U.S. GOVERNMENT PUBLISHING OFFICE

28–561 WASHINGTON : 2018

JOB CREATION, COMPETITION, AND 

SMALL BUSINESS’ ROLE IN THE UNITED STATES 

ECONOMY 

HEARING 

BEFORE THE

COMMITTEE ON SMALL BUSINESS 

UNITED STATES 

HOUSE OF REPRESENTATIVES 

ONE HUNDRED FIFTEENTH CONGRESS 

SECOND SESSION 

HEARING HELD 

FEBRUARY 14, 2018 

Small Business Committee Document Number 115–054 

Available via the GPO Website: www.fdsys.gov 

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Congress.#13
(II) 

HOUSE COMMITTEE ON SMALL BUSINESS 

STEVE CHABOT, Ohio, Chairman 

STEVE KING, Iowa 

BLAINE LUETKEMEYER, Missouri 

DAVE BRAT, Virginia 

AUMUA AMATA COLEMAN RADEWAGEN, American Samoa 

STEVE KNIGHT, California 

TRENT KELLY, Mississippi 

ROD BLUM, Iowa 

JAMES COMER, Kentucky 

JENNIFFER GONZA ́ LEZ-COLO ́ N, Puerto Rico 

BRIAN FITZPATRICK, Pennsylvania 

ROGER MARSHALL, Kansas 

RALPH NORMAN, South Carolina 

JOHN CURTIS, Utah 

NYDIA VELA ́ ZQUEZ, New York, Ranking Member 

DWIGHT EVANS, Pennsylvania 

STEPHANIE MURPHY, Florida 

AL LAWSON, JR., Florida 

YVETTE CLARK, New York 

JUDY CHU, California 

ALMA ADAMS, North Carolina 

ADRIANO ESPAILLAT, New York 

BRAD SCHNEIDER, Illinois 

VACANT 

KEVIN FITZPATRICK, Majority Staff Director 

JAN OLIVER, Majority Deputy Staff Director and Chief Counsel 

ADAM MINEHARDT, Staff Director 

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C O N T E N T S 

OPENING STATEMENTS 

Page 

Hon. Steve Chabot ................................................................................................... 1 

Hon. Nydia Vela ́zquez ............................................................................................. 2 

WITNESSES 

Mr. Steven H. Strongin, Head, Global Investment Research Division, Goldman Sachs, New York, NY .................................................................................. 4 

Mr. JR Foster, President and CEO, Robert Louis Group, Cincinnati, OH ......... 6 

Ms. Jessica Johnson-Cope, President, Johnson Security Bureau, Inc., Bronx, 

NY ......................................................................................................................... 7 

APPENDIX 

Prepared Statements: 

Mr. Steven H. Strongin, Head, Global Investment Research Division, 

Goldman Sachs, New York, NY ................................................................... 25 

Mr. JR Foster, President and CEO, Robert Louis Group, Cincinnati, 

OH .................................................................................................................. 131 

Ms. Jessica Johnson-Cope, President, Johnson Security Bureau, Inc., 

Bronx, NY ...................................................................................................... 133 

Questions for the Record: 

None. 

Answers for the Record: 

None. 

Additional Material for the Record: 

None. 

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(1) 

JOB CREATION, COMPETITION, AND SMALL 

BUSINESS’ ROLE IN THE UNITED STATES 

ECONOMY 

WEDNESDAY, FEBRUARY 14, 2018 

HOUSE OF REPRESENTATIVES, 

COMMITTEE ON SMALL BUSINESS, 

Washington, DC. 

The Committee met, pursuant to call, at 11:02 a.m., in Room 

2360, Rayburn House Office Building, Hon. Steve Chabot [chairman of the Committee] presiding. 

Present: Representatives Chabot, Radewagen, Knight, Kelly, 

Blum, Comer, Gonza ́lez-Colo ́n, Fitzpatrick, Marshall, Norman, Curtis, Vela ́zquez, Evans, Murphy, Lawson, Espaillat, Schneider, and 

Adams. 

Chairman CHABOT. The Committee will come back to order. 

We will now shift to a hearing on the Role of Small Businesses 

in the American Economy. And we want to thank our witnesses for 

being here today. And we will get to you very shortly. 

The American economy, I believe, is poised for great things. Significant growth is occurring across the Nation, and Americans, and 

particularly entrepreneurs, are finally, once again, optimistic about 

the future of business. In fact, the National Federation of Independent Optimism Index of their members recently reached one of 

the strongest readings in the 45-year history of the survey, and it 

is just getting started. 

Congress and the President have worked together to end the oppressive regulatory burden of the past several years, and the proof, 

as they say, is in the pudding. Multinational corporations, like 

Apple and Chrysler and IBM are again investing heavily in American manufacturing and American jobs, giving the burgeoning economy an enormous boost. 

All that good news comes even before we consider the effect of 

the significant pro-growth policies of the tax cuts we passed at the 

end of last year. Again, American companies are stepping up and 

investing in their infrastructure and their workforce. Because of the tax overhaul, over $3 billion in bonuses have been 

given to employees at the largest companies, like AT&T, American 

Airlines, Fifth Third Bank, and on and on. But it is working for 

small firms, too, like the $1,000 bonuses given to Sheffer Corporation’s 126 employees in Blue Ash, Ohio, next door to my district. 

But as always, we can do more. Much more. Our small businesses, the true engines of our economy, unfortunately, continue to 

experience a rigid lending environment. While large companies can 

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turn to debt and equity markets to raise capital, small businesses 

all over the country regularly turn to conventional bank lending to 

finance their projects, and at times, small firms are unable to access conventional lending so they have nowhere to turn for the capital to grow their businesses and create jobs. 

Making access to capital easier for small firms has been a priority of this Committee since day one. Recent research conducted 

by Goldman Sachs has shown that while some areas of the country 

have experienced a falling of sorts in credit markets, the same cannot be said for largely urban and predominately rural areas of our 

country. For a rising tide to truly raise all boats, we must continue 

to find ways to help small businesses in those areas. 

We have an excellent panel of policy experts and small business 

owners to explain this new research and offer suggestions as to 

what the Federal Government can do better. That includes mimicking some of the successes found in Goldman Sachs 10,000 Small 

Businesses Initiative that has helped over 7,000 small firms in all 

50 states get started or expand. 

I am looking forward, as I know we all are, to this discussion this 

morning. 

And I would now like to yield to the ranking member, Ms. 

Vela ́zquez, for her opening statement. 

Ms. VELA ́ ZQUEZ. Thank you, Mr. Chairman. And thank you for 

holding this timely hearing. 

Today, we will touch on one of the central issues for small business formation and growth, namely capital access. In recent years, 

we have seen a decline in entrepreneurship, with the low point arriving in 2014, when just 450,000 businesses were started. This reduction in business formation can be attributed to a number of factors, but the availability of affordable credit has certainly been one 

of the reasons. 

Lack of capital remains an ongoing problem for many businesses, 

regardless of their size or location. However, this issue is particularly pronounced for women and minorities, even though they are 

the fastest growing groups of entrepreneurs. We are potentially losing out on millions of jobs that could be created by these firms, and 

if lending shrinks due to recent market volatility, it will be much 

worse. 

That is why today’s hearing is so timely, so we can learn about 

private sector initiatives that could complement our government efforts to grow our nation’s entrepreneurial sector. Entrepreneurial 

development initiatives prove to be critical by providing counseling 

and training resources to help small businesses start, grow, and 

compete in the market. 

While the Small Business Administration and other federal agencies provide support in these crucial areas, private sector alternatives often have the capacity for filling in gaps. 

One such initiative is the 10,000 Small Businesses program, a 

public-private partnership designed to promote growth and job creation potential for small business owners. Efforts like this one are 

critical in helping small business owners who strive to grow and 

create meaningful impact in their communities. By leveraging the 

ability of community development, financial institutions, this proSBREP-219A with DISTILLER

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gram has reached businesses in every state, as well as Puerto Rico 

and D.C. 

CDFIs and the Treasury’s CDFI Fund help small businesses access credit opportunities when traditional financial institutions fail 

to lend. 

With accessible rates and transparent terms, they help increase 

the likelihood of a small firm’s success. In fiscal year 2016 alone, 

CDFIs made over 39,000 loans or investments totaling over $3.6 

billion and financed more than 11,000 small businesses. 

This hearing gives us the opportunity to hear from business 

founders regarding their experiences in starting and running a 

business and research showing the challenges they overcame to become successful. Hearing your experiences and stories helps the 

committee make better decisions as we work to foster an environment conducive to small business growth. 

With that, I want to thank all the witnesses for their participation and insights. And welcome. I really appreciate that you are 

here this morning. 

I thank the chairman, and I yield back. 

Chairman CHABOT. Thank you very much. The gentlelady 

yields back. 

And if Committee members have opening statements prepared, I 

would ask that they be submitted for the record. 

And I will take just a moment to explain our timing lights. The 

rules are very simple. You get 5 minutes and the lights assist you 

in that. The green light will be on for 4 minutes, and then the yellow light will come on to let you know you have got a minute to 

wrap up. And then the red light will come on and you are supposed 

to wrap up then. And we ask you to kind of stay within that. If 

you go a little long we will allow you to have a little extra time, 

but try to stay within if at all possible. 

And I would now like to introduce our very distinguished panel 

here this morning. 

Our first witness is Steven Strongin, head of Global Investment 

Research at Goldman Sachs. He is also a member of their Management Committee, Firm-wide Client and Business Standards Committee, and Firm-wide Reputational Risk Committee. Prior to joining the firm, he spent 12 years at the Federal Reserve Bank of Chicago, most recently, as the director of Monetary Policy Research. 

He earned his undergraduate and graduate degrees in Economics 

from the University of Chicago, and a graduate degree from Northwestern University’s Kellogg School of Management. And we thank 

you for being here this morning, Mr. Strongin. 

Our second witness is J.R. Foster, President and CEO of the Robert Louis Group, or RLG, in America’s greatest city, Cincinnati, 

Ohio. I happen to represent Cincinnati. RLG is a full service commercial real estate brokerage and facilities management firm focused on representing the real estate and facility needs of companies, governmental agencies, nonprofits, and investors. RLG’s integrated services allow them to achieve optimum results across their 

clients’ entire real estate portfolio. While headquartered in Cincinnati, they have additional offices in several lesser cities, like 

Chicago, and Columbus, Ohio. Just kidding. And we thank you for 

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your time here this morning. They are all great cities. Not as good 

as Cincinnati, but they are great cities. 

And I would now yield to the ranking member for introduction 

of the next witness. And she comes from a pretty special city, too. 

Ms. VELA ́ ZQUEZ. Thank you, Mr. Chairman. 

It is my pleasure to introduce Ms. Jessica Johnson-Cope, President and Principal of Johnson Security based in the Bronx, New 

York. Johnson Security is a third-generation, family-owned firm, 

which has been recognized as one of the 5,000 fastest growing private companies in America for 3 years, and the 2013 Black Enterprise Family Business of the Year. Ms. Johnson-Cope earned a 

Bachelor of Science in Industrial Engineering from Northwestern 

University, and a master’s degree in Market Research from the 

University of Georgia. She is also a graduate of the inaugural class 

of the Goldman Sachs 10,000 Small Businesses Initiative. Thank 

you for joining us, and I look forward to your testimony. Thank 

you. 

Chairman CHABOT. Thank you very much. 

Mr. Strongin, you are recognized for 5 minutes. 

STATEMENTS OF STEVEN H. STRONGIN, HEAD, GLOBAL INVESTMENT RESEARCH DIVISION, GOLDMAN SACHS; JR FOSTER, PRESIDENT AND CEO, ROBERT LOUIS GROUP CINCINNATI; JESSICA JOHNSON-COPE, PRESIDENT, JOHNSON 

SECURITY BUREAU, INC. 

STATEMENT OF STEVEN H. STRONGIN 

Mr. STRONGIN. Thank you, Chairman Chabot, and Ranking 

Member Vela ́zquez. It is a pleasure to be here and to get a chance 

to talk about small businesses. 

You very aptly summarized what I think is the core economic 

issue we face in small businesses, which has been slow growth and 

access to credit. When you look at the data, it is stark. Given the 

most recent data we have, for the first time in modern times, in 

fact, before we had data, small businesses today are actually in 

smaller numbers than they were at the beginning of the recession. 

So we have actually not had a net increase in small businesses 

over this time period. 

This coincides with the 10,000 Small Businesses Summit. We use 

that as an opportunity to talk to the small businesses, to better understand what the challenges were, and to try to construct what 

would be a practical way of addressing those issues. 

In the process of doing that, I think there are two broad issues 

which I think this Committee is in position to think about addressing. The first is the sheer volume of rules and regulations faced by 

small businesses. When you are a large business, you have large 

groups of people who figure out what the rules are, who track them 

down, and help you comply with them. When you are a small business that falls to the CEO. That is an enormous challenge that in 

many cases has changed growth plans, has changed the ability to 

expand into new regions, has changed the actual business models 

of these firms. 

When you talk to small businesses, and we did at length and surveyed them, the number one request you hear from them is essenSBREP-219A with DISTILLER

5 

tially a central registry of what all the rules and regulations are 

that they need to deal with, whether it be state or local. I think 

it would also probably end up being the greatest database of red 

tape in the history of mankind. But I think it would actually help 

people run their businesses in a much more coherent way. 

The second thing that comes out of that, and I will come a little 

bit quickly to the causes of this, is a more centralized way of meeting certification standards and examinations. One of the things I 

think that Congress has done well over the last 20 or 30 years as 

the regulatory burdens have increased, is they have sought to exempt small businesses. But one of the problems is, when you actually talk to small business, is those exemptions have not worked, 

and in some cases have actually added to the burdens. 

And the reason for that comes in two flavors. The first is what 

I would call indirect regulation. If you want to deal with a large 

corporation, they become responsible for making sure that their 

contractors meet all the rules. So instead of a small business having to get certified once for money laundering, Foreign Corrupt 

Practices Act, discrimination, small business statutes, they end up 

having to certify with every single one of their customers that they 

meet the standards necessary for that customer, which turn out to 

be the same for everyone because it is the same Federal rules that 

are being required to be met. So the exemption turns what would 

have been one form into 50 or 100 forms that are essentially identical and all need to be processed. Right? And so what requires essentially is a more central repository of meeting those requirements and that serving as the exemption or safe harbors for their 

customers when they hire them that they do not become responsible for every bit of their behavior. That indirect regulation has 

ended up being a major issues for these firms, sometimes in ways 

that are almost impossible to overcome. 

The other broad category is what I would call accidental regulation. Both the ranking member and the chairman brought up quite 

correctly that access to capital is a key issue. Our survey, for example, indicated that for the 10,000 Small Businesses, if you could 

double the amount of financing they had they would increase employment by 30 percent. The economic consequence of that is incredible, particularly when you think about the fact that half of 

employment in the United States is in small businesses. 

Why do they not have that access to capital? What are the issues 

in access to capital? And I think this is where the conversation 

often becomes confused. The reality of small businesses is that 

most of the lending, 70 percent in the case of 10,000 Small Businesses, is based on FICO scores, which essentially means it is consumer credit, not business credit. And so that as we think about 

new business credit programs we miss 70 percent of the issue, particularly when you are thinking about startups, which both the 

chairman and ranking member brought up. That almost inevitably 

has to do with mortgages, second mortgages, credit cards, personal 

lending, not with special lending programs. 

So as we think about the regulatory burdens, right, a lot of them 

come out of the consumer programs and not out of the business 

programs, and so it takes a much broader look at the issues to understand what the real hurdles are to running a small business, 

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founding a small business, and growing a small business today. As 

you will hear from the business owners themselves, the amount of 

creativity needed to find financing means they are looking at every 

possible channel. And when you look at actual credit channels, 

what that means in essence is that the consumer channels and the 

small business channels and small lending channels pick up the 

dominant amount of that financing because they are the big 

sources of funds. 

And so as we think about really addressing the issues, it is centralizing and simplifying the processes, and it is actually understanding which credit channels they use and addressing those that 

I think would provide the most impact and provide the most relief 

and the greatest growth in small business. 

Thank you very much. 

Chairman CHABOT. Thank you very much. 

Mr. Foster, you are recognized for 5 minutes. 

STATEMENT OF J.R. FOSTER 

Mr. FOSTER. Mr. Chairman, members of the Committee, thank 

you for the opportunity to testify today. 

This is a big moment for my family and myself. My parents have 

been married 56 years and counting. They never graduated past 

the tenth grade in high school. My father spent 46 years working 

in a transmission plant in Cincinnati, Ohio for General Motors in 

a small town called Norwood. From his backbreaking work that he 

was able to put forth at General Motors, he sent me to Cincinnati 

Country Day High School, a college prep high school, as well as 

DePaul University in Greencastle, Indiana. 

As a first generation college graduate and growing up in a blue 

collar neighborhood in Cincinnati on the west side of Cincinnati, I 

know a little bit about hard work and overcoming the odds. They 

say that to who much is given, much is required, and I am honored 

to be here. 

My name is J.R. Foster, and I am the CEO and founding member 

of Robert Louis Capital and Robert Louis Group based in Cincinnati, Ohio. Of the thousands of commercial real estate brokerage 

and investment banking firms in the country, I am a rarity among 

the bunch. My company is one of the only minority-owned and minority-certified commercial real estate brokerage, facility management, and access to capital firms in the country. 

Our approach is twofold. We help corporations, government agencies, and nonprofits with their real estate brokerage and facility 

management needs, and we do so in a way that also can help them 

secure minority spend goals. Secondly, we are leading the charge, 

actually leading the charge in helping small business owners gain 

access to capital. Last year alone we helped over 300 businesses secure $345 million in capital ranging from SBA loans to conventional and alternative debt. 

I am here today because I am one of the recent graduates of the 

Goldman Sachs 10,000 Small Businesses program, and I am proud 

to represent my fellow alumni, the program, and the small business owners who share my same story. I personally knew I had the 

drive and the determination to start my own company so I did so. 

When I was 31 years old, my best friend, now business partner and 

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I, left two well-paying jobs on Wall Street to start our own company. What I did not realize is all the hurdles that come with being 

a small business owner, and a minority-business owner at that. 

You take a leap of faith without knowing the underlying pitfalls 

that derail, frustrate, and leave some of the best minds in America 

for broke. By our second year in business, I found myself lost in 

a sea of managing employees; customers; contractors; payroll; marketing, which I know nothing about; and the like. 

I needed something more than my corporate career had taught 

me. By chance, I was introduced to the Goldman Sachs 10,000 

Small Businesses program which we affectionately call 10KSB. 

After a year of great coursework, excellent classroom engagement, 

and a dialogue with over 100-plus small business owners, my cohort, I was able to start excelling at areas where I fell short. I also 

discovered that our local Chamber of Commerce in Cincinnati and 

other minority organizations like the Urban League and AfricanAmerican Chamber were also great in helping build capacity of 

small business owners. 

After graduating the program, over the past three years, we have 

increased our employee count. We were able to secure additional financing for growth, and our revenue has gone from $250,000 in 

2014 to well over $2 million at the end of 2017, basically doubling 

year after year. 

What I ask of the chairman and the Committee is to help level 

the playing field for small business owners, and minority business 

owners at that. Having spent the last two days of the 10KSB Summit here in D.C., I have continued to hear access to capital on the 

minds of my fellow alumni. Far too often, business owners are 

scraping together funds using high-interest credit cards and also 

taking on private capital partners that ultimately put them in the 

golden handcuffs. Even with SBA lending, having already tarnished their credit, overleveraged themselves with debt, they quickly become unable to qualify for government-backed loans, and I see 

this every day because we are on the frontlines of helping clients 

secure capital. So I ask that you consider helping a business like 

mine create a credit-friendly, national lending platform and ecosystem that business owners can have a centralized place to secure 

capital and where banks compete for their business. 

Thank you for your time today. It has been a pleasure speaking 

with you, and I am honored to be here. 

Chairman CHABOT. Thank you very much. Appreciate your testimony. 

Ms. Johnson-Cope, you are recognized for 5 minutes. 

STATEMENT OF JESSICA JOHNSON-COPE 

Ms. JOHNSON-COPE. Mr. Chairman and members of the Committee, thank you for your time today. I am reminded of the days 

when I walked the halls of this building as a congressional page. 

I am Jessica Johnson-Cope, president and CEO of Johnson Security Bureau based in the Bronx, New York. I am also the vice 

president of the Soap Box located in Brooklyn, New York. 

Johnson Security provides professional security guard and armored car services. Since 1962, three generations of my family 

have helped to protect the people, places, and valuable property 

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around New York City. My grandparents left their home in the segregated South in search of opportunity. To them and many others, 

small business ownership represented those opportunities, the 

chance to live the American Dream, and to provide for their family. 

I am the beneficiary of their vision and their hard work. For the 

past 10 years, I have led Johnson Security. Shortly after I took 

over the business due to the untimely passing of my father, I applied to the Goldman Sachs 10,000 Small Businesses program with 

hopes of keeping our doors open long enough to celebrate our 50th 

anniversary. Even though I had watched my father and grandmother make significant business milestones, I did not feel like I 

was efficiently equipped to help Johnson Security reach its full potential. 10,000 Small Businesses provided me with the tools I needed—executive business education, networking and peer learning 

opportunities with my peers in the program, business advisory 

services, and preparation to obtain financing. 

Since completing the program, Johnson Security has created over 

150 jobs. We have access to capital. We have done business with 

at least seven other program alumni. Additionally, we are preparing for the next phase of innovation and job creation. 

Based on the success of Johnson Security and using lessons from 

10,000 Small Businesses, my husband and I started a second business, the Soap Box, where we are able to live out his family’s entrepreneurial vision. The Soap Box provides premium laundry services 

in the Bedford-Stuyvesant neighborhood where we live. The Soap 

Box not only allows us to save our clients time, it allows us to employ seven people and to transform our community while collaborating with other small businesses. Our work comes with its challenges though as we try to navigate burdensome regulations. Nonetheless, we are determined to continue to grow. 

The impact of the 10,000 Small Businesses program is evidenced 

not only in the impact that I have shared with you but also in the 

outcome that the 2,200-plus program alumni who have gathered 

here in D.C. have witnessed in addition to the research that Steve 

just presented. 

My peers and I face many challenges as we grow our business. 

The current business environment makes it increasingly difficult to 

businesses like ours to survive, let alone to grow. One challenge is 

finding capable talent. In addition to leading my family business, 

I serve on a New York State Workforce Investment Board. In this 

capacity, I hear about candidates who lack the technical skills that 

we need as our industries advance. Additionally, I hear of the number of people coming into the workforce without key skills that include communication and critical thinking skills, basic soft skills. 

I know of countless small business owners who would welcome 

workforce development investment from the government. By providing small businesses with better information on, and access to 

WIOA initiatives, you can better make a significant difference in 

addressing some of the workforce disadvantages small businesses 

like ours face 

Another challenge is in obtaining capital, as you have heard. It 

can be even more difficult for minorities and women-owned businesses. Johnson Security received financing and we have been able 

to use that money to grow. You can ensure that the Nation’s busiSBREP-219A with DISTILLER

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nesses can effectively utilize the SBA programs that are intended 

to help businesses like ours. 

Federal contracting is yet one additional area where you can remove some of the barriers to small business success. Johnson Security has leveraged many of the small business Federal business 

programs to become a contractor. However, we know of many agencies that have fallen short of their subcontracting goals. You can 

put stronger accountability measures in place to ensure that more 

contracts are awarded to our Nation’s qualified small businesses. 

In closing, the Goldman Sachs 10,000 Small Businesses program 

has been instrumental in the growth not only of Johnson Security 

Bureau, but the Soap Box, and over 6,700 companies across this 

Nation. I encourage you to promote the program to viable firms in 

our districts and to watch and see the impact that that will have 

on our economy. I also implore you to consider making changes to 

some of the regulations that are hindering small business growth. 

Mr. Chairman, I thank you for your time and attention this 

morning. I look forward to the work this Committee will do to continue to help make our Nation’s small businesses big. 

Chairman CHABOT. Thank you very much. Appreciate it. 

And I recognize myself for 5 minutes to begin the questioning. 

And I will begin with you, Mr. Strongin. 

On a macroeconomic level, have we been doing the right things 

over the past year with eliminating some of the regulatory burdens 

and lowering taxes as was done recently in the tax bill? Would you 

expect to see positive trends in small business formation in the 

near future? And how long does it take to have those incentives 

reach the person wanting to start a business? 

Mr. STRONGIN. I think there are two aspects to that. It is certainly the right direction. I think when you look at the sheer volume of rules, one of the small business owners used the phrase, 

‘‘the death of 1,000 cuts.’’ 

Chairman CHABOT. Would you mind pulling the mic a little 

closer? We have got some competition at the door. 

Mr. STRONGIN. No problem. One of the small business owners 

used the phrase, ‘‘the death of 1,000 cuts.’’ And I am afraid, you 

know, when you cut that by 10 percent, it is still not that pleasant. 

And so I think as you think about really changing the burden, you 

actually have to think about things like safe harbors and common 

certifications that will cut through hundreds, if not thousands of 

rules in one step, rather than, you know, surgically removing bits 

and pieces. And so I think that broadly it will help. 

I also think that when you look at the consumer and financing 

side, that the changes there have actually so far been quite modest. 

You know, there is certainly intent, whether it be with the Fed or 

the CFIB to change the rules, but when you look at the academic 

work, it has been very clear that small business lending and consumer lending and particularly startup financing has been one of 

the areas in which the regulators have put the greatest burden on 

capital standards, and particularly, and I think this is something 

that gets missed, when you look at business formation in low-income and rural areas where FICO scores tend to be low, those burdens are extraordinarily high. And so I really do think it will be 

important to look very carefully at the lending standards that were 

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developed post-financial crisis to give them a greater friendliness 

to lending for the purposes of small business startups and small 

business operations. 

Chairman CHABOT. Okay. Thank you very much. 

And could you, I will just follow up with a question, do you have 

an opinion relative to, say, Dodd-Frank, what effect that has had 

on access to capital with small businesses across the country? 

Mr. STRONGIN. One of the difficulties in analyzing Dodd-Frank 

is that when it generates—I think the current count is 23,000 

pages at the Federal Register—that it becomes a little difficult to 

separate out one item from the next. 

Chairman CHABOT. Yeah. 

Mr. STRONGIN. The way we have approached this question is 

looking at the cumulative impact. And when you look at the cumulative impact, we are roughly 700,000 small businesses short of 

where you would have been under pre-financial crisis rules. That 

is a great number of small businesses. So that financial burden 

looks quite high. When you look also at what I would call the leap 

phase of small businesses, when they go from small to not small, 

that has equally been hit in the numbers. And the number of public companies has been falling because those are the two places 

where it is the greatest leap of faith in the process. And when you 

create a system that is anti-risk, it is the moments of that leap of 

faith that are, of course, going to get hit the worst. 

Chairman CHABOT. Okay. Thank you very much. 

Mr. Foster and Ms. Johnson-Cope, I will ask you both, if you 

could, could you tell us how the 10,000 Small Businesses program 

has directly impacted you all, and do you think this is something 

that could be replicated in other parts of the country? 

Mr. FOSTER. For myself and for our firm, it has helped tremendously. I mean, the Goldman Sachs 10,000 Small Businesses program has allowed us to leverage my alumni that are in the room. 

Right? As a small business, you do not really have the opportunity 

to go out and start a board of directors. And so being able to leverage the folks that are in my cohort who have like-minded experiences that I have gone through, it is more of a sounding board of 

folks that have reached those same kind of hurdles and trying to 

get over those hurdles. So for us, we have been able to leverage 

that community that Goldman Sachs provides, as well as I think 

the program should be replicated and produced across the country. 

Chairman CHABOT. Thank you very much. 

Ms. Johnson-Cope? 

Ms. JOHNSON-COPE. As a graduate of the inaugural class in 

New York City, we had the opportunity not just to build relationships with the community college partner, LaGuardia Community 

College, with the other program participants, but also with members of the administration at Goldman Sachs and members of the 

city administration in New York City. So the program represented 

the best of public-private partnership. And instead of giving us a 

golden ticket, it gave us the opportunity to learn how to navigate 

corporate, private sector business opportunities for us to grow, as 

well as how to take advantage of some of the publicly available resources. So just bringing better attention to what resources were 

SBREP-219A with DISTILLER

11 

available to us, that has helped tremendously, and then the relationships have really put us over the top. 

Chairman CHABOT. Thank you very much. My time is expired. 

The ranking member is recognized for 5 minutes. 

Ms. VELA ́ ZQUEZ. Thank you, Mr. Chairman. 

Mr. Strongin, in your written testimony you touch on the geographic concentration of capital. Besides location preferences, there 

is a tendency for banks and venture capitalists to invest more in 

male-owned than female-owned businesses. Minority-owned firms 

fare just as poorly. In your experience, what impediments are there 

for minorities and women to gain access to capital? 

Mr. STRONGIN. This goes back to what I was talking about 

when I was talking with the chairman about anti-risk. It is not 

that women or poor communities are sort of worse risk inherently, 

but they typically have less equity in their homes and they typically have—— 

Ms. VELA ́ ZQUEZ. I am not referring to poor communities. I am 

referring to minority business owners who might be doing quite 

well, even medium size, yet the data showed that access to capital 

is more difficult to come by than white male owned. 

Mr. STRONGIN. I did understand the question. 

One of the issues you run, and this is equally true of rural lending, is that when you look at the way the risk calculations are 

done, you take account of both where you do business, how you do 

business, and the assets held by the business. And so what you get 

is a reflection of the asset concentration that mirrors the business 

problem you just raised. Is it the groups who have the greatest 

asset calculations because of their personal assets typically have an 

easier time getting funding? You also have an issue that those people who are doing business in well diversified richer communities 

have an easier time getting credit because they are less risk. All 

right. And so one of the things, and this goes to the heart of whenever you talk about entrepreneurship, if you do not embrace risk, 

you end up disenfranchising large groups of people who want to 

make that leap. 

Ms. VELA ́ ZQUEZ. Okay. Thank you. 

Mr. Foster, I would like to hear your take on that question. 

Mr. FOSTER. We represent or have 170 banks that we work 

with across the country and it is interesting to see the type of companies that come to our table looking for access to capital. And 

those that come to us that are minority, women-owned, LGBT, veteran-owned businesses, and mostly the minority and women-owned 

set, find challenge the greatest challenge because I think banks 

provide a higher scrutiny on them than their majority counterparts. And we see it across the board, whether it is credit score, 

FICO, whether it is P&L and balance sheets. I think they have less 

access to some of the best minds, CPA firms, legal counsel, which 

hinders them when they actually are putting their package together for lending. And so what we have tried to do is create a 

level playing field so that we provide that expertise when they cannot afford to. 

Ms. VELA ́ ZQUEZ. Thank you. 

The U.S. inflation grew over 2 percent in January, making it 

more likely that the Federal Reserve will raise interest rates quickSBREP-219A with DISTILLER

12 

ly this year. This in turn will make the cost of capital more expensive for small businesses. What impact will this have on women 

and minority borrowers who continue to struggle getting loans? 

I am sorry but—— 

Mr. STRONGIN. No, it is quite all right. 

Ms. VELA ́ ZQUEZ. Am I becoming; right? 

Mr. STRONGIN. No, I mean, this goes to how you think about 

growth from the deepest level. Whenever you talk about any issue 

related to social mobility, the faster the economy grows, the more 

impact you will have on disadvantaged communities. And so the 

strength of the recovery will be very important for the positive. 

Equally, and this I think is the point, the increase in interest rates 

acts as a counterbalance there because it makes it harder for those 

who do not already have that capital to get it. And so it is going 

to work both ways. The business opportunity is going to rise. The 

ability to exploit it is going to go down. 

Ms. VELA ́ ZQUEZ. Ms. Johnson, please, can you talk to us about 

the workforce disadvantages that small businesses like yours face 

compared to larger counterparts? 

Ms. JOHNSON-COPE. So I mentioned potentially greater access 

to and information on the WIOA initiatives. What I have seen serving on the New York State Workforce Investment Board is that 

typically, the WIOA programs are focused toward the large corporations and small businesses do not even know they exist. And 

when the grant and funding opportunities are presented, you have 

to have a massive program and someone who specializes in writing 

grants and writing proposals, and as a small business owner, typically we do not have that personnel. We do not have the resources 

to go after those opportunities, and the large corporations do not 

welcome us to be a part of their proposals to take advantage of 

those initiatives. And so if we cannot even get people who can provide good customer service skills, we cannot look at people who 

have good computer skills or additional skills that are needed as 

we try to compete not only as small businesses but as we compete 

as a Nation. 

Chairman CHABOT. The ranking member’s time has expired. 

Ms. VELA ́ ZQUEZ. Thank you. 

Chairman CHABOT. Thank you. 

Ms. VELA ́ ZQUEZ. Thank you. 

Chairman CHABOT. The gentlelady from American Samoa, Ms. 

Radewagen, who is the chairman of the Subcommittee on Health 

and Technology is recognized for 5 minutes. 

Mrs. RADEWAGEN. Talofa. Good morning. Thank you, Mr. 

Chairman, and the ranking member for holding this hearing today, 

and thank all of you for testifying today. I represent the territory 

of American Samoa, a little jewel of the Pacific. 

Small businesses are a little different at home. Almost every 

family has one. In fact, 99 percent of our businesses in American 

Samoa are small businesses. So there is growing produce or livestock that they sell at the market. These small businesses are our 

community, our family. 

This leads me to my first question. Both Ms. Johnson-Cope and 

Mr. Foster, can you talk a little bit about how your companies are 

helping to invigorate your communities, and how successful small 

SBREP-219A with DISTILLER

13 

firms can have a ripple effect on the surrounding areas in a symbiotic relationship? American Samoa, our only source of higher education is our local community college, and Ms. Johnson-Cope, I see 

as part of your experience with the 10,000 Small Businesses program, you mentioned a community college partner, LaGuardia 

Community College. Would you say that the college was offering 

courses to their students that would make it easier for you to make 

that student your next employee? Is the curriculum beneficial for 

employers? Are they producing graduates with enough skills, or are 

you finding that you still have to invest resources into training? I 

am interested in seeing what I can bring back to my own community college to help develop small businesses in American Samoa. 

Ms. JOHNSON-COPE. So through the relationship with the 

Goldman Sachs 10,000 Small Businesses program, I have had the 

opportunity to work with Dr. Gail Mellow, the president at 

LaGuardia Community College. And we have had very extensive 

discussions on how their curricula could better demonstrate what 

employers like Johnson Security need in terms of workforce development in terms of skills and talent. And so to that end, we are 

looking at creating a special security initiative to help better prepare some of my employees, as well as other students that come 

through the college. The challenge is for the community college environment there are so many other issues at hand. Everyone is expected to go to college. There is a negative perception for people 

who go through community colleges, and many community colleges, 

there may not be as strong a link to the corporate world, the small 

business world, and so the relationships and the curriculum do not 

match up on a one-to-one basis. But through 10,000 Small Businesses, we are having the opportunity to have those discussions 

and shape the curriculum that will make a difference. And we do 

see a ripple effect in our community. So as an example, my business is located in the same neighborhood where I grew up. So I 

have to be accountable to my neighbors and the people that remember me as a child, and I can see the difference that we make 

in that we are putting people to work. We are taking them out of 

the homeless shelters. We are taking them off of the public funding 

rosters and it is making a difference. We cannot do it for everyone, 

and we cannot do it without the help of leaders like yourself. 

Mrs. RADEWAGEN. Mr. Foster? 

Mr. FOSTER. So our experience is twofold. We have the fortunate nature of being on the access to capital side, so we are very 

much engaged with local community organizations that are helping 

put folks back to work. So one of the organizations that we work 

closely with is the Joseph House in Cincinnati, which is an institution that helps veterans that are coming back into the workforce 

either find employment and/or start their own company. And so on 

the side of starting their own company, we are helping them put 

forth access to capital. We are at least helping them with programs 

to get access to capital ready. 

On the flip side, the other side of the coin, we have one of the 

largest minority-owned facility management companies in Cincinnati, and of the 120 contract workers that we have, more than 

half of our folks are from the workforce development startup communities. So you have those that we are putting back to work, 

SBREP-219A with DISTILLER

14 

whether they are out of the prison system or out of a veteran situation. So it gives us the ability to kind of give back to the community in that way through workforce development. 

Mrs. RADEWAGEN. Thank you. 

Mr. Strongin, I just wanted to mention that with regard to at 

least microfinance business loans, out in our neck of the woods 

they tend to favor women because they find that the women are 

the ones who pay their debts and the men tend to allow their loans 

to go into arrears. I just thought I would throw that in. 

Thank you, Mr. Chairman. I yield back. 

Mr. STRONGIN. We have another program called 10,000 Women 

that has used that globally quite well. 

Mrs. RADEWAGEN. Cool. Thank you, Mr. Chairman. I yield 

back. 

Chairman CHABOT. Thank you very much. The gentlelady’s 

time is expired. 

The gentleman from Pennsylvania, Mr. Evans, who is the ranking member of the Subcommittee on Economic Growth, Tax, and 

Capital Access is recognized for 5 minutes. 

Mr. EVANS. Thank you, Mr. Chairman. 

Mr. Strongin, I want to have you respond to something Mr. Foster said, and the phrase he used is ‘‘credit friendly lending ecosystem.’’ So in your mind, I am interested in you telling me what 

do you think is a credit friendly lending ecosystem? What do you 

think that is from your perspective? Because on your page 17 you 

have ‘‘putting the cost of new bank regulations in economic context,’’ as well as I heard the chairman ask the question about 

Dodd-Frank. So I am trying to understand in your mind what you 

think that means. 

Mr. STRONGIN. It is actually a great phrase because I think one 

of the real problems in the way the financial system has evolved 

is it is friendlier to some activities than others. And so in the case 

of small businesses, inventory financing is okay. Asset purchases is 

tough but doable. But true growth funding is virtually impossible. 

Mr. EVANS. And I heard you yesterday say at this roundtable, 

you raised the question around the tax policy. Yesterday, do you recall when you raised a question around, well, we make decisions 

about tax policy. We just passed a tax bill and the impression I got 

from you yesterday was you raised some questions about what we 

did with that tax bill and decisions we made. Do you recall that 

conversation yesterday? 

Mr. STRONGIN. I do. 

Mr. EVANS. Okay. So can you speak to a tax bill that was 

pushed through this process, how exactly does that in a specific 

way help in terms of small businesses? 

Mr. STRONGIN. I want to start with a bit of information that 

Jessica normally actually provides about the way they have community impact. When you talk to the small businesses, one of the 

things you hear over and over again is the incredible work they do 

in taking people who are otherwise not ready for the workforce, investing time and effort into those people, and creating people who 

are truly productive members of our society and have much better 

lives. The tax code, as it is currently structured, provides no tax 

benefits for that investment at all. It does not recognize it because 

SBREP-219A with DISTILLER

15 

it is not a structured investment in the way that a bank thinks of 

an investment. It is the sweat and time of the business owner 

themselves, and that is not recognized as investment. 

On the other hand, if you buy a machine to replace that person, 

that is recognized by the tax code as an investment. That is not 

a particular attack on the last tax bill; that is an attack on the last 

40 tax bills, that we do not recognize the fact that the time and 

effort and sweat of these business leaders to create a better workforce and to strengthen our communities is not recognized as the 

investment it really is. 

Mr. EVANS. Okay. I understand that. And understand, I have 

only been here for 13 months. So that is the only bill that I dealt 

with. So you talk about the 40 tax bills. What I am trying to do 

is figure out a way that nexus. How do we, in a very specific way, 

move the needle? When you talked about the disconnect on economic growth and small businesses and large businesses, so I am 

trying to understand something. And second, let me piggyback real 

quick, CDFIs. I think the conversation came up about CDFIs. Goldman Sachs put up like 200 and what, 50 million or something 

CDFIs. You chose to use that mechanism versus the financial aspect of going to banks. Talk a little bit about that. 

Mr. STRONGIN. This goes to the ecosystem question that you 

raised, is that you need different types of financing at different moments in a firm’s lifetime. The startup tends to be very mortgage, 

credit card, personal asset intensive. When they are healthier and 

larger, it tends to be more the sort of standard bank lending to 

small businesses. When you need to put that leap to an investment, when you are going to grow a business from 30 employees 

to 200 employees, that is when these special lending programs become very important, like the CDFIs. They have been in special 

cases very successful, but broadly, they have never been large 

enough to make a broad scale macroeconomic difference. To certain 

businesses they have been very, very important and very helpful. 

And from the standpoint of our own experience with it, we have 

had people who have been helped. Interestingly enough, they were 

not the people we set out to help. The actually people in the 10,000 

Small Businesses program actually have not used our CDFI to a 

great extent. Some have, but it turned out that a different group 

of small business owners came in and used it. 

And that goes to your ecosystem. You really need healthy lending 

and access to capital along the entire lifespan of these firms, and 

that tends to be different answers at different points in their lifespan. 

Mr. EVANS. I yield. 

Chairman CHABOT. Thank you very much. The gentleman’s 

time has expired. 

The gentleman from Iowa, Mr. Blum, who is the chairman of the 

Subcommittee on Agriculture, Energy, and Trade, is recognized for 

5 minutes. 

Mr. BLUM. Thank you, Chairman Chabot. Thank you to our 

panelists for being here today. 

I am a small business owner myself, and I represent northeastern Iowa. And as I tour my district of 20 counties, the biggest 

issue that small businesses have in my district is finding employSBREP-219A with DISTILLER

16 

ees. And I have talked to Secretary Mnuchin about this. I have 

talked to Speaker Ryan about this. I believe the tax reform we just 

passed could lead to 4 percent economic growth sustained over the 

next 10 years, certainly 3-1/2 percent. But I think a couple things 

could hold us back and I would just like to get your thoughts on 

these. The biggest thing is finding employees. And what comes to 

my mind is some sane immigration policy, and also, a sane welfare 

reform policy. So I would love to hear your thoughts. I do not want 

this to get political but finding employees is a challenge. And just 

deliver your thoughts on where do we look for employees? Is the 

government helping or hurting in that aspect of it? 

Mr. STRONGIN. So the representative would like me to talk 

about immigration and welfare without being political? 

Mr. BLUM. That is a challenge, is it not? 

Mr. STRONGIN. That will be an interesting challenge. 

Mr. BLUM. Point well taken. 

Mr. STRONGIN. You are quite right. Immigration, and if you 

talk to business leaders broadly, particularly corporate CEOs, they 

will talk about immigration and flexible immigration and skillbased immigration as one of their top priorities. Because when you 

are trying to grow a firm, very typically there will be specific 

skillsets you are missing, and the ability to get the best people for 

those specific skills is very important. 

When you go to less skilled labor, immigration also plays a role. 

So does the educational system. So do the incentives to work. One 

of the things that I think is very important, and my panelists can 

talk to this better, is the fact that we do not recognize how small 

businesses actually create workers and train workers, and the way 

that interacts with the minimum wage among other roles is an 

issue. Small businesses get no training credits. They receive no 

training credits from when they take someone who has not graduated high school, who potentially has been incarcerated, who has 

potentially been unemployed because of structural dislocations 

from a factory in a rural town, and they train that person. They 

give them new skills, and they employ them. That process is completely unrecognized by the system today. And the notion that we 

would then potentially create some significant grant form so they 

could qualify goes right back into the red tape issue. 

And so I think a true appreciation of the role these businesses 

play will in some part help you with that workforce problem because that is how you create it. 

Mr. BLUM. That is a good point. I would like to hear from the 

other panelists as well. 

Mr. FOSTER. Our biggest challenge on the facility management 

side is workforce because of the folks that we employ. The folks 

that are pushing brooms and turning wrenches often do not come 

from the background of college graduates and whatnot. And so as 

you mention, our biggest challenge is we are pulling direct capital 

from our company to train those folks, right, and not getting a 

strong return as it relates to the contract with our client. So what 

we are having to do is really do grassroots training. Create facilities and create training. And what we have done in Cincinnati is 

we have partnered with other like-minded business owners who 

also are going through the same thing that we are going through. 

SBREP-219A with DISTILLER

17 

We partnered with a general contracting company in Cincinnati 

and we are putting their folks and our folks through the same rigorous training but also pulling from the same candidates. So we 

can also flex workers from their contracts to our contracts to make 

sure that we are providing the right sort of customer and client 

first attention to the contract. 

Ms. JOHNSON-COPE. What I have noticed is that there are people who are sitting on the sidelines who are not in the job market 

even though the statistics show that employment levels are improving. And I guess that is a good place to have a conversation with 

small business owners, with the people who are sitting on the 

fringes and not working, and understand where is the disconnect 

that makes them not want to work. I have seen young people who 

have turned down job opportunities because they are waiting for 

that $15 an hour job because of the promise of a higher minimum 

wage. At the same time, they are currently not working, they do 

not have a good set of skills, and not willing to get those skills, but 

they have the promise of a higher minimum wage. And so it is important to have a discussion not only with the business owners but 

with the elected officials, those people that are sitting on the 

fringe. And then also understanding where are we going as a Nation in terms of our jobs so that we can make sure that we can invest in the skills that people need because if you had thought back 

10, 20 years ago, we were not thinking that people would be largely 

using the Internet and that robots would be replacing people, so we 

need to be thinking forward about what jobs are going to come and 

then engage the people who are not working to figure out how to 

put them to work. 

Mr. BLUM. Thank you very much. And I yield back the time I 

do not have. 

Chairman CHABOT. The gentleman yields back. 

The gentleman from Florida, Mr. Lawson, who is the ranking 

member of the Subcommittee on Health and Technology is recognized for 5 minutes. 

Mr. LAWSON. Thank you, Mr. Chairman, and welcome to the 

Committee. 

I was just sitting here listening to a great deal of what you all 

were stating, and I have been in business for the past 36 years, 

and when I first went in I was in the insurance business. And over 

the years in dealing with attorneys, doctors’ offices, and everybody 

else, when you are in interviews and stuff like that it was always 

about access to capital. So some 40 years later the same issue is 

surfacing about access to capital. And since the downturn in the 

economy since 2008, the same things happens now with small businesses. And then you are seeing some increases in small businesses 

except for African-American businesses. Can you tell me, because 

it has been an issue for a long time, what is it going to take in your 

opinion to increase the growth when access to capital to AfricanAmerican businesses so they can hire in some of these disadvantaged communities, what you talked about, Mr. Strongin, before, 

because that is where it needs to increase so you can actually put 

people to work and at the same time help improve the economy. 

And the last thing I want all you all to address, and I always 

ask this in the Committee, what can this Committee do to really 

SBREP-219A with DISTILLER

18 

help small businesses? You know, when you talk about DoddFrank, 7,000 pages of information that people have to go through, 

what can we do? And I am going to try to cut it short because I 

would like to hear from all of you all about how can we increase 

it? 

Mr. STRONGIN. When you talk to the small business owners 

themselves, and they will do this far better than I, starting a small 

business is an act of faith in yourself and in the economy. And the 

lending and access to capital around that is inherently going to be 

a fairly risky process. And if you look at the history of that process, 

it has always been sort of personal lending, savings, family help. 

That is not really going to change. We are not going to create a 

program where we are going to give everyone one chance at a small 

business. It is about the small business owners’ faith in themselves 

and allowing them to take that chance. 

What happened post-crisis is we developed a belief that people 

were no longer capable of making that decision for themselves. We 

began to leave that decision to the banks, that the banks were supposed to prevent people from taking bad risks. That act of faith is 

often a bad risk. The statistics on success in starting a small business are frightening. It is all the more credit and more amazing 

when you see people do it and succeed or do it a second time or 

a third time and succeed. And that really does require an attitude 

toward risk that is different. And it is something we have done in 

the past. If you look at the financial crisis in the 1980s, the number 

one goal of financial policy in the 1980s was to maintain credit to 

those businesses, and they succeeded and you had small business 

growth. That was not without a price. The S&L crisis was the bill 

for that policy but it maintained a level of entrepreneurship. It created an amazing number of small business jobs. And it allowed 

that entrepreneurial spirit to go. But it was very much an ideological embracing of risk. This time we have decided that risk itself 

is a problem. That is the access we have to develop these decisions 

on, and that is the act of faith that drives entrepreneurship and 

growth, not a program. 

Mr. LAWSON. Mr. Foster? 

Mr. FOSTER. From my standpoint, it starts earlier than that. I 

think it starts with access to education. I think it starts with access to opportunity. And then you get to access to capital. Because 

I think in our community, the black communities, African-American communities and minority communities as a whole, we do not 

get a lot of opportunity to experience being a business owner, seeing our families, our father, our mother being a business owner. 

Right? And so first, you need to start at the education level and 

what does it mean inside of our school systems to run a business? 

Can we get programs to help youngsters understand what it means 

to run a business? And then once that, you have the opportunity 

and the mindset, and then you can start putting in programs like 

Access to Capital at an early age. So that is my thought. And then 

from there it starts to grow throughout the lineage of minority and 

African-American households. 

Mr. LAWSON. Mr. Chairman, I yield back. 

Chairman CHABOT. Thank you very much. The gentleman 

yields back. 

SBREP-219A with DISTILLER

19 

And the gentlelady from Puerto Rico, Ms. Jenniffer Gonza ́lezColo ́n, who has unfortunately had to experience when a hurricane 

comes through and wipes out a great deal of the infrastructure and 

the challenge that that is is recognized for 5 minutes. 

Ms. GONZA ́ LEZ-COLO ́ N. Thank you, Mr. Chairman. And thank 

you for your leadership, allowing us, and the small businesses in 

Puerto Rico to recover with the measures that are so important to 

do so. So this kind of hearing, it is important to us. And I will first 

of all say thank you to the Goldman Sachs 10,000 Small Business 

program. We actually got 10 or more people from Puerto Rico into 

your program. Actually, one of them is here today, Iris Vincent, 

from Primary Corp in Puerto Rico. And we feel very proud about 

her. She is an entrepreneur, small business woman that has been 

awarded actually by her leadership on the island and by the Small 

Business Administration. And actually, that will be my first question. 

Do you think the territories, and we are not just talking about 

Puerto Rico. We are talking about the U.S. Virgin Islands, American Samoa, Guam, Northern Marianas, and even, of course, you 

do not count Washington, D.C., as a territory, but do those territories have different challenges in terms of accessing those kinds 

of loans and investments to make that first effort to establish a 

firm? 

Mr. STRONGIN. They do. One of the aspects of the modern set 

of rules is that almost any area that faces special challenges, right, 

whether it be rural farming communities or territories where the 

risk profile is higher, faces difficulties in getting credit from the 

centralized banks. The way we now score banks on their lending 

practices and the way we view discrimination means that any area 

that is higher risk creates legal challenges for the bank if they lend 

into it. 

When I was at the Federal Reserve was the period where we 

phased in CRA, which had exactly the opposite intent. Right? It 

was about getting credit into those communities. The way we now 

score banks, we make that provision of credit sort of regulatorily 

dangerous because bad performance, higher rates to different areas 

all create potential legal problems. 

Ms. GONZA ́ LEZ-COLO ́ N. What can this Committee do to help 

those territories to access that? 

Mr. STRONGIN. So I think that from the standpoint of the way 

the regulation of banks is set, it really has to be about more the 

actual risk allowing the lending to be more about the borrower and 

less about the borrower group. I do not want to suggest that banks 

are perfect in any stretch of the imagination. 

Ms. GONZA ́ LEZ-COLO ́ N. No. 

Mr. STRONGIN. When it comes to the way they embrace each 

and every community, but when you set up the rules to enforce 

very precise treatment, inevitably those rules will be highly discriminatory against some communities and in favor of others. And 

the way the current rules are set up, it actually hurts the communities most in need of help, the ones with very specific economic 

structures, right, where they tend to get bad weather. Farming 

communities because of similar weather issues are very high-risk 

SBREP-219A with DISTILLER

20 

areas, and so they tend to have the greatest problems getting credit. 

Ms. GONZA ́ LEZ-COLO ́ N. Can you and all the witnesses provide 

a list for the Committee of those recommendations that you understand will help us out, because my time is almost set to expire and 

I want to make another question. You can submit that to the chairman. 

But I am very impressed about the testimonies regarding Mr. 

Foster and Ms. Johnson regarding how your businesses grew, grew 

your revenues, created more jobs, expanded your operation. You 

accessed financing. So for me it is important to know what skills 

do that program, the 10,000 Goldman Sachs program, actually help 

to improve and develop? What are those skills that are mostly 

needed that makes a difference between that kind of program and 

others? 

Ms. JOHNSON-COPE. The first skill I would say is confidence, 

because it is one thing for me to do business with business in my 

community that are small just like I am. To have to make a case 

to a firm like Goldman Sachs and to large corporations as to why 

they should do business with me, it gave me an air of confidence 

that prepared me to go into other corporations and to ready my 

business and ready my team to provide our services on a grander 

scale and to show people in our community that we were able to 

go beyond what we had previously seen as our limit. So confidence 

is that first skill. 

Another skill would be just in financial management. To look at 

dollars and add a zero to the level and volume of contracts we had 

previously done. It opened our eyes to bigger opportunities. And so 

it allowed us to walk into more contracts and to prepare to create 

those jobs that our community needed. So confidence and financial 

management. 

Chairman CHABOT. The gentlelady’s time has expired. 

The gentlelady from North Carolina, Ms. Adams, who is the 

ranking member of the Subcommittee on Investigations, Oversight, 

and Regulations is recognized for 5 minutes. 

Ms. ADAMS. Thank you, Mr. Chairman. Thank you, Ranking 

Member Vela ́zquez, for hosting today, and to all of the witnesses, 

thank you very much for your testimony. 

Mr. Strongin, HBCUs are well suited to foster entrepreneurship 

and start-up business growth due to access to high caliber human 

capital, our students and professors, while also providing a support 

structure to establish new ventures. I was delighted to see that 

Goldman Sachs is recognizing the untapped potential of HBCU institutions and is partnering with at least one HBCU. Last year, the 

Goldman Sachs 10,000 partnered with Morgan State, and so I have 

a couple of questions for you. First of all, if you could expand on 

Goldman’s partnership with Morgan, what is Morgan’s role in the 

partnership, and do you have future plans to partner with other 

HBCUs? 

Mr. STRONGIN. The last part of that is easier for me to describe 

than the first. 

Ms. ADAMS. Okay. 

Mr. STRONGIN. The answer to that is yes. We are looking to expand the program broadly. This year we set up a national cohort 

SBREP-219A with DISTILLER

21 

that would allow us to bring people from across all 50 states and 

even where we did not have a partner. We continue to search out 

partners, particularly in areas where the benefit would be greatest 

and where we can stretch into the black community, into the Hispanic community. Also, into the rural communities. One of the 

things the research has shown very strongly is that small businesses are incredibly important for creating resilience in communities and very important for renewal of communities. Much better 

than a single factory from a large corporation. And so in our own 

view of creating a healthy economic environment, creating a good 

ecosystem for small business we think is the single greatest thing 

we can do to improve community resilience particularly in those 

communities that have been hardest hit. And that can either be a 

geographic community, or an ethnic community, or a territory. It 

really has to do with dealing with the major economic forces we 

face today of technological disruption, globalization, the issues in 

urban communities, the issues in rural communities we face, that 

when you are trying to fix those issues, that expanding outreach, 

particularly across those communities that need that help, this is 

the best place to do it. And so it is why the program was formed 

in the first place, and it is why we are attempting to expand it. 

And it is why we brought everyone together at the summit, to communicate that to Congress, right, so they can understand why we 

think this is part of the answer. 

Ms. ADAMS. Yeah, well, you are certainly very visible today, and 

I want to commend you on your program and those nice scarfs that 

the folks are wearing. Wonderful. Wonderful. I see Joyce Brayboy, 

and I want to thank you for being here. And all of the folks from 

Goldman Sachs. I had an opportunity to visit the headquarters up 

in New York a few months back. 

Diverse business owners add to the supply chain in valuable 

ways, and research shows that companies that embrace diversity 

are more profitable than companies that do not. So does Goldman 

Sachs’s 10,000 Small Businesses program teach businesses how to 

navigate other companies, supply diversity programs, and how does 

this program serve as a feeder into that chain? 

Mr. STRONGIN. It certainly does. I mean, the graduates can 

speak to than better than I can. I will note before I pass it to them, 

because they will do it better than me—— 

Ms. ADAMS. We have got 1 minute. 

Mr. STRONGIN.—is that part of the proposal is I think that is 

also something you can help with, which is by making the certifications more common and more simple, it will make it much easier 

for those businesses to succeed. 

Ms. ADAMS. Okay. 

Mr. FOSTER. Yeah, I will add just a quick comment to that. I 

think Goldman Sachs, and just the program as a part, has done a 

great job at helping us navigate negotiating, contracts, compliance, 

risk, things that come along with a small business that we necessarily do not see on a day-to-day basis because our heads are 

down and our eyes are on our business, but Goldman Sachs kind 

of allows us to think of our business in a different way. 

Ms. JOHNSON-COPE. I would like to add, my grandmother was 

a graduate of Fayetteville State University. 

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22 

Ms. ADAMS. All right. 

Ms. JOHNSON-COPE. And a lifelong supporter of HBCUs. And 

as a result of graduating from the Goldman Sachs 10,000 Small 

Businesses, I got an opportunity to do business with a large corporation that now asks who else are you doing business with as a 

result of working with us? So they want to see that the Me Too effect works in a positive way. If you can do business with a corporation like a Goldman Sachs, that you are actually going to leverage 

that opportunity to get experience in other corporations, because if 

it is working, then other companies want to take advantage of that. 

Ms. ADAMS. Right. Thank you. I tip my hat and shout out to 

all the HBCUs, and especially those in North Carolina. We have 

more. Nothing could be finer than to be in North Carolina at an 

HBCU. 

Thank you, Mr. Chairman. I yield back. 

Chairman CHABOT. Thank you very much. The gentlelady’s 

time is expired. 

The gentleman from Illinois, who I believe will be our last questioner today, Mr. Schneider, who is the ranking member of the 

Subcommittee on Agriculture, Energy, and Trade, is recognized for 

5 minutes. 

Mr. SCHNEIDER. Thank you, Chairman, and Ranking Member 

for having this Committee. I want to thank the witnesses for joining us today and sharing your experiences. 

I am a huge fan of the 10,000 Small Businesses. I had a chance 

to work with it in Chicago. I know many alumni. I know what you 

do, and I am just grateful for all of that. 

As my predecessor speaker talked about colleges, I am going to 

do my one little pitch and take that prerogative. As an industrial 

engineering graduate of Northwestern University, it is good to have 

you here and see your success, but also as a graduate of Kellogg, 

to have two Northwestern people here is remarkable. But I also 

have to give credit to the purple tie since even though you did not 

go to Northwestern, we have got the trifecta. 

This is an important program, and Ms. Johnson-Cope, I want to 

start with you because your story caught my attention. Third generation business? 

Ms. JOHNSON-COPE. Yes, that is correct. 

Mr. SCHNEIDER. So you went to school. You studied engineering. Did you know when you went to college that you would come 

back and work in this business? 

Ms. JOHNSON-COPE. When I went to college, I knew I wanted 

to be a boss, but I did not think that I would come back to run the 

family’s business. And what I find, in a lot of second and third generation potential business owners, the invitation is not there to 

come and help run the business because we see business differently 

than the previous generations have. And so one of the recommendations I have made to SBA Administrator McMahon is to 

maybe look at how we can recreate SCORE to engage younger people and encourage them to go into entrepreneurial ventures, particularly for family-owned businesses, because I know it is something that I did not necessarily think about, but once I stepped into 

my role it seemed very natural. 

SBREP-219A with DISTILLER

23 

Mr. SCHNEIDER. And just to convey my bias, I spent much of 

my career consulting to family-owned businesses and working in 

family business. And my wife is in a family business. I think the 

advantage, and Mr. Strongin, you pointed to something about communities. The fact that small businesses—and I will add family 

businesses—are important for resilience, and the resourcefulness of 

communities, I think we need to make sure we continue to push 

that forward. 

Having been in a third generation business, and Mr. Foster, I 

will come to you next on this because it is a different experience 

than for Ms. Johnson-Cope, how has the 10,000 Small Businesses 

experience, the classroom program dealing with other people who 

may have started businesses, different experiences than you, how 

has that affected your approach to business? Ms. Johnson-Cope 

first. 

Ms. JOHNSON-COPE. So we all cook at home; right? So it is 

one—— 

Mr. SCHNEIDER. No. 

Ms. JOHNSON-COPE. You do not even make toast? So it is one 

thing to try to cook at home based on what you have watched 

someone before you do. It is another thing to go to culinary school 

and learn how to do it professionally. And so the Goldman Sachs 

10,000 Small Businesses program actually gave me context to what 

I had watched growing up. And then it taught me how to leverage 

the experience I had gained working for other businesses outside 

of my family business and to actually lead my firm. Because the 

jobs that I had did not teach me how to be a CEO. If I had waited 

until I had worked my way up through IBM where I previously 

worked, it would have been 20-some years before I would have 

been CEO, if that. Right? And so the Goldman Sachs 10,000 Small 

Businesses program actually gave me a shorter runway to pick up 

the skills that I needed to lead and actually be the CEO of a company, to grow the business, and to make decisions on a high level 

that I would not have that opportunity to do had I been working 

for someone else or had I been trying to figure out those skills on 

my own. 

Mr. SCHNEIDER. Mr. Foster, your experience. You said you 

came from New York. 

Mr. FOSTER. Well, I lived in New York doing investment banking. 

Mr. SCHNEIDER. Doing investment banking. Okay. But very 

different experiences than going back home and starting a business 

with a friend as a partner, which I imagine sometimes strains 

friendship and sometimes strengthens it. How has this affected 

what you are trying to do? 

Mr. FOSTER. From the 10,000 Small Businesses standpoint? 

You know, as she said, it really shortened that runway. And for 

me, it reinforced all the things that I had been experiencing prior 

to joining the program. And also as I mentioned earlier, just the 

community of folks to leverage within my cohort was second to 

none because you do not know what you do not know. And when 

you are in business and you are going through trying to win contracts, trying to manage employees, you are just doing it as you 

think you should do it, right, and then going through the program 

SBREP-219A with DISTILLER

24 

and then coming out of the program, I just had so much of a 

stronger toolkit behind me. And so that is how it has helped me. 

Mr. SCHNEIDER. Great. And I am almost out of time so I am 

going to ask a rhetorical question of Mr. Strongin, about something 

you said in your submitted testimony that I think is really important. And it is the statistic that between 1977 and 2007, so a 30- 

year period, projections for small business startup and development, there are 675,000 ‘‘missing businesses.’’ I think there are a 

lot of reasons for that. We have talked about some of them here, 

but promoting a culture of entrepreneurship, helping young people 

understand that they can be their own boss, they can pursue their 

own dream, I think our role—I say all the time there are four 

things needed for success—a business model. You guys are responsible for that and Goldman is helping with that. But access to capital, access to talent, and a stable and conducive business environment, that we all have to work together. Congress has to do its 

part. But promoting that and trying to fill that gap, because if we 

are going to continue to grow our economy, whether it is after recovery in difficult places, in communities that are trying to turn 

around having lost major companies, or just in general looking at 

a new economy developing every decade, we need to promote a 

strong startup culture and give the people in those businesses the 

skill. 

So let me close and say thank you to Goldman Sachs for doing 

this program. It is a fabulous program, and thanks to both of our 

witnesses from experience. You did a great job. And with that I 

yield back. 

Chairman CHABOT. Thank you very much. The gentleman’s 

time has expired. 

And we want to thank our panel here this morning and now this 

afternoon for really excellent testimony. I think it was a very enlightening discussion. Great questions from the folks up here on 

both sides and great answers from you all. So hopefully we can replicate much of what you have accomplished across the country and 

have more and more small businesses created all over American 

and thrive and get the American economy booming. So thank you 

very much for participating in this today. 

I would ask unanimous consent that all members have 5 legislative days to submit statements and supporting materials for the 

record. 

Without objection, so ordered. 

And if there is no further business to come before the Committee 

other than Happy Valentine’s Day, everybody, the Committee is adjourned. Thank you. 

[Whereupon, at 12:17 p.m., the Committee was adjourned.] 

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25 

A P P E N D I X 

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Testimony of Steven H. Strongin 

Managing Director 

Goldman Sachs & Co. 

United States Honse of Representatives Committee on Small Business 

"Helping Small Businesses Overcome Barriers to Growth" 

February 14, 2018 

Chairman Chabot, Ranking Member Velazquez and Members of the Committee, we thank you for 

inviting us to present our findings regarding the small business landscape. We hope our thoughts prove 

helpful. lam Head of Global Investment Research and Chair of the Global Markets Institute ('"GMI") at 

Goldman Sachs (the "Firm"). Prior to joining the Firm in 1994, I spent 12 years at the Federal Reserve. I 

am pleased on behalf of the Firm to answer your questions regarding the work that underpins our views 

on the state of small businesses. 

This hearing coincides with a summit hosted by the Firm entitled: "10,000 Small Businesses: The Big 

Power of Small Business." As part of this two-day event, more than 2,200 graduates of the Firm's 10,000 

Small Businesses program 1 are gathered together in-person in Washington, D.C. in an effort to express the 

unique challenges they face and to progress possible solutions as they work to grow and to compete 

successfully in their respective markets. 

We believe the Summit represents an important opportunity for small business owners to contribute in 

their own words their ideas as to how to progress America's small business agenda. The aim is to renew 

our collective focus on the vital relationship between entrepreneurship and economic growth, including 

the link between small business formation and innovation, as well as economic and social mobility for 

American workers. 

A. Small business formation has slowed 

Behind the focus on small businesses is a series of stark facts: even as the American economy is more 

than I 00 months into the current recovery- now the third longest on record- the "small business 

economy" has continued to face some serious challenges. 

Perhaps the simplest and most economically significant demonstration of the challenges faced by small 

businesses is that the number of small firms actually declined over the five years from the start of the 

recent recession- the only such decline since the data became available in the late 1970s. 2 Relative to the 

1 Goldman Sachs 10,000 Small Businesses is an 
26 

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trend growth rate experienced from 1977 until 2007, there are roughly 675,000 fewer small businesses 

operating today than we would have expected. 

Exhibit 1: The number of small firms declined after the ouset of the crisis and remains below trend 

Data are available from 1977 until 2015 

5,500,000 

5,000,000 

€ 4,500,000 

"' • ! 

§ 4,000,000 

2 

3,500,000 

3,000,000 

Linear regression from 

1977 through 2007 

{R2 ,0.99) 

(1982, -130,000 ~missing" small businesses) 

"•"Firms wlth <500 employees 

Source: U.S. Census Bureau, Goldman Sachs Global Investment Research 

This is five times the largest prior gap of 130,000 small firms experienced in 1982, which was also the 

last time the U.S. economy endured a recession as severe as what was experienced in 2008, both of which 

were related to financial crises. See Exhibit 1 above. It is worth noting that the policy response to the 

1980s crisis was centered on maintaining the flow of bank credit to communities and to individual 

borrowers. 3 While there were downsides to this approach, it contributed to a strong economic recovery, 

particularly as it relates to jobs. 

The pattern of job growth following the 1982 recession reflects a strong small-business recovery. Four 

years after the end of the 1982 recession, there were nearly 9 million more jobs at small firms than there 

were before the recession began, reflecting the rapid pace of the recovery. Over the same timeframe, large 

firms added nearly 3.5 million jobs, roughly 60% below the comparable figure for small firms. 

During the current economic recovery, where policy has largely been driven by the belief that too much 

access to credit was the problem, the exact opposite pattern has emerged in business formation and job 

creation. Four years after the end of the 2008 recession, there were 2 million fewer jobs at small firms 

than there were before the recession began. At the same time, there were 1.5 million more jobs at large 

firms than there were prior to the recession. Exhibits 2A and 2B below compare the change in jobs during 

the 1982 and 2008 recessions and recoveries. 

1990s: Summary and Implications," Vol. 1, Chapter I 

2 
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Exhibit 2A: Job gains (losses) during the 1982 and 2008 recessions 

The change in jobs by firm size 

19821recesslonl 

M2008lrecessionl 

0.0 

100·249 250-499 500-999 1,000-2.499 2,5(l{NUl99 5,000.9,999 10.000-.-

Firm size, by number of employees 

Source: U_S, Census Bureau, Goldman Sachs Global Investment Research 

Exhibit 2B: Policy matters: job gains (losses) during each recovery 

The change in jobs by firm size 

19B3-19B6{r(";"(1VCry) 

100-249 1,000-2.499 v;oo-4.999 5,ooo-s.sss 1o.ooo+ 

Firm sh:e, by number of employees 

Source: US. Census Bureau, Goldman Sachs G!oballnvestment Research. 

Beyond new firm formation, and job growth, the resulting differential between large firm and small firm 

wage growth is equally stark. Although wages (indexed to 1996 levels) at both large and small 

establishments increased nearly in tandem during the decade before the crisis, these two figures have 

since diverged and now reflect a gap of nearly 20 percentage points. This suggests that small businesses 

continue to struggle, and that their employees may be paying an ongoing price in the form of lost wages. 

There are a lot of theories about why the current recovery has felt uneven, with large firms performing 

well while smaller firms have struggled but these explanations in isolation are probably not truly 

sufficient to explain what has actually happened. This is largely because the bifurcation in the recovery 

3 
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isn't the result of any single rule or factor. Rather, it is the cumulative result of the effects of direct and 

indirect regulation, coupled with demographic changes and housing and fiscal headwinds. 

Since the broad deregulatory wave of the early 1980s, the volume of rules and of regulations that apply 

across industries has multiplied, with greater scope and seemingly increasingly severe enforcement. 4 

In particular, new banking regulations have made bank credit both more expensive and less available, 

affecting small businesses disproportionately as they lack access to affordable alternatives. The impact 

these rules have had on consumer credit, including on credit cards and home loans, is particularly 

problematic for small businesses. While the topic of consumer credit may not seem relevant in the context 

of new firm formation or small business growth, the reality is that start-up and growth financing often rely 

on the owner's ability to use credit cards, second mortgages and other personal sources ofcredit. 5 

Exhibit 3: Rates have risen most in the lending markets that are most exposed to regulatory change 

Change in average lending spreads, comparing 2013 with prc-2008 spreads, plotted against our 

assessment of the degree of banking intensity and the extent of regulatory change in 12 key lending 

markets 

-150 

0.0 0.5 

Near-andswb·pr>mucreditcard • 

Primecredrtcard. 

0 Sma!lbUSIMSSCred<t 

•Consumercred•t 

+Cred•tfac!litywherepricingdataisNA 

LO 2.0 

Deg~ee of banking lntenslw and regulatory change 

Source: Goldman Sachs Global fnves.tment Research, For additional detail, sec the Global Markets Institute publication "Who pays tOr bank 

regulation?" (June 2014), 

4 
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As it relates to mortgages for borrowers with "sub-prime" credit, the problem is particularly acute, as 

Exhibit 3 above shows. Since 2010 there has been a pronounced drop-off in mortgage availability for 

borrowers with FICO scores below 620, who are typically considered to be sub-prime. This represents a 

significant change relative to mortgage availability prior to the recent recession, as Exhibit 4 shows. The 

reduction in mortgage availability helps to explain why the homeownership rate is now at the lowest level 

in nearly 25 years. Importantly, as it relates to small businesses, this means that the equity and credit 

small businesses require to open and to operate are more limited than in the past. 

Exhibit 4: The mortgage market has concentrated around higher-credit score borrowers 

Change in the share of mortgage borrowers, by credit score: 2000-2006 vs. 2010-2016 

1 0 

~ 

~ o.z 

!£ 

~ 0.0 

" ill 

m 

&: . 0.4 

Change ln share of borrowers receiving mortgages 

post·crisis. by FICO score 

Increase in share of 

all mortgages 

Decre'ase in share of 

ail mortgages 

Source: Black Knight, Goldman Sachs Global Investment Research. 

In our recent survey of over 1,000 small business owners who have participated in the Firm's 10,000 

Small Businesses program, 70% of founders said their personal credit score was important to secure the 

financing necessary to start their businesses, while 80% of all business owners (founders and nonfounders alike) said their personal credit score would be used to secure new financing today. What's 

more, for businesses formed in the last five years relative to those formed prior to 2007, there has been a 

notable shift from the use of home loans, personal loans and personal credit cards to greater use of 

retirement funds, personal savings and private investments to cover start-up costs. 6 

Even as entrepreneurs and small businesses have had difficulty accessing capital, large firms have been 

able to tap into the public capital markets at low rates. This means that we've effectively seen the 

financing costs oflarge corporations decline relative to small businesses' costs, putting smaller firms at a 

competitive disadvantage. This, in all likelihood, is a major reason why large companies have 

experienced a stronger recovery than have smaller ones. 

While banking regulation has played a key role, regulation outside of banking has also weighed on small 

firms. Data from the U.S. Government Accountability Onice (GAO) show that the issuance of"major" 

6 See Appendix A for more detail about this survey, 

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rules rose significantly after 2008. Nearly 800 major rules were issued at the federal level between 2008 

and 2016, which is around 50% more than the preceding nine-year period. 

It is unclear whether these economy-wide regulations can fully explain the bifurcation between the 

economic prospects of large and small !inns, but regulation would typically have a disproportionate 

impact on the ability of small firms to compete, despite often subjecting larger firms to notable increases 

in direct regulatory scrutiny and higher absolute costs. The negative competitive effects for small firms 

arise because of the relatively fixed-cost nature of complying with regulations; large firms have a much 

larger volume of business over which to spread higher fixed regulatory costs than do small firms. And 

even when small firms are formally exempted from regulations, they may still feel the impact because 

they may effectively be required to meet what soon become de facto standards for the industry as a whole. 

Put more simply, regulation is primarily a fixed cost- so the smaller the business, the greater the burden. 

B. Why should America care? 

Small businesses are an essential part of the U.S. economy. They provide jobs to nearly 60 million people 

-that's just shy ofhalfthe non-farm private workforce- while also supporting workforce dynamism and 

social mobility.' Small businesses employ a more diverse group of individuals than do large firms, with a 

larger share of employees who are younger (less than 25 years old), have a formal education below the 

high-school level, and are older (65 years or older). They also employ a higher share of women and of the 

disabled. 8 Small businesses are a key generator of social and economic mobility and thus are an important 

source of stability and renewal. 

The individuals who work for small businesses benefit from the significant investments their employers 

make in training them. This is despite the fact that such investments in human capital can be one-sided, 

since employers have no way to guarantee that they will be able to recoup the costs of these investments 

over time. The impact small businesses have on their local communities is all the more meaningful in 

rural areas, where employment at larger corporations may not be an option. 

In the face of accelerating technological change, small businesses may also be more resilient sources of 

employment. Consider the activities that are well-suited for machines: they tend to be data-intensive, 

repetitive and standardized- work for which technology and machines are more efficient than people, 

especially when done at scale. At the same time, people maintain a competitive advantage over machines 

in almost all contexts in which repetition and measurement are not central or even possible. Jobs that 

require people also frequently involve interpersonal interaction or have a social aspect, which tends to 

mean they can be done only on a small scale. Such unique, small-scale, person-dependent work is often a 

defining characteristic of the jobs available at small businesses. 

As they have in the past- from the agricultural revolution to the information age- small businesses can 

serve as a "safety net" for the individuals who must transition between jobs or careers due to automation. 

Small businesses may be better able to leverage the specialized skills that larger firms no longer need, or 

create new types of jobs and serve as a key source of training. 

Census Bureau, U.S. Bureau of Labor Statistics "fllis figure excludes the more than 24 million non-employers as of20! 5 

Census Uureau 

6 
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The role that small businesses play as drivers of innovation is worth acknowledging as welL In fact, the 

U.S. Small Business Administration has found that small innovative firms generate 15 times as many 

patents-per-employee than do large innovative firms! 

Taken together, these factors demonstrate society's stake in the health of small businesses because small 

businesses are essential in addressing some of the largest sources of stress in modern society. These 

include technological disruption, globalization and the divergence in economic outcomes based on 

educational attainment or the urban/rural distribution of the population. But given recent trends, the 

benefits small businesses bring to society as drivers of economic and social mobility are no longer 

guaranteed. Additionally, the long-run implications of the U.S. economy becoming increasingly 

dependent on a shrinking pool of the largest businesses should be causes for concern for policymakers 

and regulators alike. 

C. What can be done to encourage small business growth? 

Given the relative resource disparity that exists between large and small firms, operational processes that 

are lime consuming, paperwork-intensive and overly complex or frequently changing create a 

disproportionate burden for small businesses. In response to the survey of 10,000 Small Businesses we 

mentioned above, owners have identified that determining which rules apply to them, understanding these 

rules and navigating frequent rule changes are some of the key challenges they face. 

Beyond the logistics of navigating regulation directly, a heavy indirect regulatory burden is often passed 

down from larger firms or from the public sector to the small businesses they work with; this may occur 

in cases where small firms would otherwise be formally exempt from the rules. This "inherited" burden of 

regulatory compliance makes it increasingly difficult for small firms to compete and to win business from 

bigger corporate clients and from the government. 

Since the broader U.S. economy benefits from thriving small businesses, policymakers should evaluate 

how the current regulatory environment affects small firms' ability to grow. Moreover, greater publicsector support is needed to rebalance the risk inherent in investing in human capital and to support small 

businesses as they hire and train tomorrow's workforce. In the recent past, recognition of the challenges 

facing small businesses has grown and steps have been taken to lighten the burden, but far more will need 

to be done to reinvigorate small business growth. 

Some specific recommendations we think should be considered include: 

1. Adding to the Small Business Administration's (SBA) mission to help small businesses by 

finding ways to navigate regulations and other requirements more easily. Two substantive ways 

to do this include: 

a. Providing a centralized repository of federal, state and local rules that would create one 

location for small business owners to find the full set of rules as well as those most likely 

to apply to them. This could substantially improve transparency and lessen unanticipated 

fines or other delays faced by small firms caught oft~guard by changes in rules that 

evolve frequently. 

7 
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b. Creating a common certification standard that can be used by all governmental agencies 

and programs as a form of verification of the suitability of a given small business to 

compete for opportunities that require them to meet various federal and state 

requirements, such as Anti-Money Laundering (AML) rules or other vendor certifications 

that are demanded either directly by the government or by corporations to meet their own 

government obligations. 

2. Exempting from or lessening the burden of various consumer lending rules to more easily and 

affordably enable personal lending to small business owners for the purpose of financing their 

businesses. A separate, simplified set of unified rules could be considered as an alternative in this 

regard. Simplified paperwork and less "red tape" would also be viewed positively by small 

business owners. 

3. Considering ways to reward the training small business owners provide their employees. This 

could be in the form of expanded tax credits that automatically extend to small businesses that 

hire new employees. Alternatively, small businesses could be allowed to pay a "training wage" 

for some predetermined and fixed period oftime in exchange for formal training funded by the 

small business employer. 

Appendix A: 10,000 Small Businesses overview and new research 

Appendix B: Global Markets Institute: Reinvigorating Small Businesses: ldent(/j>ing Obstacles and 

Finding Solutions to Drive Growth and Joh Creation 

8 
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Appendix A: 10,000 Small Businesses overview and new research 
34 

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SUMMIT 

THE BIG POWER OF 

SMAll BUSINESS 

ABOUT 10,000 SMALL BUSINESSES 

FEBRUARY 13-14, 2018 

WASHINGTON, DC 

srnal! busim~sses across 

rncd:a1l number of ernploveus is 

to a 

10 
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THE RESEARCH mBIBIBIII~~,-----· SURVEY OF GOLDMAN SACHS 70,000 SMALL BUSINESSES AND RELATED FOCUS GROUPS 

TOP 3 BARRIERS TO GROWTH --- 1} Atlracting 11ew employees and rnar'!agin9 the hiring process 

2} Securlnq fi1wndng 

3) Training employees 

KEY FINOINGS ------~~,,_ 

70% stru~m!n to find and retain skinnd ta!e11t, and them foro 

find themsulves plnying significant ro!o in training tfwirOlllj11oyoes, 

POSSIBLE SOLUTIONS , J ' ~,~ ,0y~ 
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Appendix B: Global Markets Institute: Reinvigorating Small Businesses: IdentifYing Obstacles and 

Finding Solutions to Drive Growth and Job Creation 

12 
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The Global Markets Institute is the public· policy research unit of Goldman Sachs Global Investment Research, 

designed to help improve public understanding of capital markets and their role in driving economic growth. 

14 
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Reinvigorating small businesses 

Identifying obstacles and solutions 

to drive growth and job creation 

This publication is a compendium of reports previously issued by the Global Markets 

Institute, including "Who pays for bank regulation?" {June 2014), "The two-speed economy" 

(April2015) and "Narrowing the jobs gap: overcoming impediments to investing in people" 

(July 2016). 

The quality of the current U.S. economic recovery- now among the longest on record- has varied 

widely for small firms relative to large ones. Despite what the national economic data would suggest, 

new finn formation has been softer than in the past and small businesses have suffered tepid 

employment, revenue and wage growth relative to large firms. 

The most widely-cited and most likely explanation for this bifurcation, which we discuss at length in 

"The two-speed economy;' is that the cumulative impact of post-crisis regulations and related policy 

actions contributed to this outcome. For example, new banking regulations have made bank credit both 

more expensive and less available, which has affected consumers and small firms disproportionately 

since they largely lack alternative sources of financing. At the same time, large firms have been able to 

tap into the public capital markets at low rates (see "Who pays for bank regulation?"). 

The soft small business environment should be a cause for concern for pollcymakers and regulators 

alike. Small businesses support workforce dynamism, employing a more diverse group of individuals 

than do large firms; for example, small firms have a larger share of employees who are younger (Jess 

than 25 years old), have a formal education below the high-school !eve!, and are older (65 years or 

older). Small firms also serve as a critical "safety net" for individuals shifting between jobs, or even 

careers. 

These dynamics are exacerbated by ongoing technological disruption of the labor market On the one 

hand, the activities that are offloaded to machines tend to be data-intensive, repetitive and standardized 

-work for which technology and machines are more efficlent than people, especially when done at 

scale. On the other hand, people maintain a competitive advantage over machines in almost all contexts 

in which repetition and measurement are not central or even possible. Jobs that require people also 

frequently involve interpersonal interaction or have a social aspect, which tends to mean they can be 

done only on a small scale. 

Small businesses, which often define their competitive advantage as their ability to offer personalized 

service and bespoke output, are important sources of employment amid the changing jobs landscape. 

They may be able to better leverage the specialized skills that larger firms no longer need, create new 

types of jobs that offer a safety net and also serve as a key source of training (see "Narrowing the jobs 

gap: overcoming impediments to investing in people"). However, given !ower rates of new firm 

formation relative to the historical trend- there are roughly 675,000 "missing" small firms 1-the safety 

net small firms can provide is no longer guaranteed. 
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Who pays for bank regulation? 

L Who pays for bank regulation? 

H. How to assess who pays for bank regulation 

111. lower-income consumers and small businesses are paying more as a result of new bank regulation 

!V. Putting the cost of new bank regulation into economic context 

V. Conclusion 

Appendix A: Select rules and regulations applicable to US banks enacted since 2008 

Appendix B: Benchmark maturities and proxies used in our analysis 

The two-speed economy 

!.The changing shape of the US economy 

!!.The recovery has been slow and uneven 

!!I. Assessing the impact of regulation on small firms 

IV. Reduced competition from small firms appears to be affecting the investment decisions of large firms 

V. Conclusion 

Appendix A: Defining "small" businesses 

Appendix B: Employment figures and wage data 

Narrowing the jobs gap: overcoming impediments to investing in people 

Narrowing the jobs gap: key points 

L Narrowing the jobs gap: overcoming impediments to investing in people 

1!. Why technological progress can hurt today's jobs even as it benefits the economy's future 

IlL Technology versus individuals in the 21st century 

IV. The investment analysis: impediments to investing in people 

V. The disconnect between individual loss and aggregate gain creates policy challenges 

V!. Conclusion 

Appendix A: Technological innovation has fueled job destruction and creation throughout American history 

Appendix B:The natural 'arc' of occupations and industries 

Appendix C: How uncertainty keeps individuals from moving out of declining industries 

Bibliography 

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In the wake of the financial crisis, a wide range of new and revised rules, regulations and 

practices have been imposed on the US banking industry. These include measures to 

strengthen and raise capital, reduce leverage, improve balance sheet liquidity and bring 

greater standardization and transparency to derivatives markets. They also include new 

rules around credit card availability and debit~interchange fees, along with heightened 

regulatory and judicial scrutiny of bank lending and other practices. 1 

While many of these steps are designed to strengthen the safety and soundness of the 

banking system, they also act as a tax on banks: by changing relative prices, regulation 

makes some activities more expensive and others cheaper. Taxed activities become more 

expensive for banks to produce and for their customers to consume. As in many markets, 

higher costs typically reduce the amount of activity undertaken. Thus the bank tax affects 

the distribution of activities across different types of consumers and businesses in a way 

that allows clear winners and losers to emerge. This then leads to two questions: 'who 

ultimately bears the cost of bank regulation?' and 'what are the broader economic 

implications?'. 

The multiplicity and complexity of post~crisis regulations complicate the process of 

answering these two key questions. Largely because multiple new rules affect the same 

activities, there is substantial uncertainty as to which rule is binding at any point in time. 

This makes it extremely challenging not only to assess which rule ultimately determines 

the cost to the end~user of bank services, but also to understand each rule's effect on the 

broader economy. 

Economic assessments are made that much harder because the public discourse tends to 

be about macroeconomics, typically focusing on the impact to overall GOP or employment, 

or one of abstract financial theory. This macroeconomic focus leads to muddled results, 

because while it may be possible to estimate the initial economic impact of a new rule, 

there is almost always a policy response that can offset much of the aggregate effects that 

are visible in the macroeconomic data. The availability of these offsets transforms the 

public dialogue into a discussion of the ability of policy to offset the aggregate effects of 

regulation, rather than a discussion of the cost of each new rule itself or of who bears the 

cost. 

A way to better understand the impact of new bank regulation is to focus on the 

microeconomic impact of the new rules within the economy, rather than across the 

economy as a whole. Looking at regulation from a microeconomic perspective shows that 

the cumulative impact of the new rules is more straightforward than the current public 

discourse might suggest. 

In practice, the microeconomic cost of regulation is determined by two factors: the size of 

the regulatory burden and the degree to which less-regulated alternatives are accessible. 

As a result, consumers and businesses that have ready access to alternative sources of 

finance are less likely to pay the incremental tax that regulation imposes. Conversely, 

consumers and businesses without access to effective alternatives to bank lending are 

more likely to pay. This is particularly true in cases where the new rules single out certain 

activities as especially concerning and impose further taxes, whether in the form of higher 

capital charges, more stringent regulatory supervision or activity~specific legal and 

regulatory costs and restrictions. 

While there is some added subtlety to the results of our analysis, we find in general that 

low-income consumers and small businesses- which generally have fewer or less 

' See Append1x A for a hst of new rules and regulat1ons Imposed smce the cns1s. 

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effective alternatives to bank credit- have paid the largest price for increased bank 

regulation. For example, for a near~minimum wage worker who has maintained some 

access to bank credit {and it is important to note that many have not in the wake of the 

financial crisis), the added annual interest expenses associated with a typical level of debt 

would be roughly equivalent to one week's wages. For small and mid-sized businesses the 

damage from increased bank regulation is even greater: their funding costs have increased 

175 basis points (bp) more than those of their larger peers, when measured against the 

pre-crisis period. That funding cost differential is enough to seriously damage the ability of 

smaller firms to compete with their larger competitors. This fact has become all too evident 

in the economic statistics and is already changing the shape of American business, as 

small and mid-sized firms, the historic engines of US job creation, shrink and sometimes 

disappear, displaced by large corporations. 

The key to assessing the impact of bank regulation within the economy is examining how 

its effects differ across markets. Two factors are at play. The first is the importance of bank 

intermediation in any particular market segment, which can be seen in the degree to which 

consumers and businesses can substitute away from banks for their financing needs. We 

term this 'banking intensity.' The second is the extent to which various bank activities have 

been affected by new capital charges, other regulations or heightened judicial and 

regulatory scrutiny. 

Exhibit 1 shows the results of the analysis we have developed for measuring these factors 

across 12 key lending markets.2 This is a qualitative analysis designed to capture the 

importance of banks to each market, the availability of alternative sources of finance and 

the impact of changes in regulation since 2008. 

We look first at the 'banking intensity' of different credit categories, assessing the extent of 

banks' participation- and the availability of potential substitutes- in both the origination of 

credit and the holding of credit risk on banks' balance sheets. To do this we use a simple 

scale, assigning a zero to markets that have robust alternative sources of credit, or to those 

where credit is largely held off banks' balance sheets; one point to markets where banks 

dominate in either or both origination and credit retention; and a half point to markets 

where origination and risk retention are split between banks and other providers. 

Next, we evaluate the degree and extent to which regulatory change has affected each 

market, adding an incremental half point if bank lending is affected in either of two ways: 

Capital costs are effectively higher due to increases in direct capital charges, 

higher riskMretention requirements or other legal or regulatory restrictions. 

Examples include the Basel Ill treatment of mortgages through operational risk 

and the Federal Reserve's treatment of unfunded commitments in CCAR {the 

annual Comprehensive Capital Analysis and Review) and its supplementary 

leverage ratio rule. 

Credit exposures have effectively been brought back on banks' balance sheets as 

banks face the imposition and enforcement of 'special representations and 

warranties,' along with greater legal risk. Mortgage settlements are the prime 

example. 

~We focus on 12 markets, wh1ch together account for roughly $20trn of the total $27trn 1n non-financ1a!, norr 

government debt outstand1ng m the US. accord111g to the Federal Reserve. 

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We aggregate scores on these three measures to derive an estimate of the total exposure 

of each market to regulatory change. Markets with two points are most affected; markets 

with zero points are least affected. 

Exhibit 1: Assessment of banking intensity and regulatory changes across key lending 

markets 

Near·andsub-primecredltnard 

Prime credit card 

Homeaquitv 

Jumbo mortgage 

Sm~llunratedcorporate loan 

ClassScommcrei3lrca!esllltelCRE) 

Conlormmgmortgage 

Madrumunratedcorporateloan 

largeinvestmuntgmdecorporate 

LMgehlghyieldoorporate 

Aunsmenlofhankinglnloosityandregutatorychanga 

(AlRelianceonbanks {B)Highflreffflctive 

fororlgin/ltionandlor ~>apital~>harges 

holding 10. 0.5, 11 (0 or 0.5) 

{ClSpocialrepsand 

wananllfll or hlghet R;mking (A+B•CJ 

scrutiny(OorO.Sl 

Sowce Goldman Sachs Global investment Resemch 

Our next step is to identify changes in lending rates, shown in Exhibit 2. We compare the 

prevailing interest rate in each category in 2013 against the average over 2000-2007, which 

we use as a non-crisis base!ine.3 To adjust for the overall level of interest rates across loan 

maturities, we use the relevant non-bank benchmark rates for each activity, namely US 

Treasuries of differing maturities. The relevant benchmarks and the proxies we use for 

each category of activity are laid out in Appendix B. 

:>These are preva1lmg market rates. not speCifiC to any type of lender. Because we focus on relative pncmg, not 

absolute costs, our results are largely msens1tJVe to the cho1ce of baseline tm1e penod, 

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Exhibit 2: lending rates have risen significantly for most markets compared to the 2000~ 

2007 average 

prevailing !ending rates, expressed as spreads over applicable benchmark 

Form of lending Price {spread over applicable pricing benchmark) 

Loan/borrower type 2000.200712008-2010 1 2013 13 vs. pte•'OS (bp) 

Credit card 10.6% 13.2% 12.8% 224bp 

Higher FICO 9.6% 10.8% 11.6% 199bp 

lower FICO 10.3% 13.3% 13YY" 280bp 

Residential mortgage 

Jumbo 1.7% 3.0% 2.1% 45bp 

Conforming 1.7% 1.9% 1.8% 14bp 

FHA/VA 1.8% 2.1% 1.6% -24bp 

Sub-prime .. 

Auto 3.4% 4.3% 3.3% ·17bp 

Home equity 2.7% 4.5% 3.8% 102 bp 

Commercia! real estate 

ClassA(higher-credit) 

ClassB(mid-credit) 1.7% 2.6% 2.3% 66bp 

SmaHerCRE 

Commercial&!ndustrial 

LargeiGcorporotes 1.5% 2.7''1<, 1.5% ~2 bp 

largeHYcorporates 5.5% 9.3% 4.7% -84bp 

Medium unrated corporate 3.5% 5.6% 4.1% 55bp 

Small unrated corporate 2.4% 3.3% 2.8% 41 bp 

Average 4.6% 6.1% 5.3% 68bp 

Source· Goldman Sachs Global Investment Research. See Appendix B for relevant prox1es and benchmarks 

Finally, we combine these analyses to assess the impact of the regulatory tax burden by 

plotting the assessment of regulatory change against the change in prevailing lending rates. 

Exhibit 3 shows the results, which are both large and uneven across different markets. The 

markets that are most exposed to regulatory change have seen lending rates rise 

most significantly, while the markets that are least exposed- where strong non~bank 

alternatives exist- have seen lending spreads fall from the pre~crisis period. 

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Exhibit 3: Rates have risen most in the markets that are most exposed to regulatory change 

change in prevailing lending rates, compared to pre~crisis levels, plotted against our assessment of the degree of banking 

intensity and regulatory change in 12 key lending markets 

2 

. 

i 

! 

300 

iii~ 150 

lg; 

= v ~ ~ 

Sub·primeresidentia!mortgage 

Near-andsub·prunecreditcard • 

Prlmecreditcard. 

Homeequ1ty 

Medlumunratedcooporateloan H ClassBCRE{mld·cred•t+ 

,, .,!),. o~largelnvestmentgradecorpora!e i • FHANA mortgage 

Conforming mortgage .. 

oJumbomortgage 

Sma!!unratedcorporateloan 

c -sol l .large!liglly•e!dC<Jrporate 

""' ·100 1 

·150; 

0.0 

Degree of bunking intensity and regulatory change 

•Largebusmesscredil 

"Smallbusinesscredll 

•Consumercwdit 

•Cred•tfac•htywherapriclngdatalsNA 

,, 

Source. Goldman Sachs Global investment Research 

Ill. Lower-income consumers and small businesses are paying more 

~S_(l_resu!~!'~~~~(l_ll}~.-~.El~-lJ~Iation~~-~-~~~--~~ -~~ ~~ ~- --·~-~~---~~-~ 

As shown in Exhibits 1 through 3, different dynamics are playing out across the consumer 

and corporate lending markets, reflecting differing levels of regulatory scrutiny and 

degrees of banking intensity. But the overall conclusion is clear: consumers and businesses 

with few alternative sources of finance bear a disproportionate burden of the tax from 

increased bank regulation. 

This is true even in markets where bank regulation has changed lending dynamics for 

consumers of all income levels and commercial borrowers of all sizes. Consumers with 

savings or businesses with strong balance sheets can effectively act as their own 

alternative source of finance- i.e. they can choose to rely on their savings or reserves 

rather than borrow at excessively high rates. In contrast, consumers who lack a financial 

cushion have little choice but to pay the higher rates, or to cut spending. In either case, 

their overall consumption will be lower. 

Consumer lending markets 

First, consider the automobile loan market which has been largely untouched by 

regulatory reform and which therefore provides a useful baseline to assess whether factors 

other than regulation have affected lending or rates. Although a considerable share of the 

auto financing market is served by captive finance companies, which principally fund 

themselves in public markets through unsecured term debt and asset~backed securities, 

banks also play a direct role in auto financing. We estimate that banks originate and hold 

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on their balance sheets roughly one~third of the total market, and accordingly assign this 

market a banking~intensity score of 0.5. With no significant post~crisis regulatory 

intervention, we do not add any incremental points. Looking at the cost of direct bank 

financing, which is a reasonable proxy for the overall market, we see that spreads over the 

benchmark have narrowed by 17bp against the pre-crisis level, making auto loans one of 

the few consumer markets where funding is less expensive today than prior to the crisis. 

Second, ln clear contrast, consider the credit card market, where new regulations affect 

consumers across the board, and where lower~income borrowers are hurt most. Credit 

card debt is originated almost entirely by banks, with roughly 70'% of it held on banks' 

balance sheets, giving a banking intensity score of one to each of the three segments we 

look at (prime, near~prime and sub~prime). All three categories bear higher effective capital 

charges, for which we assign an additional half point; the near-prime and sub-prime 

markets have also felt the effects of heightened legal and regulatory scrutiny, for which we 

assign a further half point. This makes near- and sub-prime credit cards, with a total score 

of two points, the most affected of the 12 lending markets we discuss in this paper. 

Credit card pricing and availability have been dramatically affected both by the Credit 

CARD Act of 2009 (the CARD Act) and, more recently, by scrutiny from the new Consumer 

Financial Protection Bureau. The CARD Act has notably reduced the availability of credit 

cards for lower~income and younger borrowers. It eliminated banks' ability to reprice credit 

to reflect actual delinquency. In the past, if borrowers missed payments, card companies 

could raise their rates to reflect the higher risk from the actual delinquency. Today, card 

companies are prevented from doing so, meaning that they need to charge higher rates 

from the outset in order to compensate for the potential risk that a borrower might miss a 

payment at some time in the future. 

Exhibit 2 above illustrates the dynamics of credit card pricing in recent years, showing that 

lower~income borrowers have been most affected. Rates have risen significantly with 

spreads now at !east 200bp wider than the pre-crisis period, even for prime borrowers. And 

the differential by FICO scores (and implicitly by income)4 has widened most significantly, 

as spreads for borrowers with low FICO scores have expanded 280bp. 

However, a focus on pricing obscures the fact that many would-be borrowers have been 

priced out of the credit card market entirely. Outstanding credit card debt is 14% !ower than 

the pre-crisis peak, with the data strongly suggesting that !ower-income borrowers have 

been most affected. As Exhibits 4 and 5 below show, the distribution of FICO scores has 

been stable since 2005, but the availability of credit cards has shifted dramatically, with 

upper-income households now dominating the market. In 2005, 26% of the credit extended 

went to sub-prime or deep subwprime credit (FICO scores of 660 or below); this figure is just 

11% today. The market is currently dominated by 'super-prime' borrowers (FICO scores of 

roughly 720-850), who account for 58% of the credit outstanding, up from 40% in 2005. 

4 Although FICO scores do not translate d1rect!y into income, a paper from the Federal Reserve Banks of Boston and 

Kansas C1ty suggests that sub--pnme end deep sub-pnme card holders have Incomes below $50.000, while superpnme card holders have 1ncomes above $75,000. Sec Effects of Credrt Scores on Coflsumer Payment Cho1ce, 

Fum1ko Hayash1 and Joanna Stavms, Federal Reserve Bank of Kansas C1ty Research Worktng Paper RWP 12-03, 

February 2012 

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Exhibit 4: The distribution of FICO scores across US 

consumers has been relatively stable ... 

Exhibit 5: ... but the distribution of credit cards is shifting 

towards prime borrowers 

100% 

90% 

80% 

j 70% 

~ 0 60% 

~ 

50% 

40% 

" ~ 30% 

20% 

10% 

0% 

100% 

90% 

.§ 

l 80% 

~ 70% 

~ 

1 60% 

~ 50% 

i 40% 

t 30% ) 20% 

10% 

0% 

2005 2007 2009 2011 2013 

11 Super·prime Iii! Prime M Sub-prime Deep sub-pnme 

Many low-income borrowers who have been priced out of the credit card market entirely 

have turned to alternative sources of credit- but in this case their alternatives are payday 

lenders, pawnshops and other non-bank sources where borrowing costs are typically far 

higher. Data from US Census Bureau surveys indicate that the universe of borrowers from 

non-bank sources has expanded significantly during the downturn. The demographic 

composition of borrowers also changed, becoming increasingly older, non-minority and 

more educated, and with more married couples and higher-income households relying on 

non-bank credit as we!l.5 Forty-five percent of recent users indicated in the survey that they 

had turned to non-bank credit to meet basic living expenses. These borrowers may be able 

to maintain their previous levels of consumption, but at a high cost: interest rates from 

non-bank lenders tend to have annual percentage rates (APRs) that run to three digits, 

rather than the 15%-30% rates typically seen with credit cards. 

Third, consider the conforming mortgage market, where rates have risen and !ow-income 

borrowers may be unable to obtain credit as a result of new rules and regulations. 

Mortgage origination is split between banks and non-bank lenders, and mortgages are held 

both on banks' balance sheets and by non-bank investors. Accordingly, we assign a 

banking intensity score of 0.5. Mortgages are also now subject to heightened scrutiny in 

several forms: new rules on 'qualified mortgages' and higher risk-retention requirements 

for non-qualifying mortgages; heightened repurchase risk; and stricter regulatory scrutiny 

of pre-crisis underwriting practices. For these factors, we assign another half point. 

~See the 2011 FDIC National Sutvoy of Unbanked and Underbankf.ld Households, 

Census Bureau 1n conjunction w1th the FDIC. 

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Overall, spreads for conforming mortgages have expanded 14bp since before the crisis. 

But this is not an across-the~board increase. Exhibit 6 shows the pricing spread between 

high-FICO mortgages and low-FICO mortgages. Both are conforming, governmentguaranteed mortgages, meaning that there is no credit risk to the lender. Nonetheless, 

banks charge dramatically different rates for borrowers of different credit quality. Prior to 

2008, a borrower with a FICO score of 620 paid roughly 3.5% {or 21bp in absolute terms) 

more than a borrower with a score of 800. Today, that differential is as much as 8.7% (or 

39bp), This effectively prices many lower-credit borrowers out of the conforming mortgage 

market entirely. 

Exhibit 6: The differential between high- and low-FICO mortgage borrowing has widened, 

even for government-guaranteed loans 

pricing spread by borrower's FICO score over an 800 FICO mortgage loan 

10% 

1i 

3 9% 

. 

~ 8% 

tE~ "' 7% 

~ 6% 

g 5% 

G)~ .,_ 

~ 4% 

;; 3% 

~ 

f 2% 

~ 

" 1% 

g> 

" ;t 0% 

-1% 

-2014 -2006 

--=rn--~rnmm=••m••~•~ 

FICO score of borrower 

Source· eMBS, Goldman Sachs Global investment Research 

In fact the sub-prime mortgage market has dried up almost completely since 2008, with 

just $4bn originated in each of the last five years, compared to $625bn in the peak year of 

2005. Banks face higher risk retention requirements and capital charges for these loans, 

along with heightened regulatory scrutiny around pre~crisis lending practices and 

repurchase risk. As a result, many banks are no longer willing to participate in this market 

or will only do so at rates that are prohibitively expensive for borrowers. 

The jumbo mortgage market also faces heightened regulatory scrutiny, particularly 

stricter standards for lenders in assessing borrowers' ability to repay. Some lenders have 

raised down payment requirements and others have pulled back from the business. 

Originations today are roughly half the 2000-2007 annual average, and spreads have 

expanded 45bp. Jumbo mortgages are an important segment of the market in states with 

higher average home prices. 6 

~States where more than 15% of houses are valued at more than $500,000 •ndude Cahforma, Conf'ectlcut Hawa11, 

Maryland, Massachusetts, New Jersey, New York and V1rg1n1a. 

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The related home equity market also illustrates these dynamics well. Banks are 

responsible for virtually all origination of home equity loans and hold roughly 85% of the 

risk on their balance sheets; we give this market one point on the banking intensity scale. 

Home equity also receives an incremental half point for special regulatory scrutiny, in the 

form of higher risk weights through operational risk and CCAR, and thus effectively higher 

capital charges, along with higher risk-retention requirements. Together, with a lack of 

MBS investor appetite, these factors have pushed pricing sharply higher (with spreads 

expanding 102bp relative to the pre-crisis average) and originations dramatically lower 

{roughly 20% of the pre-crisis annual average}. 

Bank regulation has had the effect of expanding credit availability in one segment of the 

market: mortgages guaranteed by the Federal Housing Administration (FHA) and Veterans 

Affairs Department (VA). FHA/VA loans are offered on flexible terms (recently made more 

flexible} to low- or no-credit borrowers (FHA) or to veterans (VA), and their guaranteed 

status gives them no repayment risk. Effectively this market has become a governmentguaranteed substitute for the private sub-prime market. Not surprisingly, origination, which 

largely occurs within banks, has soared and is now more than two and a half times the precrisis average. Pricing has also improved, with spreads 24bp narrower than pre·20081evels. 

These loans make up less than 20% of the total mortgage market, but they illustrate the 

way in which policy interventions have shifted the allocation of credit. 

Exhibit 7 shows the changes in origination activity in different segments of the mortgage 

market. 

Exhibit 7: FHA/VA loans supplant sub·prime mortgages 

change in origination ($bn) 

Corporate funding markets 

Switching our focus to commercial lending, we see a clear differentiation between the 

larger firms that have ample access to alternative sources of funding, often at attractive 

rates, and the small and mid-sized firms that are much more reliant on banks and, 

consequently, are paying more for credit today. 

Consider commercial real estate (CRE) !ending. This is a highly bank-intensive business, 

to which we assign one point, along with a further half point for higher capital 

requirements. The volume of debt outstanding is down by more than 20% in both the Class 

B (non-super-prime commercial real estate) and smaller CRE markets, while spreads for the 

Class 8 market have widened by 66bp, suggesting that even those borrowers who can get 

credit are paying notably more. 

Also observe the sharp disconnect by size within commercial and industrial (C&I) lending. 

At one end of the spectrum are the smaller unrated corporate loans. Because banks 

originate 100% of this market and hold 100% of the risk on their balance sheet, we give this 

market one point for banking intensity. The market gains another half point for the impact 

of the Base! Ill leverage ratio's treatment of unfunded commitments. Credit is still available, 

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with the total debt outstanding today 6% higher than the pre~crisis peak, but spreads have 

expanded by 41 bp. This suggests that smaller unrated corporates continue to borrow from 

banks because they lack effective alternatives, but that they are paying considerably more 

for credit today. 

The picture is slightly different in the mid~sized unrated corporate loan market. We 

assign a half point for banking intensity, given that while banks still originate close to 100% 

of these loans, the growing role of alternative providers from the asset management 

industry has driven the share of risk held on banks' balance sheets to just 19% today, down 

from nearly 50% prior to the crisis. We also assign an incremental half point for regulatory 

changes in the market, particularly CCAR treatment and new limits on leveraged lending 

imposed in 2013. Bank pricing in the mid~sized corporate market has expanded by 55bp, 

suggesting again that corporales with few alternatives to banks are paying notably more 

for credit today. 

At the other end of the spectrum are the large corporations that can borrow in public debt 

markets- both investment grade II G) and high yield IHY). Banks do not play a role in 

originating !G or HY debt, other than in underwriting, and hold less than 5% of the total 

market risk on their balance sheets. Not surprisingly, we assign zero points for such low 

banking intensity. We also do not assign incremental points for special regulatory or 

judicial scrutiny, because these markets have been largely unaffected by the regulatory 

changes aimed at banks. 

Large IG and HY corp orates today have access to funding at rates that are considerably 

more attractive than prior to the crisis. In fact, large high yield corporate debt shows the 

largest improvement in funding costs across the 12 markets we assess (with spreads 84bp 

narrower than before the crisis). Lower funding costs have not surprisingly attracted a 

broader range of issuers in the wake of the crisis, with some firms that had previously been 

reliant on bank debt shifting their funding mix towards bonds, new entrants joining the 

market and in some cases companies issuing public debt to pay down bank borrowings. 

Private placements have also provided an important source of financing for some larger 

corporates. However, it is important to note that public debt issuance itself carries an 

additional regulatory and compliance burden, meaning that it is not available for all firms. 

Here too, size is a key factor in determining whether firms can access the lower borrowing 

rates that bond markets now offer, 

The strength of the public debt markets can be seen in numerous ways. Yields are at 

historic lows across the credit spectrum, while issuance is reaching a!l~time highs in both 

the IG and the HY markets, Firms are financing on very attractive terms, including 

'covenant-lite' and payment-in~kind (PIK) deals and dividend recapitalizations. New and 

infrequent issuers are raising funds at rates that would have been unavailable just a few 

years ago. Strong inflows into these markets reflect investors' demand for yield and market 

resiliency, as well as the entrance of non~traditionallenders such as hedge funds and 

insurance companies, who are beginning to disintermediate banks. 

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To put our analysis into a broader economic context, we look at the impact of lower 

availability and higher cost of credit across both consumer and corporate borrowers. We 

begin with consumers by examining the effects of new bank regulation on a household 

with the US median annual income of $50,000. We estimate that the higher payments 

associated with the types of mortgages and credit card debt this household would 

consume, offset by lower auto loan payments, equates to an incremental $200 in interest 

expenses each year.7 

A household in the 20th-40th percentile by income, which earns $38,000 on average, fares 

worse. We assume it does have access to credit but note that more than 40% of these 

households do not. lfthe household does have credit, it may pay an incremental $300 each 

year for its mortgage and credit card debt, even considering the offsetting reduction in auto 

payments, This means that the relative impact is almost twice as large as it is for the 

median household: 80bp of annual income compared to 40bp. For a minimum-wage earner 

working eight hours a day, $300 is a full week's worth of work. 

Turning to corporates, small businesses8 tend to fund themselves through a mixture of 

credit card debt, bank loans and bank lines of credit. Credit cards are a principal source of 

funding tor most small businesses, given that many have limited access to bank finance. 

Therefore these firms are hurt by higher credit card rates and lower availability of credit, as 

well as by higher borrowing rates for bank loans and lines of credit. 

The actual costs of higher credit for small businesses are difficult to tabulate, given the lack 

of detailed data on the distribution of small firms' sources of borrowing. However, cost 

itself is not the key concern- the principal issue is small firms' ability to compete with 

larger businesses. In fact, some of the most striking macroeconomic implications of our 

analysis stem from the disparity between funding costs for small and large businesses. 

Smaller firms are considered the key driver of job creation, particularly when assessed by 

the number of local employees per dollar of revenue, given that they are typically more 

labor*intensive than large firms. Exhibit 8 illustrates the fact that small firms have lagged 

large firms in job creation since the start of the post*crisis economic recovery, which is a 

break from the historical norm and may reflect the competitive funding dynamics. 

'Relying on Census Bureau data, we look at the median characteristics of a US household of three people. This 

household has annual income of $50.000 and debt outstanding of $130.500. We use the med1an levels of household 

debt outstanding, SPeC1f1cally home debt of $117,000, credit card debt of $3,500 and an auto loan of $10,000). We 

apply the relevant Increase in spreads {mortgage + 14bp, credit card + 199bp, and auto loan -17bp) to each category 

to 1dent1fy the mcreased Interest expenses. 

s The US has a total of 28 million sma!l bus1nesses, of which roughly 23 miUion are owner/operator businesses; the 

remammg 5 mii!Jon have at least one employee in add1t1on to the owner/operator (termed 'employer f1rms'). 

Accordmg to the US Census Bureau, the overwhelmmg maJOrity l99.7%l of employer firms 111 the US have fewer 

than 500 employees. These 5 mil!!on 'small' busn:esses collectively employ approx1mately 55 m1lhon people and 

have an annual paymll of $2.2 tnlllon. 

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Exhibit 8: Job creation for small firms is lagging in this recovery, in a break from the 

historical pattern 

year-on-year net change in employment 

6% 

4% 

2% 

0% 

-2% 

-6% 

-8% 

-10% """'~-Net employment growth at firms with <500 employees 

-12% -Net employment growth at firms with 500+ employees 

Source Goldman Sachs Global Investment Research, Bureau of Labor StatiSI!CS 

These competitive dynamics are even more apparent in the divergence between the 

Institute for Supply Management's (ISM) purchasing managers' index, which measures the 

overall health of large firms based on five indicators, 9 and the small-firm equivalent from 

the National Federation of Independent Businesses {NFIB). 10 Before the crisis, these two 

indices tracked quite closely, but since then the large-firm ISM has indicated strong growth 

and a fairly normal cyclical recovery, while the small-firm index indicates that smaller firms 

have remained in recession. See Exhibit 9. 

A similar demonstration of the way in which large firms have fared better than their 

smaller counterparts during an economic recovery that has significantly lagged historic 

norms is the performance of revenues for S&P 500 non-financial firms. These have actually 

been at the top end of the historical range for a cyclical recovery, suggesting that large 

firms have taken significant market share from small and midwsized firms. See Exhibit 10. 

'

1 The ISM's monthly composite mdex 1s based on live md1cators: new orders, productiOn, employment, supplier 

delivenes and mventones 

'

0 Indicators underlymg the NFIB survey are plans to mcrease employment, cap1tal outlays and 1nventones; 

expectations for the econom1c outlook, sales, cred:t cond1t1ons and expans1on; ard current mventory. JOb open•ngs 

and earnmgs trends 

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Exhibit 9: Optimism is rising among large firms, but still lagging among small firms 

shaded areas indicate recessionary periods 

Exhibit 10: S&P 500 non-financials' sales are at the top end of the historical range 

cumulative% change in sales from end of recession 

50 ' 

~ 25 

~ 

~ 

i 

;; 

E 

~ 

-;!. (25) 

{50) 

-12 -10 -8 -6 -4 -2 10 12 14 16 18 20 22 24 

Quarters from recession end 

Source Goldman Sachs Global Investment f!esearch 

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Banks and their shareholders pay too 

As with any form of tax, the cost is ultimately borne by the targeted firms as well as by 

their customers. So although our analysis has focused on the ov.erall economic impact, it is 

important to note that banks themselves have also paid the cost of increased regulation. 

There are direct costs, including compliance and back~office operations that have expanded 

significantly to address new rules, including the Vo!cker Rule and derivatives clearing. Ex~ 

post scrutiny into pre~crisis mortgage practices, among other issues, has led five ofthe six 

largest US banks to provision nearly $80bn in aggregate legal reserves since 2010, 

according to company filings. 

While not the focus of our study, we note that bank shareholders have also paid a price for 

increased regulation. Between late 2008 and the end of 2009, the six largest US banks 

raised nearly $170bn in fresh equity, diluting existing shareholders by at least 5% and as 

much as 82% in the most extreme case (see Exhibit 11 ). The additional capital has 

contributed to a sharp fall in those banks' return on tangible equity {RoE), which is now 

10% on average, against an average of 31% for the 2000~2007 period. Lower RoEs have in 

turn reduced bank equity valuations and thus the value of bank shares. We estimate that 

the observed decline in the six largest US banks' ROE over this period has reduced the 

value of their shares by more than 20%. See Exhibit 12. 

Exhibit 11: Shareholders of the six largest US banks have 

been significantly diluted 

Exhibit 12: The average price4o-tangible book multiple 

for the six largest US banks has contracted by more than 

common equity raised by six largest US banks 2008~2009 20% vs. pre-crisis levels 

BankofAmenca 

Goldman Sachs 

Jf>Mo<gan 

MorganS1<1nley 

WellsFaf\J() 

presentat,ons 

received 

{Sbnl 

t.-'ommon ~>>qwty shares from 

Common 

equity 

raised($bn) 

Common equity 

raisl!das%of 

TARPt._mds 

1(14% 

Commnn 

Bank of Ameru;:a figures Include funds .t rece1vod afrer 1ts 

''""'"'w" .of Nfem'!L";ch. 

Goldman Sachs Global Investment Research 

9% 11% 13% 

2013 ROTCE 

Source. Goldman Sachs Global Investment Research. f actSe! 

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It is important to note that we do not attempt to analyze whether the new lending rates are 

better or worse characterizations of risk than the pre-crisis rates. Our calculations simply 

show the degree to which new rules and regulations have affected lending and where 

those effects have been most acute within the economy. The normative conclusion that can 

be drawn from the role of market substitutability is that markets and regulators differ 

meaningfully in their assessment of risk. For example, the relative normalcy of auto 

lending, which is one of the bright points in the current economic cycle, suggests that the 

regulatory burden of new bank regulation bears much of the responsibility for changes in 

pricing across the rest of the consumer lending categories we assess. Increased bank 

regulation has had real economic impacts and may be a significant contributing factor to 

the ongoing sluggishness of consumer spending. A similar story can be told in the 

commercial lending markets, where the economic recovery for the large firms that now 

enjoy a substantial funding advantage has been rapid and generally in line with previous 

economic cycles, while the small and mid-sized businesses that are more dependent on 

banks have lagged substantially. 

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Appendix A: Select rules and regulations applicable to US banks 

enacted since 2008 

Capital requirements and planning; liquidity restrictions; enhanced prudential 

standards 

Basel !II risk-based capital requirements and revisions to risk-weightings 

G-SIB capital surcharges and US-based SIFI capital surcharges 

Leverage ratio 

Comprehensive Capital Analysis and Review (CCAR}: capital plans, risk-based 

capital requirements, leverage constraints, annual stress tests (among other 

components} 

Net Stable Funding Ratio (NSFR) 

Liquidity Coverage Ratio (LCR) 

Resolution planning ('living wills') 

Supervisory guidance on leveraged lending activities 

Single-counterparty credit limits 

Consumer protection 

Credit CARD Act 

Durbin Amendment {interchange rule) 

Qualified Mortgage/Ability to Repay rule 

Securitization 

Credit risk retention requirements 

Due diligence analysis and disclosure requirements for asset-backed securities 

Structure and activity restrictions 

Vo!cker Rule restricting proprietary trading 

Regulation of over-theMcounter (OTC} derivatives activities, including (but not limited 

to): 

Goldman Sachs Global Investment Research 

Mandatory central clearing 

Trade execution (regulated platforms) 

Trade reporting to data repositories 

Margin requirements for uncleared derivatives 

Business conduct standards 

Registration of securities-based swap dealers and swap dealers 

Treatment of cross-border transactions 

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Exhibit 13: Summary of proxy used for each lending market and the relevant risk~free 

benchmark 

Goldman Sachs Global Investment Research 

Loan/borrower type 

Cred1tcard 

H1gher FICO 

Lowerf!CO 

Residential mortgage 

Conformmg 

FHANA 

Sub-prime 

Jumbo 

Auto 

Home equity 

ommercial re~l estate (CRE) 

C!assA(h!gher-<.:red!t) 

ClassB (mid-<.:reditl 

Sma!lerCRE 

ommercial & industria! 

Largemvestmentgradecorporate 

Largehighyieldcorporate 

Mediumunratodcorporate 

Small unrated corporate 

Key lending markets 

Prbx:y used 

Go!diplatinumcardAPRofferings 

SwndardcardAPRoffering 

Average GSE-eligible mortgage rate 

Average FHA-elig1hle mortgage rate 

Subprimepnv<Jte-labc!MBS 

Bankratfl-30yearloans 

Commercwl bank- new car loan 

Mid-pnce HELOC via bankrate.com 

Llfe msurance com. mortgages 

CMBS conduit com. mortgages 

DomestiC bank CRE loans 

1Boxx IG corporate bonds 

BAMUBarclays high-yield indkes 

S&P leveraged loan mdex 

Domest1c bank C&l loans 

Risk-free benchmark 

1-YearTreasury 

1-YearTreasury 

10-yearTreasury 

10-yearTreasury 

10-yea! Treasury 

10-yeurTreasury 

5-yearTreasury 

10-yearTreasury 

10-yearTreasury 

10-yearTreasury 

10-yearTreastlly 

Appllcab!eTreasury 111 

ApplicabteTreasury 111 

3-monthTreasury 

3-monthTreasury 

36 

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SteveStrongin 

1121?)3S7A/OG 

Amanda Hindlian 

1(212i902·191S 

KobySadan 

1{212)902-7009 

The Goldman Sachs Group, Inc. 

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Although recent economic data have generally begun to Improve, the pace of the postcrisis recovery has been far weaker than the historical pattern suggests it should be. We 

estimate that If the current recovery had followed the historical norm seen in US economic 

cycles since 1980, GOP growth since the end of the crisis in mid-2009 would be nearly nine 

percentage points higher today, and roughly five million more jobs would have been 

created over the course of the recovery. 

Macroeconomic factors have weighed heavily on post-crisis economic growth. These 

include demographic changes and housing and fiscal headwinds, which together account 

for roughly 75% of the weakness seen this recovery relative to the historical norm, 

according to our US Economics research team.1 However, looking at "the recovery" solely 

from the macroeconomic perspective overlooks the significant differences in how it has 

played out across various parts of the economy. The quality of the recovery has varied 

widely for large and small firms- and for the people who work for them- and perceptions 

of the strength of the recovery have tended to follow personal experience rather than the 

macroeconomic average. 

Specifically, when we look beneath the economy-wide numbers, we see that large 

corporations have performed well, generating strong revenue growth, rising employment 

and robust wage growth. Small firms, in contrast, have suffered low rates of business 

formation and tepid employment growth. Employees of small firms have also seen 

significantly weaker wage growth than employees of large firms have enjoyed. 

The two-speed economy is evident across a broad range of data.2 Revenues for the S&P 

500 (ex-financials) grew roughly 6% annually between 2009 and 2014, well above the 

average for the prior four recoveries, while small businesses haven't yet fully recovered 

from the recession. Survey data suggest that growth rates for small firms have only 

recently shown signs of converging toward the growth rates indicated by large firm 

surveys. 

Perhaps the simplest and most economically significant demonstration of the challenges 

facing smaller firms is that the number of these businesses actually declined over the five 

years from the start of the crisis- the only such decline since the data became available in 

the late 1970s. The result is an estimated 600,000 "missing" small firms, and six million 

jobs associated with these firms, as of 2012. Although it is unclear what percentage of 

these jobs were truly lost- as some might have been absorbed by large firms- this 

dynamic nevertheless represents a meaningful structural shift in the economy. 

Employment data tell a similar story. Available US Census Bureau data show that jobs at 

firms with more than 500 employees grew by roughly 42,000 per month between 2010 and 

2012, exceeding the best historical performance over the prior four recoveries. In contrast, 

jobs at smaller firms declined by roughly 700 per month over the same period, a sharp 

contrast to the average monthly growth of roughly 54,000 jobs over the prior four 

recoveries. While the US Census Bureau data is only available through 2012, it enables us 

to quantify the relative shift in the share of employment between large and small firms. 

Other data series- such as small business surveys, the US Bureau of Labor Statistics {BLS) 

1 The Goldman Sachs US Economics tenm has published extensively on the macroeconomic factors affecting the 

recovery. For example. see Hatzius et al. "'US Economics Analyst: Socking with Stronger." May 2014, Hatzius eta!, 

"US Econorwcs Analyst· More Cyclical than Secular," December 2013, Mende, "US Daily. Assessmg the Slowdown 

m Potent•al G1owth. ··November 2013. 

1: GIVen the Wide scope of ISSues we d1scuss 'throughout th1s paper, we rely on a range of data sources covenng 

d1ffermg twne penods dependmg on data ava1labtlity, wh1ch 1n some cases 15 l1m1ted. We use the longest-runn1ng 

data senes wherever poss1b!e. Throughout the paper we note the relevant 11meframe and data source. 

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firm employment dataset and the household employment survey of sole proprietorshipsindicate that there has not been a significant change in these patterns since 2012. 

Also significant is the gap that has developed in wage growth between large and small 

business establishments. Although wages (indexed to 1996 levels) at both large and small 

establishments increased nearly in tandem during the decade before the crisis, these two 

figures have since diverged and now reflect a gap of roughly 20 percentage points. This 

suggests that small businesses continue to struggle, and that their employees may be 

paying an ongoing price in the form of lost wages. 

While there may always be some debate about the complex and fingering nature of the 

effects of the crisis, particularly on business decisions, the most widely~cited and perhaps 

the most likely explanation for much of the split that we observe between the performance 

of large and small businesses is the cumulative impact of the new regulations and related 

policy actions that have been taken since the crisis.3 

As we discussed in our June 2014 paper, "Who pays for bank regulation?",4 new banking 

regulations have made bank credit both more expensive and less available. This affects 

small firms disproportionately because they largely lack alternative sources of finance, 

whereas large firms have been able to shift to less~expensive public market financing. 

While banking regulation has played a key role, regulation outside of banking has also 

raised the fixed costs of doing business. It is unclear whether these economy~wide 

regulations can explain the bifurcation between large and small firms, but regulation would 

typically have a disproportionate impact on the ability of small firms to compete, despite 

often subjecting larger firms to notable increases in direct regulatory scrutiny and higher 

absolute costs. The negative competitive affects for small firms arise because of the 

relatively fixed-cost nature of complying with regulations; large firms have a much larger 

volume of business over which to spread higher fixed regulatory costs than do small firms. 

And even when small firms are formally exempted from regulations, they may still feel the 

impact because they may effectively be required to meet what soon become de facto 

standards for the industry as a whole. 

Even as large firms experience a relatively robust recovery, they appear to be investing less 

than we would expect given their historically high profit margins, and investing with a bias 

toward shorteHerm projects; this dynamic may be playing out because large firms are 

facing less competition from smaller firms. Investments in intellectual property, for 

example, are tracking nearly five percentage points below even the low end of the 

historical experience and more than 20 percentage points below the historical average. 

Considered in isolation, the negative impacts of each of the rules imposed since the crisis 

may not be significant. Cumulatively, however, they have had a clear and meaningful 

impact on the relative competitiveness of small businesses. The question of whether this 

trade~off is acceptable is both a political and an economic judgment. Taken together, the 

reduced competitiveness of small firms and the changing investment decisions of larger 

ones are reshaping the competitive structure of the US economy in ways that are likely to 

reverberate well into the future, and in ways that any future evaluation of the aggregate 

effects of post~crisis regulations should consider. 

J See, for example, Koppl, "From Cns:s to Confidence· Macroeconomics after the Crash," December 2014; DuyganBump et al. "Financmg Constramts and Unemployment· Ev1dence from the Grear Recession," October 201<1 and 

Baker, Bloom and Dav1s, "Has Economic Policy Uncertainty Hampered the Recovery?," February 2012. 

"See http://www.goldmansachs.corn/our~thinkmg/public·policy/regulatory·reform/who-pays·for·bank-regulatlon,html 

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II. The recovE!ry ~C:lli ~~er:~_s_!~~~(Jnd uneven 

Although recent macroeconomic data have generally begun to improve, US economic 

activity since the 2008 financial crisis has lagged previous recoveries by a wide margin (see 

Exhibit 1 ). We estimate that if the current recovery had followed the historical norm seen in 

US economic cycles since 1980, growth in GDP since the end of the crisis in mid~2009 

would be nearly nine percentage points higher today than the 14% that has been recorded. 

A longer time horizon shows an even more dramatic underperformance: the current 

recovery lags the !ow end of the historical range of recoveries dating as far back as the late 

1940s (see Exhibit 2 for a historical list}. 

Exhibit 1; The recovery in real GOP lags historical recoveries 

Reflects recoveries between 1949 and 2014; growth in real GOP 

50 

40 

. 

g' 30 

~ 

.~ 20 .E 

. 

~ 

. 10 

" 

{10) 

lll!ll Range of previous ten recoveries 

.... _ ... Average of previous ten recoveries 

- Current recovery (Quarter 0 = 20 20091 

·4 ·2 10 12 14 16 18 20 22 

Quartets from recession end 

Source Bureau of [conorrHc AnalySIS fBE/\J, Goldman Sachs Global Investment flosearch 

May 1954 10 

April 1958 

February 1961 10 

November 1970 11 

March 1975 16 

July 1980 6 

November 1982 16 

March 1991 

November 2001 

June 2009 18 

Source· NatiOnal B"reau of Econom1c Research INBEA!. Goldman Sachs Global investment Resoarch 

Goldman Sachs G!oballnvestment Research 

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What can explain this anomalous weakness? Several macroeconomic factors have 

contributed, including demographic changes and housing and fiscal headwinds, which 

taken together account for roughly 75% of the weakness seen this recovery relative to the 

historical norm, according to our US Economics team. Yet to speak about "the recovery" 

overlooks the very different ways it is playing out across different parts of the economy. 

The recovery felt by large firms and the people who work for them is very different from 

the recovery felt by small firms and the people who work for them. We see this divergence 

across a wide range of indicators, as we discuss next.5 

Large firms outpace small firms in revenue growth 

Consider revenue growth since the end of the recession in mid-2009. Although the largest 

companies, the S&P 500 {excluding financials),t' saw their revenues decline significantly 

during the crisis, they have since experienced a recovery in revenue growth that outpaces 

the historical trend over the past 35 years. The revenues of these firms are 40% higher 

today than at the end of the recession; this figure is roughly seven percentage points above 

the average rebound seen at the same point in the prior recoveries since 1980 (see Exhibit 

3). Such strong revenue growth for the largest US companies helps to explain why the S&P 

500 index has reached all-time highs, despite the generally lackluster recovery. 

Using IRS data that is available over a shorter timeframe to examine a broader universe of 

large US firms- those with more than $50 million in annual revenue- we find that 

revenues grew 8% on a compounded annual basis between 2009 and 2011. Smaller firms 

in the same dataset fared poorly in comparison: those with less than $10 million in annual 

revenues enjoyed only 2% growth over the same timeframe. 

Exhibit 3: S&P 500 companies (ex~financials} have experienced historically robust revenue 

growth since the recession ended in 2009 

Reflects recoveries since 1980 (latest available data are as of 402014) 

. 

"' . 

c 

1i 

~ 

·; 

:; 

E 

~ 

-f. 

60 

50 

40 

30 

20 

10 

110) 

-3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 Quarters from recession end 

Sourco· Compustat Goldman Sachs Global lnvestmunt Rosoarcn 

~In th1s paper we def:ne "small" bus1nesses as f1rms or establishments with fewer than 500 employees. Appendix 

A shows a d1fferent cut-off, defw:mg "srr.all" busmesses as those w1th fewer than 100 employees. The results of our 

analys1s are stmtlar regardless of whether we use 500 or 100 as the cut-oft 

n Consistent w1th Industry pract1ce that reflects the substar>tta! d1fferences 1n busmess models between fmanc1a! and 

non·f1nanc1al f1rms. we exclude fmanc1a!s from our analys1s of U1e S&P 500. 

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Surveys indicate that small firm growth has only recently shown 

signs of converging toward large firm growth 

The two key indices of business conditions also reflect a divergence in growth rates 

between large and small firms, as shown in Exhibit 4. The Institute for Supply Management 

(!SM) surveys measure business conditions indicative of current and future growth among 

larger firms, while the National Federation of Independent Business {NFI B) index measures 

similar metrics among smaller firms.? The ISM and the NFIB measures tracked closely from 

the late 1990s until the crisis, when they began to diverge significantly. While both 

measures have improved since the recession ended, the NF!B's assessments of conditions 

and its implied growth rates for smaller firms have only recently shown signs of 

converging toward those indicated by the ISM. 

Exhibit 4: NFIB and ISM surveys indicate that small firm growth has only recently shown 

signs of converging toward large firm growth 

2007 

Source. ISM NF-iB, NBtF( Golclman ::..'ad1s Gloi>al!nves/ment Reso:,l!cfl 

The number of small firms is declining 

2011 2(113 

i 80 

2015 

We see the challenging operating environment for small firms reflected in the decline in 

the number of these businesses since the start of the crisis. Available US Census Bureau 

data show that the number of small firms declined over the five years that followed the 

onset of the crisis- the first such occurrence since the data became available in 1977 {see 

Exhibit 5). 

1 The NF!B small business optimism mdex is based on a monthly survey of NflB member businesses, which are 

pnmanly f1rms w1th annual gross receipts of less than $10 million 1http1/www.nf,b.com/foundations/researchfoundatlon). The ISM surveys members of the ISM Bus mess Survey Committee and publishes monthly d1ffus1on 

md1ces related to both the manufactunng and the non-manufacturmg sectors; we rely here on the compoSite readmg 

denved by Haver Analyt1cs (http://www.lsm.ws/mdex.efm). 

44 

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Using a simple trend line, we estimate that if the number of firms with fewer than 500 

employees had grown in~line with the historical pattern seen from 1977 through 2007, 

there would have been roughly 600,000 more small businesses in 2012. This measure of 

"missing" small businesses is nearly five times the largest prior gap of 130,000 seen in 

1982. Historically, small businesses have employed an average of 10 people on a weighted 

basis. This suggests that the shortfall of roughly 600,000 small businesses might account 

for about six million associated small business jobs in 2012, although it is unclear whether 

these jobs were truly lost, since some might have shifted to large businesses. 

Exhibit 5: The number of small firms declined over the five years from the onset of the 

crisis 

Data available from 1977 to 2012 

5,500,000 

5.000,000 

~ 4,500,000 

• i 4,000,000 

z 

(19S2,-130,000"miss.ing"smaHbuslnesses) 

3,500,000 

3,000.000 

1977 1982 1987 1992 1997 2002 2007 2012 

Firmswith.::500employees 

Source.· US Census Bureau, Goldman Sachs Gioba! Investment Resedrch 

Employment at small firms is lagging substantially 

The problems facing small firms can also be seen in the employment data. Exhibit 6 shows 

US Census Bureau data measuring employment among firms of different sizes between 

the !ate 1970s and 2012. The cumulative change in employment at firms with fewer than 

500 employees had historically outpaced the comparable figure for larger firms; in recent 

years this trend has reversed, with the cumulative rise in employment at smaller firms 

running significantly below the cumulative increase at larger firms. 

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Exhibit 6: Cumulative change in employment at smaller firms has lagged the comparable 

figure for larger firms 

Data available from 1977 to 2012 

35,00MOO 

·~ E 3o,ooo,ooo 

" 

~ 

~ 25,000,000 

~ ~20,000,000; 

~ 

·=15.000,000 

f 

u 10,000,000 

j 

.:15,000,000 

~ 0 

197719791981199319851997198919911993199519971999 20012003 2005 2007 2009 2011 

~··,~firms with <500 employees -Firmswith500!employees 

Source. US Census Buroav, Goldman Sachs Global Investment Research 

Exhibit 7 uses the same US Census Bureau dataset to show the average monthly change in 

employment for the four prior recoveries since the early 1980s. Jobs at firms with more 

than 500 employees grew by roughly 42,000 per month between 2010 and 2012, exceeding 

the best historical performance over the prior four recoveries. In contrast, jobs at firms with 

fewer than 500 employees declined by nearly 700 per month over the same timeframe, 

whereas this figure had grown by roughly 54,000 per month on average over the prior four 

recoveries. 

Exhibit 7: Relative to history, monthly employment at smaller firms during the early years 

of the recovery has lagged the comparable figure for larger firms 

Average monthly change in employment at firms by size; data available from 1977 to 2012 

1981-1983 

1983-1985 

1992-1994 

2002-2004 

2010·2012 

Average of prior four recoveries 

since the early 1980s 

-27,000 

146,000 

57,000 

42,000 

54,000 

Source US Census Bureat( Go!clman Sachs Global investment Researcn 

Goldman Sachs Global Investment Research 

-29,000 

32,000 

41,000 

-53,000 

42,000 

·2,000 

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The US Census Bureau data series we examine above is only available through 2012, but it 

allows us to quantify the relative shift in the share of employment between large and small 

firms. Other data series- such as small business surveys, the BLS employment dataset and 

the household employment survey of sole proprietorships- suggest that there has not 

been a meaningful change in these patterns since 2012. See Appendix B for more detail 

regarding differences in the BLS and US Census Bureau employment datasets. 

Sole proprietorships have also posted a weak recovery 

Sole proprietorships, which are not included in the small business data discussed above, 

play a key role in the economy. These businesses can act as a critical safety valve for 

unemployed workers. Given the severity of the recent recession, growth in this category 

should have been strong- but here too the data show that the recovery has been notably 

weak. 

The US Census Bureau counted nearly 23 million sole proprietorships in 2012, reflecting an 

increase of just 5% since the end of the recession; this is a fraction of the 15% increase over 

the comparable timeframe during the 2001 recovery. A longer~running and more frequently 

reported dataset from the BLS that tracks unincorporated self~employed workers {a subset 

of sole proprietorships) shows that growth in this category has run below even the low end 

of the historical experience since 1980: the number of unincorporated self~employed 

workers declined by 150,000 between 2010 and 2012, with a further decline of more than 

170,000 during the subsequent two years. This equates to a total reduction in 

unincorporated self~employed workers of 3% between 2010 and 2014, See Exhibits 8 and 9, 

Exhibit 8: Growth in unincorporated self~employed 

workers has been well below the historical post· 

recession trend 

Reflects recoveries between 1980 and 2014 

Vu .. lr<>m••-ulon•nd ' 

Source. BLS Current Population Survev, Go!dmar> Sachs Global lnvcsrmont 

1\esearr:h 

Goldman Sachs Global Investment Research 

Exhibit 9: Unincorporated self-employed workers are a 

shrinking part of the labor force 

Self~employed workers as a proportion of the total civilian 

labor force 

6.5% 

Source. BLS Current Populat10n Survov. Goldman Sachs Global Investment 

Rtl$Bd!Ch. 

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Wage growth lags at small establishments 

The wage data also highlight the divergent positions of small and large estabflshments.6 

Indexed to 1996 levels, wage growth at establishments with more than 500 employees 

outpaced wage growth at smaller establishments by a cumulative six percentage points 

during the 14 years from 1996 through 2009.9 However, over the subsequent five years, the 

gap expanded by an additional14 percentage points, more than twice the divergence seen 

from 1996 through 2009 in fewer than half as many years. 10 See Exhibit 10. 

Exhibit 10: Wage growth at large establishments has outpaced wage growth at small 

establishments 

Average weekly wages in the first quarter of each year, indexed to 1996 

120% 

60% 

$ 

~ 60% i 

~ 40% 2 

~ 

20% 

0% 

0H.I6 01-98 01-00 Ol-02 01-04 01·06 01·08 01-10 01·12 01-14 

-··"Establishmentswith-o500employeus -Estabhshmentswith500+employees 

Source. BLS. Goldman Sachs G!obai Investment Flesearch. 

8 While a smg!e busmess can have more than one establishment (which can be thought of as a swrefront), small 

f1rms typir.a!Jy have JUSt one. 

~Wages mdude bonuses, stock optiOns. severance pay, prOfit dJstnbut1ons. cash value of meals and Jodgmg, 11ps 

and other gratutt1es, and. m some states. employer contnbut!ons to certam deferred compensatiOn plans such as 

~Ol(k) plans 

·v AlthougM the data begm m 1990, our analysis begms 1n 1996 because of a reportmg anomaly in 1995. See 

Appendix 8 for the lui! t1me-se11es. 

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While there will likely always be debate about the complex and lingering nature of the 

effects of the crisis, perhaps the most plausible explanation for the post-crisis bifurcation 

between large and small firms is the cumulative impact of new regulations, for two 

principal reasons. 

First, by increasing capital requirements and imposing other restrictions on banks, new 

regulations have effectively increased the cost and reduced the availability of credit for 

small firms, which lack alternative sources of finance. 

Second, by tightening regulatory requirements across the broader economy {not just for 

banks), new regulations have raised the fixed cost of doing business. This is a hardship for 

all firms, and it is not clear whether these regulations can fully account for the bifurcation 

we see between small and large firms. Nonetheless, these non-bank regulations are 

particularly challenging for the smaller firms that lack a sufficiently large revenue base over 

which to amortize these higher fixed costs. 

Small firms are hurt most by higher bank borrowing costs 

Heightened regulation since the crisis has succeeded in increasing the safety and 

soundness of the banking system. But, as we discussed in our June 2014 paper, "Who pays 

for bank regulation?", new regulations have also effectively acted as a "tax" on banks, 

changing the relative prices of different activities, making some activities more expensive 

and others cheaper. The impact across bank customers is uneven: those customers who 

can find less expensive sources of financing turn to them, while those without alternatives 

are forced to bear the higher costs of the taxed activities or are unable to access credit. 

In our earlier paper, we reviewed the new regulatory landscape across a broad range of 

lending markets and looked at changes in lending rates, measured against a 2000~2007 precrisis baseline. We found the impact of new regulation to be striking: the markets most 

exposed to regulatory change, and in which there are few alternative providers of financing, 

have seen lending rates rise most significantly, while the markets least exposed- or where 

strong non-bank finance alternatives exist- have actually seen lending spreads fall from 

the pre-crisis period. See Exhibit 11. 

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Exhibit 11: lending rates have been affected by post~crisis banking regulation 

Prevailing lending rates, expressed as spreads over applicable benchmarks 

Loar\1 borrower tYpe 2000-2007 2008·2010 2014 14vs. pre-'08 

Cred1tcard 106% 132% 131% 249bp 

H1gherF!CO 96% 108% 116% 200 bp 

Lower FICO 103% 133% 131% 281 bp 

Residential mortgage 

Jumbo 17% 30% 20% 29bp 

Conforming 17% 19% 18% 9bp 

FHNVA 18% 2.1% -31bo 

Subpnma 

Homeeqwly 27% 45% 34% 65bp 

Commercial real estate 

ClassA(hlgher..credlt} 

ClassB(mld·cred•t) 17% 26% 21% 47bp. 

SmallerCRE 

Commercial&industnal 

LargeiGcorporates 15% 27% 13% -23bp 

LargeHYcorporates 93% 40% ·147bp 

Medlumunratedcorporate 35% 56% 45% 93bp 

Small unrated corporate 24% 33% 27% 31bp 

The tax from increased bank regulation falls disproportionately on the smaller businesses 

that have few alternative sources of finance, We see this in the muted recovery in bank 

lending to small businesses: outstanding commercial and industrial (C&1) loans for less 

than $1 million are still well below the peak 20081evel and are only 10% above the trough 

seen in 2012, In contrast, larger C&lloans outstanding {above $1 million) are more than 

25% higher than the peak in 2008, as Exhibit 12 shows. Moreover, the cost of the smallest 

C&lloans has risen by at least 10% from the pre~crisis average. The evidence suggests that 

smaller firms continue to borrow from banks- when they can get credit- because they lack 

effective alternative sources of finance, It also suggests that they are paying notably more 

for credit today; this weighs on their ability to compete with larger firms and to create new 

jobs. 

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Exhibit 12; Lending to small businesses has lagged during the current recovery 

C&lloans outstanding (202008 through 402014) 

130% 

«) 120% 

~ 

~ 110% 

.. 

~ 

.s: 100% 

.E 

. 

"' 90% . 

c 

~ 

u 

;f. 80% 

70% 

C&! Loans> $1MM 

-- ~C&Iloans<:$100K 

C&! loans $250K-$1MM 

--C&lloans <: $1MM 

~ C&lloans $100K-$250K 

Source. FDIC Quarterly Bankmg Profile, Gotdman Sachs Global tnvas!ment Aese,•rch 

In contrast, since the crisis, the largest firms have built up their cash reserves. Nonfinancial S&P 500 companies hold roughly $1.4 trillion in aggregate in cash and equivalents 

on their balance sheets, an increase of approximately 80% from the pre-crisis peak. This 

makes them less likely to require new external funding. 

When large firms do seek external funding, many have access to public debt markets, in 

which yields are near historical lows. However, it is important to note that public debt 

issuance itself carries regulatory and compliance obligations, making it too expensive for 

some firms, Here too size is a key factor in determining whether firms can access the lower 

borrowing rates that bond markets now offer- and the smallest firms often find these costs 

too great. 

Funding for new businesses has been particularly affected by new regulations. Their very 

nature as new firms makes it difficult for them to obtain funding in a credit~constrained 

environment. Typically they rely on bank loans and credit cards, along with savings from 

friends and family for initial funding. 

These lending channels have generally been constrained by post-crisis regulations, with 

higher prices and lower availability of credit. Credit card debt, for example, has been 

affected not only by stronger bank capital requirements, but also by the Credit CARD Act of 

2009 and greater oversight from the Consumer Financial Protection Bureau. Exhibit 11 

above illustrates the dynamics of credit card pricing in recent years: rates have risen 

significantly, with spreads now at least 200 basis points wider than the pre·crisis period, 

even for prime borrowers. Many would-be borrowers have been priced out of the market 

entirely: there are nearly 85 million fewer credit card accounts than at the peak in 2008, a 

reduction of more than 15%. 

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Regulatory costs create competitive disadvantages for small firms 

While we see the new regulations affecting banks as a key driver of the slow and uneven 

recovery, they are not the only factors. Regulations affecting many other areas of the 

economy, such as labor and healthcare, have raised the fixed costs of doing business for 

large and small firms alike- but the competitive consequences differ. 

Data from the US Government Accountability Office {GAO) show that the issuance of 

"major" rules has risen significantly in the wake of the crisis and has remained elevated 

since then. Roughly 575 major rules were issued at the federal level between 2008 and 

2014, some 45% more than the preceding seven-year period, and the share of major rules 

in the overall total has risen as well. See Exhibit 13. 

Exhibit 13: "Major" federal rules issued annually since 2001 

A "major rule" costs the US economy $100 million or more annually or results in adverse effects 

on factors such as competition, investment and employment 

Number of major rules issued {lHS) 12% 

100 , 

. > 10% . ~ .. 

. . 80 

~ 8% ~ , 

. ] 

g~ ,; 60 ~. 

6% 0. 

1 ;;\: 2 2 .. ~ 40 4% . ·~ . 

2 ~ 20 . 2% ~ 

l 0% 

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 

Source GAO, Goldman Sachs Global !nvvstmem Rest)i){Cfl 

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Regulation entails costs for both set-up and ongoing compliance. Many of these costs are 

"fixed,'' meaning that a firm must bear the cost regardless of its size. The consequences 

differ for large and small firms. Large firms typically bear far higher total costs, but smaller 

firms often bear far higher unit costs- meaning a higher cost per employee or per dollar of 

revenue. For example, the National Association of Manufacturers finds that regulatory 

costs for companies with fewer than 50 workers are 30% higher per employee than for 

large firms; in the manufacturing sector, the costs for small firms are more than twice as 

high per employee.11 

In effect, higher fixed costs of regulation mean that the government has created economies 

of scale in regulatory compliance, and that the economically optimal size of a company has 

generally risen. At a minimum, higher unit costs make small firms less competitive; at 

worst, they can operate as barriers to entry for new competitors across many sectors. 

Exempting smaller firms from regulation would not necessarily help them to compete 

more effectively in a highly regulated environment. Small firms may be subject to the 

standards that are imposed on larger firms on a de facto basis, even if not on a de jure 

basis. This is because regulatory standards for large firms often become the baseline for 

the industry as a whole, forcing small firms to comply as a precondition for doing business 

with large firms, regardless of whether small firms are officially covered by the regulation. 

This trend is fueled by the growing practice of enforcing regulations via third partiesholding firms responsible for the conduct of their clients, suppliers or distributors. For large 

firms, particularly consumer-facing ones, the potential reputational and legal risks of 

dealing with small firms that are subject to less stringent standards may more than 

outweigh other factors !ike cost savings or convenience. In effect small firms may avoid 

the government paperwork faced by large firms, but they are not always exempted from 

complying with similar standards, nor can they necessarily avoid the associated costs. 

'' See Cram and Cram, "The Cost of Federal Regulation to the US Economy, Manufactuni1g, and Smalf Business, " 

September 2014, 

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IV. Reduced competition from small firms appears to be affecting 

the investment decisions of firms 

The impact of the two·speed economy extends beyond the small firms themselves. The 

competitive disadvantages facing smaller firms appear to be driving larger firms to invest 

less, and in shorter-term projects, than has historically been the case. This outcome is likely 

to be to the long-term detriment of the US economy. 

Exhibit 14 shows investment in capital expenditures by non-financial S&P 500 companies 

over the prior 12-month period, measured against revenues. Capital expenditures as a 

proportion of revenues are only slightly lower than the historical average (by 10 basis 

points), but this figure is skewed by investments that reflect structural shifts in the energy 

industry, specifically in shale. After excluding energy, capital expenditures as a percentage 

of sales are more than 100 basis points below the average since the early 1990s. This figure 

is particularly surprising given these firms' historically robust net profit margins today. 

Analysis of a broader dataset suggests that the largest firms are not simply redirecting 

their funds elsewhere. As Exhibit 15 shows, the recovery in total investment across the US 

economy- including investment in plants, equipment and intellectual property (but 

excluding investments in the energy sector) 12 - is considerably weaker than in previous 

recoveries. 

Exhibit 14: Trailing 12·month capital expenditures as a 

percentage of S&P 500 revenues {excluding financials) 

are still below trend 

Exhibit 15: lackluster recovery in private fixed asset 

investment in the US (excluding oil and gas) 

Reflects recoveries between 1954 and 2013 

Rangeol~mormnereoovenes 

___ .Averageoipnorl\<r,erecovene• 

.100 -Curmn!rccovcry1Yeor0~2009) 

& 

~ 80 

.:1:60 < 

~ E40 • 

;I( ' ~0 ' 

Source BEA Go!dmon Sachs Global investment Research 1~1 7otal pnvate 

frxed asset IIWestment rncludes plant equrpment and mtei!ectual property. 

'

1 Pnvate non-resJdent1al1nvestment, excluding investments m 011 and gas; data based on the Bureau of Econom1c 

Analysis' nat1onal mcome and product account data. 

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The typical pattern in a slow economic recovery is that firms limit their more cyclical 

investing, such as Investments in equipment, and choose instead to dedicate resources to 

projects that are designed to benefit from an upturn over the longer term, such as capitalintensive plants. This cycle has bucked that trend. The upturn in equipment investment has 

been slightly better than the historical average of the prior nine recoveries since the mid1950s, as Exhibit 16 shows. At the same time, investment in plants has lagged and is 

trending well below the historical average over the same timeframe {again excluding oil 

and gas), as Exhibit 17 shows. 

Exhibit 16: The current recovery has seen an upturn in 

private equipment investment {excluding oil and gas) ... 

Reflects recoveries between 1954 and 2013 

Exhibit 17: ... while private plant investment (excluding 

oil and gas} has lagged significantly 

Reflects recoveries between 1954 and 2013 

] -~~- Averageofpnormnerewvu"es 

-current,er.ovmy(Year0~2009! 

Sourc<r B£A Goldman Sachs Global Investment Research Source BEA. Go/d.man Sachs Global investment Research 

What lies behind this atypical bias toward short-term investments On the form of 

equipment} and against longer-term investments (in the form of plants)? Regulation may 

be driving the shift, in an indirect way. 

A number of statements from CEOs of major US firms suggest that uncertainty around 

future regulation may be responsible for the reluctance to invest for the longer term. There 

also appears to be concern that regulation has become more results-oriented than processoriented, meaning that lf specific regulations fail to produce certain outcomes, they can 

and will be changed with retroactive effect. The result is lasting operational uncertainty for 

US businesses, manifested in a change in the time convexity of investment: investment 

goes to projects that pay off over the short term rather than the long term. 

Examples from two sectors help to illustrate this point. First, consider petrochemicals, 

which are used in everything from plastics to medicines to paint. Petrochemicals are 

energy-intensive, not only because they are derived from crude oil or natural gas, but also 

because their production requires energy. As the supply of US shale gas has risen, the cost 

of producing petrochemicals has declined dramatically, making long-term investments in 

the sector more attractive economically. 

Even so, many long-term investment projects in petrochemicals have been delayed or put 

on hold, as Exhibit 18 shows. 13 Environmental regulations have existed in the sector for 

years, suggesting that the current delays do not reflect newly heightened environmental 

regulatory concerns. A more likely explanation is that these delays reflect uncertainty 

around the future regulation of natural gas- which is the critical element to attractive longterm investments in the sector. 

13 See Strongm et al, "Unlockmg the Econom~c Potentta/ of North Amenca's Energy Resources," June 2014 

(http·/J'NWw.go!dmansachs.corn/our·thmkmg/our-conferences/north-amencal1-energy-summ1VUnlockmg-theeconomlc-potentlal-of-north-amencas.pdfl. 

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2016 2017 

2016 2018 

2015 2019 

2016 2017 

750 2H2016 Indefinite Hold 

400 2017 

330 2016 

Second, in contrast. consider the US paper industry. Paper manufacturing has been in 

decline since the early 1990s, reflecting the secular shift of newspapers, magazines and 

documents to digital format. The secular decline in demand and output was matched by 

underinvestment (and an aging capital stock) from the early 1990s until the late 2000s. 

Since then, however, the industry has seen a surprising trend relative to the underlying 

decline: paper output has risen, due largely to cheaper input costs, in particular shale gas. 

As a result, the US has gone from a net importer of paper products over the 2000s to a net 

exporter since 2009. In fact, the pace of growth in investments in plant, equipment and 

intellectual property in the paper sector is outpacing the historical trend seen for recoveries 

since 1960. This likely reflects the rapid payback period associated with paper investments. 

Even given ongoing regulatory uncertainty, these investments are economically viable 

because their payback is much quicker than that available in other natural~gas~consuming 

industries, 

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V. Conclusion 

Global Marke\S InStitute 

While perhaps not on a rule~by~rule basis, in the aggregate the cumulative effects of post· 

crisis regulations appear to have had a negative impact on the relative competitiveness of 

small businesses, reshaping the U.S. economy- and likely in ways that were unintended. 

Each new regulation was not meant to create negative outcomes: each was aimed instead 

at addressing other policy issues, such as ameliorating the risks of another financial crisis, 

protecting workers or providing greater access to healthcare. Whether the trade-offs 

created by the cumulative effects of new regulations are acceptable is both a political 

question and an economic one, but the issues we observe in this paper should be 

considered as part of any future evaluation of the aggregate effects of the new rules. 

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We define "small" businesses throughout this paper as firms or establishments with fewer 

than 500 employees. As we show in Exhibits 19, 20 and 21, using an alternative definition 

of ''small" businesses- those with fewer than 100 employees- yields similar conclusions 

to those we observe in the body of the paper. 

Exhibit 19: The number of firms with fewer than 100 employees declined over the five 

years from the onset of the crisis 

Data available from 1977 to 2012 

5,500,000 

5,000,000 

14,500,000; 

0 

j 

~ 4,000,000 

z 

3,500.000 

1982 1987 1992 

"Firmswith<100emptoyees 

Source: US Census Bureau, Goldman Sachs Global Investment llesearch 

Exhibit 20: Wage growth at establishments with more than 100 employees has outpaced 

wage growth at smaller establishments 

Average weekly wages in the first quarter of each year, Indexed to 1996 

100% 

01-02 01-10 

-Establishments with 100+ employees 

Source BL S, Goldman Sachs Global Investment Research 

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Exhibit 21: Cumulative change in employment at firms with fewer than 100 employees has 

lagged the comparable figure for larger firms 

Data available from 1977 through 2012 

40,000,000 

,;35,000,000 

l 

~30,000,000 

~ 

Ezs,ooo,ooo 

i 

~ 20,000,000 

~15,000,000 

~ 

110,000,000 

-5,000,000 

u 

1977 1!.179 1981198319851987\98919911993199519971999 20012003 2005 2007 2009 2011 

firmsw!tll<100emp!oyees -F~r~nswith100+emp!oyces 

Source· US Census Bureau, Goldman Sachs Giotlal Investment Research 

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We use the US Census Bureau's Longitudinal Business Database (LBD} in our analysis of 

firm employment. The LBO is based on a survey of US businesses with paid employees. 

The data are available annually from 1977 to 2012 {thus providing a long time series but 

failing to provide data after 2012}. The data show the number of firms in operation during 

each year, classified by number of employees. The LBO uses a "mean-sizing" approach. 

For example, a firm may have had five employees last year ("t-1 "}and 25 this year ("t"), or 

an average of 15 employees between the two years. The firm would thus be classified in 

the bucket of firms with "10-19" employees this year, from a bucket of "5-9" employees in 

the prior year. 

The BLS Business Employment Dynamics (BED) data series is an alternative measure of job 

growth at small businesses. However, the BLS BED data assess job growth by size class, 

rather than jobs within a given size class, and thus the data are not directly applicable to 

the question at hand, namely the relative shift in the share of employment between large 

and small firms. The BED data are based on a quarterly census of US businesses covered 

by state unemployment insurance programs. The data are then linked over time to provide 

a longitudinal hlstory. 14 The BED data are available quarterly from 1993 to 2014 {providing 

a shorter time series than the LBO but offering more recent data). 

The BED relies on a "dynamic-sizing" methodology, which allocates a firm's quarterly 

employment gain or loss to each respective size class in which the change occurred. Firms 

are initially assigned to a size class based on their employment in the previous quarter, and 

over-the-quarter employment changes are distributed to the appropriate size category 

when a size-class threshold has been crossed. For example, if a firm grows from three 

employees to 13 employees, the growth of 10 would be allocated as follows: size class 1-4 

employees would be credited with the growth of one employee (the growth from three to 

four), size class 5-9 employees would be credited with the growth of five employees (the 

growth from four to nine), and size class 10-19 employees would be credited with the 

growth of four employees (the growth from nine to 13).15 See Exhibits 22 and 23. 

Exhibit 22: Firms with more than 100 employees have 

added more jobs than small firms since the end of the 

recent crisis .. 

Exhibit 23: ... contributing to a wider gap in employment 

relative to history 

Cumulative employment on an annual basis since 1992 

Annual data available 1993-2013 

' ~ 14.000.000 

fn.oooooo 

! 1:.::::: 

J 5(!00,000 j 0000000 

Source 8/.S, Goldman Sachs Global investment Rt1search 

See "Emp!oyrnenl growth by Stze class frrm and establishment data," December 2011, 

{http·jfwww .bls.gov/opub/mlr/2011 (12/artl full.pdll 

"Employment dynam1cs: small and large firms over the bus1ness cycle,' March 2007, 

{httpJ/www.bls.gov/opub/mlr/2007/03/art3fuiLpdll. 

Goldman Sachs Global Investment Research 

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A final note: The wage data referenced in this paper come from the BLS Quarterly Census 

of Employment and Wages (QCEW). The data are available beginning in 1990; however, we 

begin our analysis in 1996 due to a significant data anomaly in 1995. Although we cannot 

be certain, the anomaly may arise because the data were previously reconstructed from an 

older classification system. As Exhibits 24 and 25 below show, beginning our analysis in 

1990 and excluding the anomaly in 1995 yields similar results to those we observe in our 

prior analysis, again whether we set the threshold for "small" businesses at 100 employees 

or at 500 employees. 16 

Exhibit 24: Wage growth at establishments with more 

than 100 employees has outpaced wage growth at 

smaller establishments during the current recovery 

Average weekly wages in the first quarter of each year, 

indexed to 1990 

Exhibit 25: Wage growth at establishments with more 

than 500 employees has outpaced wage growth at 

smaller establishments during the current recovery 

Average weekly wages in the first quarter of each year, 

indexed to 1990 

-r See the BLS QCE:VV for addttiOnal detat!: http://www.bls.gov/cew/datatoc.htm 

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The Goldman Sachs Group, Inc, 

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Although technological change is good for the economy over the long run, it isn't necessarily good for everyone, 

particularly in the short term. The economy as a whole benefits from the higher living standards that 

technological innovation generates. But for the people whose jobs are displaced by technology, the macro 

benefits are of little comfort. 

Occupations and industries follow a natural evolution. Early on, new job opportunities are plentiful and the work 

is often well-compensated. Over time, jobs become vulnerable to automation, outsourcing or falling wages (or 

some combination of the three). This process reflects the normal course of economic demand, not any changes 

in policy. As automation becomes cost-effective, people's economic role shifts from 'doing' the work to 

'organizing, coordinating and supervising' the increasingly complex resources and activities behind it. Today, 

the pace of this evolution is accelerating as measurement technologies and data~collection capabilities improve, 

putting more jobs at risk. 

The broader economy benefits if more people who are at risk of job displacement retrain and shift to new 

industries where their competitive advantages over machines offer better long-term economic prospects. But an 

investment analysis shows that while changing careers makes sense at the macro level, the decision is more 

complex from an individual's perspective, particularly since she must shoulder the burden of investing in human 

capital on her own. Often, waiting for even an unlikely job opening in her current occupation can be a superior 

choice to switching careers, because of the uncertainty involved. 

This dynamic has helped create a 'jobs gap'- the gap that often exists between the types of jobs that people 

want and the types of jobs that are available. Closing the jobs gap requires a new approach to risk-sharing, one 

that spreads the burden of investing in human capital more broadly. This risk-sharing approach should include a 

greater educational focus on social skills, creativity and judgment, not only STEM subjects; expanded incentives 

for corporate job training; standardized labor contracts; innovative financing structures to support investments 

in human capital and career transitions; !ower barriers to entry into certain professions; increased support for 

small-business creation; and regulation that supports the growth of the 'freelance economy.' 

Exhibit 1: As economic activity expands, technology doesn't eliminate the need for people- it changes their role 

Over time, people's principal economic role has evolved from physically 'doing' work to 'organizing, coordinating and 

supervising' complex resources and activities. As economic activity expands, more people are needed (rather than fewer) to 

manage the increasing number and sophistication of non~labor inputs 

Labor 

Total economic activity over time 

Source: Goldman Sachs Globallnves/men! Research 

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I. Narrowing the jobs gap: overcoming impediments to investing 

in 

Conflict between technological progress and labor dates back centuries. By allowing 

people to offload tasks to machines, technological innovation eliminates some jobs but 

also paves the way for new forms of employment and for higher living standards overall. 

As part of this process, the nature of work evolves; over time, people have shifted from 

'doing' physical labor to 'organizing, coordinating, and supervising' increasingly complex 

resources. in this way, technology has underpinned the innumerable ways in which 

economic activity has expanded, modernized and become more inclusive and flexible. 

The activities that are offloaded to machines tend to be data-intensive, repetitive and 

standardized- work for which technology and machines are more efficient than people, 

especially when done at scale. Many occupations (and on a larger scale, many industries) 

follow a natural evolution. In the early days they are small-scale, innovative, creative and 

often well-compensated; people dominate. In the later phases these jobs and industries 

become large-scale, standardized and repetitive and the jobs typically become less 

remunerative; cost-effective automation displaces people. Given the rapid improvements in 

measurement and data-collection tools, the pace of these transitions is accelerating and the 

need to identify how best to deploy- and subsequently redeploy -labor has become more 

pressing. 

While the benefits of technological progress are felt by the economy as a whole over time, 

this is of little comfort to the individuals whose jobs are displaced by technology {with clear 

parallels to the impact of globalization). They find themselves in an untenable position as 

their skills become obsolete, their human capital erodes and their jobs cease to be 'good.' 

Existing incentives and policies make successful career transitions difficult, particularly for 

people with significant work experience and above-average earnings. Often, the 

individual's best economic alternative is to wait and see whether she can find employment 

that leverages her existing skills- rather than to invest in new employment possibilitieseven if finding a new job in her current industry is highly unlikely. 

An investment analysis uncovers the economics driving the decisions of whether, and how, 

to make the investments in human capital that will narrow the 'jobs gap.' This is the gap 

that often exists between the types of jobs that people want and the types of jobs that are 

available. The economy in the aggregate benefits if the individuals who are at risk of being 

displaced by technological innovation move to industries with better longMterm prospects. 

Yet it can be extremely difficult to make these career transitions successfully and to bridge 

the 'jobs gap' without external assistance. 

Companies' incentives to formally invest in employees' human capita! are dampened by 

the risk that the investments will be one-sided; employees may leave, taking the benefits of 

their training with them before the company has had a chance to recoup the expense. As a 

result, the burden of investing in human capital falls principally on individuals, who may 

not be well-placed to bear it. 

The economics of these investment decisions point to the public-policy changes needed to 

narrow the jobs gap, namely by providing greater assistance to individuals and to 

businesses in order to encourage broad-based investments in human capital. These 

changes include a greater educational focus on the skills that underpin 'adaptive' 

occupations, changes to labor contracts, expanded incentives to encourage private-sector 

investment in job training, innovative financing structures to support the potentially costly 

process of career transitions and support for small businesses and the freelance economy. 

In effect, a new approach to risk-sharing is needed. 

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II. Why technological progress can hurt today's jobs even as it 

benefits the future --=:.: __ : __ : __ :_ _____________________________ _ 

Today's rapid spread of technology is only the latest phase in a long historical story that 

has played out in the US (and elsewhere} many times before. In the 191

h century, new 

agricultural technology vastly increased farming productivity and output, reducing the 

need for agricultural labor and capital. These surplus resources were reallocated to the 

burgeoning manufacturing sector beginning in the late 191

h century and extending into the 

mid-2011' century. Subsequent innovations in machine-production processes led to a boom 

in manufacturing that again reduced the need for labor and capital, freeing up the 

resources that drove the later 201

h-century information revolution. Productivity gains from 

that information revolution have in turn paved the way for the current era of the web, big 

data and machine learning. 

These historical transformations share common features. Initially, the industry that lay at 

the center of innovation drew inflows of capital and labor, supporting high-profile 

investments and disrupters and seeming to promise vast opportunities and the extensive 

creation of high-paying jobs. Productivity rose, making the goods these sectors produced 

cheaper and more abundant and transforming expensive luxuries into affordable everyday 

items. But at the same time, higher productivity also reduced the need for labor and the 

returns to capital in that sector, encouraging both to move elsewhere. Perhaps counterintuitively, on a relative basis, the sector that was once at the forefront of technological 

innovation ultimately employed fewer people, required less capital and consumed a 

smaller share of total spending. The reallocation of excess capital and labor to other 

sectors, where lower initial levels of productivity created opportunities for higher returns, 

started the cycle again. 

This shift from novel to unremarkable makes economic sense. Today, agriculture employs 

just 2% of the American workforce, down from 80% in the early 191

h century, while 

manufacturing employment has fallen to roughly 10% today from a peak of nearly 30% in 

1960. See Exhibit 2. Spending patterns have changed: food accounts for less than 10% of 

consumer spending today, down from nearly 25% just 80 years ago, as Exhibit 3 shows. 

Appendix A tracks these economic transformations in more detaiL 

Exhibit 2: The share of labor in both agriculture and 

manufacturing has declined over time, while the share of 

labor in services has increased 

Share of workers aged 16+ in labor force 

Source lf"UMS·USA, Urwers1ty of Mmnesota, wvvw.1pums.org, Golamar; 

Sac!ls Global Investment /lesearch Note· data aro not avail,<blo for 1890 

Goldman Sachs Global Investment Research 

Exhibit 3: Food has accounted for a decreasing 

proportion of consumer spending over time 

Share of annual consumer spending on food and drink 

HMO 1950 1960 1970 1SSO 1990 2000 2010 

Source. Bureau of EconomiC .l\nalys 1S, Goldman Sachs Global lnvesmwnr 

f/(>soarch 

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From doing to organizing 

Exhibit 4 illustrates the evolution of economic activity over a very long time frame. 

Economic activity has never been only about people. 'Non-labor inputs' have been 

important since the hunter-gatherer age, beginning with plants and animals, moving 

through tools and machinery and extending to the network connectivity of today. Starting 

at a point in the past when the scope of labor inputs was roughly equivalent to that of nonlabor inputs, people spent as much time 'doing' physical work as they did 'coordinating' 

non-labor inputs {the far-left circle below), Over time, as non-labor inputs have become 

more numerous and increasingly sophisticated, they have dramatically broadened the 

scope of what a single person can accomplish and have expanded the universe of 

economic activity (ortotal production, often approximated today by GOP} (as shown in the 

far-right circle below), 

Exhibit 4: As economic activity expands, technology doesn't eliminate the need for people- it changes their role 

Over time, people's principal economic role has evolved from physically 'doing' work to 'organizing, coordinating and 

supervising' complex resources and activities. As economic activity expands, more people are needed (rather than fewer) to 

manage the increasing number and sophistication of non-labor inputs 

Labor 

l 

Labor 

l 

Labor 

l 

.. Non-labor inputs 

Total economic activity over time 

2>oune· Go!dmdn Sdd:s Global investment f'lesearct1 

At first glance- and particularly from the perspective of a person whose job has been 

threatened by or lost to automation- this illustration may suggest that technology is 

pushing people to the fringes and ultimately eliminating them from the world of work 

entirely. But the reality is that people remain critical to economic activity: the key is that the 

nature of 'work' has changed over time as the ratio of non-labor to labor lnputs has 

shifted.1 

1 See for example, Katz and Margo, "Techmcal change and the relative demand for sk1/led labor: the United States m 

htstoncal perspect;ve, '2013. 

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Technology reduces the scope of work that involves heavy physical labor, dangerous 

machinery and tedious repetition. This pushes people into new roles: organizing, 

structuring and bringing their problem-solving skills to bear on the ever·growing realm of 

non·labor inputs. Organizing and coordinating rely more on attributes like creativity, 

judgment and social skills, and less on physical attributes like strength, speed, good 

eyesight and manual dexterity. 

Non-labor inputs don't eliminate people from the economic equation. Instead the existence 

and sophistication of the non-labor inputs allow people to stretch their capabilities by 

focusing on organizing and supervising the tools that generate the output. 

Consider farming. For centuries the scope of a farmer's activity was limited to what a 

family could grow, by hand, on a small patch of land. Tools like the steel plow and the 

grain drill made labor more efficient and allowed farmers to cultivate bigger plots; the work 

itself became more complex as people were required to master use of the new tools. When 

machinery entered the mix, farmers could do more: cultivate more land, farm multiple 

crops in size, install efficient irrigation systems and move beyond subsistence agriculture. 

Today, thanks to information technology and network connectivity, much of farming can be 

done remotely. 

The same is broadly true in occupations not typically thought of as techno!ogy·intensive, 

such as housekeeping. Technology has not eliminated physical labor, but it has reduced 

the intensity of such work. Modern machinery and cleaning products have dramatically 

expanded the productive capacity of housekeepers and have shifted the work away from a 

complete reliance on heavy physical labor and toward a greater role in 'coordinating' the 

use of new products. 

Or consider the historical development of transport, which initially was all about laborwalking. Non~labor inputs from the horse to the cart to the stagecoach and ultimately the 

car changed the dynamic, and walkers became riders whose principal role was to direct 

and control the new mode of transport. Trains and planes went one step further, 

concentrating the organizational activity in just a few positions (engineers, pilots and 

controllers); fewer actors can now move many more people. 

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Replacing yesterday's jobs with today's 

As occupations and industries evolve, they follow what can be thought of as a natural'arc.' 

We show this progression in Exhibit 5 and discuss the economics behind it in greater detail 

in Appendix B. 

In the early days of an industry -the price-elastic phase- falling prices result in rapid 

growth in demand and attract labor and capital. During this period, particularly the early 

part, there are typically few formal requirements for employment, and wages are abovemarket in order to compensate for risk and to attract highly motivated and flexible 

employees. These favorable dynamics are shown as the 'price-elastic phase' of the arc in 

Exhibit 5. 

A dramatically different dynamic begins to unfold as demand growth slows and the 

industry enters the price-inelastic phase. Productivity now outstrips demand growth, 

demand for both labor and capital begins to shrink, and jobs become vulnerable to 

automation, outsourcing or falling wages (or some combination of the three), The wage 

premium shrinks and the present value of the employment declines. 'Good' jobs lose their 

luster and, once automation fully sets in, disappear. The jobs that do remain in the industry 

are less repetitive and more complex; they require employees to continue building job- or 

industry-specific skills even when the employment outlook for the industry is in structural 

decline. The inflection in demand and spending is shown as the start of the 'price~ine!astic 

phase' in Exhibit 5, while the accompanying decline in employment is illustrated in Exhibit 

6. 

This transformation reflects the normal evolution of demand rather than any changes in 

policy. No matter what the price, after a certain point greater consumption becomes less 

fulfilling and often simply impracticaL The transition from price-elastic to price-inelastic is 

typically driven by a combination of broad adoption and natural constraints on greater 

consumption (such as a 2000-calorie diet or a finite number of leisure hours}. Policy can 

ameliorate some of the impact of this shift, but it cannot change the underlying dynamic. 

Similarly, trade and globalization may accelerate this process, but they are not the 

underlying causes. 

Exhibit 5: The natural 'arc' of an occupation or industry 

In the price-elastic phase, the sector attracts labor, capital 

and a larger proportion of spending, but these decline in the 

price-inelastic phase. See Appendix 8 

Exhibit 6: Higher US agricultural productivity ultimately 

led to inelastic demand and fewer labor inputs 

See Appendix B 

Time, mto.,sutedlny'""~ 

SoureR Go!ciman Sachs Glohal Investment Research Sowce. Goldman Sacns Glob<'!!lnvestmenr Research 

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This change in dynamic drives the public narrative that technology is eliminating 'good' 

jobs, namely the we!l~paying manufacturing jobs that characterized the US economy from 

the 1950s through the 1970s {with the impact of automation intensified by trade and 

globalization). When US manufacturing was on an upswing, those jobs promised long 

careers with good wages and steady pensions. But the very fact that those jobs consisted 

of repetitive and standardized tasks, done at scale, made them inherently susceptible to 

automation, outsourcing or lower wages. Today, these jobs are not as 'good' as they once 

were: for decades, manufacturing jobs enjoyed a meaningful wage premium to nonmanufacturing jobs, but this differentia! has all but disappeared in recent years, as Exhibit 7 

shows. And there are fewer of them: on an absolute basis, manufacturing has lost nearly 7 

million jobs since 1980, even as the labor force has grown by more than 50 million people. 

See Exhibit 8. 

Exhibit 7: The historical wage premium for 

manufacturing work has all but disappeared 

Ratio of manufacturing to non-manufacturing hourly wages, 

by earner percentiles 

Exhibit 8: Manufacturing employment has shrunk while 

the labor force has grown 

US workforce by industry 

I 140,W0,(!()0 

};120.000.000 

1 ""·"'"·""' ~ 

! 

' I 

Source JPUMS·USA. Urwersnv of M'nnesota, w>VW 1pums org, Goldman 

Sachs Cilobal/nveslment Research 

Technology doesn't just eliminate jobs- it also creates new ones. In some cases the links 

are direct: new jobs emerge to support the new technologies themselves and to fuel the 

new businesses- and even the new industries- that those technologies make possible. As 

an example: the invention of the automobile in the early 20111 century destroyed jobs for 

carriage-makers and stable-workers, but it also created new jobs, not only in auto 

manufacturing but also in gas stations, dealerships and car~repair shops. In other cases the 

link is indirect: technology allows for the creation of jobs in entirely unrelated industries 

because it frees up excess labor, capital and income that can be put to work elsewhere. 

This is the story of the transformation of the US economy from one dominated by 

manufacturing to one dominated by services, which we discuss in more detail in Appendix 

A. 

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Looking at the evolution of employment over the course of prior technological revolutions 

illuminates the core of what technology is and what it can do. Over time, machines have 

consistently excelled in jobs done at scale- repeated tasks that are capable of 

accurate measurement, that use standardized components and processes and that 

are performed in controlled environments in order to produce consistent outcomes. 

This hasn't changed. What has changed is the scope of activities in which machines can 

excel and the pace at which such transitions are occurring. 

In just the past two decades, tremendous increases in analytics capability, the development 

of more precise measurement techniques and the emergence of advanced processing 

capability and near-infinite data-storage capacity have expanded the range of jobs that are 

susceptible to automation. Machine learning is the most recent example of what happens 

when simple brute-force pattern recognition is combined with massive databases or with 

cheap, highly flexible and accurate sensors that can generate vast amounts of data. 

Perhaps the most remarkable illustration of the pace of change is the self-driving car, which 

only 15 years ago was still a dream given the context-specific nature of driving and its 

intense reliance on human judgment. Thanks to technological advancements in sensors, 

global positioning systems and learning algorithms, which gather and process billions of 

data points instantaneously, driverless cars are a reality today and in another decade may 

be the norm. 

Yet even as the universe of things that can be measured and automated grows, the 

inherent limits on technology remain. The key limiting factor on automation is its reliance 

on data. Data allow for clear and consistent inputs, standard production processes and 

consistent outcomes. Without data, automation and technology cannot be as effective as a 

person would be. Despite fears that technology will eliminate employment across the 

board, automation is actually only well-suited for tasks that meet rigid and limiting 

characteristics. 2 

The changing nature of work: the rise of adaptive occupations 

Given these limits, it is not surprising that we also see growth in 'adaptive occupations; 

which require the attributes machines lack. Adaptive occupations respond to and generate 

the eternal demand for the 'new'- the creation of original content the identification of 

previously unmet or unrecognized needs, the unique situation that can't be replicated or 

that can only be resolved through the application of specialized skills, experience or 

judgment. 

People maintain a competitive advantage in almost all contexts in which repetition and 

measurement are not central or not even possible. They have a lasting competitive 

advantage in jobs that require personal attributes like judgment, creativity, problemsolving and the ability to read social cues. They also have a lasting competitive advantage 

in jobs that involve questions of taste or complex customer preferences, jobs that occur in 

new or unique settings and jobs that require direct interpersonal interaction. Similarly, 

people are needed for jobs in which the process and the outcome depend on variable and 

changing factors, such as the physical and social environment, the degree of customization 

required and the level of professional expertise needed. In all of these cases, machines 

don't work as effectively. 

Adaptive occupations frequently involve interpersonal interaction or a social aspect; the 

interaction is most often direct and physical but can also be done remotely. This need for 

7 See Au tor," Po!any!'s paradox and the shape of employment growth" 2014. 

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interpersonal interaction also means that many adaptive jobs can only be done on a small 

scale. And while most are found in service industries, adaptive occupations can also 

include small·scale goods production. 

Though they generally deal with things more than with people, many traditional trades 

(such as electricians, carpentry, plumbing, locksmiths and tailors) also fall into the category 

of adaptive occupations. These trades involve site· and context~speclfic work and typically 

require a combination of specialized training, the exercise of professional judgment and 

interaction with customers. People working in adaptive trades gain professional expertise 

by doing the same work over and over again, but the work is sufficiently different each 

time that it can't be automated: every project is unique. 

Exhibit 9 highlights some adaptive occupations that the Bureau of Labor Statistics expects 

to show rapid growth over the coming decade. 

Exhibit 9: Adaptive occupations are expected to see robust growth 

Selected occupations projected by the BLS to have the fastest growth rates between 2014-2024 

79 111 32 41% $55,170 

Homahaaltha,des 914 1.262 348 38% $21,920 

Nurse practitioners 127 172 45 35% $98<190 

Phys1caltherap•sts 211 283 72 34% $84,020 

Ambulance drivers and attendants, excL EMTs 20 33% $23,740 

Physic•anass1stants 

Operahonsresearchana!ysts 

Porsona!fmanc•Bladv•sors 

lnterpretorsandtrnnslawrs 

Optomctnsts 

Web developers 

Occupational therapists 

Personalcareairles 

Phlebotomists 

I 

94 123 29 30% $98,180 

91 "' 28 30% $78,630 

249 323 74 30% $89,160 

61 79 18 29% $44,190 

52 2 7'~(, $103,900 

149 183 40 27% $64.970 

115 145 30 27% $80,150 

1,768 2,227 458 26% $20,980 

113 141 28 25% $31.630 award 

Technology can play a role in many adaptive occupations by automating the routine tasks. 3 

In these cases, automation doesn't compete with people. Instead, it allows people to 

devote more time, energy and resources to the areas where they have a natura! 

competitive advantage over technology, and where they add the most value- the creative 

or non~routine parts of the job. This is the dynamic illustrated in Exhibit 4, playing out on 

the smaller scale of a single occupation. As an example, consider how vast data-processing 

and computing power have changed the job of a litigator. Automating the previously labor· 

intensive process of discovery opens more time for the higher·skil! tasks of strategy, 

writing and trial advocacy. 

Over time, even adaptive occupations can evolve into jobs that can be automated in ways 

that eliminate the role of individual labor. As we mentioned earlier, the key is data. Once 

processes are no longer new, and once people have exercised their professional judgment 

3 The benefitS from m1xmg people and machmes s~em from the d1stmCt1on between tasks and JObs. Tasks are 

spec1f1c acttv1t1es, JObs cons1st of clusters of tasks. meanmg that <nd1v1dual tasks can be automated even 1f whole 

)Otls cannot See Autor, "The 'task. approach' to labor markets. an overvww, "Januory 2013. 

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in similar circumstances thousands of times, data as to what works and what doesn't 

becomes available. Once data makes standardization possible, then machines and 

processes can be designed to do the work more quickly, more effectively or more cheaply 

(or all three). At this point, the individuals who find themselves displaced by automation 

will fare better if they look for new employment elsewhere, in fields where this level of data 

doesn't yet exist and where technology is not (yet) able to replace labor. 

The pace at which occupations and industries move along this natural arc is accelerating, 

reflecting the ways in which the scale of business has grown, data collection has become 

easier and measurement technologies have become cheaper and more flexible. This makes 

narrowing the jobs gap- redeploying people to new opportunities that are not only more 

critical to the overall health of the economy but also better for the affected individuals 

themselves- all the more urgent. 

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The impact of technological change can be personal and quite painful. It makes hard-won 

skills obsolete, diminishes- if not destroys- human capital and often leads to permanently 

lower income. But at the macro level, technological change is impersonal and beneficial, 

replacing existing products with newer and cheaper goods that generate higher standards 

of living and overall prosperity. The net result is positive for the economy as a whole, 

especially over the long term. But this is of little consolation to the individuals whose jobs 

have been displaced along the way and who feel that the social contract has failed them 

even though they have 'played by the rules.' 

The problem is that it is difficult for individuals to anticipate when and how the rules will 

change. Many career paths look predictable and profitable- until suddenly a person 

realizes that his 'good' job is in a declining industry being transformed by automation, 

offshoring, falling wages or some combination of the three, 

To cope with the increasingly rapid and highly personalized deprecation of their own 

human capital, individuals will need to find effective ways to retrain and to refresh and 

redeploy their own skills. The challenge is in finding how to make the economics of this 

new investment work. It is clearly in the broader interest to make that investment- but 

under existing incentives, it is often in neither a company's nor a person's own economic 

interest to do so. 

To see the problem from a corporate standpoint, consider a company facing an 

economically equivalent choice between investing in technology and hiring a person, when 

the machine and the person have the same direct costs and produce the same output. In 

this (somewhat artificial) scenario, the company will almost certainly choose to invest in 

the technology rather than hire and invest in training the person. 

There are many reasons why this is the case. The obvious ones are the tax and accounting 

rules that typically favor investing in capital (machinery) rather than labor {people). Over 

the longer term, two other factors likely matter more. The fact that technology !ends itself 

to scale more effectively than people do means that an evenly balanced choice today will 

strongly favor technology as the better decision for the future. And perhaps most 

important is the fact that the employer's investment in a machine has less payback risk 

than does an equivalent investment in a person, particularly since people can change 

employers and take any acquired skills with them. 

From the individual's standpoint, the decision whether to retrain is a classic investment 

problem, involving the nature of human capital. Human capital is effectively a highly 

concentrated portfolio of non-transferable assets with heavy sunk costs in the form of 

education, training, licensing and experience. 

Someone seeking to develop the new human capital needed for success in a different field 

must write off a significant share of his existing stock. To benefit from the higher expected 

returns in the new industry, this person will need to recreate all of these investments, 

which will take time- with no guarantee that his future earnings will match what he earned 

in the past. Along with the significant uncertainty as to the ultimate returns from the career 

change, there is also the high likelihood of a reduced income for the foreseeable future, not 

just during training but also during the early years of the new job. This makes changing 

careers both expensive and risky, particularly if the person doesn't have external help. 

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Alternatively, the person at risk of being displaced can wait and hope that an employment 

opportunity will arise in his current industry, one that allows him to preserve the value of 

his accumulated human capital. Even industries in decline generate job openings and 

opportunities as they shrink; for the person on the ground who sees the gross flows of job 

creation rather than the net number, there is always the chance that one will become 

available to him. In contrast, there is little chance of returning to his former situation once 

he leaves his current industry, given how quickly human capital atrophies. 

Faced with this choice, the natural inclination is to 'wait and see for now.' As we discuss in 

much greater detail in Appendix C, the choice to postpone making a decision can be 

economically rational for the person, even though it is a worse outcome for the economy 

as a whole.4 Exhibits 10 and 11 illustrate this dynamic for a worker considering shifting to a 

new industry. Given the magnitude of the loss from changing careers and the fact that a 

delay will barely affect the net present value of the new occupation {because the choice will 

still exist in the future), even a small probability that the prospects for his current job will 

improve can be enough to make delaying a better choice, at least in the near term. 

Because 'wait and see' is the easier choice for the person caught between two uncertain 

outcomes, it makes economic sense to repeat that short delay, time after time. The risk is 

that 'for now' may become 'forever,' and in the end the person may never make the 

transition to a new career with a higher net present va!ue.5 

Exhibit 10: A net present value analysis suggests that a 

person displaced by technology should opt to change 

careers immediately ... 

Exhibit 11: ... but this analysis overlooks the fact that 

the person can wait and postpone making a decision 

See Appendix C for the NPV analysis 

See Appendix C for the NPV analysis 

Final 

NPV 10 20 

$700,000 

$500,000 

$300,000 

$100,000 

{$100,000) 

($300,000) 

{$500,000) 

($700,000) 

Industry A income, if good outcome 

30 40 50 60 70 80 

0 5 10 15 20 25 30 35 40 45 50 

Industry A Income, if bad outcome 

10 20 

$700,000 

$600,000 

$500,000 

$400,000 

$300,000 

$200,000 

$100,000 

$0 

{$100.000) 

!ndllstry A income, if good outcome 

30 40 50 60 70 80 

0 5 10 15 20 25 30 35 40 45 50 

Industry A income, 1f bad outcome 

Source Goldman Sachs Global Investment ffese.:;rch Source· Goldman Sachs Global Investment Research 

.: The economic losses assocmted w1th job displacement a0d the value of retraining are wel!-recognlzed. But 

research often overlooks the dislocations that 1nd1v1duals sustain m th1s process as well as the 1dea that what might 

be economically rat1onal for a person may not align w1th what is best for the economy as a wl"lole. See for exarnole 

Neal, "!ndustry-soecdrc human capital" evrdence frorn drsp/aced workers," 1995, Jacobson, LaLonde and Sullivan, 

"Is retrammg diSplaced workers a good mvestmentl, ~ 2005, O'Leary. "'Policies for displaced workers· an American 

perspective," 2010 

c See Jacobson. Lalonde and Sui!JVan. "'Eammgs losses of displaced workers," 1993. 

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The problem is especially acute for more-experienced and higher-skilled individuals. For 

them, the loss from writing-off existing human capital is larger, the period over which the 

new investment can pay off is typically shorter and the likely costs of disruption (not only 

to the person, but also to the person's family) are higher. Thus the value of the probability 

-however small- that this person's prospects in his job will improve makes it far more 

difficult for well-established and experienced individuals to choose to retrain, reinvest in 

their human capital or relocate. As we discuss in more detail in Appendix C, the 'wait and 

see' option may appear particularly attractive for them. 

Yet the 'wait and see' approach is not the best answer for the economy as a whole. The 

aggregate decisions of many individuals to leave their current jobs and retrain for new, 

more promising occupations- rather than to stay put and wait to make the decision- will 

benefit the broader economy, generating higher income and a more efficient allocation of 

capital and labor. This more efficient allocation will support the creation of new jobs. See 

Exhibit 12, which illustrates how the distribution of average wages narrows as more people 

leave industries with weak career prospects. 

Overcoming the obstacles that prevent people from changing careers can be extremely 

challenging and will require the greatest changes to existing institutional arrangements. 

Exhibit 12: The option value of waiting is high for an individual, but minimal for the 

broader economy 

Distribution of wages changes as the number of people changing careers rises 

60% 

g40% 

~ 

~30% 

:g 

~20% 

~ 

10% 

8% 

4% 

3% 

0% 

$24,000 $36,000 

Average annual wagl'! for 1 or more workan (40 yn; or old) after switching careers 

.._·Groupof2wotkers 

....,._Gro"p of C. wor~ers 

Source Goldman Sachs Global investment Research 

Goldman Sachs Global tnvestrnent Research 

-..Group of 3 workers 

~·*"·Groupof100workers{RHS) 

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V. The disconnect between individual loss and aggregate gain 

.cr~~~~_polic;_y._c;_~~l!~.".'.~!:! .. __________ .... 

Our investment analysis points to the need to consider how changes in public, educational 

and employment policies can improve the likelihood of successful career transitions, 

reduce the frictions that changing careers generates and put more people on the path to 

new jobs and higher wages. In effect, this means re~thinking risk~sharing. Spreading the 

costs and the risks of career transitions makes sense if the view is that the broader 

economy benefits from the average increase in income for individuals who change 

occupations or industries, as well as from a higher-skilled labor force and from a labor 

market that values these skills. 

Easing career transitions will require a reassessment of education and job-training, a 

rethinking of employment from the firm's perspective and the development of innovative 

financing structures. Other important steps to shift some of the burden of risk away from 

the individual will include decoupling benefits from employment, removing unnecessary 

barriers to entry into professions, regulating the 'freelance economy' in ways that do not 

stifle its growth and reducing the regulatory burden that impedes small~business creation.5 

Educating tomorrow's workforce today 

Today's educational system reflects an outdated paradigm in which young people learn a 

single trade or skillset, find lifetime employment in a single industry and then retire with a 

steady pension. But today's labor market- and especially tomorrow's- is more likely to 

see people shift from one trade or ski!lset to another, and from one industry to another, for 

the second or even third phases of their careers. 

The conventional view about the relationship between technological change and education 

is that more students should study STEM subjects {science, technology, engineering and 

math). While there is generally an understanding that people cannot outrun technology in 

many fields, the intent is to help them drive the development and application of technology. 

Because teaching STEM is (largely) scalable, this is also an attractive approach for 

po!icymakers looking for easily scalable solutions to employment or education. 

But studying math and science- while undoubtedly important- isn't the answer to the 

question of how individuals will adapt to the new labor market. It's unrealistic to think that 

everyone wants to or will become a scientist. a coder or a technology developer, despite 

teachers' best efforts and despite deep investments in STEM education. Nor is it realistic to 

think that even STEM professions will be protected from automation- and thus protect 

employees- in the long run. Consider what happened to pioneers in computer 

programming: programmers with extensive knowledge of COBOL were once highly valued, 

but newer and simpler languages have since pushed those skills to the fringes. 

~,For a diSCussion of the challenges facmg small businesses, see http'/lwww.goldmansachs.corn/our-thmking/publicpo!icy /regulatory~ref orm/2 -speed-economy .ht mt 

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Because it will take longer for computers to replicate the social skills that 

underpin interpersonal interactions. preparation for the work of the future 

requires an emphasis on a different set of skills. Individuals will get ahead based on 

their judgment, critical thinking, creativity and abilities to interpret fluid situations and 

interact with others. To prepare students for this world of work, education will need to 

stress 'foundational middle skills'7 - not just literacy and numeracy, but also adaptability, 

problem-solving, common sense and team-building skills, This is less a question of 

curriculum per se but more a question of how subjects are taught- how interactive they 

are, how much the problems reflect 'real life,' how much teamwork is required and how 

team dynamics are assessed. Making resilience training a formal part of education may 

also bolster people's ability to adapt to rapidly changing labor markets in the future. 

Community colleges have historically been a convenient and affordable option for people 

seeking postsecondary education. But these institutions have come under pressure in 

recent years- with public funding cuts, higher tuition, decreasing enrollment and 

completion rates well below 50%8 - and there is room to improve upon the traditional 

structure, which has typically included a mix of developmental education and job~training 

curriculum. Reorienting community-college programs to focus more on apprenticeships 

and other forms of job training, and offering direct paths to jobs at local businesses upon 

completion, would be a practical way to leverage existing infrastructure to support 

investments in human capital. 

Rethinking risk for both employees and employers 

The incentives that exist today make it difficult for private~sector employers- from large 

companies down to the smallest firms- to make meaningful investments in human capital. 

The key problem lies in companies' inability to guarantee a reasonable return on their 

investments. Some skills are firm-specific, but for the most part human capital is fungibleand increasingly so as a facility with technology generates skills that can be transferred 

across businesses and even industries. 

An employer choosing to invest in formal training faces the risk that an employee will leave 

the firm, taking her skills and knowledge {potentially to a competitor} before the employer 

has had a chance to recoup the expense. !n contrast, companies investing in technology 

face no such risk. Machines can break, or turn out faulty products, but there is no risk that 

they will walk out the door. This can make machines the better investment choice. 

Businesses face a harsh reality; they have limited funds and must invest selectively- with a 

focus on achieving reasonable returns- in order to remain competitive and profitable over 

the long term. 

Because of this. it is clear that companies need support in adjusting the way they 

approach hiring and training, especially as it relates to people who are switching 

occupations or industries. Hiring, especially hiring people in mid-career shifts, must 

become more economically rational and involve less financial and legal risk for employers 

than is the case today. 

;·See Aut or, "Why are there still so many jobs? The history and future of workplace automation 'Summer 2015. 

~ See Bailey and Cho, "Developmefltai education m commumty colleges," 2010. 

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These risks point to the need to expand tax and other incentives for on·the-job and 

professional training for firms of all sizes. This would be an important shift in US tax policy, 

which for decades has encouraged investments in physical capital, through such 

provisions as accelerated depreciation and tax credits for technology. In effect this means 

that the tax system has worked to accelerate the pace of job destruction. Creating new 

incentives for investing in human capital would encourage job creation instead. The 

advantages shouldn't be limited to large corporations, particularly since much of the 

training for adaptive trades will take place at small firms, Broad tax advantages for training 

should extend as far as the 2.7 million small businesses that file taxes asS corporations, 

which make up close to half of all small-employer firms in the US, and to the owners of the 

20 million sole proprietorships, given that human capital is acquired across a range of 

opportunities. 

Formal apprenticeship programs can offer people of any age the chance to learn 

new skills without incurring large amounts of debt or foregoing current income. 

Research sponsored by the US Labor Department estimates that participants who have 

successfully completed existing government-overseen apprenticeship programs would 

earn, on average, an incremental $240,000 over the course of a 36-year career. Expanding 

the tax credits that are available to offset some of the cost could make these programs 

more attractive to employers. At the same time, a 'no-fault' trial period of employment 

would also reduce the risk that a company would be tied to an unsuitable hire. 

As existing apprenticeship programs may be lengthy and biased toward younger 

individuals with less work experience. introducing ~experienced~worker 

apprenticeship' programs could be particularly helpful for older individuals in 

transition to second or third careers. Ensuring that they do not forego income while 

they retrain would reduce the uncertainty around the decision to change careers and would 

make it more economically attractive to do so quickly. 

Apprenticeships may be most appropriate in adaptive trades and other fields where handson learning is critical, as well as in fields where licenses are required. Broadening these 

programs beyond traditional fields like construction, machinery, the electrical industry and 

cosmetology would seem to make sense (medical residencies and internships offer 

possible models). Community colleges offer another affordable avenue for apprenticeships 

or similar programs. 

In apprenticeships and other hiring contexts, employees and employers alike 

could benefit from standardized labor contracts. Under these contracts, which could 

be tailored for each industry, an employee would commit to a set period of employment in 

exchange for a certain level of employer-provided training. Both sides would benefit: the 

employee would have the commitment that she would receive formal or on-the·job 

training, while the employer could benefit from the greater likelihood of recouping its 

investment. As examples, contracts might be roughly akin to the agreements in Reserve 

Officers' Training Corps (ROTC} orthe service commitments required when the military 

pays for medical or law schooL 

Legal limits to the enforceability of employment commitments mean that these contracts 

would need to be designed carefully. The employment would be an explicit exchange of 

the employee's labor for employer-provided training, with the acknowledgment that 

training can be assigned a monetary value because it deepens and expands the employee's 

own human capital. Termination provisions allowing the employee to break the contract by 

reimbursing the firm for the value of receiving this human capital could protect the 

employee and strengthen the employer's incentives to provide the training. In addition, 

standardization would lead to greater consistency and predictability for employees, thus 

reducing employee concern and enhancing the likelihood of compliance. 

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Developing innovative financing approaches 

Retraining and changing careers carries meaningful economic risk. Retraining itself may or 

may not be expensive, but the opportunity costs can be significant. and wages are likely to 

be lower in (at least) the first few years of a new occupation. From a financial standpoint, 

changing jobs is particularly challenging for older people, who are more likely to have 

commitments that cannot be put on hold, such as home ownership, medical bills or 

dependents' education expenses. 

Allowing people to finance retraining by tapping into private savings that are 

currently earmarked for retirement- 401(k) funds and IRAs- without penalty is 

one route. Another is creating separate •career transition' savings accounts that 

are tax~advantaged but more easily accessible. without penalty# and that can be 

used to pay living expenses during retraining. 

These approaches wlll not work for everyone, particularly for younger people who have not 

had time to build a savings cushion. A further option would be to make Social Security 

funds available to cover the costs of retraining as well as living expenses during a 

transition period- essentially an advance on future distributions. Because this would have 

obvious implications for Social Security's long-term funding, such a program might require 

people who drew down funds in mid-life to increase their contributions later in life or to 

postpone their retirements (which would also increase the net present value of their new 

jobs). 

Risk8 sharing can also be extended to the public financing of higher and 

vocational education,. again on the grounds that a highly skilled workforce is in 

the common interest. The current structure of the student loan market could benefit 

from a fundamental review: outstanding student debt is now above $1.3 trillion, and more 

than seven million people are in default. Student loans offering lncome~based repayment 

programs may offer a less onerous and more effective way to finance education without 

imposing life-long burdens on borrowers. To this end, the federal government has 

introduced income-based repayment programs for federal student loans with the goal of 

promoting affordability.9 Similar incentives could be expanded to support vocational 

training for younger people and for a broad range of training efforts later in life. 

Revising employee8 benefits policies would also shift some of the risk and 

encourage employment regardless of the prospective employee'"s age or previous 

work history. Decoupling benefits from employment and making them more portable 

would improve labor~market flexibility and could make smaller businesses more attractive 

as employers. Large firms are currently considerably more likely than smaller firms to offer 

retirement plans, medical care and paid sick leave, as Exhibit 13 shows. Recent data from 

the Bureau of Labor Statistics indicate that retirement plans are not currently available at 

more than half of all private businesses that employ fewer than 50 people. While this is in 

part a matter of cost, it is also a question of accessibility: reducing administrative burdens 

would make it easier for small firms to offer these benefits. 

~ 1 he "Pay as You Earn· repayment plan for federal student loans, launched in 2012, caps !oan~service payments at 

10% of the borrower's annual d1scret10nary tncome. Th1s plan also offers debt forgJVeness of any remammg balance 

after 10 years for people w!1o work m pubhc serv1ce and after 20 years for other borrowers. See a!so 

https //www.nevvyorkfed.org/medlahbrary/medla/research/staff_reports/sr668.pdf 

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Exhibit 13: large firms are more likely to offer employee benefits 

Share of establishments (by size) that offer employees access to selected benefits, 2015 

100% 

I 90% 

~ 

80% 

• 70% 

~.;; •Paid sick leave 

~i 60% 

-A 50% .~ 2 .. iliP<ndvacatJon 

Paid holidays 

,a~ 40% 

: g Retlrament 

~ 30% Medica! care 

j 20% 

• 

~ 10% 

0% 

1to49 50to99 100to499 500ormora 

# of employees 

Sourco. US Bureau of Labor Stat1sfics, Nat,onal Compe0sat10n Survey, Goldm<~n S,lchs Global Investment Research 

Reducing barriers to entry and supporting the freelance economy 

Second and third careers will not necessarily involve jobs at existing firms, particularly 

large firms. Many people will become self-employed, start their own businesses or join 

small companies. To support these transitions, entrance into new professions should be 

made easier, with limits on self~regulatory organizations' ability to create barriers to entry 

that reduce competition and constrain geographic mobility. 

A recent White House report indicates that some 25% of US workers now require a license, 

a five-fold increase from the early 1950s; two-thirds of the increase reflects a rise in the 

number of occupations that require a license rather than a rise in the number of people in 

these jobs. Although more than 1000 occupations are regulated across the country, fewer 

than 60 are regulated by every state; 10 see Exhibit 14. Licensing costs can be a prohibitive 

barrier to entry for someone looking to move to a new occupation. For example, a 

minimum-wage earner in Louisiana who wants to obtain a retail florist license faces upfront costs equivalent to at least a week's wages, with annuallicense*renewal fees costing 

a day's pay for even an experienced florist. 

'"See "Occupational !icensmg: a framework for po/!cvmakers, "Ju!y 2015; 

https·ffwww.whltehouse.gov/Sites/default/fl!es/docs/licensing_report_ftna!_nonembargo.pdf 

Goldman Sachs Globallnvestment Research 

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Exhibit 14: licensing requirements vary across the country 

Selected occupations requiring licenses, licensing fees and median wages 

51 sso 2.6X 

51 $90 $16.00 2.2X 

51 $100 $14.00 L9X 

51 $90 $15.00 2.1X 

50 $130 $12.00 1.7X 

49 $100 $22.00 3.0X 

46 $440 

37 $210 $15.00 2.1X 

37 $90 $12.00 1.7X 

34 $210 $2LOO 2.9X 

33 $310 $15.00 2.1X 

33 $10.00 1AX 

29 $80 

" $70 24 $170 $9,00 1.2X 

20 $90 $13.00 1.8X 

17 $120 $16.00 2.2X 

16 $770 $21.00 2.9X 

13 $150 $19.00 2.6X 

2.1X 

Supporting individuals undertaking career transitions also means approaching 

regulation of the 'freelance economy• in ways that do not impede its growth. The 

freelance economy is already a crucial safety net for many, including those whose current 

jobs are being automated away. Offering individuals the opportunity to easily monetize 

their existing assets and skills- spare rooms, free time, driving licenses, cooking talentsis a particularly good way of offsetting some of the opportunity costs of retraining. Rules 

around classification of employees and independent contractors, working conditions, pay, 

benefits, liability and insurance should all be viewed with an eye toward supporting the 

freelance economy rather than stifling it. 

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VI. Conclusion 

Global M<lrkets Institute 

Technological disruption of the labor market has been under way for decades, eliminating 

some jobs while simultaneously improving living standards and laying the foundation for 

new occupations and new industries to emerge. Thanks to advancements in measurement 

technologies and data-collection capabilities, the pace of this disruption is accelerating, and 

the need to identify how best to deploy labor is becoming more pressing. 

Technology-driven change can and should be viewed as an opportunity- not as a 

relentless threat, But making this opportunity a reality for many people will require a new 

approach to risk-sharing to reduce the uncertainty that comes with undertaking career 

transitions. From a public-policy perspective, this will require modernizing education, 

revisiting the structure of employment and offering greater financial support to individuals 

and businesses seeking to invest in human capital. We believe that policy changes such as 

these are critical first steps to closing the jobs gap by better aligning what is economically 

rational for an individual with what is beneficial for the economy as whole. 

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Appendix A: Technological innovation has fueled job destruction 

a nd_~!~~!i~-~-!h ro~~~() ut ~rt.:!~!J~~~-~-~~!~~y__ ____________________ ------------· 

Earlier transitions in the US economy offer insights into the way that technology has 

fundamentally reshaped the labor market. In both the 19th-century shift from farming to 

manufacturing and the 20th-century information revolution, technology eliminated entire 

categories of jobs while also driving job growth in new fields and previously unimagined 

occupations. 

At the start of the 19th century, agriculture dominated the US economy, accounting for 

80% of total employment and more than half of gross domestic product. Farms were 

generally individually owned and produced a range of crops on a single plot, largely for 

personal use or local consumption. Productivity and output were relatively low, and 

although farming had advanced beyond the subsistence level, it remained labor-intensive, 

small-scale and fragmented. 

New farming technology introduced from the 1840s, including factory-made agricultural 

machinery and commercially produced fertilizer, made large-scale commercial farming 

feasible for the first time. These new tools drove rapid improvements in productivity and 

accelerated growth in per capita output; though the historical data are limited, Exhibit 15 

tracks the improvement in corn yield since 1900. As productivity rose, agriculture's share of 

total employment declined meaningfully, falling just below 50% by 1880 and to 40% by 

1900. By 1950 the proportion of the labor force working in agriculture had dwindled to 

roughly 10% and, thanks to continuing increases in productivity, today this figure is just 2%. 

See Exhibit 16. 

Exhibit 15: Technology has contributed to higher 

agricultural yields 

Exhibit 16: Agricultural employment share has declined 

overtime 

Corn yield, bushels/acre 

• 1100 

; 

" so ,; 

'~ 60 

~ 40 

20 

1910 192:0 1930 1940 19&0 1960 1970 19$0 19S(l :woo 2010 

Source. US Department of Agnculrum. Goldman Sachs Global Investment 

Research 

Goldman Sachs Global Investment Research 

Agricultural employment share of the labor force 

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On the surface, the severe contraction in agricultural employment experienced after 1850 

was a negative consequence of technology. However, this technological change allowed 

the country to move into a new phase of economic growth, in several ways. 

First, higher agricultural productivity freed up a large part of the workforce and allowed 

labor to shift to manufacturing. Manufacturing was a critical source of employment for 

displaced farmers as well as for new entrants into the labor force (women and immigrants); 

manufacturing employment rose from roughly 600,000 in 1850 to nearly four million by 

1900. While farming generally required specific traits and skills- for example, physical 

strength and situational experience -large~scale manufacturing processes simplified and 

deconstructed larger tasks into a series of smaller ones. People could be taught how to 

perform these bite-sized tasks on the job, thereby developing new and specialized sets of 

skills. 

Second, the rise of mechanized manufacturing in the late 19th and early 20th centuries 

dramatically improved the quantity and quality of output across a wide range of industries. 

Consider the shoe industry, where automation has had a dramatic impact on product 

availability, customer choice and cost. For centuries shoes were fabricated by hand, with 

little variation or customization except at the highest end; they came in just a few sizes and 

typically didn't distinguish between right foot and left. In the 19th century, technological 

advances including the introduction of rolling and sewing machines allowed for faster 

production and higher output. With greater volume, producers were able to gather enough 

data to standardize their production to more effectively serve the mass market; they could 

refine shoe sizes to fit most of the population and could make the production of 'right' and 

'left' shoes the norm. 

Individual craftsmen undoubtedly felt the pain of this technological transition, and few 

people train to become cobblers today. The shoe designers who have replaced cobblers 

bring a different set of skills to the job. Yet consumers have clearly benefited from their 

inexpensive access to a dazzling array of choices; the average American bought more than 

seven pairs of shoes in 2013 alone. 

This dynamic is also evident in the mechanization of automobile manufacturing. Early 

automobiles were labor-intensive, highly customized and expensive: in 1900, the more 

than two dozen automobile manufacturers in the US produced just a few thousand cars in 

total. Later, the standardization of parts, machine-based manufacturing and assembly-line 

production made it possible to mass-produce cars that the average American household 

could afford. The company that pioneered this approach- Ford Motor Companyproduced more than one million Model T cars on average each year between 1913 and 

1927 while reducing the price by roughly two-thirds. 

After the turn of the 20th century, the pace of job growth in manufacturing began to exceed 

the pace of population growth: the share of the workforce employed in manufacturing 

jumped from 15% in 1900 to 25% in 1920. By 1960, the sector employed nearly one~third of 

working Americans, 

Even so, it wasn't long before further technological innovations caused the industrial 

revolution to give way to the information revolution and the growing prominence of the 

services sector. !n 1945 half of the private workforce was employed in a goods-producing 

industry (a category that includes manufacturing}. But as post~war capital investment drove 

meaningful increases in manufacturing productivity, the share of employment engaged in 

manufacturing began to decline. The labor shift was rapid: between 1945 and the mid~ 

1990s, the goods~producing share of the private labor force fell from roughly 50% to less 

than 25%, while the services share grew from roughly 50% to just over 75%. Today, the 

services sector employs 85% of the private workforce, while the share in goods-producing 

industries is just 15%. See Exhibits 17 and 18. 

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Exhibit 17: Manufacturing employment share has 

declined sharply since 1970 

Manufacturing employment share of the labor force 

Sovrce IPUMS-USA, Unrvers;ty of Mmnesora, www 1pums.org, Goldman 

Sachs Global Investment Research 

Global Marl\ets lnst1tutc 

Exhibit 18: The share of the workforce producing services 

has grown rapidly in the post~war period 

Services vs. goods"producing employment share 

,·-Good•·produc•ngwor~ersasa%of1heto:alptlva1eworkforce 

-Serv<ee~rov•dlng workms as~% ol1ho 101~1 pnv~:e workforce 

Source: US Bureau of Labor SWtiSIICS, Goldman Sachs G!oballnvestmem 

Research 

This shift away from manufacturing and into services took place amid, and drove, a rise in 

overall educational levels. In 1940, just 10% of the adult workforce had completed at least 

one year of college, and more than half hadn't made it past primary school. By 1980, when 

manufacturing employment peaked, nearly one"third of the adult workforce had completed 

at least one year of college, and only 15% of the workforce had finished their education at 

primary schooL Today, roughly 60% of the adult civilian population has completed at least 

one year of college, while just 5% finished their formal education at primary school. See 

Exhibit 19. 

The latest Bureau of Labor Statistics employment~projection data suggest that six of the 

ten occupations expected to show the fastest job growth by 2024 require at least an 

associate's degree; all ten of the occupations expected to pay the highest wages require at 

least a bachelor's degree as wei! as some form of on~the~job training as a requirement to 

achieve competency, The Importance of forma! education continues to rise: for nearly the 

past 25 years, unemployment rates have been highest among adults who have not 

graduated from high school and lowest among college graduates. 

Ultimately, automation has continuously placed downward pressure on the prices of 

manufactured goods, raising lfvlng standards and freeing up consumer spending power to 

be redeployed elsewhere, in sectors that themselves have created new employment. In 

1930, nearly 40% of consumer spending was dedicated to non~durab!e goods like clothing, 

shoes and gas. Today, the relative economic importance of these items to the consumer 

has tumbled: spending on them has been nearly halved, freeing up resources to be spent 

on durable goods (housing, cars} and services (education, health care, entertainment)- and 

creating new jobs in the process of supplying these new needs. See Exhibit 20. 

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Exhibit 19: Educational levels have risen over time 

Civilian population by highest level of educational 

attainment, snapshots of 1940 vs. 1980 vs. 2014 

Gotdman Sachs G!oba! Investment Research 

Global Markets !nst1tute 

Exhibit 20: Technology and productivity gains have 

driven down consumer spending on non-durable goods 

Proportion of annual consumer spending on non-durable 

goods 

Source· Bureau of Econom1c AnalysiS, Goldman Sachs G!oba/lnvestment 

Rosoarcil 

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There are typically two distinct narratives about the interaction of technology with 

industries or jobs. The first relates to the promise of new technology as a focal point for 

investment, offering unlimited employment opportunity and the potential to create social 

good. The second, more draconian take, sees technology as the relentless destroyer of 

'good' jobs. 

In practice, occupations and industries tend to follow a predictable arc that ultimately 

encompasses both narratives. 11 The early phases are characterized by enthusiasm and 

discovery: jobs are loosely defined and the necessary credentials have not yet been 

specified or perhaps even invented. From a consumption standpoint, price elasticities tend 

to be high, meaning that every one percentage point drop in price created by better 

productivity- reflecting advancements in technology- generates more than one 

percentage point of demand. As a result, the market grows, as does the need for new 

capital and more employees. 

These dynamics are depicted in Exhibit 21, which illustrates how the share of spending 

dedicated to goods in a sector that is experiencing fast productivity growth increases when 

prices are elastic- the early stages of the arc- and declines in the later stages, when prices 

are inelastic. 

Exhibit 21: The natural'arc' of an occupation or industry 

In its early phases, the sector at the center of innovation attracts labor and capita! and captures a 

large proportion of spending. Over time, it requires less labor and capital and captures a smaller 

proportion of spending 

100 

Prlce~elastic phase Price~ine!astic phase 

Time, measured in years 200 

Source· Goldman Sachs Global investment Research 

11 See Jacobson, Lalonde and Sullivan, "Long-term eammgs losses of high-sen,onty displaced workers, 'November 

1993. 

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An extrapolation of the early phases of the arc suggests that the new occupation or 

industry will continue to offer unlimited growth and employment opportunities. 

Unfortunately, the early phases cannot last. As history has shown, in the end all industries 

(at least so far) hit a limit in demand as the value of the technology that underpins them is 

pushed to its limits. As a recent example: the promise of unlimited media streaming is 

constrained by the simple reality that there are only 24 hours in a day and that people will 

need to spend some of this time doing other things. 

Unsurprisingly, the growth trajectory of the industry changes as it approaches these limits. 

This is illustrated by the 'price-inelastic phase' shown in Exhibit 21. If the pace of 

consumption growth does not keep up with the pace of productivity growth, then higher 

levels of productivity simply translate to 'producing more of what is needed using fewer 

resources.' The result is a flight of capital and the elimination of employment, as what had 

been 'good jobs' become dead ends. 

Over time each new industry- and each new technology- has experienced the same 

transformation. Think of the agricultural revolution: the promise of new agricultural 

technology seemed unlimited as consumption went from 1000 mediocre-tasting calories to 

2000 tasty ones. However, as daily consumption passed 2000 calories, the marginal value 

of each additional unit began to diminish rapidly. Demand became highly inelastic, 

meaning that for every one percentage point drop in price, demand grew by much less 

than one percent. Exhibit 22 shows the labor-market implications of this shift for the US 

agricultural industry between the mid-19th and the late-20th centuries: as demand became 

inelastic, the share of labor in agriculture declined precipitously, 

Exhibit 22: Higher productivity in agriculture in the mid-19th century ultimately led to 

inelastic demand and fewer labor inputs 

As demand becomes inelastic, the share of labor dedicated to the industry declines 

60 

,s 

·~ 

~ 50 

1Z . .., :~ 40 ~ 2 

~ 0 "' > "0.!:: 

~ ·~ 30 

.. 

~1 0 CL 20 

:!i 

o:.c 

~ 10 

~ 

:;'!. 

\ Agriculture employment share: 

-Actual 

Model prediction 

1850 1870 1890 1910 1930 1950 1970 1990 2005 2007 2009 

Year 

Sourco IPUMS US/\, Uwvon.>1ly of Mmnosota, wwvv tpums org, Goldman Sachs Global/nvosmwnt Rosoarch 

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Each repetition of this cycle has left society better off, since people are able to consume 

new, less-expensive and better-quality goods, at a higher level of overall income and social 

welfare. But these transformations are not experienced as positively by the individuals 

directly affected by the transition from the price-elastic to the price-inelastic phase. The 

early phases of the cycle, which are characterized by the need to attract employees to new 

and risky businesses, generate jobs with low barriers to entry, high relative wages and high 

mobility. Over time, these dynamics foster growth in related 'enabling' industries, 

including technical training classes, specialized employment agencies, dedicated 

educational programs and eventually licensing and degree programs- in other words, an 

organized path to success, which contributes to the view that job creation will remain 

robust for a long period. 

As the industry matures, the pool of jobs tends to shrink to those that require more 

extensive education and stricter credentials. At the same time, the present value of 

employment falls, and individuals' significant investments in industry-specific human 

capital are set against a structurally deteriorating employment picture. 

Eventually, and usually without warning, the cycle turns and the job destruction begins. 

This inflection does not occur because the individual has failed. Rather, it occurs because 

the industry has become saturated and the underlying technology has run out of new 

applications. Ironically, it is the industry's inherently greater level of productivity at this 

point- which creates more output by using less rather than by employing more- that is at 

fault. From an economic standpoint, in the resource-attracting early phases, the market is 

characterized by persistent factor shortages and rents for all parties. In the later phases, the 

market is characterized by persistent input surpluses and falling factor payments, 

particularly wage income. 

Once again, from the standpoint of the economy at large, this transition- from emerging to 

mature- produces positive outcomes: welfare improvements expand and are spread more 

evenly. However, to those caught in the reversal, this natural transition seems more 

personal and possibly even malicious. This persistent gap- between the benefits that 

accrue to the broader economy and the pain experienced by the individual- helps to 

determine who wins and who loses over the course of an industry's arc. 

Modeling the shift from price-elastic to price-inelastic 

In the section below, we present a model that illustrates the effect of productivity growth 

on labor in a slightly different way. The conclusion is the same: any industry that is subject 

to an extended period of rapid productivity growth will- by the very fact of that 

productivity growth- shrink as a share of the economy, as a source of jobs and as a point 

of accumulation of capital. 

Rather than show how the arc plays out over time in a single sector, this mode! considers 

the problem from the perspective of a two-sector economy, in which the sectors are 

distinguished solely by productivity growth. The sector with high productivity growth is the 

sector with innovative technology; the sector with low productivity growth can here be 

thought of as 'the rest of the economy.' Our base case assumes fully mobile labor and 

capital and Leontief preferences and Cobb~Douglas production, and we show labor, capita! 

and budget share over time. 

This model has three parts: first, we consider consumption assuming prices are given and 

utility is maximized; second, we examine production assuming interest rates (cost of 

capital) and wages (cost of labor) are given and profits are maximized; and third, we 

analyze the conditions necessary for the market to clear {for consumption to equal 

production). 

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Part 1: Consumption 

On the consumption side, we assume a representative agent has to consume equal 

amounts of two goods or services C1 and C2 •

12 1n each period t, he maximizes his utility 

Ut = min(CH, Cu) 

subject to his budget constraint 

PuCH + PuC2t = Yt 

where P1 and P2 are the prices of the two goods andY is his income. The solution to this 

problem is: 

Part II: Production 

On the production side, we assume competitive firms produce the two goods or services. 

To understand how each firm maximizes its profits, we reference the standard Cobb· 

Douglas production function, which uses capital (K) and labor (L) as inputs. 

1 1 

Fu = A1tK~l.~t 

Ar measures productivity at timet. For simpli~ity, we assume productivity at each firm 

grows at a constant rate over time: Att = A(l + g1)f and Au= A(l + g2 )t. 

Normalizing the unit cost of capital as 1 and denoting the unit cost of labor as w, we can 

write the following profit functions: 

nlt Pu ( AuKALt)- Kll - wL1t 

-Ku -wLu 

The first·order conditions from profit maximization imply 

Ku = wLu and Ku = wLu 

For simplicity, we assume the market is competitive and there are no barriers to entry. As a 

result, each firm earns zero profit in equilibrium and we have: 

2/W 2/W Ptt =- andPu =- Au Au 

This result suggests that as productivity increases (i.e., higher Au and Au) the price of each 

good or service falls. In addition, if technological innovations cause productivity to grow 

faster for good or service 1 than for good or service 2, then the price of good or service 1 

should fall faster than the price of good or service 2. 

'

7 Essentially, we are using a Leont1ef ut1hty funct1on. We use th1s speCific utility functiOn to simplify our ana!ys1s, but 

the conc!us1ons rema111the same as long as the two goods or serv•ces are not h1ghly substitutable. 

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Part Ill: Market clearing 

In equilibrium, consumers consume exactly the same amount that firms produce: 

This market~c!earing condition helps us solve for the equilibrium capital and labor inputs 

Y, 

Ku = 2(1 +a-') 

Y, 

Lu = 2w(1 +a-t) 

Where a represents the productivity growth differentia!: 

1+ a 

To illustrate the intuition behind these results, we use an example where productivity in the 

manufacturing sector grows faster than productivity in the services sector (i.e., g1 > g2 ). In 

this case, a is bigger than 1 and at approaches infinity in the limit. This implies that, over 

time, both capital and labor devoted to sector 1 {e.g., manufacturing) decrease, whereas 

both capital and labor devoted to sector 2 (e.g., services) increase. 

Lastly, we can solve for C1 and C2: 

Y, Cu = C:u = -----,--.'---,--,-

2rw(A~t +~) 

Productivity growth (i.e., increases in A1t and Au} allows consumption to rise given the 

same income. 

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Appendix C: How uncertainty keeps individuals from moving out of 

industries 

We use an investment analysis to illustrate the dynamics behind individuals' decisions to 

stay put in declining industries or to move to industries with better long~term prospects. 

This analysis shows how uncertainty can cause people to choose to remain in their current 

industries even if they believe that the balance of probabilities points to stagnant or 

falling incomes there and higher incomes elsewhere. Reluctance to transition to a new 

career will be even stronger among older and higher-skilled individuals. Even relatively 

mild resistance to such transitions can have significant macro effects: aggregate income 

will be lower and more~productive sectors will be deprived of labor, while lowerproductivity sectors will face large labor overhangs. 

We use a stylized example to show how a single individual might react to the threat of 

displacement due to technological change. Some people will be in better starting positions, 

others in worse, and it is difficult to calibrate this analysis exactly. But academic work on 

displacement and retraining shows that this is an important question worth empirical 

examination. 13 

Our indicative example considers a person working in industry A, which is facing 

considerable uncertainty over its future profitability, such as the US manufacturing sector 

today. Despite the cloudy outlook, there is a small possibility that prices and incomes in 

that sector could rise again to the levels seen over previous decades {what we call the 

'good state' of industry A). However, there is a much greater probability that employees' 

incomes will stagnate or fall even further as low prices continue to squeeze margins and 

companies reduce costs wherever possible to maintain competitiveness {what we call the 

'bad state' for industry A). 

Given this outlook, the person may choose to shift careers by leaving industry A, retraining 

and permanently moving to a new industry (B) that is not facing the same long-term 

challenges and where future income is less uncertain, for instance as with today's service 

and IT sectors. However, this decision carries its own costs, both direct (potentially 

expensive retraining) and indirect (opportunity costs). In addition, the seniority and human 

capital this person has gained through formal training as well as through 'learning-bydoing' may be lost or become irrelevant. Accordingly, we assume a less uncertain but 

lower income stream from moving to industry B. See Exhibit 23. 

''See for example Jacobson, Lalonde and Sullivan, "Is retr.aining displaced workers a good investment?" 2005. 

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Exhibit 23: A person considering changing careers faces uncertainty whatever the decision 

Potential outcomes for a person considering a career transition 

/ !N!T!Al INCOME $ 40,000 

Supple/Y!ent 

STAY IN 

INDUSTRY A 

SWITCH TO 

INDUSTRY 6 

10% ~ HIGH INCOME $ 50,000 

~ {GOOD STATE FOR INDUSTRY A) 

90~ LOW INCOME $ 20,000 

(BAD STATE FOR INDUSTRY A) 

~"' ~ HIGH INCOME $ 35,000 

5~ (GOOD STATE FOR INDUSTRY B) 

50~ LOW INCOME $ 25,000 

(BAD STATE FOR INDUSTRY 8) 

'Wait' doesn't mean 'do nothing' when it comes to deciding 

whether to change careers 

We use first a Net Present Value {NPV) and then a Real Option Valuation {ROV} technique 

to demonstrate the role that income uncertainty plays in affecting the person's decision to 

stay or to shift industries. 

We begin with the expected Net Present Value analysis, assuming 25 more years of 

working life {for a 40-year-o!d who will retire at 65). The expected NPV of remaining in 

industry A {assuming a 5% real discount rate) is $364,000. However, if the person 

immediately undertakes retraining and moves to a new industry, then the expected NPV 

will be $452,000 (assuming that retraining costs $1,000 and that the person can 

immediately start working in industry B, i.e. that there are no opportunity costs from 

training). Accordingly, out of these two possible paths, the option to 'switch industries 

immediately' will be preferred. See Exhibit 24. 

Exhibit 24: A simple net present value analysis suggests that the person should opt to 

change careers immediately . , . 

Expected NPV of future income streams 

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However, as Exhibit 25 shows, additional paths are available. The person can also choose 

to wait one period and then decide whether to transition to a new industry depending on 

the realized outcomes for industry A and Bin the second period. If income in industry A 

falls to the low level ($20,000 in our example/ and the person moves to industry B 

(regardless the state of industry 8}, then expected NPV rises to $490,000, which is higher 

than either of the two paths we initially considered. 

Accordingly, the rational decision is to 'keep your options open' for now and only make the 

decision whether to change careers later, once the current uncertainty has been resolved. 

This result is critical, since it shows why not making the move to the industry with better 

prospects can be the rational thing to do- at least in the shorHerm. 

Exhibit 25: , .. but the simple NPV analysis overlooks the fact that the person can wait and 

postpone making the decision 

Expected NPV of future income streams 

The ability to delay making the decision can also be viewed as a 'real option.' In finance, an 

option gives the opportunity- but not the obligation- to buy or sell a security at a 

previously agreed price. In our analysis, the ability to wait and make the careeHransition 

decision later is also an opportunity, but not an obligation, to move to industry B. We can 

use the same pricing concepts from finance- namely constructing a risk-free portfolio and 

relying on arbitrage conditions to equilibrate prices over different states of the world- to 

price the value of this option to the person. 

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Real option theory explicitly shows the value of waiting 

We start by considering the person's long position in a put option, which is the ability to 

stay in industry AY' See Exhibit 26. 

Exhibit 26: The person holds a long put position in industry A 

Value of the rea! put option vs. NPV of switching to a new industry immediately 

Fln8! 

NPV 10 

$700,000 

$500,000 

$300,000 

$100,000 

{$100,000) 

{$300,000) 

($500,000) 

{$700,000) 

Industry A income, if good outcome 

20 30 40 50 60 70 so 

-NPVof,witoh>ngit~ Immediately" Js chosen 

Value of real option 

0 5 10 15 20 25 30 35 40 45 50 

Industry A income, if bad outcome 

Final Industry A income, if good outcome 

NPV 10 20 30 40 50 60 70 80 

$700,000 

$600,000 

$500,000 

$400,000 

$300,000 

$200,000 

$100,000 

$0 

($100,000) 

0 5 10 15 20 25 30 35 40 45 50 

Industry A income, if bad outcome 

Source: Goldman Sachs Global investment Research 

If the worst outcome for industry A Is greater than or equal to the best outcome for 

industry 8, then the person will always choose to stay in industry A, even if the state of 

industry A worsens. The NPV of changing careers immediately is negative and the value of 

the option to wait for now an-d move in the future also becomes zero in this region. But if 

the best outcome for industry A falls !ow enough (keeping volatility between the outcomes 

constant for now}, then it will always be optimal for the person to move to industry B, as 

the expected NPV of the 'switch immediately' strategy rises above the value of the real 

option to wait (even if there are retraining costs). 

The complication for the person is that between these edge cases, the put option does 

have value, and this value is greater than the expected NPV of immediately transitioning to 

a new career (see the middle section of the chart on the right side of Exhibit 26}. The value 

of the put option in this region is the value to the person of certainty about industry A's 

future wages, and the person is prepared to delay making a decision in order to achieve 

this certainty. Stated another way, the expected NPV of making a decision before knowing 

the outcome in the next period has to be more than just positive- it has to be larger than 

the certainty value that would be achieved by waiting (today's option value}. 

'' To plot Exh1b1ts 26 and 27, we change the realized levels of income in the good and bad states, but throughout the 

analysis we maintam a fixed range between these outcomes. Th1s mamtams a constant vo!atd1ty between outcomes. 

Volatd1ty IS 1tself a key vanable m determmmg the value of the optiOn, wh1ch we explore later in this ana!ys1s. To 

s1rnphfy the analySIS (ensunng a 'closed·form' solutiOn), we also set the mdustrv·B mcome to 1ts expected value of 

$30,000 m both the good and bad states. ehmmatmg the uncertmnty_ 

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The person also holds a long position in a call option, reflecting the ability to change 

careers and move into industry 8. 15 Again we can determine the value of this option using 

real option theory, as shown in Exhibit 27. The chart on the right side of Exhibit 27 shows 

three distinct regions. If the best outcome for industry B offers a very low wage (below the 

worst outcome for industry A), then there is no incentive to change jobs, and the call 

option is worthless. If the worst outcome in industry B is better than or equal to the best 

outcome in industry A, then the NPV of changing careers immediately is greater than the 

option value of the call, and the person will indeed make the transition immediately. 

Between these regions we again see a range of outcomes where the call option has a 

positive value that is greater than the NPV of transitioning immediately. In these cases, the 

optimal decision is to wait. 

Exhibit 27: The person also holds a long call position in switching to industry B 

Value of the real call option vs. NPV of switching to a new industry immediately 

Final 

NPV 

$500,000 

$400,000 

$300,000 

$200,000 

$100,000 

$0 

{$100,000) 

{$200,000) 

{$300,000) 

($400,000) 

{$500,000) 

10 20 

Industry 8 income, if good outcome Final 

30 40 50 60 70 NPV 

10 20 30 40 50 

Industry B income, if bad outcome 

$500,000 

$400,000 

$300,000 

$200,000 

$100,000 

$0 

j$100,000) 

10 

Industry 8 income, if good outcome 

20 30 40 50 60 70 

0 5 10 15 20 25 30 35 40 45 50 

Industry 8 income, if bad outcome 

Source Ciold!llan Sachs Globallnvvstment Research 

Combining these results shows that a person has strong incentives to wait over a large 

range of expected income levels. There is tangible benefit from following this strategy 

since both the put option {trying to mitigate the downside of remaining in industry A) and 

the call option {trying to maximize the upside from moving to industry B) have value in this 

range. 

In our two-period model, the person always makes a decision by the second period. 

However, in a more realistic multi-period scenario, uncertainty may persist for some time, 

and the 'wait' strategy could remain the optimal strategy for much longer. Accordingly, the 

rate of transfer between industries A and 8 would be much lower than either a simple 

expected NPV analysis or a two-period ROV model would assume. We also assume 

independence between the outcomesHl in each industry, which is unlikely to be the case in 

the real world, since national and global business cycles affect many industries 

simultaneously. Cross-sector correlation both raises the option value of waiting and 

complicates the pricing of these options significantly, 

'"To Slmp!lty the analys1s (ensunng a 'dosed-form' solut1onl for different levels of mcome m Industry 8, we set the 

mdustrv-A tncome to 1ts expected value of $23,000 tn both the good and bad states (te. we e!irnmate the uncertamty 

from the mdustry-A mcome), 

'li More techn1ca!ly we actually went further by removmg uncertainty from tndustry 8 lfl the put-optton calculation 

and uncertamty fror'Yl industry A tn the ca!l-optton calculation. 

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Older and higher-skilled individuals will wait longer, while younger 

people will move sooner 

Throughout this analysis, we have compared the option value of waiting against making 

the immediate decision to change careers while keeping the range between the binary 

'good' and 'bad' outcomes fixed. This is equivalent to keeping the volatility of outcomes 

fixed. 

However, in the real world, an older person or one with highly specialized skills who is 

considering changing careers will face much greater volatility than a younger person or 

one who is less skilled or has more generalist or transferable skills. If an older person 

remains in industry A, he is likely to see a proportionally higher income under the 'good' 

scenario than a younger one would, because his greater human capital and seniority give 

him a stronger wage bargaining position. On the other hand, if the older person moves to 

industry B, the usefulness of his previously accumulated human capital is unclear. This 

person may see a large decline in the industry~B income if his skills are irrelevant, but he 

also may see only a small decline if he can successfully transfer his human capital. This 

adds volatility to the expected industry-8 income. In contrast, a younger person deciding to 

retrain and enter industry 8 takes significantly less risk because she is transferring- or 

losing- a much lower level of accumulated human capital {since she has had less time in 

which to build it). Exhibit 28 shows these dynamics by outlining a set of possible outcomes 

for a person in her mid~20s who earns the median income for this age group of $30,000. 

Exhibit 28: A younger person considering changing careers sees less uncertainty, as wages 

are lower across the board 

Potentia! outcomes for a younger or lower~income person considering changing careers 

/ INITIAL INCOME $ 30,000 

Supplement 

Goldman Sachs Global Investment Research 

STAY 1N 

INDUSTRY A 

SWITCH TO 

INDUSTRY B 

10% ~ HIGH INCOME $ 40,000 

~ (GOOD STATE FOR INDUSTRY A) 

90~ LOW1NCOME $ 15,000 

(BAD STATE FOR INDUSTRY A) 

~o' ~ HIGH INCOME $ 25,000 

5~ {GOOD STATE FOR INDUSTRY B) 

50~ LOW INCOME $ 20,000 

{BAD STATE FOR INDUSTRY 8) 

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Exhibits 29 and 30 show the investment analysis for this scenario. Repeating the expected 

NPV analysis, we find that again the 'wait now and move only if industry A enters the bad 

state' strategy maximizes present value. However, plotting the values of the expected NPV 

from changing careers immediately against the real option value of waiting, while once 

again maintaining a constant variance {remembering that the variance is lower this time 

around), shows that the range of incomes where waiting is the optimal strategy has 

decreased. This is true for both the put option {for potential industry-A incomes) and the 

call option11 (for potential industry-B incomes),Hl Accordingly, a younger person, who faces 

less uncertainty thanks to her lower starting salary, should spend less time waiting and will 

be more likely to take the opportunity to change careers immediately. 

Exhibit 29: A young person's put option is worth less, making waiting less attractive 

Value of a young person'~ real put option vs. NPV of changing careers immediately 

Final 

NPV 20 

$800,000 

$600,000 

$400,000 

$200,000 

$0 

($200,000) 

{$400,000) 

0 5 

Industry A income, if good outcome 

40 60 80 

-NPV of switching if "switch 

immediately" is chosen 

Value of real option 

10 15 20 25 30 35 40 45 50 55 60 

Industry A income, 1f bad outcome 

Fmal 

NPV 

$800,000 

$700,000 

$600,000 

$500,000 

$400,000 

$300,000 

$200,000 

$100,000 

$0 

($100,000) 

Industry A income, if good outcome 

20 40 60 80 

0 5 10 15 20 25 30 35 40 45 50 55 60 

Industry A income, if bad outcome 

5Jource Goldman Sachs Global investment f?escarcn 

Exhibit 30: A young person's call option is also worth less. while the NPV from changing careers is worth more 

Value of a young person's rea! call option vs. NPV of changing careers immediately 

Fin a! Industry 8 income, if good outcome Final Industry B income, if good outcome 

NPV 10 15 20 25 30 NPV 10 15 20 25 30 

$140,000 $160,000 

$140,000 

$90,000 $120,000 

$40,000 $100,000 

$80,000 

{$10,000) $60,000 

{$60,000) $40,000 

$20,000 {$110,000) $0 

($20,000) 

10 15 20 25 10 15 20 25 

Industry B income, if bad outcome Industry B income, if bad outcome 

Source. Goldman Sachs Global Investment Rf'searc:h 

'

7 To Simplify the ana!ys1s (ensurmg a 'closed-form' so!ut1on) lor different levels of income m industry 8, we set the 

industry-A 1ncome to tts expected value of $17.500 m both the good and bad states {I.e. the mdustry·A mcome ts 

nowcertam). 

IH As before, to simplify the analysis (ensunng a 'dosed-form' solution) we agam set the other mdustry's mcome to 

11s expected value 

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Limiting the downside will encourage more individuals to make 

career transitions more quickly 

For both older, higher-income and younger, lower-income individuals, we notice the 

exactly the same pattern in the 'kink' points between waiting and changing careers 

immediately (Exhibits 26-27 and 29-30). 

For the put option: If the best outcome for industry A is worse than the worst 

outcome in industry 8 (adjusted for retraining costs), then it will always be optimal 

to move to industry 8, because the expected NPV of the 'move immediately' 

strategy rises above the value of the real option to wait. 

For the call option: If the worst outcome in industry 8 {adjusted for retraining 

costs) is better than the best outcome in industry A, then the NPV of moving 

immediately is greater than the option value of the call, and the person will move. 

The reason for this pattern is the 'bad-news principle,' which tells us that the decision to 

wait is only sensitive to the downward move in income. Stated differently, it is the ability to 

avoid the consequences of making the wrong decision (the 'bad news') that makes waiting 

attractive. 

Policies that limit the 'bad news' would encourage more people to make successful career 

transitions in the near term. For the put option this would mean placing a ceiling on wages 

under the 'good outcome in industry A' scenario, which would be hard to implement in 

practice. For the call option this would mean placing a floor on wages under the 'bad 

outcome in industry B' scenario. While subsidizing wages for a prolonged period would be 

infeasible, this policy support might only be needed in the short term to encourage 

employers to hire people who are transitioning between fields. 

The accumulation of new human capital through '!earning by doing' would lead to higher 

incomes over the longer term. Policy support could also take many other forms, including 

subsidized retraining and support in finding new jobs in industry B. Most importantly, since 

it is uncertainty which leads individuals to delay making career transitions, the existence of 

any credible policy support- even if most people never use it- should induce most people 

to make more immediate decisions to change careers. 

In the aggregate, the economy benefits from many individual 

decisions 

For the individual, the decision to join a new industry is a 'one~shot deal': his income may 

go up or down after he has already paid the cost of retraining and allowed his existing 

human capita! to erode. But for the broader economy~ the average effectiveness of 

retraining is viewed as the average increase in income for the people who do change 

careers. This benefit is experienced on a collective basis, not by the individual. 

If there are many new industries {and if the good and bad states in each are not perfectly 

correlated) then by averaging the outcome for many people who shift careers, we get a 

bell~curve (binomial) distribution, rather than the binary {Bernoulli) distribution that the 

person sees. As the number of people considering changing careers increases, the variance 

of the overall distribution of outcome falls towards zero (the bell curve quickly narrows and 

becomes more like a spike.) As this variance falls, the social option value of waiting (both 

call and put) also tends to zero. In the extreme case of infinite decisions, there is no 

uncertainty and the economy will always achieve the expected NPV. See Exhibit 31. 

Accordingly, if the expected NPV of moving to industry 8 is greater than the expected NPV 

of staying in industry A, then it will be optima! to move immediately. 

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Exhibit 31: The option value of waiting is high on an individual basis, but minimal from a 

broader economic perspective 

The distribution of the average wage narrows as the number of people changing careers rises 

50% 

i30% 

~ 

~2:0% 

~ 

10% 

S24,000 $30,000 $32,000 $34.000 

'10% 

, 9% 

' 7% 

' 4% 

3% 

' 2% 

'% 

0% 

$36,000 

A11erage annu11l wage for 1 or more worker$ {40 yr$ or old) after switching eareers 

->~~-Oroupo!Zwon.:ers 

..,._Groupof5workers 

-Groupof3workers 

• 1worker 

Source Goldman Sachs G/oballnves!ment Research 

~""'"""Groupcf4 workers 

~·Groupof100workers(RHS) 

~ 

l 

~ 

£ 

The economy can also internalize positive externalities from the decisions of more people 

to change careers. There could be benefits for the growth of industry B through 

normalizing the labor/capital mix {as firms in that industry are no longer deprived of labor), 

positive returns to scale and network effects from more people in the industry. For industry 

A, a quicker resolution to the labor overhang should also generate higher income for those 

people who do remain, because the reduction in labor will increase the marginal product of 

labor, giving fundamental support for higher wages. 

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and earnings", National Bureau of Economic Research 

Acemoglu 0., Autor D., Dorn D., Hanson G., Price B. (2014) "Return of the Solow paradox? 

IT, productivity, and employment in U.S. manufacturing", National Bureau of Economic 

Research 

Autor 0. (2013) "The 'task approach' to labor markets: an overview", National Bureau of 

Economic Research 

Autor 0. (2014) "Polanyi's paradox and the shape of employment growth", National 

Bureau of Economic Research 

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Disclosures 

This report has been prepared by the Global Markets Institute, the public policy research unit of the Global Investment Research Division of 

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Mr. Chairman and members of the committee, thank you for the 

opportunity to testify at today’s hearing. My name is J.R. Foster, 

Founder and CEO of Robert Louis Companies based in Cincinnati, 

Ohio. I feel very fortunate to have a few moments to speak with 

you about my story as a small business owner. 

Of the thousands of commercial real estate and investment banking companies in the country, I am a rarity among the bunch. My 

company is one of the only minority-owned full service commercial 

real estate brokerage, facility management and access to capital 

firms in the country. Our approach is two-fold. We help large corporations, government agencies and non-profits with their real estate brokerage and facility management needs—and do so in a way 

that can also help them reach their minority inclusion goals. Secondly, we are leading the charge in helping small business owners 

gain access to capital and debt financing. Last year alone, we 

helped over 200 small business owners secure $345 million in capital ranging from SBA loans to conventional and alternative debt. 

I am here today because I am one of the recent graduates of the 

Goldman Sachs 10,000 Small Businesses program and I’m proud to 

represent my fellow alumni, the program, and other small business 

owners who share my story. 

I personally knew I had the drive and determination to run my 

own company. So when I was 31 years old, my best friend and now 

business partner left two well-paying jobs on Wall Street to do so. 

What I did not realize is all of the hurdles that comes with being 

a small business owner, and a minority business owner at that. 

You take a leap of faith without knowing the underlying pitfalls 

that can derail, frustrate and leave some of the best minds in the 

country for broke. 

By our second year in business, I found myself lost in the sea of 

managing employees, customers, contractors, payroll, marketing, 

and the like. I needed something more than my corporate career 

had taught me. 

By chance, I was introduced to the Goldman Sachs 10,000 Small 

Businesses program (which we affectionately call 10KSB). After a 

year of course work, excellent class room engagement, and dialogue 

with the 100 (plus) small business owners in my cohort—I was able 

to excel in areas where I fell short. I also discovered that our local 

chamber of commerce in Cincinnati and other minority organizations like the Urban League have been helpful in growing the capacity of small business owners. 

Since graduating from the program, over the past three years we 

have increased our employee count, secured additional financing for 

growth and our revenue has gone from $350K in 2014 to well over 

$2MM at the end of the 2017. Basically, doubling year after year. 

What I ask of the Chairman and the committee is to help level 

the playing field for all small business owners. Having spent the 

last two days at the 10KSB Summit here in DC, I’ve continued to 

hear access to capital on the minds of my small business alumni. 

Far too often business owners are scaping funds together, using 

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mately put them in golden handcuffs. Even with access to SBA 

lending—having already tarnished their credit and over leveraged 

themselves with debt, they quickly become unable to qualify for 

government backed loans. I see this every day as my company 

strives to help companies gain access to capital. 

I ask that you consider helping a business like mine create a 

credit-friendly national lending platform and ecosystem that business owners can have a centralized place to secure capital and 

where banks compete for their business. 

Thank you for your time today. I have enjoyed sharing my small 

business experience and am grateful to be here. 

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Testimony of Ms. Jessica Johnson-Cope 

President & CEO 

Johnson Security Bureau, Inc. 

Before the House of Representatives Committee on Small Business 

Mr. Chairman and members of the Committee, thank you for 

your time and for the opportunity to testify at today’s hearing. I 

am Jessica Johnson-Cope, President and CEO of Johnson Security 

Bureau, Inc., located in the Bronx, New York. I am also the Vice 

President of the Cope Brothers & Sons, LLC dba the Soap Box, located in Brooklyn, NY. 

Johnson Security Bureau, Inc. (www.johnsonsecuritybureau.com) 

provides professional security guard and armored car services. 

Since 1962 three generations of my family have helped to protect 

people, places, and valuable property across New York City. My 

grandparents left their homes in the segregated South in search of 

opportunities. To them, and many others, small business ownership 

represented freedom: the chance to live the American dream while 

providing for their family. I am the beneficiary of their vision and 

hard work. 

For the past 10 years I have led Johnson Security. Shortly after 

I took over the business, due to the untimely passing of my father, 

I applied to the Goldman Sachs 10,000 Small Businesses Program 

with hopes of keeping Johnson Security’s doors open long enough 

to celebrate our 50th anniversary. Even though I had watched my 

father and grandmother achieve significant business milestones, I 

did not feel sufficiently equipped to help Johnson Security reach its 

full potential. 10,000 Small Businesses provided the tools I needed, 

in executive business education through a local community college 

partner (CUNY LaGuardia Community College); networking and 

peer learning opportunities with other program participants; business advisory services and mentoring; and preparation to obtain financing. 

Since completing the program, Johnson Security has created over 

150 jobs. Our revenues have increased more than 10-fold. Our operations have expanded into two neighboring states. We have done 

business with at least seven (7) other program graduates. Additionally, Johnson Security has successfully applied for financing to support our growth. Our team is now preparing for the next phase of 

innovation and job creation. 

Based on Johnson Security’s success, and using lessons learned 

from 10,000 Small Businesses, my husband and I started another 

company, the Soap Box (www.soapbox.nyc), where we continue his 

family’s entrepreneurial legacy. The Soap Box provides premium 

laundry services in the Bedford Stuyvesant neighborhood where we 

live. The Soap Box not only allows us to save our clients time, it 

allows us to employ seven (7) people, and to transform our community, while collaborating with other local businesses. Our work 

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comes with challenges though as we try to navigate burdensome 

regulations. Nonetheless we are determined to continue to grow. 

The impact of the 10,000 Small Businesses program is evidenced 

not only in the results I’ve cited, but also in the outcomes the 

2,200+ program alumni who have gathered here in Washington, 

D.C. this week have experienced, and in the research data that 

have been presented. 

My peers and I face many challenges as we grow our businesses. 

The current business environment makes it increasing difficult for 

small businesses to survive, let alone grow. One challenge is finding capable talent. In addition to leading our family businesses, I 

serve on the New York State Workforce Investment Board. In this 

capacity, I hear of many job candidates who lack technical skills 

that are required as industries advance. I also hear of a number 

of people entering the workforce who lack key soft skills, such as 

communication and critical thinking skills. 

I know countless small business owners who welcome workforce 

development investment from the government. By providing small 

businesses with better information on and access to local Workforce 

Innovation & Opportunity Act (WIOA) initiatives, you can make a 

significant difference in addressing some of the workforce disadvantages small businesses like our face compared to larger corporate 

competitors. 

Another challenge is in obtaining the capital firms like ours 

need, which can be even more difficult for minority and womenowned businesses. Johnson Security received financing that provided working capital to mobilize new projects, cover payroll expenses, and expand our marketing efforts. You can ensure that our 

nation’s small businesses can effectively utilize the U.S. Small 

Business Administration (SBA) lending programs that are intended 

to benefit firms like ours. 

Federal contracting is another area where you can remove some 

barriers to small business success. Johnson Security is a federal 

contractor that has leveraged federal small business programs as 

a business development tool. There are several agencies that fall 

short in meeting the small business contracting goals. You can put 

stronger accountability measures in place to ensure more contracts 

are awarded to our nation’s qualified small businesses. 

In closing, the Goldman Sachs 10,000 Small Businesses program 

has been instrumental in the growth of Johnson Security Bureau, 

Inc., the Soap Box, and more than 6,700 other program alumni, 

particularly in job creation, and in access to capital. I encourage 

you to promote the program to viable firms in your districts. Watch 

and see what impact those businesses will have on our economy. 

I also implore you to consider making changes to some of the regulations that are hindering small business growth. 

Mr. Chairman, I thank you for your time and attention this 

morning. I look forward to the work this Committee will continue 

to do to help make our nation’s Small Businesses Big! 

Æ 

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