S. HRG. 111–1150 

MINORITY ENTREPRENEURSHIP: EVALUATING 

SMALL BUSINESS RESOURCES AND PROGRAMS 

ROUNDTABLE 

BEFORE THE

COMMITTEE ON SMALL BUSINESS AND 

ENTREPRENEURSHIP 

UNITED STATES SENATE 

ONE HUNDRED ELEVENTH CONGRESS 

FIRST SESSION 

SEPTEMBER 24, 2009 

Printed for the Committee on Small Business and Entrepreneurship 

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Available via the World Wide Web: http://www.fdsys.gov 
MINORITY ENTREPRENEURSHIP: EVALUATING SMALL BUSINESS RESOURCES AND 

PROGRAMS 
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WASHINGTON : 

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66–497 PDF 2013

S. HRG. 111–1150 

MINORITY ENTREPRENEURSHIP: EVALUATING 

SMALL BUSINESS RESOURCES AND PROGRAMS 

ROUNDTABLE 

BEFORE THE

COMMITTEE ON SMALL BUSINESS AND 

ENTREPRENEURSHIP 

UNITED STATES SENATE 

ONE HUNDRED ELEVENTH CONGRESS 

FIRST SESSION 

SEPTEMBER 24, 2009 

Printed for the Committee on Small Business and Entrepreneurship 

( 

Available via the World Wide Web: http://www.fdsys.gov 
(II) 

COMMITTEE ON SMALL BUSINESS AND ENTREPRENEURSHIP 

ONE HUNDRED ELEVENTH CONGRESS 

MARY L. LANDRIEU, Louisiana, Chair 

OLYMPIA J. SNOWE, Maine, Ranking Member 

JOHN F. KERRY, Massachusetts 

CARL LEVIN, Michigan 

TOM HARKIN, Iowa 

JOSEPH I. LIEBERMAN, Connecticut 

MARIA CANTWELL, Washington 

EVAN BAYH, Indiana 

MARK L. PRYOR, Arkansas 

BENJAMIN L. CARDIN, Maryland 

JEANNE SHAHEEN, New Hampshire 

KAY HAGAN, North Carolina 

CHRISTOPHER S. BOND, Missouri 

DAVID VITTER, Louisiana 

JOHN THUNE, South Dakota 

MICHAEL B. ENZI, Wyoming 

JOHNNY ISAKSON, Georgia 

ROGER WICKER, Mississippi 

JAMES E. RISCH, Idaho 

DONALD R. CRAVINS, JR., Democratic Staff Director 

WALLACE K. HSUEH, Republican Staff Director 
(III) 

C O N T E N T S 

OPENING STATEMENTS

Page 

Landrieu, Hon. Mary L., Chair, and a U.S. Senator from Louisiana .................. 1 

WITNESSES

Hontz, Karen, Republican Government Contracting staff, Committee on Small 

Business ................................................................................................................ 3 

Walker, Matt, Republican Deputy Staff Director, Committee on Small Business ........................................................................................................................ 3 

Reece, Adam, Republican Contracting staff, Committee on Small Business ...... 3 

Williams, Dr. Rube, President and CEO, Jet Learning Laboratory, Inc. ........... 3 

Wilkerson, Dwayne, President and Co-Owner, The Marrd Group, LLC ............. 3 

Robinson, Anthony, President, Minority Business Enterprise Legal Defense 

and Education Fund ............................................................................................ 3 

Reid, Royalyn, President and Co-Founder, Consumer and Market Insights ...... 3 

Jordan, Joe, Associate Administrator, Government Contracting and Business 

Development, U.S. Small Business Administration .......................................... 3 

Johnson-Pata, Jacqueline, Executive Director, National Congress of American 

Indians .................................................................................................................. 4 

Gatling, Denise, Director of Global Supplier, Diversity and Business Development, GlaxoSmithKline ....................................................................................... 4 

Cotton, Walter, Managing Partner, MR–IT@GOV ................................................ 4 

Boston, Dr. Thomas ‘‘Danny,’’ Professor of Economics, Georgia Tech, Atlanta, 

Georgia, and Director of Research and Innovation, EUQUANT ...................... 4 

Bangs, Dr. Ralph, Associate Director, Center on Race and Social Problems, 

School of Social Work, University of Pittsburgh ............................................... 4 

Alford, Harry, President and CEO, National Black Chamber of Commerce ...... 4 

Willis, Greg, Democratic Procurement Counsel, Committee on Small Business ........................................................................................................................ 4 

Denlinger, Stephen, President Latin American Management Association ......... 6 

Burnell, Charlotte, President, Strategic Planning Associates, LLC .................... 13 

Cravins, Donald, Democratic Staff Director and Chief Counsel, Committee 

on Small Business ................................................................................................ 16 

ALPHABETICAL LISTING AND APPENDIX MATERIAL SUBMITTED

Alford, Harry 

Testimony .......................................................................................................... 4 

Prepared statement .......................................................................................... 39 

Asian American Institute 

Prepared statement .......................................................................................... 77 

Bangs, Dr. Ralph 

Testimony .......................................................................................................... 4 

Research summary ........................................................................................... 65 

Boston, Dr. Thomas ‘‘Danny’’ 

Testimony .......................................................................................................... 4 

Executive Summary and Background of Business Development Index ....... 66 

Burnell, Charlotte 

Testimony .......................................................................................................... 13 

Cotton, Walter 

Testimony .......................................................................................................... 4 

Cravins, Donald 

Testimony .......................................................................................................... 16 
Page

IV 

Denlinger, Stephen 

Testimony .......................................................................................................... 6 

Gatling, Denise 

Testimony .......................................................................................................... 4 

Hontz, Karen 

Testimony .......................................................................................................... 3 

Jordan, Joe 

Testimony .......................................................................................................... 3 

Information for the record ............................................................................... 38 

Johnson-Pata, Jacqueline 

Testimony .......................................................................................................... 4 

Landrieu, Hon. Mary L. 

Testimony .......................................................................................................... 1 

The National Center for American Indian Enterprise Development 

Prepared statement .......................................................................................... 68 

Reece, Adam 

Testimony .......................................................................................................... 3 

Reid, Royalyn 

Testimony .......................................................................................................... 3 

Robinson, Anthony 

Testimony .......................................................................................................... 3 

Prepared statement .......................................................................................... 50 

Prepared statement dated May 22, 2007 ........................................................ 58 

Sumner, Michael 

Prepared statement .......................................................................................... 83 

Report: ‘‘Free to Compete?’’ .............................................................................. 88 

Report: ‘‘A Vision Fulfilled?’’ ............................................................................ 140 

Wainwright, Jon S. 

Prepared statement .......................................................................................... 184 

Walker, Matt 

Testimony .......................................................................................................... 3 

Wilkerson, Dwayne 

Testimony .......................................................................................................... 3 

Williams, Dr. Rube 

Testimony .......................................................................................................... 3 

Willis, Greg 

Testimony .......................................................................................................... 4 
(1) 

MINORITY ENTREPRENEURSHIP: EVALUATING SMALL BUSINESS RESOURCES AND 

PROGRAMS 

THURSDAY, SEPTEMBER 24, 2009 

UNITED STATES SENATE, 

COMMITTEE ON SMALL BUSINESS

AND ENTREPRENEURSHIP, 

Washington, DC. 

The Committee met, pursuant to notice, at 10:02 a.m., in Room 

SR–418, Russell Senate Office Building, Hon. Mary L. Landrieu 

(chair of the committee) presiding. 

Present: Senators Landrieu and Risch. 

Staff present: Donald Cravins, Gregory Willis, Karen Hontz, 

Matt Walker and Adam Reece. 

OPENING STATEMENT OF HON. MARY L. LANDRIEU, CHAIR, 

AND A U.S. SENATOR FROM LOUISIANA 

Chair LANDRIEU. Good morning, everyone. 

Thank you so much for joining me this morning for this roundtable on minority entrepreneurship during the Congressional Black 

Caucus week. We made a special effort to host this particular 

roundtable this week because of our many special guests in town. 

Before I begin, because I am going to ask all of our roundtable 

members to briefly introduce themselves, I want to take a point of 

personal privilege and welcome two special individuals from Louisiana. 

Dwayne Wilkerson, CEO of the Marrd Group in New Orleans, 

and Ms. Charlotte Burnell, owner of Strategic Planning Associates, 

from Metairie, Louisiana. I am grateful for both of them joining 

this national roundtable this morning. 

I want to thank all of you for taking the time to be here as we 

examine an important issue vital to the growth and development 

of our nation and how we support the minority community’s efforts 

to open, own, and grow their own businesses. We know that entrepreneurship, particularly small business development, but large as 

well—because minority businesses—both large and small are going 

to have a great role to play in this nation coming out of this recession. I believe that the nation has not yet quite tapped into the 

strength and potential of this particular group. 

One of our nation’s greatest assets is our diversity. Yes, it can 

be challenging. Yes, it can be complicated at times, but actually, it 

is a great strength that allows us today, and hopefully in the fu-
2 

ture, to be the most competitive nation in a growing global marketplace. 

We are literally the only nation that looks and speaks like every 

other nation on earth. We should be proud of that, and grab it and 

understand it as the strength that it is. 

The number of businesses in our minority communities continues 

to grow, adding to our competitive advantage. Minority business 

enterprises accounted for more than 50 percent of the two million 

new businesses created in the last 10 years. 

There are now more than four million minority-owned companies 

in the United States, with annual sales totaling nearly $700 billion. 

These businesses cross the entire industrial base from financial 

services and health care, to construction and transportation. While 

the numbers of minority-owned businesses are a source of optimism, and hold promise for the future, much more needs to be 

done to encourage and strengthen the minority business communities. 

They make up 32 percent of the nation’s population. Minority 

business owners, however, make up only 18 percent of firms. Nonminority firms bring in about $448,000 in annual sales, while minority firms are less than half of that. Clearly, the potential for 

small business growth and entrepreneurship, as I said, has not 

been fully tapped and there are barriers to entry that continue to 

exist despite our good efforts. 

Capital, including venture capital, can sometimes be a serious 

barrier. The Federal Government, which is the largest purchaser of 

goods and supplies and services in the world, sometimes there are 

barriers to entry there. 

The question today is, particularly to the SBA contracting and 

access to capital programs, how are these efforts through the SBA 

working to eliminate these barriers and how could they work better? I am looking forward to hearing from the experts on this panel 

today. 

We know there are some issues. For example, African Americans 

receive only about 5 percent of the loans from the SBA 7(a) program. A 2005 SBA report also found that African-American and 

Hispanic firm owners face higher loan denials. 

Obtaining venture capital is even tougher for minorities as the 

venture capital world is still 77 percent white and male. Part of 

this is due to the networks that are developed. The peers, the mentors, and the social networks are not yet completely as open as they 

could be. That is a fact. It is not an excuse, and we need to work 

through it. 

So we want to open up opportunities, as best we can, using appropriately the power of the government not only for African-Americans, but also for Hispanic, Asian, and women-owned firms. 

I am very proud of the team we have assembled here. I know 

that I am joined in many of these efforts, in spirit, by my ranking 

member, Olympia Snowe, the great Senator from Maine, who is not 

with us this morning, but is represented by her staff. 

She is actually marking up the health care bill in Finance. She 

told me yesterday she would much prefer to be with us. I think last 

night they were working well into the night and will be for the 
3 

next couple of weeks, so I want to acknowledge Senator Snowe and 

her staff and thank them for cooperating with us in this effort. 

Let me begin, if I could, starting here with Karen. We will go 

around this way. Because these are rather informal roundtables 

and not official hearings, I would like to have you all introduce 

yourselves. 

Following introductions, I will start with a couple of questions. 

I am then going to turn the program over to Greg Willis, who is 

the Chief Contracting staff member on the Small Business Committee, and to Don Cravins, who is our Staff Director, who will continue the questioning. I will not be able to stay the whole time, but 

I will be here for the first part. 

So, Karen, why don’t we start with you? Just introduce yourself 

and we will go around. 

Ms. HONTZ. Thank you, Senator. 

I am Karen Hontz. I am the lead for government contracting on 

the Small Business Committee for Ranking Member Snowe. 

Mr. WALKER. I am Matt Walker. I am Deputy Staff Director for 

the Republicans here on the Committee, and I just wanted to thank 

Chair Landrieu and her staff for working together with us in a bipartisan way over and over again on key issues that matter so 

much to Ranking Member Snowe. 

Thank you. 

Mr. REECE. Adam Reece. I am also on the contracting staff of the 

Small Business Committee for Senator Snowe. 

Dr. WILLIAMS. My name is Rube Williams. I am the President 

and CEO of Jet Learning Laboratory, an organization located in 

Houston. We were founded for scientific research, particularly nuclear and space systems, and also educational services related to 

mathematics and science. 

Chair LANDRIEU. Thank you. 

Mr. WILKERSON. My name is Dwayne Wilkerson. I am President 

and CEO of the Marrd Group, a small minority business in New 

Orleans, a contracting firm, and I am glad to be invited to this 

roundtable. 

Chair LANDRIEU. Thank you, Dwayne. 

Mr. ROBINSON. Good morning, Madam Chairwoman. Anthony 

Robinson. I am with the Minority Business Enterprise Legal Defense and Education Fund, a Washington-based legal advocacy organization on behalf of minority businesses and also representing 

the Unity Group, which is a coalition of minority and womenowned businesses who have organized themselves around the issue 

of establishing a federal predicate for minority business programs. 

Chair LANDRIEU. Thank you. 

Ms. REID. Good morning. I am Royalyn Reid. I am the President 

of Consumer and Market Insights. We are a marketing, research, 

training, and event planning firm from Dallas, Texas. We are also 

8(a), HUBZone, woman-owned and minority-owned. 

Chair LANDRIEU. All of her bases are covered. 

[Laughter.] 

Mr. JORDAN. I am Joe Jordan. I am the Associate Administrator 

for Government Contracting and Business Development at the 

SBA. It is pleasure to be here, yet again this week, to talk about 
4 

these really important issues. I am very excited to hear about how 

everybody on the panel is dealing with SBA programs. 

So thank you. 

Chair LANDRIEU. Thank you. 

Ms. JOHNSON-PATA. I am Jacqueline Johnson-Pata. I am the Executive Director of the National Congress of American Indians. We 

are located here in Washington, D.C. We are a group that represents the interests of the tribal governments in the country on 

all issues, including government contracting and economic development. 

Chair LANDRIEU. Thank you 

Ms. GATLING. I am Denise Jane Gatling. I am the Director of 

Global Supplier Diversity and Business Development for 

GlaxoSmithKline, a research-based pharmaceutical company. 

Our mission challenges us to enable people to do more, feel better and live longer; and one of the ways we feel we can do this is 

through our inclusion of diverse suppliers. 

So thank you very much for having us here today. 

Chair LANDRIEU. Thank you. 

Mr. COTTON. My name is Walter Cotton, the Managing Partner 

of MR–IT. We provide staff orientation, expert consulting services 

and community communication solutions. We are an 8(a), veteranowned small business and always look forward to finding some 

good partners. 

Chair LANDRIEU. Thank you. 

Dr. BOSTON. Good morning, Senator. My name is Danny Boston. 

I am a Professor of Economics at Georgia Tech, in Atlanta, and I 

am also a business owner of EUQUANT, which is a consulting company which does economic and statistical research, focusing specifically on minority businesses. 

Chair LANDRIEU. Thank you. 

Dr. BANGS. I am Ralph Bangs, Associate Director of the Center 

on Race and Social Problems at the University of Pittsburgh, and 

I do research on discriminatory actions by local government against 

qualified minority businesses and women-owned businesses for contract opportunities. 

Chair LANDRIEU. Thank you. 

Mr. ALFORD. I am Harry Alford, Cofounder, President, and CEO 

of the National Black Chamber of Commerce. We have a reach to 

over 100,000 businesses. We have 151 chapters in the United 

States and 80 chapters offshore. We are the largest black business 

association in the world. 

Chair LANDRIEU. Thank you, Harry. 

Mr. WILLIS. My name is Greg Willis. I am the procurement counsel for Senator Landrieu, who is Chair of the Senate Small Business Committee. 

Chair LANDRIEU. Thank you all so much, and again the audience, 

for joining us. 

The record of the Committee will be open for two weeks. We will 

be happy to receive testimony for those invited to participate in the 

roundtable as well as for others who are here this morning or listening to this roundtable. 

Again, the intent is to bring ideas to the table, to help strengthen 

the SBA’s work as the lead advocacy agency of the Federal Govern-
5 

ment, to open contracting opportunities, to help enforce the laws 

that are already on the books, and to identify what barriers there 

may be in minority, women-owned businesses participating in government contracting. 

The Federal Government is the largest purchaser of goods and 

services in the world. We want to focus on this. One of the major 

efforts of this Administration, and underway now, is the stimulation of this economy through additional federal spending and investments. It is a major priority of this Administration. 

I would like to begin by asking for you all to comment. What are 

you hearing from your organizations or what are you experiencing 

yourself in terms of participating in the expenditure of stimulus 

dollars that were invested in many infrastructure projects, educational opportunities, services, et cetera? 

We want to hear from minority businesses about what you are 

hearing and what you are experiencing, so we can focus on what 

we could potentially do better in that regard during the next couple 

of months. 

If you want to speak, please take your name plate and stand it 

up like this, and I will recognize you as we can. I do not know who 

wants to start. 

Ms. Reid, why don’t we start with you? 

Ms. REID. Senator, I am very involved in the Dallas, Texas, area. 

I am involved with the Dallas-Fort Worth Minority Business Council, as well as the Women’s Business Council Southwest, in which 

I am active and on the board. 

What I have observed in our area is that everyone is very interested. There are so many small businesses that are desperate. You 

see new businesses forming everyday from those that are being laid 

off. 

We hear about the stimulus money, but I have been to events 

that the word is not getting out and the right people are not communicating. You have some people up there speaking and they do 

not know anything. 

You see a lot of small businesses leaving even more frustrated 

and more confused. There must be some kind of way we can truly 

get that information down to the areas that really need it. 

I know that David Hansen mentioned this morning that they are 

focusing on the state and local levels, and that was encouraging because just what I have seen at the grassroots in that area is just 

not getting down to the people who really need it. 

Chair LANDRIEU. Mr. Robinson. 

Mr. ROBINSON. Prior to this morning, Madam Chairwoman, I 

would have stated emphatically that there was a great deal of frustration within the minority business community about the expenditures taking place with the stimulus funding. 

I had an occasion this morning, at a breakfast of the National 

Association of Minority Contractors, where an unscientific poll was 

taken of those members in that organization. I was surprised at 

the number of people participating who did raise their hand. 

What I would like to point out to the Committee is that because 

the stimulus money is governed by FAR, it has a fundamental flaw. 

You may be aware that under the federal acquisition streamlining 

and federal acquisition reform that took place in the 1990s. Many 
6 

of the socioeconomic indexes that required participation by minority and women-owned firms were gutted. And a lot of what we are 

seeing with bundling and the lack of minority participation, has its 

root causes in FAR and what took place with federal acquisition reform and federal acquisition streamlining. 

So if we are going to have the infrastructure in place to assure 

that participation, Congress is going to have to address that issue 

once again in order to secure participation in those projects. 

Chair LANDRIEU. Again, that is the federal acquisition regulation 

and it was passed in? 

Mr. ROBINSON. I mean FAR has already been in place, but the 

streamlining and the reform took place in the mid-1990s. 

Chair LANDRIEU. In the mid-1990s. 

Would anybody else like to comment on that? 

Harry. 

Mr. ALFORD. Yes, ma’am. We have done surveys and polls. You 

could bring more feed to the trough; but if you got the same pigs 

at the trough, nothing new is happening. If African-American firms 

are getting 1.1 percent of the Federal Highway Administration contracts and Hispanics are getting 1.6 percent, it is going to remain 

the same, as Tony just said, if it does not change. So nothing is 

changing on the formula related funding. 

We are going to hang in there and hopefully try to affect change 

on the discretionary fund. That is our hope for the coming year. 

The Indiana Legislative Black Caucus summoned me to Indiana 

to help them understand where the stimulus money was in Indiana. I had three staffers work a week trying to figure out, despite 

all the transparency on the website, to find it; and we found $4.3 

billion in Indiana; and they did not have a clue of how to get it or 

if anyone was getting it. 

Chair LANDRIEU. Thank you for the comments. 

Mr. Denlinger. 

Mr. DENLINGER. Thank you. Good morning, everyone. My name 

is Steve Denlinger. I am the President of LAMA. I am also the federal contracting advocate for the U.S. Hispanic Chamber of Commerce. 

I just got back from a week at the national convention of the U.S. 

Hispanic Chamber of Commerce and the overwhelming sense I get, 

and it is just widespread, is that they know there is lots of stimulus money out there but there is no systematic way to find out 

where it is being spent. 

More than anything, we need a systemic way of providing the minority business community with an understanding of where those 

projects are taking place. I think it is as simple as funding some 

of the major minority women-owned, and so forth, trade associations, to make sure that the word is getting out. The word is not 

getting out. The people do not know where the action is. 

Chair LANDRIEU. Go ahead. 

Ms. JOHNSON-PATA. I would just like to make a couple of recommendations. I totally agree that too many people are feeding 

from the top. I think the Department of Energy is a good example 

of a large amount of money going to existing contractors. I think 

the stimulus has tried to get the money out as quickly as possible. 
7 

They are using the contracting vehicles that were in place. You see 

it across the country. 

But, it did not stipulate anything new particularly from the 

small business community. A couple of recommendations would be 

to do some kind of review of who is getting the contracts. I know 

there is already transparency about that, but some kind of analyzing of exactly how many are really going to small businesses 

through the subcontracting plans. 

We were hoping that even though big companies still got the contracts, that they would actually expand in subcontracting, but we 

have not yet seen that come to fruition. 

Also, one of the things that we did in Indian country, because we 

wanted to take advantage of our very first opportunity to be part 

of Recovery Act funds, was a number of webinars and other kinds 

of things on a regular basis. We had a place for information that 

people could go to who have questions. 

On everything else we have information. Every piece of the recovery except for the contracting. We have not been able to get, as 

everybody indicated, a clearinghouse basically of what is coming up 

and where the opportunities may potentially be. 

Chair LANDRIEU. Let’s hear from Joe, who represents the SBA, 

and I know they are trying their very best. But I think that, Jacqueline, you raised an excellent point. I do not speak for the 

Obama Administration or for President Obama. I understand that 

part of their focus was getting the money out quickly because the 

nation needed that push, but you are right. Doing that, if the same 

contractors were in place, is sort of a counter effort to not take the 

time to try to expand. There is a little bit of tension there, but perhaps we could figure out a way to move through that. 

Mr. Jordan. 

Mr. JORDAN. Absolutely. Thank you. I certainly hear the frustration. The Administration hears that quite a bit. 

I did want to just briefly present what people talk about and the 

things they have heard. I want to present a few of the facts that 

I have, which are all publicly available, and also talk a little bit 

about what the President and Vice President have asked the Secretary of Commerce and Administrator Mills to do about the stakeholder outreach initiative. I have heard over and over, within this 

room and outside of it, about word not getting out. 

We certainly want to address that issue, and to the extent possible, enlist all of your help in addressing that. 

In terms of the SBA loan programs, the Recovery Act provided 

$375 million in funds to support the SBA loan programs. That has 

supported about $10.7 billion in small business lending across the 

country. It is over indexed in minority and women groups. 

Minority-owned businesses have received 20 percent of Recovery 

Act-based SBA loans and women-owned small businesses have received 19 percent. Mr. Cotton, and others, would be interested to 

know that veteran-owned businesses received 9 percent. 

We are here to talk about contracts, what has been going on with 

federal contracting and federal Recovery Act contracts. As you all 

know, we have a goal. The Federal Government has a goal that at 

least 23 percent of Federal contracts should go to small businesses. 
8 

Through the Recovery Act, thus far, we are just at that 23 percent, and I am cautiously optimistic that will continue. If you look 

at the trend, it has been moving up and then staying in that range 

right around the goal. 

Small disadvantaged businesses, which include the 8(a) companies, are at 10.6 percent, more than twice the goal. Women-owned 

businesses, unfortunately, have no tool the contracting officers currently use. We certainly are working on that. They are at 3.6 percent. 

Service-disabled veteran-owned businesses are at 3.7 percent. It 

would be great if we could exceed that goal. And minority-owned 

businesses, of all sizes, are at 14 percent of Recovery Act contracting dollars. 

And then lastly HUBZone, Historically Unrealized Business Zone 

companies, have a 3 percent goal, and they are running at more 

than twice that, at 6 percent. 

At the federal level, the contracts certainly are getting into the 

hands of the people that we all want them to. It is not just the 

same group of contractors. 

There are three challenges that I see. One, assuring that happens at the state and local level, and as MBDA Director Hansen 

referred to, we are working hard to talk about that. Chair Landrieu 

and Ranking Member Snowe, as well as Administrator Mills, have 

all written letters to the nation’s governors urging them to use 

small businesses and disadvantage small businesses with their 

state Recovery Act contracts. 

We also need to ensure that these numbers that I listed at the 

federal level will continue. Then, we need to make sure that any 

successes we see here in the stimulus, apply to the regular $500 

plus billion in annual federal contracting. 

The speed with which these funds are being dispersed is a challenge, but it is also a real opportunity. It is an opportunity to have 

that transparency and accountability, and prove which approaches 

worked and which ones were less effective. 

With the stakeholder outreach initiative, I will just briefly say 

that what we are trying to do is host and participate in all federal 

agencies, host and participate in a number of events around the 

country to get the word out on federal contracting, and state and 

local contracting. 

Also, on SBA.gov, there is now the ‘‘How to Win Recovery Act 

Contracts’’ with free training available to all businesses primarily 

focusing small businesses, especially those who may not have previously contracted with the Federal Government. 

We are trying to bring in new companies. We understand that 

many small businesses have had their commercial buyer base recede during these tough times, and we want to help them understand how to contract with the Federal Government. 

So there are a number of things we are doing. To the extent that 

we can do more, myself, the Administrator and our team, are absolutely willing to listen and discuss with you all the ideas that you 

have because we want to get this right. 

Chair LANDRIEU. Thank you, Mr. Jordan. 

One minute, Harry. 
9 

Mr. Jordan, thank you so much for your enthusiasm and for 

leaning forward. I have had several conversations with the Administration, and particularly Ms. Mills, about this and I know that 

she is committed. 

But one of the issues that came up yesterday, and I am going to 

get to those who want to ask questions, are laws on the books for 

all the different agencies, the goals, the 23 percent, et cetera. 

And, as we talked the day before yesterday, about some of the 

larger companies bidding for federal work and indicating on those 

bids that they are using small business subcontractors, we also 

identified that just because the bid says that they are going to be 

using small business contractors, does not mean that in the execution of the work they actually did. 

We are finding that with the gap, we are looking for ideas and 

suggestions to do more monitoring and really tough evaluation. I 

have had several small businesses from Louisiana, who are trying 

to do work with the Federal Government, who have said to me, 

‘‘Senator, we are part of the bid. That is not the problem. The problem is when the contract is let, we are not a part of the work, so 

we are not actually participating in a real way.’’ 

I do not know if some of you have had that experience, but it 

would be a good time to speak now, if that has been your experience, or if you have had a different experience. Please share. 

Dr. Boston. 

Dr. BOSTON. Yes, Senator. I want to just really reenforce, particularly, the last point which you made. It is true that both at the 

federal level and particularly at the state level there are often contracts that let individual vendors indicate that they will be used, 

and then if there is no monitoring process to ensure that happens, 

often it does not happen. That is one of the problems. 

I was delighted to hear the figures that were cited by Mr. Jordan. The other problem is that there is, really an endemic problem, 

regulatory problem in the SBA, as it relates to small disadvantaged 

businesses because it constrains their ability to grow and that 

would allow them to get the larger contracts. 

It is primarily related to the whole issue of personal net worth. 

I have some comments on that. I will not take up the time right 

now, but there are a number of problems with that. 

Even with the money, and if the money is reaching minority 

businesses particularly through the SDB program, what you have 

are businesses that are restricted because of the capacity that they 

can attain and thereby fostering a continuing relatively small 

group of firms, and not firms that ultimately break out and grow 

in scale, capacity to be mainstream players in society. 

Chair LANDRIEU. Thank you. That issue has come up before and 

we are evaluating it. In your written comments to the Committee, 

you could go into more detail. We thank you so much. 

Harry, go ahead. 

Mr. ALFORD. Madam Chair, could we get a detailed report of that 

10 percent? It started to sound like Katrina to me. Congresswoman 

Barbara Lee got a report from the Corps of Engineers, and here is 

their minority report on ANC companies. No blacks, whatsoever, 

had to go to the White House to get it changed around. 
10 

And to hear hurry, hurry, hurry. Just like Katrina. Please send 

me that report so that we can verify that and then see what the 

real numbers are or support your claim. 

Mr. JORDAN. All these numbers are publicly available on the Federal Procurement Data System, FPDS NJ. 

Mr. ALFORD. Just send me the report please. 

Chair LANDRIEU. Yes. We will get a copy to everyone here. 

And, Joe, thank you for making that available on the website. 

However, Mr. Alford has hit on the same point. We not only want 

to make sure that agencies say these are the minority companies 

they are working with, but instead, that the large contractors are 

actually doing that. The Corps of Engineers is one of the agencies, 

Harry, that I hear some complaints about. So thank you for raising 

that. 

Mr. Denlinger and then Mr. Cotton. 

Mr. DENLINGER. Just a couple of quick follow-ups. On the point 

you just made about the subcontracting opportunities disappearing, 

that is nothing new. That has been the circumstance of the last—— 

Chair LANDRIEU. Please speak into your mic if you would. 

Mr. DENLINGER [continuing]. Yes. The issue of vanishing subcontracts, is, of course, long-term, chronic, and an issue that I was 

going to address in my remarks later on with respect to the need 

for subcontract reform. 

The missing ingredient is a contract. If there is not a contract between the subcontractor and the prime contractor, by the time the 

prime contractor gets the contract, he forgets about the subs that 

he was purportedly going to use to fulfill the minority subcontracting plan. 

With respect to subcontracting reform, we need a contract between the prime contractor and the subcontractor at the time the 

prime contractor submits his bid. 

The other item is a barometer. There are certain things you can 

use as a barometer to get a sense of how effective the outreach is 

with respect to stimulus and other programs. 

One barometer is the extent to which associations, like LAMA, 

receive outreach information from the federal agencies and the 

SBA and so forth. 

LAMA has been around for 35 years. Everybody knows who it is 

and what it reaches. I have not received one item from any federal 

agency about any stimulus funding, period. If the agencies are not 

reaching us, how, in God’s green earth, am I going to believe that 

they are reaching our members across the country. It just is not 

happening. 

The outreach mechanism is missing. The heart is good. The heart 

is sound. We are very happy with the tone and the disposition of 

this Administration. But the mechanism is missing. 

Chair LANDRIEU. Thank you very much. I am going to ask the 

staff to really work on that specific issue today because it is something that our committee can do to help put a database together. 

We have access to it. Thank you for that suggestion. 

Mr. Cotton. 

Mr. COTTON. Thank you, Madam Chairman. 

One of the critical issues that often is overlooked in this area of 

large business subcontracting is the need for us to influence the 
11 

spirit of subcontracting. Absent an enforcement mechanism that allows us to change the behavior of these large prime contractors is 

not going to change because we have a subcontracting intention 

which is incongruent to their fiduciary responsibility and to their 

shareholders, which is to increase their value. 

So as long as prime contractors are not, and I do not want to use 

the word ‘‘punished,’’ but I think we are talking behavior modification here. They have to understand the interdependent nature of 

the request that we are making to help subsidize the viability of 

our small business community. 

Until we put a mechanism in place, that either holds them accountable for not meeting their stated subcontracting plan irrespective of whether they do it with the small businesses that they won 

the bid with or not, the fact that they have done it, is a vehicle 

that impacts their ability to acquire future contracts because of 

their poor performance against those goals. We are going to continue to chase this issue around and around. 

We need a—I do not want to use the word ‘‘punitive.’’ But we 

need a behavior modification vehicle put in place. 

Chair LANDRIEU. Thank you for being so tactful. A very good suggestion. 

Ms. Gatling, you represent a large company. 

Ms. GATLING. Yes. 

Chair LANDRIEU. One of the largest in the world. Could you comment about what your company has done to change behavior, to 

refocus, and some of the strategies that you are using or have used 

that could be helpful? 

Ms. GATLING. Yes, Madam Chair. 

Contract consolidations and utilization of major suppliers is 

something that a major corporation like GSK, because we are global, has to do. And we have to have the capacity of the small business in order to do work on that large scale. 

What we have done is bring in a large supplier and asked that 

they come to us with their diversity strategy. When they are bidding on the work with us, they have to bring the strategy to us. 

It has to be a strategy that we know is going to work for that community. 

We also listen to the small business community to find out what 

are some of the issues in working with a prime supplier. A lot of 

the messages are that they are not getting the contracts, so the 

work is not funneling there. 

So what we do is monitor. When we give the contract to the 

prime supplier, we monitor their usage of those small businesses. 

We ask that they report their numbers into a reporting system that 

we monitor. Then it becomes part of their evaluation when we 

evaluate them on a yearly basis. 

Monitoring is very key in this instance. 

Chair LANDRIEU. One of the strategies the staff could consider is 

looking at what some of the largest companies in the world are 

doing, and seeing how that compares to what the Federal Government and state governments are doing. While one is a business and 

one is a government, they are structured in much the same way. 

These companies are procuring lots of goods and services, and they 

are huge, but not as large as the Federal Government. 
12 

I think we could look to practices in the private sector and see 

how the private sector potentially is going. I am not saying everyone does it well, but there has to be somebody out there that is 

doing a good job. We can see what it is they are doing, how they 

are enforcing it, what they are suggesting and maybe bring some 

of those best practices to the government. 

Ms. Reid and then Mr. Jordan. 

Ms. REID. And one thing, Senator, thank you so much for acknowledging the checks and balances because I do agree that is 

very important. 

I personally understand that challenge, because even being a 

small business, I am committed to do those numbers as well. I 

know once we get contracts, you really have to work at it. But we 

are committed to do that as well. 

One thing I have noticed, even with our successes and lack of 

success in that area, was a correlation between the firms as well 

as government agencies that have strong minority, women business 

enterprise programs or omnibus programs. 

I think that would be important too to look at. Those who are 

successful, not only in size, can look at some of those agencies within the government that are doing well. We hear a lot about those 

that are not, but there are some that have strong programs which 

have been part of our success story as well. 

I do not want to get us off course, but I would like to go back 

and just add some anecdotal information to the issue that was discussed with Mr. Jordan. 

Of course, I do appreciate all that SBA is doing and has done. 

But one thing that we are seeing with those programs and even 

with those numbers are, first of all, challenging to even get through 

because of the red tape to get to that program. 

You have a lot of small businesses falling off. My company does 

a lot better because we are an 8(a). We are used to all of that. We 

considered one of the SBA programs for the stimulus package that 

was being overseen by the bank. As a matter of fact, once I visited 

my SBA office, I knew more than the bank. 

Even at that time the people who were operating it did not even 

have that information or knowledge, so they were learning along 

the way. I just took the initiative with my local SBA because I 

knew more. 

I think that is one thing we really need to look at of what is 

going on. 

Then, looking at some of the requirements. For $30,000, it was 

stringent on what you could spend it on. You could only spend it 

on passed bills that have shown a pattern. We have to look to try 

to see what bills could get up to that $30,000 to qualify. Sometimes 

you even have to look at some of those details. 

I do appreciate SBA working to be a good steward of checks and 

balances. But they are so stringent that you cannot even pass, even 

from the grassroots level. We look at what is going on with big 

businesses all the time. Then we see all of the hoops we have to 

jump through. 

Chair LANDRIEU. To access some of the stimulus funding is very 

difficult. 

Ms. REID. Yes. 
13 

Chair LANDRIEU. We have been joined by Senator Risch from the 

State of Idaho. We are very happy to have the Senator join us for 

just a few minutes. 

Let me go on. 

Dr. Bangs. 

Dr. BANGS. Yes. Thank you. 

In terms of the point that was mentioned earlier, that local governments can be a major bottleneck to getting stimulus spending 

to minority and women firms, our research on discriminatory practices by local government strongly supports that view because there 

are a lot of actions out there that are inhibiting or excluding qualified minority and women businesses from local government prime 

contracts. 

The problem is not just the subcontracting that is not getting 

from the prime contractors to the subcontractors. The problem in 

local government as well as the federal governments often is that 

they are not having equal opportunity for qualified firms for the 

prime contracts. 

Those exclusionary practices include continued bundling, not 

breaking contracts into smaller sizes so that different sizes of firms 

can compete, having slow-pay systems so that small firms cannot 

get the money in time for these projects and so they cannot survive, or even apply for projects because they know that many local 

governments are not paying on time. 

Those are just a couple of the mechanisms that exclude small 

businesses, and in particular, minority and women businesses. 

Chair LANDRIEU. Thank you for raising another issue that comes 

up from small businesses, the prompt payment from the Federal 

Government, that sometimes, at the local, state, or Federal levels 

do not pay promptly. It can literally bankrupt a small business because you do not have the staying power that large businesses 

might have, such as the strength of credit. 

It is important for governments to pay promptly. That in itself 

can be a barrier that small businesses just cannot take in terms 

of doing business with someone that is not going to pay them for 

six months or a year. 

Mr. Robinson. 

Mr. ROBINSON. Madam Chairman, as you know, the Congress 

passed the Prompt Pay Act, but there is a fundamental flaw in that 

much of the transportation money does not apply because the 

Prompt Pay Act flows through state governments. 

Congress might want to consider revisiting that Prompt Pay Act, 

to make it apply to all federal monies that flow, even indirectly 

through state and local governments, where much of the problem 

exists relative to that. 

Chair LANDRIEU. Thank you. That is an excellent suggestion. 

We have been joined by Ms. Burnell. Thank you very much for 

being here from Jefferson Parish. We really appreciate it. I know 

you have your name plate up, so do you want to introduce yourself 

and then make a comment? 

Ms. BURNELL. Yes. First of all, I would like to introduce myself. 

I am Charlotte Burnell, and I am a small business and 8(a) business in the Senator’s district. 
14 

We have had a lot of money, besides stimulus money. We have 

been dealing with recovery projects which have really had a tremendous impact economically in our area. 

However, just as several of you have said, we have had strong 

subcontracting plans and outreach programs. But because there is 

not strong compliance and monitoring, the dollars never get to the 

small businesses that are in the subcontracting plans. 

That enforcement mechanism is very important. I know in some 

of the Corps of Engineers contracts that have been done in New 

Orleans, they have actually assessed some financial penalties. But 

nobody is monitoring it to enforce the financial penalties. 

The language looks good. It is just not being enforced. Monitoring 

of who is being hired and where the dollars are going, beyond the 

subcontracting plans, and the actual dollars that are reported to 

Congress that are getting to the small businesses, I think, would 

be an important issue to all of us. 

Chair LANDRIEU. Thank you. 

Ms. Pata and I will come back to Mr. Alford. 

Ms. JOHNSON-PATA. I wanted to follow up on the subcontracting 

plans, and certainly, we support improvement of subcontracting 

plans. In fact, one of our recommendations that we put forward is 

having to monitor. I think the monitoring should go one step further than the subcontracting plans. 

I think the details should be in the contracts and that there 

should be follow-up with monitoring and compliance. I think it also 

follows up with joint ventures and mentor prote ́ge ́. We should improve the goals and the monitoring of those goals because I think 

even small businesses and joint ventures of the small businesses 

and mentor prote ́ge ́, also get left off the table when it comes to 

really delivering the goods and services for the dollar amounts. 

I have some specific recommendations about maybe some items 

that could be monitored or reported, on a regular basis so that they 

could be reviewed. 

The other recommendation I wanted to put on the table when 

talking about these subcontracting plans, and when you mentioned 

it earlier, Mr. Cotton, on perhaps making that be part of the original contract. It seems the strengthening of teaming arrangements 

might be a good opportunity for us. 

One of the recommendations we put forward was just a pilot program on teaming which would require that the Federal Government look for contracts earlier in advance so you could put the 

right teams together. 

But if you could pool together a group of small businesses to be 

eligible as a team, you have to make some changes in legislation 

to make them eligible collectively, so that they could team, some 

of these larger contracts or midlevel contracts that small businesses are not eligible for. 

I think that might be something interesting to explore, too, because there are a lot of small businesses, as we have heard here 

today, that would like to pool together. 

Chair LANDRIEU. That is an excellent suggestion. I am going to 

call on Mr. Boston now and I am going to turn the panel over to 

Don Cravins and Greg Willis. The Senator may want to add a few 

comments or questions himself, but this has been a very informal, 
15 

very open Senate roundtable. I have found these to be very effective and they are really helping us to understand what some of the 

barriers are, and how our laws, while they may be well-intentioned, 

are not working as well as we would like in order to get some 

changes. 

Let me call on Mr. Cotton, and I am going to turn it over to Don 

Cravins. Thank you all so much, and again the record will be open 

for two weeks. This roundtable will continue probably until about 

11:15 or 11:30. Thank you so much. 

Go ahead, Mr. Cotton. 

Mr. COTTON. One of the points that I want to follow up on that 

you made is relative to that issue. I think for many years, time has 

been used to keep small businesses out of the contracting pool. And 

that is the available pool of capacity that only teams of small businesses could meet in terms of the needs of consolidated or bundled 

contracts. 

My study of the Code of Federal Regulations, and my study of 

the FAR, indicates that there are already authorities, mechanisms 

in place, that empower the small business community to utilize 

strategies like alliances, joint venturing (as probably the most dominant), to put together teams that could attack a number of opportunities within their size for their industry. 

But there are other vehicles out there, like the utilization of the 

SBA Business Development Mentor Program, which is underutilized as a capacity generator and that would allow small businesses 

to put themselves in a position to, and since we are keeping this 

informal, I am going to use a little vernacular here, change the 

game. 

Allow them to put themselves in a position to bring a response 

to any requirement that comes out that would be on par with those 

that are delivered by the individuals that are always feeding at the 

trough. 

The point that you made, which is very relevant and resonated 

with me, is the fact that we have to get a lot better about being 

proactive and utilizing resources, like our PCRs, to bring opportunities to the visibility of the small business community at the requirement phase of the acquisition cycle which would give the 

small business community enough time to build capable teams to 

respond to them. 

This I think is consistent with the statement that the young lady 

on the end made a little bit earlier when she said, ‘‘Once I sat 

down and studied the regulations, I was smarter than the people 

who were responsible for the program I went for lending.’’ 

We have to collectively, as a group, make the commitment to getting ourselves approved, understanding these programs and regulations that are available to us, and then constructing solutions that 

are going to be in the best interest of our economy as a whole. 

So as we sit oftentimes, and I am going to say this directly to 

my brothers and sisters that are small business owners, as we sit 

oftentimes and point a single finger at the Federal Government or 

at the large contractor that is not letting a subcontract to us, we 

have to be assured that we have covered these three fingers that 

are pointing back at us. 
16 

We have to be assured that we have left no stone unturned, that 

we have utilized joint venturing, tried to find a mentor who could 

augment our capacity, and put us in a position to allow the intention of the Small Business Act to be realized, which is the maximum practicable opportunity to participate in federal contracting. 

That is the enormous language that we have underutilized because we as a collective, and I am talking about the government 

in concert with the small businesses, have not developed a strategy 

to pursue. I will stop there. 

Mr. CRAVINS. Thank you, Mr. Cotton. 

I am going to call on some of the others. Keep your comments 

as brief as you can because I want to get Senator Snowe’s staff involved so they can ask some questions as well. 

Dr. Williams, I know you have had your name plate turned up 

for awhile. 

Dr. WILLIAMS. Thank you, Mr. Cravins. I wanted to make a comment concerning the lines of monitoring. A few years ago, I was 

part of a team to develop a proposal with a very large firm to do 

some work in what we call ‘‘the second line of defense’’ where you 

install radiation detectors and such in places like Russia, Ukraine, 

places like that. 

This is work I have done and have helped to get the contract 

over into the 8(a) bucket. All right. When we put the first team together that was possible for getting it over to the bucket, and then 

decided to join a large firm, they systematically began to reduce 

our influence on that contract. 

I am talking about inside of the technology parts. I did not see 

anyone in that organization that was particularly more knowledgeable about technology than myself. And I know that is just the 

tendency for the way things go. 

When we got toward the end, I was beginning to decide not to 

put too much effort toward the end, and they did not actually get 

the contract. But the fact is that in this business of bait and 

switch, you can kind of see it coming. 

One thing I do not really see as practical is to have monitors. 

Then you have to monitor this and monitor that. Someone has to 

monitor the monitors. 

I think one thing is that there is a belief system and there is this 

need, to maximize profit. A belief system is sometimes habit. We 

can do this. We want to do this ourselves. 

Also, you know that you do something, you develop the capability; and if you let someone else do it, they develop the capability. 

That is really kind of against the competitiveness. 

You have to expect large businesses are going to cut us out because, unless you are vital, you just have to have them. 

I think, though, that some of this could change. I was in an aerospace conference last week. They made it very clear that it looks 

like an impossible task to be able to have the input of personnel 

in the next 20, 30, 40 years that are technical and are able. 

One thing, I think is we may be able to use, national responsibility, this thing about national health. For national health, many 

industries, and most industries, know that they cannot get the people they are going to need as far as technical folks for the future. 

They are just not there. If you just project and you do your best 
17 

and you rebuild all the schools, it is still not there. So you have 

a problem. 

A part of that problem could be facilitated in the right direction 

if you think about the fact that income correlates with educational 

successes. 

When minority businesses are funded, you are going to have a 

lot better spread of wealth in minority communities. I know it is 

not something that people have well considered and it may not be 

something that folks want to consider, but I think that if you look 

at it from this standpoint, it is sort of a national emergency. It is 

national health. It is national security. 

I think if you could get a little bit of esprit de corps in these larger organizations, that are not going to be functioning well, they are 

going to be giving up on their work to other countries because the 

people are not being trained. 

And by funding small businesses, you are going to increase the 

numbers of folks. People have a hard time dealing with the delay. 

We are talking about a 10- to 20-year delay, but it is like global 

climate change. If it hits you, you are dead. You are done. 

So you have to get ahead. I just wanted to put out there that not 

just monitoring, but maybe the cause du jour, may be by spreading. 

I know people do not like the idea of spreading the wealth, but you 

want to spread the technological capability. 

The main thing people do not give you contracts for is because 

you instantly create a competitor. If you can do that, you are going 

to sustain something that is going to fall off here in the near future. 

Mr. CRAVINS. Thank you, Dr. Williams. 

We are going to move to Dr. Boston. I told Greg in the interim, 

doc, that when you put a lot of lawyers and PhDs on a panel, it 

is dangerous. Go ahead, Dr. Boston. 

[Laughter.] 

Dr. BOSTON. I will try not to live up to that reputation. 

I want to make a couple of very quick points. One about the 

issue of prompt payment. Prompt payment has to be monitored 

down at all levels, not just the first level. For example, in North 

Carolina, the Department of Transportation has a payment system 

whereby if you submit an invoice, they pay you immediately. 

But if you talk to subcontractors, they are complaining about not 

getting paid. The prime is paid immediately, but the subcontractors 

are not. It has to be monitored. 

Secondly, there are a number of ways of monitoring. You do not 

just have to monitor with physical individuals. You can also set up 

appropriate data systems to do the monitoring. And if you are 

tracking with appropriate data systems, then you can also determine whether or not there is compliance. 

In regard to the SBA, one of the gaps in terms of data systems 

that really needs to be addressed is subcontracting data, particularly, that come from corporations that do business with the government. 

We have the FPDS that tracks absolutely perfectly, but we do 

not know what is going on underneath that. 

Just two more very quick points. One is the contract issue. There 

needs to be a letter of intent. I do not think you can have a con-
18 

tractor, beforehand, execute a contract without a letter of intent. 

That has to be monitored. 

Then finally on the mentor-prote ́ge ́ relationship. I think Ms. Gatling can talk to this. One of the problems that major corporations 

are having is that when they engage in mentor-prote ́ge ́ relationships and are able to grow corporations in partnership to get into 

the value aspect of their supply chain, they are no longer eligible 

to participate in the SDB program. That is a real problem. 

Mr. CRAVINS. Mr. Alford. 

Mr. ALFORD. A strong bid language precludes all of that. We 

write bid specifications for some municipalities. You put in the bid 

specification that must support the documentation of minority business subcontracting. If there is a change, you must report that 

change. And if a minority falls off, he must be replaced by another 

minority. If you do not do that, you are in breach of contract. There 

are remedies to that, fines, removal from the contract. 

Remember, Tony, we got Hunt Construction banned for five 

years from doing any work for the State of Indiana for that same 

business. Then we got them knocked off the short list of a basketball arena in St. Louis and off the short list of a baseball stadium 

in San Francisco. The CEO of Hunt Construction came and made 

peace, and they have been a good little angel ever since. Janet Reno took Peter Kiewit to the wall, fined him $700,000 

and carted some of the fronts off to jail. We need the Justice Department to get involved in this to set some examples. Just a couple of examples and everybody gets the message. 

Mr. CRAVINS. Thank you, Mr. Alford. 

At this time I will turn it over to my colleagues from Senator 

Snowe’s staff. Ms. Hontz. 

Ms. HONTZ. Thanks, Don. 

We managed to cover a lot of issues on the agenda. I wanted to 

remind you as well that the record will be open. I know we could 

talk for days on all of these issues, but we are really looking to set 

a base and get some information for legislation that we would hope 

to be developing shortly after we conclude these roundtables. I encourage you to submit information. 

We touched on net worth, but I want to go to something that is 

somewhat related, which is size standards. In Tuesday’s Roundtable, we heard pros and cons. If you raise standards for procurement, which some agreed is important, you may be hurting those 

small businesses that are just trying to get into the government 

contracting arena; therefore, I would like to have a few comments 

on the record about size standards. I understand that Joe is caught 

in the middle of these issues but he needs to hear your comments 

as well because size standards fall under his purview. 

Mr. Robinson, I believe you were the first one to have your name 

plate up. 

Mr. ROBINSON. Yes. I have been a proponent of reforming size 

standards for a few years because they have not been changed, the 

bulk of them have not been changed, as I said before. There were 

some tweaks on some subindustries, but there has not been a real 

overhaul of size standards to see whether or not they are still consistent with what would be considered small, and other than small, 

in today’s industries. 
19 

I would think that a serious, and I think the last Administration 

had begun to take a major look at that, would encourage to continue. 

I would also like to take this opportunity to make sure that we 

do not miss the 800-pound gorilla in the room. As we look at these 

various issues to tweak and make programs, improve the programs’ 

delivery and make them better, and speak to the congressional 

mandate that these programs developed competitively viable companies, that we also appreciate the fact that the courts are looking 

at these programs as we are. As Congress is. 

If we have not established a robust predicate for these programs, 

the courts will do as it just did the DOD program this past November. It is absolutely critical that this Committee, as it looks at 

these program modifications and changes, also establishes a robust 

predicate to make sure that as the courts review these programs, 

that they are preserved. 

Ms. HONTZ. I just wanted to point out Constitutional issues are 

on the agenda; and we are going to have discussion for the record. 

Mr. Denlinger. 

Mr. DENLINGER. Coming in on size standards, size standards 

present some of the most difficult issues that our companies confront. I am going to focus on a relatively small slice of the size 

standard issue. 

There are number of codes wherein the size standards are so 

small, that we push companies out of the size standard classification into competition that is unsustainable in the open world. 

SDB has a responsibility for helping develop small business so 

they can compete once they are no longer small. Let me give you 

the example. And we are talking about base maintenance. We are 

talking about certain aspects of environmental remediation, range 

operations, certain elements of information technology such as systems integration and so forth. 

Focusing on systems integration in the IT world for a moment, 

the present size standard to graduate out of the small business category, companies need sales of $23 million, a three-year average of 

$23 million. 

If you take a company that has $23 million, or a little bit over 

that three-year average, and put them out there to compete against 

the Lockheed Martins and the Northrop Grummans, it is insane, 

just absolutely insane. 

It is a complete abrogation of SBA’s responsibility to protect and 

support small business. We need a rational, logical look, at certain 

industries where we are graduating companies out of the small 

business category prematurely. 

Think for a moment. What does it take, for a company to be able 

to compete in the systems integration business, once they are no 

longer small? That is probably a company that is maybe 1/10 of the 

size of the very largest companies or the dominant companies in 

the industry. 

That ought to be somewhere along the lines of the formula used 

for determining when companies should graduate. That is a whole 

different number than the way it is today. 
20 

We see a serious and sustained look at size standards based on 

some, particularly, those industries where we know instinctively 

and we have known for years, that the size standard is too small. 

We need to be careful that we do not injure smaller companies. It might be a case where there are no $5 million size companies 

that are going to be competing for systems integration contracts. 

We are not competing against. We are not putting large small 

businesses against small small businesses. 

There are some protections that could be built in, but I think we 

really need to address this issue seriously. We will have some recommendations on that point. 

Ms. HONTZ. Thank you. 

Dr. Boston. 

Dr. BOSTON. Yes. I agree completely. If you could imagine how 

the size standards constraint small businesses in regards to them 

graduating out of the program, it is even more onerous when you 

consider minority businesses in the SDB program because they 

graduated unrelated to size, but related to personal net worth. 

But the other issue with size standards is that there is no, as I 

understand it and I have looked, and my company is currently researching that, we do not understand the guidelines as to how 

those size standards are formed. 

They are adjusted, but they are only adjusted on the basis of inflation and so that they can tend to just increase very very incrementally. For example, in professional services, the size standard 

for a company is about $6 million. 

I have talked to diversity directors at major corporations. For example, one major corporation says that, in order for a minority firm 

to operate in our program, they have to have $25 million in revenue. There is another financial services company that says we 

have a minimum of $10 million. Size standards are really unrelated to industry criteria and they are an impediment. 

Again, the size standards obviously have been there, but I agree 

that they need to be related to industry criteria such as, for example, the concentration in industry and construction. What is the required on-average bonding capacity? Those kinds of things are important and not just by an inflation adjustment. 

Ms. HONTZ. Thank you. 

Mr. Wilkinson. 

Mr. WILKERSON. Yes. I want to touch on something and Dr. Boston brought it up just now about the bonding capacity. I am from 

New Orleans, and as you know, Mr. Cravins, we have some special 

challenges down there. 

One of the challenges that we have as a small minority business 

subbing underneath these big contractors is our bonding. 

We are not able to come up with this bonding. When you talk 

about the subcontracting plan that big contractors put in place and 

they say ‘‘Okay, we are going to use this minority and that minority,’’ when it comes out, they are not using that minority. 

One of the reasons why is because he may come to me and say, ‘‘Okay, Dwayne, we have $5 million that we are going to send to 

you all,’’ and all of a sudden he sends us the $5 million and we do 

not have the capacity to get the bonding because of us being a new 

company in New Orleans. 
21 

So then he turns around, he goes back and he says, ‘‘Well, we 

cannot come up with this bonding that we need.’’ 

He goes back to whoever he has to report to, whatever regulatory 

person that he has to see and says, ‘‘Well, we reached out and they 

were not able to make their bonding.’’ 

What we need from the SBA is for the government to come in 

and work with us on the surety bonds, put something in place to 

say, ‘‘We are going to help assist you all with this bonding,’’ because as a small company, if we are liquid, say we have a half a 

million dollars liquid, and we need a $5 million bond, and the people tell us, ‘‘You need to put that half a million dollars up on this 

bond,’’ how are we going to pay the payroll? 

Essentially, just like with the feds not getting paid enough. Any 

misstep with a small company down there, with us, you say, ‘‘There 

is a 60-day turnaround for us to get paid.’’ Any misstep for us and 

we are bankrupt two weeks after that because we are leveraged all 

the way to the hilt. 

I think that our problem down there is, basically in order for us 

to get to the next level for SBA, the government needs to step in 

and help put a surety bond, some type of thing in place, to help 

the businesses down there. 

Mr. WALKER. If I could just go on with that for a second. One 

of the things that some members of this Committee worked on in 

the stimulus, specifically Chair Landrieu, Ranking Member Snowe 

and Senator Cardin, was to increase surety bonding for small businesses from the current level, which was $2 million, up to a new 

level of $5 million. 

I just wanted to find out, if word on the street, was that the SBA 

had implemented that change and if that is being worked in a 

manner that is helpful and useful, and whether people are able to 

take advantage of the new increased bonding limits. 

Mr. WILKERSON. Okay. I am hearing it from around the table 

here right now, but I have never heard of it. It is not getting out. 

Where do I go to see this? I mean I am online everyday. I am looking for anything. I am looking for all kinds of help down in New 

Orleans to try to build. I am from New Orleans. We are rebuilding 

this city, and this is our chance. I do not know where to go. 

Where do we go to find that? 

Mr. WALKER. What I would suggest doing—Mr. Jordan could 

probably speak to this issue a little better—is to contact the SBA 

to find out more details on what they are doing to implement the 

provision. 

The SBA will certainly be the first line of contact but also feel 

free to call our office as well and we would be pleased to put you 

in contact with the right people. 

Ms. HONTZ. Mr. Jordan, it is your turn. 

Mr. JORDAN. Thank you. Briefly on the surety bonding, I would 

encourage you to do the same thing that I would tell you to do for 

any contracting or SBA program you were interested in or wanted 

to learn more about which is in your district office. 

New Orleans has a great district office. They will be happy to 

give you all the information. We have certainly increased the Recovery Act surety bond limits to $5 million as Matt said. 
22 

What I have heard has been very positive. I would encourage all 

of you to look into it and let me know if there are other things that 

you can do. 

With regard to the size standards, I just briefly want to address 

this. That is certainly something I hear quite a bit about. While it 

was around this forum, it sounded like the vast majority of people 

were recommending an increase. I hear just as many people come 

to me and say, ‘‘No, no, they are too high as they are.’’ 

In fact, subsequent to the roundtable that was held on Tuesday 

where this issue was discussed, I walked off and the first person 

who came running up to me was a woman who said, ‘‘Don’t you 

dare raise the size standards.’’ 

It is common, when Mr. Denlinger talked about the $23 million 

example, and how it is very difficult for the business once it exceeds the size standard, to compete as an other than small entity. 

It is often, from what we hear, that it is difficult for a new business 

who is just entering that industry to compete with a $23 million 

business. 

So we are very sensitive to this issue, and we want to get to the 

right answer. What are we doing about that? 

We are undergoing a comprehensive size standards review. Several people have talked about different thoughts on the methodology that we would use and that is very exciting to me, because 

we hope to soon put out for public comment the methodology that 

we are proposing to use as well as several different industries to 

which we have recommended an adjustment to the size standard. 

There are a few things that we are looking to do here. One, get 

the level right so that small business growth continues to happen 

within that small business industry. Also, as many people have 

pointed out, once a small business starts to approach a size standard, it does not feel constrained. Rather, it continues to grow when 

it is other than small. 

We also want to limit confusion. Size standards are actually indexed to inflation for that very reason, among others, but that is 

a big reason we do not want them constantly changing and for 

there to be confusion. 

We do absolutely understand that there is a need to review the 

size standards, and we are doing that. I know that is something 

that this Committee—for all of you who may not know, has been 

very diligent about pursuing. The Administrator and Administration are absolutely pursuing it. 

Ms. HONTZ. In the interest of time, the constitutional issues are 

something on which we really want to spend some time. 

Mr. Denlinger and Ms. Gatling, if you could submit whatever you 

were going to say for the record, I would appreciate it. 

Don, do you want to continue? 

Mr. CRAVINS. One of the things that Senator Landrieu asked me 

to do, and I did not do was to take a point of personal privilege 

and welcome two good friends of mine. I had the pleasure of serving with these two ladies in the Louisiana legislature. 

They are here. Representative Regina Barrow, who is the Chair 

of the Louisiana Black Caucus and a champion of small business 

in her own right, from the great city of Baton Rouge. 
23 

And Representative Pat Smith, who I got a chance to serve with 

for a brief time in the Louisiana legislature, also from Baton Rouge 

and a champion of small business. 

Welcome to the Committee. 

[Applause.] 

Mr. CRAVINS. I know Greg wants to talk about 8(a) which I know 

is a very important issue to many of you at this table. 

So Greg. 

Mr. WILLIS. We are going to try to move fairly quickly to get to 

the constitutional issues as quickly as possible, but one of the 

things that I have heard and the Committee has heard for a number of years, is the constraints that the 8(a) program places on minority small business owners, or socially and economically disadvantaged business owners as they try to grow. One of the major 

issues has been the net worth threshold. 

We want to hear from folks about what their thoughts are on 

where the dollar limit is now, ways to change it, ways to improve 

the environment for small business owners, so that once they get 

into the program, they have the ability to grow and be viable after 

they exit the program. 

So Dr. Boston. 

Dr. BOSTON. Right. I think, above all other problems that have 

to be addressed, is the problem of personal net worth. Clearly, in 

order for the program to be constitutional, there has to be some 

type of parameters which define eligibility to the program so that 

you do not restrict certain businesses, only businesses of certain 

characteristics. But personal net worth is not that. 

It is unrelated to any industry criteria. There is no understanding of why it was that, where it was set. It has not been 

changed in 10 years, so $750,000 today, is actually worth a half 

million dollars. And personal net worth is closely related to firm 

revenues. So if you cap one, you cap the other. 

More importantly, personal net worth is related to bonding capacity. If personal net worth is too low, your ability to get bonding 

is too low. 

It is related to your ability to raise finance and capital. It is unrelated to, for example, if I have a company in the manufacturing 

industry or in a service industry or in a construction industry—I 

have the same personal net worth threshold and it is unrelated to 

the capital requirements of those different industries. It just does 

not make sense. 

It needs to be either eliminated altogether or supplemented with 

something else. We have been working with an alliance to come up 

with an alternative that we call ‘‘a business development index’’ 

that relates more specifically to industry criteria, some of the kinds 

of things that he was talking about. 

How much concentration in the industry, what is the average 

revenue, bonding requirement? Those kinds of things as a criteria 

for entry into the 8(a) program and the SDB program. But not personal net worth. 

It will continue to make, particularly minority businesses will 

continue to make them small. And I will just stop. I know I am 

running on and on. 
24 

In Georgia there was an audit done of businesses in the DBE 

program and that audit indicated that 17 of those firms that were 

doing business with the Georgia Department of Transportation had 

to be graduated because their owners’ personal net worth exceeded 

the limit. 

We tracked those companies on a month-to-month basis, and six 

months after they were graduated, their revenues fell by 45 percent. 

Those companies were having all kinds of problems. That has to 

really be changed. It works counter to what the SBA really wants 

to do, and that is to grow these companies and give them opportunities. Personal net worth is actually working counter to that. 

And again I have talked to Ms. Gatling a great deal about that, 

and she has brought a lot of these issues to my attention particularly on the corporate sector. 

Mr. WILLIS. Mr. Denlinger and then Ms. Gatling. 

Mr. Denlinger. You hit the point right on the head. Your points 

are so well taken. Net worth is built into the statute because the 

statute requires that the companies prove socio and economic disadvantage. 

But we forget that the point was to achieve entry into the program, not for participation in the program. That is punitive. That 

is contrary to common business sense to limit net worth. 

On the entry our position for years has been the $250,000 net 

worth that encourages only the smaller, least-capable companies 

coming into the program. We need companies that are strong. But 

once they are in the program, we need them to develop their net 

worth to the maximum extent possible. 

Why? So that they are bankable. So that they can get the capital 

to finance the growth of their business. When they go to the bank, 

what do the banks ask for? For the owner’s net worth. 

The same thing for bonding. The points are very well taken. We 

need to eliminate net worth during program participation and go 

back to the original concept which is a criteria for entry into the 

program, not for continued participation in the program. 

Mr. WILLIS. Ms. Gatling. 

Ms. GATLING. Yes. From a corporate perspective, many corporate 

organizations have objectives with the SBA. What we are finding 

with the small disadvantaged business category, if you cap that net 

worth, you are looking at a small pool of suppliers that are eligible 

to assist corporate America. I mean all corporations. 

If you take a look at a number of these companies, they do not 

really have what we need in order to meet those objectives. 

I do agree that we need to take a look at the net worth cap. I 

am not sure what that number should be, but I believe that we 

should also look at the success of a business’ characteristics because we have some categories that I know that corporate America 

is responsible for procuring in, such as women-owned businesses or 

HUBZones or veteran-owned businesses that do not have a net 

worth cap. 

We are finding that those companies are successful based on 

business characteristics. I think that we should look more at business characteristics versus a net worth cap. 

Mr. WILLIS. Mr. Alford. 
25 

Mr. ALFORD. Mr. Wilkerson, I present to you Mr. David Kay. 

Dave, raise your hand. If you need some bonding, see Mr. Kay. He 

is a magician. 

Mr. WILKERSON. I am definitely going to go see him. 

Mr. ALFORD. I put my word on it. 

Small disadvantaged business they do not certify that any more. 

Does it exist actually or has it become self-certification? 

Mr. WILLIS. It is self-certification. 

Mr. ALFORD. So it is fraud basically, right? If you self-certify—— 

Mr. WILLIS. There is the potential for fraud, but there is not necessarily fraud. 

Mr. ALFORD. On this net worth business in 8(a), Russell Kelly, 

please raise your hand. 

This man lost everything in Katrina. He went to apply for 8(a) 

and they told him he is too rich. Lost everything. He is going to 

reapply. 

Mr. WILLIS. Okay. 

Mr. ALFORD. That is all I have to say. 

Mr. WILLIS. Dr. Boston. 

Dr. BOSTON. Just one last point. The other problem is that by restricting access to those programs to businesses whose owners fall 

under the personal net worth, what you end up doing is also having businesses that, when corporations use them, are using the low 

value chain. If, for example, an auto parts company or some other 

type of manufacturing company really wants a parts manufacturer, 

well, if they found a parts manufacturer, that owner’s personal net 

worth is likely to be above the threshold. 

What they do, because they are obligated to meet certain utilization goals, they go and they might get a minority firm to do maintenance work or something else. So they are not in the real high 

value chain or the high value section of the supply chain. 

Mr. WILLIS. Thank you. 

Mr. Robinson. 

Mr. ROBINSON. I would just want to remind everyone that Congress is the cornerstone legislation for these programs, the 8(a) program, 95–507. The purpose of the program is to develop competitively valuable companies. That is the purpose. 

I think we have lost sight of that, and one way in which that 

sight has been lost, I would suggest, is in the personal net worth 

category. 

Mr. WILLIS. Thank you. I will turn it over to Karen quickly and 

then we will move on to the last issue on the docket. 

Ms. HONTZ. Thanks, Greg. 

Actually I am going to turn it over to Matt Walker. But Senator 

Snowe is very concerned about some of the recent GAO decisions 

that created a super preference for HUBZones. 

HUBZones, I might add, are important to Maine because Maine 

is very rural. But she feels very strongly that programs should not 

be pitted against one another, that we need to increase the pie for 

small businesses, and not fight among ourselves but get out there 

and get more business. There is $500 billion or more that the Federal Government buys 

in products and services every year. In fiscal year 2008, small businesses got about $90 billion of that. There is room for growth. 
26 

Matt, would you like to expound upon that? 

Mr. WALKER. Yes. I think my colleague led into it well and I just 

wanted to follow up on that. Senator Snowe worked very closely 

with Chair Landrieu as well on this provision, and as Karen says, 

it is a provision that is difficult. 

Senator Snowe realizes the importance of true parity among the 

programs and the detriment of fighting amongst the programs. 

One of the provisions Senator Snowe included, in addition to the 

others, would try to achieve more parity by allowing all of the programs to have a mentor-prote ́ge ́ component. 

We are interested in hearing about the benefits of the mentorprote ́ge ́ program, specifically how it has worked, how it has not 

worked, and how it can be an effective tool. 

In the interest of time I am not going to dwell on this because 

I know there are other issues to get on to. 

Mr. Cotton, you and I have spoken about this in the past and you 

have spoken very eloquently to the benefits of the program as well 

as its potential. Again, while recognizing the limited time, maybe 

you can say a few brief words on this for the record. 

Mr. COTTON. I think that the mentor-prote ́ge ́ program that the 

SBA, their business development mentor-prote ́ge ́ program, is an excellent tool to cause capacity creation for the small business community, and I think it was a stroke of genius to offer that as a possibility through the amendment to the other socioeconomic groups. 

But I want to speak to that issue of parity that you addressed 

that is also a part of the amendment and address a question that 

Ms. Hontz asked earlier. What kind of solutions can we offer that 

they can consider for legislation as we move forward to address the 

problem? 

One area that I think that we should consider is taking the contracting authority that exists under the 8(a) program which resides 

with the SBA. The SBA becomes the contractor of record between 

the agency and allows the other programs to enjoy that benefit as 

well. It allows the small disadvantaged business program, womenowned business program, and the veteran business program to 

enjoy that ability. 

What that would do is produce an organic vehicle that gives a 

complete advantage to these groups because in some instances, it 

would allow them to operate at a contracting level that is above the 

commercial product tier, the commercial product buy, Part 8 of the 

FAR, and move that group, that entire population, out of the competitive pool where large businesses are taking advantage of them. 

I will give you more details on that in writing, but I think that is 

a good suggestion. 

Mr. WALKER. Thank you very much. Again, unfortunately, we 

have got to move on. 

Mr. DENLINGER. I just want to say that we very very strongly 

support that leveling of the playing field and true parity across the 

programs. 

The decision as to which program to use, in any given requirement is something that should reside in the contracting office if the 

contracting officer is sitting there saying I have goals to meet with 

these various programs. I am doing really well with 8(a). So I am 

going to go with HUBZone on this one. Or the same thing with 
27 

women’s preference or the veteran-owned preference. So we really 

strongly support this. 

Mr. WALKER. Thank you. 

Mr. ROBINSON. On Mr. Cotton’s point relative to the delegation, 

part of the problem existing now is that SBA has delegated a lot 

of that authority to the agencies, and it no longer resides within 

SBA itself, and part of the problem when it was with SBA, was 

that it was not exercised. 

There would have to be a major overhaul in both attitude and 

personnel for that to be effectively implemented. 

Mr. WALKER. Thank you. 

Greg. 

Mr. WILLIS. Thanks, Matt. I appreciate it. 

We are going to move pretty quickly now. One of the issues that 

has come to the forefront in the last two years has been the issue 

of building the predicate for the benefit of these race-conscious programs. 

I wanted to allow folks to talk about where we are with respect 

to building that predicate in response to the Rothe decision from 

last November. I also wanted to talk about some of the statistical 

evidence that can be presented concerning discrimination contracting, in general. 

So we will start with Mr. Alford. 

Mr. ALFORD. That is so overrated. Any person who just passed 

the bar exam can look at the numbers and see the disparate impact. The numbers I put there for federal highways for black contractors, some states do not even do business at all with federal 

funds. 

1.1 percent black, 1.6 percent Hispanic. Back in the mid-1980s 

we were doing 8 percent. Now we are doing 1.1. And I think Mr. 

Jenkins, who is my numbers cruncher, can present data that would 

justify these programs. 

It is pretty simple if we had a Justice Department that would 

just argue for it. The data is there. 

But let me say, and Tony brought up a point about personnel, 

when the National Black Chamber of Commerce started in 1993, 

the SBA had 5,000 employees and a budget of over $900 million. 

Today, they have 1,700 employees with a budget of less than $400 

million. 

It is like Eisenhower going into a concentration camp after World 

War II. It was a mess, worse than we thought. When this Administration comes in, we need to get funding and build back the personnel who can provide good technical assistance to our people in 

the field. 

You talk about SBA in New Orleans. Is there an SBA in New 

Orleans? Three or four people maybe. It used to be 30 something. 

Mr. WILLIS. Dr. Bangs. 

Dr. BANGS. In terms of local government, some of the data are 

there and some are not. In local government, our research finds 

that many local governments do not have data that they report on 

minority and women shares of contracts; and if they have data on 

minority and women shares, it is often exaggerated. It is inaccurate. 

Mr. ALFORD. We are talking Federal Government? 
28 

Dr. BANGS. Well, yeah, but when it comes down from the federal 

and state government to local government, in terms of the problem 

at local government, a fair amount of federal money is spent. 

Mr. ALFORD. May I? If they are not keeping the data they are 

in violation of Title VI of the Civil Rights Act and should not receive federal funds. 

Show me a city that is not keeping the data. I will show you a 

city I would like to go see. 

Dr. BANGS. Part of the problem is that there is no federal monitoring investigation. There is very little federal monitoring investigation and enforcement of the constitutional laws—— 

Mr. ALFORD. Violating the Civil Rights Act. 

Dr. BANGS. The Civil Rights Act and so on. We need a larger federal role in order to address the local government problem which 

is huge. The market for contracts is large at the local level, and minority and women businesses are getting very small shares and we 

know that because we go collect the data and verify the data. 

There is a huge problem. We need a larger federal role in addressing this problem. 

Mr. WILLIS. Thank you. 

Dr. Boston. 

Dr. BOSTON. Yes. In regards to the issue of a factual predicate, 

the first thing is, I have been an advocate for many many years 

that there should be some type of, for lack of a better word, a congressional commission on factual predicate standards because local 

and state governments are spending literally millions and millions 

of dollars to commission disparity studies, all of which do not conform to any real standard, and once they are done, it is no guarantee they will not be overruled. 

There is too much variation in the standards and expectations in 

regard to predicates. 

The second point is that with regard to the Rothe decision, that 

decision was related to the Department of Defense’s program. I 

have submitted in earlier testimony, a report that was done that 

indicated using Federal Government data, that is, the small business data, records on 43,000 contractors with the Federal Government that indicated that firms that participate in the SDB program 

still encounter discrimination, that is, that if they were compensated based on their attributes, the industry that they operate 

in, the years that they had been in business and so on and so forth, 

if they were compensated at the same rate at which non-SDB firms 

are compensated, that their revenue would be $900,000 greater 

than it is. 

Mr. WILLIS. Per firm? 

Dr. BOSTON. Per firm, on average, it would be $900,000 greater. 

That has already been submitted to the record. 

Mr. WILLIS. Can you resubmit that for this Congress? 

Dr. BOSTON. I can. I will. 

Mr. WILLIS. Thank you. 

Mr. ROBINSON. In the testimony that I will be presenting today, 

we will provide anecdotes of individual testimonies of discrimination in the marketplace, specifically around access to capital, the 

SBA’s Special Small Business Investment Corporation, the lack of 
29 

minority participation in that, and what we believe to be the exclusion of minorities from participation in that program. 

The issue of discrimination is absolutely imperative and should 

be established on the record. We will get that information. 

Mr. WILLIS. Can you speak a little bit more about, one of the 

issues that keeps coming up regarding access to long term capital 

for minority and women-owned firms? We held a hearing last Congress and I have come to the belief that access to that kind of mezzanine financing is the difference between businesses dying, and 

them really exploding, and what SBA had this morning with the 

SBIC program. I am going to ask Mr. Jordan to speak to that as 

well. 

But, Mr. Robinson, can you talk about that? 

Mr. ROBINSON. I believe that the way to get that capital to minority firms is through using minority firms. They tend to have the 

relationships. They tend to understand the community, the challenges of that community. And the problem that I have with SBA’s 

program is the lack of minority participation that could leverage 

five, ten to one, the capital that those firms have available to them, 

to get out to minority communities. 

Until we have greater participation of minority firms in programs, in venture capital, the mezzanine capital market is the way 

you get that capital to those communities by having those firms 

who are managed and controlled by minorities participating in 

those programs. 

Mr. WILLIS. Mr. Jordan, a series of quick questions about that. 

The SBIC program, as I understand it, licenses firms who raise private capital and then leverage that capital to disburse to different 

companies. How many of those licenses are held by women and minorities? 

And my understanding is also, and correct me if I am wrong, 

that once someone is licensed, they have to come back and get approval for disbursal of capital. 

First, how many minorities and women have licenses? Second, 

how often do they get to disburse capital from the program? If you 

do not have that information right now, we want you to submit it 

for the record before the two weeks is out. 

Mr. JORDAN. Sure. As you know, Mr. Willis, the SBIC does not 

fall under my personal purview but I did bring some statistics that 

specifically speak to the first part of your question. But I will certainly supplement those with the entirety of the answer. 

I brought fiscal year 2007 and 2008 data. In fiscal year 2007, 

there were 2,057 businesses in the SBIC program. Businesses financed through the SBIC program, and 247 of them were minorityowned so that is 12 percent. 

In fiscal year 2008 of the 1,905 firms, 219 were minority-owned 

so that is 11.5 percent. And I was told to keep in mind that very 

few businesses in the SBIC program are 50 percent owned by any 

individual. 

Since I have the microphone for just a minute, can I quickly 

speak about the 8(a) program? I will say it very briefly. I did not 

have a chance during that entire conversation. 

I did want to say we are extremely proud of the progress the 8(a) 

business development program has made in delivering true busi-
30 

ness development, growth and assistance to socially and economically disadvantaged small businesses. 

Over the last five years, every single socially disadvantaged 

group has seen tremendous growth in their participation with 8(a) 

contracts. It is not just one particular sector, but across the board. 

The 7(j) training and management assistance is something that 

we are very proud of, but we are also putting a lot of focus on going 

forward to ensure that this program, as several of you said, meets 

its mission of being a true business development program. 

I know the net worth issue is one that is quite contentious and 

there are certainly people on both sides of that. 

One thing that was not mentioned is that $700,000 net worth cap 

does not include equity in your home, does not include equity in 

your business. 

We are looking at changes to the 8(a) program. We hope to have 

some potential regulations out for public comment quite soon as 

well. 

Certainly all of you would be very excited to have you engage in 

that public comment process. I did just want to say that. 

Mr. WILLIS. No problem. Just as a follow-up, of the number of 

companies that were financed through the SBIC program, what 

was the average size of the deal that they do versus the size of nonminority firms? 

Mr. JORDAN. I do not have that with me. As with the disbursal 

of capital, I get that. 

Mr. WILLIS. Disbursal of capital, and overall what was the percentage of dollars that went to minority firms? Eleven or 12 percent of the companies were but the actual dollars that were disbursed to those companies. 

Mr. JORDAN. Sure. I will get you those for women as well. 

Mr. ALFORD. Mr. Chair, while you are at it, that 12 percent minority, how many were black? 

Mr. WILLIS. We would like the breakdown of ethnic and racial 

groups as well as women. 

Mr. Denlinger. 

Mr. DENLINGER. I want to kind of backup and suggest it is time 

to take a look at the broad perspective and this is probably a very 

good time to do that. 

One of the things that I see across the government is this chronic, knee-jerk built-in preference for large business. We have not 

broken that mentality. That culture pervades the Federal Government, the federal buying activity. 

Why, for example, should over 50 percent of the federal IT dollars go to just ten large businesses. Why? That should scream out 

to be addressed in some fashion. 

We need size standards reform so that small businesses can actually compete for some of that effectively. We need larger small 

businesses to be able to back up those monopolies. 

Let me talk, just a moment or two, about the ‘‘rule of two.’’ The 

‘‘rule of two’’ is a very powerful, underutilized resource. The ‘‘rule 

of two’’ basically says that if there are two or more small businesses that are ready, willing, able, and capable of bidding out a 

requirement, it has to be set aside for small business competition. 
31 

But between that law, in the FARs, and the actuality, a lot of 

stuff falls through the cracks. We need a bigger focus on fully implementing the ‘‘rule of two.’’ Let me give you an example. 

The Air Force in 2008 missed its small business goal of 23 percent by seven points, achieving only slightly we will just say 16 

percent. That is a huge deficit. That is a loss of billions in contracting to the small business community. 

At the same time, the Air Force is considering consolidation ac- tions that take small business requirements to the tune of $449 

million. Lump them into a large bundled contract that only large 

businesses are going to be able to participate in. 

So in addition to missing the goal, the Air Force is taking actions 

that will dramatically result in the reduction of the small business 

participation. 

The SBA, through one of its PCRs, procurement center representatives, in California said to the Air Force, not so fast. We see 

what you are doing. We know you want to consolidate this. 

We are going to go out there and take a look at the capability 

in the small business community so that we can satisfy ourselves 

as to whether or not there is sufficient capability in the small business community to keep that range of operation, which is $440 million in the small business arena. It was performed successfully by 

a small business over the period of the last contract. 

We need a sharper focus on full implementation of the ‘‘rule of 

two.’’ We need size standards that enable us to break the large 

business monopoly, and we need a philosophical change. This Committee can lead in that regard, to break the monopoly of large business. 

We think about a 23 percent goal. It sounds really good. But the 

flip side of that you are saying 77 percent of the federal procurement dollar is the province of large business. 

Why? It makes no sense. We have agencies in the Federal Government that are achieving 40 and 50 percent small business contracting. That goal needs to be increased to at least 40 percent. 

I hear people saying, ‘‘It should be 25 percent or why bother?’’ 

It needs to be substantially more, and we need to think about that 

in terms of breaking the monopolies that large businesses have. 

This culture that pervades our procurement offices all across the 

country is large business preference. Thanks. 

Mr. WILLIS. Dr. Boston. 

Dr. BOSTON. For the record I just want to let Mr. Jordan know 

the comments that I offer were not comments that were designed 

to condemn the 8(a) program. 

In fact, as a part of the same study that I will submit to the 

record, one of the things we did was to look at the contribution that 

the 8(a) and SDBs make annually to the economy. 

We did ask, using the methods that we use statistically, what is 

added to the economy by virtue of having these roughly 7,000 firms 

participate in the program? We found that on an annual basis, about $6 billion and created 

about 123,000 jobs, would not be there but for that program. They 

were creating jobs in overwhelmingly high poverty areas of central 

cities. So the program is very important. In fact, it is why we are 

so interested in making sure that it becomes even more effective. 
32 

The last point is that the very importance of the program relates 

to the fact that, because there are still discriminatory barriers in 

society as a whole, minority firms generally tend to pursue government contracts in a much larger percentage than is there representation among the general population. 

If you look at all the small business contractors, what you will 

find is that minority firms represent about 39 percent of all small 

business federal contractors, where only 18 percent represent society as a whole. 

The Federal Government, local, and state governments really become the first point of market entry. So again it was in that spirit 

that we are offering ways, we think, that would actually make the 

programs much more effective even than they are right now. 

Mr. WILLIS. Mr. Alford. 

Mr. ALFORD. To tie in with Dr. Boston, when the National Black 

Chamber of Commerce was incorporated in 1993, there were 

300,000 black-owned businesses doing $30 billion a year. Today 

there are over a million black-owned businesses doing over $80 billion per year. 

Despite the growth, despite the increase in capacity and businesses that are ready, willing, and able, our share of the federal 

procurement dollar is shrinking year by year despite our continual 

growth. 

I want this Administration to understand that things are bad, 

and it is not your fault. These were not your numbers. You do not 

have to be defensive. We want to work with you. Do not think we 

are coming to criticize you. We know it is bad. Let us work as a 

team and turn it around. 

Mr. WILLIS. Mr. Robinson. 

Mr. ROBINSON. It is always hard coming behind Harry. One area 

that we have not touched on in the entire morning that I would 

like to get at least on the table represents another SBA program. 

That is the SBIR and STTR program, the research and development component of the program, and the lack of minority participation in that program as well. 

I would like to suggest to SBA, and I would like to talk with 

them about this, ways in which the Federal Government spends 

over $300 billion annually in research and development. 

As technology becomes an increasing important driver in the 

economy, it is going to be increasingly important that minority 

firms participate, in a significant way, in technology development 

and deployment. 

The SBIR and STTR program is not addressing that at all. I 

would suggest that some out-of-the-box thinking relative to the participation of minority institutions and historically black colleges 

and universities, may represent a clear platform to get the involvement of the minority business community involved in research and 

development at the Federal Government. 

Of all of the federal labs that are associated with academic institutions, no federal lab is associated with a historically black college 

or minority institution in this country, and thus we are out of the 

cycle of the research and development that takes place that is driving the economy. 
33 

So I would suggest that the Committee and SBA take a very 

strong look at that issue and how we get that turned around. 

Mr. WILLIS. Mr. Cotton. 

Mr. COTTON. Yes. I have one thought that I think we want to 

add to the record and that is the fact that we need to start a dialogue on how we create a mechanism that teaches our small business communities how to access the market of the 21st century, 

which we know, is going to be increasingly a global marketplace. 

It is going to require a skill set which our small business community is demonstrating a woeful deficit in and that is the skill set 

or ability to use alliances, joint ventures, strategic partnerships to 

overcome regulatory, geographic barriers, cultural barriers. 

I think that we might want to talk at some point or add to the 

dialogue how we create a mechanism that is going to educate our 

small business community on preparing themselves to access the 

market of the 21st century. 

Mr. WILLIS. Ms. Gatling, I was about to call on you. 

Ms. GATLING. Yes. What I would like to say about that is that 

in corporate America, we have realized that there is a need to have 

more globalization with the suppliers. And one of the organizations 

that many of us belong to is the National Minority Supplier Development Council. 

One of the things that they have is a global link initiative where 

they have gone into other countries to duplicate the NMSDC 

model, and we found that that is working very well. 

As we embark on this solution, I think it is very very important 

that you bring corporate America to the table. We do have a Corporate Advisory Council that has been set up through the supplier 

business initiative that was started a couple of years ago with the 

Congressional Black Caucus Foundation. 

I would encourage you to tap into that. We will be happy to assist with bringing the right corporate partners to the table to get 

the solutions because you definitely need to have our input on that. 

Mr. COTTON. One last follow-on thought to this idea of preparing 

ourselves for the 21st century. One of the things that we also need 

to take a look at is that portion that the governments spend, that 

is exempt from the small business goaling requirements because it 

is that portion of the spending which would be a good incubator. 

It would be a good learning environment for our small business to 

acquire a globalization. 

Mr. WILLIS. Are you talking about those contracts below 

$100,000 or are you talking about overseas—— 

Ms. GATLING. Designated overseas. It is in our recommendations. 

Mr. COTTON. Designated oversees. 

Mr. WILLIS. I think I have one last question for Dr. Boston. I 

have one question for SBA. But, Dr. Boston, I will give you the last 

comment before that. 

Dr. BOSTON. I just wanted to emphasize. We have been talking 

about small businesses. There was a U.S. Commission on Small 

Business Innovation in 2005. That commission found that small 

businesses were three times more innovative than large businesses 

and their innovations had 13 times the impact as did the innovations of large businesses. 
34 

So small businesses really become the driving force of our economy as we go forward. Some of the figures that have been cited 

here in this panel indicate the growing importance of minority 

businesses among all small businesses. 

While we look at how many economists, and we look at changes 

that take place demographically in the workforce and do the projections to 2050, if you did those same kind of projections for the business sector, what you would find is the demographics of the small 

business sector are changing even more rapidly than in the workforce where minority business are becoming an increasingly important part of the health and vitality of the country. 

It really mandates that we focus on program strategies and policies that will be designed to create a more open, diverse society and 

a platform that all business owners can fulfill their potential. 

Mr. WILLIS. One of the issues that we have also heard a lot 

about, at least the Committee has, from small business owners is 

the lack of technical assistance from SBA’s side. They really have 

had a difficult time getting the kind of management training and 

those kind of things that are supposed to be part of the SBA’s 8(a) 

program, and generally, it would be nice to have all small businesses particularly minority small businesses. 

Section 4(b)(1) of the Small Business Act gives the Administrator 

the authority to appoint an Associate Administrator for minority 

small business and capital ownership development. 

According to the Act, the Associate Administrator shall be an employee of the agency but shall basically formulate and execute the 

8(a) program and the 7(j) program. 

Is that position currently filled? Have you ever heard of that position? 

Mr. JORDAN. Yes, it is currently filled. Joe Lodo is the Associate 

Administrator. 

Mr. WILLIS. We would love to hear more from him about what 

he is doing under your auspices to improve the 8(a) program. 

Mr. JORDAN. Yes, absolutely, and the 7(j) training program as 

well. As you know, the President’s budget included an increase in 

the 7(j) funding because we really do believe that effectively delivering the training and management technical assistance is vitally 

important to the true business development nature of the 8(a) program. 

Mr. WILLIS. That is good to hear. I mean we have had a number 

of complaints about the technical assistance part of the 8(a) program, that people really are receiving it. 

Ms. Burnell. 

Ms. BURNELL. Greg, to further what you were saying, part of the 

problem I see as an 8(a) business, those staff levels in the SBA offices, these people are working as hard as they possibly can. They 

have programs, but they just do not have the time or the people 

to get them out to us. 

We made note in the New Orleans office. I had a meeting with 

the SBA people before I came up here. In 1985 or 1986 there were 

over 100 people in the office. Today they have seven. 

Now they are being asked to do things with HUBZones and go 

out and do site visits and verify payrolls. All of these programs are 

great, but you need people to help implement them, not just put-
35 

ting them on paper and handing it to the SBA because those same 

seven people that we work with in New Orleans, cannot deliver all 

the products. 

So that is why you get complaints. Some of the programs are 

there. There is just nobody to implement them. 

Mr. WILLIS. In our budget we definitely have asked for increases, 

and we will continue to do that. 

Royalyn, and then I am going to turn to Karen and then we will 

close. 

Ms. REID. Mine is very quick. I just want to say in my area, in 

the Dallas-Fort Worth, Texas, area, we experienced the exact same 

problem that Ms. Burnell mentioned. 

Mr. ALFORD. In the field there is no SBA literally. In effect, I 

should say there is no SBA in the field. 

Ms. HONTZ. Since I get the last word, I really want to thank all 

of you for coming today and spending the time and for all of your 

preparation. I look forward to your submissions and additional suggestions for the record that we can study. 

We know the old problems. You have brought up some new problems. We would like some new solutions to these problems. 

Again thank you so much for your time. 

Mr. WILLIS. As a reminder, the record will be open for two 

weeks. Please submit any documents by then, by close of business 

on Thursday, October 8. 

Thank you for your participation. 

[Whereupon, at 11:58 a.m., the Committee was adjourned.] 

(37) 

APPENDIX MATERIAL SUBMITTED 
SBICPr;ogram 

Flnandng, hi M!oolitv.Qwned/w\bmen.Owned, and 

Piscal Y¢iI(2o¢r, ?008 and 2099 

repared: Oetobe[2,ZOW 

FiscaJYear Fiscal Year 2007 

Black-Owned 

Hispanic-Owned 

Native American.Owned 

Asia Pacific-OWned 

Subcontinent Asian-Owned 

Fiscal Year 2006 

Black-OWned 

Hispanic-Owned 

Nallve American-OWned 

Asia Pacific-Owned 

Subcontinent Asian-Ownad 

Fiscal Year 201)9 

Black-OWned 

Hispanic-Owned 

Native American-OWned 

Asia Pacific-OWned 

Subcontinent Asian-OW11ed 

Total FY 2007 to FY 2009 

Fisca/Year2007 Fiscal Year 2006 Fisca) Year 2009 

Total FY 2007 to FY 2009 

Fiscal Year 2007 

Fiscal Year 2008 

Fiscal Year 2000 

TotaJ FY 2007 to FY 2009 

--.- Number of Businesses Financed ____ < 

Minority-Owned li...Qt 

ill ". 40 

2 2. 

57 

m 

00 

30 

20 

71 

ill 

48 

33 

o 

20 

44 

2.057 

1,905 1,481 

= 

5.B 

1.' 

0.1 

1.4 

2.' 

ill 

5.0 

1 .• 

0.1 

1.0 

3.7 

!!.ll 

3.2 

2.2 

0.0 

1.4 

3.0 

._-- Number of Busimnuiss Financed --_ 

58 2,057 2.8 

54 1,005 2.B 

'" 1,481 2.' 

--- Number of Businesses Financed -_. 

2,057 0.2 

1,005 0,2 

1,481 0.5 

Dollar Amount of Financing ($ in millions) 

Minority·Owned 

Businesse.!; 

W.< 

$18.7 $33.7 

$1.1 $9.3 

$29.6 

12il 

$42.9 

$9.& $0.5 

$8" 

$31.4 

lli.1 

$10.5 

$1M 

$0,0 

$23.2 $17.4 

$254A 

$2,647.8 

$2,427.4 $1,856,1 

:sa,931,3 

Dollar Amount of Financing ($ in millions) 

Women-Owned "-'l 

II 

1.3 

M 

U 

1.1 

il 

u 

U 

M M 

1.3 

li 

M 

1.0 

M 

1.2 

M 

U 

$27.6 $2,647.8 1.0 

$31,7 $Z,4Z7.4 1.3 

i26.a $1,856,1 1.' 

$88.1 $6,931,3 12 

Dollar Amount of Financing ($ In million&;) 

$4.1 $2,847,8 0.2 $0.5 $2,427.4 0.0 

$6.7 $1,85Ei.1 0.4 

$11.3 $6,931.3 0.2 

•• -_._ .... - Number of F!nanclngs 

3,43B 

-

• W 

• 

n 

ill 3,372 

115 

5 

lli 2,697 

a 

m 9,507 

--------- Number of Financings 

Businesses SBIC Program 

77 3,438 84 3,372 

56 2.697 

217 9,507 

------.--- NumberofFlnanclngs 

3,438 

3,372 

13 2,697 

24 9,507 
39 

National Black Chamber of Commerce 

1350 Connecticut Avenue NW Suite 405, Washington DC 20036 

202-466-6888 202-466-4918fax m~,~i!2'!!~!~~!.",~[£l !!1!f!;!1!!'!l"'~!Q''!!'!!!~!:i!;.,9"!:9 

CONGRESSIONAL TESTIMONY 

September 24, 2009 

Presented To: 

Senate Small Business Committee 

Honorable Mary Landrieu, Chair 

Honorable Olympia Snowe, Ranking Minority Member 

Presented By: 

Harry C. Alford 

PresidenUCEO 
40 

Honorable Chair Landrieu and Ranking Member Snowe, the National Black Chamber of 

Commerce holds much gratitude that you have invited us to this hearing. As you know we are 

the largest Black business association in the world. We are nonpartisan, nonprofit with a mission 

to economically empower African American communities through entrepreneurship and good 

policy. The NBCC proudly represents the over I million small businesses that are Black owned. 

It is the fastest growing group per the US Census Bureau (45% growth over five years). We 

hope to begin making a significant milestone today. 

In regards to unemployment there are a few serious things the federal government can do. It can 

cease supporting discrimination through non enforcement of some significant laws and it can 

prevent serious negative impact from some upcoming programs. Without doing this the recovery 

act and any other major initiative will have little if not negative impact on minority communities, 

in particular, Black communities. 

Section 3 of the HUD Act (24 CFR part 135) became law in 1968 after the first Watts Riot. It 

was strengthened in 1992 after the Rodney King Riot. It is the Equal Opportunity Program 

involving HUD funds and is a great job creator and business developing tool. Under this law up 

to 30% of all new jobs created through HUD Funding are to go to people living in public housing 

facilities and others who live under the poverty level. They are considered Section 3 residents. 

Businesses who hire Section 3 residents are considered Section 3 businesses and are entitled to 

10% of all contracts funded through HUD monies. This is a beautiful law and where we have 

applied it great results occurred. However, of the more than 5,000 HUD grantees less than I 

percent actually complies with the law. Less than a half of one percent actually even bother to 

send in their annual reports. 

On the job training of minorities and women is anathema to construction unions and they have 

fought this fiercely. HUD does not enforce Section 3. They have never fined, banned nor held 

funds to any of the thousands of recalcitrant grantees. HUD has relented to the construction 

unions that discriminate freely against people of color and women. If Section 3 was enforced it 

would bring over 100,000 new jobs to African Americans alone each and every year. We need 

enforcement of Section 3. 

Another big opportunity to ease the unemployment in minority communities is that of the 

Federal Highway Administration. The Disadvantaged Business Enterprise (DBE, 49 CFR part 

26) is the enforcement mechanism for Title VI of the Civil Rights Act of 1964. It is to ensure 

against discrimination within the contract letting by divisions of US DOT. In the beginning, 

1982, minority contractors were doing well in business development and volume increases. 

Now, despite significant growth by all ethnicities in construction capacity the volume of business 

done through our state departments of transportation via USDOT funding has been dropping 

since the middle of the Clinton Administration. Today it is almost nonexistent. Black contractors 

do no more than 1.1 % of the volume while Hispanic contractors barely reach 1.6%. (A state by 

state breakdown of Black contracting is attached). That is 28% of the national population only 
41 

participating in 2.7% of a major federal program. This is clear disparate impact and it directly 

affects employment activity within the minority communities. This year with recovery dollars, 

the Federal Highway Administration will be funded by more than $54 billion. It's too bad that 

Blacks and Hispanics will have very little participation in the relief. There might as well be a 

sign saying "No Coloreds Allowed" as I remember visiting Louisiana in my early years. But this 

time it is not local governments doing it but the federal government. 

Construction union shops that monopolize these highway contracts do not adequately employ 

minorities or women. In fact, they do not even comply with Executive Order 11246 (John F. 

Kennedy). State departments of transportation do not comply with Executive Order 11246 nor 

enforce it with their prime and subcontractors. In fact, in February, 1999, the Federal Highway 

Administration canceled Executive Order 11246. A copy of that cancellation is attached. Since 

then state departments and local contractors have become basically white male organizations. 

Dr. Martin Luther King and all of those other greats who gave their lives for equal opportunity 

have been betrayed. 

If Title VI of the Civil Rights Act and Executive Order 11246 which ensures Title VII of the 

Civil Rights Act were enforced it would amount to 500,000 new jobs for African Americans 

each and every year. That would certainly address the "double the national average" 

unemployment Blacks, Hispanics and other minorities suffer. The above two programs (Federal 

Highways and Section 3) if implemented and enforced via the intent of Congress would bring 

600,000 new jobs to the Black community each year. Should Congress hold itself responsible 

for doing this? 

Those are the laws written decades ago. Now let's go to potentially lethal initiatives (job killers). 

It was a proud moment when President George W. Bush announced his executive order to ban 

Project Labor Agreements (PLA's) on federally funded projects. PLA's make a project basically 

union only or at least abide by union agreements. President Bush stated, "I cannot support 

Project Labor Agreements as they discriminate against small business and minorities." He was 

absolutely correct. 98% of Black owned contracting firms are not union. They are not 

welcomed nor would unions allow their employees into their trades. The only Black presence in 

union crafts is cement and general laborer. Everything else is practically exclusive to white 

males. If President Bush is correct then what is the rationale for President Barack Obama to 

cancel his executive order and reinstate Project Labor Agreements via his recent executive order. 

Construction unions by nature of their employment roles cannot comply with Executive Order 

11246. What is about to happen is Presidential endorsed discrimination. It is damaging, anti civil 

rights and human rights and definitely voids out the Civil Rights Act of 1964. I beg Congress to 

prevent this until construction unions integrate. They have had 45 years to integrate and still 

refuse. They should be banned rather than rewarded exclusivity for racist and sexist hiring 

patterns. They usually fool local officials with pre-apprentice training programs but they never 

lead to job placement - never. 
42 

The next potential negative initiative is the Waxman/Markey Bill which is headed for the Senate. 

Our study done by Charles River Associates has been accepted by many prestigious 

organizations. In that study, it clearly shows that certain geography will suffer the greatest 

impact from losing the estimated 3.3 million jobs as a result of this bill being enacted. Attached 

is a map showing a 700 mile radius around Nashville, Tennessee. This area accounts for 86% of 

the national Black population. As you will see the greatest job loss would land into this area. 

We pray that this bill is killed and we can start over with a responsible bill that doesn't target 

specific groups for pain. 

In essence, we are most concerned about activity that feeds unemployment and will sustain it and 

activity that will, in fact, increase unemployment in Black and other minority communities. It 

doesn't have to be that way. The "ball" is in your court. Let's enforce the good laws and 

prevent the bad ones from exacting their dirty deeds. 

In regards to foreclosures we can enhance employment by attending to the above. Increasing 

employment would directly affect peoples' ability to pay their mortgages. There isn't much we 

can actually do but let the market take its course. Hopefully, we won't go down that avarice road 

of sub-prime mortgages again and reign in renegade investors. Banks have been bailed out for 

the most part but the individual mortgage holders have to feel the pain and take their losses. 

We are interested in the billions of dollars HUD has allotted under its Housing Stabilization 

Program. It is designed to provide technical assistance to citizens who have or are seeking 

mortgages. Where is this money going? Is it effective? We are having trouble identifying it at 

the street level. We are suspicious and ask for a thorough audit by Congress. Another question 

is: Why are many realtors and developers refusing FHA backed mortgages now? What can we 

do to make them more attractive to lenders? 

Finally, we should manage the Community Reinvestment Act a lot better. We shouldn't let it be 

used to gentrify Black communities. Greedy investors and institutions use the CRA credit 

process to quickly move and renovate a stable community. By doing so they drive up property 

values to the point that stable residents can no longer afford their homes and properties via 

increased property taxes, rent, etc. They are pushed out with the assistance of housing 

authorities who provide Section 8 rental vouchers to the residents provided that they move 

clearly out of their neighborhoods. Victims have been transplanted from Washington, DC to 

Hagerstown, MD; from Chicago to Danville, IL, etc. As opposed to empowering a community 

they transform it and orchestrate complete gentrification. The very people we are supposed to be 

helping become worse off than ever. 

Once again, thank you for this great opportunity. We hope we have provided information that 

can be helpful in your leadership. Please don't hesitate to seek more information from us or to 

ask for more data. 
How does this effect African American Communities?: Due to their Geographic proximity, 

AA Communities will lose a larger percentage of Household income. 

Fig .. ", 3.10, Proj<>Ct"d regionai d'$tributi"n 01 elmn!!,," '0 2Q3(l oou""hold purch.sing pow", 

d"" lQ AC ESA •• tatOO in j<l""S of 2010 ,n""me level .. 

Source.' eRA Model Resuirs. 2009 
First Hall of Second Half 

2008 Fiscal of 2008 Black Total Percentage of Bl

State Year Fiscal Year Contracts Contracts Participation 

Number of Number of Total Dollar Total Dollar 

Contracts DolJarValue Contracts DollarVa!ue Value Value 

AL 18 $1,580,413 27 $3,607,291 $5,187,704 $390,456,454 AK 0 $0 0 $0 $0 $200,582,736 

AZ 0 $0 0 $0 $0 $515,487,918 

AR 23 $3,380,063 42 $5,687,211 $9,067,274 $279,764,747 

CA 12 $2,256,905 5 $910,516 $3,167,421 $2,303,616,727 CO 3 $49,811 3 $282,500 $332,311 $174,452,186 CT 8 $1,852,394 14 $1,781,051 $3,633,445 $550,514,942 

DE 5 $84,737 5 $525,785 $610,522 $67,600,111 

DC 6 $3,441,955 10 $8,254,448 $11,696,403 $78,058,538 

Fl 10 $340,988 31 $4,660,737 $5,001,725 $868,564,488 

GA 63 $8,142,042 42 $3,350,652 $11,492,694 $322,093,516 

HI 0 $0 0 $0 $0 $22,082,644 

10 0 $0 0 $0 $0 $224,961,344 

IL 51 $3,656,428 99 $7,961,589 $11,618,017 $793,976,836 IN 75 $2,623,315 44 $2,558,597 $5,181,912 $701,324,924 IA 6 $395,418 11 $743,149 $1,138,567 $636,106,399 

KS 14 $972,679 25 $1,258,462 $2,231,141 $293,638,590 
Second Half 

First Half of of 

2008 Fiscal 2008 Fiscal Black Total I Percentage of B

State I Ve., Vear Contracts Contracts Participation 

Number of Number of Total Dollar Total Dollar 

Contracts Dollar Value Contracts Dollar Value Value Value 

KY 2 82,503 10 $3,448,243 $3,530,746 $502,568,300 

LA 42 $4,886,175 76 $8,732,717 $13,618,892 $485,674,287 

ME 0 $0 1 $1,000 $1,000 $173,601,541 MD 46 $5,004,888 70 $9,673,803 $14,678,691 $444,230,492 

MA 13 $2,074,984 15 $3,419,124 $5,494,108 $519,556,933 

MI 125 $7,715,832 182 $11,618,026 $19,333,858 $1,840,730,378 

MN 2 $112,910 5 $544,078 $656,988 $290,801,443 

MS 5 $610,499 4 $671,633 $1,282,132 $418,478,250 

MO 58 $9,093,969 19 $9,559,253 $18,653,222 $2,379,557,734 MT $0 0 $0 $0 $273,847,429 

NE 21 $1,435,692 40 $1,696,656 $3,132,348 $188,231,557 NV 0 $0 0 $0 $0 $188,938,520 NH 0 $0 1 $4,590 $4,590 $82,562,529 NJ 4 $564,231 6 $18,300,401 $18,864,632 $462,860,033 NM 0 $0 0 $0 $0 $303,555,539 

NY 12 $2,157,498 21 $3,252,055 $5.409,553 $1,126,205,810 NC 50 $2.400,572 100 $5,758,109 $8,158,681 $9'19,538,701 
FI",j Half 01 Second Half 

I 2008 Fiscal of 2008 Black Total St.t" I Year Fiscal Year Contracts Contracts 

Number-of Number of 

Contracts Oo!!arVa!ue Contracts Dollar Value T ota! Dollar Value Total Dollar Value 

ND 0 ° 0 ° 0 336,225,800 OH 80 8,612,987 90 13,515,024 22,128,011 1,013,409,541 

OK 1 10,400 3 303,412 313,812 829,274,079 OR 0 0 0 0 0 196,538,276 

PA 53 3,695,960 0 0 3,695,960 785,969,030 

PR 0 0 0 0 0 113,662,391 

RI 7 3,822,925 11 3,890,486 7,713,411 111,130,177 

SC 36 2,653,411 35 2,200,029 4,853,440 279,418,134 

SD 3 40,691 4 53,170 93,861 344,410,866 

TN 26 5,163,370 26 39,744,459 44,907,829 995,290,878 TX 76 12,351,512 59 8,928,131 21,279,643 1,984,081,620 

UT 1 246,409 2 996,931 1,243,340 290,604,877 I 

VT 0 0 0 0 0 149,857,008 

VA 13 4,548,063 15 2,315,636 6,863,699 507,768,963 

WA 8 457,255 19 984,451 1,441,706 539,438,642 I WI! 8 1,368,422 12 3,803,444 5,171,866 525,674,026 

WI 99 4,746,588 155 9,920,762 14,667,350 566,180,165 I WY 0 0 0 0 0 399,659,591 
47 
48 

FHW A Order 4710.8 - Clarification of Federal Highway Administration (FHW A) and Sta... Page I of 2 

U.S. Department 

of Transportation 

Federal Highway 

Administration 

Par.l. Purpose 

2. Background 

3. Applicability 

Order 

Subject 

CLARIFICATION OF FEDERAL HIGHWAY ADMINISTRATION (FHWA) 

AND STATE RESPONSIBILITIES UNDER EXECUTIVE ORDER 11246 

AND DEPARTMENT OF LABOR (DOL) REGULATIONS IN 41 CFR 

CHAPTER 60 

Classification Code 

4710.8 

Date 

February 1, 1999 

4. Authority and Responsibilities 

5. Cancellation 

1. PURPOSE. To define FHWA's authority and responsibility concerning Executive Order (EO) 11246, as 

amended, and DOL regulations, set forth in 41 CFR Chapter 60. 

2. BACKGROUND. Under EO 11246, "Equal Employment Opportunity," the FHWA is required to include 

certain nondiscrimination and equal employment opportunity provisions in direct Federal contracts and 

federally assisted construction contracts. The provisions have been established by the DOL. Office of 

Federal Contract Compliance Programs (OFCCP) and are set forth in 41 CFR Part 60-1, "Obligations of 

Contractors and Subcontractors." and 41 CFR Part 60-4, "Construction Contractors Affirmative Action 

Requirements." 

3. APPLICABILITY. This Order applies to all direct Federal contracts and federally assisted construction 

contracts and subcontracts. 

4. AUTHORITY AND RESPONSIBILITIES 

a. Department of Labor: Under Section 303 of EO 11246. only the DOL has the authority to determine 

compliance with EO 11246 and its implementing regulations. The FHWA and the State highway 

agency do not have independent authority to determine compliance with EO 11246,41 CFR 

Chapter 60. or the minority and female participation goals established by OFCCP, pursuant to 41 

CFR Chapter 60. 

b. State highway agencies and FHWA: 

(1) The State highway agency and FHWA have responsibility to ensure that reCipients of Federal-aid 

funds include the required contractual language relating to equal employment opportunity, as set 

forth in 41 CFR Parts 60-1 and 60-4, either explicitly or by reference. 

(2) The State highway agency and the FHWA have the authority and the responsibility to ensure 

compliance with 23 USC Section 140 and Title VI of the Civil Rights Act of 1964, as amended, and 

related regulations. including 49 CFR Parts 21 and 23, and 23 CFR Parts 200, 230, and 633. 

Pursuant to this authority, the State highway agency and the FHWA may conduct compliance 

reviews of contractors on federally funded highway projects to determine compliance with these 

laws and related regulations. State highway agencies shall prepare complete, written reports of 

findings of the compliance reviews. These reports, and the evidence on which they are based, shall 

be available for FHWA analysis. 

mhtml:tile:IIC:\Documents and Settingsljedwards.NATIONALBCC\Local Settings\Tempo... 9/23/2009 
49 

FHWA Order 4710.8 - Clarification of Federal Highway Administration (FHWA) and Sta ... Page 2 of2 

(3) If the State highway agency or the FHWA becomes aware of any possible violations of EO 

11246 or 41 CFR Chapter 60, each has the authority and the responsibility to notify the OFCCP. 

(4) The FHWA and the State highway agency shall not make any determinations regarding 

compliance with EO 11246 or 41 CFR Chapter 60. 

5. CANCELLATION. The FHWA Form 86, Compliance Data Report, is hereby canceled. 

Original signed by: 

Kenneth R. Wykle 

Federal Highway Administrator 

Related Sites: 

Leadership Conference on Civil Rights - The Executive Order on Affirmative Action (EO. 11246): One of Our 

Nation's Most Successful Civil Rights Programs 

FHWA Home I Directives I Orders I Feedback 

OFHWA United States Department of Transportation ¥ Federal Highway Administration 

mhtml:file:IIC:\Documents and Settings\jedwards.NA nONALBCC\Local SettingsITempo... 9/23/2009 
50 

l'arrcn J. Mitchell 

Founder and Chairman 

Anthony W. Robinson 

President 

of W. I'resident 

.~"~.1',, Business Legal Defense and Educational Fund 

Before the United States Senate Committee 

on Small Business and 

Washington, DC 

2009 

1100 Mercantile lane Suite 115·A 20774 
51 

Testimony of Anthony W. Robinson, President 

Minority Business Legal Defense and Educational Fund 

Before the United States Senate Committee on Small Business And 

Entrepreneurship 

Washington, DC 

2 
52 

Testimony of Anthony W. Robinson 

9/24/09 

Good morning Madam Chairwoman and members of the Committee on Small 

Business and Entrepreneurship. My name is Anthony W. Robinson, and I am president 

of the Minority Business Enterprise Legal Defense and Educational Fund, affectionately 

referred to as MBELDEF. MBELDEF was founded and established in 1980 by the late 

former Maryland Congressman Parren J. Mitchell to act as a national advocate and legal 

representative for the minority business community. The organization has monitored 

barriers to minority business formation and development. We serve as a national 

advocate and legal representative for minority business enterprises (MBEs) by promoting 

policies affecting equitable and full participation of minority enterprises in the 

mainstream marketplace. We work with businesses in every sector of the American 

economy and we work with businesses in every comer of the country. We seek to 

advocate on behalf of firm owners from alI historically underutilized minority groups. 

We attempt to provide non-partisan opinions on matters affecting minority firms and 

small businesses in general. 

MBELDEF is a member of the Unity Group, which was established in March 

2009, and is a new and growing coalition of minority business groups, women business 

groups and civil rights groups dedicated to supporting, defending, strengthening and 

expanding federal programs intended to eliminate discrimination against minority and 

women business owners. This coalition represents tens of thousands of minority- and 

women-owned businesses. We also represent many committed and forward-looking 

majority businesses dedicated to the elimination of business discrimination. We are 

committed to ending discrimination so that we can harness all of our nation's ingenuity, 

creativity and diversity to grow our economy to its fullest potential. On behalf of both 

MBELDEF and the Unity Group, we appreciate the Committee providing us this 

opportunity to come before you to represent the tens of thousands minority and small 

entrepreneurs who continue to rely on the federal marketplace as their primary source of 

income. 

As you may be aware, since the federal government's first efforts to level the 

playing field on behalf of the minority business community in the 1970s, there has been 

substantial progress. I should note that assisting minority businesses has always been a 

bi-partisan effort. In fact, in the 1970s, President Nixon was instrumental in promoting 

equal opportunity for minority businesses. And Assistant Secretary of Labor Arthur 

Fletcher worked closely with Senator Ed Brookes and Congressman Mitchell to pass the 

earliest minority business legislation. Minority firms have grown quantitatively and 

qualitatively. However, as Dr. Wainwright, a noted expert in this area recently testified 

before the House Committee on Transportation and Infrastructure, the percentages of 

minority owned businesses compared to each minority group's population are 

disproportional. For example, Dr. Wainwright has noted that although African 

Americans constitute 12.7 percent of the U.S. population, they make up only 5.3 percent 

3 
53 

of U.S. businesses, and earn only 1.0 percent of sales and receipts. l Latinos represent 

13.4 percent of the population, account for only 7.0 percent of the businesses, and earn 

only 2.5 percent of sales and receipts? Asians and Pacific Islanders make up 5.0 percent 

of the business population, yet earned only 3.8 percent of sales and receipts. Native 

Americans represent only 0.9 percent of all businesses, but earned only 0.3 percent of 

sales and receipts.3 Lastly, women earn only 10.7 percent of sales and receipts, although 

they make up 28.9 percent of U.S. businesses and represent 50.9 percent of the 

population.4 

Even though minority firms exist, they are not given the same opportunity to 

succeed as non-minority firms. Capital and credit access, the fuel driving our market 

oriented economy, as we have painfully learned from this recent depression, continues to 

be evasive for the minority and woman entrepreneur. Again, Dr. Wainwright's work in 

this area is illuminating. For example, in recent testimony he noted: 

When minority-owned firms did apply for a loan, their loan requests were 

substantially more likely to be denied than non-minorities, even when 

differences like firm size and credit history are accounted for. 5 The loan 

application denial rate for African-American-owned businesses is 44.3 

percentage points higher than that for White male-owned firms.6 Denial 

rates were 18-24 percentage points higher for Hispanic or Latino-owned 

firms and 5-9 percentage points higher for nonminority female-owned 

firms than for their nonminority male-owned counterparts. Significant 

loan denial disparities were also observed for Native American-owned 

firms in some cases (18-19 percentage points higher).7Furthermore, when 

minority-owned firms did receive a loan, they were obligated to pay 

higher interest rates on the loans than was true of comparable 

nonminority-owned firms.8 African-Americans pay approximately 1.7 

percentage points more, on average, for their business credit than do 

nonminority males, declining slightly to 1.5 percentage points when 

1Testimony Concerning the Challenges Faced by Disadvantaged Business Enterprises in the Transportation 

Sector, Testimony of Dr. Jon S. Wainwright available at 

http://Transportation.house.govfMediaffilefFu II %20Committeef200903 26fW ainwright.pdf (2009). 

2 [d. 

3 [d. 

4 Id. 

5 Testimony Concerning the Challenges Faced by Disadvantaged Business Enterprises in the 

Transportation Sector, Testimony of Dr. Jon S. Wainwright available at 

http://Transportation.house.govfMediaffilefFull%20Committee/20090326fWainwright.pdf (2009). 

6Discrimination Facing Small Minority-Owned and Women- Owned Businesses in Commercial Credit 

Markets 

Testimony of Jon S. Wainwright, Ph.D., available at http://sbc.senate.govfhearings/testimonyl080911-

Wainwright-testimony.pdf (2008). 

, Testimony Concerning the Challenges Faced by Disadvantaged Business Enterprises in the 

Transportation Sector, Testimony of Dr. Jon S. Wainwright available at 

http://transportation.house.gov fMediaifilefFull%20Committeef200903 26fW ainwri ght. pdf (2009). 

, [d. 

4 
54 

creditworthiness and other firm and owner controls are taken into 

account. 9 

Researchers have also shown that banks pay attention to different characteristics 

when they evaluate the loan applications of women and minority-owned businesses when 

compared with male and white-owned firms. 10 There exist asymmetries in a sense that 

banks treat women and minority-owned firms less favorably than male and white-owned 

firms. For example, a credit score of 2 would increase the probability of loan denial for 

both women and men, but it increases the probability more for women (by 3.2%) than 

men (by 0.1%).11 Credit rationing is found to have a discouraging effect on a minority 

and women owner's probability of applying for a loan for the lowest 10th percentile of 

women-owned firms and highest 10th percentile of minority-owned firms. 12 

In addition, there is a good deal of evidence that the under-representation of 

women and minorities in construction especially is due to widespread and pervasive 

discrimination that has changed little over time. Not only is the proportion of firms 

owned by African Americans especially relatively low, so also are their representation in 

the construction workforce in general and in self-employment in particular. Where firms 

owned by minorities and women do exist in construction they are more likely than nonminority males to be in special trades rather than heavy and civil. 13 They are also more 

likely to be sub-contractors than prime contractors. 14 This does not appear to be because 

of a lack of an ability to expand to undertake these activities because it is research has 

made clear that small construction companies can expand rapidly as demand changes by 

hiring workers and renting equipment and making use of sub-contractors. 15 A particular 

concern in construction is that it is hard for minority and women-owned firms to obtain 

capital, especially working capital, and this causes increased difficulties when bonds have 

to be posted. 16 This is often made more difficult still when bonding firms are members of 

local construction associations.17 Also unions are pervasive in the sector and these 

unions have tended to be dominated by white males and have successfully controlled 

entry to craft jobs (Ashenfelter, 1972).18 

9Testimony Concerning the Challenges Faced by Disadvantaged Business Enterprises in the Transportation 

Sector, Testimony of Dr. Jon S. Wainwright available at 

http://transportation.house.gov/Media/fiIe/Full%20Committee/20090326/Wainwright.pdf(2009). 

10 Naranchimeg Mijid, Dissertation Abstract: Gender, Race and Credit Rationing of Small Businesses: 

Empirical Evidence from the 2003 Survey of Small Business Finances (2009), available at 

http://www.kauffman.orgjuploadedFileslResearchAndPolicylEmergingScholarslKDFP/mijidnaranchimeg.pdf. 

11 Id. 

12 Id. 

Il David G. Blanchflower & Jon Wainwright, An Analysis of the Impact of Affirmation Action Programs 

on Self-Employment in the Construction Industry (2005), available at http://www.nber.orgjpapers/wI1793. 

14Id. 

15 Id. 

16 Id. 

17 Id. 

18 Id. 

5 
55 

I would like to give you some examples of real business owners who have 

confronted discrimination. It is critical that the Committee understand how very difficult 

it is for these businesspersons to come forward and share their experiences. By coming 

forward, they are putting their businesses in jeopardy of being blackballed and frozen out 

of future business opportunities with larger companies that dominate their market or 

industry. I hope that you all will carefully consider the sort of courage and commitment 

to justice required to take those kinds of risks. I will submit letters and emails providing 

details of these entrepreneurs' stories for the record, but in the interest of time, I will 

provide only a short synopsis of the difficulties they have experienced. And Mr. 

Chairman, I would like to ask permission to submit a number of supporting documents 

for the record after the hearing. 

• Charles Richardson is an African American engineer with more than 30 years of 

experience. His practice has included leadership and supervisory positions in an array 

of construction projects, including fossil-fuel and nuclear power plants, commercial 

and institutional buildings, schools, roads, bridges, and facilities for the U.S. armed 

forces. In addition, his firm, High Plains Technical Services, Inc., is the only African 

American-owned firm certified to do bridge and roadwork for the Oklahoma 

Department of Transportation. Despite Mr. Richardson's depth of experience, his firm 

has encountered substantial obstacles that impede the growth of his business, 

including slow and no pay practices. For instance, for four years, Mr. Richardson's 

firm has not been paid $108,000 for work on a contract for the Oklahoma University 

System. Payment to his firm has been withheld, even though the State's contract audit 

department agreed the contract and invoice instruments were valid. Moreover, the 

legal counsel of the University system stated, on more than one occasion, that there 

was no objection to the merits of the claim for payment. Currently, Mr. Richardson is 

petitioning the state legislature to seek relief. 

• Donald Greaves is an African American owner of a physical and life science research 

and development company. He has worked in energy commodities for 20 years. His 

two business partners have extensive experience in this field: one having negotiated a 

deal with the Vietnamese government for offshore drilling, the other owning and 

operating his own commodities trading firm in the World Trade Center. Mr. Greaves 

sought a loan from JP Morgan Chase to purchase an oil refinery. In applying for the 

loan, Mr. Greaves communicated to the bank that he had collateral for the loan from 

independent investors and that he had a letter of intent from Texaco to purchase one 

million tons of diesel fuel upon his acquisition of the refinery. JP Morgan Chase 

denied his application. The bank's grounds for denial were that it did not find the 

company's name in the business registry or any databases. However, Mr. Greaves' 

company was legally registered in the state of Wyoming when he applied for the loan. 

When Mr. Greaves brought up the history of discrimination against minority owned 

businesses to Mr. Nicholas, the bank's Vice President, he responded by stating that he 

would not "put history on the shoulders" of his ban1e 

Prior to JP Morgan Chase notifying Mr. Greaves of the denial of his loan application, 

a representative of the oil refinery contacted Mr. Greaves to tell him that the bank had 

6 
56 

already told the refinery's representatives that it was denying Mr. Greaves' loan 

application. By doing so, JP Morgan inappropriately, and possibly unlawfully 

interfered with the business relationship between Mr. Greaves' company and the oil 

refinery. Subsequently, Mr. Greaves discovered that JP Morgan Chase loaned the 

same amount of funds that he had requested to a large, non-minority owned company 

that ultimately purchased the oil refinery. Unlike Mr. Greaves' company, this 

company offered no collateral to secure the loan. For its actions related to this matter, 

Mr. Greaves filed suit against JP Morgan Chase for fraudulent concealment and 

tortuous interference with a business relationship, and the case is currently pending in 

the U.S. Court of Appeals for the Second Circuit. 

• The Oklahoma Department of Transportation (ODOT) has continued to use a 

selection and contract awarding system that has passively participated in the 

discrimination existing in Oklahoma's architectural, engineering and construction 

markets. ODOT's selection committees and contracting boards are predominantly 

comprised of non-minorities. Without a diverse selection committee, it is unlikely that 

ODOT contracts will be awarded to minority business owners. Further, ODOT works 

with the Oklahoma Chapter of the Association of General Contractors (AGC) to 

determine utilization goals for Disadvantaged Business Enterprises (DBEs) The AGC, 

however has supported and offered resources to initiatives abolishing affirmative 

action in local, state, and federal contracting over the past 20 years. ODOT does not 

work with any minority owned business associations to determine DBE utilization 

goals. 

Also, ODOT's Minority Business utilization Goals and Attainment for the past three 

fiscal years have not counteracted marketplace discrimination. African Americans 

received none of the contracts ODOT awarded from 2006 to 2008. ODOT's Goal 

Setting and Attainment reports group all DBEs together instead of separating DBEs by 

racial or ethnic minority affiliation. Because of the grouping of all DBEs, it is not 

apparent in these reports that ODOT has not contracted with an African American 

owned business for the past three fiscal years.19 

• Fish & Fisher is a black-owned general contracting company in Jackson, Mississippi. 

The company worked on a new Nissan plant in Canton, Mississippi, and helped 

expand the Jackson-Evers International Airport. Despite its work on those significant 

projects, Fish & Fisher was not included in the bidding process when contracts were 

awarded for the construction of a new Toyota plant in Blue Springs, Mississippi in 

2007. Only five companies were invited to bid on the project, and Fish & Fisher was 

relegated to work as a subcontractor on the job. Even when the state of Mississippi 

had allocated $300 million in incentives to bring the plant to Mississippi, only certain 

companies with special ties were among the five companies allowed to bid. In an 

19 Complaint Letter from the Oklahoma Legislative Black Caucus to Ray La Hood, Secretary, Department 

of Transportation (Feb. 17, 2009). 

7 
57 

effort to obtain a remedy, Fish & Fisher filed a federal lawsuit to challenge the private 

bidding process that occurred for the Toyota job. 

• Stanley Tucker is an African-American male who is the Managing Partner of MMG 

Ventures, LP, a Minority Enterprise Small Business Investment Company, and also 

serves as the Director of the Maryland State Small Business Financing and 

Development Authority. He has over 15 years of experience as a private equity 

financier. He has raised capital from public and private sources, sat on the board of 

minority managed banking institutions, planned and strategized venture capital exits, 

and conducted the entire activities and duties attendant to managing a venture capital 

firm. Mr. Tucker applied for a Participating Securities license and leverage from the 

Small Business Administration (SBA) over a period of several years, but the SBA 

never granted this license. Because of the SBA's repeated failure to approve his 

requests, Mr. Tucker's firm could not be licensed. This neglect discouraged Mr. 

Tucker from applying for any additional leverage from the SBA. Undercapitalizing 

the community of MBEs that he serves. 

• Anna Peay is the Minority Business Enterprise ("MBE") Coordinator for Advance 

Tactics Security, Inc. ("Advance Tactics"), a locally owned and operated MBE located 

in Indianapolis, Indiana. The company is about 70 percent minority. Advance Tactics 

is a certified minority vendor by the City of Indianapolis, the State of Indiana, and the 

Indiana Minority Supplier Development Council, ("IBDC/IMSDC"). The company 

provides security service personnel, both armed and unarmed guards, off duty police 

officers, traffic directors, parking lot attendants, flag men, and lobby customer service 

representatives to many companies in the greater Indianapolis area. 

Although Advance Tactics operates a qualified security business, the company has 

faced discrimination from other companies and has been left without a remedy. In 

one instance, Advance Tactics agreed to become the subcontractor of Securatec for a 

security project offered by the city of Indianapolis. Securatec is a Women Business 

Enterprise based out of Chicago. In its bid, Securatec promised the city of 

Indianapolis and Advance Tactics that it would give Advance Tactics 15 percent of 

its contract business. This 15 percent is a city guideline to help disadvantaged 

minority businesses receive work. However, once Securatec won the bid, it only 

hired one of Advance Tactics' employees. With this employment, Advance Tactics 

only received about I percent of the project money promised to the company. 

Ms. Peay complained to the city of Indianapolis about Securatec's decision to use 

Advance Tactics to receive the bid from city and then withhold the promised work. 

The city of Indianapolis told Ms. Peay that she had to resolve this problem with 

Securatec. When Ms. Peay tried to speak with Securatec, the company decided to 

complain about Advance Tactics sole employed employee. Then the company 

subsequently fired that worker and hired him as their own employee. Secuartec 

refuses to hire any other Advance Tactics employee for the remainder of this 3-year 

contract. Thus, when Ms. Peay sought to resolve this issue amicably and talk to the 

city about a breach of its project guidelines, Ms. Peay was ignored. 

8 
58 

Parrcn J. Mitchell 

Founder and Chairman 

Anthony W. Robinson 

President 

MilWl'ity Business Enluprise legal o.rn:nse and E~ation fund, Inc, 

www.mbeldef.org 

Testimony of Anthony W. Robinson, President 

Minority Business Legal Defense and Educational Fund 

Before the United States Senate Committee 

on Small Business and Entrepreneurship 

1100 Mercantile Lane 

Washington, DC 

May 22, 2007 

Suite 115-A Largo, Maryland 20774 
59 

Testimony of Anthony W. Robinson, President 

Minority Business Legal Defense and Educational Fund 

Before the United States Senate Committee on Small Business And 

Entrepreneurship 

Washington, DC 

Good morning Mr. Chairman and members of the Committee on Small Business 

and Entrepreneurship. My name is Anthony W. Robinson, and I am president of the 

Minority Business Enterprise Legal Defense and Educational Fund, affectionately 

referred to as MBELDEF. MBELDEF was founded and established in 1980 by the late 

former Maryland Congressman Parren J. Mitchell to act as a national advocate and legal 

representative for the minority business community. The organization has monitored 

barriers to minority business formation and development. We serve as a national 

advocate and legal representative for minority business enterprises (MBEs) by promoting 

policies affecting equitable and full participation of minority enterprises in the 

mainstream marketplace. We work with businesscs in every sector of the American 

economy and we work with businesses in every comer of the country. We seek to 

advocate on behalf of firm owners from all disadvantaged minority groups. We attempt 

to provide non-partisan opinions on matters affecting minority firms and small businesses 

in general. 

MBELDEF is a member of the Unity Group, which was established in March 

2009, and is a new and growing coalition of minority business groups, women business 

groups and civil rights groups dedicated to supporting, defending, strengthening and 

expanding federal programs intended to eliminate discrimination against minority and 

women business owners. This coalition represents tens of thousands of minority- and 

women-owned businesses. We also represent many committed and forward-looking 

majority busincsses dedicated to the elimination of business discrimination. We are 

committed to ending discrimination so that we can harness all of our nation's ingenuity, 

creativity and diversity to grow our economy to its fullest potential. On behalf of both 

MBELDEF and the Unity Group, we appreciate the Committee providing us this 

opportunity to come before you to represent the tens of thousands minority and small 

entrepreneurs who continue to rely on the federal marketplace as their primary source of 

income. 

As you may be aware, since the federal government's first efforts to level the 

playing field on behalf of the minority business community in the 1970s, there has been 

substantial progress. I should not that assisting minority businesses has always been a bipartisan effort. In fact, in the 1970s, President Nixon was instrumental in promoting 

equal opportunity for minority businesses. And Assistant Secretary of Labor Arthur 

Fletcher worked closely with Senator Ed Brookes and Congressman Mitchell to pass the 

earliest minority business legislation. Minority firms have grown quantitatively and 

qualitatively. However, the percentages of minority owned businesses compared to each 

minority group's population are disproportional. For example, although African 

2 
60 

Americans comprised 12.7 percent of the U.S. population, they accounted for only 5.3 

percent of its businesses, and earned only 1.0 percent of sales and receipts. I Latinos 

represent13.4 percent of the population, account for only 7.0 percent of the businesses, 

and earn only 2.5 percent of sales and receipts? Asians and Pacific Islanders make up 

5.0 percent of the business population, yet earned only 3.8 percent of sales and receipts. 

Native Americans represent only 0.9 percent of all businesses, but earned only 0.3 

percent of sales and receipts.3 Lastly, women comprise of 50.9 percent of the population, 

and accounted for only 28.9 percent of the businesses, and earn only 10.7 percent of sales 

and receipts.4 

Even though minority firms exist, they are not given the same opportunity to 

succeed as non-minority firms. Capital and credit access, the fuel driving our market 

oriented economy, as we have painfully learned from this recent depression, continues to 

be evasive for the minority and woman entrepreneur. For example, when minorityowned firms did apply for a loan, their loan requests were substantially more likely to be 

denied than non-minorities, even when differences like firm size and credit history are 

accounted for. 5 The loan application denial rate for African-American-owned businesses 

is 44.3 percentage points higher than that for White male-owned firms.6 Denial rates 

were 18-24 percentage points higher for Hispanic or Latino-owned firms and 5-9 

percentage points higher for nonminority female-owncd firms than for their nonminority 

male-owned counterparts. Significant loan denial disparities were also observed for 

Native American-owned firms in some cases (18-19 percentage points higher). 7 

Furthermore, when minority-owned firms did receive a loan, they were obligated 

to pay higher interest rates on the loans than was true of comparable nonminority-owned 

firms.s African-Americans pay approximately 1.7 percentage points more, on average, 

for their business credit than do nonminority males, declining slightly to 1.5 percentage 

points when creditworthiness and other firm and owner controls are taken into account. 9 

'Testimony Concerning the Challenges Faced by Disadvantaged Business Enterprises in the Transportation 

Sector, Testimony of Dr. Jon S. Wainwright available at 

http://Transportation .house.gov lMediaifile/Full%20Committee/200903 26/W ainwright. pdf (2009). 2 1d. 

3 1d. 

4 Id. 

5 Testimony Concerning the Challenges Faced by Disadvantaged Business Enterprises in the 

Transportation Sector, Testimony of Dr. Jon S. Wainwright available at 

http://Transportation.house.govlMediaifile/Full%20Committee/20090326/Wainwright.pdf (2009). 

6Discrimination Facing Small Minority-Owned and Women- Owned Businesses in Commercial Credit 

Markets 

Testimony of Jon S. Wainwright, Ph.D., available at htt:p://sbc.senate.govlhearings/testimony/080911-

Wainwright-testimony.pdf (2008). 

7 Testimony Concerning the Challenges Faced by Disadvantaged Business Enterprises in the 

Transportation Sector, Testimony of Dr. Jon S. Wainwright available at 

htt:p:lltransportation.house.gov/MediaifilelFull%20Committee/20090326IWainwright.pdf(2009). 

'ld. 

9Testimony Concerning the Challenges Faced by Disadvantaged Business Enterprises in the Transportation 

Sector, Testimony of Dr. Jon S. Wainwright available at 

http://transportation.house.gov/MediaifilelFull%20Committee/20090326IWainwright.pdf(2009). 

3 
61 

Banks pay attention to different characteristics when they evaluate the loan 

applications of women and minority-owned businesses when compared with male and 

white-owned firms. 10 There exist asymmetries in a sense that banks treat women and 

minority-owned firms less favorably than male and white-owned firms. For example, a 

credit score of 2 would increase the probability of loan denial for both women and men, 

but it increases the probability more for women (by 3.2%) than men (by 0.1 %).ll Credit 

rationing is found to have a discouraging effcct on a minority and women owner's 

probability of applying for a loan for the lowest 10th percentile of women-owned firms 

and highest 10th percentile of minority-owned firms. 12 

In addition, there is a good deal of evidence that the under-representation of 

women and minorities in construction especially is due to widespread and pervasive 

discrimination that has changed little over time. Not only is the proportion of firms 

owned by African Americans especially relatively low, so also are their representation in 

the construction workforce in general and in self-employment in particular. Where firms 

owned by minorities and women do exist in construction they are more likely than nonminority males to be in special tradcs rather than heavy and civil. 13 They are also more 

likely to be sub-contractors than prime contractors. 14 This does not appear to be because 

of a lack of an ability to expand to undertake these activities because it is well-known that 

small construction companies can expand rapidly as demand changes by hiring workers 

and renting equipment and making use of sub-contractors. 15 A particular concern in 

construction is that it is hard for minority and women-owned firms to obtain capital, 

especially working capital, and this causes increased difficulties when bonds have to be 

posted.16 This is often made more difficult still when bonding firms are members of local 

construction associations. 17 Also unions are pervasive in the sector and these unions have 

tended to be dominated by white males and have successfully controlled entry to craft 

jobs (Ashenfelter, 1972).18 

I would like to give you some examples of real business owners who have 

confronted discrimination. It is critical that the Committee understand how very difficult 

it is for these businesspersons to come forward and share their experiences. By coming 

forward, they are putting their businesses in jeopardy of being blackballed and frozen out 

of future business opportunities with larger companies that dominate their market or 

industry. [hope that you all will carefully consider the sort of courage and commitment 

10 Naranchimeg Mijid, Dissertation Abstract: Gender, Race and Credit Rationing of Small Businesses: 

Empirical Evidence from the 2003 Survey of Small Business Finances (2009), available at 

http://www.kauffinan.org/uploadedFiles/ResearchAndPolicylEmergingScholars/KDFP/mijidnaranchimeg.pdf: 

"Id. 

121d. 

(3 David G. Blanchflower & Jon Wainwright, An Analysis of the Impact of Affirmation Action Programs 

on Self-Employment in the Construction Industry (2005), available at http://www.nber.org/papers/wI1793. 

'4 Id. 

IS Id. 

16 Id . 

• 7 Id. 

18 Id. 

22 Citing data from the Project Labor Agreement Task Force Report, July 2007, received at Sept. 20,2007 

meeting of the meeting of the Project Labor Task force (441 41h st. NW, WDC, Room 117 :6:30 PM) 

4 
62 

to justice required to take those kinds of risks. I will submit letters and emails providing 

details of thcse entrepreneurs' stories for the record, but in the interest of time, I will 

provide only a short synopsis of the difficulties they have experienced. And Mr. 

Chairman, I would like to ask permission to submit a number of supporting documents 

for thc record after the hearing. 

• Charles Richardson is an African American engineer with more than 30 years of 

experience. His practice has included leadership and supervisory positions in an array 

of construction projects, including fossil-fuel and nuclear power plants, commercial 

and institutional buildings, schools, roads, bridges, and facilities for the U.S. armed 

forces. In addition, his firm, High Plains Technical Services, Inc., is the only African 

American-owned firm certified to do bridge and roadwork for the Oklahoma 

Department of Transportation. Despite Mr. Richardson's depth of experience, his firm 

has encountered substantial obstacles that impede the growth of his business. For 

instance, for four years, Mr. Richardson's firm has not been paid $108,000 for work 

on a contract for the Oklahoma University System. Payment to his firm has been 

withheld, even though the State's contract audit department agreed the contract and 

invoice instruments were valid. Moreover, the legal counsel of the University system 

stated, on more than one occasion, that there was no objection to the merits of the 

claim for payment. Currently, Mr. Richardson is petitioning the state legislature to 

seek relief. 

• Donald Greaves is an African American owner of a physical and life science research 

and development company. He has worked in energy commodities for 20 years. His 

two business partners have extensive experience in this field: one having negotiated a 

deal with the Vietnamese government for offshore drilling, the other owning and 

operating his own commodities trading firm in the World Trade Center. Mr. Greaves 

sought a loan from IP Morgan Chase to purchase an oil refinery. In applying for the 

loan, Mr. Greaves communicated to the bank that he had collateral for the loan from 

independent investors and that he had a letter of intent from Texaco to purchase one 

million tons of diesel fuel upon his acquisition of the refinery. IP Morgan Chase 

denied his application. The bank's grounds for denial were that it did not find the 

company's name in the business registry or any databases. However, Mr. Greaves' 

company was legally registered in the state of Wyoming when he applied for the loan. 

When Mr. Grcaves brought up thc history of discrimination against minority owned 

businesses to Mr. Nicholas, the bank's Vice President, he responded by stating that he 

would not "put history on the shoulders" of his bank. 

Prior to IP Morgan Chase notifying Mr. Greaves of the denial of his loan application, 

a representative of the oil refinery contacted Mr. Greaves to tell him that the bank had 

already told the refinery'S representatives that it was denying Mr. Greaves' loan 

application. By doing so, IP Morgan inappropriately, and possibly unlawfully 

interfered with the business relationship between Mr. Greaves' company and the oil 

refinery. Subsequently, Mr. Greaves discovered that IP Morgan Chase loaned the 

same amount of funds that he had requested to a large, non-minority owned company 

that ultimately purchased the oil refinery. Unlike Mr. Greaves' company, this 

company offered no collateral to secure the loan. For its actions rclated to this matter, 

5 
63 

Mr. Greaves filed suit against JP Morgan Chase for fraudulent concealment and 

tortious interference with a business relationship, and the case is currently pending in 

the u.s. Court of Appeals for the Second Circuit. 

• The Oklahoma Department of Transportation (ODOT) has continued to use a 

selection and contract awarding system that has passively participated in the 

discrimination existing in Oklahoma's architectural, engineering and construction 

markets. ODOrs selection committees and contracting boards are predominantly 

comprised of non-minorities. Without a diverse selection committee, it is unlikely that 

ODOT contracts will be awarded to minority business owners. Further, ODOT works 

with the Oklahoma Chapter of the Association of General Contractors (AGC) to 

determine utilization goals for Disadvantaged Business Enterprises (DBEs) The AGC, 

however has supported and offered resources to initiatives abolishing affirmative 

action in local, state, and federal contracting over the past 20 years. ODOT does not 

work with any minority owned business associations to determine DBE utilization 

goals. 

Also, ODOrs Minority Business utilization Goals and Attainment for the past three 

fiscal years have not counteracted marketplace discrimination. African Americans 

received none of the contracts ODOT awarded from 2006 to 2008. ODOrs Goal 

Setting and Attainment reports group all DBEs together instead of separating DBEs by 

racial or ethnic minority affiliation. Because of the grouping of all DBEs, it is not 

apparent in these reports that ODOT has not contracted with an African American 

owned business for the past three fiscal years. 

• Fish & Fisher is a black-owned general contracting company in Jackson, Mississippi. 

The company worked on a new Nissan plant in Canton, Mississippi, and helped 

expand the Jackson-Evers International Airport. Despite its work on those significant 

projects, Fish & Fisher was not included in the bidding process when contracts were 

awarded for the construction of a new Toyota plant in Blue Springs, Mississippi in 

2007. Only five companies were invited to bid on the project, and Fish & Fisher was 

relegated to work as a subcontractor on the job. Even when the state of Mississippi 

had allocated $300 million in incentives to bring the plant to Mississippi, only certain 

companies with special ties were among the five companies allowed to bid. In an 

effort to obtain a remedy, Fish & Fisher filed a federal lawsuit to challenge the private 

bidding process that occurred for the Toyota job. 

• Stanley Tucker is an African-American male who is the Managing Partner ofMMG 

Ventures, LP, a Minority Enterprise Small Business Investment Company, and also 

serves as the Director of the Maryland State Small Business Financing and 

Development Authority. He has over 15 years of experience as a private equity 

financier. He has raised capital from public and private sources, sat on the board of 

minority managed banking institutions, planned and strategized venture capital exits, 

and conducted the entire activities and duties attendant to managing a venture capital 

firm. Mr. Tucker applied for a Participating Securities license and leverage from the 

Small Business Administration (SBA) over a period of several years, but the SBA 

never granted this license. Because of the SBA's repeated failure to approve his 

6 
64 

requests, Mr. Tucker's finn could not be licensed. This neglect discouraged Mr. 

Tucker from applying for any additional leverage from the SBA. 

• Anna Peay is the Minority Business Enterprise ("MBE") Coordinator for Advance 

Tactics Security, Inc. ("Advance Tactics"), a locally owned and operated MBE located 

in Indianapolis, Indiana. The company is about 70 percent minority. Advance Tactics 

is a certified minority vendor by the City of Indianapolis, the State of Indiana, and the 

Indiana Minority Supplier Development Council, ("IBDC/IMSDC"). The company 

provides security service personnel, both anned and unanned guards, off duty police 

officers, traffic directors, parking lot attendants, flag men, and lobby customer service 

representatives to many companies in the greater Indianapolis area. 

Although Advance Tactics operates a qualified security business, the company has 

faced discrimination from other companies and has been left without a remedy. In 

one instance, Advance Tactics agreed to become the subcontractor of Securatec for a 

security projcct offered by the city of Indianapolis. Securatec is a Women Business 

Enterprise based out of Chicago. In its bid, Securatec promised the city of 

Indianapolis and Advance Tactics that it would give Advance Tactics 15 percent of 

its contract business. This 15 percent is a city guideline to help disadvantaged 

minority businesses receive work. However, once Securatec won the bid, it only 

hired one of Advance Tactics' employees. With this employment, Advance Tactics 

only received about I percent of the projcct money promised to the company. 

Ms. Peay complained to the city of Indianapolis about Securatec's decision to use 

Advance Tactics to receive the bid from city and then withhold the promised work. 

The city of Indianapolis told Ms. Peay that she had to resolve this problem with 

Securatec. When Ms. Peay tried to speak with Securatec, the company decided to 

complain about Advance Tactics sole employed employee. Then the company 

subsequently fired that worker and hired him as their own employee. Secuartec 

refuses to hire any other Advance Tactics employee for the remainder of this 3-year 

contract. Thus, when Ms. Peay sought to resolve this issue amicably and talk to the 

city about a breach of its project guidelines, Ms. Peay was ignored. 

7 
65 

ENDING BARRIERS FOR MINORITY & WOMEN·OWNED BUSINESSES IN PRIME CONTRACTS 

Research Summary for the Senate Committee on Small Business and Entrepreneurship 

September 24, 2009 

Ralph Bangs, PhD, Associate Director, Center on Race and Social Problems, School of Social 

Work, University of Pittsburgh, 412 624-7379, email: rbangs@pitt.edu 

Audrey Murrell, PhD, Director of Berg Center for Ethics and Leadership, Katz Graduate School 

of Business, University of Pittsburgh, 412 648-1651, email: amurrell@katz.pitt.edu 

Statement of the Issue 

The 14th Amendment to the U.S. Constitution, the Civil Rights Act of 1964, and state and local laws 

promise equal access by all groups to economic and other opportunities. However, in the policy area 

of government contracts with businesses, there is much evidence that governments have erected 

and/or failed to remove barriers that limit access by qualified minority and women-owned firms. 

Summary of Research Findings 

Through monitoring prime contract opportunities, interviews with minority/women-owned firms, and 

examining overall utilization rates, our research finds that: 

1. Minority and women-owned businesses receive small shares of prime contracts awarded by 

local government 

2. Discriminatory barriers and actions by government inhibit access by qualified minority and 

women businesses to prime contract opportunities. The barriers and actions are: 

• Slow pay 

• Large contract sizes 

• Non-competitive and partially-competitive contracting processes 

• Limited publicity of contract opportunities 

• Limited time for preparing bids and proposals 

• Unclear bid specifications 

• High and unreasonable bond requirements 

"Low-ball" bids due to excessive use of change orders 

Recommendations for Action 

• Close monitoring and strict enforcement of rules requiring open bidding process for prime 

contract opportunities (e.g., reasonable public notice, accurate bid specifications) 

• Requiring local agencies receiving federal funds to set MIWBE goals and make efforts to 

achieve the goals with close monitoring of participation rates for MIWBEs 

• Investigating low participation rates, complaints and possible cases of discrimination 

• Convening groups to identify best practices, guidelines and effective remedies with local 

engagement that includes coordinated efforts with other government offices and agencies 

• Providing incentives to local and state governments that demonstrate success in improving 

utilization rates and capacity-building for MBEslWBEs in contracting work. 
66 

STUDY: Business Development Index (to Supplement or Replace Personal Net Worth) 

September 25t DATE: ., 2009 

BY: Thomas D. Boston, Professor of Economics, Georgia Tech and CEO of EUQUANT, INC. 

~ EXECUTIVE SUMMARY 

~ In 1998 the SDB Program sponsored by the U,S, Small Business Administration was modified by the 

establishment of the Personal net worth (PNW) ceiling or cap, The $750,000 ceiling was designed to 

narrowly tailor the SDB Program in response to the US Supreme Court's decision in the case of Adarand, 

While the modification was intended to restrict the access to federal preferential procurement to 

disadvantaged business owners, in practice the ceiling has severely constrained the capacity of 

participating firms, Increasing the PNW ceiling is a necessary condition, but it is a very short-run solution 

to a major regulatory impediment. 

EuQuant is currently working to create a Business Development Index (BDI) to replace or to supplement 

the Personal Net Worth (PNW) ceiling, The BD! will improve the effectiveness of the SDB program by 

replacing or supplementing the PNW ceiling and by refocusing the program on the mission of business 

development rather than on disadvantaged business criteria, The BD! is a multi-dimensional yardstick 

that takes into consideration business, industry and market criteria in determining the SDB Program 

eligibility, We believe that the economic benefits of using a BD! approach are significant. 

~ BACKGROUND 

The government's SDB Program was established to help mitigate the effects of discrimination on the 

performance of businesses owned by minorities and other socially and economically disadvantaged 

peoples, 

Certification as a SDB means that the firm has the follOwing characteristics: 

Meets small business size standards for their sector/industry 

51 % owned and controlled by a socially and economically disadvantaged individual 

PNW of less than $750,000 1 

The program has demonstrated a noticeable impact on the businesses that participate. 

+$2,8MM in revenue for SDB participants relative to non-SDB participants 

Graduates of the SDB program have demonstrated better sustain ability 

However, a case study of firms that were graduated unexpectedly because of PNW revealed that 

revenue declined by 45% as a result. 

The PNW Ceiling of 750,000 decreases the effectiveness ofthe SDBs: 

The Following are some Disadvantages Created by the PNW Ceiling 

1, The $750,000 PNW ceiling has not been adjusted for inflation since it was established more 

than a decade ago; this makes its real value today slightly greater than $500,000, 

I Excluding the equity in their bu.siness and primary residence. 

11 P age 
67 

2, EUQuant's research found that personal net worth is closely related to business capacity and 

therefore if PNW is set too low, business capacity will also be very low, 

3, One PNW ceiling was set for all businesses regardless of the industry in which they operate, 

Therefore, manufacturing and construction companies face the same ceiling as do retail 

establishments, 

4, Bonding and access to capital are heavily dependent upon the owner's personal net worth, 

Therefore, the PNW ceiling has severely constrained the growth of SDB bonding capacity, 

5, Firms at the $750,000 level are not yet ready for program graduation and face a challenging 

transition period to longer run sustainability, 

In an era when corporations are reducing the size of their supply chains in response to global competition, it 

is more important than ever for SDBs to build scale and capacity, 

~ THE BUSINESS DEVELOPMENT INDEX SOLUTION 

By replacing the PNW Ceiling with the BDI, the program eligibility criteria will be relevant to the 

marketplace and greatly improve the ability of SDBs to create greater scale and capacity and thereby 

make greater employment and income contributions to their local communities. 

The BDI will enable SDB qualification criteria to be based on a number of factors other than the owners 

PNW, Some of the factors include the following: Firm's bonding capacity relative to industry standard; 

Industry of operation; Degree of Industry concentration; Number of employees; Firm's revenues; Firm's 

Legal form of Organization; Years in operation; Government contract awards received by firm; Years 

registered as a government vendor; Degree of contracting disparity in private and public sector industry; 

Business capacity in a discrimination free market. 

We also propose a phase-out transition period wherein businesses, having reached the BD] threshold, will 

have a three year program eligibility transition period to adjust to graduation, This is intended to 

circumvent sudden drops in revenue that have been experienced by businesses that must graduate 

unexpectedly, 

~ CONCLUSION 

The SDS program has demonstrated its effectiveness, but its structure impedes the development of SDB 

capacity, The program eligibility standard must be improved upon, The inclusion of a BD! (in place of or 

as a supplement to personal net worth) will allow the SDS program to have an even greater impact than 

has been the case up to now, 

21Page 
68 

Statement of the National Center for American Indian Enterprise Development 

the ~ational Center 

for American Indian Enterprise Development 

5047 

STATEMENT 

OF THE 

NATIONAL CENTER FOR AMERICAN INDIAN ENTERPRISE DEVELOPMENT 

FOR THE 

SENATE COMMITTEE ON SMALL BUSINESS AND ENTREPRENEURSHIP 

ROUNDTABLE DISCUSSION 

ON 

"MINORITY ENTREPRENEURSHIP: EVALUATING SMALL BUSINESS 

RESOURCES AND PROGRAMS" 

SEPTEMBER 24, 2009 

Headquarters: 

953 East Juanita Avenue' Mesa, AZ 85204 800·4NCAIED· www.ncaied.org 
69 

Statement orthe National Center ror American Jndian Enterprise Development 

STATEMENT 

FOR THE 

SENATE COMMITTEE ON SMALL BUSINESS AND ENTREPRENEURSHIP 

ROUNDTABLE DISCUSSION 

ON 

"MINORITY ENTREPRENEURSHIP: EVALUATING SMALL BUSINESS 

RESOURCES AND PROGRAMS" 

SEPTEMBER 24, 2009 

Chairwoman Landrieu and Ranking Member Snowe, the National Center for American Indian 

Enterprise Development (the "National Center" or "NCAIED") presents this statement for the 

Committee's Roundtable Discussions on September 22 and 24, 2009 focusing on the Small 

Business Administration ("SBA") small business contracting programs and resources for 

minority entrepreneurship. We include recommendations for actions that Congress should take 

and actions that should be accomplished by the SBA and other appropriate federal agencies. 

This year, the National Center celebrates its 40th Anniversary as the Nation's longest serving 

Native business development assistance provider whose mission is to develop the American 

Indian private sector as a means to help Native communities become self-sufficient. The 

National Center has long played a pivotal role in spurring the Congress and federal agencies to 

support Native and minority business development. National Center witnesses have testified 

repeatedly before Congress, most recently at this Committee's Roundtable Discussion on April 

2,2009 on SBA's Entrepreneurial Development Programs. We have worked closely with other 

national organizations to improve the SBA's 8(a) and other small business contracting programs 

and to advance other Native business and economic development initiatives. The National 

Center also collaborated in formulating and then participating in the first-ever consultations that 

the SBA conducted with Indian tribes to discuss 8(a) regulatory proposals. 

The National Center bases its comments on countless hours of assisting Native clients who are 

individual Native Americans, Indian tribes, tribal enterprises and other Native-owned companies 

as they struggle to grow, diversify, thrive and return economic benefits to their Native 

communities and other areas where their companies generate revenues and jobs. NCAIED's 

conferences and training sessions provide additional opportunities for Native-owned enterprises 

to learn from contracting experts, and receive valuable guidance on best practices to ensure their 

compliance with the spirit and letter of the rules applicable to small and minority companies. 

BACKGROUND ON THE NATIONAL CENTER 

Formed in 1969, the National Center has evolved into a national organization with supporting 

non-profit centers across the country providing procurement technical assistance, business 

development and management consulting services to Indian tribes, Alaska regional and village 

corporations CANCs"), Native Hawaiian organizations, and businesses owned by tribes, ANCs, 

and individual Native Americans, Alaska Natives, and Native Hawaiians. Our experienced 

Native American business and procurement consultants assist clients ranging from first 

generation Native entrepreneurs to sophisticated tribal enterprises. We help clients develop 

5047870 
70 

Statement of the National Center for American Indian Enterprise Development 

business feasibility studies, business plans, banking relationships and lines of credit, marketing 

and growth strategies. We are supported by, and also help, the major federal contracting 

agencies by coaching contractors on applications for certifications and registrations, fmding 

capable Native companies to fulfill federal requirements, and providing contractors guidance on 

Mentor Protege and SBA contracting programs (e.g., 8(a), SDB, HUBZone, SDBVOB, WEE, 

etc.), and Electronic CommercelElectronic Data Interchange. 

In addition to client work at its centers, the NCAIED produces various events that train, promote 

and market Native enterprises to the public and private sectors. One such event is NCAIED's 

phenomenally successful annual Reservation Economic Summit & American Indian Business 

Trade Fair ("RES"). At RES 2009, over 2,500 individuals and 300 exhibitors attended, including 

tribes, ANCs, Native enterprises, Fortune 500 and other major corporate representatives, and 

federal, state, local and tribal procurement officials. Through our centers, RES conferences and 

other events with bid matching opportunities, NCAIED estimates that its operations have: 

? assisted approximately 80% of the tribes in the lower 48 states and more than 25,000 

Native enterprises; 

? trained over 10,000 tribal members; and 

? helped NCAIED clients receive nearly $3 billion in contract awards (translating to 

roughly 50,000 jobs) in the last 4 years alone. 

SBA PROGRAMS AND RESOURCES 

The National Center collaborates with the SBA, but it receives no grant or cooperative assistance 

funding from the agency. Most of the National Center's experience with the SBA is based on its 

centers' experience over the years in assisting Native companies with their efforts to access SBA 

programs and resources. The NCAIED's assistance centers and their clients suffer continuing 

frustration with the paperwork shuffie experienced in dealing with the SBA's financing and 

certification applications. No matter how hard NCAIED staff and clients work to ensure that 

their applications are "complete" when submitted to lessen workloads of the SBA staff reviewing 

the applications, the SBA's chronic understaffing stymies progress. Lack of trained, experienced 

staff, especially procurement-related staff, causes delays and frustration for everyone - from 

private applicants, to bankers, to dedicated SBA officials trying to review and process 

applications, provide assistance, monitor compliance, and accomplish needed reforms. 

For the last several years, this Committee and its House counterpart have been pressing to 

increase the SBA's budget and workforce, as well as strengthen and reauthorize SBA's various 

programs. The National Center has joined the call for more resources for the SBA, and has 

worked collaboratively with the National Congress of American Indians ("NCAI") and the 

Native American Contractors Association ("NACA") to develop joint proposals to improve 

provisions of the SBA's 8(a) program that apply specifically to 8(a) companies owned by tribes, 

ANCs and Native Hawaiian organizations, improve other SBA contracting programs, and 

increase funding for Native American business outreach and entrepreneurial development 

initiatives. Attached to this testimony is a copy of the Joint Statement on the NCAIED-NCAINACA legislative proposals. 

5047870 
71 

Statement of the National Center for American Indian Enterprise Development 

A major goal of the National Center -- and of SBA small business contracting programs 

generally -- is capacity building. In one-on-one counseling sessions with clients, and in training 

sessions offered at its conferences, the National Center focuses on building the capacity and 

capabilities of Native-owned businesses to grow and succeed by utilizing the various tools 

authorized by the Congress: the Sea) and other contracting programs, the Mentor-Protege 

Program, and Joint Venture provisions. Our centers also assist clients seeking financing from 

lenders, sometimes including loan guarantees offered by the SBA or the Department of Interior, 

and trying to secure bonding from sureties. While we assist both small and larger Native-owned 

companies, it is not surprising that the smaller companies need more time-consuming assistance. 

Increasingly, however, federal agencies are adopting the "Strategic Growth Initiative" of the 

Minority Business Development Agency that requires its Minority and Native American 

Business Enterprise Centers to meet higher goals based on assisting companies in obtaining 

larger contracts and financing packages. The SBA's Small Business Development Centers 

("SBDCs") also seem to be adopting this "Strategic Growth Initiative" approach. Obviously, 

larger companies that can capture larger contracts and qualify for larger financing packages will 

enable their supporting business assistance centers to report greater returns on the federal 

business assistance dollars invested. This trend parallels the increasing tendency of federal 

contracting agencies to bundle and consolidate contracting actions for which only larger 

companies can compete and win. The problem with focusing most attention on the strategic 

growth initiative approach is that it overlooks the vast majority of small and minority businesses 

that also seek financing and sales to commercial and government buyers. Help is needed at both 

ends of the spectrum to enable small and minority businesses to capture what the Congress has 

deemed to be a fair small business share of federal contract award dollars. 

CONTINUING BARRIERS TO SMALL! MINORITY CONTRACTING GROWTH 

As noted by the Committee's leadership, while federal contract award dollars have more than 

doubled over the last five years, small and minority businesses' percentage shares of that federal 

market have declined significantly. There is general agreement that the following problems have 

contributed to this decline: 

• Bundling/consolidating contracts into sizes beyond most small contractors' capabilities; 

• Huge growth in emergencyfoverseas contracts not subject to small business contracting 

requirements or goals; 

• Barriers to growth, such as 1) the existing SBA limitations on individual owners' net 

worth that prematurely graduate entrepreneurs from the SBA's Sea) and SDB programs 

before they can build their companies into stronger competitors able to pursue and 

perform larger contracts, and 2) lack of access to financing and bonding; 

• Lax compliance with, and limited or non-existent enforcement of; I) subcontracting plan 

requirements, 2) government-wide and agency small and minority business contracting 

goals, and 3) companies' size limits and proper coding of contract awards made to 

companies that actually qualify as small and minority owned; and 

5047870 
72 

Statement oftbe National Center for American Indian Enterprise Development 

• Downsizing of the federal procurement workforce, compounding the above problems, as 

overworked contracting personnel have had to deal with higher volumes of contracting 

actions, pressures to meet deadlines and small business goals, and little or no time to 

monitor compliance with existing rules designed to 1) prevent or reduce contract 

bundling and consolidation, 2) enforce subcontracting plan requirements, and 3) enforce 

limits on subcontracting, among other key areas requiring additional oversight. 

The above problems could be compounded by pressures to meet the noble, but daunting, 

requirements imposed by the new Obama Administration's initiatives to expedite federal actions 

to disseminate economic stimulus funds provided in the American Recovery and Reinvestment 

Act ("ARRA") to "shovel ready" and other projects across the country. Coupled with these 

contracting actions are heightened reporting and oversight responsibilities of federal procurement 

and other officials to ensure transparent and effective utilization of the ARRA funds. 

To develop proposed solutions, the National Center has been collaborating with NCAI and 

NACA on workshops and consultations to collect as much input as possible from interested 

parties on how to improve the SBA's small business contracting programs and expand the small 

business share of the federal market. We have developed a common agenda to advance Native 

business and economic development initiatives, increase federal contracting and partnering 

opportunities for all types of small and small disadvantaged businesses, and promote 

transparency and compliance with all applicable procurement rules. We have reached out to 

other organizations to find common ground and work together on solutions that will cause the 

federal contracting agcncies to meet (and possibly even exceed) thcir individual agency goals 

and the government-wide 23% small business contracting goal. 

RECOMMENDATIONS 

The National Center's recommendations include those in the attached NCAIED-NCAI-NACA 

Joint Statement, as well as other specific actions for the Congress to take, and corrective actions 

for the SBA and federal procurement agencies to implement to strengthen their oversight of 

contracting activities. 

Prompt Congressional Actions Needed: 

1. Authorize the SBA Office of Native American Affairs 

The National Center has long advocated the formal authorization and adequate funding of the 

SBA's Office of Native American Affairs in entrepreneurial development legislation, and 

participated in this Committee's Roundtable Discussion on S. 1229 on June 11, 2009. The 

National Center believes that a fortified Office of Native American Affairs, with its own budget, 

can provide the additional administrative and procurement assistance support and oversight 

needed. We urge the Senate to approve S. 1229 promptly. In conference negotiations with the 

House of Representatives, we urge that the conferees agree to authorize a $2 million budget for 

the Office of Native American Affairs and at least $10 million for grants for Native American 

business centers that include little, or no, non-federal match requirement. We also urge a 

similarly low non-federal match requirement for any veterans business entrepreneurial grants to 

be authorized in this important legislation. 

5047870 
73 

Statement of the National Center for American Indian Enterprise Development 

2. Appropriate Adequate Funds for SBA's Native American Outreach Program 

The National Center also has urged that, in advance of enactment of the Native American 

entrepreneurial development authorization discussed above, the Congress must approve 

appropriations well above the meager $1 million for Native American Outreach provided in the 

last eight budget requests. NCAlED, NACA and NCAI have jointly advocated for at least $6 

million for Native American Outreach for FY 2010 (some which would fund the operations of 

the Oft1ce of Native American Affairs), and more funds to advance the SBA's regulatory form 

agenda for the 8(a) program. We appreciate Chairwoman Landrieu's efforts to increase the 

Native American Outreach budget by $500,000 for FY 20 I 0 and hope the final figures will go up 

even further in conference. 

3. Reauthorize the SBA's SmalllMinority Business Contracting Programs 

For the last several Congresses, this Committee has developed impressive proposals to improve 

and reauthorize SBA's small business contracting programs. We hope the prospects for 

movement look better now, because the need grows daily to enact legislation that will create 

parity among the small business contracting programs, enforce subcontracting plans, help build 

small and minority businesses' capacity, and ensure that the federal contracting agencies 

improve their records of meeting both their prime contracting and subcontracting goals for 

awards to small and minority businesses. With the significant growth in the federal market, there 

is no good excuse for the continual declines in the total dollar value and the percentage share of 

overall contract awards to small businesses. The National Center supports the following 

proposals, most of which are included in the attached NCAlED-NACA-NCAI Joint Statement: 

• Fulfill Congressional intent to further federal Indian Self-Determination policy set forth 

in 25 U.S.C. 450a by preserving the provisions that promote the competitive viability of 

8(a) enterprises owned by tribes, ANCs and NHOs that help generate revenues, jobs 

and benefits to support their Native communities and develop more self-sufficient 

Native economies; 

• Limit bundling and consolidation of contracts, break up such contracts for award to 

small businesses, and authorize set aside or other procurement procedures to enable 

teams of Native-owned and other small firm to pursue bundled/consolidated contracts; 

• Require federal agencies to request information on contractors' capabilities with 

enough lead time prior to announcing their procurements, so as to allow small business 

contractors sufficient time to form joint ventures or other teaming arrangements to bc 

capable of securing larger contract awards; 

• Improve enforcement of and increase the Government-wide contracting goals for 

awards to small business (to not less than 30% of total contract awards to small 

business, and not less than 8% of total contract and subcontract awards to small 

disadvantaged business and 8(a) concerns); 

• Make overseas contracts subject to small business contracting requirements and goals; 

5047870 
74 

Statement of the National Center for American Indian Enterprise Development 

• Ensure parity among the various small business contracting programs; 

• Strengthen SBA's authority to negotiate with individual contracting agencies to 

establish goals higher than their current levels, and to require the agencies to be more 

accountable for their past performance and future plans for making more small business 

awards in each subcategory of small business contracting; 

• Increase net worth thresholds above $250,000 for individuals to qualify for 8(a) 

certification, and above $750,000 for continued 8(a) program participation, and include 

annual inflationary adjustments to any new thresholds established; 

• Improve and facilitate small businesses' access to financing and surety bonding; 

• Increase the competitive thresholds to enable individual-owned 8( a) companies to 

pursue larger contracts and build capacity; 

• Encourage or require small businesses with larger contracts to implement 

subcontracting plans to develop stronger business alliances among all types of small 

business contractors, including 8(a), SDB, HUB Zone, SDVOB, and WOB concerns; 

• Strengthen enforcement of subcontracting plans, including incentives for meeting or 

exceeding subcontracting plan goals and penalties for failure to meet such goals; 

• Direct the SBA to develop regulations, with appropriate safeguards, that will enable the 

SBA to accept a company's certification that it has received through a Federal, state or 

local government certification process, or from a responsible national certifying entity; 

• Increase size standards with adjustments at least for inflation, if not also to take into 

account the capital requirements for each industry; and 

• Enhance the SBA's BusinessLINC concepts by extending the SBA's authority to cosponsor business outreach events together with private, public, and non-profit entities 

and to issue grants to such entities to expand databases of and business-to-business 

relationships between, large and small businesses interested in participating in MentorProtege, joint venture or other teaming arrangements to pursue commercial and 

government contract opportunities. 

CONCLUSION 

The National Center appreciates the opportunity to submit this statement. We look forward to 

working with the Committee as it develops and considers legislation to address improvements in 

federal contracting provisions, especially those that apply to Native contractors, so as to keep 

both federal Indian and procurement policies in proper balance. 

Attachment (1) 

5047870 
75 

o 

Native American Contractors Association 

JOINT LEGISLATIVE PROPOSAL 

ON SMALL BUSINESS CONTRACTING 

SEPTEMBER 25, 2007 

Expand Small Business Contracting Opportunities 

Tn reauthorizing the Small Business Act's contracting programs, Congress must include 

stronger provisions to ensure small businesses actually receive the federal contract support 

required by law for decades. \'Vhile the federal contracting market has doubled in size since 

2000, small businesses' percentage share of that market has declined significantly due to: 

• Bundling! consolidation of contracts into sizes beyond most small contractors' 

capabilities; 

• Huge growth in emergency! overseas contracts not subject to small business 

contracting requirements or goals; 

• Barriers to growth that make it difficult for small contractors to compete for larger 

contracts; 

• Lax compliance with subcontracting plan requirements and limited enforcement; and 

• Downsizing of the federal procurement workforce, compounding the above 

problems, as overworked contracting personnel must deal with higher volumes of 

contracting actions, pressures to meet deadlines and small business goals, and little or 

no time to monitor compliance with existing rules designed to prevent! reduce 

contract bundling! consolidation, enforce subcontracting plan requirements and 

other limits on subcontracting. 

To enable small businesses, particularly 8 (a) fimls, to compete for a larger share of 

government contracts, the federal government must take immediate actions to reverse these 

trends, including enhancing incentives for contracting officers to increase awards to 8(a) and 

other small businesses. In considering small business contracting legislation, Congress 

should adopt provisions to: 

1. Fulfill Congressional intent to further the Indian Self-Determination policy set forth 

in 25 lTS.C. 450a by preserving the provisions that promote the competitive viability 

of "Native enterprises" small business concerns certified by SBA as owned by Tndian 

Tribes, Alaska Native regional or village corporations, or Native Hawaiian 

Organizations that help support their Native communities by developing more sclfsufficient Native economics; 

2. Support provisions that tighten limits on bundling and consolidation of contracts, 

break up such contracts for award to small businesses or employ procurement 
76 

procedures to enable teams of Native enterprises and other small businesses to 

pursue larger contracts. Require contracting agencies to issue a Request For 

Information (RFI) to small businesses so they have a chance to form teams to pursue 

these larger contracting opportunities (sections 1001 and 1002 of S. 3778 of the 109'h 

Congress proposed such teaming approaches); 

3. Increase the Government-wide contracting goals for awards to small business (along 

the lines of section 201 of H.R. 1873) of not less than 30% of total contract awards 

to small business, and not less than 8% of total contract and subcontract awards to 

small disadvantaged business concerns; 

4. Include overseas contracts within the Government-wide contracting goals (like 

section 202 of H.R. 1873), and require reporting of awards to small businesses as 

prime or subcontractors performing contracts overseas (as proposed in section 1306 

ofS.3778); 

5. Enhance the ability of individuals to qualifY for certification as 8 (a) program 

participants and to pursue larger contracts on a competitive or non-competitive basis 

(as proposed in sections 202 ofH.R. 2532); 

6. Increase the net worth thresholds, including annual inflationary adjustments, for 

individuals seeking to qualifY and retain eligibility for certification as 8(a) program 

participants (along the lines of section 1242 of S. 3778, or section 202 of H.R. 2532); 

7. Double each competitive thresholds specified in 15 U.S.c. 637 (d) (1) (D) (ii) , (as 

proposed in section 202 of ILR. 2532); 

8. Encourage small businesses with larger contracts to implement subcontracting plans 

to develop stronger business alliances among all types of small business contractors, 

including 8(a) and other small disadvantaged concerns, HUBZone, service disabled 

veteran-owned, women-owned and other small businesses; 

9. Revisit size standards (as both the Senate and House Small Business Committees 

have proposed), but leave in place the new requirements for small business 

recertification that just became applicable on June 30, 2007; and 

10. Support legislative or administrative directives for SBA to accept certifications by 

other federal, state and local governments, under such criteria as SBA may prescribe 

by regulation or order, in certifYing small disadvantaged businesses, and other 

subcategories of small businesses for which certifications are required (sections 1221, 

1232 and 1241 ofS. 3778). 
77 

OCTOBER 8, 2009 TESTIMONY BEFORE THE UNITED STATES SENATE 

COMMITTEE ON SMALL BUSINESS AND ENTREPRENEURSHIP 

I. Introduction 

SUBMITTED BY ASIAN AMERICAN INSTITUTE 

Ami D. Gandhi, Esq. 

Legal Director 

4753 North Broadway Street, Suite 904 

Chicago, Illinois 60640 

Phone: 773-271-0899 x 103 

E-mail: ami@aaichicago.org 

Asian American Institute (AAI) applauds the United States Senate Committee on Small 

Business and Entrepreneurship for addressing minority business concerns at its recent roundtable 

hearing. AAI is a pan-Asian, non-partisan organization whose mission is to empower and 

advocate for the Asian American community in the Chicago area through research, education, 

and coalition-building. AAI partners with affiliate organizations located in Washington, D.C., 

San Francisco, and Los Angeles. The organizations collectively have local and national 

expertise on civil rights issues that affect Asian Americans. 

Asian Americans continue to face discrimination in public and private settings. Recent 

findings, as well as past research, show evidence of such discrimination. AAI submits this 

testimony to convey that Asian Americans do face discrimination in government contracting and, 

for all the reasons explained below, it is crucial for Asian Americans to be included in minority 

government contracting programs. 

II. Why Asian Americans Must Remain in 

Minority Government Contracting Programs 

The pervasive discrimination against Asian American-owned businesses prevents them 

from competing on equal footing for public contracts. Extensive evidence of discrimination 

against Asian Americans is documented in various sources, including the recent report 

commissioned by the City of Chicago ("2009 Chicago Report")} whose recommendations were 

adopted in the Chicago minority business enterprise ordinance enacted in July of 20092

• Asian 

American-owned businesses face discrimination in obtaining government contracts - as well as 

in obtaining bonding, credit, fair prices from suppliers, access to social networks, and 

information about contracting opportunities. 

In addition to data evidencing discrimination, the unique history, culture, and 

demographics of Asian Americans must also be considered in order to accurately assess 

discrimination against Asian American-owned businesses. Asian Americans have experienced 

racial discrimination in virtually all areas of life. Since this nation's earliest days, discriminatory 

federal, state, and private actions have denied Asian Americans equal rights not only in the 

sphere of government contracting, but also in the areas of citizenship, immigration, land 

ownership, education, marriage, and business. Discrimination against Asian Americans 

Testimony of A,ian American Institute to 

United States Senate Small Business Committee 

October 8, 2009 

Page I 
78 

continues to this day, particularly in government contracting, and more than justifies their 

inclusion in minority government contracting programs. 

II. Evidence of Discrimination Against Asian Americans 

The data regarding minority-owned businesses in Chicago provides an important example 

of discrimination against Asian Americans in the United States at large. As set forth in detail in 

the 2009 Chicago Report, a recent study of Asian American construction contractors "found that 

a significant majority had experienced discrimination in the last five years. These [Asian 

American contracto/'!,j reported that without [Chicago's minority business enterprise 1 program 

they could not survive. Prime contractors did not hire them as a subcontractor on private sector 

projects despite using them on public sector projects with goals. They also reported of 

difficulties in obtaining bonding and working capital." 2009 Chicago Report at 64 (emphasis 

added). Additionally, "[tJhere is now evidence that Asians are discriminated against in the credit 

market." !d. at 59. 

The 2009 Chicago Report goes on to state, 

[DJiscrimination continues to exist in the Chicago construction market. It is 

exacerbated by discrimination in the credit market that acts as a market failure, 

which means this discrimination persists. Firms owned by minorities ... are unable 

to obtain loans when they apply for them, even with the same characteristics as 

white men. When they do get them they have to pay higher interest rates. When 

banks do not know the race of the owner, there is no difference, suggesting this 

is ... due to ... discrimination ... There is no evidence ... that suggests that. .. the 

observed discrimination has diminished over time. 

2009 Chicago Report at 94-95. See id. at 59, 94-95, 99-100. 

A 2007 report regarding the City of Chicago Minority Business Enterprise Program 

("2007 Chicago Report")] stated that, with regard to Asian American-owned businesses, "[tJhere 

is quantitative evidence - especially from the credit market and on unemployment and wages, 

plus anecdotal evidence of discrimination that is stronger than it was in 2004 ... " !d. 

Other evidence also demonstrates that there Asian American contractors justly belong in 

minority government contracting programs.4 For example, research commissioned by Cook 

County of Illinois shows that Asian subcontractors received zero dollars during the time period 

when Cook County suspended its M/WBE program for construction contracts. See Colette Holt, 

Review of Compelling Evidence of Discrimination Against Minority- and Women-Owned 

Business Enterprises in the Chicago Area Construction Industry and Recommendations for 

Narrowly Tailored Remedies for Cook County, Illinois (2006) (providing further documentation 

of discrimination against Asian American contractors in the Chicago area). 

III. Context for Understanding Discrimination Against Asian Americans 

The United States Senate Small Business Committee should consider the unique history 

and demographics of Asian Americans in order to accurately assess and understand 

Testimony of Asian American Institute to 

United States Senate Small Business Committee 

October 8, 2009 

Page 2 
79 

discrimination against Asian American-owned businesses. Asian Americans are an extremely 

diverse group in terms of socio-economic status, education, language, religion, and other factors. 

Research conducted on Asian American contractors - and the interpretation of such research 

should account for this diversity. In particular, lawmakers and researchers should guard against 

concluding that all Asian Americans are economically successful, because it is merely a myth 

that Asian Americans are the "model minority". AAI recommends that, in the future, 

governmental bodies that study minority businesses should employ more rigorous research 

techniques that account for the unique ways in which Asian American-owned businesses 

experience discrimination. 

A. Past and Present Discrimination Against Asian Americans 

From the very beginning of American history, Asian Americans have faced governmental 

discrimination that has prejudiced their ability not only to obtain government contracts, but also 

to exercise the most basic rights. For many years, laws banned Asian Americans and other 

minorities from becoming naturalized citizens and severely restricted the ability of Asians to 

enter the United States as immigrants. The few Asians who overcame the discriminatory 

immigration laws then faced significant barriers in exercising even basic rights, such as the rights 

to marry' and to obtain an education.6 Asian Americans' business rights were also unfairly 

hampered; for example, local ordinances in Chicago unfairly restricted the economic growth and 

advancement of Chinese-owned businesses.7 Further, until as recently as the late 19405, Illinois 

and several other states prohibited Asian Americans, including American-born citizens of Asian 

descent, from acquiring land. 8 Yet, the most egregious example of the effects of discrimination 

against Asian Americans was the brutal internment of approximately 120,000 Japanese 

Americans during World War II. 9 

Ominously, another study shows that many Americans continue to harbor racist views 

against Asian Americans. This study found that approximately 25% of the American public hold 

decisively negative views of Chinese Americans, and 46% of those surveyed believe that 

"Chinese Americans passing on information to the Chinese government is a problem.,,10 

Moreover, approximately 15% of those polled believed that Chinese Americans were "[m]ore 

willing than others to use shady practices," and also that Chinese Americans are "twofaced" and 

"conceited."l! In the past decade, Chicago and other cities across the United States have seen a 

number of hate crimes and hate incidents involving Asian Americans. And post-9111, South 

Asian Americans and other Asian Americans have increasingly faced unjust racial profiling on 

the local and national levels. 12 

Although often touted as a "model minority," Asian Americans nationally and locally 

face many economic problems, as shown by data from the United States Census of 2000. In 

Chicago, for example, Korean Americans have a poverty rate of 30% - higher than the poverty 

rates of whites, Latinos, and African Americans. The overall poverty rate for Asian Americans 

is 14% (compared to 9% for whites) and certain subsets of Asian Americans, such as Hmong and 

Cambodian Americans, have extremely high poverty rates of 60% and 40% (much higher than 

the rates of African Americans and Latinos). 

Testimony of Asian American Institute to 

United States Senate Small Business Committee 

October 8, 2009 

Pagel 
80 

B. Discrimination Against Asian Americans in Business 

Discrimination against Asian Americans continues to this day, particularly in the business 

setting. Asian Americans receive unduly low returns on their education, as compared to whites. 

Equal Access at 33. For example, "[e]ven in Chicago, where educational attainment for Asians 

is significantly higher than for non-Hispanic whites, Asians earn only 71 cents to every dollar 

earned by non-Hispanic whites. In other words, Asians are having difficulties translating their 

education into earnings." [d. Asian Americans often have the "inability to find job opportunities 

commensurate with [their] education and training"Y Similarly, the United States Commission 

on Civil Rights has found that being of "Asian descent" had a "negative effect" on an 

employee's chance to move upward into management. 14 Indeed, one study stated that Asian 

Americans "face the worst chance [among all racial groups] of being advanced into management 

positions.,,15 

Disturbingly, the underlying racism that gave rise to the internment of Japanese 

Americans during World War II still appears to be with us today, and it forms the backdrop that 

this Committee should consider in assessing the concerns of Asian Americans. Minority 

contracting programs are a necessary step to begin to break the cycle of discrimination and 

disadvantage. 

C. Specific Research Considerations for Asian Americans 

Asian Americans have a unique history of discrimination and, as such, a one-size-fits-all 

assessment will not exhaustively measure the discrimination that Asian Americans currently 

face. There are inherent limitations in many research studies that have attempted to measure 

discrimination against Asian Americans. When interpreting such research studies, lawmakers, 

researchers, and government contracting officials should consider the following points: 

a. 

b. 

c. 

"Household income" is not necessarily a reliable indicator of the success 

or disadvantage faced by Asian Americans. Many Asian American 

families live in joint or multi-generational households; plus, the household 

income might not account for unpaid or marginally paid family members 

who assist with the business. 

"Self-employment" or "entrepreneurship" is not necessarily a reliable 

indicator of the success or disadvantage faced by Asian Americans. For 

example, statistics on relatively high self-employment rates of Asians can 

indicate discriminatory racial barriers that drive Asian Americans to be 

self-employed such as workplace discrimination in the mainstream 

market. inability to advance meaningfully in businesses that are owned by 

others, or underemployment in mainstream markets commensurate with 

their levels of education. 

As explained above, Asian Americans experience an unduly low return on 

their education. Therefore, numbers depicting "net worth," "household 

incomes," and "self-employment" do not paint a complete picture of 

Testimony of Asian American In.flitute to 

United Slate.f Senate Small Business Committee 

October 8, 2009 

Page 4 
81 

d. 

e. 

f. 

IV. Conclusion 

whether Asian Americans suffer discrimination or social disadvantage, 

because Asian Americans with a seemingly high net worth or income 

might still be receiving an unfairly low return on education. 

Asian Americans are quite diverse in terms of ethnicities, socio-economic 

status, languages spoken, and several other factors. In order to obtain 

more comprehensive facts regarding discrimination against Asian 

American contractors, data regarding the subgroups within the Asian 

American community would need to be dis aggregated. 

Asian American contractors have suffered ongoing repercussions from 

previously being excluded from minority government contracting 

programs. Confusion still exists among government contracting 

authorities and the general public regarding whether Asian Americans face 

discrimination, and whether they are a part of minority contracting 

programs. 

Asian American construction contractors face discrimination not only in 

obtaining government contracts, but also in obtaining bonding, credit, fair 

prices from suppliers, access to social networks, and information about 

contracting opportunities. Asian American contractors also have concerns 

about enforcement and monitoring of minority government contracting 

programs, because of past and present misuse of such programs. Future 

research should investigate these practices as they affect Asian Americans. 

Asian American contractors in the United States have suffered and continue to suffer 

discrimination, and Asian Americans must be included in minority government contracting 

programs. 

SOURCES 

I David G. Blanchflower, Report on Ihe City o/Chicago 's MWBE Program (June 2009). 

2 Substitute Ordinance Amending Chapter 2-92 of the Chicago Municipal Code (passed July 29, 2009). 

3 David G. Blanchflower, Report 10 City o/Chicago: An evaluation o.(whether Asian-ownedjirms should 

be included in the City a/Chicago's aspirational goals program in construction (2007). 

4 See, e.g., Equal Access: Unlocking Government Doors(or Asian American Businesses, Asian American 

Justice Center, ISBN 1-932526-11-0 (2008). 

Testimony of Asian American Institute to 

United Slates Senate Small Business Committee 

OctolJer 8, 2009 

PageS 
82 

5 See, e.g, Ancheta, Angelo N" Race, Rights and the Asian American Experience, at 30 (1985) (noting 

that laws prohibiting intermarriage with Asians were common and remained on the books until the United 

States Supreme Court ruled them to be unconstitutional in Loving v. Virginia, 388 U.S. I (1967)). Even 

Illinois had a statute in 1829 that prohibited interracial marriage between whites and people of color. See 

Karthikeyan, Hrishi, Preserving Racial Identity: Population Patterns and the Application of Antimiscegenation Statutes to Asian Americans, 1910-1950,9 Asian L.J. I (2002). 

6 Like other racial minorities, Asian American children were required to attend segregated schools. See, 

e.g., Ronald Takaki, A History of Asian Americans: Strangers From A Different Shore at 201 (1998); Lum 

v. Rice, 275 U.S. 78,86-87 (1927) (applying separate-but-equal doctrine of Plessy v. Ferguson, 163 U.S. 

537 (1896), to Chinese citizens). 

7 See Yick Wo v. Hopkins, 118 U.S. 356, 373-74 (1886) (striking down ordinances as a violation of equal 

protection because of the discriminatory manner in which they were enforced). 

8 See Dudley O. McGovney, The Anti-Japanese Land Laws of California and Ten Other States, 35 CaL L. 

Rev. 7 (1947) (detailing the history of preclusion of Japanese Americans from land-ownership in eleven 

states). 

9 See Korematsu v. United States, 323 U.S. 214 (1944); Adarand Constructors, Inc. v. Pena, SIS U.S. 

200, 235-36 (recognizing that the internment of Japanese Americans upheld in Korematsu was 

"illegitimate" and noting Congressional finding that "these actions [of relocating and interning civilians 

of Japanese ancestry] were carried out without adequate security reasons ... and were motivated largely 

by racial prejudice, wartime hysteria, and a failure of political leadership") (citation omitted), 

10 See Committee of 100, American Attitudes Toward Chinese Americans and Asian Americans at 12, 15 

(Apr. 25, 2001). 

II See id. at 13; Thomas B. Edsall, 25% of us. View Chinese Americans Negatively, Poll Says, 

Washington Post at A-4, Apr, 26, 2001 (discussing Committee of 100 survey results). 

12 See Chandrasekhar, Charu, Flying While Brown: Federal Civil Rights Remedies to Post-9III Airline 

Racial Profiling of South Asians, 10 Asian L..I. 215, 216 (2003); Lan, Shanshan, Chinese Americans in 

Multiracial Chicago: A Story of Overlapping Racializations, 13 Asian L..I. 31, 37 (2006) (detailing 

various incidents of violence in Chinatown and adjacent areas). 

13 See Deborah Woo, The Glass Ceiling and Asian Americans: A Research Monograph at 44 (.Iuly 1994) 

(unpublished manuscript) at 44. 

14 Id. at 42 (citing to the U.S. Comm'n on Civil Rights, Economic Status of Americans of Asian Descent: 

An Exploratory Investigation (1988)) ("Glass Ceiling and Asian Americans"). 

I5 LEAP Asian Pacific American Pub. Policy lnst. & UCLA Asian American Studies Ctr., The State oj 

Asian Pacific America at 215-216 (1993). 

Testimony of Asian American Institute to 

United State" Senate Small Business Committee 

October 8, 2009 

Page 6 
83 

r leyL 

UNIVERSITY OF CALIFORN A 

TheltonE Henderson 

Center for Social Justice 

The Testimony of 

Michael Sumner, PhD 

at the Roundtable entitled: 

IfMinority Entrepreneurship: Evaluatin~ Small Business 

Resources and Programs' 

before the u.S. Senate Committee on Small Business and 

Entrepreneurship 

September 24, 2009 
84 

Thank you, Madam Chairwoman and members of the Senate Small Business and Entrepreneurship 

Committee, for the opportunity to discuss minority entrepreneurship. My name is Michael Sumner, and 

I am the Research Manager at the Thelton E. Henderson Center for Social Justice at the University of 

California, Berkeley, School of Law. My colleagues and I have researched the effects of equal 

opportunity programs on small businesses owned and operated by people of color and women of all 

racial and ethnic groups. 

With regard to equal opportunity programs, our research found evidence that: 

• Discrimination and disparity, both present day and resulting from the legacy of past 

discrimination, are still prevalent for entrepreneurs of color and female entrepreneurs of 

all races and ethnicities. 

• Equal opportunity programs can aid in leveling the playing field. 

• Removing or weakening programs intended to combat discrimination reduces equal 

opportunity. 

• Program participants had clear ideas on ways in which equal opportunity programs could 

help them more freely compete. 

Our research focused on the California transportation construction industry, where a Disadvantaged 

Business Enterprise (DBE) program has been operated by the State Department of Transportation, or 

Ca!trans. DBEs are small businesses majority owned and operated by people of color and women of all 

races and ethnicities. 

The Caltrans DBE program is very similar to the FederaI8(a) program run by the Small Business 

Administration. In fact, the DBE program and the 8(a) program share a Memorandum of Understanding 

(MOU) for mutual certification of small businesses owned and operated by people of color and women 

of all racial and ethnic groups. 

Our research focused on the effectiveness of the DBE program before and after the mid-1990s, when 

then-Governor Pete Wilson, Ward Connerly, and allies successfully curtailed equal opportunity 

programs. Beginning with an Executive Order in 1995 and culminating in the passage of Proposition 209 

in 1996, traditional affirmative action programs were ended in the state. With respect to public 

contracting, a federal exception required Caltrans continue its DBE program for federal awards, but the 

program was ended for state awards. 

In overview, our research found that equal opportunity programming enabled small businesses 

owned and operated by people of color and women of all races and ethnicities to more equally 

compete, and that the elimination of traditional affirmative action programs had a doubly negative 

Testimony of Michael Sumner, PhD 2 
85 

effect. Minority entrepreneurs lost a program designed to remedy past and current discrimination and 

disparity, and an apparent "chilling effect" may have created a climate in which discrimination and 

disparity became more widespread. 

We began our research by examining over twenty years of data regarding awards from Caltrans to DBE' 

and to non-DBEs, We found that on average awards to DBEs rose between the mid-1980s and the mid1990s, highlighting the success of the equal opportunity program. 

However, when equal opportunity programs were threatened and removed, federal awards to DBEs 

plunged. In 1996, the portion of awards to DBEs dropped by nearly 50 percent and there has been a 

sustained reduction of greater than 50 percent since the mid-1990s.' ln fact, a program that disbursed 

28 percent of awards to DBEs in 1994 now disburses only about 2 percent of awards to DBEs, in a state 

in which the population is over 50 percent people of color and almost 25 percent white women.' 

We found that the DBE program was seen as less helpful after most traditional equal opportunity effor 

were eliminated or weakened, according to contractors we surveyed - DBE owners and operators who 

were certified in 1996 and stayed in business for at least 10 years. We also found that businesses owne 

by African Americans and those owned by women, particularly women of color, struggled the most. 

In focus groups, interviews, and in-depth profiles, DBE contractors mentioned a number of barriers to 

their success. They mentioned an industry culture in which they perceived a "good old boy" network, 

one which systematically excludes people of color and women. These methods include keeping DBEs 

from gaining access to information about requests for bids and proposals and ignoring quality bids by 

DBEs. 

DBE owners said the race- and gender-conscious DBE program opened doors by helping DBEs build 

relationships with prime contractors. In their words, it encouraged prime contractors to "pick up the 

phone," However, after the end to traditional affirmative action programs, DBE firms reported that the 

"phone stopped ringing," 

I A 2007 Insight Center for Community and Economic Development study "State Policies and Programs for Minor 

and Women-Business Development" documented similar trends in Washington state, with increasing awards to I 

when equal opportunity programs were utilized and a sharp decrease after the anti-affirmative action Initiative 2 

was passed in 1998, 

2 An Availability and Disparity study commission by Caltrans completed in 2007 found that in California between 

2002 and 2006, there was significant disparity for most small businesses owned by people of color and women fc 

federal awards, It also found roughly twice as much disparity for state awards, for which no equal opportunity 

program operated, 

Testimony of Michael Sumner, PhD 
86 

As large amounts of capital are needed for loans, bonding, and insurance, both present day and the 

vestiges of historic discrimination tend to leave people of color and women undercapitalized. For 

instance, one contractor shared a story of being asked to provide collateral for a $200,000 loan he was 

attempting to secure. His attorney said that similarly situated White male clients were able to secure 

loans of that size without collateral. 

When the anti-affirmative action Proposition 209 passed, it was perceived by DBE contractors as 

reinforcing a system of exclusion. Although billed as a way a way to create equal opportunity, they felt it 

never addressed what many consider the root causes of the imbalance, such as the "good old boy" 

network. It also led to a "chilling effect" on the climate of diversity in the state. For example, one 

woman-owned firm that participated in our study reported that: 

"When Proposition 209 passed, I was working on $200,000 worth of projects. The day after 

Proposition 209 passed, the senior project manager walked up to me and said, 'Hey, Prop 209 

passed, and we don't have to use you anymore: I didn't say anything to him at first, but the next 

day, I told him that I wanted to talk to him about what he had said to me. I said, 'Did it occur to 

you that I've been working here for a number of years and that I have always finished on time or 

early ... and how many letters do you have from clients praising my cleanliness and 

professionalism?' Well, he didn't care. He just looked at me and said, 'Well, it's true. Prop 209 

passed, and we don't have to use you anymore.' The next year, my projects plummeted to 

$30,000. To this day, I have to call and remind clients that I'm in still in business" 

Unfortunately, our research indicates that the discrimination faced by this woman was not an isolated 

experience. Many women in the male dominated field of transportation construction confront a hostile 

working environment, facing both physical and emotional intimidation on the job, such as being 

randomly quizzed to prove their knowledge of the industry. Women also reported receiving the "run 

around" when trying to file a grievance or discrimination complaint. 

Although most were very concerned by the loss of a robust DBE program, contractors saw areas in 

which even the earlier, more vigorous DBE program could be improved. Contractors stressed the 

importance that whatever components are put into place, that they be effective and utilize best 

practices. 

For example, they observed that the DBE program only encouraged their participation at a 

subcontracting level, offering no help for reaching the more lucrative and stable prime contracting 

market. This finding from our research points out the tremendous importance of the 8(a) program 

which, as I understand it, focuses on prime contracting opportunities. 

Testimony of Michael Sumner, PhD 4 
87 

They also reiterated difficulties in areas such as securing bonding, financing, and insurance - which are 

core elements and key for capacity building in the transportation construction industry, and are areas in 

which racial and gender discrimination are widespread. 

In summary, our research points to the need for robust equal opportunity programs which utilize best 

practices. 

The programs should be championed by leaders in key positions and should work in partnership 

with ethnic Chambers of Commerce, professional networks, and advocacy organizations to 

counter discriminatory and isolated social networks, including "good old boy" networks. The 

programs should include elements that help entrepreneurs gain access to key information, 

expand their networks, and identify mentors. 

The programs should include help with securing bonding, financing, and insurance, access to 

which these entrepreneurs are likely to be denied because of historic and present day 

discrimination. 

The programs should minimize the burdens on entrepreneurs applying for certification. While 

certification for programs such as 8(a) or DBE need to weed out false front organizations, 

minimizing paperwork and creating MOUs with other contracting agencies can avoid 

certification from becoming unduly burdensome. 

• The programs should promote prompt payment, unbundled contracts, and increased lead-time, 

elements that are race- and gender-neutral. 

The programs should include a data collection and analysis mandate. Trends should be studied 

over time rather than focusing on year-to-year trends to ensure the utilization of best practices. 

The research I have mentioned today is available in more detail in our reports, "Free to Compete? 

Measuring the Impact of Proposition 209 on Minority Business Enterprises" and "A Vision Fulfilled? The 

Impact of Proposition 209 on Equal Opportunity for Women," which are freely available on our website, 

www.law.berkeley.edu/HendersonCenter.htm. I am also submitting copies of the reports with my 

testimony today and ask that it be made a part of the record. 

Thank you very much for your consideration. 

Testimony of Michael Sumner, PhD 5 
88 
89 
90 

Fl'ee to Colftpete? 

Measuring the Impact of Proposition 209 

on Minority Business Enterprises 

Table of Contents 

Executive Summdry 

Litera.ture "c'ne'N" .... "."" .. ". 

Results: MBE Survival and Awa~d Access 

Results: Survey" 

Results: Focus Groups and Interviews,., 

Contmctor Pronles 

Discussion 

Recommendations 

12 

lG 

"." 20 

34 

48 

AUGUST 2006 
91 

Executive Summary 

Affirmative action programs wcre initiated at thc 

federal level in the 1960s to level the playing field for 

people who had been excluded from equal opportunities due to discriminatory laws and biased practices. 

These programs, which developed over the following 

two decades at the federal, state, and local levels of 

government, were designed to expand the participation of people of color and women in higher education, 

public contracting, and public employment. Following 

the 1989 Supreme Court decision in City of Richmond 

v. J.A. Croson Company, public contracting affirmative 

action programs throughout the country underwent a 

considerable amount of reconstruction. As a result of 

this decision, race~conscious affirmative action prow 

grams in public contracting needed to be supported 

by research demonstrating the prevalence of discrimination and underutilization of firms owned by 

underrepresented groups. In California, the legality of 

all race-conscious affirmative action programs, even if 

supported by findings of underutilization, was put into 

question when a majority of voters passed Proposition 

209, the California Civil Rights Initiative, in 1996. This 

law ended race~conscious goals and affirmative action 

programs that were designed to facilitate equal access 

to public education, contracting, and employment. 

California's transportation construction indus~ 

try is the source of over $950 million in public contracts 

from the federal portion of awards alone. As the primary granting agency fortransportation construction, the 

California Department of Transportation (Caltrans) 

has strong potential to affect wealth and employment 

among California's racially and ethnically diverse 

popUlation. Before Proposition 209, Caltrans administered a race~conscious Disadvantaged Business 

Enterprise (DBE) program designed to increase the 

level of participation of businesses considered to 

be disadvantaged in all federal and state contracting activitics. The DBE program includes Minority 

Business Enterprises (MBEs), which are firms owned 

and run by contractors of color, as well as Women 

Business Enterprises (WBEs), and Disabled Veteran 

Business Enterprises (DVBEs). The implemcntation 

2 FREE TO COMPETE? 

of Proposition 209 and subsequent legal battles ended 

Caltrans' race-conscious DBE program for all but the 

federal portion of awards. The results of a disparity 

study commissioned by Caltrans expected in 2007 may 

restore a race~conscious program, but as of this report 

the program is race-neutral. 

In 2006, the Discrimination Research Centcl 

(DRC) set out to measure the impact of Proposition 

209 on businesses that were certified as MBEs in 1996 

Free to Compete? intends to clarify how Caltrans 

race~conscious affirmative action program affected 

transportation construction companies owned by 

people of color both before and after Proposition 209 

Using a four-pronged approach, DRC analyzed MBE 

survival and award access, surveyed transportation 

construction contractors whose surviving businesses 

were certified MBEs in 1996, led focus groups with 

MBE owners, and conducted in-depth case studies 

Using this multi-method approach, DRC document 

ed a significant impact of Proposition 209 on MBEs 

Among DRC's key findings are: 

Only one-third of certified MBEs in California's 

1996 transportation construction industry are still 

in business today. In 1996, Caltrans listed 3,269 

transportation construction contractors who 

were certified as Minority Business Enterprises. 

Out of those businesses, 32 percent continued to 

be in operation. However, without a comparative 

figure for an appropriate non-MBE comparison 

group in the transportation construction industry, the interpretation of this survival rate is unclear. 

• After the passage of Proposition 209 in 1996, MBEs 

experienced a greater than 50 percent reduction of 

total awards and contracts from Caltrans, In the 

nine years leading up to the passage of Proposition 209 in 1996, MBEs received, on average, 16.0 

percent of award revenue for Caltrans projects 

with federal funding. However, this amount was 

reduced to 7.9 percent of award revenue in lbe 

nine years after the passage of Proposition 209 in 
92 

1996. DRC found that although MBEs always received over ten percent of total awarded revenue 

before 1996 (with the percentage reaching as high 

as 20.1 percent in Fiscal Year 1994), participation 

by MBEs never reached above ten percent of total revenue awarded after 1996. The number of 

contracts awarded to MBEs has declined over 50 

percent since Fiscal Year 1999, the first year these 

records were available by ethnicity for MBEs. African American-owned MBEs showed the largest 

reductions relative to other MBEs. 

MBEs reported that the aspects of the federal raceconscious DBE program that were the most helpful hefore 1996, such as good faith efforts by prime 

contractors and pre-bidding conferences, were less 

helpful after 1996, After Proposition 209 passed, 

a OBE program for federal funding still operated, but it was much smaller in scope than previously. In general, surviving MBEs did not find 

the OBE program to be very helpful before or after 

1996. The fiduciary aspects of the program, such 

as assistance with loans and bonds, were seen as 

significantly less helpful than other aspects of the 

program, both before and after 1996. 

• Among surviving MBEs, those owned by African 

Americans and women of color have experienced 

more of an impact from Proposition 209 than 

other MBEs. Following Proposition 209, most 

of the surviving MBEs remained steady or grew 

in terms of the number of contracts received per 

year, total revenue, the number of employees, and 

the number of services offered. However, African 

Amcrican- and women-owned MBEs, on average, 

did not fare as well. 

Surviving :viBEs could not have initially succeeded, 

or maintained their succ~, without incentives in 

place that helped provide equaI access to bids, Focus 

groups and in-depth profiles reveal that MBR owners face many financial, social and political obsta~ 

des to overcoming a "good old boy" network. Contractors of color agreed that success and survival 

are always contingent upon positive professional 

relationships and skill, but that a lack of access to 

projects has hindered growth for some. 

This study found significant barriers for 

contractors of color who seek to participate on 

equal footing with their white counterparts in 

California's public transportation construction industry. Assuming that it is a compelling interest for 

California to support the expanded participation of 

people of color in the transportation construction 

industry, ORC suggests that public agencies partner with ethnic Chamber of Commerce chapters and 

advocacy, research, and community organizations 

to provide technical assistance for MBEs regarding 

their initial access to this industry. As part of any existing or new OBE program designed to foster equal 

opportunity, these efforts would also sustain and 

grow MBEs in order to promote healthy competition 

among equally prepared and resourced candidates. 

DRC also recommends continued research on the 

impact of anti-affirmative action law and policies, to 

further illuminate the extent to which they have impacted not only surviving certified MBEs, but also 

firms that did not survive, those that did not maintain 

MBE certification, and those that have launched in the 

post-Proposition 209 climate. _ 

DISCRIMINATION RESEARCH CENTER 3 
93 

Introduction 

In an era of racial segregation and epidemic poverty, 

President Lyndon B. Johnson proposed a series of corrective responses to fulfill the civil and human rights 

that had previously been denied to people of color. As 

a way to foster a culture of inclusion in employment, 

and later in education, affirmative action programs 

were initiated with the intention that they would open 

doors for those populations previously locked out by 

centuries of slavery and servitude, decades of Jim 

Crow segregation, criminalization, and other cultural 

and institutional measures. 

Between 1969 and 1989, race-conscious remedies to discrimination in public contracting expanded 

throughout state, city, and local governments.' While 

programs varied among localities, many included outreach, training, and mentorship programs as tools to 

strengthen the competitiveness of Minority Business 

Enterprises (MBEs). Several of these programs also 

included race-conscious participation goals, such as 

procurement set-aside programs, diversity goals, and 

incentives, to increase MBE utilization and establish 

a climate in which business owners of color could 

competitively bid and receive public contracts. Those 

decades saw impressive growth in the number of firms 

owned by people of color. 

The Dismantling of Affirmative Action 

in Public Contracting 

Regents ~f the University of California v. Bakke was 

one of the first cases to challenge affirmative action, 

specifical1y in higher education admission decisions. 2 

However, it was not until the late 19808 that efforts 

were made to dismantle affirmative action in public 

contracting. The 1989 Supreme Court decision in 

City of Richmond v. J.A. Croson Company' fed growing national debate on affirmative action in public 

contracting. In order to use race-conscious affirmaI Wainwright, 1. S. (2000). Racial Discrimination and Minority 

Enterprise. New York & London: Garland Publishing, Inc. 

A Member of the Taylor & Francis Group. 

, 438 U.S. 265 (1978). 

3 488 U.S. 469 (I989). See legal review for further explanation. 

4 FREE TO COMPETE? 

tive action measures, the Court decided that entities 

must first document discrimination or under-representation against specific groups of people, and 

then create narrowly tailored measures to address 

this discrimination, using race-conscious measures 

on1y where race-neutral means arc not sufficient.4 

As a result, MBE programs, which numbered over 

200 nationwide in 1989, as well as any proposed af, 

firmative action plans, needed disparity studies to 

provide evidence of a gap between the availability 

and utilization rates of MBEs. Many affmnative 

action programs that were developed to increase utilization of people of color in public contracting were 

affected by this decision, including those adminis, 

tered by the California State Personnel Board and 

the Office of Small and Minority Business (OSMB).5 

In California, MBEs were further jeopardized in 

1995, when then-Governor Pete Wilson vetoed a bill, 

sponsored by then-Assemblymember Barbara Lee, 

which would have commissioned a statewide study 

to support participation goals for MBEs, Women 

Business Enterprises (WBEs), and disabled person, 

owned business enterprises. After the veto, state 

agencies that still had participation goals, such as 

the Department of General Services, Department 

of Corrections, and Department of Transportation 

(Caltrans),6 were at risk of being dismantled in eourt 7 

Later in 1995, Wilson issued Executive Order W,124, 

95, which required all state agencies to dismantle 

H preferential treatment requirements" that exceeded 

federal or slate law. 

~ Bendick, Jr., M. (1990, Spring}. "The Croson Decision Mandates 

that Set-Aside Programs be Tools of Business Development." 

George Mason University Civil Rights Law Journal. 1(1),87-104. 

5 Ong, P. (1997, October). "Introduction." In P. Ong, ed., The Impact 

of Affirmative Action on Puhiic-.)'ertor E'mploymmt and Contracfing 

in California. Berkeley, CA: California Policy Seminar. 9(3), 1-7. 

6 California Department of Transportation, Caltrans, and 

CA DOT are used interchangeably in this report. 

7 Jung, D. & Wadia, C. (1996, February). Alfirmative Action and 

the Courts. Sacramento, CA; Public Law Research Institution. 
94 

The 1990s show a long record of attempts in 

California to further remove affirmative action measures 

in public education, hiring, and contracting through 

efforts in the Assembly, Senate, and on the ballot. All 

attempts were defeated in committee until Proposition 

209, also known as the California Civil Rights Initiative, 

reached the baUot in November 1996. This proposition 

passed by 55 percent of the vote and legally ended many 

affirmative action programs throughout the state. With 

the passage of Proposition 209, Wilson presented a list of 

30 statutes that violated the new amendment. including 

a range of Ia\vs relating to affirmative action in educa~ 

tion, government, health and safety, labor, and public 

contracting and hiring. As a result, state and some fed~ 

eral race-conscious measures designed to boost MBE 

participation in public contracting were deemed illegal 

in California. However. some programs continued. including the Cal trans Disadvantaged Business Enterprise 

(DBE) program, a race-conscious program justified by 

federal transportation funding requirements' Thus, 

the MBE program was merged into the DBE program. 

which consisted or firms owned by people of color, women of all ethnicities, and disabled veterans. For MBEs. 

the program was allowed to operate only for the federal 

portion of awards." 

Proponents of Proposition 209 argued that 

legislative responses to discrimination should emphasize individual merit rather than special privileges and 

thereby end preferential treatmcnt.JO Opponents of 

Proposition 209 argued that its language was misleading 

to the public. Language used in the proposition suggested that affirmative action programs were providing an 

unfair advantage to candidates who were perceived as 

under-qualified rather than providing opportunity to 

qualified yet historically excluded individuals. After sur-

"I Chung, L McCabe. L, Seigel, S" & Gen, S. (2006. June). 

Experience.l, Percepliolls, and Pnji'rel1(cs of CaIrraJ1s' CcrtUicd 

DBEs. San Francisco, CA: San Francisco State University Pllblk 

Administration Program & Asian. lnc. 

~ See legal review for further explanation, 

10 Jahhm. N.W. (2001), "Affirmative Action and thc ~tigl11a of 

Gender and Ethnieity; Californi<l in the 1990's: Journal of 

Asian and African Studies, 36(3), 253~274. 

viving a number of legal and constitutional chal1enb'es, 

Proposition 209 went into effect in 1997Jl 

As of this report's publishing, a decade has 

passed since Proposition 209 disputed Lyndon B. 

Johnson's proposal that America correct a discrimi~ 

natory past through race~conscious measures. Since 

the passage of Proposition 209, most research on its 

impact has focused on higher education, resulting in 

a paucity of research to measure its effects on M BEs 

seeking public contracts. 

Free to Cornpete? Aleasuring the Irnpact of 

Proposition 209 on Minority Business Enterprises 

reports on the ways in which the removal of race-conscious programs affected public contractors of color 

in California. This report examines whether MBEs 

have been provided with the equal opportunity to 

compete in California's transportation construction 

industry, focusing on those contractors who work 

with Caltrans. This report seeks to answer the question that is at the core of President Johnson's vision 

of how to provide equal opportunity for communities of color: Are MBEs free to compete? • 

II Federal courts upheJd the constitutionality of Proposition 109 

in Coolitionjbl" Economic Equily v. rVil,)"(!I1, 122 E3d 692 (9th Cir. 

1997). See also legal rcview for further explanation, 

DISCRIMINATION RESEARCH CENTER 
95 

Legal Review 

On a national scale, affirmative action programs designed to increase MBE participation experienced 

considerable reconstruction following the 1989 Supreme Court decision in City of Richmond v, J A. Croson Company." After the passage of Proposition 209 

in 1996, further debate about the constitutionality of 

affirmative action in public contracting played out in 

California courts. This reVIew highlights relevant major cases and their impact on public contracting in 

California's transportation industry. 

Affirmative Action and Strict Scrutiny 

In 1989, seven years before Proposition 209 was 

passed in California, a U.S. Supreme Court decision 

did much to create the framework within which future 

affirmative action programs would be built. In the decision of City of Richmond v. J.A, Croson Company,13 

the United States Supreme Court declared that the 

city's race-conscious affirmative action program was 

unconstitutional under the Fourteenth Amendment"s 

Equal Protection Clallse, which allows for the use 

of race-based measures to remedy the effects of 

past discrimination if they survive "strict scrutiny," the highest standard of judicial review in the 

United States. 

To pass strict scrutiny, race-conscious affirmative action programs must follow t\"O criteria. 

Tn the first. the program mllst serve a compelling 

governmental interest. The Supreme Court allowed 

government entities to take remedial measures to 

ameliorate the effects of current and past discrimination that they participated in creating. Second. 

the program must be carefully defined to meet the 

narrow tailoring requirement, which states that only 

those racial groups with a demonstrated history of 

discrimination should be included. As such, all affirmative action programs that make classifications 

on the basis of race need to be supported by facts 

indicating a presence of discrimination, and the 

488 u.s. 469l!989). 

I' /hid. 

6 FREE TO COMPETE',' 

programs must include effective and efficient means 

of removing the impact of discriminatioll. 14 To do 

this, government entities should consider race-neu~ 

tral alternatives in addition to race-conscious ones, 

and the programs they enact should have a reasonable expiration or renewal date. Attempts should 

also be made to minimize the harm or disadvantage endured by individuals not benefiting from a 

program.;5 While the strict scrutiny test allows for 

carefully crafted ordinances. policies, and statutes 

to exist, these same ordinances, policies, and statutes, no matter how meticulously drawn up, would 

likely be considered illegal in California in the years 

following the passage of Proposition 209. 

Analyzing Proposition 209: Discrimination 

and Preferential Treatment 

Proposition 209, adopted as Article I. Section 31 in 

the California State Constitution, drastically changed 

the fate of affirmative action in California. Section 31 

declares that: ';'the state sha11 not discriminate against. 

or grant preferential treatment to, any individual or 

group on the basis of race, sex, color, ethnicity, or na· 

tional origin in the operation of public employment. 

public education, or public contracting:'16 The law 

applies to state and local governments such as cities. 

counties, and municipal districts. Since its passage. 

Proposition 209 has been challenged, analyzed, and 

examined in court, consistently resulting in a broad· 

ly defined ban on preferential measures created with 

the intent to protect the interests of communities that 

have faced historical discrimination, 

In the 2000 California Supreme Court case 

Hi- Voltage J.Yire Works, inc. v. City o/San Jose,17 the 

Court struck down an outreach program established 

by the City of San Jose that was designed to increase 

participation by available MBEs and WBEs in pub· 

'4 Ibid. 

I' See Grulter, 539 e<s. at 341. 

16 Cal, Const. art. I. sec. 3!(a) (West 2006). 

F 24 Cal. 4th 537 (2000). 
96 

lie works contracting. Due to Proposition 209. the 

Court rejected the City of San Jose '$ race-conscious 

outreach program, which included a participation 

component that authorized quotas and set-asides 

that were preferential in nature.H In IIi-Voltage, the 

Court decided that the terms "discriminate" and 

'preferential treatment," as used in Section 31, were 

to be defined as the Civil Rights Act of 1964 originally defined them: "discriminate" means to "make 

distinctions in treatment; show partiality or prejudice." and "preferential"l11cans "giving of priority or 

advantage to one person ... over others."19 This interpretation of the Civil Rights Act reflected the Court's 

belief that: "however it is rationalized, a preference 

to any group constitutes inherent inequal1ty.'·~n 

Redefining "Discrimination" 

Opponents of Proposition 209 have attempted to 

challenge the way that key terms such as "racial discrimination" have been defined by the California 

Supreme Court. In 2003, state legislators passed and 

then-Governor Gray Davis signed into law Assembly 

Bill No. 703, which was codified as California 

Government Code Section 8315.11 This law declared 

that "racial discrimination" and "discrimination on 

the basis of race" were not defined within Section 

31(a) of the state constitution, as was decided in 

Hi-li'oltage. Instead. the terms were those defined 

in the International Convention on the Elimination 

of All Forms of Racial DiscriminationJ2 as adopted 

by the General Assembly of the United Nations and 

I' Ibhtat 562 

I~ Ibid. at 559-60. 

,1' Ihid. at 56J. 

,1 Cal. Gov. Code § 8315 (2006 West). 

'2 In defining dISCriminatIOn, thc Internationa! Comcntion states 

in part that "special measures taken for the sole purpose of 

sccuring adequate advancemcnt of certain racial or ethnic 

groups or individuals requiring such pfotection as may be 

necessary ill order to cnsure such groups Of indIvIduals equal 

enjoyment or exercise of !mmun 

freedoms shall 

ratified by the United States Senate as a treaty on 

June 24, 1994. 

The City defendant in Coral Construction, 

Inc. v. City and County of San Francisco argued 

that Congress' ratification of the International 

Convention "preempt[ed] Proposition 209 by operation of the Supremacy Clause of the United States 

Constitution."13 The Superior Court, however. rejected the defendant's contention, arguing that 

California Government Code Section 8315 included 

qualifying language that provided that affirmative 

action measures would only fall outside of the definition of discrimination if "such measures Idid] 

not. . .lead to the maintenance of separate rights for 

different racial groups. The Court prohibited the 

usc of affirmative action by San Frandsco because 

"the City's publie contracting program violates this 

provision by seeking separate rights for different 

racial groups and women through its public contral:ting program."c< The Court also reasoned that 

the United States Senate ratified the treaty "subject to reservations," thus nullifying its ability to 

Cowl Consl(Ucriof/, ~o. 4~!~49 at *1-t 

>, lhid. at *15 (citing Cal. GO"\."t Code ~ 83J5(h)(4)). 

" Ibid, 

DISCRIMINATION RESEARCH CENTER 7 
97 

Legal Review 

preempt Proposition 209's ban on preferential treatment within California.16 

Challenges within the Courts 

Several court challenges to Proposition 209's ban 

on preferential programs in public contracting have 

involved the Equal Protection Clause, In the case 

Coalition for Economic Equity v. Wilson. 27 pro-affir~ 

mative action organizations argued that Proposition 

209's elimination of local governments' abilities to 

enact preferential treatment programs for women 

and people of color, and the transfer of such power to 

higher and more remote levels of the state, imposed 

an unequal political structure that ran counter to 

the Fourteenth Amendment's equal protection guarantees." The District Court concluded that the extra 

burden on women and people of color to petition for 

preferential programs could not withstand the exacting review of strict scrutiny, and thus violated the 

Equal Protection Clause." 

The Ninth Circuit Court of Appeals disagreed 

with the District Court's reasoning and rejected the 

plaintiffs' claim, concluding that Pfoposition 209 

was not discriminatory in nature and did not deny 

women and people of color equal protection of the 

law because it applied in a non-discriminatory manl1er to all individuals living in the state." The Court 

held that Proposition 209 did not sefve "as an impediment to protection against unequal treatment but as 

an impediment to receiving preferential treatment,"}) 

It concluded that even though the Equal Protection 

Clause allows for race- and gender-conscious measures to remedy the effects of past discrimination, 

the clause does not mandate these measures. 

:;6/hul 

2" Coalition/or Economic Equity I'. Wilson. 121 E3d 692, 703 

(9th Cif. !997). 

n Ihid. at 702-03. 

~9 Ibid. at 703. 

111 lhid. at 706-07. 

II fhi/I, al 708. 

8 FREE TO COMPETE? 

Seven years after Coalition for Economic 

Equity, the City and County of San Francisco used 

a similar defense to protect its Minority/Women! 

Local Business Utilization Ordinance that granted 

a number of benefits and preferences to MBEs and 

WBEs, including a bid discounting program for MBE 

and WBE prime contractors. Tn Coral Construction, 

Inc. v. CUJ-! and County of San Francisco,J2 the defendant city challenged the constitutional validity 

of Proposition 209, afguing that "the state may not 

grant power to local authorities over contracting de· 

cisions and then selectively withdraw that power in a 

way that burdens minorities. The Superior Court 

rejected the defendant city's claim.:'"1 

Anothef post-Proposition 209 Fourteenth 

Amendment claim was advanced in L. Tarango 

Trucking v. County of Contra Costa. 35 In L. Tarango 

a group of MBEs and WBEs brought a class action 

against the County of Contra Costa alleging that the 

County failed to rigorously enforce its existing af 

firmative action ordinance and failed to collect data 

on its utilization of women and minority contrac 

tors, and that both were violations of the Fourteenth 

Amendment. As a result of Proposition 209, the coun 

ty suspended its MBE/WBE program and adopted a 

new outreach program that encouraged outreach to 

MBEs, WBEs, Small Business Enterprises (SBE), and 

Local Business Enterprises (LBE) "without setting 

specific numerical goals for utilization of those types 

of businesses in County contracts."36 After cvaluat 

ing the facts of the case, the U.S. District Court held 

that the County of Contra Costa's failure to actively 

\, Coral Construction. Inc. v. Cit)' and County (!fSan Francisco. 

California Stlperior Court. County of San Fmncisco, 

No. 421249 (July 26, 2004). 

Ihid. at *!S. 

1,1 Ibid. at *16. 

I' L. Tarango Trucking v, County of Contra Costa, 

181 F. Supp. 2d !On (N.D. C<lL 20(1). 

v, IhM. at 1034-35, 
98 

enforce its outreach 

program was not 

product of intentional 

discrimination.J7 

Although not directly related to Proposition 

209, the Equal Protection 

case i\1onterey j\1echanical 

Co. v. WiL'iOn 38 hadimportant 

effects on the transportation 

construction industry. In 

lvlonterey Mechanical, the 

Ninth Circuit Court of 

Appeals struck down a 

California statute that required general contractors 

to either subcontract-or demonstrate good faith efforts to subcontract-IS percent of their work to 

MBEs, five percent to WBEs, and three percent for 

disabled veteran-owned businesses," The Court held 

that this statute violated the Equal Protection Clause 

of the Fourteenth Amendment because the law was 

not designed to remedy past discrimination against 

people of color and women who have not been specifically discriminated against by the state ofCalifornia 40 

The Court also decided that the law needed to be narrowly tailored in a way that would allow it to address 

past discrimination while maintaining the rights of 

non-DBEs.41 Since the defendants did not provide 

specific proof that each orthe groups included within 

the statute's definition of the term "minority,,·n actu-

'Illid. 

\~ A-ionlerc), Mecitanit'al Co, 125 F,3d at 714 (9th eif. 1997). 

l~ [hid. at 702, 704. 

"0 Thid. at 712-13. 

.~J [hid. at 714. 

.)1 The statute specifically defined 'minority" in thc !{)lIowing manner; 

"Minority:' for purposes of this section. mcans a citizen or 

Jawful permanent resident of the United States who is an ethnic 

person of color and who is: B!a<:k (a person having origins in 

any of the Black racial groups of Africa); Hispani<: (a person 

ofMeJlican. Puerto Rican. Cuban. Centra! or South American, 

or other Spanish or Portuguese culture or origin regardless of 

race); Native American (an American Indian. Eskimo. ;\leut. 

ally suffered discrimination in the awarding of 

contracts by the state, the 

Appellate Court conclnded 

that the statute failed to 

meet the narrow tailoring 

prong of the strict scrntiny 

test. As a consequence, the 

Court reasoned, many affirmative action programs 

are over-inc1usiveY and 

this particular statute's use 

of racial classifications violated the Equal Protection 

Clause of the Fourteenth Amendment." Following the 

Monterey Mechanical Co. v. TVilson decision in 1997, 

Caltrans eliminated its MBE program, but continned 

its race-conscious DBE program. consistent with 

federal funding requirements. 

Efforts to Limit the Reach of Proposition 209 

Some federal statutes and regu1ations permit or mandate the use of affirmative action-type programs to 

remedy past discrimination, so another strategy that 

some local governments and affirmative action advocates have used to circumvent the broad reach of 

Proposition 209 has been to utilize the federal funding exception contained within Section 31(e) or the 

California state constitution . .J~ 

or Native H<lwaiian): Pacdk~Asial1 (a 

from Jap'i/1, China, Taiwan. Korca, 

the Philippines. Samoa. Guam. or the United States Trust 

Territories of tbe PacIfic including the Northern Marian<ls); 

Asian-Indian (a person whose origins are from India. Pakistan. 

or Bangladesh); or any other group of natural persons identified 

as minorities in the respective project specIfications of an 

awarding department or participating local agency. 

Ca!. Pub. Cont. Code § 10115.1(d) (West 20(6). 

-I' Supra. note 3R, 

4·' lhui 

4' Section 31(c) siates that '·nothing in this section shall be 

interpreted as prohibiting action which must be laken to 

establish or maintain eligibility for any federal program, where 

DISCRIMINATION RESEARCH CENTER 
99 

Legal Review 

In a 2004 case, C & C Construction, Inc. v, 

Sacramento ,Wunicipal Utility District,46 a California 

Court of Appeal evaluated the legality of the 

Sacramento Municipal Utility District (SMUD) 

1998 Equal Business Opportunity Program. SMUD 

implemented the affirmative action program 

after commissioning a disparity study in 1998. Even 

though it documented improvement in the utilization of contractors of color over the years since its 

previous disparity study was commissioned in 1993, 

it revealed that "a statistically significant disparity 

continued to exist among certain subsets of minority contractors in identified categories of SMUD"s 

contracting:'4~ This affirmative action program provided a five percent price advantage and extended 

evaluation credits for prime contractors that met 

a subcontractor MBE/WBE participation goal of 

eight percent on certain proposals;w Additionally, 

the program mandated broad outreach procedures 

to provide notification of requests for bids to subcontractors;''} and it also required contractors to 

document their good faith efforts, "0 The bid of any 

ineligibility would result in a loss of federal funds to the state." 

Cal. Canst. art. L sec. ]!(e) (West 2006). 

,~ C&C COflstrllc(icm, 122 Ca!. App. 4th 284 (3d DisL 2004). 

4- lhiti. at 294. 

"~ Ibid. at 294. 

~9 These procedurl's include written evidence that 

the contractor has: (1) attended a SMUD affirmative action 

program briefing so that the contractor may fully understand 

the program requirements, (2) requested assistance from 

SMCD's afJinnati\e actlOll plOgnl1l1 (lnke, en identified 

specified units of work that imprme the hkelihond of 

subcontracting, (4) contacted potential minority subcontractors 

not less than 10 days prior to the proposal due date. and (5) 

contacted interested minority subcontractors subsequent to the 

initial contact to determine with certainty whether they were 

interested In performing the s.pccific work on the project 

,I' In order to meet the good faith requirement to comply with 

the SMUD program's goals. contractors had to document 

their efforts to do the following: (l) Efforts to comply with the 

notifi.cati('n procedures. (2) advertisements at knst 10 days prior 

contractor who failed to meet these procedures 

would subsequently be rejected by SMUD. 

SMUD argued that while its program constituted "preferential treatment" under Section 31 ofthe 

California Constitution, its program was nonethe~ 

less permissible under the section's federal funding 

exception because SMUD received funding from 

the Departments of Energy (DOE), Defense (DOD). 

and Transportation (DOT). Each of these federal 

departments and their agencies required that any 

entity that receives federal funding would be bound 

by regulations adopted in compliance with Title VI 

of the Civil Rights Act of 1964, whieh forbids discrimination based on race, color, or national origin 

in all programs that receive financial assistance from 

the federal government. 51 SMUD argued that its afH 

firmative action program was in compliance with the 

regulations issued by the DOE, DOD, and DOT. and 

it would risk losing important financial assistance if 

it removed the program. 

Despite these federal regulations and the 

results of the disparity study. the Appellate Court 

concluded that SMUD's affirmative action program was illegal. The Court found that the federal 

departments called for the use of both race-neutral 

and race-based programs to remedy existing or past 

discrimination; they did not mandate solely the use 

of race-based measures. <;2 The Court also argued 

that even though SMUD commissioned disparity 

studies, it did not evaluate the effectiveness of race~ 

neutral methods to remedy discrimination, 53 While 

the Court accepted that there was empirical data 

American firms, 0) prO~ls!On oflllrormatlOl1 to tht" llrms 011 

m",,'''''''''"'. and reqUlremcnts for the sub~ontraets 

assistance in reviewing those plans and specifications, (4) 

written proposals received from the firms seeking subcontract 

work and, if rejected, reasons why the proposals were rejected. 

and (5) efforts to assi~t the firms contacted in obtaining' 

bonding. insurance and lines of credit, ifrequired. 

'\ 42 U.S.c. § ~WOOd (West 2006). 

<;: Supra, note 46, at 308~09. 

targeting African- 11 Ibid. 

1O F'REE TO COMPETE') 
100 

supporting the existence of past and ongolOg dlS~ 

crimination in the awarding of contracts by SMUD 

and in the Sacramento area. proof of such discrimi~ 

nation in public contracting did not justify the use of 

affirmative action. This Court opinion established 

judicial precedent that has made it more difficult for 

other municipalities to qualify for Section 3l's fed~ 

eral funding exception. 

[n this current legal climate, the ten years [01· 

lowing the passage of Proposition 209 have shown 

resistance from the courts to allow affirmative ac· 

tion programs for MBEs seeking public contracts. 

Even with empirical evidence and disparity studies 

indicating under~representation and potentially un~ 

fair practices. Proposition 209 has made it difficult 

for any county, city, or local municipality to main· 

tain or justify race·consclous equal opportunity 

action programs that could increase participation 

and development of businesses owned by contrac~ 

tors of color .• 

DISCRI\1rNATION RESEARCH CENTER 1; 
101 

Literature Review 

One of the Hrst models of affirmative action in 

public contracting was the Philadelphia Plan, implemented in the late 1960s by then-Assistant Secretary 

of Lahor, Dr. Arthur Fletcher. This program set up 

goals and timetahles for the participation of business 

owners of color on federal contracts in Pennsylvania. 

1'vlany programs were to follow in other cities; in 

1970 the U.S. Department of Labor announced that 

unless cities formulated their own measures for ending discrimination in the construction industry, the 

Philadelphia Plan prototype would be employed. 54 

Throughout the 1970s and 1980s. before Croson, federal, state, and local governments imp1emented a 

wide range of afflrmative action programs for MBEs 

by formally encouraging their participation in government processes. 55 These programs fell under two 

main categories: 1) those that used race as a factor 

in the awarding of contracts, and 2) those that increased the capacity of firms owned hy people of 

color. Included among efforts in the first category are 

programs such as source contracts. race-conscious 

set-asides, bid preferences, subcontractor compensation clauses, notification of bidding opportunities 

to businesses owned by people of color. the usc of 

good faith effort goals for prime or subcontracting, 

and the operation of certification programs to reduce false MBE fronts.'" Included among efforts in 

the second category are lending assistance programs 

to expand working capital, outreach efforts to bring 

more MBEs into existing networks, and technical assistance programs to help with bidding procedures. s7 

While the first strategy directly increased the number 

'4 Office of the AS$lstant Secn~tary fix Administration 

and Management. 'Nixon and Ford Administrations." 

In Retrieved March 14, 2006, from 

5'lIpra, note 1, 

<{, EnchauteguL M,E" Fix, M" Loprcst. P., von def Lippe, 

S,e., & Wissokcr. D, (1997). Do Miflority-Olrncd Businesses 

Gef a Fail' Share (~r Government Contracts? Washington, DC: 

The Urban Institute, 

<7 Supra, note 1. 

12 FREE TO COMPETE? 

of contracts awarded to MBEs 1 the second increased 

the number of MBEs that would be eligible and competitive in a public bidding proeess. 

While the Croson decision established stringent standards for race-conscious set-asides and 

procurement programs, it also acknowledged that 

past discrimination, current bias, systemic favoritism, and patterns of exclusion against people of color 

still remained a challenge for MBE development and 

viability.58 In recognition of these barriers, Croson 

allowed that certain MBE programs, if narrowly 

and appropriately tailored, could he developed to 

offset any discrimination against a certain group. 

Under Croson. any race-conscious program must 

provide a benefit beyond receiving a contract under 

the set-aside program; the program must additionally provide "opportunity to strengthen the firm-to 

develop a track record, enhance staff experience, or 

expand its scale of opcrations--so that it can more 

effectively compete for future contracts not covered 

by set asides:'" In theory, these programs would help 

to hoost business skills and ameliorate the detrimen~ 

tal effects of having unequal capital, less powerful 

networks. and discrimination in the market. 

Barriers to Minority Business Enterprise 

Development and Viability 

To remain competitive in a public bidding process. 

securing adequate financing and capital, particu~ 

larly working capital. is vital. For YlBEs, securing 

capital can present morc of a challenge than for 

white-owned firms.6tJ Historical discrirnination---resuIting in lower incomes, fewer assets, fewer personal 

contacts who are able to finance firms. and discriminatory bank and commercial loan practices~makes 

,1 Supra. note 56. 

;'\ Supra. note 4. p 9i, 

(". Supra. note 56: Sec also: BlallchHowcr, D.G. & Wainwright, 

Cambridge. MA: 7'J"ational Bureau of Economic Research. 
102 

establishing adequate capital 

a challenge for MBEs.61 In a 

study commissioned by the 

City of San Diego in 1995, 

MBEs reported that they 

had experienced discrimination in securing loans and 

that non-MBE/WBE suppliers had sold them supplies 

at a higher price than they 

would have charged white 

males.62 These factors work against the viability and 

growth opportunities of MBEs; many are ultimately 

prevented from increasing business volume and are 

delayed in bidding on large public contract opportunities. Some race-conscious programs allowed under 

Croson were designed to make securing capital more 

equitable: some set out to remove discriminatory 

lending practices, others developed loan programs 

set up by agencies and local governments, and others 

subsidized costs of insurance or bonding. 63 

Networks arc key to securing public contracts 

and developing a successful business. Businesses 

owned by people of color tend to lack networks with 

people in decisionMmaking positions to the same degree as their nonMMBE counterparts.64 These strong 

social ties .... ·-·dcveloped through business contacts 

and through education and social activity-"" create 

networks that are very difficult for MBEs to access. 

These networks control large sections of the pubJlc 

contracting market and have historically excluded 

new members based on race. ethnicity or gender. This 

type of "good old boy" network can create a powerful 

barrier to accessing opportunities to bid for businesses owned by people of color, especially women 

M DEGAlTMS. (1995, May). Ci(yo/Sun Diego MBE/WBE 

Predicate Study Report. V 1. San Diego, CA: City of San 

Diego. See a/sa: Blanchflo\vcr. 0.0 .. & Wainwright, L 

Ihid.; Supra. note 4. 

DEGA/TMS, [hid. 

P Supra, note 4. 

,,~ Supra, note 56. 

of color.'" While good faith 

effort requirements created 

by race-conscious programs 

were intended to lessen the 

effects of exclusionary networks, collusion and "bid 

rigging" remain as barriers 

to receiving subcontracts 

in public construction projects.06 MBEs have reported 

in interviews that bid rigging-when general contractors receive bids from 

several subcontractors and then a110w businesses 

within their network to know the lowest bid. essentially giving them a second opportunity to underbid··-is 

a practice that hurts MBE opportunity to compete 

on a level playing ficld.&7 Prime contractors can claim 

to have made a good faith effort to include MBEs on 

public projects while continuing to award subcontracts to those non-MBE businesses in their network.68 

Agencies and local governments can reduce the effects of favoritism by ensuring equal opportunity 

for MBEs and that the bid processes are fair, open, 

and impartial.1i9 

Another major barrier to the growth and 

competitiveness of MBEs is the negative stereotype that these firms are under-performing. Biased 

beliefs can also impede the progress of MBEs. 

Interviews with white males in the San Diego business community in 1995 revealed stereotypical and 

harmful attitudes regarding people of color's capabilities for owning or managing a businessJo In 

addition to providing major barriers for MBE participation in business opportunities. these negative 

attitudes also increase the pressure for MBEs to 

"< DEGA/TMS, Supra. note 61. 

f.(, Bl<lnch!lower. D.G., & Wamwnght. J., Supra. note 60. 

(,' !hid. 

M DEGA/TMS, Supra, note 6l. 

60 Supra. note 4 

'Itt DEGA/TMS. Supra, note 61. 

DISCRIMINATION RESEARCH CENTER 13 
103 

Literature Review 

perform better than their white male counterparts. 

While previous discriminatory treatment in employment, education. and training opportunities 

can negatively affect management practices and 

expertise.11 training and counseling can improve the 

overall business savvy of MBEs. Race-conscious setaside programs and bid systems can help to develop 

track records for MBEs, allowing them to access the 

larger breadth and depth of experience required to 

make them more competitive.7~ In a study commissioned by Caltrans, contractors recommended that 

the agency adjust the type and size of work (e.g .. the 

magnitude of individual contracts, the nature of the 

work, and the time available to complete the work) 

to make bidding more attractive,') If large government contracts are not broken down into smaller 

projects. small businesses cannot compete. and they 

must then rely on prime contractors awarding them 

subcontracts. This returns MBEs, which tend to be 

smal1er, to the problems experienced when competing against non-:vtBEs. as described aboveJ4 

Disparity Studies Reveal Under-Representation 

Disparity studies examine the "underlying factual predicate for race andlor gender-conscious 

preference programs for contracting and procurement in accordance with Croson. After the Croson 

decision, many state and local governments commissioned disparity studies to measure differences 

between the proportion of avuilable MBEs and the 

distribution of government contracts in order to 

determine whether underutllization of MBEs justifies a racc·consdous DBE program. These disparity 

I Supra. note 56: SeC' also: DEGA/TMS, note 6L 

'2 Supra. notes I and 4, 

-, Rouen. L. & Mitchel!. D.,J. (2005, October 24). Cali/im/ia 

Constl"llclion Market Analysis: Ca1lses oj"Bidding Trends and 

Dl"ision of Construction. om.:c of Construction Engineering. 

'4 Supra. note 56. 

" DEGAfTMS. SlIpra. note 61. 

H FREE TO COMPETE? 

studies have also documented the role that state and 

local governments, unions, prime contractors. bonding companies. suppliers and financers have played 

in perpetuating discrimination and blocking opportunity to succeed.~6 By showing that there are large 

and statistically significant disparities against a par~ 

ticular group of business owners who are people of 

color, a government entity can and should initiate 

or continue an affirmative action program.77 While 

these studies are important to build consensus regarding the need for affirmative action measures 

and for providing benchmarks for future evaluation, 

it is important to note that earlier studies have overlooked businesses that have gone out of business and 

do not include those entrepreneurs who have not had 

the opportunity to enter certain lines of business because of systemic discrimination and bias.~R 

Studies have consistently shown that par~ 

ticipation in public contracting continues to be a 

"f, Supra, note 56; Sec also: Blanehflower, D.G. & Wainwright. L 

nOle60 

Supra. note l. 

lbicl-
104 

challenge to communities of color both before the 

enactment and after the enforcement of Proposition 

209. In one study pre-Proposition 209, it was found 

that MBEs that relied heavily on government contracts were more likely than comparable small 

businesses to go out of business following Croson. 7

') 

In a study commissioned by the Department of 

Minority Business Enterprise of the Commonwealth 

of Virginia, so it was found that in the five-year period 

from 1997 through 2002. spending with MBE firms 

was less than .44 percent of total spending. The 

study, which controlled for management experience 

and owner education, found that substantial disparities existed particularly for African American, Asian 

American, and Native American construction prime 

contractors and subcontractors. In a 2005 disparity study commissioned by New Jersey. statistically 

significant disparity was found in construction and 

construction-related services for businesses owned by 

African Americans, Asian Americans, and Latinos.sl 

Many other disparity studies have been performed 

in states and municipal localities across the nation 

following Croson. Some of these include the states of 

North Carolina,82 Texas, and Maryland,S' as well as 

the City of San Dieg084 and an upcoming report for 

the City of Oakland."' In 1997, the Urban Institute 

analyzed the results of 58 disparity studies across 

the nation and found substantial disparity in gov-

~ Bates, T., & Williams, D. (1996, May). "Do Preferential 

Procurement Programs Bendlt Mlnority Business'?" 

The American Economic Reriew. 86(2).294-297. 

MGT of America. (2004. January 12), A ProcuremNlf Disparitr 

Study o/the Commonwealth of Virginia. Tallahassee, 

FL: Department of Minority Business Enterprisc, 

Commonwealth of Virginia. 

,1 Mason Tillman Associates, Ltd. State of .New Jersey 

Construction Services DL~parity Study. October 2005. 

~:? Office for Historically linderutllizcd Businesscs. {200}). 

JIisforicafly Underutili:::ed Businesses Annual Report. Raleigh, 

NC: State of North Carolina Department of Administration. 

SI Supra, note 56, 

M DEGA/TMS, Supra, note 61. 

0' Mason Tillman was commissioned to do this report in 2006. 

ernment contracting. The study found that MBEs 

nationally received 57 cents of each dollar that they 

would be expected to receive based on their total 

share of available contractors. S6 

Programs designed to level the playing field 

and ensure equitable utilization rates are allowed to 

exist because of the government's compelling interest to remedy their role in allowing past and current 

discrimination. Few researchers, however, have performed cost/benefit analyses au the monetary effects 

of afflrmative action programs on the government. 

One study, though it was limited in scope and examinined only short-term costs, suggested that the 

Caltrans affirmative action program raised the price 

of winning bids,R7 Other studies have suggested that 

increasing the participation rates of MBEs in public 

contracting and providing equal opportunity for everyone can increase the competitiveness of a bid and 

be more cost effective for governments.8R A reduction 

in competitiveness was such a concern for Caltrans 

that in 2005, a market analysis was commissioned 

to determine why the number of contractors bidding for Caltrans construction projects had declined 

in previous years. while the submitted low bids for 

these same contracts had increased relative to the 

department's estimates. As these factors increased 

necessary funding levels for new construction work, 

the analysis was to also determine whether these factors made up a trend of declining level of competition 

for contracts. RQ Caltrans sent a survey to contractors 

to find out the causes of the increa~ingly expensive 

,~ 5Jupra, note 56. 

B~ Murton, J. (2005, September). flo->\' Costly is Al}irmatirc Action? 

GOl'ernment Contracllllj; and Cali!iJrnia's PropositIOn ]09. Santa 

Cruz. CA: University of Santa Cruz Department of Economics. 

% Supra, note 73. See also: Ayres, I., & Cramton, P. (1996. 

April). "Pursuing: DefiCIt Reductiml through Diversity: 

I low Affirmative Action and the FCC lncrea!'~d Aucti,ln 

Competition. Stanford Law Rel'ielt': 48(4), 761-815; Maryland 

Genera! Assembly. (2005). Pro,uremel1l-Minonty Business 

Enterprise and Smal! Business Resen'e Pf()J.;rams. Hll 1432 fiscal 

and Policy Note. 

,'~ fbil", Rauen, L. & MitchelL D.J. 

DrSCRIMINATION RESEARCH CENTER 15 
105 

Litel'ature Review 

and reduced number of bids, and 70 percent of the 

respondents reported that they had reduced their 

volume of Cal trans bids or stopped bidding Caltrans 

jobs altogether. The most frequent recommendation 

that surveyed contractors gave to improve the pro· 

cess was that Caltrans should be fair; in other words. 

they should administer the contract fairly and deve!· 

op bettcr working relationships.9{) 

Impact ofRacewSpeciftc Remedies vs. 

Non Race~Specific Remedies 

Since 1982, the u.s. Department of Transportation 

(USDOT) has offered race·conscious programs to 

increase the participation of DBEs'll in federal high· 

way, transit, and airport contracts."2 Due to the 

federal funding requirement, Caltrans continued a 

race· conscious DBE program following the passage 

of Proposition 209, although the department did 

subsequently cut its DBE goal from 20 percent to 10 

percent. By 1997. actual DBE participation had fallen from 26 percent to 12 percent,93 While the actual 

participation rate was still above stated goals. it is 

notable that the rate had fallen almost exactly by the 

same percentage by which the goal had dropped. 

W Ibid, 

?I The Caltrans DRE program includes women, peopJe or color, 

and disabled veterans 

0" BlanchHower. D.G & Wainwrtght. L Supra. note 60. 

'" Ibrd. 

FREE TO CO\1PETE? 

Research has highlighted the role of raceconscious goals in the participation rates of DBEs. 

In 2000, USDOT allowed its grant recipients (e.g .. 

state transportation agencies such as Caltrans) to set 

annual goals for participation by MBEs and WBEs 

\\'ith either a race/gender·conscious component, or 

a race/gender-neutral component. or a combination 

of the twoY4 Researchers from the National Bureau 

of Economic Research (NBER) found that between 

2000 and 2002, 35 percent of state transportation 

agencies chose to adopt either predominantly or entirely race/gender-neutral DBE goals. The increased 

usc of race·ncutral goals in the implementation of 

transportation programs coincided with decreased 

participation of DBEs. From 1998 to 2002, the 

proportion of federal aid dollars awarded to DBEs 

decreased by 30 percent."> 

An analysis performed by the Urban Institute 

compared jurisdictions where race-conscious programs were in place with those without such programs. 

Disparity was greater in jurisdictions where there 

were no goals articulated in programs.96 After Croson, 

participation of MBEs in Richmond, Virginia re· 

duced drastically from 30 percent to four percent.'J7 

In a review of states and localities that removed race· 

conscious programs, NBER found that "once these 

programs arc removed, the utilization of MWBEs 

drops precipitou!:ily" and that "there is no evidence .. 

that suggests that when programs are removed utilization ofminoritics goes up or remains constant. The 

evidence is universally that utilization drops."9~ 

This downward trend continues. In January 

2006. the Alaska Department of Transportation adopted a race·neutral policy, and only one percent 

of contracts (out of SIlO mimon in available funds) 

J~ Ibid 

4< Ihid 

% Supra. note 56. 

""Ihid. 

(), /hid. 
106 

went to MBEs in the first half of 2006:" In Atlanta, 

MBE participation in city contracts declined from 

35 percent to 14 percent following an end to the 

city's equal opportunity program, and in the city 

of Tampa. participation of African American and 

Latino contractors fell by 99 percent and 50 percent, 

respectively.lOn In San Jose, participation by people of 

color in the city's prime contracts fell by more than 

80 percent immediately following the suspension of 

the city~s race-conscious programs. Similar patterns 

are visible in cities and counties across the country 

that have adopted race-neutral programs. 

In May 2006, Caltrans changed its OBE 

program from being a race-conscious program to 

a race-neutral program,Hll eliminating mandated 

participation goals and incentives for prime contractors to provide equal opportunity for firms owned 

by people of color. This change resulted from the 

ruling in the case of J-Vestern States Paving Co., Inc. 

1', Washington State Department of Transportation. 

I n this case, the Ninth Circuit Court of Appeals 

found that Washington State's transportation OBE 

program was unconstitutional because there was 

not sufficient evidence of discrimination to support 

a race-conscious program. The ruling applied to 

all states and localities within the Court's jurisdiction, which includes California. Caltrans evaluated 

its OBE program and found that available disparity studies conducted in California were limited in 

scope to a local government agency or a project, 

geographically and chronologically limited, and did 

not provide "statistical evidence" of discrimination 

"~ Campbell, M. (2006, May 14). "$ludy to Determillc if 

State DOT Discriminates in Contracting," Alaska Journc1/ 

o/Commertl!. Retrieved July 19, 2006. from http://www. 

alaskajournal.com/stories/051406/hom~20060514003.shtml 

BlanchOower. D.G. & Wainwright. L Supru, note 60. 

:(11 Supra. note 8. 

in transportation contracting. 10:'. A disparity study is 

expected to be released by Caltrans in 2007.103 

While disparity studies investigate underutilization of businesses, this study investigates the 

impact of Proposition 209 on the fate of businesses 

that were certified MBEs in the transportation construction industry in 1996, as well as on the trends 

in Caltrans awards over time. Free to Compete? 

}..1easuring the Impact of Proposition 209 on lUinority 

Business Enterprises lntends to clarify how Caltrans' 

race~col1sciou::; affirmative action program affected 

transportation construction companies owned by 

people of color before Proposition 209, and how its 

impact continued after the passage of Proposition 

209, through the examination of MBE survival and 

award access, a survey of transportation construction contractors whose surviving businesses were 

certified MBEs in 1996, focus groups with MBE 

owners, and in-depth case studies. _ 

Kempton. W. (2006, \-fay 1). [Letter to Transportation 

Construction Community], Retrieved July 19,2006, from 

http://w~\ .. \\.·.d0t.ea. gov/hq/h epl d oell me nts/d i rectors ."lct tct. pd f 

1(" fMd. 

DISCRIMINATION RESEARCH CENTER 17 
107 

Methodology 

ORC implemented a multi-method approach to collect data on the impact of Proposition 209 on MBEs. 

Empirical data in this report \vere gathered using four 

distinct methodologies: an aggregate analysis ofMBE 

survival and award access, a survey of contractors 

li'om surviving firms that were certified MBEs in 1996. 

focus groups consisting ofMBE owners, and in~depth 

case studies of MBE owners. 

A legal review provided an analysis of the 

legal arguments throughout the United States, noting trends at the national, regional, and local levels. 

A literature review examined previous research that 

documented the barriers facing MBEs and the impact of removing race-conscious DBE programs in 

California and other states. 

ORC collected and analyzed quantitative 

data provided by Caltrans from the Quarterly/Annual 

1405 Reports from Fiscal Year (FY) 1985 through 

FY 1998. the Quarterly Report of OBE Awards and 

Commitments from FY 1999 through FY 2002, and 

the Uniform Report ofOBE Awards or Commitments 

and Payments from FY 2003 through FY 2005. The 

total and relative amounts of revenue from Caltrans 

to MBEs were examined for trends before and after 

1996. 

Additionally. DRC collected data for 3,269 instate !inns listed in the 1996 volumes of the Department of 7}-amportatiol1 Disadvantaged Business (DB), 

State Woman Business Enterprise (SWBE), and State 

Minority Business Enterprise (SMBE) List that were 

certified as 5MBEs1

04 and that worked in the construction industry during that period. Due to a limited sample size, the 100 MBEs categorized as Spanish 

American and Portuguese American were not included in this study. A search by DRC researchers indicated that of the 3.169 companies that were certiflCd 

as 5MBEs in 1996 and categorized as being owned by 

Hispanic/Latino American, Asian Indian American, 

Asian Pacific American, African American, or Native 

American contractors. 1.005 were either verified as 

In this report, enterpri~es owned hy it person of color will 

be referred to as MBEs. 

FREE TO COMPETE? 

being in business or possibly still in business as of the 

beginning of 2006.105 

DRC contacted contractors from surviving 

MBEs in order to investigate their experiences since 

1996. A sample size of at least 24 respondents from 

each of the three largest groups (Hispanic/Latino 

American, Asian Pacific American, and African 

American) was desired. After receiving a letter alerting 

them that they may be contacted to complete a survey, 

MBEs were randomly selected in May and June of 

2006 to complete a 20-minute, 98-question survey. 

Surveys were administered by phone, fax, or mail. 

The survey investigated hO\v the Cal trans 

race-conscious DBE program was used before and 

after 1996 and also how MBE firms have changed in 

the past ten years. Programs in this analysis included: 

mentoring opportunities, networking events to 

establish relationships with primc contractors 

and suppliers, diversity goals, technical assistance 

programs. and pre-bidding conferences. Additionally. 

ORC measured changes in the size and viability of the 

firms since 1996. 

The analysis of MBE data yielded results 

indicating differences in the trends across time 

periods and differences among dcmographic groups. 

In order to assess the importance of these differences, 

a variety of statistical tests were conducted. 106 

Focus groups and interviews were conducted 

to collect the input of contractors and to identify 

and discuss themes in preliminary research findings. 

Five focus groups were held in regions throughout 

Ill' Differences in surv ival rates were analyzed using Chi-squares. 

1996 

were analyzed using paired t-tests. Differences in ch<lnges over 

time by ethnieity or sex were analyzed using independent samples 

t-tests on change scores from before 1996 until after 1996. 

and after 1996< For dichotomous variables. dif1"erenecs between 

ethnic groups Ot ~ex over time wcre analyzed using McNemar 

tesiS. and differences at each time point were analYYl.xJ lIsing 

Chi-squares. 
108 

California, including Orange County, San Diego, and 

the San Francisco Bay Area. Tn total, six men and 

two women participated in the focus groups, with 

five African American men. two Asian American 

women, and one Native American man contributing. 

These focus groups focused on Proposition 209, equal 

opportunity in bidding, and benefitsJchallenges of 

the MBE program. Participants included owners of 

construction firms who were survey participants and! 

or referred to DRC by business networks for people of 

color. The focus groups influenced who was chosen for 

in-depth interviews and shaped the themes in the rest of 

the report. Four MBEs were selected to participate in 

an in-depth interview detailing their work experience. 

Of these interviews. two MBE personal profiles were 

selected for inclusion in this report. 

Limitations 

The limitations of this study include the following: 

• The non-uniform method that Caltrans collects 

and presents data on MBEs, DBES, and WBEs 

causes comparisons to be less precise both for 

comparing data collected in 1996 and 2006, as 

well as for data collected within those years. Additional1y, the way in which firms are categorized 

as DBEs, MBEs, or WBEs makes it impossible 

to identify, with exact precision. the amount and 

number of contracts awarded to male and female 

contractors of color. Data from Caltrans are 

also not disaggrcgated by speciilc ethnicity for 

the Asian Pacific American and Hispanic/Latino 

American groups, limiting analyses for these populations. 

• At the time of this study, DRC was unabJe to obtain disaggregated data (via reports) on awards 

for state contracts. The method that Caltrans 

uses to report the percentage of contracts awarded to MBEs, DBEs, and WBEs includes projects 

with at least some federal dollars. Until FY 2002, 

the total awarded amount and amount awarded 

to MBEs consisted of both the federal and state 

portion of awards with at least some federal d01-

lars. However, starting in FY 2003, only the federal portion of these awards was documented. 

• The survey includes the common limitations that 

are associated with using self-reported data and 

data about recalled experiences from over ten 

years ago, 

[n some cases~ the sample size of the survey 

did not provide enough statistical power to determine whether apparent differences were statistically significant or due to random chance. Due to 

the small number of women-owned MBEs in the 

sample, caution should be used in the interpretation of results for women~O\\med MBEs. 

DRC sampled only businesses that were certified MBEs in 1996 and were still in operation ten 

years later. As the businesses that did not survive could not be surveyed, the sample will only 

be reflective of the businesses that survived. not 

those which failed. 

Despite these limitations, this report gives 

valuable new information, enlightening an area in 

which virtually no systematic information is otherwise available. This report constitutes one of the 

first systematic, data driven analyses of the effect of 

Proposition 209 on MBEs, By using multiple methodologies, DRC was able to examine trends that 

may only be noticeable as aggregate data affecting 

the survival of all MBEs, as the combined surveyed 

experiences of surviving firms, or in the detailed, 

personal experiences of MBE contractors. Findings 

that arc evident in more than one of these methodologies are worthy of special notice. _ 

DISCRIMINATION RESEARCH CENTER 
109 

Results: MBE Survival and Award Access 

Decline in MBEs 

In 1996, 3,269 transportation construction businesses were registered with Caltrans as Minority 

Business Enterprises (MBEs). Today. only L005 

(32%) of those enterprises have remained in business 

(see Table 1). Of those, a small percentage (3')1,,) no 

longer qualifies for the MBE program. Requirements 

for certification include a minimum of 51 percent mi~ 

nority ownership, daily management of the business 

by one or more of such individuals, and an adjusted 

net worth that does not exceed $750.000.<07 

The 3,269 MBEs that were in existence ten 

years ago were owned by members of the following 

ethnicities: Hispanic/Latino American (38{Xl), Asian 

Pacific American (24%), African American (23(%). 

Native American (5%). Asian Indian American (5 1%), 

11,0 Disad\l.U1taged Bllsint!ss Enterprise Program Plan. (2006. May). 

Retrieved July 19. 2006. from http://www.doLca.govfhq/bcp/ 

DBE_.Program.httn 

Table 1: Ethnic and sex breakdown of MBEs certified in 1996 and in business in 2006' 

Number of cerlifled Number of :..1BEs definitely or 11 

MBEs in 1996 possibly still in business 

M BE survival ratc 

ipf"fcenta/!I" (!l tota!) (percentage (d (ola!;' I 

r'-ro-ta-I-Sl-,m-p-]e-' -+----).-26-9-(-IO-O-'>~-,)---+-- LaOS (100%,) -1-----)-2%------i 

Hispanic/Latino 

American 

Asian Pacific 

American 

African 

American 

Native American 

Asian Indian 

American 

Portuguese 

American! 

Spanish 

American§ 

Men 

Women 

L253(38%) 403 (40%) I 795 (24%,) 282 (28'!;,) 35% 

765 (23%) 209 (21%) 

178 (5%) 

)0% 

73 (2%) 

27(1%) 

2,782 (85°.1(,) 869 (86%) 

487 (15%) 136 (14';,,) 29%t 

'Percentages may not add to 100'>~ due to rounding. 

Amencan-owned MBEs ar!3 not included in this survival rate 

1996, Portnguc~e American-\1wned and Spam~h Amcf!can-owned MBEs were not investigated. 

80 TO COMPETE? 
110 

Portuguese American (2\%). and Spanish American 

Across ethnic categories, the vast majority of 

owners were male (85%). 

Today, the breakdown of ~BE ownership 

by ethnic groups remains similar to ten years ago. 

Of the 1,005 surviving businesses: 40 percent are 

owned by Hispanic/Latino Americans, 28 percent 

are owned by Asian Pacific American, 21 percent are 

owned by African Americans, six percent are owned 

by Native Americans, and five percent are owned by 

Asian Indian Americans. DRC did not follow up with 

Portuguese American and Spanish American firms 

due to their small sample size. O\vnership by men 

(86%) is still much more prevalent than ownership 

by women (14l%). 

The average survival rate for the certified 

MOEs in 1996 that were included in this study was 

32 percent. as 1.005 out of 3.169 businesses survived. 

DRC found that African American-owned MBEs 

\vere significantly less likely to survive than those 

o\vned by other contractors of color: with 209 out of 

76j still in operation, the survival rate was only 27 

percent.l()~ As less than one-third of certified MBE~ 

from 1996 have survived. it is clear that few of these 

firms were able to successfully endure in the field 

prodncl!d through random chance 

of transportation construction. However, without 

comparing this survival rate to one for an appropriate comparison group, the impact of Proposition 

209 on this survival rate is unclear. 

A study by the UC Berkeley Center for Labor 

Research and Education found that the field of con~ 

struction has been one of the top industries to employ 

African American workers since 1970.l!N By the year 

2000, employment in construction dropped three 

spots from the seventh spot, and was ranked as the 

tenth largest employer of African American workers, 

It should be noted that \vhile the field is employing 

less African Americans as a whole. it still remains 

one of the top employers of African Americans in 

Northern California's Bay Area. For instance, it is 

the sixth largest employer in San Francisco, and the 

third largest in the East Bay.!]!) 

Results: MBE Survival and Award Access 

Table 2 and Figure I illustrate the dollars awarded for 

Caltrans transportation construction projects, in totaL 

to MBEs. and to non-MOEs. from FY 1985 through 

FY 2005 1

!1 for contracts that included at least some 

1970 2000 San Francisco. C/\ 

[hut. 

L'~ISCRIMINAT!ON RESEARCH CENTER 
111 

Results: MBE Survival and Award Access 

Table 2: Real dollars of Caltrans FHWA awards, in total, to MBEs, and non-MBEs, 

and the percentage awarded to MBEs, by Fiscal Year' 

Total contracts Total contracts Total contracts 

(rca/dol/a!') toMBEs to non-MBEs 

r 1"('(11 dollar) (fi!al dollar J 

FY 1985 SI,158.113.l)76 5123,661,900 51,034,451,175 

I FY 1986 $1,370,029,809 $142,977,070 SI,227,()52,738 

FY 1987 $1,223,039,243 5214,754,645 51,008284,598 

FY 1988 $1,158,538,172 $224,829,961 $933,708,211 

FY 1989 $1,658,869,859 $237.281,922 51.421,586,937 

FY 1990 51,476,107,167 $219,751,334 51,256,355,833 

FY 1991 $1,636,573,778 $237,699.437 51,398,874,341 

FY 1992 $1.532,763,920 $221,930,996 $1,3 I 0,832,923 

FY 1993 51,370,615.212 $216,068,982 51,154,546,230 

FY 1994 51,260,329,054 5253,071,067 51,007,257,987 

FY 1995 52,047,681,743 $394.491,745 51,653,189,998 

FY 1996 $1,356,302,349 $151,257,519 $ 1,205,044,830 ... _. __ ._.- ._---_._. __ ._-------_ .. __ . __ .... 

FY 1997 $1,099,407,742 $102,367,546 $997,040,196 

FY 1998 $998.25L155 586,780532 $911,470,623 

FY 1999 $1,762,918.522 5116,751,788 $1,646,166,734 

FY 2000 51,617,164,423 $115,859,590 $1,501 ,304,833 

FY 2001 $2,602.318,432 $196,726,855 $2,405,591,577 -- FY 2002 $3,367,574,097 $194,953,657 $3.172.620,441 

FY 2003' S962,226.135 $95,060,)79 5867,165,756 

FY 2004' $1,719,791,608 5135.403,605 $1,584,)88,002 

FY 2005' 5958,505,986 575,799,497 $882,706,489 

"Tota!contracts to MBEs and tot':lll'ontracts to nOll-MBE~Ilh1Yllotsum to totalcontracb due (0 rounding, 

Percentage 

of total dollars 

toMBEs 

lO.7iX) 

10.4(/0 

17.60,<) 

19.4'>:, 

14.3% 

14.9''1,) 

14.5% I ,--

14.5'% 

15.8%, 

20.1%) 

19.3(;'~1 

11.2%. -------_ ... __ .. _. __ ._--_.-

9.3(10 

8.7(;(, 

6.6% 

7.2(~, 

7.6% 

5.8% 

I 9.9% 

I 7.9% 

7.9% 

'; Total (;ontructs. total contracts to MBEs. and total contracts to non-MBE:: for these years only include the federal portion or these awards 

22 FREE TO COMPETE? 
112 

Figure I: Real dollar amounts of Caltrans FHWA awards to MBEs and non-MBEs, by Fiscal Year 

FY FY FY FY FY FY 

1985 1986 1987 InN 1989 1990 19~.l ]994 1995 19% 1997 19<)8 1999 2(lOO ZOO! 2003' 2004' 20()~' 

, Only the federal portion of awarded proj~cts is reported. 

federal funding. The percentage of dollars awarded to 

MBEs is calculated by dividing the amount awarded 

to MBEs by the total value of projects awarded in that 

fiscal year. 

Dollar values are inflation-adjusted 2005 real 

dollar amounts using the Consumer Price Index (epl) 

as the measure of inflation.112 From FY 1985 through 

FY 2002, the federal and state portions of awards with 

some rederal funding arc reported, but starting in FY 

2003, only the federal portion of awards is reported. This 

m The natlOmd {'PI was deemed;l hctlcr mflatlOo adjuster than 

the California CPI rlue hl the methodology used to create the 

California CPL 

Clnon-MBEs 

contributed 10 a reduction in the reported level of funding~ both in total amount awarded and amount awarded 

to MBEs in particular. Additionally, in FY 2003 there 

was a sizeable reduction in the value of awards in transportation construction in general. a trend that was even 

more pronounced for Caltrans.J L\ 

The total amount of money awarded by Caltrans 

to contractors has increased since FY 1985. though it 

has varied from year to year. The lluctuation of awards 

is partly due to a variation in public projects for a particular year. For instance, an increase in funding in FY 

2004 is due in part to seven contracts over 550 million 

111 .)'upra. note 73. 

DISCRIMINATION RESEARCH CENTER 23 
113 

Results: MBE Survival and Award Access 

being awarded in that time period. Other large increases in funding for particular years are due to large-scale 

projects, including the Richmond-San Rafael Bridge 

and the Bay Bridge retrofits, 

The real dollars awarded to MBEs demonstrate a steady increase over time from FY 1985 until 

FY 1995, There is a clear reduction in the total value 

of contracts awarded to MBEs after FY 1995, Not 

only was this reduction maintained over time, but 

additional reductions occurred for the next several 

years, Almost 5400 million real dollars were awarded 

to MBEs in FY 1995, but MBEs were awarded only 

5100 million real dollars just two years later, a reduction that lasted for four years. 

Some of the reductions in MBE funding can 

be explained by the fact that the amount awarded by 

Caltrans to all enterprises was reduced during the 

same time period. However. not only did the absolute level of runding decline. but the percentage of 

funds awarded to MBEs declined as well during the 

same time period, From FY 1985 through FY 1995, 

the percentage of total dollars awarded to MBEs increased from to.7 percent to 19.3 percent, and even 

reached as high as 20.1 percent in FY 1994, However, 

there is a sharp decline after FY 1995, with total 

MBE participation never exceeding ten percent after 

FY 1997, 

During the nine years before the passage of 

Proposition 209, the percentage of awards to MBEs 

was 16.0 percent. However, that percentage significantly fell by more than half, to 7,9 percent for the 

nine years after the passage of Proposition 209, Of 

particular interest is FY 2002, This year had the highest amount of money awarded by Caltrans, yet it was 

also the year that MBEs received the lowest proportion of awards (5,8'%), Strong leadership and advocacy 

from business councils have encouraged discussion 

and activity to support the participation of MBEs to 

reverse this trend. 

The rate at which MBEs are awarded contracts has seen a steady decline over the past ten 

years, Between FY 1999 and FY 2005, the number of 

contracts awarded to MBEs was also reduced by 52 

percent, from 834 in FY 1999 to 400 in FY 2005 (see 

Table 3: Total number of Caltr.ns t'HWA prime contracts and subcontracts to DBEs owned 

by contractors of color, by Fiscal Year 

Tota! sample American Asian Pacific 

American 

04 128 65 

92 60 

>73 68 57 64 

286 52 66 44 51 

310 42 68 41 43 

256 28 101 112 69 

209 41 74 35 41 

SO!lra: Qu"rler~}' RI!/JOYI ofJ)REA1!'I!rdl' andCflmmilfllfllHjmm FY J99Q· FY 20(12 & ['niform Repnr/ ofDBEAwurdJ' Of l()/l1mitmmf.l and Pllrmrnfs [rom rr 200J· FY 2005 

FREE TO COMPETE' 
114 

Figure 2: Total number of Callrans FHWA prime contracts and subcontracts to DBEs owned 

by contractors of color, by Fiscal Year 

600+------------------------=~~~----------------------------------------------- 1 500+---~r_-----------------------------=~F-------~~~---------=~~--------­

~ 400t------------~~~~~~~~~--------------------------------------~~---

§ 

z 300+---------------------------------~~~~------~~--~~---------------------

200+-----------------------------------------------------------------------~~~---

100 

FY 1999' FY 2000' FY2001' FY 2002~ FY 200}! FY 2004! FY2005' 

~T[)talSamplc 

S(iurte: Q~(1rterZI' Reparll!f DRE A wards and ("ommitmrnIS from FY [999 - FY 2002 & Unifllrnl Report of DBE Awards (lr Commitmellls al!d Paymaas fmm fT 20113 ~ FI' 2005 

Contracts represent largely thos~ awarded to male contractors of wi or, though a small number of white disabled veterens and women may be 

included. 

j Contracts represent those awarded [0 male and female contractors of COIOf. 

Table 3 & Figure 2),114 African American contractors 

saw the 1argest reduction in the number of contracts, 

from FY 1999 to FY 2005, 61 percenL Hispanic/Latino 

American contractors saw a 57 percent reduction, but 

'I' For FY 1999 through FY 2002, data on the number of 

contracts by ethnicity was reported only for the group labeled 

"DDE," which largely consisted of men of eO lor. !\ small number 

of white disabled veterans and women, both of color and white, 

arc also included. In FY 2003, the reporting structure was 

amended. and the data on the number of contracts by cthnicity 

include men and womcn or color only. 

held the most amount of contracts. Asian Indian 

American contractors experienced the least amount 

of reduction (31 (%), but also held the least amount 

of contracts overall. It is important to note that the 

number of contracts would likely have been reduced 

by even more than 52 percent if data from before FY 

1999 had been available, due to the reduction in total 

and relative real dollars awarded to MBEs between 

FY 1995 and FY 1997 that is not reflected in these 

numbers. _ 

D1SCR!M1NAT!ON RESEARCH CENTER 25 
115 

Results: Survey 

ORe identified 3,269 certified MBEs in 1996, and 

contacted MBEs still operating today in order to assess their attitudes and opinions of the DBE program 

before and after 1996, as well as their current business situation.115 Specifically, for the DBE program, 

iiI Duc 10 the 1m\' number of certified MBEs in 1996. Porluguese 

American-owned and Spanish American-owned MBEs were not 

invcstigat~d. 

DRC focused on lending programs, mcntorship, technical assistance, and pre-bidding conferences that 

MBEs were offered as part of small business development, as well as outreach efforts that were offered 

by the state to MBEs. ORe also assessed the current 

contracts, revenues and employees of the MBEs. 

ORe identified L005 companies that were 

certified MBEs in 1996 and were either definitely or 

Table 4: Ethnic and sex breakdown ofMBEs certified in 1996, in business in 2006, and contacted by DRCt 

I 

Number Number of MBEs DRC attempted Completed survey Response rate 

of certiiied deflnitely or to survey 

MBEs in 1996 possibly still in 

(per('entage (~r (olaU business 

(pcTC<:ntageoj'lotal) 

Total sample 3.269 (100%) 1.005 (100%) 732 lOO 14~!') 

Hispanic! 

Latino 1.253 (WX,) 403 (40%) 283 28 10%, 

American 

Asian Pacific 795 (24(%) 282 (2W'A») 173 30 lr;·o American 

African 765 (23%) 209 (21%) 189 30 16% 

~ 

American 

57(6%) 43 19°/.) 

Asian Indian 178 (5%.) 54(5%) 44 9% American 

Portugucs~ 73(2%) American: 

Spanish 27(1%) American~ 

!\olen 2,782 (85'%) 869 (86%) 640 79 \2% 

\\-'omen 487 (t5!1'O) 92 21 2J% 

, Percentages may not add to IOO'Y) due to rounding 

; Due to the low number ofcertJ!led MBEs In 1996. Portuguese American-owned and Spanish American-owned MBEs were not investigated, 

~6 FREE TO CO?v1PETE'J 
116 

Table 5: Participation in the DBE program 

Lending programs Mentorship opportunitcs Technical assistance Pre-bidding conferences 

Prc-96 Post-96 Pre-96 Post-96 Pre-96 Post-96 Pre-96 Post-96 

Total sample 4% 4';/0 5% 6()/o WYo ll''i;, 56tt/o 46'% 

Hispanic/Latino 4~{) 0% 4% I 4% O~;;) 4% 38%) 38% American 

! Asian Pacific ()l/fl 0'% I 7% 3% 10% !4% 62(/-(, 45% American 

African 11'>" 7% 7% 10% llr/;, 14% 64% 54°;;, American 

Men 4% 4°;{) 6°A) 5(~«, 9(% 12(% 55(!j) 46% 

Women S% 5% 6"", 5(~!(. 5%) 10% 60Q

/" 45% 

SOllra: Cid~r(Jrnia Mi!7Nity BUI'iness En/uprise Program SlIm:f', Di,<crirnil1aliOll Rmwch C{'"ler. ::006 

possibly still in business in 2006. DRC attempted to 

contact 732 of these companies, and received 100 

completed surveys. resulting in a response rate of 14 

percent for contacted businesses (see Table 4). The 

goal of completing at least 24 surveys with the three 

largest ethnic groups, Hispanic/Latino American. 

Asian Pacific American, and African American contractors, was met. 

Of the 1996 certified MBEs still in operation today, Hispanic/Latino American-owned MBEs 

were the largest, both in 1996 and currently, followed by Asian Pacific American~owned and African 

American-owned MBEs. There was a significant tendency for Asian Pacific American-owned MBEs, and 

a trend for African American-owned MBEs, to be 

more likely to respond than the rest. particularly 

compared with Hispanic/Latino American-owned 

MBEs. As a result, there were relatively similar numbers of Hispanic/Latino American-owned (n=28), 

African American-owned (n=30) and Asian Pacific 

American-owned (n=30) MBEs in the survey sample. There were eight Native American-owned and 

four Asian Indian American-owned MBEs that rcsponded to the survey.'I(, Although few MBEs were 

owned by women, a significantly higher response 

rate. almost double that of men-owned MBEs. resulted in a sample size of 21 women-owned MBEs. 

On average, MBEs had been in business for 22 years, 

with Hispanic/Latino American-owned and womenowned firms slightly younger than the others. 

Lending Programs, Mentorship Opportunities, 

and Technicalll.ssistance 

Few survey respondents participated in any lending 

programs, mentorship opportunities. or technical 

assistance, regardless of whether or not the opportunities were affiliated with the Caltrans DBE program 

(see Table 5). On average, no more than four percent 

of contractors of color had used a lending program, 

no more than six percent had taken advantage of any 

formal mentorship opportunity, and no more than 

11 percent had received any formal tcchnical assistance, either before or after 1996. Of the contractors 

who utilized these programs, some were programs 

116 Due to the SInull number of Asian Indian American- and 

Natlve American-owned MBEs, survey results for these 

groups will not be presented, 

DISCRIMINATION RESEARCH CENTER 27 
117 

Results: Survey 

offered by Caitrans, while others were programs offered by other agencies. However, due to low usage 

among our respondents, it was not possible to further subdivide the usage of these programs between 

Caltrans and non-Caltrans offered programs. 

Pre~Bidding Conferences 

Before 1996, the majority (56%) of the survey respondents were invited to attend pre-bidding conferences. 

Before 1996, Hispanic/Latino American contractors 

were significantly less likely to be invited than other 

contractors of color. After 1996, however, there was a 

trend for contractors of color to receive fewer invitaTable 6: Prime contractor outreach efforts 

tions to pre-bidding conferences, with the invitation 

rate (46%) dropping by ten percentage points. 

The number of pre-bidding conferences that 

contractors attended also decreased significantly, 

from 2.4 conferences per year hefore 1996 to 1.3 

conferences per year after 1996. African American 

contractors attended significantly more pre-bidding 

conferences per year than other contractors of color. 

both before 1996 (4.6 conferences per year) and after 

1996 (2.5 conferences per year). 

Outreach Efforts 

Overall, a majority of contractors reported heing 

contacted by prime contractors as part of good faith 

efforts, both before 1996 (75%) and after 1996 (70\%) 

(see Table 6). Before 1996, on average. contractors reported that 13 percent of their revenue was the result 

of good faith efforts by prime contractors. However, 

the percent of revenue coming from this outreach 

evidenced a trend towards reducing after 1996, to 

nine percent of total revenue. Although not reaching 

significance. women-owned MBEs saw a trend of reduced outreach and reduced revenue from good faith 

efforts, while men-owned MBEs evidenced a less proSour!'!" California ,Vin{)rity BU.li!lf.1< En/(I"/,riff Pro1!ram i'iufl'q. Dismminl1lJ1)/I Rrmlrch Crnter, 10116 

?,8 FREE TO COMPETE"' 
118 

nounced trend. Contractors of color also reported 

that these good faith outreach efforts were significantly less helpful after 1996 (2.1 on a I to 5 scale) as 

compared to before 1996 (2.5 on a I to 5 scale). 

DBE Program Utilization 

The most utilized aspect of the OBE program was 

targeted outreach efforts by prime contractors: 

more than two-thirds of contractors were contacted 

by prime contractors, both before and aner 1996. 

Many contractors received invitations to pre-bidding 

conferences, with over 45 percent of contractors being 

invited, both before and after 1996. The other aspects 

of the DBE program, technical assistance, mentorship, 

and lending programs. were sparsely used. 

Interestingly, the aspects of the DBE program that were the most used before 1996 were the 

aspects that experienced the largest drop in usage afTable 7: MBE program helpfulness - How helpful was the MBE program to: 

Total sample 

Ilispanie/Latino 

American 

! Asian Pacific ! American 

I African I American 

M~n 

! Women 

Subcontract with Develop relationships Join or expand 

prime contmctors? with suppliers? networks that made 

it easier for firm to 

receive contracts? 

Pre-96 Posi-96 Pre-96 Post-96 

2.4 2.1 1.6 1.6 2.1 1.8 

1.9 1.9 1.3 I..l 1.5 U 

2.9 1.4 2.3 2.0 

2.2 I 2.0 2.3 2.2 

2.3 2.2 1.5 1.6 1.9 1.9 

2.8 1.8 2.3 1.6 3.0 1.8 

Develop a more 

extemive track 

record? 

P 

2.2 2.1 

1.4 1.6 

2.7 2.4 

2.6 2.4 

2.1 2.1 

2.6 1.7 

Expand the scope of 

services provided? 

Post-96 

2.1 1.9 

1.3 1.4 

2.3 2.0 

2.6 2.5 

2.0 2.0 I 2.8 1.7 

SO!ll"ff: California MillQrifr BusineH Elllrrpl"i.l"f PmKram SUn'fY, DiscriminatiQn R!'\rarch ('trller, 1006. 011 II scale III I If) 5, Il-'h(')"f J is "nlll al all htlpJid'· (Iud 5 is ·'>rry helpful. '. 

DISCRfMINATION RESEARCH CENTER 29 
119 

Results: Survey 

ter 1996. In other words. while usage of mentorship 

opportunities, technical assistance, and lending programs remained the same or showed trends towards 

increasing after 1996, the usage of targeted outreach 

efforts and pre-bidding conferences dropped by five 

to ten percentage points after 1996. Analyses indicated that all eight items measuring the helpfulness 

of the DBE program could be incorporated into one 

"overall helpfulness" scale.'" Additionally. a second 

"fiduciary helpfulness" subscale consisting of the 

three fiduciary-related items (helping with credit, 

loans. and bonds) could also be formed. Analyses of 

these two scales and the eight individual items found 

that. overall. respondents did not find the DBE program very helpful in the areas listed in the survey 

(see Table 7). Before 1996, overall helpfulness was 

only 2.0 on a I to 5 scale, with the highest scoring aspect of the DBE program .... help with subcontracting 

with prime contractors~only managing an average of 2.4 on a 1 to 5 scale. The fiduciary aspects of 

the DBE program were seen as less helpful than the 

other aspects of the DBE program, both before and 

after 1996. 

After 1996, the overall helpfulness of the pro· 

gram was significantly reduced, down to 1.8. The two 

most helpful items, both relating to receiving contracts. 

Table 8: Challenges to working with the state - How much of a challenge was caused by: 

Number of h(lUl'S Amount of lead Getting the Costs involved in 

religibility needed to prepare a time given to information submitting the 

bid or proposal for respond to a request required or ques- required documents 

bid? a public contract? for proposals? tions answered prior to be ccrliiled as 

to the bid due date? an MBR? 

Prc-96 Post-96 Pre-96 Post-96 i Pre-96 Post-96 Pre-96 Post-96 Pre-96 Post-96 

tTotal sample 3.0 3.1 3,2 3.2 2.8 2.9 2.8 2.8 3.2 3.2 

I Hispanic/Latino Amerkan 2.4 2.5 3.2 3.1 2.2 2.3 2-/) 2,6 3.1 3.0 

I Asian Paeilk American 3.1 3.0 3.0 3.0 2.7 2.8 2.9 2.7 2.9 3.0 

1 African American 3.5 3.4 3.4 3.1 3.2 3.1 2.8 2.8 3.6 3.2 

I Men 3.0 3.1 3.3 3.3 2.8 2.8 2.9 2.9 3.3 3.2 

I Women 3.4 3.4 2.6 2.6 2.4 3.1 2.3 1.3 2.4 3.0 

Smm;'(': Calijornil1 MifJoritr Busi/lt'ss Ellttrprisf Program Sum'>', Disaimination ReSflJfi'h Center. 20(J6. On II sl'ille nI j In 5. where I i\' "/l(!f if I'hal/enge al lIlt·· and 5 iI' "UII nlreme ('hallenge .. 

30 FREt TO COMPETE? 
120 

"subcontracting with prime contractors" and "joining 

or expanding networks that made it easier to receive 

contracts" each declined significantly since 1996, while 

other items showed reduction trends. 

On the whole HispanicfLatino American contactors found the DBE program, including fiduciaryand contract~related aspects significantly less helpful. 

both before and after 1996, while African American 

contractors found the DBE program more helpful, 

particularly the fiduciary-related aspects. Female contractors of color found the DBE program to be significantly less helpful over time relative to their male 

counterparts. 

Overall, respondents reported that each of 

the difficulties they experienced with the state was 

moderately challenging (see Table 8). There were no 

significant changes in attitude aftcr 1996. The challenges that received the highest scores were: 1) the 

number of hours needed to prepare a bid or proposal 

for a public contract, and 2) the costs involved to be 

certified as an MBEiDBE. 

Before 1996, the amount of lead time given 

to a request for proposals was less of an issue for 

HispanicfLatino American contractors but more of 

an issue for African American contractors. Female 

contractors of color found the amount of lead time 

given to be increasingly chal1cnging. 

Table 9: Number of employees and contracts 

Before 1996. HispaniciLatino American 

contractors found the qualification/eligibility requirements for a bid to be more difficult than did African 

American and other contractors of color. African 

American contractors found the costs associated with 

DBE certification. as well as the number of hours 

needed to prepare a bid or proposaL to be easier over 

time. 

State of the Minority Business Enterprise 

For the surveyed MBEs. the period after 1996 evidenced some modest gains in growth, with the total 

number of contracts increasing significantly, and 

the number of employees holding steady (see Table 

9). However, while men-owned MBEs advanced, 

women-owned :vrBEs did not. Over time. women 

showed a significant relative worsening in the num~ 

ber of contracts compared to men-owned MBEs, and 

the same pattern of results for the number of employees. HispaniciLatino American-owned MBEs 

showed significantly more growth than Asian Pacific 

American-owned MBEs, resulting in a significantly 

larger number of employees today, 

The vast majority of MBEs reported that the 

number or type of services they offer"--"such as cement pouring, heavy equipment rentaL or structural 

engineering-had increased or stayed the same since 

Number of employees Number of employees Number of total contracts Number of total contmcts 

(!IIediatl! (mean) (median) /mean) 

Prc~96 Post¥96 Prc-96 Post-96 Prc-96 I Post-96 Pre-96 I Post-96 

Totalsamplc 20 22 20 20 

* Hispanic/Latino American 9.5 20 33 25 I 20 61 

Asian Pacific American 6.5 10 I 22.5 ! 88 

African American 32 21 6.5 i 10 22 31 

Men 22 26 20 I 20 64 I 77 

Women 15 I 10 27 T 17 

S(/Urce: Califomii! JfinlJrity Busflles:l Entrrprisc Program Sun'''.!', Discriminution Research Cnller. 2()O6, 

DISCRIMINATION RESEARCH CENTER 
121 

Results: Survey 

Table 10: Number of services and percent of contracts and revenue from Caltrans 

, Numbcr of services offcred Percent of contracts coming Percent of rcycnue coming 

ire/alive 10 199fJ) from Caltrans from Caltrans 

Percent Percent Percent Prc-96 Post~96 Prc~96 Post~96 

offering fewer offering same offering more 

Total sample 9% 54% 37'Yo 7% 4'% 12<)';) 6% 

Flispanic/Latino 0% 44'% 56%) 1% 0%, 5°;;, 3f

}'O American 

Asian Pacillc 0'% 69% 3l'>;) 81

/:) 10'% 16% 11'};) American 

African 22% 44'% 3J% 8'% O{>~) 14% 2% American 

Men 8% 52{~i(1 40% 5% 3% 81

% 5°j() 

Women 11% 63% 26'% 15% I 9% 280

;;) 10% 

Source: Californiil Minority Business fntfl'pl'isc Pm~ram Surrey. Discrimination Researth C(,rlli'r, 200n 

1996 (see Table 10). On average, 37 percent of the surVL"J respondents: offered more services and 54 percent 

offered the same number of services. For African 

American-owned MBEs, 22 percent reported offering 

fewer services, a significantly higher rate than that of 

the Hispanic/Latino American-owned or Asian Pacific 

American-owned MBEs, of which none reported offering fewer services. African American-owned MBEs 

were only 30 percent of the sample, but represented RO 

percent of the MDEs who reported offering lewer services, Hispanic/Latino American~owned MBEs saw 

the most growth, with 56 percent offering more services 

currently as compared to 1996, significantly more than 

the other MBEs. Asian Pacific American-owned MBEs 

were significantly more likely than other MBEs to report offering the same number of services. 

MBEs saw a significant reduction in the percentage of revenue and a trend towards reduction in 

contracts that came from Caltrans since 1996. Before 

1996, women-owned MBEs received a signifkantly huger number of contracts and percentage of their revenue 

FREE TO COMPETE? 

from Caltrans relative to men-owned MBEs in 1996. 

However, a significant 66 percent reduction in revenue 

and a trend evidencing a 42 percent reduction in the 

percentage of contracts coming from Caltrans resulted 

in men- and women-owned MBEs receiving equal pro· 

portions of contracts and revenue from Caltrans. 

Currently, Asian PacifIc American-owned 

MBEs receive significantly more of their revenue 

from Caltrans than other MDEs, and they showed a 

significant rela tive increase in the percentage of contracts coming from Caltrans ~ompared to African 

American-owned MBEs. 

Survey Limitations 

Caution should be used in interpreting the results of 

this survey since only surviving MBEs were examined. 

The experiences of MBEs that did not survive may be 

different from those that survived. Additionally, with 

a response rate of [4 percent, it is not possible to draw 

strong inferenccs for the entire sample of surviving 

MBEs .• 
122 

DlSCRlMINATION RESEARCH CENTER 33 
123 

Results: MBE Focus Groups and Interviews 

The goal of the focus groups and interviews was to 

provide an opportunity for MBE-owners to discuss 

the impact of Proposition 209 on public contracting in 

California's transportation construction industry. To 

measure this impact. questions were posed in the following areas: 

The culture vf the construction illdusl1)': What aspects of the construction industry are not directly 

related to race or ethnicity, but could have an impact on contractors of color? 

The business challenges/or MBEs: What are the 

main challcnges for MBEs when establishing a 

business in the transportation construction industry? 

The federal DBE program: What benefits and 

challenges exist for MBEs regarding California's 

implementation of the federal DBE program'! 

The impact of Proposition 209: What was the 

impact of Proposition 209? Were there any 

collateral eITects? 

• MBE survival strategies: \VIlat arc some of the 

main reasons why so many MBEs who were 

in operation in 1996 are not alive today? What 

strategies contribute to the survival and/or longevity of MBEs? 

The Culture of the Construction Industry 

Participants agreed that it is the general culture of 

the construction industry for prime contractors to 

operate within a virtually indestructible "good old 

boy" network that values personal relationships. 

Participants also reported that it is more beneficial 

for an MBE to be a prime contractor and thereby 

avoid relying 011 other companies to provide con~ 

tracts. In general. people in this industry reward 

people they know and trust with work. Participants 

reported that collusion is perceived as a part of the 

industry culture and that forming meaningful re~ 

lationships with other prime bidders or awarding 

FREE TO COMPETE? 

agencies is essentiaL Without these relationships, 

businesses cannot survive in this industry. 

The Business Challenges for MBEs 

Participants indicated that there arc many obstacles 

to success for MBEs. Securing bonding, financing, 

and insurance were reported as the most challeng~ 

lng aspects of operating a business. Because many 

MBEs are small businesses and subcontractors, they 

rely on working with prime contractors. Slow payment from awarding agencies and prime contractors 

was also identified as a major barrier for MBEs. 

many of whom tend to be small businesses that need 

prompt payment to cover necessary expenses. Cash 

flow problems were considered common barriers 

for MBEs, largely due to the owners' relative inexperience operating a business. Participants also 

reported that they have personally been confronted 

with negative stereotypes about MBEs being "underperformers" or "inefficient:) This can be overcome 

by developing relationships with prime contractors 

andlor awarding agencies and efficiently produc~ 

ing high quality work. Still, these relationships can 

only be fostered if an MBE has the time and money 

to invest in this type of outreach. While DBE programs provided incentives for bids that included 

the participation of MBEs, participants noted that 
124 

breach of contract was 

also a common challenge. 

While MBEs may have 

been used to secure bids, 

participants reported that 

many MBEs never ac~ 

tually conducted their 

contracted work on a 

project. Participants also 

reported that the private 

industry was more in~ 

e1ined to work with firms 

that have the ability to 

work regionally or nationally. which is beyond the 

capacity of many MBEs. 

The Federal DBE Program 

Participants agreed that the most valuable aspect of 

the federal OBE program was that it opened a door 

for MBEs by providing a needed incentive for prime 

contractors to "pick up the phone." Partic1pants also 

agreed that every project builds a resume. As such. 

one of the most valuable aspects of the DBE programs offered by Caltrans was that these programs 

encouraged utilization by providing announcements 

for jobs, thereby helping people of color gain access 

to opportunities that might not have otherwise been 

shared with them in a timely manner. 

Particlpants criticized several aspects of the 

DBE programs as well. Large firms did not enthusiastically support these programs. so MBEs were often 

given late notification about bidding opportunities and 

good faith efforts were often haphazardly implemented. The programs only marginally opened the door to 

MBEs; the "good old boy" network is still the prevailing culture in construction. The programs also did not 

effectively address many of the business challenges f<lf 

MBEs, such as slow payment or bonding and financing issues. Participants reported that there was little 

to no enforcement regarding prompt payment and no 

formal mechanism to address the attitude that MBEs 

were "lucky to be here" 

and should not complain. 

Participants also 

noted that DBE programs incorporated a 

significant amount of 

"hand-holding," which did 

not encourage MBE owners to learn the business 

aspects or their industry. 

Instead, participants in~ 

dicated that many MBEs, 

though highly skilled 

in their crafts, were encouraged to compete for 

business on a "secondtier" as subcontractors with large, prime firms that. 

in general, do not mentor MBEs in business. Without 

addressing the business development of MBE firms 

through education, DBE programs were perceived by 

many of the participants as contributing to the negative stereotypes that follow MBEs in the construction 

industry. Perceived as a "hurdle system" to label businesses owned by people of color, participants reported 

that prime contractors continue to view these programs as "subservient" and therefore use their power 

and leverage to withhold payment and set up MBEs 

for failure. Participants agreed that they should be 

evaluated not by whether they are people of color. but 

rather, on the merit of their skill, work, and reputation. 

Participants agreed that the promise of equal access to 

bids would provide this opportunity. 

The Impact of Proposition 209 

Participants agreed that j(ll" those MBE firms that relied on the race-conscious D BE measures to provide 

opportunities for contracts, the effects of Proposition 

209 were more pronounced. For those participants 

whose firms did rely on subcontracts with prime 

companies (due to special trade or other reasons), 

Proposition 209 eliminated the incentives for prime 

contractors to cal1 them. Participants reported that 

DISCRiMINATION RESEARCH CENTER 35 
125 

Results: MBE Focus Groups and Interviews 

many prime companies interpreted Proposition 209 

as a reason to avoid working with MBEs altogether. 

This forced a number of MBE firms to downsize services and layoff employees. both of which impacted 

these firms' ability to compete. 

Participants were split on the personal impact 

of Proposition 209. While a number of participants 

indicated that after the proposition passed, they were 

virtually shut out of the business by prime contractors. others reported that they suffered no negative 

impact as a result of Proposition 209. For those whose 

businesses were not harmed by Proposition 209, the 

main reason was that they had formed relationships 

with awarding agencies or prime contractors that 

gave them equal opportunity to compete with other 

prime contractors. Participants who reported no impact were also more likely to be prime bidders on 

contracts. 

Participants agreed that there were collateral 

impacts of Proposition 209 that included unemploy~ 

ment as a result of lay-offs, fewer resources for 

immigrant communities to learn English. fewer reFREE TO 

sources to support local organizations, and negative 

health outcomes as a result of stress. Participants reported that Proposition 209 did not fix the problem 

of unequal access to competitive bids: instead. it reinforced the system of exclusion that already existed 

and strengthened lingering preconceptions about 

the work product of people of color. Participants 

interpreted race-neutral strategies to encourage 

:viBE participation as a signal that little to no people 

of color ,"vould be a'\.\>·arded public contracts postProposition 209. Race-neutral strategies were viewed 

as a strategy to strengthen the "good old boy" network by ignoring the legacy of racial discrimination. 

MBE Survival Strategies 

While participants acknowledged that many small 

businesses fail. they also noted that the federal DBE 

program has never fulfilled the promise of equal access to contracts. Participants also reported that a 

lack of business savvy on the part of many MBEs contributes to their failure. A lack of access to bonding 

and financing coupled with the demands of build-
126 

ing networks where their presence is not necessarily 

encouraged often proves fatal for MBEs. Below is a 

summary of the survival strategies used by MBEs in 

California's transportation construction industry: 

• Expand services: MBEs reported that expanding 

the type of services offered generates new business and allows for the type of flexibility required 

to survive. 

Become a part of the network: MBEs consistently reported that building relationships with 

granting agencies and prime contractors is essential to the survival of any construction business. Participants reported that through formal 

business associations and boards, MBEs can 

directly combat many of the challenges that impede progress for businesses owned by people of 

COIOf. 

• Build capacity: MBEs reported that in order to 

survive, firms owned by people of color need to 

utilize basic business development practices to 

invest in their own companies so as to support 

their ability to work on projects in other cities and 

communities (including those outside of Ca1ifor~ 

nia), and to compete as a prime contractor. 

• Promote the business mode! of diversity: MBEs 

reported that many prime contractors. once they 

recognize the business benefit of working with 

people of color, respond favorably to fostering relationship with MBEs. 

Contract with the private sector: Though many 

I\.1BEs reported that access to contracts in the private sector was often as challenging as those in 

the public sector1 contracts with private industries~ 

including individual clients, were seen as a strategy to sustain their business. 

• Be persistent: MBEs agreed that in order to survive. 

an owner must be persistent. Participants agreed 

that MBEs should seek every opportunity to demonstratc their ability to perform well and commit 

themselves to developing relationships with individuals, companies. and public agencies .• 

DISCRIMINATION RESEARCH CENTER 
127 

Miguel Galarza 

Yerba Buena Engineering & Construction, Inc. 

Anative of San Francisco. ~igucl Galarza gre\v 

up wanting to be an architect. While he was 

discouraged counselors \vho he 

should pursue labor, fGcused. He had a for 

hands. so at age 

struction·---iormally 

might aid his dream 

When he heard that Chinese 

a civil rights and advocacy organization. was 1ooking for to participate in a cityv"ide carpenter 

he up. For six 

hut a 

for a firm in San 

in J996. Miguel honed many of 

his skills during the nine years that he worked with 

thi~ hrm. However. his concern began to grow when 

he noticed that this tlrm \vas reliant on 

the DBE program to provide contracts. reajlLcd 

that the firm \vas a "DBE baby"-a tlrm born from the 

come from prime contractors 

,ut,eo.ntraetor work \vlth 111'm:- t1wncd by wom~n and 

people of coloe This firm worked almost 

through the DBE When Proposition 

passed and set-aside programs in the 

TO 

state ended, this firm became unstable, because the owner's business model had been to on 

the DBE program for its business and grmvth, 

In San Francisco. a knmvn to be progressive on a issues. the impact or 

Proposition 209 took time to materialize, For a \",hile, 

a number firms, many of which \\fere owned 

continued to \vork \vith MBEse These 

firm~ understood that it \'V~lS in their best businessand community~interest to cultivate a """''''''''''1' with Jv1BE firms and to foster their opportunities 

UCJ:eIC'pnlen1. Still. Miguel was uneomfortmodel of relying on the DBE 

to provide contracts that \vould sustain 

business. He understood that the federal DBE 

business enwrap it;; existence around the race~conscious 

programs. and motivated by a desire to allow his hard 

\york and to generate \vealth for him and his 

family, he it \\:as time for a challge. 

In 2002, \1igucl launched out and founded 

Verba Buena Engineering and Construction, a heavy 

cngineering eOll'Struction Jjrm. l'sing the ORE 

gram to make initial contact \vith granting 

Miguel actively pursued and \von prime contracting 

bids. Once those bids were won, Miguel focused on 

fulfilling the terms of the contract. 

, and sometimes excccding:- . the goals of 

the contract. Determined not to usc the DBE program 

T\1iguc] also focused on developing 

and other prime 

"'<"OM,m" relationships into 
128 

mentorship opportunities. Miguel learned successful 

business strategies from a number of major compa~ 

nics. For six years. he was coached on how to support 

the basic business practices that could foster growth 

in his organization. Ad\'ic~ such as "leave the profit in 

the company instead of using it as a personal profit." 

"learn accounting and always pay your taxes on time," 

and "bid as a prime contractor" became part of his 

organizational mantra. He knew that his access to 

this kind of "know-how" was rare. Prime contractors 

do not make a practice of showing MBEs the tricks of 

the trade. strategies that may turn many of them into 

serious competitors. So, to him. the advice gleaned 

He knew that his 

access to this kind of 

"know-how" 

was rare. 

from these relationships was more valuable than 

the diversity goals articulated through the various 

DBE programs in which he had participated. Miguel 

worked hard. took smaller projects so that he would 

not have to wait years to see a profit, and left money 

in (he bank so that he could bond. Within a year of 

founding, Yerba Buena Engil1ceringand Construction 

had three employees and earned $500,000 in revenue. 

In 2006. Verba Buena Engineering and Construction 

employed 30 people and earned over $7 million in 

revcnue. These lessons combined to serve as his realworld PhD~~"earning him not only the business savvy 

to expand his business model beyond the scope of the 

DBE program, but also providing him with the clout 

in the community to share his strategies with others. 

In 2003. Miguel joined the hoard of the San 

Francisco Hispanic Chamber of Commerce. In 2005, 

\1iguel was elected as its Vice President. That year, 

he also won California Businessman of the Year, and 

in 2006 he was nominated for the California Small 

Business Administration's award for Businessman of 

the Year. He recognizes that many MBEs are craftsmen, and his mentorship emphasizes the business of 

creating a Minority Business Enterprise. He coaches other MBEs on how to overcome the pitfalls that 

often contribute to their failure. He helps them un~ 

derstand how to make money hy performing quickly 

and efficiently. and by understanding the dynamics 

and importance of maintaining a c<l:;h How. lIe helps 

them channel their passion for the work such that they 

do not have to rely on special programs. but rather, to 

cultivate personal and professional relationships that 

can lead to the creation of new opportunities. 

For \IIiguel, the impact of Proposition 209 was 

more visible among those who would have been his 

compctitors-~ those who. in their reliance on the race~ 

conscious DBE program. may not have been able to 

survive in an industry run on personal relationships. 

Unlike many ::viBEs he has known over the years, his 

phone did not stop ringing as a result of Proposition 

209 because he had developed relationships that could 

weather the storm. Still. he recognizes that without the 

DBE program, and its incentives to make contracting 

agencies look in his direction, he would likely have 

been initially shut out of the process, standing on the 

other side of a door that remains closed to many peo~ 

pIe of color struggling to realize their dreams of equal 

opportunity and prosperity __ 

DlSCRIMINAT10~ RESEARCH CENTER 
129 

Robert Wilson 

Wilson Electrical Company 

Raised in Flint, Michigan, Robert \Vilson carne 

to Californi~1 in 1981 searching for a place 

among a niche of contractors do~ 

ing \vark with the oil rig;,; Martinez. As a member of 

the International Brotherhood of Electrical Workers, 

Robert worked for several years as an industrial dcc~ 

trician. His reputation as a skilled electrician ted him 

to many In 1984. he decided to start his o\vn 

business, so took the test to become a contractor 

and immediately began looking t()f \vork. He also 

"H>"'~'"""~'J certified as an MBE firm with Ca1tra115 

and every major contracting agency in thL" San 

Francisco and East Bay areas. 

Robert's first for 

SI12.000 to work with San Francisco Airport. I Ie 

\\'<1S told that certain bonding agencies had relationships with ;Vi BE contractors and that he should to 

these institutions to secure bonding for the 

\Vhen Robert went to secure a bond with the agency 

that \vas designated the DRE program, the 

agent looked at him responded, "Here comes 

another one:' and then moments later. denied the [cthe statement \,·:as curious, but 

at that time. Instead, he went 

that he 

secure bonding after be had 

already completed half of the project. This time, his 

request \vas only for $50.000. which was immediately 

approved. When Robert inquired about why he was 

denied the first time. he \vas shncked by the response. 

SuIJcc'ntr'acl:ing MBE i1rms. Robert was told. \vere 

subject to funding~-"'up to S50,000. [n other 

words, the agency approved by the DBE program 

generally \vould not approve loans over S50,000 for 

suhcontracting MBF firms. Rohert interpreted this 

as a to keep MBE subcontractors from ever competing the bigger projects. He 1'topped working 

through this bonding agency when he realized that 

through other agencies. he "vas able to secure a bond 

for SlOO.OOO or more. 

,",vas more of an obstacle than 

anticipated. StilL he wanted to pursue 

development in \I,.'hat he thought was the 

American way~ - he'd go to a bank ft1r a loan. When 

he was awarded a 5400.000 contract through the San 

Francisco Airport he again attempted to secure a 

bond. this time more prepared for what awaited him 

at the financial institutions. Understanding many of 

the obstacles that prevent African Americans from 

securing loans. he stacked his tcam"""comprised of an 

attorney, an insurance agent. and a bonding agent .. · 

with white males, thinking that might buffer him 

from any racially-motivated negative preconceptions. 

Together. entered the bank, hoping to secure '-1 

loan for When the introduced the 

team and indicated that they were to secure a 

It)an to support the devdopmenl of \Vilson Electrical 

they v,'ere told that Robert would have to 

At that moment. Robert's attorney 

his book and motioned for Robert and the rest 

orthe team to leave the bank. Once outside, the attorney told Robert that he had secured loans 

for his white credentials 

without any bank or requests 

for collateral. Robert continued to 
130 

fight for the survival for his business. His expertise 

and reputation as a skilled electrician followed him, 

and his business did grow. In 1995, at the height of his 

business, Robert's company earned revenue in excess 

of 5600,000 a year and employed more than 20 electri~ 

cians. many of whom were also African American. 

Then, in 1996, Proposition 109 passed, and 

Robert immediately began to feel the effects. Right 

away. he heard rumors that "minorities were flO 

longer needed·' had been written on Caltrans speci~ 

fication booklets, and that prime contractors hac.I 

begun to circulate materials that indicated ways to 

avoid contacting people of color for bids on projects. 

After 1996, Rohert noticed that the number of cans 

from prime contractors began to decline. He noticed 

a steady rejection of his bids. In one instance, he 

,"vatched as his bid for an Alameda County project 

was "shopped around" to competitors. After working 

on the Cypress Freeway in 1999, Robert decided to 

bid on work for the Day Bridge. He submitted what he 

thought was a competitive bid. but ended up not being 

the low bic.Ider. Then. he learned that Caltrans issued 

an addendum to prime contractors indicating that 

they would receive 5500,000 to submit a hid for the 

contract, while subcontractors, many of which were 

MBE firms, did not receive uny money. To Rohert, 

this was a clear signal. He decided to stop "spinning 

his wheels." and has not suhmitted a bid on Caltrans 

projects since. Robert continued to make efforts to 

generate business for his company. hut few resulted 

in actual contracts. Prime contractors seemed to feel 

that they did not need him anymore, and therefore. 

closed the door of opportunity. 

Gradually. Robert had to layoff his employees, strap on his tool helt and start doing \",'ork himself. 

He adjusted the foclls of his company, moving [rom 

inc.Iustrial electric projects to residential projects. In 

2004, his business eventually hit a low, earning only 

$40,000. Robert was evicted from his apartment and 

could barely survive. Robert persevered, knowing 

Then, in 1996. Proposition 209 

passed, and Robert 

to feel the effects. 

he could turn things around. Two major electrical 

cngineering companies tapped him for mentorship 

and began working with him to reinvigorate his business. His reputation landed him in th~ executive onices 

of these major companies, earning him the gift of their 

business savvy"~--savvy that has helped Robert breathe 

life into a company that was once onlife-supporL 

Robert attributes the survival of his business 

to his belief in God. his knowledge of the trade, his 

ability to he flexible, and his ability to live with 

minimal resources. While he knows that Proposition 

209 ended the primary strategy used to get prime 

contractors to pay attention to small tlrms that were 

owned by people of color, he also learned. as a result 

of Proposition 209. that "business has no color:' From 

his experience of success, loss. and rebuilding, Robert 

has identified stumbling blocks and shown a way to 

hr~ak down the financial barriers that keep MBEs 

from succeeding as public contractors, and established 

himself as a survivor. in morc ways than one .• 

DlSCnl11lNATION RESI:ARCl-l CENTER 
131 

Discussion 

FREE TO COMPETE? 

Overal1, themes from the [our data collection methods-·MBE survival and award access, survey, focus 

groups, and contractor profiles-highlight consistent themes that clarify how MBEs were affected 

by the impact of Proposition 209 and other anti-affirmative action measures. There are clear negative 

repercussions from Proposition 209-both Caltrans 

and the MBEs themselves reported that Caltrans 

utilized MBEs less frequently after Proposition 209. 

However, many of the surviving MBEs reported 

that on the whole they did not see dramatic changes 

to their business models, their business growth, or 

their perceptions of the federal OBE program after 

Proposition 209. 

Surviving MBEs did not tend to place a high 

value on most aspects of the race-conscious DBE 

program. Since the federal OBE program was, in 

general, only modestly utilized and valued by these 

firms, little room was left for negative effects due to 

Proposition 209 and other anti~affirmative action 

measures. Of most value to surviving MBEs were the 

aspects of the DBE program that provided assistance 

with networking, such as outreach and pre-bidding 

conferences. These components. as the most utilized 

and valued aspects of the OBE program both before 

and after 1996, are perceived by surviving MBEs as 

key to making public bidditlg processes fair. As supported by thc qualitative data presented in this report. 

MBEs do not want to rely on a race-conscious DBE 

program; instead they seek to remedy a history of 

racial discrimination through a facilitation of equal 

opportunity and access to business development and 

bids. Of greatest emphasis has been outreach and 

pre-bidding conferences; however, since 1996, these 

networking efforts have tapered off considerably. 

On average. the surviving MBEs that were 

surveyed had matured positively since 1996. Overall, 

these MBEs grew in terms of the number of employees. 
132 

and most are now offering the same, or more, 

services than in 1996. 

For these MBEs. expanding their type of services 

was the primary strategy 

used to survive decreases 

in outreach following 

Proposition 209. This 

helped them to maintain 

a steady number of total 

contracts from private and public sources between 

1996 and 2006, a time in which OBEs experienced 

less business with Caltrans. Surveyed contractors reported that the percentage of revenue coming from 

Caltrans has dropped since 1996, with a downward 

trend in the percentage of contracts as well. These 

observations are consistent with Caltrans awards 

data confirming that the number of contracts and total revenue awarded to MBEs has dropped since the 

mid-1990s, with the percentage of awards secured 

by MBEs being reduced by over 50 percent, fro111 

16.0 percent of total awards in the years preceding 

Proposition 209 to 7.9 percent of total awards in the 

years following the passage of Proposition 209. DRC 

found that although MBEs always received over ten 

percent of total revenne before 1996 (with the percentage reaching as high as 20.1 percent in FY 1994), 

participation by MBEs never reached ten percent of 

revenue awarded after 1996. 

Women-owned and African American-owned 

MDEs fared more poorly over the last ten years than 

the other MBEs. Women-owned MBEs consistently 

showed a pattern of shrinking business; the num~ 

ber of employees~ the total number of contracts, and 

the percentage of contracts and revenues obtained 

from Caltrans all demonstrated patterns of poorer 

outcomes relative to men-owned MBEs. Though 

women-owned MBEs 

may have found OBE 

programs more useful 

before 1996 than 111enowned MBEs, their 

perceptions of helpfulness were reduced in the 

past ten years. 

Though African 

American-owned MBEs 

showed some prosperity, these firms still consistently showed a pattern of 

poorer outcomes relative to other MBEs. Although 

several of the trends did not reach the traditional level 

of significance, African American-owned MBE firms 

were often on the worse-off end in measures of health 

for their enterprises. African American-owned MBEs 

were also significantly more likely to have decreased 

the number of services offered. rather than expanding 

like many of their peers. The evidence in this report, 

as exemplified in the contractor profile of Mr. Robert 

Wilson, appears to show that many African Americanowned MBEs are struggling to stay alloat. • 

DiSCRiMiNATlON RESEARCH CENTEH 43 
133 

Recomm.endations: 

Strategies for Providing Equal Opportunity 

Public contracts remain unavailable to a considerable portion of people of color in Californias 

transportation construction industry. Data consistently demonstrate the under-representation of these 

f1rms among those that arc awarded public contracts, 

and barriers continue to keep MBEs from equaJ access 

to competitive prime-and sub-contracts. This study 

finds significant barriers for contractors of color who 

seek to ..... participate on equal footing with their white 

counterparts in California's public transportation 

construction industry. To ensure equal opportunity 

for MBEs seeking public contracts in California's 

transportation construction industry, DRC recommends increased attention and action in four primary 

areas, including J) equal opportunity programming, 

2) capacity of businesses owned by people of color, 

3) advocacy for the business model of diversity, and 

4) continuation of research on the impact of anti-affirmative action laws and policies, 

Equal Opportunity Programming 

The findings of this report suggest that while MBEs 

do not perceive Caltrans' implementation of the federal race-conscious DBE program as perfect, there 

were specific components that were considered effective elements to improve MBE access to public 

contracts, Standards set by the Croson decision have 

resulted in a generation of disparity studies that consistently provide evidence of MBE under utilization, 

further sustaining the life of many race-conscious 

DBE programs. While Proposition 209 remains in effect, legal challenges to these types of programs are 

likely to continue in California. As noted earlier in 

this report, at the time of this study, Caltrans commissioned a disparity study to determine whether there 

is a legal justification to continue implementing the 

federal race-conscious DBE program in California. 

Nevertheless, the findings of this study reflect the 

FREE TO COMPETE? 

need for a specific, race-conscious strategy to ensure 

equal opportunity to compete for public contracts 

in California's transportation construction industry 

Sp~cific recommendations are as follows: 

Reconrmendation: Public agencies should develop 

a new equal opportunity program that emphasizes the most useful aspects of the race-conscious 

DBE program and incorporates new strategies 

to involve people of color. For example, public 

agencies should consider sending opportunity announcements by mail to all contractors instead of 

using the Internet as the main outreach tool. Pu bUe 

agencies should also advertise opportunities in the 

ethnic media in order to reach communities of color, Other components of a new program to facilitate MBE access to opportunities should include 

articulated diversity goals and dollar amounts for 

underrepresented racial and ethnic groups as well 

as tailored strategies to enforce these goals. These 

recommendations are important to ensure that 

outreach efforts are more than just good faith 

efforts; instead, these efforts must be indicative 

of equal opportunity among California's diverse 

communities. 

• Recornmendation: Public agencies should develop 

equal opportunity programming that includes 

formal relationships with ethnic local, regionaL 

and statewide chapters of the Chamber of Commercc to host pre-bidding conferences so that opportunities are shared with business enterprises 

connected to networks that include strong representation from people of color. A stronger presence of people of color on the business councils 

and boards of major government granting agencies, contractor associations. and unions is also 

key to developing a climate in which open dia-
134 

logue and strategic pJanning can ensure the devel~ 

opment and implementation of strategies to pro~ 

vide MBEs with the equal opportunity to receive 

public contracts. 

• Recommendation; Public agencies should change 

the nomenclature of equal opportunity programs 

to support a positive view of diversity as a busi~ 

ness model. Being labeled a "Disadvantaged Busi~ 

ness Enterprise" is not appealing to any entrepre~ 

neur, especially MBEs, which arc already plagued 

by negative racial stereotypes that impede their 

efforts to compete on equal standing with their 

white counterparts. For example, private indus~ 

try has implemented its equal opportunity efforts 

through "Diversity Business Enterprise" pro· 

grams and goals. 

• Recommr?l1dalion: Public agencies should develop equal opportunity programming that includes 

routine, yet random. assessments of fairness in 

the bidding process. MBEs reported collusion, 

"bid-rigging," and other illegal practices that 

undermine MBE access to public contracts. A 

routine audit of practices should minimize the 

prevalence of these activities. 

Capacity of Businesses 

Owned by People of Color 

The findings of this report suggest that while MBEs 

are subject to unequal access to public contracts, other 

factors also impact whether they are free to compete 

in California's transportation construction industry. Capacity is an important predictor of whether a 

business will succeed or fail in the construction industry. For example, the number of Small Business 

Enterprises (SBEs) has also decreased in the past ten 

experiencing a survival rate of approximate30 percent. which is similar to that of the 1996 

certified MBEs. As most MBEs arc small business 

enterprises, their ability to sustain their capacity 

is criticaL While Proposition 209 ended race-conscious efforts to level the playing field for businesses 

owned by people of color, any effort to enforce equal 

opportunity must include strategies designed to build 

the capacity of these business enterprises. Specific 

recommendations are as follows: 

• Recommendation: Public agencies should implement strong enforcement strategies at public 

transportation agencies to ensure prompt payment of contractors at the agency or prime con~ 

tracting level, and at the sub~contracting leveL 

m Office of Small Businc.;s and DVBE Ct'rtification: 

hrm~ t 'crtilicd lTI {<)96 

D1SCRIMINATION RESEARCH CENTER 
135 

Recomn1.endations 

• Recommendation: Public agencies should invest 

in technical assistance for businesses owned by 

people of color. In partnership with nonprofit 

small business development corporations, pub~ 

lic agencies should provide technical assistance 

in areas of securing loans and bonds, entrepre~ 

neurial training and other educational services 

for small businesses owned by people of color. 

To reach a greater number of MBEs, public 

agencies should also establish satellite offices 

in communities of color that provide technical 

assistance (e.g .. information regarding opportu~ 

nity announcements. financial lending programs, 

various insurance options for subcontractors) to 

businesses in the community. 

• Recommendation: Public agencies should partner 

wilh ethnic Chamber of Commerce chapters. ap~ 

prenticeship programs. and community colleges 

at the regional and local level to sponsor workshops on the business of construction. Many 

the data in this report capture 

tr¢ndsfrom MBEs that survived 

afterPropositionl09; however, 

tbeydo .not capture trends 

and barriers for those whoSe 

businesses falled. 

FREE TO COMPETE? 

contractors understand the craft of construction 

but fail due to a lack of command for basic busi~ 

ness practices (e.g .. accounting), Access to 1rain~ 

ing and education in this arena could facilitate a 

greater ability to operate a successful business. 

Advocacy (or the Business Model of Diversity 

Increasing the participation of MBEs should not only 

concern public agencies, MBEs, and advocates. Equal 

opportunity in public contracting affects the econom· 

ic well-being of every community. 

Recommendation: Organizations that otTer lega! 

and/or political advocacy are critical conveners 

of community partners (including community 

members, attorneys, academics. policy analysts, 

researchers, und youth) that also have a vested 

stake in ensuring equal opportunity for businesses owned by people of color. These organizations 

should continue to form partnerships that can 

strengthen the visibility of MBEs in the develop~ 

ment of solutions to rebuff efforts that undermine 

equal opportunity for people of color. 

• Recommendation: Community organizers should 

develop multi~cthnic, multi-generational coali~ 

tions to increase accountability among state 

agencies and prime contractors. One strategy to 

increase accountability among public agencies 

and enforce a commitment to the business model 

of diversity is to implement Community Benefit 

Agreements. JW Community Benefit Agreements 

offer a broader, more flexible vision for how to 

maximize the power of community organizing so 

Community Bt:m:fit Agreement\" Mal",,, U,·"",,,'nanl 

Accountable. Washington, DC: Good Jobs First and the 

California Partnership for Working Families. 
136 

that local redevelopment efforts include concrete 

benefits for the community in which these activities occur. These agreement.s include, but arc not 

limited to, selecting MBEs for local projects. 

Continuation of Research on the Impact of 

Anti-Affirmative Action Laws and Policies 

The development of research-based policies to protect the civil rights of all Americans is critical: for 

that reason, research must continue to measure the 

impact of Proposition 209 on MBEs seeking public 

contracts with federal, state, and local contracting 

agencies. While the data in this report demonstrate 

an impact of Proposition 209 on the access to bidding and awards for construction businesses owned 

by people of color in the transportation industry. tbey 

also reflect a need for additional research in at least 

four specific arc as. 

• Recommendation: Research the extent to which 

collusion, "good old boy" networks, and other 

violations of equal opportunity occur and impact businesses owned by people of color. This 

includes continuing research to analyze if there is 

a prevalence of racial discrimination and/or differential treatment in lending and bonding practices at financial institutions. 

Recommendation: Research the trends for MBEs 

who did not survive in the post-Proposition 209 

climate. The data in this report capture trends 

from MBEs that survived after Proposition 209; 

however, they do not capture trends and barriers 

for those whose businesses failed. Research examining the economic trends of this population 

is necessary to fully understand the range and 

depth of Proposition 209's impact on MBEs ill 

California's transportation construction industry. Of additional value would be an analysis of 

best practices to promote success among MBEs, 

and the development of a realistic and accessible 

training tool for MBEs, agencies and/or corporations interested in fostering a diverse pool of contractors with which to conduct business, 

Recommendation: Research the impact of Proposition 209 on MBEs offering professional services. 

While this report documents the impact of the 

proposition on a large segment of the transportation construction industry, it does not fully capture the experiences of MBEs in professional services (e.g., architecture, engineering) who do not 

participate in public bidding processes. but rather 

in selection processes that may foster bias and/or 

discrimination. 

Recommendation: In order to further illuminate 

the ~lBE experience, research should include 

non-MBEs in future research, including SBEs 

and non-MBE DilEs. Adding these experiences 

will help clarify what is unique about the MBE 

experiences and what is shared with other COlTIparible enterprises. 

Recornmendation: Caltrans and other public 

agencies should develop a system of collecting 

and reporting data that clearly denotes categories 

for reporting on race, eihnicity, and gender for 

federal and state contracts, _ 

DISCRlMINATION RESEARCH CENTER 47 
137 

Conclusion 

FRE~ TO CO:\1PETE? 

In transportation construction-and the construction 

industry in general~~every project builds a resume. 

Every job makes an MBE more competitive for the 

next project. In theory, each MBE firm should be free 

to compete with non-MBE firms and be granted equal 

opportunity to compete on the same tier as their 000-

MBE counterparts. California is at a crossroads, 

reflecting on its response to an anti~affirmativc action 

law that has reshaped the landscape of opportunity 

for its communities of color. Ten years have passed 

since California voters reversed the course set fOfth 

by this country's leadership in 1965. Still, according to 

a 2006 polL California voters share a core value that 

celebrates equal opportunity and fairness. California 

voters also support public action as a strategy to ensure that everyone, irrespective of race or ethnicity, 

has an equal opportunity to succeed. 12fl 

The struggle for equal access to public contracts continues; however, the opportunity to shift the 

paradigm remains. California can no longer afford to 

engage in racial politics-as-usua1. As entrepreneurs 

and skilled craftsmen and craftswomen, MBEs have 

earned the right to equal opportunity and participation in state contracts. In a state as richly diverse as 

California, it is imperative for its leadership and corporations to embrace the business enterprises owned 

by people of color, for its own sake. As a state that is 

comprised of a majority of people of color, providing equal opportunity for the economic development 

of these communities is imperative. California's cco~ 

nomic vitality depends on iL • 

of North"'r1l Ca!lfornill, (2006), Survey ftndmgs on Ril\'wl 
138 
139 
140 
141 

Auth.ors 

Monique,W: MQrris" MS Michael D.,Sumner, 'Ph)) 

Jessica Z. Borja 

Additional sUPPQ.rtjrum,' 

Dia.ne T. Chin,-:tl> 

Mary Louise Frampton, J1? :Oa~cy, Vaughn 

Willoughby Anderson' 

Mary Elliott, PhD 

MollyHlggin. 

Erica Malve~~-Mil1er 

Jennifer Navarro Sata Fierre, ¥A 

AcknowledgllLents 

ThIS report was f~ded ~Y a grant from the Fulft!~rlg tbe Dream FundlPublicInterest Proj'ects, 

the T!teltott,E, Hendtrsrm Cen'ter f(ir~()cial Justice at the University {)/ Ca/ifomia, Berkeley School 

of L!Iw acknowledges t~efoll~w!ng nrganizfltions'ana indivulu,!!s foy/heh- as$iSla1tce and support 

regarding this. report: 

Open SotietyJnstitute 

Oilifornia Coni1¥issil?n{)~ the,Sta~ qfWomen 

California ~p~ei1t of'trahIWc)rtatiQ-u 

Equal Justice SOCiety 

Equal ,Rig~ts Advocates 

L~wyers C01J:!.mittef fot,Civil'Rights -of the San Francisco Bay Area 

National Assoda:tihn of Women BUslness'Owners 

Natipnal Economic ~velopmet)t and Law Center 

:t~t' tmpact Fund 

The California Coalition to.Anniyze the'lmpact of Proposition 209 

San Diego Hispanic Chamber ofCammerce 

Amanda Berger 

Ja,ttBrown 

Dominique C, Fulling 

Vivian HQang 

Aiteen C. I:ternandez Benjamin Todd jealoUS 

Jovita jenkins 

McHyMartin 

Melanie McLeod 

Eva Jefferson Paterson 

'Steven C, Pitts 

Alvin Starks 

Kimberly Thomas~Rapp 

BethYouhn 

Lastly, we 'tI!ish if> extend o{ty gratitude to the public contractors who participated in this study 

an4Jor whom this work contfnues, 
142 

II. Vision Fulfilled? 

The Impact of Proposition 209 on Equal Opportunity 

for Women Business Enterprises 

Table of Contents 

Executive "UIrITn;orv "'" 

Introduction 

Result:::;: WBE AwardAccess", 

Results: WBE 

Results: VVBE Focus Groups and Interviews 

Recommendations " 

lO 

l5 

24 

33 

S~PTEMBER 2007 
143 

Executive Summary 

Affirmative action programs were initiated in the 

1960s to correct patterns of discrimination against 

people of color and women of all racial groups in 

order to fulfill a vision to include all in the mainstream of the nation. Designed to open the doors of 

opportunity for all people, these programs sought 

to level the playing field in public employment, public contracting, and education. However, beginning 

in 1989 with the Supreme Court's ruling in City of 

Richmond v. J.A. Croson Company, the courts began to narrowly restrict mandatory affirmative 

action programs in public contracting. In California, 

growing efforts to eliminate affIrmative action culminated in 1996, when voters passed Proposition 

209, the California Civil Rights Initiative. This law 

ended virtually all affirmative action programs in 

public education, public employment, and public contracting. Although the federal district court 

ruled that Proposition 209 was unconstitutional, the 

Court of Appeals reversed the lower court and upheld the initiative. 

California's transportation construction 

industry is the source of over $2 billion in public 

contracts each year and will disburse several billion 

dollars in bond money to contractors throughout 

the state. As the largest granting agency for transportation construction statewide, the California 

Department of Transportation (Cal trans) has 

tremendous capacity to increase the wealth and 

employment opportunities among California's diverse population. To correct the historic exclusion 

of people of color and women of all racial groups 

from the transportation construction industry, 

Caltrans initiated a race- and gender-conscious 

Disadvantaged Business Enterprise (DBE) program and administered it for two decades until 

1996 when Proposition 209 eliminated affirmative action for all but federally funded projects. In 

May 2006, Caltrans discontinued the remaining 

race- and gender-conscious aspects of the federal 

program and adopted a race- and gender-neutral 

program. 

~ A VISION FULFILLED? 

In 2007. the Thelton E. Henderson Center for 

Social Justice (HCSJ) at the u.c. Berkeley School 

of Law completed an evaluation of the impact of 

Proposition 209 on businesses that were certified as 

Women Business Enterprises (WBEs) in 1996, when 

the initiative was passed. A Vision Fu{/illed? analyzes 

how the elimination of race- and gender-conscious 

programs have affected women-owned businesses 

in California's transportation construction industry 

Five distinct methodologies were used to analyze and 

document the impact of Proposition 209 on women· 

owned businesses. The study's research team analyzed 

WBE access to awards, measured the survival rate 

it)f 1996 certilled WBEs, surveyed those WBEs who 

survived, led focus groups with surviving WBEs, and 

conducted in-depth interviews with surviving WBE 

contractors. By using multiple methods, the research 

team was able to document and verify a significant 

impact of Proposition 209 on WBEs. Key findings 

include: 

After the passage of Proposition 209, real dollars awarded to certified WBEs feU hy roughly 40 

percent. In 1985, certified WBEs wcre awarded 

2.1 percent of federally funded Cal trans projects. 

This percentage steadily increased thereafter to 

reach an average of 6.7 percent in the six years 

leading up to and including 1996, the year that 

Proposition 209 was passed. With the elimination 

of the Caltrans affirmative action program, this 

percentage dropped significantly to 3.8 percent in 

the years that followed the passage of Proposition 

209. White women-owned WBEs mirrored these 

trends closely while women of color-owned WBEs 

showed a different pattern. Prior to 1991, women 

of color-owned WBEs had received no awards at 

all. By 1993 they were receiving almost 2 percent 

of the awards but thereafter this number dropped 

to 1 percent and has remained steady since that 

time, for the years that data were collected. 

Only 36 percent of WBEs certified with Caltr.ns 

in 1996 are still in business today, In 1996, 2,096 
144 

transportation construction businesses were 

owned by women and registered with Caltrans 

as WBEs. Today, only 763 of those businesses are 

still in operation, 79 percent of which are owned 

by white women. However, without an appropriate comparison group. the interpretation of the 

relative success of WBEs is difficult to ascertain. Finns owned by African American women 

were significantly less likely to survive than other 

WEEs. 

WEEs reported that the overan helpfulness of the 

DBE program fen significantly after 1996. Following the passage of Proposition 209, WBEs 

reported a decline in the quality of pre-bidding 

conferences, "good faith" outreach efforts initiated by prime contractors, and the DEE program in 

general. Surviving WBEs also reported a regular 

inability to work with Caltrans. Women of colorowned WEEs reported relatively more difficulties 

post-Proposition 209 than white-owned WEEs. 

• Sunil'ing WBEs have struggled to overcome gender bias in the transportation construction industry. 

Focus groups and interviews reveal that the transportation construction industry 8ti11 embraces a 

"good old boy" network that is difficult fClr women 

to access and overcome. Participants attributed 

their success in the construction industry to continued visibility to potential clients, shifting their 

focus from public agencies, strategically responding to requests for proposals, and exercising legal 

recourse when necessary. 

A Vision Fulfilled? has found that women 

face significant barriers when trying to participate in California's transportation construction 

industry. To support equal opportunity for womenowned businesses to participate in this field, H CSJ 

recommends the augmentation and enforcement 

of a robust DBE program that utilizes gender-conscious equal opportunity goals and programming, 

The findings of this report suggest that women are 

currently underrepresented among firms receiving 

pubic contracts, and that this underrepresentation has been hastened by the implementation of 

Proposition 209, Because of California's ongoing 

interest in supporting the equal participation of 

women in the transportation construction industry, HCSJ also suggests that Caltrans and other 

public agencies provide training for key leadership at contracting agencies to address historical 

and present manifestations of gender bias and 

institute policies to enforce anti-discrimination in 

the workplace and on public projects. The development of additional structures to support and 

encourage the participation of women along key 

pathways to becoming entrepreneurs is also criticaL Other recommendations include improved 

data collection for women-owned businesses, 

continued research on the impact of Proposition 

209 on women in the transportation construction 

industry, and advocacy for implementing the business model of diversity .• 

THEI,TON E. HENDERSON CENTER FOR SOCIAL JUSTICE 
145 

Introduction 

"1 see afuture ofjustice---the simple human/ustiee afequal rights.fin' all nun and/or all women, 

guaranteed equal rights at last under the Constitution of the United States of America ... 1 IFemf 

women/ree to pursue without lirni! the fUlll{fe o.f what they H'antjor themselves .. .! IVan! the 

people in business free to pursue It'ith boldness antifreedom new ideas ... and J want minority 

citizcns/iti(Y' tojoin the mainstream a/American life. I need/(Jt all (~lyou to join me fnfu(filling 

that vision ... l/H'c succumb to a dream world then we'll tvake to a nightmare. But IIit'c start Jl'ith 

reality andftght to make our dreams a reality, then Arnericans will have a good IVe, a life of 

meaning and purpose in a nation that:r; strong and secure. "-President Jimmy Carlo· 1 

For centuries, women have been engaged in a struggle 

to achieve parity with men in access to employment 

and other opportunities that foster economic development. While some doors have been opened to include 

women in industries that have historically excluded 

them, there continue to be significant barriers to their 

full and equal participation. Prior to the 1940s, it was 

not common for white women to formally work in the 

labor market. Wh ile women of color have a long history of such participation in the labor force, primarily 

as domestic and agricultural workers. it was not until 

the early 1940s that women of all racial groups began 

to comprise a sizeable percentage of working adults. 

This growth filled the blue-collar vacancies caused by 

men joining the military during World War II, a time 

in which the numbers of women in the labor force increased by nearly 32 percent. 2 

Twenty years later, largely in response to the 

Civil Rights Movement of the 1960s, the federal government enacted a series of corrective responses to 

racial and gender discrimination. These responses 

included a series of art1rmative action programs that 

implemented systems of accountability via goal-set~ 

ting and incentives to encourage the participation of 

those who had faced historical exclusion and discrimination in the public sector. 

In 1961, President Kennedy signed Executive 

Order 10925, in which he called upon federal con1 President Jimmy Carter, Second Presidential Nomination 

Acceptance Specch. Delivered on August 14, 1980. 

) Arriola, E.R. (1990, Fall). "What's the Big Deal? Women in the 

New York City Construction Industry and Sexual Harassment 

Law. 1970·1985," Columhia Ullman RighlS La\)' Review. 22,21-71. 

4 A VISION FULfILLED? 

tractors to use "affirmative action to ensure that 

applicants are treated equally without regard to race. 

color. religion. sex, or national origin." President 

Johnson signed Executive Order 11246 in 1965, establishing a series of contracting and employment 

programs to guard against the underutilization of 

and discrimination against people of color. This order was amended in 1967 to include gender-responsive 

strategies for women of all racial groups who had also 

encountered measurable discrimination. With diversity established as a compelling government interest, 

Disadvantaged Business Enterprise (DBE) programs 

were developed. StilL it was not until the early 1980s 

that the federal government began to prioritize including women as equal citizens~~allowing equal access 

to employment and other systems to foster their economic development. 

While there is some evidence to suggest 

that women have been ihe largest beneficiaries of 

affirmative action since the 1980s. the legal and political discourse and media coverage have, in general, 

treated women as an afterthougbt.·; In addition to 

President 10hnson's two-year delay before amending his Executive Order to include women. there 

was also a delay in President Richard Nixon's effort 

to include women in programs to support equal opportunity. In 1971, President Nixon's Order No.4 

was expanded to include women·---a full year after it 

, Wise, T. (1998, Fall), "Is Sisterhood Conditional': White Women 

and the Rollhack of Affirmative Action" N WSA Journal. 10(3), 

J-26. Sec al:>o Jackson. 1. (1999, Jallu"fy/h,hnm,,). "Affirmative 

Action Coverage Ignores Women Dis"i"in,,,ion, A sixmonth study of media l:ovcrage." Extra.! 
146 

had already authorized flexible goals and timetables 

to correct the under utilization of Minority Business 

Enterprises (MBEs) by federal contractors. It was not 

until President Jimmy Carter's administration that 

significant strides were made to support the development of women~owned businesses. In 1979. President 

Carter established the National Women's Business 

Enterprise policy, which encouraged the nation to 

take affirmative action in supporting women's businesses. The nation responded and began a trend that 

would increase the participation of Women Business 

Enterprises (WBEs) on public projects. 

Still, longstanding prejudice, cultural bias, and 

discriminatory practices have placed women at a comparative disadvantage to mcn.4 This is especiaJly true 

in fields traditionally dominated by men, including the 

transportation construction industry. The percentages 

of women in the construction industry as tradespersons 

and business owners have always been small, While 

gender-conscious affirmative action programs have 

supported an increase in the number of women participating in public contracting, the federal government 

has never been able to reach its target of awarding five 

percent of contracts to women . .'i The inability to reach 

this modest goal reflects the difficulty for women entrepreneurs to enter and succeed in the male-dominated 

transportation construction industry. 

The Dismantling of GenderMConscious 

Affirmative Action in Public Contracting 

Despite a significant increase in the visibility and 

participation of women-owned businesses in public contracting in the 1980s. there were a number of 

legal challenges to the merits of affirmative action 

-' Otten, L A. (199~). Women's Rights<1nd the Law. Westport. CT: 

J>raegcr Paperback. See also Cheng. A. S. (2002). "AfTmnath'c 

Action for the Female Entreprenem: GcnJcr as a Presumed 

Socially Disadvantaged Group For 8(<1) Program Purposes:' 

American Universil)" Journu{ (~f" Gmder. Social PoliO' & rhe Law. 

10(1),185-231. 

"' Rand Corporation for the Small Dusiness Administration. 

(2007). The Utili:::atian a/Women-Owned Small Businesses in 

Fednal Contracting. 

that impacted the enforcement of gender-responsive 

remedies to exclusion and discrimination. In 1989. 

the US. Supreme Court ruling in City 0/ Richmond 

v . .r.A. Croson Company began the erosion of judicial 

support for race" and gender-conscious equal opportunity programs. Following that decision were a 

number of cases that indirectly and directly impacted 

the use of gender-responsive equal opportunity programs in public contracting.' In the 1990s, a growing 

effort to eliminate affirmative action programs in 

education and public services culminated in 1995 

with Proposition 209, a ballot initiative designed to 

eliminate affirmative action in public education, public employment, and public contracting. Entitled the 

California Civil Rights Initiative, Proposition 209 

passed with 55 percent of the public vote in 1996. After 

surviving a series of legal challenges, Proposition 209 

became law in 1997. Since the elimination of affirmative action in California, relatively little research has 

been conducted on any potential changes in public 

contracting and employment and how these changes 

have impacted women in business. As of this report's 

publishing, a decade has passed since Proposition 209 

amended California's constitution to eliminate raccand gender-conscious equal opportunity programs in 

public education, employment. and contracting. 

A Vision Fu(filled? The Impact (~(" Proposition 

209 on Equal Opportunity jor Women Business 

Enterprises reports on the ways in which the removal 

of gender-conscious equal opportunity programs affected women seeking public contracts in California's 

transportation construction industry from 1996 to 

2007, focusing on public contracting trends in the 

state Department of Transportation (Caltrans). This 

report investigates whether the transportation con~ 

str uction industry has successfully responded to 

President Jimmy Carter's call to action in 1980. Have 

we fulfilled the vision ofajust society in which women 

have an equal ability to freely pursue their business 

ambitions'! _ 

h Sec Legal Revjc\-v for further explanation. 

THELTON E. HENDERSON CENTER rOR SaCrAL JUSTICE 5 
147 

Legal Review 

Overview of Affirmative Action Jurisprudence 

In the early years of aCflrmativc action) the courts consistently upheld governmental programs designed to 

correct entrenched patterns of race- and gender-based 

exclusion and discrimination. For example, in 1979, 

the U.S. Supreme Court held that the use of temporary, 

voluntary affirmative action programs to remedy past 

discrimination did not conflict with the Civil Rights 

Act of 1964-' In 1987, the Court reiterated the ~iew 

that gender-based classifications in hiring designed to 

remedy the imbalance of women in traditionally segregatedjob categories was consistent with the purpose 

of the Civil Rights Act of 1964. 

TWo years later, however, in City of Richmond 

v. l.A. Croson Company.~ the Supreme Court struck 

down the City of Richmond's affirmative action plan 

and declared that racial classifications which benefited 

people of color would be analyzed by the same strict 

constitutional scrutiny used to evaluate laws that discriminated against such people of color. Applying this 

"strict scrutiny" standard, the Court held that government-initiated race-conscious affirmative action 

programs must serve a compelling government interest and be narrowly tailored to achieve this interest. 

To demonstrate a compelling interest, reasoned the 

Court, the governmental entity was required to show 

that it had discriminated against people of color in the 

past and to prove that an affirmative action program 

was necessary to address the effects of such discriminatioll.9 Thc program was also required to be narrowly 

tailored to benefit only those who could demonstrate 

that they had been vlctims of discrimination. H) The 

Court indicated that local entities could amend their 

affirmative action programs to correct discriminatory 

practices that had a statistically demonstrated disparate impact;] and set defined goals, expiration dates, 

, United Steelworkers 1'. f,Veber, 443 U.S. 193 (1979). 

'488 U.S. 469 (1989). 

9 Ihl<[. at 496-97. 

10 Ibid. at 506. 

11 Ibid. ilt 509. 

A VISION FULFILLED? 

and procedures for mitigating the effects on those not 

benefiting from them. 12 Government entities were also 

instructed to consider possible race-neutral programs 

that extend opportunities to all through race-neutral 

classifications and to a void disadvantaging those not 

eligible for government programsY 

While this ruling specifically addressed only 

racial classifications. the opinion had a significant 

practical impact on gender-based affirmative ac· 

tion programs as welL In the wake of the Croson 

decision, many agencies across the country imme· 

diately dismantled their race- and gender-c(;nscious 

anti-discrimination programs, while others suspended 

programs pending the results of the disparity studies 

required hy the rUling. 

However, the u.s. Supreme Court has consis· 

tently held that gender-based classifications are subject 

to "intermediate" scrutiny, a different constitutional 

standard than race-based classifications. In cases such 

as United Slates l'. Virginia," the Court has held that 

gender~based classifications must only serve an important government interest and be substantially related 

to this interest. In applying this "intermediate scruti· 

ny," a lesser level of scrutiny, the Court has recognized 

that men and women arc not similarly situated SOclOlogically, pbysiologically, or legallyL' Indeed, in many 

instances, the Court has shown a tendency to defer to 

the legislature's identification of an important interest 

that would be advanced by policic< promoting gender 

equality and engaging in only a minimal analysis of 

whether there is a substantial relationship between the 

policy or program being challenged and the identified 

government interest. 16 Despite this different standard., 

the Supreme Court has never explicitly established a 

separate level of scrutiny for gender-based affinnative 

action programs. 

I; Ibid. at 510. 

I, Ibid, at 507. 

:4 5181..1.S. 5!5 (1996). 

1< Ibid. at 5::13~34. 

1(, Sec ,\-fichae/ M. l', Superior ('OUI"I (~f"Sonoma Cmmry, 450 U.S. 

464,473 (1981). 
148 

Prior to the enactment of Proposition 209, 

a California statute17 required general contractors, 

including those in the transportation construction 

industry, to demonstrate a "good faith" effort to subcontract five percent of their work to WBEs, as well 

as 15 percent to MBEs and three percent to disabled 

veteran-owned businesses. 18 In Monfere:v IWechanical 

Co. 1'. Wilson, the Ninth Circuit Court of Appeals held 

that the statute violated the Equal Protection Clause 

because California had not ofrered legislative or factual findings proving past discrimination by the state 

against the benefited groups as required by Croson.JC! 

Because of this narrow holding, the court did not address the question of what constitutional standard 

should be applied in this case.:o 

Proposition 209 and Immediate Challenges 

Notwithstanding the federal courts' guidelines for 

crafting affirmative action programs that met constitutional standards, Proposition 209 barred all affirmative 

action programs that used race-based or gender-based 

classifications. Proposition 209, enacted as Article L 

Section 31 oftheCalifornia State Constitution. reads in 

part, "the state shall not discriminate against or grant 

preferential treatment to, any individual or group on 

the basis of race, sex, color~ ethnicity, or national origin 

in the operation of public employment, education, or 

public contracting,"ll Subsection C further states that 

'nothing in this section shall be interpreted as prohihiting bona fide qualifications based on sex which arc 

reasonably necessary to thenormal operation of public 

employment, public education, or puhlic contracting:'22 I mmediately after the enactment of Proposition 

209, groups representing the interests of women and 

people of color filed a complaint against the State 

I~ Cal. Pub. C~lllt. Code ~ 10,1 15 (Dc~ring 1994). 

1$ 125 F3d 702. 704 (9th CiL 1997). 

I" Ibid. at 702, 

c() Ihid. at 713. 

21 Cal. COllSt. art L sec. 3l(a). 

n Ibid. atsec31(cL 

... Proposition 209 barred all 

affirmative action programs that 

used race-based or gender-based 

classifications. 

of California challenging the law as violative of the 

Equal Protection Clause." Tbe plaintiffs asserted that 

Proposition 209 created an invalid political structure 

that limited the ability oflocal governments to remedy 

the effects of past discrimination.~4 The district court 

prohibited the implementation of Proposition 209 on 

the grounds that it singled out people of color and 

women of all racial groups for unique political burdens, could not withstand the strict scrutiny test under 

the Equal Protection Clause, and was contrary to the 

purpose of (he Civil Rights Act of 196425 

However, on appeal, the Ninth Circuit Court 

of Appeals held that because women and people of 

color constitute a majority of the popUlation they 

could not have voted to "stack the political deck" 

against themselves and that it is for the people, not the 

courts. to determine whether the initiative vindicated 

compelling state interests." The court also noted 

that affirmative action programs would generally be 

viewed as attempts to grant preferential treatment. 

which would be contrary to the Equal Protection 

Clause." It noted that while carefully crafted race- or 

gender~based preferences could sometimes be justified 

under the Constitution, the Equal Protection Clause 

does not mandate thcm. 215 The ruling encompassed 

not only numerical goal-oriented programs, but also 

any targeted outreach programs based on race or gender, including those operating in the transportation 

construction industry. 

Although the court cited Virginia for its gender-based classifications standard, its actual analysis 

conflated the constitutional requirements for racc- and 

gcnder-hascd classifications and thus appears inconsistent with most federal jurisprudence on the issue. 

~l Coalition/or Economic Equity I'. rVifson. 946 E Supp. 1480 (N.D, 

Cal. \996). 

24 llnd, at \50:>;-09. 

2< Ihid. 

2,\ Coalition for Economic Equity.,. Wilson, 122 F.3d 692. 707 (9th 

Cif. 1997). 

)~ Ibid. at 708. 

Ibid. 

THELTON HENDERSON CENTER FOR SOCIAL JUSTICE 7 
149 

Legal Review 

Challenges to Gender-Based Affirmative 

Action Post-Proposition 209 

Since the enactment of Proposition 209, attempts to 

defend affirmative action at any level of government 

in California have largely been unsuccessfuL In 2000, 

a general contracting firm challenged a program 

that had been established by the City of San Jose in 

1983 to encourage public works projects participation by WBEs and MBEs-" Under this program, the 

City established a preference for granting contracts 

to bidders who had demonstrated reasonable efforts 

to subcontract with a specific percentage of WBEs, 

documented solicitations of WBEs. and provided justification for insufficient representation of WBE and 

MBE subcontractors. 3D Ruling that Proposition 209 

prohibits programs from considering race or gender 

in its formal outreach and procurement programs, 

the California Supreme Court struck down the City's 

outreach requirements,J) The Court ruled that some 

forms of outreach would still be permissible under 

Proposition 209, including efforts to increase opportunities and participation in public employment and 

contracting directed to all types of subcontractor enterprises. such as small business enterprises. The court 

also ruled that other attempts to make information 

about public employment, education and contracting 

more widely available would be permissible,3~ 

In an attempt to comply \\lith Proposition 209, 

many local governments responded by immediately 

suspending WBE and MBE certification programs and 

attempting to develop programs that could legally provide assistance to women contractors and contractors of 

color. For example, the County of Contra Costa instituted 

a new outreach program that encouraged participation 

from an array of small and developing businesses, in24 /If-Voltage rVire TVorks, Inc. ... City o(San Jose. 24 Cal. 4\h 53i 

(lOOO). 

to Ibid. at 543.544. 

't lhu/. at 563·565. 

'" lhid. at 566. 

8 A VISION FULFILLED? 

cluding WBEs, without specilic hiring goals.)) In 2001 a 

group of WBEs and MBEs brought a class action lawsuit against the County, contending that its contracting 

system was invalid because it had a disparate impact on 

them. Plaintiffs also argued that the subjectivity of the 

system allowed the County to discriminate against WBE 

contractors}4 The court ruled against the plaintiffs on 

the grounds that they had not oflercd sumc;ent data to 

prove disparate impact and had not demonstrated that 

the discrimination was intentionaV5 

However, a recent Court of Appeals opinion 

may signal a shift in Proposition 209 jurisprudence. 36 

When two construction companies challenged 

San Francisco's Minority/Women/Local Business 

Utilization Ordinance for its use of race- and genderconscious classifications, the City raised a number of 

defenses, including a political restructuring argument. 

an international human rights approach, and an assertion that elimination of its program would threaten its 

continued receipt of federal funds . .\? The City'S record 

included a 2003 disparity analysis condtlct~d by the 

City's Human Rights Commission, which showed that 

the City was actively discriminating against women 

in its contracting and that its discriminatory practices had a statistically disparate impact on women. 

This study also showed that the City's discriminatory 

contracting practices violated federal law and that 

gender-conscious remedial programs would be required to bring the City lnto compliancc.J.8 Though 

the Court of Appeal held that the City had not met its 

burden of producing substantial evidence that it would 

lose its federal funding without gender-based remediq L. TaranRo n'ucking 1". County (((Contra Costa. !Sl F. Supp. 2d 

lOli, 1034-35 (N.D. Cal. 200n 

1\ Ibid. at 1023-1024. 

" Ihid. at 1032 

1(. Coral Construction. If/'. 1". City and Cmmt)' o(San Francisco, 

149 Cal. App. 4th 1118 (lst Dist. 200i). N~tc:' the California 

Supreme Court granted review of this decision on August 22, 

2007. 

H [hid. at 1231-1240. 

'~[hid. at 1229-!230. 
150 

a1 measures.·w it did determine that the trial court had 

failed to consider whether the City's program was a 

narrowly-tailored program designed to remedy past 

discrimination as constitutionally required. 4

() In its 

opinion, the Court stressed that while the trial court 

had focused on the requirements of Section 31 of the 

California Constitution, "[t]he federal equal profecrion 

clause is the last word.''41 

As noted above, San Francisco defended its 

race~based affirmative action program on the grounds 

that its receipt offederal funding requires it to comply 

with Title VI of the Civil Rights Act of 1964;" which 

bars race-based discrimination in all programs receiving federal financial assistancc.jJ The Court of 

Appeal concluded that the agency's affirmative action 

program violated Proposition 209 and that no federal 

law mandated the use of race-based affirmative action when race-neutral measures had not been tcsted. 44 

However, the court's holding did not extend to gender-based affirmative action programs because only 

the race-based aspects of the agency's program were 

challenged.4s Although federal requirements must be 

documented for any race- or gender-based program 

to be defended under the federal funding exemption, 

there does not appear to be any specific case law addressing how the exemption would bc evaluated in the 

gender context. 

Response of the California Transportation 

Contracting Industry 

In general, the California transportation contracting 

industry has taken a cautious approach in response 

to recent federal affirmative action jurisprudence. In 

2005, the U.S. Court of Appeals for the Ninth Circuit 

N Ibid. at 1234. 

~I) lhid. at 1250. 

~l Ihid. at 1247 (emphasis in original). 

~: 42 US.C § 2000J. (West 2006) 

"' 122 Cal. ApI'. 4'h 194. 304 (3d Dist. 2004). 

4,) [hu/. at 311<,.12. 

!< !hid, at 292. 11.2. 

struck down a State of Washington DBE program 

with a minority utilization requiremenL16 Concerned 

about maintaining its federal funding, Caltrans suspended its race- and gender-based DBE program in 

favor of race-nentral measures in 2006 after concluding that evidence provided by a past disparity study 

would be insufficient to meet federal constitutional 

standards. Caltrans has hired a consultant to conduct 

an availability and disparity analysis in order to assess 

whether race- and gender-conscious programs should 

be reinstated. While Caltrans' initial announcement 

regarding the abandonment of its DBE program did 

not explicitly refer to gender-based remedial programs 

- a reminder that jurisprudence in this area remains 

unsettled - its analysis found justification for a genderconscious equal opportunity program.47 

Whether at a federal or state level. judicial 

analysis of gender-hased classifications in affirmative 

action programs has not reached the same level of 

development as that for race-based classifications in 

such programs. Perhaps a more prohing analysis will 

follow in which courts will clarify what constitutional 

standard should be applied to gender-based affirmative action programs. With the present uncertainty 

however, under Proposition 209, gender-based programs to assist WBEs seeking public contracts have 

been dit1icult to maintain in California. _ 

.l~ Western States Paring Co. l". rFashington Slate Department of 

Transp0/"filflOll. 407 E.1d 9S3 (9 \ ('ir. 2(05). 

Transportation. (2007. June). AvailabilifY and Disparity Stut(r. 

THt::LTON E. HENDERSON CEi'JTER rOR SOCIAL JUSTICE 
151 

Literature Review 

Since its inception, the transportation construction 

industry has traditionally been male-dominated. 

Between 1980 and 1996, the percentage of women in the 

construction trades tripled. yet still only accounted for 

less than three percent of the construction workforce.4

8. 

Women entering non-traditional fields often face 

strong resistance. often to the extent that their skills or 

experiences arc overlooked orundermined.49 Pervasive 

sexual harassment, unequal treatment. and intimidation in the construction field has had devastating 

effects on the advancement ofwomen. 5

(l Nevertheless, 

in part due to gender-conscious goals and procurement 

programs, many women-owned businesses have made 

great strides over the last several decades. For example, in 1972, women owned five percent (approximately 

400.0(0) of businesses nationwide;" however, by 2002. 

the number of businesses owned by women jumped 

to nearly 6.5 million) representing approximately one 

third of all businesses in the country.S1 

While the overall number of businesses owned 

by women has increased over time, these businesses 

have been clustered in industries sueh as retail and 

personal servicesY Women have remained relatively 

invisible as competitors in industries that are traditionally male, such as the construction industry, and 

face unique challenges to their participation as skilled 

tradespersons, business owners, and public contractors. Nationwide, of the 2.8 million construction 

businesses, only seven percent are women-owned. 54 

-I, DiscriminatIOn Research Center and Equal Rights Advocate,>. 

(2004. June). 

Construction 

4~ Payne. B. J. (!990), "Is Women Dusincss Enterprise 

Discrimination 11 Reality?, Journal of' the TransportatiON 

Research Board. /2~2. 

,II Supra, note 48. 

'\ VS Censtis Bureau. (l972). "Table 1." Women-Owned Busines.l·cs, 

'2 US Census Bureau. (2002). "Women-Owno.)d Firms, Table I." 

Survey of' Business OlFner.~. 

"INd. 

10 US Census Bureau. (2002). "Women-Owned Finns, Table It" 

Surrey olEusflles.'; Owners 

10 A ViSION rULFILLEIY' 

Projections based on figures from the 1997 and 2002 

Economic Census estimate that between 1997 and 

2006 the number of women-owned construction 

businesses decreased by 45 percent, including a 42 

percent decline in the number of employees, and a 

35 percent decline in annual sales nationwide. 55 The 

challenge faced by women in non-traditional fields, 

such as construction, is having to prove that they are 

equally qualified to compete with men. Affirmative 

action programs have attempted to help women break 

into and compete equally in all fields SInce the 1960s, 

However, the success of women~owned businesses 

have become increasingly limited in non-traditional 

industries since the elimination of such programs. 

Gender .. Conscious Affirmative Action 

Programs 

One of the first uses of affirmative action in public 

contracting, the Philadelphia Plan. was put into operation in the late 1960s by then-Assistant Secretary of 

Labor, Dr. Arthur Fletcher. Using participation goals 

and timetables, the program sought the inclusion of 

businesses owned by members ofhistoric~ll1y disadvantaged groups on federal contracts in Pennsylvania. 56 

In the decades that followed. with the development and implementation of equal opportunity 

programs across the nation. business ownership began to expand among groups that had faced historical 

discrimination, Federal, state, and local governments 

developed various affirmative action programs aimed 

at strengthening the competitiveness of undcruti~ 

lized businesses, but these programs regularly did 

not include women. In the late 1970s, in response to 

the lobbying efforts of female entrepreneurs, the fed~ 

Actual numbers \vill be 

Economic Census. Center for 

Women's Rusiness Research. (2006, September). Women-Owned 

Businesses in ,he Unired States 2000. Fact Sheet. Washington, 

DC. 

'0 Ort1:ce uC tht~ Assistant Secretary for Administration and 

Management. "Nixon and Ford Administrations." In Brie/ 

IliSIOI'Y q/ DOL. Retrieved March 24, 2006. from http://www.dol. 

gov!oasam/programsihistory/d\)khp07.htm. 
152 

eral government created the Interagency Task Force 

on Women Business Ownership. In its report. "The 

Bottom Line: Unequal Enterprise in America/' the 

task force reviewed the status of women-owned busj~ 

nesses in the United States. In 1979, President Jimmy 

Carter responded to the barriers documented in the 

report by establishing the Office of Women's Business 

Ownership within the Small Business Administration 

(SBA). Soon after, the office began to proactively 

encourage the participation of women-owned businesses in government projects, marking an important 

step for firms owned by women. 57 

Gender-conscious equal opportunity programs were initiated with the intention of opening 

doors for women who had faced discrimination as 

a result of their gender. In the transportation construction industry and for women in general, the 

development of specific gender-conscious programs 

came only after programs were already broadly established for people of color. For example, in 1965, 

Executive Order 11246 required federal contractors 

and subcontractors to maintain written affirmative 

action plans for underutilized businesses owned by 

people of color. However, it was not until two years 

later, in 1967, that Executive Order 11375 extended 

these guidelines to include women of all races. 58 

In 1982, Congress established the DBE program through the U.S. Department of Transportation 

(USDOT) to encourage the participation of small 

businesses owned by people of color, including 

"vomen of color, and other socially and economically 

disadvantaged groups. including disabled veterans, in 

federally funded projects. However, small businesses 

owned by women of all racial groups were not included in this program until five years later, in 1987, when 

the Surface Transportation and Uniform Relocation 

<, National Women's BUSiness Council. (2002, December). Support 

(or H'(Jff/en's Enterprise in the United States: Lessons Learned. 

<, Office of Federal Contract Compliance Programs. "Executlve 

Order !1246. As Amended." Retrieved :\0.2007. from 

Assistance Act was enacted.s'! For women, the path 

to equal rights and opportunities through American 

policies is often fraught with inconsistencies, despite 

the establishment of policies aimed to correct racial 

discrimination. 

Barriers to Success for Women Business 

Enterprises 

For women, the ability to own a business is often 

challenged by specific issues that prevent them from 

participating on equal footing with men. In California 

and elsewhere, these include poor agency data collection regarding the participation of women, gender 

discrimination, unequal access to capital and financial support for women-owned businesses, barriers 

presented by the intersection hetween race and gender, and the impact of Proposition 209 on pathways to 

entrepreneurship. 

Poor Agency Data Collection Regarding the 

Participation of Women 

The House Small Business Committee has found that 

"miscoding:' or awarding contracts that are intended 

for small businesses to ineligible large businesses, is 

problematic among many federal departments. The 

committee found that in 2005 the SBA had reported an 

inflated small business participation rate 01'25 percent 

Once miscoding was factored in, this rate fell to 22 

percent, accounting for a total of $1 1.9 bi1lion wrongfully awarded. llSDOT also reported a miscoding rate 

of 25 percent.60 Such a high rate ofmiscoding creates a 

false perception of participation of small businesses in 

the marketplace, resulting in the reduction of genuine 

opportunities for all ~mall businesses. especially those 

owned by women. 

<'! Blanchflower. D.G .. and Wainwright. J. {lOO), ~o\'embcr), An 

f'mgrams 011 8('(1: 

No.W11793. 

0(1 House Small Business Committee Democratic Stare (2006, July). 

.""{'orecal'd Vlf: Faulty At'Coul1ting hy Administratw" Resuits in 

.Hissed Opporfuniries/i.>r Small Businesses. 

Tf!ELTON E HENDERSON CENTER FOR SOCIAL JUSTICE 11 
153 

Literature Review 

Gender Discrimination 

Gender discrimination has had a consistent and sub· 

stantial presence in the history of women-owned 

business in the construction industry. The traditional 

path toward upward mobility begins with entry-level 

workers who increase their skills by receiving direct 

mentors hip and skill development from supervisors, 

trade schools, or apprenticeship programs, experience 

that can eventual1y lead them to become managers 

and contractors themselves. 61 Unfortunately, gender 

discrimination in the traditionallv male construction 

industry has prevented women from accessing and 

obtaining we1l-paying construction jobs. which can interfere with their ability to acquire the necessary work 

experience to qualify them as future contractors.6~ 

Although women-owned firms tend to be smaller and 

younger, there is evidence that their limited access to 

markets for business can be attributed. in part, to their 

being women-owned. That is, as women-owned businesses face discriminatory barriers which prevent them 

from selling their goods and services. women-owned 

businesses are unable to grow as quickly as male-owned 

businesses. 63 A study published in 2003 found WBEs 

faced barriers to accessing larger contracts. The study 

found that when the value of subcontracts increased, 

the share of awards to women-owned small businesses 

decreased. For example, when federal prime contractors subcontract more than $1 million, WBEs receive 

less than half the share that they would ifsubcontracts 

offered were less than $1 million, receiving only four 

percent compared to nine percent of the dollars. This 

can be explained in part by the fact that smaller businesses in general have difficulty competing for and 

~I This differs from engineering, where the majority of individuals 

working in the engineering industry have at least a four-vear 

college degree. BBe Research and Consulting for the C,,;lifornia 

Department ofTnmsportation, (2007, June), Artlilabibty and 

Disparity Study. 

,<2 Slipra. note 48, See also supra, note 61 

,,' Bates. T. (2002, Jul}). "Restricted Access to Markel 

Characterizes Women-Owned Businesses < Journal olBusiness 

Venturin~. 17,313-324, 

A VlSION FULFILIJED? 

obtaining very large subcontracts (such as those that 

are several million dollars). M 

Previous studies that have examined economic 

data and collected anecdotal evidence have established 

that discrimination in market access continues to exist 

for womenwowned businesses, particularly for women 

of color.(i~ Women business-owners are regularly ex· 

cluded from "good old boy" networks, not informed 

of bidd ing opportunities. and arc barred from bids 

entirely. They have also reported discriminatory com· 

petition such as unequal pricing for different firms 

and biased standards of review. Resistance to worn· 

en entering the construction industry is also found 

within unions. Women are discouraged from pursuing unionizatIon by being subject to exclusionary 

entrance procedures that include advance payment 

of fees, secretive or limited application acceptance 

dates, difficult testing, or requirements that mandate 

that the applicant complete a certain number of hours 

for an industry employer prior to applying.(i(i These 

practices undermine the ability of women to compete 

and also impact whether women are able to launch 

and sustain viable enterprises. Some WBEs have reo 

sponded by focusing on companies with whom thev 

have built relationships or by simply staying out ofth~ 

public contracting sector altogether.67 

In a Pennsylvania-based focus group that 

included WBEs who bid for state and municipal 

contracts, participants stated they felt that male con· 

tractors and vendors held prejudicial views regarding 

the ability of WBEs to complete a job and generally 

regarded them as "unsophisticated, lacking necessary 

equipment and resources. and not having needed ex1,1 National Women's Bminess Council. (2002, September). r!iimINIOwned Small Businesses in Federal Subcontracting: .lleasures 

and Data 

(,< Supra. note 59. 

(.1, Supra, note 48. 

1" Mel ,ywont. R. (20(1.1. June). '·Reconstructing Aftlrmative 

Action; Opinion:; differ as to the damage done and how to repair 

it." ,'lImoril), Business Entrepreneur. 20(3). !6 
154 

perience in or knowledge of contracting procedures.~·68 

This is compounded hy the prevalent negative perception among prime contractors that affirmative action 

programs give preference to unqualified applicants, 

affecting an women, especially women of COlO1~M 

Although studies have shown no evidence of weaker 

labor market performance among heneficiaries of 

affirmative action programs,7o WBEs reported that 

they must make an extra effort to prove their abilities to prime contractors in order to win a subcontract 

award, even when fully qualified l,lt the job, Others 

have responded to negative stereotypes by lowering 

their prices or increasing the amount of work with~ 

out increasing the submitted bid price.71 Other studies 

report that prime contractors abuse the WBE good 

faith efforts in order to win contracts··listing WBEs 

as onc of their subcontractors, but never following 

through with actual subcontracting projects.n 

Unequal Access to Capital & Financial Support 

Access to financial capital is: an important component 

to success. In its 1997 report summarizing disparities in 

government contracting. the Urban Institute found that 

limited experience in borrowing, difliculty demonstrating creditworthiness. having low income, low rates of 

home ownership and poor capital resources limit WBEs' 

~'us Commission on Civil Rights. "BanieTS Facing Minority~ 

and Womcll~Owned Businesses." rn Barrter.\· Facing MillorifY~ 

and Women-Owned Busil1l!sses in Pennsylnmia, Retrieved 

December 8, 2006 from hup:lIwww,useer.govfpubs/sac/pa0802! 

ch3.htm. 

,,~ Jahhra. N, W. (2001. August). "Affirmative Action and the 

Stigma of Gender and Ethnieity: Caiifz1r11ia in the 1990s:' 

Action: What Do We 

.Manaf(emenl, 25(2). 463.490. 

") US Commission on Civil Rights. "Developments in Minorityand Women Owned Business Utiliz<ltion at the Stale and 

Local Levels." In ffacna,,"ann< 

Businesses in Pennsy/wmia December S, 2006 from 

http://www.usccLgov/pubs/saclpi.lOS02Ich5.htm. 

"~ Supra, note 59. Sec also supra. note 68. 

It' BEs reported tllm the)' must 

make an extra efJ(Jrt to prove their 

ability to prime contractors in 

order to win a subcontract award, 

el'en whenfidly qualifiedfi)r thejob. 

access to financial resources. Insufficient funding puts 

small businesses. including WBEs, at risk of defaulting 

on their bonds or other financial commitments, especially if there is delay in payment tor work completed. 77 

In 2004, the National Women's Business Council, 

a hi-partisan Federal advisory council, found that while 

the SBA has increased the number of total dollars 

loaned to women~owned firms at a faster rate than to 

other firms) the actual number ofloans and investments 

to women-owned businesses is not growing at the same 

pace. Between 1998 and 2003, the SBA increased the dollars loaned to and invested in womcn~owned businesses 

by 30 percent, compared to a 21 percent lncrease in dollars loaned to all small businesses. Over the same period, 

however, the number of loans and equity investments to 

women-owned small businesses grew hy only 41 percent, 

much lower than the 57 percent increase to all businesses. 

The cause for this disparity is unknown given that other 

studies have documented that women·owned firms do 

not differ significantly from the average American firm 

regarding bill payments, financial strength, and overall 

creditworthiness.74 

Capital created through homeownership is often necessary to start or expand a business. Barriers 

to homeownership and home equity growth for women 

can negatively affect their opportunities for business 

growth. Historical evidence of gender discrimination 

in lending practices is evident; for instance. the availahility of loans to WOmen was often reduced hecause 

of the perceived risk associated with being single or 

of childbearing agc.7'i These practices have since been 

"" Bonds guarantee thal '"a contractor will fully perform the 

contract and offcr protections against breach" US Commission 

on Civil Rights. Supra, note 68. 

".j N<ltional Women's Business Council. (2004, April). Trends 

In SBA-backed Financinf{ to Women~()\l'ned Businesses. 

rr!098~FY20()3. 

" Stcphanopou\os. O. & Edky, C (l995)'Aflirmaliyc action 

rt'view Report to the President. Washington D.C: U S. 

THHTON E, HENDERSON CENTER fOR SOCL~L JUSTICE 13 
155 

Literature Review 

outlawed. but barriers to home ownership and equity 

growth continue to exist for women of all racial groups. 

The Intersection between Race and Gender 

Women of color face unique challenges that often com~ 

pound the impact of discrimination based upon race, 

ethnicity, and gender. The legacy of slavery and other 

culturally destructive policies produced unique work 

histories, standards and expectations regarding the 

mandatory or necessary participation of women of 

color in the workforce. However, while women of color were expected to work. they were not encouraged to 

own, Still, despite significant social and economic barriers to building economic self-sufflciency, women of 

color often managed to own successful businesses that 

were in typically gendered fields, such as hair care, food! 

restaurants. laundry. and domestic or personal service. 

Because women of color. particularly African American 

women, were largely never accepted as "housewives," expectations regardjng their participation in manual labor 

varied greatly from their white counterpartsJ{i 

Like their male counterparts, many women of 

color have historically become entrepreneurs as a way 

to escape racism and discrimination. 77 This racism, 

inflicted by unions, employers, project managers, and 

others, has served as a constant reminder for women 

of color that they were often their own best advocates. 

It has been observed that "whatever the hierarchy of 

preferenee[,J ... black women could always be found at 

the bottom."78 

Still, many of the obstacles that have historically 

prevented women of color from entering and succeeding 

as entrepreneurs linger in the modern climate of opportunity. Indeed, women of color must not only overcome 

Government Printmg Office. Set also supra. note 61. 

-h Davis. A.Y. (1983). Hlomen. Race, and ClIlSS. New York. NY: 

Vintage Books. 

Lerner. G. (1972). Black ITiHnen in Whit,' America. New York. 

NY: Vintage Books. 

-~ Andersoll, K. (1982. Junc). "Last Hired. First fired: Black 

Women Workers. during World. War II: Jowna/ 0/ American 

llisfol'\'.69. 

A VISION FULFILLED? 

those barriers in place for women, but those that exist for 

people of color as well. Women of color face obstacles to 

business ownership such as lower rates of homeowner~ 

ship, or lower home values for those that do own homes) 

higher denial rates for business loans, and lower amounts 

of loans for those that receive them.79 For women of color, the odds of opening a business are much lower than 

those for their white counterparts. A study by the SBA 

shows that as women they are 62 percent as likely to 

open a business as men; as people of color) their chances 

of opening a business are only 55 percent as likely.so 

Unfortunately, the po,ition faced by women 

of color as unique from both men of color and white 

women in non-traditional industries is often difficult 

to study because of limited data. As i, currently the 

case with Caltrans, many agencies do not collect data 

for women of color separate from their male or white 

female counterparts. While women of color are often 

subject to experiences that are not comparable with 

those of men and white women, policies that affect either group have not responded to the unique barriers 

they face to full and equal participation. 

Impact of Proposition Z09 on Pathways to 

Entrepreneurship 

Prior to the passage of Proposition 209, many of 

California\; business enterprise programs increased 

MBE and WBE participation in public contacting and 

helped to mitigate the underutilization seen in that are~ 

na.81 However, the proposition appears to have halted 

and even reversed these gains. Most notably. Caltrans 

experienced a significant decline in the amount award-

~» Supra, note 61- See also supra. note 75. 

,0 The SBA does not provide 

from white women or men of color. 

group is ddlicult to ascertain. HCT Partners. LLC for the Small 

Business Administration. (2007, July), The E[(eCl (~r '1T'ea/th and 

RaeI.;' on Start-up Rares. 

~1 Dng. P .• cd. (1997).111(' Impact of Affirmative Action on PlIhiicSector Employment and Contracting in C(Jl~r()rnia. Berkeley, CA: 

California Policy Seminar. 9(3). !-7. 
156 

ed to MBEs, falling from 16 percent to 7.9 percent 82 

In California, the number of women employed in thc 

construction industry had initially increased by 26 

percent between 1990 and 1996; it declined by 33 percent after the passage of Proposition 209. The number 

of women in apprenticeship programs also declined 

after the proposition passed, further hindering their 

advancement in the field and their ability to secure 

more lucrative salarics.s3 

A 2007 Caltrans study found racial and gender 

disparity in subcontracts and prime contracts at the 

state and federal levels for WBEs. illustrating that after the removal of DBE goals on federal projects. the 

utilization ofWBEs dropped (0 "less than one-half of 

what would be anticipated from the relative availability of women~owned firms:'8J. 

There is a dearth of research on several issues 

important to understanding women business enterprises. affirmatiYe action) and other gender-conscious 

remedies to discrimination. Even more scarce is research that examines the unique intersection between 

race and gender, and that which can provide analyses 

of how women have been impacted by the removal of 

race- and gender-conscious equal opportunity programs. However, existing studies suggest that women 

have faced a spectrum of barriers related to access~ 

ing male-dominated networks, accessing credit and 

other forms of financial support, and overcoming 

gender discrimination in male-dominated industries. 

Literature on WBEs also reveals a trend of declining 

participation by WBEs when there is an absence of 

gender-conscious goals, strategies, and outreach programs in place to counter discrimination and enforce 

equal opportunity. _ 

R7. Discrimination Research Center. (2006, August). Free (0 

Compete?: MeasurinK [he lmpu("f of Proposition 209 (Ill Minority 

Business Enterprises 

~, Supru. note 48. 

M Supra, note 61. 

Methodology 

A multi-method approach was used (0 determine the 

impact of Proposition 209 on WIlEs." These included 

analyses of award data provided by Caltrans, the survival rate of certified 1996 WBEs, a statewide survey 

of surviving WBEs, focus groups, and in-depth interviews with surviving WBEs.S6 

Aggregate, quantitative data provided by 

Caltrans for women of color-owned WBEs, whiteowned WBEs. and to WBEs in total was collected and 

analyzed for each Fiscal Year (FY) from FYs 1985 

through 2006. These data included the total donars 

awarded to each group, as wel1 as relative amounts 

awarded for all Federal Highway Administration 

(FHWA) Cal trans awards. Data were provided by 

Caltrans through several summary sheets. These included the Quarterly/Annual 1405 Reports of DBE 

0' A WBE is a small business majority owned and controlled by 

one or more women. 

R(, Data o:ol1cction for the survival and survey sections was 

completed by the Discrimination Research Center. 

THELTON HENDERSON CENTER FOR SOCIAL JUSTICE 15 
157 

Methodology 

Awards and Commitments for FY 1985 through FY 

1998, the 1405 Quarterly/Annual Reports of DEE 

Awards and Commitments for FY 1999 through FY 

2002, and the Uniform Report of DBE Awards or 

Commitments and Payments for FY 2003 through 

FY 2006. 

The research team collected data for 2,096 

in-state women~owned businesses listed in the 1996 

volumes of California's Department of Tran.\]Jortation 

Disadvantaged Business (DR), State fVomen Business 

Enterprise (SWBE), and State A1inority Business 

Enterprise (SMBE) List. All women-owned, 1996 certified DBEs were included. In the initial search. which 

took place in winter 2006 through spring 2007, the researchers utilized a minimum of two internet phone 

book searches to locate current status information of 

all 2,096 ccrtWed WEEs. Any business that was likely 

to he still in husiness (i.e., finding a business with the 

same name and at the same location as in 1996) or 

possibly still in business (i.e .. a business listing with a 

similar name, location. andlor contact information) 

was contacted to verify its current status. Businesses 

were then labeled as definitely still in business, possibly still in business, or definitely out of business. 

For the survival rate analyses. businesses that were 

definitely or possibly still in business were considered 

as "in business." The survival rate for white-owned 

WBEs was compared to the rate for women of colorownedWBEsY 

The researchers surveyed all surviving 1996 

certified WBEs to ascertain their business experiences: 

both before and after 1996. WEEs were contacted in 

the spring of 2007 to complete an 89-item, 20 minute 

questionnaire. Surviving WBE owners and managers 

were queried regarding their experiences with the DBE 

program, pre-bidding conferences, good faith outreach efforts, their relationship with the state. and the 

state oftheir business before and after 1996. Statistical 

tests were performed to check for differences across 

time and between white-owned and women of color-

~" Differences in survival rate were analyzed using Chi-~quares. 

A VIS [ON FULFILLED? 

owned WBEs,1\8 Due to a limited sample size, tests 

could not be performed among ethnic subgroups (e.g., 

Hispanic/Latina American. Asian Pacific American, 

and African American). In an effort to bypass the 

limited statistical power of each individual question, 

the HCSJ researchers compared, for each of the items 

in the survey~ whether reported outcomes were better, 

worset or the same for women of color-owned WBEs 

relative to white-owned WBEs at each time point, 

before 1996 and after 1996. as well as for the relative 

change from before 1996 to after 1996." 

Focus groups and interviews were held with 

WBEs from a variety of regions in California, including San Diego, Los Angeles, Central Valley, the 

San Francisco Bay Area. and Sacramento. All parM 

ticipants were California-based companies owned 

by women that were certified as WBEs in 1996. All 

WBEs who participated in this qualitative examination voluntarily chose to participate in focus groups 

and interviews after completing the survey. _ 

,~ Response rates \\erc analyz(;'d using Chi~squarcs. For 

continuous variables. changes ovcr time from before 1996 

until after 1996 were ana!YLed using paired t-tests, Differences 

in changes over time by race/ethllicity were analyzed using 

independent samples t-tests on change scores from before 1996 

until after 1996. Differences <1t each time point by race/ethnicity 

were analyzed ,,,i,t. it,d,",,,d,,,t point. before 1996 and after 1996. 

differences over time were analyzed. using McNemar tests, 

differences at each time point were analyzed using Chi-squares, 

and differences over time by race/ethnicity were analyzed using 

logistic regressions 

g9 III total. 34 items were used ill this nna!ysis. For items in which 

a median and mean were both presented in this report, only 

the median was used. For items concerning revenue from prebidding conl~renecs and outreach efforts, only results for the 

entire sample were used. Significance testing was performed 

using the hinomia! distribution test on better versus worse 

lower difficulties, and greater revenue and contracts. 
158 

Results: WBE Award Access 

In California's transportation construction industry, 

contracts awarded to firms owned by women experienced a significant decline following the passage and 

implementation of Proposition 209. Table I and Figure 

I illustrate the dollars awarded for Caltrans transportation construction projects. in total from FY 1985 

through FY 2006, and to WBEs and non-WBEs from 

FY 1985 through FY 2002 for the FHWA contracts. 

Dollar values are inflation-adjusted 2006 real dollar 

amounts using the Consumer Price Index (Cpr) as the 

measure of inflation. The relative amount awarded to 

WBEs is calculated by dividing the amount awarded 

to WBEs by the total value of projects awarded in that 

fiscal year. 

In FY 2003, Caltrans switched to the federally 

mandated Uniform Report of DBE Commitments! 

Awards and Payments. Due to this change, Caltrans 

shifted to reporting only the federal portion of awards 

for projects with at least some federal funding, contributing to a reduction in the total reported level of 

awards as well as in the portion awarded to DBEs. 

Another change that occurred in the transition to the federally mandated Uniform Report in FY 

2003 was a change in the subcategories of ODEs for 

which award data were provided. Before the change to 

the Uniform Report, Caltrans had provided data separately for DBEs owned by men of color and \vomen 

of color. However, the Uniform Report format only 

provides pooled data for men of color and women of 

color together. Thus, since FY 2003, it has been impossible to identify the contracts awarded to DBEs 

owned hy women of color. However. awards to WBEs 

owned by white women remain a distinct available 

category in the Uniform Report, and these data are 

provided for all years. 

The transition to the Uniform Report in FY 

2003 resulted in the loss not only of the category of 

women of color-owned WBEs, but the categories of 

WBEs in total and non-WBEs. For the 1405 Quarterly! 

Annual Reports, used from FY 1985 through FY 2002, 

award data for WBEs in total was tallied by adding together awards for women of color-owned WBEs and 

white women-owned WBEs. However, due to the removal of the women of color category. it is impossible 

to determine the amount awarded to WBEs in total 

and nOD-WBEs from FY 2002 through FY 2006.90 

The total amount of money awarded by 

Caltrans to contractors has increased since FY 1985, 

though it has varied from year to year, in part due to 

variations in public projects for any particular year. 

In general, the value of awards to WBEs increased from FY 1985 through FY 1995, rising six-fold 

from FY 1985 to FY 1995. However, in FY 1996, there 

was a greater than two~thirds reduction in awards. 

The amount awarded to WBEs decreased further 

in FY 1997 and saw only modest increases over the 

next several years. The latter half of the 1990s saw an 

erasure of the gains made in WBE award access experienced in the earlier half of the 1990s. 

The latter ha(l<!l the 1990s saw 

an erasure of the gains made in 

WEE mFaI'd ([ecess experienced 

;'1 the earlier hall 0/ the 1990s. 

Award values to white-owned WBEs contribute to the vast majority of awards to WBEs, and thus 

trends for white-owned WBEs reflect the trends seen 

for WBEs in total. In the ten years between FY 1985 

and FY 1995. the amount of real dollars awarded to 

white~owned WBEs increased five~fold. However. that 

entire gain was nearly lost in FY 1996. Since then, increases have occurred, but have never approached the 

absolute level of funding seen in FY 1995, and in recent years have been hovering at FY 1985 levels. 

The pattern for women of color-owned WBEs 

is drastically different than the pattern seen for whiteowned WBEs. According to the 1405 reports, there 

were no awards to women of color~O\vned WBEs from 

9" A request to receive award data for WBEs owned by women of 

color or WBEs in total1ty was unable to be fulfilled by Caltrans, 

THELTON E, HENDERSON CENTER FOR SOCU\L JUSTICE 17 
159 

Results: WEE Award Access 

TABLE 1: Real dollars of Cal trans FHWA awards in total, to WBEs owned by white women, 

women of color, and in total, and to non~\VBEs, by Fiscal Yeart 

r.::-----" White-owned WnEs W'"ilfW'. Women of color-owned All Contracts 

WilEs 

FY Total dollar Percent lhtaldollar Percent Total dollar Total dollar Percent Total dollar 

awarded awarded awarded awarded aWdfdcd awarded awdTded Awmded 

FY85 SO 0% $25,327.252 2,1"% $25327252 $1 170.039.241 979% $U95.366.493 

FY86 SO OYo $33,789.583 2.4% $33789,581 $1.180.310441 97 6(~) SI,414.100.024 

FY87 SO 0(% 551.471.821 4.1% $51,471.82 1.2lO,909142 959% $1.262381.163 

FY 88 SO 0% $49.601,236 4.1% $49.601,236 4.1°;;, $1.146.204.028 95.9% 51.195.805,264 

FY89 SO 0% $61.655,194 3.6% $61,655.194 3.m);, SI,650,576'()96 96.4% $ 1.712.23 I ,290 

FY90 SO 0% 548.962.303 321% 548,962,303 3.2~,\, SI,474.627.305 96.8%, $1,523.589.608 

FY91 SO I 0% S83.313.833 4.9'>(\ $83.313.833 4.9\;1.) $ 1.605.904.171 95.P{) 51.689.218,004 

FY92 $10,322, III 0,7% $lOO.017N7 6.3% SII0.J39,159 7.0% 51.471.729.699 93.0% $l.582,068,858 

FY93 524.584,435 1.7% $99,715.020 I 7'()% $124.299.455 8,8% 51,290.404.803 91.2% SI.414.704.258 

FY94 512.101.563 0,9% S99.613.380 7.T~/o $111.714.942 8.6(;1., S 1.189.155,545 91.4i

X, SI.300,870,488 

FY95 $23.630.089 1.1% $ 138,616.833 6,6% 5162,246.922 7.7~1" 51,951.303.297 92.3%, 52.113,550.219 

FY 96 516.171,043 1.2% 532.935,677 2.4% $49.106.720 3S/1) 51.350.824.268 96.5% $1,399.930,988 

FY 97 58.007.271 O.TV" S32.703.547 2.9t

lr, $40,710.817 3,6% SI,094'()61.947 96.4"'" 51.134,772,765 

FY 98 510.708.143 1.0% $48.920.783 4.7% $59.628.925 5,8';;;' I $970.733,315 94.2%1 51.030.362.240 

FY 99 517,217,425 0.9(;':0 $33.212,481 l,go/" $50.429,906 2,8% I $1.769.197.016 97.2%, SI.819.626.922 

FYOO $16,282.528 1,0% $57.862.741 33% 574.145.269 4.4(\1,\ ' 51.595.039.032 95,6%, S1.669.184,301 

FYOI SI6.964.692 0.6% $62.213.882 2.3'% $79.178.574 2.9{% $2.606.849.521 97,1% $2,686.028,095 

FY02 534.497,654 1.01% 583.081,469 2.4% $117.579.122 3.4% 53358,320.878 96.6'% $3.475.900.000 

FY03t - - $19.422.942 2,0% ~~ 

- I $993.178.391 

FY04+ - .~ $43.959.425 2.50/,) I - $1,775.112,7JO 

FY05t ~ -, $24.060.275 1.4% - I 5989,338,574 

FY06t , "" $25.569,370 L3°!i) " -- I SI.986.840.436 

or Awards to women ()fco!or~owned WBEs and whilC-OWlH,:d WBES may not sum to WBEs in total, and WEEs. in total and non·WBBs may not sum 

to total contracts, due to roulldillg. 

t Tow! awards and awards. to white-o ..... ned WBES for these years include only the federal portion llfthese award", Data arc not available lor WBEs. 

in total, \~()me(l of color-owned WBE~, and non~\VBEs for these years 

18 A VISION FULF1LLED? 
160 

Figure 1: Real dollars of Caltraus FHWA awards to WBEs and non-WBEs, by Fiscal Year 

$.3 j 

SUi 

.~ $:! 5 

~ 

.5 

§ $20 

~ 

" $15 

~ ~ 

~ $1.0 i 

. SO.5 

1 $00 

FY FY FY FY FY FY FY J'Y FY FY FY I-Y FY FV FY FY FY FY FY FY FY FY 

85 86 88 89 90 91 92 93 94 95 96 97 98 99 00 OJ 02 o:<t 04t 051' OM 

owncdWBEs. 

FY 1985 through FY 1991. However, it is possible that 

awards to women of color-owned WBEs were commingled with DBEs owned by men of color or white 

women during this time period. In FY 1992. roughly 

10 million real dollars were awarded to women of colorowned WBEs, and the value has generally increased 

over time, up to a peak of34 million real dollars in FY 

2002, though reductions were seen in several years. 

The relative awards to white- and women of 

color-owned WBEs can be seen in Figure 2 and Table 

1. The first year of recorded data was produced in FY 

1985 and showed that the relative amount awarded to 

WBEs in total compared to non-WBEs was roughly 

two percent. On average, the relative proportion of 

awards to WBEs in total increased steadily until the 

mid-1990s, reaching a peak of nine percent in FY 

1993. After modest drops the next two years. the rate 

decreased nearly two-thirds in one year. to below 

four percent of awards, in FY 1996. The rate varied 

between three and six percent the next several years. 

Data are not available for WBEs in total in the years 

since FY 2002. In the six years that followed the pas-

'fHELTON E. HENDERSON CENTER FOR SOCIALJUSTfCE 19 
161 

Results: 'WEE Award Access 

sage of Proposition 209, awards to WEEs dropped 

significantly, to 3.8 percent relative to 6.7 percent 

of awards in the six years preceding the passage of 

Proposition 209. 

Because white women-owned WBEs constitute the vast majority of WEEs in total, the pattern 

of awards received by them mirrors the trend for 

WBEs in total. For white women-owned WBEs, relative award levels peak at nearly eight percent in FY 

1994, but then drop to just over two percent in FY 

1996. With the exception of two years (FYs 1998 and 

2(00). white-owned WEEs have never again received 

more than two and one-half percent of awards. Whiteowned WBEs hovered at or just above two percent for 

several years, until FY 2006, when awards to white 

owned-WBEs were just over one percent. In the ten 

years following the passage of Proposition 209, awards 

to white-owned WEEs significantly decreased by almost 50 percent, from 5.0 percent to 2.6 percent. 

Figure 2: The percentage of Caltrans FHWA awards to WBEs owned by white women, women of color, 

and in total, by Fiscal Year 

9% 

1 T:';, 

:;:; 6'% 

2 'c 5'/'0 

" .& 4% 

c 

8 3~1,) 

~ 

"""""""""""""""""""""" 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 00 01 02 03'1' 04'1' 05'1' 06t 

white-owned WBb; -----.--- WBEs in total 

t Only the federal portion of awurded projects is reported. Award datu arc not available for women of color-owned WBEs or WREs in total. 

20 A VISION FULrILLED? 
162 

The relative amount of awards received by 

women of color-owned WBEs was reported as zero 

percent from FY 1985 through FY 1991. This percentage rose to almost two percent of awards in FY 1993, 

but then dropped to roughly one percent of awards 

for FYs 1994 through 2002. Data are not available for 

FYs 2003 through 2006, but given the corresponding 

drop in awards to white-owned WBEs, it would seem 

unlikely that awards to women of color-owned WBEs 

increased during those years. In the six years following the passage of Proposition 209, awards to women 

of color-owned WBEs did not evidence any significant 

changes, with 0.9 percent of awards going to firms 

owned by women of color before and after the passage 

of Proposition 209. Awards to women of color-owned 

WBEs were modest before the passage of Proposition 

209 and remained low after Proposition 209. 

There are several limitations for these analyses, The non-uniform methods used to collect and 

categorize WEEs and non-WBEs over time makes 

comparisons by year less than ideal, as well as making it difficult to identify, with exact precision, the 

amount and number of contracts awarded to WBEs 

and non-WBEs. It is also impossible to report on the 

total amount and relative portion of awards that went 

to business owned by women that were not certified as 

WBEs. Additionally, the research team was not able to 

obtain rcports which summarized awards for WBEs 

and non-WBEs for state contracts. Since the implementation of Pcoposition 209, the DBE program only 

operates for contracts with at least some federalmoney. As previously mentioned, since Caltrans switched 

to the Uniform Reports in FY 2003, it no longer provides information separately for OBEs owned by men 

of color and women of color, making it impossible 

to report on recent trends to women of C010l--owned 

WBEs or WBEs in totaL a 

In the six years that followed the 

passage o{Proposition209, awards 

to WBEs dropped sign !ficQn tiy, to 

3.8 percent relative to 6.7 percent 

of awards in the six years preceding 

the passage o{ Proposition 209, 

'I'HE1TON HENDERSON CENTER FOR SOCIAL JUSTICE ?: 
163 

Results: WBE Survival 

In 1996, there were 2,096 flnns certified as Women 

Business Enterprises, Of the 2,096 WBEs certified 

with Caltrans in 1996, 1,599, or 76 percent, were white 

owned. The remaining 497, or 24 percent, were owned 

by women of color. Today, the breakdown of surviving 

1996 firms is similar to eleven years ago, with 79 percent owned by white women and 21 percent owned by 

women of COIOf. Table 2 provides the 11 year survival 

of certified women-owned DBEs from 1996. 

The average survival rate for WBEs in total 

over the 11 year period from 1996 to 2007 was 36 percent, with 763 out orthe 2,096 WBEs identified as being 

definitely or possibly in business. For white-owned 

WBEs, 38 percent or 602 out of 1599 businesses survived. This was significantly higher than the survival 

rate for \\I<omen of color-owned WBEs. for whom only 

161 out of 497 businesses had definitely or possibly 

survived. The resulting survival rate was 32 percent. 

African American-owned WBEs evidenced 

the lowest survival rate (27(;/{)), significantly lower than 

both white- (38%)) and Asian Pacific American-owned 

(391%) WBEs. There were no other significant differ~ 

enees in the survival rate between any of the other 

racial/ethnic groups. 

With an II-year survival rate of less than 40 

percent for all races and cthnicities, the difficulties for 

women-owned businesses to compete in the transportation construction industry arc apparent. However. 

without an appropriate comparison group) such as 

the survival of small businesses primarily owned by 

white men, it is difficult to ascertain the relative sue~ 

cess ofWBEs and the impact of Proposition 209 upon 

them. 

One reason for the lower survival rate of businesses owned by women of color relative to those 

owned by white women may be the double jeopardy 

Table 2: Total WBEs certified in 1996 and in business in 2007, and racial and ethnic breakdown of 1996 

and 2007 surviving businessest;-+ _________ .,-________ --,-________ ----, 

Number of certiiled Number of WREs definitely WBE survival rate 

WBEsin 1996 or possibly 31i11 in business 

! percentage oj total) (peln.'n1age of total) 

Total sample 2.096 (100%) 76:1 (loorvo) 36% 

White women 1.599 (76%) 602 (79{~/"») 38"i;) 

Women of eolor 497 (24%) 161 (21':".) 320;(1 

Hispanic/Latina American 149 (]I~!(.) 49 (6'::,) 3YY(. 

Asian Pacific American 143 (?!.{,) 56 (7%) 39% 

African American t50 (7%) 41 (5%) 27% 

Native American§ 27(1%)) 8(1%) 3cr% 

Asian Indian American§ 28(1%) 7(1%) 2Yh, 

,Youree. CalijiJrnili Women Business Entapflse Surrey, Tll('!({lfl E. Ih'nderson Center jor Social iusti(c, 20(J? 

t Percentage~ may not add up to 100 percent because of f(lunding 

13 PortugUCSt' Amcrlcan- and ~ Spanish American-owned \VREs certified in 1996 were not investigated. and arc 

§ Due (0 the low number of Native Ame.r"ICiln- and Asi<)n Indian Anwrican-owned bu~ll1et>Se$. caution should be med when interpreting thes.e results, 

which v, i!l not be discussed in (he main body of {hi~ report 

22 A VISION FULrILLED? 
164 

women of color face as being both "non~white" and 

"non-male;' in an industry that is still dominated by 

white men. \Vhile white women-owned businesses 

may face difficulties based on their gender, women of 

color-owned businesses may face obstacles pertaining 

to both their race and gender. 

However, this double jeopardy for women of 

color is often overlooked. Women of color are often 

treated. both historically and currently, as either being a woman or person of color, but not both, This 

includes current requirements by the US Department 

of Transportation which only counts women of colorowned DBEs as "non-white." but makes no further 

distinction between men and women of color. 

WBEs owned by Asian Pacific American women had the highest survival rate, which wassignificantly 

higher than the rate for African American~owned 

WBEs and non-significantly surpassed the survival 

rate for white-owned WBEs. Across the nation, the 

number of firms owned by Asian Pacific American 

women increased by 80 percent, suggesting a network 

nationwide to support entrepreneurship,')! 

Businesses owned by African American women had the lowest survival rate. significantly lower 

than both Asian Pacific American- and white-owned 

businesses, highlighting the difficulties for African 

American women to succeed in the transportation 

construction industry. Across the nation. there are an 

estimated 849.430 firms owned by African American 

women, generating more than $36 billion in sales annually, and employing 2R7,913 people,"' Still, more 

research is needed to understand potential barriers 10 business survival for firms owned by African 

American women in the transportation construction 

industry .• 

01 Center for Women's Business Research. (2006). Businesses 

Owned by Asian Ameriatn Women in the [,'nired Stales, Fact 

Sheet. 

'Ie Center for Women's Business Research. (2006). Businesses 

Owned by All-imn American Women in the ['lIited ,r.;fules 

Businesses owned hy Aft'ican 

American women had the 100vest 

survival rate, Significantly 10lVer than 

hoth Asian Pacific American- and 

white-owned businesses, highlighting 

the difficultiesfCir African American 

lVomen to succeed in the transportation 

construction industn', 

TBELTON E. HENDERSON CENTER FOR sacrAL JUSTICE 
165 

Results: Survey 

Surviving 1996 certified WIlE, paint a mixed picture 

for the DBE program and the current environment 

of the transportation construction business. The 763 

firms identified a, 1996 certified WIlEs confirmed as 

surviving or possibly surviving businesses were contacted and asked to complete a questionnaire (see 

Table 3). Of the 763 attempts. 105 WIlEs completed 

the questionnaire, resulting in a response rate of 14 

percent. This response rate, 14 percent. was identical 

for white-owned WBEs and women of color-owned 

WBEs, resulting in 83 completions with white-owned 

WIlE, and 22 completions with women of color-owned 

WBEs. As there were only six to seven completions 

with Hispanic/Latina American-owned, Asian Pacific 

American~owned. and African American-owned 

WBEs and one completion each for NatIve Americanowned and Asian Indian-owned WBEs, survey results 

were not broken down by a specific race or ethnicity. 

though comparisons were made between WBEs owned 

by white women and those by women of color. As the 

vast m<:\jority of WBEs were owned by white women, 

results for white-owned businesses have a considerable 

effect on the pattern of results for WIlE> in generaL 

Table 3: (\;umber of completed surveys and response rate, in total and by race/ethnicity 

Total sample 

White 

Women of color 

Hispanic/Latina Amcrican§ 

Asian Pacific American§ 

African American§ 

Native American§ 

Asian Indian American§ 

Number of WBEs definitely 

r p~ssibly.still in business 

I p"nlntogl' 0/ /owl) 

763 (100%) 

602(79%) 

161 (21%) 

56(7%) 

41 (5%) 

8(1%) 

7(1%) 

businesses, cautioo should be used when interpret in!! thes<~ results 

Lending Programs, Mentorship Opportunities 

and Technical Assistance 

The use of lending programs, mentorship opportunities and technical assistance by WBEs was modest (see 

Tilble 4). At no point did a quarter of the WIlEs surveyed use any of these three programs. White-owned 

and women of color-owned \VBEs reported similar 

usage of the programs, and there were no changes 

after 1996 relative to before 1996. or these program" 

technical assistance programs were used the most and 

lending programs were used the least. 

24 A VISION rULrnLED0 

Response rate I 

105 (100%) 14% 

83 (79%) 14% 

22 (2bu) 

7(7%) 14% 

6(6%) 

1(1%) 13% 

1(1%) 14'% 

Indian Ame'rican-owllcd 

Pre-bidding Conferences 

Pre-bidding conferences are meetings during which 

projects are openly discussed and requirements are 

reviewed for potential bidders. Most WIlEs utilized 

pre-bidding conferences, with more than half of 

WBEs making use of pre-bidding conferences before 

and after 1996 (see Table 5). The percentage of WIlEs 

attending pre-bidding conferences showed a trend toward increasing. with 59 percent attending before 1996 

and 69 percent attending after 1996. This increase was 

significant for white~owned, but not women of color-
166 

,"'oura: Cal((omia Women Business ElIl£'l"prisc Survey. Thdton E, Henderson Center/or Socia! Justice, 2007. 

owned WBEs. WBE owners received significantly 

fewer invitations to attend pre-bidding conferences 

after 1996 (reduced from 28 to 11 conferences), invitations were sent with significantly less advance notice 

(reduced from 3.9 to 3.1 on a I to 5 scale with 5 being 

more timely), and significantly fewer conferences were 

attended after 1996 (seven conferences before 1996 and 

three conferences after 1996). WBE contractors also 

said pre-bidding conferences were signiikantly less 

helpful after 1996 relative to before 1996 (down from 

2.6 to 1.7 on a I to 5 scale, with 5 being more helpful). 

Women of color-owned WBEs reported that pre-bidding conferences were significantly less helpful after 

1996 than white-owned WBEs. The percentage of revenue that was derived from contracts in which WBEs 

attended conferences was 17 percent before 1996 and 

11 percent after 1996 for those who attended conferences, though this was not a significant decline. 

WBE contractors reported that invitations 

to pre-bidding conferences were most commonly received by traditional mail, both before and after 1996 

(see Table 6). About 50 percent of WBE contractors 

reported receiving invitations by fax and roughly 25 

percent reported receiving invitations by phone both 

SO/ire(': Cul{fo/'IJirl 1VoIIJ('l! Business Hntr:rprise Surrey. The/ton E. }fendcrSOll Ccnter/or Sodal JUS/ICC, :!O()7. 

THELTON E. HENDERSON CENTER FOR SOCIAL JUSTICE 25 
167 

Results: Survey 

Source. California i-f!i:mlol Business Enterprise Suney. Thelton E, lIendcrs(I!l ('{'Illapn Social Jusli<"c, 2007. 

before and after 1996. Invitations by email, virtually unused before 1996, became nearly as popular as 

traditional mail after 1996, rising from two percent 

before 1996 to 57 percent after 1996. 

Outreach Efforts 

Prime contractors arc required to make a best etTOft 

- in "good faith" - to include DBEs in public projects, 

Good faith efforts can be made by sending notices by 

fax or email. or by making a phone call or in-person 

visit to inquire ahout the interest and availability of a 

DBE to participate in public projects. On average. 74 

Table 7: Prime contractor outreach efforts 

percent of WBEs were contacted via good faith outreach efforts by prime contractors before 1996 and 72 

percent were contacted after 1996 (see Table 7). For 

women of color-owned WBEs, 81 percent reported 

that they were contacted by prime contractors before 

1996 but only 62 percent were contacted after 1996, 

while white women-owned W BEs reported 73 and 75 

percent involvement before and after 1996, respective~ 

ly. The percentage of revenue that resulted from good 

faith outreach efforts was reduced significantly over 

time for WBEs. Although the number of times WBE 

contractors were contacted did not decrease. the good 

Source. C'aii/ol'flia W{I/llt'fl Busitu'.I'S Emerpn.\e Suney, Thcftoll E. lIender.\'ol1 ('Cllfer for Social JUS/lte, 2007, 

26 A VISION FULFILLED? 
168 

Table 8: Methods used to contact WEEs by prime contractors for outreach eUorts 

By mail By phone Bycmail By fax 

Pre-96 Post-96 Pre-96 Post-96 Prc-96 Post-96 Pre-96 Post-96 

I Total sample 47(Y~ 39{X) 65i

j'() 61% 11(% 39'J'o 53°;" 65% 

I White women 43')'0 35i

:«1 70';;, 650/0 9%, 3fiYo 52% 63%, 

I Women of color 64% 5Y;;) 4YYo 451

% 18%) 45(;;(1 5YY() 73% 

Source.' Call'fiJrnia fVomen Business E1IIctpri.1t' Su/'\'cy, The/IOn E. H('l1der,wm Center [or Sodal 1[1,1[1('('. 2(107. 

faith outreach efforts were seen as significantly less 

helpful, dropping from 2.4 to 1,9 on a I to 5 scale, with 

5 being more helpful. 

WBE contractors reported that the timeliness 

of good faith outreach efforts did not change after 

1996. On average, WBEs felt that the amount of lead 

time (3.3 and 3.1 before and after 1996, respeetively, 

on a 1 to 5 scale in which 5 is mOre timely) was not 

long enough, even if they usually made the necessary 

deadlines. WBE contractors also reported that prime 

contractors mentioned trying to fill their quota more 

than half the time, both before and after 1996. This 

percentage was significantly reduced. from 64 percent 

to 52 percent, after 1996, most likely reflecting the reduced importance ofDBE goals. 

As seen in Table 8, the telephone and fax were 

the most popular methods for reaching WBEs for good 

faith outreach efforts. In 1996, the telephone was the 

most popular method. However. a significant increase 

in the use of fax machines after 1996 elevated it to 

the same popularity as the telephone, Email was used 

only 11 percent of the time in 1996. but a significant 

increase after 1996 resulted in a tie with traditional 

mail, at 39 percent. 

Table 9: DBE program helpfulness - How helpful was the DBE program to: 

! Total sample 

I White women 

I Women of color 

Subcontract with I Develop n:lati~mships Join or expand 

prime contractors?' with supphers? networks that made 

it easier for flrm to 

rL"Ceive contracts? 

Pre-96 Post-96 Prc-96 Postw96 Pre-96 Post-96 

2.5 1.9 1.8 1.6 1.4 1.7 

2.5 2.0 U 1.7 1.4 1.7 

2.6 1.7 18 1.4 2.5 1.8 

Qualify for loan More easily secure 

program? bonding? 

1.4 1.6 1.3 1.3 

1.4 1.6 1.3 1.2 

1.4 1.5 1.4 1.4 

Develop a more Expand the scope of 

extensive track services provided? 

record? 

Pre-96 Post-96 Pre-96 Post-96 

2.5 1.9 2.2 I.R 

2.6 1.9 2.1 1.7 

2.4 1.9 2.6 2.0 

The/ton E. HenderSOI! Cen/a jor 5·or ial Juslice, 2007. On II s( (iii' (~f 1 10 5. ,,,"herc I is 'nota/uti 

THELTON E. HENDERSON CENTER FOR SOCIAL JUSTiCE 27 
169 

Results: Survey 

Qualifications 

orcligibility 

requirements 

needed to bid? 

Number of hours Amount of lead timel Getting the 

~ecdcd to prepare a given to respond information required 

bId or proposal for a to a request for I or questions 

Costs involved in I 

submitting the 

required documents 

to be certified a~ 

aWBE'? 

publk l:ontract? proposals? answered prior to 

Pre-96 P05t-96 Pre-96 Post-96 

I Total sample 2.8 2.9 3.3 3.3 

I \\Ibite women 2.8 2.8 3.2 3.2 

I Women of color 2.7 3.t 3.5 3.5 

DBE Program Helpfulness 

WBE contractors were asked eight questions about 

the helpfulness of the DBE program before and after 

1996 (see Table 9). None of the eight items were seen 

as very helpful. as the scores ranged from L3 to 2.5 

on a I to 5 scale, with 5 being more helpful. Of the 

eight aspects, those that were seen as the most helpful before 1996 were helping with subcontracting with 

prime contractors, developing a more extensive track 

record, joining or expanding the networks that made it 

easier for their firm to receive contracts. and expand~ 

ing the scope of services provided. All four of these 

aspects were seen as less helpful after 1996 for WBEs 

in total, with white-owned WBEs reporting a signiHcant reduction for the first three aspects and women of 

color-owned WBEs reporting a significant reduction 

for the first two aspects. 

Data reduction techniques<)~ indicated that 

two scales could be constructed based on these eight 

items. The first was an overall helpfulness scale, containing all eight of the items, and the second was a 

fiduciary scale, consisting of the items relating to obtaining credit, loans, and bonding. As seen \;ith the 

factor 

that plltlcd positively from all eight aspects. and a second t~H'tor 

which pulled positively from the three fiduciary !tt;ms. 

A VISION FULFILLED? 

I the bid due date? 

Prc-96 Post-96 Pre-96 Post~96 Prc-96 Post-96 

2.6 2.7 2.9 2.8 J.t 3.0 

2.6 2.7 2.9 2.8 3.1 3.0 

2.6 2.6 2.8 2.9 2.8 2.8 

individual items. the overall DBE helpfalness scale 

indicated that the program was not seen as very helpful by WBEs in 1996. registering only 2.1 on a I to 5 

scale, with 5 being more helpfuL The helpfulness was 

significantly reduced to 1.8 after 1996. The reduction 

was significant for white women-owned WBEs as well. 

Although women of color-owned WBEs registered 

an even larger drop than white women-owned WBEs, 

this drop did not reach significance due to the smaller 

sample size. 

Results from the fiduciarv scale indicate that 

this aspect of the program was s~en as the least helpful aspect of the program, registering only a 1.5 (on 

a I to 5 scale) before 1996 and a 1.6 after 1996. This 

difference was not significant, and there were no differences between white- and women of color-owned 

WilEs. 

Challenges to Working with the State 

On average. WBE contractors found warkinl)' with 

the state moderately challenging, with no diffe~ences before or after 1996 (see Table 10). Scores varied between 2.6 and 3.3 (on a onc to five scale, with five being 

the most difficult). The most challenging aspect was 

reported as the number of hours needed to prepare a 

bid or proposal for a public contract, while the least 
170 

Table II: Percentage of time spent in different aspect of position§ 

Administrative Trade Craft Other skilled labor Other non-skilled 

labor 

I Total Sample smll) 15% 6% 16% 3% 

I White Women 53~;, 161

;.1, 6iX, l6% 2'1<) 

! Women of color 66% 11% 7%\ 13\/(1 3(% 

Source, California lVomen Business Enterprise Survey. Thefton E_ Ifendf!fwrl Cen/erjol' SocialltlSlhe, 2007. 

§ May not add to 100 percent due to rounding and due to contractors not rcaching a total of 100 percent 

challenging aspect was the amount of lead time given 

to respond to a request for proposals. 

State of the Women~owned Business Enterprise 

Since 1996. certified WBEs have maintained modest 

success. Surveyed businesses had been in business for 

an average of 22 years and most female contractors 

had managed their business for nearly the entire tIme, 

On average, WBE contractors surveyed owned roughly 

85 percent of their business. Over 60 percent of WBE 

owners surveyed owned 100 percent of the business. 

Just under 20 percent of those surveyed owned either 

50 or 51 percent of their business. with the majority of 

these businesses being co-owned with spouses and/or 

family. At the present time. WBE contractors spent 

more than half of their time with administrative concerns (see Table II). 

There was no growth in the number of employees. with a mean of five employees before 1996 

and four after 1996 and a median of nine employees at 

both time points (see Table 12). There was no significant change in the number of contracts, with a mean 

of 133 before 1996 and 91 after 1996. while the median 

held steady at 12 contracts. 

Surviving WBEs did see growth in total revenue; with revenue increasing from $1.2 million before 

1996 to $1.8 million after 1996 (see Table 13). [ncreases 

were significant [or both white women-owned and 

women of color-owned WBEs, though white-owned 

WBEs had significantly higher revenue than women 

of color-owned WBEs both before and after 1996. 

Median revenue increased more modestly, from 

$468.000 to $550,000. 

The growth seen by WBEs does not appear to 

have been a result of working with Caltrans (see Table 

14). The percentage of revenue coming from Caltrans 

dropped from nine percent before 1996 to four percent 

after 1996. a pattern of reduction that was significant 

for white-owned WBEs. The percentage of contracts 

coming from Caltrans and the nu mber of contracts 

from Caltrans prime contractors evidenced a similar 

pattern of reduction but were not significant. 

Table 12: Number of employees and contracts _______ -, ________ ,-_______ -, 

Im,dian/ 

Number of employees Number of total contracts Number of total contracts 

'mean, (meduUlI (meun! 

Pre·96 Post-96 Prc-96 Post-96 Pre-96 Post-96 Pre--96 Post-96 

! Total sample 4 12 12 133 91 

\ White women 10 12 12 165 107 

! Women of color ) 14 10 27 37 

,)'(JUf( e. Cal{fi)miu Women Business Enterprise Surrey, The/Ion E. Henderson Cenler (or Soria! JuSlice, 2(107, 

THtLTON E. HENDERSON CENTER FOR SOCIAL JUSTICE 2,9 
171 

Results: Survey 

Table 13: WBE total revenue r--------------------------,-------------------------, 

Source, Caltfornia W(I!l/cn Business Enterprise "",'urn'v, Thellofl l\. Henderson Crlllerji!r Sutial Justice, 2007 

Trends indicated that a large number of 1996 

certified WBEs had little contact with Caltrans, before and after 1996_ Over 60 percent of WBEs in total, 

white owned WBEs, and women of color owned WBEs 

surveyed indicated that zero percent of their contracts 

came from Caitrans, zero percent of their revenue 

came from Caltrans. or that none of their contracts 

came from Caltrans prime contractors, both before 

and after 1996_ 

However, despite the fact that more than twothirds ofWBEs received no revenue or contracts from 

Caltrans_ it appears that some WBEs were able to 

begin working with Caltrans in at least some form. 

The proportion of WBEs that received none of their 

revenue from Caltrans was significantly reduced from 

81 percent before 1996 to 70 percent after 1996_ The 

proportion of WBEs that received no contracts from 

Caltrans prime contractors was significantly reduced 

from 80 percent before 1996 to 67 percent after 1996. 

A similar trend was seen for the proportion ofWBEs 

that received zero percent of their revenue from 

Caltrans sources, which was 79 percent before 1996 

Source. Caifjormtl WomClI Business Enterprise ~\'lIrr('l', Theftotl r:. fhndersofl CCl1lcr/(J}' Soda/ Justice, lOr)? 

30 A VISION FULFILLED? 
172 

Table 15: Number of services ,-----~-----------------------------------------, 

Source: Ca!J/ornia IF omen Business Enterprise Survey, Thellon E, Ilenderson Center jot' Social Justice. 2007. 

§ May not add to 100 pcrc~nt due to rounding 

and 70 percent after 1996. Still. the improvement seen 

by surviving WBEs in their ability to secure at least 

{)ne contract or similar source of revenue via Caltrans 

is restrained by the fact that the vast majority ofWBEs 

did not secure any business from Caltrans despite being certified with Caltrans. 

The vast majority of WBEs offered the same 

number of services (46 percent) or more services (41 

percent) than they did in 1996 (see Table 15). Around 

one in ten were offering fewer services. There were 

no differences between white owned- and women of 

color-owned WBEs. 

Hiring Trends and Outcomes anlong Women of 

Color-owned and White-owned WBEs 

There was no overall change in the demographic make~ 

up of WBEs in terms of the percentage of employees 

that were people of color or women after 1996 (see 

Table 16). Women of color-owned WBEs hired significantly more people of color, both before and after 

1996. More than half of the employees of women of 

color-owned WBEs were people of color before and 

after 1996, while less than 20 percent of employees of 

white-o\\'11ed WBEs were people of color. Furthermore} 

women of color-owned WBEs hired slgnillcantly more 

women than white owned-WBEs after 1996, though 

more than half of the employees of both white-owned 

and women of color-owned WBEs were women before 

and after 1996. 

In this section, several differences are noted 

between responses given by WBEs owned by women 

of color and those owned by white women. However, 

many differences were not statistically significant. in 

part due to limited power. making it difficult to report on the overall trends for these two groups of 

WBEs. Thus, HCSJ examined the overall pattern of 

results for the items in the survey in aggregate. Before 

1996, women of color-owned WBEs appeared evenly 

matched relative to white-owned WBEs, reporting 

hetter outcomes than white-owned WBEs on 50 percent of the items and a worse outcome on 41 percent of 

the items. However, after 1996, women of eo I or-owned 

WBEs reported better results on only 24 percent ofthe 

items and worse on 65 percent of the items, a statistically significant difference. The relative change from 

before 1996 to after 1996 shows a similar pattern, with 

women of color-owned WBEs reporting significantly 

more negative outcomes (68 percent) than positive 

outcomes (24 percent). Thus. there is a clear pattern 

that women of color-owned business were more impacted in the post~Proposition 209 environment than 

white-owned business among surviving 1996 certified 

WBEs. 

In summary, WBEs were likely to have maintained or increased the num ber of services provided 

and showed growth in total revenue. However. there 

was no growth in the number of employees or the 

number of contracts from Caltrans. Most surviving 

1996 certified WBEs have never worked with Caltrans 

THELTON E HENDERSON CENTER FOR SOCIAl.,jUSTICE 
173 

Results: Survey 

Source: California fVomell Busim-'ss EllIerpl'ise SUrI'cy. Thelton. E. HcnderSOIl Cen/er.!l)r Social JWlice, :lOf}? 

in any capacity, both before and after 1996, though 

there was a modest improvement post-Proposition 

209 in the ability for surviving WOEs to secure at least 

some work through Caltrans. 

On the whole, WBE contractors did not find 

the DBE program to be particularly e!l'ective. either 

before or after the passage of Proposition 209. WBE 

contractors reported that the DBE program became 

even less helpful after the passage of Proposition 

209, In particular, items related to networking and 

expanding the scope of their business saw the largest drop. Although WBEs did not see a reduction in 

being contacted at least occasionally after 1996, good 

faith efforts and pre-bidding conferences show a pattern of reduced helpfulness and usefulness after 1996. 

There arc several limitations that constrain 

these findings. This includes common limitations 

which are associated with using recalled. self-reported data derived in part from over eleven years ago. 

For some analyses, the sample sizes offered limited 

statistical power to determine whether apparent differences were statistically significant or due to random 

chance. The limited sample size also does not allow 

for analyses by geographic area, years in business, 

relative success of the WBE or other factors that may 

influence responses. The small number or women of 

color~owned WBEs surveyed requires caution to bc 

uscd in the interpretation of results for this group 

and also results in an inability to analyze results for 

racial and ethnic subgroups. As only surviving certi~ 

A VISION FULFiLLED? 

fled WBE businesses were sampled, the results may 

not indicate the pattern of results that would occur for 

non-WBEs, WBEs that did not survive, or for womenowned business that chose not to certify. Some of the 

reduced contact with the DBE program, effectiveness 

of the DBE program, and importance of the DBE program may reflect the natural growth of WBEs rather 

than the reduced effectiveness of the DBE program 

after 1996. Finally, many of those surveyed were unable to answer some or all ofthe questions pertaining 

to the helpfulness of the DBE program or relationship 

with the state because they did not use the program or 

interact with the state and with the bidding process, 

largely because many of those surveyed indicated 

they primarily or completely do not bid for public 

contracts. 
174 

Results: WBE Focus Groups and Interviews 

The goal of the focus groups and in-depth interviews 

was to provide an opportunity for owners of surviving WBEs to discuss the impact of Proposition 209 

on public contracting in California's transportation 

construction industry, and on their businesses in partkular. To measure this impact, questions were posed 

in the following areas: 

• The culture of the transportation construction 

industry: What aspects of the transportation 

construction industry culture potentially affect 

women ditTerently than men'! What aspects of the 

transportation construction industry may not be 

directly related to gender but could have an impact on women in public contracting? 

• The business challenges for WBEs: What are the 

main challenges for WBEs when establishing and 

developing a business as a professional, supplier, 

or trades person in the transportation construction industry? 

• The federal DBE Program: What were the benefits 

and challenges associated with California's implementation of the federal DBE program? 

• The impact of Proposition 209: What was the impact of Proposition 2091 Were there any collateral 

effects? 

• WBE survival strategies: W11at have been the primary strategies used by women to sustain their 

businesses in the transportation construction industry? How were these strategies impacted by 

Proposition 209" 

Culture oflhe Transportation 

Construction Industry 

Participants agreed that the bureaucracy of public 

agencies often challenges the ability of WBEs to be 

competitive in the transportation construction industry, Slow payments. the lack of en for cement with regard 

to good faith efforts so as to minimize fraud, breach 

of contract, important omissions from instructions, 

and incomplete explanations of guidelines related to 

projects were examples provided by participants to illustrate the manner in which the success of WBEs is 

undermined in the transportation construction industry. Participants agreed that it remains a significant 

challenge for women to access what is perceived as 

a "good old boy" network that rewards personal relationships, Participants agreed that the process offiling 

a grievance or discrimination complaints is also challenging) which many participants interpreted as a lack 

of Willingness among the agency to correct the institutional biases that are often sustained through existing 

networks between prime contractors and agency project managers. 

Many of these agency challenges were perceived as exacerbated by the historical and current 

challenges faced by women in the transportation 

construction industry. While women tend to be more 

accepted as professionals or administrators, women 

who own companies in heavy construction still face 

a fair amount of overt discrimination. Participants 

agreed that women in the transportation construction 

industry are constantly challenged to demonstrate 

their knowledge and endure the humiliation of being 

randomly quizzed on industry standards by men who 

questioned their command of their work. 1n certain 

professions, such as architecture, there may be other 

factors that steer women away from tbe industry~including long hours. lack of substantial networks to 

obtain projects, and an underrepresentation of women in upper-level decision-making positions in firms. 

However. women who own companies and compete 

for public contracts in heavy construction and the 

trades often face a tremendous amount of physical 

and emotional intimidation, exhibited through the 

usc of demeaning language, physical threats, dismissive behavior, and other actions that show a disrespect 

for women in the industry. 

THELTON HENDERSON CENTER fOR SOCIAL JUSTfCE 33 
175 

Results: WBE Focus Groups and Interviews 

"Once, a prime contractor didn't want to pay us 

for work that we'd completed, When I visited him 

to tell him thai we were going lofile a lien aga ins{ 

Ihem, he lirerallyjumped ill myface, with his cigar hanging fi'om his mouth, and was yelling at 

me, He was yelling, 'Who do you think you are' 

I'm not going to have no little girlfiling paperwork 

agaillst me!' I was shocked, of course, hut I had to 

just laugh it off I've been in this llUsiness for over 

25 years I " ~ WBE owner 

Participants agreed that Caltrans and other 

contracting agencies should improve their policies to 

ensure a more equit<lble distribution of contracts and 

to ensure fairness in the bidding and awarding process. 

Whi1e some women described experiences in which 

they were the low bidder and were forced to "fight" 

(i,e" file a formal complaint, make a public complaint, 

challenge the legitimacy of awards, etc.) in order to 

maintain the integrity of a fair public contracting 

process, others reported never having experienced 

collusion, bid-rigging, or other unethical processes. 

Business Challenges forWBEs 

Participants agreed that women face a series of unique 

challenges when establishing and developing their 

business in the transportation construction industry. 

While WBEs arc fully capable of working on a number of projects, many described being hindered by 

bonding requirements that arc prescribed accorJing 

to the assets of the company, Participants agreed that 

bonding and access to financial support from lending 

institutions are difficult for WBEs, particularly those 

that are also small businesses. 

"We're fully capable of'responding to large projects, but we always have bonding problems, We 

can't get more than $10 million in bonding because 

of the assets of our company, If you're a small 

husiness. I1mv can you compete with a multi-millionaire?'" They always say, 'we'li help you with 

bonding and business loans,' Well, I've been in 

34 A ViSION 

busineSS/Of 20 years and rl'e never heen ahle to 

get help in this area," ~ WBE OH'ner 

The suggestion that women are covers for 

l11ale~owned business haunts many WBEs. While 

participants were spIlt on the degree to which women 

served as covers for male-owned businesses, all agreed 

that it is not unreasonable for contracting agencies to 

explore the validity of women-owned businesses. The 

consensus among all participants was that the over· 

whelming majority ofWBEs are legitimate businesses 

and that those which are not hinder the ability of 

some WBEs to be taken seriously. 

The Federal Disadvantaged Business 

Enterprise (DBE) Program 

Participants cited obtaining economic upward mobili· 

ty as the primary reason for certifying as a WBE under 

the Disadvantaged Business Enterprise (DBE) pro, 

gram. The overwhelming reason women participated 

as WBEs in the DBE program was to increase their 

access to public projects. and thereby increase their 

income. Participants varied in their responses regard~ 

ing the usefulness of the DBE program, While some 

acknowledged that they were able to develop networks 

and access contracts through the DBE program, others expressed a great deal of dissatisfaction with the 

program. 

"[ dOll't even get calls from higfirms any more, I gel 

notices about johs that are cmnpletely unrelated to 

what I do-it makes me crazyI'" J,VBE OHmer 

Participants agreed that statewide, the DBE 

program---and in particular, its implementation 

of goals and good faith efforts to include WBEs on 

public projects~"·-was problematic on many levels. 

Participants expressed a great deal of dissatisfaction 

with the good faith effort. claiming that because the 

initiative has no strong enforcement, there are many 

opportunities forthis effort to fail. Participants agreed 

that while they receive requests for bids or propos-
176 

als, they are often unrelated to their company's focus. 

Participants considered it a common occurrence for 

WBEs to be contacted for projects within unrealistic 

timeframes, and for WBEs to spend time and money 

preparing bids for projects on which primc contractors never intended to use their services. Without 

enforcement, WBEs described good faith efforts as a 

"waste of time" and a strategy used by many prime 

contractors to appear as if they werc fulfilling a requirement without any intention of actual1y working 

with them. Many participants interpreted the general 

lack of confidence in the WBE program and its core 

good faith effort as a function of the ongoing overt 

and covert sexism they experience in the transportation construction industry in general. 

The Impact of Proposition 209 

Participants agreed that when Proposition 209 eliminated affirmative action in public contracting, thcre 

was a shift in the way that project managers and prime 

contractors engaged them. While some participants 

described little change because they had never been 

able to access Caltrans' public contracts, most participants described marked declines in contracts and 

contract amounts following the elimination of raceand gender-conscious equal opportunity programs. 

"When Proposition 209 passed, I was working 

on $200,000 worth of'projects. The day afier 

Proposition 209 passed. the senior proiect manager 

walked lip to me and said, 'Hey, Prop 209 passed, 

and lve don't haJ1e to use you anymore.' I didn't say 

anything to him atfirst, but the next day. I told 

him that I wanted to talk to him about what he had 

said to me. I said, 'Did it occur to ).lOU that I've 

been working here for a number a/years and that 

I hal'e alwaysfinished on time or ear(v ... and how 

many letters do you havefrol11 clients praising my 

cleanliness and professionalism?' Well, he didn't 

care. Hejust looked at me and said, 'Well, it's true. 

Prop 209 passed, and we don't have to use you 

anymore, ' The next year, my pY(~iects plummeted 

to $30,000. To this day, I have to call and remind 

clients that I'm in still ill business.. .do you think 

my male counterparts have to do that?" • WEE 

OHmer 

Many participants questioned the usefulness of Proposition 209. They expressed concern that 

while Proposition 209 was designed to enforce race 

and gender neutrality, it did nothing to challenge the 

"good old boy" network that still operates at many 

key levels in the public contracting industry, WBEs 

were beginning to make advancements in California's 

transportation construction industry when the proposition was implemented. In fact. awards to WBEs 

~xperienced the most gains during the six years prior to the passage of Proposition 209. WBEs agreed 

that the biggest impact of Proposition 209 was the 

elimination of participation goals, which affected the 

outreach efforts of prime contractors and the systems 

to hold state agencies and prime contractors account~ 

able for their contracting decisions and practices. 

WBE Survival Strategies 

Overall, participants agreed that women, in general, 

were just beginning to become more visible in the transportation construction industry when Proposition 209 

passed. To maintain their businesses in a challenging 

industry climate, WBEs attributed their longevity to 

the following strategies: 

Remain risible. WBEs have to ensure that they 

maintain contacts and networks that can increase 

their visibility. Given the unreliability of good 

faith efforts. WBEs must engage other organizations, including civil, professional, or social networks that can engage potential clients andfor 

contractors. 

ShiftfoclIs}i'om public agencies. WBEs agreed that 

shifting focus from pub1ic agencies to private sector and nonprofit organizations helps to sustain 

businesses owned by women. WBEs also emphaTHELTON E HENDERSON OENTER FOR SOCIAL JUSTIOE 35 
177 

Results:MBE Focus Groups and Interviews 

sized maintaining contact with existing clients in 

order to increase the likelihood of winning other 

projects from them in the future. 

• Strategically respond to R(!quest for Proposals 

(RFPs). WBEs agreed that it is critical for women 

to gauge which outreach efforts are genuine and 

limit the number of RFPs to which they respond. 

Because preparing a bid and proposal can be 

very expensive, many participants suggested that 

WBEs only spend the time and money to respond 

to RFPs that perfectly match their expertise and 

that arc received in a timely fashion. 

• Exercise legal recourse when necessary. WllEs 

who were victims of discrimination survived as 

a result of receiving financial awards from class 

action litigation. When necessary and justified. 

WBEs suggested women use legal advocacy and 

protection to remedy discrimination. _ 

A VISION FUlXJLLED0 
178 

Discussion 

Proposition 209 ended California's ability to implement the nation's leading strategy to correct racial and 

gender discrimination. From the five methods used 

to analyze the impact of Proposition 209 on Women 

Business Enterprises in California's transportation 

construction industry---Caltrans contract awards to 

WBEs, the survival of 1996 certified WBEs, a statewide survey of surviving WBEs, focus groups with 

surviving WBEs, and in-depth interviews with surviving WBEs---there arc several themes that demonstrate 

the degree to which women-owned businesses were impacted by the removal of race- and gender-conscious 

equal opportunity programs in California. 

The quantitative data reveal that race- and 

gender-conscious policies that were previously implemented to remedy discrimination and hostility 

against women in the transportation construction industry before 1996 were at least partially successful in 

increasing participation among women-owned finns. 

However, the culture of the transportation construction industry appears to challenge, at every step, the 

inclusion of women. These trends appear to be more 

pronounced for women of color, particularly African 

American-owned WBEs, though it is important to 

note that their small representation within the industry and thus in this study, precludes the possibility of 

painting a comprehensive picture of their experiences 

in California's transportation construction industry 

before and after the elimination of affirmative action. The dearth of research on women of color in this 

industry, and in general, reflects a need for greater 

understanding about the specific barriers that prevent 

the devclopment and success of Hrms owned hy women of color in this industry. 

The quantitative data reveal that the number 

and percentage of awards to women decreased after 

the elimination of these goals. The qualitative data 

suggest that the climate of the industry became increasingly hostile to women after the elimination of 

gender.consclous goals-reflecting an entrenched 

social bias against women in the transportation construction industry. While surviving WBEs in this study 

maintained modest success and relative longevity in 

the industry, it is important to note that the majority 

of them indicated that this was a result of working 

with the private and nonprofit sectors. Access to pub w 

lie contracts remains a challenge. 

Race- and gender-conscious remedies to dis w 

crimination, including affirmative action programs, 

were designed to correct a history of bias and excluSiOll. The findings of this study suggest that just as 

women were beginning to make advances in the public 

domain·-as evidenced by increased Caltrans awards 

for WBEs and as supported by aspects of the Caltrans 

DBE program, including the pre-bidding conferences, 

with some regularity-the removal of affirmative ae w 

tion programs impeded this progress~ and in many 

ways, erased it altogether. _ 

.. just as lvomen l1'ere heginning 

to make advances in the puhlic 

domain r, -l the removal of 

affirmatil'c action prof;rams 

impeded this progress, and in 

many 1\'a)'s, erased it altogether, 

THELTON E. HENDERSON CENTER FOR SOCIAL JUSTtCE 37 
179 

Recommendations: 

Strategies for Providing Equal Opportunity 

Women continue to face significant barriers to equal 

participation in California's transportation construction industry. Data consistently demonstrate the 

under representation of women-owned firms among 

those awarded public contracts. This study and other 

examinations of equal opportunity in California public contracting find signific<lot disparities for women 

following the elimination of gender-conscious equal 

opportunity programs. To ensure equal opportunity 

for WBEs seeking public contracts in California's 

transportation construction industry, HeS] recommends increased attention and action in five primary 

areas, including: I) equal opportunity goals and programming, 2) culture of transportation construction 

industry toward women, 3) data collection for womenowned businesses, 4) continued research on the impact 

of anti-affirmative action legislation on pathways to 

entrepreneurship for women, and 5) advocacy for the 

business model of diversity. 

Equal Opportunity Progranuning 

The findings of this report suggest an inconsistent application of the legal standards as they pertain to 

gender-conscious equal opportunity programs. which 

negatively impacts women-owned businesses who seek 

to participate in gender-conscious remedies to discrimination. While federal case law has generally indicated 

that gender-based classifications are to be reviewed according to a more flexible standard under the Equal 

Protection Clause than the strict scrutiny rule applied to 

race-based classifications, affirmative action programs 

designed to remedy discrimination against women have 

been analyzed as if they were race-conscious programs. 

Specific recommendations are as follows: 

• Rc?commenciation: Design gender-conscious programs to meet the federal standards for genderbased classifications and develop tailored programs that respond to the needs of women of all 

racial groups. Caltrans and other public contract~ 

ing agencies should develop and implement specific remedies for women of color where there is 

demonstrated disparity. Numerical goals should 

38 A VISION FULfILLED? 

be articulated regarding the participation of women of color in proportion to their availability. 

Recommendation: Implement gender-conscious 

goals with strict enforcement and review policies. 

Caltrans and other public contracting agencies 

should develop strategies to confirm and enforce 

good faith outreach and participation efforts. 

Goals should be developed using mechanisms 

both to encourage interpretation of WBE participation goals as minimal goals and to develop 

incentives to reward firms that exceed these goals. 

Culture orTransportation Construction 

Industry toward Women 

The findings of this report highlight that gender discrimination continues to exist at all stages along the 

pathway to entrepreneurship in the transportation 

construction industry. While no single agency or institution can eradicate racial and gender discrimination, 

there are a number of strategies that can be implemented to challenge discriminatory actions toward women: 

Recommendation: Training for key leadership at 

contracting agencies on the historical and present manifestations of gender bias and policies to 

enforce anti-discrimination in the workplace and 

on public projects.. Caltrans and other public contracting agencies should routinely provide equal 

opportunity and sexual harassment training to 

prime contractors, project managers, inspectors. 

and other key personnel involved with the public 

contracting process. 

Recommendation: Examine and expand representation of women business owners on small 

business councils. Caltrans and other public con~ 

tracting agencies should routinely examine the 

representation of women, including women of 

color, on councils charged with the task of reviewing and developing policies and practices regarding the equitable distribution of public contracts. 
180 

Recommendation: Build networks to support ca· 

pacity~building among firms o\vncd by women. 

Caltrans and other public contracting agencies 

should consider partnering with organizations. 

including Chambers of Commerce, to increase 

the outreach and participation of women-owned 

firms in the transportation construction industry. 

Professional networks, advocacy organizations, 

and Chambers of Commerce should partner with 

Caltrans and other public contracting agencies to 

provide technical assistance and support for the 

capacity-building of firms owned by women in 

the transportation construction industry. 

Recommendation: Develop structures to support 

and encourage the participation of women in key 

institutions that provide entrepreneurial path~ 

ways. Institutions that provide training and education on trades, professional schools, and unions 

should develop mechanisms to ensure equal access for women to gain experience. 

• Recommendation: Enforce anti-discrimination 

policies in lending, bonding, and insurance. 

Legislators and federal equal opportunity enforcement officers should monitor the extent to 

which lending institutions are in compliance with 

anti-discrimination laws. Lending, bonding~ and 

insurance institutions should continue to implement self-monitoring processes to ensure a bjective decision-making in rewarding credit. loans, 

bonding, and other forms of financial support to 

businesses owned by women in the transportation 

construction industry. 

Data Collection for Women-Owned Businesses 

The findings of this report revealed significant challenges to collecting comprehensive. longitudinal data 

for women of all racial groups. Data collection is essential to developing informed policies and tailored 

responses to discrimination. Specific recommendations are as follows: 

Recommendation: Separate data by race, ethnicity, 

gender, award type and award amount. Caltrans 

and other public contracting agencies should 

ensure that the collection of demographic data 

distinguishes data pertaining to women of color 

from data relating to men of color or white wom~ 

en. This will ensure a more accurate analysis of 

trends regarding firms owned by women and ensure that women of color are not treated as invisible entities in analyses of potential disparity. 

Reconllnendation: Legislation to enforce accurate 

data collection and recording for ten years within the state of California. Policymakers should 

consider legislation to mandate the collection 

and storage of accurate dis aggregated data from 

Caltrans and other public contracting agencies. 

Many agencies misinterpreted Proposition 209 

as a mandate to eliminate data collection efforts. 

Enforcing data collection at these agencies would 

ensure accurate analyses and monitoring regarding award trends for all businesses. 

Research on the Impact of Anti-af:6rmative 

Action Laws on WBEs 

The findings of this report highlight the dearth of 

research on trends for women in the transportation 

construction industry and other traditionally male 

industries following the removal of affirmative action programs. In order to develop informed and 

tailored policies to encourage the participation of 

women~owned firms in industries in which they are 

underrepresented, more information is needed on their 

experiences. Specific recommendations are as follows: 

Recommendation: Continued research on the impact of Proposition 209 on \vomen in the transportation construction industry. More research 

is needed regarding the impact of eliminating affirmative action in specific segments of the transportation construction industry, including professional services, supplying, and constructionltrades. 

THELTON HENDERSON CENTER FOR SOCIAL JUSTICE 39 
181 

Recommendations: 

• Recomnlendation: Continued research on the impact of Proposition 209 and barriers to capacitybuilding for businesses owned by women. More 

research is needed on the successful pathways to 

entrepreneurship for women and on the impact 

of eliminating affirmative action on women in 

key areas of capacity-building, including access 

to technical assistance regarding business management. training/apprenticeship programs. representation in unions and other areas. 

• Recommendation: Increased research on the intersection between race and gender in measuring the 

impact of anti-affirmative action laws and policies. More research is needed regarding the specific ways in which women of color are impacted 

by the elimination of race- and gender-conscious 

remedies to discrimination, 

Advocacy for the Business Model of Diversity 

The findings of this report suggest a failure to equally 

engage women-owned businesses following the elimination of affirmative action in California. Engaging the full 

spectrum of California's business community fosters the 

broader implementation of economic development opportunities, Specific recommendations are as follows: 

Recomrne,ufation: L~lltrans and other public contracting agencies should examine and evaluate successful 

prdCtices in the private sector. Many plivate enterprises have successfully demonstmted a business model 

that enCOlU'ages the participation of diverse business 

enterptises. Examining and implementing outreach 

and utilization strategies can help to eradicate hiased 

or discriminatory decision-making that negatively impacts women in traditionally male industries, 

Recommendation: Caltrans and other public contracting agencies should consider implementing incentives 

and awards for businesses that exceed participation 

goals for underrepresented groups and actively demonstrate a commitment to engaging in business practices that extend beyond personal networks. _ 

"~o A VISION FULFILLED? 

Conclusion 

The structural exclusion of one group from any public 

process because of race, ethnicity, gender or national 

origin is not only illegal. it is antithetical to any demonstration of the ideals of our nation, Our whole 

society loses when significant segments of our extend· 

ed community are unable to freely compete, President 

Carter's vision of a democracy inclusive of everyone. 

including women, has yet to be fully realized. This 

collective struggle for equity is a call to action for leg· 

islators, academics. legal advocates. and the voting 

public to mobilize our nation to develop la\\'s, policies. 

and practices that reflect the salient virtues of fairness 

and equal opportunity and that protect everyone from 

discrimination. The right to exist free of discrimina· 

tion is not only a core social justice issue. but also, an 

essential human right. 

A number of reports have revealed a lack of 

fairness and equal access to public contracts that 

result from the absence of gender-conscious equal op· 

portunity programs. California. along with the rest 

of the nation. must continue to examine the degree 

to which we have upheld our promise of enforcing 

equal opportunity. Across the nation. women-owned 

businesses emerge as important employers in our socicty--spending approximately $546 billion annually 

on salaries and benefits.'N Engaging these women as 

equal participants and competitors-thereby fulfilling the vision of a fair democracy-not only benefits 

women. It benefits liS alL _ 

q.j CCllt~r for Women's Business Research. (2006), Key Facts abollt 

Women-Owned BUSinesses, Update. 
182 

Th~lto~ E.' ... aerson Center Cor SochdJu:stic:e 

ullivimity ofCaliIonlla, Bed<eley School of Law 

!l1af[, 

Mary Louise Frampton, Dir~ctQr 

Diane T Chin, Associate Director 

Monique W. Morris, Senior Research Fellow 

Michael D. Sumner, Research Fellow 

Jessica,Z. Borja, Research Associate 

Mary Eillott, Program Administrator 

Jennifer Navarro, Prog~ Assistant 

ll.dvIsoryCo......u, 

The Honorable Thelton E. Henderson 

The Honorable Ken Kawaichi, Ret. 

The Honorable John RacaneIli, Ret. 

Th. Honorable John True III 

Mario Barnes 

Angela Blackwell 

Barbara Bryant 

Abby Ginzherg 

Irma Herrera 

Judith Droz Keyes 

Bemida Reagan 

Amita; Schwartz 

Brad Seligman 

Ellen Widess 
183 
184 

NERA Economic Consulting 

Evidence of Discrimination Impacting Minority-Owned and 

Women-Owned Businesses 

Testimony of Jon S. Wainwright, Ph.D., Vice President, NERA Economic 

Consulting 

Before the Committee on Small Business and Entrepreneurship 

United States Senate 

September 24, 2009 

Chairman Landrieu, Ranking Member Snowe, and Members of the Committee: 

Thank you for the opportunity to submit testimony for this roundtable. My name is Jon 

Wainwright. I hold a Ph.D. in economics from the University of Texas at Austin. Currently, I am 

a Vice President with National Economic Research Associates, also known as NERA Economic 

Consulting, in Chicago, Illinois and Austin, Texas. 

NERA is a global firm of experts dedicated to applying economic, finance, and quantitative 

principles to complex business and legal challenges. For nearly half a century, NERA's 

economists have been creating strategies, studies, reports, expert testimony, and policy 

recommendations for government authorities and the world's leading law firms and corporations. 

We bring academic rigor, objectivity, and real world industry experience to bear on issues arising 

from competition, regulation, public policy, strategy, finance, and litigation. NERA's clients 

value our ability to apply and communicate state-of-the-art approaches clearly and convincingly, 

our commitment to deliver unbiased findings, and our reputation for quality and independence. 

Our clients rely on the integrity and skills of our unparalleled team of economists and other 

experts backed by the resources and reliability of one of the world's largcst economic 

consultancies. With its main office in New York City, NERA serves clients from over 20 offices 

across North America, Europe, and Asia Pacific. 

I. Introduction 

For twenty years, I have devoted the greater part of my professional life to studying race and sex 

discrimination and its impact on business enterprise and entrepreneurship in the United States. 

During this time I have served as the project director and principal investigator for almost 30 

studies of business discrimination against minorities and women undertaken since 2000 and prior 

to that time worked on perhaps a dozen more. I have authored a book and several articles on thc 

subject and provided expert testimony in federal and state courts on these and other labor and 

business related matters on many occasions. 
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NERA Economic Consulting 

I was fortunate to have been mentored at the start of my career by two of the country's leading 

scholars in this field-Dr. Ray Marshall, Professor Emeritus at the Lyndon B. Johnson School of 

Public Affairs at The University of Texas at Austin and former Unitcd States Sccretary of Labor, 

and Dr. Andrew Brimmer, former member of the Board of Governors of the Federal Reserve, 

former Assistant Secretary of Commerce, and Professor Emeritus at thc University of 

Massachusetts, Amherst. 

A key lesson I absorbed from these men was expressed by Professor Marshall in this way: 

"Institutionalized discrimination in business transactions is deeply 

rooted in the American economy. There can be no doubt that 

business discrimination inflicts serious damage on the society, 

polity, and economy. Governments have a responsibility to 

improve public understanding of the seriousness of this problem 

and to take positive steps to address it. These positive steps must 

include public education, specifically outlawing this form of discrimination, using governments' purchasing power to help those 

who are being discriminated against while rewarding those who do 

not discriminate, and developing race neutral programs to help all 

small businesses." [ 

If you accept that discrimination in business transactions has become institutionalized in the 

American economy, then it is difficult to argue with the logic of Dr. Marshall's conclusions. 

During the last twenty years, the primary bulwark against business discrimination has been the 

policy of using public sector purchasing power to support the entrepreneurial endeavors of 

minority-owned, women-owned, and other small disadvantaged businesses and to promote fair 

and full access to government contracting and procurement opportunities as well as to mitigate 

the impact of business discrimination in the private sector. The Disadvantaged Business 

Enterprise (DBE) Program and Small and Disadvantaged Business (SDB) Program are key 

examples of such policies at the federal leveL 

II. Findings and Conclusions from NERA's Disparity Studies Completed Since 2000 

I would like to address my remarks today to the state of minority-owned and women-owned 

businesses as documented in numerous studies and related research I have directed at NERA in 

the last 10 years, and the implications of these findings for the continuing need for the public 

sector to use its purchasing power to help remedy the ill effects of business discrimination. Many 

of these studies included one or more entities participating in the USDOT's DBE Program 

through a state department oftransportation, a transit authority, or an airport.2 

Ray Marshall, "Minority and Female Business Development After Croson." Working Paper, 2000. 

Augusta-Richmond County, GA, 2009: Salt Lake City International Airport, 2009: Memphis International 

Airport, 2008; City of Austin, Texas (including Austin-Bergstrom International Airport), 2008; Illinois State Toll 

Highway Authority. 2006; Maryland Department of Transportation, State Highway Administration, 2006; 

Maryland Department of Transportation, Maryland Aviation Administration, 2006; Maryland Department of 

Transportation, Maryland Transit Administration, 2006; State ofMassachusetrs, 2006; City and County of 

2 
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NERA Economic Consulting 

It is important to acknowledge as well the enormous amount of relevant evidence that already 

appears in thc Congressional record. A useful synopsis of this evidence was provided by the 

Tenth Circuit Court of Appeals in their decision in Adm'and Constructors.3 Additionally, the 

U.S. Senate Committee on Small Business and Entrepreneurship, for example, held hearings in 

May 2007 and September 2008 regarding closely related subject matter. The Subcommittee on 

Information Policy, Census, and National Archives of the U.S. House Committee on Oversight 

and Government Reform held a hearing in September 2008 on how information policy affects 

competitive viability in minority contracting. The U.S. Committee on Transportation and 

Infrastructure held a hearing on challenges facing DBEs in the transportation sector this past 

March as well. 

The disparity studies on which this testimony is drawn span a wide range of geographic 

locations-from Pennsylvania and Massachusetts in the North; to Georgia, Texas and Tennessee 

in the South; to Maryland in the East; to Washington, Colorado, and Utah in the West, to Illinois, 

Minnesota, and Missouri in the Midwest. 

Despite the geographic diversity our studies represent, the findings from these studies show far 

more similarities than differences-minority-owned businesses and women-owned businesses 

throughout the nation and across a wide variety of industry sectors continue to face large 

disparities in almost every aspect of business enterprise activity that can be quantified. 

II.A. Data from the Survey of Business Owners 

One important source of data that we draw upon in our DBE studies is the Census Bureau's 

Survey of Business Owners (SBO), performed every fivc years. According to the most recent 

data available from the SBO, there are substantial disparities between the share of minorities in 

the general population and their share of the business population. Specifically: 

• Although African Americans comprised 12.7 percent of the U.S. population, they 

accounted for only 5.3 percent of its businesses. 

• Although Hispanics and Latinos comprised 13.4 percent of the population, they 

accounted for only 7.0 percent of the businesses. 

• Although women comprised 50.9 percent of the population, they accounted for only 28.9 

percent of the businesses. 

Denver (including Denver International Airport), 2006; st. Louis Regional Transit, 2005; Washington 

Department of Transportation, 2005; Minnesota Department of Transportation, 2005; Missouri Department of 

Transportation, 2004; Illinois Department of Transportation, 2004; Minnesota Department of Transportation, 

2000; Chicago Metra, 2000. 

3 Adarand Constructors, [nco V. Slater, 228 F.3d 1147, 1166-1175 (10th Cir. 2000) (discussing evidence before 

Congress of business discrimination against minorities in the construction industry in enacting the 

Disadvantaged Business Enterprise Program for federal-aid transportation contracts, Pub.L. No.1 00-17, 101 

Stat. 132 (1987), Pub.L. No. 102-240, 105 Stat. 1914 (1991) and Pub.L. No. 105-178,112 Stat. 107 (1998), and 

the implementing regulations at 49 CFR Part 26 (1999». 

3 
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NERA Economic Consulting 

Moreover, the minority and female share of business sales and receipts is far lower than their 

share of the business population. 

• Although African Americans comprised 5.3 percent of all U.S. businesses, they earned 

only 1.0 percent of sales and receipts. 

• Although Hispanics and Latinos comprised 7.0 percent of all businesses, they earned only 

2.5 percent of sales and receipts. 

• Although women comprised 28.9 percent of all businesses, they earned only 10.7 percent 

of sales and receipts. 

Similar disparities are observed for other minority groups as well. Asians and Pacific Islanders 

comprised 5.0 percent of the business population yet earned only 3.8 percent of sales and 

receipts. Native Americans comprised 0.9 percent of all businesses but earned only 0.3 percent 

of sales and receipts. 

These disparities between the size of the minority and female business populations and their 

share of sales and receipts are very large. They are also statistically significant, meaning they are 

unlikely to result from chance alone. While the exact proportions vary, large and statistically 

significant disparities are observed in all 50 states and the District of Columbia, for all minority 

groups-African-Americans, Hispanics and Latinos, Asians and Pacific Islanders, and Native 

Americans--as well as for women. These disparities are found in the economy as a whole, in the 

Construction sector, and in virtually all other industry sectors. This is documented below in 

Tables lA through 20F. Similar findings from current and past SBO reports appear in most of 

NERA's disparity studies. 

n.B. The Concept of "Capacity" 

Some people have argued that the statistical evidence in disparity studies should be adjusted for 

something they call "capacity." By this they often seem to mean that disparity study statistics 

should be adjusted for the size of firms or size of contracts firms have completed in the past. 

Based upon my own experience as an expert in the field of economics and regarding minorityowned and women-owned business issues in particular, I do not agree with this argument, for the 

following reasons. 

The main problem with the argument that statistical evidence in disparity studies should be 

adjusted for so-called "capacity" measures is that such an approach prevents accurate 

measurement of the existence of discrimination. Many, if not all, "capacity" indicators are 

themselves impacted by discrimination. Therefore, it is not good social science to limit 

availability measures by factors such as firm age, revenues, or numbers of employees. Moreover, 

disparity studies already adjust for more appropriate measures related to "capacity" such as 

geographic market and industry code. 

The reality is that large, adverse statistical disparities between minority-owned or women-owned 

businesses and non-minority male-owned businesses have been documented in numerous 

4 
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NERA Economic Consulting 

research studies and reports since Croson.4 Business outcomes, however, can be influenced by 

multiple factors, and it is important that disparity studies examine the likelihood of whether 

discrimination is an important contributing factor to observed disparities. 

One traditional way that the linkage between statistical disparities and discrimination has been 

established is to consider the size of the observed disparities. That is, the larger the disparity, the 

less likely it becomes that non-discriminatory factors can account for the entire difference. 

Another traditional way that the linkage between statistical disparities and discrimination has 

been established is through the introduction of qualitative, or "anecdotal," evidence. If the thrust 

of such qualitative evidence is consistent with the statistical disparities observed, the case for the 

linkage is strengthened. 

Some critics ofDBE, SDB, and similar programs and some courts have criticized the evidentiary 

value of disparity statistics, claiming that the availability measure in the disparity statistic does 

not factor in "capacity" or, stated another way, claiming that availability statistics may include 

firms that are not "qualified, willing, and able" to perform the work. For several reasons, such 

criticisms are unwarranted and unscientific. 

First, terms such as "capacity," "qualifications," and "ability" are not well defined in any 

statistical sense. Does "capacity" mean revenue level, employment size, or bonding limits? Does 

"qualified" or "able" mean possession of a business license, certain amounts of training, or types 

of work experience? Also, does the meaning of such terms differ from industry to industry, state 

to state, or through time? 

Second, it is important to understand that when measuring the existence of discrimination, the 

statistical method used should not improperly limit the availability measure by incorporating 

factors that are themselves impacted by discrimination such as, firm age, revenues, bonding 

limits, or numbers of employees. 

In understanding this problem, it is helpful to consider an extreme example where discrimination 

has prevented the emergence of any minority-owned firms. Suppose that racial discrimination 

was ingrained in a state's highway construction market. As a result, few minority construction 

employees are given the opportunity to gain managerial experience in the business; minorities 

who do end up starting construction firms are denied the opportunity to work as subcontractors 

for non-minority prime contractors; and non-minority prime contractors place pressure on unions 

not to work with minority firms and on bonding companies and banks to prevent minority-owned 

construction firms from securing bonding and capital. In this example, discrimination has 

essentially prevented the emergence of a minority highway construction industry with 

"capacity." Those minority firms that exist at all will be smaller and have lower revenues and 

employees than firms that are not subject to the same discrimination. 

In this situation, excluding firms from an availability measure based on their "capacity" in a 

discriminatory market would preclude a government agency from doing anyihing to rectify the 

continuing support of a clearly discriminatory system with public dollars. There is no recognition 

4 Enchautegui. e/ al 1996. 

5 
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NERA Economic Consu!ting 

that discrimination has prevented the emergence of "qualified, willing and able" minority firms. 

Without such firms, there can be no statistical disparity. 

Therefore, focusing on the "capacity" of businesses in terms of employment, revenue, bonding 

limits, number of trucks, and so forth is simply wrong as a matter of economics because it can 

obscure the existence of discrimination. A truly "effective" discriminatory system would lead to 

a finding of no "capacity," and under the "capacity" approach, a finding of no discrimination. 

Consider, for example, using revenue as the measure of qualifications. Revenues simply measure 

the value of contracts that firms are receiving. If minority-owned and women-owned businesses 

are subject to marketplace discrimination, their revenues will be smaller than nonminority maleowned businesses because they will be less successful at obtaining work. Using revenues as a 

measure of DBE availability in contracting is like using pay as a measure of qualifications in an 

equal-pay case. Revenue, like pay, measures the extent to which a firm has succeeded in the 

marketplace-it does not measure the ability to succeed and should not be used in such a 

manner. 

Of course, the government is not so helpless in the face of the current effects of discrimination, 

and governments have quite rightly responded to the existence of discrimination by instituting 

programs like the DBE and SDB programs. Interestingly, the existence of these types of 

programs in the public sector, even while such programs are relatively rare in the private sector, 

has resulted in a situation where minority firms may more available for public sector work than 

for private sector work, despite the relatively greater bureaucratic barriers to entry (e.g., 

certification requirements, reporting requirements, etc.) precisely because of the efforts to 

remedy discrimination in the public sector. 

Third, in dynamic business environments, and especially in the construction sector, such 

"qualifications" or "capacity" can be obtained relatively easily. It is well known that small 

construction companies can expand rapidly as needs arise by hiring workers and renting 

equipment. Many general contractors subcontract the majority of a project. Subcontracting is one 

important source of this elasticity, as has been noted by several academic studies. Bourdon and 

Levitt, for example, in their study of construction labor markets, observed that: 

"One of the unique aspects of the construction industry is the prevalence of 

subcontracting. Construction projects are undertaken by a multitude of firms 

assembled for brief periods of time on a site then disbanded. General contractors 

can undertake projects of considerable scale without large amounts of direct labor 

or fixed capital; subcontractors can start with one or two employees and bid only 

on particularly highly specialized contracts."s 

Thus, the "capacity" and "qualifications" of firms in the construction sector are highly elastic. 

Firms grow quickly when demand increases and shrink quickly when demand decreases. 

5 Bourdon and Levitt, 1980. 

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NERA E.conomic Consulting 

Academic studies have also found that, absent discrimination, entry into the construction 

industry is not difficult. Bourdon and Levitt attribute this to subcontracting opportunities.6 Eccles 

observes that entry is easy based on the large number of small firms and that capital requirements 

for fixed assets are small. 7 Gould, who followed the careers of six construction contractors, also 

demonstrates ease of entry.8 He further notes that there is movement between small and large 

firms not only via subcontracting but also by experienccd staff at larger firms leaving to form 

smaller new firms. Similar kinds of elasticity exist as well in many industries beyond 

construction. 

Fourth, even where "capacity" -type factors have been controlled for in statistical analyses, 

results consistent with business discrimination are still typically observed. For example, many 

jurisdictions have demonstrated that large and statistically significant differences in commercial 

loan denial rates between minority and non-minority firms were evident even when detailed 

balance sheet and creditworthiness measures were held constant. Similarly, economists using the 

decennial census data have demonstrated that statistically significant disparitics in business 

formation and business owner earnings between minorities and non-minorities remain even after 

controlling for a host of additional factors including educational achievement, labor market 

experience, marital status, geographic mobility, number of workers in the family, number of 

children, immigrant status, disability status, veteran status, interest and dividend income, labor 

market attachment, industry, geographic location, and local labor market variables such as the 

unemployment rate, population growth rate, governmcnt employment rate, or per capita income9 

Ray Marshall, in partnership with Andrew Brimmer, conducted one of the first post-Croson 

disparity studies, for the City of Atlanta in 1990. Drawing on that experience, he summarizes 

well the arguments against using the outcomes of discrimination to measure "capacity"IO 

6 Ibid. 

7 Eccles, 1981. 

8 Gould, 1980. 

The problem of establishing statistical proof of whether or not 

minority contractors are "qualified, willing and able" is 

particularly challenging. Croson provides limited guidance on this 

question.... Unfortunately, this lack of guidance has made it 

possible for courts and opponents of [DBE and SDB] programs to 

argue that the failure to produce perfect statistical evidence-i.e., 

timely and highly specific, and methodologies that control for 

evcrything except discrimination-invalidates these programs 

despite the fact that the most reliable statistics and the most 

appropriate methodologies confirm the persistence of 

discrimination. Our evidence for Atlanta suggests that even highly 

qualified black contractors are disadvantaged relativc to similarly 

9 Wainwright, 2000. 

10 Marshall. 2002. 

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NERA Economic Consulting 

situated white contractors .... Once contractors are able to obtain 

contracts, they usually are able to expand their capacity. 

In a dynamic business environment, it would be difficult to argue, 

as some critics have, that qualifications are determined mainly by 

size .... Moreover, as the Tenth Circuit Court of Appeals observed 

in Adarand VII, there is no credible evidence that minority 

contractors who have been hired under [DBE or SDB] programs 

have lacked adequate qualifications. 

Nevertheless, analyses of available data for business owners that 

enable personal characteristics and other factors to be controlled 

for [generate results that remain] compatible with racial exclusion. 

There therefore is no credible evidence that the large disparities in 

the utilization of minority contractors can bc cxplained by the lack 

of qualifications or the unwillingness to contract. Indeed, strong 

historical, anecdotal and survey evidence ... demonstrates that 

minority contractors are more willing than white males to contract 

with governmental entities, even though they recognize that public 

contracting is less desirable than the mainstream private sector, 

where their opportunities are greatly restricted. 

To summarize, there are several reasons why I do not agree that the statistical analysis in 

disparity studies should adjust for "capacity." These reasons include that the term "capacity" has 

been ill-defined; that small firms, particularly in the construction industry, are highly elastic with 

regard to ability to perform; and that many disparity studies have shown that even when 

"capacity" and "qualifications" type factors are held constant in statistical analyses, evidence of 

disparate impact against DBE and SDB firms tends to persist. However, the most important 

reason I disagree with the use of "capacity" to limit measures of availability and other measures 

of disparity is that most, if not all, identifiable indicators of capacity are themselves impacted by 

discrimination. 

II.C. Public Use Microdata Samples and Current PopUlation Survey Data 

It is, however, fair to ask whether the disparities documented in the SBO data result primarily 

from discrimination, either past, present or both, or whether they result from other factors not 

tainted by discrimination. I I 

Our disparity studies have put such questions to the test using the public use microdata samples 

(PUMS) from the two most recent decennial censuses, as well as microdata from the Current 

Population Survey (CPS). The advantage of the PUMS and CPS data is that they allow us to 

11 This was the subject ofa book I authored, Racial Discrimination and Minority Business Enterprise: Evidence 

from the 1990 Census, New York and London: Garland Publishing, 2000. As all of the studies submitted for the 

record attest, similar results are observed using the 2000 decennial census data. 

8 
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NERA EconomIC Consulting 

compare these percentages while holding a wide variety of other, potentially non-discriminatory, 

factors constant, such as industry, geography, education, age, and labor market status. 12 

Like the SBO, the PUMS and CPS data sources show large and statistically significant 

disparities between the percentage of minorities and women who choose to form businesses and 

the percentage of comparable non-minority males who choose to form businesses. Such 

disparities are observed for the nation as a whole and throughout the states, and in the economy 

as a whole as well as across different industry sectors, including construction and constructionrelated professional services. 

As shown below in Table 2IA, our disparity studies have found that even when these other 

attributes are held constant using regression analysis, the disparities between African-Americans, 

Hispanics and Latinos, Asians, American Indians and Alaska Natives, Native Hawaiians and 

Pacific, and women business owners on the one hand and their non-minority male counterparts 

on the other, tend to remain large, adverse, and statistically significant. The overwhelming 

majority of the cases included in Table 2lA show large disparities. The data in the Construction 

sector also show large and statistically significant disparities consistent with discrimination, as 

shown in Table 2IB. 

Furthermore, even for those minorities and women who manage against the odds to form their 

own businesses, their entrepreneurial eamings tend to lag far behind their non-minority male 

counterparts. As shown below in Table 22B, for example, minority and female business ov..ner 

earnings in construction and construction-related professional services average roughly 25 

percent lower than thcir non-minority male counterparts, again even when other, nondiscriminatory, attributes are held constant. For African Americans, Native Americans, and nonminority women, the disparities are even larger. 

In sum, the evidence gathered from PUMS and CPS data sources, as documented below and in 

our many DBE studies, strongly suggests that business discrimination is the principal 

explanation for the disparities in the SBO data. 

12 We have also tested the hypothesis, with similar results, including additional factors such marital and family 

status, immigration status, ability to speak English, military service and veteran status, disability status, and asset 

levels. 

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NERA Economic Consulting 

III. Conclusion 

In sum, the evidence gathered from PUMS and CPS data sources, as documented below and in 

our many disparity studies, strongly suggests that business discrimination is the principal 

explanation for the disparities observed in the SBO data. 

I am optimistic that the statistical evidence will one day show that programs such as DBE and 

SDB are no longer needed, because minority-owned and women-owned businesses will have 

achieved competitive parity with their nonminority male-owned counterparts. However, my own 

research and that of my colleagues demonstrates that this day has not yet arrived. 

Thank you. I will be pleased to answer any questions. 

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NERA Economic Consulting 

Table lAo Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, African Americans, All Industries, 2002 

State 

Alabama 

Alaska 

Arizona 

Arkansas 

California 

Colorado 

Connecticut 

Delaware 

District of Columbia 

Florida 

Georgia 

Hawaii 

Idabo 

Illinois 

Indiana 

Iowa 

Kansas 

Kentucky 

Louisiana 

Maine 

Maryland 

Massacbusetts 

Michigan 

Minnesota 

Mississippi 

Missouri 

Montana 

Nebraska 

Nevada 

New Hampshire 

New Jersey 

New Mexico 

New York 

North Carolina 

North Dakota 

Ohio 

Oklahoma 

Oregon 

Pennsylvania 

Rhode Island 

South Carolina 

South Dakota 

Tennessee 

Texas 

Utah 

Vennont 

Percentage 

of All 

Finns 

9.26% 

1.49% 

1.66% 

4.28% 

3.88% 

1.52% 

3.42% 

6.70% 

25.86% 

6.63% 

13.41% 

0.82% 

0.31% 

7.17% 

3.24% 

0.68% 

2.04% 

2.52% 

12.24% 

0.24% 

15.65% 

2.27% 

6.03% 

1.77% 

13.33% 

3.81% 

0.22% 

1.44% 

2.56% 

0.37% 

5.12% 

1.13% 

7.58% 

8.11% 

0.14% 

4.36% 

2.55% 

0.74% 

2.83% 

nla 

9.77% 

0.18% 

5.90% 

5.12% 

0.34% 

0.29% 

Percentage 

of All Sales 

0.62% 

0.18% 

0.16% 

0.27% 

0.35% 

0.20% 

0.19% 

0.18% 

1.47% 

0.53% 

0.77% 

0.12% 

0.08% 

0.43% 

0.35% 

0.11% 

0.16% 

0.39% 

0.59% 

0.04% 

1.25% 

0.19% 

0.54% 

0.15% 

0.94% 

0.30% 

0.03% 

0.10% 

0.29% 

0.07% 

0.38% 

0.29% 

0.43% 

0.59% 

0.03% 

0.40% 

0.23% 

0.15% 

0.22% 

nla 

0.63% 

0.10% 

0.40% 

0.35% 

0.13% 

0.05% 

Percentage 

of All 

Employers 

2.96% 

0.66% 

0.66% 

1.38% 

1.48% 

0.68% 

0.97% 

1.97% 

9.23% 

1.95% 

3.88% 

0.31% 

0.34% 

1.73% 

1.28% 

0.35% 

0.96% 

0.92% 

3.55% 

0.10% 

4.23% 

0.87% 

1.68% 

0.46% 

4.39% 

1.73% 

nla 

0.62% 

1.08% 

0.23% 

1.86% 

0.50% 

1.81% 

3.07% 

nla 

1.56% 

0.96% 

0.39% 

1.17% 

nla 

3.31% 

0.11% 

2.16% 

1.79% 

0.15% 

0.15% 

Percentage 

of All 

Employer 

Sales 

0.46% 

0.14% 

0.13% 

0.18% 

0.26% 

0.16% 

0.14% 

0.11% 

1.28% 

0.36% 

0.55% 

0.10% 

0.07% 

0.35% 

0.31% 

0.10% 

0.13% 

0.35% 

0.40% 

0.03% 

0.92% 

0.15% 

0.47% 

0.12% 

0.59% 

0.24% 

nla 

0.09% 

0.23% 

0.06% 

0.31% 

0.27% 

0.31% 

0.45% 

nla 

0.34% 

0.18% 

0.13% 

0.18% 

nla 

0.42% 

0.10% 

0.29% 

0.26% 

0.13% 

0.05% 

Disparity 

Ratio-All 

Finns 

0.07 

0.12 

0.10 

0.06 

0.09 

0.13 

0.05 

0.03 

0.06 

0.08 

0.06 

0.15 

0.26 

0.06 

O.II 

0.16 

0.08 

0.15 

0.05 

0.18 

0.08 

0.08 

0.09 

0.08 

0.07 

0.08 

0.13 

0.07 

O.II 

0.19 

0.07 

0.26 

0.06 

0.07 

0.24 

0.09 

0.09 

0.20 

0.08 

0.06 

0.58 

0.07 

0.07 

0.38 

0.18 

Disparity 

Ratio 

Employers 

0.16 

0.22 

0.19 

0.13 

0.18 

0.24 

0.14 

0.06 

0.14 

0.19 

0.14 

0.33 

0.21 

0.20 

0.24 

0.29 

0.13 

0.38 

O.II 

0.33 

0.22 

0.18 

0.28 

0.27 

0.13 

0.14 

0.14 

0.22 

0.26 

0.16 

0.53 

0.17 

0.15 

0.22 

0.19 

0.34 

0.16 

0.13 

0.90 

0.14 

0.14 

0.86 

0.33 

11 
195 

NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Firms Employers Sales 

Virginia 7.77% 0.67% 3.39% 0.55% 0.09 0.16 

Washington 1.49% 0.23% 0.84% 0.21% 0.16 0.25 

West Virginia 1.30% 0.11% 0.39% 0.08% 0.08 0.22 

Wisconsin 1.70% 0.15% 0.76% 0.12% 0.09 0.16 

Wyoming 0.28% 0.03% 0.24% 0.02% 0.10 0.10 

Notes: The disparity ratio is derived by dividing the percentage of sales by the corresponding percentage of firms. A 

disparity ratio of zero indicates complete disparity while a value of I indicates parity. Disparity ratios in italics are 

statistically significant at a l-in-20 probability level or better. 

12 
196 

NERA Economic Consulting 

Table I B. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Hispanics and Latinos, All Industries, 2002 

State 

Alabama 

Alaska 

Arizona 

Arkansas 

California 

Colorado 

Connecticut 

Delaware 

Dist of Columbia 

Florida 

Georgia 

Hawaii 

Idabo 

Illinois 

Indiana 

Iowa 

Kansas 

Kentucky 

Louisiana 

Maine 

Maryland 

Massachusetts 

Michigan 

Minnesota 

Mississippi 

Missouri 

Montana 

Nebraska 

Nevada 

New Hampshire 

New Jersey 

New Mexico 

New York 

North Carolina 

North Dakota 

Ohio 

Oklahoma 

Oregon 

Pennsylvania 

Rhode Island 

South Carolina 

South Dakota 

Tennessee 

Texas 

Utah 

Velmont 

Percentage 

of All 

Firms 

0.82% 

2.00% 

9.21% 

1.00% 

14.70% 

5.17% 

3.12% 

1.38% 

4.60% 

17.33% 

2.71% 

3.12% 

2.28% 

4.13% 

1.26% 

0.65% 

1.90% 

0.70% 

2.33% 

0.54% 

3.46% 

2.83% 

1.34% 

0.90% 

0.71% 

0.83% 

0.96% 

1.35% 

5.75% 

0.73% 

7.03% 

21.73% 

9.58% 

1.41% 

0.41% 

0.87% 

1.87% 

2.12% 

1.26% 

3.91% 

1.03% 

0.51% 

0.95% 

18.41% 

2.68% 

0.62% 

Percentage 

of All Sales 

0.28% 

0.37% 

1.32% 

0.23% 

2.04% 

1.33% 

0.33% 

0.12% 

0.51% 

3.80% 

0.57% 

0.73% 

0.48% 

O.64~t. 

0.16% 

0.12% 

0.29% 

0.27% 

0.60% 

0.15% 

0.64% 

0.32% 

0.40% 

0.10% 

0.15% 

0.15% 

0.22% 

0.31% 

1.11% 

0.21% 

0.85% 

5.40% 

0.71% 

0.30% 

0.04% 

0.14% 

0.58% 

0.56% 

0.18% 

0.32% 

0.27% 

0.20% 

0.23% 

2.33% 

0.38% 

0.10% 

Percentage 

of All 

Employers 

0.90% 

1.85% 

5.30% 

0.84% 

7.06% 

3.48% 

1.70% 

0.72% 

3.18% 

11.09% 

1.66% 

2.05% 

1.82% 

2.69% 

0.81% 

0.58% 

1.47% 

nla 

1.63% 

0.32% 

2.00% 

1.41% 

0.90% 

0.57% 

0.56% 

0.63% 

nla 

0.94% 

3.18% 

0.65% 

3.78% 

15.08% 

3.26% 

1.09% 

0.25% 

0.67% 

1.40% 

1.56% 

0.72% 

1.20% 

0.90% 

0.49% 

0.92% 

9.47% 

1.82% 

0.35% 

Percentage 

of All 

Employer 

Sales 

0.26% 

0.34% 

1.10% 

0.20% 

1.68% 

1.21% 

0.28% 

0.09% 

0.48% 

3.27% 

0.48% 

0.66% 

0.41% 

0.57% 

0.14% 

0.11% 

0.25% 

nla 

0.56% 

0.13% 

0.54% 

0.26% 

0.39% 

0.08% 

0.13% 

0.14% 

n/a 

0.29% 

0.96% 

0.18% 

0.73% 

4.83% 

0.56% 

0.25% 

0.03% 

0.13% 

0.53% 

0.52% 

0.15% 

0.20% 

0.25% 

0.19% 

0.21% 

1.88% 

0.32% 

0.08% 

Disparity 

Ratio-All 

Finns 

0..34 

0..19 

0..14 

0..23 

0..14 

0..26 

D.1I 

0..0.9 

D.1I 

0..22 

0..21 

0..23 

0..21 

0..16 

0..13 

0..19 

0..15 

0..39 

0..26 

0..28 

0..19 

D.1I 

0..30. 

a.1I 

0..21 

0..18 

0..23 

0..23 

0..19 

0..28 

0..12 

0..25 

0.0.7 

0..21 

0..0.9 

0..16 

0..31 

0..26 

0..14 

0..0.8 

0..26 

0..40. 

0..24 

a. 13 

0..14 

0..15 

Disparity 

Ratio 

Employers 

0..29 

0..18 

0..21 

0..24 

0..24 

0..35 

0..16 

0..12 

0..15 

0..29 

0..29 

0..32 

0..23 

0..21 

0..17 

0..19 

0..17 

0..34 

0..41 

0..27 

0..19 

0..43 

0..14 

0..22 

0..22 

0..31 

0..30. 

0..28 

0..19 

0..32 

0..17 

0..23 

0..13 

0..19 

0..38 

0..34 

0..21 

0..17 

0..28 

0..39 

0.23 

0.20. 

0..17 

0..22 

13 
197 

NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity Percentage of All State of All of All Sales of All Employer Ratio-All Ratio 

Finns Employers Sales Firms Employers 

Virginia 3.59% 0.62% 1.79% 0.53% 0.17 0.30 

Washington 2.20% 0.34% 1.74% 0.30% 0.16 0.18 

West Virginia 0.57% 0.22% 0.81% 0.20% 0.38 0.25 

Wisconsin 0.95% 0.22% 0.77% 0.21% 0.23 0.27 

Wyoming 2.49% 0.66% 1.95% 0.63% 0.26 0.32 

Notes: See Table lAo 

14 
198 

NERA Economic Consulting 

Table Ie. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Asians, All Industries, 2002 

State 

Alabama 

Alaska 

Arizona 

Arkansas 

California 

Colorado 

Connecticut 

Delaware 

Dist of Columbia 

Florida 

Georgia 

Hawaii 

Idaho 

Illinois 

Indiana 

Iowa 

Kansas 

Kentucky 

Louisiana 

Maine 

Maryland 

Massachusetts 

Michigan 

Minnesota 

Mississippi 

Missouri 

Montana 

Nebraska 

Nevada 

New Hampshire 

New Jersey 

New Mexico 

New York 

North Carolina 

North Dakota 

Ohio 

Oklahoma 

Oregon 

Pennsylvania 

Rhode Island 

South Carolina 

South Dakota 

Tennessee 

Texas 

Utah 

Vermont 

Percentage 

of All 

Firms 

1.38% 

3.07% 

2.68% 

0.96% 

12.77% 

2.35% 

2.38% 

2.98% 

5.11% 

2.68% 

3.99% 

45.28% 

0.91% 

4.64% 

1.40% 

0.76% 

1.62% 

1.08% 

2.50% 

0.62% 

5.90% 

3.21% 

2.09% 

1.73% 

1.56% 

1.45% 

0.51% 

1.00% 

5.23% 

1.22% 

7.33% 

1.73% 

8.50% 

2.13% 

0.49% 

1.68% 

1.57% 

3.02% 

2.59% 

1.75% 

1.51% 

0.43% 

1.59% 

4.49% 

1.46% 

0.60% 

Percentage 

of All Sales 

0.56% 

0.91% 

0.73% 

0.37% 

4.50% 

0.64% 

0.48% 

0.53% 

0.94% 

1.04% 

1.08% 

18.88% 

0.39% 

1.27% 

0.54% 

0.20% 

0.39% 

0.48% 

0.55% 

0.27% 

1.89% 

0.77% 

0.64% 

0.38% 

0.87% 

0.42% 

0.22% 

0.49% 

1.35% 

0.43% 

2.18% 

0.73% 

1.76% 

0.58% 

0.25% 

0.57% 

0.47% 

0.87% 

0.69% 

0.49% 

0.81% 

0.15% 

0.50% 

1.14% 

0.48% 

0.17% 

Percentage 

of All 

Employers 

2.17% 

4.05% 

3.36% 

1.84% 

15.24% 

2.94% 

3.24% 

3.96% 

10.11% 

3.78% 

5.97% 

43.92% 

1.29% 

5.43% 

2.11(~/o 

1.12% 

2.36% 

1.89% 

3.07% 

1.28% 

7.44% 

3.76% 

2.80% 

1.61% 

2.34% 

2.19% 

0.90% 

1.53% 

5.37% 

2.07% 

8.46% 

2.52% 

8.40% 

2.84% 

0.97% 

2.71% 

2.28% 

3.42% 

3.17% 

1.78% 

2.47% 

0.46% 

2.86% 

5.99% 

1.81% 

1.00% 

Percentage 

of All 

Employer 

Sales 

0.53% 

0.82% 

0.67% 

0.36% 

4.17% 

0.58% 

0.41% 

0.49% 

nla 

0.99% 

1.00% 

17.73% 

0.38% 

1.19% 

0.52% 

0.18% 

0.36% 

0.47% 

0.47% 

0.26% 

1.76% 

0.72% 

0.60% 

0.35% 

0.79% 

0.40% 

0.22% 

0.49% 

1.17% 

0.39% 

2.06% 

0.69% 

1.58% 

0.54% 

0.25% 

0.54% 

0.42% 

0.76% 

0.63% 

0.44% 

0.79% 

0.14% 

0.47% 

1.04% 

0.45% 

nla 

Disparity 

Ratio-All 

Firms 

0.41 

0.30 

0.27 

0.39 

0.35 

0.27 

0.20 

0.18 

0.18 

0.39 

0.27 

0.42 

0.43 

0.27 

0.38 

0.26 

0.24 

0.45 

0.22 

0.45 

0.32 

0.24 

0.31 

0.22 

0.56 

0.29 

0.44 

0.49 

0.26 

0.35 

0.30 

0.42 

0.21 

0.27 

0.52 

0.34 

0.30 

0.29 

0.27 

0.28 

0.54 

0.34 

0.31 

0.25 

0.33 

0.28 

Disparity 

Ratio 

Employers 

0.24 

0.20 

0.20 

0.19 

0.27 

0.20 

0./3 

0.12 

0.26 

0.17 

0.40 

0.29 

0.22 

0.24 

0.16 

0.15 

0.25 

0.15 

0.21 

0.24 

0.19 

0.21 

0.22 

0.34 

0.18 

0.24 

0.32 

0.22 

0.19 

0.24 

0.27 

0.19 

0.19 

0.26 

0.20 

0.18 

0.22 

0.20 

0.25 

0.32 

0.31 

0.16 

0.17 

0.25 

15 
199 

NERA E:conomic Consulting 

Percentage Percentage Percentage Disparity Disparity Percentage of All State of All of All Sales of All Employer Ratio-All Ratio 

Finns Employers Sales Firms Employers 

Virginia 5.75% 1.38% 6.05% 1.27% 0.24 0.21 

Washington 5.75% 1.59% 6.01% 1.46% 0.28 0.24 

West Virginia 1.09% 0.51% 2.12% 0.50% 0.47 0.23 

Wisconsin 1.26% 0.34% 1.61% 0.32% 0.27 0.20 

Wyoming 0.76% 0.25% 1.34% 0.24% 0.33 0./8 

Notes: See Table lAo 

16 
200 

NERA Economic Consulting 

Table lD. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms. American Indians and Alaska Natives, All Industries, 2002 

State 

Alabama 

Alaska 

Arizona 

Arkansas 

California 

Colorado 

Connecticut 

Delaware 

Dis! of Columbia 

Florida 

Georgia 

Hawaii 

Idaho 

Illinois 

Indiana 

Iowa 

Kansas 

Kentucky 

Louisiana 

Maine 

Maryland 

Massachusetts 

Michigan 

Minnesota 

Mississippi 

Missouri 

Montana 

Nebraska 

Nevada 

New Hampshire 

New Jersey 

New Mexico 

New York 

North Carolina 

N ortb Dakota 

Ohio 

Oklahoma 

Oregon 

Pennsylvania 

Rhode Island 

South Carolina 

South Dakota 

Tennessee 

Texas 

Utah 

Vermont 

Percentage 

of All 

Firms 

0.94% 

8.29% 

1.72% 

1.09% 

1.31% 

0.85% 

0,40% 

nla 

0,47% 

0.64% 

0.66% 

0.90% 

0.94% 

0.35% 

0,45% 

0.27% 

0.79% 

0,44% 

0,82% 

0.50% 

0,81% 

0,40% 

0.73% 

0.62% 

0.36% 

0.75% 

1.98% 

0.29% 

1.12% 

0,42% 

0.37% 

4.99% 

0.65% 

0.93% 

1.50% 

0.38% 

5,86% 

1.02% 

nla 

0.51% 

0,49% 

1.87% 

0,78% 

0.93% 

0.59% 

0,41% 

Percentage 

of AI! Sales 

0.18% 

6,02% 

0.17% 

0.19% 

0.14% 

0.14% 

0.04% 

nla 

0.05% 

0.06% 

0.08% 

0.15% 

0.28% 

0.04% 

0.05% 

0.04% 

0.15% 

0.03% 

0.10% 

0.06% 

0.11% 

0.06% 

0.09% 

0.07% 

0.05% 

0.08% 

0.48% 

0.03% 

0.14% 

0.06% 

0.03% 

0,52% 

0,04% 

0.10% 

0.29% 

0.05% 

1.28% 

0.14% 

nla 

0.04% 

0.06% 

0.22% 

0.15% 

0,17% 

0,06% 

0.11% 

Percentage 

of AI! 

Employers 

0.69% 

4.76% 

0,49% 

0.50% 

0.54% 

0.50% 

n/a 

nla 

033% 

0.23% 

0.42% 

nla 

0.54% 

0.20% 

0.27% 

nla 

0.60% 

0.15% 

030% 

0.32% 

0.35% 

0.24% 

0,40% 

0,43% 

nla 

039% 

1.26% 

0.11% 

0.59% 

0.29% 

0.18% 

LI4% 

0.23% 

0.55% 

0.55% 

0.20% 

3.53% 

0.53% 

nla 

0.13% 

0.32% 

0.73% 

0,38% 

0.61% 

0.36% 

0.18% 

Percentage 

ofAl! 

Employer 

Sales 

0.16% 

6.07% 

0.14% 

0.16% 

0.11% 

0.11% 

nla 

nla 

0,05% 

0.04% 

0.06% 

nla 

0.26% 

0.03% 

0.05% 

nla 

0.14% 

0.02% 

0.08% 

0.05% 

0.09% 

0.05% 

0.08% 

0.06% 

nla 

0.06% 

0,43% 

0.03% 

0.10% 

0.05% 

0.02% 

0,45% 

0.03% 

0.07% 

0.26% 

0.05% 

LIO% 

0.10% 

nla 

0.02% 

0.05% 

0.21% 

0.12% 

0.15% 

0.05% 

0.10% 

Disparity 

Ratio-All 

Firms 

0.19 

0,73 

0.10 

0,18 

O,ll 

0,16 

0.09 

0./0 

0.09 

0.12 

0,17 

0,3(} 

O,ll 

0,12 

0.13 

0,20 

0.06 

0.12 

0.13 

0.13 

0.14 

0.12 

O.ll 

0,12 

0,10 

0.24 

0.11 

0,13 

0,15 

0,09 

(},11 

0,06 

(},11 

0,19 

0.14 

0.22 

0,13 

0,08 

0.12 

0.12 

0.19 

0,19 

0,09 

0.27 

Disparity 

Ratio 

Employers 

0,23 

1.28 

0,29 

0.31 

0,20 

(},23 

0,14 

0,16 

0,15 

0.48 

0,16 

0,/7 

0.24 

(},11 

0,27 

0,15 

0.24 

0,20 

0,19 

0,15 

0.14 

0,34 

0.25 

0,/7 

0,17 

0,14 

0.39 

0,/3 

0,14 

0.48 

0,23 

0,31 

0,20 

0,19 

(},16 

0,28 

0.32 

0,25 

0,13 

0,54 

17 
201 

NERA Economic Consu!tlng 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Virginia 0.50% 0.08% 0.36% 0.07% 0.17 0.19 

Washington 1.23% 0.22% 0.72% 0.19% 0.18 0.27 

West Virginia 0.36% 0.04% 0.30% 0.03% 0.11 0.09 

Wisconsin 0.64% 0.10% 0.35% 0.09% 0.15 0.25 

Wyoming 1.12% 0.18% 0.87% 0.15% 0.16 0./8 

Notes: See Table lAo 

18 
202 

NERA Economic Consulting 

Table IE. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Native Hawaiians and Pacific Islanders, All Industries, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 0.03% 0.00% 0.01% 0.00% 0.06 0.24 

Alaska 0.24% 0.02% 0.22% nla 0.09 

Arizona 0.09% 0.01% 0.07% 0.01% 0.13 0.14 

Arkansas 0.03% 0.00% nla nla 0.09 

California 0.24% 0.04% 0.15% 0.03% 0.18 0.22 

Colorado 0.08% 0.01% 0.05% 0.01% O.II 0.16 

Connecticut 0.06% 0.02% nla nla 0.36 

Delaware 0.03% nla nla nla 

Dist of Columbia nla nfa nla nla 

Florida 0.10% 0.01% 0.04% 0.00% 0.07 0.13 

Georgia 0.03% 0.00% 0.03% 0.00% 0.13 0.08 

Hawaii 8.42% 2.16% 4.26% 1.98% 0.26 0.46 

Idaho 0.08% 0.01% nla nla 0.15 

Illinois 0.07% nla nla nla 

Indiana 0.03% 0.02% nla nla 0.61 

Iowa 0.01% 0.00% 0.00% nla 0.39 

Kansas 0.02% 0.01% nla nla 0.42 

Kentucky 0.02% nla 0.00% nla 

Louisiana nla nla nla nla 

Maine nla nla nla nla 

Maryland 0.02% nla 0.04% 0.01% 0.24 

Massachusetts nla nla nla nla 

Michigan 0.03% 0.00% nla nla 0.17 

Minnesota nla nla nla nla 

Mississippi 0.07% 0.00% nla nla 0.07 

Missouri 0.02% 0.01% nla nla 0.35 

Montana 0.04% 0.00% nla nla 0.12 

Nebraska 0.01% nla 0.00% 0.00% 

Nevada 0.18% 0.04% nla nla 0.20 

New Hampshire 0.01% nla nla nla 

New Jersey 0.06% 0.00% nla nla 0.07 

New Mexico 0.10% 0.02% nla nla 0.19 

New York 0.18% 0.01% 0.D4% nla 0.04 

North Carolina 0.03% 0.00% nla nla 0.07 

North Dakota 0.00% nla 0.00% 0.00% 

Ohio nla nla nla nla 

Oklahoma 0.10% 0.00% 0.03% 0.00% 0.05 0.10 

Oregon 0.12% 0.02% 0.08% 0.02% 0.18 0.21 

Pennsylvania 0.03% 0.00% nla nla 0.13 

Rhode Island nla nla nla nla 

South Carolina 0.01% 0.00% nla nla 0.29 

South Dakota 0.02% nla 0.01% nla 

Tennessee nla nla nla nla 

Texas 0.08% 0.00% nla nla 0.05 

Utah 0.22% 0.10% 0.18% 0.10% 0.47 0.58 

Vermont nla nla nla nla 

19 
203 

NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Virginia 0.08% 0.03% 0.07% nla 0.32 

Washington 0.16% 0.05% 0.09% 0.05% 0.33 0.55 

West Virginia 0.01% nla 0.00% 0.00% 

Wisconsin 0.03% 0.00% 0.01% 0.00% 0.03 0.12 

Wyoming 0.04% 0.00% 0.00% 0.00% 0.04 

Notes: See Table IA. 

20 
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NERA Economic Consulting 

Table IF. Percentage or Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Women, All Industries, 2002 

State 

Alabama 

Alaska 

Arizona 

Arkansas 

California 

Colorado 

Connecticut 

Delaware 

Dist of Columbia 

Florida 

Georgia 

Hawaii 

Idaho 

Illinois 

Indiana 

Iowa 

Kansas 

Kentucky 

Louisiana 

Maine 

Maryland 

Massachusetts 

Michigan 

Minnesota 

Mississippi 

Missouri 

Montana 

Nebraska 

Nevada 

New Hampshire 

New Jersey 

New Mexico 

New York 

North Carolina 

North Dakota 

Ohio 

Oklahoma 

Oregon 

Pennsylvania 

Rhode Island 

South Carolina 

South Dakota 

Tennessee 

Texas 

Utah 

Vermont 

Percentage 

of AI! 

Firms 

26.43% 

26.24% 

28.79% 

23.74% 

29.93% 

29.08% 

27.23% 

24.14% 

33.23% 

28.41% 

29.09% 

30.18% 

23.71% 

29.74% 

27.39% 

26.98% 

27.18% 

25.66% 

26.43% 

24.01% 

30.98% 

28.73% 

29.59% 

27.92% 

25.11% 

27.41% 

24.42% 

26.61% 

28.13% 

24.74% 

26.13% 

30.91% 

29.59% 

27.06% 

23.25% 

28.12% 

25.73% 

29.49% 

25.98% 

26.52% 

26.22% 

22.40% 

25.96% 

27.02% 

25.12% 

26.26% 

Percentage 

of All Sales 

4.29% 

5.08% 

4.83% 

3.85% 

4.92% 

4.25% 

3.14% 

1.74% 

2.25% 

5.70% 

4.06% 

6.91% 

4.42% 

4.08% 

3.41% 

3.17% 

3.02% 

3.33% 

3.76% 

4.40% 

4.63% 

3.57% 

3.68% 

3.52% 

4.79% 

4.14% 

4.79% 

4.16% 

5.86% 

4.99% 

4.19% 

5.44% 

4.10% 

4.43% 

3.12% 

3.61% 

4.69% 

4.21% 

4.09% 

5.48% 

4.29% 

2.58% 

4.04% 

3.63% 

4.06% 

3.64% 

Percentage 

of AI! 

Employers 

15.77% 

18.87% 

16.60% 

14.92% 

17.18% 

18.36% 

14.66% 

14.86% 

17.92% 

18.09% 

17.02% 

19.32% 

13.72% 

16.53% 

14.77% 

14.04% 

15.78% 

15.01% 

15.54% 

14.88% 

17.24% 

15.88% 

15.61% 

14.71% 

15.67% 

16.69% 

16.41% 

14.95% 

15.36% 

15.80% 

15.46% 

18.54% 

15.74% 

16.14% 

11.87% 

15.11% 

15.97% 

16.30% 

15.28% 

14.40% 

15.55% 

13.61% 

14.78% 

17.43% 

12.69% 

13.41% 

Percentage 

of AI! 

Employer 

Sales 

3.870/0 

4.53% 

4.26% 

3.50% 

4.25% 

3.69% 

2.68% 

1.45% 

n1a 

5.01% 

3.60% 

6.17% 

3.96% 

3.69% 

3.07% 

2.86% 

2.68% 

2.95% 

3.36% 

3.83% 

3.99% 

3.07% 

3.29% 

3.15% 

4.27% 

3.80% 

4.16% 

3.91% 

5.17% 

4.56% 

3.79% 

4.81% 

3.55% 

4.02% 

2.74% 

3.23% 

4.25% 

3.66% 

3.76% 

4.92% 

3.86% 

2.31% 

3.61% 

3.18% 

3.66% 

3.00% 

Disparity 

Ratio-All 

Finns 

0.16 

0.19 

0.17 

0.16 

0.16 

0.15 

0.12 

0.07 

0.07 

0.20 

0.14 

0.23 

0.19 

0.14 

0.12 

0.12 

O.ll 

0.13 

0.14 

0.18 

0.15 

0.12 

0.12 

0.13 

0.19 

0.15 

0.20 

0.16 

0.21 

0.20 

0.16 

0.18 

0.14 

0.16 

0.13 

0.13 

0.18 

0.14 

0.16 

0.21 

0.16 

0.12 

0.16 

0.13 

0.16 

0.14 

Disparity 

Ratio 

Employers 

0.25 

0.24 

0.26 

0.23 

0.25 

0.20 

0.18 

0.10 

0.28 

0.21 

0.32 

0.29 

0.22 

0.21 

0.20 

0.17 

0.20 

0.22 

0.26 

0.23 

0.19 

0.21 

0.21 

0.27 

0.23 

0.25 

0.26 

0.34 

0.29 

0.24 

0.26 

0.23 

0.25 

0.23 

0.21 

0.27 

0.22 

0.25 

0.34 

0.25 

0.17 

0.24 

0.18 

0.29 

0.22 

21 
205 

State 

Virginia 

Washington 

West Virginia 

Wisconsin 

Wyoming 

Notes: See Table lA. 

Percentage 

of All 

Firms 

29.66% 

29.40% 

27.68% 

26.49% 

24.38% 

Percentage Percentage of All of All Sales Employers 

3.96% 17.35% 

3.88% 16.21% 

3.82% 14.76% 

4.03% 14.99% 

3.37% 15.63% 

NERA Economic Consulting 

Percentage Disparity Disparity of All Ratio-All Ratio Employer Finns Employers Sales 

3.52% 0.13 0.20 

3.41% 0.13 0.21 

3.38% 0.14 0.23 

3.75% 0.15 0.25 

nla 0.14 

22 
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NERA EconomIC Consulting 

Table 2A. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, African Americans, Forestry, Fishing, Hunting & Agricultural Support Services, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage ofAl! of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 4.73% 1.54% 2.74% 1.11% 0.33 0.40 

Alaska 

Arizona 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Arkansas 2.96% 0.61% 0.21 

California 0.49% 0.04% 0.08 

Colorado 

Connecticut 

Delaware 0.00% 0.00% 

District of Columbia 

Florida 2.41% 1.47% 0.61 

Georgia 4.42% 1.41% 2.77% 0.32 

Hawaii 

Idaho 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Illinois 

Indiana 

Iowa 0.08% 0.00% 

Kansas 

Kentucky 

Louisiana 3.26% 1.83% 0.56 

Maine 

Maryland 

Massachusetts 

Michigan 

Minnesota 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Mississippi 13.29% 3.89% 4.86% 2.85% 0.29 0.59 

Missouri 0.00% 0.00% 

Montana 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Nebraska 

Nevada 

New Hampshire 0.05% 0.00% 

New Jersey 0.72% 0.00% 

New Mexico 0.28% 

New York 

North Carolina 2.99% 1.38% 1.58% 0.46 

North Dakota 0.08% 0.00% 

Ohio 0.18% 0.00% 0.00% 0.00 

Oklahoma 0.00% 0.00% 0.00% 0.00 

23 
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NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Finns Employers Sales 

Oregon 0.01% 0.00% 0.00% 0.00 

Pennsylvania 

Rhode Island 

South Carolina 7.25% 3.58% 6.89% 3.36% 0.49 0.49 

South Dakota 0.06% 0.00% 

Tennessee 0.48% 0.34% 0.00% 0.00% 0.69 0.00 

Texas 1.86% 

Utah 0.00% 0.00% 0.00% 0.00 

Vermont 

Virginia 4.35% 5.50% 

Washington 

West Virginia 0.55% 0.14% 0.00% 0.00% 0.26 0.00 

Wisconsin 0.01% 0.00% 0.00% 0.00 

0.00% 0.00% 

24 
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NERA Economic Consulting 

Table 2B. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Hispanics and Latinos, Forestry, Fishing, Hunting & Agricultural Support Services, 2002 

Percentage Percentage Percentage Disparity Disparity 

State ofAH Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 1.03% 0.21% 0.35% 0.09% 0.20 0.26 

Alaska 1.23% 

Arizona 8.93% 16.54% 

Arkansas 

California 13.74% 16.12% 17.58% 16.86% 1.17 0.96 

Colorado 2.69% 4.22% 

Connecticut 0.83% 0.00% 

Delaware 

District of Columbia 2.63% 0.00% 

Florida 12.61% 8.81% 10.51% 8.92% 0.70 0.85 

Georgia 2.28% 

Hawaii 

Idaho 2.45% 3.64% 

minois 

Indiana 0.21% 

Iowa 

Kansas 1.50% 0.00% 0.00% 0.00 

Kentucky 

Louisiana 

Maine 

Maryland 0.91% 

Massachusetts 0.85% 0.23% 

Michigan 

Minnesota 

Mississippi 0.19% 0.22% 

Missouri 

Montana 0.18% 0.21% 

Nebraska 

Nevada 

New Hampshire 0.00% 0.00% 0.00% 0.00 

New Jersey 1.88% 

New Mexico 18.88% 17.29% 

New York 

North Carolina 0.90% 0.37% 

North Dakota 0.00% 0.00% 

Ohio 0.60% 0.53% 0.26% 0.87 

Oklahoma 2.93% 

25 
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NERA EconomIC Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 1.73% 4.24% 3.74% 2.45 

Pennsylvania 

Rhode Island 

South Carolina 

South Dakota 2.13% 2.29% 

Tennessee 

Texas 16.57% 7.33% 

Utah 

Vermont 

Virginia 1.04% 0.38% 

Washington 1.96% 1.22% 2.32% 0.62 

West Virginia 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Wisconsin 0.38% 0.00% 0.00% 0.00 

26 
210 

NERA Economic Consulting 

Table 2C. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Asians, Forestry, Fishing, Hunting & Agricultural Support Services, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 3.44% 0.23% 0.00% 0.00% 0.07 0.00 

Alaska 

Arizona 

Arkansas 

California 4.36% 4.10% 4.44% 4.17% 0.94 0.94 

Colorado 

Connecticut 0.53% 0.00% 

Delaware 1.43% 2.17% 

District of Columbia 5.26% 0.00% 

Florida 1.73% 0.65% 0.07% 0.38 

Georgia 

Hawaii 41.09% 23.08% 

Idaho 

Illinois 0.35% 0.00% 0.00% 0.00 

Indiana 0.00% 0.00% 

Iowa 

Kansas 

Kentucky 

Louisiana 12.03% 6.85% 0.00% 0.00% 0.57 0.00 

Maine 

Maryland 0.85% 0.00% 

Massachusetts 0.57% 0.00% 

Michigan 

Minnesota 

Mississippi 9.18% 4.21% 0.00% 0.00% 0.46 0.00 

Missouri 

Montana 

Nebraska 

Nevada 2.00% 1.47% 

New Hampshire 

New Jersey 1.16% 0.39% 

New Mexico 

New York 

North Carolina 1.66% 0.72% 0.44 

North Dakota 

Ohio 0.49% 0.38% 0.00% 0.00% 0.78 000 

Oklahoma 0.00% 0.00% 0.00% 0.00 

27 
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NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Finns Employers Sales 

Oregon 0.34% 

Pennsylvania 0.40% 0.00% 0.00% 0.00 

Rhode Island 

South Carolina 

South Dakota 0.00% 0.00% 

Tennessee 0.21% 

Texas 8.90% 0.00% 

Utah 

Vermont 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Virginia 

Washington 1.28% 0.63% 0.49 

West Virginia 0.06% 0.00% 0.00% 0.00 

Wisconsin 0.33% 

0.00% 0.00% 

28 
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NERA Economic Consulting 

Table 20. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, American Indians and Alaska Natives, Forestry, Fishing, Hunting & Agricultural Support Services, 

2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 1.00% 

Alaska 25.38% 11.67% 5.93% 11.66% 0.46 1.96 

Arizona 

Arkansas 

California 

Colorado 1.79% 0.00% 

Connecticut 

Delaware 0.00% 0.00% 

District of Columbia 2.63% 0.00% 

Florida 0.69% 0.11% 0.16 

Georgia 

Hawaii 0.23% 0.00% 

Idaho 

Illinois 0.58% 

Indiana 0.34% 

Iowa 0.00% 0.00% 0.00% 0.00 

Kansas 

Kentucky 1.07% 0.00% 0.00% 0.00 

Louisiana 3.48% 1.62% 0.00% 0.00% 0.47 0.00 

Maine 0.31% 0.39% 0.25% 1.24 

Maryland 0.00% 0.00% 

Massachusetts 0.38% 0.00% 

Michigan 1.27% 

Minnesota 0.68% 0.27% 0.00% 0.00% 0.40 0.00 

Mississippi 

Missouri 1.17% 0.27% 

Montana 1.55% 1.55% 1.07% 1.25% 1.00 1.17 

Nebraska 

Nevada 1.29% 0.00% 

New Hampshire 0.20% 0.00% 

New Jersey 

New Mexico 7.86% 1.27% 0.00% 0.00% 0.16 0.00 

New York 

North Carolina 

North Dakota 1.46% 0.00% 

Ohio 0.38% 0.00% 0.00% 

29 
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NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Finns Employers Sales 

Oklahoma 6.97% 1.50% 0.00% 0.21 

Oregon 

Pennsylvania 0.18% 

Rhode Island 0.07% 0.00% 0.00% 0.00 

South Caro I ina 

South Dakota 0.06% 0.00% 

Tennessee 0.80% 0.27% 

Texas 

Utah 0.77% 0.00% 

Vermont 

Virginia 

Washington 2.49% 0.88% 1.58% 0.87% 0.35 0.55 

West Virginia 

Wisconsin 0.32% 0.33% 1.04 

30 
214 

NERA EconomIC Consulting 

Table 2E. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Native Hawaiians and Pacific Islanders, Forestry, Fishing, Hunting & Agricultural Support Services, 

2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alahama 0.02% 0.00% 0.00% 0.00 

Alaska 

Arizona 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Arkansas 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

California 

Colorado 0.00% 0.00% 

Connecticut 0.00% 0.00% 0.00% 0.00 

Delaware 0.00% 0.00% 

District of Columbia 0.00% 0.00% 

Florida 0.37% 0.00% 0.00% 0.00 

Georgia 0.02% 0.00% 0.00% 0.00 

Hawaii 19.54% 

Idaho 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Illinois 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Indiana 0.00% 0.00% 

Iowa 0.00% 0.00% 0.00% 0.00 

Kansas 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Kentucky 0.00% 0.00% 0.00% 0.00 

Louisiana 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Maine 

Maryland 0.00% 0.00% 

Massachusetts 0.00% 0.00% 0.00% 0.00 

Michigan 0.00% 0.00% 

Minnesota 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Mississippi 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Missouri 0.00% 0.00% 

Montana 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Nebraska 0.00% 0.00% 0.00% 0.00 

Nevada 

New Hampshire 0.00% 0.00% 0.00% 0.00 

New Jersey 0.00% 0.00% 0.00% 0.00 

New Mexico 0.07% 0.00% 0.00% 0.00 

New York 

North Carolina 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

North Dakota 0.00% 0.00% 

Ohio 0.00% 0.00% 0.00% 0.00% 

31 
215 

NERA Economic Consu!ting 

----------_. 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oklahoma 0.00% 0.00% 0.00% 0.00 

Oregon 

Pennsylvania 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Rhode Island 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

South Carolina 

South Dakota 0.00% 0.00% 

Tennessee 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Texas 0.00% 0.00% 

Utah 0.00% 0.00% 0.00% 0.00 

Vermont 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Virginia 0.00% 0.00% 

Washington 

West Virginia 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Wisconsin 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

0.00% 0.00% 

32 
216 

NERA Economic Consulting 

Table 2F. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Women, Forestry, Fishing, Hunting & Agricultural Support Services, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 6.06% 1.90% 4.15% 1.77% 0.31 0.43 

Alaska 10.98% 5.59% 15.13% 6.59% 0.51 0.44 

Arizona 12.00% 6.26% 9.06% 5.42% 0.52 0.60 

Arkansas 10.01% 6.49% 0.65 

California 12.20% 8.33% 10.19% 8.04% 0.68 0.79 

Colorado 8.86% 9.34% 

Connecticut 8.37% 

Delaware 6.15% 2.17% 

District of Columbia 18.42% 0.00% 

Florida 13.47% 13.10% 17.54% 12.82% 0.97 0.73 

Georgia 7.76% 4.32% 7.81% 0.56 

Hawaii 8.08% 

Idaho 8.86% 3.06% 0.35 

lllinois 7.97% 5.28% 7.66% 0.66 

Indiana 

Iowa 9.94% 6.58% 0.66 

Kansas 5.47% 2.75% 

Kentucky 12.57% 

Louisiana 9.61% 5.85% 0.61 

Maine 7.02% 3.67% 2.75% 3.50% 0.52 1.27 

Maryland 8.51% 

Massachusetts 9.01% 8.45% 18.86% 0.94 

Michigan 12.82% 

Minnesota 8.83% 2.74% 0.31 

Mississippi 7.60% 6.79% 7.34% 6.44% 0.89 0.88 

Missouri 5.06% 

Montana 7.62% 5.09% 0.67 

Nebraska 9.58% 6.02% 

Nevada 12.30% 27.94% 

New Hampshire 4.63% 7.94% 12.96% 1.71 

New Jersey 10.47% 13.73% 

New Mexico 17.33% 2.29% 0.13 

New York 12.93% 5.62% 10.94% 0.43 

North Carolina 9.48% 4.40% 7.14% 0.46 

North Dakota 9.16% 

Ohio 10.06% 4.10% 4.87% 0.41 

Oklahoma 12.57% 15.30% 3.80% 1.22 

33 
217 

NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Finns Employers Sales 

Oregon 12.21% 5.34% 8.48% 4.25% 0.44 0.50 

Pennsylvania 11.91% 4.93% 7.59% 0.41 

Rhode Island 3.81% 3.36% 0.88 

South Carolina 10.58% 7.59% 0.72 

South Dakota 

Tennessee 6.29% 5.41% 0.86 

Texas 8.14% 10.75% 

Utah 5.50% 12.00% 

Vermont 6.31% 

Virginia 11.08% 14.63% 

Washington 10.93% 2.86% 5.59% 0.26 

West Virginia 

Wisconsin 10.83% 3.95% 0.36 

8.90% 

34 
218 

NERA Economic Consulting 

Table 3A. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, African Americans, Mining, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage ofAl! of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 0.30% 0.00% 0.00% 0.00 

Alaska 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Arizona 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Arkansas 

California 0.87% 0.07% 0.83% 0.08 

Colorado 0.03% 0.11% 

Connecticut 0.00% 0.00% 

Delaware 0.00% 0.00% 

District of Columbia 28.57% 0.00% 

Florida 0.45% 0.00% 

Georgia 

Hawaii 0.00% 0.00% 

Idaho 0.00% 0.00% 0.00% 0.00 

I!Iinois 

Indiana 

Iowa 0.00% 0.00% 

Kansas 0.15% 0.00% 0.00% 0.00 

Kentucky 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Louisiana 

Maine 0.00% 0.00% 

Maryland 2.90% 0.00% 0.00% 0.00 

Massachusetts 0.00% 0.00% 0.00% 0.00 

Michigan 

Minnesota 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Mississippi 

Missouri 0.00% 0.00% 0.00% 0.00 

Montana 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Nebraska 0.38% 0.00% 

Nevada 0.77% 0.52% 

New Hampshire 0.00% 0.00% 

New Jersey 

New Mexico 

New York 0.67% 

North Carolina 1.38% 0.00% 0.00% 0.00 

North Dakota 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Ohio 0.40% 0.00% 0.00% 0.00 

Oklahoma 

35 
219 

NERA EconomIC Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 0.00% 0.00% 

Pennsylvania 0.14% 0.00% 0.00% 0.00 

Rhode Island 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

South CaroUna 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

South Dakota 0.00% 0.00% 0.00% 0.00 

Tennessee 

Texas 

Utah 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Vermont 0.00% 0.00% 

Virginia 

Washington 0.00% 0.00% 

West Virginia 0.26% 0.01% 0.00% 0.00% 0.05 0.00 

Wisconsin 0.00% 0.00% 0.00% 0.00% 000 0.00 

0.06% 0.14% 

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Table 3B. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Hispanics and Latinos, Mining, 2002 

Percentage Percentage Percentage Disparity Disparity Percentage of All State of AI! of All Sales of All Employer Ratio-All Ratio 

Finns Employers Sales Firms Employers 

Alabama 

Alaska 0.32% 0.00% 0.00% 0.00 

Arizona 8.46% 

Arkansas 

California 2.24% 0.17% 2.48% 0.08 

Colorado 

Connecticut 1.52% 0.00% 

Delaware 0.00% 0.00% 

District of Columbia 0.00% 0.00% 

Florida 

Georgia 0.42% 0.70% 

Hawaii 0.00% 0.00% 

Idaho 0.80% 0.00% 

Illinois 

Indiana 0.21% 0.42% 

Iowa 0.00% 0.00% 

Kansas 0.88% 0.25% 0.29 

Kentucky 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Louisiana 

Maine 0.00% 0.00% 

Maryland 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Massachusetts 1.20% 

Michigan 0.04% 0.24% 

Minnesota 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Mississippi 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Missouri 0.19% 0.00% 

Montana 0.13% 0.00% 0.00% 0.00 

Nebraska 

Nevada 1.16% 

New Hampshire 0.00% 0.00% 

New Jersey 3.80% 0.00% 0.00% 0.00 

New Mexico 4.23% 0.19% 5.25% 0.16% 0.05 0.03 

New York 

North Carolina 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

North Dakota 0.23% 0.00% 0.00% 0.00 

Ohio 0.32% 0.03% 0.10 

Oklahoma 0.53% 0.00% 0.00% 0.00 

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Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Finns Employers Sales 

Oregon 

Pennsylvania 

Rhode Island 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

South Carolina 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

South Dakota 0.00% 0.00% 0.00% 0.00 

Tennessee 1.06% 0.00% 0.00% 0.00 

Texas 2.73% 0.55% 0.20 

Utah 0.33% 0.34% 

Vermont 0.00% 0.00% 

Virginia 0.44% 

Washington 

West Virginia 0.29% 

Wisconsin 0.35% 0.00% 0.00% 0.00 

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Table 3C. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Asians, Mining, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 0.15% 0.00% 0.00% 0.00 

Alaska 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Arizona OA3% 

Arkansas 0.08% 0.39% 

California 2.27% OA1% 

Colorado 

Connecticut 0.00% 0.00% 

Delaware 0.00% 0.00% 

District of Columbia 0.00% 0.00% 

Florida 0.23% 0.00% 

Georgia 

Hawaii 15.38% lLlI% 

Idaho OAO% 0.00% 

Illinois 

Indiana 

Iowa 0.00% 0.00% 

Kansas 0.02% 0.12% 

Kentucky 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Louisiana 0.16% 

Maine 0.00% 0.00% 

Maryland IAS% 0.00% 0.00% 0.00 

Massachusetts 0.00% 0.00% 0.00% 0.00 

Michigan 0.26% 

Minnesota 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Mississippi 0.06% 0.00% 0.00% 0.00 

Missouri 

Montana 0.13% 0.00% 0.00% 0.00 

Nebraska 0.38% 0.00% 

Nevada 0.19% 0.00% 0.00% 0.00 

New Hampshire 0.00% 0.00% 

New Jersey 0.63% 0.00% 0.00% 0.00 

New Mexico 0.86% 0.04% IAO% 0.04% 0.05 0.03 

New York 3.76% 0.00% 0.00% 0.00 

North Carolina 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

North Dakota 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Ohio 0.90% 

Oklahoma 0.34% 0.03% 0.08 

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Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 0.00% 0.00% 

Pennsylvania 0.42% 

Rhode Island 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

South Carolina 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

South Dakota 0.93% 0.00% 

Tennessee 0.21% 0.00% 0.00% 0.00 

Texas 0.32% 0.14% 0.51% 0.45 

Utah 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Vermont 0.00% 0.00% 

Virginia 

Washington 

West Virginia 

Wisconsin 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

0.28% 0.42% 

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Table 3D. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, American Indians and Alaska Natives, Mining, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of AI! Percentage of AI! of AI! Ratio-All Ratio 

Firms of AI! Sales Employers Employer Firms Employers Sales 

Alabama 1.22% 0.00% 0.00% 0.00 

Alaska 4.46% 4.35% 

Arizona 0.65% 0.00% 0.00% 0.00 

Arkansas 0.34% 0.39% 

California 

Colorado 

Connecticut 

Delaware 0.00% 0.00% 

District of Columbia 0.00% 0.00% 

Florida 

Georgia 

Hawaii 0.00% 0.00% 

Idaho 0.80% 0.00% 

Illinois 

Indiana 0.00% 0,00% 0.00% 0.00 

Iowa 0.00% 0.00% 

Kansas 0.24% 0.04% 0.00% 0.00% 0.15 0.00 

Kentucky 0.10% 0.00% 0.00% 0.00 

Louisiana 0.89% 0.15% 0.17 

Maine 0.00% 0.00% 

Maryland 0.00% 0.00% 0.00% 0.00% 0,00 0,00 

Massachusetts 0.00% 0.00% 0.00% 0.00 

Michigan 0.00% 0.00% 0.00% 0.00% 0,00 0,00 

Minnesota 0.00% 0.00% 0.00% 0.00% 0.00 0,00 

Mississippi 0.36% 

Missouri 0.00% 0.00% 0,00% 0.00 

Montana 0.63% 

Nebraska 0.38% 0.00% 

Nevada 0.77% 

New Hampshire 0.00% 0.00% 

New Jersey 

New Mexico 0.64% 

New York 

North Carolina 0.00% 0.00% 0.00% 0.00% 0.00 0,00 

North Dakota 0.23% 0.00% 0.00% 000 

Ohio 0.00% 0.00% 0,00% 0.00% 0.00 0.00 

Oklahoma 3.26% 0.63% 2.63% 0.56% 0.19 0,21 

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Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 4.58% 

Pennsylvania 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Rhode Island 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

South Carolina 

South Dakota 0.00% 0.00% 0.00% 0.00 

Tennessee 0.21% 0.00% 0.00% 0.00 

Texas 0.85% 0.06% 0.07 

Utah 0.49% 

Vermont 0.00% 0.00% 

Virginia 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Washington 

West Virginia 

Wisconsin 0.35% 0.61% 

0.57% 0.28% 

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Table 3E. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Native Hawaiians and Pacific Islanders, Mining, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 0.00% 0.00% 0,00% 0.00% 0,00 0.00 

Alaska 0.00% 0.00% 0.00% 0.00% 0,00 0.00 

Arizona 0.00% 0.00% 0,00% 0.00% 0.00 0,00 

Arkansas 0,00% 0,00% 0.00% 0.00% 0,00 0.00 

California 0.00% 0.00% 0.00% 0,00% 0,00 0,00 

Colorado 0.00% 0,00% 0.00% 0.00% 0,00 0,00 

Connecticut 0.00% 0.00% 

Delaware 0.00% 0.00% 

District of Columbia 0.00% 0.00% 

Florida 0.00% 0.00% 

Georgia 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Hawaii 15.38% 22.22% 

Idaho 0.00% 0.00% 0.00% 0,00 

Illinois 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Indiana 0.00% 0.00% 0.00% 0,00 

Iowa 0,00% 0.00% 

Kansas 0.02% 0.12% 

Kentucky 0.00% 0.00% 0,00% 0.00% 0.00 0,00 

Louisiana 0.00% 0.00% 0.00% 0.00% 0.00 0,00 

Maine 0.00% 0.00% 

Maryland 0.00% 0,00% 0.00% 0.00% 0.00 0,00 

Massachusetts 0.00% 0.00% 0.00% 0.00 

Michigan 0.00% 0,00% 0.00% 0.00% 0,00 0,00 

Minnesota 0.00% 0.00% 0.00% 0,00% 0,00 0.00 

Mississippi 0,00% 0.00% 0.00% 0.00% 0,00 0,00 

Missouri 0.00% 0,00% 0.00% 0,00 

Montana 0.00% 0.00% 0.00% 0.00% OJ)O 000 

Nebraska 0.00% 0.00% 

Nevada 0.19% 0.00% 0.00% 0,00 

New Hampshire 0.00% 0.00% 

New Jersey 0.00% 0.00% 0,00% 0.00% 0,00 0,00 

New Mexico 0.00% 0.00% 0.00% 0,00% 0,00 0.00 

New York 0.00% 0.00% 0.00% 0.00% 0.00 0,00 

North Carolina 0.00% 0.00% 0.00% 0.00% 0,00 0,00 

North Dakota 0.00% 0.00% 0.00% 0.00% 0,00 0,00 

Ohio 0.00% 0.00% 0.00% 0.00% 0.00 0,00 

Oklahoma 0.00% 0.00% 0.00% 0.00% 0.00 0,00 

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Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Finns Employers Sales 

Oregon 0.00% 0.00% 

Pennsylvania 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Rhode Island 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

South Carolina 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

South Dakota 0.00% 0.00% 0.00% 0.00 

Tennessee 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Texas 

Utah 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Vermont 0.00% 0.00% 

Virginia 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Washington 0.00% 0.00% 

West Virginia 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Wisconsin 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

0.00% 0.00% 0.00% 0.00% 0.00 0.00 

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Table 3F. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Women, Mining, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

firms of All Sales Employers Employer firms Employers Sales 

Alabama 10.52% 1.18% 0.11 

Alaska 6.37% 0.10% 6.96% 0.02 

Arizona 14.75% 3.75% 0.25 

Arkansas 13.36% 3.24% 8.24% 2.78% 0.24 0.34 

California 15.90% 1.40% 0.09 

Colorado 13.84% 1.15% 5.62% 0.85% 0.08 0.15 

Connecticut 16.67% 

Delaware 19.05% 23.53% 

District of Columbia 14.29% 0.00% 

florida 13.06% 4.53% 

Georgia 9.62% 

Hawaii 7.69% 11.11% 

Idaho 8.03% 9.03% 1.12 

Illinois 14.59% 1.22% 9.30% 0.08 

Indiana 12.41% 4.20% 

Iowa 9.68% 12.94% 

Kansas 15.74% 3.91% 14.04% 3.17% 0.25 0.23 

Kentucky 9.82% 1.08% 2.38% 0.11 

Louisiana 10.56% 0.52% 4.16% 0.47% 0.05 0.11 

Maine 11.61% 14.29% 

Maryland 7.97% 6.33% 

Massachusetts 7.19% 

Michigan 12.29% 3.35% 4.33% 3.17% 0.27 0.73 

Minnesota 6.05% 2.01% 

Mississippi 9.53% 3.96% 5.49% 4.02% 0.42 0.73 

Missouri 

Montana 11.31% U6% 8.89% 0.10 

Nebraska 14.23% 

Nevada 10.83% 0.38% 0.04 

New Hampshire 

New Jersey 8.86% 

New Mexico 12.10% 0.80% 10.86% 0.71% 0.07 0.07 

New York 4.35% 5.63% 

North Carolina 10.38% 

North Dakota 5.03% 2.20% 

Ohio 11.42% 4.02% 12.95% 3.64% 0.35 0.28 

Oklahoma 13.59% 6.50% 8.84% 6.28% 0.48 0.71 

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Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 9.86% 11.51% 

Pennsylvania 6.56% 4.62% 4.87% 0.70 

Rhode Island 

South Carolina 7.45% 3.57% 

South Dakota 6.54% 2.38% 12.28% 0.36 

Tennessee 8.26% 3.49% 2.01% 0.42 

Texas 14.28% 0.72% 9.86% 0.58% 0.05 0.06 

Utah 7.52% 0.97% 3.77% 0.13 

Vermont 

Virginia 10.04% 1.36% 0.14 

Washington 5.71% 

West Virginia 12.36% 0.60% 2.95% 0.46% 0.05 0.16 

Wisconsin 3.85% 2.80% 3.64% 0.73 

7.74% 0.29% 4.25% 0.27% 0.04 0.06 

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Table 4A. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, African Americans, Utilities, 2002 

Percentage Percentage Percentage Disparity Disparity 

State ofAII Percentage ofAIl of All Ratio-All Ratio 

Finns of All Sales Employers Employer Finns Employers Sales 

Percentage Percentage Percentage Di'parity Disparity 

State ofAII Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 5.40% 0.00% 

Alaska 2.07% 0.00% 

Arizona 

Arkansas 0.64% 0.00% 

California 0.38% 0.00% 0.00% 0.00 

Colorado 0.00% 0.00% 0.00% 0.00 

Connecticut 3.31% 1.85% 

Delaware 2.38% 0.00% 

District of Columbia 17.14% 0.00% 

Florida 2.72% 0.63% 

Georgia 

Hawaii 0.00% 0.00% 

Idaho 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Illinois 3.91% 0.51% 

Indiana 0.69% 0.00% 0.00% 0.00 

Iowa 0.89% 0.00% 0.00% 0.00 

Kansas 1.00% 0.00% 0.00% 0.00 

Kentucky 

Louisiana 4.16% 0.00% 0.00% 0.00 

Maine 0.00% 0.00% 

Maryland 

Massachusetts 2.40% 0.00% 0.00% 0.00 

Michigan 

Minnesota 0.81% 0.99% 

Mississippi 3.42% 

Missouri 2.14% 0.00% 0.00% 0.00 

Montana 0.00% 0.00% 

Nebraska 0.00% 0.00% 

Nevada 0.85% 0.00% 

New Hampshire 0.00% 0.00% 

New Jersey 3.87% 5.32% 

New Mexico 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

New York 4.89% 0.00% 0.00% 0.00 

North Carolina 

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Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

North Dakota 0.00% 0.00% 0.00% 0.00 

Ohio 4.17% 0.64% 

Oklahoma 0.95% 0.56% 

Oregon 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Pennsylvania 1.35% 0.00% 0.00% 0.00 

Rhode Island 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

South Carolina 7.46% 0.00% 0.00% 0.00 

South Dakota 0.00% 0.00% 

Tennessee 2.81% 1.25% 

Texas 2.01% 

Utah 0.00% 0.00% 0.00% 0.00 

Vermont 0.00% 0.00% 

Virginia 6.64% 0.00% 

Washington 0.22% 0.00% 0.00% 0.00 

West Virginia 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Wisconsin 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Wyoming 0.00% 0.00% 

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Table 4B. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Hispanics and Latinos, Utilities, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Finns Employers Sales 

Alabama 0.00% 0.00% 0.00% 0.00 

Alaska 0.69% 0.00% 

Arizona 2.87% 

Arkansas 0.00% 0.00% 0.00% 0.00 

California 8.59% 0.22% 

Colorado 0.68% 

Connecticut 1.l0% 0.00% 0.00% 0.00 

Delaware 2.38% 0.00% 

District of Columbia 

Florida 

Georgia 0.37% 0.00% 0.00% 0.00 

Hawaii 2.44% 0.00% 

Idaho 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Illinois 3.37% 0.51% 

Indiana 0.46% 0.00% 0.00% 0.00 

Iowa 0.45% 0.00% 0.00% 0.00 

Kansas 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Kentucky 0.35% 0.00% 

Louisiana 0.23% 0.00% 0.00% 0.00 

Maine 0.00% 0.00% 

Maryland 2.79% 

Massachusetts 1.96% 0.00% 0.00% 0.00 

Michigan 0.19% 0.00% 

Minnesota 0.27% 0.00% 0.00% 0.00 

Mississippi 0.00% 0.00% 0.00% 0.00% 000 0.00 

Missouri 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Montana 0.00% 0.00% 

Nebraska 1.25% 0.00% 

Nevada 2.54% 0.00% 

New Hampshire 0.00% 0.00% 

New Jersey 10.71% 

New Mexico 9.22% 0.01% 0.83% IJ.OO 

New York 

North Carolina 8.06% 

North Dakota 0.00% 0.00% 0.00% 0.00 

Ohio 0.54% 0.00% 0.00% 0.00% 0.00 0.00 

Oklahoma 0.24% 0.00% 0.00% 0.00 

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Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Pennsylvania 0.98% 0.00% 0.00% 0.00% 0.00 0.00 

Rhode Island 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

South Carolina 

South Dakota 

Tennessee 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Texas 5.84% 0.02% 1.16% 0.00 

Utah 1.02% 0.00% 

Vermont 0.00% 0.00% 

Virginia 1.66% 0.00% 

Washington 0.44% 0.58% 

West Virginia 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Wisconsin 0.36% 0.00% 0.00% 0.00 

0.00% 0.00% 

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Table 4C. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Asians, Utilities, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 0.32% 0.00% 

Alaska 0.00% 0.00% 0.00% 0.00 

Arizona 

Arkansas 0.00% 0.00% 0.00% 0.00 

California 4.49% 0.00% 0.00% 0.00 

Colorado 0.68% 0.00% 1.58% 0.01 

Connecticut 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Delaware 0.00% 0.00% 

District of Columbia 0.00% 0.00% 

Florida 0.50% 

Georgia 1.12% 0.00% 0.00% 0.00 

Hawaii 21.95% 

Idaho 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Illinois 0.53% 0.00% 0.00% 0.00 

Indiana 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Iowa 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Kansas 0.50% 0.00% 0.00% 0.00 

Kentucky 0.00% 0.00% 0.00% 0.00 

Louisiana 

Maine 0.00% 0.00% 

Maryland 0.70% 0.00% 0.00% 0.00 

Massachusetts 

Michigan 0.39% 0.00% 

Minnesota 0.54% 0.00% 0.00% 0.00 

Mississippi 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Missouri 0.27% 0.00% 0.00% 0.00 

Montana 0.00% 0.00% 

Nebraska 0.00% 0.00% 

Nevada 1.69% 0.00% 

New Hampshire 0.00% 0.00% 

New Jersey 

New Mexico 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

New York 

North Carolina 0.16% 0.00% 0.00% 0.00 

North Dakota 0.00% 0.00% 0.00% 0.00 

Ohio 2.00% 0.00% 0.00% 0.00 

Oklahoma 

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Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 0.37% 0.00% 0.00% 0.00 

Pennsylvania 0.25% 0.00% 0.00% 0.00 

Rhode Island 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

South Carolina 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

South Dakota 0.00% 0.00% 

Tennessee 0.70% 0.00% 0.00% 0.00 

Texas 

Utah 0.51% 0.00% 

Vermont 

Virginia 0.00% 0.00% 0.00% 0.00 

Washington 0.66% 0.58% 

West Virginia 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Wisconsin 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

0.00% 0.00% 

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Table 4D. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, American Indians and Alaska Natives, Utilities, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of AI! of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 0.00% 0.00% 0.00% 0.00 

Alaska 

Arizona 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Arkansas 0.32% 0.56% 

California 4.62% 0.04% 0.01 

Colorado 0.23% 0.53% 

Connecticut 2.76% 1.85% 

Delaware 0.00% 0.00% 

District of Columbia 0.00% 0.00% 

Florida 

Georgia 

Hawaii 0.00% 0.00% 

Idaho 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Illinois 0.89% 

Indiana 0.23% 0.00% 0.00% 0.00 

Iowa 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Kansas 1.00% 0.00% 0.00% 0.00 

Kentucky 0.00% 0.00% 0.00% 0.00 

Louisiana 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Maine 0.00% 0.00% 

Maryland 0.35% 0.00% 0.00% 0.00 

Massachusetts 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Michigan 0.19% 0.81% 

Minnesota 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Mississippi 0.19% 0.00% 0.00% 0.00 

Missouri 1.07% 0.65% 

Montana 0.65% 0.00% 

Nebraska 1.25% 0.00% 

Nevada 0.85% 0.00% 

New Hampshire 0.00% 0.00% 

New Jersey 0.60% 0.00% 

New Mexico 

New York 10.30% 0.00% 0.00% 0.00 

North Caro lina 0.16% 0.81% 

North Dakota 0.00% 0.00% 0.00% 0.00 

Ohio 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Oklahoma 

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Percentage Percentage Percentage Disparity Disparity 

State ofAl! Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 0.37% 0,00% 0,00% 0,00 

Pennsylvania 0,00% 0,00% 0,00% 0,00% 0,00 0,00 

Rhode Island 0,00% 0,00% 0,00% 0,00% 0,00 0,00 

South Carolina 0,00% 0,00% 0,00% 0,00% 0,00 0,00 

South Dakota 0,96% 0,00% 

Tennessee 0.35% 0.00% 0.00% 0,00 

Texas 

Utah 0.51% 0.00% 

Vermont 0.00% 0.00% 

Virginia 0.00% 0,00% 0.00% 0,00 

Washington 0.00% 0.00% 0,00% 0.00% 0.00 0,00 

West Virginia 0.54% 0.00% 0.00% 0.00 

Wisconsin 0.36% 0.00% 0.00% 0.00 

0.00% 0.00% 

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Table 4E. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Native Hawaiians and Pacific Islanders, Utilities, 2002 

Percentage Percentage Percentage Disparity Disparity Percentage of All State ofAIl of All Sales of All Employer Ratio-All Ratio 

Firms Employers Sales Firms Employers 

Alabama 0.00% 0.00% 0.00% 0.00 

Alaska 0.00% 0.00% 0.00% 0.00 

Arizona 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Arkansas 0.00% 0.00% 0.00% 0.00 

California 0.06% 0.00% 0.00% 0.00 

Colorado 0.00% 0.00% 0.00% 0.00 

Connecticut 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Delaware 0.00% 0.00% 

District of Columbia 0.00% 0.00% 

Florida 0.00% 0.00% 0.00% 0.00 

Georgia 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Hawaii 0.00% 0.00% 

Idaho 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

minois 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Indiana 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Iowa 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Kansas 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Kentucky 0.00% 0.00% 0.00% 0.00 

Louisiana 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Maine 0.00% 0.00% 

Maryland 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Massachusetts 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Michigan 0.00% 0.00% 0.00% 0.00 

Minnesota 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Mississippi 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Missouri 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Montana 0.00% 0.00% 

Nebraska 0.00% 0.00% 

Nevada 0.00% 0.00% 

New Hampshire 0.00% 0.00% 

New Jersey 0.00% 0.00% 0.00% 0.00 

New Mexico 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

New York 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

North Carolina 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

North Dakota 0.00% 0.00% 0.00% 0.00 

Ohio 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Oklahoma 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

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Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Firms Employers Sales 

Oregon 0,00% 0,00% 0,00% 0,00% 0,00 0,00 

Pennsylvania 0,00% 0,00% 0,00% 0,00% 0,00 0,00 

Rhode Island 0,00% 0,00% 0,00% 0,00% 0,00 000 

South Carolina 0,00% 0,00% 0,00% 0,00% 0.00 0,00 

South Dakota 0,00% 0.00% 

Tennessee 0,00% 0,00% 0,00% 0,00% 0,00 0.00 

Texas 0.00% 0,00% 0.00% 0.00 

Utah 0.00% 0.00% 0.00% 0.00 

Vermont 0,00% 0.00% 

Virginia 0.00% 0,00% 0.00% 0.00 

Washington 0,00% 0,00% 0.00% 0,00% 0.00 0.00 

West Virginia 0,00% 0,00% 0,00% 0.00% 0.00 0.00 

Wisconsin 0.00% 0,00% 0,00% 0.00% 0.00 0,00 

0.00% 0,00% 

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Table 4F. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Women, Utilities, 2002 

Percentage Percentage Percentage Disparity Disparity 

State ofAI! of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 3.81% 1.44% 

Alaska 9.66% 

Arizona 9.09% 0.29% 4.65% 0.26% 0.03 0.06 

Arkansas 5.75% 1.12% 

California 12.18% 0.03% 4.68% 0.02% 0.00 0.00 

Colorado 14.67% 2.63% 

Connecticut 3.87% 3.70% 

Delaware 9.52% 5.88% 

District of Columbia 2.86% 0.00% 

Florida 13.04% 0,14% 0,01 

Georgia 7.25% 0.28% 3.39% 0.04 

Hawaii 2.44% 0.00% 

Idaho 

!Hinois 5.51% 5.05% 

Indiana 7.60% 0.40% 3.16% 0.05 

Iowa 8.48% 

Kansas 12.44% 0.00% 0.00% 0.00 

Kentucky 16.84% 2.00% 

Louisiana 8.31% 0.35% 3.39% 0.04 

Maine 3.18% 

Maryland 11.85% 

Massachusetts 8.71% 1.90% 

Michigan 13.54% 2.42% 

Minnesota 5.68% 

Mississippi 6.45% 0.30% 3,70% 0.28% 0.05 0.08 

Missouri 

Montana 5.19% 2.25% 

Nebraska 2.50% 0.00% 

Nevada 13.56% 2.17% 

New Hampshire 4.64% 2.27% 

New Jersey 13,99% 2.13% 

New Mexico 8.25% 0.19% 4.17% 0,02 

New York 19.98% 

North Caro lina 6.58% 

North Dakota 1.33% 3.23% 

Ohio 15,61% 0.37% 8.97% 0.02 

Oklahoma 7.16% 2.79% 

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Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 3.72% 0.06% 2.68% 0.02 

Pennsylvania 7.49% 3.72% 

Rhode Island 13.79% 0.01% 0.00% 0.00% 0.00 0.00 

South Carolina 2.99% 0.94% 

South Dakota 3.85% 0.00% 

Tennessee 

Texas 11.05% 0.07% 5.30% 0.0] 

Utah 

Vermont 

Virginia 18.72% 5.31% 

Washington 10.62% 4.09% 

West Virginia 6.99% 0.36% 0.05 

Wisconsin 20.29% 0.05% 7.50% 0.00 

6.10% 

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Table SA. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, African Americans, Construction, 2002 

Percentage Percentage Percentage Disparity Disparity Percentage of All State of All of All Sales of All Employer Ratio-All Ratio 

Firms Employers Sales Firms Employers 

Alabama 5.71% 1.09% 3.12% 0.74% 0.19 0.24 

Alaska 0.44% 0.13% 0.23% 0.11% 0.30 0.46 

Arizona 0.57% 0.10% 0.20% 0.09% 0.18 0.45 

Arkansas 2.60% 1.38% nla nla 0.53 

California 2.10% 0.47% 1.05% 0.40% 0.22 0.38 

Colorado 0.65% 0.24% nla nla 0.36 

Connecticut 2.13% 0.39% 0.97% 0.28% 0.18 0.28 

Delaware nla nla nla nla 

Dist of Columbia 34.90% nla 17.16% 7.05% 0.41 

Florida 4.15% 0.59% 1.67% 0.45% 0.14 0.27 

Georgia 6.19% 1.68% 2.96% 1.42% 0.27 0.48 

Hawaii nla nla nla nla 

Idabo nla nla nla nla 

Illinois 2.79% 0.80% 0.94% 0.74% 0.29 0.79 

Indiana 0.89% 0.97% 0.65% 1.02% 1.09 1.57 

Iowa 0.22% 0.15% 0.13% 0.14% 0.68 /.04 

Kansas 1.09% 0.52% 1.17% 0.48% 0.48 0.41 

Kentucky nla nla nla nla 

Louisiana 9.90% 1.34% 2.92% 0.77% 0.14 0.26 

Maine 0.04% nfa 0.04% nla 

Maryland 7.12% 2.05% 2.69% 1.82% 0.29 0.68 

Massachusetts 1.18% 0.55% 0.59% 0.51% 0.47 0.87 

Michigan 1.64% 1.33% 0.85% 1.32% 0.81 1.55 

Minnesota 0.73% 0.18% 0.11% 0.15% 0.25 1.40 

Mississippi 10.47% 2.14% 5.65% 0.98% 0.20 0.17 

Missouri 1.50% 0.62% 0.77% 0.60% 0.41 0.78 

Montana nla nla nla nla 

Nebraska 0.51% nla 0.54% nla 

Nevada 1.18% 0.37% nla nla 0.31 

New Hampshire n/a nla nla nla 

New Jersey 2.42% 0.58% 1.31% 0.47% 0.24 0.36 

New Mexico 0.60% 0.16% nla nla 0.27 

New York 4.86% 0.77% 1.52% 0.67% 0.16 0.44 

North Caro lina 4.22% 0.87% nla nla 0.21 

North Dakota 0.00% 0.00% 0.00% 0.00% 

Ohio 2.04% 1.45% 1.37% 1.50% 0.7I UO Oklahoma 1.41% 0.32% 0.26% 0.16% 0.23 0.61 

Oregon 0.41% 0.30% 0.38% 0.31% 0.74 0.80 

Pennsylvania 1.41% 0.38% 0.54% 0.35% 0.27 0.64 

Rhode Island nla nla nla nla 

South Carolina 6.65% 1.44% 3.95% 0.99% 0.22 0.25 

South Dakota nla nla nla nla 

Tennessee 2.72% 0.70% 1.39% 0.57% 0.26 0.41 

Texas 2.16% 0.57% 0.92% 0.41% 0.26 0.45 

Utah 0.25% 0.03% 0.02% nla 0.12 

Vermont nla nla nla nla 

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Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Finns Employers Sales 

Virginia 4.10% 1.05% 2.71% 0.88% 0.26 0.33 

Washington 0.55% 0.28% nJa nJa 0.52 

West Virginia 0.54% 0.94% 0.29% 0.97% 1.73 3.32 

Wisconsin 0.54% 0.40% nJa nJa 0.75 

Wyoming 0.13% nla nJa nJa 

Notes: See Table 1 A. 

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Table SB. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Hispanics and Latinos, Construction, 2002 

Percentage Percentage Percentage Disparity Disparity Percentage of All State of All of All Sales of All Employer Ratio-All Ratio 

Finns Employers Sales Finns Employers 

Alabama 1.23% 0.44% 1.32% 0.28% 0.36 0.21 

Alaska 2.20% 0.86% 2.50% 0.81% 0.39 0.32 

Arizona 11.66% 2.73% 6.97% 2.47% 0.23 0.35 

Arkansas 1.50% 0.76% 0.44% 0.66% 0.51 1.48 

California 15.38% 4.30% 8.25% 3.71% 0.28 0.45 

Colorado 7.35% 2.61% 5.50% 2.22% 0.36 0.40 

Connecticut 3.50% 0.64% 1.67% 0.44% 0.18 0.26 

Delaware 1.16% 0.58% 0.25% 0.36% 0.50 1.45 

Dist of Columbia 19.76% nJa 10.65% nla nJa 

Florida 17.44% 5.15% 8.25% 3.90% 0.30 0.47 

Georgia 5.77% 1.39% 1.95% 0.62% 0.24 0.32 

Hawaii 3.40% 1.31% 3.05% nla 0.38 

Idaho 2.01% 1.63% 1.93% 1.67% 0.81 0.87 

Illinois 4.52% 1.52% 2.24% 1.38% 0.34 0.61 

Indiana 1.67% 0.73% 0.97% 0.62% 0.44 0.64 

Iowa 0.73% 0.29% 0.46% 0.18% 0.39 0.40 

Kansas 2.49% 1.53% n/a nla 0.61 

Kentucky 0.79% 0.43% 0.41% 0.32% 0.55 0.77 

Louisiana 3.23% 1.84% 0.82% 1.70% 0.57 2.07 

Maine 0.31% 0.33% 0.28% 0.37% 1.04 1.34 

Maryland 8.43% 1.89% 3.13% 1.44% 0.22 0.46 

Massachusetts 2.05% 0.75% 1.15% 0.67% 0.37 0.58 

Michigan 1.33% 0.75% 0.95% 0.70% 0.57 0.73 

Minnesota 0.88% 0.42% 0.67% 0.35% 0.47 0.52 

Mississippi 0.75% 0.57% 0.31% 0.49% 0.76 1.59 

Missouri 0.72% 0.43% 0.68% 0.41% 0.59 0.60 

Montana nJa nJa nla nla 

Nebraska 1.35% 0.33% nJa nla 0.24 

Nevada 7.05% 2.70% 3.93% 2.64% 0.38 0.67 

New Hampshire nla nJa nJa nJa 

New Jersey 6.97% 2.13% 3.33% 1.83% 0.31 0.55 

New Mexico 29.50% 17.20% 25.44% 15.39% 0.58 0.60 

New York 7.59% 1.72% 2.74% 1.48% 0.23 0.54 

North Carolina 2.26% 1.11% 1.32% 0.72% 0.49 0.55 

North Dakota nJa nla nla nla 

Ohio 0.76% 0.32% 0.58% 0.27% 0.42 0.47 

Oklahoma 2.27% 1.03% 1.49% 0.82% 0.46 0.55 

Oregon 1.69% 1.10% 1.92% 1.10% 0.65 0.57 

Pennsylvania 1.22% 0.36% 0.65% 0.28% 0.29 0.44 

Rhode Island nla nla nla nJa 

South Carolina 1.41% 0.67% 1.13% 0.58% 0.48 0.51 

South Dakota nJa nla nla nJa 

Tennessee 1.47% 0.34% 0.71% 0.22% 0.23 0.31 

Texas 30.86% 7.30% 11.30% 4.71% 0.24 0.42 

Utah 2.78% 0.77% 1.60% 0.68% 0.28 0.43 

Vennont nla nla nJa nJa 

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Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Firms Employers Sales 

Virginia 7.24% 1.99% 2.10% 1.41% 0.28 0.67 

Washington 1.67% 0.76% 1.78% 0.76% 0.45 0.43 

West Virginia 0.35% 0.96% 0.41% 1.02% 2.75 2.50 

Wisconsin 0.70% 0.37% 0.58% 0.35% 0.53 0.61 

Wyoming 1.23% 0.44% 1.32% 0.28% 0.36 0.21 

Notes: See Table lA. 

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Table Sc. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Asians, Construction, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage ofAll of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 

Alaska 1.73% 0.43% 0.67% 0.32% 0.25 0.48 

Arizona 0.55% 0.14% nla nla 0.25 

Arkansas nla nla nla nla 

California 4.77% 1.55% 3.57% 1.30% 0.32 0.36 

Colorado 0.88% 0.21% 0.54% 0.17% 0.24 0.31 

Connecticut 0.30% 0.26% 0.27% 0.27% 0.86 1.01 

Delaware nla nla nla nla 

Dist of Columbia 2.69% nla 6.80% nla 

Florida 0.75% 0.36% 0.45% 0.35% 0.48 0.78 

Georgia 0.69% 0.40% nla nla 0.58 

Hawaii 37.27% 27.68% 35.62% 27.67% 0.74 0.78 

Idaho 0.31% 0.16% 0.24% 0.14% 11.51 0.58 

lIIinois 0.80% 0.60% 0.65% 0.59% 0.74 0.90 

Indiana 0.35% 0.08% nla nla 0.23 

Iowa nla nla nla nla 

Kansas 0.32% 0.06% nla nla 0.19 

Kentucky 0.17% 0.27% 0.20% 0.29% 1.62 1.50 

Louisiana 0.63% 0.21% nla nla 0.34 

Maine nla nla nla nla 

Maryland 4.14% 1.28% 1.49% 0.31 

Massachusetts 1.21% 1.O3%~ 0.54% 1.03% 0.85 1.90 

Michigan 0.34% 0.25% 0.26% 0.24% 0.72 0.95 

Minnesota 0.47% 0.44% nla nla 0.92 

Mississippi nla nla nla nla 

Missouri 0.23% 0.29% 0.23% nla 1.22 

Montana 0.18% 0.15% nla nla 0.87 

Nebraska nla nla nla nla 

Nevada 1.11% 0.48% 0.70% 0.47% 0.44 0.66 

New Hampshire nla n/a nla nla 

New Jersey 1.33% 0.77% 0.89% nla 0.58 

New Mexico nla nla nla nla 

New York 4.12% 1.15% 1.93% 1.03% 0.28 0.53 

North Carolina 0.53% 0.34% 0.40% 0.31% 0.65 0.76 

North Dakota nla nla nla nla 

Ohio 0.43% 0.39% nla nla 0.91 

Oklahoma 0.57% 0.10% nla nla 0.18 

Oregon 0.86% 0.30% 0.67% 0.25% 0.35 0.38 

Pennsy Ivania 0.72% 0.23% 0.23% 0.20% 0.32 0.88 

Rhode Island 0.38% 0.25% 0.06% nla 0.67 

South Carolina nla nla nla nla 

South Dakota nla nla nla nla 

Tennessee 0.47% 0.16% 0.32% 0.13% 0.35 0.39 

Texas 1.02% 0.40% 0.69% 0.36% 0.39 0.52 

Utah 0.42% 0.66% nla nla 1.57 

Vermont nla nla nla nla 

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Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Firms Employers Sales 

Virginia 3.14% 0.86% 1.28% 0.58% 0.27 0.45 

Washington 2.10% 1.09% 1.72% 1.06% 0.52 0.62 

West Virginia 0.15% 0.15% nla n/a 0.96 

Wisconsin 0.21% 0.06% nla nla 0.26 

Wyoming 0.13% nla nla nla 

Notes: See Table IA. 

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Table 50. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, American Indians and Alaska Natives, Construction, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 1.30% 0.56% 1.31% 0.53% 043 0.40 

Alaska 5.08% 15.03% 5.24% 15.67% 2.96 2.99 

Arizona 2.05% 0.56% 0.80% 0.51% 0.27 0.64 

Arkansas 1.81% 1.53% J.l9% 1.51% 0.84 1.26 

California 2.15% 0.70% 1.27% 0.62% 0.33 0.49 

Colorado 1.18% 0.31% 0.87% 0.24% 0.26 0.28 

Connecticut 0.53% 0.09% nla nla 0.16 

Delaware nla n/a nla nla 

Dist of Columbia 0.75% nla 0.00% 0.00% 

Florida 1.00% 0.17% nla nla 0.17 

Georgia 1.03% 0.17% 0.26% 0.03% 0.16 0.12 

Hawaii 0.54% nla nla nla 

Idaho 1.47% 0.84% nla nla 0.57 

Illinois 0.33% 0.13% 0.22% 0.12% 0.39 0.55 

Indiana 0.20% 0.23% nla nla 1.16 

Iowa nla nla nla nla 

Kansas 1.21% 0.71% 0.90% 0.69% 0.59 0.77 

Kentucky nla nla nla nla 

Louisiana 1.05% 0.29% nla nla 0.28 

Maine 0.81% 0.18% nla nla 0.22 

Maryland 2.07% 0.32% nla nla (U5 

Massachusetts 0.67% 0.07% 0.29% 0.05% (J.] I 0.18 

Michigan 0.95% 0.34% 0.48% 0.31% 0.36 0.65 

Minnesota 0.66% 0.21% 0.42% 0.20% 0.32 0.48 

Mississippi 0.38% 0.03% nla nla 0.08 

Missouri 1.36% 0.39% nla nla 0.28 

Montana 2.30% 1.91% 1.81% 1.99% 0.83 1.10 

Nebraska 0.33% 0.29% 0.20% 0.28% 0.86 1.36 

Nevada 2.07% 0.29% J.l0% 0.26% 0.14 0.23 

New Hampshire 0.79% 0.38% nla nla 0.47 

New Jersey 0.38% nla 0.16% nla 

New Mexico nla nla nla nla 

New York 0.96% 0.19% 0.38% 0.14% 0.20 0.37 

North Carolina 1.34% 0.48% 0.95% 0,38% 0.36 0.40 

North Dakota 1.93% 1.02% 1.68% 1.00% 0.53 0.60 

Ohio 0.48% 0.15% nla nla 0.32 

Oklahoma 8.30% 5.39% 5.00% 4.75% 0.65 0.95 

Oregon 1.36% 0.64% 1.03% 0.60% 0.47 0.58 

Pennsylvania 0.37% 0.08% 0.23% 0.07% 0.21 0.28 

Rhode Island nla nla nia nla 

South Carolina 0.58% 0.17% nla nla 0.29 

South Dakota 2.65% 1.74% 1.85% 1.79% 0.66 0.97 

Tennessee 1.03% 0.35% nla nla 0.34 

Texas 1.09% 0.57% 0.91% 0.54% 0.53 0.60 

Utah 0.92% 0.22% 0.48% 0.18% 0.23 0.37 

Vermont 0.91% 0.38% 0.31% 0.27% 0.42 0.85 

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Percentage Percentage Percentage Disparity Disparity 

State of All Percentage ofAIl of All Ratio-All Ratio 

Finns of All Sales Employers Employer Finns Employers Sales 

Virginia 0.75% 0.30% 0.40% 0.20% 0.40 0.50 

Washington 1.06% 0.66% 0.92% 0.63% 0.62 0.68 

West Virginia 0.55% 0.13% 0.09% 0.12% 0.24 1.33 

Wisconsin 0.57% 0.32% 0.31% 0.31% 0.55 1.00 

Wyoming 1.82% 0.84% nla nla 0.46 

Notes: See Table lAo 

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Table SE. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Native Hawaiians and Pacific Islanders, Construction, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Finns Employers Sales 

Alabama 0.00% nJa 0.01% nJa 

Alaska nJa nla nla nla 

Arizona 0.14% nJa nla nJa 

Arkansas nJa nJa nla nla 

California nJa nJa nJa nJa 

Colorado 0.14% 0.03% 0.09% nJa 0.24 

Connecticut nla nla nla nla 

Delaware 0.00% 0.00% 0.00% 0.00% 

Dist of Columbia 0.06% nla 0.00% 0.00% 

Florida nJa nla nla nJa 

Georgia 0.03% 0.03% 0.07% 0.03% 0.89 0.44 

Hawaii 12.87% 4.66% n/a nla 0.36 

Idaho nJa nJa nJa nJa 

llIinois nJa nJa nJa nJa 

Indiana nJa nJa nJa nla 

Iowa 0.01% nJa nla nJa 

Kansas 0.00% 0.00% 0.00% 0.00% 

Kentucky 0.01% nJa nJa nJa 

Louisiana 0.00% nla 0.01% nJa 

Maine 0.01% nla 0.04% nla 

Maryland 0.01% n/a 0.01% nla 

Massachusetts nJa nJa nla nJa 

Michigan 0.00% nJa 0.01% nJa 

Minnesota nla nla nJa nJa 

Mississippi 0.02% 0.02% 0.02% nia 0.74 

Missouri nJa nJa nJa nJa 

Montana 0.00% 0.00% 0.00% 0.00% 

Nebraska 0.01% nJa 0.00% 0.00% 

Nevada 0.06% nJa nJa nla 

New Hampshire nla nla nJa nla 

New Jersey 0.03% nJa 0.07% nla 

New Mexico 0.01% nJa 0.02% nJa 

New York nla nla nJa nJa 

North Caro lina 0.01% 0.00% n/a nJa OA7 

North Dakota 0.00% 0.00% 0.00% 0.00% 

Ohio nJa nJa nla nJa 

Oklahoma 0.50% 0.06% nJa nJa O.II 

Oregon 0.08% 0.09% nJa nJa l.05 

Pennsylvania nJa nJa nJa nla 

Rhode Island 0.02% nJa 0.00% 0.00% 

South Carolina nla nla nla nla 

South Dakota 0.00% 0.00% 0.00% 0.00% 

Tennessee 0.00% nJa 0.01% nla 

Texas nla nJa nJa nJa 

Utah 0.17% 0.82% nJa nJa 4.85 

Vermont 0.00% 0.00% 0.00% 0.00% 

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Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Finns Employers Sales 

Virginia 0.02% nla 0.05% nla 

Washington 0.13% n/a 0.18% nla 

West Virginia 0.00% 0.00% 0.00% 0.00% 

Wisconsin nla nla nla nla 

Wyoming 0.03% nla 0.00% 0.00% 

Notes: See Table IA. 

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Table SF. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employers 

Firms, Women, Construction, 2002 

State 

Alabama 

Alaska 

Arizona 

Arkansas 

California 

Colorado 

Connecticut 

Delaware 

Dist of Columbia 

Florida 

Georgia 

Hawaii 

Idaho 

Illinois 

Indiana 

Iowa 

Kansas 

Kentucky 

Louisiana 

Maine 

Maryland 

Massachusetts 

Michigan 

Minnesota 

Mississippi 

Missouri 

Montana 

Nebraska 

Nevada 

New Hampshire 

New Jersey 

New Mexico 

New York 

North Carolina 

North Dakota 

Ohio 

Oklahoma 

Oregon 

Pennsy Ivania 

Rhode Island 

South Carolina 

South Dakota 

Tennessee 

Texas 

Utah 

Vermont 

Percentage 

of All 

Firms 

7.45% 

10.30% 

7.47% 

7.37% 

5.98% 

7.85% 

6.85% 

5.19% 

5.25% 

8.33% 

6.96% 

8.03% 

6.89% 

8.92% 

7.45% 

6.74% 

6.57% 

7.62% 

7.06% 

6.12% 

8.14% 

6.44% 

8.01% 

6.61% 

5.14% 

8.21% 

7.09% 

4.55% 

9.79% 

3.38% 

7.37% 

10.34% 

8.11% 

8.05% 

4.80% 

7.55% 

7.37% 

6.29% 

6.18% 

6.96% 

6.66% 

6.48% 

8.30% 

7.22% 

6.66% 

6.20% 

Percentage 

of All Sales 

3.97% 

8.39% 

4.69% 

4.05% 

4.97% 

3.99% 

5.69% 

4.30% 

nla 

5.31% 

3.76% 

3.62% 

4.92% 

7.87% 

4.32% 

4.59% 

4.57% 

5.30% 

5.64% 

5.45% 

5.46% 

4.00% 

4.98% 

3.98% 

5.70% 

5.50% 

5.34% 

3.13% 

5.22% 

4.64% 

7.55% 

6.92% 

6.65% 

5.30% 

nla 

5.05% 

5.40% 

3.72% 

4.79% 

10.55% 

5.45% 

4.21% 

3.99% 

5.15% 

3.61% 

nla 

Percentage 

of All 

Employers 

6.96% 

nla 

7.23% 

5.55% 

5.65% 

7.32% 

7.03% 

7.36% 

10.36% 

7.38% 

6.49% 

5.93% 

5.88% 

10.83% 

5.85% 

4.60% 

nla 

6.75% 

7.89% 

5.47% 

7.75% 

6.31% 

6.49% 

6.49% 

6.12% 

8.05% 

7.35% 

4.22% 

9.21% 

3.35% 

7.76% 

nla 

8.51% 

7.64% 

5.56% 

8.00% 

6.61% 

5.84% 

7.01% 

7.80% 

5.55% 

3.90% 

6.40% 

9.19% 

5.06% 

2.67% 

Percentage 

of All 

Employer 

Sales 

3.75% 

nla 

4.34% 

4.11% 

4.95% 

3.89% 

5.68% 

nla 

nla 

5.05% 

3.53% 

3.56% 

4.97% 

8.12% 

4.36% 

4.60% 

nla 

5.29% 

5.66% 

5.32% 

5.40% 

3.98% 

4.94% 

3.93% 

5.07% 

5.57% 

5.49% 

3.21% 

5.09% 

5.22% 

7.78% 

nla 

6.71% 

5.24% 

nla 

5.16% 

5.69% 

3.60% 

4.98% 

11.20% 

5.50% 

4.26% 

3.69% 

5.18% 

3.59% 

nla 

Disparity 

Ratio-All 

Firms 

0.53 

0.81 

0.63 

0.55 

0.83 

0.51 

0.83 

0.83 

0.64 

0.54 

0.45 

0.71 

0.88 

0.58 

0.68 

0.70 

0.70 

0.80 

0.89 

0.67 

0.62 

0.62 

0.60 

1.11 

0.67 

0.75 

0.69 

0.53 

1.37 

1.02 

0.67 

0.82 

0.66 

0.67 

0.73 

0.59 

0.77 

1.52 

0.82 

0.65 

0.48 

0.71 

0.54 

Disparity 

Ratio 

Employers 

0.54 

0.60 

0.74 

0.88 

0.53 

0.81 

0.68 

0.54 

0.60 

0.84 

0.75 

0.75 

1.00 

0.78 

0.72 

0.97 

IUO 

0.63 

0.76 

0.61 

0.83 

0.69 

0.75 

0.76 

0.55 

1.56 

1.00 

0.79 

0.69 

0.65 

0.86 

0.62 

0.71 

1.44 

0.99 

1.09 

0.58 

0.56 

0.71 

69 
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Percentage Percentage Percentage Disparity Disparity 

State ofAl! Percentage of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Finns Employers Sales 

Virginia 6.81% 4.59% 6.97% 4.58% 0.67 0.66 

Washington 6.87% 3.37% 5.42% 3.26% 0.49 0.60 

West Virginia 6.03% 7.84% 7.75% 7.96% 1.30 1.03 

Wisconsin 6.52% 5.63% 5.49% 5.87% 0.86 1.07 

Wyoming 7.77% 6.60% 9.07% 6.69% 0.85 0.74 

Notes: See Table I A. 

70 
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NERA Economic Consutting 

Table 6A. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, African Americans, Manufacturing, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Firms Employers Sales 

Alabama 3.23% 0.06% 0.81% 0.05% 0.02 0.06 

Alaska 0.66% 0.01% 0.01 

Arizona 0.52% 0.07% 0.21% 0.06% 0.13 0.31 

Arkansas 1.23% 0.04% OA5% 0.03 

California 1.08% 0.11% 0.64% 0.10% 010 0.16 

Colorado 0.75% 0.08% 0.32% 0.11 

Connecticut 0.72% 0.10% 0.13 

Delaware 1.69% 0.15% 

District of Columbia 21.79% 2.72% 

Florida 3.63% 0.24% 1.27% 0.22% 0.07 0.17 

Georgia 4.20% 0.08% 0.54% 0.07% 0.02 0.13 

Hawaii 0.89% 0.08% 0.22% 0.09 

Idaho 0.10% 0.00% 0.00% 0.00% 0.00 0.00 

Illinois 1.66% 0.14% 0.55% 0.08 

Indiana 

Iowa 0.25% 0.04% 0.29% 0.04% 0.18 0.15 

Kansas 

Kentucky 0.94% 0.23% 0.64% 0.24 

Louisiana 6.20% 0.03% 1.49% 0.02% 0.00 0.01 

Maine 0.09% 0.05% 

Maryland 

Massachusetts 

Michigan IAI% 0.25% 0.79% 0.25% 0.18 0.31 

Minnesota 0.36% 

Mississippi 4.54% 0.11% 1.55% 0.11% 0.03 0.07 

Missouri 

Montana 0.07% 0.08% 

Nebraska 0.26% 0.05% 

Nevada 0.86% 0.04% OAO% 0.05 

New Hampshire 0.28% 0.14% 

New Jersey 1.77% 0.19% 0.73% 0.11 

New Mexico 

New York 2.89% 0.22% 1.29% 0.21% 0.08 0.16 

North Carolina 2.51% 0.11% 0.62% 0.10% 0.04 0.17 

North Dakota 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Ohio 1.23% 0.12% 0.62% 0.12% 0.09 IU8 

Oklahoma 

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Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 

Pennsylvania 0.75% 0.17% 0.58% 0.17% 0.22 0.28 

Rhode Island 

South Carolina 4.01% 0.05% 0.86% 0.05% 0.01 0.06 

South Dakota 0.06% 0.00% 0.00% 0.00 

Tennessee 1.72% 0.15% 0.34% 0.15% 0.09 0.43 

Texas 2.05% 0.07% 0.56% 0.06% 0.04 O.ll 

Utah 

Vermont 0.04% 0.09% 

Virginia 2.62% 0.13% 1.34% 0.13% 0.05 0.10 

Washington 0.68% 0.04% 0.94% 0.04% 0.06 0.04 

West Virginia 0.19% 0.00% 0.00% 0.00 

Wisconsin 0.12% 0.00% 0.00% 0.00 

0.08% 0.18% 

72 
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NERA EconomIC Com:ulting 

Table 6B. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Hispanics and Latinos, Manufacturing, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage ofAll of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 

Alaska 1.71% 0.04% 0.83% 0.03% 0.02 0.03 

Arizona 6.61% 0.54% 4.43% 0.52% 0.08 0.12 

Arkansas 0.45% 0.05% 0.31% 0.05% O.ll 0.15 

California 12.50% 1.69% 8.62% 1.63% 0.14 0.19 

Colorado 3.58% 0.61% 2.61% 0.59% 0.17 0.23 

Connecticut 1.52% 0.14% 1.13% 0.14% 0.09 0.12 

Delaware 0.51% 0.60% 

District of Columbia 8.65% 

Florida 15.54% 2.59% 10.41% 2.46% 0.17 0.24 

Georgia 1.48% 0.18% 0.54% 0.18% 0.12 0.33 

Hawaii 2.74% 2.16% 

Idaho 1.06% 0.07% 0.78% 0.07 

Illinois 2.82% 0.46% 2.13% 0.45% 0.16 0.21 

Indiana 0.48% 0.02% 0.22% 0.02% 0.04 0.08 

Iowa 0.25% 0.12% 0.29% 0.12% 0.50 0.42 

Kansas 1.04% 0.13% 0.56% 0.13% 0.12 0.22 

Kentucky 0.22% 0.01% 0.18% 0.01% 0.06 0.07 

Louisiana 1.51% 0.05% 0.70% 0.05% 0.04 0.07 

Maine 0.19% 0.22% 

Maryland 1.98% 0.21% 0.89% 0.20% O.ll 0.22 

Massachusetts 1.60% 0.21% 1.26% 0.20% 0.13 0.16 

Michigan 1.19% 0.36% 1.13% 0.36% 0.30 0.32 

Minnesota 0.25% 0.02% 0.06 

Mississippi 

Missouri 0.61% 0.05% 0.74% 0.05% 0.08 0.06 

Montana 

Nebraska 1.00% 0.82% 

Nevada 4.48% 0.86% 3.73% 0.82% 0.19 0.22 

New Hampshire 0.35% 0.24% 0.45% 0.24% 0.68 0.53 

New Jersey 4.88% 0.43% 3.58% 0.41% 0.09 O. fl 

New Mexico 13.69% 3.07% 16.95% 2.98% 0.22 0.18 

New York 6.36% 0.39% 2.76% 0.37% 0.06 0.13 

North Carolina 1.25% 0.16% 1.08% 0.16% 0.13 0.14 

North Dakota 0.17% 0.14% 

Ohio 0.47% 0.06% 0.34% 0.06% 0.13 0.18 

Oklahoma 1.14% 0.57% 1.24% 0.57% 0.50 

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Percentage Percentage Percentage Disparity Disparity Percentage of All State of All of All Sales of All Employer Ratio-All Ratio 

Firms Employers Sales Firms Employers 

Oregon 1.42% 0.52% 1.28% 0.52% 0.37 0.41 

Pennsylvania 0.56% 0.07% 0.42% 0.07% 0./2 0.16 

Rhode Island 3.30% 0.13% 1.13% 0.10% 0.04 0.09 

South Carolina 

South Dakota 0.48% 0.33% 

Tennessee 

Texas 13.89% 0.75% 7.40% 0.71% 0.05 0.10 

Utah 1.57% 0.11% 0.90% 0.11% 0.07 0.12 

Vermont 0.25% 0.00% 0.17% 0.00% 0.01 0.01 

Virginia 1.68% 0.22% 1.45% 0.22% 0.13 0.15 

Washington 1.17% 0.09% 1.26% 0.09% 0.08 0.07 

West Virginia 0.23% 0.00% 0.14% 0.01 

Wisconsin 0.65% 0.27% 0.73% 0.27% 0.42 0.37 

0.83% 0.01% 0.71% 0.02 

74 
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NERA Economic Consulting 

Table 6C. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Asians, Manufacturing, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Finns Employers Sales 

Alabama 0.95% 0.21% 1.00% 0.21% 0.22 0.21 

Alaska 1.71% 0.41% 

Arizona 1.64% 0.47% 2.05% 0.46% 0.28 0.23 

Arkansas 0.24% 0.22% 0.21% 0.93 

California 10.62% 2.63% 12.07% 2.59% 0.25 0.21 

Colorado 2.34% 0.16% 1.89% 0.14% 0.07 0.08 

Connecticut 1.16% 0.23% 0.84% 0.20 

Delaware 1.95% 0.29% 1.05% 0.28% 0.15 0.27 

District of Columbia 6.41% 2.30% 9.52% 0.36 

Florida 2.15% 0.63% 1.70% 0.61% 0.29 0.36 

Georgia 2.66% 0.42% 3.37% 0.42% 0.16 0./2 

Hawaii 40.66% 11.94% 44.94% 0.29 

Idabo 0.63% 0.04% 0.50% 0.07 

minois 4.19% 1.07% 3.08% 1.06% 0.26 0.35 

Indiana 0.65% 0.52% 0.45% 0.52% 0.80 1.15 

Iowa 0.15% 0.02% 0.14 

Kansas 0.57% 0.59% 

Kentucky 1.23% 1.81% 

Louisiana 

Maine 0.23% 0.02% 0.33% 0.07 

Maryland 4.17% 0.80% 4.05% 0.79% 0.19 0.20 

Massachusetts 2.32% 0.57% 1.87% 0.56% 0.24 0.30 

Michigan 1.12% 0.38% 1.04% 0.37% 0.34 0.36 

Minnesota 1.38% 0.43% 

Mississippi 0.96% 0.71% 0.87% 0.71% 0.73 0.81 

Missouri 0.72% 0.70% 

Montana 0.50% 0.01% 0.64% 0.02 

Nebraska 0.55% 0.38% 

Nevada 2.43% 0.78% 2.01% 0.77% 0.32 0.38 

New Hampshire 0.70% 0.42% 0.73% 0.42% 0.60 0.58 

New Jersey 3.67% 0.90% 3.54% 0.89% 0.25 0.25 

New Mexico 1.39% 0.45% 1.77% 0.45% 0.33 0.25 

New York 8.04% 1.31% 6.52% 1.29% 0.16 0.20 

North Carolina 1.21% 0.22% 1.01% 0.21% 0.18 0.21 

North Dakota 0.17% 0.00% 0.00% 0.00 

Ohio 0.85% 0.16% 0.86% 0.16% 0.19 0.18 

Oklaboma 0.90% 0.31% 0.58% 0.31% 0.35 

75 
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NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Finns Employers Sales 

Oregon 2.30% 0.21% 1.32% 0.20% 0.09 0.15 

Pennsylvania 2.02% 0.37% 1.79% 0.37% 0.18 0.20 

Rhode Island 2.50% 0.25% 0.47% 0.22% 0.10 0.48 

South Carolina 0.76% 1.07% 0.62% 1.07% 1.42 1.74 

South Dakota 0.30% 

Tennessee 0.83% 0.22% 0.89% 0.21% 0.26 0.24 

Texas 4.95% 0.41% "3.42% 0.39% 0.08 O.ll 

Utah 

Vermont 0.46% 

Virginia 3.04% 0.20% 3.38% 0.20% 0.07 0.06 

Washington 4.98% 0.53% 3.90% 0.51% O.ll 0./3 

West Virginia 0.23% 0.35% 

Wisconsin 0.67% 0.10% 0.15 

0.23% 0.00% 0.00% 0.00 

76 
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NERA Economic Consulting 

Table 6D. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, American Indians and Alaska Natives, Manufacturing, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 0.66% 

Alaska 3.81% 2.90% 

Arizona 5.46% 0.06% 0.29% 0.04% 0.01 0.15 

Arkansas 

California 0.90% 0.08% 0.49% 0.08% 0.09 0.16 

Colorado 0.49% 0.02% 0.03 

Connecticut 

Delaware 0.25% 0.00% 0.00% 0.00 

District of Columbia 1.60% 0.68% 

Florida 1.20% 0.06% 0.05 

Georgia 0.89% 0.04% 0.05 

Hawaii 0.79% 0.11% 

Idaho 1.72% 0.08% 0.22% 0.07% 0.05 0.31 

Illinois 0.22% 0.01% 0.04 

Indiana 0.60% 0.02% 0.07% 0.01% 0.03 0.19 

Iowa 0.10% 0.00% 0.00% 0.00 

Kansas 0.68% 0.03% 0.56% 0.03% 0.05 0.05 

Kentucky 0.68% 

Louisiana 0.45% 0.01% 0.02 

Maine 

Maryland 

Massachusetts 

Michigan 0.62% 0.06% 0.09 

Minnesota 0.86% 0.06% 0.45% 0.06% OJJ7 0.13 

Mississippi 0.26% 0.12% 

Missouri 0.27% 0.01% 0.04 

Montana 1.62% 0.15% 1.21% 0.13% OJJ9 0.11 

Nebraska 0.10% 0.00% 0.00% 0.00 

Nevada 0.47% 0.46% 

New Hampshire 0.14% 0.23% 

New Jersey 

New Mexico 19.27% 0.18% 1.71% 0.09% 0.01 0.05 

New York 0.80% 0.02% 0.12% 0.02 

North Carolina 

North Dakota 0.58% 0.58% 

Ohio 0.09% 0.01% 0.16 

Oklahoma 5.77% 0.67% 3.21% 0.65% 0.12 

77 
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NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 0.47% 0.09% 0.32% 0.08% 0.18 0.26 

Pennsylvania 

Rhode Island 

South Carolina 

South Dakota 2.41% 

Tennessee 0.83% 0.02% 0.39% 0.02% 0.03 0.06 

Texas 

Utah 

Vermont 0.25% 0.09% 

Virginia 

Washington 1.04% 0.10% 0.10 

West Virginia 0.45% 0.07% 

Wisconsin 0.36% 0.06% 0.16 

0.98% 0.18% 1.07% 0.17% 0,18 0./6 

78 
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NERA Economic Consult!ng 

Table 6E. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Native Hawaiians and Pacific Islanders, Manufacturing, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 0.01% 0.00% 0.00% 0.00 

Alaska 0.26% 0.00% 0.00% 0.00 

Arizona 0.02% 0.02% 

Arkansas 0.02% 0.00% 0.00% 0.00 

California 0.08% 0.02% 0.07% 0.02% 0.30 0.36 

Colorado 0.02% 0.00% 0.00% 0.00 

Connecticut 0.01% 0.00% 0.00% 0.00 

Delaware 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

District of Columbia 0.00% 0.00% 0.00% 0.00 

Florida 

Georgia 

Hawaii 3.53% 1.11% 3.02% 0.3/ 

Idaho 0.03% 0.00% 0.00% 0.00 

Illinois 

Indiana 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Iowa 0.02% 0.03% 

Kansas 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Kentucky 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Louisiana 0.01% 0.00% 0.00% 0.00 

Maine 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Maryland 0.04% 0.00% 0.00% 0.00 

Massachusetts 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Michigan 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Minnesota 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Mississippi 0.02% 0.04% 

Missouri 0.02% 0.03% 

Montana 0.03% 0.08% 

Nebraska 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Nevada 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

New Hampshire 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

New Jersey 0.01% 0.01% 

New Mexico 0.02% 0.00% 0.00% 0.00 

New York 

North Carolina 0.01% 0.00% 0.00% 0.00 

North Dakota 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Ohio 0.01% 0.01% 

Oklahoma 0.01% 0.00% 0.00% 0.00 

79 
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NERA E::conomic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Finns Employers Sales 

Oregon 0.03% 0.02% 

Pennsylvania 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Rhode Island 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

South Carolina 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

South Dakota 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Tennessee 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Texas 0.05% 

Utah 0.17% 0.07% 

Vermont 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Virginia 

Washington 0.11% 0.03% 

West Virginia 0.04% 0.00% 0.00% 0.00 

Wisconsin 0.01% 0.00% 0.00% 0.00 

80 
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NERA Economic Consulting 

Table 6F. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Women, Manufacturing, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Finns Employers Sales 

Alabama 16.60% 2.86% 11.92% 2.85% 0.17 0.24 

Alaska 25.87% 15.94% 

Arizona 19.60% 1.77% 13.63% 1.71% 0.09 0.13 

Arkansas 17.51% 1.80% 10.38% 1.78% 0.10 0.17 

California 18.52% 3.36% 13.76% 3.29% 0.18 0.24 

Colorado 19.45% 1.70% 12.02% 1.62% 0.09 0.14 

Connecticut 16.82% 1.89% 10.56% 1.84% 0.11 0.17 

Delaware 16.60% 0.84% 9.32% 0.83% 0.05 0.09 

District of Columbia 28.21% 17.69% 

Florida 18.97% 3.00% 13.33% 2.87% 0.16 0.22 

Georgia 17.37% 2.21% 11.86% 2.18% 0.13 0.18 

Hawaii 30.22% 3.50% 16.49% 0.12 

Idaho 15.26% 1.83% 10.34% 1.78% 0.12 0.17 

Illinois 16.90% 3.43% 12.28% 3.41% 11.20 0.28 

Indiana 13.10% 1.67% 10.18% 1.66% 0.13 0.16 

Iowa 13.10% 1.21% 8.48% 1.19% 0.09 0.14 

Kansas 16.67% 1.65% 12.07% 1.63% 0.10 0.14 

Kentucky 17.05% 1.72% 11.17% 1.71% 0.10 0.15 

Louisiana 17.56% 1.27% 15.02% 1.25% 0.07 0.08 

Maine 23.35% 2.62% 15.59% 2.55% 0.11 0.16 

Maryland 21.87% 2.69% 15.51% 2.64% 0.12 0.17 

Massachusetts 17.15% 2.08% 9.28% 2.03% 0.12 0.22 

Michigan 15.55% 1.67% 10.48% 1.65% 0.11 0.16 

Minnesota 16.64% 3.17% 10.16% 3.14% 0.19 0.31 

Mississippi 15.53% 2.01% 10.53% 2.00% 0.13 0./9 

Missouri 16.94% 1.42% 11.82% 1.39% 0.08 0.12 

Montana 20.34% 1.90% 11.76% 1.77% 0.09 0.15 

Nebraska 17.30% 3.09% 12.21% 3.07% 0.18 0.25 

Nevada 17.62% 6.78% 12.63% 6.69% 0.38 0.53 

New Hampshire 19.72% 3.27% 15.20% 3.21% 0.17 0.21 

New Jersey 16.56% 2.68% 13.19% 2.63% 0.16 0.20 

New Mexico 28.78% 2.14% 15.88% 1.98% 0.07 0.12 

New York 19.92% 3.69% 14.53% 3.62% 0.19 0.25 

North Carolina 17.94% 1.78% 11.92% 1.76% 0.10 0.15 

North Dakota 12.51% 1.38% 8.82% 1.35% 0.11 0.15 

Ohio 15.58% 2.46% 10.66% 2.44% 0.16 0.23 

Oklahoma 15.53% 2.44% 13.73% 2.40% 0.16 

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Percentage Percentage Percentage Disparity Disparity 

State of AlI Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 20.34% 2.55% 12.06% 2.50% 0.13 0.21 

Pennsylvania 14.68% 1.84% 10.29% 1.82% 0.13 0.18 

Rhode Island 16.21% 3.26% 11.04% 3.20% 0.20 0.29 

South Carolina 16.95% 1.42% 11.49% 1.40% 0.08 0.12 

South Dakota 14.76% 1.64% 11.61% 1.63% 0.11 0.14 

Tennessee 13.93% 1.92% 9.68% 1.90% 0.14 0.20 

Texas 20.59% 1.78% 14.09% 1.73% 0.09 0.12 

Utah 19.44% 2.70% 10.99% 2.65% 0.14 0.24 

Vermont 21.28% 1.32% 11.13% 1.23% 0.06 0.11 

Virginia 20.80% 2.02% 13.26% 1.99% 0.10 0.15 

Washington 18.27% 1.99% 11.16% 1.93% 0.11 0.17 

West Virginia 13.87% 1.92% 7.03% 1.90% 0.14 0.27 

Wisconsin 15.57% 3.02% 10.29% 3.01% 0.19 0.29 

15.04% 1.25% 12.66% 1.19% 0.08 0.09 

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Table 7 A. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, African Americans, Wbolesale Trade, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of AI! Percentage of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Firms Employers Sales 

Alabama 

Alaska 0.17% 0.16% 

Arizona 0.72% 0.03% 0.04 

Arkansas 1.I7% 0.00% 0.00% 0.00 

California 1.07% 0.17% 0.16 

Colorado 

Connecticut 1.24% 

Delaware 2.32% 0.11% 

District of Columbia 16.50% 6.25% 

Florida 2.36% 0.13% 1.06% 0.10% 0.05 0.10 

Georgia 4.19% O.ll% 1.04% 0.10% 0.03 0.09 

Hawaii 0.40% 0.12% 

Idaho 0.25% 

Illinois 1.64% 0.04% 0.48% 0.03 

Indiana 1.02% 0.29% 0.13% 0.29% 0.29 2.22 

Iowa 0.26% 0.13% 0.34% 0.51 

Kansas 0.57% 

Kentucky 

Louisiana 3.85% 0.20% 1.29% 0.19% 0.05 0.15 

Maine 0.10% 0.06% 

Maryland 6.75% 0.26% 1.32% 0.23% 0.04 0.18 

Massachusetts 

Michigan 1.80% 0.18% 0.74% 0.18% 0.10 0.24 

Minnesota 

Mississippi 

Missouri 0.86% 0.07% 0.59% 0.07% 0.08 0.11 

Montana 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Nebraska 0.15% 0.04% 

Nevada 

New Hampshire 0.16% O.ll% 

New Jersey 1.64% 0.12% 0.71% 0.11% 0.07 0.16 

New Mexico 0.05% 0.00% 0.00% 0.00 

New York 1.96% 0.09% 0.69% 0.05 

North Carolina 2.98% 0.22% 0.51% 0.20% 0.07 0.40 

North Dakota 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Ohio 1.49% 0.17% 0.73% 0.17% 0.12 0.23 

Oklahoma 0.57% 0.03% 0.10% 0.02% 0.05 0.25 

83 
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Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Finns Employers Sales 

Oregon 0.28% 0.02% 0.16% 0.02% 0.07 0.12 

Pennsylvania 0.81% 0.04% 0.27% 0.05 

Rhode Island 0.61% 0.07% 

South Carolina 3.46% 0.09% 0.03 

South Dakota 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Tennessee 2.29% 0.06% 0.03 

Texas 2.43% 0.14% 0.06 

Utah 0.03% 0.00% 0.00% 0.00 

Vermont 0.06% 0.00% 0.00% 0.00 

Virginia 2.93% 0.26% 0.72% 0.24% 0.09 0.34 

Washington 

West Virginia 

Wisconsin 0.47% 0.15% 0.04% 0.26 

0.08% 0.00% 0.00% 0.00 

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NERA Economic Consulting 

Table 7B_ Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Hispanics and Latinos, Wholesale Trade, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 0.86% 0.09% 0.11 

Alaska 0.59% 0.32% 

Arizona 6.09% 0.94% 3.93% 0.89% 0.15 0.23 

Arkansas 0.52% 0.07% 

California 7.59% 1.29% 5.76% 1.24% 0.17 0.22 

Colorado 3.04% 0.39% 1.60% 0.38% 0.13 0.23 

Connecticut 1.98% 0.41% 0.49% 0.21 

Delaware 0.87% 0.07% 0.08 

District of Columbia 5.89% 6.25% 

Florida 19.61% 4.99% 17.96% 4.79% 0.25 0.27 

Georgia 2.26% 0.39% 1.12% 0.37% 0.17 0.33 

Hawaii 

Idaho 4.13% 0.24% 0.06 

Illinois 2.49% 0.39% 1.81% 0.38% 0.16 0.21 

Indiana 

Iowa 0.24% 0.05% 0.19 

Kansas 0.58% 0.03% 0.05 

Kentucky 

Louisiana 2.58% 0.64% 1.56% 0.62% 0.25 0.40 

Maine 0.22% 

Maryland 2.10% 0.41% 0.20 

Massachusetts 0.74% 0.24% 0.45% 0.24% 0.32 0.53 

Michigan 0.79% 0.15% 0.73% 0.14% 0.19 0.19 

Minnesota 0.36% 0.01% 0.14% 0.01% 0.03 0.05 

Mississippi 0.21% 0.02% O.ll 

Missouri 0.48% 0.08% 0.54% 0.08% 0.18 0.16 

Montana 0.39% 0.56% 

Nebraska 

Nevada 4.40% 0.46% 1.54% 0.36% 0.10 0.23 

New Hampshire 1.72% 0.16% 0.09 

New Jersey 4.53% 0.66% 2.19% 0.63% 0.15 0.29 

New Mexico 8.14% 2.63% 8.53% 2.46% 0.32 0.29 

New York 3.86% 0.49% 1.56% 0.46% 0.13 0.29 

North Carolina 0.97% 0.14% 0.61% 0.13% 0.14 0.22 

North Dakota 0.17% 0.00% 0.00% 0.00% 0.00 0.00 

Ohio 0.53% 0.02% 0.46% 0.02% 0.04 0.04 

Oklahoma 1.13% 0.80% 0.72% 0.80% 0.71 1.11 

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Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Finns Employers Sales 

Oregon 

Pennsylvania 0.57% 0.10% 0.30% 0.10% 0.18 0.32 

Rhode Island 1.05% 0.07% 1.12% 0.07 

South Carolina 0.56% 0.13% 0.23 

South Dakota 0.11% 0.01% 0.18% 0.01% 0.13 0.08 

Tennessee 0.66% 0.25% 0.39 

Texas 9.38% 1.74% 5.96% 1.68% 0.19 0.28 

Utah 0.78% 0.37% 0.56% 0.37% 0.48 0.66 

Vermont 0.18% 0.13% 

Virginia 1.57% 0.84% 0.56% 0.84% 0.54 1.49 

Washington 1.12% 0.21% 0.72% 0.20% 0.19 0.28 

West Virginia 

Wisconsin 

0.76% 

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Table 7C. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Asians, Wholesale Trade, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 

Alaska 

Arizona 2.03% 0.61% 1.67% 0.57% 0.30 0.34 

Arkansas 0.33% 0.17% 0.30% 0.18% 0.53 0.58 

California 19.97% 6.15% 22.02% 5.94% 0.31 0.27 

Colorado 1.45% 0.21% 1.47% 0.20% 0.14 0.14 

Connecticut 2.40% 0.20% 1.95% 0.18% 0.08 0.09 

Delaware 2.67% 0.26% 0.10 

District of Columbia 11.62% 15.49% 

Florida 2.82% 1.03% 3.14% 1.00% 0.37 0.32 

Georgia 4.07% 0.79% 4.80% 0.77% 0.19 0.16 

Hawaii 42.32% 20.80% 38.35% 20.28% 0.49 0.53 

Idaho 0,57% 0.70% 0.43% 0.70% 1.24 1.64 

Illinois 4.85% 1.27% 4.74% 1.25% 0.26 0.26 

Indiana 1.10% 0.41% 1.04% 0.40% 0.37 0.39 

Iowa 0.60% 

Kansas 1.69% 0.57% 1.85% 0.56% 0.34 0.30 

Kentucky 0.56% 0.08% 0.28% 0.07% 0.14 0.25 

Louisiana 2.02% 0.62% 0.31 

Maine 

Maryland 4.92% 1.42% 5.17% 1.39% 0.29 0.27 

Massachusetts 2.71% 0.46% 2.48% 0.44% 0.17 0.18 

Michigan 1.95% 0.24% 1.51% 0.22% 0.12 0.15 

Minnesota 1.42% 0.33% 0.88% 0.23 

Mississippi 0.91% 1.20% 0.99% 1.19% 1.32 1.20 

Missouri 1.13% 0.53% 1.19% 0.53% 0.47 0.45 

Montana 0.09% 0.08% 

Nebraska 

Nevada 4.09% 1.24% 2.54% \.I 8% 0.30 0.46 

New Hampshire 0.40% 0.18% 0.42% 0.17% 0.46 0.39 

New Jersey 9.62% 2.80% 9.30% 2.76% 0.29 0.30 

New Mexico 1.50% 0.58% 0.39 

New York 10.58% 2.36% 11.37% 2.30% 0.22 0.20 

North Carolina 1.43% 0.64% 1.44% 0.64% 0.45 0.44 

North Dakota 1.06% 0.50% 1.65% 0.51% 0.47 0.31 

Ohio 1.41% 0.47% 1.13% 0.46% 0.33 0.41 

Oklahoma 1.29% 0.27% 1.30% 0.25% 0.21 a 

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Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of AU of All Ratio-All Ratio 

Firms of AU Sales Employers Employer Firms Employers Sales 

Oregon 3.00% 0.58% 2.18% 0.55% 0.19 0.25 

Pennsylvania 1.69% 0.68% 1.88% 0.66% 0.40 0.35 

Rhode Island 

South Carolina 1.16% 0.35% 1.52% 0.34% 0.30 0.22 

South Dakota 0.37% 0.19% 0.45% 0.52 

Tennessee 1.13% 0.33% 1.37% 0.33% 0.30 0.24 

Texas 5.40% 1.18% 5.98% 1.15% 0.22 0.19 

Utah 1.64% 0.39% 1.48% 0.37% 0.24 0.25 

Vermont 

Virginia 4.28% 0.83% 2.83% 0.78% 0.19 0.28 

Washington 7.21% 2.37% 7.14% 2.31% 0.33 0.32 

West Virginia 0.28% 0.41% 

Wisconsin 1.33% 0.34% 0.94% 0.33% 0.26 0.35 

0.00% 0.00% 0.00% 0.00% 0.00 0.00 

88 
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Table 7D. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, American Indians and Alaska Natives, Wholesale Trade, 2002 

Percentage Percentage Percentage Disparity Disparity 

State ofAll Percentage of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Firms Employers Sales 

Alabama 

Alaska 1.95% 2,01% 2,24% 2,03% 1.03 0,91 

Arizona 1,03% 0,06% 0,15% 0,06% 0,06 0.38 

Arkansas 0,60% 0,05% 0.08 

California 0,30% 0.03% 0.22% 0.03% 0,10 0,13 

Colorado 0.40% 0.08% 0.43% 0.08% 0,21 0.19 

Connecticut 0.03% 0.00% 0.00% 0.00 

Delaware 0.06% 0.00% 0.00% 0.00 

District of Columbia 1.85% 2.45% 

Florida 0.39% 0.01% 0.11% 0.01% 0.04 0.12 

Georgia 0.42% 0.06% 0.36% 0.15 

Hawaii 

Idaho 0.16% 0.43% 0.30% 0.43% 2.71 1.42 

Illinois 0.28% 

Indiana 

Iowa 0.09% 0.03% 

Kansas 

Kentucky 0.08% 0.00% 0.00% 0.00 

Louisiana 0.24% 0.03% 0.13 

Maine 0.13% 0.00% 0.00% 0.00 

Maryland 0.14% 0.19% 

Massachusetts 0.04% 

Michigan 

Minnesota 

Mississippi 

Missouri 0.29% 0.01%) 0.05 

Montana 

Nebraska 0.00% 0.00% 0.00% 0.00% 0,00 0,00 

Nevada 0.29% 0.04% 0.14 

New Hampshire 0.05% 0.00% 0.00% 0.00 

New Jersey 0.17% 

New Mexico 31.79% 0.52% 0.98% 0.31% 0,02 0.32 

New York 

North Carolina 0.42% 0.05% 0.25% 0.05% 0.12 0.20 

North Dakota 0.50% 0.60% 0.35% 0.59% 1.20 1.70 

Ohio 0.26% 0.01% 0.04 

Oklahoma 3.28% 0.37% 1.67% 0.33% 

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Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Firms Employers Sales 

Oregon 0.58% 0.04% 0.07 

Pennsylvania 0.16% 0.01% 0.11% 0.01% 0.06 0.07 

Rhode Island 0.14% 0.00% 0.00% 0.00% 0.00 0.00 

South Carolina 0.08% 0.01% 0.14 

South Dakota 0.21% 0.00% 0.00% 0.00 

Tennessee 0.19% 0.38% 

Texas 0.51% 0.10% 0.19 

Utah 0.33% 0.02% 0.06 

Vermont 

Virginia 0.13% 

Washington 0.49% 0.14% 0.29 

West Virginia 0.21% 0.03% 0.00% 0.00% 0.16 0.00 

Wisconsin 

0.34% 0.16% 

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Table 7E. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Native Hawaiians and Pacific Islanders, Wholesale Trade, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 

Alaska 0.08% 0.00% 0.00% 0.00 

Arizona 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Arkansas 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

California 0.07% 0.00% 0.06% 0.00% 0.06 0.06 

Colorado 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Connecticut 0.00% 0.00% 0.00% 0.00% 0.00 000 

Delaware 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

District of Columbia 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Florida 

Georgia 

Hawaii 3.63% 3.10% 3.86% 3.13% 0.85 0.81 

Idaho 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Illinois 0.03% 0.00% 0.00% 0.00 

Indiana 0.01% 0.01% 

Iowa 0.01% 0.00% 0.00% 0.00 

Kansas 0.01% 0.00% 0.00% 0.00 

Kentucky 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Louisiana 

Maine 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Maryland 0.01% 0.00% 0.00% 0.00 

Massachusetts 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Michigan 0.01% 0.01% 

Minnesota 0.01% 0.00% 0.00% 0.00 

Mississippi 0.02% 0.04% 

Missouri 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Montana 0.04% 0.08% 

Nebraska 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Nevada 0.04% 0.04% 

New Hampshire 0.03% 0.05% 

New Jersey 

New Mexico 0.04% 0.00% 0.00% 0.00 

New York 

North Carolina 0.01% 0.00% 0.00% 0.00 

North Dakota 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Ohio 

Oklahoma 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

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Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 0.06% 0.10% 

Pennsylvania 

Rhode Island 0,00% 0.00% 0.00% 0,00% 0.00 0.00 

South Carolina 0,01% 0.02% 

South Dakota 0,00% 0,00% 0,00% 0.00% 0.00 0,00 

Tennessee 0,02% 0,02% 

Texas 0.01% 0,00% 

Utah 0.08% 0,03% 

Vermont 0,00% 0.00% 0.00% 0.00% 0.00 0,00 

Virginia 0.01% 0.00% 0.00% 0.00 

Washington 

West Virginia 0.00% 0,00% 0,00% 0,00% 0.00 0,00 

Wisconsin 0.01% 0,00% 0.00% 0.00 

0.00% 0,00% 0,00% 0,00% 0.00 0.00 

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Table 7F. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Women, Wholesale Trade, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Finns Employers Sales 

Alabama 12.97% 5.07% 9.55% 5.02% 0.39 0.53 

Alaska 23.62% 5.00% 8.95% 4.89% 0.21 0.55 

Arizona 18.03% 6.03% 11.10% 5.96% 0.33 0.54 

Arkansas 12.70% 2.04% 9.01% 2.01% 0.16 0.22 

California 19.57% 4.56% 15.49% 4.46% 0.23 0.29 

Colorado 17.98% 3.77% 11.65% 3.73% 0.21 0.32 

Connecticut 14.86% 2.93% 10.90% 2.87% 0.20 0.26 

Delaware 11.25% 6.34% 

District of Columbia 14.48% 12.50% 

Florida 17.03% 7.81% 13.46% 7.69% 0.46 0.57 

Georgia 15.99% 3.55% 10.58% 3.50% 0.22 0.33 

Hawaii 22.56% 8.64% 17.04% 8.29% 0.38 0.49 

Idaho 11.79% 5.09% 4.63% 5.04% 0.43 1.09 

Illinois 16.19% 3.11% 11.89% 3.07% 0.19 0.26 

Indiana 14.43% 3.63% 9.41% 3.57% 0.25 0.38 

Iowa 9.54% 6.24% 6.26% 6.25% 0.65 1.00 

Kansas 14.71% 1.92% 6.92% 1.89% 0.13 0.27 

Kentucky 14.37% 2.40% 8.35% 2.35% 0.17 0.28 

Louisiana 16.74% 4.77% 12.85% 4.71% 0.28 0.37 

Maine 12.53% 4.07% 0.33 

Maryland 16.15% 3.80% 12.40% 3.75% 0.24 0.30 

Massachusetts 15.91% 3.48% 10.12% 3.43% 0.22 0.34 

Michigan 15.11% 3.94% 9.25% 3.92% 0.26 0.42 

Minnesota 14.77% 3.45% 9.33% 3.43% 0.23 0.37 

Mississippi 14.54% 6.52% 9.98% 6.47% 0.45 0.65 

Missouri 14.75% 5.06% 9.41% 5.04% 0.34 0.53 

Montana 12.33% 2.90% 9.19% 2.88% 0.24 0.31 

Nebraska 11.90% 4.27% 8.81% 4.26% 0.36 0.48 

Nevada 13.85% 14.11% 8.78% 14.14% 1.02 1.61 

New Hampshire 12.17% 3.44% 7.28% 3.40% 0.28 0.47 

New Jersey 14.46% 3.63% 10.99% 3.58% 0.25 0.33 

New Mexico 34.74% 10.46% 18.09% 10.25% 0.30 0.57 

New York 16.38% 4.43% 12.18% 4.35% 0.27 0.36 

North Carolina 16.62% 5.97% 10.52% 5.96% 0.36 0.57 

North Dakota 12.15% 1.41% 4.94% 0.12 

Ohio 16.88% 3.81% 9.82% 3.76% 0.23 0.38 

Oklahoma 13.01% 2.65% 9.50% 2.60% 0.20 0.27 

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Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Firms Employers Sales 

Oregon 13.85% 3.40% 9.19% 3.38% 0.25 0.37 

Pennsylvania 16.37% 7.02% 9.87% 7.00% 0.43 0.71 

Rhode Islaod 12.61% 3.13% 5.54% 3.02% 0.25 0.55 

South Carolina 15.52% 6.08% 9.45% 6.07% 0.39 0.64 

South Dakota 11.83% 3.42% 8.49% 3.38% 0.29 0.40 

Tennessee 15.43% 5.96% 9.30% 5.93% 0.39 0.64 

Texas 16.53% 3.31% 10.66% 3.26% 0.20 0.3! 

Utah 14.98% 6.00% 9.47% 5.96% 0.40 0.63 

Vermont 7.59% 2.66% 4.51% 0.35 

Virginia 17.71% 5.24% 1O.29% 5.19% 0.30 0.50 

Washington 16.30% 3.62% 9.12% 3.55% 0.22 0.39 

West Virginia 13.58% 1.96% 7.88% 1.91% 0.14 0.24 

Wisconsin 15.74% 6.00% 9.18% 5.98% 0.38 0.65 

19.93% 10.36% 

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Table SA. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, African Americans, Retail Trade, 2002 

Percentage Percentage Percentage Disparity Disparity Percentage of All State of All of All Sales of All Employer Ratio-All Ratio 

Firms Employers Sales Firms Employers 

Alabama 6.57% 0.65% 2.03% 0.54% 0.10 0.27 

Alaska 1.32% 0.43% 0.33 

Arizona 1.38% 0.17% 0.39% 0.15% 0.12 0.38 

Arkansas 2.84% 0.20% 0.53% 0.15% 0.07 0.28 

California 3.27% 0.25% 0.77% 0.17% 0.08 0.22 

Colorado 1.64% 0.21% 0.88% 0.16% 0.13 0.18 

Connecticut 2.69% 0.26% 0.10 

Delaware 6.31% 0.28% 0.98% 0.04 

District of Columbia 28.21% 3.26% 8.17% 0.12 

Florida 5.14% 0.42% 1.88% 0.34% 0.08 0.18 

Georgia 11.76% 1.25% 3.02% 1.10% 0.11 0.37 

Hawaii 0.58% 0.01% 0.06% 0.02 

Idaho 

lllinois 4.13% 0.51% 1.12% 0.47% 0.12 0.41 

Indiana 1.95% 0.41% 0.86% 0.38% 0.21 0.45 

Iowa 0.34% 0.26% 0.76 

Kansas 1.38% 0.24% 0.61% 0.20% 0.17 0.33 

Kentucky 1.73% 0.56% 1.02% 0.55% 0.32 0.54 

Louisiana 7.81% 0.52% 2.46% 0.40% 0.07 0.16 

Maine 0.18% 

Maryland 13.73% 0.47% 1.85% 0.32% 0.03 0.17 

Massachusetts 2.35% 0.29% 0.59% 0.26% 0.13 0.45 

Michigan 3.85% 0.76% 0.78% 0.73% 0.20 0.94 

Minnesota 1.28% 0.31% 0.53% 0.24 

Mississippi 10.01% 0.76% 2.70% 0.52% 0.08 0.19 

Missouri 2.80% 0.21% 1.03% 0.19% 0.08 0.18 

Montana 0.10% 0.02% 

Nebraska 0.98% 0.19% 0.49% 0.19% 0.19 0.38 

Nevada 2.33% 0.11% 0.80% 0.09% 0.05 0.11 

New Hampshire 0.24% 

New Jersey 4.54% 0.42% 1.35% 0.37% 0.09 0.27 

New Mexico 0.95% 0.93% 0.53% 0.94% 0.98 1.78 

New York 5.91% 0.70% 1.75% 0.60% 0.12 0.34 

North Carolina 6.85% 0.84% 0.12 

North Dakota 0.18% 

Ohio 2.71% 0.65% 1.02% 0.63% 0.24 0.62 

Oklahoma 1.82% 0.16% 0.38% 0.14% 0.09 0.36 

95 
279 

NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 0.75% 0.37% 0.41% 0.37% 0.50 0.89 

Pennsylvania 1.95% 0.15% 0.92% 0.12% 0.08 0.13 

Rhode Island 3.89% 0.26% 0.96% 0.22% 0.07 0.23 

South Carolina 8.33% 0.68% 1.97% 0.59% 0.08 0.30 

South Dakota 

Tennessee 4.49% 0.24% 1.25% 0.16% 0.05 0.13 

Texas 3.92% 0.41% 1.04% 0.38% O.ll 0.36 

Utah 0.23% 0.60% 0.27% 0.62% 2.64 2.31 

Vermont 0.11% 0.06% 

Virginia 6.18% 0.37% 1.86% 0.32% 0.06 0.17 

Washington 1.14% 0.46% 0.67% 0.45% 0.40 0.67 

West Virginia 0.45% 0.02% 0.05 

Wisconsin 1.23% 0.15% 0.57% 0.13% 0.12 0.23 

Wyoming 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

96 
280 

NERA Economic Consulting 

Table SB. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Hispanics and Latinos, Retail Trade, 2002 

Percentage Percentage Percentage Disparity Disparity 

State ofAl! Percentage ofAJI ofAl! Ratio-All Ratio 

Finns of All Sales Employers Employer Finns Employers Sales 

Alabama 0.54% 0.16% 0.60% 0.15% 0.30 0.25 

Alaska 

Arizona 10.04% 1.65% 5.38% 1.42% 0.16 0.26 

Arkansas 

California 14.91% 2.46% 7.10% 2.11% 0.16 0.30 

Colorado 5.48% 3.52% 2.33% 3.49% 0.64 1.50 

Connecticut 2.90% 0.39% 1.84% 0.30% 0.13 0.16 

Delaware 1.57% 0.14% 0.73% 0.09% 0.09 0.12 

District of Columbia 3.53% 2.85% 

Florida 13.40% 3.22% 11.15% 2.99% 0.24 0.27 

Georgia 2.08% 0.95% 1.33% 0.91% 0.45 0.68 

Hawaii 2.15% 1.14% 1.63% 1.13% 0.53 0.69 

Idaho 

Illinois 4.13% 0.66% 2.79% 0.57% 0.16 0.20 

Indiana 1.18% 0.16% 0.52% 0.14% 0.14 0.27 

Iowa 

Kansas 2.00% 0.46% 0.23 

Kentucky 0.83% 0.12% 0.52% 0.08% 0.14 0.16 

Louisiana 

Maine 

Maryland 1.97% 0.29% 1.62% 0.25% 0.15 0.16 

Massachusetts 2.70% 0.30% 1.54% 0.22% 0.11 0.14 

Michigan 1.17% 0.99% 0.65% 1.00% 0.85 1.54 

Minnesota 0.75% 0.11% 0.63% 0.09% 0.14 0.14 

Mississippi 0.93% 0.16% 0.17 

Missouri 0.67% 0.22% 0.33 

Montana 1.20% 0.15% 0.13 

Nebraska 1.26% 0.25% 0.64% 0.21% 0.20 0.33 

Nevada 5.62% 1.08% 2.69% 1.01% 0.19 0.38 

New Hampshire 0.47% 0.05% 0.47% 0.04% 0.11 0.08 

New Jersey 7.08% 1.23% 5.35% 1.11% 0.17 0.21 

New Mexico 20.06% 7.13% 14.20% 6.76% 0.36 0.48 

New York 9.25% 1.62% 5.53% 1.44% 0.18 0.26 

North Carolina 1.24% 0.35% 0.82% 0.32% 0.28 0.39 

North Dakota 0.14% 

Ohio 0.89% 0.27% 0.68% 0.26% 0.31 0.38 

Oklahoma 1.55% 0.50% 1.04% 0.46% 0.32 0.44 

97 
281 

NERA tconomic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 1.86% 0.67% J.l8% 0.64% 0.36 0.54 

Pennsylvania 1.40% 0.38% 0.27 

Rhode Island 6.22% 0.60% 2.13% 0.41% 0.10 0.19 

South Carolina 0.64% 0.29% 0.56% 0.29% 0.46 0.52 

South Dakota 0.42% 0.26% 

Tennessee 0.56% 0.22% 0.54% 0.20% 0.39 0.37 

Texas 16.63% 3.39% 8.65% 3.02% 0.20 0.35 

Utah 2.81% 0.35% 2.19% 0.32% 0.12 0.15 

Vermont 0.73% 0.25% 0.22% 0.35 

Virginia 1.67% 0.21% 0.76% 0.18% 0.12 0.23 

Washington 1.89% 0.30% 1.64% 0.27% 0.16 0./6 

West Virginia 0.55% 0.21% 0.49% 0.20% 0.38 0.42 

Wisconsin 1.12% 0.20% 0.87% 0.19% 0.18 0.22 

0.00% 0.00% 0.00% 0.00% 0.00 0.00 

98 
282 

NERA Economic Consulting 

Table Sc. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Asians, Retail Trade, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Firms Employers Sales 

Alabama 2.10% 0.67% 3.22% 0.57% 0.32 0.18 

Alaska 3.03% 1.07% 4.06% 0.98% 0.35 0.24 

Arizona 3.30% 0.76% 5.00% 0.68% 0.23 0.14 

Arkansas 0.94% 0.36% 1.55% 0.32% 0.38 0.21 

California 16.39% 6.00% 19.43% 5.48% 0.37 0.28 

Colorado 3.07% 1.21% 5.36% 1.10% 0.39 0.20 

Connecticut 4.61% 1.13% 6.64% 0.95% 0.25 0.14 

Delaware 4.56% 1.67% 8.13% 1.59% 0.37 0.20 

District of Columbia 15.61% 7.09% 27.30% 0.45 

Florida 4.38% 1.29% 6.84% 1.17% 0.29 0.17 

Georgia 6.55% 2.36% 11.82% 2.23% 0.36 0.19 

Hawaii 55.78% 24.53% 53.07% 24.01% 0.44 0.45 

Idabo 1.01% 0.45% 1.24% 0.43% 0.45 0.35 

Illinois 5.56% 1.62% 8.47% 1.52% 0.29 0.18 

Indiana 1.04% 0.37% 1.65% 0.36% 0.36 0.22 

Iowa 0.69% 0.44% 1.05% 0.43% 0.64 0.40 

Kansas 1.56% 0.33% 1.92% 0.28% 0.21 0.15 

Kentucky 0.63% 0.24% 0.87% 0.22% 0.38 0.26 

Louisiana 3.94% 1.08% 6.77% 0.96% 0.27 0.14 

Maine 

Maryland 8.02% 2.77% 14.55% 2.61% 0.35 0.18 

Massachusetts 4.41% 1.35% 5.78% 1.24% 0.31 0.22 

Michigan 1.75% 0.56% 2.59% 0.53% 0.32 0.21 

Minnesota 1.56% 0.33% 1.30% 0.27% 0.21 0.21 

Mississippi 2.46% 1.10% 3.24% 0.95% 0.45 0.29 

Missouri 1.27% 0.50% 2.16% 0.48% 0.39 0.22 

Montana 

Nebraska 1.01% 2.03% 2.01 

Nevada 7.09% 1.34% 8.71% 1.22% 0.19 0.14 

New Hampshire 1.50% 0.33% 0.22 

New Jersey 11.01% 3.16% 14.81% 2.99% 0.29 0.20 

New Mexico 1.87% 0.66% 2.41% 0.61% 0.35 0.25 

New York 11.61% 3.65% 15.52% 3.46% 0.31 0.22 

North Carolina 2.70% 0.73% 4.01% 0.66% 0.27 0.16 

North Dakota 0.21% 0.21% 

Ohio 1.51% 0.67% 2.70% 0.65% 0.44 0.24 

Oklahoma 2.32% 0.54% 2.66% 0.37% 0.23 0.14 

99 
283 

NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage ofAl! of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 3.57% 1.22% 3.82% 0.96% 0.34 0.25 

Pennsylvania 3.09% 1.02% 4.56% 0.91% 0.33 0.20 

Rhode Island 2.69% 0.50% 2.37% 0.42% 0.19 0.18 

South Carolina 2.43% 0.85% 4.01% 0.76% (J35 (J19 

South Dakota 0.19% 0.07% 0.46% 0.07% 0.38 0.16 

Tennessee 2.11% 0.78% 3.79% 0.74% 0.37 0.19 

Texas 6.55% 2.17% 11.68% 1.95% 0.33 0.17 

Utah 1.51% 0.52% 1.67% 0.46% 0.34 0.28 

Vermont 0.38% 0.32% 

Virginia 5.30% 1.74% 7.27% 1.62% 0.33 0.22 

Washington 6.98% 2.60% 9.40% 2.43% 0.37 0.26 

West Virginia 0.51% 0.06% 0.81% 0.12 

Wisconsin 1.32% 0.65% 2.46% 0.58% 0.49 0.24 

Wyoming 0.41% 0.14% 0.77% 0.13% 0.34 0.17 

100 
284 

NERA Economic Consulting 

Table SD. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, American Indians and Alaska Natives, Retail Trade, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 0.86% 0.27% 0.53% 0.24% 0.31 0.46 

Alaska 7.94% 4.00% 9.04% 3.96% 0.50 0.44 

Arizona 2.21% 0.22% 0.73% 0.18% 0.10 0.25 

Arkansas 0.94% 0.15% 0.16 

California 

Colorado 0.87% 0.11% 0.21% 0.09% 0.12 OA5 

Connecticut 0.46% 0.04% 0.08 

Delaware 

District of Columbia 1.21% 0.12% 0.10 

Florida 0.77% 0.05% 0.22% 0.03% 0.07 0,15 

Georgia 0.67% 0.11% 0.16 

Hawaii 

Idabo 1.12% 0.37% 0.41% 0.35% 0.33 0.87 

Illinois 

Indiana 0.34% 0.04% 0,/3 

Iowa 

Kansas 0.82% 0.58% 0.61% 0.59% 0.71 0.96 

Kentucky 

Louisiana 

Maine 0.85% 0.07% 0.08 

Maryland 0.36% 0.14% 

Massachusetts 

Michigan 0.63% 0.17% 0.16% 0.16% 0.27 1.00 

Minnesota 

Mississippi 

Missouri 0.64% 0.10% 0.32% 0.08% 0.16 0.23 

Montana 

Nebraska 0.14% 0.01% 0.04 

Nevada 1.09% 0.09% 0.51% 0.07% 0,08 0.14 

New Hampshire 

New Jersey 0.21% 0.08% 0.13% OAl 

New Mexico 2.88% 0.65% 1.08% 0.63% 0.22 0.58 

New York 0.38% 0.09% 0.16% 0.08% 0.23 0.46 

North Carolina 1.l0% 0.09% 0.45% 0.06% 0.08 0.14 

101 
285 

NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

North Dakota 0.57% 0.20% 0.35% 0.17% 0.34 0.49 

Ohio 0.51% 0.14% 0.27 

Oklahoma 5.58% 1.54% 2.97% 1.46% 0.28 0.49 

Oregon 0.62% 0.06% 0.09 

Pennsylvania 0.15% 0.03% 0.21% 0.03% 0.20 0.14 

Rhode Island 

South Carolina 0.61% 0.03% 0.04 

South Dakota 1.67% 0.36% 0.34% 0.35% 0.22 1.02 

Tennessee 0.75% 0.19% 0.25 

Texas 0.95% 0.24% 0.26 

Utah 0.61% 0.04% 0.46% 0.04% 0.06 0.08 

Vermont 0.21% 

Virginia 0.40% 0.04% 0.10 

Washington 1.11% 0.32% 0.68% 0.31% 0.29 0.46 

West Virginia 

Wisconsin 0.48% 0.07% 0.14 

1.02% 0.11% 0.34% 0.11% 0.11 0.31 

102 
286 

NERA Economic Consulting 

Table SE. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Native Hawaiians and Pacific Islanders, Retail Trade, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 

Alaska 0.12% 0,00% 0,00% 0,00% 0,02 0,00 

Arizona 0,04% 0,01% 

Arkansas 0,01% 0,00% 0,00% 0,00 

California 

Colorado 

Connecticut 0,00% 0,00% 0,00% 0,00% 0.00 0,00 

Delaware 0,00% 0,00% 0,00% 0,00% 0,00 0.00 

District of Columbia 0,07% 0.00% 0,00% 0.00 

Florida 0,11% 0.00% 0.02 

Georgia 

Hawaii 8,88% 2,24% 3.89% 2,12% 0,25 0,55 

Idabo 0,07% 0,00% 0,00% 0,00 

lllinois 

Indiana 0,00% 0,00% 0,00% 0,00 

Iowa 0,01% 0.01% 

Kansas 0,01% 0,01% 

Kentucky 0,02% 0,00% 0,00% 0,00 

Louisiana 

Maine 0,00% 0,00% 0,00% 0,00% 0,00 0,00 

Maryland 

Massachusetts 0.02% 

Michigan 

Minnesota 

Mississippi 0,00% 0,00% 0,00% 0,00% 0,00 0,00 

Missouri 0,00% 0,01% 

Montana 0,01% 0,02% 

Nebraska 0,01% 0,00% 0,00% 0,00 

Nevada 0,22% 0,04% 0,06% 0.Q4% 0,18 0,61 

New Hampshire 0,01% 0,00% 0,00% 0,00 

New Jersey 

New Mexico 0,12% 0,10% 

New York 0.31% 

North Carolina 0,01% 0,00% 0,01% 0,12 

North Dakota 0.00% 0,00% 0,00% 0,00% 0,00 0,00 

Ohio 

Oklahoma 

103 
287 

NERA Economic Consu!tlng 

Percentage Percentage Percentage Disparity Disparity 

State ofAl! Percentage of All ofAl! Ratio-All Ratio 

Finns of All Sales Employers Firms Employers 

Oregon 0.10% 0.01% O.lI 

Pennsylvania 0.01% 0.00% 0.00% 0.00 

Rhode Island 

South Carolina 

South Dakota 0.02% 0.03% 

Tennessee 

Texas 

Utah 0.40% 

Vennont 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Virginia 

Washington 0.21% 0.01% 

West Virginia 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Wisconsin 

0.03% 0.00% 0.00% 0.00% 0.00 0.00 

104 
288 

NERA EconomiC Consulting 

Table SF. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Women, Retail Trade, 2002 

State 

Alabama 

Alaska 

Arizona 

Arkansas 

California 

Colorado 

Connecticut 

Delaware 

District of Columbia 

Florida 

Georgia 

Hawaii 

Idaho 

Illinois 

Indiana 

Iowa 

Kansas 

Kentucky 

Louisiana 

Maine 

Maryland 

Massachusetts 

Michigan 

Minnesota 

Mississippi 

Missouri 

Montana 

Nebraska 

Nevada 

New Hampshire 

New Jersey 

New Mexico 

New York 

North Carolina 

North Dakota 

Ohio 

Oklahoma 

Percentage 

of All 

Firms 

35.53% 

38.44% 

35.19% 

31.89% 

34.55% 

40.57% 

32.59% 

33.71% 

35.23% 

33.61% 

37.79% 

39.07% 

31.07% 

40.13% 

40.08% 

36.51% 

38.08% 

35.87% 

35.28% 

34.45% 

40.37% 

33.77% 

37.45% 

37.40% 

35.15% 

37.33% 

29.98% 

34.48% 

38.31% 

32.03% 

31.93% 

35.77% 

32.06% 

36.75% 

33.48% 

41.05% 

37.11% 

Percentage 

of All Sales 

4.65% 

7.89% 

3.78% 

6.31% 

4.72% 

4.87% 

5.07% 

3.69% 

4.21% 

4.39% 

9.67% 

4.80% 

5.00% 

4.39% 

4.22% 

5.21% 

4.42% 

5.10% 

4.98% 

3.79% 

5.77% 

4.69% 

3.57% 

6.29% 

4.61% 

5.01% 

3.75% 

3.08% 

7.52% 

4.30% 

5.60% 

5.85% 

6.22% 

4.84% 

4.04% 

4.93% 

Percentage 

of All 

Employers 

20.33% 

24.45% 

17.72% 

19.22% 

19.43% 

24.28% 

17.21% 

15.42% 

17.64% 

19.81% 

19.52% 

27.00% 

19.84% 

19.71% 

18.69% 

17.82% 

18.77% 

16.03% 

18.80% 

21.15% 

19.11% 

19.01% 

16.62% 

16.50% 

20.94% 

17.77% 

20.20% 

16.59% 

17.93% 

18.80% 

16.25% 

24.43% 

18.29% 

19.57% 

14.73% 

18.80% 

19.72% 

Percentage 

of All 

Employer 

Sales 

4.16% 

7.50% 

3.33% 

5.92% 

4.17% 

4.38% 

4.71% 

3.37% 

3.77% 

3.93% 

9.25% 

4.39% 

4.58% 

3.99% 

3.89% 

4.75% 

3.86% 

4.66% 

4.64% 

3.36% 

5.37% 

4.36% 

3.21% 

5.74% 

4.18% 

4.54% 

3.53% 

2.68% 

7.32% 

3.93% 

5.23% 

5.34% 

5.86% 

4.67% 

3.58% 

4.43% 

Disparity 

Ratio-All 

Firms 

0./3 

0.21 

O.ll 

0.20 

0.14 

0.12 

0.16 

O.ll 

0.13 

0.12 

0.25 

0.15 

0.12 

O.ll 

0.12 

0.14 

0.12 

0.14 

0.14 

0.09 

0.17 

0.13 

0.10 

0.18 

0.12 

0.17 

O.ll 

0.08 

0.23 

0.13 

0.16 

0.18 

0.17 

0.14 

0.10 

0.13 

Disparity 

Ratio 

Employers 

0.20 

0.31 

0.19 

0.31 

0.21 

0.18 

0.27 

0.22 

0.19 

0.20 

0.34 

0.22 

0.23 

0.21 

0.22 

0.25 

0.24 

0.25 

0.22 

0.18 

0.28 

0.26 

0.19 

0.27 

0.24 

0.22 

0.21 

0.15 

0.39 

0.24 

0.21 

0.29 

0.30 

0.32 

0.19 

0.22 

105 
289 

NERA EconomIC Consulting 

Percentage Percentage Percentage of All Disparity Disparity 

State of AI! of All Ratio-All Ratio 

Finns of All Sales Employers Employer Firms Employers Sales 

Oregon 37.19% 5.10% 22.87% 459% 0.14 0.20 

Pennsylvania 35.69% 3.87% 18.06% 3.42% 0.11 0.19 

Rhode Island 28.40% 8.16% 18.66% 7.89% 0.29 0.42 

South Carolina 36.36% 552% 19.01% 4.99% 0.15 0.26 

South Dakota 28.53% 2.71% 13.47% 2.45% 0.10 0.18 

Tennessee 34.09% 3.83% 18.40% 3.28% 0.11 0.18 

Texas 37.72% 438% 20.29% 3.88% 0.12 0.19 

Utah 35.89% 3.88% 1754% 359% 0.11 0.20 

Vermont 2931% 3.75% 14.65% 338% 0.13 0.23 

Virginia 4133% 430% 20.71% 3.89% 0.10 0.19 

Washington 38.56% 4.85% 21.64% 4.45% 0.13 0.21 

West Virginia 40.23% 5.68% 16.47% 5.11% 0.14 0.31 

Wisconsin 40.91% 4.19% 17.79% 3.78% 0.10 0.21 

32.69% 0.00% 22.92% 0.00% 0.00 0.00 

106 
290 

NERA Economic Consulting 

Table 9A. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, African Americans, Transportation and Warehousing, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 10.30% 1.97% 4.56% 0.85% 0.19 0.19 

Alaska 2.41% 0.18% 0.08 

Arizona 3.16% 0.34% 0.94% 0.15% 0.I1 0.16 

Arkansas 5.77% 0.70% 1.70% 0.13% 0.12 0.08 

California 5.00% 0.76% 1.93% 0.37% 0.15 0.19 

Colorado 4.74% 0.42% 0.54% 0.05% 0.09 0.09 

Connecticut 12.08% 1.23% 2.38% 0.44% 0.10 0.19 

Delaware 10.37% 1.38% 4.46% 0.58% 0.13 0.13 

District of Columbia 68.32% 9.86% 21.88% 0.14 

Florida 10.77% 1.33% 3.82% 0.50% 0.12 0.13 

Georgia 25.89% 2.75% 6.36% 1.26% O.ll 0.20 

Hawaii 0.70% 0.04% 0.00% 0.00% 0.05 0.00 

Idaho 

Illinois 9.49% 1.27% 2.92% 0.82% 0.13 0.28 

Indiana 4.42% 0.66% 1.71% 0.45% 0.15 0.26 

Iowa 0.68% 

Kansas 2.10% 0.51% 1.57% 0.45% 0.24 0.29 

Kentucky 2.45% 0.35% 1.14% 0.20% 0.14 0.18 

Louisiana 20.03% 1.97% 6.27% 0.86% 0.10 0.14 

Maine 0.84% 0.53% 0.64 

Maryland 34.99% 7.27% 10.31% 3.99% 0.21 0.39 

Massachusetts 9.88% 0.94% 1.58% 0.29% 0.10 0.18 

Michigan 6.58% 1.32% 2.89% 1.01% 0.20 0.35 

Minnesota 5.83% 0.35% 0.48% 0.06 

Mississippi 22.11% 3.99% 7.39% 1.32% 0.18 0.18 

Missouri 4.71% 0.87% 1.74% 0.52% 0.18 0.30 

Montana 

Nebraska 1.08% 0.08% 0.41% 0.07 

Nevada 

New Hampshire 

New Jersey 10.60% 0.92% 2.57% 0.34% 0.09 0.13 

New Mexico 0.81% 0.42% 0.52 

New York 17.71% 2.35% 2.61% 0.13 

North Carolina 18.20% 3.08% 6.71% 1.33% 0.17 0.20 

North Dakota 0.09% 0.21% 

Ohio 5.85% 1.10% 2.41% 0.69% 0.19 0.29 

Oklahoma 2.83% 0.33% 0.55% 0.04% 0.12 0.07 

107 
291 

NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 1.34% 0.15% 0.54% 0.11 

Pennsylvania 4.72% 0.58% 0.89% 0.31% 0.12 0.35 

Rhode Island 4.25% 0.60% 0.14 

South Carolina 23.66% 4.44% 6.88% 1.24% 0.19 0.18 

South Dakota 0.03% 0.00% 0.00% 0.00 

Tennessee 8.47% 0.97% 3.20% 0.30% 0.11 0.09 

Texas 11.07% l.ll% 1.79% 0.30% 0.10 0.17 

Utah 0.98% 0.10% 0.10 

Vermont 

Virginia 20.18% 3.31% 9.12% 1.86% 0.16 0.20 

Washington 5.61% 0.74% 0.72% 0.41% 0.13 0.58 

West Virginia 

Wisconsin 1.79% 0.24% 0.63% 0.09% 0.14 0.14 

Wyoming 0.09% 0.00% 0.00% 0.00 

108 
292 

NERA Economic Consulting 

Table 9B. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Hispanics and Latinos, Transportation and Warehousing, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 0.55% 0.10% 0.19 

Alaska 2.58% 0.16% 0.06 

Arizona 12.37% 1.71% 5.37% 1.17% 0.14 0.22 

Arkansas 0.86% 0.18% 0.21 

California 32.63% 6.57% 13.19% 3.72% 0.20 0.28 

Colorado 7.22% 1.88% 4.54% 1.54% 0.26 0.34 

Connecticut 8.33% 0.89% 0.11 

Delaware 1.11% 0.15% 

District of Columbia 2.92% 1.88% 

Florida 31.34% 6.68% 15.33% 4.35% 0.21 0.28 

Georgia 2.82% 0.45% 1.21% 0.33% 0.16 0.28 

Hawaii 

Idaho 5.04% 1.65% 0.33 

Illinois 8.42% 1.60% 4.41% 0.99% 0.19 0.22 

Indiana 1.33% 0.17% 0.56% 0.09% 0.13 0.16 

Towa 0.36% 0.13% 0.15% 0.13% 0.38 0.90 

Kansas 2.61% 0.42% 1.70% 0.19% 0.16 0.11 

Kentucky 0.63% 0.19% 0.30 

Louisiana 1.74% 0.27% 1.46% 0.22% 0.16 0.15 

Maine 0.22% 

Maryland 3.020/0 1.37% 2.82% 1.18% 0.45 0.42 

Massachusetts 5.85% 1.09% 0.19 

Michigan 1.13% 0.42% 0.37 

Minnesota 1.03% 0.36% 0.35 

Mississippi 

Missouri 0.42% 0.10% 0.56% 0.07% 0.24 0.13 

Montana 1.05% 

Nebraska 

Nevada 6.58% 1.41% 1.77% 0.89% 0.21 0.50 

New Hampshire 0.63% 0.13% 

New Jersey 21.15% 3.01% 5.62% 1.41% 0.14 0.25 

New Mexico 32.79% 6.99% 21.15% 4.86% 0.21 0.23 

New York 19.20% 2.89% 4.42% 1.12% 0.15 0.25 

North Carolina 

North Dakota 0.59% 0.20% 0.34 

Ohio 

Oklahoma 1.91% 0.78% 

109 
293 

NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All ofAl! Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 3.19% 0.64% 0.92% 0.38% 0.20 0.41 

Pennsylvania 1.51% 0.37% 0.25 

Rhode Island 4.49% 1.02% 

South Carolina 0.83% 0.17% 0.14% 0.07% 0.21 0.53 

South Dakota 0.54% 0.36% 0.67 

Tennessee 0.56% 0.11% 0.42% 0.07% 0./9 0.17 

Texas 31.55% 6.07% 18.32% 3.40% 0.19 0.19 

Utah 3.79% 0.35% 0.09 

Vermont 0.39% 0.20% 

Virginia 4.29% 0.72% 1.61% 0.26% 0./7 0.16 

Washington 3.77% 0.67% 3.04% 0.46% 0.18 0./5 

West Virginia 0.24% 0.03% 0.12 

Wisconsin 0.88% 0.33% 0.37 

2.03% 

110 
294 

NERA Economic Consulting 

Table 9C. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Asians, Transportation and Warehousing, 2002 

Percentage Percentage Percentage Disparity Disparity 

State ofAl! Percentage ofAl! ofAl! Ratio-All Ratio 

Finns of All Sales Employers Finns Employers 

Alabama 0.56% 0.13% 0.24 

Alaska 6.36% 0.29% 0.25% 0.05 

Arizona 1.92% 0.30% 0.78% 0.21% 0.16 0.26 

Arkansas 0.23% 0.03% 0.30% 0.15 

California 14.32% 4.26% 9.00% 3.21% 0.30 0.36 

Colorado 1.20% 0.31% 0.26 

Connecticut 

Delaware 0.90% 0.59% 

District of Columbia 5.20% 5.00% 

Florida 1.62% 0.30% 0.80% 0.22% 0.18 0.27 

Georgia 1.45% 0.29% 0.60% 0.21% 0.20 0.34 

Hawaii 61.91% 22.60% 30.97% 20.99% 0.37 0.68 

Idaho 

Illinois 7.89% 1.35% 2.08% 0.94% 0./7 0.45 

Indiana 0.44% 0.14% 0.20% 0.13% 0.32 0.63 

Iowa 0.26% 0.10% 0.24% 0.37 

Kansas 0.76% 0.46% 0.91% 0.46% 0.61 0.50 

Kentucky 0.30% 0.26% 0.68% 0.26% 0.87 0.38 

Louisiana 2.64% 0.27% 0.83% 0.15% 0.10 0.18 

Maine 0.20% 0.11% 0.16% 0.53 

Maryland 4.29% 1.07% 

Massachusetts 2.30% 0.37% 0.68% 0.24% 0.16 0.35 

Michigan 1.88% 0.48% 1.18% 0.25 

Minnesota 1.07% 0.30% 0.77% 0.28% 0.28 0.37 

Mississippi 0.06% 

Missouri 0.32% 0.12% 0.39 

Montana 0.21% 0.67% 

Nebraska 

Nevada 4.08% 2.02% 1.77% 1.87% 0.49 1.06 

New Hampshire 0.36% 

New Jersey 8.06% 1.33% 3.40% 0.92% 0./7 0.27 

New Mexico 

New York 18.52% 4.62% 5.43% 2.80% 0.25 0.52 

North Carolina 1.11% 0.16% 0.18% 0.09% 0.14 0.50 

North Dakota 0.03% 0.00% 0.00% 0.1)0 

Ohio 0.57% 0.28% 0.67% 0.27% 0.49 0.39 

Oklahoma 0.24% 0.12% 0.23% 0.50 

111 
295 

NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of AI! Percentage of AI! of All Ratio-All Ratio 

Firms ofAl! Sales Employers Employer Finns Employers Sales 

Oregon 0.82Y, 039% 038% 039% OA8 1.03 

Pennsylvania 1.54% 0.23% 0.23% 0.14% 0.J5 0.62 

Rhode Island 

South Carolina 0.45% 033% 

South Dakota 0.05% 0.10% 

Tennessee 

Texas 1.84% 033% 0.69% 021% 0.J8 0.31 

Utah 1.42% 0.07% 

Vermont 0.11% 0.03% 0.00% 0.23 

Virginia 10.76% 0.97% 0.98% 020% 0.09 020 

Washington 8.12% 1.85% 1.23% 1.35% 0.23 UO 

West Virginia 0.13% 0.14% 

Wisconsin 1.23% O.ll% 0.12% 0.02% 0.09 0.19 

0.09% 0.15% 

112 
296 

NERA Economic Consulting 

Table 90. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, American Indians and Alaska Natives, Transportation and Warehousing, 2002 

Percentage Percentage Percentage Disparity Disparity 

State ofAIl Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 1.56% 0.64% 0.47% 0.42% 0.11 0.91 

Alaska 9.62% 2.40% 8.04% 2.28% 0.25 0.28 

Arizona 1.12% 0.06% 0.05 

Arkansas 0.75% 0.06% 0.00% 0.00% 0.09 0.00 

California 1.93% 0.30% 0.48% 0.11% 0.16 0.23 

Colorado 2.32% 0.65% 1.54% 0.54% 0.28 0.35 

Connecticut 

Delaware 

District of Columbia 0.11% 0.00% 

Florida 0.68% 0.11% 0.32% 0.04% 0.16 0.13 

Georgia 0.86% 0.11% 0.13 

Hawaii 0.39% 0.00% 0.00% 0.00 

Idaho 

Illinois 0.75% 0.09% 0.04% 0.12 

Indiana 0.71% 0.13% 0.18 

Iowa 

Kansas 

Kentucky 

Louisiana 0.99% 0.19% 0.19 

Maine 0.37% 0.26% 0.70 

Maryland 

Massachusetts 

Michigan 0.92% 0.23% 0.26% 0.18% 0.24 0.69 

Minnesota 0.62% 0.04% 0.07 

Mississippi 

Missouri 

Montana 1.82% 0.25% 0.14 

Nebraska 

Nevada 2.01% 0.69% 0.35 

New Hampshire 0.33% 

New Jersey 1.09% 

New Mexico 

New York 0.34% 0.11% 0.34 

North Carolina 

North Dakota 0.86% 0.09% 0.31% 0.11 

Ohio 0.48% 0.10% 0.02% 0.21 

Oklahoma 8.64% 3.02% 4.82% 2.05% 

113 
297 

NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Finns Employers Sales 

Oregon 0.78% 0.17% 0.22 

Pennsylvania 

Rhode Island 0.41% 0.00% 0.00% 0.00 

South Carolina 

South Dakota 

Tennessee 0.64% 0.12% 0.19 

Texas 0.84% 0.08% 0.09% 0.01% 0./0 0.12 

Utah 0.19% 0.14% 

Vermont 

Virginia 0.84% 0.54% 0.33% 0.46% 0.64 1.38 

Washington 1.64% 0.35% 1.69% 0.27% 0.22 0.16 

West Virginia 

Wisconsin 0.63% 0.08% 0.13 

1.20% 0.15% 

114 
298 

NERA Economic Consulting 

Table 9E. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Native Hawaiians and Pacific Islanders, Transportation and Warehousing, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 

Alaska 0.14% 0.12% 

Arizona 

Arkansas 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

California 0.41% 0.12% 0.31 

Colorado 0.05% 0.00% 0.00% 0.00 

Connecticut 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Delaware 

District of Columbia 0.06% 0.00% 

Florida 

Georgia 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Hawaii 6.44% 4.39% 9.40% 4.24% 0.68 0.45 

Idaho 

Illinois 

Indiana 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Iowa 0.01% 0.00% 0.00% 0.00 

Kansas 0.09% 0.30% 

Kentucky 0.02% 0.04% 

Louisiana 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Maine 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Maryland 

Massachusetts 

Michigan 0.00% 0.00% 0.00% 0.00 

Minnesota 

Mississippi 0.0]% 0.00% 0.00% 0.00 

Missouri 

Montana 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Nebraska 0.00% 0.00% 0.00% 0.00% 0.00 OJJO 

Nevada 

New Hampshire 0.00% 0.00% 0.00% 0.00% 0.00 OJ)O 

New Jersey 

New Mexico 

New York 

North Carolina 0.00% 0.00% 0.00% 0.00 

North Dakota 0.00% 0.00% 0.00% 0.00% 0.00 OJ)O 

Ohio O.Ol~/o 0.00% 0.00% 0.00 

Oklahoma 

115 
299 

NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State ofAl! Percentage of All ofAl! Ratio-All Ratio 

Finns of All Sales Employers Employer Finns Employers Sales 

Oregon 0.14% 

Pennsylvania 

Rhode Island 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

South Carolina 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

South Dakota 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Tennessee 0.01% 

Texas 

Utah 0.46% 0.12% 0.49% 0.26 

Vermont 

Virginia 

Washington 

West Virginia 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Wisconsin 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

0.00% 0.00% 0.00% 0.00% 0.00 0.00 

116 
300 

NERA Economic Consulting 

Table 9F. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Women, Transportation and Warehousing, 2002 

State 

Alabama 

Alaska 

Arizona 

Arkansas 

California 

Colorado 

Connecticut 

Delaware 

District of Columbia 

Florida 

Georgia 

Hawaii 

Idaho 

Illinois 

Indiana 

Iowa 

Kansas 

Kentucky 

Louisiana 

Maine 

Maryland 

Massachusetts 

Michigan 

Minnesota 

Mississippi 

Missouri 

Montana 

Nebraska 

Nevada 

New Hampshire 

New Jersey 

New Mexico 

New York 

North Carolina 

North Dakota 

Ohio 

Oklahoma 

Percentage 

of All 

Finns 

12.52% 

9.79% 

12.88% 

9.78% 

9.35% 

13.15% 

16.76% 

11.72% 

13.25% 

13.03% 

8.44% 

9.79% 

10,48% 

13,06% 

7,41% 

7.51% 

11.30% 

12,73% 

9.27% 

11.70% 

12,60% 

12,96% 

10,58% 

9.42% 

12,50% 

9,76% 

9,89% 

17.85% 

10,60% 

11.89% 

10,56% 

9,09% 

10,92% 

6,90% 

14.13% 

12.33% 

Percentage 

of All Sales 

6,34% 

3.78% 

4.79% 

2,71% 

4,63% 

5,49% 

4,49% 

7,48% 

4,34% 

5,42% 

6,58% 

5,75% 

5,56% 

4,87% 

3,82% 

3,57% 

3,05% 

6,02% 

6,42% 

7,03% 

5.79% 

6,13% 

6,10% 

4,73% 

9.35% 

5,14% 

12,08% 

3.85% 

4.40% 

4.71% 

3,43% 

5,77% 

5,11% 

4,11% 

5,37% 

4,57% 

Percentage 

of All 

Employers 

10,55% 

8,29% 

13.Q4% 

8,87% 

11,48% 

10.41% 

14.48% 

13,67% 

13.71% 

12.46% 

14.48% 

7,51% 

12.12% 

10,25% 

5.13% 

10.44% 

15,77% 

]0,73% 

8,03% 

14.20% 

11.26% 

11.43% 

7.24% 

9,96% 

12,04% 

6,67% 

7,59% 

9,91% 

7.29% 

11.36% 

10,33% 

11.63% 

]3,93% 

6,37% 

11.27% 

10,10% 

Percentage 

of All 

Employer 

Sales 

5.95% 

3,64% 

4.40% 

2,33% 

4,59% 

5,27% 

3,94% 

3,70% 

5.16% 

6,59% 

5,56% 

5,56% 

4,52% 

3,49% 

3.57% 

2,74% 

5,78% 

7,03% 

6,45% 

5.41% 

5.56% 

6,13% 

4,73% 

9.44% 

4,79% 

12,66% 

2,91% 

4.29% 

4,64% 

3,05% 

5,61% 

5,03% 

4,13% 

5.22% 

3,85% 

Disparity 

Ratio-All 

Firms 

0.51 

0.39 

0.37 

0,28 

0,50 

0.42 

0,27 

0,64 

0.33 

0.42 

0,78 

0,59 

0,53 

0.37 

0,52 

0.48 

0.27 

0.47 

0,69 

0,60 

0.46 

0.47 

0,58 

0,50 

0.75 

0,53 

1.22 

0,22 

0.41 

0.40 

0.33 

0,63 

0.47 

0,60 

0.38 

0,37 

Disparity 

Ratio 

Employers 

0.56 

0.44 

0.34 

0.26 

0.40 

0,51 

0,27 

0,27 

0.41 

0.46 

0,74 

0.46 

0.44 

0,68 

0.34 

0,17 

0,54 

0,88 

0.45 

0.48 

0.49 

0,85 

0.48 

0,78 

0,72 

1.67 

0.29 

0,59 

0.41 

0,29 

0,48 

0.36 

0,65 

0.46 

0,38 

117 
301 

NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Firms Employers 

Oregon 11.61% 7.14% 12.75% 7.32% 0.62 0.57 

Pennsylvania 11.00% 5.67% 11.12% 5.76% 0.52 0.52 

Rhode Island 16.29% 2.12% 8.02% 0./3 

South Carolina 12.90% 4.55% 12.49% 3.75% 0.35 0.30 

South Dakota 7.06% 5.02% 8.33% 5.41% 0.71 0.65 

Tennessee 11.63% 3.61% 9.69% 3.40% 0.31 0.35 

Texas 11.05% 4.23% 10.26% 3.94% 0.38 0.38 

Utah 14.15% 3.68% 9.77% 3.45% 0.26 0.35 

Vermont 11.43% 1.22% 

Virginia 11.52% 6.17% 12.80% 6.16% 0.54 0.48 

Washington 11.85% 4.70% 10.27% 4.50% 0.40 0.44 

West Virginia 12.59% 5.39% 11.23% 5.05% 0.43 0.45 

Wisconsin 11.09% 5.42% 10.04% 5.26% 0.49 0.52 

8.67% 3.76% 9.02% 3.77% 0.43 0.42 

118 
302 

NERA Economic Consulting 

Table lOA. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, African Americans, Information, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage ofAll of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 6.38% 0.44% 2.95% OAI% 0.G7 0.14 

Alaska 

Arizona 1.53% 0.05% 0.23% 0.04% 0.04 0.17 

Arkansas 

California 3.76% 0.29% 2.38% 0.26% 0.08 0.1I 

Colorado 1.42% 0.05% 0.34% 0.04 

Connecticut 3.88% 0.11% 0.77% 0.09% 0.03 O.ll 

Delaware 6.56% 0.80% 

District of Columbia 14.63% 0.28% 1.61% 0.23% 0.02 0.14 

Florida 5.06% 0.37% 1.00% 0.35% 0.07 0.34 

Georgia 13.74% 0.18% 3.50% 0.15% 0.01 0.04 

Hawaii 1.74% 0.29% 

Idaho 0.39% 0.00% 0.00% 0.00 

Illinois 6.22% 2.21% 2.37% 2.19% 0.35 0.93 

Indiana 2.89% 0.38% 0.13 

Iowa 

Kansas 

Kentucky 1.68% 

Louisiana 

Maine 0.14% 0.00% 0.00% 0.00 

Maryland 14.86% 0.44% 3AO% 0.36% 0.03 0.10 

Massachusetts 2.76% 0.04% 0.01 

Michigan 4.86% 0.32% 2.98% 0.29% 0.07 0.10 

Minnesota 1.57% 0.14% 0.51% 0.14% 0.09 0.27 

Mississippi 8.86% 0.16% 1.46% 0.02 

Missouri 2.94% 0.05% 0.54% 0.02 

Montana 0.09% 0.00% 

Nebraska 1.87% 0.06% 1.81% 0.03 

Nevada 1.89% 0.20% 0.42% 0.16% 0.10 0.39 

New Hampshire 0.24% 0.19% 

New Jersey 

New Mexico 1.28% 0.39% 

New York 

North Carolina 7.89% 0.14% 1.55% 0.11% 0.02 0.07 

North Dakota 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Ohio 3.95% 0.09% 0.02 

Oklahoma 

119 
303 

NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 

Pennsylvania 2.76% 0.09% 0.38% 0.08% 0.03 0.20 

Rhode Island 1.79% 0.38% 

South Carolina 7.18% 0.11% 0.01 

South Dakota 0.14% 0.00% 0.00% 0.00 

Tennessee 3.98% 0.20% 1.39% 0.17% 0.05 0.12 

Texas 4.93% 0.12% 1.73% 0.10% 0.02 0.06 

Utah 0.28% 0.23% 

Vermont 0.27% 0.00% 0.00% 0.00 

Virginia 6.47% 0.15% 2.91% 0.13% 0.02 0.05 

Washington 

West Virginia 0.60% 0.00% 0.00% 0.00 

Wisconsin 

0.18% 0.00% 

120 
304 

NERA Economic Consulting 

Table lOB. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Hispanics and Latinos, Information, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of AI! Percentage of AI! of AI! Ratio-All Ratio 

Finns of AI! Sales Employers Employer Finns Employers Sales 

Alabama 1.32% 0,03% 0,57% 0,03% 0,03 0,05 

Alaska 0,62% 0,91% 

Arizona 4,19% 0,26% 2.46% 0.22% 0,06 0,09 

Arkansas 

California 7,26% 0.49% 2,86% 0.41% 0,07 0.14 

Colorado 

Connecticut 

Delaware 2,06% 0,80% 

District of Columbia 3.73% 

Florida 14,28% 1.31% 10,21% 1.14% 0,09 O,ll 

Georgia 1.67% 0,06% 0,04 

Hawaii 5,92% 

Idabo 4.51% 0.10% 1.75% 0,09% 0,02 0,05 

Illinois 3,26% 0,19% 0,71% 0,16% 0,06 0,23 

Indiana 1.56% 

Iowa 0.56% 0,11% 

Kansas 0,87% 

Kentucky 0.68% 0,12% 

Louisiana 

Maine 1.91% 0.11% 0,79% 0,08% 0.06 0,]0 

Maryland 2.21% 0,18% 1.42% 0.15% 0.08 O,lO 

Massachusetts 2.76% 0,12% 3,14% 0,10% 0,04 0,03 

Michigan 1.41% 0,03% 0,02 

Minnesota 

Mississippi 0.34% 0,21% 

Missouri 

Montana 0.37% 0,51% 

Nebraska 0,80% 0.36% 

Nevada 2.58% 0,19% 1.25% 0,09% 0,07 0,08 

New Hampshire 0.59% 0.19% 

New Jersey 3,93% 0,14% 1.96% 0,11% 0,04 0,06 

New Mexico 9.23% 0,50% 0.05 

New York 4,77% 0,13% 1.92% 0.10% 0,03 0,05 

North Carolina 1.66% 0,07% 1.43% 0,06% 0,04 0,04 

North Dakota 0.82% 0,00% 0.00% 0.00% 0,00 0,00 

Ohio 0,95% 0.02% 0.19% 0.02% 0.02 0.09 

Oklahoma 

121 
305 

NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Firms Employers Sales 

Oregon 1.61% 0.18% 0.11 

Pennsylvania 0.88% 0.17% 

Rhode Island 

South Carolina 0.46% 0.00% 0.00% 0.00 

South Dakota 0.28% 0.35% 

Tennessee 

Texas 10.58% 0.29% 5.12% 0.25% 0.03 0.05 

Utah 

Venuont 0.54% 0.25% 

Virginia 2.85% 0.21% 0.65% 0.20% 0.07 0.30 

Washington 1.58% 0.04% 0.88% 0.04% 0.02 0.04 

West Virginia 0.50% 0.00% 0.00% 0.00 

Wisconsin 

1.76% 0.00% 

122 
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Table lOe. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Asians, Information, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Finns Employers Sales 

Alabama 

Alaska 1.70% 0.91% 

Arizona 1.86% 0.14% 1.92% 0.12% 0.08 0.06 

Arkansas 0.88% 

California 7.57% 1.50% 7.61% 1.45% 0.20 0.19 

Colorado 2.55% 0.76% 2.49% 0.75% 0.30 0.30 

Connecticut 2.05% 0.37% 0.18 

Delaware 3.09% 0.40% 

District of Columbia 2.56% 0.54% 0.26% 0.48 

Florida 1.79% 0.23% 2.05% 0.21% 0.13 0.10 

Georgia 2.44% 0.60% 3.41% 0.58% 0.25 0.17 

Hawaii 26.91% 3.49% 25.14% 3.19% 0.13 0.13 

Idaho 

Illinois 3.48% 3.97% 

Indiana 

Iowa 0.56% 0.04% 0.07 

Kansas 

Kentucky 0.71% 0.23% 

Louisiana 1.78% 0.12% 0.07 

Maine 0.34% 0.00% 0.00% 0.00% 0.01 0.00 

Maryland 3.97% 3.03% 0.26% 0.09 

Massachusetts 3.50% 0.24% 3.26% 0.07 

Michigan 1.41% 0.15% 0.11 

Minnesota 1.08% 0.14% 0.68% 0.13% 0.12 0.19 

Mississippi 2.43% 0.08% 0.03 

Missouri 1.29% 0.04% 1.76% 0.03 

Montana 0.09% 0.26% 

Nebraska 0.87% 0.00% 0.00% 0.00 

Nevada 5.87% 0.42% 0.07 

New Hampshire 0.94% 0.38% 

New Jersey 6.29% 0.54% 4.85% 0.09 

New Mexico 

New York 5.49% 0.48% 4.43% 0.45% 0.09 0.10 

North Cam lina 2.15% 0.22% 1.49% 0.20% 0.10 0.14 

North Dakota 0.33% 0.00% 0.00% 0.00 

Ohio 1.81% 0.38% 0.21 

Oklahoma 0.76% 0.35% 

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Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 0.80% 0.51% 0.64 

Pennsylvania 1.71% 0.36% 1.74% 0.21 

Rhode Island 2.09% 0.20% 2.69% 0.15% 0.09 0.06 

South Carolina 0.39% 0.14% 

South Dakota 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Tennessee 

Texas 3.78% 0.25% 4.15% 0.23% 0.07 0.06 

Utah 1.42% 0.15% 0.1I 

Vermont 0.09% 0.00% 0.00% 0.00 

Virginia 5.85% 0.35% 4.11% 0.33% 0.06 0.08 

Washington 4.50% 0.11% 3.23% 0.02 

West Virginia 0.70% 0.61% 

Wisconsin 

Wyoming 0.35% 0.00% 

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Table IOD. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, American Indians and Alaska Natives, Information, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Finns of All Sales Employers Finns Employers 

Alabama 2,22% 

Alaska 6,64% 1.86% 11.87% 0,28 

Arizona 

Arkansas 

California 1.17% 0,04% 0,04 

Colorado 

Connecticut 

Delaware 0,39% 0.00% 0.00% 0,00 

District of Columbia 0.52% 0.00% 0,00% 0,00 

Florida 0.21% 0,00% 0,16% 0,00% 0,02 0,02 

Georgia 0,86% 0,02% 0,17% 0,02 

Hawaii 

Idaho 0.31% 

Illinois 0.27% 0,00% 0,00% 0,00 

Indiana 

Iowa 

Kansas 

Kentucky 0.21% 0,23% 

Louisiana 0,92% 

Maine 0,07% 0.20% 

Maryland 1.07% 0.37% 

Massachusetts 

Michigan 0,69% 0.09% 

Minnesota 0,07% 0,06% 

Mississippi 1.89% 

Missouri 0,23% 0.00% 0,00% 0,00 

Montana 0.92% 0,26% 

Nebraska 0,93% 1.63% 

Nevada 

New Hampshire 

New Jersey 

New Mexico 1.82% 0.19% 

New York 0.58% 0,01% 0.26% 0,01 

Nortb Carolina 0,60% 0.02% 0,]]% 0,04 

Nortb Dakota 2,14% 0,62% 3,07% 0.29 

Ohio 0,07% 0.00% 0,00% 0.00 

Oklahoma 

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Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 1.94% 0.08% 0.04 

Pennsylvania 

Rhode Island 0.10% 0.00% 0.00% 0.00 

South Carolina 1.51% 

South Dakota 0.85% 0.70% 

Tennessee 0.43% 0.27% 

Texas 1.21% 0.06% 0.05 

Utah 0.19% 0.00% 0.00% 0.00 

Vermont 0.27% 0.25% 

Virginia 0.12% 0.09% 

Washington 

West Virginia 0.40% 0.01% 0.00% 0.00% 0.01 0.00 

Wisconsin 0.42% 0.13% 0.66% 0.13% 0.31 0.20 

1.06% 0.46% 

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Table 10E. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Native Hawaiians and Pacific Islanders, Information, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of AI! Percentage of All of AI! Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 0.03% 0.11% 

Alaska 

Arizona 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Arkansas 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

California 

Colorado 0.01% 0.00% 0.00% 0.00 

Connecticut 0.24% 

Delaware 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

District of Columbia 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Florida 0.01% 0.00% 0.00% 0.00 

Georgia 

Hawaii 6.79% 1.72% 3.47% 0.25 

Idaho 0.08% 0.00% 0.00% 0.00 

Illinois 

Indiana 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Iowa 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Kansas 0.00% 0.00% 0.00% 0.00% 000 0.00 

Kentucky 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Louisiana 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Maine 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Maryland 0.01% 0.06% 

Massachusetts 0.07% 

Michigan 

Minnesota 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Mississippi 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Missouri 

Montana 0.00% 0.00% 0.00% 0.00 

Nebraska 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Nevada 

New Hampshire 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

New Jersey 0.02% 0.00% 0.00% OJ)O 

New Mexico 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

New York 

North Carolina 0.01% 0.00% 0.00% 0.00 

North Dakota 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Ohio 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Oklahoma 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

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Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Finns of All Sales Employers Firms Employers 

Oregon 0.24% 

Pennsylvania 0.01% 0.03% 

Rhode Island 0.10% 0.00% 0.00% 0.00 

South Carolina 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

South Dakota 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Tennessee 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Texas 0.02% 0.00% 0.00% 0.00 

Utah 

Vennont 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Virginia 0.51% 

Washington 

West Virginia 0.10% 0.00% 0.00% 0.00 

Wisconsin 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

0.00% 0.00% 0.00% 0.00 

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Table IOF. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Women, Information, 2002 

Percentage Percentage Percentage Disparity Disparity 

State ofAl! Percentage ofAl! ofAl! Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 28.95% 2.07% 15.91% 1.91% 0.07 0.12 

Alaska 23.30% 1.60% 22.37% 1.53% 0.07 0.07 

Arizona 25.16% 7.63% 15.40% 7.50% 0.30 0.49 

Arkansas 25.97% 3.30% 10.45% 3.25% 0.13 0.31 

California 21.07% 2.27% 12.44% 2.12% 0.11 0.17 

Colorado 26.32% 1.07% 14.26% 0.94% 0.04 0.07 

Connecticut 23.80% 3.83% 11.41% 0.16 

Delaware 22.01% 12.80% 

District of Columbia 35.78% 13.98% 1.14% 0.08 

Florida 24.10% 3.03% 16.45% 2.88% 0.13 0.17 

Georgia 27.26% 5.68% 15.89% 5.53% 0.21 0.35 

Hawaii 24.47% 1.40% 12.14% 1.06% 0.06 0.09 

Idaho 23.00% 2.33% 14.04% 2.18% 0.10 0.16 

Illinois 25.39% 3.24% 13.48% 3.08% 0.13 0.23 

Indiana 24.90% 2.28% 0.09 

Iowa 24.39% 1.46% 11.34% 1.33% 0.06 0.12 

Kansas 22.83% 2.19% 11.37% 2.13% 0.10 0.19 

Kentucky 24.77% 3.54% 13.75% 3.40% 0.14 0.25 

Louisiana 22.02% 8.22% 17.01% 8.11% 0.37 0.48 

Maine 27.68% 5.20% 3.94% 5.00% 0.19 1.27 

Maryland 30.29% 1.34% 16.93% 0.04 

Massachusetts 29.96% 0.89% 10.46% 0.74% 0.03 0.07 

Michigan 31.44% 1.99% 17.42% 1.75% 0.06 0.10 

Minnesota 27.81% 1.12% 10.53% 0.97% 0.04 0.09 

Mississippi 25.02% 1.99% 9.39% 1.85% 0.08 0.20 

Missouri 22.86% 2.64% 0.12 

Montana 29.27% 3.38% 14.14% 0.12 

Nebraska 20.95% 8.10% 15.91% 8.05% 0.39 0.51 

Nevada 19.55% 7.32% 10.97% 7.09% 0.37 0.65 

New Hampshire 25.24% 1.36% 6.04% 0.05 

New Jersey 23.71% 1.20% 13.77% 0.05 

New Mexico 29.08% 3.08% 15.89% 2.75% O.ll 0.17 

New York 29.98% 1.40% 14.23% 1.20% 0.05 0.08 

North Carolina 21.84% 2.51% 8.70% 2.38% 0.11 0.27 

North Dakota 23.72% 0.85% 9.58% 0.73% 0.04 0.08 

Ohio 28.40% 2.39% 9.12% 2.16% 0.08 0.24 

Oklahoma 22.46% 3.87% 13.15% 3.77% 0.17 

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Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 23.14% 1.90% 5.85% 1.56% 0.08 0.27 

Pennsylvania 25.27% 2.43% 11.51% 2.29% 0.10 0.20 

Rhode Island 29.05% 21.27% 17.31% 0.73 

South Carolina 27.79% 3.60% 14.82% 3.36% 0.13 0.23 

South Dakota 27.48% 16.84% 

Tennessee 20.96% 2.20% 14.58% 2.05% 0.11 0.14 

Texas 25.77% 2.05% 13.57% 1.92% 0.08 0.14 

Utah 20.68% 2.98% 12.16% 2.72% 0.14 0.22 

Vermont 31.34% 6.10% 12.56% 5.53% 0.19 0.44 

Virginia 29.28% 2.17% 11.13% 2.07% 0.07 0.19 

Washington 27.27% 0.84% 11.60% 0.75% 0.03 0.06 

West Virginia 23.65% 1.35% 11.31% 1.18% 0.06 0.10 

Wisconsin 24.95% 1.91% 8.87% 1.77% 0.08 0.20 

25.40% 6.95% 13.89% 0.27 

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Table llA. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, African Americans, Finance and Insurance, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 

Alaska 0.98% 0.25% 

Arizona 1.45% 0.02% 0.02 

Arkansas 2.35% 0.07% 0.46% 0.04% 0.03 0.08 

California 2.91% 0.09% 1.32% 0.04% 0.03 0.03 

Colorado 1.10% 0.04% 0.42% 0.03% 0.04 0.07 

Connecticut 

Delaware 

District of Columbia 11.83% 0.36% 7.82% 0.35% 0.03 0.05 

Florida 4.05% 0.17% 1.82% 0.14% 0.04 0.08 

Georgia 8.22% 0.26% 4.08% 0.18% 0.03 0.04 

Hawaii 

Idaho 0.11% 0.14% 

lIlinois 3.13% 0.15% L71% 0.13% 0.05 0.08 

Indiana 3.12% 0.08% 2.94% 0.05% 0.02 0.02 

Iowa 

Kansas 0.87% 0.01% 0.0] 

Kentucky 1.36% 0.07% 0.48% 0.06% 0.05 0.13 

Louisiana 5.75% 0.34% 2.74% 0.28% 0.06 0.10 

Maine 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Maryland 9.29% 0.28% 3.82% 0.03 

Massachusetts 1.37% 0.02% 0.49% 0.01 

Michigan 4.21% 0.13% 1.40% 0.08% 0.03 0.06 

Minnesota 0.69% 0.02% 0.03 

Mississippi 7.03% 0.20% L76'10 0.13% 0.03 0.07 

Missouri 2.39% 0.06% 1.30% 0.02 

Montana 0.03% 0.08% 

Nebraska 

Nevada 1.61% 0.10% 1.30% 0.05% 0.06 0.04 

New Hampshire 

New Jersey 3.86% 0.07% 1.67% 0.02 

New Mexico 0.75% 0.04% 0.05 

New York 3.19% 0.07% 1.21% 0.06% 0.02 0.05 

North Carolina 6.62% 0.14% 3.36% 0.08% 0.02 0.02 

North Dakota 0.03% 0.10% 

Ohio 2.33% 0.04% 1.43% 0.03% 0.02 0.02 

Oklahoma 1.94% 0.05% 0.37% 

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Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of AI! Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 0.45% 

Pennsylvania 1.87% 0.10% 1.19% 0.08% 0.05 0.07 

Rhode Island 1.12% 0.01% 0.78% 0.01% 0.01 0.01 

South Carolina 7.28% 0.22% 2.67% 0.13% 0.03 0.05 

South Dakota 0.22% 0.00% 0.00% 0.00 

Tennessee 4.03% 0.09% 1.73% 0.06% 0.02 0.04 

Texas 3.05% 0.11% 1.44% 0.08% 0.04 0.06 

Utah 

Vermont 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Virginia 5.21% 0.08% 2.49% 0.06% O.OJ 0.02 

Washington 1.36% 0.24% 1.04% 0.23% 0.18 0.22 

West Virginia 

Wisconsin 0.92% 0.01% 0.01 

0.11% 0.34% 

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Table lIB. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Hispanics and Latinos, Finance and Insurance, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Firms Employers Sales 

Alabama 039% 0.01% 0.03 

Alaska 0.54% 0.25% 

Arizona 4.05% 0.21% 4.80% 0.17% 0.05 0.04 

Arkansas 

California 834% 039% 4.43% 0.25% 0.05 0.06 

Colorado 3.54% 0.29% 2.80% 0.22% 0.08 0.08 

Connecticut 0.89% 0.02% 0.02 

Delaware 0.67% 0.00% 0.00 

District of Columbia 

Florida 11.42% 1.25% 10.24% 1.08% 0.11 0.11 

Georgia 1.36% 0.05% 0.99% 0.02% 0.03 0.02 

Hawaii 1.70% 0.04% 0.13% 0.03 

Idaho 

Illinois 2.26% 0.11% 1.54% 0.10% 0.05 0.06 

Indiana 0.97% 0.03% 0.03 

Iowa 038% 

Kansas 0.87% 0.01% 0.02 

Kentucky 

Louisiana 1.73% 0.16% 1.06% 0.13% 0.09 0.12 

Maine 0.24% 

Maryland 1.34% 0.04% 0.98% 0.03 

Massachusetts 0.74% 0.02% 0.02 

Michigan 0.64% 0.03% 0.05 

Minnesota 0.34% 0.01% 0.03 

Mississippi 0.24% 0.01% 0.04% 0.05 

Missouri 0.55% 0.01% 0.16% 0.03 

Montana 0.17% 0.02% 0.14 

Nebraska 0.55% 0.19% 0.34 

Nevada 3.10% 0.29% 0.09 

New Hampshire 0.17% 0.01% 0.06 

New Jersey 3.26% 0.13% 2.70% 0.10% 0.04 0.04 

New Mexico 16.70% 1.74% 12.81% 1.40% 0.10 0.11 

New York 336% 0.10% 2.17% 0.09% 0.03 0.04 

North Carolina 0.61% 0.03% 0.05 

North Dakota 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Ohio 0.81% 0.05% 0.71% 0.05% 0.07 0.07 

Oklahoma 0.97% 0.10% 0.84% 

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Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 1.28% 0.02% 0.02 

Pennsylvania 0.61% 0.02% 0.86% 0.02% 0.04 0.02 

Rhode Island 

South Carolina 

South Dakota 

Tennessee 

Texas 7.88% 0.53% 6.90% 0.45% 0.07 0.07 

Utah 2.47% 0.07% 0.03 

Vennont 0.73% 0.37% 

Virginia 1.68% 0.03% 0.02 

Washington 1.21% 0.07% 1.35% 0.05% 0.06 0.04 

West Virginia 

Wisconsin 0.65% 0.03% 0.05 

1.96% 0.59% 0.30 

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Table 11 C. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Asians, Finance and Insurance, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All ofAl! Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 

Alaska 2.69% 0.14% 0.99% 0.06% 0.05 0.07 

Arizona 1.21% 0.19% 1.33% 0.17% 0.16 0.13 

Arkansas 0.39% 

California 12.45% 1.01% 8.92% 0.80% 0.08 0.09 

Colorado 1.28% 0.09% 0.89% 0.05% 0.07 0.06 

Connecticut 1.88% 0.09% 1.56% 0.06% OJ)5 0.04 

Delaware 

District of Columbia 5.46% 0.03% 0.01 

Florida 1.08% 0.13% 1.32% 0.07% 0.12 0.06 

Georgia 1.38% 0.10% 1.28% 0.06% 0.08 0.05 

Hawaii 46.38% 3.42% 28.66% 2.14% 0.07 0.07 

Idaho 

Illinois 3.29% 0.19% 2.18% 0.14% 0.06 0.06 

Indiana 0.72% 0.03% 0.37% 0.02% 0.05 0.05 

Iowa 0.09% 0.00% 0.21% 0.04 

Kansas 0.44% 0.32% 

Kentucky 0.64% 

Louisiana 0.62% 0.10% 0.15 

Maine 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Maryland 

Massachusetts 1.93% 0.06% 0.82% 0.03% 0.03 0.04 

Michigan 1.56% 0.05% 0.60% 0.02% OJ)3 0.04 

Minnesota 1.13% 0.07% 0.26% 0.06 

Mississippi 

Missouri 

Montana 0.06% 0.08% 

Nebraska 

Nevada 3.88% 1.54% 2.78% 1.45% 0.40 0.52 

New Hampshire 1.17% 

New Jersey 5.12% 0.20% 2.30% 0.14% 0.04 0.06 

New Mexico 1.04% 0.17% 1.67% 0.15% 0.16 0.09 

New York 4.60% 0.31% 3.31% 0.24% 0.07 0.07 

North Carolina 0.88% 0.01% 0.34% 0.01% 0.02 0.02 

North Dakota 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Ohio 0.94% 0.05% 0.95% 0.03% 0.05 0.03 

Oklahoma 0.71% 

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Percentage Percentage Percentage Disparity Disparity 

State of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Finns Employers Sales 

Oregon 2.46% 0.22% 0.09 

Pennsylvania 1.15% 0.05% 0.49% 0.04% 0.04 0.07 

Rhode Island 

South Caro lina 0.28% 0.04% 0.13 

South Dakota 

Tennessee 

Texas 2.31% 0.24% 1.98% 0.18% 0.10 0.09 

Utah 0.79% 0.02% 0.02 

Vennont 

Virginia 2.94% 0.15% 2.56% 0.13% 0.05 0.05 

Washington 4.59% 0.38% 0.08 

West Virginia 0.32% 0.01% 0.02 

Wisconsin 1.02% 0.01% 0.56% 0.01% 0.01 0.01 

0.16% 

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Table liD. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, American Indians and Alaska Natives, Finance and Insurance, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage ofAll of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 

Alaska 4.48% 2.73% 0.61 

Arizona 

Arkansas 

California 0.89% 0.02% 0.35% 0.01% 0.03 0.04 

Colorado 1.10% 0.07% 0.23% 0.06% 0.07 0.28 

Connecticut 

Delaware 0.06% 0.17% 

District of Columbia 1.12% 0.00% 0.00% 0.00 

Florida 0.87% 0.03% 0.40% 0.02% 0.04 0.06 

Georgia 0.27% 

Hawaii 

Idaho 

Illinois 0.39% 0.01% 0.18% 0.01% 0.03 0.04 

Indiana 

Iowa 0.17% 0.01% 0.40% 0.01% 0.06 0.03 

Kansas 

Kentucky 0.14% 0.00% 0.03 

Louisiana 0.35% 0.05% 0.14 

Maine 

Maryland 0.76% 0.01% 0.02 

Massachusetts 

Michigan 

Minnesota 0.24% 0.00% 0.00% 0.00 

Mississippi 0.16% 

Missouri 

Montana 0.03% 0.00% 0.00% 0.00 

Nebraska 0.13% 

Nevada 

New Hampshire 

New Jersey 0.35% 

New Mexico 0.82% 0.03% 0.04 

New York 

North Carolina 

North Dakota 0.06% 0.00% 0.00% 0.00 

Ohio 

Oklahoma 3.79% 0.39% 3.02% 0.32% 0.10 

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Percentage Percentage Percentage Disparity Disparity 

State of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 

Pennsylvania 0.28% 0.00% 0.01 

Rhode Island 0.07% 

South Carolina 0.63% 0.02% 0.03 

South Dakota 

Tennessee 0.53% 

Texas 0.41% 0.07% 0.33% 0.06% 0.17 0.20 

Utah 

Vermont 

Virginia 

Washington 0.66% 

West Virginia 0.06% 0.00% 0.00% 0.00 

Wisconsin 0.25% 0.01% 0.05 

138 
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Table llE. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Native Hawaiians and Pacific Islanders, Finance and Insurance, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of AI! Percentage of All of AI! Ratio-All Ratio 

Firms ofAl! Sales Employers Employer Firms Employers Sales 

Alabama 0.01% 0.00% 0.00% 0.00 

Alaska 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Arizona 

Arkansas 

California 0.15% 0.00% 0.01 

Colorado 

Connecticut 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Delaware 

District of Columbia 0.07% 0.00% 0.00% 0.00 

Florida 

Georgia 0.01% 0.00% 0.00% 0.00 

Hawaii 3.62% 0.07% 1.25% 0.02 

Idaho 

Illinois 

Indiana 0.01% 0.02% 

Iowa 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Kansas 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Kentucky 

Louisiana 0.01% 0.00% 0.00% 0.00 

Maine 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Maryland 0.02% 

Massachusetts 

Michigan 

Minnesota 0.01% 0.02% 

Mississippi 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Missouri 0.02% 0.00% 0.00% 0.00 

Montana 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Nebraska 0.01% 0.00% 0.00% 0.00 

Nevada 

New Hampshire 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

New Jersey 0.01% 0.02% 

New Mexico 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

New York 

North Carolina 

North Dakota 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Ohio 0.00% 0.00% 0.00% 0.00 

Oklahoma 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

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Percentage Percentage Percentage Disparity Disparity 

State ofAl! Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 

Pennsylvania 

Rhode Island 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

South Carolina 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

South Dakota 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Tennessee 0.01% 0.00% 0.00% 0.00 

Texas 

Utah 

Vermont 0.06% 0.00% 0.00% 0.00 

Virginia 

Washington 

West Virginia 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Wisconsin 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

0.00% 0.00% 0.00% 0.00% 0.00 0.00 

140 
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NERA Economic Consulting 

Table IIF. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Women, Finance and Insurance, 2002 

Percentage Percentage Percentage Disparity Disparity 

State ofAn Percentage of An of An Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 19.21% 1.51% 11.04% 1.26% 0.08 O.ll 

Alaska 23.46% 2.32% 16.38% 2.11% 0.10 0./3 

Arizona 19.07% 0.82% 14.65% 0.60% 0.04 0.04 

Arkansas 19.40% 3.19% 10.30% 2.92% 0.16 0.28 

California 21.40% 1.30% 14.86% 1.02% 0.06 0.07 

Colorado 20.92% 1.61% 15.32% 1.31% 0.08 0.09 

Connecticut 18.03% 0.29% 8.89% 0.18% 0.02 0.02 

Delaware 13.63% 0.24% 11.83% 0.02 

District of Columbia 14.52% 10.31% 

Florida 21.18% 1.51% 16.94% 1.14% 0.07 0.07 

Georgia 19.69% 1.60% 14.70% 1.42% 0.08 0.10 

Hawaii 13.22% 1.00% 12.39% 0.78% 0.08 0.06 

Idaho 14.73% 1.01% 10.91% 0.71% 0.07 0.07 

Illinois 17.37% 0.87% 11.68% 0.73% 0.05 0.06 

Indiana 14.51% 2.22% 8.53% 2.12% 0.15 0.25 

Iowa 17.74% 0.61% 10.68% 0.51% 0.03 0.05 

Kansas 15.76% 0.96% 12.27% 0.86% 0.06 0.07 

Kentucky 13.43% 1.84% 10.86% 1.75% 0.14 0.16 

Louisiana 18.09% 1.56% 12.40% 1.30% 0.09 0./0 

Maine 

Maryland 17.76% 0.81% 14.09% 0.70% 0.05 0.05 

Massachusetts 15.81% 0.38% 9.13% 0.29% 0.02 0.03 

Michigan 19.03% 1.04% 12.87% 0.86% 0.05 0.07 

Minnesota 13.53% 0.60% 8.92% 0.52% 0.04 0.06 

Mississippi 22.63% 1.44% 11.85% 1.09% 0.06 0.09 

Missouri 18.28% 1.59% 15.14% 1.42% 0.09 0.09 

Montana 18.35% 1.79% 10.23% 1.43% 0.10 0.14 

Nebraska 15.44% 0.56% 11.28% 0.45% 0.04 0.04 

Nevada 22.68% 1.93% 14.16% 1.19% 0.08 0.08 

New Hampshire 15.39% 0.70% 10.90% 0.58% 0.05 0.05 

New Jersey 15.27% 0.56% 10.84% 0.04 

New Mexico 20.17% 1.36% 17.18% 1.04% 0.07 0.06 

New York 16.38% 0.49% 10.88% 0.40% 0.03 0.04 

North Carolina 20.37% 0.64% 13.16% 0.48% 0.03 0.04 

North Dakota 13.15% 0.96% 8.90% 0.65% 0.07 0.07 

Ohio 15.74% 0.57% 10.68% 0.46% 0.04 0.04 

Oklahoma 17.00% 5.78% 15.53% 5.62% 0.34 0.36 

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Percentage Percentage Percentage Disparity Disparity 

State of AI! Percentage of AI! of All Ratio-All Ratio 

Finns of All Sales Employers Employer Finns Employers Sales 

Oregon 19.91% 0.98% 15.71% 0.79% 0.05 0.05 

Pennsylvania 14.81% 0.84% 8.89% 0.75% 0.06 0.08 

Rhode Island 

South Carolina 19.11% 3.27% 13.85% 3.15% 0.17 0.23 

South Dakota 

Tennessee 18.65% 0.69% 11.89% 0.59% 0.04 0.05 

Texas 19.80% 1,40% 15.37% 0.97% 0.07 0.06 

Utah 17.30% 1.11% 10.18% 0.83% 0.06 0.08 

Vermont 16.28% 

Virginia 18.08% 0.38% 14.40% 0.29% 0.02 0.02 

Washington 17.65% 1.98% 13.79% 1.79% 0.11 0.13 

West Virginia 12,49% 1.13% 6.57% 0.98% 0.09 0.15 

Wisconsin 16.01% 0,45% 10.00% 0.36% 0.03 0.04 

15.96% 1.37% 12.79% 1.22% 0.09 0.10 

142 
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NERA Economic Consulting 

Table 12A. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, African Americans, Real Estate and Rental and Leasing, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 3.55% 0.73% 1.99% 0,44% 0.21 0.22 

Alaska 0.68% 0.17% 0.14% 0.26 

Arizona 0.74% 0.12% 0.16 

Arkansas 

California 2.24% 0.33% 0.71% 0.12% 0.15 0.17 

Colorado 1.31% 0.44% 0.33 

Connecticut 0.99% 0.22% 0.22 

Delaware 1.79% 1.43% 

District of Columbia 12.09% 4.32% 1.34% 0.31 

Florida 2.71% 0.74% 0.27 

Georgia 7.94% 1.29% 2.30% 0.50% 0.16 0.22 

Hawaii 

Idaho 0.40% 0.07% 0.18 

Illinois 3.64% 0.88% 1.74% 0.62% 0.24 0.36 

Indiana 1.64% 0.27% 0.17 

Iowa 0.16% 0.07% 0.00% 0.00% 0.43 0.00 

Kansas 0.80% 0.82% 0.78% 1.00% 1.02 1.28 

Kentucky 1.16% 0.35% 0.30 

Louisiana 4.28% 0.98% 1.20% 0.42% 0.23 0.35 

Maine 

Maryland 7.54% 1.27% 2.53% 0.17 

Massachusetts 0.99% 0.28% 0.48% 0.08% 0.28 0.17 

Michigan 2.61% 0.79% 2.03% 0.65% 0.30 0.32 

Minnesota 0.90% 0.17% 0.00% 0.00% 0.18 0.00 

Mississippi 5.60% 2.59% 2.31% 1.56% 0.46 0.67 

Missouri 2.59% 0.49% 0.60% 0.19% 0.19 0.31 

Montana 

Nebraska 0.44% 0.11% 0.00% 0.00% 0.26 0.00 

Nevada 2.58% 0.42% 0.82% 0.07% 0.16 0.08 

New Hampshire 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

New Jersey 2.11% 0.41% 0.20 

New Mexico 

New York 3.12% 1.18% 0.38 

North Carolina 3.17% 0.48% 1.94% 0.33% 0.15 0.17 

North Dakota 

Ohio 2.45% 0.43% 1.06% 0.21% 0.18 0.20 

Oklahoma 1.15% 0.34% 0.55% 0.23% 0.30 0.4 [ 

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Percentage Percentage Percentage Disparity Disparity 

State of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 0.28% 0.14% 0.11% 0.06% 0.48 0.50 

Pennsylvania 1.16% 0.18% 0.51% 0.13% 0.16 0.26 

Rhode Island 0.55% 0.11% 

South Carolina 2.33% 0.41% 0.92% 0.22% 0.17 0.24 

South Dakota 

Tennessee 3.55% 0.72% 0.20 

Texas 2.75% 0.47% 0.84% 0.18% 0.17 0.21 

Utah 

Vermont 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Virginia 3.20% 0.71% 0.82% 0.25% 0.22 0.31 

Washington 1.02% 0.19% 0.31% 0.18 

West Virginia 0.38% 0.05% 0.00% 0.00% 0.14 0.00 

Wisconsin 0.55% 0.10% 0.00% 0.00% 0.18 0.00 

0.02% 0.00% 0.00% 0.00 

144 
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NERA Economic Consulting 

Table 12B. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Hispanics and Latinos, Real Estate and Rental and Leasing, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio·AIl Ratio 

Firms of All Sales Employers Firms Employers 

Alabama 0.23% 0.08% 0.03% 0.34 

Alaska 1.02% 

Arizona 3.65% 1.16% 2.63% 0.74% 0.32 0.28 

Arkansas 

California 7.04% 2.24% 2.80% 1.06% 0.32 0.38 

Colorado 2.34% 1.63% 1.53% 1.73% 0.70 1.l3 

Connecticut 0.96% 0.25% 0.26 

Delaware 0.33% 0.03% 0.10 

District of Columbia 

Florida 10.83% 4.95% 9.60% 3.47% 0.46 0.36 

Georgia 0.96% 0.41% 1.26% 0.30% 0.43 0.23 

Hawaii 1.52% 0.21% 0.14 

Idaho 1.36% 0.64% 0.47 

Illinois 2.82% 0.91% 0.32 

Indiana 0.65% 0.37% 1.21% 0.35% 0.57 0.29 

Iowa 0.28% 0.56% 

Kansas 1.06% 0.57% 0.54 

Kentucky 0.24% 0.19% 0.03% 0.77 

Louisiana 0.97% 0.30% 1.51% 0.21% 0.31 0.14 

Maine 0.29% 0.62% 0.14% 2.11 

Maryland 1.29% 0.50% 0.39 

Massachusetts 1.30% 0.48% 0.81% 0.22% 0.37 0.27 

Michigan 0.49% 0.19% 0.37% 0.14% 0.39 0.39 

Minnesota 0.42% 0.30% 0.71 

Mississippi 0.26% 

Missouri 

Montana 0.41% 0.25% 0.61 

Nebraska 0.52% 0.14% 0.26 

Nevada 3.52% 1.13% 2.07% 0.56% 0.32 0.27 

New Hampshire 

New Jersey 3.06% 0.93% 0.30 

New Mexico 8.29% 2.68% 4.85% 1.83% 0.32 0.38 

New York 2.81% 0.91% 1.92% 0.69% 0.32 0.36 

North Carolina 0.48% 0.14% 0.55% 0.11% 0.29 0.20 

North Dakota 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Ohio 0.60% 0.17% 0.32% 0.17% 0.29 0.55 

Oklahoma 0.81% 0.35% 0.43 

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Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 1.42% 0.61% 0.43 

Pennsylvania 0.51% 0.14% 0.29% 0.07% 0.28 0.24 

Rhode Island 0.60% 0.16% 0.00% 0.00% 0.27 0.00 

South Carolina 

South Dakota 

Tennessee 

Texas 6.61% 2.08% 4.08% 1.27% 0.31 0.31 

Utah 1.44% 0.42% 0.29 

Vennont 0.25% 

Virginia 1.62% 0.90% 1.17% 0.75% 0.56 0.64 

Washington 0.97% 0.27% 0.28 

West Virginia 0.23% 

Wisconsin 0.46% 0.13% 0.28 

146 
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NERA Economrc Consulting 

Table 12C. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Asians, Real Estate and Rental and Leasing, 2002 

Percentage Percentage Percentage Disparity Disparity 

State ofAlI Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 0.41% 0.19% 0.47 

Alaska 

Arizona 1.76% 0.90% 0.51 

Arkansas 

California 11.50% 5.44% 9.28% 3.72% 0.47 0.40 

Colorado 1.37% 0.98% 1.l7% 1.09% 0.72 0.93 

Connecticut 0.86% 0.51% 0.47% 0.24% 0.59 0.52 

Delaware 1.41% 0.23% 0.20% 0.16 

District of Columbia 

Florida 1.26% 0.58% 1.27% 0.31% 0.46 0.25 

Georgia 1.73% 1.06% 1.93% 0.82% 0.62 0.42 

Hawaii 46.88% 22.27% 37.57% 14.71% 0.48 0.39 

Idaho 0.56% 0.26% 0.46 

Illinois 2.93% 1.15% 2.57% 0.91% 0.39 0.36 

Indiana 0.86% 0.48% 0.56 

Iowa 0.51% 0.28% 0.00% 0.00% 0.55 0.00 

Kansas 0.93% 0.45% 0.49 

Kentucky 0.52% 0.24% 0.46 

Louisiana 1.06% 0.57% 0.97% 0.40% 0.54 0.42 

Maine 

Maryland 3.07% 1.00% 2.51% 0.60% 0.33 0.24 

Massachusetts 1.43% 0.48% 0.90% 0.33 

Michigan 1.32% 0.96% 0.65% 0.14% 0.72 0.21 

Minnesota 1.55% 0.52% 0.55% 0.16% 0.33 0.30 

Mississippi 0.44% 0.41% 0.87% 0.94 

Missouri 0.83% 0.30% 0,37 

Montana 0.19% 0.08% 0.00% 0.00% 0.41 0.00 

Nebraska 0.40% 

Nevada 4.59% 2.47% 3.64% 1.45% 0.54 0.40 

New Hampshire 1.01% 0.69% 0.68 

New Jersey 4.62% 2.15% 3.84% 1.23% 0.47 0.32 

New Mexico 0.73% 0.26% 0.36 

New York 4.61% 2.50% 4.97% 2.20% 0.54 0.44 

North Carolina 1.01% 0.43% 0.65% 0.24% 0.43 0.37 

North Dakota 0.29% 

Ohio 1,07% 1.01% 1.21% 0.78% 0.94 0.65 

Oklahoma 0.81% 0.41% 0.44% 0.22% 

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Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 1.96% 2.00% 2.58% 2.26% 1.02 0.87 

Pennsylvania 1.46% 0.78% 1.06% 0.41% 0.54 0.38 

Rhode Island 1.29% 0.69% 0.53 

South Carolina 0.70% 0.38% 0.54 

South Dakota 

Tennessee 0.76% 0.51% 0.67 

Texas 2.86% 1.56% 3.57% 1.28% 0.55 0.36 

Utah 0.73% 0.40% 0.54 

Vermont 

Virginia 3.06% 1.24% 2.33% 0.71% 0.41 0.31 

Washington 4.24% 1.75% 3.27% 1.22% 0.41 0.37 

West Virginia 0.80% 0.59% 1.37% 0.60% 0.74 0.44 

Wisconsin 0.43% 0.44% 1.02 

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Table 12D. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, American Indians and Alaska Natives, Real Estate and Rental and Leasing, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 0.46% 0.18% 0.39 

Alaska 3.04% 11.10% 6.18% 15.19% 3.65 2.46 

Arizona 

Arkansas 0.31% 0.05% 0.00% 0.00% 0.15 0.00 

California 0.72% 0.15% 0.33% 0.10% 0.21 0.31 

Colorado 0.35% 0.09% 0.30% 0.08% 0.27 0.28 

Connecticut 0.18% 0.03% 0.18 

Delaware 

District of Columbia 0.02% 0.00% 0.00% 0.00 

Florida 

Georgia 

Hawaii 

Idaho 

Illinois 0.27% 

Indiana 

Iowa 

Kansas 

Kentucky 

Louisiana 0.45% 0.30% 0.66 

Maine 

Maryland 

Massachusetts 0.34% 0.05% 0.14 

Michigan 0.77% 0.11% 0.28% 0.06% 0.15 0.20 

Minnesota 

Mississippi 

Missouri 0.64% 0.07% 0.11 

Montana 

Nebraska 

Nevada 1.08% 0.36% 0.14% 0.05% 0.34 0.35 

New Hampshire 

New Jersey 

New Mexico 0.78% 0.22% 0.29 

New York 

North Carolina 0.39% 0.20% 0.52% 0.19% 0.51 0.37 

North Dakora 0.33% 0.14% 0.00% 0.00% 0.42 0.00 

Ohio 0.19% 0.11% 0.57 

Oklahoma 3.18% 1.79% 0.56 

149 
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Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 

Pennsylvania 0.14% 0.06% 0.40 

Rhode Island 

South Carolina 

South Dakota 

Tennessee 

Texas 0.55% 0.11% 0.20 

Utah 

Vermont 0.08% 0.06% 0.00% 0.00% 0.76 0.00 

Virginia 0.21% 

Washington 0.76% 0.44% 0.58 

West Virginia 

Wisconsin 

0.22% 0.07% 0.00% 0.00% 0.32 0.00 

150 
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NERA Economic Consulting 

Table 12E. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Native Hawaiians and Pacific Islanders, Real Estate and Rental and Leasing, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 0.00% 0.00% 0.00% 0.00% 000 0.00 

Alaska 

Arizona 

Arkansas 

California 0.14% 0.02% 0.16 

Colorado 

Connecticut 

Delaware 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

District of Columbia 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Florida 

Georgia 

Hawaii 7.70% 3.59% 10.46% 3.14% 0.47 0.30 

ldabo 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Illinois 

Indiana 

Iowa 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Kansas 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Kentucky 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Louisiana 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Maine 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Maryland 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Massachusetts 

Michigan 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Minnesota 

Mississippi 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Missouri 0.01% 0.00% 0.00% 0.00% 0.30 0.00 

Montana 

Nebraska 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Nevada 

New Hampshire 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

New Jersey 

New Mexico 

New York 

North Carolina 

North Dakota 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Ohio 

Oklahoma 

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Percentage Percentage Percentage Disparity Disparity 

State of AI! Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 

Pennsylvania 0.00% 0.01% 

Rhode Island 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

South Carolina 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

South Dakota 0.02% 0.00% 0.00% 0.00 

Tennessee 

Texas 0.00% 0.00% 0.00% 0.00 

Utah 

Vermont 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Virginia 

Washington 

West Virginia 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Wisconsin 0.00% 0.00% 0.00% 0.00 

0.02% 0.00% 0.00% 0.00 

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Table 12F. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Women, Real Estate and Rental and Leasing, 2002 

Percentage Percentage Percentage Disparity Disparity 

State ofAll Percentage ofAll of All Ratio-All Ratio 

Finns of All Sales Employers Employer Finns Employers Sales 

Alabama 21.52% 9.38% 16.77% 6.96~'O 0.44 0.42 

Alaska 18.38% 12.23% 21.84% 12.19% 0.67 0.56 

Arizona 26.06% 8.62% 19.87% 5.86% 0.33 0.29 

Arkansas 19.46% 10.07% 11.96% 7.62% 0.52 0.64 

California 25.98% 10.79% 18.91% 7.29% 0.42 0.39 

Colorado 22.21% 10.20% 22.16% 8.27% 0.46 0.37 

Connecticut 23.80% 9.22% 15.22% 5.49% 0.39 0.36 

Delaware 22.01% 2.10% 17.20% 1.07% 0.10 0.06 

District of Columbia 21.50% 21.03% 

Florida 28.57% 11.28% 22.85% 7.78% 0.39 0.34 

Georgia 27.77% 8.87% 23.24% 5.69% 0.32 0.24 

Hawaii 27.92% 9.15% 21.76% 5.99% 0.33 0.28 

Idaho 18.15% 13.15% 25.07% 16.12% 0.72 0.64 

Illinois 25.09% 8.67% 18.48% 6.28% 0.35 0.34 

Indiana 23.09% 9.05% 19.29% 5.72% 0.39 0.30 

Iowa 19.30% 9.36% 16.92% 7.82% 0.49 0.46 

Kansas 21.02% 7.97% 18.85% 6.03% 0.38 0.32 

Kentucky 19.38% 9.90% 21.72% 9.20% 0.51 0.42 

Louisiana 23.39% 7.63% 17.35% 5.01% 0.33 0.29 

Maine 22.29% 12.42% 16.14% 12.09% 0.56 0.75 

Maryland 21.95% 11.32% 19.22% 9.56% 0.52 0.50 

Massachusetts 27.76% 10.13% 19.20% 7.08% 0.37 0.37 

Michigan 21.60% 8.50% 17.30% 6.32% 0.39 0.37 

Minnesota 18.48% 7.01% 18.06% 5.61% 0.38 0.31 

Mississippi 24.00% 11.81% 23.92% 8.34% 0.49 0.35 

Missouri 22.81% 8.47% 19.36% 6.38% 0.37 0.33 

Montana 17.48% 14.91% 19.27% 17.22% 0.85 0.89 

Nebraska 19.50% 13.10% 21.48% 14.93% 0.67 0.69 

Nevada 26.08% 12.96% 17.91% 10.49% 0.50 0.59 

New Hampshire 24.42% 11.87% 22.95% 10.17% 0.49 0.44 

New Jersey 24.33% 9.96% 15.73% 7.52% 0.41 0.48 

New Mexico 21.52% 10.70% 19.78% 8.46% 0.50 0.43 

New York 20.16% 9.09% 13.06% 7.41% 0.45 0.57 

North Carolina 22.93% 9.37% 19.93% 6.77% 0.41 0.34 

North Dakota 16.72% 10.66% 

Ohio 22.55% 7.97% 15.40% 4.82% 0.35 0.31 

Oklahoma 21.85% 8.98% 17.79% 7.71% 

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Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Finns Employers Sales 

Oregon 22.52% 10,98% 20.27% 8,19% 0.19 0.10 

Pennsylvania 21.29% 8,63% 16,07% 6.10% 0.11 0,38 

Rhode Island 20,52% 10,06% 8,05% 6.16% 0.19 0,77 

South Carolina 20,59% 8,58% 19,30% 6,27% 0.12 0,32 

South Dakota 13,42% 11.46% 20.94% 13,94% 0,85 0.67 

Tennessee 22,44% 8,97% 19,30% 6,51% 0.10 0,34 

Texas 23,43% 8,37% 18.03% 6,34% 0.36 0,35 

Utah 18,59% 8,43% 18,87% 6,24% 0.15 0.33 

Vermont 19,96% 10.24% 15.65% 10,64% 0,51 0,68 

Virginia 24,71% 9,91% 20,08% 6,69% 0.10 0,33 

Washington 21.59% 9.55% 17,37% 8.52% 0.14 0,49 

West Virginia 20,83% llA9% 13,13% 11.53% 0.55 0,88 

Wisconsin 17,99% 9,02% 16.23% 8,55% 0.50 0.53 

21.31% 12,43% 17.32% 8,67% 0.58 0,50 

154 
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NERA Economtc Consulting 

Table 13A. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, African Americans, Professional, Scientific and Technical Services, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 5.89% 2.48% 2.53% 2.30% 0.42 0.91 

Alaska 1.36% 0.59% 0.44 

Arizona 1.27% 0.34% 0.54% 0.24% 0.27 0.44 

Arkansas 2.65% 0.48% 0.89% 0.24% 0.18 0.27 

California 2.81% 0.57% 1.26% 0.43% 0.20 0.34 

Colorado 1.05% 0.43% 0.55% 0.37% 0.41 0.68 

Connecticut 2.13% 0.35% 0.62% 0.28% 0.16 0.45 

Delaware 4.79% 0.45% 1.84% 0.09 

District of Columbia 14.72% 6.81% 

Florida 3.66% 1.02% 1.37% 0.82% 0.28 0.60 

Georgia 9.63% 2.03% 3.44% 1.54% 0.2! 0.45 

Hawaii 0.58% 0.08% 0.21% 0.04% 0.14 0.20 

Idaho 0.38% 0.24% 0.63 

Illinois 4.20% 0.93% 1.69% 0.77% 0.22 0.45 

Indiana 2.65% 0.57% 1.57% 0.45% 0.21 0.29 

Iowa 0.70% 0.35% 0.34% 0.31% 0.50 0.91 

Kansas 1.39% 0.32% 0.70% 0.22% 0.23 0.32 

Kentucky 1.76% 0.35% 0.49% 0.25% 0.20 0.51 

Louisiana 6.43% 1.82% 2.72% 1.54% 0.28 0.57 

Maine 0.43% 0.03% 0.00% 0.00% 0.06 0.00 

Maryland 12.48% 3.91% 4.71% 3.38% 0.31 0.72 

Massachusetts 1.60% 0.32% 0.87% 0.26% 0.20 0.29 

Michigan 4.03% 1.10% 1.91% 0.88% 0.27 0.46 

Minnesota 1.07% 0.29% 0.46% 0.24% 0.27 0.51 

Mississippi 8.ll% 3.70% 3.98% 3.09% 0.46 0.78 

Missouri 2.81% 0.54% 1.55% 0.43% 0.19 0.28 

Montana 0.26% 0.08% 0.32 

Nebraska 

Nevada 1.98% 0.66% 0.80% 0.50% 0.33 0.62 

New Hampshire 

New Jersey 3.98% 0.83% 1.77% 0.64% 0.21 0.36 

New Mexico 0.70% 0.47% 0.49% 0.49% 0.68 1.00 

New York 4.62% 0.60% 1.55% 0.40% 0.13 0.26 

North Carolina 5.69% 0.99% 2.56% 0.79% 0.17 0.31 

North Dakota 0.14% 0.08% 

Ohio 3.08% 1.01% 1.41% 0.90% 0.33 0.64 

Oklahoma 1.69% 0.56% 0.87% 0.52% 

155 
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NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 0.46% 0.19% 0.51% 0.16% 0.42 0.32 

Pennsylvania 2.29% 0.55% 1.04% 0.44% 0.24 0.42 

Rhode Island 1.27% 0.42% 0.41% 0.36% 0.33 0.89 

South Carolina 5.99% 0.97% 2.54% 0.72% 0.16 0.28 

South Dakota 0.15% 0.00% 0.00% 0.00 

Tennessee 4.13% 0.86% 1.81% 0.72% 0.21 0.40 

Texas 3.64% 0.76% 1.32% 0.62% 0.21 0.47 

Utah 0.45% 0.13% 0.18% 0.12% 0.30 0.67 

Vermont 0.25% 0.16% 0.15% 0.18% 0.63 1.18 

Virginia 4.78% 2.43% 2.91% 2.33% 0.51 0.80 

Washington 1.24% 0.51% 1.00% 0.46% 0.41 0.46 

West Virginia 1.50% 0.91% 0.61 

Wisconsin 0.99% 0.35% 0.57% 0.29% 0.35 0.51 

0.55% 

156 
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NERA Economic Consulting 

Table 13B. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Hispanics and Latinos, Professional, Scientific and Technical Services, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 0.78% 3.15% 1.02% 3.37% 4.04 3.32 

Alaska 1.29% 0.32% 0.48% 0.20% 0.25 0.41 

Arizona 5.51% 1.65% 3.03% 1.38% 0.30 0.45 

Arkansas 0.75% 0.15% 0.20 

California 7.40% 2.24% 4.37% 1.86% 0.30 0.42 

Colorado 3.10% 1.17% 2.36% 1.07% 0.38 0.45 

Connecticut 1.72% 0.70% 1.44% 0.65% 0.41 0.45 

Delaware 1.37% 0.21% 0.15 

District of Columbia 3.51% 1.39% 2.91% 1.36% 0.40 0.47 

Florida 13.02% 5.13% 9.48% 4.41% 0.39 0.47 

Georgia 1.94% 0.70% 0.96% 0.61% 0.36 0.64 

Hawaii 1.97% 0.83% 2.01% 0.70% 0.42 0.35 

Idaho 1.77% 1.02% 1.74% 1.04% 0.58 0.60 

Illinois 2.38% 0.64% 1.42% 0.54% 0.27 0.38 

Indiana 0.91% 0.31% 0.53% 0.24% 0.34 0.46 

Iowa 0.70% 0.08% 0.05% 0.12 

Kansas 1.54% 0.44% 0.88% 0.35% 0.29 0.10 

Kentucky 0.94% 0.49% 0.52 

Louisiana 1.83% 0.93% 0.51 

Maine 0.33% 0.07% 0.09% 0.03% 0.22 0.28 

Maryland 2.60% 0.99% 1.83% 0.88% 0.38 0.48 

Massachusetts 1.72% 0.51% 0.70% 0.44% 0.30 0.62 

Michigan 1.16% 0.41% 0.52% 0.35% 0.35 0.66 

Minnesota 0.96% 0.16% 0.17 

Mississippi 0.76% 0.24% 0.51% 0.15% 0.31 0.30 

Missouri 0.89% 0.36% 1.04% 0.33% 0.11 0.32 

Montana 0.85% 0.45% 0.53 

Nebraska 0.93% 0.23% 0.26% 0.19% 0.25 0.72 

Nevada 

New Hampshire 

New Jersey 3.81% 1.02% 2.19% 0.81% 0.27 0.37 

New Mexico 13.51% 7.70% 10.46% 7.19% 0.57 0.69 

New York 4.53% 0.91% 1.74% 0.59% 0.20 0.34 

North Carolina 1.33% 0.57% 0.78% 0.51% 0.43 0.65 

North Dakota 0.58% 

Ohio 0.70% 0.34% 0.46% 0.33% 0.48 0.70 

Oklahoma 1.40% 1.08% 0.77 

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Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 1.66% 0.62% 0.68% 0.54% 0.37 0.80 

Pennsylvania 1.14% 0.71% 0.92% 0.68% 0.62 0.74 

Rhode Is land 2.52% 0.60% 0.91% 0.48(% 0.24 0.52 

South Carolina 1.08% 0.73% 0.48% 0.76% 0.68 1.58 

South Dakota 0.53% 0.13% 

Tennessee 0.68% 0.43% 0.69% 0.41% 0.64 0.59 

Texas 8.98% 3.45% 6.10% 2.95% 0.38 0.48 

Utah 2.35% 0.78% 1.78% 0.61% 0.33 0.34 

Vermont 

Virginia 2.34% 1.62% 1.92% 1.59% 0.69 0.83 

Washington 1.82% 0.76% 1.19% 0.70% 0.42 0.58 

West Virginia 0.79% 1.66% 1.55% 1.69% 2.10 1.09 

Wisconsin 1.04% 0.67% 0.83% 0.58% 0.64 0.70 

158 
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Table 13C. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Asians, Professional, Scientific and Technical Services, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage ofAlI of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 1.08% 2.73% 0.65% 2.83% 2.52 4.39 

Alaska 1.00% 1.28% 0.84% 1.28% 1.27 1.52 

Arizona 2.14% 1.13% 1.75% 1.03% 0.53 0.59 

Arkansas 0.75% 0.45% 0.69% 0.44% 0.60 0.64 

California 11.48% 4.84% 10.10% 4.33% 0.42 0.43 

Colorado 1.72% 1.56% 1.67% 1.57% 0.91 0.94 

Connecticut 2.22% 1.35% 1.67% 1.18% 0.61 0.71 

Delaware 4.19% 2.40% 5.64% 0.57 

District of Columbia 2.34% 2.18% 

Florida 2.05% 1.23% 1.52% 1.22% 0.60 0.80 

Georgia 2.93% 2.24% 3.03% 2.21% 0.77 0.73 

Hawaii 42.01% 32.94% 46.20% 33.58% 0.78 0.73 

Idaho 1.38% 1.23% 1.55% 1.25% 0.89 0.80 

Illinois 4.77% 2.10% 4.10% 1.99% 0.44 0.49 

Indiana 1.24% 0.80% 0.75% 0.73% 0.64 0.97 

Iowa 1.00% 0.78% 1.06% 0.77% 0.77 0.73 

Kansas 1.94% 0.45% 1.51% 0.35% 0.23 0.23 

Kentucky 0.83% 0.74% 0.71% 0.76% 0.89 1.06 

Louisiana 1.11% 0.53% 0.48 

Maine 0.48% 0.20% 0.43 

Maryland 5.34% 4.75% 6.09% 4.82% 0.89 0.79 

Massachusetts 3.01% 2.14% 2.73% 2.13% 0.71 0.78 

Michigan 2.53% 2.97% 2.65% 2.97% 1.18 1.12 

Minnesota 2.12% 1.09% 1.83% 0.51 

Mississippi 0.65% 0.35% 0.42% 0.25% 0.54 0.60 

Missouri 1.28% 0.59% 1.25% 0.55% 0.46 0.43 

Montana 0.79% 1.05% 1.33 

Nebraska 

Nevada 3.81% 1.98% 3.46% 1.58% 0.52 0.46 

New Hampshire 1.46% 1.24% 2.67% 1.20% 0.85 0.45 

New Jersey 9.18% 5.51% 11.18% 5.37% 0.60 0.48 

New Mexico 1.48% 1.79% 1.74% 1.91% 1.21 1.10 

New York 6.70% 1.93% 5.08% 1.70% 0.29 0.33 

North Carolina 1.93% 1.27% 1.43% 1.24% 0.66 0.86 

North Dakota 

Ohio 1.91% 2.23% 2.12% 2.26% 1.16 1.06 

Oklahoma 1.07% 0.79% 1.09% 0.80% 0.73 0.74 

159 
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Percentage Percentage Percentage Disparity Disparity 

State of AI! of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 2.35% 1.66% 1.63% 1.52% 0.70 0.93 

Pennsylvania 2.23% 1.71% 1.99% 1.67% 0.77 0.84 

Rhode Island 1.35% 1.19% 1.18% 1.27% 0.89 1.07 

South Carolina 0.93% 0.29% 0.42% 0.21% 0.3I 0.5I 

South Dakota 0.36% 

Tennessee 1.24% 1.31% 0.84% 1.34% 1.06 1.60 

Texas 3.53% 2.10% 3.13% 1.96% 0.60 0.63 

Utah 1.34% 0.95% 0.65% 0.81% 0.70 1.24 

Vermont 0.50% 0.40% 0.80 

Virginia 5.49% 4.98% 6.43% 5.02% 0.91 0.78 

Washington 4.10% 2.32% 3.63% 2.15% 0.56 0.59 

West Virginia 0.90% 2.08% 0.72% 2.14% 2.31 2.98 

Wisconsin 1.29% 1.83% 1.11% 1.90% 1.41 1.72 

1.43% 

160 
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Table I3D. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, American Indians and Alaska Natives, Professional, Scientific and Technical Services, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Firms Employers 

Alabama 0.84% 0.55% 0.66 

Alaska 5.23% 9.05% 2.10% 9.83% 1.73 4.67 

Arizona 1.25% 0.26% 0.44% 0.14% 0.20 0.32 

Arkansas 0.66% 0.37% 0.63% 0.32% 0.56 0.51 

California 0.86% 0.16% 0.54% 0.10% 0./8 0.18 

Colorado 0.58% 0.17% 0.47% 0.13% 0.30 0.27 

Connecticut 0.31% 0.12% 0.37 

Delaware 0.23% 0.09% 

District of Columbia 0.55% 0.30% 

Florida 0.50% 0.18% 0.28% 0.16% 0.36 0.58 

Georgia 0.61% 0.14% 036% 0.11% 0.23 0.30 

Hawaii 0.54% 0.10% 

Idaho 0.47% 0.11% 0.37% 0.07% 0.23 0.18 

Illinois 0.26% 0.04% 0.15% 0.03% 0.15 0.20 

Indiana 0.58% 0,12% 0.42% 0.09% 0.20 IUO 

Iowa 0.22% 0,09% 0,00% 0,00% 0.42 0.00 

Kansas 0.48% 0.34% 0.71 

Kentucky 0.40% 0.09% 0.23 

Louisiana 0.53% 0,28% 0,23% 0.27% 0.53 1.19 

Maine 0.39% 0,13% 0.34 

Maryland 0.58% 0.46% 0.47% 0.45% 0,78 0,95 

Massachusetts 0,26% 0,03% 0.13 

Michigan 0.48% 0.10% 0.53% 0,08% 0.2/ 0.15 

Minnesota 

Mississippi 0.88% 0.08% 0.09 

Missouri 0.63% 0.33% 0.52 

Montana 2.25% 0,81% 0.87% 0.43% 0.36 0.49 

Nebraska 0.39% 0.15% 0.10% 0.12% 0.37 /,18 

Nevada 0,98% 0.49% 0.57% 0.36% 0.50 0,64 

New Hampshire 

New Jersey 0.50% 0.14% 0.43% 0.28 

New Mexico 2.75% 1.16% 1.55% 1.03% 0.42 0.66 

New York 0.44% 0.05% 0.26% 0,03% 0.12 0.11 

North Carolina 0.56% 0.30% 0.37% 0.29% 0.53 0.78 

North Dakota 

Ohio 0.39% 0.11% 0.35% 0,10% 0.28 0.28 

Oklahoma 5.31% 2,64% 4.02% 2.39% 0.50 0.60 

161 
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Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 0.93% 0.17% 0.29% 0.05% 0.18 0.17 

Pennsylvania 0.29% 0.06% 0.15% 0.05% 0.21 0.32 

Rhode Island 0.19% 0.07% 

South Carolina 0.69% 0.18% 0.26 

South Dakota 2.67% 0.75% 0.28 

Tennessee 0.82% 0.32% 1.05% 0.30% 0.38 0.28 

Texas 0.93% 0.26% 0.51% 0.22% 0.28 0.44 

Utah 

Vermont 0.10% 0.17% 0.15% 0.20% 1.66 1.37 

Virginia 0.50% 0.21% 0.54% 0.20% 0.42 0.36 

Washington 0.91% 0.27% 0.51% 0.23% 0.30 0.45 

West Virginia 

Wisconsin 0.41% 0.18% 0.43 

162 
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Table 13E. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Native Hawaiians and Pacific Islanders, Professional, Scientific and Technical Services, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Firms Employers 

Alabama 

Alaska 0.09% 0.06% 

Arizona 0.06% 0.02% 0.25 

Arkansas 0.02% 0.02% 

California 0.21% 0.03% 0.15 

Colorado 0.12% 0.02% 0.07% 0.02% 0.16 0.24 

Connecticut 0.02% 

Delaware 0.01% 0.00% 0.00% 0.00 

District of Columbia 

Florida 0.05% 0.00% 0.04 

Georgia 

Hawaii 6.33% 2.49% 3.37% 1.92% 0.39 0.57 

Idaho 0.02% 0.00% 0.00% 0.00 

Illinois 

Indiana 0.05% 

Iowa 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Kansas 0.02% 0.00% 0.00% 0.00 

Kentucky 

Louisiana 0.01% 0.01% 

Maine 0.01% 0.00% 0.00% 0.00 

Maryland 0.01% 0.01% 

Massachusetts 

Michigan 

Minnesota 0.01% 0.00% 0.00% 0,00 

Mississippi 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Missouri 0.00% 0.00% 0.00% 0.00 

Montana 

Nebraska 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Nevada 0.08% 0.03% 

New Hampshire 0.02% 0.00% 0.00% 0.00 

New Jersey 

New Mexico 0.03% 0.01% 0.00% 0.00% 0.]9 0.00 

New York 

North Cara lina 

North Dakota 0.04% 0.00% 0.00% 0.00 

Ohio 

Oklahoma 

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Percentage Percentage Percentage Disparity Disparity 

State ofAIl Percentage ofAll of All Ratio-All Ratio 

Finns of All Sales Employers Employer Firms Employers Sales 

Oregon 

Pennsylvania 

RlJode Island 0.01% 0.00% 0.00% 0.00 

South Carolina 0.00% 0.00% 0.00% 0.00 

South Dakota 

Tennessee 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Texas 

Utah 

Vennont 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Virginia 0.12% 0.15% 1.22 

Washington 0.10% 0.02% 0.05% 0.18 

West Virginia 0.03% 0.00% 0.00% 0.00% 0.09 0.00 

Wisconsin 

0.00% 0.00% 0.00% 0.00% 0.00 0.00 

164 
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NERA Economic Consulting 

Table 13F. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Women, Professional, Scientific and Technical Services, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 26.77% 7.92% 15.74% 6.72% 0.30 0.43 

Alaska 32.70% 12.77% 20.75% 11.09% 0.39 0.53 

Arizona 29.31% 9.11% 19.52% 7.27% 0.31 0.37 

Arkansas 25.40% 11.11% 19.83% 9.67% 0.44 0.49 

California 29.77% 7.92% 18.09% 5.95% 0.27 0.33 

Colorado 30.11% 7.61% 21.23% 6.26% 0.25 0.29 

Connecticut 27.07% 7.47% 15.95% 5.79% 0.28 0.36 

Delaware 27.39% 6.55% 21.98% 5.26% 0.24 0.24 

District of Columbia 35.27% 4.33% 18.01% 3.67% 0.12 0.20 

Florida 27.51% 10.06% 20.08% 8.30% 0.37 0.41 

Georgia 29.15% 8.59% 18.60% 6.81% 0.29 0.37 

Hawaii 28.57% 8.58% 15.70% 7.04% 0.30 0.45 

Idaho 24.82% 8.68% 13.83% 7.62% 0.35 0.55 

Illinois 29.16% 6.88% 18.20% 5.46% 0.24 0.30 

Indiana 26.77% 9.23% 16.62% 7.70% 0.34 0.46 

Iowa 26.15% 7.69% 16.84% 6.41% 0.29 0.38 

Kansas 27.68% 7.55% 19.51% 6.48% 0.27 0.33 

Kentucky 25.76% 8.45% 15.49% 6.93% 0.33 0.45 

Louisiana 26.13% 7.40% 13.78% 5.77% 0.28 0.42 

Maine 27.74% 6.68% 15.80% 4.52% 0.24 0.29 

Maryland 31.51% 10.07% 21.88% 8.73% 0.32 0.40 

Massachusetts 30.39% 6.31% 16.17% 4.58% 0.21 0.28 

Michigan 27.66% 7.07% 17.15% 5.78% 0.26 0.34 

Minnesota 29.01% 8.74% 19.44% 7.23% 0.30 0.37 

Mississippi 26.77% 9.36% 16.46% 7.76% 0.35 0.47 

Missouri 27.10% 6.01% 18.45% 4.87% 0.22 0.26 

Montana 31.78% 10.82% 22.95% 8.67% 0.34 0.38 

Nebraska 26.82% 7.63% 17.53% 6.37% 0.28 0.36 

Nevada 24.79% 8.94% 15.61% 7.14% 0.36 0.46 

New Hampshire 25.64% 9.46% 18.25% 7.27% 0.37 0.40 

New Jersey 26.56% 7.93% 16.33% 6.57% 0.30 0.40 

New Mexico 31.93% 9.88% 23.19% 7.42% 0.31 0.32 

New York 29.33% 7.31% 16.97% 5.53% 0.25 0.33 

North Carolina 29.35% 9.24% 18.49% 7.49% 0.31 0.41 

North Dakota 23.40% 5.41% 18.95% 4.36% 0.23 0.23 

Ohio 26.D4'10 7.19% 15.50% 5.65% 0.28 0.36 

Oklahoma 25.55% 7.84% 17.83% 6.71% 0.31 

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Percentage Percentage Percentage Disparity Disparity 

State ofAl! Percentage of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Finns Employers Sales 

Oregon 32.16% 10.84% 20.18% 9.19% 0.34 0.46 

Pennsylvania 26.17% 6.56% 15.84% 5,32% 0.25 0.34 

Rhode Island 29.04% 8.56% 15.90% 5.77% 0.29 0.36 

South Carolina 26.89% 7.90% 17.02% 6.81% 0.29 0.40 

South Dakota 22.90% 7.51% 16.52% 6.37% 0.33 0.39 

Tennessee 27.97% 8.81% 17.58% 6.96% 0.32 0.40 

Texas 26.67% 8.47% 17.69% 7.05% 0.32 0.40 

Utah 20.27% 6.01% 12.54% 4.97% 0.30 0.40 

Vennont 31.34% 13.15% 13.83% 10.35% 0.42 0.75 

Virginia 30.00% 6.96% 22.12% 6.01% 0.23 0.27 

Washington 31.l4% 7.49% 18.74% 5.82% 0.24 0.31 

West Virginia 26.81% 10.12% 16.97% 9.03% 0.38 0.53 

Wisconsin 26.06% 8.38% 15.83% 7.02% 0.32 0.44 

25.34% 7.94% 17.68% 6.48% 0.31 037 

166 
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Tablel4A. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, African Americans, Management of Companies and Enterprises, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 0.69% 0.69% 

Alaska 0.00% 0.00% 

Arizona 0.17% 0.17% 

Arkansas 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

California 0.68% 0.68% 

Colorado 0.15% 0.15% 

Connecticut 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Delaware 

District of Columbia 3.61% 0.61% 3.61% 0.61% 0.17 0.17 

Florida 0.25% 0.00% 0.25% 0.00% 0.00 0.00 

Georgia 0.82% 0.82% 

Hawaii 0.53% 0.53% 

Idabo 0.00% 0.00% 

Illinois 0.33% 0.00% 0.33% 0.00% 0.00 0.00 

Indiana 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Iowa 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Kansas 0.65% 0.00% 0.65% 0.00% 0.00 0.00 

Kentucky 0.42% 0.42% 

Louisiana 1.33% 1.33% 

Maine 0.00% 0.00% 

Maryland 1.97% 1.97% 

Massachusetts 0.37% 0.37% 

Michigan 

Minnesota 

Mississippi 0.79% 0.79% 

Missouri 0.63% 0.63% 

Montana 0.00% 0.00% 

Nebraska 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Nevada 

New Hampshire 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

New Jersey 0.20% 0.20% 

New Mexico 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

New York 0.21% 0.21% 

North Carolina 0.77% 0.77% 

North Dakota 0.00% 0.00% 

Ohio 0.87% 0.87% 

Oklahoma 0.47% 0.47% 

167 
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NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Finns Employers Sales 

Oregon 0.21% 0.21% 

Pennsylvania 0.36% 0.36% 

Rhode Island 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

South Carolina 0.49% 0.49% 

South Dakota 0.00% 0.00% 0.00% 0.00% 0.00 0,00 

Tennessee 0.57% 0.00% 0.57% 0.00% 0.00 0,00 

Texas 

Utah 0.00% 0.00% 0.00% 0,00% 0,00 0.00 

Vennont 0.00% 0.00% 

Virginia 0.70% 0.70% 

Washington 0.69% 0.00% 0.69% 0.00% 0.00 0.00 

West Virginia 0.00% 0.00% 

Wisconsin 0.45% 0,00% 0.45% 0.00% 0.00 0,00 

0.00% 0.00% 

168 
352 

NERA Economic Consulting 

Table 14B. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Hispanics and Latinos, Management of Companies and Enterprises, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Finns Employers Sales 

Alabama 0.23% 0.23% 

Alaska 1.04% 1.04% 

Arizona 1.39% 1.39% 

Arkansas 0.34% 0.34% 

California 

Colorado 

Connecticut 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Delaware 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

District of Columbia 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Florida 2.22% 2.22% 

Georgia 0.37% 0.37% 

Hawaii 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Idabo 0.65% 0.65% 

Illinois 0.39% 0.39% 

Indiana 0.15% 0.15% 

Iowa 0.51% 0.51% 

Kansas 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Kentucky 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Louisiana 0.67% 0.67% 

Maine 0.00% 0.00% 

Maryland 0.49% 0.49% 

Massachusetts 0.25% 0.25% 

Michigan 0.09% 0.09% 

Minnesota 

Mississippi 

Missouri 0.13% 0.13% 

Montana 0.00% 0.00% 

Nebraska O.OO(VO 0.00% 0.00% 0.00% 0.00 0.00 

Nevada 

New Hampshire 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

New Jersey 

New Mexico 5.81% 5.81% 

New York 0.31% 0.01% 0.31% 0.01% 0.03 0.03 

North Carolina 0.22% 0.22% 

North Dakota 0.00% 0.00% 

Ohio 0.07% 0.07% 

Oklahoma 0.47% 0.47% 

169 
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NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Firms Employers Sales 

Oregon 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Pennsylvania 

Rhode Island 0.92% 0.92% 

South Carolina 0.24% 0.24% 

South Dakota 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Tennessee 0.29% 0.29% 

Texas 

Utah 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Vermont 0.00% 0.00% 

Virginia 1.06% 1.06% 

Washington 0.14% 0.14% 

West Virginia 0.00% 0.00% 

Wisconsin 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

3.08% 3.08% 

170 
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NERA Economic Consulting 

Table 14C. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Asians, Management of Companies and Enterprises, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 0.92% 0.92% 

Alaska 3.13% 3.13% 

Arizona 

Arkansas 0.34% 0.34% 

California 4.56% 4.56% 

Colorado 2.23% 0.02% 2.23% 0.02% 0.01 0.01 

Connecticut 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Delaware 

District of Columbia 0.52% 0.52% 

Florida 1.60% 0.29% 1.60% 0.29% 0.18 0.18 

Georgia 0.55% 0.55% 

Hawaii 14.74% 9.30% 14.74% 9.30% 0.63 0.63 

Idaho 0.00% 0.00% 

!lUnois 1.04% 1.04% 

Indiana 0.15% 0.15% 

Iowa 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Kansas 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Kentucky 0.21% 0.21% 

Louisiana 1.55% 0.00% 1.55% 0.00% 0.00 0.00 

Maine 1.34% 1.34% 

Maryland 0.49% 0.00% 0.49% 0.00% 0.00 0.00 

Massachusetts 

Michigan 0.46% 0.46% 

Minnesota 0.52% 0.00% 0.52% 0.00% 0.00 0.00 

Mississippi 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Missouri 

Montana 0.00% 0.00% 

Nebraska 0.74% 0.74% 

Nevada 2.47% 2.47% 

New Hampshire 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

New Jersey 1.61% 1.61% 

New Mexico 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

New York 

North Carolina 0.44% 0.44% 

North Dakota 1.14% 1.14% 

Ohio 

Oklahoma 0.00% 0.00% 0.00% 0.00% 0.00 

171 
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NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 1.69% 1.69% 

Pennsylvania 051% 0.00% 051% 0.00% 0.00 0.00 

Rhode Island 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

South Caro tina 0.73% 0.73% 

South Dakota 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Tennessee 

Texas 2.42% 2.42% 

Utah 1.00% 1.00% 

Vermont 1.14% 1.14% 

Virginia 0.23% 0.23% 

Washington 

West Virginia 0.00% 0.00% 

Wisconsin 1.04% 0.11% 1.04% 0.11% 0.11 O.II 

0.00% 0.00% 

172 
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NERA Economic Consulting 

Table 14D. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, American Indians and Alaska Natives, Management of Companies and Enterprises, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage ofAl! ofAl! Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 0.23% 0.23% 

Alaska 17.71% 17.71% 

Arizona 0.35% 0.35% 

Arkansas 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

California 0.09% 0.09% 

Colorado 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Connecticut 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Delaware 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

District of Columbia 0.52% 0.52% 

Florida 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Georgia 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Hawaii 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Idaho 0.00% 0.00% 

Illinois 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Indiana 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Iowa 0.25% 0.25% 

Kansas 0.22% 0.22% 

Kentucky 0.21% 0.21% 

Louisiana 0.22% 0.22% 

Maine 0.00% 0.00% 

Maryland 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Massachusetts 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Michigan 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Minnesota 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Mississippi 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Missouri 0.13% 0.13% 

Montana 0.99% 0.99% 

Nebraska 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Nevada 

New Hampshire 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

New Jersey 0.20% 0.20% 

New Mexico 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

New York 0.05% 0.05% 

North Carolina 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

North Dakota 0.00% 0.00% 

Ohio 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Oklahoma 1.88% 1.88% 

173 
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Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Firms Employers Sales 

Oregon 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Pennsylvania 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Rhode Island 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

South Carolina 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

South Dakota 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Tennessee 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Texas 0.16% 0.16% 

Utah 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Vermont 0.00% 0.00% 

Virginia 0.12% 0.12% 

Washington 0.55% 0.55% 

West Virginia 0.00% 0.00% 

Wisconsin 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

0.00% 0.00% 

174 
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Table l4E. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Native Hawaiians and Pacific Islanders, Management of Companies and Enterprises, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio·All Ratio 

Firms of All Sales Employers Firms Employers 

Alabama 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Alaska 0.00% 0.00% 

Arizona 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Arkansas 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

California 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Colorado 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Connecticut 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Delaware 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

District of Columbia 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Florida 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Georgia 0.00% 0,00% 0.00% 0.00% 0.00 0.00 

Hawaii 1.58% 1.58% 

Idaho 0.00% 0.00% 

Illinois 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Indiana 0.00% 0.00% 0.00% 0.00% 0,00 0,00 

Iowa 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Kansas 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Kentucky 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Louisiana 0,00% 0.00% 0.00% 0.00% 0.00 0.00 

Maine 0.00% 0.00% 

Maryland 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Massachusetts 0.00% 0.00% 0.00% 0.00% 0,00 0.00 

Michigan 0.00% 0.00% 0.00% 0.00% 0,00 0.00 

Minnesota 0.00% 0.00% 0.00% 0.00% 0,00 0,00 

Mississippi 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Missouri 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Montana 0.00% 0.00% 

Nebraska 0.00% 0.00% 0.00% 0.00% 0.00 0,00 

Nevada 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

New Hampshire 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

New Jersey 0.00% 0.00% 0.00% 0.00% 0.00 0,00 

New Mexico 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

New York 0.00% 0.00% 0.00% 0.00% 0,00 0.00 

North Carolina 0.00% 0.00% 0.00% 0.00% 0,00 0.00 

North Dakota 0.00% 0.00% 

Ohio 0,00% 0.00% 0,00% 0.00% 0.00 0,00 

Oklahoma 0.00% 0.00% 0.00% 0.00% 0.00 

175 
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Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Pennsylvania 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Rhode Island 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

South Carolina 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

South Dakota 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Tennessee 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Texas 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Utah 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Vermont 0.00% 0.00% 

Virginia 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Washington 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

West Virginia 0.00% 0.00% 

Wisconsin 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

0.00% 0.00% 

176 
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Table 14F. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Women, Management of Companies and Enterprises, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 5.31% 5.31% 

Alaska 

Arizona 4.35% 0.35% 4.35% 0.35% 0.08 0.08 

Arkansas 6.53% 4.43% 6.53% 4.43% 0.68 0.68 

California 7.01% 0.82% 7.01% 0.82% 0.12 0.12 

Colorado 2.38% 2.38% 

Connecticut 

Delaware 3.94% 3.94% 

District of Columbia 5.15% 5.15% 

Florida 6.71% 2.12% 6.71% 2.12% 0.32 0.32 

Georgia 3.66% 3.69% 3.66% 3.69% 1.01 1.01 

Hawaii 6.84% 6.84% 

Idaho 7.74% 7.74% 

Illinois 7.70% 1.56% 7.70% 1.56% 0.20 0.20 

Indiana 

Iowa 7.63% 0.24% 7.63% 0.24% 0.03 0.03 

Kansas 5.16% 5.16% 

Kentucky 3.77% 3.87% 3.77% 3.87% 1.03 1.03 

Louisiana 7.98% 0.97% 7.98% 0.97% 0.12 0.12 

Maine 4.03% 4.03% 

Maryland 5.91% 5.91% 

Massachusetts 3.23% 3.23% 

Michigan 3,14% 3.14% 

Minnesota 4.78% 4.78% 

Mississippi 4.33% 2.31% 4.33% 2.31% 0.53 0.53 

Missouri 4.28% 2.76% 4.28% 2.76% 0.64 0.64 

Montana 5.94% 5.94% 

Nebraska 

Nevada 13.91% 2.19% 13.91% 2.19% 0.16 0.16 

New Hampshire 2.82% 2.82% 

New Jersey 2.61% 0.62% 2.61% 0.62% 0.24 0.24 

New Mexico 5.81% 5.81% 

New York 

North Carolina 7.37% 2.81% 7.37% 2.81% 0.38 0.38 

North Dakota 6.82% 6.82% 

Ohio 6.97% 2.69% 6.97% 2.69% 0.39 0.39 

Oklahoma 8.71% 3.43% 8.71% 3.43% 0.39 

177 
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Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Finns Employers Sales 

Oregon 7.82% 3.69% 7.82% 3.69% 0.47 0.47 

Pennsylvania 3.71% 0.97% 3.71% 0.97% 0.26 0.26 

Rhode Island 3.67% 3.67% 

South Carolina 6.07% 1.02% 6.07% 1.02% 0.17 0.17 

South Dakota 

Tennessee 3.72% 3.72% 

Texas 10.82% 1.12% 10.82% 1.12% 0.10 0.10 

Utah 4.01% 4.01% 

Vermont 2.27% 2.27% 

Virginia 5.87% 2.10% 5.87% 2.10% 0.36 0.36 

Washington 4.02% 0.86% 4.02% 0.86% 0.21 0.21 

West Virginia 

Wisconsin 8.21% 1.80% 8.21% 1.80% 0.22 0.22 

4.62% 4.62% 

178 
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NERA Economic Consulting 

Table 15A. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, African Americans, Administrative and Support and Waste Mgmt. and Remediation Services, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All ofAl! Ratio-All Ratio 

Finns of All Sales Employers Employer Finns Employers Sales 

Alabama 17,79% 1.84% 4.38% 1.28% 0,10 0.29 

Alaska 2.37% 0.37% 1.97% 0.27% 0,16 0,14 

Arizona 3,68% 0,96% 1.53% 0,84% 0,26 0,55 

Arkansas 

California 5.02% 1.04% 3,78% 0,78% 0,21 0,21 

Colorado 2.42% 0.38% 1.65% 0.28% 0,16 0,17 

Connecticut 3,17% 0,79% 0,25 

Delaware 12,96% 1.12% 6,94% 0,09 

District of Columbia 35,66% 11.40% 

Florida 9,24% 1.39% 2.92% 1.10% 0.15 0.38 

Georgia 21.60% 2.36% 5,74% 1.54% 0, II 0,27 

Hawaii 0,60% 0.49% 0.46% 0.49% 0,81 1.08 

Idaho 

Illinois 6,23% 0,88% 2,52% 0,70% 0,/4 0,28 

Indiana 4.20% 0,79% 0,]9 

Iowa 0,90% 

Kansas 4,68% 1.30% 2,60% 1.08% 0.28 0,41 

Kentucky 4,87% 0,95% 2,67% 0,70% 0,]9 0,26 

Louisiana 22,16% 2,99% 6,03% 2,25% 0,]4 0,37 

Maine 0.46% 

Marylnnd 19.32% 3.62% 7,61% 2,86% 0,]9 0,38 

Massachusetts 2,57% 0,86% 1.45% 0,84% 0.34 0,58 

Michignn 7,80% 2.38% 3,17% 2.25% 0,30 0,7] 

Minnesota 2,29% 1.47% 1.51% 0,64 

Mississippi 20,92% 1.89% 6,17% 0,87% 0.09 0,/4 

Missouri 4,87% 1.25% 3,30% 1.13% 0,26 0,34 

Montnna 0,14% 

Nebraska 2,23% 0.33% 0,89% 0,28% 0,]5 0,32 

Nevada 3,09% 0,80% 1.75% 0,80% 0.26 0.46 

New Hampshire 0,28% 0.36% 0.38% 0.38% 1.32 0,98 

New Jersey 5,37% 1.85% 2,61% 1.71% 0,34 0,66 

New Mexico 

New York 8,02% 1.13% 2.37% 0,83% 0,14 0,35 

North Carolina 14.20% 2,71% 6,92% 2,32% 0,19 0,34 

North Dakota 0,11% 

Ohio 6.47% 1.22% 2.47% 0,93% 0.19 0,38 

Oklahoma 5,10% 0,92% 3,14% 0,69% 0./8 0,22 

179 
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Percentage Percentage Percentage Disparity Disparity 

State of AI! Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Firms Employers 

Oregon 1.29% 0.17% 0.43% 0.13 

Pennsylvania 4.24% 0.99% 1.99% 0.79% 0.23 0.40 

Rhode Island 2.23% 0.16% 0.45% 0.07% 0.07 0.17 

South Carolina 15.58% 2.63% 4.84% 1.99% 0.17 0.41 

South Dakota 0.34% 

Tennessee 8.97% 1.86% 4.77% 1.48% 0.21 0.31 

Texas 8.48% 0.98% 3.81% 0.64% 0.12 0.17 

Utah 0.34% 0.08% 0.25 

Vermont 0.07% 0.22% 

Virginia 14.43% 3.08% 7.92% 2.75% 0.21 0.35 

Washington 1.98% 0.68% 1.45% 0.63% 0.34 0.43 

West Virginia 1.42% 0.30% 0.30% 0.21 

Wisconsin 1.74% 1.03% 1.41% 1.03% 0.59 0.73 

0.27% 

180 
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NERA Economic Consulting 

Table 15D. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Hispanics and Latinos, Administrative and Support and Waste Mgmt. and Remediation Services, 

2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 0.90% 1.41% 1.57 

Alaska 2.37% 1.89% 0.80 

Arizona 17.21% 2.90% 7.21% 2.10% 0.17 0.29 

Arkansas 1.26% 0.05% 

California 33.99% 6,98% 14,39% 5,33% 0,21 0,37 

Colorado 7,98% 1.70% 0.21 

Connecticut 6.29% 0,99% 2,72% 0,81% 0,16 0,30 

Delaware 

District of Columbia 8.51% 2,98% 

Florida 26,31% 3,70% 9,89% 2,74% 0,14 0,28 

Georgia 4.46% 0,86% 1.73% 0,67% 0,19 0,39 

Hawaii 5.44% 1.51% 1.18% 0,28 

Idaho 

Illinois 6.27% 3,25% 5,61% 3,14% 0,52 0,56 

Indiana 2,04% 0,24% 0.12 

Iowa 0,68% 

Kansas 2,10% 0,83% 2.Q4'10 0,76% 0,39 0,37 

Kentucky 0.55% 0.46% 0,60% 0.45% 0,85 0,75 

Louisiana 4.41% 0,75% 2,06% 0,60% 0,]7 0.29 

Maine 0.51% 0,35% 

Maryland 6.42% 1.97% 2,60% 1.69% 0,31 0,65 

Massachusetts 5.38% 2.43% 2,18% 2.37% 0.45 1.08 

Michigan 1.96% 0,97% 1.60% 0,96% 0,50 0.60 

Minnesota 1.06% 0,23% 0,92% 0,18% 0,22 0.20 

Mississippi 0,69% 0,82% 

Missouri 0,94% 0,57% 0.43% 0,55% 0,60 1.28 

Montana 

Nebraska 1.12% 0,27% 0,24 

Nevada 12.47% 2.40% 7,09% 2,13% 0,19 0,30 

New Hampshire 0.76% 0.46% 0.44% 0.46% 0,61 1.06 

New Jersey 

New Mexico 36,00% 9,75% 18.50% 0,27 

New York 18,90% 1.80% 3,93% 1.13% 0,]0 0,29 

North Carolina 1.49% 0,60% 1.61% 0,56% 0.40 0,35 

North Dakota 0.36% 

Ohio 0,73% 0.34% 0,63% 0.32% 0.46 

181 
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Percentage Percentage Percentage Disparity Disparity 

State of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Finns Employers Sales 

Oklahoma 4.28% 0.92% 2.04% 0.79% 0.22 0.39 

Oregon 4.03% 1.03% 3.23% 0.87% 0.26 0.27 

Pennsylvania 2.02% 0.37% 0.56% 0.29% 0.18 0.52 

Rhode Island 6.15% 0.53% 0.09 

South Carolina 1.13% 0.27% 0.24 

South Dakota 

Tennessee 1.07% 1.15% 1.06% !.I 8% 1.08 1.11 

Texas 30.49% 3.85% 11.69% 2.73% 0.13 0.23 

Utah 

Vermont 0.69% 

Virginia 9.11% 2.42% 4.44% 2.20% 0.27 0.49 

Washington 3.09% 0.62% 2.27% 0.47% 0.20 0.21 

West Virginia 0.15% 0.09% 0.55 

Wisconsin 1.56% 0.88% 1.09% 0.86% 0.56 0.79 

182 
366 

NERA Economic Consulting 

Table 15C. Percentage afFirms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Asians, Administrative and Support and Waste Mgmt. and Remediation Services, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 0.55% I.l2% 0.80% 1.07% 2.04 1.34 

Alaska 5.80% 2.62% 10.56% 2.36% 0.45 0.22 

Arizona 2.03% 0.72% 0.79% 0.68% 0.35 0.86 

Arkansas 0.29% 0.39% 0.10% 1.36 

California 9.27% 3.27% 6.99% 2.89% 0.35 0.41 

Colorado 2.60% 0.62% 1.89% 0.56% 0.24 0.30 

Connecticut 1.56% 0.81% 0.52 

Delaware 

District of Columbia 2.56% 1.93% 4.27% 1.92% 0.75 0.45 

Florida 1.54% 0.37% 1.14% 0.34% 0.24 0.29 

Georgia 2.91% 1.45% 0.50 

Hawaii 40.80% 17.40% 31.24% 15.92% 0.43 0.51 

Idabo 0.94% 0.62% 0.66 

Illinois 2.48% 2.38% 2.49% 2.43% 0.96 0.97 

Indiana 1.18% 0.91% 0.77 

Iowa 0.33% 0.79% 0.39% 2.43 

Kansas 1.46% 1.81% 

Kentucky 0.39% 0.08% 0.13% 0.03% 0.21 0.26 

Louisiana 0.67% 0.42% 0.26% 0.39% 0.63 1.50 

Maine 

Maryland 4.26% 2.87% 2.23% 2.82% 0.67 1.26 

Massachusetts 1.87% 0.78% 1.73% 0.73% 0.42 0.42 

Michigan 0.88% 1.54% 1.63% 1.59% 1.75 0.97 

Minnesota 1.80% 0.79% 1.04% 0.70% 0.44 0.67 

Mississippi 0.54% 0.18% 0.33 

Missouri 0.55% 0.69% 

Montana 0.18% 0.08% 

Nebraska 

Nevada 4.19% 1.07% 3.53% 0.95% 0.26 0.27 

New Hampshire 

New Jersey 

New Mexico 1.04% 1.07% 0.98% 1.10% 1.03 1.12 

New York 7.02% 1.22% 2.87% 0.97% 0.17 0.34 

North Carolina 1.38% 1.13% 0.82 

North Dakota 0.07% 0.14% 

Ohio 1.01% 0.65% 0.89% 0.65% 0.64 0.73 

Oklahoma 0.99% 0.50% 1.35% 

183 
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NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Finns Employers Sales 

Oregon 2.68% 1.40% 2.28% 0.52 

Pennsylvania 1.28% 0.70% 1.02% 0.64% 0.54 0.63 

Rhode Island 0.78% 0.50% 0.38% 0.52% 0.65 1.35 

South Carolina 0.76% I.Il% 0.66% I.I2% 1.46 1.70 

South Dakota 0.08% 

Tennessee 0.71% 0.23% 0.33 

Texas 3.07% 1.25% 2.24% I.I2% 0.41 0.50 

Utah 1.21% 0.60% 1.76% 0.56% 0.49 0.32 

Vermont 

Virginia 4.11% 3.74% 0.91 

Washington 7.39% 1.72% 4.21% 1.47% 0.23 0.35 

West Virginia 0.29% 0.90% 0.53% 0.95% 3.06 1.78 

Wisconsin 0.73% 0.27% 0.27% 0.25% 0.37 0.92 

184 
368 

NERA Economic Consulting 

Table ISD. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, American Indians and Alaska Natives, Administrative and Support and Waste Mgmt. and 

Remediation Services, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Finns Employers Sales 

Alabama 1.32% 1.01% 0.74% 1.03% 0.76 1.38 

Alaska 8.92% 37.75% 4.23 

Arizona 1.61% 0.28% 0.17 

Arkansas 1.38% 0.32% 0.34% 0.15% 0.23 0.45 

California 2.12% 0.46% 0.96% 0.40% 0.22 0.42 

Colorado 0.57% 0.78% 1.37 

Connecticut 0.28% 

Delaware 

District of Columbia 0.21% 0.13% 

Florida 0.56% 0.08% 0.47% 0.06% 0.14 0.13 

Georgia 0.39% 0.25% 0.63 

Hawaii 0.32% 0.59% 

Idaho 0.36% 0.78% 0.18% 0.80% 2.16 4.52 

Illinois 

Indiana 

Iowa 

Kansas 1.55% 0.46% 

Kentucky 0.83% 0.09% 0.09% 0.11 

Louisiana 1.02% 0.08% 0.08 

Maine 

Maryland 1.26% 0.21% 0.48% 0.17 

Massachusetts 

Michigan 0.58% 0.17% 0.28 

Minnesota 0.91% 0.46% 1.02% 0.46% 0.50 0.46 

Mississippi 

Missouri 0.85% 0.19% 0.54% 0.16% 0.23 0.30 

Montana 2.68% 0.43% 0.16 

Nebraska 0.18% 

Nevada 1.46% 0.13% 0.56% 0.08% 0.09 0.15 

New Hampshire 

New Jersey 0.55% 

New Mexico 3.90% 3.29% 2.56% 3.38% 0.84 1.32 

New York 1.16% 0.18% 0.82% 0.16 

North Carolina 0.95% 0.21% 0.31% 0.18% 0.22 0.58 

North Dakota 0.76% 0.35% 0.68% 0.46 

Ohio 0.50% 0.28% 0.55 

185 
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NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Firms Employers Sales 

Oklahoma 5.56% 3.48% 2.85% 3.32% 0.63 1.16 

Oregon 0.94% 0.35% 1.08% 0.33% 0.38 0.30 

Pennsylvania 0.12% 0.04% 0.31 

Rhode Island 

South Carolina 0.34% 0.32% 0.59% 0.31% 0.92 0.53 

South Dakota 2.59% 2.72% 1.05 

Tennessee 0.66% 0.24% 0.23% 0.23% 0.37 1.00 

Texas 

Utah 

Vermont 

Virginia 0.27% 0.10% 0.38 

Washington 1.91% 0.53% 0.28 

West Virginia 0.02% 0.00% 0.00% 0.00 

Wisconsin 1.25% 0.19% 0.68% 0.13% 0.15 0.20 

1.52% 0.42% 0.27 

186 
370 

NERA Economic Consulting 

Table 15E. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Native Hawaiians and Pacific Islanders, Administrative and Support and Waste Mgmt. and 

Remediation Services, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 

Alaska 0.52% 0.48% 0.92 

Arizona 

Arkansas 

California 

Colorado 

Connecticut 

Delaware 0.03% 0.09% 

District of Columbia 0.03% 0.00% 0.00% 0.00 

Florida 

Georgia 

Hawaii 13.12% 4.35% 7.12% 4.0So/() 0.33 0.57 

Idaho 

Illinois 0.00% 0.00% 0.00% 0.00 

Indiana 

Iowa 0.01% 0.00% 0.00% 0.00 

Kansas 

Kentucky 0.01% 0.00% 0.00% 0.00 

Louisiana 0.00% 0.00% 0.00% 0.00 

Maine 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Maryland 0.01% 0.05% 

Massachusetts 

Michigan 0.00% 0.01% 

Minnesota 

MisSissippi 

Missouri 

Montana 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Nebraska 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Nevada 0.15% 0.04% 0.29 

New Hampshire 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

New Jersey 

New Mexico 0.03% 0.00% 0.00% 0.00 

New York 

North Carolina 0.00% 0.01% 

North Dakota 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Ohio 

187 
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NERA 

EconomlC Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oklahoma 

Oregon 

Pennsylvania 

Rhode Island 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

South Carolina 

South Dakota 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Tennessee 0.01% 

Texas 

Utah 

Vermont 

Virginia 0.14% 

Washington 0.20% 

West Virginia 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Wisconsin 

0.00% 0.00% 0.00% 0.00% 0.00 0.00 

188 
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NERA Economic Consulting 

Table l5F. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Women, Administrative and Support and Waste Mgmt. and Remediation Services, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 35.67% 10.29% 21.23% 9.11% 0.29 0.43 

Alaska 32.33% 7.97% 24.83% 7.06% 0.25 0.28 

Arizona 36.60% 10.81% 20.06% 9.94% 0.30 0.50 

Arkansas 31.27% 15.17% 20.14% 14.85% 0.49 0.74 

California 37.73% 11.92% 17.51% 10.37% 0.32 0.59 

Colorado 41.25% 8.71% 24.32% 7.67% 0.21 0.32 

Connecticut 32.05% 7.18% 13.42% 6.05% 0.22 0.45 

Delaware 35.80% 9.75% 20.02% 9.29% 0.27 0.46 

District of Columbia 35.77% 23.58% 

Florida 37.76% 9.05% 21.90% 8.13% 0.24 0.37 

Georgia 36.42% 8.25% 18.58% 7.04% 0.23 IU8 

Hawaii 35.36% 12.70% 21.11% 11.25% 0.36 0.53 

Idaho 34.00% 10.42% 17.58% 9.21% 0.31 0.52 

Illinois 39.05% 12.17% 20.33% 11.27% 0.3/ 0.55 

Indiana 33.94% 9.85% 20.39% 9.04% 0.29 0.44 

Iowa 36.93% 10.30% 19.66% 9.41% 0.28 0.48 

Kansas 35.30% 8.03% 21.45% 7.00% 0.23 0.33 

Kentucky 34.11% 11.40% 18.05% 10.06% 0.33 0.56 

Louisiana 34.25% 10.73% 21.66% 9.93% 0.31 0.46 

Maine 31.75% 5.68% 11.21% 4.54% 0.18 0.4/ 

Maryland 37.66% 13.51% 21.61% 12.23% 0.36 0.57 

Massachusetts 33.91% 9.14% 17.29% 8.34% 0.27 0.48 

Michigan 36.63% 10.18% 19.97% 9.27% 0.28 0.46 

Minnesota 37.04% 8.31% 21.40% 7.32% 0.22 0.34 

Mississippi 30.29% 11.11% 17.38% 9.54% 0.37 0.55 

Missouri 35.60% 9.37% 20.68% 8.34% 0.26 0.40 

Montana 35.00% 18.77% 23.21% 17.77% 0.54 0.77 

Nebraska 31.64% 4.67% 12.86% 4.10% 0./5 0.32 

Nevada 31.61% 7.73% 18.92% 6.98% 0.24 0.37 

New Hampshire 36.63% 9.43% 19.02% 8.34% 0.26 0.44 

New Jersey 35.15% 14.38% 16.71% 13.58% 0.41 0.81 

New Mexico 36.04% 11.19% 23.57% 10.51% 0.3/ 0.45 

New York 38.04% 10.86% 18.06% 9.70% 0.29 0.54 

North Carolina 31.67% 13.41% 21.27% 12.67% 0.42 0.60 

North Dakota 25.85% 

Ohio 37.17% 9.63% 19.85% 8.57% 0.26 0.43 

Oklahoma 34.59% 10.28% 19.05% 9.37% 

189 
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NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 37.67% 11.42% 17.66% 10.27% 0.30 0.58 

Pennsylvania 34.55% 9.63% 16.75% 8.59% 0.28 0.5/ 

Rhode Island 36.98% 6.92% 13.76% 5.56% 0./9 0.40 

South Carolina 33.42% 8.40% 16.78% 7.10% 0.25 0.42 

South Dakota 31.62% 10.00% 16.31% 9.21% 0.32 0.56 

Tennessee 30.50% 8.07% 14.76% 6.93% 0.26 0.47 

Texas 36.10% 8.08% 21.51% 6.90% 0.22 0.32 

Utah 31.20% 10.43% 13.75% 9.67% 0.33 0.70 

Vcnnont 35.92% 8.12% 12.95% 5.00% 0.23 0.39 

Virginia 37.18% 11.93% 22.73% 11.19% 0.32 0.49 

Washington 39.97% 9.14% 22.10% 7.96% 0.23 0.36 

West Virginia 37.87% 8.64% 18.22% 7.19% 0.23 0.39 

Wisconsin 31.48% 10.53% 20.45% 10.15% 0.33 0.50 

32.94% 15.39% 17.64% 15.10% 0.47 0.86 

190 
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NERA Economic Consulting 

Table 16A. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, African Americans, Educational Services, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 10.92% 0.95% 

Alaska 

Arizona 

Arkansas 6.72% 0,23% 0.23% 0.03 

California 4.30% 0.43% 1.69% 0.29% 0.10 0.17 

Colorado 1.40% 0.51% 0.08% 0.16 

Connecticut 

Delaware 12.82% 0.00% 

District of Columbia 

Florida 6.85% 0.74% 4.13% 0.11 

Georgia 15.40% 0.75% 4.05% 0.37% 0.05 0.09 

Hawaii 

Idaho 

Illinois 7.79% 1.78% 

Indiana 

Iowa 2.04% 

Kansas 3.26% 0.00% 0.00% 0.00 

Kentucky 3.01% 0.15% 

Louisiana 19.26% 0.81% 2.19% 0.63% 0.04 0.29 

Maine 

Maryland 16.74% 1.73% 3.29% 0.10 

Massachusetts 

Michigan 7.59% 0.78% 3.13% 0.10 

Minnesota 1.94% 0.07% 

Mississippi 17.21% 2.36% 0.23% 0.14 

Missouri 5.92% 0.00% 0.00% 0.00 

Montana 

Nebraska 

Nevada 

New Hampshire 

New Jersey 6.45% 0.42% 3.18% 0.07 

New Mexico 

New York 8.96% 1.67% 0.27% 0.16 

North Cara Iina 

North Dakota 0.00% 0.00% 0.00% 0.00 

Ohio 5.81% 0.59% 0.10 

Oklahoma 4.15% 1.34% 1.43% 

191 
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NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Firms Employers Sales 

Oregon 

Pennsylvania 4.63% 

Rhode Island 

South Carolina 9,87% 0.27% 0.12% 0,03 

South Dakota 

Tennessee 8.86% 0.19% 0.02 

Texas 6.05% 1.07% 2.54% 0.94% 0.18 0.37 

Utah 

Vermont 

Virginia 7.92% 1.28% 4.23% 0,16 

Washington 

West Virginia 

Wisconsin 2.82% 0.42% 

0.00% 0.00% 

192 
376 

NERA Economic Consulting 

Table 16B. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Hispanics and Latinos, Educational Services, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 

Alaska 0.60% 

Arizona 

Arkansas 

California 9.30% 1.36% 3.69% 1.12% 0.]5 0.30 

Colorado 3.80% 1.41% 

Connecticut 1.70% 0.58% 

Delaware 1.19% 0.45% 

District of Columbia 2.78% 0.05% 0.02 

Florida 11.80% 2.22% 6.38% 1.98% 0.19 0.31 

Georgia 1.85% 0.28% 

Hawaii 2.43% 

Idaho 

Illinois 3.34% 0.13% 1.21% 0.09% 0.04 0.08 

Indiana 1.51% 

Iowa 0.82% 0.03% 0.03 

Kansas 0.94% 0.17% 

Kentucky 

Louisiana 

Maine 

Maryland 3.13% 2.96% 

Massachusetts 2.24% 0.05% 0.02 

Michigan 1.95% 0.27% 0.14 

Minnesota 1.l0% 0.05% 0.07% 0.05 

Mississippi 

Missouri 1.73% 0.02% 0.08% 0.01 

Montana 0.56% 

Nebraska 

Nevada 3.19% 0.50% 0.16 

New Hampshire 

New Jersey 5.66% 2.94% 

New Mexico 12.80% 

New York 6.77% 0.20% 2.45% 0.12% 0.03 0.05 

North Carolina 1.86% 0.04% 0.29% 0.02% 0.02 0.07 

North Dakota 0.11% 0.78% 

Ohio 0.95% 0.10% 0.34% 0.07% 0.11 0.21 

Oklahoma 1.51% 0.57% 

193 
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NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 0.87% 0.30% 

Pennsylvania 1.75% 0.16% 1.85% 0.15% 0.09 0.08 

Rhode Island 1.12% 0.31% 

South Carolina 1.67% 0.15% 0.09 

South Dakota 0.00% 0.00% 

Tennessee 1.22% 0.10% 

Texas 

Utah 3.26% 0.70% 

Vermont 0.27% 

Virginia 2.50% 0.87% 0.60% 0.35 

Washington 2.00% 0.55% 1.65% 0.27 

West Virginia 0.54% 

Wisconsin 

194 
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NERA Economic Consulting 

Table 16C. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Asians, Educational Services, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of AI! Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 0.77% 0.82% 

Alaska 1.81% 1.l6% 

Arizona 2.31% 

Arkansas 0.04% 0.00% 

California 9.72% 1.59% 9.90% 1.38% 0.16 0.14 

Colorado 2.07% 0.54% 2.31% 0.51% 0.26 0.22 

Connecticut 

Delaware 2.07% 4.98% 

District of Columbia 2.54% 0.26% 

Florida 1.29% 0.44% 0.34 

Georgia 2.48% 0.55% 4.49% 0.52% 0.22 0.12 

Hawaii 32.43% 3.84% 21.56% 0.12 

Idaho 0.99% 

Illinois 3.78% 0.35% 1.70% 0.09 

Indiana 1.36% 0.61% 

Iowa 1.34% 0.69% 

Kansas 0.69% 0.83% 

Kentucky 

Louisiana 1.39% 

Maine 0.38% 0.24% 

Maryland 6.56% 0.89% 4.96% 0.14 

Massachusetts 3.12% 0.13% 1.92% 0.04 

Michigan 2.32% 0.35% 1.10% 0.15 

Minnesota 1.77% 0.00% 0.00% 0.00 

Mississippi 

Missouri 1.71% 0.12% 1.17% 0.07 

Montana 0.07% 0.00% 

Nebraska 1.l0% 0.25% 

Nevada 3.53% 0.48% 

New Hampshire 0.58% 0.03% 0.20% 0.05 

New Jersey 5.45% 1.12% 4.99% 0.20 

New Mexico 1.17% 0.11% 0.09 

New York 5.37% 0.39% 4.63% 0.07 

North Carolina 1.23% 0.12% 0.10 

North Dakota 

Ohio 1.57% 0.17% U5% 0.10% 0.11 0.09 

Oklahoma 1.26% 0.32% 

195 
379 

NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State ofAl! Percentage of All ofAl! Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 2.28% 0.40% 

Pennsylvania 2.10% 0.08% 0.04 

Rhode Island 

South Carolina 3.00% 0.23% 0.73% 0.08 

South Dakota 

Tennessee 1.32% 0.31% 

Texas 3.32% 0.60% 2.05% 0.18 

Utah 1.43% 1.05% 

Vermont 0.86% 0.32% 

Virginia 4.09% 4.07% 

Washington 

West Virginia 1.03% 0.07% 0.00% 0.00% 0.07 0.00 

Wisconsin 1.71% 0.28% 0.16 

0.68% 

196 
380 

NERA Economic Consulting 

Table 160. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, American Indians and Alaska Natives, Educational Services, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 4.07% 0.00% 

Alaska 

Arizona 

Arkansas 

California 

Colorado 

Connecticut 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Delaware 0.08% 0.00% 

District of Columbia 

Florida 

Georgia 

Hawaii 

Idaho 

Illinois 

Indiana 0.11% 0.00% 0.00% 0.00 

Iowa 

Kansas 

Kentucky 0.33% 

Louisiana 

Maine 0.00% 0.00% 

Maryland 

Massachusetts 

Michigan 

Minnesota 

Mississippi 

Missouri 

Montana 5.07% 0.40% 

Nebraska 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Nevada 0.77% 0.00% 0.00% 0.00 

New Hampshire 

New Jersey 0.22% 

New Mexico 4.32% 0.55% 0./3 

New York 

North Carolina 

North Dakota 

Ohio 

Oklahoma 

197 
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NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 0.45% 0.08% 0.79% 0.17 

Pennsylvania 

Rhode Island 0.25% 0.00% 0.00% 0.00 

South Carolina 

South Dakota 4.57% 0.00% 

Tennessee 

Texas 1.13% 0.13% 0.34% O.II 

Utah 

Vermont 

Virginia 0.02% 0.05% 

Washington 1.84% 0.11% 

West Virginia 

Wisconsin 1.25% 0.00% 0.00% 0.00 

198 
382 

NERA Economic Consulting 

Table 16E. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Native Hawaiians and Pacific Islanders, Educational Services, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of AI! Percentage of All of AI! Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 0.00% 0.00% 

Alaska 0.09% 0.00% 

Arizona 0.01% 0.00% 0.00% 0.00 

Arkansas 0.00% 0.00% 0.00% 0.00 

California 

Colorado 

Connecticut 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Delaware 0.00% 0.00% 

District of Columbia 0.00% 0.00% 0.00% 0.00 

Florida 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Georgia 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Hawaii 14.95% 1.42% 

Idaho 0.00% 0.00% 

Illinois 

Indiana 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Iowa 0.00% 0,00%) 0.00% 0.00% 0.00 0.00 

Kansas 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Kentucky 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Louisiana 0.02% 0.00% 0.00% 0.00 

Maine 0.00% 0.00% 

Maryland 0.00% 0.00% 0.00% 0.00 

Massachusetts 0.0]% 0.00% 0.00% 0.00 

Michigan 0.0]% 0.00% 0.00% 0.00 

Minnesota 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Mississippi 0.00% 0.00% 0.00% 0.00% 1).00 0.00 

Missouri 0.02% 0.00% 0.00% 0.00 

Montana 0.00% 0.00% 0.00% 0.00 

Nebraska 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Nevada 0.10% 0.00% 0.00% 0.00 

New Hampshire 0.00% 0.00% 0.00% 0.00% 0.1)0 0.00 

New Jersey 0.01% 0.00% 0.00% 0.00 

New Mexico 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

New York 

North Carolina 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

North Dakota 0.00% 0.00% 0.00% 0.00 

Ohio 0.00% 0.00% 0.00% 0.00% 0.00 OJ)O 

Oklahoma 0.00% 0.00% 0.00% 0.00 

199 
383 

NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 0.23% 0.01% 0.00% 0.00% 0.06 0.00 

Pennsylvania 0.01% 0.00% 0.00% 0.00 

Rhode Island 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

South Carolina 0.02% 0.00% 0.00% 0.00 

South Dakota 0.00% 0.00% 

Tennessee 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Texas 

Utah 

Vermont 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Virginia 

Washington 0.01% 0.00% 

West Virginia 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Wisconsin 0.02% 0.08% 

0.00% 0.00% 

200 
384 

NERA Economic Consulting 

Table 16F. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Women, Educational Services, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Finns Employers Sales 

Alabama 43.01% 27.45% 

Alaska 39.83% 21.97% 

Arizona 45.70% 11.58% 26.97% 10.89% 0.25 0.40 

Arkansas 45.56% 5.07% 27.79% 0.11 

California 45.51% 6.02% 21.84% 4.61% 0.13 0.21 

Colorado 43.47% 6.24% 25.08% 4.78% 0.14 0.19 

Connecticut 44.75% 1.50% 19.37% 0.67% 0.03 0.03 

Delaware 46.26% 

District of Columbia 39.70% 12.63% 

Florida 47.32% 6.69% 28.44% 5.61% 0.14 0.20 

Georgia 54.97% 5.22% 35.20% 4.06% 0.09 0.12 

Hawaii 31.05% 3.26% 23.22% 0.10 

Idaho 45.91% 

Illinois 50.75% 4.09% 24.38% 3.03% 0.08 0.12 

Indiana 47.37% 4.25% 27.05% 3.38% 0.09 0.12 

Iowa 42.46% 3.46% 14.97% 2.89% 0.08 0.19 

Kansas 45.01% 6.11% 22.61% 0.14 

Kentucky 41.95% 4.85% 19.33% 4.03% 0.12 0.21 

Louisiana 44.87% 4.87% 25.32% O.II 

Maine 38.78% 

Maryland 51.70% 4.82% 27.51% 0.09 

Massachusetts 47.03% 1.93% 18.56% 1.36% 0.04 0.07 

Michigan 45.94% 6.22% 30.24% 4.56% 0.14 0.15 

Minnesota 44.55% 5.21% 22.23% 0.12 

Mississippi 45.18% 5.27% 22.55% 4.19% 0.12 0.19 

Missouri 45.71% 2.18% 20.17% 1.58% 0.05 0.08 

Montana 42.85% 8.78% 29.08% 0.20 

Nebraska 44.35% 4.87% 34.41% O.Il 

Nevada 36.28% 11.98% 20.29% 9.67% 0.33 0.48 

New Hampshire 46.45% 2.52% 24.45% 1.80% 0.05 0.07 

New Jersey 45.12% 5.71% 26.58% 0.13 

New Mexico 49.81% 7.39% 0.15 

New York 48.36% 3.16% 23.11% 0.07 

North Caro lina 51.24% 3.80% 28.17% 2.86% 0.07 0.10 

North Dakota 34.25% 

Ohio 50.32% 4.69% 25.21% 3.70% 0.09 0.15 

Oklahoma 44.89% 9.57% 18.23% 0.21 

201 
385 

NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All of AI! Ratio-All Ratio 

Finns of All Sales Employers Employer Finns Employers Sales 

Oregon 44.50% 3.53% 19.86% 2.26% 0.08 O.II 

Pennsylvania 45.70% 2.26% 18.30% 1.65% 0.05 0.09 

Rhode Island 51.32% 1.17% 7.81% 0.56% 0.02 0.07 

South Carolina 40.58% 5.55% 26.76% 0.14 

South Dakota 37.51% 

Tennessee 42.32% 2.43% 14.46% 1.58% 0.06 O.II 

Texas 48.44% 8.82% 29.14% 7.12% 0.18 0.24 

Utah 48.04% 8.96% 20.59% 6.40% 0.19 0.31 

Vermont 35.88% 13.69% 

Virginia 46.55% 8.49% 23.47% 0.18 

Washington 50.08% 7.43% 23.11% 0.15 

West Virginia 49.24% 5.45% 17.13% 0.11 

Wisconsin 49.21% 4.48% 22.83% 3.40% 0.09 0.15 

35.10% 17.97% 

202 
386 

NERA Economic Consulting 

Table 17 A. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, African Americans, Health Care and Social Assistance, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio·All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 18.56% 1.59% 6.17% 1.36% 0.09 0.22 

Alaska 4.90% 0.39% 1.47% 0.28% O.OS 0.19 

Arizona 3.77% 0.54% 1.55% 0.42% 0.14 0.27 

Arkansas 9.36% 0.71% 3.12% 0.54% O.OS 0.17 

California 8.90% 1.20% 3.23% 0.88% 0.14 0.27 

Colorado 3.01% 0.23% 1.11% 0.17% 0.07 0.15 

Connecticut 10.07% 0.38% 1.48% 0.23% 0.04 0.15 

Delaware 17.27% 0.99% 4.61% 0.56% 0.06 0.12 

District of Columbia 39.90% 3.58% 20.00% 0.09 

Florida 17.21% 1.12'10 3.41% 0.66% 0.07 0.19 

Georgia 26.11% 2.21% 8.79% 1.66% O.OS 0.19 

Hawaii 1.61% 0.08% 0.11% 0.05% 0.05 0.47 

Idaho 0.51% 0.04% 0.07 

minois 24.15% 1.12'10 3.73% 0.70% 0.05 0.19 

Indiana 10.12% 0.76% 2.97% 0.59% O.OS 0.20 

Iowa 2.26% 0.13% 0.40% 0.08% 0.06 0.21 

Kansas 5.09% 0.48% 1.60% 0.32% 0.09 IUO 

Kentucky 7.10% 0.45% 1.23% 0.34% 0.06 0.27 

Louisiana 26.51% 1.77% 7.79% 1.39% 0.07 O.IS 

Maine 

Maryland 29.19% 2.45% 7.60% 1.56% O.OS 0.20 

Massachusetts 4.19% 0.24% 1.14% 0.16% 0.06 0.14 

Michigan 17.71% 1.11% 3.41% 0.70% 0.06 0.20 

Minnesota 5.77% 0.28% 0.88% 0.17% 0.05 0.20 

Mississippi 26.40% 2.42% 10.93% 2.08% 0.09 0.19 

Missouri 10.13% 1.05% 4.62% 0.90% 0.10 0.20 

Montana 

Nebraska 4.74% 0.20% 1.39% 0.10% 0.04 0.07 

Nevada 3.67% 0.60% 2.13% 0.56% 0./6 0.27 

New Hampshire 

New Jersey 13.02% 1.27% 3.74% 1.07% 0.10 O.2S 

New Mexico 2.40% 0.13% 0.74% 0.09% 0.06 0.12 

New York 16.36% 1.21% 3.44% 0.80% 0.07 0.23 

North Carolina 17.39% 1.85% 8.03% 1.58% 0.11 0.20 

North Dakota 0.29% 0.16% 

Ohio 12.51% 0.72% 2.66% 0.45% 0.06 0.17 

Oklahoma 6.94% 0.84% 2.68% 0.68% 

203 
387 

NERA 

EconomIC Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage ofAll of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 1.66% 0.09% 0.50% 0.06% 0.06 0.11 

Pennsylvania 7.79% 0,56% 2.28% 0.43% 0.07 0.19 

Rhode Island 3,86% 0.57% 0,15 

South Carolina 16.66% 1.42% 6.22% 1.27% 0.09 0,20 

South Dakota 

Tennessee 13.44% 1.66% 5.28% 1.34% 0.12 0,25 

Texas 10.51% 1.35% 4.59% 1.10% 0.13 0.24 

Utah 0.42% 0.10% 0.25 

Vermont 

Virginia 15.25% 1.19% 5.64% 0.95% 0.08 0.17 

Washington 2.06% 0.64% 1.75% 0.61% 0.31 0.35 

West Virginia 4.47% 0.14% 1.24% 0.07% 0.03 0,06 

Wisconsin 6.57% 0.39% 2.96% 0.29% 0,06 0,/0 

204 
388 

NERA Economic Consulting 

Table 17B. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Hispanics and Latinos, Health Care and Social Assistance, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 0.73% 0.30% 0.87% 0.28% 0.41 0.32 

Alaska 5.83% 0.56% 0.10 

Arizona 12.92% 0.94% 3.55% 0.63% 0.07 0.18 

Arkansas 1.45% 0.75% 2.37% 0.70% 0.52 0.30 

California 18.70% 1.72% 4.66% 1.25% 0.09 0.27 

Colorado 7.49% 0.78% 1.98% 0.56% 0.10 0.28 

Connecticut 6.92% 0.49% 1.72% 0.42% 0.07 0.24 

Delaware 2.57% 0.53% 1.38% 0.50% 0.21 0.36 

District of Columbia 4.23% 0.50% 2.53% 0.46% 0.12 0.18 

Florida 18.24% 4.54% 14.97% 4.05% 0.25 0.27 

Georgia 2.57% 0.50% 1.47% 0.37% 0.19 0.25 

Hawaii 

Idaho 2.85% 0.21% 0.86% 0.17% 0.08 0.19 

Illinois 

Indiana 1.32% 0.21% 0.95% 0.16% 0.16 0.17 

Iowa 0.98% 0.13% 0.14 

Kansas 2.03% 0.59% 2.24% 0.57% 0.29 0.25 

Kentucky 0.71% 0.26% 0.62% 0.22% 0.36 0.36 

Louisiana 2.60% 0.97% 2.21% 0.92% 0.37 0.42 

Maine 1.03% 0.18% 0.17 

Maryland 3.50% 1.95% 2.28% 1.88% 0.56 0.83 

Massachusetts 6.04% 0.31% 1.04% 0.17% 005 0.17 

Michigan 2.61% 0.52% 1.29% 0.46% 0.20 0.36 

Minnesota 1.72% 0.15% 0.51% 0.13% 0.09 0.25 

Mississippi 1.73% 0.36% 0.21 

Missouri 1.06% 0.17% 0.65% 0.15% 0.16 0.23 

Montana 

Nebraska 

Nevada 5.46% 0.73% 1.90% 0.61% 0.13 0.32 

New Hampshire 

New Jersey 9.27% 0.83% 3.21% 0.67% 0.09 0.21 

New Mexico 32.19% 3.37% 7.73% 2.92% 0.10 0.38 

New York 16.63% 1.34% 3.02% 1.04% 0.08 0.34 

North Carolina 1.74% 0.26% 0.75% 0.22% 0.15 0.30 

North Dakota 

Ohio 1.60% 0.32% 1.22% 0.29% 0.20 0.24 

Oklahoma 1.61% 0.38% 1.26% 0.34% 0.24 

205 
389 

NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Firms Employers Sales 

Oregon 3.54% 0.43% 1.29% 0.34% 0.12 0.27 

Pennsylvania 2.32% 0.20% 0.78% 0.16% 0.09 0.20 

Rhode Island 10.23% 0.62% 0.06 

South Carolina 0.73% 0.16% 0.23 

South Dakota 0.34% 0.04% 0.13 

Tennessee 0.77% 0.19% 0.25 

Texas 20.09% 3.74% 10.14% 3.45% 0.19 0.34 

Utah 3.30% 0.48% 0.14 

Vermont 0.43% 0.08% 0.31% 0.19 

Virginia 3.50% 0.40% 1.56% 0.35% (1./ 1 0.22 

Washington 3.91% 0.44% 1.47% 0.31% 0.11 0.21 

West Virginia 0.85% 0.37% 0.44 

Wisconsin 1.38% 0.20% 0.98% 0.17% 0.14 0.17 

3.76% 0.10% 0.03 

206 
390 

NERA Economic Consulting 

Table 17C. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Asians, Health Care and Social Assistance, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 2.15% 1.05% 2.90% 0.97% 0.49 0.33 

Alaska 2.76% 0.92% 2.30% 0.82% 0.33 0.36 

Arizona 3.71% 1.72% 5.63% 1.61% 0.46 0.29 

Arkansas 1.72% 0.77% 2.62% 0.73% 0.45 0.28 

California 15.00% 7.34% 20.01% 6.85% 0.49 0.34 

Colorado 2.16% 0.79% 2.84% 0.74% 0.37 0.26 

Connecticut 2.90% 0.97% 3.89% 0.92% 0.34 0.24 

Delaware 4.25% 1.73% 7.55% 1.65% 0.41 0.22 

District of Columbia 3.33% 4.31% 

Florida 4.12% 2.47% 6.53% 2.46% 0.60 0.38 

Georgia 2.50% 1.23% 3.99% 1.20% 0.49 0.30 

Hawaii 47.42% 20.34% 50.60% 17.96% 0.43 0.35 

Idaho 0.96% 0.35% 0.37 

Illinois 7.03% 3.31% 10.30% 3.09% 0.47 0.30 

Indiana 3.32% 2.33% 5.82% 2.28% 0.70 0.39 

Iowa 1.10% 0.77% 2.01% 0.76% 0.70 0.38 

Kansas 2.20% 1.57% 3.69% 1.55% 0.72 0.42 

Kentucky 3.00% 2.02% 4.97% 1.99% 0.67 0.40 

Louisiana 2.60% 1.71% 3.62% 1.59% 0.66 0.44 

Maine 0.72% 0.16% 0.22 

Maryland 6.70% 3.54% 10.71% 3.35% 0.53 0.31 

Massachusetts 3.82% 0.87% 3.87% 0.74% 0.23 0.19 

Michigan 4.05% 2.94% 7.19% 2.75% 0.73 0.38 

Minnesota 2.12% 0.38% 1.94% 0.18 

Mississippi 1.37% 0.89% 2.27% 0.82% 0.65 0.36 

Missouri 2.25% 0.93% 3.50% 0.86% 0.42 0.25 

Montana 0.37% 

Nebraska 1.17% 0.85% 1.97% 0.85% 0.73 0.43 

Nevada 10.00% 4.29% 11.81% 3.96% 0.43 0.34 

New Hampshire 1.26% 0.55% 0.44 

New Jersey 8.99% 3.18% 9.61% 2.92% 0.35 0.30 

New Mexico 1.55% 1.36% 3.23% 1.34% 0.88 0.42 

New York 8.49% 2.93% 8.11% 2.38% 0.34 0.29 

North Carolina 2.16% 0.94% 0.43 

North Dakota 0.53% 0.31% 0.89% 0.57 

Ohio 3.81% 2.05% 7.06% 1.94% 0.54 0.28 

Oklahoma 2.21% 1.08% 3.21% 1.05% 0.49 

207 
391 

NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 3.47% 1.11% 3.59% 0.98% 0.32 0.27 

Pennsylvania 4.03% 1.55% 5.34% 1.48% 0.38 0.28 

Rhode Island 2.13% 0.70% 2.43% 0.64% 0.33 0.26 

South Carolina 1.85% 0.89% 2.31% 0.84% 0.48 0.36 

South Dakota 0.62% 0.28% 0.67% 0.45 

Tennessee 2.19% 0.69% 0.31 

Texas 5.53% 2.58% 8.08% 2.51% 0.47 0.31 

Utah 1.21% 0.37% 1.37% 0.33% 0.31 0.24 

Vermont 0.55% 

Virginia 5.75% 1.87% 6.76% 1.76% 0.33 0.26 

Washington 5.56% 1.83% 5.59% 1.65% 0.33 0.30 

West Virginia 4.55% 3.56% 11.14% 3.56% 0.78 0.32 

Wisconsin 2.19% 0.89% 2.70% 0.84% 0.40 0.31 

208 
392 

NERA Economic Consulting 

Table 17D. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, American Indians and Alaska Natives, Health Care and Social Assistance, 2002 

I Percentage Percentage Percentage Percentage of All Disparity Disparity 

State of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 0.75% 0.10% 0.13 

Alaska 

Arizona 3.44% 0.23% 0.66% 0.18% 0.07 0.28 

Arkansas 1.61% 0.32% 1.03% 0.32% 0.20 0.31 

California 2.11% 0.14% 0.48% 0.09% 0.07 0.19 

Colorado 1.06% 0.09% 0.09 

Connecticut 

Delaware 0.10% 0.06% 

District of Columbia 0.12% 0.00% 0.00% 0.00 

Florida 0.82% 0.05% 0.07 

Georgia 0.64% 0.10% 0.28% 0.16 

Hawaii 0.54% 0.03% 0.05 

Idaho 

Illinois 

Indiana 

Iowa 

Kansas 0.96% 0.05% 0.05 

Kentucky 

Louisiana 

Maine 

Maryland 

Massachusetts 

Michigan 0.90% 0.07% 0.50% 0.06% 0.08 0.12 

Minnesota 

Mississippi 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Missouri 0.53% 0.05% 0.10 

Montana 3.15% 0.18% 1.54% 0.11% 0.06 0.07 

Nebraska 

Nevada 0.58% 0.26% 0.58% 0.26% 0.45 0.45 

New Hampshire 0.51% 0.08% 

New Jersey 0.53% 0.02% 0.03 

New Mexico 4.21% 0.18% 0.34% 0.08% 0.04 0.23 

New York 1.24% 0.07% 0.20% 0.04% 0.05 0.21 

North Carolina 1.47% 0.10% 0.40% 0.07% 0.07 0.18 

North Dakota 4.85% 0.10% 0.00% 0.00% 0.02 0.00 

Ohio 0.31% 0.03% 0.11 

Oklahoma 6.90% 1.58% 4.29% 1.42% 

209 
393 

NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage ofAlI of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 1.22% 0,09% 0.0.8 

Pennsylvania 0,25% 0,01% 0,05 

Rhode Island 0,78% 0,02% 0,00% 0,00% 0,03 0,00 

South Carolina 0.24% 0,05% 0,52% 0,05% 0,J9 0,09 

South Dakota 

Tennessee LlO% 0,29% 0.26 

Texas 1.39% 0,14% 0.46% 0,13% O,JO 0.28 

Utah 

Vermont 0,12% 0,06% 

Virginia 0,92% 0,07% 0,07 

Washington 1.78% 0,17% 0,31% 0,11% 0,/0 0..34 

West Virginia 

Wisconsin 

210 
394 

NERA Economic Consulting 

Table 17E. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Native Hawaiians and Pacilic Islanders, Healtb Care and Social Assistance, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 0.00% 0.01% 

Alaska 

Arizona 0.09% 0.30% 

Arkansas 0.01% 0.00% 0.00% 0.00 

California 

Colorado 0.04% 

Connecticut 

Delaware 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

District of Columbia 0.02% 0.06% 

Florida 

Georgia 0.01% 0.00% 0.00% 0.00 

Hawaii 7.28% 0.45% 0.06 

Idaho 0.07% 0.00% 0.00% 0.00 

Illinois 0.28% 

Indiana 

Iowa 0.01% 0.00% 0.00% 0.00% 0.01 0.00 

Kansas 0.00% 0.00% 0.00% 0.00 

Kentucky 0.01% 0.00% 0.00% 0.00% 0.02 0.00 

Louisiana 0.01% 0.00% 0.00% 0.00% 0.04 0.00 

Maine 0.02% 0.00% 0.00% 0.00 

Maryland 0.02% 0.01% 

Massachusetts 0.01% 0.00% 0.00% 0.00 

Michigan 

Minnesota 0.00% 0.01% 

Mississippi 0.01% 0.00% 0.00% 0.00 

Missouri 0.00% 0.00% 0.00% 0.00 

Montana 0.01% 0.00% 0.00% 0.00 

Nebraska 

Nevada 0.04% 0.03% 

New Hampshire 

New Jersey 

New Mexico 0.03% 0.00% 0.00% 0.00% 0.01 0.00 

New York 0.58% 0.02% 0.03 

North Carolina 0.02% 0.00% 0.08 

North Dakota 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Ohio 

Oklahoma 

211 
395 

NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 

Pennsylvania 

Rhode Island 0.01% 0.00% 0.00% 0.00 

South Carolina 0.01% 0.00% 0.00% 0.00 

South Dakota 0.02% 0.06% 

Tennessee 0.01% 0.00% 0.00% 0.00 

Texas 

Utah 

Vermont 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Virginia 

Washington 

West Virginia 

Wisconsin 

0.00% 0.00% 0.00% 0.00% 0.00 0.00 

212 
396 

NERA Economic Consulting 

Table 17F. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Women, Health Care and Social Assistance, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 45.11% 5.34% 18.93% 4.68% 0.12 0.25 

Alaska 49.87% 5.79% 21.76% 4.36% 0.12 0.20 

Arizona 48.89% 6.18% 18.81% 4.89% 0.13 0.26 

Arkansas 43.24% 5.53% 18.72% 4.95% 0.13 0.26 

California 52.56% 8.36% 23.76% 6.58% 0.16 0.28 

Colorado 50.48% 6.44% 21.28% 4.85% 0.13 0.23 

Connecticut 51.98% 5.22% 19.34% 4.09% 0.10 0.21 

Delaware 44.85% 3.76% 19.05% 2.75% 0.08 0.14 

District of Columbia 46.69% 18.85% 

Florida 48.79% 6.30% 20.94% 5.01% 0.13 0.24 

Georgia 52.76% 5.87% 22.70% 4.67% 0.11 0.21 

Hawaii 40.24% 5.84% 16.06% 4.13% 0.15 0.26 

Idaho 44.19% 6.16% 18.86% 4.67% 0.14 0.25 

JIlinois 54.90% 5.38% 18.86% 4.18% 0.10 0.22 

Indiana 51.59% 4.98% 21.25% 3.99% 0.10 0.19 

Iowa 58.25% 4.20% 17.29% 2.69% 0.07 0.16 

Kansas 54.27% 5.41% 17.43% 3.91% 0.10 0.22 

Kentucky 47.52% 4.85% 20.48% 4.22% 0.10 0.21 

Louisiana 48.80% 6.03% 17.99% 5.01% 0.12 0.28 

Maine 46.33% 3.44% 22.75% 2.34% 0.07 0.10 

Maryland 56.92% 6.43% 19.59% 4.42% 0.11 0.23 

Massachusetts 50.51% 5.10% 21.55% 3.86% 0.10 0.18 

Michigan 55.58% 5.51% 21.48% 4.08% 0.10 0.19 

Minnesota 60.47% 4.26% 19.49% 2.60% 0.07 0.13 

Mississippi 43.63% 6.27% 19.92% 5.48% 0.14 0.28 

Missouri 51.57% 5.64% 21.31% 4.81% 0.11 0.23 

Montana 42.59% 3.86% 21.84% 2.40% 0.09 0.11 

Nebraska 58.63% 5.09% 23.93% 3.85% 0'()9 0.16 

Nevada 42.44% 5.42% 16.84% 3.88% 0.13 0.23 

New Hampshire 48.60% 4.78% 24.88% 3.82% 0.10 0.15 

New Jersey 44.77% 7.56% 19.46% 6.58% 0.17 0.34 

New Mexico 51.63% 6.42% 18.01% 5.27% 0.12 0.29 

New York 55.64% 7.24% 17.93% 5.32% 0.13 0.30 

North Carolina 48.30% 5.95% 22.36% 5.10% 0.12 0.23 

North Dakota 48.07% 2.96% 15.96% 1.70% 0.06 0.11 

Ohio 50.57% 4.99% 16.07% 3.96% 0.10 0.25 

Oklahoma 44.02% 6.81% 20.16% 5.85% 0.15 0.29 

213 
397 

NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State ofAl! Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 54.32% 5.12% 21.77% 3.29% 0.09 0./5 

Pennsylvania 43.40% 3.91% 17.12% 3.09% 0.09 0.18 

Rhode Island 49.43% 6.10% 19.34% 4.86% 0.12 0.25 

South Carolina 41.89% 4.21% 20.60% 3.63% 0./0 0.18 

South Dakota 47.45% 2.86% 17.60% 1.80% 0.06 0.10 

Tennessee 46.20% 4.86% 17.30% 3.78% 0.11 0.22 

Texas 49.92% 6.22% 21.82% 5.03% 0.12 0.23 

Utah 43.65% 4.70% 13.48% 3.80% 0.11 0.28 

Vermont 54.54% 5.02% 22.65% 3.33% 0.09 0.15 

Virginia 52.98% 5.31% 20.34% 4.24% 0.10 0.21 

Washington 49.47% 6.59% 24.51% 5.19% 0.13 0.2/ 

West Virginia 46.03% 3.46% 14.15% 2.71% 0.08 0.19 

Wisconsin 53.78% 3.32% 20.28% 2.39% 0.06 0.12 

45.06% 17.08% 

214 
398 

NERA Economic Consulting 

Table 18A. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, African Americans, Arts, Entertainment and Recreation, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of AI! of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 8.38% 0.86% 0.10 

Alaska 

Arizona 

Arkansas 3.51% 0.27% 0.64% 0.08 

California 5.74% 2.86% 3.86% 2.57% 0.50 0.67 

Colorado 1.80% 0.31% 0.50% 0.25% 0.17 0.49 

Connecticut 3.29% 

Delaware 7.10% 0.32% 

District of Columbia 23.72% 7.11% 0.30 

Florida 6.02% 1.44% 1.83% 1.16% 0.24 0.63 

Georgia 16.42% 4.44% 3.23% 0.27 

Hawaii 

Idaho 0.05% 0.16% 

Illinois 7.88% 1.45% 1.86% 0.75% 0.18 0.40 

Indiana 2.83% 0.05% 

Iowa 

Kansas 2.60% 0.40% 0.20% 0.15 

Kentucky 4.30% 0.76% 0.68% 0.31% 0.18 0.45 

Louisiana 12.71% 0.68% 0.05 

Maine 0.31% 0.24% 0.00% 0.80 

Maryland 14.94% 

Massachusetts 3.50% 0.88% 0.78% 0.62% 0.25 0.80 

Michigan 

Minnesota 2.08% 

Mississipp i 7.58% 7.48% 2.97% 0.99 

Missouri 5.08% 0.66% 0.13 

Montana 

Nebraska 0.89% 0.47% 0.26% 0.53 

Nevada 3.93% 1.80% 0.46 

New Hampshire 0.69% 0.23% 0.00% 0.00% 0.33 0.00 

New Jersey 7.22% 2.31% 2.23% 1.12% 0.32 0.50 

New Mexico 2.10% 0.40% 0.00% 0.00% 0.19 0.00 

New York 6.84% 1.63% 2.33% 0.93% 0.24 0.40 

North Carolina 7.52% 0.85% 2.28% 0.38% 0.1I 0.16 

North Dakota 0.67% 0.00% 0.00% 0.00 

Ohio 4.90% 0.34% 0.07 

Oklahoma 3.65% 

215 
399 

NERA I::conomic Consulting 

Percentage Percentage Percentage Disparity Disparity Percentage of All State of All of All Sales of All Employer Ratio-All Ratio 

Finns Employers Sales Firms Employers 

Oregon 

Pennsylvania 3.26% 0.36% 0.84% 0.18% 0.11 021 

Rhode Island 4.68% 0.47% 0.00% 0.00% 0.10 0.00 

South Carolina 6.97% 1.68% 0.24 

South Dakota 

Tennessee 

Texas 6.50% 0.82% 1.64% 0.48% 0.13 0.29 

Utah 0.51% 0.24% 0.00% 0.00% 0.48 0.00 

Vermont 0.60% 0.12% 0.20 

Virginia 7.39% 1.20% 3.91% 0.69% 0.16 0.18 

Washington 2.24% 0.26% 

West Virginia 2.06% 0.00% 0.00% 0.00 

Wisconsin 

0.23% 0.00% 

216 
400 

NERA Economic Consulting 

Table 18B. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Hispanics and Latinos, Arts, Entertainment and Recreation, 2002 

Percentage Percentage Percentage Disparity Disparity Percentage of All State of All of All Sales of All Employer Ratio-All Ratio 

Firms Employers Sales Firms Employers 

Alabama 0.74% 0.10% 

Alaska 1.21% 0.00% 

Arizona 5.90% 1.13% 0.19 

Arkansas 0.52% 0.00% 0.00% 0.00 

California 8.60% 2.00% 2.67% 1.13% 0.23 0.42 

Colorado 4.12% 0.78% 1.24% 0.19 

Connecticut 2.08% 0.33% 

Delaware 0.56% 0.06% 0.00% 0.00% 0.10 0.00 

District of Columbia 3.72% 0.79% 

Florida 12.00% 3.44% 0.29 

Georgia 

Hawaii 3.98% 

Idaho 

Illinois 3.24% 0.84% 1.I7% 0.60% 0.26 0.51 

Indiana 1.23% 0.87% 0.71 

Iowa 

Kansas 2.29% 0.56% 0.24 

Kentucky 0.72% 0.15% 0.20 

Louisiana 3.10% 0.46% 0./5 

Maine 

Maryland 1.93% 

Massachusetts 2.11% 0.34% 0.16 

Michigan 1.46% 0.15% 0.10 

Minnesota 1.00% 0.07% 0.00% 0.00% 0.07 0.00 

Mississippi 0.59% 

Missouri 1.37% 0.26% 0.21% 0.17% 0.19 0.81 

Montana 0.26% 0.00% 0.00% 0.00 

Nebraska 2.04% 0.39% 0.31% 0.80 

Nevada 5.46% 1.87% 1.90% 0.62% 0.34 0.33 

New Hampshire 

New Jersey 3.72% 0.69% 2.16% 0.47% 0.19 0.22 

New Mexico 14.09% 2.70% 4.33% 1.38% 0.19 0.32 

New York 5.38% 1.26% 1.90% 0.77% 0.23 0.41 

North Carolina 1.16% 1.95% 1.68 

North Dakota 

Ohio 1.24% 0.18% 0.11% 0.14 

Oklahoma 1.34% 0.30% 

217 
401 

NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Firms Employers 

Oregon 1.66% 0.08% 

Pennsylvania LlO% 

Rhode Island 2.52% 

South Carolina 0.66% 0.06% 0.00% 0.00% 0.09 0.00 

South Dakota 0.25% 0.17% 

Tennessee 1.11% 0.27% 0.29% 0.17% 0.24 0.60 

Texas 10.82% 2.10% 3.54% 1.12% 0.19 0.32 

Utah 2.32% 0.00% 0.00% 0.00 

Vermont 

Virginia 2.54% 

Washington 1.53% 

West Virginia 

Wisconsin 0.95% 0.09% 0.10 

1.82% 0.26% 

218 
402 

NERA EconomIC Consulting 

Table lSC, Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Asians, Arts, Entertainment and Recreation, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Firms Employers Sales 

Alabama 0.97% 0,309'0 0.00 

Alaska 1.31% 1.01% 0.42% 0.77 

Arizona 1.95% 0.73% 0.37 

Arkansas 0.87% 1.71% 3.58% 1.95% 1.96 0.54 

California 5.43% 2.07% 3.78% 1.78% 0.38 0.47 

Colorado 1.29% 0.61% 0.70% 0.53% 0.47 0.76 

Connecticut 1.11% 

Delaware 

District of Columbia 1.15% 

Florida 1.33% 0.89% 0.79% 0.85% 0.67 1.09 

Georgia 1.59% 1.00% 1.98% 0.92% 0.63 0.46 

Hawaii 28.19% 18.18% 19.95% 17.19% 0.64 0.86 

Idaho 

Illinois 2.45% 

Indiana 

Iowa 0.60% 0.47% 0.30% 0.77 

Kansas 0.90% 0.49% 0.54 

Kentucky 0.49% 1.26% 0.93% 1.25% 2.59 1.34 

Louisiana 0.80% 0.14% 0.17 

Maine 0.37% 0.00% 

Maryland 1.80% 1.63% 1.80% 0.91 

Massachusetts 2.06% 0.79% 0.38 

Michigan 

Minnesota 1.65% 0.25% 0.15 

Mississippi 0.42% 0.00% 0.00% 0.00 

Missouri 0.62% 0.26% 0.57% 0.42 

Montana 

Nebraska 0.55% 0.65% 

Nevada 4.58% 1.02% 0.21% 0.22 

New Hampshire 1.32% 0.00% 0.00% 0.00 

New Jersey 

New Mexico 1.63% 0.21% 0.13 

New York 5.04% 0.98% 1.47% 0.53% 0.19 0.36 

North Carolina 1.13% 0.18% 0.15 

North Dakota 

Ohio 1.01% 0.24% 0.24 

Oklahoma 

219 
403 

NERA E:conomic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage ofAl! ofAl! Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 2.60% 1.38% 0.68% 0.53 

Pennsylvania 1.43% 0.20% 0.14 

Rhode Island 0.96% 

South Carolina 0.66% 0.88% 0.23% 1.34 

South Dakota 0.35% 

Tennessee 

Texas 2.74% 1.06% 1.62% 0.67% 0.39 0.42 

Utah 0.70% 0.14% 

Vermont 

Virginia 2.63% 0.62% 0.24 

Washington 2.61% 1.81% 0.70 

West Virginia 

Wisconsin 1.46% 0.22% 0.15 

0.05% 0.00% 

220 
404 

NERA Economic Consulting 

Table 18D. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, American Indians and Alaska Natives, Arts, Entertainment and Recreation, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Finns Employers Sales 

Alabama 

Alaska 6.13% 0.42% 

Arizona 1.99% 0.29% 0.00% 0.00% 0.15 0.00 

Arkansas 

California 

Colorado 0.90% 0.13% 0.14 

Connecticut 1.38% 0.11% 0.00% 0.08 

Delaware 0.26% 0.19% 0.32% 0.72 

District of Columbia 

Florida 0.38% 0.09% 0.22 

Georgia 

Hawaii 2.16% 0.47% 0.22 

Idaho 

Illinois 0.74% 0.07% 0.10 

Indiana 1.18% 0.04% 0.03 

Iowa 

Kansas 0.90% 

Kentucky 0.57% 0.06% 0.00% 0.00% 0.11 0.00 

Louisiana 

Maine 0.95% 0.03% 0.00% 0.04 

Maryland 

Massachusetts 0.41% 0.04% 

Michigan 

Minnesota 0.81% 0.11% 0.00% 0.00% 0.14 0.00 

Mississippi 

Missouri 0.87% 0.13% 0.31% 0.15 

Montana 

Nebraska 0.10% 0.00% 0.00% 0.00 

Nevada 0.90% 0.03% 0.00% 0.00% 0.03 0.00 

New Hampshire 

New Jersey 

New Mexico 4.47% 0.68% 0.15 

New York 0.53% 

North Carolina 1.13% 0.10% 0.09 

North Dakota 2.51% 0.29% 

Ohio 0.51% 0.05% 0.00% 0.00% 0.10 0.00 

Oklahoma 6.42% 1.07% 2.44% 0.62% 0.17 0.25 

221 
405 

NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Firms Employers 

Oregon 0.94% 0.08% 

Pennsylvania 0.56% 0.03% 0.06 

Rhode Island 

South Carolina 

South Dakota 2.46% 0.21% 0.00% 0.00% 0.09 0.00 

Tennessee 0.45% 

Texas 0.70% 

Utah 

Vermont 

Virginia 

Washington 

West Virginia 

Wisconsin 1.77% 0.10% 0.00% 0.00% 0.06 0.00 

1.37% 0.00% 

222 
406 

NERA Economic Consulting 

Table 18E. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Native Hawaiians and Pacific Islanders, Arts, Entertainment and Recreation, 2002 

Percentage Percentage Percentage Disparity Disparity 

State ofAll Percentage of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Finns Employers Sales 

Alabama 0.00% 0.00% 0.00% 0.00% 0.00 Ii. 00 

Alaska 

Arizona 

Arkansas 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

California 

Colorado 0.06% 0.05% 

Connecticut 0.01% 0.00% 

Delaware 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

District of Columbia 0.00% 0.00% 0.00% 0.00 

Florida 

Georgia 0.03% 0.00% 0.00% 0.00 

Hawaii 12.71% 3.52% 6.42% 2.64% 0.28 0.41 

Idaho 0.02% 0.00% 0.00% 0.00 

Illinois 

Indiana 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Iowa 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Kansas 0.01% 0.00% 0.00% 0.00 

Kentucky 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Louisiana 0.01% 0.00% 0.00% 0.00 

Maine 0.02% 0.00% 

Maryland 0.01% 0.00% 

Massachusetts 

Michigan 0.00% 0.00% 0.00% 0.00 

Minnesota 

Mississippi 0.02% 0.00% 0.00% 0.00 

Missouri 

Montana 0.04% 0.00% 0.00% 0.00 

Nebraska 0.06% 0.00% 0.00% 0.00 

Nevada 

New Hampshire 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

New Jersey 

New Mexico 

New York 

North Carolina 

North Dakota 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Ohio 0.01% 0.03% 

Oklahoma 0.02% 0.10% 

223 
407 

NERA EconomiC Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 

Pennsylvania 0,01% 0,00% 0,00% 0,00 

Rhode Island 

South Carolina 0.01% 0,00% 0,00% 0,00 

South Dakota 0,04% 0,00% 0,00% 0,00 

Tennessee 0,04% 0,00% 0,00% 0,00% 0,11 0.00 

Texas 0,03% 

Utah 0.41% 0,18% 0.45 

Vermont 0,00% 0,00% 0,00% 0,00% 0,00 0,00 

Virginia 

Washington 0.41% 0,02% 0,00% 0,00% 0.04 0,00 

West Virginia 0.00% 0,00% 0,00% 0,00% 0.00 0,00 

Wisconsin 0,01% 0.Q4% 

0,00% 0,00% 0,00% 0,00 

224 
408 

NERA Economic Consulting 

Table 18F. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Women, Arts, Entertainment and Recreation, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage ofAl! of All Ratio-All Ratio 

Firms of All Sales Employers Firms Employers 

Alabama 27.01% 5.35% 9.01% 2.34% 0.00 0.26 

Alaska 

Arizona 32.10% 4.89% 21.10% 3.15% 0.15 0.15 

Arkansas 24.17% 9.95% 16.99% 6.58% OA1 0.39 

California 30.35% 10.50% 19.08% 8.54% 0.35 0.45 

Colorado 31.66% 6.85% 18.63% 4.85% 0.22 0.26 

Connecticut 32.87% 5.97% 13.75% 0.18 

Delaware 16.15% 2.60% 12.30% 0.16 

District of Columbia 43.74% 7.07% 21.65% 0.16 

Florida 28.29% 4.69% 15.99% 2.88% 0.17 0.18 

Georgia 33.70% 8.63% 17.99% 4.88% 0.26 0.27 

Hawaii 35.10% 11.27% 14.91% 7.33% 0.32 0.49 

Idaho 21.79% 8.18% 9.54% 7.40% 0.38 0.78 

Illinois 30.47% 8.69% 19.13% 7.09% 0.29 0.37 

Indiana 24.48% 2.48% 9.08% 1.32% 0.10 0.15 

Iowa 18.83% 4.95% 9.90% 3.53% 0.26 0.36 

Kansas 20.66% 7.60% 18.83% 6.46% 0.37 0.34 

Kentucky 25.36% 6.77% 0.27 

Louisiana 26.39% 3.39% 12.22% 2.38% 0.13 0.19 

Maine 28.25% 13.08% 24.09% 0.46 

Maryland 32.20% 7.45% 16.04% 0.23 

Massachusetts 36.17% 8.52% 16.48% 5.12% 0.24 0.31 

Michigan 30.82% 6.46% 15.78% 4.57% 0.21 0.29 

Minnesota 28.74% 6.18% 15.07% 4.47% 0.22 0.30 

Mississippi 18.64% 6.24% 0.33 

Missouri 23.45% 8.26% 13.60% 7.52% 0.35 0.55 

Montana 24.10% 14.39% 20.66% 13.98% 0.60 0.68 

Nebraska 21.68% 5.52% 8.94% 3.23% 0.25 0.36 

Nevada 33.48% 10.67% 24.58% 8.10% 0.32 0.33 

New Hampshire 29.39% 7.63% 10.86% 6.01% 0.26 0.55 

New Jersey 31.11% 12.03% 16.99% 9.15% 0.39 0.54 

New Mexico 32.63% 6.58% 19.20% 3.41% 0.20 0.18 

New York 34.53% 10.84% 16.72% 7.09% 0.31 OA2 

North Caro Iina 28.56% 7.49% 13.77% 4.92% 0.26 0.36 

North Dakota 13.20% 25.10% 1.90 

Ohio 28.10% 5.67% 10.57% 3.43% 0.20 0.32 

Oklahoma 24.66% 6.84% 22.44% 5.66% 0.28 0.25 

225 
409 

NERA E.conomic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State ofAl! ofAl! Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 29.43% 8.62% 0.29 

Pennsylvania 28.95% 6.99% 12.62% 5.08% 0.24 0.40 

Rhode Island 25.37% 12.72% 27.36% 12.48% 0.50 0.46 

South Carolina 30.45% 9.35% 16.68% 8.12% 0.31 0.49 

South Dakota 17.61% 6.18% 15.21% 5.61% 0.35 0.37 

Tennessee 25.87% 9.21% 13.37% 7.32% 0.36 0.55 

Texas 27.77% 6.25% 16.04% 4.35% 0.23 0.27 

Utah 26.74% 5.59% 0.21 

Vermont 31.51% 7.78% 0.25 

Virginia 31.89% 7.61% 13.69% 5.37% 0.24 0.39 

Washington 32.85% 7.26% 16.51% 5.39% 0.22 033 

West Virginia 25.54% 4.89% 25.81% 4.20% 0.19 0.16 

Wisconsin 25.46% 5.96% 15.30% 4.78% 0.23 0.31 

Wyoming 21.79% 11.28% 

226 
410 

NERA Economic Consulting 

Table 19A. Percentage of Firms and Sales and Corresponding Disparity Ratios, AU Firms and Employer 

Firms, African Americans, Accommodation and Food Services, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 9.81% 2.17% 0.22 

Alaska 0.98% 0.29% 0.54% 0.29 

Arizona 1.45% 0.28% 0.19 

Arkansas 

California 2.25% 0.98% 1.22% 0.94% 0.43 0.77 

Colorado 1.48% 0.59% 0.93% 0.57% 0.40 0.62 

Connecticut 2.45% 0.29% 0.52% 0.24% 0.12 0.46 

Delaware 3.79% 0.65% 0.17 

District of Columbia 14.96% 4.48% 

Florida 5.69% 0.99% 0.17 

Georgia 11.08% 2.37% 0.21 

Hawaii 0.21% 

Idaho 0.13% 0.04% 

Illinois 4.43% 1.31% 2.20% 1.28% 0.29 0.58 

Indiana 2.08% 0.55% 0.85% 0.52% 0.27 0.60 

Iowa 0.55% 0.18% 0.33 

Kansas 1.46% 1.39% 1.12% 1.23% 0.95 1.10 

Kentucky 3.06% 1.71% 1.28% 1.71% 0.56 1.33 

Louisiana 11.82% 2.43% 3.28% 2.23% 0.21 0.68 

Maine 0.08% 0.06% 

Maryland 10.64% 3.14% 0.30 

Massachusetts 1.15% 0.52% 0.47% 0.45 

Michigan 3.80% 1.41% 1.60% 1.36% 0.37 0.85 

Minnesota 0.70% 0.48% 0.52% 0.46% 0.69 0.89 

Mississippi 13.24% 0.89% 0.07 

Missouri 3.23% 1.32% 1.48% 1.18% 0.41 0.79 

Montana 

Nebraska 1.26% 0.22% 0.76% 0.17 

Nevada 1.11% 0.21% 0.44% 0.19% 0.19 0.44 

New Hampshire 

New Jersey 2.85% 0.88% 1.24% 0.85% 0.31 0.68 

New Mexico 0.40% 0.09% 0.22 

New York 4.06% 1.19% 0.29 

North Carolina 4.69% 1.82% 2.40% 1.82% 0.39 0.76 

North Dakota 0.18% 0.06% 

Ohio 3.79% 1.44% 1.83% 1.41% 0.38 0.77 

Oklahoma 1.83% 0.31% 0.77% 0.28% 0.17 0.36 

227 
411 

NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 0.56% 0.22% 0.39 

Pennsylvania 2.39% 1.27% 2.20% 1.27% 0.53 0.58 

Rhode Island 1.13% 0.46% 0.41 

South Carolina 9.37% 1.12% 2.82% 1.02% 0.]2 0.36 

South Dakota 

Tennessee 5.89% 1.78% 2.73% 1.75% 0.30 0.64 

Texas 4.64% 1.45% 0.31 

Utah 0.35% 0.11% 0.30 

Vermont 0.15% 0.00% 0.00% 0.00 

Virginia 4.91% 1.49% 2.34% 1.41% 0.30 0.60 

Washington 0.66% 0.18% 0.15% 0.17% 0.27 1.07 

West Virginia 0.68% 0.12% 0.]8 

Wisconsin 1.70% 1.71% 1.00% 1.72% 1.01 ].72 

0.10% 0.06% 

228 
412 

NERA Economic Consulting 

Table 19B. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Hispanics and Latinos, Accommodation and Food Services, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of AI! Percentage of AI! of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 2.29% 

Alaska 3.06% 3.14% 1.02 

Arizona 11.25% 3.31% 0.29 

Arkansas 2.28% 1.23% 1.87% 1.23% 0.54 0.66 

California 13.72% 4.60% 8.70% 4.24% 0.34 0.49 

Colorado 8,47% 4.89% 7.92% 4.80% 0.58 0.61 

Connecticut 3.55% 1.58% 2.99% 1.55% 0.44 0.52 

Delaware 1.90% 1.69% 0.89 

District of Columbia 6.23% 1.01% 4.11% 1.00% 0.16 0.24 

Florida 11.68% 3.36% 0.29 

Georgia 4.77% 2.37% 6.18% 2,42% 0.50 0.39 

Hawaii 1.53% 0.17% 0.11 

Idaho 4.38% 2.78% 0.63 

Illinois 6.41% 2.57% 4.99% 2.47% 0.40 0.49 

Indiana 2.46% 0.89% 2.33% 0.85% 0.36 0.37 

Iowa 2.29% 1.52% 2.37% 1.44% 0.66 0.61 

Kansas 3.93~/~ 2.38% 4.27% 2.43% 0.6\ 0.57 

Kentucky 

Louisiana 3.24% 2.33% 0.72 

Maine 

Maryland 4.18% 0.83% 2.08% 0.80% 0.20 0.39 

Massachusetts 3.24% 0.87% 2.24% 0.68% 0.27 0.30 

Michigan 1.34% 0.49% 1.23% 0.49% 0.36 0.40 

Minnesota 1.34% 0.89% 1.34% 0.88% 0.67 0.65 

Mississippi 2.01% 0.61% 2.26% 0.58% 0.30 0.25 

Missouri 1.43% 0.71% 1.38% 0.69% 0.49 0.50 

Montana 0.72% 0.73% 0.97% 1.02 

Nebraska 2.90% 1.00% 2.76% 0.89% 0.35 0.32 

Nevada 8.35% 0.65% 7.03% 0.08 

New Hampshire 0.34% 0.14% 0.42 

New Jersey 8.25% 1.83% 6.26% 1.74% 0.22 0.28 

New Mexico 21.76% 13.22% 19.81% 13.13% 0.61 0.66 

New York 8.02% 1.62% 3.75% 1.54% 0.20 0.41 

North Carolina 2.63% 1.14% 0.43 

North Dakota 0.74% 0.57% 

Ohio 1.44% 0.67% 0.46 

Oklahoma 4.40% 2.22% 2.23% 

229 
413 

NERA EconomIC Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Firms Employers Sales 

Oregon 2.62% 1.12% 2.43% 1.08% 0.43 0.45 

Pennsylvania 1.37% 0.22% 1.04% 0.19% 0.16 0.18 

Rhode Island 3.93% 1.04% 1.41% 0.98% 0.27 0.69 

South Carolina 2.20% 1.58% 2.94% 1.62% 0.72 0.55 

South Dakota 0.55% 0.71% 

Tennessee 2.40% 1.49% 0.62 

Texas 22.32% 6.40% 17.55% 6.24% 0.29 0.36 

Utah 4.93% 1.73% 4.87% 1.72% 0.35 0.35 

Vermont 

Virginia 4.32% 1.85% 3.10% 1.86% 0.43 0.60 

Washington 4.74% 3.18% 4.97% 3.15% 0.67 0.63 

West Virginia 2.00% 1.43% 2.92% 1.46% 0.71 0.50 

Wisconsin 1.64% 1.04% 1.52% 1.03% 0.63 0.68 

2.68% 2.79% 

230 
414 

NERA Economic Consulting 

Table 19C. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Asians, Accommodation and Food Services, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Firms Employers Sales 

Alabama 10.97%. 6.14% 13.57% 6.10% 0.56 0.45 

Alaska 11.47% 9.58% 17.56% 9.52% 0.84 0.54 

Arizona 11.96% 4.64% 14.05% 4.49% 0.39 0.32 

Arkansas 9.33% 7.04% 12.42% 7.11% 0.75 0.57 

California 33.22% 16.80% 38.95% 16.43% 0.51 0.42 

Colorado 10.55% 4.25% 12.30% 4.19% 0.40 0.34 

Connecticut 10.48% 3.98% 10.10% 3.80% 0.38 0.38 

Delaware 10.69% 2.36% 8.83% 0.22 

District of Columbia 26.03% 6.28% 32.43% 0.24 

Florida 12.41% 5.94% 16.46% 5.96% 0.48 0.36 

Georgia 19.94% 8.97% 26.14% 8.77% 0.45 0.34 

Hawaii 54.88% 16.73% 54.11% 16.31% 0.30 0.30 

Idaho 4.73% 2.73% 0.58 

Illinois 13.03% 5.63% 14.46% 5.55% 0.43 0.38 

Indiana 9.33% 2.97% 10.54% 2.90% 0.32 0.28 

Iowa 5.43% 3.02% 6.12% 2.98% 0.56 0.49 

Kansas 11.72% 5.82% 13.82% 5.86% 0.50 0.42 

Kentucky 7.97% 3.92% 10.23% 3.90% 0.49 0.38 

Louisiana 8.73% 4.20% 12.30% 4.10% 0.48 0.33 

Maine 5.11% 3.98% 6.93% 4.07% 0.78 0.59 

Maryland 19.43% 7.19% 21.49% 6.94% 0.37 0.32 

Massachusetts 12.15% 6.44% 14.41% 6.46% 0.53 0.45 

Michigan 7.26% 3.05% 8.29% 3.01% 0.42 0.36 

Minnesota 6.96% 5.23% 8.08% 5.23% 0.75 0.65 

Mississippi 10.74% 3.58% 15.02% 3.53% 0.33 0.23 

Missouri 8.97% 3.97% 10.75% 3.96% 0.44 0.37 

Montana 3.52% 1.58% 0.45 

Nebraska 5.22% 2.82% 5.77% 2.72% 0.54 0.47 

Nevada 16.52% 1.06% 17.24% 1.02% 0.06 0.06 

New Hampshire 8.27% 5.05% 10.59% 5.00% 0.61 0.47 

New Jersey 15.77% 5.36% 15.70% 5.16% 0.34 0.33 

New Mexico 9.79% 4.55% 11.32% 4.48% 0.46 0.40 

New York 19.34% 6.98% 15.96% 6.56% 0.36 0.41 

North Carolina 13.26% 6.15% 15.28% 5.97% 0.46 0.39 

North Dakota 4.66% 

Ohio 8.17% 4.60% 9.22% 4.51% 0.56 0.49 

Oklahoma 11.66% 5.84% 13.90% 5.74% 0.50 0.41 

231 
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NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of AI! of All Ratio-All Ratio 

Finns of All Sales Employers Employer Finns Employers Sales 

Oregon 14.49% 9.13% 16.32% 9.08% 0.63 0.56 

Pennsylvania 11.21% 4.70% 10.22% 4.42% 0.42 0.43 

Rhode Island 6.12% 2.99% 6.02% 2.86% 0.49 0.48 

South Carolina 10.81% 5.50% 12.76% 5.40% 0.51 0.12 

South Dakota 1.39% 

Tennessee 13.55% 6.94% 17.89% 6.69% 0.51 0.37 

Texas 16.08% 7.85% 19.87% 7.68% 0.49 0.39 

Utah 10.60% 5.01% 12.46% 5.07% 0.47 0.11 

Vennont 4.70% 

Virginia 21.28% 10.03% 24.34% 9.95% 0.47 0.41 

Washington 19.17% 6.85% 18.98% 6.49% 0.36 0.34 

West Virginia 4.81% 2.72% 5.06% 2.59% 0.57 0.51 

Wisconsin 5.08% 2.87% 5.98% 2.84% 0.57 0.48 

6.69% 3.67% 0.55 

232 
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NERA Economic Consulting 

Table 19D. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, American Indians and Alaska Natives, Accommodation and Food Services, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 

Alaska 4.45% 3.21% 4.16% 3.15% 0.72 0.76 

Arizona 0.42% 0.12% 0.20% 0.12% 0.29 0.59 

Arkansas 

California 

Colorado 0.70% 0.22% 0.32 

Connecticut 

Delaware 0.05% 0.07% 

District of Columbia 0.21% 0.15% 

Florida 0.15% 0.01% 0.09 

Georgia 

Hawaii 0.13% 0.04% 

Idaho 

Illinois 

Indiana 

Iowa 0.09% 0.23% 0.13% 0.24% 2.50 1.85 

Kansas 

Kentucky 

Louisiana 

Maine 

Maryland 0.24% 

Massachusetts 

Michigan 0.52% 0.16% 0.56% 0.3/ 

Minnesota 

Mississippi 0.09% 

Missouri 0.24% 

Montana 

Nebraska 0.29% 0.06% 0.18% 0.05% 0.20 0.28 

Nevada 0.50% 035% 

New Hampshire 0.03% 0.00% 0.00% 0.00 

New Jersey 

New Mexico 1.52% 0.05% 0.04 

New York 

North Carolina 0.71% 0.18% 0.65% 0.17% 0.25 0.27 

North Dakota 

Ohio 

Oklahoma 4.09% 1.24% 4.15% 1.21% 

233 
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NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Firms Employers Sales 

Oregon 0.45% 0.13% 0.28 

Pennsylvania O.IS% 0.07% 0.26% 0.07% 0.39 0.27 

Rhode Island 

South Carolina 0.30% O.IS% 0.40% 0.15% 0.59 0.37 

South Dakota 

Tennessee 0.56% 0.04% 0.08 

Texas I.4S% 0.57% 0.38 

Utah 

Vermont 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Virginia 0.44% 0.32% 0.74 

Washington 0.54% 

West Virginia 

Wisconsin 0.34% 0.07% 0.21 

Wyoming 

234 
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NERA Economic Consulting 

Table 19E. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Native Hawaiians and Pacific Islanders, Accommodation and Food Services, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage orAll orAll Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Alaska 0.06% 0.06% 

Arizona 0.12% 0.01% 0.09% 0.07 

Arkansas 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

California 0.05% 0.02% 0.44 

Colorado 

Connecticut 

Delaware 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

District of Columbia 0.05% 0.00% 0.00% 0.00 

Florida 0.03% 

Georgia 

Hawaii 3.95% 0.61% 0.15 

Idaho 0.19% 0.23% 1.21 

Illinois 

Indiana 

Iowa 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Kansas 

Kentucky 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Louisiana 

Maine 

Maryland 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Massachusetts 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Michigan 0.01% 0.00% 0.00% 0.00 

Minnesota 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Mississippi 0.02% 0.00% 0.00% 0.00 

Missouri 0.01% 0.01% 

Montana 0.10% 0.03% 

Nebraska 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Nevada 

New Hampshire 

New Jersey 

New Mexico 0.02% 0.00% 0.00% 0.00 

New York 

North Carolina 

North Dakota 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Ohio 0.00% 0.00% 0.00% 0.00 

Oklahoma 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

235 
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NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Finns Employers Sales 

Oregon 

Pennsylvania 

Rhode Island 0.06% 0.00% 0.00% 0.00 

South Carolina 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

South Dakota 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Tennessee 

Texas 

Utah 

Vermont 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Virginia 

Washington 0.07% 0.01% 0.09 

West Virginia 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Wisconsin 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

0.00% 0.00% 0.00% 0.00% 0.00 0.00 

236 
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NERA Economic Consulting 

Table 19F. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Women, Accommodation and Food Services, 2002 

Percentage Percentage Percentage Disparity Disparity 

State of AI! Percentage of AI! of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 30.29% 8.97% 23.28% 8.53% 0.30 0.37 

Alaska 23.63% 11.41% 23.11% 11.05% 0.48 0.48 

Arizona 22.40% 7.85% 21.57% 7.60% 0.35 0.35 

Arkansas 24.28% 10.26% 20.67% 10.19% 0.42 0.49 

California 23.91% 9.74% 20.53% 9.18% 0.41 0.45 

Colorado 24.77% 7.71% 20.60% 7.47% 0.31 0.36 

Connecticut 19.84% 5.42% 14.71% 0.27 

Delaware 22.06% 9.09% 20.42% 8.83% 0.41 0.43 

District of Columbia 21.92% 15.85% 

Florida 25.01% 7.83% 20.41% 7.52% 0.31 0.37 

Georgia 29.74% 8.34% 20.60% 7.69% 0.28 0.37 

Hawaii 32.77% 9.97% 28.66% 9.65% 0.30 0.34 

Idaho 23.68% 8.52% 20A2~/o 7.98% 0.36 0.39 

Illinois 21.75% 7.76% 18.29% 7.51% 0.36 0.41 

Indiana 21.26% 6.20% 19.10% 6.09% 0.29 0.32 

Iowa 25.42% 8.98% 21.80% 8.82% 0.35 0.40 

Kansas 23.28% 9.13% 22.13% 9.08% 0.39 0.41 

Kentucky 27.51% 9.33% 22.10% 8.94% 0.34 0.40 

Louisiana 27.12% 8.02% 21.31% 7.66% 0.30 0.36 

Maine 24.36% 13.24% 21.35% 13.04% 0.54 0.61 

Maryland 20.12% 6.19% 15.32% 5.80% 0.31 0.38 

Massachusetts 21.51% 9.18% 18.59% 9.04% 0.43 0.49 

Michigan 23.62% 8.02% 19.1l% 7.77% 0.34 0.41 

Minnesota 21.06% 8.13% 18.36% 8.06% 0.39 0.44 

Mississippi 26.68% 6.04% 0.23 

Missouri 25.25% 7.71% 21.92% 7.67% 0.31 0.35 

Montana 26.49% 11.06% 22.02% 10.95% 0.42 0.50 

Nebraska 22.58% 9.07% 20.55% 8.91% 0.40 0.43 

Nevada 23.39% 2.80% 18.41% 2.71% 0.12 0.15 

New Hampshire 22.52% 9.10% 17.50% 8.80% 0.40 0.50 

New Jersey 19.18% 5.63% 13.78% 5.32% 0.29 0.39 

New Mexico 24.91% 9.46% 20.65% 9.29% 0.38 0.45 

New York 24.88% 9.83% 17.15% 9.31% 0.40 0.54 

North Carolina 23.63% 7.45% 19.38% 7.30% 0.32 0.38 

North Dakota 24.02% 

Ohio 24.72% 7.75% 18.59% 7.29% 0.31 0.39 

Oklahoma 27.07% 11.01% 21.02% 10.54% 0.41 0.50 

237 
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Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Firms Employers Sales 

Oregon 22.89% 10.87% 19.62% 10.52% 0.47 0.54 

Pennsylvania 22.24% 9.97% 20.73% 9.83% 0.45 0.47 

Rhode Island 21.33% 9.55% 15.33% 9.01% 0.45 0.59 

South Carolina 23.76% 9.17% 19.56% 8.78% 0.39 0.45 

South Dakota 18.78% 6.52% 18.42% 6.50% 0.35 0.35 

Tennessee 28.52% 7.02% 17.31% 6.52% 0.25 0.38 

Texas 3l.l2% 9.79% 24.62% 9.35% 0.31 0.38 

Utah 19.72% 6.97% 17.39% 6.94% 0.35 0.40 

Vermont 26.18% 12.65% 22.92% 12.46% 0.48 0.54 

Virginia 23.18% 6.18% 17.80% 5.93% 0.27 0.33 

Washington 22.52% 8.35% 19.90% 8.20% 0.37 0.41 

West Virginia 30.89% 8.26% 27.82% 8.07% 0.27 0.29 

Wisconsin 23.12% 1l.l8% 20.67% 10.73% 0.48 0.52 

22.08% 8.99% 23.31% 8.99% 0.41 0.39 

238 
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NERA Economic Consulting 

Table 20A. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, African Americans, Other Services (Except Public Administration), 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Firms Employers Sales 

Alabama 16.43% 4.45% 4.49% 2.51% 0.27 0,56 

Alaska 2.29% 0.59% 0.35% 0.26 

Arizona 1.46% 0.41% 0.75% 0.28 

Arkansas 7.43% 2.40% 1.71% 0,60% 0.32 0.35 

California 4,99% 1.11% 1.26% 0.47% 0.22 0.37 

Colorado 1.52% 0.58% 0,67% 0.43% 0.38 0,65 

Connecticut 5,12% 1.33% 2,02% 0.74% 0.26 0.37 

Delaware 11.09% 2.86% 1.23% 1.15% 0.26 0.93 

District of Columbia 51.44% 15.99% 

Florida 9,70% 2.81% 2.40% 1.15% 0.29 0.48 

Georgia 19.84% 5.72% 5.33% 2,78% 0.29 0,52 

Hawaii 0.95% 0,51% 0.38% 0.40% 0,54 1.04 

Idaho 0.11% 

Illinois 11.15% 2.79% 1.83% 1.45% 0.25 0,79 

Indiana 5.28% 1.30% 0.25 

Iowa 0,63% 0.34% 0.52% 0,34% 0.54 0,66 

Kansas 2.93% 0.80% 0,91% 0.38% 0.27 0.41 

Kentucky 3.35% 0,99% 0.91% 0.34% 0.29 0.37 

Louisiana 18,98% 4.51% 4.34% 1.70% 0.24 0.39 

Maine 

Maryland 22.00% 4,97% 4.61% 2,70% 0,23 0.59 

Massachusetts 2.44% 0,93% 1.55% 0.75% 0.38 0.49 

Michigan 10.20% 2.17% 1.70% 1.22% 0.21 0.72 

Minnesota 1.24% 0.38% 0.31 

Mississippi 19.64% 7,05% 6.28% 3.98% 0.36 0.63 

Missouri 5.52% 1.87% 1.74% 0.95% 0.34 0.55 

Montana 

Nebraska 1.96% 0.58% 0,32% 0.36% 0.30 1.12 

Nevada 4.18% 1.41% 1.49% 0.78% 0.34 a.52 

New Hampshire 

New Jersey 7.06% 1.79% 3.11% 1.42% 0.25 0.46 

New Mexico 1.40% 0.42% 0.30 

New York 11.74% 2.87% 2.31% 1.25% 0.24 0,54 

North Carolina 12.25% 3.48% 4.33% 1.74% 0.28 0.40 

North Dakota 

Ohio 6.34% 1.63% 2.38% 0.86% 0,26 0.36 

Oklahoma 3,71% 1.34% 1.46% 1.06% 0.36 0.73 

239 
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Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 0,82% 0.30% 0,11% 0,36 

Pennsylvania 3.68% 1.02% 1.40% 0,66% 0.28 0.47 

Rhode Island 2.35% 0.48% 0.20 

South Carolina 16,61% 5,54% 6.05% 2,66% 0,33 0.44 

South Dakota 0.06% 0.14% 

Tennessee 10,12% 2.62% 3,06% 1.03% 0,26 0,34 

Texas 7.70% 2.15% 2,70% 1.24% 0.28 0.46 

Utah 0.69% 0,15% 0.10% 0.06% 0,22 0,62 

Vermont 0.26% 0.00% 0.00% 0.00 

Virginia 12.17% 3,38% 4,73% 2.33% 0.28 0.49 

Washington 2,29% 1.25% 1.60% 1.08% 0,54 0,68 

West Virginia 1.51% 0.43% 0,28 

Wisconsin 2,87% 0,82% 1.02% 0.44% 0.29 0,43 

240 
424 

NERA Economic Consulting 

Table 20B. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Hispanics and Latinos, Other Services (Except Public Administration), 2002 

Percentage Percentage Percentage Disparity Disparity 

State ofAl! of All Ratio-Al! Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 0.71% 0.23% 0.13% 0.09% 0.33 0.70 

Alaska 1.93% 0.79% 2.35% 0.41 

Arizona 13.83% 6.18% 8.53% 3.61% 0.45 0.42 

Arkansas 0.70% 0.83% 

California 20.98% 9.81% 12.12% 6.71% 0.47 0.55 

Colorado 6.80% 3.03% 4.84% 1.89% 0.45 0.39 

Connecticut 3.44% 1.18% 2.44% 0.34 

Delaware 1.59% 0.84% 0.53 

District of Columbia 7.10% 9.53% 

Florida 23.61% 10.96% 12.17% 7.72% 0.46 0.63 

Georgia 1.35% 

Hawaii 5.70% 2.62% 0.46 

Idaho 2.93% 0.77% 

Illinois 4.66% 2.34% 3.89% 1.82% 0.50 0.47 

Indiana 

Iowa 0.49% 0.35% 0.72 

Kansas 2.52% 1.64% 0.66% 0.40 

Kentucky 0.59% 0.45% UO% 0.76 

Louisiana 2.82% 1.18% 1.55% 0.80% 0.42 0.51 

Maine 1.01% 0.45% 0.44 

Maryland 3.57% 1.58% 2.05% 1.30% 0.44 0.63 

Massachusetts 4.12% 1.36% 1.93% 0.33 

Michigan 1.32% 0.55% 0.80% 0.42 

Minnesota 0.95% 0.36% 1.02% 0.25% 0.38 0.24 

Mississippi 0.32% 0.19% 

Missouri 1.05% 0.49% 0.44% 0.47 

Montana 1.67% 0.58% 2.18% 0.25% 0.34 0.12 

Nebraska 1.53% 0.43% 0.41% 0.22% 0.28 0.52 

Nevada 8.50% 2.90% 4.34% 1.94% 0.34 0.45 

New Hampshire 0.68% 0.45% 0.18% 0.22% 0.66 1.21 

New Jersey 9.96% 3.72% 5.78% 3.21% 0.37 0.55 

New Mexico 34.73% 20.06% 25.03% 16.52% 0.58 0.66 

New York 17.35% 4.59% 5.96% 2.91% 0.26 0.49 

North Carolina 1.I9% 0.67% 0.76% 0.40% 0.57 0.52 

North Dakota 

Ohio 0.94% 0.63% 0.54% 0.52% 0.67 0.96 

Oklahoma 2.24% 1.73% 2.08% 0.77 

241 
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Percentage Percentage Percentage Disparity Disparity 

State ofAlI Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Firms Employers 

Oregon 2,39% 1.80% 

Pennsylvania 1.23% 0,65% 

Rhode Island 5,59% 1.32% 1.57% 0,61% 0,24 0,39 

South Carolina 1.23% 0.45% 0,93% 0.300/0 0,37 0,33 

South Dakota 0.37% 

Tennessee 1.15% 0.47% 0,60% 0.33% 0.41 0,55 

Texas 22.35% 9.34% 13.93% 6,71% 0.42 0.48 

Utah 3.38% 1.55% 3,26% 0,72% 0.46 0.22 

Vermont 0.68% 0.00% 0.00% 0,00 

Virginia 3.40% 1.17% 1.86% 0.83% 0.35 0,45 

Washington 3,06% 1.16% L19% 0.88% 0.38 0.74 

West Virginia 

Wisconsin 0,82% 0.48% 0.75% 0.36% 0,59 0,49 

3,54% 

242 
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Table 20C. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Asians, Other Services (Except Public Administration), 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 1.88% 0.90% 1.54% 0.54% 0.48 0.35 

Alaska 6.54% 3.47% 0.53 

Arizona 4.71% 2.43% 5.09% 2.21% 0.52 0.43 

Arkansas 1.49% 0.88% 1.03% 0.43% 0.59 0.42 

California 16.62% 11.40% 23.02% 10.48% 0.69 0.46 

Colorado 5.37% 2.68% 5.60% 1.82% 0.50 0.32 

Connecticut 4.12% 2.45% 5.70% 2.19% 0.59 0.39 

Delaware 4.94% 2.48% 4.10% 1.45% 0.50 0.35 

District of Columbia 8.83% 24.88% 

Florida 4.47% 2.67% 4.00% 2.25% 0.60 0.56 

Georgia 9.63% 6.14% 8.89% 4.73% 0.64 0.53 

Hawaii 49.06% 37.48% 57.70% 36.36% 0.76 0.63 

Idaho 1.01% 0.93% 2.22% 0.92% 0.92 0.42 

Illinois 6.42% 4.09% 7.94% 3.18% 0.64 0.40 

Indiana 1.68% 1.12% 1.72% 0.83% 0.67 0.48 

Iowa 0.89% 0.71% 0.95% 0.62% 0.81 0.64 

Kansas 2.14% 1.29% 2.56% 1.09% 0.60 0.43 

Kentucky 1.99% 1.39% 2.32% 1.12% 0.70 0.49 

Louisiana 4.01% 1.54% 3.22% 1.01% 0.38 0.31 

Maine 1.05% 1.34% 1.50% 1.43% 1.28 0.95 

Maryland 10.54% 5.64% 11.78% 4.42% 0.53 0.38 

Massachusetts 6.16% 2.45% 4.14% 1.67% 0.40 0.40 

Michigan 2.95% 2.29% 3.48% 2.29% 0.78 0.66 

Minnesota 2.43% 1.26% 3.31% 1.12% 0.52 0.34 

Mississippi 

Missouri 2.84% 1.57% 4.10% 1.18% 0.55 0.29 

Montana 

Nebraska 1.82% 0.55% 0.30 

Nevada 6.71% 3.65% 4.34% 1.50% 0.54 0.35 

New Hampshire 1.93% 1.63% 0.85 

New Jersey 10.90% 5.84% 10.85% 4.96% 0.54 0.46 

New Mexico 3.19% 2.34% 3.85% 1.73% 0.73 0.45 

New York 11.81% 8.06% 13.65% 7.19% 0.68 0.53 

North Carolina 4.04% 2.91% 3.86% 2.37% 0.72 0.61 

North Dakota 0.50% 

Ohio 2.05% 1.17% 3.00% 1.07% 0.57 0.36 

Oklahoma 2.35% 1.27% 2.34% 0.67% 0.54 0.29 

243 
427 

NERA Economic Consulting 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Finns Employers Sales 

Oregon 5.17% 2.82% 5.35% 2.02% 0.54 0.38 

Pennsylvania 4.41% 2.10% 4.36% 1.57% 0.48 0.36 

Rhode Island 2.35% 0.87% 1.52% 0.54% 0.37 0.36 

South Carolina 2.07% 1.67% 3.13% 1.29% 0.81 0.41 

South Dakota 

Tennessee 2.26% 1.20% 2.44% 0.84% 0.53 0.34 

Texas 8.74% 4.09% 6.79% 2.46% 0.47 0.36 

Utah 2.46% 1.30% 2.22% 0,89% 0,53 0.40 

Vermont 0,77% 0.55% 0,71 

Virginia 10.70% 5,69% 8.73% 4.12% 0.53 0.47 

Washington 9.39% 4,97% 10.65% 3.82% 0,53 0,36 

West Virginia 1.09% 0.63% 0,68% 0.22% 0,58 0,32 

Wisconsin 1.45% 0.58% 0,87% 0.32% 0.40 0.37 

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Table 20D. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, American Indians and Alaska Natives, Other Services (E~cept Public Administration), 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage ofAIl of All Ratio-All Ratio 

Finns of All Sales Employers Employer Firms Employers Sales 

Alabama 0.58% 0.77% 0.93% 0.82% 1.33 0.88 

Alaska 

Arizona 1.88% 0.72% 0.62% 0.46% 0.38 0.75 

Arkansas 1.37% 0.82% 0.60 

California 1.46% 0.41% 0.58% 0.24% 0.28 0.41 

Colorado 1.02% 0.26% 0.25% 0.10% 0.26 0.40 

Connecticut 0.74% 0.22% 0.29 

Delaware 

District of Columbia 0.13% 0.16% 

Florida 0.68% 0.25% 0.36 

Georgia 0.62% 0.42% 0.94% 0.40% 0.68 0.43 

Hawaii 

Idaho 0.39% 0.20% 0.10% 0.52 

Illinois 0.42% 0.42% 0.99 

Indiana 0.58% 0.30% 0.52 

Iowa 

Kansas 0.87% 1.09% 2.18% 1.16% 1.24 0.53 

Kentucky 0.25% 0.10% 0.40 

Louisiana 0.55% 0.33% 

Maine 

Maryland 0.41% 

Massachusetts 0.39% 0.10% 0.17% 0.06% 0.25 0.36 

Michigan 1.08% 0.31% 0.41% 0.21% 0.28 0.52 

Minnesota 

Mississippi 0.23% 0.16% 0.68 

Missouri 0.58% 0.17% 0.21% 0.11% 0.29 0.54 

Montana 2.28% 0.68% 0.30 

Nebraska 

Nevada 1.44% 0.65% 0.45 

New Hampshire 

New Jersey 

New Mexico 5.21% 0.87% 0.58% 0.35% 0.17 0.60 

New York 1.09% 0.29% 0.27% 0.12% 0.27 0.45 

North Carolina 1.09% 0.62% 0.82% 0.30% 0.57 0.37 

North Dakota 

Ohio 

Oklahoma 6.77% 2.87% 2.78% 2.00% 0.42 0.72 

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Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Oregon 1.68% 0,70% 0.11 

Pennsylvania 

Rhode Island 

South Carolina 0.57% 0,19% 0,34 

South Dakota 2,28% 0,38% 0,14% 0,16 

Tennessee 0,92% 0,33% 0,35% 0.27% 0,36 0,78 

Texas Ll2% 0,30% 0,20% 0,10% 0,27 0.47 

Utah 

Vermont 0,04% 0,00% 0,00% 0,00 

Virginia 0,72% 0.31% 0.44 

Washington 1.56% 0.52% 1.01% 0.40% 0,34 0.40 

West Virginja 0.34% 0,14% 0.42 

Wisconsin 0,71% 0,19% 0.20% 0,08% 0,27 0.40 

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Table 20E. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Native Hawaiians and Pacific Islanders, Other Services (Except Public Administration), 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Firms of All Sales Employers Employer Firms Employers Sales 

Alabama 0.01% 0.00% 0.00% 0.00 

Alaska 0.04% 0.00% 0.00% 0.00 

Arizona 

Arkansas 

California 

Colorado 

Connecticut 

Delaware 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

District of Columbia 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Florida 0.10% 0.02% 0.16 

Georgia 0.07% 0.03% 0.44 

Hawaii 8.17% 3.39% 4.14% 3.06% 0.41 0.74 

Idaho 

Illinois 

Indiana 0.01% 0.01% 0.01% 0.83 

Iowa 

Kansas 

Kentucky 

Louisiana 

Maine 0.01% 0.00% 0.00% 0.00 

Maryland 

Massachusetts 

Michigan 

Minnesota 

Mississippi 

Missouri 0.00% 0.00% 0.00% 0.00 

Montana 

Nebraska 

Nevada 

New Hampshire 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

New Jersey 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

New Mexico 0.01% 0.04% 

New York 0.34% 0.00% 

North Carolina 

North Dakota 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Ohio 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Oklahoma 

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Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Firms Employers Sales 

Oregon 

Pennsylvania 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

Rhode Island 0.00% 0.00% 0.00% 0.00% 0.00 0.00 

South Carolina 0.01% 0.00% 0.00% 0.00% 0.02 0.00 

South Dakota 

Tennessee 0.01% 0.00% 0.00% 0,00% 0.45 0,00 

Texas 

Utah 0.28% 0.03% 0.00% 0.00% 0.12 0.00 

Vermont 0.00% 0.00% 0.00% 0.00% 0,00 0,00 

Virginia 

Washington 0.19% 0.13% 0.67 

West Virginia 0.01% 0.00% 0.00% 0,00 

Wisconsin 0.00% 0.01% 

0.03% 0.00% 0.00% 0.00 

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Table 20F. Percentage of Firms and Sales and Corresponding Disparity Ratios, All Firms and Employer 

Firms, Women, Other Services (Except Public Administration), 2002 

Percentage Percentage Percentage Disparity Disparity 

State of All of All Ratio-All Ratio 

Finns of All Sales Employers Employer Firms Employers Sales 

Alabama 37.93% 13.88% 18.88% 9.90% 0.37 0.52 

Alaska 34.84% 19.74% 0.57 

Arizona 35.28% 14.95% 19.12% 10.63% 0.42 0.56 

Arkansas 33.05% 13.72% 16.36% 9.93% 0.4! 0.61 

California 38.96% 15.81% 21.15% 10.14% 0.41 0.48 

Colorado 41.77% 14.50% 27.66% 9.85% 0.35 0.36 

Connecticut 38.69% 15.25% 24.68% 11.37% 0.39 0.46 

Delaware 31.60% 13.44% 22.81% 9.57% 0.43 0.42 

District of Columbia 40.81% 26.98% 10.06% 0.37 

Florida 36.68% 16.79% 23.02% 12.09% 0.46 0.53 

Georgia 40.93% 17.52% 22.28% 12.26% 0.43 0.55 

Hawaii 41.42% 16.51% 27.13% 11.39% 0.40 0.42 

Idaho 33.68% 10.73% 14.46% 6.16% 0.32 0.43 

Illinois 39.34% 13.81% 21.01% 9.11% 0.35 0.43 

Indiana 37.40% 12.62% 17.51% 8.87% 0.34 0.5/ 

Iowa 34.43% 13.00% 21.62% 9.86% 0.38 0.46 

Kansas 33.62% 12.98% 22.73% 10.16% 0.39 0.45 

Kentucky 35.63% 12.16% 17.80% 7.57% 0.34 0.43 

Louisiana 36.68% 13.06% 17.29% 8.56% 0.36 0.50 

Maine 34.62% 13.60% 17.44% 7.09% 0.39 0.41 

Maryland 37.44% 12.81% 20.20% 9.80% 0.34 0.49 

Massachusetts 39.15% 15.45% 24.77% 12.10% 0.39 0.49 

Michigan 42.02% 12.37% 22.96% 8.86% 0.29 0.39 

Minnesota 36.64% 12.03% 20.85% 8.33% 0.33 0.40 

Mississippi 39.09% 16.07% 16.38% 8.88% 0.41 0.54 

Missouri 36.59% 15.89% 20.63% 13.07% 0.43 0.63 

Montana 35.31% 11.26% 13.08% 5.73% 0.32 0.44 

Nebraska 34.63% 14.04% 23.99~/o 11.95% 0.41 0.50 

Nevada 39.11% 14.29% 15.40% 7.68% 0.37 0.50 

New Hampshire 38.60% 16.86% 26.01% 13.77% 0.44 0.53 

New Jersey 35.19% 13.72% 26.13% 11.14% 0.39 0.43 

New Mexico 38.23% 13.73% 15.45% 9.50% 0.36 0.61 

New York 38.92% 13.42% 21.37% 9.16% 0.34 0.43 

North Carolina 38.31% 15.26% 18.32% 9.87% 0.10 0.54 

North Dakota 30.08% 12.75% 6.76% 0.53 

Ohio 38.61% 13.70% 24.54% 10.78% 0.35 0.44 

Oklahoma 36.08% 14.63% 16.85% 9.79% 0.58 

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Percentage Percentage Percentage Disparity Disparity 

State of All Percentage of All ofAl! Ratio-All Ratio 

Finns of All Sales Employers Employer Finns Employers Sales 

Oregon 42.29% 13.27% 18.80% 6.98% 0.31 0.37 

Pennsylvania 36.07% 12.49% 25.82% 9.76% 0.35 0.38 

Rhode Island 38.17% 17.11% 25.39% 13.60% 0.45 0.54 

South Carolina 37.62% 15.77% 19.95% 10.31% 0.42 0.52 

South Dakota 30.64% 11.18% 18.34% 6.92% 0.36 0.38 

Tennessee 38.39% 14.91% 21.30% 10.52% 0.39 0.49 

Texas 35.36% 13.15% 20.26% 8.94% 0.37 0.44 

Utah 40.58% 13.52% 20.13% 9.10% 0.33 0.45 

Vennont 35.34% 15,38% 23.45% 13.47% 0.44 0.57 

Virginia 41.70% 17.05% 23.57% 13.75% 0.41 0.58 

Washington 42.00% 12.70% 19,86% 8.22% 0,30 0.41 

West Virginia 36.48% 15.72% 21.81% 11.61% 0.43 0,53 

Wisconsin 35.42% 13,80% 24.25% 11.05% 0.39 0.46 

35.78% 13.90% 17.54% 10.92% 0,39 0.62 

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Table 21A. Actual and Potential Business Formation Rates, All Industries, Recent NERA Economic 

Consulting Disparity Studies 

Business Expected 

Race/Sex, Location Formation Rate Business Disparity Ratio Formation Rate (%) (%) 

(I) (2) (3) 

Augusta-Richmond County, GA-SC 

African-American 3.5 8.0 43.8 

Hispanic or Latino 9.1 14.2 64.1 

Asian 18.8 20.3 92.6 

Native American 6.4 9.8 65.3 

Nonminority female 7.7 7.4 104.1 

All minority and female 6.5 7.5 86.7 

Austin, TX MSA 

African-American 4.7 9.4 50.0 

Hispanic or Latino 6.4 10.0 64.0 

Asian 6.7 8.3 80.7 

Native American 6.9 10.2 67.6 

Nonminority female 10.6 13.6 77.9 .. 

All minority and female 8.4 11.7 71.8 

Chicago. IL MSA 

African-American 4.9 9.4 52.1 

Hispanic or Latino 4.0 7.5 53.3 

Asian 9.0 10.5 85.7 

Native American 5.7 9.1 62.6 

Nonminority female 7.0 9.9 70.7 

All minority and female 6.1 9.7 62.9 

Denver. CO MSA 

African-American 6.1 10.6 57.5 

Hispanic or Latino 4.4 7.9 I 55.7 

Asian 10.9 12.4 I 87.9 

Native American 4.7 8.1 58.0 

Nonminority female 10.5 13.4 78.4 

All minority and female 8.6 11.1 77.5 

Maryland-DC-N. VA 

African-American 5.2 8.1 64.2 

Hispanic or Latino 7.2 8.8 81.8 

Asian 11.2 10.2 109.8 

Native American 5.1 8.5 60.0 

Nonminority female 8.8 9.9 88.9 

All minority and female 7.9 9.9 79.8 

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I Business Expected 

Race/Sex, Location Formation Rate Business Disparity Ratio Formation Rate (%) (%) 

Memphis, TN-MS-AR MSA 

African-American 5.3 6.3 84.1 

Hispanic or Latino 10.7 8.5 125.9 

Asian 6.5 8.1 80.2 

Native American 6.5 9.8 66.3 

Nonminority female 6.4 9.4 68.1 

All minority and female 6.0 11.2 53.6 

St. Louis, MO MSA 

African-American 3.9 6.9 56.5 

Hispanic or Latino 5.1 4.3 118.6 

Asian IJ.l 7.3 152.1 

Native American 16.7 7.6 219.7 

Nonminority female 6.4 7.8 82.1 

All minority and female 6.1 8.0 76.3 

Illinois 

African-American 4.7 8.2 57.3 

Hispanic or Latino 4.0 7.5 53.3 

Asian 8.9 lOA 85.6 

Native American 7.3 10.6 68.9 

Nonminority female 6.9 9.6 71.9 

All minority and female 6.3 9.5 66.3 

Massachusetts 

African-American 4.0 8.5 47.1 

Hispanic or Latino 4.4 7.9 55.7 

Asian 5.6 8.9 62.9 

Native American 9.1 12.5 72.8 

Nonminority female 7.2 10.1 71.3 

All minority and female 6.6 12.1 54.5 

Missouri 

African-American 4.4 9.6 45.8 

Hispanic or Latino 5.7 9.1 62.6 

Asian 10.9 9.9 110.1 

Native American 10.3 8.6 119.8 

Nonminority female 7.4 9.9 74.7 

All minority and female 7.1 10.2 69.6 

Minnesota 

African-American 3.2 10.1 31.7 

Hispanic or Latino 4.1 10.1 40.6 

Asian 4.9 9.1 53.8 

Native American 5.1 8.5 60.0 

Nonminority female 7.7 11.6 66.4 

All minority and female 7.2 lJ.l 64.9 

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Business Expected 

Race/Sex, Location Formation Rate Business Disparity Ratio Formation Rate (%) (%) 

Utah 

African-American 4.8 9.3 51.6 

Hispanic or Latino 4.1 9.2 44.6 

Asian 8.0 10.2 78.4 

Native American 4.6 10.0 46.0 

Nonminority female 8.7 8.6 101.2 

All minority and female 7.9 8.9 88.8 

Washington State 

African-American 5.7 10.4 54.8 

Hispanic or Latino 5.9 11.4 51.8 

Asian 9.3 9.8 94.9 

Native American 8.0 11.3 70.8 

Nonminority female lOA 10.6 98.1 

All minority and female 9.4 10.7 87.9 

Notes: The figure in column (I) is the average self-employment rate weighted using PUMS popuiationbased person weigbts. The figure in column (2) is derived by inflating the figure in column (I) according to 

the corresponding coefficient from the business formation regression analysis, which holds constant 

industry, geography, education, age, and labor market status. Column (3) is column (I) divided by column 

(2). "ula" indicates no adverse disparity observed. If there is parity in the relevant marketplace, then the 

disparity ratio will equal 1.000 because the expected business formation rate (that is, the business fonnation 

rate that would be observed in a non-discriminatory marketplace) will be equivalent to the actual business 

fonnation rate. In cases where adverse disparities are present in the relevant marketplace, then the disparity 

ratio will be less than 1.000 because expected business formation rates will exceed current business 

formation rates. 

Source: 2000: Five Percent PUMS. 

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Table 21B. Actual and Potential Business Formation Rates, Construction and Construction-Related 

Industries, Recent NERA Economic Consulting Disparity Studies 

Business Expected 

Race/Sex, Location, Transportation Formation Rate Business Disparity Ratio Mode Formation Rate (%) (%) 

(I) (2) (3) 

Augusta-Richmond County. GA-SC 

African-American 6.9 16.6 41.6 

Hispanic or Latino 36.7 50.7 72.4 

Asian 0.0 5.7 0.0 

Native Ameri~an 0.0 8.0 0.0 

Nonminority female 19.0 27.5 69.1 

All minority and lemale 14.5 24.8 58.5 

Austin. TX MSA 

African-American 17.7 27.4 64.6 

Hispanic or Latino 10.8 18.4 58.7 

Asian 18.6 24.2 76.9 

Native American 39.3 46.9 83.8 

Nonminority female 11.7 24.2 48.3 

All minority and female 11.5 20.1 57.2 

Chicago. lL MSA 

African-American 20.2 16.0 126.3 __ 

Hispanic or Latino 10.5 18.1 58.0 

Asian 9.9 15.6 63.5 -- Native American 8.0 16.0 50.0 

Nonminority female 11.0 19.5 56.4 ... 

All minority and female 12.1 17.8 68.0 

Denver, CO MSA 

African-American 30.3 23.4 129.5 

Hispanic or Latino 7.3 19.8 36.9 

Asian 12.4 18.1 68.5 

Native American 3.3 11.3 29.2 .. 

Nonminority female 12.5 21.0 59.5 

All minority and female 10.3 18.9 54.5 

Memphis, TN-MS-AR MSA 

African-American 14.6 24.3 60.1 

Hispanic or Latino 12.6 20.2 62.4 

Asian 0.0 5.6 0.0 

Native American 28.8 36.4 79.1 .-

Nonminority female 21.9 30.5 71.8 

All minority and female 15.8 24.4 64.8 

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Business Expected 

Race/Sex, Location, Transportation Formation Rate Business Disparity Ratio Mode Formation Rate (%) (%) 

St. Louis, MO MSA 

African-American 11.6 21.3 54.5 

Hispanic or Latino 6.7 14.4 46.5 

Asian 6.3 12.0 52.5 

Native American 40.6 48.6 83.5 

Nonminority female 16.1 13.8 116.7 

All minority and female 14.6 15.1 96.7 

Illinois 

African-American 19.3 17.1 112.9 

Hispanic or Latino 10.7 14.8 72.3 

Asian 9.5 15.1 62.9 

Native American 10.9 18.9 57.7 

Nonminority female 12.5 18.4 67.9 

All minority and female 12.7 18.0 70.6 

Maryland-DC-N, VA 

African-American 11.3 21.1 53.6 

Hispanic or Latino 7.1 14.7 48.3 

Asian 16.8 22.8 73.7 

Native American 7.2 15.2 47.4 

Nonminority female 9.5 18.0 52.8 

All minority and female 10.0 18.6 53.8 

Massachusetts 

African-American 14.0 23.7 59.1 

Hispanic or Latino 14.9 22.5 66.2 

Asian 21.0 26.7 78.7 

Native American 23.8 31.8 74.8 

Nonminority female 12.9 25.7 50.2 

All minority and female 15.0 23.6 63.6 

Missouri 

African-American 12.8 22.8 56.1 

Hispanic or Latino 10.2 17.7 57.6 

Asian 8.0 18.9 423 

Native American 19.7 11.9 165.5 

Nonminority female 17.1 19.5 87.7 

All minority and female 16.2 19.9 81.4 

Minnesota 

African-American 4.6 14.3 32.2 

Hispanic or Latino 11.5 19.1 60.2 

Asian 16.1 21.8 73.9 

Native American 6.5 14.5 44.8 

Nonminority female 16.8 253 66.4 

An minority and female 15.1 23.2 65.1 

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Business Expected 

Race/Sex, Location, Transportation Formation Rate Business Disparity Ratio Mode Formation Rate (%) (%) 

Utah 

African-American 15.9 25.7 61.9 

Hispanic Or Latino 6.4 20.4 31.4 

Asian 8.9 14.6 61.0 

Native American 5.7 13.6 41.9 

Nonminority female 14.3 22.8 62.7 

All minority and female 10.2 20.5 49.8 

Washington 

African-American 5.5 25.5 21.6 

Hispanic Or Latino 10.5 18.1 58.0 

Asian 13.4 19.0 70.5 

Native American 13.3 20.9 63.6 

Nonminority female 14.5 18.7 77.5 

All minority and female 14.4 20.7 69.6 

Notes and Source: See Table 21A. 

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Table 22A. Actual and Potential Business Owner Earnings, All Industries, Recent NERA Economic 

Consulting Disparity Studies 

Race/Sex, Location Business Earnings 

Deficit (%) 

(I) 

Augusta-Richmond County, GA-SC 

African-American -27.9 

Hispanic or Latino -18.6 

Asian -3.5 

Native American -38.0 

N onminority female -58.4 

Austin. TX MSA 

African-American -30.0 

Hispanic or Latino -19.0 

~ -4.1 

. e American -38.4 

Nonminority female -44.0 

Chicago. IL MSA 

African-American -28.4 

Hispanic or Latino -19.0 -- Asian nla 

Native American -38.1 

Nonminority female -43.7 

Illinois 

African-American -12.5 

Hispanic or Latino -12.9 

Asian -16.1 

Native American -17.7 

Nonminority female -21.1 

Denver, CO MSA 

African-American -28.0 

Hispanic or Latino -18.7 

Asian -3.6 

Native American -38.0 

Nonminorily female -30.0 

Memphis. TN-AR-MS MSA 

African-American -30.1 

Hispanic or Latino -19.0 

Asian -4.1 

Native American -38.4 

Nonminority female -44.0 

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Race/Sex, Location Business Earnings 

Deficit (%) 

Maryland-DC-N. VA 

African-American -27.9 

Hispanic or Latino -18.8 

Asian -3.8 

Native American -38.0 

Nonminority female 43.7 

Massachusetts 

Afi"ican-American -28.0 

Hispanic or Latino -18.7 

Asian -3.5 

Native American -38.0 

Nonminority female -43.7 

Missouri 

African-Am erican -36.0 

Hispanic or Latino -21.3 

Asian 4.4 

Native American -48.5 

Nonminority female 48.9 

Minnesota 

African-American -28.0 

Hispanic or Latino -18.7 

Asian -3.5 

Native American -38.0 

Nonminority female -43.7 

Utah 

African-American -28.0 

Hispanic or Latino -18.7 

Asian -3.5 

Native American -38.0 

Nonminority female -58.4 

Washington State 

African-American -30.0 

Hispanic or Latino -19.0 

Asian -4.1 

Native American -38.4 

Nonminority female -44.0 

Notes The figure in column (1) is the percentage by which minority or female business owner earnings are 

lower than comparable non-minority male earnings, based on results of the business owner earnings 

regression analysis, which holds constant industry, geography, education, age, and labor market status. 

Source: Five Percent Decennial Census PUMS. 

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Table 22B. Actual and Potential Business Owner Earnings, Construction and Construction-Related 

Industries 

Race/Sex, Location Business Earnings 

Deficit(%) 

(1) 

Augusta-Richmond County. GA-SC 

African-American -28.8 

Hispanic or Latino -14.3 

Asian -5.5 

Native American -36.8 

Nonminority female -51.2 

Austin, TX MSA 

African-American -33.8 

Hispanic or Latino nla 

Asian -6.9 

Native American -35.3 

Nonminority female -50.5 

Chicago. IL MSA 

African-American -29.2 

Hispanic or Latino -14.7 

Asian -5.7 ... - Native American -36.8 

Nonminority female -51.2 

Denver. CO MSA 

African-American -29.0 

Hispanic or Latino nla 

Asian -5.7 

Native American -36.8 

Nonminority female -51.3 

Memphis, TN-AR-MS MSA 

African-American -34.0 

Hispanic or Latino -14.8 

Asian -6.9 

Native American -35.4 

Nonminority female -50.6 

St. Louis. MO MSA 

African-American -41.2 

Hispanic or Latino nla 

Asian I nla 

Native American nla 

Nonminority female -30.8 

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Race/Sex, Location Business Earnings 

Deficit (%) 

Iliinois 

African-American -9.6 

Hispanic or Latino -4.3 

Asian -11.9 

Native American 7.0 

Nonminority female -27.1 

Maryland-DC-N VA 

African-American -28.8 

Hispanic or Latino -14.6 

Asian -6.0 

Native American -36.7 

Nonminority female -S1.3 

Massachusetts 

African-American -29.0 

Hispanic or Latino -14.4 

Asian -S.5 

Native American -36.7 

Nonminority female -78.S 

Missouri 

African-American -41.6 

Hispanic or Latino -16.0 

Asian 0.0 

Native American -43.6 

Nonminority female -69.8 

Minnesota 

African-American -29.0 

Hispanic or Latino -14.5 

Asian -S.6 

Native American -36.7 

N onminority female -S1.3 

Utah 

African-American -29.0 

Hispanic or Latino -14.S 

Asian -S.6 

Native American -36.7 

Nonminority female -S1.3 

Washington State 

African-American -33.8 

Hispanic or Latino -14.7 

Asian -6.9 

Native American -3S.4 

Nonminority female -SO.S 

Notes and Source: See Table 22A. 

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References 

Bourdon, Clinton C. and Raymond E. Levitt. 1980. Union and open-shop construction, 

compensation, work practices, and labor markets. Lexington Books: Lexington, Massachusetts. 

Eccles, Robert G. 1981. "Bureaucratic versus Craft Administration: The Relationship of Market 

Structure to the Construction Firm." Administrative Science Quarterly. Vol. 26. 

Enchautegui, Maria E., Michael Fix, Pamela Loprest, Sarah von der Lippe, Douglas Wissoker. 

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