee has
done in this area and I would personally like to thank all of the
Committee Members and their staff for working to ensure that the DBE
program continues to create a fairer marketplace in which women and
minority owned businesses are able to find opportunities in
transportation sector. For a number of years, this Committee has worked
in a bipartisan manner to shore up and maintain this program by:
Monitoring Current Discrimination and the Present Day
Effects of Past Discrimination: Holding hearings like this one permit
the Committee to hear directly from DBEs and ACDBEs and their
representatives about the discrimination they experience as they
attempt to establish and grow their businesses. It is critically
important that Congress and the public have a full understanding of the
types of discrimination that persist across the nation so that they can
support and improve the programs intended to address such
discrimination.. We are grateful to this Committee for the work it has
done in this area.
Legislative Modifications to the Current Program that
Foster a Fairer Marketplace: Similarly, this Committee has also worked
to incorporate needed statutory modifications into legislation that has
moved through this committee. Again, for example, in the 2018 FAA
Reauthorization, the Committee addressed a long-standing discriminatory
small business ``size standard'' barrier to DBEs involved in FAA-
assisted contracting. The legislation rectified this matter by
conforming the DBE size standard for programs authorized by the FAA
bill to those set by the U.S. Small Business Administration. The prior
definition had not used size tests that are generally applicable under
the Small Business Act, but instead imposed an arbitrary rule that
reduced the size standard for DBEs by approximately 30% as compared to
the size standard set in the Small Business Act. We note as well that
H.R. 2, which recently passed the House of Representatives, would
eliminate the discriminatory small business standard with respect to
all DOT modes--highways, transit, and rail.
These efforts have been substantive and helpful in ensuring that
the DBE program continues to be a success. However, while I and AMAC
applaud the Committee for its efforts in assisting women and minority
owned businesses, I want to take some time to let Members know that
many of these policy gains (particularly in airport concessions space)
will likely be lost as a result of the COVID-19 Pandemic--if Congress
does not provide direct and immediate assistance to concessionaires.
The COVID crisis has absolutely decimated women and minority owned
airport businesses. From the vantage point of the airport sector, I can
say that this crisis and the resulting economic downturn has been
absolutely devastating. Airport concessionaires including Disadvantaged
Business Enterprises (ACDBEs) are the third major partner in an
ecosystem that serves air travelers. Concessionaires take empty airport
terminals and turn them into vibrant shopping and dining destinations
that generate important revenues for themselves and fees that are paid
to airports. These concessionaires are major sources of employment and
taxes for surrounding communities and they help to grow the airports in
which they are located by providing (in aggregate and pre-COVID times)
approximately $2.5 billion in non-aeronautical revenue to airports.
This revenue fuels new airport growth by underpinning airport bond
financing, development, and growth.
However, as airport concessionaires, these businesses are uniquely
dependent on the flow of passengers in and around airports. Our
revenues rise and fall based on Airline passenger traffic. If there is
no traffic, we cannot survive. With COVID-19, we have seen this traffic
fall sharply in some cases up to 95% of pre-pandemic totals. This
dramatic fall in potential customer traffic has already caused many
ACDBEs to close their doors permanently. Those that are still open are
barely surviving and have seen their revenues drop by 95 percent or
more. Unlike the rest of the economy, industry experts don't expect
this industry to bounce back quickly. Instead these experts expect
passenger traffic (and subsequently business sales) to remain depressed
for at least 18-36 months. Prior to this pandemic, ACDBE program had
created several success stories of businesses that not only scaled
within their home airport but were able to open new operations in
airports across the country. This program saw businesses that had begun
to setup joint ventures with larger businesses to grow their
operations, and had also seen older ACDBEs act as mentors to other
businesses that had just entered this space. COVID-19 could undo all of
this progress. I don't want to sound alarmist, but the industry and
ACDBEs in particular are at a crossroads.
Although in response to the pandemic Congress has enacted programs
intended to assist small businesses, they are not well suited to the
airport environment. As a result, concessionaires continue to struggle
to secure adequate resources to survive the COVID crisis. ACDBEs, which
are already hindered by discrimination in many aspects of their work,
are even more vulnerable to the pandemic. As I said earlier, these
businesses have unique challenges that can't be solved by short term
programs like the Paycheck Protection Act and often need more funding
than what is currently available under the Economic Injury Disaster
Loan. ACDBEs also find themselves ill-equipped to participate in
programs like the Main Street Lending Program and airport
concessionaires unlike the passenger air carriers, air cargo carriers,
or associated contractors received no explicit assistance in Phase III
of the CARES Act.
Although DBEs and ACDBEs, in particular, are severely impacted by
the pandemic, this economic devastation is not limited to the aviation
sector. Minority businesses in general have been decimated by the
pandemic. All across the country, minority businesses are shutting down
permanently. Lacking pre-existing relationships with banks, many of
these businesses were unable to access loans from the first round of
the PPP. Many of these companies simply folded, taking jobs and
potential revenues with them. This country can't afford to lose a
generation of minority entrepreneurs. These businesses are sources of
income, skills training, and development for many minority communities.
I ask that as you look into the issues surrounding the DBE program that
you also look at what can be done in the short-term to protect and
sustain businesses under the current economic climate. This Committee
and the DBE program has done an amazing job of helping to build a
transportation marketplace that is more equitable and fairer than it
would have been without your efforts. To protect and maintain these
efforts, I ask that Members continue to not only support the DBE
program, but to also work to support the ACDBEs and DBEs as they seek
to get back on their feet.
Thank you for this opportunity to testify before the House
Committee on Transportation and Infrastructure on behalf of AMAC. Our
group and the thousands of Airport Concessionaires that we represent
look forward to working with the Committee to advance policies that
will continue to protect and enhance the DBE program.
Mr. DeFazio. Thank you for your testimony.
Ms. Norman, you may proceed.
Oh, wait, I am sorry, I skipped someone.
Mr. McDonald, you may proceed.
Mr. McDonald. Thank you, Chairman DeFazio, and good
morning, committee members. My name is Sandy McDonald, and I am
the director of the Office of Economic and Small Business
Development in Broward County. I am also here on behalf of
COMTO, the Conference of Minority Transportation Officials,
this morning. And my office is also a member of the Airport
Minority Advisory Council.
It was an excellent start in 1983, when the provision was
made to authorize highway and Federal assistance programs to
allocate at least 10 percent of the funds to be spent with
DBEs. In 1987 the program progressed, and included women during
the reauthorization.
The DBE program, as we know it today, is one of the most
significant tools for guaranteeing the participation of
minority-owned and women-owned businesses in the Federal
procurement of goods and services in the arenas of highway,
aviation, and transit. But we also know we can do more.
In Broward County alone, the DBE program accounts for 408
businesses, of which 210 are women-owned. Throughout the State
of Florida, there are over 4,000 certified DBEs documented. The
significance of the number of DBEs in my county and State is
only one important factor to consider. Equally as important are
the number of jobs these DBEs provide and account for
throughout the State and the country. But yet we know we can do
more.
Broward County believes the success of our DBEs comes from
the additional assistance we are willing to offer in our
program. All DBE program administrators are required to meet
eight objectives of the DBE program under part 26. However, the
following specific objective, ``to assist the development of
firms that can compete successfully in the marketplace outside
the DBE program,'' is one we put extra emphasis on and apply to
grow our minority and women participation and, yes, grow our
overall economy.
The DBE program in Broward County develops and directly
affords our minority- and women-owned businesses the chance to
perfect their craft, realize their growth, build capacity, and
nurture relationships that can carry them far beyond a single
contract. Going through the process for a DBE is invaluable.
Whether they win or lose a specific bid, it allows them to
create relationships that lead to partnerships that have the
potential to result in future contracting opportunities. And it
is that potential with our firms we want to build on even more.
Providing this opportunity through Department of
Transportation contracting for minority- and women-owned
businesses goes far beyond the one single contract. It is
imperative that a DBE program achieves the outlined objectives.
It is these objectives that provide opportunities for DBEs, and
are the standard that DBELOs--Disadvantaged Business Enterprise
Liaison Officers--such as myself, govern our programs by. We
recognize that there is always room for improvement. We accept
the challenges that arise as opportunities to expand on the
original intent, and to continue the purpose of the program.
I have seen the professional growth of DBEs over time. I
have witnessed the evolution of business owners with an idea
who started operations in small residential markets, and then
expanded to commercial markets, and prepared themselves for
Government procurement. I have certified businesses who met all
the eligibility criteria for DBE participation, but were not
familiar with Government bidding or establishing professional
relationships. I have worked with established DBE businesses
who have used their talents and experiences to grow their
business beyond my county, and beyond my State, and to provide
their service in multiple States.
I have also, unfortunately, seen those businesses who were
not given the opportunity this program should allow. We can
actually do more.
The DBE program affords minority- and women-owned
businesses the chance to start, develop, and master their
abilities, and grow beyond their initial footprint and the
program. For this reason and many more, the DBE program needs
to continue for an additional 37 years and beyond.
While my office in Broward County continues to find more
ways to increase our DBE participation while focusing on
successful contracting awards to DBEs, we also pay attention to
the areas where there are opportunities to grow, and embrace
the challenges that could make this program even better. The
success of our program and the impact it has on the local and
State economy is an ideal example of the importance of the DBE
program to drive equality in the field of transportation.
And yes, I will say without question, COVID has impacted
our community in the worst way, and we believe the DBE program
will be one of those starts that helps us to bring our
community back and support the minority- and women-owned
businesses.
Thank you for this opportunity.
[Mr. McDonald's prepared statement follows:]
Prepared Statement of Sandy-Michael E. McDonald, Director, Office of
Economic and Small Business Development, Broward County, Florida
Greetings Chairman DeFazio and Committee Members:
My name is Sandy-Michael E. McDonald and I am the Director of the
Office of Economic and Small Business Development for Broward County,
Florida. I also serve as the Disadvantaged Business Enterprise Liaison
Officer (DBELO) and Airport Concession Disadvantaged Business
Enterprise Liaison Officer (ACDBELO) for the administering of the DBE
and ACDBE programs under 49 CFR Parts 26 & 23. As the DBELO/ACDBELO, it
is my responsibility, and that of my office, to ensure that the
objectives of the Disadvantaged Business Enterprise (DBE) and the
Airport Concessions Disadvantaged Business Enterprise (ACDBE) programs
are adhered to. This includes certifying eligible applicants and
confirming that program activities and projects are monitored and
reported accurately. As this Committee on Transportation and
Infrastructure convenes to hear testimony on the topic of ``Driving
Equality: The U.S. Department of Transportation's Disadvantaged
Business Enterprise Program'', I would like to share some of my
thoughts, professional experiences, and observations of my daily role
in driving equality and using the DBE program to do so.
Opening Statement
It was an excellent start in 1983 when the provision was made to
authorize highway and federal financial assistance programs to allocate
at least 10% of the funds to be spent with DBEs to ensure that
minorities would have an opportunity to participate and compete. In
1987, as the program progressed, it included women during the
reauthorization. The DBE program as we know it today, is one of the
most significant tools for guaranteeing the participation of minority-
owned and women-owned businesses in the federal procurement of goods
and services in the arenas of Highway, Transit and Aviation. However,
it also serves as a foundation for other federal procurement programs
and contracting opportunities.
In Broward County alone, the DBE program accounts for 408
businesses; of which 210 are women-owned. Throughout the State of
Florida there are over 4,043 certified DBEs documented. The
significance of the number of DBEs in my county and state is only one
important factor to consider. Equally as important, are the number of
jobs these DBEs provide and account for throughout the state and
country. The implications and impact on labor and economics of these
combined factors are not singular, but exponential. As an office, we
are excited about growing the number of DBEs in the county, and
throughout the state. We are even more excited about developing DBEs to
participate successfully in the process, and then, preparing them to
win contracts. That is the true value of the program.
Broward County believes the success of our DBEs comes from the
additional assistance we are willing to offer in our program. All DBE
program administrators are required to meet the eight objectives of the
DBE Program under 49 CFR Part 26.1. However, the following specific
objective: ``To assist the development of firms that can compete
successfully in the marketplace outside the DBE program'', is the one
we apply to grow our minority and women participation, and to grow our
overall economy. We support this by preparing minority and women owned
businesses to contract and provide services in all areas of government,
private industry, national and international markets, as well as to
produce more entrepreneurs and startup businesses.
Need of the Program--Then and Now
Broward County clearly understands the importance and the need for
the DBE program since its inception to the present. Through the
projects and procurement of our Aviation and Transit Departments, our
DBEs are given the opportunity to not only participate as a
subcontractor, but to also serve as Prime Contractors (Primes). Due to
our unbundling and small business development, our DBEs can serve as
Primes on contracts and offer additional opportunities to other DBEs as
subcontractors. The DBE program in Broward County develops and directly
affords our minority and women owned businesses the chance to perfect
their craft, realize their growth, build capacity, and nurture
relationships that carry them far beyond a single contract. Going
through the process for our DBEs is invaluable. Whether they win or
lose a specific bid, it still allows them to create relationships that
lead to partnerships that have the potential to result in future
contracting opportunities outside of the government. Providing this
opportunity through DOT contracting for minority and women owned
businesses goes far beyond the contract.
It is imperative that a DBE program achieves the following
objectives:
a) To ensure nondiscrimination in the award and administration of
DOT-assisted contracts in the Department's highway, transit, and
airport financial assistance programs;
b) To create a level playing field on which DBEs can compete
fairly for DOT-assisted contracts;
c) To ensure that the Department's DBE program is narrowly
tailored in accordance with applicable law;
d) To ensure that only firms that fully meet this part's
eligibility standards are permitted to participate as DBEs;
e) To help remove barriers to the participation of DBEs in DOT-
assisted contracts;
f) To promote the use of DBEs in all types of Federally assisted
contracts and procurement activities conducted by recipients.
g) To assist the development of firms that can compete
successfully in the marketplace outside the DBE program; and
h) To provide appropriate flexibility to recipients of Federal
financial assistance in establishing and providing opportunities for
DBEs.
It is these objectives that provide opportunities for DBEs, and are
the standard that DBELOs, such as myself, govern ourselves and the
program. These along with the principles of professionalism and
personal compassion, commitment, interest in growing and sustaining
minority and women owned businesses, and striving for a greater
economy, is why my office and Broward County supports and takes
seriously our role and responsibility.
We recognize that there is always room for improvement. We accept
the challenges that arise as opportunities to expand on the original
intent, and to continue the purpose of the program. Broward County uses
the DBE program and county contracting funded by DOT to stabilize and
grow our economy and workforce. Now, more than ever, due to the COVID-
19 public health crisis, industries such as aviation and transit have
been adversely impacted, and to a degree, completely shut down in some
locations for 5 months or more. Broward is identifying opportunities
through Master Plans and through previously dedicated funding sources,
to continue projects that will put some of our DBEs back to work and
assist in the rejuvenation of our economy. We also realize that for the
DBEs we have certified over the years, a significant part of developing
them is also making sure they have the necessary access to capital.
DBEs must be able to not only win a contract, but also to execute the
contract over time. They must be able to meet all their financial
obligations as they await payment. Clearly, this is a priority for all
small businesses, especially minority and women owned businesses.
Broward County is committed to leveraging resources to assist our
businesses in being prepared financially. Another key element of
developing our DBEs is making sure they have examples of best practices
and access to information sharing. We continue to grow in that area;
this includes building Mentor-Protege relationships, as well as
business development workshops on topics and areas of need and demand.
Closing Remarks
I have seen the professional growth of DBEs over time. I have
witnessed the evolution of business owners with an idea who started
operations in small residential markets and then expanded to commercial
markets and prepared themselves for government procurement. I have
certified businesses who met all the eligibility criteria for DBE
participation but were not familiar with government bidding or
establishing professional relationships. I have worked with established
DBE businesses who have used their talents and experiences to grow
their business beyond my county and beyond my state to provide their
services in multiple states.
The DBE program affords minority and women owned businesses the
chance to start, develop, master their abilities, and grow beyond their
initial footprint and the program. For these reasons, and many more,
the DBE program needs to continue for an additional 37 years and
beyond. While my office and Broward County continues to find more ways
to increase our DBE participation numbers, while focusing on the
successful contracting awards to DBEs, we will also pay attention to
the areas where there are opportunities to grow and embrace the
challenges that could make this great program even better. We will
continue to work to make sure that more than our county office and
staff are aware of the success of the DBE program and its participants.
The participants themselves and their businesses are the best way to
tell the story, and to have a voice for recruitment of new DBEs.
Existing DBEs are the best trainers to share what the best business
practices are. Existing DBEs are the demonstrators of how to contribute
to the economic vitality, success, and a growing economy. Broward
County will continue to do its part to meet and exceed all the
objectives of the 49 CFR to maintain a successful DBE program. The
success of our program and the impact it has on the local and state
economy is an ideal example of the importance of the DBE program to
drive equality in the field of transportation. Broward County
exemplifies what DBEs, in partnership with government, working within a
federal program that is committed to utilizing a target group, can
produce.
Thank you for this opportunity to share my knowledge and experience
with the DBE program. The impact the program has historically had on
the economy, and the effect it continues to have should not be
minimized. I am in full support of the continuation of the program in
the interest of driving equality.
Mr. DeFazio. Thank you, Mr. McDonald. While you are
testifying, if you wonder why I am looking over there, somehow
some people show up on that screen, and some people only show
up over there. So I don't know--I would hope, if our tech
person is listening, when someone is speaking, if we could pop
them up on the main screen, so we can just look forward.
With that, Ms. Norman, you may proceed.
Ms. Norman. Thank you very much, Mr. Chairman and members
of the Transportation and Infrastructure Committee. Thank you
all so much for allowing me to be a part of this process, and I
am very honored and pleased to appear before you today. My name
is Sandra D. Norman. I am division administrator for civil
rights with the Virginia Department of Transportation.
As director, I know firsthand of the DBE program's
importance that is within your jurisdiction. I am very
supportive of the DBE program that assists minority- and women-
owned businesses who are ready, willing, and able to compete
and perform contract work as either a prime contractor or
subcontractor. I believe it is the right thing to do. It
continues to drive equality and inclusiveness.
The DBE program for the United States meets constitutional
tests. Every court has held that the DBE program regulations
and 49 CFR 26 are constitutional.
Why is the DBE program important? Here are some of my
thoughts for you to consider.
The DBE program has its roots in the Civil Rights Act of
1964. It has been regulated through a series of reauthorization
legislative initiatives. The DBE program applies to airport and
surface transportation, highway, transit, and aviation. The DBE
program has been enacted by Congress to address historical
discrimination against minority-owned firms in the
transportation industry, and to ensure that minority- and
women-owned businesses have a fair chance to participate in
contracting opportunities made possible by Federal financial
assistance.
The DBE program, with its rigid certification requirements,
presents an excellent opportunity for a win-win for all
parties.
It is a success for VDOT, and a success for the community.
We want the residents of those communities to benefit from the
public investment in that community. The majority of employment
growth in the United States comes from small businesses. When
small businesses are allowed to do contract work, it is an
opportunity for people who might have been excluded from the
relevant workforce to showcase their talents and skills, get
training, and work within the transportation industry to have
more employment opportunities in the future.
Advancing diversity and making money are not conflicting
goals. It is good for business and good for society.
DOT's DBE program is as relevant today as ever to level the
playing field in transportation for individuals, businesses,
and communities of race, color, and gender. Our country suffers
when talented people who have new ideas and who want to work
hard are denied the opportunity to compete because of their
ethnic background, race, or gender. And that is why there is a
continuing need for the Disadvantaged Business Program, a need
to ensure that small businesses can compete fairly for Federal-
funded, transportation-related projects.
The DBE program, independent of the inherent challenges and
the nature that comes with those challenges, has provided
opportunities for minorities and women-owned small businesses
and other contractors to participate in an arena that has
historically not seen such participation. It has allowed people
to create jobs, and give their employees a quality of life
which they would not have been able to do before the DBE
program.
So, independent of all the challenges, the right part of
the program is access, access to many construction projects
that use governmental money that will have a requirement with a
designated percentage of the total contract values awarded,
making sure they are awarded to the DBEs. This allows access to
DBE businesses that may not have been able to compete on price
with larger operations to win contracts on projects.
In addition to the financial benefit, contacts are made
with respective industries that may lead to additional work. It
is about people.
It is about jobs. And too often we forget that our
industry's golden nuggets are the people who participate in the
DBE program, our small businesses and the thousands upon
thousands of people they employ.
Oftentimes we forget that the faces behind the businesses
also want to leave a legacy for their children, grandchildren,
and for generations yet unborn.
In closing, the success of DOT's DBE program depends on the
rich diversity, skills, and talents of our DBEs. VDOT, as an
agency, will continue to serve as a model DBE program to ensure
that minority- and women-owned businesses have a fair
opportunity to participate in contracting opportunities at
VDOT. Therefore, we are committed to championing and
strengthening our DBE program.
It is the real-life stories of discrimination for minority
and women business owners that are vital to assisting courts,
policymakers such as yourselves, and the public to understand
the need to preserve and improve the Government DBE program
that helps to drive equality and inclusiveness within the U.S.
DOT DBE program.
Again, I am honored, and thank you so much for your time
and consideration.
[Ms. Norman's prepared statement follows:]
Prepared Statement of Sandra D. Norman, Division Administrator, Civil
Rights, Virginia Department of Transportation
Thank you very much, Mr. Chairman, and members of the
Transportation and Infrastructure Committee. Thank you all so much for
allowing me to be a part of this process and I am very honored and
pleased to appear before you today.
My name is Sandra D. Norman, Division Administrator for Civil
Rights for the Virginia Department of Transportation (VDOT). As
Director, I know firsthand of the DBE Program's meaning that is within
your jurisdiction. I am very supportive of the DBE program that assists
minority and women-owned businesses who are ready, willing, and able to
compete and conduct contract work as either a Prime Contractor or
Subcontractor. I believe it is the right thing to do.
The Disadvantaged Business Enterprise (DBE) program for the U.S.
meets constitutional tests. Every court has held that the DBE program
regulations at 49 CFR Part 26 are constitutional.
Why is the DBE Program Important, great question Mr. Chairman? Here
are my thoughts for Transportation and Infrastructure (T&I):
The Disadvantaged Business Enterprise Program (DBE) has its roots
in the Civil Rights Act of 1964. It has been regulated through a series
of reauthorization legislative initiatives. The DBE program applies to
airports and surface transportation (Highway and Transit). The DBE
Program has been enacted by Congress to address historical
discrimination against minority-owned firms in the transportation
industry and to ensure that minority and women-owned businesses have a
fair opportunity to participate in contracting opportunities made
possible by Federal financial assistance
The DBE program, with its rigid certification requirements,
presents an excellent opportunity for a win-win for all parties. It is
a success for VDOT and a success for the community. We want the
residents of those communities to benefit from the public investment in
that community. The majority of employment growth in the United States
comes from small businesses. When small businesses are allowed to do
contract work, it is also an opportunity for people who might have been
excluded from the relevant workforce to showcase their talents and
skills, get trained and work within the transportation industry to have
more employment opportunities in the future. Advancing diversity and
making money are not conflicting goals; it is good for business and
good for society.
Our DBE Program is as relevant today as ever: to level the playing
field in transportation for individuals, businesses, and communities of
race, color, and gender. Our Country suffers when talented people, who
have new ideas, and who want to work hard, are denied the opportunity
to compete because of their ethnic background, race, or gender. And
that is why there is a continued need for the Disadvantaged Business
Program, a need to ensure that small disadvantaged business enterprises
can compete fairly for federal funded transportation related projects.
The DBE program, independent of the inherent challenges and the
nature that comes with those challenges, has provided opportunities for
minorities and women-owned small businesses and other contractors to
participate in an arena that had historically not seen such
participation. It has allowed people to create jobs and give their
employees a quality of life, which they would not have been able to do
before the DBE program. So independent of all the challenges we have,
the right part of the program is ACCESS. Access to many construction
projects that use governmental money that will have a requirement with
a designated percentage of the total contract values awarded are
awarded to DBEs. This allows access to DBE businesses that may not be
able to compete on price with larger operations to win contracts on
projects that such businesses may not traditionally be able to win on
price alone. In addition to the financial benefit, contacts are made
with respective industries that may lead to additional work. It is
about people, it is about jobs, and too often, we forget that our
industry's golden nuggets are the people who participate in the DBE
program and the thousands upon thousands of people they employ.
Oftentimes we forget that the faces behind the businesses also want to
leave a legacy for their children, grandchildren, and for generations
yet unborn.
The success of VDOT's DBE Program depends on the rich diversity,
skills and talents of our DBEs. VDOT will continue to serve as a model
DBE Program to ensure that minority and women-owned businesses have a
fair opportunity to participate in contracting opportunities at VDOT.
Therefore, we are committed to championing and strengthening our DBE
Program. It is the real life stories of discrimination from minority
and women business owners that are vital to assisting courts,
policymakers such as yourselves, and the public to understand the need
to preserve and improve the government disadvantaged business programs
that help to DRIVE EQUALITY.
Again, I am honored, and thank you very much for your time and
consideration.
Mr. DeFazio. Thank you, Ms. Norman.
Dr. Wainwright, you may proceed for 5 minutes.
Mr. Wainwright. Thank you, Chairman DeFazio, Ranking Member
Graves, members of the committee. Good morning. I appreciate
the invitation to appear here today. My name is Jon Wainwright.
I hold a Ph.D. in economics from the University of Texas at
Austin. Until my recent retirement after 24 years, I served as
a managing director at NERA Economic Consulting. My primary
career focus has been analyzing the effects of discrimination
on minorities and women.
My written testimony contains 90 pages of analysis
conducted and compiled for this hearing. I will attempt to
summarize. I have performed extensive original research using
95 existing disparity studies, as well as data covering
millions of firms from the Census Bureau Survey of Business
Owners, the Annual Business Survey, and the American Community
Survey. My testimony is a continuation of similar research I
have performed over the course of my career as an economist.
I conclude that there is strong evidence, both past and
present, of large, adverse, and statistically significant
disparities facing minority-owned and women-owned business
enterprises in the United States. Moreover, these disparities
cannot be explained solely or even primarily by differences in
factors that are untainted by discrimination. In other words,
these disparities are primarily due to discrimination and its
destructive effects.
I reached this conclusion from three main sources of
empirical evidence.
First, disparity studies overwhelmingly demonstrate adverse
findings for minority- and women-owned businesses. The vast
majority of the 95 disparity studies I reviewed in my testimony
identified large, adverse disparities affecting minority- and
women-owned businesses in both construction and professional
services like architecture and engineering. In construction, 72
percent of disparities were adverse, and 81 percent of those
were large and adverse. In construction-related professional
services, 77 percent were adverse and 97 percent of those were
large and adverse. I am confident that, if a similar analysis
were conducted with additional studies such as the 40 that have
been introduced into the record here today, it would reveal
similar results.
Second, census data shows large, adverse, and statistically
significant disparities. The most recent complete census showed
that, for every dollar of sales and receipts earned by
nonminority male-owned firms, African Americans earned just
$.34, Hispanics just $.47, and Asians just $.47. American
Indian and Alaska Native-owned firms earned just $.43. Native
Hawaiian and other Pacific Islander owned firms earned just
$.49, and women earned just $.41.
Third, statistical regression analysis shows that
historical and current disparities are largely due to
discrimination. The most recent American Community Survey shows
that the rate of business formation for African Americans would
be 120 percent higher in the absence of discrimination. For
Hispanics, the figure is 41 percent; for Asians, 30 percent
higher; for American Indians and Alaska Natives, 43 percent
higher; for Native Hawaiians and other Pacific Islanders, 58
percent higher; for women, 44 percent higher, in the absence of
discrimination.
In closing, there is still some good news. As my testimony
shows, and as you have heard today from the other witnesses,
although severe disparities persist, we are making progress,
thanks primarily to public efforts like the DBE and ACDBE
programs. Still, now is not the time to reduce our efforts to
eliminate business discrimination and its effects. Indeed, the
evidence is overwhelming that, if we eliminate or reduce these
programs, much greater disparities will very quickly occur.
The best metaphor I can offer is to consider someone like
myself, who takes blood pressure medication: if you take my
blood pressure while I am on my meds, it will read close to
normal. Obviously, that does not mean that any responsible
doctor will say it is time to stop taking my medicine. This is
precisely why I and other researchers in this area try to
examine both public-sector contracting markets, where
affirmative measures like the DBE program are found, as well as
private-sector contracting markets, where such programs are
rare and, consequently, discrimination remains almost totally
undermediated.
The bottom line is this: despite admirable progress,
discrimination and its destructive effects are deeply rooted in
the American economy. Such discrimination makes it immeasurably
harder for women and minorities to form and grow their own
firms. This reality has innumerable harmful consequences for
our economy and for our Nation. For all these reasons, I
strongly urge you to reauthorize the DBE program. Thank you
very much.
[Mr. Wainwright's 55-page prepared statement follows. The
transcript resumes on page 95.]
Prepared Statement of Jon S. Wainwright, Ph.D., Affiliated Consultant,
NERA Economic Consulting
Chairman DeFazio, Ranking Member Graves, and Members of the
Committee:
Thank you for the invitation to appear here today. My name is Jon
Wainwright. I hold a Ph.D. in economics from the University of Texas at
Austin. Until my recent retirement after 24 years, I served as a
Managing Director at NERA Economic Consulting in Austin, Texas and
Chicago, Illinois. NERA is a national and international economic
consulting firm dedicated to applying economic, finance, and
quantitative principles to complex business and legal challenges. One
of my primary areas of interest as a professional economist has been
documenting and analyzing the effects of discrimination on minorities,
women, and other disadvantaged groups.
I would like to ask the Committee's permission to include my entire
testimony in the record as if read in full and to supplement my
testimony with additional material if needed.
A. Introduction
I have been asked to provide a statistical overview of the
historical and current state of Minority-Owned and Women-Owned Business
Enterprise (M/WBE) in the United States, for the economy as a whole and
particularly in those industry sectors relevant to Federal surface and
aviation transportation funding.
My findings are drawn from evidence in numerous studies of M/WBE
participation in public sector contracting activity that have been
performed in the wake of the U.S. Supreme Court's ruling in City of
Richmond v. J. A. Croson Company,\1\ many of which I conducted myself.
These disparity studies examine statistical evidence of M/WBE
participation in public sector and private sector business activity
compared to M/WBE representation in the relevant business populations,
and offer explanations for the disparities observed between these
factors. They also include qualitative, or anecdotal, accounts from
both M/WBEs and non-M/WBEs regarding these disparities.
---------------------------------------------------------------------------
\1\ 488 U.S. 469 (1989).
---------------------------------------------------------------------------
Additionally, I have drawn findings from the few primary sources of
statistical evidence that exist regarding M/WBEs, namely the Census
Bureau's historical Survey of Business Owners, its new Annual Business
Survey, and its ongoing American Community Survey. The Survey of
Business Owners and its recent successor, the Annual Business Survey,
provide information regarding the total number of M/WBEs in the
country, their gross sales and receipts, and their employment and
payroll, both in absolute terms as well as relative to their
nonminority, male-owned counterparts. The American Community Survey is
an annual version to the old decennial census long form and provides
evidence regarding patterns of business formation by minority and
female entrepreneurs and associated business earnings relative to their
nonminority, male-owned counterparts.
In preparing this testimony, I conducted extensive original
research using all of the above-mentioned sources of evidence. This
research is a continuation of similar research I have performed over
the course of my career as an economist. Based on the findings
presented below, I conclude that there is strong evidence, both past
and present, of large, adverse, and statistically significant
disparities facing minority-owned and women-owned business enterprises
in the United States. Moreover, these disparities cannot be explained
solely, or even primarily, by differences between the relevant
populations in factors untainted by the effects of discrimination.
These disparities are primarily due to discrimination and its effects,
in the economy as a whole, as well as in the markets such as
construction, architecture, and engineering that most relevant to
Federal surface and aviation transportation funding.
1. Qualifications
I hold a Ph.D. in economics from the University of Texas at Austin.
My graduate curriculum included advanced courses in statistics,
econometrics and labor economics, among others. Prior to joining NERA
in 1995, I served as a Research Associate Professor at the Lyndon B.
Johnson School of Public Affairs at the University of Texas at Austin
and also headed my own economic consulting firm. While at NERA, I
conducted economic and statistical studies of discrimination for
attorneys, corporations, governments and non-profit organizations. I
also conducted research and advised clients on adverse impact and
economic damage issues arising from contracting activities, hiring,
termination, performance assessment, compensation, and promotion. I
have extensive experience producing, processing, and analyzing large
and complex statistical data bases, including public sector contracting
and purchasing data, as well as with myriad socioeconomic and
demographic datasets produced by the Census Bureau and other official
statistical agencies.
Over the course of my career, I have conducted economic and
statistical research and assisted in litigation concerning the minority
and female participation in public contracting activities. From 2004
through 2018, I directed NERA's national discrimination consulting
practice. In that capacity, I served as the project director and
principal investigator for more than 40 studies of business
discrimination, and prior to that time as principal or co-principal
investigator on approximately a dozen additional business
discrimination studies. I have authored two peer-reviewed monographs
and several articles and white papers on this and related subjects,
including Guidelines for Conducting a Disparity and Availability Study
for the Federal DBE Program, published in 2010 by the Transportation
Research Board of the National Academy of Sciences.
Between 2010 and 2013 I served as the principal economic and
statistical expert on behalf of the U.S. Department of Justice,
testifying in four cases challenging Federal policies to promote
participation by minority-owned and/or women-owned businesses in
Federal contracting activities. These were:
Kevcon, Inc. v. The United States (United States Court of
Federal Claims), concerning the Small Business Administration's 8(a)
minority business set-aside program.\2\
---------------------------------------------------------------------------
\2\ Wainwright, Jon S. (2010).
---------------------------------------------------------------------------
Geyer Signal, Inc. and Kevin Kissell v. Minnesota
Department of Transportation, et al. (United States District Court for
the District of Minnesota), concerning the USDOT Disadvantaged Business
Enterprise Program.\3\
---------------------------------------------------------------------------
\3\ Wainwright, Jon S. (2012).
---------------------------------------------------------------------------
Midwest Fence Corporation v. United States Department of
Transportation, et al. (United States District Court for the Northern
District of Illinois, Eastern Division), concerning the USDOT
Disadvantaged Business Enterprise Program.\4\
---------------------------------------------------------------------------
\4\ Wainwright, Jon S. (2013b), (2013c).
---------------------------------------------------------------------------
Rothe Development, Inc. v. Department of Defense and
Small Business Administration (United States District Court for the
District of Columbia), concerning the Small Business Administration
8(a) minority business set-aside program.\5\
---------------------------------------------------------------------------
\5\ Wainwright, Jon S. (2013a).
I have been repeatedly qualified as an expert economic and
statistical witness in both Federal and state courts and have testified
in these and related matters on 20 occasions. I have also testified
before the U.S. Congress on these matters on five previous occasions.
My current curriculum vitae is attached to this testimony. The
source material relied on in reaching my findings and conclusions are
noted below in the body of my testimony.
2. Discrimination and its Effects, Historically and Currently,
Consistently Disadvantages Minority- and Women-Owned Business
Enterprises
As other researchers have noted, and as demonstrated in many of the
studies, reports, and other testimony submitted to Congress, minorities
and women have been historically and consistently disadvantaged by the
effects of discrimination in business enterprise.\6\ Despite progress
in some areas, these disadvantages are still present in business
markets.\7\ As my testimony demonstrates, although severe disparities
persist between non-minority male owned firms and minority- and women-
owned firms, we are making progress thanks to programs like the
Disadvantaged Business Enterprise Program. Still, now is no time to
reduce our efforts to eliminate business discrimination and its
effects. Indeed, much of the progress that has been achieved is due to
the effect that programs like the DBE program have had. The evidence is
overwhelming that, were we to eliminate or reduce these programs, much
greater disparities would very quickly occur. The best metaphor I can
think of is the person who takes blood pressure medicine. If we take
that person's blood pressure while they are taking their medicine,
their blood pressure will appear normal but that does not mean that any
responsible doctor would argue that the person should stop taking their
blood pressure medicine. This is precisely why I and other researchers
in this area try to examine both the public sector contracting markets
where affirmative measures like the DBE program are found as well as
the private sector contracting markets where such programs are much
more rare. This is also why, although my testimony includes voluminous
data from public sector sources like disparity studies, I also include
a great deal of information from Census sources which examine markets
that are largely unremediated by programs like the DBE program.
---------------------------------------------------------------------------
\6\ See, e.g., U.S. Department of Commerce (2015); Lowrey (2010a);
Lowrey (2010b); Marshall (2002); Wainwright (2000).
\7\ See, generally, U.S. Small Business Administration (2010).
---------------------------------------------------------------------------
African Americans are 13.3 percent of the general population, 12.6
percent of the civilian labor force, and 12.2 percent of total
employment. However, at last count, African Americans owned only 9.5
percent of the nation's businesses, and earned a mere 1.26 percent of
all business sales and receipts.\8\
---------------------------------------------------------------------------
\8\ General population statistics are from the U.S. Census Bureau
(2017a); civilian labor force and total employment figures are from the
Bureau of Labor Statistics (2018a, 2018b, 2018c); business enterprise
statistics are from the 2012 Survey of Business Owners, U.S. Census
Bureau (2018b). Note: Publicly owned companies have been excluded from
all calculations in this report that use Survey of Business Owners or
Annual Business Survey statistics.
---------------------------------------------------------------------------
Hispanics are 18.2 percent of the general population, 17.1 percent
of the civilian labor force, and 17.0 percent of total employment.
However, at last count Hispanics owned only 12.2 percent of the
nation's businesses, earned less than 4.0 percent of all business sales
and receipts.
American Indians and Alaska Natives are 1.3 percent of the general
population, but they are only 1.0 percent of the business population
and earned just 0.32 percent of business sales and receipts.
Asians and Pacific Islanders represent 6.1 percent of the general
population, 6.2 percent of the civilian labor force, and 6.2 percent of
total employment. While Asians own 7.1 percent of the nation's
businesses, they earned only 5.9 percent of business sales and
receipts.
Women represent 50.9 percent of the general population, 46.9
percent of the civilian labor force, and 46.9 percent of total
employment. However, they are only 36.4 percent of the business
population and earn only 11.9 percent of business sales and receipts.
Even those minorities and women who manage against the odds to
start their own businesses must compete in a business enterprise system
that has long been dominated by non-minority male-owned firms.\9\ The
advantages enjoyed by non-minority males in this context are borne out
in the statistics. In a groundbreaking pair of studies of employer
business closure rates, Professor Ying Lowrey documented that existing
African American-owned, Hispanic-owned, Asian and Pacific Islander-
owned, and women-owned businesses across a wide variety of industry
groups suffered substantially higher closure rates during the 2002-2006
period than did their nonminority male counterparts.\10\ More recently,
Professor Rob Fairlie has shown that African American, Hispanic Asian,
American Indian and Alaska Native, and female small businesses closed
at higher rates than their non-minority male counterparts during the
first month of widespread COVID-19 induced shelter-in-place
restrictions in April of this year.\11\
---------------------------------------------------------------------------
\9\ See, e.g., Wainwright (2000), pp. 17-22, and the studies cited
therein.
\10\ Lowrey, Ying (2010a), pp. 20-21; Lowrey, Ying (2010b), p. 16.
The comparison was between non-publicly held establishments that were
in business in 2002 but had closed by 2006 versus all non-publicly held
establishments in business in 2002.
\11\ Fairlie, Robert (2020). p. 16.
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Even among larger firms, such as those with one or more paid
employees, the disparities between minorities and women, on the one
hand, and non-minority males, on the other, are stark. In 2017, for
every dollar in sales and receipts earned by non-minority male-owned
employers, African American-owned employers earned 45 cents, Hispanic-
owned employers earned 57 cents, Asian and Pacific Islander-owned
employers earned 63 cents, American Indians and Alaska Native-owned
employers earned 67 cents, and women-owned employers earned 61
cents.\12\
---------------------------------------------------------------------------
\12\ U.S. Census Bureau (2020a). For employer firms, the most
recent data are from the 2017 Annual Business Survey, released in May
2020.
---------------------------------------------------------------------------
The overwhelming majority of businesses have less than 10
employees, and only a small fraction have more than 500 employees.
Minority- and women-owned firms are over-represented in the former
category and under-represented in the latter. For the smallest firms in
2017 (the most recent data available), 78 percent of non-minority male-
owned firms had less than 10 employees, compared to 82.1 percent of
African American-owned firms, 82.3 percent of Hispanic-owned firms,
81.2 percent of Asian and Pacific Islander-owned firms, 82.2 percent of
American Indian and Alaska Native-owned firms, and 82.2 percent of
women-owned firms.\13\ For the largest firms in 2017, 0.21 percent of
nonminority-owned male firms had 500 or more employees, compared to
0.12 percent of African Americans, 0.1 percent of Hispanics, 0.07
percent of Asians and Pacific Islanders, 0.11 percent of Native
Americans, and 0.1 percent of women.\14\
---------------------------------------------------------------------------
\13\ U.S. Census Bureau (2018b, 2018c 2018d).
\14\ Ibid.
---------------------------------------------------------------------------
B. Studies Conducted Since 2000 Provide Strong Evidence of Disparities
Against Minority- and Women-Owned Businesses
As mentioned above, between 2010 and 2013 I served as an expert
witness on behalf of the U.S. Department of Justice in its defense of
two challenges to the SBA 8(a) Program and two challenges to the USDOT
DBE Program. As part of this work, I collected and reviewed every known
study of M/WBE disparities published since 2000.
1. Data and Methods
Table 1 identifies 95 studies of minority and female business
enterprise completed between 2000 and 2012. These studies examined M/
WBE participation in public contracting and procurement for 127
different public entities and/or funding sources. The studies span 32
different states that collectively account for over 80 percent of the
general population of the United States.\15\ Of the 95 studies, 21 were
conducted under my direction. Over the course of these studies, I
personally examined and analyzed tens of billions of dollars worth of
public sector spending across tens of thousands of contracts and
subcontracts. The remaining 74 studies covered an even larger number of
public contracts and public dollars.
---------------------------------------------------------------------------
\15\ U.S. Census Bureau (2011e).
---------------------------------------------------------------------------
All of the disparity studies in Table 1 examined minority-owned
business enterprises as well as non-minority women-owned business
enterprises. Typically, M/WBEs include businesses owned by African
Americans, Hispanics, Asians and Pacific Islanders, American Indians
and Alaska Natives, and non-minority women.
A wide variety of government types are represented as well in these
disparity studies. Some studies encompassed the entire state (i.e.,
Indiana, Maryland, Minnesota, New York, Texas, and Virginia), others
were performed for single state agencies (i.e., Department of
Transportation studies in Alaska, Arizona, California, Colorado,
Georgia, Hawaii, Idaho, Illinois, Kansas, Maryland, Minnesota,
Missouri, Montana, Nevada, North Carolina, Oklahoma, Oregon, Virginia,
and Washington and the Division of Capital Asset Management and the
Housing Finance Agency in Massachusetts), others were done for cities
(i.e., Atlanta, Augusta, Austin, Baltimore, Boston, Charlotte,
Cincinnati, Columbia, Dayton, Denver, Durham, Fort Worth, Houston,
Kansas City, Memphis, Milwaukee, Minneapolis, Nashville, Philadelphia,
Phoenix, Portland, San Antonio, St. Louis, St. Paul, Tallahassee,
Tucson, and Tulsa), others covered counties (i.e., Pima, AZ; Broward,
FL; Leon, FL; Richmond, GA; Wyandotte, KS; Durham, NC; Davidson, TN),
and still more were for a variety of special districts including
schools, public utilities, housing authorities, airports, and transit
agencies.
All 95 studies identified included contracts and procurements for
public works in construction, and a large majority also included
contracts in the construction-related professional services (``CRS'')
sector, which includes architecture, engineering, and related services.
Construction and CRS activities include the public works performed by
highway departments, transit agencies, and airports under USDOT
jurisdiction.\16\
---------------------------------------------------------------------------
\16\ Construction prime contractors and subcontractors also
purchase a variety of supplies and materials (e.g., steel, concrete,
asphalt), as well as trucking services.
---------------------------------------------------------------------------
Many of the disparity studies in Table 1 encompass public
contracting and purchasing activities in other industry sectors as
well. This reflects the fact that state and local governments, and
their prime contractors and vendors, purchase goods and services from
practically every major industry. In addition to construction and CRS,
these include agriculture, mining, utilities, transportation, wholesale
trade, retail trade, finance and insurance, real estate, professional
and technical services, administrative and support services, waste
management services, educational services, health care and social
assistance services, food services, and others. NERA's most recent
study for the State of Maryland, for example, encompassed 695 distinct
industries.\17\
---------------------------------------------------------------------------
\17\ NERA Economic Consulting (2017), p. 45. However, public sector
spending is not typically distributed evenly among industries. In the
State of Maryland's case, 261 industries (38 percent) accounted for 99
percent of all spending over the study period.
---------------------------------------------------------------------------
In addition to covering construction, CRS, and other industries,
the 95 studies in Table 1 span the country geographically, representing
all four Census Regions and all nine Census Divisions. In all, 32
states plus the District of Columbia are represented here, as well as
53 of this Committee's 67 members.
As part of my work on behalf of USDOJ, I reviewed all of 95 studies
identified in Table 1. Typically, these studies include an Executive
Summary, a review of case law pertaining to M/WBEs, a review of the
government's purchasing and contracting policies as they pertain to M/
WBEs, a chapter estimating the availability of M/WBEs, a chapter
estimating the utilization of M/WBEs, a chapter comparing availability
and utilization to assess disparities, and a chapter examining
anecdotal evidence of discrimination. Often, these disparity studies
also included one or more chapters examining evidence of disparities
and discrimination in the wider market area, surrounding a particular
government's jurisdiction. These are referred to as ``private sector''
or ``economy-wide'' analyses.
2. Findings
Each study is different. They were prepared by different
consultants, for different governments, in different parts of the
country, with differing levels of resources. They examined different
periods of time and used a variety of methods for assessing
utilization, availability, and disparity, and for gathering anecdotal
information.\18\
---------------------------------------------------------------------------
\18\ A detailed discussion of the differences in methods employed
by different consultants is provided in Wainwright and Holt (2010), pp.
29-53.
---------------------------------------------------------------------------
Nevertheless, the striking similarities among these studies
strongly outweigh the differences. Foremost among these is an almost
universal finding that historical and contemporary discrimination
adversely impacts all different types of M/WBEs throughout the United
States, in the construction sector, the CRS sector, and in other
industry segments as well.
To begin to see this, Table 2 presents specific statistical
findings from the studies listed in Table 1. One primary function of a
disparity study is to gather information on a government entity's prime
contracting and subcontracting activity during the time period being
studied. Since the Federal DBE Program applies to both prime
contracting and subcontracting, I focused my review on the combined
utilization of M/WBEs as both prime contractors and subcontractors.\19\
---------------------------------------------------------------------------
\19\ Depending on how any given study's statistics were presented,
I had to carry out certain additional calculations in order to present
the information in Table 2 in a consistent manner. For example, a study
might show the total number of prime contract construction dollars
accruing to M/WBEs in one table, the total number of subcontract
construction dollars accruing to M/WBEs in another table, and the total
number of construction dollars overall in yet another table.
Calculating overall M/WBE prime contract and subcontract utilization
thereby required adding the figure in the first table to the figure in
the second table and dividing the sum by the figure in the third table.
These figures, in turn, might then be combined with availability
statistics from one or more tables in the study in question to form the
relevant disparity index.
---------------------------------------------------------------------------
I reviewed each study's findings concerning:
The percentage utilization of M/WBEs in construction
spending,
The percentage availability of M/WBEs for construction
spending,
The percentage utilization of M/WBEs in CRS spending, and
The percentage availability of M/BEs for CRS spending.
Several appear more than once in Table 2 since they provided
statistical evidence in more than one relevant category. Columns (1)
and (2) in Table 2 identify the state and political subdivision for
which each disparity study was performed. Columns (3) and (6) present
the utilization statistics for construction and CRS, respectively.
Columns (4) and (7) present the availability statistics for
construction and CRS, respectively. Columns (5) and (8) present the
disparity indexes for construction and CRS, respectively. Column (9)
indicates the years covered by each study. Column (10) provides the
page citations for the statistical data presented.
The disparity indexes presented in column (5) for construction and
column (8) for CRS are formed by dividing the M/WBE utilization
percentage by the M/WBE availability percentage, and multiplying the
result by 100. A disparity index of 100 or more indicates that M/WBEs
are being utilized at or above their market availability level. A
disparity index of less than 100 indicates that M/WBEs are being
utilized at or below their market availability level. A disparity index
of 80 or lower is commonly taken as an indicator that discrimination is
adversely affecting M/WBEs.\20\
---------------------------------------------------------------------------
\20\ Although not the same as statistical significance, the ``four-
fifths rule'' says that a disparity index of less than or equal to 80
(on a scale of zero to 100, zero being perfect disparity and 100 being
perfect parity), because it is large, or ``substantively'' significant,
indicates the presence of discrimination. See 29 C.F.R. Sec. 1607.4(d).
---------------------------------------------------------------------------
The substantial majority of the disparity studies reviewed and
presented in Table 2 identified large adverse disparities affecting M/
WBEs in both construction and CRS.\21\ There are 206 disparity indexes
altogether--127 for the construction sector and 79 for the CRS sector.
---------------------------------------------------------------------------
\21\ In Table 2, disparity indexes of 80 or lower are highlighted
in boldface type. Disparity indexes above 80 but still less than 100
(which would indicate parity with non-M/WBEs) are highlighted in
boldface italicized type.
---------------------------------------------------------------------------
In construction, 74 of 127 disparity indexes, or 58
percent, fall at or below 80; and 91 of 127, or 72 percent, are less
than 100.
In CRS, 59 of 79 disparity indexes, or 75 percent, fall
at or below 80; and 61 of 79, or 77 percent, are less than 100.
Combining the results from both industry sectors, 133 of
206 disparity indexes, or 65 percent, fall at or below 80; and 152 of
206, or 74 percent, are less than 100.
Notably, the general consistency of these results occurs despite
these studies having been undertaken by different consultants, using
differing methods, at different points in time, with different budgets,
and for a wide variety of state and local government agencies in a wide
variety of geographic locations. Perhaps most notably, these
disparities exist despite the fact that, in the overwhelming majority
of studies there was a strong, mature MBE or DBE program in place aimed
at eliminating disparities. In other words, these disparities are so
powerful and so severe that even strong efforts to level the playing
field are simply not enough to eradicate them.
Eleven different consultants produced the studies in Table 2.
However, just four firms produced 75 percent of these studies: MGT of
America, NERA Economic Consulting, BBC Research & Consulting, and Mason
Tillman Associates.
Of the 34 construction disparity indexes from MGT of
America, 20 (59 percent) are less than or equal to 80 and 26 (76
percent) are less than or equal to 100. Of the 15 CRS disparity indexes
from MGT, 12 (80 percent) are less than or equal to 80 and 12 (80
percent) are less than or equal to 100.
Of the 24 construction disparity indexes from NERA
Economic Consulting, 16 (67 percent) are less than or equal to 80 and
17 (71 percent) are less than or equal to 100. Of the 20 CRS disparity
indexes from NERA, 10 (50 percent) are less than or equal to 80 and 11
(55 percent) are less than or equal to 100.
Of the 23 construction disparity indexes from BBC
Research & Consulting, 13 (57 percent) are less than or equal to 80 and
17 (74 percent) are less than or equal to 100. Of the 20 CRS disparity
indexes from BBC, 17 (85 percent) are less than or equal to 80 and 17
(85 percent) are less than or equal to 100.
Of the 17 construction disparity indexes from Mason
Tillman Associates, 13 (76 percent) are less than or equal to 80 and 16
(94 percent) are less than or equal to 100. Of the 12 CRS disparity
indexes from Mason Tillman, 10 (83 percent) are less than or equal to
80 and 10 (83 percent) are less than or equal to 100.
Of the 29 construction disparity indexes from the balance
of consulting firms in Table 2, 12 (41 percent) are less than or equal
to 80 and 15 (52 percent) are less than or equal to 100. Of the 12 CRS
disparity indexes from the balance of consulting firms, 10 (83 percent)
are less than or equal to 80 and 11 (92 percent) are less than or equal
to 100.
Some specific results in Table 2 are highlighted below:
Of the 33 state DOT construction disparity indexes, 26
(79 percent) are less than or equal to 80 and 29 (88 percent) are less
than or equal to 100. These include Alaska, Arizona, California,
Colorado, Georgia, Hawaii, Idaho, Illinois, Kansas, Minnesota,
Missouri, Nevada, North Carolina, Oregon, Texas, Virginia, and
Washington.
Of the 24 state DOT CRS disparity indexes, 23 (96
percent) are less than or equal to 80 and 23 (96 percent) are less than
or equal to 100. These include Arizona, California, Colorado, Georgia,
Idaho, Illinois, Missouri, Montana, Nevada, North Carolina, Oklahoma,
Oregon, Virginia, and Washington. Only Hawaii was found to have
consistently utilized M/WBEs at or above their estimated availability
in CRS.
Of the 11 statewide (excluding DOTs) construction
disparity indexes, 7 (64 percent) are less than or equal to 80 and 10
(91 percent) are less than or equal to 100. Of the 4 statewide
(excluding DOTs) CRS disparity indexes, 3 (75 percent) are less than or
equal to 80 and 4 (100 percent) are less than or equal to 100.
Of the 41 city or county construction disparity indexes,
19 (46 percent) are less than or equal to 80 and 25 (61 percent) are
less than or equal to 100. Of the 22 city or county CRS disparity
indexes, 13 (59 percent) are less than or equal to 80 and 13 (59
percent) are less than or equal to 100.
Of the 39 special district (e.g., transit agencies,
airports, housing authorities, school districts) construction disparity
indexes, 23 (59 percent) are less than or equal to 80 and 27 (69
percent) are less than or equal to 100. Of the 28 special district CRS
disparity indexes, 20 (71 percent) are less than or equal to 80 and 21
(75 percent) are less than or equal to 100.
Finally, in almost all of the studies presented, the statistical
findings are accompanied by anecdotal evidence of discrimination
against M/WBEs.\22\ Many of these studies also include statistical
evidence of disparities in the surrounding private sector--in minority
and female business formation rates, business owner earnings, and
access to commercial loans and capital. This type of statistical
evidence is especially important since it helps explain why the large
and adverse disparities observed for M/WBEs can be attributed to
discrimination rather than to other, non-discriminatory factors.
---------------------------------------------------------------------------
\22\ See also, e.g., U.S. Small Business Administration (2010),
Aparicio (2009), Asian American Justice Center (2008), Lau (2009), Quon
(2008), U.S. Congress (2007), (2008), (2009a), (2009b), and (2009c).
---------------------------------------------------------------------------
3. Conclusions from the Disparity Study Data
According to my records, there are at least another 150 disparity
studies that have been completed since I finished my work for USDOJ in
2013. There is no doubt in my mind that were I to conduct a comparable
analysis on these latest studies, I would find similar results--large
and adverse disparities that continue to face M/WBEs throughout the
country. In the next two sections of my testimony, I examine the most
recent Census Bureau data with respect to M/WBEs.
Table 1. Selected Disparity and Availability Studies Performed in the United States Between 2000-2012
----------------------------------------------------------------------------------------------------------------
Year
State Subdivision Author Type of Study Completed
----------------------------------------------------------------------------------------------------------------
AK................................ Department of D. Wilson Consulting Disparity........... 2007
Transportation and Group, LLC.
Public Facilities.
AZ................................ Arizona Department of MGT of America, Inc. Disparity........... 2009
Transportation.
AZ................................ City of Phoenix...... MGT of America, Inc. Disparity........... 2005
AZ................................ City of Tucson....... D. Wilson Consulting Disparity........... 2008
Group, LLC.
AZ................................ Pima County.......... D. Wilson Consulting Disparity........... 2008
Group, LLC.
CA................................ Bay Area Rapid Mason Tillman Disparity........... 2009
Transit (BART). Associates, Ltd..
CA................................ California Department BBC Research & Disparity........... 2007
of Transportation. Consulting.
CA................................ Los Angeles County BBC Research & Disparity........... 2010
Metropolitan Consulting.
Transportation
Authority.
CA................................ Metrolink--Southern BBC Research & Disparity........... 2009
California Regional Consulting.
Rail Authority.
CA................................ Orange County BBC Research & Disparity........... 2010
Transportation Consulting.
Authority.
CA................................ San Diego Association BBC Research & Disparity........... 2010
of Governments. Consulting.
CA................................ San Diego BBC Research & Disparity........... 2010
Metropolitan Transit Consulting.
System.
CA................................ San Mateo County CRA International... Disparity........... 2008
Transit District.
CA................................ Santa Clara Valley CRA International... Disparity........... 2007
Transportation
Authority.
CO................................ City and County of NERA................ Disparity........... 2006
Denver, Denver
International
Airport.
CO................................ Colorado Department MGT of America, Inc. Disparity........... 2001
of Transportation.
CO................................ Colorado Department D. Wilson Consulting Disparity........... 2009
of Transportation. Group, LLC.
CT................................ Metropolitan District M3C................. Disparity........... 2009
Commission.
DC................................ Washington Suburban Mason Tillman Disparity........... 2011
Sanitary Commission. Associates, Ltd..
FL................................ Broward County....... MGT of America, Inc. Disparity........... 2001
FL................................ Broward County....... NERA................ Disparity........... 2010
FL................................ City of Tallahassee.. MGT of America, Inc. Disparity........... 2004
FL................................ Leon County.......... MGT of America, Inc. Disparity........... 2009
FL................................ School District of Mason Tillman Disparity........... 2007
Hillsborough County. Associates, Ltd..
GA................................ City of Atlanta...... Griffin & Strong.... Disparity........... 2006
GA................................ Consolidated NERA................ Disparity........... 2009
Government of
Augusta-Richmond
County.
GA................................ Georgia Department of Boston Research Disparity........... 2005
Transportation. Group, Inc..
GA................................ Georgia Department of BBC Research & Disparity........... 2012
Transportation. Consulting.
HI................................ Hawai'i Department of NERA................ Disparity........... 2010
Transportation.
ID................................ Idaho Transportation BBC Research & Disparity........... 2007
Department. Consulting.
IL................................ Illinois Department Mason Tillman Disparity........... 2011
of Transportation. Associates, Ltd..
IL................................ Illinois State Toll Mason Tillman Disparity........... 2011
Highway Authority. Associates, Ltd..
IL................................ Illinois State Toll NERA................ Disparity........... 2006
Highway Authority.
IN................................ Indiana Department of BBC Research & Disparity........... 2010
Administration, Consulting.
Indiana DOT, Ball
State Univ., Indiana
State Univ., Indiana
Univ., Ivy Tech
Comm. College,
Purdue Univ., Univ.
of Southern Indiana,
Vincennes Univ..
KS................................ Kansas Department of MGT of America, Inc. Availability........ 2003
Transportation.
KS;............................... City of Kansas City; Mason Tillman Disparity........... 2006
MO Wyandotte County, Associates, Ltd..
KS; Kansas City Area
Transit Authority;
Kansas City School
District, MO.
MD................................ City of Baltimore.... MGT of America, Inc. Disparity........... 2000
MD................................ City of Baltimore.... NERA................ Disparity........... 2007
MD................................ State of Maryland.... NERA................ Disparity........... 2006
MD................................ State of Maryland.... NERA................ Disparity........... 2011
MA................................ City of Boston....... Mason Tillman Disparity........... 2003
Associates, Ltd..
MA................................ Division of Capital NERA................ Disparity........... 2006
Asset Management.
MA................................ Massachusetts Housing NERA................ Disparity........... 2006
Finance Agency.
MN................................ City of Minneapolis.. NERA................ Disparity........... 2010
MN................................ City of St. Paul and MGT of America, Inc. Disparity........... 2008
the St. Paul Housing
Authority.
MN................................ Metropolitan Airports MGT of America, Inc. Disparity........... 2009
Commission.
MN................................ Metropolitan Council. MGT of America, Inc. Disparity........... 2009
MN................................ Minnesota Department MGT of America, Inc. Disparity........... 2009
of Administration.
MN................................ Minnesota Department NERA................ Availability........ 2005
of Transportation.
MN................................ Minnesota Department MGT of America, Inc. Disparity........... 2009
of Transportation.
MO................................ Bi-State Development NERA................ Disparity........... 2005
Agency (St. Louis
Metro).
MO................................ City of St. Louis, MGT of America, Inc. Disparity........... 2001
The St. Louis
Housing Authority,
The Metropolitan St.
Louis Sewer District.
MO................................ Missouri Department NERA................ Disparity........... 2012
of Transportation.
MT................................ Montana Department of D. Wilson Consulting Disparity........... 2009
Transportation. Group, LLC.
NV................................ Nevada Department of BBC Research & Disparity........... 2007
Transportation. Consulting.
NY................................ State of New York.... NERA................ Disparity........... 2010
NC................................ City of Charlotte.... MGT of America, Inc. Disparity........... 2011
NC................................ City of Durham and Mason Tillman Disparity........... 2000
Durham County. Associates, Ltd..
NC................................ Durham County........ Griffin & Strong.... Disparity........... 2007
NC................................ North Carolina MGT of America, Inc. Disparity........... 2004
Department of
Transportation.
NC................................ North Carolina Euquant............. Disparity........... 2009
Department of
Transportation.
OH................................ City of Cincinnati... Griffin & Strong.... Disparity........... 2002
OH................................ City of Dayton....... MGT of America, Inc. Disparity........... 2008
OH................................ Northeast Ohio NERA................ Disparity........... 2010
Regional Sewer
District.
OK................................ City of Tulsa........ MGT of America, Inc. Disparity........... 2010
OK................................ Oklahoma Department BBC Research & Disparity........... 2010
of Transportation. Consulting.
OR................................ City of Portland..... BBC Research & Disparity........... 2011
Consulting.
OR................................ Oregon Department of MGT of America, Inc. Disparity........... 2007
Transportation.
OR................................ Port of Portland..... MGT of America, Inc. Disparity........... 2009
OR................................ Portland Development BBC Research & Disparity........... 2011
Commission. Consulting.
PA................................ City of Philadelphia. Econsult Corporation Disparity........... 2007
PA................................ City of Philadelphia. Econsult Corporation Disparity........... 2008
PA................................ City of Philadelphia. Econsult Corporation Disparity........... 2009
PA................................ City of Philadelphia. Econsult Corporation Disparity........... 2010
PA................................ City of Philadelphia. Econsult Corporation Disparity........... 2011
PA................................ City of Philadelphia. Econsult Corporation Disparity........... 2012
SC................................ City of Columbia..... MGT of America, Inc. Disparity........... 2006
TN................................ City of Memphis...... Griffin & Strong.... Disparity........... 2010
TN................................ Consolidated Griffin & Strong.... Disparity........... 2004
Government of
Nashville and
Davidson County.
TN................................ Memphis International NERA................ Disparity........... 2008
Airport.
TN................................ Nashville Griffin & Strong.... Disparity........... 2007
International
Airport.
TX................................ City of Austin....... NERA................ Disparity........... 2008
TX................................ City of Fort Worth; Mason Tillman Disparity........... 2010
City of Arlington; Associates, Ltd..
DFW Airport; Fort
Worth Independent
School District;
Fort Worth
Transportation
Authority; North
Texas Tollway
Authority [North
Central Texas
Council of
Governments].
TX................................ City of Houston...... NERA................ Disparity........... 2012
TX................................ City of San Antonio, MGT of America, Inc. Disparity........... 2009
Alamo Regional
Mobility Authority,
Brooks Development
Authority, CPS
Energy, Edwards
Aquifer Authority,
Port Authority of
San Antonio, San
Antonio Housing
Authority, San
Antonio Water
System, University
Health System.
TX................................ Dallas Area Rapid Mason Tillman Disparity........... 2003
Transit Authority Associates, Ltd..
(DART).
TX................................ State of Texas....... Mason Tillman Disparity........... 2007
Associates, Ltd..
TX................................ State of Texas....... MGT of America, Inc. Disparity........... 2010
UT................................ Salt Lake City NERA................ Disparity........... 2009
International
Airport.
VA................................ Commonwealth of MGT of America, Inc. Disparity........... 2004
Virginia.
VA................................ Commonwealth of MGT of America, Inc. Disparity........... 2010
Virginia.
VA................................ Virginia DOT......... MGT of America, Inc. Disparity........... 2004
WA................................ Washington Department NERA................ Availability........ 2005
of Transportation.
WI................................ City of Milwaukee.... Mason Tillman Disparity........... 2007
Associates, Ltd..
WI................................ City of Milwaukee.... D. Wilson Consulting Disparity........... 2010
Group, LLC.
----------------------------------------------------------------------------------------------------------------
Table 2. M/WBE Utilization, Availability, and Disparity: Selected Studies Performed in the U.S. Between 2000-2012
--------------------------------------------------------------------------------------------------------------------------------------------------------
State Subdivision U-CON A-CON D-CON U-CRS A-CRS D-CRS Years Page
----------------------------------------------------------------------------------------------------------------------------------------------- Spec.
---------
(1) (2) (3) (4) (5) (6) (7) (8) (9) (11)
--------------------------------------------------------------------------------------------------------------------------------------------------------
AK........................................... Department of Transportation and 10.52 14.26 73.73 2002- 4-9,
Public Facilities. 2006 4-11,
5-10,
5-13
--------------------------------------------------------------------------------------------------------------------------------------------------------
AZ........................................... Arizona Department of 7.03 15.61 45.03 5.39 27.07 19.90 2002- 4-47
Transportation. 2007
--------------------------------------------------------------------------------------------------------------------------------------------------------
AZ........................................... City of Phoenix................. 11.37 21.48 52.94 2000- 4-29,
2004 4-33
--------------------------------------------------------------------------------------------------------------------------------------------------------
AZ........................................... City of Tucson.................. 24.55 5.76 426.21 2002- 4-9,
2006 4-10,
5-10,
5-19
--------------------------------------------------------------------------------------------------------------------------------------------------------
AZ........................................... Pima County..................... 19.51 9.43 206.83 19.25 25.10 76.71 2002- 4-9,
2006 4-10,
5-13,
5-16,
5-28,
5-32
--------------------------------------------------------------------------------------------------------------------------------------------------------
CA........................................... Bay Area Rapid Transit (BART)... 19.34 34.42 56.20 2002- 4-8,
2007 5-5,
7-20
--------------------------------------------------------------------------------------------------------------------------------------------------------
CA........................................... California Department of 14.34 17.00 84.36 18.90 25.50 74.11 2002- Figs.
Transportation (federal funds). 2006 E-26, 29
--------------------------------------------------------------------------------------------------------------------------------------------------------
CA........................................... California Department of 11.41 18.70 61.00 12.04 28.20 42.68 2002- Figs.
Transportation (state funds). 2006 E-69, 70
--------------------------------------------------------------------------------------------------------------------------------------------------------
CA........................................... Los Angeles County Metropolitan 15.01 13.70 109.54 14.44 29.65 48.69 2003- E-42,
Transportation Authority 2007 E-20,
(federal funds). E-21
--------------------------------------------------------------------------------------------------------------------------------------------------------
CA........................................... Los Angeles County Metropolitan 12.20 20.80 58.65 17.81 28.80 61.84 2003- E-13,
Transportation Authority (local 2007 E-22
funds).
--------------------------------------------------------------------------------------------------------------------------------------------------------
CA........................................... Metrolink--Southern California 10.71 16.00 66.97 62.54 24.58 254.40 2003- E-42,
Regional Rail Authority 2007 E-20,
(federal funds). E-21
--------------------------------------------------------------------------------------------------------------------------------------------------------
CA........................................... Metrolink--Southern California 8.60 30.00 28.65 24.73 40.40 61.22 2003- E-13,
Regional Rail Authority (local 2007 E-22
funds).
--------------------------------------------------------------------------------------------------------------------------------------------------------
CA........................................... Orange County Transportation 36.77 26.70 137.70 13.42 23.77 56.47 2003- E-42,
Authority (federal funds). 2007 E-20,
E-21
--------------------------------------------------------------------------------------------------------------------------------------------------------
CA........................................... Orange County Transportation 52.24 30.00 174.13 24.97 31.90 78.27 2003- E-13,
Authority (local funds). 2007 E-22
--------------------------------------------------------------------------------------------------------------------------------------------------------
CA........................................... San Diego Association of 8.49 23.60 35.97 27.59 23.54 117.22 2003- E-42,
Governments (federal funds). 2007 E-20,
E-21
--------------------------------------------------------------------------------------------------------------------------------------------------------
CA........................................... San Diego Association of 0.45 22.50 1.99 18.20 27.70 65.69 2003- E-13,
Governments (local funds). 2007 E-22
--------------------------------------------------------------------------------------------------------------------------------------------------------
CA........................................... San Diego Metropolitan Transit 27.66 33.20 83.30 19.75 26.56 74.37 2003- E-42,
System (federal funds). 2007 E-20,
E-21
--------------------------------------------------------------------------------------------------------------------------------------------------------
CA........................................... San Diego Metropolitan Transit 26.75 36.90 72.49 0.00 32.90 0.00 2003- E-13,
System (local funds). 2007 E-22
--------------------------------------------------------------------------------------------------------------------------------------------------------
CA........................................... San Mateo County Transit 5.56 21.40 26.00 2002 26, 104
District.
--------------------------------------------------------------------------------------------------------------------------------------------------------
CA........................................... Santa Clara Valley 17.10 21.40 79.88 2001- 28, 104,
Transportation Authority. 2006 112
--------------------------------------------------------------------------------------------------------------------------------------------------------
CO........................................... City and County of Denver, 12.86 21.92 58.67 25.41 14.97 169.74 2000- 190
Denver International Airport. 2005
--------------------------------------------------------------------------------------------------------------------------------------------------------
CO........................................... Colorado Department of 10.56 20.21 52.25 4.69 24.07 19.48 1996- 3-20
Transportation. 2000
--------------------------------------------------------------------------------------------------------------------------------------------------------
CO........................................... Colorado Department of 16.58 23.17 71.58 21.21 41.37 51.28 2002- 4-5,
Transportation. 2007 4-6,
4-7,
5-8,
5-10,
6-6,
6-7
--------------------------------------------------------------------------------------------------------------------------------------------------------
CT........................................... Metropolitan District Commission 30.68 19.66 156.07 8.35 18.70 44.64 2005- V-112,
2008 V-114,
V-116,
V-117,
V-119,
V-121,
V-123,
V-125
--------------------------------------------------------------------------------------------------------------------------------------------------------
DC........................................... Washington Suburban Sanitary 29.57 68.38 43.24 31.49 61.12 51.52 2003- 1-15,
Commission. 2009 1-17,
2-5,
2-7,
4-21,
4-23,
4-36,
4-38
--------------------------------------------------------------------------------------------------------------------------------------------------------
FL........................................... Broward County.................. 35.70 40.57 87.99 16.04 44.95 35.68 1991- 4-18,
1999 4-21,
4-28,
4-31,
4-33,
4-37
--------------------------------------------------------------------------------------------------------------------------------------------------------
FL........................................... Broward County.................. 28.62 24.10 118.76 26.86 25.87 103.83 2005- 284
2009
--------------------------------------------------------------------------------------------------------------------------------------------------------
FL........................................... City of Tallahassee............. 28.50 34.03 83.74 1996- 4-13,
2000 4-17,
4-19
--------------------------------------------------------------------------------------------------------------------------------------------------------
FL........................................... Leon County..................... 19.56 11.92 164.04 2004- 4-10,
2008 4-12,
4-13
--------------------------------------------------------------------------------------------------------------------------------------------------------
FL........................................... School District of Hillsborough 30.49 37.58 81.12 24.69 42.99 57.45 2001- 2-5,
County. 2004 2-7,
3-4,
3-6,
5-21,
5-23,
5-32,
5-34
--------------------------------------------------------------------------------------------------------------------------------------------------------
GA........................................... City of Atlanta................. 34.02 57.63 59.04 35.03 56.30 62.21 2001- Vol. I,
2005 19, 21,
22, 30,
46, 59,
62
--------------------------------------------------------------------------------------------------------------------------------------------------------
GA........................................... City of Atlanta (Airport, local 59.17 57.63 102.66 2001- Vol. I,
dollars). 2005 19, 70,
73, 80
--------------------------------------------------------------------------------------------------------------------------------------------------------
GA........................................... City of Atlanta (Airport, 26.30 57.63 45.63 2001- Vol. I,
federal dollars). 2005 19, 83,
86
--------------------------------------------------------------------------------------------------------------------------------------------------------
GA........................................... City of Atlanta (Watershed 23.72 57.63 41.16 2001- Vol. I,
Management). 2005 19, 21,
22, 88,
91, 95
--------------------------------------------------------------------------------------------------------------------------------------------------------
GA........................................... Consolidated Government of 5.91 32.37 18.26 28.65 44.93 63.77 2003- 225
Augusta-Richmond County. 2007
--------------------------------------------------------------------------------------------------------------------------------------------------------
GA........................................... Georgia Department of 8.46 11.03 76.67 1999- 111,
Transportation. 2004 119,
123, 130
--------------------------------------------------------------------------------------------------------------------------------------------------------
GA........................................... Georgia Department of 13.23 21.50 61.52 9.31 24.40 38.17 2009- K-6,
Transportation (federal 2011 K-9
dollars).
--------------------------------------------------------------------------------------------------------------------------------------------------------
GA........................................... Georgia Department of 4.81 25.50 18.87 12.26 26.50 46.27 2009- K-7,
Transportation (state dollars). 2011 K-10
--------------------------------------------------------------------------------------------------------------------------------------------------------
HI........................................... Hawai'i Department of 32.17 54.78 58.70 62.01 51.79 119.73 2003- 331
Transportation. 2008
--------------------------------------------------------------------------------------------------------------------------------------------------------
ID........................................... Idaho Transportation Department. 14.36 16.90 84.95 6.79 12.90 52.63 2002- Figs.
2006 E-11, 20
--------------------------------------------------------------------------------------------------------------------------------------------------------
IL........................................... Illinois Department of 11.00 27.33 40.25 21.22 29.82 71.18 2006- 4-10,
Transportation. 2008 4-11,
5-3,
5-4,
7-18,
7-19,
7-21,
7-22
--------------------------------------------------------------------------------------------------------------------------------------------------------
IL........................................... Illinois State Toll Highway 11.43 19.56 58.44 23.58 19.03 123.91 2000- 49, 50,
Authority. 2005 61, 63
--------------------------------------------------------------------------------------------------------------------------------------------------------
IL........................................... Illinois State Toll Highway 11.38 39.39 28.89 16.42 41.02 40.04 2006- 4-8,
Authority. 2009 4-10,
5-4,
5-6,
7-15,
7-17,
7-20,
7-22
--------------------------------------------------------------------------------------------------------------------------------------------------------
IN........................................... State of Indiana (INDOT and 10.03 10.90 92.03 2006- O-2
INDOA). 2009
--------------------------------------------------------------------------------------------------------------------------------------------------------
IN........................................... State of Indiana (Higher Educ.). 10.69 15.10 70.79 2006- M-2
2009
--------------------------------------------------------------------------------------------------------------------------------------------------------
KS;.......................................... City of Kansas City, KS......... 18.34 25.31 72.44 15.34 36.21 42.37 2002- 3-5,
MO 2004 3-7,
4-4,
4-6,
6-21,
6-23,
6-30,
6-32
--------------------------------------------------------------------------------------------------------------------------------------------------------
KS;.......................................... Kansas City School District, MO. 34.20 25.60 133.58 2002- 3-5,
MO 2004 4-4,
6-21,
6-28
--------------------------------------------------------------------------------------------------------------------------------------------------------
KS........................................... Kansas Department of 10.31 13.75 75.01 2000- 2-10,
Transportation. 2001 2-12,
3-2,
3-3
--------------------------------------------------------------------------------------------------------------------------------------------------------
MD........................................... City of Baltimore............... 23.02 36.63 62.84 30.14 21.60 139.51 1990- 4-20,
1998 4-26,
4-29,
4-31,
4-33,
4-34
--------------------------------------------------------------------------------------------------------------------------------------------------------
MD........................................... City of Baltimore............... 25.85 22.88 112.98 31.88 27.32 116.69 2000- 217
2005
--------------------------------------------------------------------------------------------------------------------------------------------------------
MD........................................... State of Maryland............... 15.81 24.00 65.88 24.52 28.46 86.16 2000- 206
2004
--------------------------------------------------------------------------------------------------------------------------------------------------------
MD........................................... State of Maryland............... 23.45 30.26 77.51 22.31 41.34 53.97 2005- 328
2009
--------------------------------------------------------------------------------------------------------------------------------------------------------
MA........................................... City of Boston.................. 23.76 24.23 98.08 10.26 47.02 21.83 1999- 1-5,
2001 1-7,
2-4,
2-6,
4-22,
4-24,
4-29,
4-31
--------------------------------------------------------------------------------------------------------------------------------------------------------
MA........................................... Division of Capital Asset 19.44 10.39 187.10 33.79 17.86 189.19 1999- 199
Management. 2004
--------------------------------------------------------------------------------------------------------------------------------------------------------
MA........................................... Massachusetts Housing Finance 25.80 10.86 237.57 2000- 203
Agency. 2004
--------------------------------------------------------------------------------------------------------------------------------------------------------
MN........................................... City of Minneapolis............. 7.57 19.54 38.73 13.65 19.08 71.51 2003- 234
2007
--------------------------------------------------------------------------------------------------------------------------------------------------------
MN........................................... City of St. Paul................ 15.23 15.05 101.17 2002- 4-21,
2006 4-22,
4-28,
4-29
--------------------------------------------------------------------------------------------------------------------------------------------------------
MN........................................... St. Paul Housing Authority...... 6.33 10.43 60.67 2002- 6-6,
2006 6-12,
6-18
--------------------------------------------------------------------------------------------------------------------------------------------------------
MN........................................... Metropolitan Airports Commission 2.05 11.28 18.21 2004- 3-8,
2007 3-10,
3-12,
3-13
--------------------------------------------------------------------------------------------------------------------------------------------------------
MN........................................... Metropolitan Council............ 0.16 3.63 4.41 2003- 3-8,
2007 3-10,
3-13
--------------------------------------------------------------------------------------------------------------------------------------------------------
MN........................................... Minnesota Department of 3.42 2.74 124.97 2002- 3-8,
Administration. 2007 3-10,
3-14
--------------------------------------------------------------------------------------------------------------------------------------------------------
MN........................................... Minnesota Department of 5.55 15.18 36.56 2000- 69,
Transportation (federal funds). 2004 72
--------------------------------------------------------------------------------------------------------------------------------------------------------
MN........................................... Minnesota Department of 2.92 15.18 19.24 2000- 69,
Transportation (state funds). 2004 75
--------------------------------------------------------------------------------------------------------------------------------------------------------
MN........................................... Minnesota Department of 2.40 3.52 68.06 2002- 3-7,
Transportation. 2007 3-9,
3-12
--------------------------------------------------------------------------------------------------------------------------------------------------------
MO........................................... Bi-State Development Agency (St. 21.16 20.14 105.06 18.98 15.29 124.13 1997- 167
Louis Metro). 2003
--------------------------------------------------------------------------------------------------------------------------------------------------------
MO........................................... City of St. Louis............... 19.06 15.89 119.97 17.44 27.46 63.52 1995- Ex. pp.
1999 2, 4, 7,
9, 11,
12
--------------------------------------------------------------------------------------------------------------------------------------------------------
MO........................................... The Metropolitan St. Louis Sewer 13.91 15.89 87.54 15.42 27.46 56.16 1995- Ex. pp.
District. 1999 84, 86,
89, 91,
93, 94
--------------------------------------------------------------------------------------------------------------------------------------------------------
MO........................................... Missouri Department of 13.35 20.37 65.56 13.05 21.52 60.66 2005- 220
Transportation (federal funds). 2009
--------------------------------------------------------------------------------------------------------------------------------------------------------
MO........................................... Missouri Department of 6.49 20.19 32.16 12.28 21.48 57.16 2005- 224
Transportation (state funds). 2009
--------------------------------------------------------------------------------------------------------------------------------------------------------
MT........................................... Montana Department of 11.32 2.01 563.36 11.68 16.09 72.58 2000- 4-6,
Transportation. 2006 4-8,
5-18,
5-29,
5-53,
5-64
--------------------------------------------------------------------------------------------------------------------------------------------------------
NV........................................... Nevada Department of 8.70 15.60 55.79 3.03 7.80 38.89 2000- Figs.
Transportation (federal funds). 2006 E-11, 20
--------------------------------------------------------------------------------------------------------------------------------------------------------
NV........................................... Nevada Department of 8.34 12.90 64.65 3.05 10.80 28.26 2000- Figs.
Transportation (state funds). 2006 E-38, 47
--------------------------------------------------------------------------------------------------------------------------------------------------------
NY........................................... State of New York............... 12.39 22.74 54.48 19.43 24.53 79.21 2004- 292
2008
--------------------------------------------------------------------------------------------------------------------------------------------------------
NC........................................... City of Charlotte............... 19.28 35.74 53.95 13.66 18.55 73.66 2005- 3-11,
2010 3-13,
3-15,
3-16,
3-19,
3-20,
3-23
--------------------------------------------------------------------------------------------------------------------------------------------------------
NC........................................... City of Durham and Durham County 12.79 27.38 46.72 1996- 3-4,
1999 3-6,
5-9,
5-11
--------------------------------------------------------------------------------------------------------------------------------------------------------
NC........................................... Durham County................... 6.24 72.85 8.57 20.23 27.30 74.13 2001- 76, 78,
2005 82, 85,
94, 118
--------------------------------------------------------------------------------------------------------------------------------------------------------
NC........................................... North Carolina Department of 13.41 12.70 105.59 1999- 4-16,
Transportation (divisionally- 2003 4-26,
let). 4-49,
4-72,
4-90
--------------------------------------------------------------------------------------------------------------------------------------------------------
NC........................................... North Carolina Department of 9.83 29.92 32.87 14.41 20.00 72.06 1999- 4-52,
Transportation (centrally-let, 2003 4-56,
state funds). 4-70,
4-76,
4-80,
4-90
--------------------------------------------------------------------------------------------------------------------------------------------------------
NC........................................... North Carolina Department of 11.43 29.92 38.22 4.86 20.00 24.30 1999- 4-62,
Transportation (centrally-let, 2003 4-66,
federal funds). 4-70,
4-84,
4-88,
4-90
--------------------------------------------------------------------------------------------------------------------------------------------------------
NC........................................... North Carolina Department of 8.65 24.98 34.62 2004- 89, 90,
Transportation. 2008 138
--------------------------------------------------------------------------------------------------------------------------------------------------------
OH........................................... City of Cincinnati.............. 16.41 18.33 89.51 12.20 22.48 54.28 1995- 44, 45,
2001 49, 50
--------------------------------------------------------------------------------------------------------------------------------------------------------
OH........................................... City of Dayton.................. 4.73 23.91 19.80 2001- 4-11,
2006 4-17,
4-19,
4-20,
4-24
--------------------------------------------------------------------------------------------------------------------------------------------------------
OH........................................... Northeast Ohio Regional Sewer 24.44 22.31 109.55 23.78 22.03 107.94 2004- 263
District. 2008
--------------------------------------------------------------------------------------------------------------------------------------------------------
OK........................................... City of Tulsa................... 4.72 20.77 22.73 24.70 22.51 109.71 2002- 4-8,
2008 4-13,
4-14,
4-15,
4-20,
4-22,
4-23
--------------------------------------------------------------------------------------------------------------------------------------------------------
OK........................................... Oklahoma Department of 19.47 12.40 156.99 3.96 19.10 20.73 2004- K-6,
Transportation (federal funds). 2009 K-9
--------------------------------------------------------------------------------------------------------------------------------------------------------
OK........................................... Oklahoma Department of 19.82 15.40 128.70 5.00 19.90 25.13 2004- K-7,
Transportation (state funds). 2009 K-10
--------------------------------------------------------------------------------------------------------------------------------------------------------
OR........................................... City of Portland................ 7.49 5.10 146.85 34.98 14.60 239.62 2004- L-5,
2009 M-2
--------------------------------------------------------------------------------------------------------------------------------------------------------
OR........................................... Oregon Department of 19.07 27.55 69.20 3.84 46.31 8.30 2000- 4-12,
Transportation. 2007 4-21,
4-25,
4-111,
4-120,
4-123,
4-124
--------------------------------------------------------------------------------------------------------------------------------------------------------
OR........................................... Port of Portland................ 18.59 15.16 122.66 9.94 27.97 35.53 2002- 4-11,
2007 4-13,
4-15,
4-19
--------------------------------------------------------------------------------------------------------------------------------------------------------
OR........................................... Portland Development Commission. 9.29 12.37 75.06 2004- L-2,
2009 L-5
--------------------------------------------------------------------------------------------------------------------------------------------------------
PA........................................... City of Philadelphia............ 12.90 10.80 119.44 2006 17, 21
--------------------------------------------------------------------------------------------------------------------------------------------------------
PA........................................... City of Philadelphia............ 13.80 10.80 127.78 2007 36, 51
--------------------------------------------------------------------------------------------------------------------------------------------------------
PA........................................... City of Philadelphia............ 12.70 10.80 117.59 2008 vi, 45
--------------------------------------------------------------------------------------------------------------------------------------------------------
PA........................................... City of Philadelphia............ 9.30 10.80 86.11 2009 viii, 41
--------------------------------------------------------------------------------------------------------------------------------------------------------
PA........................................... City of Philadelphia............ 17.40 14.90 116.78 2010 vi, vii
--------------------------------------------------------------------------------------------------------------------------------------------------------
PA........................................... City of Philadelphia............ 13.30 11.40 116.67 2011 v, vii
--------------------------------------------------------------------------------------------------------------------------------------------------------
SC........................................... City of Columbia................ 3.42 19.03 17.96 18.15 17.14 105.90 2002- 4-10,
2005 4-15,
4-16,
4-17,
4-24,
4-26
--------------------------------------------------------------------------------------------------------------------------------------------------------
TN........................................... City of Memphis................. 18.77 18.84 99.62 2002- 112,
2007 116, 129
--------------------------------------------------------------------------------------------------------------------------------------------------------
TN........................................... Consolidated Government of 0.37 6.25 5.90 0.04 2.39 1.63 1999- 57, 65,
Nashville and Davidson County 2003 66, 68,
(Metro Purchasing). 69
--------------------------------------------------------------------------------------------------------------------------------------------------------
TN........................................... Consolidated Government of 0.02 4.27 0.40 3.30 7.24 45.58 1999- 58, 98,
Nashville and Davidson County 2003 99, 100,
(Nashville Public Schools). 102
--------------------------------------------------------------------------------------------------------------------------------------------------------
TN........................................... Consolidated Government of 12.70 12.70 100.00 0.20 7.97 2.50 1999- 60, 76,
Nashville and Davidson County 2003 77, 79
(Metro Nashville Airport).
--------------------------------------------------------------------------------------------------------------------------------------------------------
TN........................................... Consolidated Government of 20.70 16.56 125.03 29.33 10.41 281.71 1999- 61, 85,
Nashville and Davidson County 2003 86, 88,
(Metro Development and Housing 89
Authority).
--------------------------------------------------------------------------------------------------------------------------------------------------------
TN........................................... Memphis International Airport... 18.69 27.99 66.77 13.88 34.32 40.44 1999- 229
2005
--------------------------------------------------------------------------------------------------------------------------------------------------------
TN........................................... Nashville International Airport. 9.81 9.68 101.37 7.53 8.87 84.84 2003- 36, 38,
2006 39, 40,
47, 49
--------------------------------------------------------------------------------------------------------------------------------------------------------
TX........................................... City of Austin.................. 29.83 27.54 108.32 39.39 31.79 123.91 2002- 206
2006
--------------------------------------------------------------------------------------------------------------------------------------------------------
TX........................................... City of Arlington............... 10.94 66.58 16.43 13.11 54.03 24.27 2002- 2-9,
2007 2-11,
3-5,
3-7,
3-9,
5-24,
5-26,
5-33,
5-35,
5-37
--------------------------------------------------------------------------------------------------------------------------------------------------------
TX........................................... City of Fort Worth.............. 38.41 60.28 63.72 60.81 54.05 112.51 2002- 2-9,
2007 2-11,
3-5,
3-7,
5-26,
5-28,
5-37,
5-39
--------------------------------------------------------------------------------------------------------------------------------------------------------
TX........................................... DFW Airport..................... 50.72 62.82 80.74 57.53 53.80 106.93 2002- 2-9,
2007 2-11,
3-5,
3-7,
5-26,
5-28,
5-37,
5-39
--------------------------------------------------------------------------------------------------------------------------------------------------------
TX........................................... Fort Worth Independent School 27.75 66.06 42.01 28.91 53.89 53.64 2002- 2-9,
District. 2007 2-11,
3-4,
3-6,
5-26,
5-28,
5-37,
5-39
--------------------------------------------------------------------------------------------------------------------------------------------------------
TX........................................... North Texas Tollway Authority... 18.60 58.34 31.88 14.75 53.56 27.54 2003- 2-9,
2007 2-11,
3-4,
3-6,
5-26,
5-28,
5-37,
5-39
--------------------------------------------------------------------------------------------------------------------------------------------------------
TX........................................... City of Houston................. 29.87 34.74 85.97 2005- 191
2010
--------------------------------------------------------------------------------------------------------------------------------------------------------
TX........................................... City of San Antonio............. 35.19 28.14 125.09 2004- 3-9,
2007 3-15,
3-16,
3-17
--------------------------------------------------------------------------------------------------------------------------------------------------------
TX........................................... Dallas Area Rapid Transit 31.44 68.38 45.98 1996- 3-5,
Authority (DART). 2001 4-5,
4-7,
6-22,
6-29,
6-31
--------------------------------------------------------------------------------------------------------------------------------------------------------
TX........................................... State of Texas.................. 13.71 51.57 26.58 18.27 55.74 32.79 2002- 3-8,
2005 3-10,
4-6,
4-12,
6-21,
6-23,
6-37,
6-39
--------------------------------------------------------------------------------------------------------------------------------------------------------
TX........................................... State of Texas (TxDOT).......... 7.07 10.14 69.67 2006- 4-10,
2008 4-19,
5-11
--------------------------------------------------------------------------------------------------------------------------------------------------------
TX........................................... State of Texas (State Agencies). 24.04 22.10 108.78 2006- 4-10,
2008 4-20,
4-21,
5-11
--------------------------------------------------------------------------------------------------------------------------------------------------------
TX........................................... State of Texas (Universities)... 21.66 22.10 98.01 2006- 4-10,
2008 4-20,
4-21,
5-11
--------------------------------------------------------------------------------------------------------------------------------------------------------
TX........................................... State of Texas (Medical 21.95 22.10 99.29 2006- 4-10,
Institutions). 2008 4-20,
4-21,
5-11
--------------------------------------------------------------------------------------------------------------------------------------------------------
UT........................................... Salt Lake City International 5.32 17.03 31.24 0.79 18.25 4.33 2001- 258
Airport. 2006
--------------------------------------------------------------------------------------------------------------------------------------------------------
VA........................................... Commonwealth of Virginia........ 3.39 15.55 21.78 2006- 4-10,
2009 4-12,
4-20,
4-26
--------------------------------------------------------------------------------------------------------------------------------------------------------
VA........................................... Commonwealth of Virginia........ 1.35 14.66 9.19 1998- 4-16,
2002 4-23,
4-27,
4-32
--------------------------------------------------------------------------------------------------------------------------------------------------------
VA........................................... Virginia DOT (federal funds).... 6.59 10.26 64.21 9.53 15.89 59.99 1998- 11, 15,
2002 18, 22,
26, 29
--------------------------------------------------------------------------------------------------------------------------------------------------------
VA........................................... Virginia DOT (state funds)...... 8.52 10.26 82.99 5.41 15.89 34.08 1998- 34, 38,
2002 41, 45,
49, 52
--------------------------------------------------------------------------------------------------------------------------------------------------------
WA........................................... Washington Department of 14.32 19.59 73.10 10.44 14.88 70.16 1999- 63, 66,
Transportation (federal funds). 2003 72
--------------------------------------------------------------------------------------------------------------------------------------------------------
WA........................................... Washington Department of 2.97 19.59 15.16 10.66 14.88 71.64 1999- 63, 69,
Transportation (state funds). 2003 75
--------------------------------------------------------------------------------------------------------------------------------------------------------
WI........................................... City of Milwaukee............... 18.94 40.91 46.29 2005 5-11,
6-5,
6-26
--------------------------------------------------------------------------------------------------------------------------------------------------------
WI........................................... City of Milwaukee............... 31.21 13.77 226.74 2005- 4-7,
2008 4-9,
5-2,
5-7
--------------------------------------------------------------------------------------------------------------------------------------------------------
Note: Disparity indexes of 80 or lower are highlighted in boldface type. Disparity indexes above 80 but lower than 100 are highlighted in boldface
italic type.
C. There is Strong Evidence of Disparities Between Utilization and
Availability in Aggregate U.S. Business Enterprise Activity
A key rationale for the advent of public sector policies such as
the USDOT DBE Program was the Federal Government's desire to prevent
its own passive participation in private sector discrimination in
business enterprise activity.\23\ Therefore, it is important to examine
the best available evidence regarding how minorities and women fare in
the economy as a whole with respect to business enterprise activity. In
order to do this, I present evidence from the U.S. Census Bureau's past
and present data collection efforts dedicated to M/WBEs.
---------------------------------------------------------------------------
\23\ City of Richmond v. J. A. Croson Company, 488 U.S. 469, at 492
(``Thus, if the city could show that it had essentially become a
'passive participant' in a system of racial exclusion practiced by
elements of the local construction industry, we think it clear that the
city could take affirmative steps to dismantle such a system.'').
---------------------------------------------------------------------------
The Survey of Business Owners and Self-Employed Persons (SBO)
collected data on the number, sales, employment, and payrolls of
businesses owned by minorities, women, and non-minority males. This
survey was conducted every 5 years from 1972 to 2012 as part of the
Economic Census program. Data from the 2012 SBO, the most recent
available, were released in December 2015. In mid-2018, the Census
Bureau announced that the SBO would be discontinued and only partially
replaced with a new survey called the Annual Business Survey (ABS).\24\
Unfortunately, the ABS is restricted to firms with paid employees only,
as opposed to the SBO that also included nonemployer firms.\25\ Data
from the 2017 ABS, the most recent available, were released in May
2020.\26\ The SBO and ABS cover women and five groups of minorities:
(1) African Americans, (2) Hispanics, (3) Asians, (4) Native Hawaiians
and Other Pacific Islanders, and (5) American Indians and Alaskan
Natives. Comparative information for non-minority male-owned firms is
also included.\27\
---------------------------------------------------------------------------
\24\ U.S. Census Bureau (2018e).
\25\ U.S. Census Bureau (2018f). In 2012, according to the SBO,
there were about 5.1 million firms with paid employees and more than 22
million nonemployer firms.
\26\ U.S. Census Bureau (2020c).
\27\ In the American Community Survey Public Use Microdata Samples
(ACS PUMS), discussed below, the unit of analysis is the business
owner, or self-employed person. In the SBO and ABS data, the unit of
analysis is the business itself rather than the business owner.
Furthermore, unlike most other business statistics, including the other
components of the Economic Census, the unit of analysis in the SBO and
ABS is the firm, rather than the establishment.
---------------------------------------------------------------------------
The SBO and ABS contain a wealth of information on the character of
minority and female business enterprise in the U.S. as a whole as well
as in individual states and sub-state divisions.\28\ In the remainder
of this section, I present national evidence from the 2012 SBO and the
2017 ABS for the economy as whole, as well as for the construction and
architecture/engineering industries that are the main beneficiaries of
Federal surface and aviation transportation funding.
---------------------------------------------------------------------------
\28\ Appendix A, below, provides state-level data from the 2017
ABS. Appendices B, C and D, below, provide state-level data from the
2012, 2007 and 2002 SBO.
---------------------------------------------------------------------------
1. Results from the 2012 Survey of Business Owners
a. Economy-Wide Results
I begin with the 2012 SBO--the most recent and last data from this
important survey. Table 3 contains data for the U.S. as a whole and the
economy-wide (i.e. all industries combined). Panel A in this table
summarizes the SBO results for each race and/or sex grouping. For
example, Panel A shows a total of 27.18 million firms in the U.S. in
2012 (column 1) with overall sales and receipts of $11.964 trillion
(column 2). Of these 27.18 million firms, 5.14 million had one or more
employees (column 3) and these 5.14 million firms had overall sales and
receipts of $10.965 trillion (column 4). Column (5) shows a total of
56.059 million employees on the payroll of these 5.14 million firms and
a total annual payroll expense of $2.096 trillion (column 6).
The remaining rows in Panel A provide comparable statistics for
nonminority male-owned, women-owned, and minority-owned firms. For
example, Table 3 shows that there were 2.6 million African American-
owned firms counted in the SBO, and that these 2.6 million firms
registered $150.2 billion in sales and receipts. It also shows that
109,137 of these African American-owned firms had one or more
employees, and that they employed a total of 975,052 workers with an
annual payroll total of $27.69 billion.
Panel B in Table 3 converts the figures in Panel A to percentage
distributions within each column. For example, Column (1) in Panel B of
Table 3 shows that African American-owned firms were 9.51 percent of
all firms in the U.S. and women-owned firms were 36.35 percent.
Additionally, 12.16 percent of firms were Hispanic-owned, 7.06 percent
were Asian-owned, 1.0 percent were American Indian- and Alaska Native-
owned, and 0.20 percent were Native Hawaiian- and Other Pacific
Islander-owned.
Column (2) in Panel B provides the same percentage distribution for
overall sales and receipts. Table 3, for example, shows that
nonminority males owned 45.18 percent of all firms and earned 73.45
percent of all sales and receipts. In contrast:
Although African Americans owned 9.51 percent of all
firms in the U.S. in 2012, they earned only 1.26 percent of all sales
and receipts.
Although Hispanics owned 12.16 percent of all firms, they
earned only 3.96 percent, of all sales and receipts.
Although Asians owned 7.06 percent of all firms, they
earned only 5.85 percent, of all sales and receipts.
Although American Indians and Alaska Natives owned 1.0
percent of all firms, they earned only 0.32 percent of all sales and
receipts.
Although Native Hawaiians and Other Pacific Islanders
owned 0.20 percent of all firms, they earned only 0.07 percent of all
sales and receipts.
Although women owned firms 36.35 percent of all firms,
they earned only 11.87 percent of all sales and receipts.
These disparities between the availability and utilization of
minority- and women-owned firms can be viewed directly from the
disparity indexes in Panel C of Table 3. For example, Panel C shows
that African American-owned firms in 2012 received just 13.2 percent of
what would be expected based on their availability in the market. Panel
C shows as well that women-owned firms received just 32.65 percent of
what would be expected based on their availability in the market. For
Hispanics, the figure was 32.55 percent. For Asians, the figure was
82.85 percent. For American Indians and Alaska Natives, the figure was
32.33 percent, and for Native Hawaiians and Other Pacific Islanders,
the figure was 33.76 percent. These disparities are all adverse, and
statistically significant. The disparities are all large as well, with
the exception of Asian-owned firms.
We can also compare sales and receipts per firm among all firms in
2012. In Table 3, for example, average per firm sales and receipts for
non-minority male-owned firms was $715.6 thousand. In contrast:
For African American-owned employer firms, average per
firm sales and receipts was $58.1 thousand. In other words, for every
dollar of sales and receipts earned by non-minority male-owned firms,
African American-owned firms received just 8 cents.
For Hispanic-owned firms, average per firm sales and
receipts was $143.3 thousand. In other words, for every dollar of sales
and receipts earned by non-minority male-owned firms, Hispanic-owned
firms received just 20 cents.
For Asian-owned firms, average per firm sales and
receipts was $364.7 thousand. In other words, for every dollar of sales
and receipts earned by non-minority male-owned firms, Asian-owned firms
received just 51 cents.
For American Indian- and Alaska Native-owned firms,
average per firm sales and receipts was $142.3 thousand. In other
words, for every dollar of sales and receipts earned by non-minority
male-owned firms, American Indian- and Alaska Native-owned firms
received just 20 cents.
For Native Hawaiian- and Other Pacific Islander-owned
firms, average per firm sales and receipts was $148.6 thousand. In
other words, for every dollar of sales and receipts earned by non-
minority male-owned firms, Native Hawaiian- and Other Pacific Islander-
owned firms received just 21 cents.
For women-owned firms, average per firm sales and
receipts was $143.7 thousand. In other words, for every dollar of sales
and receipts earned by non-minority male-owned firms, women-owned firms
received just 20 cents.
Turning to employer firms, we see from column (3) in Table 3, that
although nonminority male-owned firms were 57.11 percent of all
employer firms, they accounted for 74.98 percent of all employer firm
sales and receipts. In contrast:
Although African Americans owned 2.12 percent of all
employer firms in the U.S. in 2012, they earned only 0.94 percent of
all sales and receipts.
Although Hispanics firms 5.6 percent of all employer
firms, they earned only 3.47 percent of all sales and receipts.
Although Asians owned 9.37 percent of all employer firms,
they earned only 5.72 percent of all sales and receipts.
Although American Indians and Alaska Natives owned 0.51
percent of all employer firms, they earned only 0.29 percent of all
sales and receipts.
Although Native Hawaiians and Other Pacific Islanders
owned 0.09 percent of all employer firms, they earned only 0.06 percent
of all sales and receipts.
Although women owned 20.16 percent of all employer firms,
they earned only 10.86 percent of all sales and receipts.
The economy-wide employer firm disparity indexes for 2012 appear in
Panel C of Table 3. Panel C shows that African American-owned firms in
2012 received just 44.4 percent of what would be expected based on
their availability in the market. Women-owned firms received just 53.85
percent of what would be expected based on their availability in the
market. For Hispanics, the figure was 61.91 percent. For Asians, the
figure was 61.11 percent. For American Indians and Alaska Natives, the
figure was 56.64 percent, and for Native Hawaiians and Other Pacific
Islanders, the figure was 64.40 percent. These disparities are all
large, adverse, and statistically significant.
Considering sales and receipts among employer firms in 2012. Table
3 shows a figure of $2.8 million for non-minority male-owned employer
firms. In contrast:
For African American-owned employer firms, average per
firm sales and receipts was $947.9 thousand. In other words, for every
dollar of sales and receipts earned by non-minority male-owned firms,
African American-owned firms received just 34 cents.
For Hispanic-owned firms, average per firm sales and
receipts was $1.32 million. In other words, for every dollar of sales
and receipts earned by non-minority male-owned firms, Hispanic-owned
firms received just 47 cents.
For Asian-owned firms, average per firm sales and
receipts was $1.3 million. In other words, for every dollar of sales
and receipts earned by non-minority male-owned firms, Asian-owned firms
received just 47 cents.
For American Indian- and Alaska Native-owned firms,
average per firm sales and receipts was $1.21 million. In other words,
for every dollar of sales and receipts earned by non-minority male-
owned firms, American Indian- and Alaska Native-owned firms received
just 43 cents.
For Native Hawaiian- and Other Pacific Islander-owned
firms, average per firm sales and receipts was $1.37 million. In other
words, for every dollar of sales and receipts earned by non-minority
male-owned firms, Native Hawaiian- and Other Pacific Islander-owned
firms received just 49 cents.
For women-owned firms, average per firm sales and
receipts was $1.15 million. In other words, for every dollar of sales
and receipts earned by non-minority male-owned firms, women-owned firms
received just 41 cents.
The problem of minority- and women-owned firms earning less has
important consequences that ripple throughout the economy. Because
these firms make less, they have to pay their employees less. This
obviously compounds race and gender disparities to the extent that
minority- and women-owned firms hire proportionately more minority and
female employees. In addition, it reduces the wealth accruing to
minorities and women and thus hinders any would-be minority and women
entrepreneurs in their efforts to create and grow their own firms thus
reinforcing the negative consequences of social and economic
disadvantage. Table 3 shows that average payroll per employee at non-
minority male-owned employer firms in 2012 was $40,573. In contrast:
For African American-owned employers, average payroll per
employee was just $28,398. In other words, for every $1 in wages earned
by employees at non-minority male-owned firms, employees at African
American-owned firms earned only 70 cents.
For Hispanic-owned employers average payroll per employee
was just $30,416. In other words, for every $1 in wages earned by
employees at non-minority male-owned firms, employees at Hispanic-owned
firms earned only 75 cents.
For Asian-owned employers average payroll per employee
was just $30,942. In other words, for every $1 in wages earned by
employees at non-minority male-owned firms, employees at Asian-owned
firms earned only 76 cents.
For American Indian- and Alaska Native-owned employers
average payroll per employee was just $33,599. In other words, for
every $1 in wages earned by employees at non-minority male-owned firms,
employees at American Indian- and Alaska Native-owned firms earned just
83 cents.
For Native Hawaiian- and Other Pacific Islander-owned
employers, average payroll per employee was just $36,681. In other
words, for every $1 in wages earned by employees at non-minority male-
owned firms, employees at Native Hawaiian- and Other Pacific Islander-
owned firms earned just 90 cents.
For women-owned employers average payroll per employee
was just $31,278. In other words, for every $1 in wages earned by
employees at non-minority male-owned firms, employees at women-owned
firms earned only 77 cents.
Table 3. Disparity Ratios from the 2012 Survey of Business Owners, United States, All Industries
--------------------------------------------------------------------------------------------------------------------------------------------------------
Number of Sales and Employer Sales and Employees Payroll
Firms Receipts Firms Receipts ------------- ($000s)
------------- ($000s) ------------- ($000s) ---------------
----------------- ----------------- (5)
(1) (2) (3) (4) (6)
--------------------------------------------------------------------------------------------------------------------------------------------------------
Panel A. Levels....................................................................................................
--------------------------------------------------------------------------------------------------------------------------------------------------------
All Firms...................................................... 27,179,380 11,964,077,871 5,136,203 10,964,584,749 56,058,563 2,096,442,212
Non-minority male.............................................. 12,280,591 8,787,915,377 2,933,198 8,221,010,815 37,750,711 1,531,662,394
African American............................................... 2,584,403 150,203,163 109,137 103,451,510 975,052 27,689,957
Hispanic....................................................... 3,305,873 473,635,944 287,501 379,994,999 2,329,553 70,855,704
Asian.......................................................... 1,917,902 699,492,422 481,026 627,532,399 3,572,577 110,543,615
Native Hawaiian/Pac. Islander.................................. 54,749 8,136,445 4,706 6,469,957 39,001 1,430,591
Am. Indian & Alaska Native..................................... 272,919 38,838,125 26,179 31,654,165 208,178 6,994,509
Female......................................................... 9,878,397 1,419,834,295 1,035,655 1,190,586,438 8,431,614 263,720,252
--------------------------------------------------------------------------------------------------------------------------------------------------------
Panel B. Column Percentages...............................................................................................--------------------------------------------------------------------------------------------------------------------------------------------------------
All Firms...................................................... 100.00% 100.00% 100.00% 100.00% 100.00% 100.00%
Non-minority male.............................................. 45.18% 73.45% 57.11% 74.98% 67.34% 73.06%
African American............................................... 9.51% 1.26% 2.12% 0.94% 1.74% 1.32%
Hispanic....................................................... 12.16% 3.96% 5.60% 3.47% 4.16% 3.38%
Asian.......................................................... 7.06% 5.85% 9.37% 5.72% 6.37% 5.27%
Native Hawaiian/Pac. Islander.................................. 0.20% 0.07% 0.09% 0.06% 0.07% 0.07%
Am. Indian & Alaska Native..................................... 1.00% 0.32% 0.51% 0.29% 0.37% 0.33%
Female......................................................... 36.35% 11.87% 20.16% 10.86% 15.04% 12.58%
--------------------------------------------------------------------------------------------------------------------------------------------------------
Panel C. Disparity Ratios (2) vs. (1) (4) vs. (3) (5) vs. (3) (6) vs. (3)
--------------------------------------------------------------------------------------------------------------------------------------------------------
Non-minority male...........................................................
African American............................................................
Hispanic....................................................................
Asian.......................................................................
Native Hawaiian/Pac. Islander...............................................
Am. Indian & Alaska Native..................................................
Female......................................................................
--------------------------------------------------------------------------------------------------------------------------------------------------------
Source: Author's calculations using 2012 SBO. Notes: (1) Figures are rounded. Rounding was performed subsequent to any mathematical calculations; (2)
Excludes publicly owned, foreign-owned, and not-for-profit firms; (3) Totals for ``All Firms'' includes firms that were equally nonminority-minority
owned; (4) Statistically significant disparity indexes are italicized; (5) ``n/a'' indicates that data were not disclosed due to confidentiality or
other publication restrictions.
b. Results for the Construction Sector
Table 4 shows comparable 2012 SBO data for the construction sector
in the U.S. as a whole.
Column (2) in Panel B of Table 4 shows that nonminority males owned
62.85 percent of all firms and earned 78.02 percent of all sales and
receipts. In contrast:
Although African Americans owned 4.67 percent of all
firms in the U.S. in 2012, they earned only 0.93 percent of all sales
and receipts.
Although Hispanics owned 16.24 percent of all firms, they
earned only 4.65 percent, of all sales and receipts.
Although Asians owned 2.63 percent of all firms, they
earned only 1.28 percent, of all sales and receipts.
Although American Indians and Alaska Natives owned 1.23
percent of all firms, they earned only 0.62 percent of all sales and
receipts.
Although Native Hawaiians and Other Pacific Islanders
owned 0.19 percent of all firms, they earned only 0.13 percent of all
sales and receipts.
Although women owned firms 9.08 percent of all firms,
they earned only 7.75 percent of all sales and receipts.
The associated 2012 disparity indexes for firms in the construction
sector can be viewed directly in Panel C of Table 4. Panel C shows that
African American-owned firms in 2012 received just 19.88 percent of
what would be expected based on their availability in the market. Panel
C shows as well that women-owned firms received 85.37 percent of what
would be expected based on their availability in the market. For
Hispanics, the figure was 28.64 percent. For Asians, the figure was
48.74 percent. For American Indians and Alaska Natives, the figure was
50.19 percent, and for Native Hawaiians and Other Pacific Islanders,
the figure was 66.26 percent. These disparities are all adverse, and
statistically significant. The disparities are all large as well, with
the exception of women-owned firms.
We can also compare sales and receipts per firm among all firms in
construction in 2012. In Table 4 average per firm sales and receipts
for non-minority male-owned firms was $508.9 thousand. In contrast:
For African American-owned employer firms, average per
firm sales and receipts was $81.5 thousand. In other words, for every
dollar of sales and receipts earned by non-minority male-owned firms,
African American-owned firms received just 16 cents.
For Hispanic-owned firms, average per firm sales and
receipts was $117.4 thousand. In other words, for every dollar of sales
and receipts earned by non-minority male-owned firms, Hispanic-owned
firms received just 23 cents.
For Asian-owned firms, average per firm sales and
receipts was $199.8 thousand. In other words, for every dollar of sales
and receipts earned by non-minority male-owned firms, Asian-owned firms
received just 39 cents.
For American Indian- and Alaska Native-owned firms,
average per firm sales and receipts was $205.8 thousand. In other
words, for every dollar of sales and receipts earned by non-minority
male-owned firms, American Indian- and Alaska Native-owned firms
received just 40 cents.
For Native Hawaiian- and Other Pacific Islander-owned
firms, average per firm sales and receipts was $271.7 thousand. In
other words, for every dollar of sales and receipts earned by non-
minority male-owned firms, Native Hawaiian- and Other Pacific Islander-
owned firms received just 53 cents.
For women-owned firms, average per firm sales and
receipts was $350 thousand. In other words, for every dollar of sales
and receipts earned by non-minority male-owned firms, women-owned firms
received just 69 cents.
Turning to employer firms, we see from column (3) in Table 4, that
although nonminority male-owned firms were 69.87 percent of all
employer firms, they accounted for 79.09 percent of all employer firm
sales and receipts. In contrast:
Although African Americans owned 1.19 percent of all
employer firms in the U.S. in 2017, they earned only 0.77 percent of
all sales and receipts.
Although Hispanics firms 6.07 percent of all employer
firms, they earned only 3.59 percent of all sales and receipts.
Although Asians owned 1.66 percent of all employer firms,
they earned only 1.19 percent of all sales and receipts.
Although American Indians and Alaska Natives owned 0.76
percent of all employer firms, they earned only 0.57 percent of all
sales and receipts.
Native Hawaiians and Other Pacific Islanders owned 0.11
percent of all employer firms, and they earned 0.12 percent of all
sales and receipts, essentially at parity.
Although women owned 8.55 percent of all employer firms,
they earned only 7.86 percent of all sales and receipts.
The employer firm disparity indexes for construction in 42012
appear in Panel C of Table 4. Panel C shows that African American-owned
firms in 2012 received just 64.51 percent of what would be expected
based on their availability in the market. Women-owned firms received
just 91.88 percent of what would be expected based on their
availability in the market. For Hispanics, the figure was 59.14
percent. For Asians, the figure was 71.94 percent. For American Indians
and Alaska Natives, the figure was 74.52 percent, and for Native
Hawaiians and Other Pacific Islanders, the figure was 101.89 percent.
The disparities for African Americans, Hispanics, Asians and American
Indians and Alaska Natives are all large, adverse, and statistically
significant. The disparity for women is adverse, and statistically
significant. The disparity for Native Hawaiians and Other Pacific
Islanders is not statistically significant.
Considering sales and receipts among employer firms in 2012, Table
4 shows a figure of $1.92 million for non-minority male-owned employer
firms. In contrast:
For African American-owned employer firms, average per
firm sales and receipts was $1.1 million. In other words, for every
dollar of sales and receipts earned by non-minority male-owned firms,
African American-owned firms received just 57 cents.
For Hispanic-owned firms, average per firm sales and
receipts was $1.01 million. In other words, for every dollar of sales
and receipts earned by non-minority male-owned firms, Hispanic-owned
firms received just 52 cents.
For Asian-owned firms, average per firm sales and
receipts was $1.22 million. In other words, for every dollar of sales
and receipts earned by non-minority male-owned firms, Asian-owned firms
received just 64 cents.
For American Indian- and Alaska Native-owned firms,
average per firm sales and receipts was $1.27 million. In other words,
for every dollar of sales and receipts earned by non-minority male-
owned firms, American Indian- and Alaska Native-owned firms received
just 66 cents.
For Native Hawaiian- and Other Pacific Islander-owned
firms, average per firm sales and receipts was $1.73 million. In other
words, for every dollar of sales and receipts earned by non-minority
male-owned firms, Native Hawaiian- and Other Pacific Islander-owned
firms received just 90 cents.
For women-owned firms, average per firm sales and
receipts was $1.56 million. In other words, for every dollar of sales
and receipts earned by non-minority male-owned firms, women-owned firms
received just 81 cents.
As discussed above, these disparities extend to the employees of
minority- and women-owned firms as well and thus cause a ripple effect
that further damages women and minorities. Table 4 shows that average
payroll per employee at non-minority male-owned employer firms in 2012
was $48,736. In contrast:
For African American-owned employers, average payroll per
employee was just $42,824. In other words, for every $1 in wages earned
by employees at non-minority male-owned firms, employees at African
American-owned firms earned only 88 cents.
For Hispanic-owned employers average payroll per employee
was just $37,977. In other words, for every $1 in wages earned by
employees at non-minority male-owned firms, employees at Hispanic-owned
firms earned only 78 cents.
For Asian-owned employers average payroll per employee
was just $45,450. In other words, for every $1 in wages earned by
employees at non-minority male-owned firms, employees at Asian-owned
firms earned only 93 cents.
For American Indian- and Alaska Native-owned employers
average payroll per employee was just $44,763. In other words, for
every $1 in wages earned by employees at non-minority male-owned firms,
employees at American Indian- and Alaska Native-owned firms earned just
92 cents.
For Native Hawaiian- and Other Pacific Islander-owned
firms, on the other hand, was $49,870. In other words, for every $1 in
wages earned by employees at non-minority male-owned firms, employees
at Native Hawaiian- and Other Pacific Islander-owned firms earned
$1.02--essentially at par with non-minority male-owned firms.
For women-owned employers average payroll per employee
was just $46,509. In other words, for every $1 in wages earned by
employees at non-minority male-owned firms, employees at women-owned
firms earned only 95 cents.
Table 4. Disparity Ratios from the 2012 Survey of Business Owners, United States, Construction
--------------------------------------------------------------------------------------------------------------------------------------------------------
Number of Sales and Employer Sales and Employees Payroll
Firms Receipts Firms Receipts ------------- ($000s)
------------- ($000s) ------------- ($000s) ---------------
----------------- ----------------- (5)
(1) (2) (3) (4) (6)
--------------------------------------------------------------------------------------------------------------------------------------------------------
Panel A. Levels....................................................................................................--------------------------------------------------------------------------------------------------------------------------------------------------------
All Firms...................................................... 2,928,015 1,200,413,658 637,296 1,083,093,941 4,764,280 225,039,336
Non-minority male.............................................. 1,840,218 936,510,929 445,288 856,603,507 3,581,982 174,571,576
African American............................................... 136,729 11,141,919 7,594 8,325,857 39,883 1,707,968
Hispanic....................................................... 475,472 55,830,007 38,704 38,900,840 222,161 8,437,113
Asian.......................................................... 76,883 15,362,433 10,567 12,919,296 54,404 2,472,635
Native Hawaiian/Pac. Islander.................................. 5,551 1,507,949 724 1,253,656 4,803 239,527
Am. Indian & Alaska Native..................................... 35,969 7,401,462 4,836 6,124,399 29,700 1,329,464
Female......................................................... 265,733 93,002,152 54,511 85,116,364 435,718 20,264,904
--------------------------------------------------------------------------------------------------------------------------------------------------------
Panel B. Column Percentages...............................................................................................--------------------------------------------------------------------------------------------------------------------------------------------------------
All Firms...................................................... 100.00% 100.00% 100.00% 100.00% 100.00% 100.00%
Non-minority male.............................................. 62.85% 78.02% 69.87% 79.09% 75.18% 77.57%
African American............................................... 4.67% 0.93% 1.19% 0.77% 0.84% 0.76%
Hispanic....................................................... 16.24% 4.65% 6.07% 3.59% 4.66% 3.75%
Asian.......................................................... 2.63% 1.28% 1.66% 1.19% 1.14% 1.10%
Native Hawaiian/Pac. Islander.................................. 0.19% 0.13% 0.11% 0.12% 0.10% 0.11%
Am. Indian & Alaska Native..................................... 1.23% 0.62% 0.76% 0.57% 0.62% 0.59%
Female......................................................... 9.08% 7.75% 8.55% 7.86% 9.15% 9.01%
--------------------------------------------------------------------------------------------------------------------------------------------------------
Panel C. Disparity Ratios....................................................................................................--------------------------------------------------------------------------------------------------------------------------------------------------------
Non-minority male...........................................................
African American............................................................
Hispanic....................................................................
Asian.......................................................................
Native Hawaiian/Pac. Islander............................................... 101.89 88.74 93.69
Am. Indian & Alaska Native..................................................
Female......................................................................
--------------------------------------------------------------------------------------------------------------------------------------------------------
Source and Notes: See Table 6.
c. Results for the Professional, Scientific, and Technical
Services Sector
Table 8 shows comparable 2012 SBO data for the professional,
scientific, and technical services sector in the U.S. as a whole.
Column (2) in Panel B of Table 8 shows that nonminority males owned
47.45 percent of all firms and earned 66.95 percent of all sales and
receipts. In contrast:
Although African Americans owned 5.35 percent of all
firms in the U.S. in 2012, they earned only 1.79 percent of all sales
and receipts.
Although Hispanics owned 7.19 percent of all firms, they
earned only 3.82 percent of all sales and receipts.
Although Asians owned 7.16 percent of all firms, they
earned 7.72 percent of all sales and receipts.
Although American Indians and Alaska Natives owned 0.8
percent of all firms, they earned only 0.36 percent of all sales and
receipts.
Although Native Hawaiians and Other Pacific Islanders
owned 0.16 percent of all firms, they earned only 0.11 percent of all
sales and receipts.
Although women-owned firms were 34.5 percent of all
firms, they earned only 15.81 percent of all sales and receipts.
The associated 2012 disparity indexes for firms in the construction
sector can be viewed directly in Panel C of Table 8. Panel C shows that
African American-owned firms in 2012 received just 33.42 percent of
what would be expected based on their availability in the market. Panel
C shows as well that women-owned firms received 45.82 percent of what
would be expected based on their availability in the market. For
Hispanics, the figure was 53.17 percent. For Asians, the figure was
107.9 percent. For American Indians and Alaska Natives, the figure was
45.12 percent, and for Native Hawaiians and Other Pacific Islanders,
the figure was 65.32 percent. With the exception of Asians, these
disparities are all large, adverse, and statistically significant.
We can also compare sales and receipts per firm among all firms in
professional services in 2012. In Table 8, average per firm sales and
receipts for non-minority male-owned firms was $319.9 thousand. In
contrast:
For African American-owned employer firms, average per
firm sales and receipts was $75.8 thousand. In other words, for every
dollar of sales and receipts earned by non-minority male-owned firms,
African American-owned firms received just 24 cents.
For Hispanic-owned firms, average per firm sales and
receipts was $120.6 thousand. In other words, for every dollar of sales
and receipts earned by non-minority male-owned firms, Hispanic-owned
firms received just 38 cents.
For Asian-owned firms, average per firm sales and
receipts was $244.78 thousand. In other words, for every dollar of
sales and receipts earned by non-minority male-owned firms, Asian-owned
firms received just 76 cents.
For American Indian- and Alaska Native-owned firms,
average per firm sales and receipts was $102.3 thousand. In other
words, for every dollar of sales and receipts earned by non-minority
male-owned firms, American Indian- and Alaska Native-owned firms
received just 32 cents.
For Native Hawaiian- and Other Pacific Islander-owned
firms, average per firm sales and receipts was $148.1 thousand. In
other words, for every dollar of sales and receipts earned by non-
minority male-owned firms, Native Hawaiian- and Other Pacific Islander-
owned firms received just 46 cents.
For women-owned firms, average per firm sales and
receipts was $103.9 thousand. In other words, for every dollar of sales
and receipts earned by non-minority male-owned firms, women-owned firms
received just 32 cents.
Turning to employer firms, we see from column (3) in Table 8, that
although nonminority male-owned firms were 59 percent of all employer
firms, they accounted for 69.13 percent of all employer firm sales and
receipts. In contrast:
Although African Americans owned 1.85 percent of all
employer firms in the U.S. in 2012, they earned only 1.52 percent of
all sales and receipts.
Although Hispanics firms 3.95 percent of all employer
firms, they earned only 3.45 percent of all sales and receipts.
Asians owned 6.79 percent of all employer firms, and they
earned 7.9 percent of all sales and receipts.
Although American Indians and Alaska Natives owned 0.48
percent of all employer firms, they earned only 0.3 percent of all
sales and receipts.
Native Hawaiians and Other Pacific Islanders owned 0.08
percent of all employer firms, and they earned 0.1 percent of all sales
and receipts.
Although women owned 22.1 percent of all employer firms,
they earned only 13.81 percent of all sales and receipts.
The employer firm disparity indexes for construction in 42012
appear in Panel C of Table 8. Panel C shows that African American-owned
firms in 2012 received just 82.26 percent of what would be expected
based on their availability in the market. Women-owned firms received
just 62.47 percent of what would be expected based on their
availability in the market. For Hispanics, the figure was 87.16
percent. For Asians, the figure was 116.31 percent. For American
Indians and Alaska Natives, the figure was 60.94 percent, and for
Native Hawaiians and Other Pacific Islanders, the figure was 116.31
percent. The disparities for women and American Indians and Alaska
Natives are large, adverse, and statistically significant. The
disparities for African Americans and Hispanics are adverse and
statistically significant. The disparities for Asians is not adverse
and is statistically significant. The disparity for Native Hawaiians
and Other Pacific Islanders is not statistically significant.
Considering sales and receipts among employer firms in 2012, Table
8 shows a figure of $1.16 million for non-minority male-owned employer
firms. In contrast:
For African American-owned employer firms, average per
firm sales and receipts was $816.2 thousand. In other words, for every
dollar of sales and receipts earned by non-minority male-owned firms,
African American-owned firms received just 70 cents.
For Hispanic-owned firms, average per firm sales and
receipts was $864.9 thousand. In other words, for every dollar of sales
and receipts earned by non-minority male-owned firms, Hispanic-owned
firms received just 74 cents.
For Asian-owned firms, average per firm sales and
receipts was $1.15 million. In other words, for every dollar of sales
and receipts earned by non-minority male-owned firms, Asian-owned firms
received just 99 cents, just slightly below parity.
For American Indian- and Alaska Native-owned firms,
average per firm sales and receipts was $604.7 thousand. In other
words, for every dollar of sales and receipts earned by non-minority
male-owned firms, American Indian- and Alaska Native-owned firms
received just 52 cents.
For Native Hawaiian- and Other Pacific Islander-owned
firms, average per firm sales and receipts was $1.27 million. In other
words, for every dollar of sales and receipts earned by non-minority
male-owned firms, Native Hawaiian- and Other Pacific Islander-owned
firms received just $1.10, slightly above parity.
For women-owned firms, average per firm sales and
receipts was $619.9 thousand. In other words, for every dollar of sales
and receipts earned by non-minority male-owned firms, women-owned firms
received just 53 cents.
Considering the employees of minority- and women-owned employer
firms in the professional services sector, Table 8 shows that average
payroll per employee at non-minority male-owned employer firms in 2012
was $63,240. In contrast:
For African American-owned employers, average payroll per
employee was just $54,911. In other words, for every $1 in wages earned
by employees at non-minority male-owned firms, employees at African
American-owned firms earned only 88 cents.
For Hispanic-owned employers average payroll per employee
was just $51,813. In other words, for every $1 in wages earned by
employees at non-minority male-owned firms, employees at Hispanic-owned
firms earned only 78 cents.
For Asian-owned employers average payroll per employee
was just $66,788. In other words, for every $1 in wages earned by
employees at non-minority male-owned firms, employees at Asian-owned
firms earned only 93 cents.
For American Indian- and Alaska Native-owned employers
average payroll per employee was just $44,013. In other words, for
every $1 in wages earned by employees at non-minority male-owned firms,
employees at American Indian- and Alaska Native-owned firms earned just
92 cents.
For women-owned employers average payroll per employee
was just $49,128. In other words, for every $1 in wages earned by
employees at non-minority male-owned firms, employees at women-owned
firms earned only 95 cents.
Payroll per employee for Native Hawaiian- and Other Pacific
Islander-owned firms, on the other hand, was $69,386. In other words,
for every $1 in wages earned by employees at non-minority male-owned
firms, employees at Native Hawaiian- and Other Pacific Islander-owned
firms earned $1.10--slightly above par with non-minority male-owned
firms.
Table 5. Disparity Ratios from the 2012 Survey of Business Owners, United States, Professional Services
--------------------------------------------------------------------------------------------------------------------------------------------------------
Number of Sales and Employer Sales and Employees Payroll
Firms Receipts Firms Receipts ------------- ($000s)
------------- ($000s) ------------- ($000s) ---------------
----------------- ----------------- (5)
(1) (2) (3) (4) (6)
--------------------------------------------------------------------------------------------------------------------------------------------------------
Panel A. Levels....................................................................................................--------------------------------------------------------------------------------------------------------------------------------------------------------
All Firms...................................................... 3,868,657 877,237,881 748,444 742,626,210 4,652,991 277,172,802
Non-minority male.............................................. 1,835,748 587,306,112 441,573 513,381,557 3,050,082 192,887,690
African American............................................... 206,942 15,682,967 13,822 11,281,769 81,170 4,457,109
Hispanic....................................................... 278,066 33,525,181 29,582 25,584,292 170,953 8,857,606
Asian.......................................................... 276,960 67,766,453 50,834 58,666,210 345,376 23,067,037
Native Hawaiian/Pac. Islander.................................. 6,292 931,973 600 764,525 3,680 255,342
Am. Indian & Alaska Native..................................... 30,966 3,168,244 3,627 2,193,127 17,882 787,037
Female......................................................... 1,334,561 138,669,937 165,437 102,552,393 774,717 38,060,358
--------------------------------------------------------------------------------------------------------------------------------------------------------
Panel B. Column Percentages...............................................................................................--------------------------------------------------------------------------------------------------------------------------------------------------------
All Firms...................................................... 100.00% 100.00% 100.00% 100.00% 100.00% 100.00%
Non-minority male.............................................. 47.45% 66.95% 59.00% 69.13% 65.55% 69.59%
African American............................................... 5.35% 1.79% 1.85% 1.52% 1.74% 1.61%
Hispanic....................................................... 7.19% 3.82% 3.95% 3.45% 3.67% 3.20%
Asian.......................................................... 7.16% 7.72% 6.79% 7.90% 7.42% 8.32%
Native Hawaiian/Pac. Islander.................................. 0.16% 0.11% 0.08% 0.10% 0.08% 0.09%
Am. Indian & Alaska Native..................................... 0.80% 0.36% 0.48% 0.30% 0.38% 0.28%
Female......................................................... 34.50% 15.81% 22.10% 13.81% 16.65% 13.73%
--------------------------------------------------------------------------------------------------------------------------------------------------------
Panel C. Disparity Ratios....................................................................................................--------------------------------------------------------------------------------------------------------------------------------------------------------
Non-minority male...........................................................
African American............................................................
Hispanic....................................................................
Asian.......................................................................
Native Hawaiian/Pac. Islander............................................... 128.42 98.66 114.92
Am. Indian & Alaska Native..................................................
Female......................................................................
--------------------------------------------------------------------------------------------------------------------------------------------------------
Source and Notes: See Table 6.
2. Results from the 2017 Annual Survey of Businesses
a. Economy-Wide Results
Turning now to the 2017 ABS, Table 6, below, presents results for
all industries combined (i.e. economy-wide) and for the United States
as a whole. Panel A summarizes the ABS results for each race and/or sex
group. For example, Panel A shows a total of 5.47 million employer
firms in the U.S. in 2017 (column 1) with overall sales and receipts of
$12.689 trillion (column 2). These 5.47 million firms had a total of
62.99 million employees (column 3) and a total annual payroll expense
of $2.618 trillion (column 4).
The remaining rows in Panel A provide comparable statistics for
non-minority male-owned, women-owned, and minority-owned firms. For
example, Table 6 shows that there were 124,004 African American-owned
employer firms counted in 2017, and that these 124,004 firms registered
$127.851 billion in sales and receipts. It also shows that these
African American-owned firms employed a total of 1.21 million workers
with an annual payroll total of $36.105 billion.
Panel B in Table 6 converts the figures in Panel A to percentage
distributions within each column. For example, Column (1) in Panel B of
Table 6 shows that African Americans owned just 2.27 percent of all
employer firms in the U.S. and women owned just 15.62 percent.
Additionally, 5.88 percent of employer firms were Hispanic-owned, 10.15
percent were Asian-owned, 0.45 percent were American Indian- and Alaska
Native-owned, and 0.13 percent were Native Hawaiian- and Other Pacific
Islander-owned.
Column (2) in Panel B provides the same percentage distribution for
overall sales and receipts for employer firms. Table 6, for example,
shows that non-minority males owned 52.08 percent of all employer firms
and earned 70.71 percent of all sales and receipts. In contrast:
Although African Americans owned 2.27 percent of all
employer firms in the U.S. in 2017, they earned only 1.01 percent of
all sales and receipts.
Although Hispanics firms 5.88 percent of all employer
firms, they earned only 3.33 percent of all sales and receipts.
Although Asians owned 10.15 percent of all employer
firms, they earned only 6.42 percent of all sales and receipts.
Although American Indians and Alaska Natives owned 0.45
percent of all employer firms, they earned only 0.3 percent of all
sales and receipts.
Although Native Hawaiians and Other Pacific Islanders
owned 0.13 percent of all employer firms, they earned only 0.07 percent
of all sales and receipts.
Although women owned 15.62 percent of all employer firms,
they earned only 9.6 percent of all sales and receipts.
These disparities between the availability and utilization of
minority- and women-owned firms can be viewed directly from the
disparity indexes in Panel C of Table 6. For example, Panel C shows
that African American-owned employer firms in 2017 received just 44.48
percent of what would be expected based on their availability in the
market.\29\ Panel C shows as well that women-owned firms received just
61.44 percent of what would be expected based on their availability in
the market. For Hispanics, the figure was 56.6 percent. For Asians, the
figure was 63.27 percent. For American Indians and Alaska Natives, the
figure was 66.89 percent, and for Native Hawaiians and Other Pacific
Islanders, the figure was 53.09 percent. These disparities are all
large, adverse, and statistically significant.
---------------------------------------------------------------------------
\29\ The disparity index is derived by dividing the share of sales
and receipts from Panel B column (2) by the share of firms in Panel B
column (1) and multiplying the result by 100.
---------------------------------------------------------------------------
Another way to look at these disparities is by comparing sales and
receipts per firm. In Table 6, for example, average per firm sales and
receipts for non-minority male-owned employer firms was $3.15
million.\30\ In contrast:
---------------------------------------------------------------------------
\30\ Per firm sales and receipts is derived by dividing the sales
and receipts amount in Panel A column (2) by the number of employer
firms in Panel A column (1).
---------------------------------------------------------------------------
For African American-owned employer firms, average per
firm sales and receipts was $1.03 million. In other words, for every
dollar of sales and receipts earned by non-minority male-owned employer
firms, African American-owned employer firms received just 33 cents.
For Hispanic-owned employer firms, average per firm sales
and receipts was $1.31 million. In other words, for every dollar of
sales and receipts earned by non-minority male-owned employer firms,
Hispanic-owned employer firms received just 42 cents.
For Asian-owned employer firms, average per firm sales
and receipts was $1.47 million. In other words, for every dollar of
sales and receipts earned by non-minority male-owned employer firms,
Asian-owned employer firms received just 47 cents.
For American Indian- and Alaska Native-owned employer
firms, average per firm sales and receipts was $1.55 million. In other
words, for every dollar of sales and receipts earned by non-minority
male-owned employer firms, American Indian- and Alaska Native-owned
employer firms received just 49 cents.
For Native Hawaiian- and Other Pacific Islander-owned
employer firms, average per firm sales and receipts was $1.23 million.
In other words, for every dollar of sales and receipts earned by non-
minority male-owned employer firms, Native Hawaiian- and Other Pacific
Islander-owned employer firms received just 39 cents.
For women-owned employer firms, average per firm sales
and receipts was $1.42 million. In other words, for every dollar of
sales and receipts earned by non-minority male-owned employer firms,
women-owned employer firms received just 45 cents.
As discussed above, these severe disparities in firm earnings have
a direct negative and compounding effect on the employees of minority-
and women-owned firms. Table 6, for example, shows that average payroll
per employee at non-minority male-owned employer firms in 2017 was
$45,555.\31\ In contrast:
---------------------------------------------------------------------------
\31\ Average payroll per employee is derived by dividing total
payroll in Panel A column (4) by total number of employees in Panel A
column (3).
---------------------------------------------------------------------------
For African American-owned employers, average payroll per
employee was just $29,882. In other words, for every $1 in wages earned
by employees at non-minority male-owned firms, employees at African
American-owned firms earned just 66 cents.
For Hispanic-owned employers average payroll per employee
was just $31,674. In other words, for every $1 in wages earned by
employees at non-minority male-owned firms, employees at Hispanic-owned
firms earned just 70 cents.
For Asian-owned employers average payroll per employee
was just $34,137. In other words, for every $1 in wages earned by
employees at non-minority male-owned firms, employees at Asian-owned
firms earned just 75 cents.
For American Indian- and Alaska Native-owned employers
average payroll per employee was just $39,756. In other words, for
every $1 in wages earned by employees at non-minority male-owned firms,
employees at American Indian- and Alaska Native-owned firms earned just
87 cents.
For Native Hawaiian- and Other Pacific Islander-owned
employers it was just $35,386. In other words, for every $1 in wages
earned by employees at non-minority male-owned firms, employees at
Native Hawaiian- and Other Pacific Islander-owned firms earned just 78
cents.
For women-owned employers average payroll per employee
was just $36,926. In other words, for every $1 in wages earned by
employees at non-minority male-owned firms, employees at women-owned
firms earned just 81 cents.
Table 6. Disparity Ratios from the 2017 Annual Business Survey, United States, All Industries
----------------------------------------------------------------------------------------------------------------
Employer Sales and Employees Payroll
Firms Receipts ------------- ($000s)
------------- ($000s) ---------------
----------------- (3)
(1) (2) (4)
----------------------------------------------------------------------------------------------------------------
Panel A. Levels.................................................................................................
----------------------------------------------------------------------------------------------------------------
All Firms............................................ 5,474,721 12,689,937,307 62,990,475 2,618,191,164
Non-minority male.................................... 2,851,098 8,972,454,223 38,973,541 1,775,434,267
African American..................................... 124,004 127,850,815 1,208,270 36,105,467
Hispanic............................................. 322,076 422,573,589 2,872,550 90,985,526
Asian................................................ 555,638 814,806,324 4,649,688 158,725,110
Native Hawaiian/Pac. Islander........................ 6,847 8,426,209 55,413 1,960,819
Am. Indian & Alaska Native........................... 24,503 37,992,217 221,193 8,793,842
Female............................................... 855,136 1,217,743,211 7,863,653 290,375,358
----------------------------------------------------------------------------------------------------------------
Panel B. Column Percentages.....................................................................................
----------------------------------------------------------------------------------------------------------------
All Firms............................................ 100.00% 100.00% 100.00% 100.00%
Non-minority male.................................... 52.08% 70.71% 61.87% 67.81%
African American..................................... 2.27% 1.01% 1.92% 1.38%
Hispanic............................................. 5.88% 3.33% 4.56% 3.48%
Asian................................................ 10.15% 6.42% 7.38% 6.06%
Native Hawaiian/Pac. Islander........................ 0.13% 0.07% 0.09% 0.07%
Am. Indian & Alaska Native........................... 0.45% 0.30% 0.35% 0.34%
Female............................................... 15.62% 9.60% 12.48% 11.09%
----------------------------------------------------------------------------------------------------------------
Panel C. Disparity Ratios (2) vs. (1) (3) vs. (1) (4) vs. (1)
----------------------------------------------------------------------------------------------------------------
Non-minority male.................................................
African American..................................................
Hispanic..........................................................
Asian.............................................................
Native Hawaiian/Pac. Islander.....................................
Am. Indian & Alaska Native........................................
Female............................................................
----------------------------------------------------------------------------------------------------------------
Source: Authors calculations from the 2017 ABS. Notes: (1) Figures are rounded. Rounding was performed
subsequent to any mathematical calculations; (2) Excludes publicly owned, foreign-owned, and not-for-profit
firms; (3) Totals for ``All Firms'' includes firms that were equally nonminority-minority owned; (4)
Statistically significant; disparity indexes are italicized; (5) ``n/a'' indicates that data were not
disclosed due to confidentiality or other publication restrictions.
b. Results for the Construction Sector
Table 7 provides comparable 2017 information for the construction
sector, which, along with architecture, engineering, and related
professional services, is a major recipient of Federal surface and
aviation transportation funding.
Although non-minority males owned 68.52 percent of all employer
firms in the construction sector, they earned 77.92 percent of all
sales and receipts. In contrast:
Although African Americans owned 1.17 percent of all
employer firms in the U.S. in 2017, they earned only 0.72 percent of
all sales and receipts. This yields a disparity index of 61.05.
Although Hispanics owned 7.16 percent of all employer
firms in the U.S. in 2017, they earned only 4.1 percent of all sales
and receipts. This yields a disparity index of 57.26.
Although Asians owned 2.02 percent of all employer firms
in the U.S. in 2017, they earned only 1.37 percent of all sales and
receipts. This yields a disparity index of 67.73.
Although Native Hawaiians and Other Pacific Islanders
owned 0.16 percent of all employer firms in the U.S. in 2017, they
earned only 0.1 percent of all sales and receipts. This yields a
disparity index of 62.97.
Although American Indians and Alaska Natives owned 0.69
percent of all employer firms in the U.S. in 2017, they earned only
0.52 percent of all sales and receipts. This yields a disparity index
of 76.15.
As a group, women fared much better in construction in 2017
compared to other disadvantaged groups. Women owned 7.15 percent of all
employer firms in the U.S. in 2017, and they earned an equivalent share
of sales and receipts--7.26 percent, yielding no adverse disparity
index. But remember, this new ABS data does not include emerging firms
that have yet grown sufficiently large to hire employees.
When we consider per firm sales and receipts for employer firms in
2017, we see that non-minority male-owned firms averaged $2.51 million.
In contrast:
For African American-owned employer firms, average per
firm sales and receipts was 1.35 million. In other words, for every
dollar of sales and receipts earned by non-minority male-owned employer
firms, African American-owned employer firms received just 54 cents.
For Hispanic-owned employer firms, average per firm sales
and receipts was 1.26 million. In other words, for every dollar of
sales and receipts earned by non-minority male-owned employer firms,
Hispanic-owned employer firms received just 50 cents.
For Asian-owned employer firms, average per firm sales
and receipts was 1.49 million. In other words, for every dollar of
sales and receipts earned by non-minority male-owned employer firms,
Asian-owned employer firms received just 60 cents.
For American Indian- and Alaska Native-owned employer
firms, average per firm sales and receipts was 1.68 million. In other
words, for every dollar of sales and receipts earned by non-minority
male-owned employer firms, American Indian- and Alaska Native-owned
employer firms received just 67 cents.
For Native Hawaiian- and Other Pacific Islander-owned
employer firms, average per firm sales and receipts was 1.39 million.
In other words, for every dollar of sales and receipts earned by non-
minority male-owned employer firms, Native Hawaiian- and Other Pacific
Islander-owned employer firms received just 55 cents.
For women-owned employer firms, average per firm sales
and receipts was 2.24 million. In other words, for every dollar of
sales and receipts earned by non-minority male-owned employer firms,
women-owned employer firms received just 89 cents.
Considering the employees of these minority- and women-owned firms,
Table 7 shows that average payroll per employee at non-minority male-
owned employer firms the construction sector in 2017 was $54,984. In
contrast:
For African American-owned employers, average payroll per
employee was just $45,869. In other words, for every $1 in wages earned
by employees at non-minority male-owned firms, employees at African
American-owned firms earned just 83 cents.
For Hispanic-owned employers average payroll per employee
was just $41,881. In other words, for every $1 in wages earned by
employees at non-minority male-owned firms, employees at Hispanic-owned
firms earned just 76 cents.
For Asian-owned employers average payroll per employee
was just $50,307. In other words, for every $1 in wages earned by
employees at non-minority male-owned firms, employees at Asian-owned
firms earned 91 cents.
For American Indian- and Alaska Native-owned employers
average payroll per employee was just $51,723. In other words, for
every $1 in wages earned by employees at non-minority male-owned firms,
employees at American Indian- and Alaska Native-owned firms earned 94
cents.
For Native Hawaiian- and Other Pacific Islander-owned
employers it was just $46,120 male-owned firms, employees at Native
Hawaiian- and Other Pacific Islander-owned firms earned just 84 cents.
For women-owned employers average payroll per employee
was just $53,318. In other words, for every $1 in wages earned by
employees at non-minority male-owned firms, employees at women-owned
firms earned 97 cents.
Table 7. Disparity Ratios from the 2017 Annual Business Survey, United States, Construction
----------------------------------------------------------------------------------------------------------------
Employer Sales and Employees Payroll
Firms Receipts ------------- ($000s)
------------- ($000s) ---------------
----------------- (5)
(3) (4) (6)
----------------------------------------------------------------------------------------------------------------
Panel A. Levels.................................................................................................
----------------------------------------------------------------------------------------------------------------
All Firms............................................ 700,453 1,544,490,456 6,120,046 324,999,296
Non-minority male.................................... 479,971 1,203,446,334 4,504,618 247,682,903
African American..................................... 8,218 11,062,034 54,093 2,481,191
Hispanic............................................. 50,187 63,362,420 327,799 13,728,565
Asian................................................ 14,169 21,160,223 82,746 4,162,689
Native Hawaiian/Pac. Islander........................ 1,093 1,517,730 7,795 359,508
Am. Indian & Alaska Native........................... 4,821 8,095,145 35,355 1,828,684
Female............................................... 50,075 112,156,157 508,141 27,092,808
----------------------------------------------------------------------------------------------------------------
Panel B. Column Percentages.....................................................................................
----------------------------------------------------------------------------------------------------------------
All Firms............................................ 100.00% 100.00% 100.00% 100.00%
Non-minority male.................................... 68.52% 77.92% 73.60% 76.21%
African American..................................... 1.17% 0.72% 0.88% 0.76%
Hispanic............................................. 7.16% 4.10% 5.36% 4.22%
Asian................................................ 2.02% 1.37% 1.35% 1.28%
Native Hawaiian/Pac. Islander........................ 0.16% 0.10% 0.13% 0.11%
Am. Indian & Alaska Native........................... 0.69% 0.52% 0.58% 0.56%
Female............................................... 7.15% 7.26% 8.30% 8.34%
----------------------------------------------------------------------------------------------------------------
Panel C. Disparity Ratios (2) vs. (1) (3) vs. (1) (4) vs. (1)
----------------------------------------------------------------------------------------------------------------
Non-minority male.................................................
African American..................................................
Hispanic..........................................................
Asian.............................................................
Native Hawaiian/Pac. Islander.....................................
Am. Indian & Alaska Native........................................
Female............................................................ 101.58 116.14 116.61
----------------------------------------------------------------------------------------------------------------
Source and Notes: See Table 6.
c. Results for the Professional, Scientific, and Technical
Sector
Table 8 provides comparable 2017 information for the professional,
scientific, and technical sector (which includes architecture,
engineering, and related professional services). This sector, along
with construction, is a major recipient of Federal surface and aviation
transportation funding.
Although non-minority males owned 56.31 percent of all employer
firms in the construction sector, they earned 66.39 percent of all
sales and receipts. In contrast:
Although African Americans owned 2.06 percent of all
employer firms in the U.S. in 2017, they earned only 1.6 percent of all
sales and receipts. This yields a disparity index of 77.65.
Although Hispanics owned 4.32 percent of all employer
firms in the U.S. in 2017, they earned only 3.2 percent of all sales
and receipts. This yields a disparity index of 74.09.
Although Asians owned 7.67 percent of all employer firms
in the U.S. in 2017, they earned only 8.84 percent of all sales and
receipts. This yields a disparity index of 115.31.
Although Native Hawaiians and Other Pacific Islanders
owned 0.12 percent of all employer firms in the U.S. in 2017, they
earned only 0.1 percent of all sales and receipts. This yields a
disparity index of 84.87.
Although American Indians and Alaska Natives owned 0.52
percent of all employer firms in the U.S. in 2017, they earned only
0.52 percent of all sales and receipts. This yields a disparity index
of 99.76.
Although women owned 19.1 percent of all employer firms
in the U.S. in 2017, they earned only 12.4 percent of all sales and
receipts. This yields a disparity index of 64.91.
When we consider per firm sales and receipts for employer firms, we
see that non-minority male-owned firms averaged $1.37 million in 2017.
In contrast:
For African American-owned employer firms, average per
firm sales and receipts was $902 thousand. In other words, for every
dollar of sales and receipts earned by non-minority male-owned employer
firms, African American-owned employer firms received just 66 cents.
For Hispanic-owned employer firms, average per firm sales
and receipts was $861 thousand. In other words, for every dollar of
sales and receipts earned by non-minority male-owned employer firms,
Hispanic-owned employer firms received just 63 cents.
For Asian-owned employer firms, average per firm sales
and receipts was $1.34 million. In other words, for every dollar of
sales and receipts earned by non-minority male-owned employer firms,
Asian-owned employer firms received just 98 cents.
For Native Hawaiian- and Other Pacific Islander-owned
employer firms, average per firm sales and receipts was $986 thousand.
In other words, for every dollar of sales and receipts earned by non-
minority male-owned employer firms, Native Hawaiian- and Other Pacific
Islander-owned employer firms received just 72 cents.
For American Indian- and Alaska Native-owned employer
firms, average per firm sales and receipts was $1.16 million. In other
words, for every dollar of sales and receipts earned by non-minority
male-owned employer firms, American Indian- and Alaska Native-owned
employer firms received just 85 cents.
For women-owned employer firms, average per firm sales
and receipts was $754 thousand. In other words, for every dollar of
sales and receipts earned by non-minority male-owned employer firms,
women-owned employer firms received just 55 cents.
Considering the employees of these minority- and women-owned firms,
Table 8 shows that average payroll per employee at non-minority male-
owned employer firms the professional services sector in 2017 was
$70,546. In contrast:
For African American-owned employers, average payroll per
employee was just $59,033. In other words, for every $1 in wages earned
by employees at non-minority male-owned firms, employees at African
American-owned firms earned just 84 cents.
For Hispanic-owned employers average payroll per employee
was just $56,567. In other words, for every $1 in wages earned by
employees at non-minority male-owned firms, employees at Hispanic-owned
firms earned just 80 cents.
For Asian-owned employers average payroll per employee
was $75,179--somewhat higher than non-minority male-owned employers.
Thus, for every $1 in wages earned by employees at non-minority male-
owned firms, employees at Asian-owned firms earned $1.07 cents,
slightly better than parity.
For American Indian- and Alaska Native-owned employers
average payroll per employee was just $60,884. In other words, for
every $1 in wages earned by employees at non-minority male-owned firms,
employees at American Indian- and Alaska Native-owned firms earned 86
cents.
For Native Hawaiian- and Other Pacific Islander-owned
employers it was just $63,009 male-owned firms, employees at Native
Hawaiian- and Other Pacific Islander-owned firms earned just 89 cents.
For women-owned employers average payroll per employee
was just $55,606. In other words, for every $1 in wages earned by
employees at non-minority male-owned firms, employees at women-owned
firms earned 79 cents.
Table 8. Disparity Ratios from the 2017 Annual Business Survey, United States,PProfessional, Scientific, and
Technical Services
----------------------------------------------------------------------------------------------------------------
Employer Sales and Employees Payroll
Firms Receipts ------------- ($000s)
------------- ($000s) ---------------
----------------- (5)
(3) (4) (6)
----------------------------------------------------------------------------------------------------------------
Panel A. Levels.................................................................................................
----------------------------------------------------------------------------------------------------------------
All Firms............................................ 794,235 922,698,077 5,339,009 362,594,623
Non-minority male.................................... 447,254 612,610,502 3,281,827 231,520,629
African American..................................... 16,392 14,787,229 96,267 5,682,935
Hispanic............................................. 34,292 29,514,634 185,395 10,487,211
Asian................................................ 60,907 81,592,941 432,567 32,520,040
Native Hawaiian/Pac. Islander........................ 971 957,403 6,118 385,489
Am. Indian & Alaska Native........................... 4,142 4,800,227 29,953 1,823,661
Female............................................... 151,694 114,396,323 751,207 41,771,294
----------------------------------------------------------------------------------------------------------------
Panel B. Column Percentages.....................................................................................
----------------------------------------------------------------------------------------------------------------
All Firms............................................ 100.00% 100.00% 100.00% 100.00%
Non-minority male.................................... 56.31% 66.39% 61.47% 63.85%
African American..................................... 2.06% 1.60% 1.80% 1.57%
Hispanic............................................. 4.32% 3.20% 3.47% 2.89%
Asian................................................ 7.67% 8.84% 8.10% 8.97%
Native Hawaiian/Pac. Islander........................ 0.12% 0.10% 0.11% 0.11%
Am. Indian & Alaska Native........................... 0.52% 0.52% 0.56% 0.50%
Female............................................... 19.10% 12.40% 14.07% 11.52%
----------------------------------------------------------------------------------------------------------------
Panel C. Disparity Ratios (2) vs. (1) (3) vs. (1) (4) vs. (1)
----------------------------------------------------------------------------------------------------------------
Non-minority male.................................................
African American..................................................
Hispanic..........................................................
Asian.............................................................
Native Hawaiian/Pac. Islander..................................... 84.87 93.73 86.96
Am. Indian & Alaska Native........................................ 99.76 107.58 96.44
Female............................................................
----------------------------------------------------------------------------------------------------------------
Source and Notes: See Table 6.
3. State-Level Results from 2002-2017
The state-level disparities observed in the 2017 ABS are documented
below in Appendix A, Tables A.1 through A.18. Data from the 2012 SBO is
presented in Appendix B, Tables B.1 through B.18. Data from the 2007
SBO is presented in Appendix C, Tables C.1 through C.18. Data from the
2002 SBO is presented in Appendix D, Tables D.1 through D.18.
The most noticeable aspect of the statistics presented in Tables
A.1 through D.18 below is how many of the disparity indexes are large,
adverse, and statistically significant.\32\ This is true for African
Americans, Hispanics, Asians and Pacific Islanders, American Indians
and Alaska Natives, and non-minority women. It is true in the
construction sector, it is true in the professional services sector,
and it is true when considering all industries combined. It is true in
all 50 states and the District of Columbia. While there is certainly
variation by race, sex, industry, geography, and time, the similarities
vastly outweigh the differences. Table 9 provides a high-level summary
of the findings of disparity from the 2007 SBO in Tables A.1 through
A.18.
---------------------------------------------------------------------------
\32\ I have measured statistical significance here using the ``two
standard deviation'' or ``5%'' level of significance typically used in
disparate impact litigation in employment and related areas.
Table 9. Prevalence of Disparities in the 2017 Annual Business Survey and the 2012, 2007 & 2002 Survey of Business Owners
--------------------------------------------------------------------------------------------------------------------------------------------------------
Fraction of Fraction of
Disparity Disparity Fraction of
Number of Indexes Indexes Disparity
Year Industry Disparity Race/Sex Group Less than Less than Indexes that
Indexes in or Equal to or Equal to are
Table 80 100 Statistically
Significant
--------------------------------------------------------------------------------------------------------------------------------------------------------
2017.................................... All Industries............. 48 AfrAmer.................... 98% 100% 88%
2012.................................... All Industries............. 96 AfrAmer.................... 97% 98% 92%
2007.................................... All Industries............. 96 AfrAmer.................... 93% 97% 90%
2002.................................... All Industries............. 100 AfrAmer.................... 98% 100% 98%
rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr
2017.................................... Construction............... 39 AfrAmer.................... 77% 82% 46%
2012.................................... Construction............... 84 AfrAmer.................... 88% 93% 80%
2007.................................... Construction............... 84 AfrAmer.................... 85% 90% 82%
2002.................................... Construction............... 69 AfrAmer.................... 86% 88% 72%
rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr
2017.................................... Professional Services...... 41 AfrAmer.................... 73% 80% 49%
2012.................................... Professional Services...... 92 AfrAmer.................... 78% 90% 70%
2007.................................... Professional Services...... 92 AfrAmer.................... 76% 88% 73%
2002.................................... Professional Services...... 86 AfrAmer.................... 94% 98% 80%
rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr
2017.................................... All Industries............. 52 Hispanic................... 87% 94% 79%
2012.................................... All Industries............. 101 Hispanic................... 87% 94% 84%
2007.................................... All Industries............. 101 Hispanic................... 82% 90% 86%
2002.................................... All Industries............. 102 Hispanic................... 100% 100% 100%
rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr
2017.................................... Construction............... 49 Hispanic................... 86% 92% 61%
2012.................................... Construction............... 95 Hispanic................... 89% 96% 79%
2007.................................... Construction............... 95 Hispanic................... 87% 93% 78%
2002.................................... Construction............... 85 Hispanic................... 88% 91% 81%
rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr
2017.................................... Professional Services...... 48 Hispanic................... 42% 65% 29%
2012.................................... Professional Services...... 97 Hispanic................... 63% 79% 54%
2007.................................... Professional Services...... 97 Hispanic................... 65% 75% 57%
2002.................................... Professional Services...... 84 Hispanic................... 93% 94% 74%
rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr
2017.................................... All Industries............. 52 Asian...................... 98% 98% 96%
2012.................................... All Industries............. 104 Asian...................... 68% 89% 73%
2007.................................... All Industries............. 104 Asian...................... 75% 96% 80%
2002.................................... All Industries............. 102 Asian...................... 100% 100% 100%
rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr
2017.................................... Construction............... 40 Asian...................... 72% 75% 38%
2012.................................... Construction............... 84 Asian...................... 70% 75% 57%
2007.................................... Construction............... 84 Asian...................... 71% 77% 54%
2002.................................... Construction............... 58 Asian...................... 74% 90% 53%
rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr
2017.................................... Professional Services...... 49 Asian...................... 14% 29% 16%
2012.................................... Professional Services...... 100 Asian...................... 21% 33% 34%
2007.................................... Professional Services...... 100 Asian...................... 15% 28% 32%
2002.................................... Professional Services...... 88 Asian...................... 64% 77% 51%
rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr
2017.................................... All Industries............. 36 NHPI....................... 81% 86% 58%
2012.................................... All Industries............. 71 NHPI....................... 86% 86% 70%
2007.................................... All Industries............. 71 NHPI....................... 86% 93% 72%
2002.................................... All Industries............. 48 NHPI....................... 100% 100% 96%
rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr
2017.................................... Construction............... 11 NHPI....................... 73% 73% 45%
2012.................................... Construction............... 33 NHPI....................... 76% 79% 74%
2007.................................... Construction............... 33 NHPI....................... 73% 79% 58%
2002.................................... Construction............... 10 NHPI....................... 70% 80% 50%
rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr
2017.................................... Professional Services...... 13 NHPI....................... 69% 77% 46%
2012.................................... Professional Services...... 31 NHPI....................... 68% 75% 73%
2007.................................... Professional Services...... 31 NHPI....................... 52% 58% 39%
2002.................................... Professional Services...... 13 NHPI....................... 92% 92% 85%
rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr
2017.................................... All Industries............. 49 AIAN....................... 76% 88% 55%
2012.................................... All Industries............. 94 AIAN....................... 89% 97% 82%
2007.................................... All Industries............. 94 AIAN....................... 91% 98% 82%
2002.................................... All Industries............. 96 AIAN....................... 99% 99% 98%
rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr
2017.................................... Construction............... 39 AIAN....................... 59% 72% 23%
2012.................................... Construction............... 74 AIAN....................... 72% 81% 53%
2007.................................... Construction............... 74 AIAN....................... 73% 85% 54%
2002.................................... Construction............... 74 AIAN....................... 81% 91% 64%
rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr
2017.................................... Professional Services...... 33 AIAN....................... 52% 67% 27%
2012.................................... Professional Services...... 79 AIAN....................... 79% 92% 51%
2007.................................... Professional Services...... 79 AIAN....................... 68% 80% 43%
2002.................................... Professional Services...... 71 AIAN....................... 90% 92% 76%
rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr
2017.................................... All Industries............. 52 NMF........................ 100% 100% 98%
2012.................................... All Industries............. 104 NMF........................ 98% 99% 98%
2007.................................... All Industries............. 104 NMF........................ 98% 100% 100%
2002.................................... All Industries............. 104 NMF........................ 100% 100% 100%
rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr
2017.................................... Construction............... 52 NMF........................ 21% 54% 2%
2012.................................... Construction............... 103 NMF........................ 30% 56% 16%
2007.................................... Construction............... 103 NMF........................ 36% 67% 23%
2002.................................... Construction............... 42 NMF........................ 71% 86% 50%
rrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrrr
2017.................................... Professional Services...... 52 NMF........................ 92% 100% 83%
2012.................................... Professional Services...... 103 NMF........................ 97% 100% 94%
2007.................................... Professional Services...... 103 NMF........................ 99% 99% 94%
2002.................................... Professional Services...... 54 NMF........................ 100% 100% 98%
--------------------------------------------------------------------------------------------------------------------------------------------------------
Source: Author's calculations from the 2017 ABS, and the 2012, 2007 and 2002 SBO. Note: ``NHPI'' stands for Native Hawaiians and Other Pacific
Islanders, ``AIAN'' stands for American Indians and Alaska Natives, and ``NMF'' stands for non-minority female.
a. Conclusions from the Survey of Business Owners/Annual
Business Survey Data
While the exact proportions vary, large and statistically
significant disparities are observed in the U.S. as a whole, in all 50
states and the District of Columbia, for all minority groups--African
Americans, Hispanics, Asians and Pacific Islanders, and American
Indians and Alaska Natives--as well as for non-minority women. These
disparities are found in the Construction sector, the Professional,
Scientific and Technical Services Sector (which includes Architecture,
Engineering and related industries), and in the economy as a whole.
D. There is Strong Evidence of Disparities and Discrimination in
Minority and Female Business Formation Rates and Earnings
It is fair to ask whether the disparities documented in most
disparity studies and in the SBO and ABS data result primarily from
discrimination, or whether they result from other, potentially non-
discriminatory, factors.
This question can be tested directly using the American Community
Survey 5-year Public Use Microdata Sample (ACS PUMS), which allows us
to examine business outcomes for different race, ethnic, and gender
groups in great detail while holding constant a wide variety of other
demographic and economic variables.
1. Discrimination Impacting Business Formation
a. Methods
To assess the extent of discrimination in business formation, I
developed three different statistical regression models.\33\ In ``Model
A'', the only independent variables included in the analysis are
indicators for race and sex and survey year. This model identifies the
raw differences in business formation rates between minorities, women,
and non-minority males, holding only time constant.
---------------------------------------------------------------------------
\33\ Regression analysis is a type of statistical analysis that
examines the correlation between two variables (``regression'') or
three or more variables (``multiple regression'' or ``multivariate
regression'') in a mathematical model by determining the line of best
fit through a series of data points. In simpler terms, regression
analysis is a statistical technique allowing the comparison between
certain business outcomes, such as business formation, business
earnings, or loan denials, and minority or female status, while holding
other, potentially non-discriminatory factors, such as geographic
location, industry affiliation, education, age, or balance sheets,
constant.
---------------------------------------------------------------------------
Next, ``Model B'' adds to the regression equation several
independent variables that are indicators of qualifications and
capacity, including schooling, state of residence, and age.\34\ This
allows us to compare individuals that are similarly situated in terms
of their educational attainment, their geographic location, and their
labor market experience.
---------------------------------------------------------------------------
\34\ A person's age is a widely used proxy for their labor market
experience and enters the regression equation quadratically.
---------------------------------------------------------------------------
Finally, ``Model C'' adds to the regression equation a large number
of independent variables that have been shown to be related to the
propensity to become a business owner. These include proxies for
individual financial assets (interest and dividend income, home
ownership status, and home property value), family structure (spouse
present in the household, number of children in the household),
mobility (lived in the same house last year), immigration status
(foreign born, years in the U.S., English proficiency), military status
(veteran), and local macroeconomic conditions by state (general
population level, unemployment rate, number of full-time government
employees, per capita personal income).\35\
---------------------------------------------------------------------------
\35\ Interest and dividend income and per capita personal income
are included in the model in their logarithmic forms.
---------------------------------------------------------------------------
Taken together, these three models allow us to test whether
discrimination is the primary explanation for observed business
disparities for minorities and women. If disparity indexes remain
adverse, large, and statistically significant throughout Models A, B
and C, then the answer is ``Yes.''
b. Data
The data used for the analyses in this section are the most recent
2014-2018 American Community Survey 5-year Public Use Microdata Sample
(ACS), which allows us to examine business outcomes for different race,
ethnic, and gender groups in great detail while holding constant a wide
variety of other demographic and economic variables.\36\
---------------------------------------------------------------------------
\36\ These ACS data were released in January 2020. See U.S. Census
Bureau (2020d).
---------------------------------------------------------------------------
The analyses undertaken in this section require individual-level
data (i.e., ``microdata'') with relevant information on business
ownership status and other key socioeconomic characteristics. The
American Community Survey is an ongoing annual survey covering the same
type of information that was formerly collected in the decennial census
``long form.'' The ACS is sent to approximately 3.5 million addresses
annually, including housing units in all counties in the 50 states and
the District of Columbia.\37\ The PUMS file from the ACS contains
records for a subsample of the full ACS. The data used here are the
multi-year estimates combining the 2014 through 2018 ACS PUMS records.
The combined file contains over six million person-level records. The
2014-2018 ACS PUMS provides the full range of population and housing
information collected in the annual ACS and in the decennial census.
Business ownership status is identified in the ACS PUMS through the
``class of worker'' variable, which distinguishes the unincorporated
and incorporated self-employed from others in the labor force. The
presence of the class of worker variable allows us to construct a
detailed cross-sectional sample of individual business owners and their
associated earnings. The ACS PUMS universe for all of the analyses
presented below includes all prime age (16-64) private sector labor
force participants.
---------------------------------------------------------------------------
\37\ U.S. Census Bureau (2013).
---------------------------------------------------------------------------
c. Economy-Wide Findings
I estimated Models A, B and C across four different industry
groupings in the U.S.: (1) the entire economy, (2) the construction
sector, and (3) the Architecture/Engineering sector. These results are
reported below in Tables 10-12.
For the economy as a whole, the results are presented in Table 10.
Model A identifies large, adverse, and statistically significant
disparities in business formation rates in 2014-2018 for all minority
groups and for women. The results for Model A show:
For African Americans, the observed self-employment rate
is 5.7 percent and the model predicts that it would be 6.7 percentage
points higher--12.5 percent--if African Americans faced the same market
outcomes as non-minority males. This yields a disparity index of 46.
For Hispanics, the observed self-employment rate is 9.2
percent and the model predicts that it would be 3.8 percentage points
higher--13 percent--if Hispanics faced the same market outcomes as non-
minority males. This yields a disparity index of 70.9.
For Asian and Pacific Islanders, the observed self-
employment rate is 10 percent and the model predicts that it would be 3
percentage points higher--13 percent--if Asian and Pacific Islanders
faced the same market outcomes as non-minority males. This yields a
disparity index of 76.8.
For American Indians and Alaska Natives, the observed
self-employment rate is 8.7 percent and the model predicts that it
would be 3.7 percentage points higher--12.4 percent--if American
Indians and Alaska Natives faced the same market outcomes as non-
minority males. This yields a disparity index of 70.3.
For minorities as a group, the observed self-employment
rate is 8.3 percent and the model predicts that it would be 4.8
percentage points higher--13.1 percent--if minorities as a group faced
the same market outcomes as non-minority males. This yields a disparity
index of 63.2.
For non-minority females, the observed self-employment
rate is 9 percent and the model predicts that it would be 4 percentage
points higher--13 percent--if non-minority females faced the same
market outcomes as non-minority males. This yields a disparity index of
69.1.
For minorities and women as a group, the observed self-employment
rate is 8.6 percent and the model predicts that it would be 4.9
percentage points higher--13.4 percent--if minorities and women as a
group faced the same market outcomes as non-minority males. This yields
a disparity index of 63.7.Despite the addition of important
qualifications and capacity variables, the results for Model B show
that, for the economy as a whole, disparities in business formation
rates remain large, adverse, and statistically significant even when we
compare individuals that are similarly situated in terms of their
educational attainment, their geographic location, and their labor
market experience. Specifically, the results for Model B show:
For African Americans, the observed self-employment rate
is 5.7 percent and the model predicts that it would be 5.9 percentage
points higher--11.6 percent--if African Americans faced the same market
outcomes as non-minority males. This yields a disparity index of 49.5.
For Hispanics, the observed self-employment rate is 9.2
percent and the model predicts that it would be 3.3 percentage points
higher--12.5 percent--if Hispanics faced the same market outcomes as
non-minority males. This yields a disparity index of 73.9.
For Asian and Pacific Islanders, the observed self-
employment rate is 10 percent and the model predicts that it would be
3.2 percentage points higher--13.1 percent--if Asian and Pacific
Islanders faced the same market outcomes as non-minority males. This
yields a disparity index of 75.9.
For American Indians and Alaska Natives, the observed
self-employment rate is 8.7 percent and the model predicts that it
would be 3.5 percentage points higher--12.2 percent--if American
Indians and Alaska Natives faced the same market outcomes as non-
minority males. This yields a disparity index of 71.4.
For minorities as a group, the observed self-employment
rate is 9 percent and the model predicts that it would be 3.6
percentage points higher--12.5 percent--if minorities as a group faced
the same market outcomes as non-minority males. This yields a disparity
index of 71.6.
For non-minority females, the observed self-employment
rate is 8.3 percent and the model predicts that it would be 4.3
percentage points higher--12.6 percent--if non-minority females faced
the same market outcomes as non-minority males. This yields a disparity
index of 65.7.
For minorities and women as a group, the observed self-
employment rate is 8.6 percent and the model predicts that it would be
4.3 percentage points higher--12.9 percent--if minorities and women as
a group faced the same market outcomes as non-minority males. This
yields a disparity index of 66.5.
In Model C, numerous additional variables are included that measure
individual financial assets, family structure, mobility, immigration
status, military status, and local macroeconomic conditions. Despite
the inclusion of all these additional explanatory variables, the
results still show that disparities in business formation rates remain
large, adverse, and statistically significant when we compare
individuals who are also similarly situated in terms of these
additional measures. The specific results for Model C show:
For African Americans, the observed self-employment rate
is 5.7 percent and the model predicts that it would be 5.4 percentage
points higher--11.2 percent--if African Americans faced the same market
outcomes as non-minority males. This yields a disparity index of 51.5.
For Hispanics, the observed self-employment rate is 9.2
percent and the model predicts that it would be 4.3 percentage points
higher--13.5 percent--if Hispanics faced the same market outcomes as
non-minority males. This yields a disparity index of 68.4.
For Asian and Pacific Islanders, the observed self-
employment rate is 10 percent and the model predicts that it would be 5
percentage points higher--14.9 percent--if Asian and Pacific Islanders
faced the same market outcomes as non-minority males. This yields a
disparity index of 66.7.
For American Indians and Alaska Natives, the observed
self-employment rate is 8.7 percent and the model predicts that it
would be 3.2 percentage points higher--11.9 percent--if American
Indians and Alaska Natives faced the same market outcomes as non-
minority males. This yields a disparity index of 73.3.
For minorities as a group, the observed self-employment
rate is 9 percent and the model predicts that it would be 3.5
percentage points higher--12.4 percent--if minorities as a group faced
the same market outcomes as non-minority males. This yields a disparity
index of 72.1.
For non-minority females, the observed self-employment
rate is 8.3 percent and the model predicts that it would be 5.1
percentage points higher--13.4 percent--if non-minority females faced
the same market outcomes as non-minority males. This yields a disparity
index of 61.9.
For minorities and women as a group, the observed self-
employment rate is 8.6 percent and the model predicts that it would be
4.5 percentage points higher--13.1 percent--if minorities and women as
a group faced the same market outcomes as non-minority males. This
yields a disparity index of 65.6.
Table 10. Actual and Potential Minority and Female Business Formation
Rates, 2014-2018, All Industries
------------------------------------------------------------------------
Current Expected Disparity
Business Business Index
Formation Formation -----------
Race, Location Rate (%) Rate (%)
------------------------ (3)
(1) (2)
------------------------------------------------------------------------
Regression Model A......................................................
------------------------------------------------------------------------
African American.................... 5.74 12.48
Hispanic............................ 9.21 12.99
Asian and Pacific Islander.......... 9.96 12.97
American Indian and Alaska Native... 8.70 12.38
Two or More Races................... 8.87 12.66
Minority............................ 8.27 13.08
Non-minority female................. 8.95 12.96
DBE................................. 8.56 13.44
Non-minority male................... 13.09
------------------------------------------------------------------------
Regression Model B......................................................
------------------------------------------------------------------------
African American.................... 5.74 11.60
Hispanic............................ 9.21 12.46
Asian and Pacific Islander.......... 9.96 13.12
American Indian and Alaska Native... 8.70 12.18
Two or More Races................... 8.87 11.06
Minority............................ 8.27 12.58
Non-minority female................. 8.95 12.50
DBE................................. 8.56 12.87
Non-minority male................... 13.09
------------------------------------------------------------------------
Regression Model C......................................................
------------------------------------------------------------------------
African American.................... 5.74 11.15
Hispanic............................ 9.21 13.46
Asian and Pacific Islander.......... 9.96 14.93
American Indian and Alaska Native... 8.70 11.87
Two or More Races................... 8.87 11.06
Minority............................ 8.27 13.35
Non-minority female................. 8.95 12.41
DBE................................. 8.56 13.05
Non-minority male................... 13.09
------------------------------------------------------------------------
Source and Notes: Calculations by the author from the 2014-2018 ACS
PUMS. Disparity Indexes in italics are statistically significant at a
95 percent probability level or better.
d. Findings for Construction
When the scope of the inquiry is limited to just the construction
industries, the results appear in Table 11. When we examine just the
construction industry, Model A identifies large, adverse, and
statistically significant disparities in business formation rates in
2014-2018 for all minority groups and for women. The results for Model
A show:
For African Americans, the observed self-employment rate
is 17.8 percent and the model predicts that it would be 8.9 percentage
points higher--26.6 percent--if African Americans faced the same market
outcomes as non-minority males. This yields a disparity index of 66.7.
For Hispanics, the observed self-employment rate is 17.9
percent and the model predicts that it would be 8.7 percentage points
higher--26.6 percent--if Hispanics faced the same market outcomes as
non-minority males. This yields a disparity index of 67.3.
For Asian and Pacific Islanders, the observed self-
employment rate is 23.6 percent and the model predicts that it would be
3.9 percentage points higher--27.5 percent--if Asian and Pacific
Islanders faced the same market outcomes as non-minority males. This
yields a disparity index of 85.9.
For American Indians and Alaska Natives, the observed
self-employment rate is 19.1 percent and the model predicts that it
would be 9.1 percentage points higher--28.2 percent--if American
Indians and Alaska Natives faced the same market outcomes as non-
minority males. This yields a disparity index of 67.9.
For minorities as a group, the observed self-employment
rate is 18.3 percent and the model predicts that it would be 8.5
percentage points higher--26.8 percent--if minorities as a group faced
the same market outcomes as non-minority males. This yields a disparity
index of 68.2.
For non-minority females, the observed self-employment
rate is 17.9 percent and the model predicts that it would be 9
percentage points higher--26.9 percent--if non-minority females faced
the same market outcomes as non-minority males. This yields a disparity
index of 66.5.
For minorities and women as a group, the observed self-
employment rate is 18.2 percent and the model predicts that it would be
8.9 percentage points higher--27.1 percent--if minorities and women as
a group faced the same market outcomes as non-minority males. This
yields a disparity index of 67.3.
Despite the addition of important qualifications and capacity
variables, the results for Model B show that, for the economy as a
whole, disparities in business formation rates remain large, adverse,
and statistically significant even when we compare individuals that are
similarly situated in terms of their educational attainment, their
geographic location, and their labor market experience. Specifically,
the results for Model B show:
For African Americans, the observed self-employment rate
is 17.8 percent and the model predicts that it would be 8.7 percentage
points higher--26.5 percent--if African Americans faced the same market
outcomes as non-minority males. This yields a disparity index of 67.2.
For Hispanics, the observed self-employment rate is 17.9
percent and the model predicts that it would be 5.6 percentage points
higher--23.5 percent--if Hispanics faced the same market outcomes as
non-minority males. This yields a disparity index of 76.1.
For Asian and Pacific Islanders, the observed self-
employment rate is 23.6 percent and the model predicts that it would be
2.9 percentage points higher--26.5 percent--if Asian and Pacific
Islanders faced the same market outcomes as non-minority males. This
yields a disparity index of 89.1.
For American Indians and Alaska Natives, the observed
self-employment rate is 19.1 percent and the model predicts that it
would be 7.9 percentage points higher--27 percent--if American Indians
and Alaska Natives faced the same market outcomes as non-minority
males. This yields a disparity index of 70.9.
For minorities as a group, the observed self-employment
rate is 17.9 percent and the model predicts that it would be 10
percentage points higher--27.9 percent--if minorities as a group faced
the same market outcomes as non-minority males. This yields a disparity
index of 64.1.
For non-minority females, the observed self-employment
rate is 18.3 percent and the model predicts that it would be 6.1
percentage points higher--24.3 percent--if non-minority females faced
the same market outcomes as non-minority males. This yields a disparity
index of 75.
For minorities and women as a group, the observed self-
employment rate is 18.2 percent and the model predicts that it would be
7.5 percentage points higher--25.7 percent--if minorities and women as
a group faced the same market outcomes as non-minority males. This
yields a disparity index of 71.
In Model C, numerous additional variables are included that measure
individual financial assets, family structure, mobility, immigration
status, military status, and local macroeconomic conditions. Despite
the inclusion of all these additional explanatory variables, the
results still show that disparities in business formation rates remain
large, adverse, and statistically significant when we compare
individuals who are also similarly situated in terms of these
additional measures. The specific results for Model C show:
For African Americans, the observed self-employment rate
is 17.8 percent and the model predicts that it would be 7.5 percentage
points higher--25.3 percent--if African Americans faced the same market
outcomes as non-minority males. This yields a disparity index of 70.4.
For Hispanics, the observed self-employment rate is 17.9
percent and the model predicts that it would be 9 percentage points
higher--26.9 percent--if Hispanics faced the same market outcomes as
non-minority males. This yields a disparity index of 66.5.
For Asian and Pacific Islanders, the observed self-
employment rate is 23.6 percent and the model predicts that it would be
6.8 percentage points higher--30.5 percent--if Asian and Pacific
Islanders faced the same market outcomes as non-minority males. This
yields a disparity index of 77.6.
For American Indians and Alaska Natives, the observed
self-employment rate is 19.1 percent and the model predicts that it
would be 7.9 percentage points higher--27.1 percent--if American
Indians and Alaska Natives faced the same market outcomes as non-
minority males. This yields a disparity index of 70.7.
For minorities as a group, the observed self-employment
rate is 17.9 percent and the model predicts that it would be 10.3
percentage points higher--28.2 percent--if minorities as a group faced
the same market outcomes as non-minority males. This yields a disparity
index of 63.4.
For non-minority females, the observed self-employment
rate is 18.3 percent and the model predicts that it would be 8.1
percentage points higher--26.4 percent--if non-minority females faced
the same market outcomes as non-minority males. This yields a disparity
index of 69.2.
For minorities and women as a group, the observed self-
employment rate is 18.2 percent and the model predicts that it would be
9.5 percentage points higher--27.7 percent--if minorities and women as
a group faced the same market outcomes as non-minority males. This
yields a disparity index of 65.8.
Table 11. Actual and Potential Minority Business and Female Formation
Rates, 2014-2018, Construction
------------------------------------------------------------------------
Current Expected Disparity
Business Business Index
Formation Formation -----------
Race, Location Rate (%) Rate (%)
------------------------ (3)
(1) (2)
------------------------------------------------------------------------
Regression Model A......................................................
------------------------------------------------------------------------
African American.................... 17.78 26.64
Hispanic............................ 17.90 26.58
Asian and Pacific Islander.......... 23.64 27.52
American Indian and Alaska Native... 19.13 28.19
Two or More Races................... 20.10 25.79
Minority............................ 18.25 26.77
Non-minority female................. 17.91 26.92
DBE................................. 18.20 27.06
Non-minority male................... 26.84
------------------------------------------------------------------------
Regression Model B......................................................
------------------------------------------------------------------------
African American.................... 17.78 26.47
Hispanic............................ 17.90 23.52
Asian and Pacific Islander.......... 23.64 26.53
American Indian and Alaska Native... 19.13 27.00
Two or More Races................... 20.10 22.43
Minority............................ 18.25 24.33
Non-minority female................. 17.91 27.92
DBE................................. 18.20 25.65
Non-minority male................... 26.84
------------------------------------------------------------------------
Regression Model C......................................................
------------------------------------------------------------------------
African American.................... 17.78 25.27
Hispanic............................ 17.90 26.90
Asian and Pacific Islander.......... 23.64 30.45
American Indian and Alaska Native... 19.13 27.06
Two or More Races................... 20.10 22.62
Minority............................ 18.25 28.24
Non-minority female................. 17.91 26.38
DBE................................. 18.20 27.65
Non-minority male................... 26.84
------------------------------------------------------------------------
Source and Notes: See Table 10.
e. Findings for Architecture/Engineering
When the scope of the inquiry is limited to just the Architecture/
Engineering industries, the results appear in Table 12. When we examine
just the Architecture/Engineering industries, Model A identifies large,
adverse, and statistically significant disparities in business
formation rates in 2014-2018 for all minority groups and for women. The
results for Model A show:
For African Americans, the observed self-employment rate
is 6.5 percent and the model predicts that it would be 5.2 percentage
points higher--11.8 percent--if African Americans faced the same market
outcomes as non-minority males. This yields a disparity index of 55.6.
For Hispanics, the observed self-employment rate is 8.4
percent and the model predicts that it would be 3.4 percentage points
higher--11.8 percent--if Hispanics faced the same market outcomes as
non-minority males. This yields a disparity index of 71.1.
For Asian and Pacific Islanders, the observed self-
employment rate is 6.5 percent and the model predicts that it would be
5.1 percentage points higher--11.5 percent--if Asian and Pacific
Islanders faced the same market outcomes as non-minority males. This
yields a disparity index of 55.9.
For American Indians and Alaska Natives, the observed
self-employment rate is 6.2 percent and the model predicts that it
would be 5.3 percentage points higher--11.5 percent--if American
Indians and Alaska Natives faced the same market outcomes as non-
minority males. This yields a disparity index of 53.7.
For minorities as a group, the observed self-employment
rate is 7.4 percent and the model predicts that it would be 4.5
percentage points higher--11.9 percent--if minorities as a group faced
the same market outcomes as non-minority males. This yields a disparity
index of 62.
For non-minority females, the observed self-employment
rate is 7.8 percent and the model predicts that it would be 4.2
percentage points higher--12 percent--if non-minority females faced the
same market outcomes as non-minority males. This yields a disparity
index of 65.4.
For minorities and women as a group, the observed self-
employment rate is 7.6 percent and the model predicts that it would be
4.7 percentage points higher--12.3 percent--if minorities and women as
a group faced the same market outcomes as non-minority males. This
yields a disparity index of 62.
Despite the addition of important qualifications and capacity
variables, the results for Model B show that, for the economy as a
whole, disparities in business formation rates remain large, adverse,
and statistically significant even when we compare individuals that are
similarly situated in terms of their educational attainment, their
geographic location, and their labor market experience. Specifically,
the results for Model B show:
For African Americans, the observed self-employment rate
is 6.5 percent and the model predicts that it would be 3.6 percentage
points higher--10.1 percent--if African Americans faced the same market
outcomes as non-minority males. This yields a disparity index of 64.6.
For Hispanics, the observed self-employment rate is 8.4
percent and the model predicts that it would be 1.6 percentage points
higher--9.9 percent--if Hispanics faced the same market outcomes as
non-minority males. This yields a disparity index of 84.4.
For Asian and Pacific Islanders, the observed self-
employment rate is 6.5 percent and the model predicts that it would be
4.4 percentage points higher--10.9 percent--if Asian and Pacific
Islanders faced the same market outcomes as non-minority males. This
yields a disparity index of 59.2.
For American Indians and Alaska Natives, the observed
self-employment rate is 6.2 percent and the model predicts that it
would be 4.4 percentage points higher--10.5 percent--if American
Indians and Alaska Natives faced the same market outcomes as non-
minority males. This yields a disparity index of 58.6.
For minorities as a group, the observed self-employment
rate is 7.8 percent and the model predicts that it would be 3.1
percentage points higher--11 percent--if minorities as a group faced
the same market outcomes as non-minority males. This yields a disparity
index of 71.4.
For non-minority females, the observed self-employment
rate is 7.4 percent and the model predicts that it would be 3.1
percentage points higher--10.5 percent--if non-minority females faced
the same market outcomes as non-minority males. This yields a disparity
index of 70.5.