Is Entrepreneurship Dead?: The Truth About Startups in America 9780300235098

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Is Entrepreneurship Dead?

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IS ENTREPRENEURSHIP DEAD? THE TRUTH ABOUT S TA R T U P S I N A M E R I C A

❉ ❉ ❉

S COT T A . S H A N E

New Haven and London

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Published with assistance from the foundation established in memory of Amasa Stone Mather of the Class of 1907, Yale College. Copyright © 2018 by Scott A. Shane. All rights reserved. This book may not be reproduced, in whole or in part, including illustrations, in any form (beyond that copying permitted by Sections 107 and 108 of the U.S. Copyright Law and except by reviewers for the public press), without written permission from the publishers. Yale University Press books may be purchased in quantity for educational, business, or promotional use. For information, please e-mail [email protected] (U.S. office) or [email protected] (U.K. office). Set in Gotham and Adobe Garamond types by Newgen North America. Printed in the United States of America. Library of Congress Control Number: 2017954786 ISBN 978-0-300-21211-2 (hardcover : alk. paper) A catalogue record for this book is available from the British Library. This paper meets the requirements of (Permanence of Paper).

ANSI/NISO Z39.48-1992

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To Hannah, Lynne, and Ryan

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Contents

Preface Introduction

ix 1

1 Something Is Happening, but We Don’t Know What It Is

17

2 The Good News: Most Measures of Entrepreneurship Have Improved

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3 Entrepreneurial Earnings Are on the Rise

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4 Riding High

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5 The Implications of Fewer Employer Startups

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6 It’s Not a Lack of Capital

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7 Don’t Blame the Regulators

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8 High Taxes Are Not the Cause

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9 It’s Not a Lack of Immigration

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10 An Aging Population Isn’t the Reason

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11 Slowing Population Growth Isn’t the Explanation

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12 Rising Student Debt Is Not the Cause

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13 Don’t Blame a Loss of Moxie

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CONTENTS

14 Employees Have Become Too Expensive

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15 Chains Have Replaced Independent Employers

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16 The Story the Data Are Telling

216

Notes

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Index

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Preface

This is not the book I intended to write. About two years ago, I sent a proposal to William Frucht at Yale University Press for a book explaining why entrepreneurship in the United States was in long-term decline. After concluding a series of conversations with entrepreneurs, academics, government officials, media pundits, and representatives of major foundations that support economic development, I had become convinced that something was seriously wrong. The experts showed me evidence of a long-term decline in business formation and gave me earnest explanations of what had gone wrong. Each one encouraged me to investigate the problem and then write a book explaining the causes and offering his or her solution. It took me longer than expected to write this book because my initial premise was wrong. American entrepreneurship isn’t in decline. But it has changed. The entrepreneurs, academics, government officials, media pundits, and economic development professionals I had spoken to were incorrect because they had looked at only a small part of the total picture. Because they often sought to advocate a particular set of policies, they had drawn conclusions from small bits of data. Examination of all of the data tells a far more complex story. The Twitter-length summary of my two and a half years of investigation is this: “Entrepreneurship up, but new employers down. Existing small biz doing OK. Labor costs and chain growth to blame.” ix

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P R E FA C E

If you think you can understand complex economic phenomena from tweets, save your money. Put the book back on the shelf. You have the answer. But for those of you who want to understand what has happened to entrepreneurship in America, read on. It’s an interesting and complex story, and one that few people in government, the media, or academia know. As someone whose job is to follow statistics on entrepreneurship intensively, I was surprised at where the data took me. I looked at statistics from the Internal Revenue Service, the Federal Reserve, the U.S. Census, the Bureau of Labor Statistics, and many other sources. At first they were a jumble of conflicting numbers, but eventually they began to tell a story. It wasn’t the story I set out to tell. Once I had all the data patterns, I went back to all the theories the policy makers, academics, and media folks were proposing, and I compared the data to their explanations to see whether they could possibly be correct. In a few cases, they could. In most cases, they could not. The data were simply inconsistent with the explanation on offer. I ended up looking through many more data sources, articles, and books than I had intended. From that process, I discovered the work of several obscure researchers who had figured out what was happening when the rest of us were largely clueless. I am indebted to the authors of the surveys, research projects, books, and articles who gathered and summarized these answers. Their work was crucial to my effort to describe the reality of entrepreneurship and how it has changed. I had the great fortune of working with Mark Schweitzer at the Federal Reserve Bank of Cleveland and Ian Hathaway of Ennsyte

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P R E FA C E

Economics, both of whom helped this book immensely. While an astute reader will see that I do not necessarily agree with everything these authors have written about entrepreneurship in recent years, their analysis of the topic has forced me to sharpen my own analysis and to look harder at what the data showed. Over the years, many colleagues have taught me a great deal about the topics discussed in this book. Howard Aldrich, Per Davidsson, Frederic Delmar, Jon Eckhardt, Bill Gartner, Dave Hsu, and Nicos Nicolaou stand out as particularly important. This book would not have been possible without their help. My editor, William Frucht, believed in this project when many others did not. He did not flinch when the book took a completely different turn from what I had initially proposed. For his willingness to take a chance on it and stick with it through the turns, I am truly grateful. Lastly, I would like to thank my wife, Lynne, daughter, Hannah, and son, Ryan. They have all helped me in their own ways: Hannah and Ryan by being excellent playmates when I needed breaks from writing, Lynne by encouraging and supporting my efforts, including the creation of this book.

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Introduction

We Americans love entrepreneurs. As Malcolm Gladwell wrote, we see company founders like Sergey Brin, Bill Gates, Steve Jobs, and Mark Zuckerberg as “our new prophets.”1 Gladwell aside, however, this attitude is not new. Entrepreneurship has been central to our nation since its inception. Entrepreneurs have played an important role in the development of new technology, the generation of wealth, and the creation of jobs and have been a major reason other nations have looked to the United States as an example. As Alexis de Tocqueville wrote (not entirely approvingly) nearly 200 years ago, “As one digs deeper into the national character of the Americans, one sees that they have sought the value of everything in this world only in the answer to this single question: how much money will it bring in?”2 The importance of entrepreneurship to America means that those in Washington take very seriously any indication of weakness in its performance. Lately, many policy makers and pundits have become worried. They have seen evidence of stagnation, even a downturn, in American entrepreneurialism. As David Burton, senior fellow in economic policy at the Heritage Foundation, told a congressional committee in 2015, “Entrepreneurship is in decline.” Americans, it appears, are not starting new businesses with paid employees at the rate they once did—at least according to several

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INTRODUCTION

data sources. For instance, the formation of “new employers”—the term the Census Bureau has given to companies with paid workers—has fallen below its replacement rate. Since 2008, according to Census Bureau records, the number of employer businesses shutting down each year has exceeded the number formed.3 If entrepreneurship were in decline, the implications could be enormous. Shrinking entrepreneurship could mean a more rigid economy, one less able to respond to shocks. Older firms are less flexible than new firms. They cannot hire and fire as quickly or shift direction as easily. A reduction in entrepreneurial activity could thus make it more difficult for the economy to respond to changes. New technology might spread through the economy more slowly; labor markets might adapt less well to recessions and recover more slowly during expansions. New employers are a key source of job creation. If American entrepreneurs are founding fewer new companies, then the economy might be producing fewer jobs, leading to less employment in the long run. The opportunity to start companies plays an important social and economic role. Starting a business has historically been a key avenue for getting ahead for those not born wealthy. A big decline in employer firm formation might mean a dramatic cut in class mobility. Janet Yellen, the chair of the Federal Reserve, does not say very much about entrepreneurship and how it affects economic mobility, but occasionally she addresses the topic. In October 2014 at the Conference on Economic Opportunity and Inequality in Boston, Yellen highlighted the adverse effects a decline in entrepreneurship could have on economic mobility: “The ownership of private businesses is a significant source of wealth and can be a vital source of opportunity

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INTRODUCTION

for many households to improve their economic circumstances and position in the wealth distribution. . . . It appears that it has become harder to start and build businesses. The pace of new business creation has gradually declined over the past couple of decades.”4 One of the hallmarks of entrepreneurship is its ability to create many Horatio Algers. Only a small fraction of new employers grow and generate wealth for their founders. If that fraction remains roughly constant yet the number of companies formed declines, it could mean less economic mobility. Fewer successful new businesses could mean fewer people riding them up the economic ladder. Moreover, economic mobility does not just come from highgrowth companies. Entrepreneurship offers a tax-favored way to earn a living and lets people boost their incomes by increasing the amount they work. Even founders of small businesses that never grow often move from poor to middle class. Another reason policy makers should be concerned about a potential decline in entrepreneurship is that new business creation is important to economic productivity. Productivity—the ability to generate more output from a given amount of inputs—is a key way for an economy to improve living standards, and investing in machinery and equipment boosts productivity. New technologies and equipment allow businesses to produce more output for each hour of worker labor. Entrepreneurship plays an important role in generating capital investment. New businesses tend to make larger investments in capital equipment and structures than comparably sized companies already in operation because these investments are necessary to get businesses going. If entrepreneurship were to decline, businesses might engage in less capital investment, which in turn would reduce productivity growth. New businesses also tend to be created with

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INTRODUCTION

current technology, which generally yields higher productivity than older technology. A decline in new businesses could also mean a decline in innovation. Not all new technologies are developed by new and small companies, of course, but many are. Small firms produce more new product innovations per dollar of research and development expenditure and per employee than large firms.5 These innovations are, of course, a key to productivity growth. When a small company comes up with a new product or service—the personal computer or the electronic spreadsheet—that advancement contributes to productivity. In contrast, businesses that die are generally the least productive. Companies that make efficient use of resources are more likely to stick around than less efficient ones. And this efficiency increases with turnover: new businesses often start because they have a better— more productive—way to accomplish the same goals as existing businesses. Constant formation of new, more productive businesses to push aside older, less productive businesses is one way that productivity increases across an economy. If this process were to slow down, the rate of productivity increase could slow as well. Many people have seen the data on new employer firm formation rates and are sounding an alarm. White papers, columns, and blog posts decry the problem. “American Entrepreneurship Is in Decline,” the headlines blare, and something needs to be done to stimulate it. Editorials assure us that policy makers must intervene to protect the country’s business founders from economic ruin. The suggestions range from issuing startup visas and boosting entrepreneurial education, to fixing the tax code, subsidizing credit, changing our culture, cutting regulation, and investing in broadband.6 The list goes on and on. In 2015, David Burton of the Heritage Foundation offered ninety-seven separate recommendations to Congress, relating to “tax policy, securities regulation and capital access, health 4

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INTRODUCTION

care, energy and environmental regulation, administrative law and regulation, employment and labor law, immigration and the legal system.”7 There are several issues with this rush to offer up solutions. The first is identifying whether there really is a problem. One indicator of entrepreneurship—the rate at which new employers are being created versus the rate at which existing ones shut down— doesn’t look good these days. But it is not the only measure of entrepreneurship; we need to look at other measures before we conclude that entrepreneurship per se is in decline. Also, these data are from the U.S. Census, and different data, like those from the Federal Reserve and the Bureau of Labor Statistics and the Internal Revenue Service, do not always agree with the Census. We should look at those sources before we rush to conclude that American entrepreneurship is in decline. The second is the problem that the rate of creation of highpotential businesses (as measured by angel- and venture-capitalbacked companies) has gone up over the same period that the rate for formation of more typical employers has gone down. We need to know if the rise in the rate of creation of those kinds of businesses makes up for the decline in the rate of formation of more typical employers before we conclude that something is wrong. But no one is weighing the value of the types of new businesses that are being created at a faster pace against the value of the companies that are being started at a slower pace. If we are creating more venture capitaland angel-backed companies, but fewer mom-and-pop retail shops, that might be OK for job creation and GDP growth. A few extra Facebooks and Googles are probably worth a lot of clothing shops on Main Street because they produce a lot more jobs and economic output. Third, the decline in the rate of formation of new employers might not in itself be a problem. Unless the decline has adversely 5

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INTRODUCTION

affected a key aspect of the economy, like productivity, employment, or GDP growth, it does not matter. People often think of new employers like motherhood, baseball, and apple pie. Somehow, they think, a high rate of business creation is important in its own right. But employer firm formation is not an end in itself. When people are creating new companies, they are allocating resources—their time and money—to the formation of those entities. If their time and money would be better spent on other things, for example, working for big companies or on leisure activities, then a high rate of new employer creation is not a good thing; it is a misallocation of resources. What we really need to know is whether the decline in the rate of employer creation has adversely affected our economy or society. The data on that question are not really convincing, as I will show. No one has linked the decline in the rate of employer creation to a fall in overall employment, a slowdown in productivity, or deceleration of GDP growth. In fact, it is possible that the decline in the rate of employer creation has kept employment, productivity, and GDP growth from being worse than it otherwise would have been. Fourth, it’s not clear that any of the proposed solutions to the decline in the rate of new employer firm formation will work. Editorial writers and elected officials tend to think that complex problems have easy solutions. Seeking to justify a position on one side or another and advocate pet policy positions, many observers look only at the numbers that fit their world views—then propose solutions that don’t fit the problem. Whatever has happened with entrepreneurship in this country will not be fixed simply by deregulating, cutting taxes, or issuing immigrant visas. The patterns may result from factors that government does not control. And every proposed solution—to anything—has

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unintended consequences. Bearing that risk makes sense only if the proposed solution addresses the actual cause of the problem. To figure that out, we need to examine the data and trace out what the decline in entrepreneurship actually consists of and whether the cause we have proposed is plausible or not. This book offers a careful look at the data—all of it—to see what has happened to entrepreneurship in America over the past thirtyplus years. I look closely at the indicators from the Federal Reserve, the Bureau of Labor Statistics (BLS), the Census Bureau, the Internal Revenue Service (IRS), and the rest of the alphabet soup of federal agencies that have collected good data on American entrepreneurship over the past several decades. I look at the private sources as well—the data from top academic institutions, like the University of Chicago, and trade associations, like the National Federation of Independent Business, that have been gathering the numbers for a long time. Those sounding the alarm are not completely wrong. Some measures are clear and should concern policy makers. Americans have cut back dramatically on starting new businesses with employees. In 2013, according to Census Bureau data, the per capita rate at which Americans started new employers was only half of its 1977 level. That is a big decline and one worthy of scrutiny. Other figures are also alarming. The BLS tells us that unincorporated self-employment—the fraction of the labor force that works for themselves in unincorporated businesses—has sunk to record lows, hitting 6.4 percent in 2015, down from 8.7 percent in 1975. The share of American households owning a business has fallen from 14.2 percent in the mid-1980s to 11.7 percent in 2013, the Federal Reserve estimates. And Americans today are less likely to start companies when they lose their jobs. The fraction of laid-off job seekers

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INTRODUCTION

looking to start companies is well below 1980s levels, according to data from the outplacement firm Challenger, Gray and Christmas. And employment in new companies is down substantially. The Census Bureau finds that American companies less than one year old accounted for only 2.0 percent of American employment in 2013, down from 5.7 percent in 1977. Yet understanding what has happened to entrepreneurship in America over the past thirty years requires more than taking a casual glance at a couple of numbers. Because no one statistic measures entrepreneurship writ large, figuring out what is going on requires looking at all of the numbers and piecing together the story they collectively tell. What has happened to entrepreneurship in America is complicated. It’s not that the data lie. The measures of entrepreneurship described above have shown long-term declines. The catch is that other data tell a different story. Put together, the evidence doesn’t warrant the conclusions that many pundits and policy makers have drawn, and it doesn’t support the solutions they are offering. The first key fact is that entrepreneurship per se is not in decline. But a particular kind of activity has been dropping over the past three-plus decades. The rate at which Americans are starting and running employer firms has fallen. However, businesses with employees are actually a small fraction (around one-fifth) of all U.S. companies. Americans haven’t stopped creating companies. Far from it. As I will show in more detail in chapter 2, IRS data indicate that the number of businesses has been growing on a per capita basis. Americans, it turns out, are creating and running businesses at a higher rate than they used to—but they are mainly starting and running businesses without employees. That nuance suggests that

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the problem with American entrepreneurship and the effective solutions to that problem are different from what many are suggesting. Boosting startups in general probably isn’t the answer, because a fall in startup creation isn’t the problem. Other patterns also cast doubt on the simple “entrepreneurs are in trouble” argument. High-potential startups backed by external equity investors are doing very well indeed. As I will show in detail in chapter 4, data from a variety of sources, including the National Venture Capital Association (the trade association of the venture finance industry) and the Center for Venture Research at the University of New Hampshire, indicate that more startups are getting angel and venture capital financing than a decade or two or three ago. And the outcomes of investments in those businesses are better than they were in the mid-1980s. America might be generating fewer typical startups—the ones that don’t grow and quickly die—but more high-potential companies that add workers, grow substantially, and soon go public or get acquired. If the rate of creation of new employers is down but the rate of creation of high-potential companies is up, then the decline has to be specific to factors that affect Main Street and not Sand Hill Road. It turns out, however, that it is not just a handful of new companies backed by left coast financiers that are doing better than several decades ago. A wider range of small business owners are doing well. Older small companies—the ones that entrepreneurs have been running for many years—have greatly improved. Business failure rates are down and real (inflation-adjusted) earnings are up compared to the 1980s. For several decades, households led by people who own their own businesses have been doing better than those led by people who work for others.

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Finally, even if the decline in the rate of employer creation was adversely affecting our economic well-being, the “solutions” being offered aren’t answers at all. As I will show, there is no compelling evidence that barriers to immigration, excessive regulation, too high taxes, student loans, or any of the myriad other so-called causes of the decline in rates of new business creation are actually responsible for the decline in the pace of employer firm formation. If these factors are not the causes of the decline, then changing them will do nothing to boost the rate at which Americans form businesses with employees. Combating the decline in new employer firm formation, if it is even a genuine problem, requires addressing the factors that are really responsible, rather than the many irrelevant factors that are often put forward as solutions, generally to further someone’s pet policy. Consider, for example, the call for more visas for immigrants seeking to start companies in the United States. There is little reason to think this policy would do anything to stem the decline in employer businesses. For startup visas to reverse this trend, two patterns would need to be present in the data. First, the decline in new employer firm formation that has occurred over the past thirty-plus years would need to have resulted from a decline in immigration. But the data show the opposite. Over the past thirty years, immigration has skyrocketed while the rate at which Americans start businesses with employees has plummeted. Second, immigrants would need to be more likely than nonimmigrants to start and run businesses with employees. But there is nothing in the data to suggest that the fraction with employer businesses is different between immigrants and non-immigrants, or that the incentives that lead American entrepreneurs to avoid employing others do not apply equally to immigrants.

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Another common “solution” to the decline in new employer business creation is tax cuts. Again, it is difficult to see how tax increases account for a nearly four-decade fall in new employer business formation. Income tax rates have tended to decline, not increase, over this period. If high taxes were the problem, then falling taxes should not be associated with a decline in employer firm formation. Or consider access to credit. American entrepreneurs are in trouble, the argument goes, because they cannot get the credit that they need. Banks cannot make money lending to small companies and are exiting the market, starving new companies of needed financing. Yet while it is true that many banks have cut back on making these loans, small business owners appear to be borrowing more now than they did in the late 1970s. If so, a lack of access to credit hardly seems to be a cause of their problems. In addition, the average small businesses seems to be doing fine. Small company failure rates are down and earnings are up. If credit access were really a problem, then all small businesses would need to be affected, not just new ones. The message echoing through the blogosphere is too simplistic. American entrepreneurship is not in decline. But it has changed in many ways. What can we learn from trying to put together the different pieces of data into a coherent story? If the overall startup rate has not declined over the past thirtysix years, but the startup rate of businesses with employees has gone down, then we cannot say that all entrepreneurship is declining. And if high-potential businesses and existing small businesses are not adversely affected by the trends that have discouraged typical new employers, then the cause of the reduction is specific to the kind of run-of-the-mill new employer businesses— dry cleaners, restaurants, retail stores, and insurance brokers—that make up the bulk

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of startups in America. Moreover, if older businesses, run by entrepreneurs who started them many years earlier, are living longer and making more money than they once did, we can’t really argue that they are in dire straits. This book provides a more precise and nuanced explanation for the change in American entrepreneurship than the story told in the policy white papers and blog posts. Ironically, the story that emerges is no less interesting than the bold headlines. In a nutshell, the story is this: entrepreneurship per se is not in decline in the United States, but American entrepreneurs are not starting businesses with employees at the pace they did a generation ago. That decline may have consequences—for employment, innovation, investment, and the overall state of the American economy. But we don’t know for sure that that is the case. We need to understand why the rate at which people start businesses with employees is down—way down—from what it was in the late 1970s and why, instead, Americans are starting and running businesses without employees. And we need to know why these changes haven’t adversely affected the rate of formation of highpotential businesses and why their impact on the stock of existing businesses with employees is much more muted. It could be that there is no problem at all. Technology simply has made it possible for more people to become entrepreneurs without employees. My neighbor Margaret is one of these new-style entrepreneurs, the owner of a non-employer business. A stay-at-home mom with school-age kids, she needs some extra income because her husband’s salary has been flat for several years. So while her children are at school, from 9:30 to 3:00, Margaret is an entrepreneur. A decade or two ago, she might have gotten a part-time job at a store in the shopping mall to make ends meet, but instead she sells things

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INTRODUCTION

on eBay. She makes more than she would in a minimum-wage job, can set her own hours, and can’t be fired or laid off. Her example shows both the opportunities and the incentives that are driving the changes in entrepreneurship. With the exception of 2008, on a per capita basis, America has had more non-employer businesses like Margaret’s every year since 1997, when records began to be kept on an annual basis. Nonemployer businesses are, in the language of the Census Bureau, which tracks them, “businesses with no paid employment and payroll.” This self-evident definition indicates an important difference between these firms and employer businesses: non-employer businesses don’t create jobs. Margaret is a fairly successful eBay seller. She has thought about hiring an assistant to post pictures of the goods online and respond to inquiries, but she doesn’t need someone every week, only during busy periods. As for expanding beyond that, she feels employees are too costly, not because of the salary but because of the benefits. She has more flexibility using contractors to do the advertising, fulfillment, and accounting that she doesn’t have time to undertake. A generation ago, Margaret could not have pulled this off. Before eBay existed, the only way to sell secondhand items was in a physical location: she would have had to travel to flea markets or else had a store. Traveling to flea markets would have kept her away from her family on weekends; a store would have meant rent, furnishings, security, and insurance—all of which cost money. And it would have meant employees: she could not have run such a business part-time, if only because she couldn’t cover her expenses staying open only during school hours, so she would have had to hire someone to sit at the counter when her kids were home. Today she has a going concern with the help of a smartphone, an Internet connection, a few

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computer programs such as QuickBooks, and frequent visits from UPS and FedEx. And she has no employees. There is also another trend. Americans are spreading their entrepreneurial activity across more and more businesses. Where one company would have sufficed thirty years ago, they now pursue the same opportunities through two businesses or more. Another of my neighbors, a fellow named Alex, has moved pretty heavily into the sharing economy, renting vacation homes he owns through online sites like HomeAway and Airbnb. Each of Alex’s three properties—a beachfront condo in Florida, a ski condo in Utah, and a pied-à-terre in Manhattan—is owned by a separate limited liability company. That structure, his lawyer told him, was the best way to minimize his exposure. Alex inherited the properties from his parents. When they owned the apartments, in the pre-Internet era, short-term rentals were too difficult to do; they rented the apartments on yearly leases and reported the income on their personal income taxes. Alex runs three times as many businesses as his parents to engage in the same amount of entrepreneurship. A third trend is the growing success of existing companies. Small businesses are doing better today than they did thirty years ago. They are living longer and providing more income. The improved performance and longevity of existing small businesses has an important effect on startup rates. If existing companies aren’t going under, fewer entrepreneurs are needed to replace them. Moreover, the people running successful companies can expand to new locations more easily than new entrepreneurs can start up. Chains, even little two- and three-outlet ones that are limited to a single city, are growing at the expense of new employer businesses. Because the amount of entrepreneurial activity a place can support depends on customer demand, the rate of new business formation is limited by the degree to which existing businesses serve the market. 14

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If existing companies are doing fine and expanding, new companies are not needed to replace them. This is self-evident in long-established locations. If Ray owns a pizzeria on Flatbush Avenue in Brooklyn, New York, he may satisfy most of the demand for pizza within a five-block radius. Ray has been running his pizza place for twenty years, which is a pretty long time according to the statistics. Before he bought the place, two previous owners had made pizza in the same location, one after another, but neither business made it to age five. With Ray’s Pizza humming along, there isn’t much opportunity for anyone else to start a traditional pizza place in Ray’s neighborhood. He pretty much meets the demand for pizza in the area. He faces competition from a dozen or so other types of inexpensive restaurants, from nationwide chains to locally owned coffee shops to trendy new offerings, but he can rely on a constant demand for pizza. Every neighborhood needs at least one pizza place. If Ray’s went under, someone else would no doubt open up a pizza shop somewhere nearby. But as long as Ray is successful, that is unlikely to happen. Now think about a place like Arizona. Over the past forty years, neighborhoods grew up out of the desert as developers built houses and offices farther out from the center of Phoenix. This created a new demand for pizza in places where there had been none. Who provided it? It turns out that the pizza parlor owners in the center of Phoenix had a big advantage over would-be entrepreneurs in starting parlors in the outlying areas. With the development of information and communications technology, they could add outlets and run them better than individual pizza shop owners could start their first restaurants. Much of the pizza outlet growth in greater Phoenix was existing operators. If you aggregate data like this, part of the reason new business formation numbers are down is that existing businesses are meeting the demand better than they once did. 15

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In the chapters that follow, I will challenge the argument that policy makers must intervene in the marketplace with a myriad of policies to reverse a decline in American entrepreneurship. I will show that American entrepreneurship isn’t in trouble. Far from it. The rate at which Americans create non-employer and high-potential businesses is up, as is business ownership. Earnings of business owners have risen in inflation-adjusted terms and have become a more important source of Americans’ compensation than was the case in the 1980s. The “entrepreneurship decline,” if such a pattern is real, lies in the decrease in the rate at which Americans form new businesses that employ others, and in the tendency of existing small businesses to not employ as many people as they once did. But even that may not be a true problem. Fewer people may be starting new businesses because existing businesses are doing better, making more money, and surviving longer than ever before. Moreover, the decline in the rate of new employer business formation may simply reflect a more efficient allocation of scarce resources in the economy toward big business and non-employers. Following the advice of policy makers and opinion leaders to cut regulations, reduce taxes, boost immigration, cut student debt payments, or any of the myriad other recommendations for reducing the decline in entrepreneurship is likely a fool’s errand. There is no evidence that the reduction in the rate of formation of employer businesses has hindered job or wealth creation, reduced productivity, or limited economic mobility. Nor is there evidence of much of a link between these policies and entrepreneurial activity. As you will see in the coming pages, to those who are concerned about American entrepreneurialism, I say, “Don’t worry. We’re good.”

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ONE Something Is Happening, but We Don’t Know What It Is

We keep reading that Americans are less entrepreneurial than they were a generation ago. “U.S. entrepreneurship is in decline,” Ben Casselman, Fivethirtyeight’s chief economics writer, said in a 2014 article on trends in startup rates.1 “We are behind in starting new firms per capita,” writes Jim Clifton, chairman and CEO of Gallup, calling it “our single most serious economic problem.”2 “Business deaths now outpace business births for the first time since researchers started collecting the data in the late 1970’s,” explains J. D. Harrison in a Washington Post article.3 This is not a recent development. The decline was exacerbated by the Great Recession of 2008, but it has been going on since at least the late 1970s, when government researchers first began tracking the data. Dane Stangler, the vice president of research and policy at the Ewing Marion Kauffman Foundation, writes that “the overall pace of business creation, which had been falling steadily for many years, decreased precipitously in the 2008 –2009 recession.”4 The trends—at least according to pundits and reporters—are grim. As Annie Lowrey puts it in New York magazine, “The country is getting less entrepreneurial.”5 Fewer people are creating new firms and older businesses are living longer. She continues, “In aggregate,

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firms are aging. People are starting fewer new businesses, and older businesses are doing better than their younger competitors. For all the talk of ‘disruption’ in today’s economy, it is better to be a big, old incumbent dinosaur than it is to be a lean, mean startup.”6 Pundits, reporters, and even policy makers who express concern about a long-term decline in entrepreneurship in America aren’t just offering their opinions. They are reacting to the data. Statistics on American entrepreneurship since the 1970s tell a tale of changes that disturb many people. To understand the alarm, we need to look at the data these authors are examining.

Unincorporated Self-Employment Is in Decline

One easy measure of entrepreneurship is self-employment, the fraction of people in the U.S. workforce who are in business for themselves. This percentage is readily available, having been collected by the Bureau of Labor Statistics (BLS), our country’s official tracker of the labor force, for decades through regular surveys. While some observers claim that self-employment, as a measure of entrepreneurship, lumps independent contractors in with people running their own companies, it does help capture what has happened over the past few decades. It shows us how many people work for themselves rather than someone else. Every month, the BLS and the Census Bureau together compile a survey called the Current Population Survey. They interview over 70,000 American households designed to represent the entire population over the age of fifteen that is not institutionalized or in the military. The story told by the Current Population Survey’s selfemployment measure is unmistakable. The fraction of people in the labor force who work for themselves but are not the heads of corporations—something called “unincorporated self-employment”—is 18

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Figure 1.1. The Unincorporated Self-Employment Rate Source: Created from data from the Bureau of Labor Statistics.

in long-term decline. These people represented 8.7 percent of the labor force in 1975 and 6.4 percent in 2015 (figure 1.1). It is easy to get tricked into thinking this decline isn’t that large. Unincorporated self-employment as a fraction of the labor force was never that large. But the decline between 1975 and 2015 amounts to a fall of more than 25 percent. Buried in the BLS’s numbers are a couple of other indicators of unincorporated self-employment that corroborate what has happened to this primary measure. One of them is part-time self-employment. Unlike the main measure of unincorporated self-employment shown above, which captures what people do in their primary job, part-time self-employment indicates what people do in any secondary work they undertake. It’s a valuable measure because many people need to work two jobs to make ends meet. While the data on secondary self-employment do not cover as long a period as the figures on primary self-employment, and far 19

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Figure 1.2. The Secondary Self-Employment Rate Source: Created from data from the Bureau of Labor Statistics.

fewer people engage in self-employment as their secondary occupation than as their primary occupation, the trend is similar. This fraction has declined from 1.55 percent in 1999 to 1.11 percent in 2015 (figure 1.2). Again, do not be deceived by the small numbers. The magnitude of the decline is substantial. In just sixteen years, the secondary unincorporated self-employment rate has fallen by 28 percent. As I mentioned earlier, many observers believe unincorporated self-employment is a poor measure of “entrepreneurship.” Working for oneself is not synonymous with running a business. Many selfemployed people are really independent contractors—people who have chosen (or have been forced by circumstance) to be paid through 1099s as opposed to W-2 forms. Therefore, using self-employment data to tease out what has happened to entrepreneurship requires an interpretation of what different types of self-employment mean.

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To figure out the unincorporated self-employment rate, the BLS surveys Americans to first determine if they are employed. If they are working, it then asks if their employer is a private company, a nonprofit organization, the government, or themselves. Here it gets tricky. Self-employed workers are further separated into those who have incorporated their businesses and those who have not. If you work for yourself and you have not incorporated your business, your data go into the measure of unincorporated selfemployment. That’s the number we looked at above. But if you have set up an S or C corporation, you will be counted as something called incorporated self-employed. The incorporated self-employment series is available only from 1989 to 2014, so it can tell us only about patterns over a shorter period than unincorporated self-employment. But incorporated selfemployment represents economic activity that much more closely resembles “entrepreneurship” than unincorporated self-employment. Few people set up a C or S corporation simply because they have been employed as contract workers or receive 1099 income. Incorporated self-employment tells a very different story from unincorporated self-employment (figure 1.3). Whereas the unincorporated variety has steadily declined since 1989, the incorporated version is higher now than it was in the late 1980s, when the government began to track it. And the increase is substantial. From 1989 to 2015, incorporated self-employment rose from 2.9 percent of the labor force to 3.7 percent. That’s a 28 percent rise in sixteen years. We now have the first chink in the armor of the “entrepreneurshipis-in-decline” story. Incorporated self-employment tells the opposite story— one of increasing entrepreneurial activity. Explaining the trends in self-employment thus requires two separate explanations, one for incorporated self-employment and one

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Figure 1.3. Incorporated Self-Employment Rate Source: Created from data from the Bureau of Labor Statistics.

for unincorporated self-employment. In fact, if we add the two rates, we find that there has been essentially no trend in self-employment. Researchers at the Pew Foundation analyzed the BLS data and concluded that the combined rate of 10 percent in 2014 is the same as it was in 1976.7 What’s happened is that the split between incorporated and unincorporated self-employment has changed, with incorporated selfemployment taking an increasing share of the total. It may be that the factors that have driven unincorporated self-employment down are specific to working for yourself but not to running an S or C corporation. Or it may be that more people have the sophistication, and access to advice, that leads them to incorporate, or that changing tax laws or regulations make it more advantageous to incorporate. It could be both. The Pew Foundation analysts have an interesting explanation for why unincorporated self-employment has fallen while incorporated self-employment has risen. Most important, this explanation doesn’t suggest that entrepreneurship per se is in decline. The researchers 22

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argue that unincorporated self-employment has fallen because the share of self-employment in agriculture, forestry, and fishing has been decreasing. These fields tend to have large numbers of unincorporated self-employed workers. Those unincorporated self-employed workers, many of them seasonal workers, are more like independent contractors than true entrepreneurs. So, in reality, the Pew Foundation folks claim, incorporated self-employment is a better marker of entrepreneurship than unincorporated self-employment. And that measure has risen. But which measure is better doesn’t really matter. Nor do the specific causes of the changes in the rates of incorporated and unincorporated self-employment. What matters is that entrepreneurship per se is not down, just a particular kind of self-employment.

Fewer People in Outplacement Services Want to Start Companies

If unincorporated self-employment were the only measure of entrepreneurship that showed a decline, the story would end here, and I would have written a blog post, not a book. But other statistics also show declining entrepreneurial activity. One of the more interesting is a quarterly survey by the outplacement firm Challenger, Gray and Christmas, which works with workers laid off from big companies to find their next gig. The outplacement firm has been surveying jobseeking managers who have used its services since 1986. The results of the quarterly survey suggest a major transformation in what people seek to do next after they have lost jobs at big firms. In a nutshell, they have become much less interested in starting companies. The percentage of people using outplacement services who wanted to start their own companies dropped from 20.3 percent in 1989 to 5.5 percent in 2014. Even if we take away the 23

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Figure 1.4. Percentage of Job Seekers Starting Their Own Businesses Source: Created from data from Challenger, Gray and Christmas.

big rise in this fraction between 1986 and 1989, the number of people in outplacement who want to go into business for themselves has fallen by half between 1986 and 2014. That’s enough of a decline to make us think something has really changed (figure 1.4). These numbers are more convincing than the data on selfemployment, which really seems to show only a shift from unincorporated to incorporated self-employment. But there is a catch. Challenger, Gray and Christmas is not the most credible source. It is a private company whose goal is not to get a representative sample for its survey, but to understand what happened to its clients. Perhaps more important, its numbers are based on people who received its 24

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outplacement services—those who happened to work at the companies that hired a particular company to provide services. We don’t have a good sense of how this biased sample compares to the general population, and this limitation makes it difficult to extrapolate from the outplacement firm’s data to entrepreneurship generally. The numbers are too fraught with potential error to be anything more than suggestive.

The Damning Evidence

Fortunately, we have some really good data on entrepreneurship. One of the best groups working on this is a set of researchers at the U.S. Census Bureau, who have gathered and analyzed a data set called Business Dynamics Statistics (BDS). These data, it turns out, offer the most convincing evidence of a long-term decline in entrepreneurship. The BDS is an annual data series that measures businesses and establishments—places where business occurs—with employees since 1977. The series captures several important dimensions about these entities, including their age and number of employees, and allows economists to measure the number of newly formed businesses and establishments, the number of people working in those businesses, the failure rate of businesses, and a variety of other things. The Census Bureau organizes it with help from the University of Maryland’s renowned labor economist John Haltiwanger and financial support of the Ewing Marion Kauffman Foundation. This series provides the most accurate measurement we have of what is going on with businesses and establishments with employees. The BDS is a census. It tracks every single business in the United States that has at least one paid employee.8 The last point is very important. The BDS tracks what economists call employer businesses 25

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—those that employ others. It does not measure non-employer businesses— companies that have zero non-owners on the payroll. This is crucial because what has happened with non-employers over the past several decades is very different from what has happened with employers. Using this database, economists Ian Hathaway of Ennsyte Economics and Robert Litan of the Brookings Institution have published several papers examining trends in what they call the “entrepreneurship rate”: the fraction of American businesses with employees that were formed each year since 1977.9 What they found has startled many in the entrepreneurship community, and it is the main cause of policy makers’ and pundits’ concern. An updated version of their measure, calculated from census data, shows that the annual rate at which Americans start new businesses with employees has fallen by roughly half since the late 1970s (figure 1.5). New employer firms accounted for 16.5 percent of all employer firms in 1977, but just 8.0 percent of all employer firms in 2013. That’s a pretty hefty decline.

Figure 1.5. New Businesses as Percentage of All Businesses with Employees Source: Created from data from the Census Bureau.

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Figure 1.6. New Employer Firms per Thousand People Source: Created from data from the Census Bureau.

Such stark results always draw skepticism. So it is important to show that the numbers are not just an artifact of how the authors have organized the data. When we look at the per capita rate of creation of new employers, rather than new employers as a fraction of all businesses, we see a similar pattern. In 1977, Americans founded 2.56 new employer businesses for every thousand people, but by 2013 that rate was down to 1.29 per thousand (figure 1.6). As the dotted lines in the last two figures show, the long-term trend for both measures is clearly downward. The actual data tend to be above the trend line in strong economic expansions and below it in recessions and tepid recoveries, but the overall pattern is decline. Hathaway and Litan are very careful researchers who don’t miss much. They examined the patterns in a variety of different ways, looking at what happened to new employer firms in different geographies, industries, and firm sizes. No matter how they sliced and diced and julienned the data, the story was the same: declining employer business formation over time.

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It was an important discovery. America is producing new businesses with employees at a much lower rate than it did three-plus decades ago. I have only one issue with what Hathaway and Litan did. They concluded from their analysis that “entrepreneurship is in decline.” But what they actually found was narrower: they showed only that the rate of creation of employer firms has gone down. Other measures of entrepreneurship, as I have shown you and will continue to show you, have actually increased.

Key Patterns in the Data

Here is what we have seen so far, in both the introduction and this chapter: 1. The rate of unincorporated self-employment has trended downward since the mid-1970s. 2. The rate of secondary self-employment has fallen since 1999. 3. Incorporated self-employment has trended upward since the late 1990s. 4. The overall self-employment rate (unincorporated plus incorporated self-employment) has been flat over time. 5. The percentage of job seekers in outplacement looking to start their own businesses has trended downward since 1989. 6. The rate of creation of new employer businesses fell by more than half between 1977 and 2013. Taken together, three important indicators of entrepreneurship in America have declined. In recent decades, the rate of unincorporated

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self-employment, the fraction of people in outplacement seeking to start businesses, and the rate of formation of new employers have all gone down. But not all of these numbers are equally troubling. The decline in the unincorporated self-employment rate can be explained fairly easily. The rate of incorporated self-employment has gone up at the same time that unincorporated self-employment has declined. Together, these two measures show no trend up or down. While the fall in the number of managers in outplacement starting businesses after losing their jobs is real, the Challenger, Gray and Christmas data are only suggestive. The figures come from a private company whose goal is not to get a representative sample in its survey. The numbers are based on people who receive outplacement services—a biased sample of people who happened to work at the companies that hired a particular company to provide services. But the third number—the one the policy makers and pundits have jumped on— offers convincing evidence of a decline in entrepreneurship in America. Carefully gathered and analyzed census data, examined a variety of different ways, show that the rate of new employer firm formation in 2013 was roughly half what it was 1977. And that pattern is very robust: it is present across metro areas, states, industries, and firm sizes. But does this fall in new employer firm formation mean that “entrepreneurship” is declining in America? Perhaps not.

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TWO The Good News: Most Measures of Entrepreneurship Have Improved

The last chapter clearly demonstrated an important fact about entrepreneurship in America. The rate at which people create new businesses with employees is half of what it was a generation ago. For policy makers, academic observers, and even concerned citizens who would like to see Americans starting more of these types of new companies that’s a troubling sign. Some economists, for example, Robert Litan and Ian Hathaway, the researchers who first identified this trend, have concluded that “the U.S. economy has become less entrepreneurial over time.”1 Policy makers, media experts, pundits, and many others have responded to this news with a call for government action. As John Dearie, the acting chief executive officer of the Financial Services Forum, and Courtney Geduldig, formerly of the Financial Services Forum and now an executive vice president at McGraw Hill M H Financial, write in their book Where the Jobs Are, “America needs to get serious about enhancing the circumstances for new business formation, survival and growth—particularly given the alarming reality that the number of new firms launched each year . . . has declined significantly in recent years.”2 I am all for government action if something is truly wrong, but these writers have put the policy cart ahead of the data horse. The 30

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rate of new employer firm formation has clearly declined, but we should not jump to the conclusion that entrepreneurship has fallen without first looking at other measures of it. It turns out that other key measures of entrepreneurship tell the opposite story. The number of businesses without employees— measured relative to the population—has been increasing for several decades. Moreover, the Internal Revenue Service’s estimates of entrepreneurial activity suggest a different pattern from those of the Bureau of Labor Statistics and the U.S. Census. Finally, measures of the stock of entrepreneurial businesses look much better than measures of the flow of those businesses over the past several decades. (I’ll define “stocks” and “flows” in a moment.) To understand what has happened to American entrepreneurship in recent decades, we need to look at these other measures and then reconcile the different estimates to figure out the true story. In a nutshell, it is a lot more complicated than just concluding from the decrease in the rate of formation of new employer businesses that American entrepreneurship is in decline. Understanding the Difference between Stocks and Flows

Our first stop toward understanding what has happened to entrepreneurship in America is a discussion of measurement. Specifically, we need to think about tracking two kinds of measures—stocks versus flows—and two types of businesses— employers and nonemployers. I realize that this is a bit academic for some people, but trust me, understanding these differences is important, even if the discussion is a bit dry. Let’s start with the difference between stocks and flows. A “stock” refers to how much of something is present at a point in time, and 31

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a “flow” refers to the rate of change in that stock. Take water in your bathtub as an example. If you fill your bathtub with water, the “stock” is the level of the water in the tub—the line across the side of the tub that the water has reached. The “flow” is the rate at which the water comes out of the tap. (Another flow is the rate at which the water goes down the drain, which will become important in a minute.) If you want to know whether your bath is ready, both the stock and flow measures are useful. If the level of water in the tub—the stock—is very low, say one inch, your bath isn’t ready yet. Similarly, if only a tiny trickle of water is coming out of the tap—the flow— that is also a negative indicator. The two measures capture different things, but both are useful. So far we have discussed two key bathtub measures, the amount of water coming out of the tap (a flow) and the level of water in the tub (a stock). But there is a third measure that is mathematically related to the other two, and that’s the flow of water down the drain. The level of water in the bathtub is a function of the amount of water coming out of the tap and the amount going down the drain. As anyone who has taken a bath knows, the level of water in the tub goes up if more water comes out of the tap than goes down the drain, and the level goes down if the opposite is the case. This is where the other flow measure, the rate at which the water swirls down the drain, becomes important. The level of water in the tub is a function of the relative rates at which water enters and drains from the tub. Boost the flow out of the tap or reduce the flow down the drain, and the level in the tub will rise. The patterns are just as true for measures of entrepreneurship as they are for measures of the water level in a tub. Some measures are stocks—for example, the per capita number of companies operating in the economy or the self-employment rate. These measures tell

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you how much entrepreneurship there is at any point in time. We can look at differences in these measures over time just as we look at differences in the water level in our tub. If the self-employment rate today is one-third higher than it was a decade ago, or if the per capita number of businesses in operation is 10 percent lower than it was five years earlier, then we know something about changes to the amount of entrepreneurship in the economy. Other measures are flows. Like the water coming out of the tap (or going down the drain), they tell us about the rate of new business creation (or failure). If the rates of new employer firm formation are down 50 percent from what they were thirty-five years ago, it also tells us something about entrepreneurship. But it doesn’t tell us whether there are more or fewer employer businesses in operation today than a decade ago. That’s because the measure does not tell us anything about the fraction of employers that go under each year. The per capita number of businesses with employees in operation at any point in time is mathematically related to the rate of new employer firm formation—the measure that Hathaway and Litan found had fallen by 50 percent over the past thirty-six years—and the rate of employer firm failure. Just as with water in a bathtub, a 50 percent decline in the rate of new employer firm formation could mean that the per capita number of employer businesses is down, that this number has remained the same, or even that it has actually risen. We can’t know which has occurred from just the change in the new employer firm formation rate. The fact that there are three possible patterns that result from a decline in the new employer firm formation rate—an increase, no change, or a decrease in the stock—means that we need to look at the data on the stock of employer businesses and the employer firm failure rate.

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What Has Happened to Employer Firm Failure Rates?

Let’s go back to the BDS data and compare employer firm stocks and flows. We know from chapter 1 that the per capita rate of new employer firm formation went down by 50 percent between 1977 and 2013. But what has happened to the stock of employer businesses? It turns out that the per capita number of employer firms was 3 percent higher in 2013 than it was in 1977. Since a 3 percent increase is very small, let’s just round it to no change. For the per capita rate of creation of new employer firms to have declined, while the per capita number of employer firms has remained the same, the per capita failure rate of employer businesses must also have gone down. Less flow into the tub was offset by less flow down the drain. It is, in fact, what has happened. The per capita rate of business failure has fallen from 2.44 employer firm closures per thousand Americans in 1977 to 1.35 in 2013, a roughly 45 percent decline. The trend is very noisy. It tends to increase in economic downturns, rising to 2.19 during the Great Recession, and decrease in economic expansions.3 But the pattern is a long-term decline. I described the failure rate in a way comparable to the new firm formation rate and the per capita number of employers in operation at any point in time. But I could have described it as a percentage of the number of employer businesses in operation. The pattern is very similar. The rate at which employer firms fail has gone from 15.7 percent of employers in 1977 to 7.9 percent in 2013, a roughly 50 percent decline in the business failure rate.4 Over the past thirty-six years, new employer firm formation rates and new employer failure rates have both declined. In fact, the two are fairly highly correlated. Between 1977 and 2013, the rate at which new employers were founded annually in the United States has a 0.62 correlation with the rate at which employers go under.

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Although that is far from a perfect statistical association—a correlation of 1.00 means that two numbers move in perfect concert—it is enough to suggest that the two numbers are related. Put simply, in years when more American employers shut down, more American employers tended to get started, and in years when fewer American businesses shut down, there were also fewer startups. While that concept might seem surprising to some people, it does makes sense. When existing companies go under, markets become underserved, creating opportunities for entrepreneurs to start new businesses to meet the demand in the newly underserved markets. Moreover, when businesses shut down, they free up capital, labor, land, machinery, and so on for new businesses to employ without having to pay a premium to bid those resources away from more established players. Without these exits releasing the resources, those assets would be too difficult or expensive for the startups to obtain. In contrast, in times when existing businesses aren’t shutting down, neither demand nor resources are being freed up for entrepreneurs starting new businesses. To make this concept more concrete, let me give an example. Suppose you live in a suburb of a mid-sized American city. Every suburb in America has some dry cleaners, pizza parlors, and shoe repair shops. For the most part, the number of dry cleaners, pizza parlors, and shoe repair shops is proportional to demand for those products. Sure, in Southern California flip-flop land, there are fewer shoe repair shops per capita than in Boston, and in New York there are probably more dry cleaners per capita than in El Paso, but there is a relatively stable ratio in each place over time. It is hard for a wouldbe business owner to start an additional pizza parlor, dry cleaner, or shoe repair shop in a given neighborhood if the number of existing establishments satisfies demand.

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What this means is that to allow entrepreneurs to start more new employer businesses, more existing employer businesses need to shut down. But we cannot know for sure the direction of the causality here. Does the decline in the failure rate cause the startup rate to decline, or does the decline in the startup rate cause the failure rate to fall? Or both? One plausible explanation is that the declining failure rate causes the startup rate to decline. The theory is that the economy has a carrying capacity. It can handle only so many businesses. If existing employer businesses become less likely to go under, as they have, it becomes more difficult for entrepreneurs to start new businesses. That makes the pace of new employer firm formation slacken, which is what we observe. Compared to 1977, in 2013, the rate at which existing businesses went under declined. So there was less space for startups to form. This argument has received some support among some economists. In a longitudinal study of Canadian manufacturing companies, economists Avid Pe’er of Rutgers University and Ilan Vertinsky of the University of British Columbia found evidence for this story. Using a wide variety of statistical techniques to control for potentially confounding factors, Pe’er and Vertinsky found that in places where more existing businesses shut down, business formation rates increased. In areas where fewer existing businesses were shuttered, business formation rates declined.5 Moreover, data from the 2014 Global Entrepreneurship Monitor, a cross-national comparison of business formation and discontinuation rates across sixty-nine countries, gathered as part of an annual effort by researchers at a wide variety of business schools to measure entrepreneurial activity across the globe, provide similar evidence. These data reveal that the total entrepreneurship activity rate—the

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fraction of a nation’s adult age population that is either starting a business or is the owner-manager of a new business— correlates 0.81 with the country’s discontinuation rate—the fraction of the adultage population that has shut down a business. Countries that have a high rate of business failure tend to have a high rate of business formation, and countries that have with a low rate of business discontinuation rates tend to have lower startup rates. What about the failure rate of new businesses? Have those declined as well? If existing businesses are failing less often, one might think that the failure rates of new businesses would do the same, because entrepreneurs are getting more selective in founding startups and at managing them. The data, however, don’t suggest that pattern. Economists Ian Hathaway and Robert Litan—the ones who identified the decline in the new employer firm formation rate— have found that new firms experienced a jump in failure rates between 1987 and 2007, but that employer firms more than one year old did not experience much of a change in failure rates over this period. This pattern, they explain, is present across industrial sectors, geographies, and firm sizes. If we look at the failure rate of businesses in their first year of operation since 1977, we can see that the effect is more muted, but it is still there. The failure rate of new businesses has risen slightly over the past three-plus decades, while the failure rate of existing businesses has fallen. New businesses are more likely to go under than they were three decades ago, but mature ones are less likely to fail. The correlation between employer firm formation and failure rates suggests that another measure of entrepreneurship, the stock of employer businesses, may be doing all right. A look at the census data suggests that is the case. The per capita number of businesses with employees was 3 percent higher in 2013 than it was in 1977. In 1977,

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there were 15.52 businesses with employees for every American. In 2013, that number was 15.99.6 If you think of our bathtub analogy for a minute, you will see why. The number of employer businesses per capita is like the level of water in a tub. The level is pretty much the same because the amount of new businesses going down the drain and the amount coming from the faucet were both about 50 percent lower in 2013 than they were in 1977. Together, these data tell us that American entrepreneurs may be less likely to start new businesses with employees than they once were because existing employers are less likely to fail. This suggests that the economy has a carrying capacity for new businesses. If existing entrepreneurs are able to keep their businesses alive longer, fewer people are starting new employer firms to replace them. That’s an interesting story, but it is not one of American entrepreneurship in decline.

The No-Decline Story Told by Other Measures

Before we accept that American entrepreneurship is in long-term decline, we should look at some other data. Several measures tell a different story from that of the Census Bureau data on new employer firm formation rates. The Federal Reserve’s Survey of Consumer Finances is one. Every three years, the Federal Reserve board of governors contracts with a reputable firm, like the National Opinion Research Center (NORC) at the University of Chicago, to survey the financial position of U.S. households. It is an expensive government study that yields very high quality data employed by numerous scholars and policy makers.

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One of the things the Survey of Consumer Finances captures is the share of U.S. households that owns “business equity,” which the Federal Reserve defines as an ownership interest in privately held sole proprietorships, partnerships, or corporations. (Business equity, by this definition, does not include investments in the stock market.) It is a reasonable measure of the fraction of American families that own private businesses—something many people would call “entrepreneurship.” Although the fraction of households with business equity slipped between 2010 and 2013, the survey data do not show a long-term downward trend. In both 1989 and 2010, the same percentage of U.S. households—11.3 percent—held business equity.7 Unlike the Census Bureau data on new employer firm formation, and consistent with its measure of new employer firms per capita, the Federal Reserve data do not show a long-term trend toward less entrepreneurship in the United States. Instead, they show that it has been pretty stable. Rob Fairlie, an economist at the University of California at Santa Cruz, created another measure of the stock of entrepreneurship for the Ewing Marion Kauffman Foundation, a nonprofit that supports academic research on the topic. The Kauffman Index of Entrepreneurial Activity, as it is called, is produced from the Current Population Survey, a representative sample of the U.S. population collected jointly by the U.S. Census and BLS. Fairlie’s analysis captures the fraction of the population that transitions into self-employment every month. The Kauffman Index of Entrepreneurial Activity was identical in 2014 and 1996, a pattern that belies the claim that the rate of entry into entrepreneurship is in decline (figure 2.1). Visual inspection of the trend line shows that, to the extent that there is any pattern at all, it is a slight increase over time.

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Figure 2.1. Percentage of Non-Business Owners Starting Businesses Source: Created from data from the Kauffman Index of Entrepreneurial Activity.

The Story of Rising Entrepreneurship

We have seen several sources that disagree with the new employer firm data on what has happened to entrepreneurship in the United States. Data on the stock of employer businesses, the Survey of Consumer Finances business equity holdings, and the Kauffman Index of Entrepreneurial Activity show little trend over the past few decades. However, other data show that entrepreneurship has actually been rising. Consider the Census Bureau’s non-employer data. This series is an annual measure of the number of the U.S. companies that have no paid workers. To be precise, the Census Bureau’s nonemployer data measures include businesses that have no employees on the payroll but have produced at least $1,000 in annual revenues and are subject to federal income tax. Non-employer businesses include both part-time and full-time entrepreneurial endeavors. The non-employer business can be the primary job of its owner or a secondary one, and it can take on a variety of legal forms, from sole proprietorship, to partnership, to Subchapter S or C corporations.

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THE GOOD NEWS

Although the number of non-employer firms did slip a little during the depths of the Great Recession, their count has generally been rising in recent years. Moreover, over the past fifteen years, the number of non-employers has grown faster than the population, leading to a rise in the per capita number of American non-employer companies. Between 1997 and 2013, the stock of American businesses without employees increased by 76 percent, five times faster than the 15 percent increase in the population. As a result, the per capita number of businesses without employees rose from 56.57 per thousand people to 72.72 (figure 2.2). The Internal Revenue Service produces several statistics that let us know what has happened to entrepreneurial activity over time. One such number is the fraction of American taxpayers who take the self-employment tax deduction. Because people can take this tax deduction only if they are actually in business for themselves, it is a good indicator of how many individual income tax filers are self-employed. Some observers believe that this measure of

Figure 2.2. Number of Non-Employers per Thousand People Source: Created from data from the U.S. Census.

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THE GOOD NEWS

self-employment is better than that produced by other government agencies. When it comes to tax data, most people provide the required information and answer honestly. Although they are legally obliged to answer inquiries from all federal agencies accurately as well, few people have been prosecuted for failing to give accurate data to the Bureau of Labor Statistics. The same cannot be said for giving false information to the IRS. The IRS’s data on self-employment are probably the best we have on the question of how many people are working for themselves—better, in fact, than the BLS data that combine incorporated and unincorporated self-employment. As we saw in chapter 1, the BLS data on the overall selfemployment rate show that the fraction of Americans in business for themselves has essentially been flat for the past several decades. The IRS data on this question cover a shorter period than the BLS data, but for the period where the two measures overlap, the IRS numbers tell a story consistent with rising, not falling, rates of entrepreneurship. The fraction of American households that took the selfemployment tax deduction on their individual income tax returns increased from 9.7 percent in 1990 to 12.8 percent in 2013 (figure 2.3). This hardly suggests declining entrepreneurship. Some people don’t like self-employment as a measure of entrepreneurship because it confounds being an independent contractor with running a business. So the IRS data on self-employment might simply show a rise in independent contractors, not more entrepreneurship. Rather than debate this point, let’s just look at some other measures of entrepreneurship from the tax authority’s data. Since 1980, the tax authority has tracked the number of passthrough entities—sole proprietorships, partnerships, and Subchapter S corporations—in the U.S. economy. This measure shows entrepreneurship on the rise. Over the past three decades, the number of pass-through entities has increased much faster than the number 42

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THE GOOD NEWS

Figure 2.3. Share of Individual Tax Returns with Self-Employment Tax Deduction Source: Created from data from the Internal Revenue Service.

of Americans. In 1980 there were 57.2 American businesses for every thousand Americans. By 2012, there were 104.4. While the 2012 figure is below the peak of 106.5 in 2007, it is nearly double its per capita level in 1980 (figure 2.4). Other IRS data show a similar pattern. The tax authority keeps track of the number of individual tax returns that show income and losses from business ownership. Like the Federal Reserve data on households with business equity, this statistic captures the portion of individual tax filers that run a company. Comparing these figures to the total number of individual returns tells us about the fraction of entrepreneurs in the economy. This measure also shows a rising pattern. The percentage of individual income tax returns with business income or loss rose to 16.0 percent in 2013, from 12.9 percent in 1990 (figure 2.5). This rise in entrepreneurial activity has been widespread. Businesses taking several legal forms have increased in absolute numbers and per capita. This means that the growth in entrepreneurship is 43

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Figure 2.4. Business Returns per Thousand People Source: Created from data from the Internal Revenue Service.

Figure 2.5. Share of Individual Income Tax Returns with Business Income or Loss Source: Created from data from the Internal Revenue Service.

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THE GOOD NEWS

not just a shift from one legal form of business to another. Proprietorships, partnerships, and corporations all increased on a per capita basis over the past three decades. The number of sole proprietorships per capita has shown a steady, almost linear increase over the past thirty years. While the number is down from its peak of 76.75 in 2007, from 1980 to 2013 the number of sole proprietorships per thousand Americans nearly doubled, from 39.22 to 76.15 (figure 2.6). Corporations display a similar pattern. In this category, which includes both traditional C corporations and Subchapter S corporations, the number rose more or less steadily from 1980 until 2006, when it peaked at 19.58 per thousand Americans. Although there has been a dip since then, the per capita number of American corporations was 56 percent higher in 2012, the latest year for which data are available, than in 1980 (figure 2.7).

Figure 2.6. Sole Proprietorships per Thousand People Source: Created from data from the Internal Revenue Service.

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THE GOOD NEWS

Figure 2.7. Corporations per Thousand People Source: Created from data from the Internal Revenue Service.

Figure 2.8. Partnerships per Thousand People Source: Created from data from the Internal Revenue Service.

The growth in the per capita number of partnerships is less linear than that of the other two business forms, but the pattern persists (figure 2.8). The per capita number of partnerships was much higher in 2012 than it was in 1980, rising from 6.06 per thousand people to 10.79 per thousand, a 78 percent increase. 46

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THE GOOD NEWS

In short, no matter how we measure businesses, we have seen a rise in the number of companies per American over the past three decades. That pattern is inconsistent with a decline in entrepreneurship. Key Patterns in the Data

1. Business failure rates have fallen since the late 1970s, increasing the amount of time that the average entrepreneur runs any given business. 2. The per capita stock of businesses with employees has remained roughly constant since 1977. 3. Employer failure and formation rates are positively correlated. 4. The number of non-employers per capita rose between 1997 and 2013. 5. A higher fraction of American taxpayers took the selfemployment tax deduction in 2013 than in 1990. 6. The fraction of individual income tax returns with business income or loss increased between 1980 and 2013. 7. The per capita number of businesses increased between 1980 and 2013. 8. The per capita number of sole proprietors, partnerships, and corporations has increased in all cases since 1980. Taken together, these data tell a different story about trends in American entrepreneurship from the one told in chapter 1. Both the formation rate and the failure rate of companies with employees have fallen significantly over the past thirty-plus years, but the stock of employers is roughly the same today as it was in the late 1970s, in proportion to the population. 47

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THE GOOD NEWS

Other measures of the stock of entrepreneurs also contradict the story of decline. The fraction of households reporting to surveyors that they hold business equity was the same in 1989 and 2010. The Kauffman Index of Entrepreneurial Activity was the same in 2014 as it was in 1996. Several data sources indicate that entrepreneurship has gone up over the past three decades. Non-employers have grown on a per capita basis since the late 1990s. The percentage of taxpayers taking the self-employment tax deduction and paying self-employment taxes has gone up. The per capita number of American businesses has risen in all categories of businesses, from proprietorships to partnerships to corporations. And more American taxpayers have business income or loss on their individual tax returns. In short, looking only at the data on the rate of creation of employer businesses gives one a misleading picture of American entrepreneurship. It isn’t in decline, but it has changed.

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THREE Entrepreneurial Earnings Are on the Rise

In the last chapter, we saw that, despite the arguments of some observers that American entrepreneurship is in decline, the data show that only some types of entrepreneurship are lower than they were in the late 1970s. There is no doubt that new businesses with employees are being created at half the rate they were a generation or so ago, that unincorporated self-employment is down, and that people who lose their jobs and are receiving outplacement services (at least the services of Challenger, Gray and Christmas) are not as interested in starting businesses as their 1980s counterparts were. But other types of entrepreneurial activity are on the rise. America has many more non-employers per capita than it did several decades ago. Incorporated self-employment rates have increased. A greater fraction of taxpayers show business income or loss on their individual tax returns, and we have far more companies of all types—sole proprietorships, partnerships, and corporations—per person than we did thirty-plus years ago. Moreover, even the data on employer businesses are equivocal. Entrepreneurs are founding businesses with paid workers at a slower rate than they once were, but older employer businesses are shutting down more slowly, leaving the stock of employers per capita slightly higher now than in the late 1970s. Because incorporated and unincorporated self-employment have moved in opposite directions,

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the overall self-employment rate is similar to what it was before the advent of the personal computer, but today a greater fraction of the self-employed are incorporated. These trends tell a complex story of what has happened to entrepreneurship in America. Most of the stories told by pundits and policy makers—about lack of access to capital, demographic shifts, stifling regulation, and high taxes—are too simplistic to explain accurately what has happened to entrepreneurship since the late 1970s. But before I attempt my own explanation, I need to highlight two other trends that many have missed: what has happened to earnings from business ownership, and what has happened to high-potential ventures. In this chapter, I focus on the first of these, profits from running one’s own business. The data on earnings from business ownership indicate that American entrepreneurs are doing just fine—better, in fact, than people who do not run their own companies. Entrepreneurial activity has become more, not less, profitable over time. And, as running a business has become more profitable, the incomes and net worth of business owners have grown faster than those of people who work for others. American Entrepreneurs Are Making More Money Than a Generation Ago

The hypothesis that American entrepreneurs are making less money than they once did is straightforward and easily testable. Their average income is either the same, higher, or lower than it was three-plus decades ago. We can figure this out by looking at how much money the average American small business has made every year in real—that is, inflation-adjusted—terms. Data on this are available from 1980.

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Almost all American small businesses are organized as passthrough entities. Unlike C corporations, which pay their own income tax, the income from a pass-through entity is transferred directly onto the owner’s individual tax return. These companies represent all but the very largest small businesses—the handful organized as C corporations. The annual income of pass-through entities thus tells us how much money American entrepreneurs are making each year (or at least provides a decent approximation). The data on these earnings come from our nation’s tax authority, which imposes steep penalties for lying on one’s return, making the numbers very reliable. If we look at the IRS data on the average American pass-through business’s income over time, we can get a pretty good sense of whether entrepreneurship is getting more profitable, or less. The average business run by an American entrepreneur is generating more income, adjusted for inflation, than it did three decades ago. With the exception of the years of the Great Recession, which adversely affected entrepreneurial earnings, as it did all other earnings, the average income of pass-through entities has seen a steady rise. Between 1980 and 2012, earnings of the average American pass-through entity rose 196 percent after accounting for inflation (figure 3.1). That’s far from a marginal increase. American entrepreneurs are making a whole lot more money than they did a generation ago. It is not true just for the entrepreneur who chose to organize his or her business as a corporation, or partnership, or sole proprietorship. If we look at specific types of businesses, we see the same patterns. The real average net income of Subchapter S corporations has risen considerably over the past three-plus decades, from $12,239 (again, in 2010 dollars) in 1980 to $107,527 in 2012 (figure 3.2). That’s

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Figure 3.1. Real Average Net Income of Pass-Through Entities Source: Created from data from the Internal Revenue Service.

Figure 3.2. Real Average Net Income of S Corporations Source: Created from data from the Internal Revenue Service.

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a nearly ninefold increase, and it comes despite the battering these incomes suffered in the Great Recession. Because the IRS is not terribly concerned about how quickly it produces its statistical data, some of its numbers are more current than others. Its information on sole proprietors is more up to date than figures on other legal forms of business. That’s a good thing. Because sole proprietors comprise roughly three-quarters of all U.S. small businesses, statistics about them tell us the most about how American small business owners are performing. The data on sole proprietorships’ profit margins show that sole proprietors are taking home a larger share of their revenues as profits every year. Once again, that’s inconsistent with the story that American entrepreneurs are earning less than they used to. If American entrepreneurs are struggling, their average net income as a fraction of revenue should be going down—they should not be taking a greater portion of their revenues as profits. As you might expect, the Great Recession was not kind to sole proprietors. But overall, sole proprietors’ margins have been trending upward since the late 1980s. From 1988 to 2013, net income as a percentage of revenue rose from 18.8 percent to 22.5 percent (figure 3.3). And margins have risen not just for sole proprietors. For Subchapter S corporations, net income as a percentage of revenue has also increased substantially. In 1980, profit margins were 1.2 percent. In 2012, they had reached 7.2 percent, a sixfold increase. Partnerships tell the same story. Since 1980, their net income as a percentage of revenue went from 3 percent to 16.6 percent, a five-and-a-halffold rise.1 In short, American entrepreneurs are making more money than they were a generation ago. The income for all types of pass-through

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Figure 3.3. Proprietors’ Net Income as a Percentage of Revenue Source: Created from data from the Internal Revenue Service.

entities is up substantially in inflation-adjusted terms. Sole proprietors and Subchapter S corporations have seen their margins increase. These changes suggest rising, rather than declining, entrepreneurship.

The Benefits of Business Ownership

Since the late 1970s, owning a business has become more profitable for Americans. Because business ownership not only remains one of the best ways for Americans to earn money and build a nest egg but has become an even better way to do so, one would expect that America’s entrepreneurs have increased their financial advantage over non-entrepreneurs in the past several decades. A very reliable source— our nation’s central bank— confirms that they have. The financial position of American entrepreneurs has improved relative to that of non-entrepreneurs.

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The Federal Reserve’s Survey of Consumer Finances, which I mentioned in chapter 2, tells us a great deal about the differences in income and net worth between American families headed by someone in business for him- or herself and families led by someone who works for another person. It shows that both the income and net worth of entrepreneurial households have outpaced those of non-entrepreneurial households over the past twenty-five years. Let’s look first at income. The median income of families headed by a self-employed person grew by 88.3 percent between 1989 and 2013, compared to 76.9 percent for those headed by someone employed by someone else. Average income also grew faster: 126.2 percent versus 111.5 percent (figure 3.4). It should not come as a surprise that the net worth of entrepreneurial households has, like their income, grown faster than that of non-entrepreneurial households. The net worth of the typical American household headed by a self-employed person rose 111.5 percent between 1989 and 2013, while that of the typical family headed

Figure 3.4. Household Income of Self-Employed People Compared to That of Employees, 1989 –2013 Source: Created from data from the Federal Reserve.

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Figure 3.5. Household Net Worth for the Self-Employed Compared to That of Employees, 1989 –2013 Source: Created from data from the Federal Reserve.

by an employee increased by 63.2 percent. The pattern was the same for the average net worth. From 1989 to 2013, the average net worth of an American household headed by someone employed by another person increased by 176.8 percent. But the average net worth of a household headed by a self-employed person went up 232.6 percent (figure 3.5). These differences have meant that American households run by someone in business for him- or herself have seen their median net worth grow faster than inflation, whereas those run by people working for others have not. We can look at the trends over time by putting in the survey data from intermediate years. The median net worth of families headed by a self-employed person increased from $306,700 in 1989 to $358,900 after inflation, a modest but clear increase. American families overall, however, saw their median net worth actually slip over that period, from $84,800 to $81,200 (figure 3.6).

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ENTREPRENEURIAL EARNINGS ARE ON THE RISE

Figure 3.6. Median Net Worth of Self-Employed and All Families in Thousands of Constant Dollars, 1989 –2013 Source: Created from data from the Federal Reserve.

Since the late 1980s, entrepreneurs have done better economically than the rest of the American population. The income and net worth of both the average and the typical American entrepreneur have risen faster than those of the average or typical non-entrepreneur. Again, that’s not something that would have happened if American entrepreneurship were in “decline” or “failing.” The Entrepreneurial Fraction of Income

Another important trend in recent decades is the rise in the share of Americans’ income that comes from entrepreneurial activities. Two very credible data sources, the IRS and the Federal Reserve, show that far more of American household income comes from entrepreneurial efforts now than a generation ago. The Federal Reserve’s Survey of Consumer Finances shows that the fraction of family income that comes from “business activity”— its measure of ownership of private companies—has increased over the

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Figure 3.7. Entrepreneurial Income as Percentage of U.S. Taxpayers’ Income Source: Created from data from the Internal Revenue Service.

past twenty-four years, from 10.9 percent of before-tax family income in 1989 to 12.7 percent in 2013. That’s a sizable rise.2 The IRS data—again, arguably the most accurate source—show a similar increase. In 1977, only 5.4 percent of American taxpayers’ income was “entrepreneurial income,” which is defined as income from Subchapter S corporations, partnerships, or sole proprietorships. By 1982, that share had fallen to 2.6 percent. But over the subsequent years, this fraction has risen substantially, reaching 9.2 percent in 2013 (figure 3.7). Has this rise in the share of entrepreneurial income primarily accrued to high-income earners, or has it been garnered by low and middle earners as well? Data collected by Emmanuel Saez of the University of California at Berkeley and Thomas Piketty of the Paris School of Economics can help us answer this question. These two economists, now famous for their work on income inequality, studied how the source of American taxpayers’ income has changed across levels of income distribution. Their data show that the share of entrepreneurial income has risen most among people at the top of the income distribution. Between 58

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1982 and 2013, for the top 10 percent of earners among American taxpayers, the share of total income that came from entrepreneurial activities rose from 5.1 percent to 17.3 percent. For those in the top 1 percent, the fraction increased from 8.2 percent to 31.3 percent, and for the top one-tenth of 1 percent, it grew from 8.0 percent to 39.2 percent. For the lucky few in the top one-hundredth of 1 percent, the portion expanded from 12.1 percent to 39.7 percent over the period (figure 3.8). Because a rising share of Americans’ income comes from entrepreneurial activities, it should not be surprising that an increasing share of their net worth consists of equity in entrepreneurial efforts.

Figure 3.8. Share of Entrepreneurial Income by Income Level Source: Created from data from Emmanuel Saez and Thomas Piketty, “Income Inequality in the United States, 1913 –1998,” Quarterly Journal of Economics 118 (2003): 1–39; tables and figures updated to 2015 Excel figures; see link at http://eml.berkeley.edu/~saez/. 59

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Figure 3.9. Business Equity as Share of Americans’ Wealth Source: Created from data from the Federal Reserve.

Statistics from the Survey of Consumer Finances show that the fraction of net worth that comes from “business equity” holdings has risen over the past two-plus decades (figure 3.9). In 1989, 26.7 percent of Americans’ net worth came from business equity; by 2013, it was 30.7 percent. These days, Americans are getting more of their money from their entrepreneurial activities than from wages, investments, or other sources than they were three decades ago. Data from two very reputable sources— our nation’s central bank and its tax authority— make this pattern abundantly clear. It’s true across all levels of the income distribution, although it is strongest for the wealthy. Because people generally allocate their time to the form of work that generates the highest returns and shy away from the types of activities that generate the lowest financial payoff, this shift suggests that Americans, on average, feel that entrepreneurship makes

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increasing economic sense. Once again, this pattern is inconsistent with declining entrepreneurship; it is instead suggestive of the activity ascending. Key Patterns in the Data

1. The average income of pass-through entities—sole proprietorships, partnerships, and S corporations—nearly tripled in inflation-adjusted terms between 1980 and 2012. 2. Since 1980, profit margins have risen at S corporations and sole proprietorships. 3. Between 1989 and 2013, median and average income and median and average net worth have risen faster in households headed by a self-employed person than in households headed by a person employed by someone else. 4. The fraction of before-tax income that American families received from owning private companies increased between 1989 and 2013. 5. The share of Americans’ taxable income coming from their entrepreneurial activities more than tripled between 1982 and 2013, a pattern present for the top income levels as well as the median. 6. The share of the net worth of American households that is devoted to equity in private companies increased between 1989 and 2013. The story told in chapter 1 of declining American entrepreneurship was based primarily on the decrease in rate of formation of new employer businesses. Some observers have claimed that entrepreneurship has been in decline for several decades.

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Chapter 2 told an entirely different story. Data from the Census Bureau, the Federal Reserve, and the IRS show that existing entrepreneurial efforts are lasting longer, and that the stock of total businesses in the economy has been growing on a per capita basis. In this chapter, we looked at entrepreneurial earnings. Once again, the data are not consistent with the story of entrepreneurship in decline. The amount of money the average small business owner makes annually has risen in inflation-adjusted terms since 1980. Profit margins have gone up since the late 1980s. Both the income and the net worth of households headed by someone in business for themselves have grown faster than those of households led by a person who works for someone else. And entrepreneurial activities account for a larger share of U.S. households’ income and net worth than they did three decades ago. This rise in earnings makes it difficult to believe that Americans’ interest in entrepreneurship has declined. Basic economics tells us that if having your own company is increasingly profitable, more people should want to have their own companies. Taken together, all of these data tell a complex story. Rather than signaling a decline in entrepreneurship, these statistics show a change in how people are approaching it. The decline has been limited largely to new employer firm formation. Moreover, it has happened because fewer entrepreneurs are starting companies with paid workers and those who are starting them are not employing as many people as a generation ago. The fraction of Americans engaging in entrepreneurial activity, and the fraction of Americans’ income that comes from these efforts, have both risen.

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FOUR Riding High

The first three chapters have shown a mixed picture of what has happened to American entrepreneurship since the late 1970s—at least for the typical startup. But focusing on typical companies might not be the right way to go. Most of the impact of entrepreneurial activity comes from the formation of high-potential businesses—the Facebooks and Instagrams and Lending Clubs—not the dry cleaners and clothing shops that dominate government statistics. A minority of new businesses actually survive over time, and very few ever grow employment, sales, or assets in a meaningful way. The entrepreneurship that matters, some observers argue, is not the broad swath of employer or non-employer businesses but the high-potential startups that are backed by sophisticated investors. Some economists who have worked with the census data on employer businesses have found evidence of a decline in high-growth companies. Ryan Decker, of the Federal Reserve, and three coauthors recently looked at the top 10 percent of U.S. employer businesses and found that the growth rate of all employers in that group began to slide around 2000, at the same time that the rate of formation of new employers in the information sector slowed down. Since 2000, the top tenth of companies has still been adding workers, but more slowly than in earlier years.1

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RIDING HIGH

This is a troubling sign. If the fastest-growing businesses aren’t adding workers as fast as they used to, employment will suffer. Highgrowth employers are, after all, the businesses adding the most jobs. In fact, this slowdown in hiring, combined with the lower rate of formation of new employers, could portend a slowdown or even stoppage of entrepreneurial job creation. But is what Decker and his colleagues measured really what people mean when they talk about high-potential businesses backed by sophisticated investors? I have no doubt that he and his colleagues have identified a decline in job creation by the fastest-growing 10 percent of companies, but I think they are measuring something other than true high-potential companies. The top tenth of employers added workers at a far faster pace than the typical or average company, but very few of these companies are the super-high-growth ventures that obtain external financing from business angels and venture capitalists, make the front page of the Wall Street Journal, go public, or get acquired at sky-high prices. That fate is limited to less than 1 percent of new businesses. This chapter focuses on what has happened to companies funded by venture capitalists and business angels—the kind of companies that have gone from tiny startup to giant corporation in a few years. These companies represent the transformational entrepreneurship that policy makers and economists alike think is crucial to the economy. Admittedly, the data on these firms are not as good as the data examined by Decker and his colleagues. The numbers discussed here don’t come from government statisticians but from private sector providers gathering information for a different purpose, or from academics working on smaller budgets. Still, they tell a consistent story. Simply put, the trends for high-potential ventures do not show much evidence of a decline in entrepreneurship. They do indicate a

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burst bubble in venture capital at the turn of the millennium, but for the most part, investment in high-potential ventures is greater now than several decades ago. The Measurement Problem

Measuring what has happened with high-potential companies over time is far harder than tracking the broader set of new employers and non-employers or earnings from entrepreneurial activity. Highpotential businesses can’t easily be observed ahead of time. New companies do not come with indicators that say “we will grow large” or “we intend to hire a lot of people”—at least, not reliable ones. Identifying high-growth companies requires the use of proxy measures. One proxy measure is to look at businesses financed by external equity investors like venture capitalists and business angels—people who are trying to find the startups with the highest potential. These investors have money at stake, and their own survival depends on their identifying the startups with the most potential for growth. Their judgment—at least that of the successful ones—is probably better than that of observers who aren’t trying to earn a return from their evaluations. Venture capitalists are partnerships that raise money from endowments, pension funds, and wealthy individuals and invest that money in young high-growth businesses, hoping to cash out when those businesses are acquired or go public. Classic examples include the firm Sequoia Capital, famous for its financing of Apple Computer and Genentech. Business angels are individuals who invest their own money in young businesses. A legendary example is Peter Thiel, who parlayed a $250,000 investment of his own money in a young Facebook into over a billion dollars in profit when the social network went public.

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By comparing the numbers of companies getting financed by these types of investors now versus in the past, and looking at whether the terms are getting more or less favorable to entrepreneurs, we can get a picture of the market for this small but important slice of American entrepreneurship. If these investors are funding a rising fraction of these startups, investor terms are becoming more favorable to entrepreneurs, and the performance of these types of businesses is improving, then we can infer that investors are bullish on these companies, and with good reason. This would be evidence against the argument that American entrepreneurship is going downhill. There are some limitations, of course, in using investments by venture capitalists and business angels to measure the number of high-growth companies. Not all high-growth companies are financed this way. Moreover, the government does not collect data on venture capitalists and business angels; private enterprises do. Their goal in doing so is not to generate data for research and analysis, making the data they do collect less reliable. Moreover, respondents do not have to answer private survey takers the way they must respond to the IRS or even the Census Bureau. They can simply ignore requests for information, raising the possibility of bias. There is also the problem of measurement over time. Data collection has become far easier than it once was. Communications and computer technologies have made it easier to survey people. As a result, information that was hard to find in the 1980s is easier to obtain today. That means that statistics on venture capital- and angelbacked companies don’t go back as far as statistics on new employers and non-employers, and comparisons with the earliest years are a bit suspect. But even if the data on high-potential ventures are not as good as we would like, ignoring what information is available doesn’t help

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us understand what has happened to these startups. We have to make the best use we can of the information we have. When looking at the numbers in this chapter, readers should be more skeptical about their accuracy than when reading numbers from the Census Bureau or the IRS. But if patterns are overwhelmingly in one direction or another, even imprecise numbers provide us with some insight into what has happened to high-potential ventures. The Number of High-Potential Companies Is Up

If trends in entrepreneurship were measured solely by what’s happened with venture capital- and angel-backed companies over the past decade, then our expectations for the future of American entrepreneurship would look just fine. There is little question that there are more Facebooks and WhatsApps and Snapchats and Ubers today than in the 1980s, both in absolute terms and relative to the population of businesses. In 2014, venture capitalists poured $30 billion into 3,665 new companies—both numbers the highest since the bubble year of 2001. Back in 1980, 413 companies received venture capital funding. Compared to 1980, venture capitalists (VCs) invested nearly fifteen times the capital in nearly nine times as many companies, according to data from the National Venture Capital Association (NVCA), the industry’s trade association.2 The NVCA reports that the number of companies receiving venture capital for the first time has also risen—from 293 businesses in 1980 to 1,410 in 2014. These numbers aren’t normalized for the volume of companies in operation. Could it be that more companies are receiving venture capital now than in 1980 because there are more companies overall? That turns out not to be the case. Compared to the stock of businesses with employees and the number of newly formed businesses

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with employees, the number of venture capital-backed businesses is higher in recent years than it was in the early 1980s. But the pattern is hardly a smooth upward trend. In 2013, the ratio of venture capitalbacked companies to both new and total employers was roughly half of its rate in 2000, the peak of the first Internet bubble. Venture capital-backed companies made up 0.7 percent of new employers and 0.07 percent of all employers in 2000 as compared to 0.33 percent and 0.03 percent in 2013.3 But the post-2000 figures may just reflect the size of the late 1990s bubble. A longer horizon tells a different story. The ratio of venture capital-backed companies to all employers in 1998 was slightly lower than in 2013, and the ratio of venture capital-backed companies to new employers in 1998 was the same as in 2013. Moreover, the ratios in 2013 were more than five times higher than they were in 1980, the first year for which data are available. In 1980, 1.15 in every 10,000 U.S. employers received venture capital backing. In 2013, 6.7 in every 10,000 did so. Compared to new employers, the rise is even starker. In 1980, just 0.09 percent of new employers received venture capital backing. In 2013, that ratio was more than nine times higher, at 0.83 percent (figure 4.1).4 The Internet 1.0 bubble obscured the long-term

Figure 4.1. Venture Capital-Backed Companies as a Share of New Employers Source: Created from data from the National Venture Capital Association and Census Bureau.

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shift. A far higher fraction of American employers receives venture capital financing now than in the mid-1980s. We can also look at the number of angel-backed companies, normalized by comparison to the number of existing and new employer businesses, by examining figures compiled by the Center for Venture Research (CVR) at the University of New Hampshire. But note that these data are not as good as the data on venture capital-backed ventures. First, the CVR does not publish its methodology for tracking angels, which raises some suspicion in the minds of researchers. One cannot be sure of the accuracy of the underlying survey of business angels. Second, the series begins in 2002, after the Internet 1.0 bubble burst. Because the data do not start until after the venture finance markets rose and then fell, they tell an incomplete story. Nevertheless, the ratio of angel-backed companies to the stock of employer businesses reveals that the trend is rising, at least over the past decade. Almost double the fraction of American employers received funds from business angels in 2013 as in 2002 (figure 4.2).5

Figure 4.2. Angel-Backed Ventures per Thousand Employers Source: Created from data from the Center for Venture Research and Census Bureau.

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If we leave aside the venture capital-backed companies, which are extremely rare, and concentrate on the angel-backed ones, we see that the pattern is the opposite of what Decker and his colleagues found. High-growth entrepreneurship measured as Decker and his colleagues calculated it declined in the 2000s, but high-growth entrepreneurship measured by angel data rose. Data like those presented in figure 4.2 make it difficult to believe high-growth entrepreneurship is really in decline. At best, the evidence is contradictory. The Number of Financiers

Another way to look at what happened with angel- and venture capital-backed companies is to examine the number of people financing them and the amount of money they have spent. If the number of investors and the amount invested is trending in the same direction as the number of ventures receiving financing, then we can have more confidence in our assessment of whether entrepreneurship is in decline. Let’s look first at venture capital firms. The data on the amount of money coming from venture capitalists and the number of people doling it out tell the same story told by the statistics on the number of companies receiving financing: a bubble around the turn of the millennium, followed by a burst and then no particular trend. These data also show that there is more venture capital activity now than there was three-plus decades ago. Looking at the amount of money, in 2008 dollars, venture capitalists committed to young companies every year since 1980, we see that VCs invest far less today than what they put into these businesses in 2000 —$27.3 billion in 2014 versus $126.8 billion in 2000 (figure 4.3). But the amount venture capitalists put into young companies in 2014 was still more than five times the amount in 1980.6

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Figure 4.3. Venture Capital Commitments (in billions of 2008 dollars) Source: Created from data from the National Venture Capital Association.

The dotted line in the figure—the ten-year moving average— offers a smoother version of what has happened over time: a rise and then a decline. No matter how you look at the figures, the amount of venture capital investment in American companies is higher today, in constant dollars, than it was several decades ago. The data on venture capital funds are similar. There was a rise and a decline, but the current level is far higher than that of the 1980s. Venture capital funds peaked during the Internet 1.0 bubble, hitting a high of 1,852 in 2001, and then declined to 1,206 by 2014 (figure 4.4). The count of firms raising funds maxed out at 1,016 in 2007 and dropped to 803 by 2014. But, once again, both numbers in 2014 were more than eight times higher than in 1980.7 Other figures reflect same pattern. As indicated by the data from the NVCA, the total amount of capital that venture capitalists have under management has shrunk from $319 billion in 2001 (measured in 2008 dollars) to $142 billion in 2014. Yet this figure is more than

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Figure 4.4. Number of Active VC Funds Source: Created from data from the National Venture Capital Association.

ten times larger than the $10.7 billion the industry managed in 1980.8 It is also higher than in every year prior to 1999. The same is true if we look at the capital under management on a per venture capital firm basis. The average venture capital firm managed less money in 2014 —$177 million in 2008 dollars—than in 2001, when it managed $345.1 million. But the average VC firm manages more inflation-adjusted dollars today than the average firm managed in 1985.9 The data on business angels, though it has been collected for a much shorter period of time, tells a similar story. There are more angels now than in 2002, and more angel money (again in constant dollars) is invested annually than twelve years ago. A greater fraction of the population is now making angel investments. The data from the CVR shows that there was one angel for every thousand Americans in 2014, up from 0.7 per thousand in 2002. Angels invested $24.1 billion (in 2010 dollars) in 2014, an increase of nearly 27 percent from what they put into young companies in 2002.10 The Angel Capital Association, the trade association for angel groups, reports that in 1999, there were fewer than 72

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100 American angel groups. By 2013, that amount had more than tripled, to 385.11 In short, the number and amounts of angel and venture capital investments are more consistent with a story of rising business creation and ownership than a story of decline. The Exit Outcomes Have Improved

We can also look at the outcomes of investments. If entrepreneurship in America is in decline, then a shrinking fraction of companies funded by venture capitalists and business angels should get acquired or go public. But if entrepreneurial activity is flat or even improving, we should see a flat or increasing share of investor-backed companies having successful outcomes. The data show that the performance of venture capital-backed startups has lately been on a roll, even though the 115 venture capitalbacked companies that went public in 2014 are short of the record of 267 in 1999.12 The rise in the number of companies going public has boosted venture capitalists’ returns on their investments. In 2014, twenty-year venture capital returns were 35.4 percent per year, more than three times the return of the S&P 500, according to Cambridge Associates.13 The American venture capital industry remains the envy of the world. A more careful look at the underlying data shows that exits of venture capital-backed companies are much better now than they were three decades ago. As indicated by data from the NVCA, there were 194 acquisitions of venture capital-backed companies in 2014 and 115 initial public offerings (IPOs), compared to one acquisition and 59 IPOs in 1980.14 High-potential ventures do not show the linear trends seen with other kinds of entrepreneurship. There was a definite bubble around 2001. But if we look at the times before and after that bubble, we 73

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see that the period before is lower on all measures, including the exit performance. There were 238 IPOs and 379 acqusitions of these types of companies in the bubble year of 2000, a time we might compare to a hundred-year flood.15 But the flood appears to have altered the landscape, and the numbers have never returned to their previous levels. One of my favorite measures of this trend is to look at exits (the number of companies that went public or were acquired) as a fraction of investments five years earlier. Since investors use five years as a rough target period for outcomes, a look across this gap tells us something about the yield on investments—the proportion of companies that gave their backers profitable exits. Exits as a fraction of venture capital-backed companies five years earlier were 21.70 percent in 2014, versus 13.32 percent in 1985 (figure 4.5).16 But this measure is down from its glory days of the late 1990s. Whether or not an exit occurred is only part of the picture. We would also like to know how much money those exits brought in.

Figure 4.5. Exits as a Fraction of VC-Backed Companies Five Years Earlier Source: Created from data from the National Venture Capital Association.

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Figure 4.6. Average Value of Exits (in millions of 2010 dollars) Source: Created from data from the National Venture Capital Association.

Bigger exits, of course, mean more money for investors and a better outcome from their efforts to finance new ventures. Again, we need to ignore the bubble. Exits (in 2010 dollars) reached an average value of $282.30 million in 2000, but the average company from which investors cashed out in 2014 was worth $229.14 million, which is far higher than the $60.47 million that the average exit raised in 1992 (figure 4.6).17 These figures, like the others we looked at, show that American entrepreneurship is doing better now than it was in the 1980s and early 1990s. The Valuations of Young Companies Have Been Rising

One final piece of information on high-potential ventures concerns valuations of young companies. The valuation of a business is the amount that its investors and entrepreneurs agree the company is worth at the time of the investment. It comes from setting the terms of the investment—this much money for that many shares in the business.

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I do not want to make too much of these numbers because they are based on the weakest data in this entire book. They come from Cooley, LLP, a Silicon Valley law firm, which aggregates them from the deals its attorneys have done. I would not hesitate to use Cooley for legal advice on how to structure my high-potential startup, but it is a law firm, not a division of the U.S. Census. It has no goal of gathering representative data. It is simply reporting numbers from the work it has done. Furthermore, the key statistic Cooley is measuring is the valuation of investments at “Series A” financings—the first round of raising capital that a new company undertakes after its seed round. A tiny fraction of the companies started in the United States every year get financing, and many that get seed round financing don’t go on to a Series A round. The sample we are looking at—approximately 400 companies per year—is a miniscule and not terribly representative portion of young businesses. To add a final caveat, the Cooley data were first collected in 2004, so they do not yield a very longterm picture. Given these limitations, what do Cooley’s data say about startup company valuations over time? I have calculated the five-quarter moving average valuation of Series A financings measured in millions of 2015 dollars (figure 4.7).18 The chart shows that these valuations have been trending upward; moreover, they have been on a tear since 2013, nearly doubling in just two years. Use your own judgment as to whether these data are strong enough to show anything about entrepreneurship. But even if you think they aren’t very useful, there is one thing they are not telling us. Nothing in the valuation data suggests that high-potential entrepreneurship has been declining.

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Figure 4.7. Five-Quarter Moving Average of Series A Valuations (in millions of 2015 dollars) Source: Created from data from Cooley, LLP.

Key Patterns in the Data

1. Venture capital-backed companies account for a much larger fraction of new and existing employer firms now than in the mid-1980s. 2. Angel-backed companies account for a larger fraction of employer firms now than in the early 2000s. 3. Though down substantially from their peaks in 2000, the number of venture capital funds, the number of venture capital firms raising new funds, venture capital commitments, and the amount of venture capital under management are all higher now than in the 1980s. 4. A higher fraction of venture capital-backed companies financed five years earlier has a positive exit, and exit values are higher now than in the 1980s. 5. The valuations of early-stage companies have risen substantially since the early 2000s.

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The numbers on high-potential ventures are less reliable and sparser than the data on more typical startups, but they provide some insight into what has happened to a particular category of entrepreneurship. They show that the kind of startups that grow very rapidly and go public or get acquired by large public businesses —businesses like Facebook and Snapchat and WhatsApp—have grown, not shrunk, over three-plus decades. The numbers for highpotential ventures and of the financial institutions that support their growth have both risen, even after the massive correction following the collapse of the Internet bubble at the turn of the millennium. The number of companies, the number of investors, and the amount of money raised or invested all show similar patterns: the figures in 2014 are several times higher than those in the 1980s and early 1990s. Nothing in the data on high-potential ventures confirms the story of a decline in American entrepreneurship. So what is going on? Entrepreneurship is not in decline. The number of high-potential businesses has increased since the 1980s despite the popping of the Internet 1.0 bubble. The system for financing those businesses is correspondingly larger. American business owners are making more money than they did in the 1980s, and more of Americans’ earnings comes from their entrepreneurial endeavors. A higher fraction of the population is running businesses, and we have many more businesses per capita than we did three-plus decades ago. The failure rate of existing small businesses is lower than it was at the time of Reagan’s “morning in America.” But all is not rosy. The rate at which Americans are starting companies with paid employees is down dramatically. The next chapter explains why that decline matters to policy makers and academics, and why you should care too.

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FIVE The Implications of Fewer Employer Startups

The strongest evidence of a decline in entrepreneurial activity is that the rate of new employer firm formation has fallen by half over the past three-plus decades. That large decline has academics, policy makers, pundits, reporters, and others concerned. Even if the experts are wrong about the breadth of the decline in entrepreneurship and founders are starting businesses without employees in place of those with paid workers, it is still a problem. New employers are a key source of employment and productivity growth, and that is one reason why so many observers urge policy makers to intervene to reverse the decline in the formation of employer businesses. This chapter focuses on the implications of the decline in the rate of formation of new employer businesses on the economy. Because a lower rate of formation of employer businesses adversely affects both employment and productivity, policy makers need to understand the true causes of this decline. The Problem: A Shift to Non-Employers

As we saw in chapter 2, the stock of employer businesses per capita was slightly higher in 2013 than it was in 1977, but the stock of non-employer businesses has risen substantially. Have entrepreneurs boosted their rate of formation of non-employers, or are nonemployers failing at a lower rate than three decades ago? And did those

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changes occur because entrepreneurs are starting non-employers in place of employers or are they independent of each other? It’s difficult to tell exactly what has happened. We lack a measure of the in-and-out flow of non-employers. The data don’t tell us whether the rate of creation of non-employers is higher than the rate of creation of employers, if the failure rate of non-employers is lower than the failure rate of employers, or both. All we can tell is that there has been a shift toward non-employers in the mix of small businesses. As long as the government has been collecting data on businesses, most American companies have been non-employers. But that the pattern has been accentuated over the past two decades. As the rate of growth of employers has slowed and the rate of growth of non-employers has accelerated, the fraction of non-employers has steadily increased. We can look at a couple of different sources of data for more information. One is the set of statistics on the stock of businesses with and without employees collected by the U.S. Census and made available by the Office of Advocacy of the Small Business Administration (SBA). Initially in one report in 1992 and then annually from 1997 to 2011, the most recent year of publication, the SBA has provided the count of employer and non-employer businesses in the United States on its website. This information allows for an easy calculation of the fraction of companies with employees as it reveals the decline in the fraction of employers. The relative growth of the two groups of companies has meant that the fraction of American businesses with employees has shrunk from 26.4 percent of the total in 1997 to 20.2 percent in 2011 (figure 5.1). Because virtually all of these companies are young and small, this transformation means that young and small businesses are far less likely to have employees now than they

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Figure 5.1. Fraction of U.S. Companies with Employees Source: Created from data from the U.S. Census.

were in the late 1990s. Although the 6.2 percentage point decline may not seem like a lot, it is. The shift amounts to a one-quarter decline in the share of young and small companies with employees. The Census Bureau did not begin collecting data on the number of businesses without employees until 1997. Therefore, its data alone provide a fairly short period over which to look at the share of employer businesses. The Internal Revenue Service, however, has collected data on the number of U.S. businesses—sole proprietorships, partnerships, and corporations—since 1980. By comparing the number of employer businesses reported by the U.S. Census with the number of total businesses reported by the IRS, we can see what has happened to the share of businesses with employees over a longer time horizon. The pattern shown by the census data alone is also present in the comparison of the IRS and census data; the combined data follow the Census Bureau’s shorter-term numbers. The decline in the fraction of businesses with employees is remarkably large. In 1980, the

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Figure 5.2. Employers as a Fraction of U.S. Businesses Filing Taxes Source: Created from data from the U.S. Census and the Internal Revenue Service.

employer firm share of total businesses, as measured by IRS data, was 27.7 percent. By 2012, it had fallen to 15.3 percent—a 44 percent decline (figure 5.2). (The IRS reports a lower fraction ratio of employer firms to total firms than does the U.S. Census because its definition of a business is more inclusive than that of the Census.) Another way to look at the data is to compare only IRS data on small businesses. The tax authority counts the number of passthrough entities in the economy—sole proprietorships plus Subchapter S corporations plus partnerships. That’s a pretty good approximation of small businesses, since virtually all of them take one of these legal forms. In 1980, there were about three such entities for every employer business in the United States. By 2012, the ratio had doubled to six-to-one.1 Stated differently, the number of passthrough businesses has increased faster than the total number of employer businesses over the past three-plus decades. Non-employers, it appears, are driving the rise in the number of pass-through businesses reported on Americans’ tax returns.

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In short, the data on employers and non-employers show that over the past several decades, non-employers have become a rising fraction of American businesses. That is important because it highlights the problem of looking at the decline in the rate of formation of new employers as an indicator of the health of American entrepreneurship. Because employers are becoming a less prevalent form of business, the decline in their formation may not be due to a drop in entrepreneurship. It could simply indicate a shift from employers to non-employers. Employment in New Firms Has Dropped

Not only are people in business for themselves less likely to have paid employees, but fewer people are working in young companies. The U.S. Census uses different data from the BLS to measure entrepreneurship. Rather than capture the fraction of the population that is self-employed, the Census looks at the types of companies people create. For our purposes, the two main categories are companies with employees, called employer businesses, and those without paid workers, called non-employer businesses, which we have discussed in earlier chapters. By definition, only the employer businesses create jobs for others. That makes the Census Bureau’s measure of employer firms its key measure of job creation. The rate of creation of these businesses was about half its 1977 level in 2013, the latest year for which data have been released (see chapter 1). That is leading to a decline in the number of people who are working at new firms. It is statistically possible, of course, for the number of people working at new firms to rise even if the rate of creation of new employers were to fall—if the average new business had many more employees now than it did three decades ago—but that is not happening. A

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Figure 5.3. New Firm Share of U.S. Employment Source: Created from data from the U.S. Census.

much smaller portion of the labor force works for new businesses today than in the late 1970s. The fraction of the labor force working for companies less than a year old fell from 5.7 percent in 1977 to 2.0 percent in 2013 (figure 5.3). Again, we shouldn’t be deceived by the small numbers here. At no point did brand-new businesses employ a very large portion of the labor force. What is important here is the size of the change. The percentage in 2013 is only a little over one-third of the 1977 percentage. Even if we allow for the possibility that the 1977 number is an outlier, the proportion of the labor force working for new businesses is much lower now than it was. Americans in the 1970s were more likely to work for new companies.

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It is important to consider where the decline is manifest. Is this just a drop in employment in companies founded the previous year, or is it more widespread? The answer, provided by Ryan Decker, an economist at the Federal Reserve, and his colleagues at the U.S. Census and University of Maryland, is that the drop is more widespread than just a decline in employment in companies in their first year of operations. Decker and his colleagues show that the fraction of people working at businesses under five years old has declined since the early 1980s.2 The labor force is shifting to work at older businesses as the creation of new employers slows. It is also uniform throughout the economy. Decker and his colleagues find that although the employment decline at young firms cuts across all sectors, it has been steepest in services and retail. We will return to the reasons later in the book. For now, it is important to note that young businesses simply do not employ as many people as they did in the late 1970s. Decker and his colleagues also addressed another question: how much of this decline comes from a decrease in the rate of formation of new employer firms, and how much is because new companies are smaller than they once were? Theoretically, the latter could account for the whole decline in employment. But Decker and his colleagues show that that is not the explanation. Their careful analysis reveals that there has been no change in the average initial size of new employer businesses;3 the average startup employs the same number of people today as its counterpart of three decades ago. The problem is that there are fewer new employers. The cumulative effect of the decreasing startup rate—what Decker and his colleagues call the “startup deficit”—is to reduce employment at new businesses not just immediately but in the cohort

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of companies going forward. As each generation of startups is smaller than the last, the number of jobs created by startups declines. Because startups increase employment at a higher rate than mature firms, this decline creates a rising deficit in job creation that slows overall job growth. The decline in job creation at new businesses is far from trivial. Census data reveal that in 2013, new businesses generated 2.2 million jobs— down from 3.7 million in 1977.4 This happened even though the private sector labor force grew from 66.1 million in 1977 to 117.3 million in 2013.5 The private sector labor force increased by 77 percent, yet the number of people working in new businesses has fallen by 39 percent. More important, this decline has occurred across the board. Decker and his colleagues showed that it is present in all major sectors of the economy—though, as mentioned earlier, it is heaviest for retail and services. It is also present in all fifty states, though greater in the South and West than in the Midwest and Northeast.6 The pattern is clear: America is creating fewer new companies with employees than it did three-plus decades ago, and these companies are employing roughly the same number of people now as then. The net effect is that new and young companies employ far fewer workers now than in the late 1970s, and this decline is present across all industries and all states. Small Businesses Are Employing Fewer People

The numbers get even more disturbing. The trends in employment are not limited to new businesses but extend to more mature companies as well. Fewer Americans work at small businesses than a generation ago. Jobs are moving away from any businesses that could be characterized as “entrepreneurial.”

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The Small Business Administration typically defines a small business as a company with fewer than 500 workers. Using this cutoff as our standard, we can look at employment trends at big and small businesses over time. Between 1990 and 2011, the SBA reports that small business employment grew by 13.3 percent, and big business employment increased by more than twice that: 28.6 percent.7 Data from the U.S. Census on the level of employment at big employers— companies with at least 500 employees—and the smallest employers—those with between 1 and 19 workers—since 1977 show this pattern quite clearly. The figure sets the level of employment for both sizes of business at 100 percent in 1977 and shows the relative level in 2013. In 2013, big company employment was 181 percent of its 1977 level, indicating that it has risen 81 percent since then, while small company employment was 144 percent of its 1977 level, showing that it has risen a little over half that, 44 percent (figure 5.4). Moreover, as you can see from the figure, the pace of hiring at the

Figure 5.4. Relative Growth of Small and Large Business Employment Source: Created from data from the U.S. Census.

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biggest and smallest employers began to diverge in the mid-1980s, with the linear trend for the biggest businesses being much higher than that for the smallest businesses over that period. More and more people are working at big businesses rather than small ones, just as more and more people are working at older companies rather than younger ones. The claim that new and small businesses are America’s job creators may be growing outdated. If employment growth has been greater at big businesses than small ones for over twenty years, it is simple mathematics to conclude that the small business share of employment must be declining. The Census Bureau tracks the number of people employed in the private sector and the size of the businesses where they work in a data series reported by the SBA. We can look at the fraction of the total private sector employment accounted for by businesses with fewer than 500 workers each year from 1987 to 2011. In 1987, businesses with fewer than 500 employees accounted for 54.5 percent of all private sector employment. In 2011, the share was down to 48.5 percent (figure 5.5).8 Since 1988, Americans have shifted from mostly working at small businesses to mostly working at large ones. We can corroborate these findings by examining other federal data. The Census Bureau’s Business Dynamics Statistics database contains information about the small-company (under 500 employees) fraction of employment in a series extending from 1977 to 2013. They show a similar pattern to that shown in the series provided by the SBA. Businesses with fewer than 500 employees accounted for 52.2 percent of all private sector employment in 1977. The fraction peaked at 54.8 percent in 1987, and by 2013 was down to 48.4 percent (figure 5.6).9 Since the late 1980s, big business has been taking an increasing share of U.S. employment, regardless of whose data we examine.

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Figure 5.5. Share of Private Sector Labor Force Employed in Small Businesses Source: Created from data from the U.S. Census.

Figure 5.6. Percentage of the Private Sector Labor Force Employed in Small Businesses Source: Created from data from the U.S. Census.

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The Productivity Challenge

Productivity is a measure of how much output we get from each unit of input in the economy. Growth in productivity is a good thing. It means we are getting better at using our resources efficiently. That is why policy makers are concerned about the decline in the U.S. productivity growth rate. We are still getting more productive, but our pace of improvement has declined. Between 1947 and 1977, U.S. productivity growth averaged 2.6 percent. But from 1977 to 2016, a period of substantial decline in the rate of formation of employer businesses, productivity growth averaged only 1.8 percent.10 Nobel laureate and Arizona State University professor Edward Prescott and UCLA professor Lee Ohanian believe that the decline in new employer firm formation rates are at least partially responsible for the slide in U.S. productivity.11 Prescott and Ohanian do not explain why this decline in employer firm formation rates has hindered productivity growth, but other experts suggest several factors. First, non-employers are a poor substitute for employers when it comes to economic impact. In 2012, the latest year for which data are available, Census Bureau figures show that the average small employer in the United States had revenues of $2,070,000, and the average nonemployer had sales of $45,000. That’s a ratio of 46:1. Non-employer businesses together only account for about 4 percent of U.S. sales.12 The substitution of non-employer businesses for employer businesses has dampened down the output side of the productivity equation. The decline in the rate of formation of new employers and the shift toward more non-employers in the business population has meant a smaller pool of the kinds of businesses that engage in substantial capital investment. Employers spend much more on equipment and structures than non-employers. Census Bureau data show that in 2013 the average non-employer spent $2,376 on equipment

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and $1,556 on structures. By contrast, the average employer spent $169,091 on equipment and $107,148 on structures.13 Surveys by the National Federation of Independent Business (NFIB) show that small businesses have reduced their rate of capital investment over time. In 2015, the NFIB survey revealed that only 26 percent of small businesses planned to make a capital expenditure in the next six months. This number is far below the fraction of 41 percent that said they would make such investments in 1996.14 If we match up Federal Reserve figures on the capital expenditures of non-corporate, non-financial businesses (a proxy for small businesses) with IRS data on the number of sole proprietorships in the economy, we can see what has happened to capital expenditures at the average small business over time. The data show that the average non-financial, non-corporate entity spent far less on equipment and structures in 2013 than it did in 1980. In 1980, the inflationadjusted amount spent by these firms divided by the number of sole proprietorships in the economy was $96,160 (in 2013 dollars). In 2013, this figure averaged only $14,433.15 The shift to non-employers could account for the slowdown in innovation we have been seeing in small businesses in recent years. Data from the U.S. Patent and Trademark Office indicate that small businesses are less innovative than they were in the late 1980s. The absence of hiring at small and young businesses could account for their slowdown in innovation since people are the ones who come up with the new ideas. Measuring small business innovation is not easy, and there are not a lot of indicators of innovativeness that have been collected over time. But one that has been gathered since the late 1980s is the fraction of patents granted to small enterprises. In 1988, small businesses accounted for 28 percent of all utility patents granted in the

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Figure 5.7. Share of U.S. Utility Patents Granted to Small Entities Source: Created from data from the U.S. Patent and Trademark Office.

United States. By 2015, the small company share of utility patents had shrunk to 19 percent (figure 5.7).16 The decline in new employer business formation might also have reduced productivity growth by lowering business dynamism. Business dynamism —the creation of new companies and the failure of old ones—is an important way that the economy reallocates resources to more productive uses. Older, less productive organizations die off and new, more productive organizations get the capital and labor that previously went to the organizations that made less efficient use of those resources. The decline in new employer business formation might be the reason why we are less productive than we once were, and consequently why our living standards have stagnated. Entrepreneurs reallocate resources from older, less productive firms to newer, more productive ones. Not only does this process put capital and labor to better use but it also keeps existing firms focused on ways to make the most productive use of their resources.17

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University of Maryland economist John Haltiwanger, an expert on the contribution of new firms to productivity, explains why. He writes, “Exiting businesses are less productive than continuing ones. Furthermore, the data show that, conditional on survival, young establishments have higher productivity levels and higher productivity gains than more mature establishments. In effect, the churning process replaces lower productivity businesses with new, more productive ones, thereby increasing productivity in the economy as a whole. . . . A large fraction of U.S. productivity gains reflect the displacement of low productivity establishments by new establishments with higher productivity.”18 To Haltiwanger, reduced business dynamism represents yet another way that the decline in new employer firm formation has hindered U.S. productivity growth. Key Patterns in the Data

1. A declining fraction of Americans work in new businesses. 2. The fall in the number of new employers, not the size of those companies, accounts for this decline. 3. The rate of employment growth at small businesses has lagged behind that of large companies. 4. As a result, fewer Americans now work in small businesses than did in the 1980s. 5. Non-employers generate far less in sales and make far less capital investment than employer businesses. 6. Small businesses now contribute significantly less to technological innovation than they did in the 1980s. 7. The decline in new employer firm formation has reduced business dynamism and, according to some economists, lowered U.S. productivity.

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Over the past three-plus decades, the rate at which Americans found businesses with employees has fallen by about half. Economists and policy makers are concerned that this decline has had adverse effects on U.S. labor markets and on U.S. productivity, and their concern appears to be warranted. The data show evidence of negative effects of the decline in employer firm formation on both employment and productivity. Still, we cannot conclude, as some authors have done, that a reduction in the new employer firm formation rate equals a decline in entrepreneurship itself. That leap makes it difficult to identify the cause of the problem and solve it. Rather than overgeneralize the problem and misdiagnose its cause and the appropriate cure, let’s take a look at likely candidates and how they stand up to the data.

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SIX It’s Not a Lack of Capital

In chapter 1 I discussed what some observers call the “decline in American entrepreneurship.” Indicators of this decline include that the fraction of outplaced executives looking to start businesses has fallen dramatically since the mid-1980s, the rate of unincorporated self-employment has been going down since at least the beginning of the 1970s, and the rate of creation of new businesses with employees is half what it was in the late 1970s. These trends have many commentators worried. They have offered up a number of reasons why “American entrepreneurship is in decline” and have proposed a wide range of “solutions” to the problem. Over the next several chapters, I will explore each of these explanations to see which ones best fit the data. One common explanation for the supposed decline is lack of access to capital. This story has two threads to it. First, savings—a key source of money for business formation—have dwindled. Too few Americans, the argument goes, have enough money saved up to start their own companies. Wages are stagnant, and as Barry Lynn and Lina Khan explain in Washington Monthly, “stagnant wages” mean that “fewer average families have the savings needed to invest in a small business.”1 That’s a problem because savings are crucial to business creation. Nearly four in five American entrepreneurs (77 percent) report that they financed their new companies at least partly

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with their own savings.2 If would-be entrepreneurs have inadequate savings to finance business formation, it would clearly reduce the amount of entrepreneurial activity. The second thread of argument is that banks have lost interest in financing small businesses. They have raised credit standards, boosted capital requirements, and simply exited the small business market. According to one group of observers, this is why startups of new employers have fallen by 50 percent in thirty-six years. The Bank Exit Story

The tale begins with the changes in commercial banking. Like most industries, banking has been much affected by massive technological changes over the past three decades. Computing—both in its ability to handle huge amounts of data and in its capacity for instantaneous communication—has transformed an industry that was once based on relationships between bankers and small business owners. Now it is based on algorithms that calculate credit scores and payment patterns. Small business lending is a poor fit with this technological revolution because it is harder to automate than consumer lending. Small businesses are very different from one another, with varied failure rates and different uses of funds, making common standards much more difficult to apply. As a result, banks have automated business loans to a much smaller extent than consumer loans. They are more expensive to underwrite and service, and they are less amenable to securitization. For a bank, large business loans are not much more timeconsuming than small business loans—the approval process and servicing are largely the same. But simply because they are bigger, big loans earn more interest than smaller ones and are thus more profitable. Rising competition in the banking sector has led bankers, 96

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particularly those running public companies, to concentrate on the more profitable larger loans at the expense of smaller ones. The combination of technology and competition has thus led banks to move out of small business lending. Since 1980, the number of independent banks in the United States has fallen by half as the banking industry consolidated.3 The decline has been particularly severe among community banks, traditionally major lenders to small businesses. Gone are the days when you could chat up your local banker for a loan at the country club or your kids’ school function: most communities no longer have local bankers. Data from the Federal Financial Institutions Examination Council (FFIEC) support this notion of a movement of banks out of the small business lending market. The FFIEC coordinates five different banking regulators. Among its many activities, it collects data on bank loans, including loans to small businesses, which it defines as those with sales of $1 million per year or less. The FFIEC data show that the portion of bank credit that goes to small businesses has declined significantly. Between 1996 and 2014 the fraction of all U.S. business loan volume going to businesses with less than $1 million in sales fell from 43.1 percent to 34.6 percent (figure 6.1).

Figure 6.1. Small Business Share of Business Loan Volume Source: Created from data from the FFIEC. 97

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Data from a different source—the Federal Deposit Insurance Corporation (FDIC)—show the same pattern. The FDIC captures a different measure of small business lending. It tracks small nonresidential and nonfarm loans, which it defines as loans of less than $1 million for both commercial and industrial purposes. According to both of these measures, small loans have become a shrinking share of business loan volume over the past two decades. The small loan share of nonfarm, nonresidential loan value was 52 percent in 1995 but only 24 percent in 2015. The small loan share of commercial and industrial loans declined from 33 percent in 1995 to 20 percent in 2015 (figure 6.2). Some observers have argued that the consolidation in the banking industry has reduced entrepreneurs’ access to capital, which in turn has depressed the rate at which would-be entrepreneurs start companies. Barry Lynn and Lina Khan argued in their 2012 Washington Monthly article that as more and more banks have exited the small business market, loan officers have lost “the leeway and local knowledge to lend to established local businesses, much less new ventures.”4

Figure 6.2. Small Loan Share of Commercial and Industrial Loan Value Source: Created from data from the FDIC.

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The obvious solution to this problem, according to the advocates of this position, is to help American entrepreneurs get access to capital. Some argue that the government should provide funding to people who lack sufficient savings. Others suggest subsidizing loans to make banks more willing to lend money. Easier access to capital, they claim, will reverse the decline in startups. But before we spend money on this solution, we should make sure that the problem actually exists. Bank Exits Don’t Mean Reduced Access to Credit

I am not convinced. For a decline in bank lending to small businesses to have caused a decline in entrepreneurship, we need to know that America’s entrepreneurs are having trouble getting access to credit. If banks are making fewer loans to small businesses, but those businesses are getting money some other way, then a shift in banking lending did not cause a decline in new employer businesses. Some observers have claimed that new and small businesses are finding it increasingly difficult to borrow. John R. Dearie, the executive vice president of the Financial Services Forum, testifying before a House subcommittee in 2014, said that increased difficulty in obtaining credit “may account, at least in part, for the declining rate of new business formation. . . . Difficulties in accessing sufficient capital and credit at reasonable terms can delay or prevent the launch of a new business, disrupt the further growth and development of an existing business, or even kill an otherwise healthy and viable business.” He added that “while securing financing has always been a major challenge for entrepreneurs . . . circumstances have become significantly more difficult in the wake of the 2008 financial crisis.”5 It seems plausible that small and new businesses faced tighter access to credit after 2008, but it was not a problem from 1980 to

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2008. Yet the fall in the rate of formation of new businesses with employees—the primary evidence for the decline in the rate of entrepreneurship—has been going on since the late 1970s. Every month since 1986, the National Federation of Independent Business (NFIB) has surveyed its members to see whether they borrow at least once a quarter. The NFIB’s January survey shows that the fraction of small businesses borrowing regularly has recently declined, from 37 percent in 2007 to 33 percent in 2015. But before the financial crisis, borrowing by small businesses showed no trend in either direction. In 1986 and 2007, a similar fraction of businesses borrowed regularly (figure 6.3). Other data show the same thing. The FDIC reports that more small business loans are available now than in the mid-1990s.

Figure 6.3. Percentage of Businesses Borrowing Regularly Source: Created from data from the NFIB.

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Although the value of those loans has not risen as fast as real GDP, which increased by 53 percent between 1995 and 2013, the value of outstanding commercial and industrial loans of less than $1 million, a common proxy for small business borrowing, has risen in inflationadjusted terms over the past eighteen years, reaching $285.8 billion (in 2011 dollars) in 2013, up from $261.3 billion in 1995.6 Many more business loans are being made now than in the 1990s, especially when lending is compared to the number of potential borrowers. For instance, a comparison of FDIC data on the number of commercial and industrial loans of less than $1 million with Census Bureau data on the number of employer businesses suggests that there are far more loans per business in 2013 than there were in 1995. In the mid-1990s there were about 1.4 loans per company; the most recent data show 4.5 loans per company.7 If we compare the number of loans with IRS figures on the number of businesses in the economy, the pattern is similar. In 1995, there were 0.28 loans per IRS-tracked business, and in 2012 there were 0.72.8 Even when we compare the number of loans to the number of total businesses in the economy—those with employees and those without—the ratio has still gone up: from 0.4 loans per business in 1995 to 0.82 loans per business in 2013.9 That’s a remarkable increase in lending, given the increase in the number of businesses over the time period. If we look more carefully at the kinds of debt commonly used by entrepreneurs, particularly in the early years of their businesses, it is hard to make the case that they face declining access to capital. It is cliché to say that entrepreneurs max out their credit cards to start their businesses. But clichés often have a ring of truth. Many people use credit cards to finance their young businesses in the very early years of operation.

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If a lack of access to credit were keeping Americans from starting businesses, we would expect to see credit card debt becoming harder to get. Rising credit card debt levels should correlate positively with new employer firm formation rates. But that turns out not to be the case. While the per capita rate of new employer firm formation has fallen by nearly half since 1980, the real value of credit card debt has increased nearly fivefold. In 1980, American consumers had $168.5 billion in credit card debt (in 2014 dollars). In 2014, the amount was $890 billion.10 It’s hard to imagine that Americans are less likely to start new employer businesses because they lack access to credit (from their credit cards) when there’s been a fivefold rise in credit card debt. Trade credit is another major source of capital for entrepreneurs, used, according to the Federal Reserve’s Survey of Small Business Finances, by nearly 60 percent of small businesses.11 If entrepreneurs are suffering from a lack of access to capital, we would expect to see a positive correlation between the level of trade credit and the level of new employer firm formation. But in fact we see the opposite. In 1980, nonfinancial non-corporate businesses, the Federal Reserve’s proxy for small companies, had $93 billion (in 2014 dollars) in trade receivables—the amount billed to customers not yet paid by them. In 2014, that amount had risen to $678.3 billion.12 A sevenfold increase in the inflation-adjusted amount of trade credit, at a time when the rate of new employer firm formation fell by 50 percent, suggests that lack of access to trade credit is not behind the decline in new employer firm formation. Aggregate data are also inconsistent with the argument that new companies cannot get financing. The Federal Reserve tracks much information on small businesses. Data from its Flow of Funds report show that small businesses are significantly more leveraged now than they were in 1980. 102

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Figure 6.4. Ratio of Liabilities to Proprietors’ Equity Source: Created from data from the Federal Reserve.

Although the years following the financial crisis have seen significant deleveraging—a fall in the ratio of liabilities to proprietors’ equity—that shift appears to reflect a movement back toward the long-term trend line. In 2005, this ratio was 49.7 percent, up from 30.7 percent in 1980. It increased to 92.4 percent in 2009 but fell back to 62.5 percent in 2015 (figure 6.4). If America’s entrepreneurs are more highly leveraged today than they were in the early 1980s, it’s hard to make the argument that lack of access to financing is keeping them from starting companies. Changes in Savings and Entrepreneurship Rates Aren’t Highly Correlated

The “personal savings rate” is the fraction of after-tax income that people do not spend on personal consumption, interest, or transfer payments. If this rate falls, it means that fewer Americans have set aside the money it takes to start a business. It also means that would-be entrepreneurs are less likely to have the financial track record needed to convince lenders that they are good credit risks. In recent years, the personal savings rate hasn’t really correlated with the per capita number of new employer firms formed annually. 103

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Figure 6.5. New Employers per Thousand People and Personal Savings Rate Source: Created from data from the Federal Reserve and the U.S. Census.

The per capita rate of formation of employer businesses—a number that was discussed at length in chapter 1—as shown in the bars in the graph and the personal savings rate, indicated by the line on the graph, don’t seem to have moved in concert since the early 1990s (figure 6.5). Especially in recent years, when the personal savings rate has risen, we should have seen a rise in the rate of employer startups if access to capital were actually a key driver of business creation. Greater savings would have meant that would-be entrepreneurs had more capital, which would have boosted their startup rate. That does not appear to have happened. The lack of correlation between personal savings and new employer firm formation might reflect the growth in personal borrowing. Since the 1990s, Americans have been borrowing far more than they once did and are using more borrowed funds to finance new businesses. The amounts they save may be less important to firm formation than they once were. Nevertheless, the data hardly support the argument that lack of access to capital is behind a decline of entrepreneurship.

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Another blow to the capital access argument is the lack of correlation between the rate of employer firm formation and household net worth. If access to capital were a key driver of business formation, we would expect to see household net worth positively correlated with employer firm formation. But the trends have gone in the opposite direction over the past twenty-five years. Between 1989 and 2013, the net worth of the average American household rose 59 percent in inflation-adjusted terms, and the employer firm formation rate fell by nearly one-third. For the typical household, net worth rose by 0.9 percent per year between 1992 and 2013, while employer firm formation was declining by nearly one-third.13 It is difficult to see a positive correlation between these sets of numbers. Not All Measures of Entrepreneurship Show Decline

In chapter 2 we saw that the failure rate of companies with employees has fallen significantly over the past thirty-plus years, leaving the stock of employers roughly the same today, relative to the population, as in the late 1970s. A constant stock of employers makes it difficult to argue that anything—access to capital or anything else—has led to a decline in entrepreneurship. Business ownership, it seems, has shifted from new companies run by people in business for themselves to not-so-new companies run by people in business for themselves. If the people providing money to entrepreneurs played a role in this shift, they would have had to prefer older small businesses over newer ones. That’s possible, but no one is telling that story. The lack-of-capital story also falls down when we consider some of the other data from chapter 2. The fraction of households holding business equity was the same in 2010 as it was in 1989. The level of entrepreneurship shown in the Kauffman Index of Entrepreneurial

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Activity was the same in 1996 and 2014. Lack of access to capital can’t explain why levels of entrepreneurship have remained the same. And lack of access to capital certainly can’t explain why entrepreneurship has gone up. That is what some measures show. We have more businesses and more non-employers per capita now than in the 1980s and 1990s. More taxpayers are taking the self-employment tax deduction and paying self-employment taxes, and a higher fraction of American taxpayers have business income or loss on their individual tax returns. How can an inability to get money account for those increases? Finally, the lack-of-capital argument certainly can’t explain what has happened with high-potential startups. The United States is both allocating more money for investment in high-potential companies and creating more high-potential businesses today than when Apple and Microsoft were startups. In short, the data patterns we would expect to see if a lack of access to capital were constraining entrepreneurship just aren’t there.

Key Patterns in the Data

1. Fewer banks are lending to small businesses than in the 1980s. 2. For twenty years before the financial crisis, when the rate of new employer firm formation was in decline, surveys by the NFIB did not show a trend toward lower borrowing by small business owners. 3. The number of loans per business has risen substantially over the past two decades even as the rate of employer firm formation has declined.

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4. Trade credit and credit card debt have risen substantially since the 1980s, even as employer firm formation has gone down. 5. Small businesses are more highly leveraged today than they were three decades ago, when rates of employer firm formation were much higher. 6. Neither household net worth nor the savings rate correlates positively with the per capita rate of employer firm formation. Many people have called for policy action to boost entrepreneurship by providing entrepreneurs and would-be entrepreneurs with easier access to financing. The theory is that entrepreneurship is declining because would-be entrepreneurs lack access to capital, but the data disagree on both counts. Even though banks have moved away from lending to small businesses in recent decades, there is little evidence for a lack of financing or that entrepreneurship, broadly defined, is in decline. The rate of creation of new employer businesses has fallen, but the data do not point to a lack of access to capital as a contributing factor. For twenty years before the financial crisis, while the rate of new employer firm formation was falling, there was no trend toward lower borrowing by small business owners. The number of loans per business has risen substantially over the past two decades. Trade credit and credit card debt have risen considerably since the 1980s. Small businesses are more highly leveraged today than they were three decades ago, when rates of employer firm formation were much higher. And in recent years, neither household net worth nor the savings rate is positively correlated with the per capita rate of employer firm formation.

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SEVEN Don’t Blame the Regulators

Many entrepreneurship advocates think regulators are responsible for the decline of American entrepreneurship. Too much regulation by the states and the federal government, they argue, is keeping Americans from starting companies.1 Tim Kane, a research fellow at the right-leaning Hoover Institution, told the House Committee on Small Business in 2015 that “government is discouraging entrepreneurship. It’s passive, maybe even unintentional, but the institutional hostility to entrepreneurs is very real.”2 David Burton of the Heritage Foundation told the same committee that “high and growing regulatory costs” and “environmental and energy regulations that raise the cost of energy and limit development of energy resources” are responsible for the decline in new business formation in the United States.3 Many small business owners agree. Consider the congressional testimony of Drew Greenblatt, the president and owner of a company called Marlin Steel Wire Products. He explained that the stack of forms he needs to fill out every year to adhere to federal and state regulations is taller than he is.4 A 2016 survey of 12,000 skilled professionals revealed that they believe regulation is the most important factor affecting the ability to start a business. “When government regulations complicate obtaining licenses and permits, hiring employees, and paying taxes, it is harder to start and grow a business,”

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wrote Lucas Puente, an economist at Thumbtack, which conducted the survey.5 To revive entrepreneurship, Burton and others advocate nothing less than a total regulatory reboot. Federal, state, and local government agencies, they say, need to examine their regulations to determine the cost of compliance by entrepreneurs and revoke or amend the ones that impose an undue burden on new and small businesses or else create an exemption for young and small companies. The latter should be subject to a less stringent regulatory framework until they reach a certain size. All proposed laws and regulations that might affect new and small businesses should include an economic cost-benefit analysis that balances the gains from the law or regulation against its costs.6 Elected officials should not pass environmental, health, and labor regulations without considering their impact on young and small companies. All regulations should have sunset provisions, and all elected bodies should create commissions to review regulations and suggest changes and expirations to them.7 Although these recommendations sound reasonable, all policy changes have consequences. Before we start altering or removing regulation in the hope of stimulating entrepreneurship, we need to know if regulation has actually hindered entrepreneurial activity and if reducing regulation would boost it. In this chapter I will present data that disagree with the claim that regulation is responsible for a drop in entrepreneurship in America over the past thirty-six years. But before I get to the data, let’s clarify exactly what advocates of the “regulation hypothesis” are arguing. The Regulation Hypothesis

In a nutshell, the regulation hypothesis is this: an increasing burden of rules and regulations has made it more difficult and expensive

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to start a business in the United States than it was a generation ago.8 Because regulators have created a climate in which would-be entrepreneurs must spend increasing amounts of time and money complying with federal, state, and local laws and rules, fewer people are starting companies.9 According to this argument, regulation creates two problems for entrepreneurs: cost and complexity. To comply with regulations, entrepreneurs must divert time and money from productive uses. The U.S. Small Business Administration estimates that annual compliance costs just for federal regulations exceeded $1.75 trillion in 2008, the most recent year for which data are available.10 A recent National Small Business Association survey suggests that the time and expense complying with state and local regulations is at least as high.11 Many states’ licensing requirements limit new business formation under the guise of protecting public safety,12 and this form of state regulation has risen dramatically. “In 1950, 5% of workers required a license or certificate,” Marie-Josée Kravis of the Hudson Institute writes in the Wall Street Journal. “Today that number is close to 30%. Fortunetellers, party planners, florists, shampoo assistants, cosmetologists, manicurists, beekeepers, librarians and many others have joined the ranks of licensed workers.”13 The regulatory burden is costly for all businesses, but it is disproportionately high for small and startup businesses, proponents of the regulatory hypothesis argue. Regulatory adherence has both learning curves and economies of scale. Making sure a workplace is safe and filling out government paperwork are in large measure fixed costs—the same whether you have one worker or 100. Because bigger companies can spread these fixed expenses over more revenue, employees, or output, the cost per employee of following regulations is much higher for a small business than a large one.14

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Academic, government, and trade association studies employing many methodologies have documented the higher compliance burden that new and small companies face. A study by economists Nicole and Mark Crain of Lafayette College showed that compliance with federal regulations cost American businesses just under $10,000 per employee (in 2014 dollars). But firms with fewer than 50 workers paid $11,724 per employee—17 percent more. For firms with at least 500 employees, the cost was only $9,083 per worker.15 The complexity of regulations also disadvantages new companies. As new regulations get added to old ones, the process of navigating the system of rule-following becomes increasingly complex. This regulatory maze deters would-be business owners who can’t figure out how to get a building permit or follow new environmental or labor regulations.16 Established firms can rely on corporate counsel, compliance officers, or other staff members to ensure that their businesses conform to regulation, but many new firms are flying blind. The result is that fewer would-be entrepreneurs will take on the risk of starting a company when they do not know how to manage a complex world of regulations.

A Suggestive Correlation

This argument is powerful, but it is a theory. Where is the evidence? And by that I mean data that come from aggregate statistics or careful studies. Anecdotes are fine, as is vivid imagery like Drew Greenblatt’s, but we can always find someone to claim that he or she would have started a company if not for the regulatory obstacles. If we are going to redo an entire regulatory regime, we need better support than a couple of examples. We have to know that rising regulation really is driving down entrepreneurship in America.

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Those advocating regulatory reduction can actually point to some compelling evidence. But to see it you have to understand how economists measure certain things. As I mentioned above, the federal government has dramatically increased the regulatory burden on businesses since the 1970s, and the courts have further expanded this effect. The government has added a bunch of new rules and regulations and has gotten rid of very few.17 This is where the creativity of economists has come into play. Each federal regulation has to be outlined in a document called the Federal Register—the repository where all federal regulations and rules are published. By counting the number of pages in this repository in each year, researchers can measure the regulatory burden over time. More pages mean more rules and regulations and a heavier burden.18 We can then compare the changes in the amount of regulation to changes in entrepreneurial activity over the same set of years. As

Figure 7.1. Regulation as Correlated with New Employer Firm Formation Source: Created from data from the U.S. Census and the Federal Register. 112

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those who claim that regulation is holding back entrepreneurship might expect, the two trends are negatively related. The per capita rate of employer business creation and the number of pages of rules in the Federal Register correlate at −0.67. That is, as the regulatory burden has risen over time, at least one measure of entrepreneurship has declined (figure 7.1).

Is This Evidence Convincing?

The policy makers and pundits who have argued that a rising regulatory tide is crippling entrepreneurship in America have not spent much time evaluating whether their claims are correct. They have preferred to focus, instead, on advocating “solutions.” A careful look at the data suggests that there is not as much support for their argument as appears at first glance.

Some Measures of Entrepreneurship Are Increasing over Time

The first problem with the overregulation argument appeared in chapter 2: not all measures of entrepreneurship show a decline. Some, in fact, are rising. If there is no decrease in entrepreneurship, it creates a problem for the argument that regulation is causing a decline. If we return to the statistics in chapter 2, we see the weakness of the overregulation argument. Alongside the negative correlation between regulation and new employer firm formation, there is a positive correlation between regulation and the per capita number of non-employer firms, the fraction of taxpayers filing self-employment taxes, the number of business tax returns per capita, and many other measures. These trends muddy the case that rising regulation is hindering entrepreneurial activity. Certain types of regulation might encourage a shift from employer businesses to non-employers. For instance, health and safety 113

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or labor regulations might lead entrepreneurs to avoid starting companies with employees. But most regulations—such as environmental rules, privacy rules, and advertising restrictions—should affect employers and non-employers similarly. Given that there is a positive correlation between overall levels of regulation and the per capita number of non-employer firms, and a negative correlation between regulation and employer firm formation, we can’t argue that regulation has a large influence on firm formation unless we know a great deal more about how regulations affect the cost of labor. Entrepreneurial Activity Is Becoming More Profitable

A second issue with the argument that regulation is to blame is that entrepreneurial activity has grown increasingly profitable. The case against regulation rests on the claim that it deters entrepreneurial activity by raising the cost of running a business. If this were true, then as regulation increases, profits should fall. But as we saw in chapter 3, American businesses are far more profitable than they were three decades ago. Profit margins are rising for sole proprietorships, partnerships, and Subchapter S corporations, and average profits at pass-through entities increased by nearly 200 percent in inflationadjusted terms between 1980 and 2012. If regulation isn’t adding enough cost to business operations to diminish profits, it is difficult to see how those costs are deterring would-be entrepreneurs. Few people focus on costs alone when deciding on whether to go into business for themselves. They focus on the difference between costs and revenues—that is, on profits. Any negative effect rising regulation has had on business’s bottom lines in the past thirty years must have been offset by something else. If there was an offsetting factor that allowed profits to rise, then would-be entrepreneurs probably were not deterred from starting companies.

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Regulation Should Also Hurt Incumbent Firms

The third issue with the overregulation argument is that regulations do not affect only new businesses: they should raise the cost of running existing businesses as well. This means that if they are making new businesses less likely to form, they should also make existing businesses more likely to fail. That is not what we see in the data. Over time, as the level of regulations has risen, the failure rate of existing businesses has gone down. One can always, of course, concoct an explanation for why regulation should be more problematic for new firms than for existing ones—for instance, that there are learning curves in regulatory compliance—but these explanations don’t hold up. Most businesses have not been in operation very long, nor have many mastered the rules of regulatory compliance in any very sophisticated way. Thus, the learning curve advantages in regulatory compliance are relatively small, making it difficult to see how regulation disproportionately hurts new businesses. Other Patterns We Should Observe

Professors Nathan Goldschlag and Alexander Tabarrok of George Mason University have long wondered if a rise in regulation has led to a decline in entrepreneurial activity in this country. As economists in a school known for its belief in minimal government regulation, they were likely predisposed to believe that increasing government regulation has contributed to the decline in entrepreneurial activity. But they are also careful scholars who let the data show them the truth, and they designed a clever test of whether small business is disproportionately affected by the rise in regulation. They argued that if there are economies of scale in regulatory compliance, then small

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business founders should respond to a rise in regulation by starting bigger companies. This would let them take advantage of economies of scale in regulatory compliance, a benefit that increases in value as the amount of regulation goes up. Goldschlag and Tabarrok used number of employees as a proxy for company size. Since new companies have no more employees on average than they had thirty years ago, the two economists concluded that there was little evidence that business owners saw the rise in regulation as a sufficient motivation to structure businesses in a way that would minimize regulation’s impact. Absent evidence that business owners were trying to offset the cost of a rising regulatory burden, Goldschlag and Tabarrok concluded that that cost did not affect them much.19 The Timing Is Wrong

Yet another problem with the argument that regulation is deterring startups is that the timing is wrong. During the time that new employer firm formation declined significantly, small business owners claimed that regulation has become less of a problem. The National Federation of Independent Business, the oldest small business trade association, has regularly surveyed its owner members since 1974. These surveys always ask respondents to name the biggest problem they face as business owners. Between 1995 and 2009 —a period of declining new employer firm formation—the fraction of small business owners saying government regulation was their biggest problem declined by two-thirds.20 That pattern makes it difficult to believe that rising regulation is actually a cause of the fall in employer firm formation. If overregulation is the reason fewer people are starting employer businesses, there should be more, not fewer, owners identifying it as a problem. Another problem with timing is the misfit between the periods when new employer firm formation rates decline and when regulation 116

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increased. Marie-Josée Kravis of the Hudson Institute attributes the decline of business formation to the “regulatory fervor of the past decade,” highlighting the Dodd-Frank legislation and Affordable Care Act as regulatory excesses that have made entrepreneurship more difficult.21 But it is hard to find a statistical link between the implementation of these laws and the decline in employer firm formation rates. The laws were not enacted until 2010, well past the point when employer firm formation began to decline. By 2010 the rate of employer firm formation had already declined by 53 percent from its 1978 peak. From 2010 until 2013, the most recent year for which data are available, the rate has actually recovered somewhat, rising a modest 3 percent. It’s not during the era of Dodd-Frank and the Affordable Care Act that employer firm formation fell down dramatically but before those laws were enacted. The Correlation Is Probably Spurious

Nathan Goldschlag and Alexander Tabarrok, who have conducted the most careful investigation of the effect of regulation on new employer firm formation, do not believe the rise in regulation has caused a decline in new employer firm formation. They think the correlation between the number of pages in the Federal Register and this measure of entrepreneurship is spurious. Rather than casually compare the two numbers, they ran complicated regression analyses to look at the correlation between these two measures over the 1999 to 2011 period for all six-digit industry codes, controlling for a variety of factors, including industry and year. They found “no obvious relationship between regulation and startups.”22 Nor did they identify any relationship between the rate of entrepreneurship and the change in regulatory stringency, different measures of specific or general regulation, or regulation by the most active federal agencies. 117

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Goldschlag and Tabarrok tried a variety of statistical permutations and still found nothing: no relationship between levels of regulation and rates of entrepreneurship. They even looked at specific industries to see if there was an effect for just a few sectors in the economy. Again, nothing. As the two economists described it, “Despite experiencing dramatic increases in regulation, the increasingly regulated industries did not see increasingly lower startup rates.”23 Basically, the relationship present in a simple correlation doesn’t hold up to more rigorous techniques. That means there are no data to suggest that increased regulation has caused a decline in new employer firm formation. The two scholars looked at other ways in which regulation could adversely affect new employer firms. If they found evidence of some other way that regulation held back the growth or survival of new employers, then we would have some suggestion that regulation negatively affected entrepreneurship, even if it didn’t cut back on the number of people starting new businesses with paid workers. One possibility is that regulation could be keeping small firms from becoming big businesses. A heavy regulatory burden could be so distracting to the founder of a small company or so costly to manage that the business cannot grow. If this were true, then we would expect to see a correlation between the level of regulation and the change in the employment of startups. But that trend is not there. The Fed’s Ryan Decker and his colleagues (described in earlier chapters) report that they have seen no evidence of regulations adversely affecting the growth of businesses.24 Goldschlag and Tabarrok argue that if regulation were really hindering new employer firm formation, we should also see different patterns of startup activity across different states, countries, and industries. Countries impose different levels of regulation on their

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businesses—Sweden, for instance, regulates its companies more heavily than Chile does—and different states have different levels of rules as well. That is one way some states claim to be more “businessfriendly” than others. Finally, some industries are regulated much more heavily than others. Manufacturers, for instance, face more rules than lawn care services. This difference in regulation across states, countries, and industries allows observers to identify the effect of government rules on levels of entrepreneurship. The primary finding is that there isn’t one. Researchers have found that over the past three-plus decades, the rate of employer firm formation has declined by similar amounts across states and countries with high and low levels of regulation. If business regulations were really affecting startup activity, then we should see differences in the rate of decline that correlate with differences in regulation. Decker and his coauthors have found that the decline in employer business formation is roughly the same in states with business philosophies as different as Texas and California. It is too constant throughout the country for regulation to be playing much of a role.25 Goldschlag and Tabarrok look across industries, rather than across states, and find similar patterns to what Decker and his colleagues observed. Although the level of regulation has varied a lot across industries in the past thirty-plus years, Goldschlag and Tabarrok have found that the degree to which new employer firm formation has fallen has been relatively constant.26 Similar declines in rates of entrepreneurship across highly regulated and lightly governed industries belie the argument that rising regulation is responsible for decreasing rates of employer firm formation.

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Not All Regulation Reduces Entrepreneurial Activity

A final challenge to the overregulation argument is that regulation does not always depress entrepreneurship. Some types of regulation are business-friendly. The best example of that lies in the rules about health insurance. Economists and policy makers disagree about the value of the Affordable Care Act and the changes it brought in how Americans get health insurance. Some observers have come out in favor of the law and others have voiced strong objections. Those who are careful analysts, however, have acknowledged that, at least in theory, the new law could be entrepreneurship-friendly. The argument goes something like this. When people have health insurance that is provided by their employer, starting your own company often means giving up that insurance. A lot of people, particularly those with non-working spouses or spouses who work in companies that do not provide employee health insurance, are reluctant to give up their jobs for fear of losing health care coverage. This concept, called “job lock” by analysts, tells us that without the Affordable Care Act, some would-be entrepreneurs are deterred from starting businesses. New regulations like the Affordable Care Act should therefore make Americans more likely go into business among themselves. The implementation of the Affordable Care Act is far too recent for us to have strong evidence one way or another about its impact on new business creation, but we have some data from state-level efforts to change health insurance laws. In the mid-1990s, some states changed their non-group health insurance markets to impose additional regulations that made it harder for insurance companies to charge different premiums to different people based on the person’s health, or to keep people from getting insurance because of preexisting

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conditions. On balance, these regulations made it easier for people starting companies to get health insurance. Did they increase startup rates in the states that implemented them? Careful research by economists Bradley Heim of Indiana University and Ithai Lurie of the U.S. Treasury shows that they did. While we might quibble about how these authors measured entrepreneurial activity, they found a pattern consistent with the argument that more regulation led to more entrepreneurship. Places that implemented heavier state regulation showed a 16 percent rise in the probability that a resident would have some self-employment income.27 Key Patterns in the Data

1. Because regulation raises the cost and complexity of starting a business, it should reduce the rate at which people start new employers. 2. Between 1977 and 2013, the per capita rate of creation of new employer businesses showed a −0.67 correlation with the number of rules pages in the Federal Register. 3. Over the same time period, the level of regulation correlates positively with the per capita number of non-employer businesses and IRS measures of the rate of entrepreneurship. 4. Owning a business is becoming more profitable over time, a pattern not expected if increasing regulation has a negative effect on entrepreneurship. 5. Major increases in regulation should be followed by declines in employer firm formation, and small business owners should report that regulation is becoming more onerous when rates of employer-firm formation decline, but we do not see these patterns in the data.

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6. The negative correlation between new employer business formation and the number of rules pages in the Federal Register, if it is real, should be present after sophisticated methods are used to test it, but it is not. 7. More regulation sometimes increases new business formation. Despite the rhetoric that it is killing entrepreneurship in America, there is little evidence that regulation has caused a decline in employer firm formation. Regulation increases the cost and complexity of business formation, yet entrepreneurship has become more profitable over time. The negative correlation between the number of federal regulations and the rate of new employer firm formation does not hold up under complex methods of statistical analysis. Periods of major regulatory increases have not been followed by declines in employer firm formation, nor do small business owners report that regulation is becoming onerous at times when new employer firm formation have declined. The rise in regulation correlates positively with an increase in some measures of entrepreneurship. Finally, evidence suggests that some new regulations—particularly rules that make it easier for people to obtain health insurance—are associated with growth in new business creation. In short, like lack of access to capital, a rise in regulation does not appear to be the “explanation” for the changes in American entrepreneurship in recent decades.

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EIGHT High Taxes Are Not the Cause

Some observers on the right think they know what is hindering entrepreneurship in America: high taxes. Right-leaning pundits are convinced that “ever higher” taxes on new and small businesses have made it impossible for entrepreneurs to make the money they once did. The reduced expectations of earnings, they say, has reduced the incentive of would-be entrepreneurs to pursue their dreams by striking out on their own. People who are considering starting a company, the story goes, see the high tax burden they will face and decide not to do it. This is the view of Tim Kane, who writes, “At the federal level, high taxes and higher uncertainty about taxes are undoubtedly inhibiting entrepreneurship.”1 American entrepreneurship is in decline because greedy and foolish policy makers have ignored a simple axiom of basic microeconomics: the more you tax something, the less of it you will have. The good news, these observers point out, is that the problem is easily solved: just cut taxes on entrepreneurs and would-be entrepreneurs. Once policy makers lower marginal income tax rates, create tax exemptions for entrepreneurs, and offer tax credits to business founders, entrepreneurial activity will take off. Advocates of this position have even been so helpful as to tell Congress exactly how to accomplish that goal. John Dearie of the Financial Services Forum told Congress, “The Internal Revenue 123

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Service should be directed to establish a new entrepreneur— or ‘e-corp’—tax status, whereby newly launched businesses would be subject to a five percent flat income tax for the critical first five years after formation. Such favorable and predictable tax treatment will help cultivate new business formation, survival, and growth by allowing new businesses to retain and reinvest most of what they earn, preserving critical cash flow, and eliminating the distraction and burden of tax complexity and uncertainty.”2 Sounds simple, straightforward, and clear. The one tiny problem is that it won’t work. Despite widespread belief in Mr. Kane’s and Mr. Dearie’s arguments, there is no evidence that federal tax policy has contributed to the decline in employer business formation over the past three decades or that exempting new businesses from taxation will do anything to alter that decline. Without a causal link between federal income tax policy and rates of entrepreneurship, these tax plans offer little benefit for entrepreneurship and could do a lot of potential harm. Taxes Don’t Reduce People’s Willingness to Start Businesses

Many policy makers and pundits have a strange view of how people decide to start a business. Would-be entrepreneurs, they think, calculate the effect of taxes when considering starting a company and refrain from going ahead if they figure their taxes will be too high. I’ve never met an entrepreneur who undertakes that calculation, and it’s not just me. Surveys of prospective entrepreneurs reveal that virtually none of them factor taxes into their decision making. Much more common is the desire for independence or autonomy, the need for a flexible schedule, the goal of introducing a new product or service to the world, or the wish to make money. It is hard to imagine

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such people deciding, at the margin, not to start businesses because their taxes would be too high. The policy makers, reporters, and academics who claim that taxes affect people’s willingness to start companies falsely infer their influence on the startup decision from the general negative view of taxes. Most people don’t like them and would prefer not to pay them. But that doesn’t mean they won’t start companies because they dislike having to pay taxes on their profits, any more than people refuse to get married because they don’t want to be nagged by their spouses. Nobody likes being nagged, but spousal nagging is almost never a deterrent to marriage. The anti-tax pundits also falsely draw inference from observations that taxes have negative effects on economic activity. They claim that tax rates must be bad for entrepreneurship because they are bad for business in general. Anthony Kim of the Heritage Foundation, for example, writes, “High tax rates and a tax code that is burdensome for both individuals and businesses clog America’s economic arteries, hindering vibrant economic growth.”3 But just because higher taxes reduce people’s incentive to work hard, this doesn’t mean they will reduce people’s motivation to start businesses. People might shift from working for others to starting businesses when taxes rise. Moreover, after-tax pay might be more of an incentive for wage work than it is for running a business. Taxes might influence my decisions about how hard to work for someone else, but not about whether to start my own business. Taxes Both Encourage and Discourage Startups

When taxes are high, entrepreneurship may be more desirable, not less, because it offers tax-avoidance opportunities that wage employment does not. When you are in business for yourself, the IRS

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knows a lot less about your income than it does when you are on a salary. Virtually everyone’s wage employment gets reported to the tax authorities on W-2 forms, but companies’ revenues and costs are not similarly reported. If you want to cheat on your taxes, you are better off running your own business. When you are running your own company, you can charge many personal expenses, like the cost of your car or part of your home, to your business. It is hard for the IRS to catch people cheating a little bit at the margin. And that is just what happens. The IRS reports that roughly onethird of the tax gap—the difference between what the IRS was owed and what it was paid—is business income that earners neglect to report on their individual tax returns. No other source of the tax gap is as large. According to Susan Nelson, writing in the National Tax Journal, 60 percent of sole proprietors underreport their income.4 When the government raises tax rates, it also increases the value of being able to cheat a little. People may be inclined to shift into entrepreneurship to keep their tax payments down when rates go up. For many businesses, this is easier than you think. A house painter could be self-employed or work for someone else. The same is true for a hairdresser or a lawn care guy. If that shifting tends to happen when tax rates rise, then we should see more, not fewer, new businesses as a result. People’s willingness to cheat on their taxes rises as rates go up. Few people think it is worth the risk of cheating if they will get only a few dollars. No one wants to risk going to prison to save the price of a venti latte at Starbucks. But they might do it for enough money to buy a new car. Legal ways to avoid taxes become more attractive as well. As marginal tax rates rise, people become more likely to start businesses because they want to avoid taxes.

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But the higher the tax rate, the less income people can take from running a business, and the less incentive they presumably have to start one. This, of course, is the argument that Tim Kane, John Dearie, and Andrew Kim are making. It is a flawed argument: the incentive does not lie solely in the income from the new business but in the difference between what a prospective entrepreneur has been making and what she could make once she is in business for herself. If taxes rise on both profits and wages, that increase might not affect the incentive in either direction. In essence, that is what researchers have found. Some studies show a small negative relationship5 between higher tax rates and the tendency to start a business, whereas others show a small positive effect.6 Taken all together, the most plausible conclusion one can draw from the studies is that tax rates have little effect. Unfortunately, people seeking to make a political point have oversold the findings in both directions. Studies by Donald Bruce and Tami Gurley7 and by Bruce and John Deskins8 have found that an increase in the marginal self-employed income tax slightly reduces the odds of entry into entrepreneurship. Many people have jumped on these findings to say that increases in tax rates caused the past three decades’ decline in employer firm formation. There are several problems with such conclusions. First, the statistical approach that Bruce and his coauthors used does not allow them to assume causality, and they are pretty careful not to do so. They know that tax rate changes are often responses to changes in economic conditions, creating a problem that economists call “endogeneity bias.” This means that the relationship between the tax rate and the tendency of people to start businesses may not reflect the impact of the tax rate but some other factor, such as general economic conditions, that influences both taxes and entrepreneurial

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activity. Briefly, when the economy is doing well, taxes often go up, but fewer people go to work for themselves because they can get other jobs. The result is a negative correlation between the tax rate and self-employment, but it is spurious to say that the tax change caused the change in self-employment. Both the tax rate and the rate of self-employment correlate with the condition of the economy. Many observers, particularly those interested in influencing policy makers, are not as careful with information as the researchers themselves. They often gloss over nuances like causality and simply say that research has proven that higher tax rates depress entrepreneurial activity. Second, a lot of other studies show the opposite from what Bruce found: they show a positive effect of tax rates on firm formation or no effect at all.9 For example, James Long found that a 10 percent increase in income taxes boosted entry into self-employment by 7.4 percent.10 Julie Berry Cullen and Roger Gordon found that reducing the marginal personal income tax rate by just 5 percent would reduce the amount of entrepreneurial activity in the United States by nearly one-third.11 Bruce and his colleagues too have found evidence that increasing the marginal personal income tax rate will increase the number of people running their own proprietorships.12 Again, although the researchers are pretty careful, the advocates are not. They often focus on the studies that support their policy preference and ignore those that don’t. But the evidence insists that the results are conflicting. Third, even when researchers find that increasing taxes depresses the tendency to start businesses, the size of the effect is too small for the explanation to hold water. Most of these studies have found such small effects that most researchers would call them trivial. Policy

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makers would need to virtually eliminate taxes to get just a small improvement in firm formation. Fourth, there is a mismatch between the data and many observers’ arguments. As we saw in chapter 1, the rates of employer firm formation have fallen in recent years. But most studies of the effect of taxes on entrepreneurial activity do not look at rates of employer firm formation. They look at Schedule C tax filings or non-employer business formation. You can probably anticipate the problem. Those forms of entrepreneurship—non-employer businesses—have recently been on the rise. How can tax rates be responsible for the decline in entrepreneurial activity when the measures of entrepreneurial activity the researchers are looking at have gone up? That makes no sense at all. Some researchers find negative effects for some people and positive effects for others. For example, Mina Bilamoune-Lutz and Pierre Garello, looking at the effect of tax rates on the rate at which people start businesses in fifteen European countries, found that higher rates of taxation discourage new firm formation among those earning a lot of money but encourage it among those earning a little.13 If taxes truly are a disincentive that keeps would-be entrepreneurs from starting companies, they should discourage entrepreneurship among people at all income levels, not just those earning a lot of money. Then There Are Three Other Problems

Those who are trying to blame the decline in employer firm formation on increased taxes may be bothered that the data will not cooperate. But the story gets worse. The statistics offer three other obstacles to their argument. First, tax rates and the rate of employer firm formation have both trended downward over time. That’s not

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the right pattern if you think tax rates have a negative effect on employer firm formation. If anything, it suggests the opposite—that higher taxes encourage entrepreneurs to start new businesses. As the tax rates have gone down, rates of new employer firm formation have declined along with them. Second, different measures of entrepreneurship move in opposite directions. That makes it difficult to argue that higher marginal income tax rates are having any particular effect. Whichever direction the taxes rates move, some measure of entrepreneurship— employer firm formation, the per capita number of non-employer businesses, the per capita number of businesses measured by IRS statistics, or something else—is likely to go in the “wrong” direction. Third, the geographic variation in the rate of new employer firm formation is not consistent with state variation in tax rates. If higher taxes lower the rate of employer firm formation, then we should expect to see higher-tax states experiencing greater declines in employer firm formation than lower-tax states. But as Federal Reserve economist Ryan Decker and his colleagues have found, that’s not the case. States with higher tax rates and those with tax rates that have increased more have not experienced greater declines in employer firm formation rates than other states. In recent decades, employer firm formation rates have fallen faster in the South and West, which tend to have lower tax rates than in the Midwest and Northeast. Moreover, California and Texas, two states with very different approaches to tax policy, show large and similar declines in entrepreneurial activity.14 If a high-tax state and a low-tax state have similar patterns of decline, something other than taxes is probably behind the trend.

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Key Patterns in the Data

1. People rarely focus on tax rates when deciding whether to start a new business. 2. High tax rates both encourage and discourage business formation, yielding no net effect. 3. The marginal income tax rate and the rate of employer firm formation have both trended downward over the past three decades. 4. Tax rates cannot correlate with all measures of entrepreneurship simultaneously because these measures move in different directions. 5. High-tax U.S. states have not seen greater declines in employer firm formation than low-tax states. There is little evidence that the decline in employer firm formation rates over the past three and a half decades is due to increased marginal income tax rates. Tax rates are almost never the deciding factor in a would-be entrepreneur’s decision to start a business, and they are not often even a consideration. Low tax rates both encourage and discourage business formation, yielding no net effect of tax rates on entrepreneurial activity. There is no correlation between rising tax rates and declining rates of employer firm formation in the United States over the past thirty-plus years. In fact, the marginal income tax rate and the rate of employer firm formation have both trended downward. High-tax U.S. states have not seen greater declines in new employer firm formation than low-tax states in recent decades. Employer firm formation correlates negatively with many other measures of entrepreneurship, such as the fraction of Americans indicating business income on their federal income taxes

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or taking the self-employment tax deduction, a pattern that makes it hard to assign any positive or negative effect from tax rates. The often-heard argument that higher tax rates depress entrepreneurship appears to be independent of the data. Many on the right simply believe this claim is true, whatever the evidence says. Economist Ian Hathaway, who was one of the first to document the decline in the rate of new employer firm formation, summarized the situation aptly in an online interview: “I don’t think taxes are actually a factor in this.”15

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NINE It’s Not a Lack of Immigration

Another explanation for the decline in employer firm formation is a lack of immigration. Several people associated with the Ewing Marion Kauffman Foundation, a research and advocacy organization in Kansas City, have argued that the solution to the post-1970s decline in employer business startups is to increase immigration. Before we start printing visas, however, we should probably try to confirm that lack of immigration is actually causing— or at least contributing to—the decline. A closer look does not provide much support for this idea. There is no evidence that too little immigration is responsible for the decline in employer firm formation and the rise in non-employer business generation. There is scant support for the idea that immigrants are more entrepreneurial than the native born or that making it easier for them to get into this country will boost entrepreneurship rates. There might be many good reasons for stapling green cards to STEM degrees or otherwise boosting immigration. I do not take a position on that issue in this book. But there is no reason to believe that trends in entrepreneurship rates in America over the past several decades have been driven by levels of immigration or that more immigration will generate more entrepreneurship.

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The Basic Argument

Before I get into the reasons why the immigration argument is flawed, I should outline what it is. This school of thought points to three reasons why we need more immigration if we want to reverse the downward trend in employer business creation. First, immigrants are more likely than the native born to start businesses. Dane Stangler, the vice president of research at the Kauffman Foundation, says that immigrants have rates of entrepreneurship that are up to twice as high as the general population’s because they are less risk averse.1 Robert Litan and his coauthor Ian Hathaway, both at the Brookings Institution, say, “We know that immigrants have a great propensity to launch new businesses—high-tech businesses in particular. . . . So we know [immigration is] something that will push the entrepreneurship rate up higher.”2 Second, by making it difficult for immigrants to enter and stay in the United States, the government has reduced the pool of people who will start businesses. This country’s antipathy toward immigration, goes the argument, has caused would-be immigrant entrepreneurs to choose other countries instead. A good example is Chile. Since 2010, Chile has given foreign entrepreneurs a $40,000 stipend, free office space, and other support if they agree to visit the country for half a year and network with locals.3 The lack of programs like Start-Up Chile puts us at a competitive disadvantage in attracting immigrant entrepreneurs and lowers our level of entrepreneurial activity.4 Third, more immigration is necessary to increase business startups because America cannot produce enough talent to meet employers’ needs. Startups can’t find the local talent that they need or afford to provide training to employees who lack the necessary skills, explains John R. Dearie of the Financial Services Forum. Moreover,

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“the scarcity of skilled talent has driven up the price with regard to salaries and benefits, [and] many cash-challenged startups simply can’t compete.”5

The Proposed Solutions

To those observers who believe these arguments, the solution to the problem of declining employer firm formation is easy. Policy makers need to adopt policies that boost immigration. Specific recommendations are not hard to find. The Kauffman Foundation’s Jonathan Ortmans suggests “the creation of a visa for immigrant entrepreneurs that allows foreign job-creators to start and operate businesses in America.”6 Robert Litan suggests “stapling a green card to a STEM degree,” updating the H-1B visa system, and making it “easier for immigrant entrepreneurs to secure long-term visas and permanent-resident status.”7 These suggestions are just the tip of the iceberg. This school of thought has many more, all with a common theme: boost immigration, and entrepreneurship in America will recover.

Should We Do It?

Are those who argue this point of view right? I don’t think so. As we have seen, there is little evidence that entrepreneurship overall is in decline. There is also little evidence that a lack of immigration has caused the decline in employer firm formation or that efforts to boost immigration will bring back the rates of employer firm formation seen in the late 1970s. The people who advocate encouraging immigration to boost entrepreneurship have not paid much attention on the data. Here are a few of the ways the data disagree with their assertions.

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Several Measures of Entrepreneurship Are Actually Rising

The first problem with the insufficient immigration argument is the one that plagues many of the arguments debunked in this book. Not all measures of entrepreneurship have been trending downward over the past several decades. As we saw, many indicators, including the per capita number of non-employer businesses, the fraction of taxpayers filing self-employment taxes, the number of business tax returns per capita and many others, have been going up. What’s gone down is a very specific measure, the rate of employer firm formation. The fact that the different measures of entrepreneurship have moved in opposite directions makes it difficult to pin what has happened on insufficient immigration. For a lack of immigration to have had these various effects on entrepreneurship over the past thirty years, immigrants would have to have very different attitudes toward the creation of employer and non-employer businesses than the native born. It is tough to see what those attitudes could be. No data suggest that immigrants are more willing than the native born to start non-employer businesses and less willing to start employers (or vice versa). Thus, there is no good explanation for why the increase in immigration in recent decades would have boosted non-employers and shrunk employers. Nor are there any data to suggest that an increase in immigrants now would boost the rate of employer firm formation. There Is No Positive Correlation between the Employer Firm Formation Rate and Immigration

Even if we restrict our examination to the rate of employer firm formation, it is hard to find evidence that more immigration will help. For that argument to have any validity at all, we would need to see a positive correlation between the new employer firm formation 136

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rate and the rate of immigration. But that is not the case. If anything, the data suggest the opposite. Scholars have documented the extensive immigration to this country that happened between 1970 and 2010. As Audrey Singer explained in 2013, “Immigration began to pick up again in earnest, increasing steadily over the four decades between 1970 and 2010. The greatest increase came in the 1990s, when more than 11.3 million immigrants arrived, a growth of 57 percent. Immigration in the 2000s slowed a bit after the recession; still, nearly 9 million immigrants arrived, boosting the U.S. foreign-born population to nearly 13 percent, the highest share since 1920.”8 While immigration into the United States was rising during this period, the rate of new employer firm formation was falling. That means more immigration is associated with less employer business creation over time, not the other way around. As we saw earlier, in 1980 the number of new employer businesses per thousand Americans was 1.98. By 2010 it had fallen to 1.26. Meanwhile, the share of the population that was not born in the United States has been trending upward. In 1980, 6.2 percent of the U.S. population was foreign born. By 2010 that share had more than doubled, to 12.9 percent (figure 9.1). Immigrants Are Not More Likely to Start Businesses Than the Native Born

Much of the argument for looser immigration policies is that those policies will boost the stock of people in this country who want to start businesses, because immigrants are supposedly more likely to start businesses than native-born Americans. Some observers claim that immigrants are twice as likely to start companies.9 If you find that claim outrageous, you are not crazy. It is not supported by carefully collected government statistics on the relative 137

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Figure 9.1. Immigration and Employer Firm Formation Source: Created from data from the U.S. Census and the U.S. Immigration and Naturalization Service.

entrepreneurial activity of the native and foreign born. Steven Camarota of the Center for Immigration Studies, a non-partisan Washington think tank, looked at the Census Bureau data on the question. In a 2012 report, he wrote, “Immigrants and natives have very similar rates of entrepreneurship—11.7 percent of natives and 11.5 percent of immigrants are self-employed.”10 Contrary to what some observers are claiming, the native born have slightly higher rates of entrepreneurship. Some studies do show evidence of a higher rate of entrepreneurship among immigrants, but the differences are very slight. For instance, research conducted by Professor Rob Fairlie of the University of California at Santa Cruz on the data from the U.S. Census’s Current Population Survey shows that “10.5 percent of the immigrant work force owns a business, compared with 9.3 percent of the nonimmigrant work force.”11 Fairlie’s careful analysis of government data

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shows a difference that is far from the factor of two claimed by the Kauffman Foundation’s Ortmans. Fairlie’s report, which was prepared for the Small Business Administration, makes another important observation as well. The higher rate of entrepreneurship among immigrants in one study might be perfectly compatible with research that shows no difference between immigrants and native-born people. There are two reasons for this. First, some studies use self-employment to measure entrepreneurship, and others use business ownership. Since some selfemployed people are not business owners, the two measures needn’t show the same patterns for immigrants and non-immigrants. Second, some studies look at the number of entrepreneurs or rate of entrepreneurship at a particular moment, whereas others look at the transition into entrepreneurship over time. Comparing stocks and flows is tricky (see chapter 2). Immigrants might have a higher rate of entry into entrepreneurship but the same rate of business ownership because they also exit from entrepreneurship at a higher rate. In fact, this is exactly what the SBA study finds. Fairlie explains that “immigrants move into and out of business ownership at a much higher rate than non-immigrants.”12 This difference has an important policy implication. If immigrants do not stay in business for as long as the native born do, then the benefit of their slightly higher rate of entry into entrepreneurship is lost. Efforts to attract a group of people who churn into and out of entrepreneurship will do little to change the stock of entrepreneurs in the economy. What about the idea that immigrants are more likely to start non-employer businesses and less likely to start employer businesses? In his exhaustive study of immigration into the United States, Steven Camarota looked at businesses led by the self-employed. He found

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that “self-employed natives are somewhat more likely to have larger businesses than self-employed immigrants”13 and that “the average self-employment income (revenue minus expenses) of immigrants is slightly higher than that of natives.”14 Both of these observations are consistent with recent decades’ trends in entrepreneurship. We have seen earnings from entrepreneurship and the rate of creation of non-employers rise, and the rate of creation of employers decline. How do we fit immigration into this picture? Perhaps as immigration has risen, there has been a shift in the pool of company founders toward those born outside the country. Because immigrants are more likely to start non-employers and less likely to start employer businesses than the native born, the growth in immigrants might have contributed to the trends we have seen. Yet it is unlikely that immigration has had much effect on these trends. Immigrants comprise a relatively small portion of the population, and they have only a slightly higher tendency to start nonemployers than the native born. It is very unlikely that the rise in immigration could account for much more than a tiny portion of the rise in non-employers and the decline in employer businesses. Even if we allow that immigration contributed some small amount to these trends, it doesn’t follow that boosting immigration is a “solution” to the problem of declining employer business formation. If you believe that this decline and the rise in non-employer businesses are bad for the economy, you should advocate policies with some chance of reversing the trends. Since immigrants are more likely to start non-employers and less likely to start employers than the native born, policies to boost immigration will move us in the wrong direction. They will exacerbate the negative movement we have seen over the past several decades.

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Other Countries Are Not Getting the Immigrants

Those advocating immigration as a solution to the problem of employer business formation face another data challenge. Other countries’ programs to encourage immigrant entrepreneurship are far too small to affect levels of entrepreneurship in the United States. Even if these programs did draw immigrant entrepreneurs, the effect is too slight to influence U.S. entrepreneurship statistics. Consider the numbers for Start-Up Chile, the example often mentioned in white papers and congressional testimony. In its first four years of operation, the program admitted 810 entrepreneurs from all countries; of these, only 132 chose to stay in Chile. We have no way of knowing how many of those companies would have been founded in the United States had we had a comparable program. But even if we assume that a similar program conducted here would have captured all of these companies, it is a miniscule addition to the number of new employer businesses being founded every year. Bringing in an additional 33 new employers in 2013, for instance, would have increased that year’s number of new U.S. companies with paid workers by eight one-thousandths of 1 percent.15 The Proposed Programs Are Costly

Government programs aren’t free. Yet those advocating new government policies always seem to ignore these programs’ costs. Advocates of the startup visa program recommend that we create a special visa for foreign-born entrepreneurs who would like to start companies in the United States. Under the plan, the country would admit entrepreneurs for two years provided they meet national security requirements and raise a minimum amount of initial funding. If a new business then produced a minimum level of verified revenue and jobs for people outside the entrepreneur’s family, the government would extend the visa for several more years. 141

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Like any other government program, this one would require a bureaucracy to administer it. Government bureaucracies cost money. We would need to ensure that the companies seeking entry had real revenues; otherwise dishonest people could simply create sham companies as a way to immigrate. We would have to verify that those applying for the program are not security threats. Even if increased immigration were to bring a boost in entrepreneurship, it would not be worth a rise in violence from immigrants. It would not be cheap to ensure that the prospective entrepreneurs were not a security risk.

Easier Immigration Won’t Solve the Skilled Talent Shortage

The argument that more liberal immigration policies would encourage the formation of employer businesses by making more trained workers available for startups is also flawed. To start with, it is inconsistent with the data. Immigration has been rising for more than three decades. If a lack of talent prevents American entrepreneurs from starting employer businesses and immigration mitigates that constraint, then the rate of formation of new employers should have risen, not fallen, over that period. Rising immigration should have made it easier for businesses to find the workers they need, and would-be entrepreneurs, seeing the talent constraint loosening, should have become more likely to start their businesses. But the rise in immigration has coincided with a decline in employer firm formation. Clearly, the story about immigration solving the talent shortage and encouraging employer firm formation can’t be right. The argument that immigration will ease employers’ access to trained labor suffers from another problem as well. The skilled talent

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shortage affects all businesses, not just startups. It is difficult to see how more immigration would provide a relative benefit to new companies. More immigration or less immigration, startups still compete with existing businesses for access to workers. Better skilled workers would reduce businesses’ need to train those workers, but it would not change the relative advantages that large, existing businesses have in attracting talent. While smaller and new businesses often offer workers advantages over big businesses—flexibility, autonomy, and a chance to take on more responsibility at a younger age—the average American worker prefers to work at older and larger companies because those businesses pay higher wages and offer more benefits.16 Even if changes to immigration policies brought more trained workers to this country, potential startups would become no more likely to attract those workers away from older and larger businesses than they are now. The boost in immigration would do little to slow the decline in employer firm formation. Key Patterns in the Data

1. The rate of immigration has increased dramatically over the past three-plus decades, a pattern inconsistent with the argument that more immigration would boost the rate of employer business formation. 2. Rising immigration has coincided with a decline in new employer firm formation over the past thirty years. 3. Explanations for why immigration is good for entrepreneurship are difficult to reconcile with the increase in nonemployer businesses in recent decades. 4. Immigrants are no more likely than the native born to start businesses.

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5. The cost of policies to encourage more immigrant entrepreneurs would be high and could very well exceed the benefit in employer business formation. There is little evidence that a shortage of immigration has caused the decline in employer firm formation. Federal government policies have not reduced immigration in recent decades, and immigrants are no more likely to start businesses than native-born citizens. The notion that restrictive immigration policies have kept would-be entrepreneurs from starting businesses by reducing the supply of talented employees does not stand up to scrutiny. Immigration rates correlate negatively with the rate of employer firm formation and positively with the rate of creation of non-employers. That pattern suggests that encouraging more immigration would not stem the decline in employer firm formation but would exacerbate it—and also exacerbate the past two decades’ shift toward non-employers. In short, the evidence simply fails to support the notion that lack of immigration is the “cause” of the decline in employer firm formation and that policies to encourage more immigration are the “solution.”

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TEN An Aging Population Isn’t the Reason

Lots of things go wrong when a nation’s population gets older, and not just for the people doing the aging. An older population places greater stress on a country’s social insurance and health care systems. It can cause a shortage of workers and push up wages. And it can lead to a decline in capital investment, which can result in diminished economic growth. Some observers say that an aging population also reduces a nation’s innovation and entrepreneurship. Some academics, journalists, and policy makers have recently put forward a hypothesis for the decline in employer firm formation in the United States: more old people. The nation’s demographics have begun to work against entrepreneurship. Compared to three decades ago, fewer people are of the age when most people start companies. The shifting age distribution, they argue, results in lower startup rates. It is an intriguing hypothesis, and there is some evidence for it. A few observers have noted that the fraction of the U.S. population between the ages of thirty-five and forty-four and the rate of new employer firm formation correlate positively in some time periods. If these commentators are right, policy makers should try to counteract the aging of the population. How? It brings us back to the policy suggestions of the previous chapter. Boosting immigration is one of the few ways we can affect the average age of the U.S. population.

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So maybe there is a different reason to promote immigration. It’s not that immigrants are more likely to start companies than the native born, but that younger people are more likely to found businesses than older ones. Encouraging immigration would increase the pool of people at prime startup age. Organizations like the Kauffman Foundation advocate immigration reform to boost entrepreneurship in America for precisely this reason. But changing the nation’s immigration policy is a big deal. As we saw in chapter 9, there is no evidence that bringing in more immigrants would increase the rate of employer businesses formation. Before we liberalize immigration in the hope of boosting entrepreneurship by increasing the number of young Americans, we should at least look for evidence of a causal link between the aging of the population and declining rates of entrepreneurship. Unfortunately, several observers have found evidence that undercuts this hypothesis. They point out that the changes in rates of entrepreneurship started too early for aging of the population to be the true cause. The decline in the rate of employer firm formation predates the decrease in the fraction of the population between thirty-five and forty-four—the prime age for starting a company—by nearly two decades. In addition, many measures of entrepreneurship have increased since 2000, a period when the fraction of the population between thirty-five and forty-four began to slide. Since there is no good reason why aging of the population would increase some measures of entrepreneurship and decrease others, the negative association with employer firm formation in some time periods looks like an accidental correlation. Once again, we need to consider whether this explanation for the decline in new employer firm formation justifies government intervention. If there is little evidence that the aging of the U.S. population

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is contributing to the decline in employer firm formation, efforts to lower the average age are probably unwarranted—at least for this purpose. The Argument

Let’s first examine the aging-population hypothesis. Younger people are more innovative, creative, and willing to take risks than older people, and thus they are more likely to start businesses.1 Moreover, when older people occupy a lot of jobs and remain in them for many years, younger people are less able to develop the technical skills or customer contacts they need to start businesses.2 As birth rates have fallen and life expectancies have grown, the U.S. population has become older, reducing the fraction of young people. The declining share of young people has resulted in a decline in new business formation.3 It is a logical argument. But does the evidence support it? The Evidence for the Hypothesis

Observers who believe that the aging of the population has contributed to the decline in the rate of entrepreneurship point to three pieces of evidence. First, as we know well, the rate of creation of new employer businesses has declined since the late 1990s, and the fraction of the American population between the ages of thirty-five and forty-four also has gone down. The second trend might have caused the first. Fewer people at an age when people tend to start businesses could lead to fewer companies getting started. Second, proponents of the aging-population hypothesis point to cross-country comparisons of startup rates. Perhaps the best work in this area has been conducted by Stanford economist Ed Lazear and two economists at Peking University, James Liang and Hui

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Wang, who together examined data from the Global Entrepreneurship Monitor, a data set that covers the adult age populations of eighty-two countries from 2000 to 2010. Using complex statistical techniques to control for a variety of different factors, Lazear and his colleagues found that countries with older populations tend to have less entrepreneurial activity. They write that “a one-standarddeviation decrease in the median age of a country increases the rate of new business formation by 2.5 percentage points, which is about forty percent of the mean rate.”4 A third piece of evidence comes from data on entrepreneurial activity over time in countries other than the United States. Many countries, like Japan and much of Europe, have aging populations as well as declining rates of entrepreneurship.5 Some observers view this correlation as a sign that the aging of the population is causing the decline in entrepreneurship. The Counterargument

The evidence above is weaker than it may appear at first glance. To begin with, if you look at the aging of the U.S. population and the rate of employer firm formation over a longer period—from the 1970s to today—there is little evidence of a negative correlation. While the trend is present since the 1990s, it isn’t there earlier. Over the whole period from 1977 to 2013, there is no correlation between the average age of the population and the rate of employer firm formation. One reason for the nonexistent correlation is that the two trends have occurred at different times. Fivethirtyeight business reporter Ben Casselman plotted the rate of employer firm formation against the proportion of the population of startup age in an article for the online publication. He found that the decline in the rate of employer firm formation began a couple of decades before the proportion of

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the population at prime startup age began to fall. As Casselman put it, “Whatever is driving down the startup rate, it began long before the boomers began to age out of their prime entrepreneurial years.”6 Ian Hathaway and Robert Litan, whose work we have discussed in earlier chapters, examined the statistical relationship between new employer firm formation rate and the age distribution of the American population from 1977 to 2013 using sophisticated econometric techniques. Their analysis yielded the same results as Casselman’s simple chart: they report that they saw no evidence for an effect of population aging on rates of entrepreneurship.7 A second reason to doubt the correlation between aging of the population and the rate of entrepreneurship is that for the past few decades, employer firm formation has been declining across all age groups except teens.8 This pattern holds across other countries as well. Analysis of the Global Entrepreneurship Monitor data by Lazear and his colleagues at Peking University showed that countries with an older population tend to have lower rates of entrepreneurship “at every age.”9 This pattern suggests that something other than the aging of the population is driving the decline in entrepreneurship. That something could be overall economic conditions. In countries that have had decades of slow economic growth, people may be more reluctant to have children because they think the economy may not support a good life for them. The same slow-growth countries might have fewer people starting businesses (at all ages) because the slow growth leads fewer people to think that they can make new companies successful. The result is that slow-growth countries have both older populations and less entrepreneurship. But one does not cause the other. Another data pattern inconsistent with the aging-population argument is that rates of entrepreneurship appear to have fallen

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most among young people. The Wall Street Journal looked into this question by examining data collected by our nation’s central bank. Using the Federal Reserve’s Survey of Consumer Finances, an everythree-year examination of the financial position of American households, the Journal reported that the business-owning share of households headed by a person below age thirty fell from nearly 11 percent in 1989 to less than 4 percent in 2013.10 The Kauffman Foundation noted the same pattern. It found that in 1996, 34.8 percent of new company founders were aged twenty to thirty-four; but only 22.7 percent were of that age in 2013.11 This is a key clue. Aging of the American population is unlikely to explain the decline in rates of entrepreneurship if business creation is falling fastest among the youngest members of the population. The segment of the population whose entrepreneurial activity is increasing is older citizens. The rate at which people ages forty-five to fifty-four tend to start and run their own businesses has actually gone up in recent decades.12 Taken together, these data patterns suggest that the aging of the population is not really problematic for entrepreneurship. A final problem with the age argument is the same issue we have seen with other potential explanations for trends in entrepreneurship. Unlike the employer firm formation rate, other measures of entrepreneurship have been increasing. Because the share of the population of prime entrepreneurship age (thirty-five to forty-four) peaked in 1998 and has since declined, that fraction is negatively correlated with several measures of entrepreneurship. For instance, from 1998 to 2013, the number of non-employer businesses increased 28 percent. The share of individual tax returns with the self-employment tax deduction rose 16.4 percent. The number of business tax returns per thousand people increased 19.6 percent. The share of individual tax returns with business income or loss went up 36.8 percent. The

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number of sole proprietorships increased 20.8 percent. The number of corporations per thousand people rose 5.7 percent. The number of partnerships per thousand Americans went up 61.2 percent. In short, six important measures of entrepreneurship went up while the fraction of Americans of prime entrepreneurship age was falling. Confronted with that kind of evidence, the aging-population story falls apart. If anything, the decline in the fraction of the population in the thirty-five to forty-four age group is associated with an increase in entrepreneurship. Key Patterns in the Data

1. From 1978 to 2013, there is no evidence of a correlation between the aging of the population and the rate of new employer firm formation. 2. The decline in the new employer firm formation rate began two decades before the proportion of the population between the ages of thirty-five and forty-four began to decline. 3. Over the past several decades, new firm formation has declined across all age groups except teens, with the greatest fall among young people. 4. Since 1998, the share of the population aged thirty-five to forty-five—the prime age for business creation—has declined, while all of the following measures of entrepreneurship have increased: the number of non-employer businesses; the share of individual tax returns with the self-employment tax deduction; the number of business tax returns per thousand people; the share of individual tax returns with business income or loss; the number of sole proprietorships; the

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number of corporations per thousand people; and the number of partnerships per thousand people. America is getting older, and that has some entrepreneurship advocates concerned. Risk taking, creativity, and innovation all decline as people age, leading these advocates to worry that the aging of the population has caused the decline in employer firm formation. To combat the decline, they have called for boosting immigration and other policies to reduce the average age of the American population. It is a flawed recommendation. True, there is a correlation between employer firm formation rates and the share of the population aged thirty-five to forty-four in the United States since 1998. Similar correlations exist between the aging of the population and entrepreneurship rates in Europe and Japan; and there is a negative correlation everywhere between median population age and rates of entrepreneurship. But overall, the evidence indicates that the aging of the population is not a cause of the decline in employer startups. The correlation between the aging of the population and the rate of employer firm formation does not hold up over longer periods. Employer startups began to decline two decades before the thirty-five-to-forty-four age group began falling as a proportion of the population. Moreover, rates of firm formation have declined across all age groups except teens for several decades, and they have fallen most among young people. Furthermore, even while the share of the population aged thirty-five to forty-four was declining, many measures of entrepreneurship were going up. Population aging isn’t the cause of the decline in new employer firm formation rates over the past three-plus decades. It isn’t even one of the causes. We have to keep looking.

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ELEVEN Slowing Population Growth Isn’t the Explanation

One interesting explanation for the decline in employer firm formation is a slowdown in population growth. If you are not a professional economist, the argument might not be intuitive to you. It goes like this: Because people aren’t having as many kids as they did in the 1970s and earlier, the American population is growing more slowly than a generation ago. That decline in population reduces both the supply of entrepreneurs and the demand for them. Together, these two effects make for a decline in the number of business creators, as measured by the rate of new employer firm formation. Is there anything to this argument? Although there is some suggestive evidence for a connection between slowing population growth and the decline in employer firm formation, for the most part the data do not support it. Before I explain why, I want to outline the slower-population-growth hypothesis and the evidence for it.

The Argument That Slower Labor Force Growth Is Responsible

A slow increase in the American population affects both supply and demand. On the supply side, when the population is growing

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more slowly, fewer people are being added to the labor force. That means fewer people who engage in any economic activity, including starting businesses. Some argue that slower population growth has also pushed wages up, because reducing the supply of labor puts upward pressure on its price. Higher wages reduce the expected profits from entrepreneurial activity and so reduce the rate of employer firm formation. Would-be entrepreneurs respond to the lower potential for profit by becoming less likely to start businesses.1 A declining rate of population growth also slows new employer firm formation on the demand side. When the population grows, someone needs to provide those added people with pizza, televisions, car seats, haircuts, household cleaners, and so on. Slower population growth means less growth in demand. While some of that reduced demand translates into lesser sales at existing firms, it also lowers the need for new companies.2 The Importance of the Question

This straightforward argument raises several important issues for our friends in Washington. First, the cause of the decline in new employer firm formation might be something that policy makers cannot counteract. It is simply beyond their control. If the cause is slowing population growth, for instance, policy makers might not have any tools to respond. We might just have to accept a rate of new employer firm formation far below that of the late 1970s as the new normal. Increasing immigration and getting people to have more kids are really policy makers’ only choices when it comes to boosting population growth. While our elected officials might pass laws that boost immigration, they cannot easily get people to reproduce. The desire to have kids depends greatly on cultural forces that government

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incentives cannot alter easily. And because immigrants are a small fraction of the population, massive changes in immigration policies would be necessary to offset a decline in the birth rate and drive up population growth. (Policy makers would love to boost the growth of the population for reasons having little to do with entrepreneurship. A growing population means a growing labor force. With a growing labor force, it is easier to maintain a rising GDP and the rising living standards that go with it.3 But that question is beyond the scope of this book.) Second, a population growth– entrepreneurship rate relationship raises a high hurdle for government intervention. Whatever policy makers do to alter the growth rate of the population, they should try to do with some understanding of what their efforts will and will not accomplish. My purpose here is not to address this issue comprehensively but to make a specific point: if our elected officials cannot easily offset the decline in the rate of employer firm formation, they might not want to try. Not only will any potential policy choices likely have unpredictable adverse consequences, but we might also need massive government interventions to generate even a small improvement in the new employer firm formation rate. But before we worry about all that, let’s see if slowing population growth is really behind the slowdown in new employer firm formation rates in recent decades. What the Evidence Shows

There is, without a doubt, some evidence that slowing population growth is responsible for the falling rate of employer firm formation. Fatih Karahan, Benjamin Pugsley, and Aysegul Sahin, researchers at the Federal Reserve Bank of New York, have examined the causes of the three-plus decade decline. Using complex statistical

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models to look at the correlation between the population growth rate and employer startups, they found that each 1 percent decline in the growth rate of the working age population leads to the same decline in the rate at which employer businesses are created.4 Other researchers have corroborated this finding by comparing different regions of the country. Ian Hathaway and Robert Litan of the Brookings Institution looked at population growth rates and rates of employer firm formation across parts of the country and found that historically “the firm formation rate tended to be higher in regions that experienced greater population growth.”5 The Challenge to the Argument

The population-growth argument is plausible and has some support from the data, but there are three problems with it. The first is that the rate of new employer business creation is actually dropping relative to the population. To illustrate this point I want to highlight a graph that appeared in chapter 1, showing the rate of creation of employer businesses on a per capita basis. Americans created 1.29 employer businesses for every 10,000 people in the country in 2013, down from 2.56 in 1977 (figure 11.1). If new employer firm formation has dropped by half when measured on a per capita basis, it means the entire drop cannot be accounted for by a decline in population growth. Something else is causing Americans to cut back on employer startups. We can compare the rate of employer firm formation to other key labor force measures to see if particular parts of the populationgrowth argument are consistent with the data. One hypothesis is that changes in the labor force mean that a smaller share of the population is working now than four decades ago. Maybe more Americans are retired, disabled, in school, incarcerated, or otherwise unable to

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Figure 11.1. New Employer Firms per Thousand People Source: Created from data from the U.S. Census.

join the labor force than in the 1970s. Lower labor force participation implies less entrepreneurship because it means Americans are doing less work of any kind. The data do not support this hypothesis. The changes in the labor force participation rate do not appear to be correlated with the decline in employer startups. Between 1977 and 2013, the labor force participation rate and the rate of employer firm formation are correlated at only 0.19, which is pretty low (figure 11.2). If we break down the numbers by time periods, we can see the lack of relationship in better detail. From 1982 to 2000, labor force participation grew from 57.2 percent to 64.4 percent. But during the same period, the per capita rate of employer firm formation decreased from 1.93 to 1.71.6 What if we compare the rate of employer firm formation with the total number of people employed? This is a way of looking at the population growth argument that is adjusted for labor force participation. This comparison strips out the effect of more people being

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Figure 11.2. Employer Firm Formation per Capita and Labor Force Participation Source: Created from data from the U.S. Census and the Bureau of Labor Statistics.

out of work or incarcerated to show how increasing the number of potential entrepreneurs affects the rate of creation of employer businesses. The result shows little support for the population-growth hypothesis. The rate of employer firm formation has gone down by more than half when measured against the number of people employed in the economy over the past three and a half decades. It has also declined by nearly half compared to the civilian labor force. In 1977, 2.6 new businesses with employees were started for every thousand people in the labor force. In 2013, it was 1.3 for every thousand.7 The numbers are similar when compared to the number of people actually employed. In 1977, 6 new employer firms were formed

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for every thousand people working in the United States. By 2013, the number was down to 2.81 (figure 11.3). In short, it is difficult to see evidence that the decline in the population has caused a fall in the rate of new employer firm formation. Few correlations suggest that pattern. The second problem with the population-growth argument is that it depends on the assumption that entrepreneurial ventures have become less profitable, but they have not. As I explained above, a key mechanism behind this argument is that lower population growth, combined with a smaller fraction of the population participating in the labor force, has pushed wages up. These higher wages have reduced the profitability of entrepreneurial activity, and the expectation of lower profits leads fewer would-be entrepreneurs to start employer businesses.

Figure 11.3. Employer Startups per Thousand Employed People Source: Created from data from the U.S. Census and the Bureau of Labor Statistics.

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But as we saw in chapter 5, entrepreneurial activity has become more profitable, not less, in recent decades. Average profits at American businesses increased by nearly 200 percent in inflation-adjusted terms between 1980 and 2012. And it is not just the earnings at big companies driving the numbers. Measures of earnings at Subchapter S corporations and sole proprietorships—meaning small businesses—are also up. Moreover, the share of individual taxpayers’ income that comes from entrepreneurial activity more than tripled between 1981 and 2013. The rising profits of American small businesses make it hard to believe that slowing population growth is responsible for the decline in employer firm formation. If lower population growth has meant higher wages, which deter would-be entrepreneurs by reducing their profit expectations, then we should see profits actually declining. Why would potential entrepreneurs expect profits to decline, from higher wages or any other cause, when it is clearly apparent that they are rising? Much more plausible is the idea that higher wages led to a shift toward non-employer businesses so that entrepreneurs could maintain their profits, something we will explore in a later chapter. A final problem with the argument that slowing population growth is behind the decline in entrepreneurship is once again that entrepreneurship has not declined. What has gone down is the rate of creation of employer businesses. Many measures of new business creation—the number of non-employers per capita, the share of individual tax returns with the self-employment tax deduction, the share of individual tax returns with business income or loss, and the number of sole proprietorships, partnerships, and corporations per capita—have increased substantially over the past several decades (see chapter 2). Slowing population growth cannot account for a decline in entrepreneurial activity if it coincides with a rise in all these measures 160

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of entrepreneurship. At most, slowing population growth has shifted people away from starting businesses with employees to starting those without. But absent a theory for why that would occur, attributing the patterns to population growth makes little sense. Key Patterns in the Data

1. Some evidence suggests that each 1 percent decline in the growth rate of the working age population leads to a 1 percent decline in the rate of employer business formation. 2. The employer firm formation rate has declined by roughly 50 percent on a per capita basis between 1977 and 2013. 3. The ratio of new firms to the number of people employed has decreased by more than 50 percent over the past threeplus decades. 4. There is very little correlation between the employer firm formation rate and the labor force participation rate over the past thirty-six years. 5. Numerous measures of entrepreneurship have increased in recent decades, despite declines in the rate of population growth. 6. The profitability of entrepreneurial activity has increased in the past three-plus decades, a pattern inconsistent with the argument that a decline in the population growth rate reduced the incentive to engage in entrepreneurship by reducing potential profits from running a business. Some economists have argued that slower population growth is responsible for the decline in employer firm formation rates over three-plus decades. Their argument is based on the idea that declining population growth has reduced the incentive to start new 161

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businesses because it has caused the profitability of entrepreneurship to decline. But running a business is much more profitable now than it was three decades ago. Moreover, most measures of entrepreneurship do not show evidence of a decline in recent decades. And the patterns of employer business formation are inconsistent with the population-growth hypothesis. The labor force participation rate and the employer firm formation rate are barely correlated over time. The ratio of employer firm formation to the number of people employed shows a decline of over 50 percent over the past thirty-six years, and the rate of employer firm formation has fallen on both per capita and per employee bases. If slower population growth were causing there to be fewer employer startups, employer firm formation per capita and per employee would be constant, not declining. In short, another hypothesis for the decline in the rate of new employer firm formation over the past three and a half decades is rejected. Slowing population growth isn’t the cause of the downshift, or even a cause.

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T W E LV E Rising Student Debt Is Not the Cause

In recent years, student debt has come under increasing scrutiny. In addition to all the other problems it creates, some have argued that it is a cause, or even the cause, of the decline in employer firm formation rates. Forget access to credit, regulation, taxes, immigration, demographics, and the host of other factors we have already discussed. “A rather more obvious suspect,” writes management consultant and Forbes columnist Steve Denning, “is the burden of Americans’ $1.2 trillion in student loan debt.”1 Purdue University president Mitch Daniels says pretty much the same thing. In a Wall Street Journal opinion piece, he placed the blame for the drop in new employer businesses squarely on rising student debt.2 Student debt is said to be a problem for three reasons. First, people laden down with debt are dependent on current income to make loan payments and therefore are unlikely to shift to starting businesses where their income might be too variable to enable them to service their loans. People who would have started companies were they debt-free are forced to delay or refrain from starting them at all. Second, these potential entrepreneurs cannot amass the savings or tap the credit necessary to launch companies. “Would-be entrepreneurs are seeing loan payments eat up cash that might be used for

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startup costs, or that would serve as cash flow for a new company,” the Kauffman Foundation’s Arnobio Morelix told the Associated Press. “Debt also affects credit scores, hurting an entrepreneur’s chances of getting a business loan,” he adds.3 The third adverse effect, observers like Denning argue, is that excessive student debt is making Americans risk averse, hindering their willingness to change jobs, relocate, or start companies. All of this is bad news for America, this group argues. As Denning put it in another column, “Student debt is . . . crushing the entrepreneurship that America needs for its prosperity.”4 So central is the problem of student debt, he writes, that “unless lawmakers across the country take radical action to address the skyrocketing cost of college, and attendant student debt burden, we can expect U.S. entrepreneurship to continue its frightening decline.”5 It could even die out entirely. This issue is leading some prominent observers to call for strong policy interventions. Rensselaer Polytechnic Institute president Shirley Ann Jackson suggests that the government forgive the student debt of anyone who starts a business.6 Others propose lowering interest rates on student loans to give would-be entrepreneurs lower monthly payments, leaving more cash for business formation. Still others think the government should eliminate restrictions on discharging student loan debt through bankruptcy or expand programs that defer payments until the borrower’s income reaches a certain level. The Obama administration called for reducing the student loan burden in order to increase entrepreneurial activity and undertook executive actions to reduce the student debt burden.7 Once again we must consider whether these arguments reflect reality. As this chapter will show, there is little evidence that student debt is the cause of the decline in employer firm formation rates in recent decades. 164

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The Supporting Evidence

Even the best case for student debt as an explanation for declining rates of entrepreneurship is a tough argument to make. Proponents of the hypothesis are positing that many young people would have become entrepreneurs had they not had so much student debt. But because it is impossible to observe what these people would have done were they not in debt, we are forced to rely on what people say they would have done. In the Gallup-Purdue Index, a web-based nationwide survey of 30,000 college graduates conducted in 2015, 12 percent of respondents with student loan debt told the researchers they have put off starting a business because of that debt.8 Millennials in particular say they are adversely affected. They report that college debt is their biggest obstacle to going into business for themselves, according to a survey conducted on behalf of two advocacy organizations, the Small Business Majority and Young Invincibles.9 Other statistics also provide some support for this argument. For instance, over the past three and a half decades, while new employer business formation has been falling, student debt has been rising. The per capita rate of employer firm formation and the inflationadjusted level of average federal and nonfederal student loans per full-time-equivalent student correlate −0.63 from 1977 to 2013. Because a correlation of 1.00 means that two measures move in perfect concert and a correlation of −1.00 means they move in perfect opposition to each other, this pattern suggests a relationship between these two values—though it does not, of course, tell us what the relationship is. Self-employed people are also less likely to have student debt than those who are not self-employed. A study conducted for the Office of Advocacy of the Small Business Administration used data from the Federal Reserve’s Survey of Consumer Finances to compare student debt levels in households led by people who were self-employed and 165

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those led by people who were not. It found that in 2012, 34 percent of self-employed people under forty had student debt, compared to 38 percent of non-self-employed people of the same age.10 Simple correlations like these, however, tell us nothing about the myriad of other factors that could be influencing these trends. Two Northeastern University researchers, Karthik Krishnan and Pinshuo Wang, recently made a more sophisticated examination of the link between student loan levels and the tendency to start a business, using data on student debt and entrepreneurship from the Survey of Consumer Finances. Krishnan and Wang found that heads of households with more student debt are less likely to start businesses than those with less. They estimated that an increase in student debt from $0 to $35,000 reduces the odds of starting a business by three percentage points, after controlling for other characteristics.11 Other scholars find similar patterns, albeit in different ways. Three economists at the Federal Reserve Bank of Philadelphia, Brent Ambrose, Larry Cordell, and Shuwei Ma, looked at the correlation between student debt levels across different U.S. counties and the change in the number of businesses with one to four employees in those counties between 2000 and 2010. They found that average student debt levels in each county correlate with the decline in the number of micro businesses.12 Counties where there was more debt saw a greater decline in the number of micro businesses.

The Argument Is Less Convincing Than at First Glance

These studies have convinced many people that rising student debt levels are responsible for falling rates of new employer firm formation. Careful investigation, however, shows the limitations of the argument and evidence. There are several reasons why student

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loan debt is an unlikely explanation for the decline in employer startups. There’s a Counterargument

The first challenge to the rising-student-debt argument is that student debt should actually increase rates of business formation. The advocates of the student debt hypothesis generally argue that student debt should make it more difficult for would-be entrepreneurs to finance their startup efforts, but student debt plays another, more positive, role in entrepreneurship. By taking on debt, people enable themselves to go to college when they otherwise could not, and that education increases their chances of becoming entrepreneurs. Here’s why: two of the big triggers of starting a business are who you know and what you know. While in college, students meet others who can help them to start companies— customers, suppliers, investors, cofounders, or employees. The knowledge they gain, whether it is learning how to keep financial records, how to present well to investors, or how to manage employees, makes them more capable of starting businesses. Finally, a college education allows some people to develop ideas for new businesses and to gain the confidence they need to take the startup plunge. Because borrowing is how many students afford higher education, a higher level of student debt means that more people have gained the knowledge and networks they need to become entrepreneurs. That access to information and contacts might outweigh the negative effects of higher debt levels on entrepreneurial activity. As Sandy Baum, a researcher at the Urban Institute, wrote in a report published in 2015, “The positive effects of education might be stronger than the negative effects of debt and liquidity constraints on the probability of engaging in entrepreneurial activity.”13

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Only Employer Formation Rates Have Fallen

The second challenge to the argument that rising student debt levels are responsible for the fall in employer firm formation is the observed data. I want to emphasize once again that not all measures of entrepreneurship have declined in recent decades. Many measures of entrepreneurship tell a very different story from the one told by the trend in employer firm formation. If we compare the measures of entrepreneurship discussed in chapter 2 to student debt levels, we can see that student debt has a net positive effect on rates of entrepreneurship. For example, the per capita number of sole proprietorships and inflation-adjusted student loan levels correlate positive 0.77 from 1980 to 2013. The correlation is particularly strong since 1995 (figure 12.1). Moreover, sole proprietorships per capita are not even the measure of entrepreneurship most strongly correlated with student loan levels. The correlation is even stronger for the fraction of individual

Figure 12.1. Student Loan Levels and Sole Proprietorships Source: Created from data from the Internal Revenue Service and the College Board.

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tax returns with business income and loss (0.83) and for use of selfemployment tax deductions (0.85). Clearly, the negative correlation between student debt and employer firm formation rates is not telling the entire story about the relationship between college debt and entrepreneurial activity. That’s a problem for those who posit a simple cause-and-effect relationship between student debt and a lack of new employer businesses. For student debt levels to have adversely affected entrepreneurship, the relationship between debt and business formation would have to be far more complex than the simple story presented by the advocates of this view. The only way to reconcile the positive correlation of student debt levels with many measures of entrepreneurship and the negative correlation with new employer firm formation rates is to argue that higher student debt causes people to start different kinds of companies. Would-be entrepreneurs would have to be somehow persuaded to change from starting employer businesses to starting businesses without employees. That shift seems unlikely, given how proponents of the studentdebt hypothesis say debt operates. Rising debt means would-be entrepreneurs can’t save or borrow to start businesses. A lack of money doesn’t differentiate between businesses with employees and those without. If student loan debt blocks would-be entrepreneurs from access to capital, then the increase in real debt levels should have caused a decline in the rate of formation of all kinds of new companies, not just those with paid workers. And we do not see that. The Timing Is Wrong

A third problem with the argument that student debt has caused a decline in entrepreneurship is the poor match between the timing

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of the rise in student debt and that of the decline in employer firm formation. Student debt didn’t really start to increase until the early 1990s. In fact, in 1992, it was 15 percent lower than in 1977 when corrected for inflation. But the per capita rate of employer firm formation during those same years declined by 29 percent, or an average of 1.9 percent per year.14 If rising student debt were really the culprit, employer firm formation should have risen between 1977 and 1992. Now let’s look at what has happened since 1992. Between that year and 2013, the rate of new employer firm formation decreased 23 percent, an average of 1.1 percent per year. Although that is a sizeable decline, it is less than half the average annual rate of decline from 1977 to 1992. In other words, since 1992, the decline in new employer firm formation has moderated—just when student debt levels were starting to take off. Between 1992 and 2013, the per capita amount of student debt more than doubled in inflation-adjusted terms. In short, when employer firm formation was declining the most, student debt levels hardly budged, but when student debt took off, employer firm formation moderated its decline (figure 12.2). In addition, between 1992 and 1995, the level of student loan debt jumped dramatically without triggering a significant fall in the employer firm formation rate. And since 2007, average student loan levels have actually declined in inflation-adjusted terms. But employer firm formation rates have continued to decrease. No Evidence That Student Loan Debt Influences Risk Aversion

A final claim made by proponents of a link between higher student debt and falling rates of employer startups is that higher levels of student debt are making Americans more risk averse and thus less

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Figure 12.2. Rate of Formation of New Employers and Student Loan Debt Source: Created from data from the U.S. Census and the College Board.

likely to start businesses. While this is an intriguing argument, the empirical evidence does not support it. There is no sign that risk taking has declined in the United States in recent years. Surveys of Americans’ attitudes show no rise in risk aversion. Similarly, data on the frequency with which people undertake risky activities, such as investing in high-risk assets or engaging in unsafe practices like unprotected sex, have not declined in recent years. Without evidence that Americans have become more risk averse, it is hard to credit the

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claim that higher student debt has made them risk averse or that this is behind the fall in employer firm formation. What Does the Evidence Really Tell Us?

Given these difficulties with the argument that student debt is behind the decline in employer firm formation, how do we explain the findings from the careful academic studies that show a negative relation between student debt levels and business formation? The answer, I think, lies in understanding what these studies measure and what they don’t, looking at what else might explain the patterns these authors found, and then reconciling their findings with what else we know about changes in rates of entrepreneurship and levels of student debt. The two best pieces of empirical evidence that suggest a relation between student debt and business creation—the studies by the Northeastern University and Philadelphia Fed researchers— don’t actually show that rising levels of student loan debt are causing the decline in business formation. (And to be fair, the scholars undertaking the studies don’t make that claim. People in advocacy groups have overstated the findings to advance a political agenda.) They look only at correlations. As with all such studies, a third factor could be causing both student loan levels and rates of business formation to change. For instance, bad economic times could force more people to borrow to pay for college and also make it more difficult to start a business. Similarly, a long-term change in family resources might be affecting both student debt levels and the willingness to start businesses. People whose parents have enough money to pay for their college education, for instance, are both less likely to have student debt and more likely to have a support infrastructure for starting a

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business. The student debt level itself is not the impediment to new business formation; it is merely a product of other factors that are also encouraging or discouraging entrepreneurship. Moreover, these studies do not even show the correlation over time between student debt levels and the rate of business formation. The Northeastern University study shows that households with more student debt are less likely to start companies than households with less. This could be true even if the effect of student debt on the odds of starting a company are too small to appreciably change the rate of employer business formation. It is also possible that the effect of student debt on the odds of starting a business varies over time. Households with more student debt might always be less likely to start companies, but today’s entrepreneurs might be willing to start companies with more student debt than yesterday’s entrepreneurs. The Philadelphia Fed study is limited in scope. Those economists examined how the average level of student debt in a county affected the formation of businesses with one to four employees. That is, they studied the effect of student debt on the stock of micro businesses in an area. They told the Wall Street Journal that they found no effect of student loan debt on the number of larger startups.15 Companies with fewer than five workers are very small enterprises, and they are very different from companies with twenty or so employees. It is entirely possible that student debt adversely affects only the number of micro businesses, not the number of small companies in general. It is also possible that student debt reduces the number of businesses with one to four employees but not the rate of creation of those businesses. Student debt might be having an adverse impact on business survival, not business formation.

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Key Patterns in the Data

1. The per capita rate of creation of new employer businesses and the real per student level of college debt correlate negatively over the period 1977 to 2013. 2. The rise in student debt correlates positively with an increase in non-employer businesses and IRS measures of small and new businesses over the same period. 3. If student debt is causing a decline in employer firm formation, increases in student debt levels should be followed by declines in employer firm formation, but these patterns are not present in the data. 4. There is no evidence that student debt levels have increased Americans’ level of risk aversion, or that an increase in risk aversion has led to a decline in entrepreneurial activity. Several policy makers and pundits have argued that the rise in student debt levels is responsible for the past few decades’ decline in employer firm formation. Arguing that student debt levels have kept would-be entrepreneurs from starting companies by reducing their savings, credit capacity, and risk-taking propensity, these observers have called for a series of policy interventions to reduce student debt in order to stimulate entrepreneurial activity. Despite some findings that people with higher levels of student debt are less likely than others to start businesses, student debt levels do not appear to have caused the decline in employer firm formation. In fact, taking on student debt may actually increase business formation by allowing more people access to a college education. Student debt levels correlate positively with several measures of entrepreneurial activity since 1980. Moreover, the timing of the rise in student

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debt does not fit with the hypotheses that it caused the decline in employer startups. The rise in student debt has not reduced entrepreneurship by making Americans more risk averse, for the simple reason that Americans have not become more risk averse. Finally, the most sophisticated studies to examine the question do not imply that student debt levels have reduced Americans’ tendency to start businesses. They merely show that households with more student debt are less likely to be business-owning households. In short, rising student debt levels are not the cause of the decline in the rate of formation of new employer businesses.

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THIRTEEN Don’t Blame a Loss of Moxie

Is a loss of moxie to blame for the decline in employer firm formation? Dane Stangler, vice president for research at the Kauffman Foundation, writes, “Many commentators, observing an overall decline in the rate of American firm formation, have wondered if Americans have somehow become more risk averse over time.”1 Stangler and other observers propose that the decline in employer firm formation over the past three-plus decades stems from a generational change in attitudes. Americans, they argue, have become less willing to engage in entrepreneurship. Compared to the Baby Boomers or the Greatest Generation, Generation X and Millennials have less moxie. They take fewer risks and try fewer new things, leaving them less predisposed to start businesses than previous generations of Americans. In addition, goes the argument, younger Americans view entrepreneurship with less interest than previous generations. Instead of having a single-minded focus on work, they are more involved in family and social causes at the expense of starting companies, a pursuit they see as imposing tremendous demands. Furthermore, for younger people, entrepreneurship and small business have lost their central place in the American psyche. Americans, commentators argue, have become less willing to view business, including small business, as positively as their parents’ and grandparents’ generations did. 176

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A change in attitudes is a plausible explanation for the decline in employer firm formation since the 1970s, and it is certainly worthy of investigation. But as this chapter will explain, it isn’t a likely cause. Surveys reveal that Americans’ interest in entrepreneurship changed little over time. No statistics show that Americans have become more risk averse and therefore less willing to start companies. Interest in business ownership has risen and fallen with the vagaries of the economy, but the trend is neither up nor down. Americans’ support for small business has remained far stronger than their feelings toward other institutions. Overall, there is little evidence of a loss of moxie. The Argument

Before we evaluate the hypothesis that Americans have lost their moxie, I want to clarify the argument itself. The central claim is that Americans have changed. We are no longer passionate about entrepreneurship. Our citizens once believed in Horatio Alger stories of people starting companies and going from rags to riches. We glorified people who started companies and used their grit and determination to rise out of poverty. Starting a business meant taking big stomach-churning risks. But Americans of past generations didn’t look for safe jobs; they didn’t try to minimize the downside or cut their losses. They reached for the brass ring. Now, the argument goes, we are not so willing to take chances. We have become frightened of the unknown. We choose jobs at big companies instead of setting out on our own. Economist Ian Hathaway told Inc. magazine that the “pay and perks” at big firms persuade “fence-sitting” entrepreneurs not to start their own companies.2 Having grown afraid of failing at their entrepreneurial efforts, Americans are less willing to try business creation than we once were. Donna Kelley, a Babson College entrepreneurship professor, told Inc. 177

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magazine, “The fear of failure . . . can reflect a greater level of caution, and a preference for more stable employment when there is high uncertainty and a less favorable environment for entrepreneurship.”3 The policy makers and pundits are posing a hypothesis: the decline in new employer firm formation over the past several decades stems from a shift in attitudes. As Ian Hathaway and Robert Litan wrote, “Individuals appear to be more risk averse . . . fewer people are launching firms.”4 That’s the theory, at least. The Evidence Disagrees

The argument that changes in attitudes are driving the decline in employer firm formation is plausible, but the data do not support it. A search for evidence corroborating any part of this hypothesis comes up short. The Decline Is Concentrated in Employer Starts

The most basic issue is one we have discussed already. Entrepreneurship is not down; only the rate of formation of employer businesses has declined. Data from both the IRS and Census Bureau show that more people are engaged in entrepreneurship now than two and three decades ago (see chapter 2). That makes the culturalshift argument difficult to accept. If people have lost interest in entrepreneurship, then the total number of entrepreneurs should have declined, but it hasn’t. It is hard to argue that a loss of moxie has affected only the formation of businesses with paid workers. There is nothing inherently more risky about starting a business with a paid worker than with a contractor. We have a similar problem trying to argue that a growing fear of failure has inhibited business startups. If Americans are more afraid of failing today than they were thirty-plus years ago, we should see 178

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a decline in all entrepreneurial activities, not merely those with paid employees. But as we have seen, the rates of business ownership and non-employer business creation are both up. These patterns are inconsistent with the idea that Americans are now afraid of failing as company founders. American Entrepreneurs Remain Positive about Business Formation

It would be easier to argue that the fall in employer firm startups is caused by a change of attitude if there were, in fact, evidence of a change of attitude: if Americans were becoming less positive about entrepreneurship than before. Negative attitudes toward entrepreneurship could explain why people were less interested in starting businesses. Continued positive views of entrepreneurship would make it more difficult to accept a loss of moxie as a convincing explanation for a decline in willingness to start employer businesses. In exploring this question, we need to tread cautiously: the data on attitudes toward entrepreneurship do not go back that far. But over the period for which they are available, there is no evidence that Americans are growing less positively disposed to business formation. Wells Fargo and the Gallup Organization have jointly surveyed a sample of 600 small business owners every quarter since 2003. One of the things they measure is how satisfied these owners are with the decision to strike out on their own. They ask the owners, “If you had it to do all over again, would you still become a small business owner, or do something else?” In 2003, 81 percent of small business owners said they would still become a small business owner. In 2014, the fraction was a statistically similar 84 percent.5 Over the same period, the per capita rate of employer firm formation fell by 25 percent. If small business owners’ dissatisfaction 179

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with the decision to open their own businesses caused this drop, we should have seen more dissatisfaction among owners. But we don’t. Americans Remain Positive about Small Business as an Institution

Or perhaps the rate of employer firm formation has dropped because Americans have soured on the concept of small business. While small, independent businesses might have been something people loved in the 1980s, today big companies might be more appealing. The ruthless efficiency of giant corporations might appeal to Americans who want to get everything—meals, clothing, auto repair —faster than ever before. People are more likely to engage in activities that others view positively versus those that they view negatively. If Americans found small businesses less appealing, fewer people might want to start them, leading to a drop in the rate of employer firm formation. The data do not support this hypothesis. Americans have actually become more positively disposed to small business as an institution over the past eighteen years. According to the Gallup Organization, 67 percent of Americans had a “great deal” or “quite a lot” of confidence in small business in 2015. That’s up slightly from 65 percent in 1997.6 It seems Americans’ confidence in small business isn’t related to their willingness to start new companies with employees. The rising confidence in small business is all the more surprising given that Americans’ approval of almost all other institutions has fallen. The Gallup Organization reports significant declines in confidence in organized religion, the Supreme Court, public schools, television news, the presidency, and the police between 1997 and 2015. Even confidence in banks and big business took a hit over the past eighteen years.

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In short, the rate of new employer firm formation has shrunk, but lack of confidence in small business isn’t the reason. More Americans Intend to Start Companies

If a change in attitudes toward entrepreneurship were the cause of the decline in new employer firm formation, we would expect to see fewer Americans intending to go into business for themselves. But entrepreneurial intentions have been rising in recent years. The Global Entrepreneurship Monitor, an annual survey, has found that in 2014, significantly more Americans intended to start a company in the next three years (12 percent) than had this intention in 2002 (9.2 percent) (figure 13.1). Given that the intention to start a business and employer firm formation have moved in opposite directions, one cannot be causing the other. Americans’ plans to become entrepreneurs, it seems, are not behind the decline in employer startups. It’s Not an Unwillingness to Take Risks

Some observers have claimed that Americans are no longer willing to take the risk of starting companies. Americans, one Wall Street

Figure 13.1. Percentage Intending to Start a Business within Three Years Source: Created from data from the Global Entrepreneurship Monitor.

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Journal article explains, have “a risk-averse culture.” Instead of thinking of the potential riches that come from starting companies, they are focused on avoiding failure.7 But several sources of data show that Americans aren’t cutting back on risk taking. One measure of this is how they invest their savings. Between 1989 and 2013, while the rate of employer business formation was declining, Americans moved their savings into riskier investments. The Federal Reserve’s Survey of Consumer Finance shows that Americans systematically shifted money from certificates of deposit, savings bonds, other bonds, and cash value life insurance into riskier assets. These four kinds of investments together accounted for 27.9 percent of American households’ financial assets in 1989, but just 8.2 percent in 2013.8 If Americans really were becoming more risk averse over the last two and a half decades, they shouldn’t have moved assets out of low risk financial instruments into higher risk ones. More direct evidence of Americans’ risk taking comes from a survey paid for by the European Community and repeated in the United States several times since the turn of the millennium. According to the Flash Euro Barometer, a periodic survey of people in numerous countries, American attitudes toward the risk of starting a business have changed little in the past twelve years. In 2000, 27 percent of Americans agreed with the statement: “One should not start a business if there is a risk it might fail.” In 2012, the fraction was statistically the same—28 percent.9 If Americans are truly becoming more risk averse, more of them should hold this attitude now than in 2000. During the thirteen-year period covered by the Euro Flash Barometer survey, creation of employer businesses per year fell by more than 23 percent. It is hard to attribute that decline to a rise in the fear of financial risk.

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Millennials Are Less Interested in Entrepreneurship than Generation Xers

Some observers argue that young people today are less interested in starting businesses than their parents were at the same age. We do not have data on the entrepreneurial interests of all young people, but we do have it for college students. Since the 1960s, researchers at UCLA have conducted an annual survey of incoming freshmen at U.S. colleges and universities. They ask about a wide range of topics, from students’ attitudes on social issues to their intended major. One question addresses students’ intended occupations. The fraction of incoming freshmen who intend to be business owners or entrepreneurs has risen since the late 1970s: 2.3 percent in 2014 versus 1.8 percent in 1977 (figure 13.2).

Figure 13.2. Percentage of Students Intending to Be Entrepreneurs or Business Owners Source: Created from data from the Cooperative Institutional Research Program at UCLA.

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More important, however, this result does not correlate with the rate of employer firm formation. As you can see from the figure, there have been two periods during which the fraction of college students intending to become entrepreneurs has risen, followed by two periods of decline. From 1977 to 1988, the percentage of college students who said they intended to start their own businesses more than doubled, from 1.8 percent to 3.9 percent. From 1988 to 1992 it fell to 2.2 percent. It then rose steadily, reaching 3.6 percent in 2005, only to decline to 2.3 percent in 2014. These waves of rising and falling interest in entrepreneurship do not correlate well with the employer firm formation rate, which hasn’t displayed similar waves but rather a long downward trend. It seems unlikely that much of a causal relation exists. The UCLA survey also asks incoming college freshmen if they would like to run their own successful business someday. It is a tougher question to interpret than the one about intended profession because we don’t know what fraction of respondents focus on the word “successful” rather than the phrase “business of my own.” We can probably assume that a fairly small fraction of students plan to be unsuccessful at whatever they intend to do. Still, the answer to this question is not consistent with a pattern of long-term decline in interest in entrepreneurship. The fraction of students expressing interest in business ownership rose from 47.1 percent in 1977 to 52.1 percent in 1988, fell to 40.9 percent in 1994, and has more or less held steady since then (figure 13.3). This pattern is very different from the steady decline in employer business formation we saw in chapter 1.

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Figure 13.3. Percentage Interested in Having a Successful Business of One’s Own Source: Created from data from the Cooperative Institutional Research Program at UCLA.

Key Patterns in the Data

1. American small business owners are as satisfied with their choice to go into business for themselves in 2014 as they were in 2003. 2. The American public has more confidence in small business today than it did in 1997 despite having less confidence in many other institutions, including banks and big business. 3. More Americans said they intended to start businesses in the next three years in 2014 than in 2002. 4. Americans are no more likely to say that fear of failure keeps them from starting businesses than they were a decade ago, and no less willing to take investment risks than they were twenty-five years ago.

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5. Although American college freshmen are less likely to intend to be successful in a business of their own in 2014 than they were in 1977, the fraction has been more or less steady since 1994 and more of them reported that they are likely to make entrepreneurship their career choice in 2014 than in 1977. Although some observers attribute the decline in employer firm formation to a change in Americans’ attitudes, the data do not support this explanation. Several surveys show that Americans’ interest in entrepreneurship has changed little over time. Small business owners are as satisfied with the choice to go into business for themselves now as they were a decade ago. The American public has more confidence in small business today than it did in the late 1990s. More Americans intend to start a business in the next three years than expressed the same intention more than a decade ago, and the people of this country are no more likely to say that fear of failure keeps them from starting businesses than they were a decade ago. More American college freshmen today say that they are likely to choose entrepreneurship as a career than in the late 1970s. In short, the data suggest that something other than a change in attitudes accounts for the fall in employer startups over the past several decades. If a lack of capital, more regulation, higher taxes, a lack of immigration, an aging population, declining population growth, rising student debt, and changing attitudes did not cause the decline, what did?

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FOURTEEN Employees Have Become Too Expensive

We have seen many flawed explanations for the decline in the rate of creation of new employer businesses. It’s time to examine some that make more sense. One of the more plausible accounts for the changes in entrepreneurial activity that have occurred over the past three-plus decades is that labor costs have risen too fast. The cost of offering benefits, particularly employee health insurance, has risen so much over the past two decades that business owners have cut back on the number of workers on their payrolls. Fewer entrepreneurs are taking them on at all, and those who do tend to hire fewer than they once did. Entrepreneurs are also using technology to automate tasks that used to require a lot of labor, contracting out work that they once did in-house, and relying more on their own efforts to do things that once required paid workers. As a result, American entrepreneurs now operate with fewer people on the payroll than their counterparts did two decades ago. This explanation is not a perfect interpretation of what has happened (in the next chapter we will see that other forces are also in play), but it is more consistent with the patterns we have observed than the accounts I reviewed in chapters 6 through 13. Rising labor costs combined with the opportunity to use technology and outside help have had an important effect on American entrepreneurship.

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Total Compensation at Private Sector Businesses Has Been Rising

It costs much more to employ people today than it did two decades ago, even after adjusting for inflation. Total compensation by private sector employers has increased in real terms over the past three decades, from $27.43 per hour (in 2011 dollars) in 1986 to $30.07 in 2015, with a nearly 19 percent rise since 1996 (figure 14.1). It is important to point out that this rise in compensation doesn’t mean Americans’ take-home pay has gone up. Workers are actually doing worse in inflation-adjusted terms. In 1986, the average private sector worker earned $20.02 per hour (in 2011 dollars). In 2014, she earned $19.91 (figure 14.2). But wages are not all that employers pay for: they also pay for workers’ benefits, and the cost of these ancillaries have been rising.

Figure 14.1. Hourly Private Sector Compensation, Including Benefits (in 2011 dollars) Source: Created from data from the Bureau of Labor Statistics. 188

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Figure 14.2. Average Hourly Wage and Benefit Costs (in 2011 dollars) Source: Created from data from the Bureau of Labor Statistics.

Between 1986 and 2014, the average cost of benefits of private sector workers have risen 16 percent in inflation-adjusted terms. As a result, benefits now account for 30.1 percent of private sector compensation, up from 27 percent in 1986. The Rising Cost of Employee Health Insurance

The biggest culprit in the rising cost of benefits is the long-term increase in the cost of providing health insurance for workers. To get a sense of how small business owners are affected, consider an American entrepreneur named Tim Anderson. Sixteen years ago, Tim founded a small air-conditioning maintenance and repair business that employs eight technicians. On many levels, it is a successful business. Last year, on revenues of just under $600,000, Tim cleared $110,000 in profit. But despite this success, Tim has been unable to provide his employees with health insurance. That is not only a problem for his workers: it hinders his ability to compete with other companies. In the past year he has lost out on hiring two technicians who went to work for larger companies because they offered health insurance. 189

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Tim wants to offer health insurance to his employees, but he can’t afford it. For himself, his eight employees, and their families, health care coverage would cost $150,000 per year. Even if he passed off 20 percent of that cost to the employees, providing coverage would wipe out his profit. So he doesn’t offer it. The Affordable Care Act was supposed to solve this problem. If Tim couldn’t provide his employees with health insurance, the government would provide his workers with subsidies to buy insurance on the new health care exchanges. But even with the subsidies, many of Tim’s employees cannot afford the coverage. Part of the problem is a misfit between what they want and what the government encourages insurers to provide. Tim’s workers are all young and healthy. They don’t earn a ton of money and they have a lot of other expenses. And they don’t want to prepay for routine care. They want coverage against a disaster, much like that provided by their homeowner’s and auto insurance. They want to protect themselves if one of their kids gets very sick and has to go to the hospital, but they can’t get that kind of coverage, so many didn’t buy health insurance at all. The Affordable Care Act (ACA) simply has not solved the problems of many entrepreneurs. The cost of employee health insurance has continued to rise. Since the law was enacted, the fraction of entrepreneurs offering health insurance to workers continues to slide. The tremendous rise in health insurance costs over the past two decades has imposed a financial burden on new and small companies. Between 1999 and 2015, the cost of employer-sponsored family health insurance at companies with between 3 and 199 employees doubled in inflation-adjusted terms, according to the Kaiser Family Foundation (figure 14.3). The cost for the average new company to provide its employees with family health insurance is 18 percent more

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Figure 14.3. Annual Small Business Health Care Premium per Employee for Family Coverage (in 2011 dollars) Source: Created from data from the Kaiser Family Foundation.

than what large businesses pay for the same coverage. As the trend line in the figure shows, at best the ACA might have slowed the rate of increase, but it hasn’t stopped it. We can see the degree to which health care costs have pinched American entrepreneurs by comparing the rise in the cost of health insurance with the change in revenues. Between 1999 and 2012, the period for which data on both measures is available, the real cost of family health insurance coverage at businesses with 3 to 199 employees rose 94 percent, while inflation-adjusted revenues at proprietorships, partnerships, and S corporations increased by just 11.5 percent.1 The fast rise in health insurance costs relative to revenues forces America’s entrepreneurs to economize on labor. Some entrepreneurs

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have shed employees and reduced others to part-time status. Others have just given up being in business for themselves. It’s Not the Increased Cost of Retirement Plans

One might be tempted to attribute this rise in benefits costs to more than just the increased cost of employee health insurance. But the numbers don’t really support that claim. True, compared to three decades ago, American business owners are devoting much more of their labor costs to funding their employees’ retirement. But the numbers are so small that they are unlikely to be driving the changes. Since 1980, the fraction of sole proprietors’ labor costs devoted to funding employees’ retirement benefits has almost tripled, but to only 3.4 percent (figure 14.4). Sole proprietors don’t represent all small businesses—the larger ones tend to be corporations or partnerships—but they do account for about three-quarters of all businesses. So the numbers for sole proprietors tend to drive overall patterns for small businesses.

Figure 14.4. Pension and Profit Sharing as a Fraction of Labor Costs Source: Created from data from the Internal Revenue Service.

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Responses to Rising Labor Costs

Private sector labor compensation has risen significantly in real terms, largely because of the rising cost of health benefits. Entrepreneurs have responded in several ways. One way has been to reduce benefits, as is apparent in the declining fraction of small businesses that offer employee health insurance. The Kaiser Family Foundation, which tracks business health care coverage, reports that only 46 percent of companies with 3 to 9 employees offered employee health insurance in 2016, down from 55 percent in 1999. For firms with 10 to 24 workers, the fraction offering health benefits was 74 percent in 1999, and only 61 percent in 2016. For businesses with 25 to 49 workers, 88 percent provided health coverage in 1999, and 80 percent in 2016.2 Even for all small businesses with 3 to 199 employees, the numbers are down: 65 percent of firms offered employee health benefits in 1999, but only 56 percent did in 2015 (figure 14.5).

Figure 14.5. Percentage of Small Firms Offering Health Benefits Source: Created from data from the Kaiser Family Foundation.

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The numbers are even lower for new businesses. The Kauffman Foundation reports that only 29.5 percent of new businesses with employees provide health insurance to their full-time employees.3 Another way that entrepreneurs have responded to the rising cost of employee health insurance has been by letting wages fall relative to those offered by large employers. Small business owners have always paid less than their larger counterparts, but the wage gap has risen substantially over the past two and a half decades. Employee compensation at businesses with fewer than 100 workers was 65.3 percent of that at companies with 500 or more workers in 1990. By 2013, that figure had fallen to 55.6 percent (figure 14.6).

Figure 14.6. 1–99 Employee Compensation as a Percentage of 500+ Employee Compensation Source: Created from data from the Bureau of Labor Statistics.

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Figure 14.7. Small Business Share of Private Sector Payroll Source: Created from data from the U.S. Census.

Payroll data also show the wage gap between big and small firms. Small business’s share of annual payroll has fallen substantially since the late 1980s. In 1988, companies with fewer than 500 workers accounted for 48.6 percent of U.S. private sector payroll. In 2011, the latest year for which data are available, the fraction had fallen to 42.0 percent (figure 14.7). A third way that America’s entrepreneurs have responded to rising labor costs has been not to hire workers the way they once did. One of the biggest trends over the past thirty-six years has been a declining tendency among people who are in business for themselves to hire other people to work for them. Compared to a generation ago, many fewer self-employed people have paid employees. One simple way to see this is to look at data from the Bureau of Labor Statistics. In 1995, 20.7 percent of self-employed Americans had employees. That might not sound like a lot, but remember that a lot 195

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of self-employed people are running service businesses or are other types of independent operators who don’t need paid workers. They either do the work for customers themselves or they hire outside contractors to help them. This relatively small number has gotten smaller over time. In 2015, only 14.3 percent of the self-employed had paid workers, and that number is a jump from 13.5 percent in 2014. Between 1995 and 2009, the fraction of self-employed Americans who hired others declined almost every year (figure 14.8). Although the number has grown recently, it is far below its levels in the late 1990s and shows little sign of returning to what it once was. Over the two decades for which we have data, the fraction of self-employed Americans with paid workers has gone down by nearly a third. As I mentioned in the first chapter, there are two main types of self-employment, unincorporated and incorporated. The BLS data

Figure 14.8. Percentage of the Self-Employed with Employees Source: Created from data from the Bureau of Labor Statistics.

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shown in figure 14.8 are for unincorporated self-employment and may not be the best measure of “entrepreneurship.” Many observers think incorporated self-employment is more informative, since people who go to the trouble of setting up a corporation are more likely to run full-time businesses that employ others, rather than merely being independent contractors. But even the incorporated self-employed are far less likely to hire other people than they were a generation ago. According to the BLS data, the fraction of incorporated self-employed with employees has fallen from 62.1 percent in 1995 to 42.1 percent in 2015. It is as if every third incorporated self-employed person in 1995 got rid of his or her workers by 2015. Where did these workers go? America’s entrepreneurs have, in part, become more efficient, decreasing the amount they spend on labor to produce each dollar of revenue. Over the past three decades, technological advances have permitted entrepreneurs to run their businesses with fewer employees. In the late 1970s and early 1980s, before small business owners had personal computers, recordkeeping didn’t mean using QuickBooks, it meant paper ledgers. Running a business was more labor intensive; fewer small business owners could get by with zero employees, and those that had workers needed more of them. Personal computers, software, smart phones, and the Internet have changed how entrepreneurs operate. More of them can do things on their own, or they can use contractors who don’t appear on their payrolls. Long-term trends in sole proprietors’ spending on labor give indirect evidence of increased labor efficiency. The IRS data show that they have dramatically cut what they spend on wages and salaries in inflation-adjusted terms over the past three-plus decades. In 2013, the average sole proprietor spent just over half as much on salaries and wages as her counterpart did in 1975. Moreover, this decline is not

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the result of a shift from fixed wages to more variable compensation. The amount the average sole proprietor pays in commissions has fallen by nearly half since 1992. It is also possible that sole proprietors’ labor bills are going down because they are spending less on labor to generate a given amount of revenue. One way to get at whether small business owners are economizing more on labor, is to look at what has happened to their labor expenditures relative to sales. Their spending on labor as a fraction of annual revenues bounced around between 1975 and 1997, yet over the entire span since 1975 it has declined by nearly one-fourth— from 3.2 percent in 1975 to 2.4 percent in 2013 (figure 14.9). Even while the cost of labor increased dramatically because of rising benefits costs, sole proprietorships cut the amount they spent to generate each dollar of revenue. Entrepreneurs also have turned to the use of contractors instead of workers on their payrolls. Independent contractors provide

Figure 14.9. Labor as a Percentage of Sales at Proprietorships Source: Created from data from the Internal Revenue Service.

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Figure 14.10. Contract Labor as a Percentage of Labor Expense Source: Created from data from the Internal Revenue Service.

a way to accomplish work goals without direct hiring. Because entrepreneurs do not generally pay contractors’ benefits, the shift to contractors helps to offset the rise in benefits costs while still allowing entrepreneurs to use the labor they need to operate their businesses. While the data on use of contract labor have a more limited scope and a shorter time horizon than some of the statistics described earlier, they suggest that entrepreneurs have been using more contract labor in recent years. Even over the brief period from 2003 to 2013, there was a large increase in the proportion of sole proprietors’ labor expense that was used for contract labor: it rose from 20.1 percent to 36.4 percent (figure 14.10). It’s the Cost of Workers, Not Access to Talent

Many observers conflate the cost of employees and access to talent, arguing that entrepreneurs are less likely to start employer firms because many new and small businesses cannot get the workers they

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need. As John Dearie and Courtney Geduldig put it in their book Where the Jobs Are, “The most serious obstacle to additional hiring by new businesses is a pronounced shortage of qualified talent.” 4 Dearie told a subcommittee of the House Committee on Small Business that “the skilled talent shortage . . . hits new businesses especially hard. . . . The shoestring circumstances of most start-ups during the initial years typically can’t accommodate the training programs necessary to turn high-potential employees into high-value employees.”5 Dearie and Geduldig reported that entrepreneurs at roundtables around the country said that this was the cause of the problem, but the data suggest otherwise. A lack of talent cannot explain the decline in the rate of employer firm formation. As several observers have pointed out, the decline in employment by new businesses stems almost completely from the decline in the number of new employers rather than their size at startup, which has remained constant over the past three decades. New businesses aren’t having troubling staffing their operations at the size at which they typically operate. Yet entrepreneurs are founding many fewer new businesses with paid workers. Moreover, if finding talent is really a problem, then bigger and more mature companies should also be experiencing it. But the data show that these businesses have had little trouble finding talent over the past three-plus decades. Employment growth at big businesses has been substantial over the past several decades. Chain businesses have been adding workers faster than new companies, as shown by an analysis I conducted with colleagues at the Cleveland Fed. (I will say more about the shift to chains in the next chapter.) If there is a shortage of qualified talent, why doesn’t it affect larger and older businesses too?

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Figure 14.11. Percentage of Small Businesses with at Least One Hard-to-Fill Job Opening Source: Created from data from the National Federation of Independent Business.

Furthermore, systematic surveys of business owners do not show evidence that they are having difficulty finding qualified workers. The National Federation of Independent Business has been surveying its members about the ease (or not) of filling job openings since 1986. While the fraction of business owners each year reporting that they have at least one hard-to-fill opening largely follows economic conditions, it has not trended upward over time. In January 2015, only 26 percent of small business owners reported trouble filling at least one position, versus 31 percent in January 2001 (figure 14.11). If a lack of training of potential employees was the reason why employment by entrepreneurs has declined over time, then we should see a rising percentage of small business owners reporting jobs that they are having difficulty filling.

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The more plausible explanation is cost. As the cost of labor has risen, people starting new businesses have become less likely to hire workers. They have used technology and contractors to reduce or eliminate their payrolls. Those two changes have led to a decline in employer business creation and a rise of businesses without employees. Opportunity Cost May Play a Role

Rising labor costs also slow the formation of employer businesses through another mechanism, rising opportunity costs. As Rob Fairlie, an economist at the University of California at Santa Cruz, explains, people who are contemplating starting a business are strongly influenced by the financial returns of the alternatives. While there are always some who will start companies regardless of how good salaries are at existing employers, most people compare the two options. When wages are rising, the opportunity cost of starting a business—the salary one must give up to do it—increases. That, in turn, reduces the motivation to start a new firm.6 As we saw earlier in this chapter, the total compensation of the average worker has been rising in recent decades. Increased compensation raises the opportunity cost of leaving a job and starting a business, and it increases the earnings threshold that the average founder of an employer business needs to achieve to justify starting the new company.7 I do not emphasize this argument, however, because rising wages should also increase the opportunity cost of starting a non-employer business. And as you no doubt realize, the number of non-employer businesses has been rising. Therefore, rising wages are more likely to have led would-be entrepreneurs to start businesses without employees than to have refrained from starting businesses in general.

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Key Patterns in the Data

1. Total compensation at private sector employers has risen in real terms since the mid-1990s, largely because of rising benefits costs. 2. America’s entrepreneurs have responded by cutting back on benefits, such as the provision of employee health insurance. 3. They have also allowed wages to fall relative to those at large employers since the mid-1980s. 4. They have reduced their employment; the self-employed are less likely to have employees now than in the mid-1990s. 5. America’s entrepreneurs have taken advantage of technology to use labor more efficiently, generating more revenues per dollar of labor expense than they did in the 1980s. 6. They have also increased their use of contract labor. Rising labor costs are at least partially responsible for the changes in entrepreneurship we have seen in this country over the past threeplus decades. Total compensation at private sector employers has risen in real terms since the mid-1990s, largely because of rising benefits costs. These increased costs have led America’s entrepreneurs not just to cut back on benefits and allow wages to fall relative to large employers but also to cut back on the use of labor. They are responding to these higher costs by using technology to become more efficient and by making greater use of contract labor. As a result, the creation of employer businesses has fallen while the creation of nonemployers has risen. I want to make clear what the changes in labor costs could explain and not explain about patterns in American entrepreneurship.

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Rising labor costs could explain what we have seen since the mid1990s. Since that time, the rate of employer firm formation has declined while other measures of entrepreneurship, like the fraction of Americans who file self-employment taxes or report business activity on their tax returns, have risen. A higher cost of labor could have encouraged many entrepreneurs to substitute technology or contractors for payroll workers, or to do without help. But the higher cost of employee compensation cannot account for the decline in employer firm formation rates and the rise in other measures of entrepreneurship between the mid-1980s and the mid-1990s. Nevertheless, the increased cost of worker compensation, particularly the rise in health and retirement benefits, has influenced several changes in American entrepreneurship. More entrepreneurs are operating without others on the payroll, and fewer are founding and managing businesses with paid workers. But this is not the sole explanation for what’s going on.

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FIFTEEN Chains Have Replaced Independent Employers

We have one final explanation to explore. This account is more plausible than those described in many of the previous chapters, and it fits the data quite well. It is the rise of chain businesses. Multi-unit chains, or companies that own more than one place of business, have grown dramatically over the past three and a half decades, helped by the rise in information and communications technology. As technology has made it easier to manage multiple business locations, chain businesses have developed an advantage over single-establishment businesses, so that these multi-establishment businesses have increasingly displaced independent companies in the marketplace. Some of this substitution has involved the replacement of small independent companies by big national chains—the Walmarts and Targets of the world. But the shift is not limited to retail. It has occurred in every sector of the economy. Moreover, most of the chains replacing the single-establishment businesses aren’t giant companies. They are dry cleaners with three locations pushing out single-location dry cleaners. Or they are chains of six Mexican restaurants in one city’s suburbs substituting for six independent restaurants. Because this shift isn’t from small to giant companies, it’s hard to say that it is “endangering” entrepreneurship

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in America. A lot of entrepreneurs are growing their businesses at the expense of other entrepreneurs. The market may simply be rewarding more talented entrepreneurs over less talented ones. That might not be a situation that justifies government intervention in the marketplace. But before we spend too much time evaluating the pros and cons of what has happened, let’s first see why the growth-of-chains hypothesis fits the data. The Growth of Chains

Chains are becoming a more dominant way for businesses to meet the American population’s demand for goods and services. Technological advancements have made it easier for a small number of chains, rather than for a large number of independent businesses, to provide these services. To understand why, we need to think about the changes in the country’s geography over the past thirty-five years. Since the late 1970s, America’s population has moved south and west, and from center cities to suburbs and even exurbs in some locations. As some metropolitan areas have grown, and rural areas have become exurbs and even suburbs, businesses have needed to create new establishments to meet the demand of people living and working in those new locations. After all, people need carpet cleaning and air-conditioning repair, restaurants and dry cleaners, clothing and hardware and furniture. So entrepreneurs have set up shop in the new suburban and exurban locations. But who are the entrepreneurs opening up in the new strip malls? Since the late 1970s the Census Bureau has collected data that help answer this question. It measures the number of new and existing business establishments with employees as well as the number of new and existing firms with employees. By measuring both new

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establishments (places where business occurs) and firms (legal entities that operate in the economy) the data allow us to compare them. When we count the number of existing or new establishments we are counting new business locations of existing companies, such as a new McDonald’s, as well as new businesses, such as Dave’s Diner, a new independent restaurant. It’s not difficult to imagine that the number of establishments might rise, but the number of firms might fall. That would happen if chains have more success than new independents. If the chains are less likely to close down and more likely to start up or grow, they will tend to replace the single-establishment companies. There is a trade-off between the growth of multi-unit establishments and new employer business formation. The more multi-unit establishments grow, the more mom-and-pop businesses have to decline. Bob Litan, one of the economists who has looked at these data, explains that the larger established businesses become, “the fewer the startups that sprout.” As he said to Inc. magazine, “If you are a city or state with a rising concentration” of chain stores, or branches of existing businesses, “you see a faster decline in your startup rate.”1 We can also look at the ratio of new businesses to new establishments. If there has been a shift toward more chain activity, then the ratio of new establishments to new employer businesses should rise over time. For instance, if the exurbs of San Jose, California, grow and a new place to get dry cleaning done is needed, that new dry cleaner is increasingly likely to be part of an existing chain of dry cleaners expanding to a new location. The numbers confirm this. Overall, in the United States, the new firm share of new establishments has fallen from 79.2 percent in 1977 to 72.4 percent in 2013. In 1977, Americans created 1.26 new establishments for every new

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business formed. By 2013, the latest year data are available, they created 1.33 new establishments for every new business.2 Another way to measure the shift to establishments is by comparing the size of the average firm to the size of the average establishment. If chains are becoming more dominant, then we should see businesses growing relative to establishments, because a chain requires more workers than a single-establishment business. People are also needed to coordinate activities across locations. The numbers are consistent with this story. In 1977 the average American company with employees had 19.3 workers. In 2013 it had 23.2, a 20 percent increase. Back in 1977, the average American establishment had 15.9 workers. In 2013, that had increased to 17.5, a rise of only 10 percent (figure 15.1). This means that the ratio between the size of the average business and the size of the average establishment has gone up, indicating a movement toward more coordinated multi-unit operations.

Figure 15.1. Firm and Establishment Size Compared Source: Created from data from the U.S. Census.

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Figure 15.2. Average Size of New Firms and All Employer Firms Source: Created from data from the U.S. Census.

A final measure of the shift from independent businesses to chains is the change in the average size of new firms versus all employer firms. New firms tend to be just big enough to meet the demands of serving customers at a single establishment, since most new firms start with one location, whereas existing firms tend to be of the size necessary for however many establishments they have. The average size of an employer firm has grown about 20 percent since 1977 because those businesses have increasingly been made up of more establishments. But the average size of new employer firms has actually fallen, from 6.7 to 5.6, a decline of 20 percent (figure 15.2). This means that existing businesses are increasing in size relative to new ones. While all firms had 2.9 times as many workers as new firms had in 1977, they now have 4.1 times as many. Compared to three decades ago, more new businesses either become chains or else fade away.

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Why the Growth in Chains?

Over time, customer demand has been served increasingly by chains rather than independent companies. Why? There could be a number of reasons, but the most compelling is the development of information and communications technologies. To grasp those changes, I need to put you back in 1977, the year of the twenty-five-hour blackout in New York City. That was also the year the first Apple II computer went on sale and the Department of Defense introduced the NAVSTAR global positioning system. Small business owners didn’t have computers, cell phones, inventory management software, QuickBooks, point-of-sale terminals, or most of the information technologies we take for granted today. A second location of a dry cleaner or restaurant or clothing store had to be operated pretty much independently, without much more realtime connection than a telephone. Compared to today, there was little that technology could do to provide an advantage to a business owner with more than one establishment. But since 1977, the enormous developments in information and communications technologies have transformed business in many ways that give multi-establishment businesses an advantage over those in just a single location. Moreover, their value is often greater for larger operations than for smaller ones because these technologies can enhance coordination and distribution across a wide range of locations. But they also help chains of any size: because they have a fixed cost component, they are cheaper to implement on a per location basis if they are being used in multiple locations simultaneously. The end result is that chains have been able to increase their efficiency—and thus productivity—faster than single-location firms, and they have been able to take an increasing share of the market. Improvements in information technology also make it easier for existing companies to move into new markets by allowing them to 210

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manage their employees more effectively. Existing companies are getting better at providing incentives to their employees to exploit opportunities for them. When employees have the resources and opportunity to help their employers exploit new markets, fewer feel the need to strike out on their own. Think about the example of a clothing store. In the 1980s the development of personal computers and the operating systems to run them made it possible to put inventory management software in retail establishments. Although such software could have been developed using mainframe computers in earlier decades, its cost and complexity meant that a regional chain with ten stores wouldn’t have had it. Now imagine what happens when someone starts selling inventory management software that runs on a PC. If a ten-store chain tries it out, the company becomes more efficient at all ten locations. The same software makes a single-location store more efficient too, but in only that one location. The software costs the same to produce whether it is bought for one location or ten, so the relative benefit of the innovation is greater for the chain. Now multiply this change across businesses in many industries with many new pieces of technology and you see a pattern emerge. The development of computer and communication technologies benefited chains more than independent businesses. As a result, we see a rising share of multi-unit establishments and a declining share of independent businesses. Not Growth in Mergers and Acquisitions

Of course, there are other broad explanations for this trend, some of which are popular in the media. They sound plausible, but I don’t think they fit the data as well. One common explanation is the acquisition of small companies by big ones. According to this story, private 211

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equity companies like Mitt Romney’s Bain Capital have transformed the American economy by buying up small independent companies to create giant chains. This story is not very consistent with the data. First of all, big companies like Apple, IBM, and Procter and Gamble don’t actually buy many startups, relative to the four to five hundred thousand created every year. The little companies acquired by big public companies number in the low thousands, at most. You can see this pattern intuitively by looking around your neighborhood. A national chain has not bought your dry cleaner. Nor the diner you frequent or your shoe repair shop. If an independent business in your neighborhood was displaced, it was most likely by a small- or medium-size chain from the next town over. Moreover, mergers and acquisitions are how entrepreneurs often generate financial returns from their efforts. Even if acquisitions by big companies were to rise, there is no reason to think that would reduce the rate at which people would start new employers. In fact, it would most likely motivate them to start more of these businesses. For the most part, the shift to chains has occurred largely among small operators, not growing from one to one thousand outlets but from one outlet to three. Moreover, the growth has occurred largely because the chains have expanded to new locations, not because companies have sought to roll up those independent businesses into a single company. Not Due to a Shift in Industrial Composition

Another alternative explanation is that the industrial composition of the U.S. economy has changed, reducing the incentive for entrepreneurs to found companies. This explanation isn’t very promising for two reasons. The first is the direction of the change in industrial

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composition: manufacturing has declined and the service industry has grown. In 1977, manufacturers made up 7.6 percent of employers, but by 2013 they comprised just 4.6 percent. By contrast, in 1977 service companies made up 32.7 percent of employers, but in 2013 they were 47.1 percent.3 Because manufacturing companies are more difficult and costly to start than service businesses, if industrial composition were the primary factor in the formation of new employers, the rate of formation should have gone up as relatively easy-to-start service businesses became a more dominant part of the economy. Moreover, the power of the decline in employer formation, and the reason we see it in the aggregate data, is that it is generic. It has taken place across all industries. This was not something that just affected food establishments or dry cleaners or pharmacies. It affected everyone who has the opportunity to have more than one place of business. That makes it difficult to buy the industrial composition story. If the shift were concentrated in some industries that were particularly hard hit by economic downturns (like construction) or were more common in industries with greater ease of starting (like personal services), then the explanation would be more plausible. But the shift to chains is widespread, affecting all sectors of the economy. That pattern requires a story that applies not just to some industries growing at the expense of others but that fits what we see throughout the economy. Is the Change a Problem?

Many policy makers have jumped from observing the decline in the formation of new employer firms to recommending policies to combat this trend. Thus far I have focused on understanding the cause of the change, on the assumption that the answer needs to

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fit the problem. If the rise of chains is behind the decline in new employer firms, “startup visas” are a non sequitur. The proportion of immigrants in the population is not related to the rise in chains, since immigrants are no more or less likely than the native born to form chain businesses. Similarly, cutting taxes or reducing regulations isn’t the cure. There is no reason to believe that tax or regulatory policy favors the formation of chains. But there is another problem with calling for policies to stop the decline, if the decline is caused by growth in chain businesses. All policies have consequences, both intended and unintended. Some downsides can’t be predicted in advance. If we adopt policies that address a problem that isn’t there, we will do little to improve the situation, but the downsides will happen anyway. It will be hard to boost the rate of new employer firm formation. Chains are growing at the expense of independent startups because they make more efficient use of information and communications technology. Taxing chains or subsidizing independent startups will distort the efficient allocation of resources by putting them to a less productive use. That is not wise policy. Society is worse off if we allocate resources away from their best and most productive uses. Some might argue that we do need to intervene in the marketplace, even if we risk a misallocation of resources, to protect disadvantaged groups. We should stop the Walmarts of the world, many say, from driving all the independent small business owners under. But most of the growth in chains that is taking market share from the independent business owners isn’t coming from the Walmarts or Targets, it’s coming from local or regional three- and four-outlet businesses. It is small business competing against small business. So forget the economic justification. What is the political justification for making it easier for a new entrepreneur to start a single-establishment business at the expense of a three- or four-establishment chain? 214

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Key Patterns in the Data

1. The ratio of new establishments to new firms has grown since 1977. 2. Firm size has grown relative to establishment size. 3. The average size of employer businesses has grown since the late 1970s, but the average size of new employers has remained about the same. 4. Technological changes in information and communication technology are a more likely explanation for the substitution of independent businesses by multi-unit companies than changes in industrial composition or large chains buying up independent single-location businesses. One reason why the rate of employer firm formation has declined and the economy has shifted toward a greater fraction of nonemployers has been the rise of chain businesses. Advances in information and communication technology have made it easier to manage multiple, dispersed business locations. This has given chains an advantage over independent, single-establishment businesses. Multi-unit businesses have grown faster in number and size than single-location businesses and have displaced the single-establishment owners in many markets. Because the growth of chains comes from more productive use of resources, government intervention to prop up singlelocation employers would be economically unwise, even if it was politically appealing.

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SIXTEEN The Story the Data Are Telling

Entrepreneurship seems to be in the very fiber of our culture. Since our nation’s inception, entrepreneurs have played an important role in the development of new technology, the generation of wealth, and the creation of jobs. The importance of entrepreneurship to America means that those in Washington take very seriously any indication that our performance at it is flagging. The implications of a decline are enormous. With fewer entrepreneurs, our economy would be less flexible and less responsive to changes. New technology would spread more slowly. Labor markets would adapt less well to recessions and recover more slowly during expansions. And many observers would want policy makers to adopt policies to stimulate entrepreneurial activity. It is no surprise, then, that economists and journalists, noting the recent slowdown in employer firm formation, have called for a policy response. They are urging our elected officials to start issuing startup visas, boost entrepreneurial education, fix the tax code, subsidize credit, change our culture, and cut regulation, among a myriad of other things. But should they? Every policy action has unforeseen consequences. Undertaking a policy is only worthwhile if the problem is severe enough to risk an unexpected outcome. If entrepreneurship

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is not really in decline, then we shouldn’t incur the negative costs of policy actions to boost it. Moreover, to be effective, an intervention has to be designed with attention to the actual nature of the problem. If entrepreneurship rates are down because entrepreneurs are deterred by too much regulation and not by lack of access to capital, then interventions to stem regulation are a better answer than boosting credit to startups. To know which “solutions” might have merit, economists and policy makers need to identify the causes of changes in entrepreneurial activity. What’s Really Happened?

Are entrepreneurs really endangered? I have spent fifteen chapters answering that question. If you have read this far, you know that they are not. We are not witnessing the disappearance of entrepreneurship in this country. Instead, we are seeing it change. There are some negative indicators. The rate of unincorporated self-employment has trended downward since the mid-1970s, and the rate of secondary self-employment has fallen since 1999. The percentage of job seekers in outplacement who say they want to start their own businesses has declined since 1989. And, of course, the rate of creation of employer businesses has fallen by half since 1977, bringing the level of formation below the replacement rate. The result has been a fall in employment at young companies, which weakens future job creation and quite possibly hinders innovation, capital investment, and productivity and GDP growth. If these were the only indicators of entrepreneurship, we would conclude that it is indeed in decline and that policy intervention makes sense. But that is not the case. The rate of creation of many kinds of

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businesses is up and the failure rate of existing employers is down. Entrepreneurs’ earnings have risen substantially in inflation-adjusted terms, and high-potential companies are doing better than they were in the 1980s. What has happened in American entrepreneurship over the past three decades is something other than a simple decline. Designing a policy response is far more complex than what most pundits are calling for. The first step in figuring out what to do is to figure out what has already happened. We can readily explain some shifts. The decline in unincorporated self-employment, both on a primary and secondary basis, represents a straightforward shift in the legal form of selfemployment. The rate of incorporated self-employment has trended upward since the late 1990s. If we combine the downward trend in unincorporated self-employment with the upward trend in incorporated self-employment, we get a flat rate over time. The most likely explanation for these offsetting trends is that the self-employed have found reason to incorporate. Perhaps the cost of incorporation has come down, or people are more concerned about liability. Whatever it is, this pattern has nothing to do with the overall condition of entrepreneurship and everything to do with a switch in legal form. We cannot dismiss other patterns as easily. The biggest issue is the divergence in trends for new employer businesses and other types of companies. As you know by now, the rate at which America is creating employer businesses is half what it was in 1977. But you also know that the per capita number of businesses without employees has risen substantially; that a rising fraction of Americans are taking the self-employment tax deduction on their individual taxes; that the fraction of individual tax returns with business income or loss has risen; and that the per capita numbers of sole proprietorships, partnerships, and corporations are all higher now than in 1980.

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Reconciling these trends suggests a very different explanation from “entrepreneurship is in decline.” The numbers point to a story about labor markets. America’s entrepreneurs appear to have shifted away from hiring employees to running businesses without workers or with off-payroll labor. Total compensation at private sector employers has risen in real terms since the mid-1990s. Wages have remained stagnant while benefits have rapidly increased. Small business owners are feeling the pinch of rising health care costs, and fewer of them provide employee health insurance now than in the late 1990s. It is reasonable to suppose that rising labor costs are an important reason fewer small businesses are taking on employees. They have shaved their hiring and increased their use of contract workers. There is also an issue in attracting labor. Small businesses have become less attractive places to work. The wages they offer have fallen relative to those at large employers since the mid-1980s. Inability to attract workers with high wages is no doubt another reason small business owners are using fewer workers. Sole proprietors have become more efficient users of labor, generating more revenues per dollar of labor expense than they did in the 1980s. Whether this is a problem remains to be considered. Responding to it, however, requires thinking hard about whether to intervene in markets to motivate America’s entrepreneurs to employ more people. Other data show another trend. Despite the 50 percent decline in the per capita rate of formation of new businesses with employees, the per capita stock of employers was higher in 2013 than it was in 1977. This means the outflow of employers is down. As employer firm formation rates have fallen over past decades, so have failure rates. Perhaps the decline in employer firm formation rates is occurring because existing employer firms are doing better.

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If existing employers are sticking around longer, there will be less need—and less opportunity—for new employers. Add to that the fact that many existing companies are expanding their geographic reach by forming chains, and we have a very different story. Advancements in information and communications technologies over the past three-plus decades have made it easier to manage multiple, geographically dispersed business locations. As a result, chain businesses— companies with more than one establishment —have developed an advantage over single-establishment businesses. The result is a displacement of independent, singleestablishment businesses by chains. This is why we observe a rising ratio of new establishments to new firms since the late 1970s. Entrepreneurship has not declined, but it has changed. Entrepreneurs are getting better at running their companies. It may be harder to break in, but once you do, your odds of success are better. Should policy makers intervene because existing entrepreneurs are making more money and failing at a lower rate? The question answers itself. Creating lots of new companies that start and fail is not a worthwhile policy goal. If entrepreneurs are becoming more profitable, less likely to fail, and more likely to expand their operations to new locations, we should be happy. Creating more new employers for the sake of having more new employers would be foolhardy. Concerning high-potential businesses, some observers don’t think that what has happened to typical companies matters much. To them, entrepreneurship is about the new business superstars— the next generation of Facebooks, Apples, Googles, and Snapchats. If those are producing profits and generating jobs, then all is well. The data show that we have little to worry about with highpotential companies. Our venture capital and angel finance system remains the envy of the world. The number of venture capital funds

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and the amount of venture capital under management are all higher now than in the early 1980s. More startups are getting angel and venture finance than received those types of financing a decade or two or three ago. Venture capital-backed companies account for a larger fraction of employer firms now than in the early 2000s. And the outcomes of those businesses are better than they were in the mid1980s, with a higher fraction of companies having positive exits and with exits valued more in real terms. The valuations of early-stage companies have risen substantially since the early 2000s. The Flawed Explanations

Policy makers, economists, and journalists have offered numerous explanations for the changes we have seen in entrepreneurship. Many of them, however, have looked at relatively little of the data and have used the decline in the rate of new employer firm formation to advocate for a particular policy intervention. A careful look at the data shows that most of these policies would do little because the factor they would address is not the cause of the supposed decline. Consider easier access to credit for new and small businesses. There is little evidence that a lack of access to capital is holding Americans back from starting companies. Most of the money that entrepreneurs use to finance their startups comes from their own savings, and the personal savings rate is uncorrelated with the rate of formation of employer businesses. Although fewer banks are lending to small businesses than did so in the 1980s, this shift does not appear to have limited small business access to credit. More small business loans are made now than in the 1990s, and small businesses are more highly leveraged now, even after significant post-financial crisis deleveraging. Moreover, many measures of entrepreneurship have shown increases in recent years.

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Another common explanation for the “decline in entrepreneurship” is high taxes. The data suggest that this is not a plausible explanation. People rarely focus on tax rates when deciding whether to start a new business. Theoretically, higher taxes both encourage and discourage business formation, yielding no net effect. Empirically, the marginal income tax rate has actually gone down over the past three decades, making it difficult to see income tax rates as an obstacle to employer firm formation. Finally, high-tax states have not seen greater declines in employer firm formation rates than lowtax states. Many observers point to regulation as a cause of the reduction in entrepreneurship. But the causal relationship between regulation and rates of entrepreneurship simply isn’t there. The rise in regulation over the past three decades correlates positively with an increase in the creation of non-employer businesses and with IRS measures of small and new businesses. Owning a business has become more profitable, not less, as regulation has increased, undermining the argument that regulation is having a dampening effect. Periods of major regulatory increases have not been followed by declines in employer firm formation, nor do small business owners perceive that regulation is becoming onerous at times when employer firm formation has declined. Finally, the negative correlation between rates of employer business formation and the number of rules pages found in some casual investigations disappears when more rigorous statistical tests are used. Many observers have called for increased immigration to counteract the decline in entrepreneurship. The data challenge this argument too. Only the creation of employer businesses is in decline, not all entrepreneurship, and there is no reason to think that immigrants are disproportionately likely to start companies with employees

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rather than businesses without them. It is difficult to see how a lack of immigration has led simultaneously to a decline in employer firm creation and a rise in non-employer form formation. In any case, there is no evidence that recent federal government policies (at least before 2017) have reduced immigration. It is difficult to see how the government has deterred entrepreneurs from coming into this country. Moreover, the data challenge the notion that immigrants are more likely to start businesses than native-born Americans. There is no difference between the two groups in the probability of starting a company. Thus, it is not clear how more immigration would generate more entrepreneurship. Some observers have claimed that rates of entrepreneurship are down because of a change in attitudes away from risk taking and willingness to pursue opportunities. The data, however, do not conform to this story. Overall rates of entrepreneurship are not down, only the formation of employer businesses. Non-employer startups have risen. It is not clear how a turn away from risk taking would cause some measures of entrepreneurship to rise and others to fall. Surveys show that Americans’ interest in entrepreneurship has changed little over time. And the ways that it has changed are not consistent with the decline in employer firm formation. Student debt is another target of blame for the decline in entrepreneurship, and it has led many to call on policy makers to intervene. But both theory and evidence contradict this argument. On the conceptual side, student debt should correlate with a rise in business formation, given the reason the students incurred the debt in the first place: to get a college education, which makes them more likely to become entrepreneurs. On the empirical side, student debt levels correlate positively with several measures of entrepreneurial

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activity since 1980, and periods of increase in student debt levels are not followed by declines in employer firm formation. Finally, there is no evidence that rising student debt has made Americans more risk averse, or that risk aversion has led to a decline in entrepreneurial activity. Some economists have argued that slower population growth is to blame. That argument doesn’t work either, because it requires the profitability of entrepreneurship to have gone down. But running a business is much more profitable now than it was three decades ago. Moreover, there is very little correlation between the employer firm formation rate and the labor force participation rate over the past thirty-six years. The ratio of firm formation to the number of people employed has decreased by more than the employer firm formation rate, suggesting that population growth is not the key force behind the decline. And changes in the population growth rate can’t account for a simultaneous decline in the employer firm formation rate and a rise in the non-employer formation rate. A final explanation is aging of the population. Risk taking, creativity, and innovation all decline as people age, and some say that the collective loss of these qualities is affecting rates of entrepreneurship. Once again, however, the data disagree. There is little correlation between the aging of the population and the rate of employer firm formation. Moreover, several measures of entrepreneurship, particularly those focused on non-employer businesses, have risen at the same time that employer firm formation has declined. Absent a theory for why an aging population should shift from employer to non-employer firm formation, the association between population age and entrepreneurship rates would seem to be spurious.

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Things Are Not All Good

I do not want to create the impression that I think all of these changes are good. We need not worry about earnings from entrepreneurial activity rising over time, or the fact that high-potential businesses are doing well. A reduced failure rate of businesses might be beneficial on average, shifting entrepreneurial success from newer efforts to more mature ones. Even the growth of chains is ambiguous. More concentrated success in the hands of entrepreneurs who have built multi-unit businesses at the expense of single establishment operations might not be a bad thing. The worrisome trend in recent decades has been the shift in entrepreneurial activity from employers to non-employers. To understand why this is a problem, you need to recognize that the two are not interchangeable. Changing between employers and non-employers is not like choosing steak or shrimp for dinner. Non-employers are much smaller companies than employers and have far less economic impact. Switching from employers to non-employers is more like giving up steak for a peanut butter sandwich. A little more peanut butter doesn’t make up for less steak. To see the magnitude of the difference, take a look at sales. In 2012, the latest year for which data are available, Census Bureau figures show that the average small employer in the United States had revenues of $2,070,000, and the average non-employer had sales of $45,000.1 That’s a ratio of 46:1. The formation of non-employers would have to be astronomically high to make up for decline in the formation of employers. Then there’s the long-term trend. Non-employer revenue growth, as small as it is, has actually been going down—by more than 24 percent in real terms since 1998. Measured in constant year dollars, the average sales at a non-employer business declined from $53,165 to $44,437 over the period.2 225

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Moreover, the shift to non-employer businesses appears to have negatively affected the economy (see chapter 5). Of all the major problems that the growth of non-employer business formation and the decline of employer business creation have caused, the biggest one is the adverse effect on employment. New businesses are a key source of job creation, and, by definition, non-employers are not contributors to employment at all. As entrepreneurs create fewer new employers, they are creating fewer jobs. The shift from employers to non-employers has created a drag on small business employment and might explain why employment growth at small companies has lagged behind that of large companies over the past two decades. The shift toward greater numbers of non-employer businesses in the economy also might have caused a decline in capital investment because employers spend so much more on equipment and structures than non-employers. The shift to non-employers could account for the slowdown in innovation we have been seeing in small businesses in recent years since people are the ones who come up with the new ideas. A decline in the rate of creation of employer businesses might be responsible for growing income inequality because business formation only helps people get ahead if they are creating substantial enough companies to earn a higher income than they would get working for someone else. Finally, the replacement of employers with non-employers may be behind slowing GDP and productivity growth because employer businesses contribute far more to these two dimensions of the economy than non-employers. Where to Concentrate Our Efforts

Many of those observing and analyzing entrepreneurship in America have followed the wrong path. In their quest to justify policy positions, they have sought simple answers to complex situations

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and argued incorrectly that the decline in the formation of employer businesses means a fall in entrepreneurship. They have then sought to link, without real evidence, that “decline in entrepreneurship” with the absence of the policies they favor. The more nuanced story is that entrepreneurship has changed. Some of the changes are benign, but others, like the shift to more businesses without employees, are more ominous. Policy makers, economists, and journalists should focus their attention on the real transformation: the decline in job creation by new and young firms. Americans are not creating companies with employees as they once did, and job creation by young and small businesses has suffered. We don’t yet know all the reasons for this shift. It would therefore be premature for me to offer a set of policy solutions. I have no wish to make my own contribution to the long list of wrong answers outlined in this book. But we do know where to start to look for answers. As we saw in chapter 14, the rising cost of employee benefits correlates with the shift to non-employer business creation. Labor markets are a good place to focus attention. They seem to offer the best explanation for the divergence between employer and non-employer businesses— something that cannot be accounted for by taxes or regulation or access to capital. Some will argue that the passage of the Affordable Care Act solved this problem. But the data show that the health care law did not stem the decline in employer firm formation or the rise in nonemployers. Moreover, we need to rule out alternative explanations for the shift to non-employers. The use of contract labor has risen over the past decade. Investigators need to remove the part of the effect that comes from shifts like these and hone in on the part that comes from the rise in benefits costs.

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Last Word

Many people are asking whether entrepreneurship is in danger. The answer is clearly “no.” But that may be the wrong question. If we ask whether we have a problem creating new employers, the answer is much closer to “yes.”

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Notes

Introduction 1. K. Bahsin, “Malcolm Gladwell on Why History Will Remember Bill Gates and Forget Steve Jobs,” Business Insider, June 7, 2012, http://www.businessinsider .com/malcolm-gladwell-on-how-we-worship-entrepreneurs-2012 – 6. 2. A. de Tocqueville, Selected Letters on Politics and Society, ed. R. Boesche, Berkeley: University of California Press, 1985. 3. R. Decker, J. Haltiwanger, R. Jarmin, and J. Miranda, “The Secular Decline in Business Dynamism in the United States,” Working Paper, 2010, University of Maryland, http://econweb.umd.edu/~haltiwan/DHJM_JEP_5_17_2013.pdf. 4. J. Yellen, “Perspectives on Inequality and Opportunity from the Survey of Consumer Finances,” October 17, 2014, https://www.federalreserve.gov/news events/speech/yellen20141017a.htm. 5. J. Plehn-Dujowich, “Product Innovation by Young and Small Firms,” report for the Office of Advocacy of the U.S. Small Business Administration, May 2013, under contract SBAHQ-11-M-0204, https://www.sba.gov/sites/default/files/files/ rs408tot.pdf. 6. I. Hathaway and R. Litan. “Declining Business Dynamism in the United States: A Look at States and Metros,” Economic Studies at Brookings, May 2014, http://www.brookings.edu /~/media /research /files /papers /2014/05/declining%20 business%20dynamism%20litan /declining_business_dynamism_hathaway_litan .pdf. 7. D. Burton. “Building an Opportunity Economy: The State of Small Business and Entrepreneurship,” Testimony before the Committee on Small Business, U.S. House of Representatives, March 5, 2015, http://www.heritage.org/research/ testimony/2015/ building-an-opportunity-economy-the-state-of-small-business -and-entrepreneurship.

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Chapter 1. Something Is Happening, but We Don’t Know What It Is 1. B. Casselman, “The Slow Death of American Entrepreneurship,” Fivethirtyeight, May 15, 2014, http://fivethirtyeight.com/features/the-slow-death-of-american -entrepreneurship/. 2. Jim Clifton, “American Entrepreneurship: Dead or Alive?” Business Journal, January 13, 2015, http://www.gallup.com/businessjournal /180431/american-entre preneurship-dead-alive.aspx. 3. J. D. Harrison, “The Decline of American Entrepreneurship in Five Charts,” Washington Post, February 12, 2015, https://www.washingtonpost.com/news/on -small-business /wp/2015/02/12/the-decline-of-american-entrepreneurship-in-five -charts/. 4. Dane Stangler, “The Looming Entrepreneurial Boom: How Policy Makers Can Renew Entrepreneurial Growth,” n.d., http://www.kauffman.org/neg/neg -intro#theloomingentrepreneurialboomhowpolicymakerscanrenewstartupgrowth. 5. Annie Lowrey, “Don’t Let the Disruption Hype Fool You: America Is Actually Getting Less Entrepreneurial,” New York, August 5, 2014, http://nymag.com/daily/ intelligencer/2014/08/america-is-getting-less-entrepreneurial.html. 6. Ibid. 7. Pew Research Center, “Three-in-Ten Jobs Are Held by the Self-Employed and the Workers They Hire,” October 22, 2015, http://www.pewsocialtrends .org /2015/10/22/three-in-ten-u-s-jobs-are-held-by-the-self-employed-and-the -workers-they-hire/. 8. R. Decker, J. Haltiwanger, R. Jarmin, and J. Miranda, “The Role of Entrepreneurship in U.S. Job Creation and Economic Dynamism,” Journal of Economic Perspectives 28, no. 3 (20014): 3 –24. 9. I. Hathaway and R. Litan, “What’s Driving the Decline in the Firm Formation Rate? A Partial Explanation,” Economic Studies at Brookings, November 2014, https://www.brookings.edu /wp-content /uploads /2016/06/driving_decline_firm_ formation_rate_hathaway_litan.pdf; I. Hathaway and R. Litan, “Declining Business Dynamism in the United States: A Look at States and Metros,” Economic Studies at Brookings, May 2014, https://www.brookings.edu/wp-content/uploads/2016/06/ declining_business_dynamism_hathaway_litan.pdf; I. Hathaway and R. Litan, “The Other Aging of America: The Increasing Dominance of Older Firms,” Economic Studies at Brookings, July 2014, https://www.brookings.edu/wp-content/up loads/2016/06/other_aging_america_dominance_older_firms_hathaway_litan.pdf.

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Chapter 2. The Good News 1. I. Hathaway and R. Litan, “The Other Aging of America: The Increasing Dominance of Older Firms. Economic Studies at Brookings, July 2014, http://www .brookings.edu /~/media /research /files /papers /2014 /07/aging%20america%20 increasing%20dominance%20older%20firms%20litan /other_aging_america _dominance_older_firms_hathaway_litan.pdf. 2. J. Dearie and C. Geduldig, Where the Jobs Are: Entrepreneurship and the Soul of the American Economy, Hoboken, NJ: Wiley, 2013. 3. Author’s calculations from U.S. Census data, https://www.census.gov/ces/ dataproducts/bds/. 4. Author’s calculations from U.S. Census data, https://www.census.gov/ces/ dataproducts/bds/. 5. A. Pe’er and I. Vertinsky, “Firm Exits as a Determinant of New Entry: Is There Evidence of Local Creative Destruction?,” Journal of Business Venturing 23 (2008): 280 –306. 6. Author’s calculations from U.S. Census data, https://www.census.gov/ces/ dataproducts/bds/. 7. Author’s calculations from the Survey of Consumer Finances data, https:// www.federalreserve.gov/econres/scfindex.htm. Chapter 3. Entrepreneurial Earnings Are on the Rise 1. Author’s calculations from IRS data, https://www.irs.gov/uac/soi-tax-stats -statistics-of-income). 2. Author’s calculations from the Survey of Consumer Finances data, https:// www.federalreserve.gov/econres/scfindex.htm. Chapter 4. Riding High 1. R. Decker, J. Haltiwanger, R. Jarmin, and J. Miranda, “The Decline of High Growth Entrepreneurship,” VOX, 2016, http://www.voxeu.org/article/decline-high -growth-entrepreneurship. 2. Author’s calculations from National Venture Capital Association data, http:// nvca.org/. 3. Author’s calculations from National Venture Capital Association data, http:// nvca.org/, and U.S. Census data, https://www.census.gov/ces/dataproducts/bds/. 4. Author’s calculations from National Venture Capital Association data, http:// nvca.org/, and U.S. Census data, https://www.census.gov/ces/dataproducts/bds/.

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5. Author’s calculations from Center for Venture Research data, https://paul college.unh.edu/research/center-venture-research/cvr-analysis-reports, and U.S. Census data, https://www.census.gov/ces/dataproducts/bds/. 6. Author’s calculations from National Venture Capital Association data, http:// nvca.org/. 7. Author’s calculations from National Venture Capital Association data, http:// nvca.org/, and U.S. Census data, https://www.census.gov/ces/dataproducts/bds/. 8. Author’s calculations from National Venture Capital Association data, http:// nvca.org/. 9. Author’s calculations from National Venture Capital Association data, http:// nvca.org/. 10. Author’s calculations from Center for Venture Research data, https://paul college.unh.edu/research/center-venture-research/cvr-analysis-reports. 11. M. Hudson, “Angel Investments in the U.S.—Helping Startups Be Successful,” Angel Capital Association, 2016, https://www.angelcapitalassociation.org/ data/Documents/Resources/ACATaiwanSummitRev09-06-16.pdf. 12. Author’s calculations from National Venture Capital Association data, http:// nvca.org/. 13. Cambridge Associates, “U.S. Venture Capital Index and Selected Benchmark Statistics,” 2014, http://www.cambridgeassociates.com/wp-content/uploads/2015/ 05/ Public-USVC-Benchmark-2014-Q4.pdf. 14. National Venture Capital Association, http://nvca.org/. 15. Ibid. 16. Author’s calculations from National Venture Capital Association data, http:// nvca.org/. 17. Author’s calculations from National Venture Capital Association data, http:// nvca.org/. 18. Author’s calculations from Cooley Venture Financing Report data, https:// www.cooleygo.com/trends/. Chapter 5. The Implications of Fewer Employer Startups 1. Author’s calculations from IRS data, https://www.irs.gov/uac/soi-tax-stats -statistics-of-income, and U.S. Census data, https://www.census.gov/ces/data products/ bds/. 2. R. Decker, J. Haltiwanger, R. Jarmin, and J. Miranda, “The Role of Entrepreneurship in U.S. Job Creation and Economic Dynamism,” Journal of Economic Perspectives 28, no. 3 (2014): 3 –24. 232

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3. Ibid. 4. Author’s calculations from U.S. Census data, https://www.census.gov/ces/ dataproducts/bds/. 5. Author’s calculations from Bureau of Labor Statistics data, https://www.bls .gov/. 6. Decker, Haltiwanger, Jarmin, and Miranda, “Role of Entrepreneurship.” 7. Author’s calculations from Small Business Administration data, https://www .sba.gov/category/advocacy-navigation-structure/research-and-statistics. 8. Author’s calculations from Small Business Administration data, https://www .sba.gov/category/advocacy-navigation-structure/research-and-statistics. 9. Author’s calculations from U.S. Census data, https://www.census.gov/ces/ dataproducts/bds/. 10. Author’s calculations from Bureau of Labor Statistics data, https://www.bls .gov/lpc/. 11. E. Prescott and L. Ohanian, “U.S. Productivity Growth Has Taken a Dive,” Wall Street Journal, February 3, 2014, https://www.wsj.com/articles/the-key-to -a-stronger-us-economy-higher-productivitythe-key-to-a-stronger-us-economy -higher-productivity-1391469120. 12. U.S. Census “Nonemployer Statistics,” https://www.census.gov/econ/non employer/. 13. Author’s calculations from U.S. Census data, https://www.census.gov/library/ publications/2017/econ/2017-csr.html. 14. Author’s calculations from NFIB Small Business Economic Trends data, http://www.nfib.com/surveys/small-business-economic-trends/. 15. Author’s calculations from the Federal Reserve Flow of Funds Report data, https://www.federalreserve.gov/releases/z1/current/, and IRS Statistics of Income data, https://www.irs.gov/uac/soi-tax-stats-statistics-of-income. 16. Author’s calculations from U.S. Patent and Trademark Office data, https:// www.uspto.gov/learning-and-resources/statistics. 17. J. Lettieri, “America without Entrepreneurs: The Consequences of Dwindling Startup Activity,” Testimony before the Committee on Small Business and Entrepreneurship, U.S. Senate, June 29, 2016, https://www.sbc.senate.gov/public/_ cache /files /0/d /0d8d1a51-ee1d-4f83-b740-515e46e861dc /7F75741C1A2E6182E1A5D 21B61D278F3.lettieri-testimony.pdf. 18. J. Haltiwanger, “Job Creation and Firm Dynamics in the United States,” Innovation Policy and the Economy 12:17–38, http://www.journals.uchicago.edu/doi/ pdfplus/10.1086/663154. 233

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Chapter 6. It’s Not a Lack of Capital 1. B. Lynn and L. Khan, “The Slow Motion Collapse of American Entrepreneurship,” Washington Monthly, July/August 2012, http://www.washingtonmonthly .com/magazine/julyaugust_2012/features/the_slowmotion_collapse_of_ame038414 .php?page=all. 2. B. Ryan, “Starved of Financing, New Businesses Are in Decline,” Business Journal, September 4, 2014, http://www.gallup.com/businessjournal /175499/ starved-financing-new-businesses-decline.aspx. 3. Roisin McCord, Edward Simpson Prescott, and Tim Sablik, “Explaining the Decline in the Number of Banks since the Great Recession,” Federal Reserve Bank of Richmond Economic Brief, March 2015, https://www.richmondfed.org/-/media/ richmondfedorg/publications/research/economic_brief/2015/pdf/eb_15 – 03.pdf. 4. Lynn and Khan, “Slow Motion Collapse.” 5. J. Dearie, Testimony before the Subcommittee on Contracting and Workforce, Committee on Small Business, U.S. House of Representatives, September 11, 2014, https://smallbusiness.house.gov/uploadedfiles/9-11-2014_dearie_testimony .pdf. 6. Author’s calculations from FDIC data, https://www.fdic.gov/bank/ analytical /qbp/timeseries/SmallBusiness&FarmLoans.xls. 7. Author’s calculations from FDIC data, https://www.fdic.gov/bank/ analytical /qbp/timeseries/SmallBusiness&FarmLoans.xls. 8. Author’s calculations from FDIC data, https://www.fdic.gov/bank/analytical / qbp/timeseries/SmallBusiness&FarmLoans.xls, and IRS Statistics of Income data, https://www.irs.gov/uac/soi-tax-stats-statistics-of-income. 9. Author’s calculations from FDIC data, https://www.fdic.gov/bank/ analytical /qbp/timeseries/SmallBusiness&FarmLoans.xls, and U.S. Census data, https://www.census.gov/programs-surveys/susb.html. 10. Author’s calculations from Federal Reserve data, https://www.federalreserve .gov/Releases/Z1/Current/. 11. Federal Reserve Survey of Small Business Finance data, https://www.federal reserve.gov/pubs/oss/oss3/nssbftoc.htm. 12. Author’s calculations from the Federal Reserve Flow of Funds Report data, https://www.federalreserve.gov/releases/z1/current/. 13. Author’s calculations from the Survey of Consumer Finances data, https:// www.federalreserve.gov/econres/scfindex.htm.

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Chapter 7. Don’t Blame the Regulators 1. T. Siems, “What Keeps Small Business Owners Up at Night?,” Financial Insights 3, no. 2 (2014), http://www.dallasfed.org/assets/documents/banking/firm/fi/ fi1402.pdf. 2. T. Kane, “Encouraging Entrepreneurship: Growing Business, Not Bureaucracy,” Testimony before the Joint Economic Committee, U.S. House of Representatives, July 12, 2016, http://www.jec.senate.gov/public/_cache/files/eafbff88 -6997-49b7-abb6-e9352cb7dc6d/kane-testimony.pdf. 3. D. Burton, “Building an Opportunity Economy: The State of Small Business and Entrepreneurship,” Testimony to the Committee on Small Business, U.S. House of Representatives, March 4, 2015, http://smallbusiness.house.gov/uploaded files/3-4-2015_final_burton_tesimony_final.pdf. 4. D. Greenblatt, “The Obama Administration’s Regulatory War on Jobs, the Economy and America’s Global Competitiveness,” Testimony before the Subcommittee on Regulatory Reform, Commercial and Antitrust Law of the Committee on the Judiciary, U.S. House of Representatives, February 28, 2013, http://www .nam.org /Issues /Regulatory-Reform /Regulatory-Challenges-to-Job-Growth-and -Global-Competitiveness--Testimony-by-Drew-Greenblatt--President-and-Owner -of-Marlin-Steel-Wire--on-Behalf-of-the-NAM/. 5. United States Small Business Friendliness Survey, https://www.thumbtack .com/survey#/2016/1/states. 6. R. Litan, “Startup Slowdown,” Foreign Affairs, January–February 2015, http:// www.foreignaffairs.com/articles/142498/robert-litan/start-up-slowdown. 7. Ewing Marion Kauffman Foundation, “The Importance of Young Firms for Economic Growth,” Entrepreneurship Policy Digest, September 25, 2014, http:// www.kauffman.org /~/media /kauffman_org /resources /2014/entrepreneurship%20 policy%20digest /september%202014/entrepreneurship_policy_digest_september 2014.pdf. 8. A. Kim, “Excessive Regulation Hurts America’s Entrepreneurs,” The Daily Signal, May 13, 2015, http://dailysignal.com/2015/05/13/excessive-regulation-hurts -americas-entrepreneurs/. 9. I. Wladawsky-Berger, “Entrepreneurship and Job Creation,” November 5, 2014, http://blog.irvingwb.com/blog/2014/11/entrepreneurship-and-the-soul-of-the -american-economy.html. 10. W. Crews, “Ten Thousand Commandments,” Competitiveness Enterprise Institute, 2014, http://cei.org/sites/default/files/ Wayne%20Crews%20-%20Ten%20 Thousand%20Commandments%202014.pdf. 235

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11. National Small Business Association (NSBA), Small Business Regulations Survey, 2017, http://www.nsba.biz/wp-content/uploads/2017/01/Regulatory-Survey -2017.pdf. 12. Wladawsky-Berger, “Entrepreneurship and Job Creation.” 13. M. Kravis, “What’s Killing Jobs and Stalling the Economy,” Wall Street Journal, June 3, 2016, http://www.wsj.com/articles/whats-killing-jobs-and-stalling-the -economy-1464992963. 14. W. Crain and N. Crain. The Cost of Federal Regulation to the U.S. Economy, Manufacturing and Small Business, September 10, 2014, http://www.nam.org/Data -and-Reports/Cost-of-Federal-Regulations/Federal-Regulation-Full-Study.pdf. 15. Ibid. 16. J. Ortmans, “The Decline in Business Formation: Implications for Entrepreneurship and the Economy,” Testimony before the Subcommittee on Contracting and Workforce, Committee on Small Business, U.S. House of Representatives, September 11, 2014, https://www.gpo.gov/fdsys/pkg/CHRG-113hhrg89676/pdf/ CHRG-113hhrg89676.pdf. 17. “The Vanishing Entrepreneur, Crushed by Red Tape and Regulations,” Washington Times, 2014, http://www.washingtontimes.com/news/2014/may/9/editorial -the-vanishing-entrepreneur/. 18. Crews, “Ten Thousand Commandments.” 19. N. Goldschlag and A. Tabarrok, “Is Entrepreneurship in Decline?,” Working Paper, 2016, George Mason University, https://mason.gmu.edu/~atabarro/Is%20 Entrepreneurship%20in%20Decline.pdf. 20. Author’s calculations from NFIB Small Business Economic Trends data, http://www.nfib.com/surveys/small-business-economic-trends/. 21. Kravis, “What’s Killing Jobs.” 22. Goldschlag and Tabarrok, “Is Entrepreneurship in Decline?” 23. Ibid. 24. R. Decker, J. Haltiwanger, R. Jarmin, and J. Miranda, “The Role of Entrepreneurship in U.S. Job Creation and Economic Dynamism,” Journal of Economic Perspectives 28, no. 3 (2014): 3 –24. 25. Ibid. 26. Goldschlag and Tabarrok, “Is Entrepreneurship in Decline?” 27. B. Heim and I. Lurie, “Did Reform of the Non-Group Health Insurance Market Affect the Decision to Be Self-Employed? Evidence from State Reforms in the 1990s,” Health Economics 23 (2014): 841– 860.

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Chapter 8. High Taxes Are Not the Cause 1. T. Kane, “The Collapse of Startups in Job Creation,” Economic Policy Briefing Paper, Hudson Institute. September 2012, http://www.hudson.org/content/ researchattachments /attachment /1067/kane--thecollapseofstartupsinjobcreation 0912web.pdf. 2. J. Dearie, Testimony before the Subcommittee on Contracting and Workforce, Committee on Small Business, U.S. House of Representatives, September 11, 2014, https://smallbusiness.house.gov/uploadedfiles/9-11-2014_dearie_testimony.pdf. 3. A. Kim, “Economic Freedom: America’s Entrepreneurial Pulse at Risk,” The Daily Signal, April 1, 2014, http://dailysignal.com//2014/04/01/economic-freedom -americas-entrepreneurial-pulse-risk/. 4. Susan C. Nelson, “Tax Policy and Sole Proprietorships: A Closer Look,” National Tax Journal 61 (2008): 421– 433. 5. D. Bruce and J. Deskins, “Can State Tax Policies Be Used to Promote Entrepreneurial Activity?,” Small Business Economics 38, no. 4 (2012): 375 –397; D. Bruce and M. Mohsin, “Tax Policy and Entrepreneurship: New Time Series Evidence,” Small Business Economics 26 (2006): 409 – 425. 6. D. Bruce, J. Deskins, and M. Mohsin, “State Tax Policies and Entrepreneurial Activity: A Panel Data Analysis,” National Tax Association Proceedings 96 (2003): 325 –335; J. Cullen and R. Gordon, “Taxes and Entrepreneurial Risk Taking: Theory and Evidence for the U.S.,” Journal of Public Economics 91, nos. 7/8 (2007): 1479 –1505; S. Parker and M. Robson, “Explaining International Variations in SelfEmployment: Evidence from a Panel of OECD Countries,” Southern Economic Journal 71 (2004): 287–301. 7. D. Bruce and T. Gurley, “Taxes and Entrepreneurial Entry: An Empirical Investigation Using Longitudinal Tax Return Data,” Annual Conference on Taxation and Minutes of the Annual Meeting of the National Tax Association 97 (2004): 336 –343. 8. Bruce and Deskins, “Can State Tax Policies Be Used to Promote Entrepreneurial Activity?” 9. Parker and Robson, “Explaining International Variations in Self-Employment”; R. Torrini, “Cross-Country Differences in Self-Employment Rates: The Role of Institutions,” Labor Economics 12, no. 5 (2005): 661– 683; D. Blau, “A Time-Series Analysis of Self-Employment in the United States,” Journal of Political Economy 95, no. 3 (1987): 445 – 467; W. Gentry and R. Hubbard, “Tax Policy and Entrepreneurial Entry,” American Economic Review Papers and Proceedings 90, no. 2 (2000):

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283 –287; M. Robson and C. Wren, “Marginal and Average Tax Rates and the Incentive for Self-Employment,” Southern Economic Journal 65, no. 4 (1999): 757–773; Y. Georgellis and H. Wall, “Entrepreneurship and the Policy Environment,” Federal Reserve Bank of St. Louis Review 88, no. 2 (2006): 95 –111. 10. J. Long, “The Income Tax and Self-Employment,” National Tax Journal 35, no. 1 (1982): 31– 42. 11. Cullen and Gordon, “Taxes and Entrepreneurial Risk Taking.” 12. Bruce, Deskins, and Mohsin, “State Tax Policies and Entrepreneurial Activity”; Bruce and Mohsin, “Tax Policy and Entrepreneurship.” 13. M. Baliamoune-Lutz and P. Garello, “Tax Structure and Entrepreneurship,” Small Business Economics 42, no. 1 (2014): 165 –190. 14. R. Decker, J. Haltiwanger, R. Jarmin, and J. Miranda, “The Role of Entrepreneurship in U.S. Job Creation and Economic Dynamism,” Journal of Economic Perspectives 28, no. 3 (2014): 3 –24. 15. J. Pethokoukis, “Where Are All the Startups? A Q&A with Ian Hathaway on the Decline of US Entrepreneurship,” AEI Ideas, October 8, 2014, https://www.aei .org/publication/startups-qa-ian-hathaway-decline-us-entrepreneurship/. Chapter 9. It’s Not a Lack of Immigration 1. Ewing Marion Kauffman Foundation, “The Economic Case for Welcoming Immigrant Entrepreneurs,” Economic Policy Institute, March 27, 2015, http:// www.kauffman.org /what-we-do/resources /entrepreneurship-policy-digest /the -economic-case-for-welcoming-immigrant-entrepreneurs. 2. I. Hathaway and R. Litan, “What’s Driving the Decline in the Firm Formation Rate? A Partial Explanation,” Economic Studies at Brookings, November 2014, http:// www.brookings.edu /~/media /research /files /papers /2014/11/driving-decline -firm -formation-rate-hathaway-litan /driving_decline_firm_formation_rate_hathaway _litan.pdf. 3. R. Litan, “Startup Slowdown: How the United States Can Regain Its Entrepreneurial Edge,” Foreign Affairs, January–February 2005, http://www.foreignaffairs .com/articles/142498/robert-litan/start-up-slowdown. 4. Ibid. 5. J. Dearie, Testimony before the Subcommittee on Contracting and Workforce, Committee on Small Business, U.S. House of Representatives, September 11, 2014, http://smallbusiness.house.gov/uploadedfiles/9-11-2014_dearie_testimony.pdf.

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6. J. Ortmans, “The Decline in Business Formation: Implications for Entrepreneurship and the Economy,” Testimony before the Subcommittee on Contracting and Workforce, Committee on Small Business, U.S. House of Representatives, September 11, 2014, http://www.kauffman.org/~/media/kauffman_org/research% 20 reports%20and%20covers /2014/09/jonathan_ortmans_testimony_september _2014.pdf. 7. Litan, “Startup Slowdown.” 8. A. Singer, “Contemporary Immigrant Gateways in Historical Perspective,” Dædalus 142, no. 3 (2013): 76 –91. 9. Ortmans, “Decline in Business Formation.” 10. S. Camarota, “Immigrants in the United States: A Profile of America’s Foreign-Born Population,” Center for Immigration Studies, 2012, p. 3, http://cis.org/ sites/cis.org/files/articles/2012/immigrants-in-the-united-states-2012.pdf. 11. R. Fairlie, “Immigrant Entrepreneurs and Small Business Owners, and Their Access to Financial Capital,” report for the Office of Advocacy, U.S. Small Business Administration, under contract no. SBAHQ-10-R-0009, May 2012, https://www .sba.gov/sites/default/files/advocacy/rs396tot.pdf. 12. Ibid. 13. Camarota, “Immigrants in the United States.” 14. Ibid. 15. Author’s calculations from Startup Chile data, http://www.startupchile.org/, and U.S. Census data, https://www.census.gov/ces/dataproducts/bds/. 16. Author’s calculations from U.S. Census data, https://www.census.gov/news room/releases/archives/business_ownership/cb12-tps80.html. Chapter 10. An Aging Population Isn’t the Reason 1. D. Kinkade, “Vanishing Act: The Decline of American Entrepreneurship,” Above the Fold, June 2, 2014, https://www.uschamber.com/blog/vanishing-act -decline-american-entrepreneurship. 2. J. Liang, J. Wang, and E. Lazear, “Demographics and Entrepreneurship,” NBER Working Paper, No. 20506, 2014, http://www.nber.org/papers/w20506. 3. D. Stangler and J. Bell-Masterson, “Can Millennials Reverse America’s Declining Rates of Entrepreneurship?,” Washington Monthly, August 17, 2014, http:// washingtonmonthly.com /2014/08/17/can-millennials-reverse-americas-declining -rates-of-entrepreneurship/.

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4. Liang, Wang, and Lazear, “Demographics and Entrepreneurship.” 5. L. Buchanan, “American Entrepreneurship Is Actually Vanishing: Here’s Why,” Inc., May 2015, http://www.inc.com/magazine/201505/leigh-buchanan/the -vanishing-startups-in-decline.html. 6. B. Casselman, “The Slow Death of American Entrepreneurship,” Fivethirtyeight, May 15, 2014, http://fivethirtyeight.com/features/the-slow-death-of-american -entrepreneurship/. 7. I. Hathaway and R. Litan, “What’s Driving the Decline in the Firm Formation Rate? A Partial Explanation,” Economic Studies at Brookings, November 2014, http:// www.brookings.edu /~/media /research /files /papers /2014/11/driving-decline-firm -formation-rate-hathaway-litan /driving_decline_firm_formation_rate_hathaway_ litan.pdf. 8. Casselman, “Slow Death of American Entrepreneurship.” 9. Liang, Wang, and Lazear, “Demographics and Entrepreneurship.” 10. R. Simon and C. Barr, “Endangered Species: Young U.S. Entrepreneurs,” Wall Street Journal, January 2, 2015, http://www.wsj.com/articles/endangered -species-young-u-s-entrepreneurs-1420246116?autologin=y. 11. E. Reedy and A. Morelix, “Student Debt and the Millennial Entrepreneurship Paradox,” Forbes, September 15, 2014, http://www.forbes.com/sites/ kauffman /2014/09/15/student-debt-and-the-millennial-entrepreneurship-paradox / #3bae1b7b2f70. 12. F. Karahan, B. Pugsley, and A. Sahin, “Understanding the 30-Year Decline in the Startup Rate: A General Equilibrium Approach,” Federal Reserve Bank of New York Working Paper, May 2015, http://www.hec.ca/iea/chaires_groupes_recherche/ macromontreal /conferences/20150602_Aysegul_Sahin.pdf. Chapter 11. Slowing Population Growth Isn’t the Explanation 1. F. Karahan, B. Pugsley, and A. Sahin, “Understanding the 30-Year Decline in the Startup Rate: A General Equilibrium Approach,” Federal Reserve Bank of New York Working Paper, May 2015, http://www.hec.ca/iea/chaires_groupes_recherche/ macromontreal /conferences/20150602_Aysegul_Sahin.pdf. 2. J. Pethokoukis, “Where Are All the Startups? A Q&A with Ian Hathaway on the Decline of US Entrepreneurship,” AEI Ideas, October 8, 2014, https://www.aei .org/publication/startups-qa-ian-hathaway-decline-us-entrepreneurship/; L. Buchanan, “American Entrepreneurship Is Actually Vanishing: Here’s Why,” Inc.,

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May 2015, http://www.inc.com/magazine/201505/leigh-buchanan/the-vanishing -startups-in-decline.html. 3. J. Hotchkiss, “Employment Growth and Labor Force Participation: How Many Jobs Are Enough?,” Federal Reserve Bank of Atlanta, Economic Review, First Quarter, 2005, https://www.frbatlanta.org/-/media/Documents/filelegacydocs/ HOTCHKISSfinal.pdf. 4. Karahan, Pugsley, and Sahin, “Understanding the 30-Year Decline.” 5. I. Hathaway and R. Litan, “What’s Driving the Decline in the Firm Formation Rate? A Partial Explanation,” Economic Studies at Brookings, November 2014, http:// www.brookings.edu /~/media /research /files /papers /2014/11/driving-decline-firm -formation-rate-hathaway-litan /driving_decline_firm_formation_rate_hathaway_ litan.pdf. 6. Author’s calculations from Bureau of Labor Statistics data, https://www.bls .gov/, and U.S. Census data, https://www.census.gov/ces/dataproducts/bds/. 7. Author’s calculations from Bureau of Labor Statistics data, https://www.bls .gov/, and U.S. Census data, https://www.census.gov/ces/dataproducts/bds/. Chapter 12. Rising Student Debt Is Not the Cause 1. S. Denning, “Why U.S. Entrepreneurship Is Dying,” Forbes, May 27, 2016, http://www.forbes.com /sites /stevedenning /2016/05/27/why-us-entrepreneurship -is-dying/#6c6db97440ab. 2. M. Daniels, “How Student Debt Harms the Economy,” Wall Street Journal, January 27, 2015, http://www.wsj.com/articles/mitchell-e-daniels-how-student-debt -harms-the-economy-1422401693. 3. J. Rosenberg, “Student Loan Debt Delays Startup Plans of Grads,” Detroit News, June 12, 2016, http://www.detroitnews.com/story/business/personal-finance/ 2016/06/12/student-loan-debt-delays-startup-plans-grads/85800204/. 4. S. Denning, “Entrepreneurship, Student Debt, and the Presidential Election,” Forbes, May 29, 2016, http://www.forbes.com/sites/stevedenning/2016/05/29/entre preneurship-student-debt-and-the-presidential-election/#35f918d442e8. 5. Denning, “Why U.S. Entrepreneurship Is Dying.” 6. G. Reader, “Bill Clinton Says Student Debt Is Holding Back Potential Entrepreneurs,” Entrepreneur, June 14, 2016, https://www.entrepreneur.com/article/ 277527. 7. The White House, the President’s Council on Jobs and Competitiveness, “Taking Action, Building Confidence: Five Common Sense Initiatives to Boost

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Jobs and Competitiveness,” October, 2011, http://files.jobs-council.com /jobs council /files/2011/10/JobsCouncil_InterimReport_Oct11.pdf. 8. Gallup Organization, The Gallup-Purdue Index Report, September 25, 2015, http://www.gallup.com/services/185924/gallup-purdue-index-2015-report.aspx. 9. George and Co., “Polls Show How Student Debt Affects Small Business Entrepreneurship,” February 2, 2016, https://www.1888pressrelease.com/polls-shows -how-student-debt-affects-small-business-entrepre-pr-582473.html. 10. B. Headd, “Student Debt among Young Entrepreneurs,” Small Business Facts, November 2014, https://www.sba.gov/sites/default/files/Student%20Debt%20 Among%20Young%20Entrepreneurs%20Nov%202014.pdf. 11. K. Krishnan, and P. Wang, “The Cost of Financing Education: Can Student Debt Hinder Entrepreneurship,” Working Paper, 2015, Northeastern University, http://papers.ssrn.com/sol3/papers.cfm?abstract_id=2586378. 12. B. Ambrose, L. Cordell, and S. Ma, “The Impact of Student Load Debt on Small Business Formation,” Federal Reserve Bank of Philadelphia Working Paper, No. 15 –26, https://www.philadelphiafed.org/-/media/research-and-data/publications/ working -papers/2015/wp15 –26.pdf. 13. S. Baum, “Does Increasing Reliance on Student Debt Explain Declines in Entrepreneurial Activity?,” Research Report, Urban Institute, 2015, http://www .urban.org /sites /default /files /alfresco/publication-pdfs /2000080-Does-Increasing -Reliance-on-Student-Debt-Explain-Declines-in-Entrepreneurial-Activity.pdf. 14. Author’s calculations from College Board data, https://trends.collegeboard .org/student-aid, and U.S. Census data, https://www.census.gov/ces/dataproducts/ bds/. 15. C. Schoenberger, “Want To Be an Entrepreneur? Beware of Student Debt,” Wall Street Journal, May 26, 2015, http://www.wsj.com/articles/want-to-be-an -entrepreneur-beware-of-student-debt-1432318500. Chapter 13. Don’t Blame a Loss of Moxie 1. D. Stangler, “The Looming Entrepreneurial Boom: How Policy Makers Can Renew Startup Growth,” Ewing Marion Kauffman Foundation: New Entrepreneurial Growth Agenda, 2017, http://www.kauffman.org/neg/neg-intro. 2. L. Buchanan, “American Entrepreneurship Is Actually Vanishing: Here’s Why,” Inc., May 2015, http://www.inc.com/magazine/201505/leigh-buchanan/the -vanishing-startups-in-decline.html. 3. Ibid.

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4. R. Litan and I. Hathaway, “Declining Business Dynamism in the United States: A Look at States and Metros,” Economic Studies at Brookings, May 2014, http://www .brookings.edu/research/papers/2014/05/declining-business-dynamism-litan 5. Author’s calculations from Gallup/ Wells Fargo Small Business Index data, https://wellsfargoworks.com/insights/small_business_index.php. 6. Gallup poll conducted June 1–5, 2016, http://www.gallup.com/poll /1597/ confidence-institutions.aspx. 7. B. Casselman, “Risk Averse Culture Affects U.S. Workers, Entrepreneurs,” Wall Street Journal, June 2, 2013, http://www.wsj.com/articles/SB1000142412788732 4031404578481162903760052. 8. Author’s calculations from Survey of Consumer Finances data, https://www .federalreserve.gov/econres/scfindex.htm. 9. European Commission, “Entrepreneurship in the EU and Beyond,” Flash Eurobarometer 354, 2012, http://ec.europa.eu/public_opinion/flash/fl_354_en.pdf. Chapter 14. Employees Have Become Too Expensive 1. Author’s calculation from Kaiser Family Foundation data, http://www.kff.org/ health-costs/report/2016-employer-health-benefits-survey/, and IRS Statistics of Income data, https://www.irs.gov/uac/soi-tax-stats-statistics-of-income. 2. Author’s calculation from Kaiser Family Foundation data, http://www.kff .org/health-costs/report/2016-employer-health-benefits-survey/. 3. Author’s calculation from Kaiser Family Foundation data, http://www.kff .org/health-costs/report/2016-employer-health-benefits-survey/. 4. J. Dearie and C. Geduldig, Where the Jobs Are: Entrepreneurship and the Soul of the American Economy, Hoboken, NJ: Wiley, 2003. 5. J. Dearie, Testimony before the Subcommittee on Contracting and Workforce, Committee on Small Business, U.S. House of Representatives, September 11, 2014, https://smallbusiness.house.gov/uploadedfiles/9-11-2014_dearie_testimony. 6. D. Stangler and J. Bell-Masterson, “Can Millennials Reverse America’s Declining Rates of Entrepreneurship?,” Washington Monthly, August 17, 2014, http:// www.washingtonmonthly.com/ten-miles square/2014/08/can_millennials_reverse _americ051694.php. 7. B. Pugsley and A. Sahin, “Grown-Up Business Cycles,” Federal Reserve Bank of New York Staff Reports, No. 707, December 2014, https://www.newyorkfed.org/ medialibrary/media/research/staff_reports/sr707.pdf.

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Chapter 15. Chains Have Replaced Independent Employers 1. L. Buchanan, “American Entrepreneurship Is Actually Vanishing: Here’s Why,” Inc., May 2015, https://www.inc.com/magazine/201505/leigh-buchanan/ the-vanishing-startups-in-decline.html. 2. Author’s calculations from U.S. Census data, https://www.census.gov/ces/ dataproducts/bds/. 3. Author’s calculations from U.S. Census data, https://www.census.gov/econ/. Chapter 16. The Story the Data Are Telling 1. Author’s calculations from U.S. Census data, https://www.census.gov/econ/. 2. Author’s calculations from U.S. Census data, https://www.census.gov/econ/ nonemployer/.

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Index

Numbers in italics indicate figures. acquisitions, 211–212 Affordable Care Act, 117, 120, 190 –191, 227 age, risk aversion and, 176 aging, entrepreneurship and, 145 –152 Ambrose, Brent, 166, 172 –173 American entrepreneurialism, 1, 4 – 6, 216 Angel Capital Association, 72 Bain Capital, 212 banks, financing by, 96 –98 Baum, Sandy, 167 BDS. See Business Dynamics Statistics benefits for employees, costs of, 187–194, 203, 219, 227 big businesses: bank lending to, 96 –97; employment trends in, 87– 88; talent for, 200; wages paid by, 194 –195 Bilamoune-Lutz, Mina, 129 Brin, Sergey, 1 Bruce, Donald, 127, 128 Burton, David, 1, 4 –5, 108 business acquisitions, 211–212 business activity, family income from, 57–58

business angels, 65 – 66, 69 –70, 72 –73, 220 –221 business deaths, outpacing business births, 17 Business Dynamics Statistics (U.S. Census Bureau), 25 –26 business dynamism, 92 –93 business equity, families’ ownership of, 39 business failures, rates of, 9, 34 business income, nonreported, 126 business ownership, earnings from, 50 –54 Camarota, Steven, 138, 139 –140 capital, access to, 95 –102, 163 –164, 169, 221 capital investment: entrepreneurship and, 3 – 4; spending on, 90 –91 Casselman, Ben, 17, 148 –149 C corporations, 21, 45, 46, 51 Center for Venture Research (University of New Hampshire), 69 chain businesses: adding workers, 200; employer startups and, 207; replacing independent companies,

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INDEX

chain businesses (continued) 205 –206; rise of, 14, 205 –215, 220; shift to, 200; technology and, 210 –211 Challenger, Gray and Christmas, 8, 23 –25 Chile, encouraging foreign entrepreneurship, 134 Clifton, Jim, 17 commercial banking, changes in, 96 –98 community banks, 97 compensation: hourly, 188; shifts in, 219 compliance: costs of, 110 –111; learning curve for, 110, 115 Cooley, LLP, 76 Cordell, Larry, 166, 172 –173 Crain, Mark, 111 Crain, Nicole, 111 credit, access to, small business creation and, 11. See also capital credit card debt, availability of, 101 Cullen, Julie Berry, 128 Current Population Survey (BLS and Census Bureau), 18, 39 CVR. See Center for Venture Research Daniels, Mitch, 163 Dearie, John R., 30, 99, 123 –124, 127, 134 –135, 200 Decker, Ryan, 63 – 64, 70, 85 – 86, 118 –119, 130 deleveraging, 103 Denning, Steve, 163, 164 Deskins, John, 127 Dodd-Frank legislation, 117

economic mobility, new businesses and, 2 –3 economy, carrying capacity of, 36, 38 e-corp tax status, 124 efficiency, 4 employer businesses: capital expenditures of, 90 –91; decline in, 26 –28, 79 – 83, 85 – 86, 90; economic impact of, 90 –91; entrepreneurial activity by, 225; failures of, 34 –37; formation rates of, 33 –37; initial size of, 85 – 86; numbers of employees in, 83 – 88; per capita number of, 27, 32 –34, 37–38; productivity and, 90, 92; stock of, 34, 37–38, 79 – 83, 105, 219 –220; tracking of, 25 –26. See also employer creation; employer startups employer creation: downturn in, 4 – 6, 12; effects of, 6; pace of, 10; significance of, 6. See also employer businesses; employer startups employer startups, 8; aging populations and, 145 –152; boosting, 214; capital access and, 95, 100 –102; chain businesses and, 207; downward trend in, 129 –130; generic decline in, 213; immigration and, 133 –146; per capita rate of, 156, 157; population growth and, 153 –162; regulation and, 116 –119; risk aversion and, 176 –178, 181–182; size of, 200, 209; slowdown in, policy responses to, 216 –217, 220 –223; student debt levels and, 163 –175; talent for, 200 endogeneity bias, 127 entrepreneurial businesses, stocks and flows of, 31–33

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INDEX

entrepreneurial income, 58 –59 entrepreneurs, financial position of, 54 –57 entrepreneurs, offering health insurance, 189 –190 entrepreneurship: aging populations and, 145 –152; Americans’ attitude toward, 1, 177–180, 216; changes in, 217–221, 227; decline in, concern about, 2 – 4, 17–18; as fraction of income, 57– 61; immigrants and, 134, 137–140; intention of, 181, 183 –184, 185; legal form of, 218 (see also C corporations; partnerships; S corporations; sole proprietorships); measures of, 5, 31; personal equity and, 59 – 60; population growth and, 155 –162; profitability of, 114, 159 –160; rate of, 26 –27, 36 –37; regulation and, 108 –121; rising indicators of, 40 – 48, 136, 150 –151, 160; in slow-growth countries, 149; social mobility and, 2 –3; spread across more businesses, 14; student debt and, 163 –175; taxation and, 123 –132; technology and, 197; transformational, 64; unincorporated self-employment as measure of, 18, 20; young people and, 183 –184, 185 establishments, new, rise of, 207–208 exit performance, for venture capitalbacked companies, 73 –75 failure, fear of, 178 –179, 182. See also risk aversion Fairlie, Rob, 39, 138 –139, 202 families, business ownership of, 39

Federal Financial Institutions Examination Council, 97 Federal Register, size of, 112 –113, 117 Federal Reserve, 38 FFIEC. See Federal Financial Institutions Examination Council flows, vs. stocks, 31–33 Garello, Pierre, 129 Gates, Bill, 1 Geduldig, Courtney, 30, 200 Gladwell, Malcolm, 1 Global Entrepreneurship Monitor, 36 –37, 148, 149 Goldschlag, Nathan, 115 –119 Gordon, Roger, 128 government action, call for, 30 –31 Great Recession, 17, 51, 53 Greenblatt, Drew, 108, 111 Gurley, Tami, 127 Haltiwanger, John, 25, 93 Harrison, J. D., 17 Hathaway, Ian, 26 –28, 30, 33, 37, 132, 134, 149, 156, 177, 178 health insurance, regulation of, 120 –121. See also Affordable Care Act health insurance for employees: cost of, 187, 189 –192; reductions in, 193. See also benefits for employees Heim, Bradley, 121 high-potential businesses, 5, 9, 50, 63, 220 –221; growth rate of, 63 – 64; investment in, 64 –72, 106; measurement problems with, 66 – 67; performance of, 73 –75; valuation of, 75 –77

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INDEX

households (U.S.), financial position of, 38 –39 immigrants: attracting of, programs for, 141–142; entrepreneurship of, 134, 137–140; non-employer businesses and, 136, 139 –140 immigration, 222 –223; employer creation and, 10; employer startups and, 133 –146 income: entrepreneurial fraction of, 57– 61; inequality of, 226 incorporated self-employment, 21–23, 197, 218. See also self-employment independent contractors, 20, 42; labor costs and, 198 –199 innovation: entrepreneurship and, 4 (see also technology); productivity and, 4; slowdown in, 91–92 Internal Revenue Service, as data source, 41– 43, 51, 53 Internet bubble, 67–71, 74 Jackson, Shirley Ann, 164 job creation, decline in, 227 job lock, 120 Jobs, Steve, 1 job seekers, desiring to start businesses, 23 –25 Kane, Tim, 108, 123, 124, 127 Karahan, Fatih, 155 –156 Kauffman (Ewing Marion) Foundation, 133, 146 Kauffman Index of Entrepreneurial Activity (Ewing Marion Kauffman Foundation), 39, 105 –106 Kelley, Donna, 177–178

Khan, Lina, 95, 98 Kim, Anthony, 125, 127 Kravis, Marie-Josée, 110, 117 Krishnan, Karthik, 166, 172 –173 labor, costs of, 187–199, 204, 219, 227 labor force participation rate, 157–159, 224 laid-off workers, starting companies, 7– 8 Lazear, Ed, 147–148, 149 Liang, James, 147–148, 149 licensing, state requirements for, 110 Litan, Robert, 26 –28, 30, 33, 37, 134, 135, 149, 156, 178, 207 Long, James, 128 Lowrey, Annie, 17–18 Lurie, Ithai, 121 Lynn, Barry, 95, 98 Ma, Shuwei, 166 mergers, 212 micro businesses, student debt and, 166, 173 Morelix, Arnobio, 163 –164 National Opinion Research Center (NORC; University of Chicago), 38 National Venture Capital Association (NVCA), 67 Nelson, Susan, 126 net worth, 56 –57; employer startups and, 105 new businesses: employment in, 8, 84 – 86; failure rates of, 37; financing for, 95 –96, 100 –105; formation of, 2 – 4 (see also employer creation); health insurance benefits and, 190 –191, 194;

248

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INDEX

productivity and, 93; regulation and, 108 –121; size of, 209; talent available for, 200; taxation and, 124 –132. See also employer startups; non-employer businesses non-employer businesses, 226: capital expenditures of, 90 –91; economic impact of, 90 –91; growth of, 40 – 41; immigrants and, 136, 139 –140; increase in, 13 –14, 31; innovation and, 91–92; per capita number of, 41; regulation and, 113 –114; sales of, 90, 225; shift to, 80 – 81, 113 –114, 225 –226; stock of, 79 – 83 non-employers, entrepreneurial activity by, 225 nonfarm loans, 98 nonresidential loans, 98 NORC. See National Opinion Research Center NVCA. See National Venture Capital Association Obama administration, 164 Ohanian, Lee, 90 opportunity costs, 202 Ortmans, Jonathan, 135, 139 outsourcing, 187 partnerships, 42 – 46, 82; income of, 53 pass-through entities, 82; income of, 51–54, 191; profitability of, 114; rise in, 42 – 45. See also partnerships; S corporations; sole proprietorships patents, slowdown in, from small businesses, 91–92 Pe’er, Avid, 36

personal savings rate, employer startups and, 103 –104, 221. See also savings Pew Foundation, 22 –23 Piketty, Thomas, 58 population, aging of, and employer startups, 145 –152, 224 population growth, employer startups and, 153 –162, 224 Prescott, Edward, 90 productivity: chain businesses and, 210; entrepreneurship and, 3 – 4; growth rate and, 90, 92 –93; innovation and, 4 profitability, increases in, 51–54, 114 Puente, Lucas, 108 –109 Pugsley, Benjamin, 155 –156 regulation, 10, 108 –121, 222; business failure and, 115; business-friendly, 120 –121; complexity of, 111, 112; differing regimes for, 118 –119; employer startups and, 116 –119; profitability and, 114 regulation hypothesis, 109 –110 retail, employment decline in, 85 retirement plans, costs of, 192 risk aversion: age and, 176; Americans’, 177–178, 181–182; changes in, 176; employer startups and, 176 –178, 181–182, 224; student debt and, 170 –172 Romney, Mitt, 212 Saez, Emmanuel, 58 Sahin, Aysegul, 155 –156 savings: business startups and, 163 –164; decline in, 95; entrepreneurship and, 103 –105; risk and, 182

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INDEX

S corporations, 21, 42 – 45, 46, 51– 54, 82 seasonal workers, 23 seed round financing, 76 self-employment: financial position and, 55 –57; meanings of, 20 –21; part-time, 19 –20; percentage of population transitioning to, 39, 40; significance of, 18; student debt and, 165 –166; tax deduction for, 41– 42, 43; taxation and, 127–128. See also incorporated self-employment; unincorporated self-employment self-employment taxes, 48, 106 Sequoia Capital, 65 Series A financings, 76 services, employment decline in, 85 Singer, Audrey, 137 slow-growth countries, entrepreneurship in, 149 Small Business Administration, Office of Advocacy, 80 small businesses: Americans’ attitude toward, 180 –181; attracting labor, 219; bank lending to, 96 –98; borrowing by, 100 –101; employment trends in, 86 – 89; health insurance benefits and, 190 –191, 193; organization of, 51 (see also C corporations; partnerships; pass-through entities; S corporations; sole proprietorships); owners’ satisfaction and, 179; profitability of, 160; regulation and, 109 –116, 118; revenues of, 90; as share of annual payroll, 195; success of, 14 –15; talent available for, 201; trade receivables for, 102; wages paid by, 194 –195, 198

small business loans, availability of, 100 –101 sole proprietorships, 42 – 45, 82; hiring by, 195 –199; income for, underreporting of, 126; labor spending by, 195 –199; prevalence of, 192; profit margins of, 53 –54; as proxies for small business, 53 Stangler, Dane, 17, 134, 176 Start-Up Chile, 134, 141 startup companies, 147–148. See also employer startups; high-potential businesses; small businesses startup deficit, 85 – 86 start-up visa program, 141–142 stocks, vs. flows, 31–33 student debt, 10; employer startups and, 163 –175, 223 –224; rising entrepreneurship and, 168 –169; selfemployment and, 165 –166 Subchapter S corporations. See S corporations Survey of Consumer Finances (Federal Reserve), 38 –39, 55, 57–58, 60 Tabarrok, Alexander, 115 –119 talent, access to, 199 –201 taxation, 10, 43, 44, 222; avoidance, 125 –127; downward trend in, 129 –130; effects of, on business, 125; employer creation and, 11; entrepreneurship and, 123 –132; negative view of, 125; new businesses and, 124 –132; self-employment and, 127–128 tax gap, 126 technology: chain businesses and, 205, 206, 210 –211; effect of, on entrepreneurship, 197; entrepreneurship and,

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Vertinsky, Ilan, 36 visas, encouraging business startups, 10

12 –14; rise in, 187; small business growth and, 15 Thiel, Peter, 65 Tocqueville, Alexis de, 1 trade credit, 102 turnover, 4

wages: falling, 194; gap in, 194 –195; stagnation of, 95 Wang, Hui, 147–148, 149 Wang, Pinshuo, 166, 172 –173 Where the Jobs Are (Dearie and Geduldig), 30, 200

unincorporated self-employment, 7, 18 –23, 197, 218 United States, industrial composition of, 212 –213 U.S. Census Bureau, 5, 25

Yellen, Janet, 2 young people, entrepreneurship and, 183 –184, 185

venture capitalists (VCs), 65 –75, 220 –221

Zuckerberg, Mark, 1

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