2015 United States Report - babson.edu USA 2015...The GEM 2015 United States Report ... GEM Activity Across Phases ... in the United States Adult Population ...

Donna J. Kelley, Abdul Ali, Candida Brush, Andrew C. Corbett, Caroline Daniels, Phillip H. Kim, Thomas S. Lyons, Mahdi Majbouri, Edward G. Rogoff

2015 United States ReportGLOBAL ENTREPRENEURSHIP MONITOR

© 2016 by Donna J. Kelley, Abdul Ali, Candida Brush, Andrew C. Corbett, Caroline Daniels, Phillip H. Kim, Thomas S. Lyons, Mahdi Majbouri, Edward G. Rogoff, Babson College and Baruch College.

Global Entrepreneurship Monitor 2015 United States Report

BABSON COLLEGEFounding and Sponsoring Institution

BARUCH COLLEGESponsoring Partner Institution

GLOBAL ENTERPRISE MONITOR 2015 TEAM

BABSON COLLEGE

Donna J. Kelley

Abdul Ali

Candida Brush

Marcia Cole

Andrew C. Corbett

Caroline Daniels

Phillip H. Kim

Mahdi Majbouri

BARUCH COLLEGE

Monica Dean

Thomas S. Lyons

Edward G. Rogoff

The authors are grateful to Marcia Cole, Monica Dean and Gil Gilead for invaluable assistance to the GEM United States Team

The Global Entrepreneurship Monitor and the authors thank the individuals in the United States who took the time to answer survey questions.

This report would not be possible without the Consortium of GEM National Teams who participated in 2015 Argentina, Austria, Australia, Barbados, Belgium, Botswana, Brazil, Burkina Faso, Cameroon, Canada, Chile, China, Colombia, Croatia, Colombia, Croatia, Ecuador, Egypt, Estonia, Finland, Germany, Greece, Guatemala, Hungary, India, Indonesia, Iran, Ireland, Israel, Italy, Japan, Kazakhstan, Latvia, Lebanon, Luxembourg, Macedonia, Malaysia, Mexico, Morocco, Netherlands, Norway, Panama, Peru, Philippines, Poland, Portugal, Puerto Rico, Romania, Senegal, Slovakia, Slovenia, South Africa, South Korea, Spain, Sweden, Switzerland Taiwan, Thailand, Tunisia, Turkey, United Kingdom, United States, Uruguay, Vietnam

Although GEM data were used in the preparation of this report, their interpretation and use are the sole responsibility of the authors.

© 2016 by Donna J. Kelley, Abdul Ali, Candida Brush, Andrew C. Corbett, Caroline Daniels, Phillip H. Kim, Thomas S. Lyons, Mahdi Majbouri, Edward G. Rogoff, Babson College and Baruch College.

Global Entrepreneurship Monitor 2015 United States Report

BABSON COLLEGEFounding and Sponsoring Institution

BARUCH COLLEGESponsoring Partner Institution

4

Table of Contents

EXECUTIVE SUMMARY ...................................................................................................9

Select Key Findings: GEM United States 2015 .............................................................9

Implications ............................................................................................................11

INTRODUCTION THE UNITED STATES ECONOMY IN 2015 .......................................12

Monetary and Fiscal Policies in 2014 ........................................................................13

The Fiscal Policy in 2015 .........................................................................................15

The GEM 2015 United States Report.........................................................................15

CHAPTER 1 UNITED STATES ENTREPRENEURIAL ACTIVITY ....................................16

GEM Activity Across Phases ......................................................................................16

Necessity-Based and Improvement-Driven Entrepreneurship ........................................17

Discontinuation .......................................................................................................18

Entrepreneurial Employee Activity .............................................................................19

Ethnicity .................................................................................................................19

Summary Comments ................................................................................................20

CHAPTER 2 SOCIAL ENTREPRENEURSHIP ...............................................................21


CHAPTER 3 AGE ....................................................................................................................25


CHAPTER 4 WOMEN’S ENTREPRENEURSHIP ...........................................................31

Attitudes about Entrepreneurship among Women in the United States ..........................33

Business Characteristics and Performance ..................................................................34

Established Business Activity, Discontinuance and Entrepreneurial Employee Activity ....36


CHAPTER 5 IMPACT CHARACTERISTICS OF ENTREPRENEURSHIP IN THE UNITED STATES: 2001–2015 ....................................................37

Industry Sector Participation .....................................................................................37

Job Expectations ......................................................................................................38

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Table of Contents

Innovation ...............................................................................................................39

Technology ..............................................................................................................40

Internationalization ..................................................................................................40


CHAPTER 6 FINANCING ENTREPRENEURSHIP ........................................................41


CHAPTER 7 ENTREPRENEURSHIP IN FIVE STATES ..................................................46

Entrepreneurial Activity ............................................................................................48

Entrepreneurial Attitudes ..........................................................................................49

Necessity- and Opportunity-Driven Entrepreneurship ...................................................49

Men and Women Entrepreneurs .................................................................................50

Entrepreneurship Rates by Age Group ........................................................................51

Entrepreneurship Rates by Education.........................................................................52

Innovation ...............................................................................................................52

Internationalization ..................................................................................................53

Finance ..................................................................................................................54

Longitudinal Analysis of Key GEM Indicators ..............................................................54


THE GLOBAL ENTREPRENEURSHIP MONITOR (GEM) .......................................... 60

SPONSORS ......................................................................................................... 60

ABOUT THE AUTHORS .................................................................................................61

CONTACTS ....................................................................................................................64

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LIST OF FIGURES

LIST OF FIGURES

Figure 1 Percentage Change in Real GDP from Previous Quarter

(seasonally adjusted annual rates) ........................................................................................ 12

Figure 2 National Unemployment Rate, seasonally adjusted, in % ........................................................ 13

Figure 3 Unemployment Rates by State, 2015 Annual Averages .......................................................... 14

Figure 4 Longitudinal Analysis of Nascent, New and Established Business Activity

in the United States Adult Population (18-64 year olds) (GEM 2005–2015) ............................ 16

Figure 5 Total Entrepreneurial Activity (TEA) Rates in the Adult Population

in 60 Economies (GEM 2015) ............................................................................................. 17

Figure 6 Longitudinal Analysis of the Proportion of Necessity-Driven Motives

among Total Entrepreneurial Activity (TEA) (GEM 2005–2015) .............................................. 17

Figure 7 Proportion of Discontinuation Due to Lack of Profits, Financing Problems

or Bureaucracy in 24 Innovation-Driven Economies (GEM 2015) ............................................ 18

Figure 8 Early-Stage Entrepreneurial Activity and Entrepreneurial Employee Activity

in 24 Innovation-Driven Economies (GEM 2015) ................................................................... 19

Figure 9 Ethnicity Breakdown of Total Early-Stage Entrepreneurial Activity

in the United States (GEM 2015) ........................................................................................ 19

Figure 10 Total Early-Stage Entrepreneurial Activity and Established Business Ownership

in the United States, Percentage of Adults in Each Ethnic Group (GEM 2015) ......................... 20

Figure 11 Male and Female Social Entrepreneurship Rates in the United States

Adult Population (GEM 2015) .............................................................................................. 22

Figure 12 Age Breakdown for Social Entrepreneurship Rates in the United States

Adult Population (GEM 2015) .............................................................................................. 22

Figure 13 Funding Sources for Social Enterprises (GEM 2015) .............................................................. 24

Figure 14 Age Distribution of Phases and Types of Entrepreneurial Activity in the

United States Adult Population (GEM 2015) ......................................................................... 25

Figure 15 Percentage of TEA with Necessity Motives by Age Group* (GEM 2015) .................................... 27

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LIST OF FIGURES

Figure 16 Entrepreneurial Attitudes and Affiliations in the United States

Working-Age Population (GEM 2015).................................................................................... 27

Figure 17 Gender Differences in TEA Rates by Age Group (GEM 2015) .................................................. 29

Figure 18 TEA Rates for Factor and Efficiency-Driven Economies,

by Region and Gender (GEM 2015) ...................................................................................... 31

Figure 19 TEA Rates for Innovation-Driven Economies,

by Region and Gender (GEM 2015) ...................................................................................... 32

Figure 20 Perceived Opportunities among Men and Women

in the United States (GEM 2001–2015) ............................................................................... 33

Figure 21 Industry Sector Distribution of Male and Female TEA Activity (GEM 2015) .............................. 34

Figure 22 New Product-Market Combinations by Gender (percentage of TEA) (GEM 2002–2015) ............. 35

Figure 23 Longitudinal Trends in Percentage of Total Entrepreneurial Activity

in Major Industrial Sectors (2001-2015) .............................................................................. 37

Figure 24 Longitudinal Trends in Percentage of Entrepreneurs Expecting to

Create 6+ Jobs in the Next Five Years (2001–2015) .............................................................. 38

Figure 25 Changes in Employee Count from Previous Year in

Established Business Owners (GEM 2015) ............................................................................ 38

Figure 26 Longitudinal Trends in Percentage of Total Entrepreneurial Activity and

New Business Ownership with New Product-Market Innovations (2002–2015) ......................... 39

Figure 27 Longitudinal Trends in Percentage of Total Entrepreneurial Activity Offering

Products or Services Based on New Technology (2002–2015) ................................................ 40

Figure 28 Sources of Funding for Entrepreneurs in the United States

(by percentage of entrepreneurs using each funding source), GEM 2015 .................................. 43

Figure 29 Sources of Funding by Gender for Entrepreneurs in the United States

(by percentage of entrepreneurs using each funding source) (GEM 2015) ................................ 43

Figure 30 Start-up Capital Requirements by Age Group for

Entrepreneurs in the United States (GEM 2015) .................................................................... 44

Figure 31 Sources of Venture Financing by Age of Entrepreneurs (GEM 2015) ........................................ 44

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LIST OF FIGURES

Figure 32 Phases of Business Activity in the United States and in Five States (GEM 2015) .....................48

Figure 33 Entrepreneurial Attitudes in the U.S. Working-Age Population:

United States and Five States (GEM 2015) ..........................................................................49

Figure 34 Percentage of Entrepreneurs with Opportunity Motives in the

United States and in Five States (GEM 2015) ......................................................................50

Figure 35 Total Entrepreneurial Activity Rates in the United States by Gender (GEM 2015) .....................50

Figure 36 Age Patterns in Total Entrepreneurial Activity in the

United States and in Five States (GEM 2015) ......................................................................51

Figure 37 Percentage of Entrepreneurs with a Post-Secondary Degree and with

Graduate Experience in the United States and in Five States (2015) ......................................52

Figure 38 Percentage of Total Entrepreneurial Activity with New Product-Market

Innovations in the United States and in Five States (GEM 2015)............................................53

Figure 39 Percentage of TEA and Established Business Owners with at Least 25%

International Customers in the United States and in Five States (GEM 2015) ..........................53

Figure 40 Start-up Funding Required and Amount of Own Funds Provided

in the United States and in Five States (GEM 2015) .............................................................54

Figure 41 Changes over Time in TEA and Intentions for the United States

and Five States (GEM 2012–2015) .....................................................................................55

Figure 42 Changes over Time in Attitudes (perceived opportunities and capabilities,

fear of failure) for the United States and Five States (GEM 2012–2015) ................................56

Figure 43 Changes over Time in Male and Female TEA Rates for the

United States and Five States (GEM 2012–2015) ................................................................56

Figure 44 Changes over Time in Internationalization Rates (percentage of TEA)

for the United States and Five States (GEM 2012–2015) ......................................................57

Figure 45 The GEM Model of Entrepreneurship Attitudes, Phases and Profile .........................................59

LIST OF TABLES

Table 1 Demographic and Economic Statistics for Five States ............................................................47

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A key aim of the United States Global Entrepreneurship Monitor is to provide a broad audience—educators, researchers, policy makers, practitioners—with information and analysis that can enhance understanding, decision making and actions with regard to entrepreneurship. The GEM 2015 United States Report highlights global and longitudinal comparisons of entrepreneurship in the United States across multiple phases and several types of entrepreneurship (independent start-up activity, entrepreneurial employee activity and social entrepreneurship). The results show demographic characteristics of entrepreneurs (gender, age and ethnicity), their motivations for starting, and the characteristics of and expectations they have for their businesses. This report also reviews the amount and sources of financing required for starting businesses and the unique entrepreneurship profiles of five geographically distant states that include state-level changes in GEM indicators from prior years.

This report paints a comprehensive and detailed picture of entrepreneurship in the United States. Within these pages, readers can extract a number of particularly noteworthy insights, some of which have been selected and reviewed below. Drawing on several of these, eight key implications are also identified, with the intention of provoking further reflection and dialogue.

SELECT KEY FINDINGS: GEM UNITED STATES 2015

1. Opportunity perceptions dropped from a high of 51% in 2014 to 47% in 2015. This is the first drop since these perceptions began to rise in 2010. While the United States reports the highest level of capability perceptions (56%) at the innovation-driven development level, one-third of these economies report higher opportunity perceptions than the United States. This suggests that Americans remain highly confident in their abilities to start a business, but are seeing fewer opportunities to do so.

2. Total entrepreneurial activity (TEA) in the United States declined by two percentage points to 12% in 2015, reversing a four-year trend of increasing TEA rates. This decline was entirely due to a drop in nascent activity, meaning that fewer people were entering entrepreneurship in 2015. New business ownership, on the other hand, remained the same as in 2014. Three other innovation-driven economies (Canada, Estonia and Australia) reported higher TEA rates than the United States.

3. Established business rates stabilized at 7%, essentially the same rate as reported in 2014. Established business ownership had dropped for three years in a row starting in 2012; this was likely influenced by the drop in start-up activity in 2009 and 2010.

4. The United States reports the highest level of opportunity-motivated entrepreneurs who are improvement-driven among the 24 innovation-driven economies. Sixty-nine percent of entrepreneurs in the United States stated they were motivated to start by the pursuit of opportunity and they desired to increase their income or the level of independence in their work.

5. Activity rates by ethnicity show the highest rates among blacks (14%), but only one-third of this level is established business ownership activity. The white population, in contrast, reports somewhat lower start-up activity (12%), with established business ownership at three-fourths the start-up level. The results on black entrepreneurship leave questions about why so many blacks start businesses, while few have transitioned to the mature phase. The Latino and Asian populations show both low start-up and low established business activity.

Executive Summary

10

6. Nationally, 12% of Americans are leading and/or trying to start a social enterprise. On average, theseenterprises engage a median number of seven paid workers and five volunteers. Although theseentrepreneurs tap a variety of funding sources, government funding is the most popular source,revealing the importance of government in helping entrepreneurs create social value.

7. Entrepreneurship peaks among 35 to 44 year olds at 17%, and this age group is also most likely to engagein entrepreneurial employee activity. The high activity rates in this age group are accompanied by thehighest levels of opportunity and capability perceptions as well as personally knowing an entrepreneur.This age group is likely to have accumulated experience, credentials, relevant networks and otherresources they can leverage for their businesses.

8 Workforce participation rates among the population aged 55 and older suggest that entrepreneurship, as well as established business ownership, is a key means of employment for those still working in their older years.

9. Age patterns in TEA rates by gender show low rates (7% to 9%) among younger women (18 to 34 years)and older women (45 to 64 years), with a spike upward to 15% in the middle (35 to 44 years) age group.Men maintain high rates throughout their working ages, declining substantially only after age 55.Additionally, while gender gaps exist in TEA rates, they are greater among established business ownersand employee entrepreneurs, indicating the importance of looking across age groups, business phasesand contexts where this activity occurs.

10. Innovation levels among women dropped in 2015 to 32% of entrepreneurs, versus 41% in 2014. Thisrepresents a reversal of a four-year trend where women reported higher innovation rates than men.

11. The decline in TEA rate was accompanied by reductions in impact indicators. Among a smaller numberof entrepreneurs that were starting and running new businesses in 2015, fewer operated in the businessservices sector, and fewer expected to create six or more jobs in the next five years.

12. Job creation and profitability declined among established business owners: 22% added at least one job inthe prior year, down from 27% in 2014. In 2015, 61% expected to be profitable, down from 91% in 2014.

13. In 2015, 10% of entrepreneurs were starting businesses based on new technology, continuing afluctuating but generally upward trend since hitting a low level of 4% in 2009.

14. Entrepreneurs needed a median level of $17,500 to start their businesses in 2015, up from $15,000 threeyears prior, when finance questions were added to the 2012 survey. Financial requirements increasedwith greater job creation ambitions and for entrepreneurs in the extractive, transforming and businessservices sectors. Entrepreneurs financed 57% of their funding needs themselves.

15. Beyond personal sources, banks were the most popular funding source for entrepreneurs, with 36% ofentrepreneurs stating they used bank financing to start their business. Government sources also play animportant role in business starts, providing funding to 22% of entrepreneurs. Crowdfunding, a still-emerging source, contributed to the financial needs of 12% of entrepreneurs.

16. An in-depth examination of five states (California, Florida, New York, Ohio, and Texas) showed thatNew York and Ohio reported lower TEA rates than the U.S. national average. Contributors to these lowrates include low opportunity motives among entrepreneurs, low activity among the middle age groups,and low and declining male participation in entrepreneurship.

17. While the United States tends toward low international sales in general, the five states examined in-depth all showed higher internationalization levels than the national average, with particularly highlevels in Florida. This follows an increase in four of the states, while California declined from previouslyhigh levels.

EXECUTIVE SUMMARY

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IMPLICATIONS

1. Entrepreneurship requires both capable and confident entrepreneurs and the presence of both opportunities and enablers in the environment. Societal-level indicators such as capability and opportunity perceptions should be assessed regularly for changes over time and with regional and economic development-level comparisons.

2. Assessment of entrepreneurship across phases is also important to determine whether there has been a change in nascent activity, whether people have sustained their businesses into maturity and so forth. Each phase of the process requires a supply of those in the prior phase and relies on capable entrepreneurs and other enablers to transition to the next phase.

3. A high level of opportunity motives suggests that entrepreneurship provides an option for people to have the career they want. While many prefer work in an organization, others may choose to follow their dreams of owning a business, bringing something new into the world and being their own boss. Entrepreneurship can also serve as an attractive alternative for younger and older Americans, women and many others, some of whom find themselves in difficult situations, such as unemployment.

4. Changes in entrepreneurship levels may be due to shifts in the demographics of entrepreneurship, such as gender, age or ethnicity. Persistent issues like low start-up rates, low business sustainability or low innovation levels might require targeted interventions.

5. Social missions are driving much entrepreneurship activity in the United States. In most cases, these entrepreneurs place social objectives above profits, but economic benefits also stem from creating new social value, creating benefits for both society and entrepreneurial stakeholders.

6. Changes in industry sector participation may have an effect elsewhere: For example, a decline in entrepreneurs competing in advanced sectors may lead to lower job creation potential or declining profitability. The overall impact of entrepreneurship may therefore depend on industry mix, and this may fluctuate differently among entrepreneurs than in the general business environment.

7. Banks are key sources of start-up funding for entrepreneurs, which has implications for policy, bank processes and human resource management. Government also plays a key role in funding entrepreneurs, including those with social missions.

8. An examination of five states (California, Florida, New York, Ohio and Texas) and comparisons with prior years (2012 or 2013) reveal considerable variations at the state level and a notable contrast with stable or incrementally changing indicators at the national level. Continual assessments and comparisons over time and with other states can help identify trends and gaps. Communication and debate about differences in entrepreneurship profiles, conditions that affect the level and nature of this activity, and the features and results of interventions, policies, and changes can go a long way toward building knowledge and informing actions that improve the quality of entrepreneurship and its contribution to state economies.

EXECUTIVE SUMMARY

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INTRODUCTION

Entrepreneurship is a complex phenomenon that is affected by many factors at multiple levels. Macroeconomic conditions represent one set of factors that affects this activity, often substantially. The current status and future prospects of the macro-economy such as growth rates, unemployment, inflation and monetary and fiscal policies, have fundamental impacts on entrepreneurship incentives, perceived opportunities and eventually entrepreneurial activities. This section briefly discusses the macroeconomic conditions in the U.S. economy in 2015.

The U.S. economy continued to grow in 2015, experiencing a positive growth rate in the first quarter (0.5% annualized rate), in contrast to the first quarter of 2014. The exceptionally cold weather in early 2014 and labor disputes in West Coast ports were mentioned as reasons for slow growth at that time. As depicted in Figure 1, growth was substantially larger after the first quarter of 2015. As a result, GDP grew by 1.8% for the year. Increases in domestic demand, particularly consumer spending and residential investment (led by higher consumer confidence and the reduction in oil prices), were key factors behind this growth rate. On the other hand, the reduction in global demand for U.S. goods—because of a sharp appreciation in the dollar and economic problems across Europe and emerging markets—was a drag on U.S. economic growth, leading to a lower growth rate in 2015 than the three previous years.

The U.S. economy had one of the highest growth rates among the advanced economies. Europe had small gains, and the emerging markets underperformed substantially. Brazil and Russia were in recession, and China’s growth rate was below expectations. The struggling global economy, in addition to the depreciation of other currencies relative to the U.S. dollar, reduced the competency and profitability of U.S. global brands.

FIGURE 1 Percentage Change

in Real GDP from Previous Quarter

(seasonally adjusted annual rates)

SOURCE OF DATA U.S. Bureau of

Economic AnalysisI II III IV I II III IV I II III IV I II III IV I II III IV I II III IV I II III IV I II III IV

2008 2009 2010 2011 2012 2013 2014 2015

6.0

4.0

2.0

0.0

-2.0

-4.0

-6.0

IntroductionThe U.S. Economy in 2015

13

The United States was the most robust performer among developed economies in 2014 as a result of upward market movement. The Dow Jones Industrial Average (DJIA, the Dow) began the year at 16,577 and broke its closing record Wall Street experienced large volatility in 2015. DJIA hit its all-time high at 18,312.30. But it lost more than 10% in August, declining to 15,666.44. Crude oil prices and uncertainty in the global economy, particularly the Chinese economy, were factors affecting volatility in the market. The stock market, however, recovered most of what it lost during the year. Both the DJIA and S&P 500 ended the year slightly lower than the end of 2014.

2015 and 2014 had the strongest job growth since 1999. The U.S. economy created 2.7 million jobs. Private sector employment had 70 consecutive months of growth by December 2015, which is a historical record. The unemployment rate fell 0.6 percentage points during 2015, reaching 5.0%, only 0.3% above its level before the recession. Figure 2 shows trends in the national unemployment rate, and Figure 3 depicts these rates across states, illustrating that unemployment was higher in Southwestern and Southern states. Average monthly job growth was 228,000 jobs per month. Almost all of this increase in employment was in full-time jobs. Average hourly earnings also increased slightly, and inflation reached 2% by November.

Since the recession, monetary and fiscal policies have been used to lift the economy out of recession. Monetary policy is determined by the Federal Reserve, and the fiscal policy is designed by Congress and the executive branch of government. A summary of these policies in 2015 follows. MONETARY AND FISCAL POLICIES IN 2014 In December 2015, the Federal Open Market Committee (FOMC) increased the interest rate, after seven years of federal funds remaining at the minimum rate. The decision was made based on the recovery of the labor markets and the strong expectation that inflation will move up to its 2% goal in the medium term. The FOMC was fairly confident that the economy would maintain conditions that allow for rate hikes to happen gradually but continuously in the future.

FIGURE 2 National Unemployment Rate (seasonally adjusted percentage)

SOURCE OF DATA U.S. Department of Labor, Bureau of Labor Statistics

IntroductionThe U.S. Economy in 2015

Recession Period

WallStreetexperiencedlargevolatilityin2015.TheDowJonesIndustrialAverage(DJIA)hititsall-timehighat18,312.30.Butitlostmorethan10%inAugust,decliningto15,666.44.Crudeoilpricesanduncertaintyintheglobaleconomy,particularlytheChineseeconomy,werefactorsaffectingvolatilityinthemarket.Thestockmarket,however,recoveredmostofwhatitlostduringtheyear.BoththeDJIAandS&P500endedtheyearslightlylowerthantheendof2014.2015and2014hadthestrongestjobgrowthsince1999.TheU.S.economycreated2.7millionjobs.Privatesectoremploymenthad70consecutivemonthsofgrowthbyDecember2015,whichisahistoricalrecord.Theunemploymentratefell0.6percentagepointsduring2015,reaching5.0%,only0.3%aboveitslevelbeforetherecession.Figure2showstrendsinthenationalunemploymentrate,andFigure3depictstheseratesacrossstates,illustratingthatunemploymentwashigherinSouthwesternandSouthernstates.Averagemonthlyjobgrowthwas228,000jobspermonth.Almostallofthisincreaseinemploymentwasinfull-timejobs.Averagehourlyearningsalsoincreasedslightly,andinflationreached2%byNovember.Sincetherecession,monetaryandfiscalpolicieshavebeenusedtolifttheeconomyoutofrecession.U.S.monetarypolicyisdeterminedbytheFederalReserve,andthefiscalpolicyisdesignedbyCongressandtheexecutivebranchofgovernment.Asummaryofthesepoliciesin2015follows.The Monetary Policy in 2015InDecember2015,theFederalOpenMarketCommittee(FOMC)increasedtheinterestrate,aftersevenyearsoffederalfundsremainingattheminimumrate.Thedecisionwasmadebasedontherecoveryofthelabormarketsandthestrongexpectationthatinflationwillmoveuptoits2%goalinthemediumterm.TheFOMCwasfairlyconfidentthattheeconomywouldmaintainconditionsthatallowforratehikestohappengraduallybutcontinuouslyinthefuture.

Figure 2: National Unemployment Rate, Seasonally Adjusted, in Percentage

Note:Thegrayboxshowstherecessionperiod.Eachtickmarkonthehorizontalaxisshowsthebeginningoftheyear.

0.0

2.0

4.0

6.0

8.0

10.0

12.0

2007 2008 2009 2010 2011 2012 2013 2014 2015 2007 2008 2009 2010 2011 2012 2013 2014 2015

12.0

10.0

8.0

6.0

4.0

2.0

0.0

Note: The gray box shows the recession period. Each tick mark on the horizontal axis shows the beginning of the year.

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After the Great Recession, when the federal funds rate was lowered to virtually zero, the Federal Reserve had to employ an unconventional instrument, named quantitative easing (QE). Under this policy, the Federal Reserve bought a large amount of mortgage-backed securities and treasury bonds, thereby increasing the money supply every month. In this way, the banks would be encouraged to lend more, especially in the mortgage market, which would ease the financial markets and the credit crunch. By the end of 2015, the large-scale asset purchases of QE increased the Fed’s balance statement to $4.4 trillion—more than five times its size in 2007.

In 2015, with the volatility in the global economy, particularly in emerging markets such as China, the Federal Reserve had to move cautiously to change policy. With oil prices down and the fear of deflationary forces, there were worries about lowering the interest rate too much. It was also a challenging process to raise interest rates when the Federal Reserve had several large-scale asset purchases. It seems that the Federal Reserve has successfully maneuvered around all these hurdles.

FIGURE 3 Unemployment Rates by State,

2015 Annual Averages

DATA SOURCE

US Department of Labor, Bureau of Labor

Statistics (accessed on May 5, 2016, via

http://www.bls.gov/lau/maps/aastrate.gif)

INTRODUCTION

15

THE FISCAL POLICY IN 2015

The budget deficit declined by 0.3 percentage points to 2.5% in 2015. This is the lowest deficit since 2007, and is below the average of the last 40 years. Moreover, since 2009, the deficit as a share of GDP fell by about 75% since 2009. This is the largest reduction in this share since the demobilization after World War II. The rise in taxes due to increases in income was one of the main contributors to the deficit reduction.

Since the end of 2013, a series of agreements within and between Congress and the White House have avoided the federal shutdown and relaxed federal debt limits and federal spending cuts. This was helpful in reducing uncertainty in the market. Overall, one can consider 2015 a relatively stable year for U.S. entrepreneurs, although the global economy faced substantial volatility.

THE GEM 2015 UNITED STATES REPORT

This report generates in-depth insights about entrepreneurship in the United States, examining multiple phases of this process, profiles of entrepreneurs and their businesses, and societal attitudes that reveal potential entrepreneurs and support for this activity. Global and longitudinal analyses enable comparisons with other economies around the world and within the United States over time. Particular attention is paid to the participation and characteristics of women and both younger and older entrepreneurs. This year, the report includes new chapters on social entrepreneurship, finance and entrepreneurship in five U.S. states.

A key aim of GEM is to inform academics, educators, policy makers and practitioners about the frequency and nature of entrepreneurship in and across economies around the world to foster better understanding, support and conditions that allow entrepreneurship to thrive. This report more specifically aims to advance knowledge about the multidimensional nature of entrepreneurship in the United States, with comparisons to other economies and insights on longitudinal changes over time.

INTRODUCTION

16

GEM ACTIVITY ACROSS PHASES

The GEM 2015 survey reported a total entrepreneurial activity (TEA) rate of 12% in the United States. This represents a decline from 14% over the previous year and reverses a four-year trend of increasing TEA rates. Figure 4 shows a longitudinal analysis of nascent, new and established business activity, breaking down TEA into its two phases: nascent (in the process of starting, less than 3 months old) and new (3 to 42 months old). As this figure reveals, the decrease in TEA is due to a drop in nascent activity. New business activity, meanwhile, continued on a stable path.

The United States still exhibits a high entrepreneurship rate for a developed economy, as shown in Figure 5. Yet the decline in nascent activity is notable, especially when it is considered along with the decline in opportunity perceptions. These results suggest that in 2015 fewer people are seeing opportunities and fewer are taking steps to start. More encouraging, however, is that the three-year drop in established business activity has abated, with 2015 levels essentially the same as in 2014.

FIGURE 4 Longitudinal Analysis of Nascent, New and Established Business

Activity in the U.S. Adult Population (18

to 64 year olds)

SOURCE OF DATA GEM 2005–2015

Chapter 1United States Entrepreneurship ActivityUnited States Entrepreneurial Activity

Activity Across PhasesThe GEM 2015survey reporteda total entrepreneurial activity (TEA) rateof 12% in theUnited States.This represents adecline from 14% over the previous year and reverses afour-yeartrend ofincreasingTEArates.Figure4showsalongitudinalanalysisofnascent,newandestablishedbusinessactivity,breaking downTEAintoits twophases: nascent (inthe process of starting, less than3 months old) andnew (3 to 42 months old). As this figurereveals, thedecreasein TEA is dueto adrop in nascent activity.Newbusinessactivity,meanwhile,continuedonastablepath.

Figure 4: Longitudinal Analysis of Nascent, New and Established Business Activity in the U.S. AdultPopulation (18 to 64 year olds), GEM 2015

TheUnitedStatesstillexhibitsahighentrepreneurshiprate for a developedeconomy, asshown inFigure5. Yet thedeclinein nascent activity is notable, especially when it is considered along with thedecline inopportunity perceptions. These results suggest that fewer people are seeing opportunitiesandfeweraretakingstepstostartin2015.Moreencouraging,however,isthatthethree-year dropinestablished business activity has abated, with 2015levels essentially thesameas in 2014.

9%

7%

7%6%

5%5%

8%

9%9%

10%

8%

4%

3%3%

5%

3% 3%

4% 4%4%

4% 4%

5%5% 5%

8%

6%

8%

9%

8% 7% 7%

0%

2%

4%

6%

8%

10%

12%

2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Nascent NewBusiness EB

17

NECESSITY-BASED AND IMPROVEMENT-DRIVEN ENTREPRENEURSHIP

Among entrepreneurs in the United States, 14% are starting out of necessity, because they have no better job options. This indicator had dropped in 2014 after lingering at high levels after the 2007–2008 recession. Similar results in 2015 suggest some stability in the return to typically low levels in the United States. Figure 6 shows longitudinal data on necessity-driven entrepreneurship.

Perhaps even more interesting is the high level of improvement-driven opportunity motives. In 2015, 69% of entrepreneurs in the United States stated they were motivated to start by the pursuit of opportunity and desired to increase their income or the level of independence in their work. This is the highest proportion reported in the innovation-driven economies.

FIGURE 5 Total Entrepreneurial Activity (TEA) Rates in the Adult Population in 60 Economies SOURCE OF DATA GEM 2015

FIGURE 6 Longitudinal Analysis of the Proportoin of Necissity-Driven Motives Among Total Entrepreneurial Activity (TEA) SOURCE OF DATA GEM 2005–2015

Figure 6: Longitudinal Analysis of the Proportion of Necessity-Driven Motives Among Total Entrepreneurial Activity (TEA), GEM 2015

Perhapsevenmoreinterestingisthehighlevelofimprovement-drivenopportunitymotives.In2015,69%ofentrepreneursintheUnitedStatesstatedtheyweremotivatedtostartbythepursuitofopportunityanddesiredtoincreasetheirincomeorthelevelofindependenceintheirwork.Thisisthehighestproportionreportedintheinnovation-driveneconomies. Discontinuation TheUnitedStatesshowsaslightlyhigherthanaveragelevelofbusinessdiscontinuation:3.6%oftheadultpopulationexitedabusinessinthepastyearversusanaverageof2.8%amongtheinnovation-driveneconomies.Thisisnottooconcerningwhenconsideringthehighrateofentrepreneurialactivityinthiscountry;therearemorethanthreeentrepreneursstartingbusinessesforeverypersonwhohasdiscontinuedoneinthepastyear.Whileanentrepreneur’sexpectationsofsuccessarejustifiablyhighattheoutset,thereisalwaysachancetheseeffortscouldleadtofailureortheneedtoexitforotherreasons.Buttheprospectofsuccesswillnotbeachievedwithoutawillingnesstoventureout.Adynamicentrepreneurialsocietythereforeneedstohavepeoplewhoarewillingtopursueentrepreneurshipandacceptfailure.Figure7showstheproportionofexitsintheinnovation-driveneconomiesduetothreereasons.Aboutone-thirdofdiscontinuationsintheinnovation-driveneconomiesareduetounprofitability,andtheUnitedStatesisjustbelowthisaverage.Relativelyfew,however,stopbecauseoffinancingproblems(lessthan5%intheUnitedStatesandjustunder8%fortheinnovation-driveneconomiesoverall).Financeproblemstendtobelowerintheinnovation-driveneconomiescomparedtotheotherdevelopmentgroups,andtheevenlowervaluesreportedintheUnitedStatesreflecttheavailabilityofavarietyoffinancialresourcesforentrepreneurs.Bureaucracycanbeanaturalconsequenceofdevelopment,and8%oftheinnovation-driveneconomiesreportthisasareasonforexits,withtheUnitedStatesfallingaroundthisaverage.

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Chapter 1United States Entrepreneurship Activity

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Figure 5: Total Entrepreneurial Activity (TEA) Rates in the Adult Population in 60 Economies, GEM 2015

Necessity-Based and Improvement-Driven EntrepreneurshipAmongentrepreneursinthe UnitedStates,14%arestartingoutofnecessity,becausetheyhavenobetterjoboptions. Thisindicator haddroppedin2014 afterlingeringat highlevelsafterthe 2007–2008recession.Similarresults in 2015suggestsomestability in thereturntotypicallylowlevels in theUnitedStates. Figure6showslongitudinaldataonnecessity-drivenentrepreneurship.

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DISCONTINUATION

The United States shows a slightly higher than average level of business discontinuation: 3.6% of the adult population exited a business in the past year versus an average of 2.8% among the innovation-driven economies. This is not too concerning when considering the high rate of entrepreneurial activity in this country; there are more than three entrepreneurs starting businesses for every person who has discontinued one in the past year. While an entrepreneur’s expectations of success are justifiably high at the outset, there is always a chance these efforts could lead to failure or the need to exit for other reasons. But the prospect of success will not be achieved without a willingness to venture out. A dynamic entrepreneurial society therefore needs to have people who are willing to pursue entrepreneurship and accept failure.

Figure 7 shows the proportion of exits in the innovation-driven economies due to three reasons. About one-third of discontinuations in the innovation-driven economies are due to unprofitability, and the United States is just below this average. Relatively few, however, stop because of financing problems (less than 5% in the United States and just under 8% for the innovation-driven economies overall). Finance problems tend to be lower in the innovation-driven economies compared to the other development groups, and the even lower values reported in the United States reflect the availability of a variety of financial resources for entrepreneurs. Bureaucracy can be a natural consequence of development, and 8% of the innovation-driven economies report this as a reason for exits, with the United States falling around this average.

CHAPTER 1

FIGURE 7 Propotion of

Discontinuation Due to Lack of Profits,

Financing Problems or Beaurocracy in 24

Innovation-Driven Economies

SOURCE OF DATA GEM 2015

Figure 7: Proportion of Discontinuation Due to Lack of Profits, Financing Problems or Bureaucracy in24 Innovation-Driven Economies, GEM 2015

Entrepreneurial Employee ActivityEntrepreneurial activity tends to be lower in the innovation-driveneconomies, onaverage, comparedtoearlier development levels, as Figure5at thebeginningof this chapterillustrates.Apartialexplanationforthis effectis thatmore attractive job options areavailable. Given that peoplemay prefer work as anemployee, this career alternativemight attract someentrepreneurial types. This explains whyentrepreneurial employeeactivity (EEA) tends to behigh in many innovation-driveneconomies. Figure 8shows that, in some economies, there are tradeoffs betweenTEAandEEArates, withone being highwhile the other is low. However, the United States is one of the economies whereboth rates arehigh,suggesting that people canexercise their entrepreneurial ambitions ineither environment.

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19

ENTREPRENEURIAL EMPLOYEE ACTIVITY

Entrepreneurial activity tends to be lower in the innovation-driven economies, on average, compared to earlier development levels, as Figure 5 at the beginning of this chapter illustrates. A partial explanation for this effect is that more attractive job options are available. Given that people may prefer work as an employee, this career alternative might attract some entrepreneurial types. This explains why entrepreneurial employee activity (EEA) tends to be high in many innovation-driven economies. Figure 8 shows that, in some economies, there are tradeoffs between TEA and EEA rates, with one being high while the other is low. However, the United States is one of the economies where both rates are high, suggesting that people can exercise their entrepreneurial ambitions in either environment.

ETHNICITY

Overall, the majority of entrepreneurs in the United States are white/Caucasian, reflecting the high proportion of whites in the U.S. population. As Figure 9 shows, blacks and Hispanics contribute appreciably to entrepreneurship in America, together representing 23% of all entrepreneurs. On the other hand, few Asians were starting or running new businesses in the United States in 2015, again reflecting the relative small population of this ethnic group.

CHAPTER 1

FIGURE 8 Early-Stage Entrepreneurial Activity and Entrepreneurial Employee Activity in 24 Innovation-Driven Economies SOURCE OF DATA GEM 2015

Figure 8: Early-Stage Entrepreneurial Activity and Entrepreneurial Employee Activity in 24 Innovation-Driven Economies, GEM 2015

Ethnicity Overall,themajorityof entrepreneursin theUnited States arewhite/Caucasian,reflectingthe highproportionof whites inthe U.S.population.AsFigure9shows, blacksandHispanicscontributeappreciably to entrepreneurship inAmerica, together representing23%ofallentrepreneurs. Ontheotherhand, fewAsians werestartingorrunningnew businessesinthe UnitedStates in2015,againreflectingtherelativesmall populationofthis ethnic group.

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FIGURE 9 Ethnic Breakdown of Total Early-Stage Entrepreneurial Activity in the United States SOURCE OF DATA GEM 2015

Figure 9: Ethnic Breakdown of Total Early-Stage Entrepreneurial Activity in the United States, GEM 2015

AnanalysisofentrepreneurshiprateswithintheseethnicgroupsshowsthehighestTEAratesamongtheblackpopulation,asFigure10illustrates.Start-uprateswerecomparablylowerintheLatinoandAsianpopulations.However,aninterestingstoryemergesinthecomparisonofTEAandestablishedbusinessrates.Althoughthesepercentagesdonotreflectlongitudinalresults(i.e.,trackingentrepreneurshipovertime),wecandrawsomeconclusionsabouttherelationshipbetweenstart-upandmaturebusinessactivity.Inthewhitepopulation,establishedbusinessactivityisthree-fourthsthelevelofstart-upactivity.Incontrast,theblackpopulationreportsestablishedbusinessownershipatone-thirdofthelevelofstart-upefforts.Theseresultsleadtoquestionsaboutwhyblacksstartathigherproportionsthanwhites,buthavefewermaturebusinesses.Perhapstheblackpopulationiscompelledtostartbusinesses,ortheyseeandactonopportunitiesmorefrequently.Yetlowerestablishedbusinessactivitymayleadtoconcernsaboutsustainability—whetherblackpopulationsarestartingbusinesseswithlong-termpotential,whethertheyhavetheintentions,abilityorresourcestostayinbusiness,andwhetherconditionsintheenvironmentallowthemtostayinbusiness.TheLatinopopulationexhibitslowstart-upactivityandthelowestestablishedbusinessactivityamongtheethnicgroups.ThissuggestspotentialareasofinvestigationaboutwhyfewLatinosarestartingorrunningbusinessesintheUnitedStates.TheAsianpopulationalsoshowslowpercentagesofthosebothstartingbusinessesandrunningestablishedones,althoughthegapbetweenthetwophasesisnotasdramaticasineithertheblackorLatinopopulations.

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20

CHAPTER 1

An analysis of entrepreneurship rates within these ethnic groups shows the highest TEA rates among the black population, as Figure 10 illustrates. Start-up rates were comparably lower in the Latino and Asian populations. However, an interesting story emerges in the comparison of TEA and established business rates. Although these percentages do not reflect longitudinal results (i.e., tracking entrepreneurship over time), we can draw some conclusions about the relationship between start-up and mature business activity.

In the white population, established business activity is three-fourths the level of start-up activity. In contrast, the black population reports established business ownership at one-third of the level of start-up efforts. These results lead to questions about why blacks start at higher proportions than whites, but have fewer mature businesses. Perhaps the black population is compelled to start businesses, or they see and act on opportunities more frequently. Yet lower established business activity may lead to concerns about sustainability—whether black populations are starting businesses with long-term potential; whether they have the intentions, ability or resources to stay in business; and whether conditions in the environment allow them to stay in business.

The Latino population exhibits low start-up activity and the lowest established business activity among the ethnic groups. This suggests potential areas of investigation about why few Latinos are starting or running businesses in the United States. The Asian population also shows low percentages of those both starting businesses and running established ones, although the gap between the two phases is not as dramatic as in either the black or Latino populations.

SUMMARY COMMENTS

This chapter reviewed global and longitudinal results and comparisons on entrepreneurial activity for the United States in 2015. A drop in nascent activity pulled down TEA rates in 2015, while new and established business activity remain virtually unchanged from 2014. Opportunity attracts the majority of U.S. entrepreneurs, particularly those desiring improvements in their income or independence. While some failures are inevitable, few of these arise from a lack of financing. This chapter reveals an additional form of entrepreneurship in the United States: employee-based entrepreneurship. The next chapter will feature another type of entrepreneurship: social enterprise activity. This chapter also revealed some interesting patterns about start-up rates and business sustainability among ethnic groups. Additional demographics—specifically gender and age—will be examined later in this report.

FIGURE 10 Total Early-Stage

Entrepreneurial Activity and

Established Business Ownership in the

United States, Percentage of Adults in Each Ethnic Group


Figure 10: Total Early-Stage Entrepreneurial Activity and Established Business Ownership in the United States, Percentage of Adults in Each Ethnic Group, GEM 2015

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21

Chapter 2Social Entrepreneurship

Social entrepreneurship is defined as the application of the skillset, mindset, processes, tools and techniques of business entrepreneurship toward the accomplishment of a social or environmental mission. It is a rapidly emerging field of entrepreneurship that attempts to use markets to address social problems that are not effectively being addressed by government or the private sector. Its rise in importance has led the GEM project to include questions about social entrepreneurship in the 2015 survey.

Nationally, 8.3% of respondents to the GEM survey reported leading an existing social enterprise, and 7% are trying to start one. There is an overlap in these results, where 3.1% of Americans are starting a social venture while leading another one. While these are relatively small numbers, they are not insignificant relative to overall entrepreneurship activity. The fact that a slightly larger percentage of Americans reported leading a social enterprise than starting one is interesting because it suggests that social entrepreneurship has already become somewhat established. However, the majority of these enterprises are less than three years old. In coming years, as this data set becomes more dynamic, we will have a clearer understanding of the growth in activity of this subset of entrepreneurship.

Women are generally assumed to play a more active role in social entrepreneurship relative to men. The 2009 GEM Report on Social Entrepreneurship indicates that the numbers of women and men in this field are about equal, which is not the case in commercial entrepreneurship, a field dominated by men. The 2015 GEM U.S. survey data shed additional light on this finding. While women account for about 39% of total entrepreneurial activity in the United States, they account for 49% of social entrepreneurship activity. Men are more likely to try to start new social enterprises. However, women lead existing social enterprises at about equal rates to men, as Figure 11 shows.

While women account for

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Examining social entrepreneurship activity by age shows that the 25 to 34-year-old age group is most active in trying to start social enterprises (see Figure 12), with the 18 to 24 year olds also quite involved. This supports a widespread observation that the so-called millennial generation is more likely than any other age group to place a high priority on socially relevant behavior. When it comes to leading a social enterprise, there is a relatively similar level of participation from ages 25 through 64, with a slight decrease in the 65-plus age group, while the youngest cohort lags behind. Overall, these results may reflect a combination of factors—that young people lack the skills, experience and confidence to lead established entities, while older social entrepreneurs are less likely to be starting from scratch.

Figure 11: Male and Female Social Entrepreneurship Rates in the United States Adult Population, GEM2015

Examining socialentrepreneurshipactivitybyageshowsthatthe25- to 34-year-oldage groupis mostactiveintryingtostartsocialenterprises(seeFigure12),withthe18 to 24 year olds alsoquite involved.This supports a widespreadobservationthat the so-called millennial generation is morelikely than anyother age grouptoplace a highpriority onsocially relevant behavior. Whenit comes toleading a socialenterprise,thereisarelativelysimilarlevelofparticipationfromages 25through64,withaslightdecrease inthe 65-plus age group, while the youngest cohort lags behind. Overall, these results mayreflect a combinationof factors—that young people lack the skills, experience andconfidence toleadestablished entities, whileolder social entrepreneurs are less likely tobe starting from scratch.

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Figure 12: Age Breakdown for Social Entrepreneurship Rates in the U.S. Adult Population, GEM 2015

Relative tojobcreation, the total mediannumber of people working ina social enterprise is 12,includingemployees, contractors and volunteers. Of this number, fivearevolunteers. With regard tofutureemployment, social entrepreneurs tend to beoptimistic. They estimatethenumber of peopleworking intheir enterprises five years from now tobe about 25 (alsoa medianscore)—a doubling of thecurrent number and another indicator of agrowth-oriented, forward-lookingbranch ofentrepreneurship.

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FIGURE 11 Male and

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Rates in the United States Adult

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FIGURE 12 Age Breakdown

for Social Entrepreneurship Rates in the U.S. Adult Population


23

Relative to job creation, the total median number of people working in a social enterprise is 12, including employees, contractors and volunteers. Of this number, five are volunteers. With regard to future employment, social entrepreneurs tend to be optimistic. They estimate the number of people working in their enterprises five years from now to be about 25 (also a median score)—a doubling of the current number and another indicator of a growth-oriented, forward-looking branch of entrepreneurship.

The amount of start-up money needed for launching social enterprises tends to vary significantly by the age of the start-up. Enterprises that are between three months and four years old required a median infusion of $46,231 in start-up capital. Social enterprises that are less than three months old report needing a median of $10,000 to start. There are several possible explanations for this result. Generally, less start-up capital may be available for social entrepreneurship than there was in the past. The social entrepreneurs behind the newest enterprises may be finding ways to leverage start-up physical, human and social capital from other sources. It is also possible that the newest social enterprises are of a nature that requires less overall start-up money (e.g., those that use open-access technology/software in conducting their business). The most recent social entrepreneurs may be better positioned financially to use their own resources to start their enterprises. In fact, they put a median of $3,480 of their own money into starting their enterprises, as compared to $442 by social entrepreneurs operating more established enterprises. Finally, businesses older than three months may simply have progressed through additional funding phases.

Overall funding for the start-up of social enterprises comes from a variety of sources: family, friends or neighbors, employers or work colleagues, banks or financial institutions, private investors or venture capitalists (VCs), government programs, and crowdfunding (see Figure 13). Social entrepreneurs who operate enterprises that are less than three months old tend to make greater use of all these forms of start-up funding than do social entrepreneurs running enterprises that are three months to four years old. Specifically, these younger enterprises use bank loans to a substantially greater degree than older social ventures do. Additionally, private investors or VCs are tapped more often by social enterprises less than three months old, compared to those more than three months old. This may reflect growing recent interest in so-called “impact investment,”

which seeks social return on investment (SROI) in addition to, or instead of, financial return on investment (ROI).1 Crowdfunding, an increasingly popular source of funding for social entrepreneurship, is used by more young social enterprises as well. The most popular funding source overall, however, is government programs, revealing the importance of public participation in the social enterprise ecosystem.

1 Lyons, T.S., & Kickul, J. (2013). “The social enterprise financing landscape: The lay of the land and new research on the horizon,” Entrepreneurship Research Journal, 3(2): 147-159.

CHAPTER 2

Overall funding for the start-up of

social enterprises comes from a

variety of sources: family, friends

or neighbors, employers or work

colleagues, banks or financial

institutions, private investors or

venture capitalists (VCs), government

programs, and crowdfunding

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government programs, revealing

the importance of public

participation in the social

enterprise ecosystem.

24

CHAPTER 2

FIGURE 13 Funding Sources for

Social Enterprises


J. Gregory Dees, viewed by many to be the “father” of the field of social entrepreneurship, identified social entrepreneurs as agents of social change who put their mission before all else, including profits.2 This is confirmed by the results of the GEM 2015 survey. When confronted with the statement that generating value to society and the environment is more important than generating financial value, 72% of respondents indicated that they “strongly agreed” or “somewhat agreed.” Only 10% strongly or somewhat disagreed. Social entrepreneurship is often considered to pursue a double (financial and social) or triple (financial, social and environmental) bottom line. When the statement “My organization puts more emphasis on social value than on environmental value” was posed to respondents, 57% strongly or somewhat agreed. Thus, in the world of social entrepreneurship, social and environmental value trump financial value, with social value considered somewhat more important.

SUMMARY COMMENTS

Social entrepreneurship engages over 12% of working-age adults in the United States, providing jobs for others and an outlet for volunteers. The majority of these entrepreneurs are more concerned with generating value to society and the environment than generating financial value. The gender gap evident in TEA rates appears to also exist in social entrepreneurship start-up efforts, although leadership of existing social enterprises is nearly equal between the genders. Younger age groups are more likely to report that they are starting a social enterprise, whereas those between 25 and 64 years of age are more likely to be leading an existing one. Social entrepreneurs are tapping a wide variety of financing sources, with government funding remaining the most popular.

2 Dees, J.G. (1998). The meaning of “social entrepreneurship.” https://entrepreneurship.duke.edu/news-item/the-meaning-of-social-entrepreneurship/

Figure 13: Funding Sources for Social Enterprises, GEM 2015

J. Gregory Dees, viewed by many to be the“father” of thefield of social entrepreneurship, identifiedsocialentrepreneursasagentsofsocialchangewhoputtheir missionbefore all else,includingprofits.3

This is confirmed by the results of the GEM 2015 survey. When confrontedwiththe statement thatgenerating value to society and the environment is more important than generating financial value, 72%of respondents indicatedthat they “strongly agreed” or “somewhat agreed.” Only 10% strongly orsomewhat disagreed. Social entrepreneurship is oftenconsideredtopursue a double (financial andsocial) ortriple (financial, socialandenvironmental) bottomline. Whenthe statement “My organizationputs more emphasis onsocial value thanonenvironmental value” was posedtorespondents, 57%strongly or somewhat agreed. Thus, inthe worldof social entrepreneurship, social andenvironmentalvalue trumpfinancial value, withsocial value consideredsomewhat more important.

Infographic:“For my organization, generating value tosociety andthe environment is more importantthangenerating financial value for the company.” Strongly agree: 56%, somewhat agree: 16%.

Summary Comments

Social entrepreneurship engages over 12% of working-age adults in the UnitedStates, providing jobs forothers andanoutlet for volunteers. The majority of these entrepreneurs are more concernedwithgenerating value to society and the environment than generating financial value. The gender gapevident in TEA rates appears to also exist in social entrepreneurship start-up efforts, although leadershipof existing social enterprises is nearly equal betweenthe genders. Younger age groups are more likely toreport that they are starting a social enterprise, whereas those between25 and64 years of age are

3 Dees, J.G. (1998). The meaning of “social entrepreneurship.” https://entrepreneurship.duke.edu/news-item/the-meaning-of-social-entrepreneurship/

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GEM research has shown how entrepreneurial attitudes and activities reach into every group of U.S. society. Certainly, when we look at entrepreneurial attitudes and activity by age, we see an almost stunning vision of a society in which people of all ages engage in the planning and operation of entrepreneurial ventures.

Figure 14 shows the relative stability of entrepreneurial intentions and activity across all age groups. Intentions to engage in entrepreneurial activity among non-entrepreneurs are high among the three youngest age groups, dropping among those 45 and over. However, when viewing this indicator relative to workforce participation rates among those 55 and older, an interesting story emerges. Among 55 to 64 year olds, workforce participation rates are 64%, bringing intentions to just over 12% among active workers. Even for the oldest group in the sample, 65 to 74 year olds with a workforce participation rate of 26%, their nominal intention rate of 5% increases to over 20% relative to those still active in the workforce. This indicates that entrepreneurship is a key means of employment for those still working in their older years.

Total entrepreneurial activity (TEA) rates show a greater variance by age compared to intentions. TEA rates peak among those 35 to 44 years old. The lower TEA rates reported in the youngest group reflect their lower workforce participation rates. Additionally, this group may have a more pressing need to earn current income, creating incentives to delay engaging in entrepreneurial ventures that might not be able to pay them until the business reaches a profitable stage. TEA rates among the oldest age group, while the lowest, also demonstrate that entrepreneurship is still popular after age 65.

Chapter 3Age

AgeGEM research hasshownhowentrepreneurialattitudesandactivities reachinto everygroupofU.S.society.Certainly,whenwelookatentrepreneurialattitudesandactivitybyage,weseeanalmoststunningvisionofasociety in which people ofall agesengagein theplanningandoperationofentrepreneurialventures.

Figure14showstherelativestabilityofentrepreneurialintentionsandactivityacross all agegroups.Intentionstoengageinentrepreneurialactivityamongnon-entrepreneurs arehighamongthethreeyoungest agegroups,droppingamongthose45andover.However,whenviewingthis indicatorrelativetoworkforceparticipationratesamongthose55andolder,aninterestingstoryemerges.Among55 to64yearolds, workforceparticipationratesare64%,bringingintentionstojustover12%amongactiveworkers.Even fortheoldestgroupin thesample,65 to74 year olds withaworkforceparticipationrateof26%,theirnominal intentionrateof5%increasestoover20%relativeto thosestillactive in theworkforce.This indicatesthatentrepreneurship is akey meansofemploymentforthosestillworkingintheirolderyears.

Figure 14: Age Distribution of Phases and Types of Entrepreneurial Activity in the U.S. Adult Population, GEM 2015

Total entrepreneurial activity(TEA)ratesshowagreatervariancebyagecomparedto intentions.TEAratespeakamongthose35to44yearsold.ThelowerTEArates reported in theyoungestgroupreflecttheirlowerworkforceparticipationrates.Additionally,this groupmayhaveamorepressing need toearn currentincome,creatingincentivestodelayengagingin entrepreneurialventuresthatmightnotbeabletopay themuntilthe businessreaches aprofitablestage. TEArates amongtheoldestage group,while thelowest, alsodemonstratethatentrepreneurship is stillpopular afterage65.Anotablepatternis revealedinthe relationshipbetweenintentionsandTEAamongthe agegroups. TEAreflectscurrentactions,whereas intentionsmeasurethegroups’projectedactionsoverthe nextthree

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FIGURE 14 Age Distribution of Phases and Types of Entrepreneurial Activity in the U.S. Adult Population SOURCE OF DATA GEM 2015

26

CHAPTER 3

A notable pattern is revealed in the relationship between intentions and TEA among the age groups. TEA reflects current actions, whereas intentions measure the groups’ projected actions over the next three years. Therefore, it is possible that more younger people currently intend to start in the future than those who are actually starting, and among 35 to 44 year olds, fewer have future intentions despite currently high TEA rates. Yet the relationship of these two indicators across the age groups raises questions about why intentions are higher than TEA among those younger than 35, and why those 35 to 44 show the reverse effect. It may be the case that young people have entrepreneurial ambition but not the means to get started. The 35 to 44 year olds may have good job alternatives and perhaps think less often about starting, yet they may have more opportunities and more resources to do so. There is yet another pattern in the older age groups where TEA rates closely mirror intentions. This suggests that action is coupled with a realistic assessment of entrepreneurial ambition.

The greatest difference in activity among age groups is in the percentages of adults with established businesses. As one would expect, this rate generally increases with age as entrepreneurs have had the time to build their ventures. The high rates of established business ownership among older adults, especially when adjusted for workforce participation rates, demonstrate a few key facts of economic life for older Americans. First, it reflects the major role entrepreneurship plays in the work life and income of these groups. Approximately one in seven people in the 55- to 64-year-old age group who is still in the workforce has a business. For those in the 65- to 74-year-old group, this number is over 40%. Second, entrepreneurship can be a flexible endeavor, allowing entrepreneurs to more or less design their own jobs. Consequently, these high rates of entrepreneurship in the older population likely comprise either those who have continued to operate businesses started in their younger years or those who have retired from traditional employment and now run their own businesses.

Entrepreneurial employee activity (EEA) mirrors the pattern in TEA, although at a lower level. Like TEA, the highest level of EEA is reported in the 35- to 44-year age group. On either end of the age spectrum, EEA is nearly nonexistent, of course, reflecting the low level of employment in the youth and older populations. Most interesting is that EEA is prevalent throughout the ages where people are most likely to be in employment: from 24 to 64 years of age. Both those early in their careers and those later in their careers have advantages: for example, youthful energy and creativity versus the experience and credibility that come with maturity. Perhaps the high levels seen among 35 to 44 year olds reflect a blend of these advantages.

Figure 15 shows the prevalence of opportunity-driven and necessity-driven entrepreneurship by age group. The low rate of necessity-driven entrepreneurship in the United States is a little different by age group, with the highest relative levels reported among the young 18 to 24 and mid-late career 45 to 54 year olds. The younger age group is not yet positioned for skilled and well-paying jobs, so for those with financial needs, necessity-motivated entrepreneurship provides a source of income. The 45 to 54 year olds, on the other hand, may find themselves out of a job, with perhaps outdated skills or age bias narrowing their options for work as an employee. It is among those generally at the height of their careers where opportunity-driven entrepreneurship strikes most often. Not only do the 35 to 44 year olds most frequently start businesses, but they also do so because they see an opportunity more often than other age groups do. By this age, they are likely to have accumulated the knowledge, experience, credibility and connections that position themselves ideally for entrepreneurship.

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FIGURE 15 Percentage of TEA with Necessity Motives by Age Group* SOURCE OF DATA GEM 2015

Figure 16 tracks attitudes regarding starting a business and whether fear of failure stands in their way. Over half of those 25 to 44 years of age see opportunities at a higher rate than their younger and older counterparts do. This is also the age range with the highest rates of entrepreneurial activity. When asked whether they possess the skills necessary to be entrepreneurs, the respondents in the middle age groups feel the strongest about their abilities. The youngest group, many of whom are still in school and who have the least business experience, score lowest on this measure. Capability perceptions decline slightly in the oldest age groups; some at this age may feel they don’t have the most updated skills for entrepreneurship. Still, over half of these people over age 65 think they have entrepreneurial capabilities, which speaks to their confidence and experience.

CHAPTER 3

FIGURE 16 Entrepreneurial Attitudes and Affiliations in the U.S. Working-Age Population SOURCE OF DATA GEM 2015

Figure16tracksattitudesregardingstartingabusinessandwhetherfearoffailurestandsin theirway.Overhalfofthose25to44years ofage seeopportunitiesatahigherrate thantheiryounger andoldercounterpartsdo.This isalsotheagerangewiththehighestratesof entrepreneurialactivity.Whenaskedwhether theypossesstheskills necessarytobeentrepreneurs,therespondentsinthemiddleagegroupsfeel thestrongest abouttheir abilities.Theyoungestgroup,manyofwhomarestillin schoolandwho have theleastbusinessexperience,scorelowestonthismeasure.Capability perceptionsdeclineslightlyin the oldest agegroups; someat thisagemay feel theydon’t havethe most updatedskills forentrepreneurship.Still,over half ofthesepeopleover age65thinktheyhaveentrepreneurialcapabilities,which speakstotheir confidenceandexperience.

Knowing anentrepreneurpositivelyinfluencesone’sownentrepreneurial ambitions, offeringexamples,role models,advisorsandcollaboratorstoinspire andsupporttheseefforts.Hereagain,weseehigherscoresamongtheagegroupswith thegreatestentrepreneurialactivity, the25to 44yearolds. Thelowestscoresonthismeasurewerereportedbytheveryoldestandyoungestgroups,albeitforlikelyverydifferentreasons. Theyoungergroupis stillin thestageofbuildingtheir professionalnetworks,andtheoldergroup,65to74yearolds,islessfocusedonbuildingnetworksthatcouldhelpwithfutureprofessional activities.

Fearoffailuredoesnotvarygreatlyacross agegroups; however,it is interestingto notethatthehighestrateofsuchfearisamong18to24yearolds, whilethelowest ratesareamongthose 55 andabove.Thisbrings intoquestionthe conventionalwisdomthatyoung peoplemay makebetterentrepreneursbecausetheydon’t know enoughtobe risk averse andhavelessto lose.Moreimportantly,itsuggeststhatgreaterperceivedskillandstrongernetworks,andperhapsaccesstoresources,empowerindividualstobelessfearfuloffailing.

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Figure 16: Entrepreneurial Attitudes and Affiliations in the U.S. Working-Age Population, GEM 2015

Entrepreneurship in the U.S.economyis primarilycomposedof consumer-orientedandbusiness-servicesbusinesses.Thisfactcomesthroughvery clearlywhenwelookatindustriesoffocusforentrepreneurs.Veryfewentrepreneursreport having businessesintheextractiveindustriessuchasmining, forestry or agriculture. Nearly 28%of 18 to24yearoldsreport havingbusinessesin thetransformingormanufacturing industries,andabout15%ofentrepreneurs in theotheragegroupshavethesetypesofbusinesses.Thehighrates ofmanufacturingbusinessesactivityamongtheyoungestpopulationrepresentsasignificantincreasebycomparisonto the2014GEMstudy,inwhich21%of18to24yearoldswerestarting andrunningthesetypesof businesses,whereas theolderagegroupsshowedlevelssimilarto the2015survey.

Businessservices,thesecondmost popularindustryfor entrepreneurs,showedwidevariabilityamongtheagegroups,rangingfrom22%to44%butwithnosteadyupwardor downwardtrendsalongtheagegroups. Finally, theconsumer-orientedbusinessesrepresentjustunderhalfofthe entrepreneurialactivityofthesamplewithouttoomuch variabilitybased onagetrends. Thissector’spopularityislikelytheresultoftheeasein whichone canenter it,generallywithout muchcapital. Moreover, virtuallyeverypotentialentrepreneurhasexperienceandknowledgeofbusinessinthissector, whichpreparesthemtoenterthis industry.

Genderissues as they pertainto workandentrepreneurshiphavegainedgreat attention, andonceagain,theGEMdatarevealimportantage-relateddifferencesinentrepreneurship betweenwomen andmen.As Figure17 shows, age-relatedpatternsin female entrepreneurship areverydifferentfromthatofmales.Maleentrepreneurship ratesstartat amuch higher levelthan female ratesintheyoungest

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CHAPTER 3

Knowing an entrepreneur positively influences one’s own entrepreneurial ambitions, offering examples, role models, advisors and collaborators to inspire and support these efforts. Here again, we see higher scores among the age groups with the greatest entrepreneurial activity, the 25 to 44 year olds. The lowest scores on this measure were reported by the very oldest and youngest groups, albeit for likely very different reasons. The younger group is still in the stage of building their professional networks, and the older group, 65 to 74 year olds, is less focused on building networks that could help with future professional activities.

Fear of failure does not vary greatly across age groups; however, it is interesting to note that the highest rate of such fear is among 18 to 24 year olds, while the lowest rates are among those 55 and above. This brings into question the conventional wisdom that young people may make better entrepreneurs because they don’t know enough to be risk averse and have less to lose. More importantly, it suggests that greater perceived skill and stronger networks, and perhaps access to resources, empower individuals to be less fearful of failing.

Entrepreneurship in the U.S. economy is primarily composed of consumer-oriented and business-services businesses. This fact comes through very clearly when we look at industries of focus for entrepreneurs. Very few entrepreneurs report having businesses in the extractive industries such as mining, forestry or agriculture. Nearly 28% of 18 to 24 year olds report having businesses in the transforming or manufacturing industries, and about 15% of entrepreneurs in the other age groups have these types of businesses. The high rates of manufacturing businesses activity among the youngest population represents a significant increase by comparison to the 2014 GEM study, in which 21% of 18 to 24 year olds were starting and running these types of businesses, whereas the older age groups showed levels similar to the 2015 survey.

Business services, the second most popular industry for entrepreneurs, showed wide variability among the age groups, ranging from 22% to 44% but with no steady upward or downward trends along the age groups. Finally, the consumer-oriented businesses represent just under half of the entrepreneurial activity of the sample without too much variability based on age trends. This sector’s popularity is likely the result of the ease in which one can enter it, generally without much capital. Moreover, virtually every potential entrepreneur has experience and knowledge of business in this sector, which prepares them to enter this industry.

Gender issues as they pertain to work and entrepreneurship have gained great attention, and once again, the GEM data reveal important age-related differences in entrepreneurship between women and men. As Figure 17 shows, age-related patterns in female entrepreneurship are very different from that of males. Male entrepreneurship rates start at a much higher level than female rates in the youngest group, and climb to a high at 25 to 34 years old, nearly sustaining this level in the next age group before falling off gradually. Female entrepreneurship, on the other hand, starts at a relatively low level, barely climbing in the 25 to 34 age group before spiking upward for 35 to 44 year olds and then dropping back to the low levels reported in the younger age groups.

The differences among women and men are greatest in the younger demographics: the 18 to 24 and 25 to 34 year olds. Some of the explanations for this include lower rates of work for women during peak childbearing years, greater difficulty in raising capital for women entrepreneurs, and less family support for entrepreneurial careers. Over time, it seems that these differences erode and the TEA rates become almost equal in older groups. If policy makers wish to see higher rates of entrepreneurship among younger women, they will need to continue to address the issues of affordable and accessible childcare and expanded and more reachable sources of financing for women entrepreneurs.

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CHAPTER 3

SUMMARY COMMENTS

Entrepreneurship peaks among 35 to 44 year olds at 17%, and the general population in this age group shows the highest level of opportunity and capability perceptions as well as personally knowing an entrepreneur. When accounting for workforce participation rates among the 55 and over population, it is evident that entrepreneurship, as well as established business ownership, is a key means of employment for those still working in their older years. The higher intentions relative to actual business starts among younger people (ages 18 to 34) bring up questions about whether they have the ambition, but not always the means, to start businesses. On the other hand, higher TEA rates relative to intentions among the 35 to 44 year olds suggest they may have less incentive, but more opportunities and resources, for entrepreneurship. Necessity entrepreneurship is highest among the youngest age group, who as yet have little experience and fewer job alternatives, as well as those in mid-late career, who may be out of jobs and unable to find decent work. Entrepreneurial employees are active throughout prime working ages of 25 to 64 years, peaking among those 35 to 44 years of age.

FIGURE 17 Gender Differences in TEA Rates by Age Group SOURCE OF DATA GEM 2015

group,andclimbtoahighat25to34yearsold,nearlysustainingthislevelinthenextagegroupbeforefallingoffgradually.Femaleentrepreneurship,ontheotherhand,startsatarelativelylowlevel,barelyclimbinginthe25to34agegroupbeforespikingupwardfor35to44yearoldsandthendroppingbacktothelowlevelsreportedintheyoungeragegroups.Thedifferencesamongwomenandmenaregreatestintheyoungerdemographics:the18to24and25to34yearolds.Someoftheexplanationsforthisincludelowerratesofworkforwomenduringpeakchildbearingyears,greaterdifficultyinraisingcapitalforwomenentrepreneurs,andlessfamilysupportforentrepreneurialcareers.Overtime,itseemsthatthesedifferenceserodeandtheTEAratesbecomealmostequalinoldergroups.Ifpolicymakerswishtoseehigherratesofentrepreneurshipamongyoungerwomen,theywillneedtocontinuetoaddresstheissuesofaffordableandaccessiblechildcareandexpandedandmorereachablesourcesoffinancingforwomenentrepreneurs.Figure 17: Gender Differences in TEA Rates by Age Group, GEM 2015

Summary Comments Entrepreneurshippeaksamong35to44yearoldsat17%,andthegeneralpopulationinthisagegroupshowsthehighestlevelofopportunityandcapabilityperceptionsaswellaspersonallyknowinganentrepreneur.Whenaccountingforworkforceparticipationratesamongthe55andoverpopulation,itisevidentthatentrepreneurship,aswellasestablishedbusinessownership,isakeymeansofemploymentforthosestillworkingintheirolderyears.Thehigherintentionsrelativetoactualbusinessstartsamongyoungerpeople(ages18to34)bringupquestionsaboutwhethertheyhavetheambition,butnotalwaysthemeans,tostartbusinesses.Ontheotherhand,higherTEAratesrelativetointentionsamongthe35to44yearoldssuggesttheymayhavelessincentive,butmoreopportunitiesandresources,forentrepreneurship.Necessityentrepreneurshipishighestamongtheyoungestagegroup,whoasyethavelittleexperienceandfewerjobalternatives,aswellasthoseinmid-latecareer,whomaybeoutofjobsandunabletofinddecentwork. Entrepreneurialemployeesareactivethroughoutprimeworkingagesof25to64years,peakingamongthose35to44yearsofage.

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Chapter 4Women’s Entrepreneurship

Globally, women are driving the world economy, controlling about $20 trillion in annual consumer spending, and this is expected to rise to nearly $28 trillion in the next five years.1 In the United States, women hold almost 52% of all professional jobs.2 This year, the number of U.S. women CEOs in Fortune 500 companies reached an all-time high with 24 women leading some of America’s top companies, more than any year since 1998.3 A recent report by the World Economic Forum shows that 35 countries have closed the gender gap in Health and Survival while others have closed the gap in education.4 Similarly, 37 countries have closed the political empowerment gender gap including many from the Middle East, North Africa and Asia Pacific.5

But worldwide, men are still engaged in venture start-up at a greater rate than women. Recent data from the Global Entrepreneurship Monitor Women’s Report show that men are almost 1.5 times more likely to be engaged in early-stage entrepreneurial activity than women.6 The individual economies show considerable variation in female and male entrepreneurial activity.

Factor and efficiency economies have some of the highest rates of entrepreneurial start-up, with some African countries showing more than one-fourth of the female population starting a business, while several Latin American and Asian economies indicate rates of one-fifth or more (see Figure 18). Notably, several of these economies—Peru, Malaysia, Thailand, Vietnam, Indonesia and Philippines—have greater rates of women’s entrepreneurship than men’s. Several other economies—Senegal, Panama, Brazil and Ecuador—have somewhat comparable rates for women and men.

FIGURE 18 TEA Rates for Factor and Efficiency-Driven Economies, by Region and Gender SOURCE OF DATA GEM 2015

Figure 18: TEA Rates for Factor and Efficiency-Driven Economies, by Region and Gender, GEM 2015

Incontrast,theinnovationeconomieshavegenerallylowerratesofstart-upcomparedtootherregionsandasystematically larger gendergap (seeFigure19). In nearlyall theseeconomies,womenarestartingbusinessesat one-halftothree-fourthstherateoftheirmale counterparts.

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1. https://hbr.org/2009/09/the-female-economy 2. Warner, J. (2014). The Women’s Leadership Gap. Center for American Progress.3. http://fortune.com/2014/06/03/number-of-fortune-500-women-ceos-reaches-historic-high/4. http://reports.weforum.org/global-gender-gap-report-2014/part-1/the-global-gender-gap-index-results-in-2014/5. Ibid.6. Kelley, D., Brush, C., Greene, P., Herrington, M., Ali, A., & Kew, P. (2015). Global Entrepreneurship Monitor Women’s Report.

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In contrast, the innovation economies have generally lower rates of start-up compared to other regions and a systematically larger gender gap (see Figure 19). In nearly all these economies, women are starting businesses at one-half to three-fourths the rate of their male counterparts.

For the United States, the gap in women’s start-up is parallel to the gaps in the UK, Australia and Israel. The gap fluctuates, but has not generally narrowed over time, with the rate of men’s entrepreneurship trending at one and a half times that of women since 2001. However, even though there is a gap, the rate of women’s entrepreneurship in the United States is higher than in most of the innovation-driven economies—even twice the rate of many innovation-driven European countries.

Within the United States, a five-state analysis reflects regional differences. In New York, the TEA rates for women and men are equal (10%), with a narrow gap reported in Texas and a slightly wider gap reported in Ohio. The gap in Florida is similar to the national-level gap, but widens in California, with men reporting over 70% higher TEA rates.

As Chapter 4 reveals, an analysis of entrepreneurship rates by age shows that TEA rates are low among young women, then spike upward among 35 to 44 year olds before falling off in the older female populations to rates similar to those reported in the youngest age groups. On the other hand, men maintain high rates throughout most of their working years, before tapering off to rates similar to women after age 55. While caring for children might explain lower rates in young women, it is curious that late-career women also exhibit low rates, particularly when labor force participation rates for women are relatively constant from ages 25 through 54.7 The upward swing among 35 to 44-year-old women may reveal the popularity of entrepreneurship as a job alternative for women re-entering the workforce after caring for children. On the other hand, entrepreneurship may simply appeal to women who have accumulated experience and knowledge during their early career, compared to work as an employee.

7 United States Bureau of Labor Statistics: bls.gov.

CHAPTER 4

FIGURE 19 TEA Rates for

Innovation-Driven Economies, by

Region and Gender


Figure 19: TEA Rates for Innovation-Driven Economies, by Region and Gender, GEM 2015

For theUnited States, thegap in women’s start-upis parallel tothe gaps in the UK, AustraliaandIsrael.The gap fluctuates, but has not generally narrowed over time, with the rate of men’s entrepreneurshiptrending at one anda half times that of womensince 2001. However, eventhoughthere is a gap, therate of women’s entrepreneurship in the UnitedStates is higher thanin most of the innovation-driveneconomies—even twicetherateof many innovation-drivenEuropeancountries.

Withinthe United States, a five-state analysisreflectsregionaldifferences.In NewYork,theTEAratesforwomen and men areequal (10%), with anarrow gap reported in Texas and aslightly wider gapreported in Ohio. Thegap in Florida is similar to the national-level gap, but widens inCalifornia, withmen reportingover 70% higher TEA rates.

As Chapter 4reveals, an analysis of entrepreneurship rates by age shows that TEA rates are low amongyoung women, thenspike upward among 35 to 44 year olds before falling off in the older femalepopulations torates similar tothose reportedinthe youngest age groups. Onthe other hand, menmaintain high rates throughout most of their workingyears, before tapering off to rates similar towomen after age 55. While caring for children might explainlower rates in young women, it is curiousthatlate-career women also exhibit low rates, particularly when labor force participation rates forwomen are relatively constant from ages 25 through54.10 The upward swing among 35-to44-year-oldwomen may reveal the popularity of entrepreneurship as a jobalternative for women re-enteringtheworkforce after caring for children. On the other hand, entrepreneurship may simply appeal to womenwho have accumulated experience and knowledgeduring their early career, compared to work as anemployee.

10 UnitedStates Bureau of LaborStatistics:bls.gov.

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CHAPTER 4

ATTITUDES ABOUT ENTREPRENEURSHIP AMONG WOMEN IN THE UNITED STATES

Key attitudes related to entrepreneurship include perceived opportunity, perceived capability to start a business, fear of failure and intention to start a business. In the United States, approximately 55% of men perceive opportunities compared to 44% of women, and this differential has remained somewhat steady over the past five years, but generally narrower than the first decade of this century (see Figure 20).

The perception of one’s capability to start a business is a second key attitude. People who believe they have the business skills and competencies to launch a venture, build a team and run the business are more likely to plan to start a business.8 When comparing women and men in the United States, perceived capabilities for starting a business vary significantly, with 62% of men believing they are capable compared to 50% of women. This gap has narrowed slightly in the past year but remains substantial over time. This suggests that men have more confidence in their ability to start a business or have had more relevant training or experience.

A third key attitude is fear of failure. Fear of failure encompasses fear of social failure (What will others think?), fear of personal failure (psychic risk), fear of monetary failure (What if I lose all my money?) and several other concerns. For this attitude, we see another gender gap, with women exhibiting a higher perceived rate of failure of 33% to 27% for men. The gender differential is somewhat narrower in 2015 than in 2014, but still shows a consistent gap.

It is not surprising that the gaps between women and men in attitudes toward opportunities, capabilities and failure are comparable to intentions to start a business. For those seeing an opportunity, we do see a slight improvement in women’s intentions to start businesses from 10% to 11% since 2014, which does narrow the gap somewhat with men (14%). This slight improvement is possibly related to increased support for women through women-focused training programs, accelerators, networks and platforms such as the U.S. Women’s Chamber of Commerce, the National Association of Women Business Owners, the Women’s Business Development Council and other platforms such as Ladies Who Launch, Chic CEO and eWomenNetwork.9

Considering results of these three attitudes together, it appears that the gender gap in TEA in the United States is related to attitudes women have toward opportunities, capabilities and failure. Most entrepreneurship in the United States is opportunity-driven rather than necessity-based, meaning that women and men have other possible sources of employment. The gap between women and men might be explained by several factors; for instance, women are more likely to have interrupted career pathways and therefore may have less confidence in their entrepreneurial skills and capabilities.10

Attitudes about Entrepreneurship among Women in the United States

Keyattitudesrelated to entrepreneurship includeperceivedopportunity, perceivedcapabilitytostartabusiness, fear offailure andintentiontostartabusiness. Inthe UnitedStates,approximately55%ofmen perceive opportunitiescomparedto 44%of women,andthis differential hasremainedsomewhatsteadyoverthepastfiveyears,butgenerallynarrowerthanthefirstdecadeofthiscentury(seeFigure20).

Figure 20: Perceived Opportunities among Women and Men in the United States, GEM 2015

Theperceptionofone’scapabilityto start abusinessis asecondkeyattitude. People whobelievetheyhavethe businessskills andcompetenciestolaunchaventure, builda team andrunthe businessaremorelikely to plan to startabusiness.11 WhencomparingwomenandmenintheUnitedStates,perceivedcapabilities for startingabusinessvary significantly,with62%ofmenbelievingtheyarecapable comparedto 50%ofwomen.Thisgaphasnarrowedslightlyinthepastyearbutremainssubstantialovertime.Thissuggeststhatmenhavemore confidencein their abilityto start abusinessorhavehadmore relevanttraining orexperience.

Athirdkey attitude is fear offailure.Fear offailure encompassesfear ofsocialfailure (Whatwillothersthink?),fearofpersonalfailure(psychic risk),fearofmonetaryfailure(WhatifIloseallmymoney?) andseveralotherconcerns.Forthisattitude,weseeanothergendergap,withwomenexhibitingahigherperceivedrate offailure of33%to 27%formen.Thegenderdifferentialis somewhatnarrowerin2015thanin 2014,butstillshowsaconsistentgap.

Itisnotsurprisingthatthegaps betweenwomenandmeninattitudestowardopportunities,capabilitiesandfailure are comparable to intentionstostart abusiness.Forthoseseeinganopportunity,wedo seeaslight improvementin women’s intentionsto start businessesfrom10%to 11%since2014,which does narrowthegapsomewhat withmen (14%).This slightimprovement is possiblyrelatedtoincreasedsupportforwomen throughwomen-focusedtrainingprograms,accelerators,networksand

11 GEM 2015/2016 Global Report.p.16.

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FIGURE 20 Perceived Opportunities among Women and Men in the United States. SOURCE OF DATA GEM 2001–2015

8. GEM 2015/2016 Global Report. p. 16.9. http://www.skilledup.com/articles/startup-business-help-resources-women-entrepreneurs10. Brush, C.G., Carter, N.M. Gatwood, E.J., Greene, P.G, & Hart, M. (2004). Clearing the Hurdles. Englewood Cliffs, NJ: Prentice Hall.

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Alternatively, women may not have the full support of their family or networks because women are often expected to care for family rather than be entrepreneurs. Many societies continue to ascribe housebound and family-related roles to women, thus implicitly marking entrepreneurship as a less-desirable career choice for women.11 Social encouragement leads to the likelihood of a successful venture start-up, and resources available to the entrepreneur are influenced by household size, the household head and the health of the household members.12 Family support is important to women, in that women receiving less social support from their families are more likely to have less confidence in their entrepreneurial activities, and they would therefore be more deeply embedded in their family, having lesser propensity to launch a venture.

Further, gender stereotyping may also play a role, in that entrepreneurship is more often associated with men than women, which results in fewer role models for women. Gender stereotypes are widely shared beliefs about characteristics attributed to women and men; they are common in U.S. society and can exert a powerful influence on the way people think and behave as well as the perceived appropriateness of behavior.13 Gender stereotypes suggest that the practice of entrepreneurship overall is seen as a masculine behavior.14 These are reinforced by the media, which promote representations of entrepreneurs as primarily male. Therefore, even though the GEM data show that 33% of men and 27% of women are likely to know entrepreneurs, women may be less likely to see themselves in an entrepreneurial role because of the perpetuation of entrepreneurship as a male occupation.

BUSINESS CHARACTERISTICS AND PERFORMANCE

As reported in past years, women entrepreneurs are much more likely to start businesses in consumer-oriented sectors than in other sectors (see Figure 21). Men entrepreneurs, on the other hand, are equally likely to start businesses in the consumer-oriented and business-services sectors. These breakdowns parallel the general population of U.S. businesses, where retail trade and consumer services compose a significant proportion of firms. While men are more likely to work in construction, women are more likely to be found in businesses that serve consumers directly.15

11 Pfau-Effinger, B. (2004). Development of Culture, Welfare States and Women’s Employment in Europe. Aldershot: Ashgate.

12 Brush, C., & Manolova, T. (2004). Household Structure. In Gartner, W.B., Shaver, K., Carter, N., & Reynolds, P. Handbook of Entrepreneurial Dynamics: The Process of Business Creation. Thousand Oaks: Sage Publications, 78-94.

13 Heilman, M.E. (1983). “Sex bias in work settings: The lack of fit model,” Research in Organizational Behavior 5, 269;Fiske, S.T. (2000). “Stereotyping, prejudice, and discrimination at the seam between the centuries: Evolution, culture, mind, and brain,” European Journal of Social Psychology. 30(3): 299-322.

14 Bruni, A., Gherardi, S., & Poggio, B. (2004). “Doing gender, doing entrepreneurship: An ethnographic account of intertwined practices,” Gender, Work & Organization. 11(4): 406-429;Bird, B., & Brush, C. (2002). “A gendered perspective on organizational creation,” Entrepreneurship Theory and Practice 26, 41-65.

15 https://www.sba.gov/sites/default/files/advocacy/SB%20Profiles%202014-15_0.pdf

equally likely to start businesses in the consumer-oriented and business-services sectors. Thesebreakdowns parallel the general populationof U.S.businesses, where retail trade andconsumer servicescomposea significant proportionof firms. While menare more likely towork inconstruction, womenaremorelikely to befound in businesses that serveconsumers directly.18

Figure 21: Industry Sector Distribution of Female and Male TEA Activity, GEM 2015

Thesectorsinwhichwefindwomen andmenstartingbusinessesarelikelyrelatedtotheamount andsource of start-upfunding. Womenentrepreneurs launchtheir businesses withhalf of what mendo(anaverageof $10,000versus $20,000). Thisispossibly linked to thefact that startingabusiness inconsumer services requires less capital, whereas starting a venture inmanufacturing or businessservicesoftenrequiresmorecapital.Alternatively,womenmayhavelessoftheirown money to investin business start-ups, whichcould, inpart, be relatedtocareer breaks andresult ina smalleraccumulationof financial capital.19

The GEM data shows that women are slightly less likely than men to use crowdfunding, but otherresearchshows that their campaigns tendtobe very successful. Onaverage, a woman’s crowdfundingcampaign receives 1.3 morecontributors thana male-led campaign, raisingan averageof 10.75% moremoney. However, this amount is relatively small compared to other funding sources: $7,000 over anine-week campaign.20 Recently, several new crowdfundingplatforms haveemerged that focuson womenentrepreneurs. Plum Alley supports women entrepreneurs, and Indiegogo notes successful women’scampaigns run on the site. Chapter 7 provides more information on finance, including gendercharacteristics.

18 https://www.sba.gov/sites/default/files/advocacy/SB%20Profiles%202014-15_0.pdf

19 Arun, S., Arun, T., & Borooah,V.K.(2004). “The Effect of Career Breaks on the Working Livesof Women,”Feminist Economics. 10(1): 65-84.20 https://www.fundable.com/crowdfunding101/crowdfunding-statistics

Extraceve 3%

Transforming

19%

Business Services

39%

Consumer Oriented

39%

MALE

Extraceve 3% Transform

ing 15%

Business Services

23%

Consumer Oriented

59%

FEMALE FIGURE 21

Industry Sector Distribution of

Female and Male TEA Activity


CHAPTER 4

CHAPTER 4

35

The sectors in which we find women and men starting businesses are likely related to the amount and source of start-up funding. Women entrepreneurs launch their businesses with half of what men do (an average of $10,000 versus $20,000). This is possibly linked to the fact that starting a business in consumer services requires less capital, whereas starting a venture in manufacturing or business services often requires more capital. Alternatively, women may have less of their own money to invest in business start-ups, which could, in part, be related to career breaks and result in a smaller accumulation of financial capital.16

The GEM data show that women are slightly less likely than men to use crowdfunding, but other research shows that their campaigns tend to be very successful. On average, a woman’s crowdfunding campaign receives 1.3 more contributors than a male-led campaign, raising an average of 10.75% more money. However, this amount is relatively small compared to other funding sources: $7,000 over a nine-week campaign.17 Recently, several new crowdfunding platforms have emerged that focus on women entrepreneurs. Plum Alley supports women entrepreneurs, and Indiegogo notes successful women’s campaigns run on the site. Chapter 7 provides more information on finance, including gender characteristics.

When it comes to product-market innovations, 2015 marks the first year since 2011 that women entrepreneurs have been less likely to innovate. This is somewhat surprising because the general trend for women was on the rise until 2014. Figure 22 shows that innovation levels increased among male entrepreneurs, after several relatively stagnant years. Women, on the other hand, have fallen back below 2011 levels after exhibiting year-on-year increases in this indicator for several years.

A comparison of profit expectations among women and men entrepreneurs shows that in 2014, nearly 63% of women expected to be profitable in the current year compared to 61% of men. In 2015, the percentage of men expecting profitability remained steady (61%), while the percentage of women dropped to 50%. The lower result for women on this indicator may be related to the industry sector: Women entrepreneurs are more active in consumer products and services, and the competition in this sector is more intense and difficult to differentiate.

16 Arun, S., Arun, T., & Borooah, V.K. (2004). “The Effect of Career Breaks on the Working Lives of Women,” Feminist Economics. 10(1): 65-84.

17 https://www.fundable.com/crowdfunding101/crowdfunding-statistics

17 https://www.fundable.com/crowdfunding101/crowdfunding-statistics

FIGURE 22 New Product- Market Combinations by Gender (Percentage of TEA) SOURCE OF DATA GEM 2002–2015

Whenitcomestoproductmarketinnovations,2015marksthefirstyearsince2011thatwomenentrepreneurshavebeenlesslikelytoinnovate.Thisissomewhatsurprisingbecausethegeneraltrendforwomenwasontheriseuntil2014.Figure22showsthatinnovationlevelsincreasedamongmaleentrepreneurs,afterseveralrelativelystagnantyears.Women,ontheotherhand,havefallenbackbelow2011levelsafterexhibitingyear-on-yearincreasesinthisindicatorforseveralyears.Figure 22: New Product Market Combinations by Gender (Percentage of TEA), GEM 2015

Acomparisonofprofitexpectationsamongwomenandmenentrepreneursshowsthatin2014,nearly63%ofwomenexpectedtobeprofitableinthecurrentyearcomparedto61%ofmen.In2015,thepercentageofmenexpectingprofitabilityremainedsteady(61%),whilethepercentageofwomendroppedto50%.Thelowerresultforwomenonthisindicatormayberelatedtotheindustrysector:Womenentrepreneursaremoreactiveinconsumerproductsandservices,andthecompetitioninthissectorismoreintenseanddifficulttodifferentiate.Established Business Activity, Discontinuance and Entrepreneurial Employee Activity Besidesentrepreneurialactivityinanindependentstart-up,GEMmeasuressubsequentphasesanddifferenttypesofentrepreneurship.Establishedbusinessactivityrepresentsownershipandmanagementofbusinessesmorethanthree-and-a-halfyearsold.In2015,justunder6%ofthefemaleworking-agepopulationintheUnitedStatesincludedestablishedbusinessowners.Atjustover9%,menwereabouttwo-thirdsmorelikelytoengageinthismaturephaseofthebusinessprocess.Discontinuanceamongwomenisslightlybelow4%andslightlyabovethisnumberformen.Withlowerstart-upactivity,alowerdiscontinuanceratemightbeexpectedforwomencomparedtomen.Entrepreneurialemployeeactivityreflectsthatentrepreneurshipcanoccurnotjustinindependentstart-ups,butalsoinexistingorganizations.Inthiscontext,womenrarelyparticipate:Only3.3%ofthefemaleworking-agepopulationstatedthattheyareengagedinentrepreneurialactivityfortheiremployer.Incontrast,7.6%ofmenareentrepreneurialemployees,overtwo-and-a-halftimesthefemalerate.Whilewomenmayfaceparticularconstraintsfromtheenvironmentrelativeto

33%

28%

26%

32%31% 35%

26%

22%

29% 33% 33% 32%34%

39%

29%27%

20%

28%

36%

27%30%

26%

34%36%

38%41%

32%

10%

15%

20%

25%

30%

35%

40%

45%

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

Male Female

36

CHAPTER 4

ESTABLISHED BUSINESS ACTIVITY, DISCONTINUANCE AND ENTREPRENEURIAL EMPLOYEE ACTIVITY

Besides entrepreneurial activity in an independent start-up, GEM measures subsequent phases and different types of entrepreneurship. Established business activity represents ownership and management of businesses more than three-and-a-half years old. In 2015, just under 6% of the female working-age population in the United States included established business owners. At just over 9%, men were about two-thirds more likely to engage in this mature phase of the business process. Discontinuance among women is slightly below 4% and slightly above this number for men. With lower start-up activity, a lower discontinuance rate might be expected for women compared to men.

Entrepreneurial employee activity reflects that entrepreneurship can occur not just in independent start-ups, but also in existing organizations. In this context, women rarely participate: Only 3.3% of the female working-age population stated that they are engaged in entrepreneurial activity for their employer. In contrast, 7.6% of men are entrepreneurial employees, over two-and-a-half times the female rate. While women may face particular constraints from the environment relative to independent start-up activity, these results leave questions about the barriers that may exist for women in organizations.

SUMMARY COMMENTS

Overall, women entrepreneurs continue to be an important part of the U.S. economy, and women in the United States are starting businesses at a greater rate than in many other innovation-driven economies. Nevertheless, a gender gap exists between women and men in terms of start-up rate, and this parallels gender gaps in attitudes: in particular, perceived opportunities, perceived capabilities, fear of failure and intention to act on an opportunity. Age-related patterns in entrepreneurial activity may explain the gender gap—while men report high rates of entrepreneurship throughout their working ages, women in the younger and older age groups report low activity. In addition, women are more likely to start businesses in consumer products and services, using less funding to get started. Innovation levels among women dropped in 2015 to 32% of entrepreneurs, versus 41% in 2014. This represents a reversal of a four-year trend where women reported higher innovation rates than men. Women rarely participate in employee entrepreneurship and exhibit relatively low rates of established business ownership, indicating the importance of recognizing gaps across phases and types of entrepreneurship.

37

Chapter 5Impact Characteristics of Entrepreneurship in the United States: 2001-2015

INDUSTRY SECTOR PARTICIPATION

A key indicator of entrepreneurship’s impact on society relates to industry sector participation. While some economies may promote the development of specific industries, highly developed economies more commonly progress toward knowledge-intensive activities and an expansion of the service sector. At early stages of economic development, the consumer-oriented sector accounts for the majority of entrepreneurial activity. At higher development levels, business services start to replace that sector and, to a lesser extent, the transforming activity sector.

As Figure 23 shows, the consumer-oriented and business-service sectors represent the majority of U.S. entrepreneurial activity since 2007. The consumer sector had accounted for around 42% to 45% of most early-stage entrepreneurial activity for most of the past decade before edging up to 47% in 2015. At the same time, the business-services sector experienced its peak at 39% in 2008 and has fluctuated after that, declining steadily in the previous two years. In 2015, 33% of early-stage businesses operated in this sector. Business start-ups in the transforming sectors decreased in 2015, following a generally declining trend beginning in 2005, while the extractive sector remains a steady but small segment of the early-stage business population.

FIGURE 23 Longitudinal Trends in Percentage of Total Entrepreneurial Activity in Major Industrial Sectors SOURCE OF DATA GEM 2001–2015

ImpactCharacteristicsofEntrepreneurshipintheUnitedStates:2001-2015IndustrySectorParticipationAkeyindicatorofentrepreneurship’simpactonsocietyrelatestoindustrysectorparticipation.Whilesomeeconomiesmaypromotethedevelopmentofspecificindustries,highlydevelopedeconomiesmorecommonlyprogresstowardknowledge-intensiveactivitiesandanexpansionoftheservicesector.Atearlystagesofeconomicdevelopment,theconsumer-orientedsectoraccountsforthemajorityofentrepreneurialactivity.Athigherdevelopmentlevels,businessservicesstarttoreplacethatsectorand,toalesserextent,thetransformingactivitysector.AsFigure23shows,theconsumer-orientedandbusiness-servicesectorsrepresentthemajorityofU.S.entrepreneurialactivitysince2007.Theconsumersectorhadaccountedforaround42%to45%ofmostearly-stageentrepreneurialactivityformostofthepastdecadebeforeedgingupto47%in2015.Atthesametime,thebusiness-servicessectorexperienceditspeakat39%in2008andhasfluctuatedafterthat,decliningsteadilyintheprevioustwoyears.In2015,33%ofearly-stagebusinessesoperatedinthissector.Businessstart-upsinthetransformingsectorsdecreasedin2015,followingagenerallydecliningtrendbeginningin2005,whiletheextractivesectorremainsasteadybutsmallsegmentoftheearly-stagebusinesspopulation.Figure 23: Longitudinal Trends in Percentage of Total Entrepreneurial Activity in Major Industrial Sectors (2001-2015)

Source:GlobalEntrepreneurshipMonitorUnitedStates2015AdultPopulationSurveyJobExpectationsFounderexpectationsthattheywillcreatejobswiththeirbusinessescanserveasasignalthattheybelievetheyhaveahighpotentialopportunityandcandrawontheirambitions,capabilitiesandhuman,

Extracpve,3%

Transforming,17%

BusinessServices,33%

ConsumerOriented,47%

0%

10%

20%

30%

40%

50%

60%

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

38

JOB EXPECTATIONS

Founder expectations that they will create jobs with their businesses can serve as a signal that they believe they have a high potential opportunity and can draw on their ambitions, capabilities and human, financial and other resources to grow their businesses. Growth-oriented entrepreneurs may not represent the majority of entrepreneurs, yet they can account for much of the job creation and economic development in a society.

As Figure 24 shows, since 2001, at least 30% of U.S. entrepreneurs have expectations to create at least six jobs in the next five years. The expectations have fluctuated from 30% in 2004 to 45% in 2014. In 2015, these expectations dipped to 39% of all entrepreneurs. These fluctuations correspond with the overall changes in the TEA rate in some cases: When TEA rates declined after the 2007–2008 recession, among those that did start, fewer expected to create six or more jobs in the next five years. Additionally, TEA rates declined in 2015, and the proportion with six or more job expectations did as well.

Since established business owners are running businesses more than three-and-a-half years old, it is possible to track actual job growth. As Figure 25 shows, in 2015, 9% of established business owners reduced their employee count, while 69% maintained the same level of employment. Only 22% added at least one job, less than was reported in 2014.

FIGURE 24 Longitudinal

Trends in Percentage of Entrepreneurs

Expecting to Create 6+ Jobs in the Next

Five Years


FIGURE 25 Changes in Employee Count from Previous Year in Established

Business Owners


Figure 25: Changes in Employee Count from Previous Year in Established Business Owners, GEM 2015

Profitability may be difficult tomeasure inentrepreneurs, not only because they haven’t beeninbusiness long enough, but alsobecausesomemay forego short-term profits tobuildlonger-termpotential. Inaddition, predictions about profitability may be difficult because of the higher degree ofuncertainty that characterizes this stage. Establishedbusinesses, onthe other hand, have been up andrunning for at least three-and-a-half years, andprofitabilitymaybemorereliablyassessed.In2015,68%of establishedbusiness owners expectedtobe profitable inthe current year, downfrom 91% in 2014.

InnovationNew businesses basedoninnovativeproducts and services createasourceof competitiveadvantageforthe entrepreneurs that introduce them as well as new value for the people intheir societies whousethese novel products andservices. Additionally, whenentrepreneurs commercializenew concepts,technologies andknowledge, their innovations contribute totheir economy’s global competitiveness.Figure 26 presents trends inthe percentage of entrepreneurs withinnovative products andservices.

From 2011 to 2015, over one-thirdof U.S. entrepreneursreported selling productsor servicesthat arenew tosome or all customers andwithfew or nocompetitors. This indicator hit its lowest level inthepost-2007–2008 recessionperiod, andhas since stabilizedat higher levels. Innovationlevels have beenconsistently lower amongestablished business owners, which is not surprisingsinceentrepreneurs aremorelikely to needinnovativeofferings to establish afoothold in the market.

9% 9%

64% 69%

11%9%

8% 6%9% 7%

2014 2015

Added3ormorejobs

Added2jobs

Added1job

Nonewjobs

Reducedemployeecount

financial and other resources to grow their businesses. Growth-orientedentrepreneurs may notrepresent the majority of entrepreneurs, yet they can account for much of thejob creation andeconomic development in asociety.

AsFigure24 shows, since 2001, at least 30% of U.S. entrepreneurs have expectations tocreate at leastsixjobsinthenextfiveyears.The expectations have fluctuatedfrom 30% in2004 to45% in2014. In2015, these expectations dippedto39% of all entrepreneurs. These fluctuations correspondwiththeoverall changes inthe TEArate insome cases: WhenTEA rates declined after the 2007–2008 recession,among those thatdid start, fewerexpected to create six or more jobs inthe next five years. Additionally,TEArates declinedin2015, andthe proportionwithsixormore job expectations did as well.

Figure 24: Longitudinal Trends in Percentage of Entrepreneurs Expecting to Create 6+ Jobs in the NextFive Years, 2001-2015

Source: Global EntrepreneurshipMonitor UnitedStates 2015 Adult PopulationSurvey

Since establishedbusiness owners are running businesses more thanthree-and-a-half years old, it ispossible totrack actual jobgrowth. As Figure 25 shows, in2015, 9% of establishedbusiness ownersreducedtheir employee count, while 69% maintainedthe same level of employment. Only 22% addedatleast onejob, lessthanwas reportedin 2014.

36%

42%

32%30%

42%

36% 35%

43%

31%

38% 38% 37% 37%

45%

39%

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

financial and other resources to grow their businesses. Growth-orientedentrepreneurs may notrepresent the majority of entrepreneurs, yet they can account for much of thejob creation andeconomic development in asociety.

AsFigure24 shows, since 2001, at least 30% of U.S. entrepreneurs have expectations tocreate at leastsixjobsinthenextfiveyears.The expectations have fluctuatedfrom 30% in2004 to45% in2014. In2015, these expectations dippedto39% of all entrepreneurs. These fluctuations correspondwiththeoverall changes inthe TEArate insome cases: WhenTEA rates declined after the 2007–2008 recession,among those thatdid start, fewerexpected to create six or more jobs inthe next five years. Additionally,TEArates declinedin2015, andthe proportionwithsixormore job expectations did as well.

Figure 24: Longitudinal Trends in Percentage of Entrepreneurs Expecting to Create 6+ Jobs in the NextFive Years, 2001-2015


Since establishedbusiness owners are running businesses more thanthree-and-a-half years old, it ispossible totrack actual jobgrowth. As Figure 25 shows, in2015, 9% of establishedbusiness ownersreducedtheir employee count, while 69% maintainedthe same level of employment. Only 22% addedatleast onejob, lessthanwas reportedin 2014.

36%

42%

32%30%

42%

36% 35%

43%

31%

38% 38% 37% 37%

45%

39%

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

CHAPTER 5

39

CHAPTER 5

Profitability may be difficult to measure in entrepreneurs, not only because they haven’t been in business long enough, but also because some may forego short-term profits to build longer-term potential. In addition, predictions about profitability may be difficult because of the higher degree of uncertainty that characterizes this stage. Established businesses, on the other hand, have been up and running for at least three-and-a-half years, and profitability may be more reliably assessed. In 2015, 68% of established business owners expected to be profitable in the current year, down from 91% in 2014.

INNOVATION

New businesses based on innovative products and services create a source of competitive advantage for the entrepreneurs that introduce them as well as new value for the people in their societies who use these novel products and services. Additionally, when entrepreneurs commercialize new concepts, technologies and knowledge, their innovations contribute to their economy’s global competitiveness. Figure 26 presents trends in the percentage of entrepreneurs with innovative products and services.

From 2011 to 2015, over one-third of U.S. entrepreneurs reported selling products or services that are new to some or all customers and with few or no competitors. This indicator hit its lowest level in the post-2007–2008 recession period, and has since stabilized at higher levels. Innovation levels have been consistently lower among established business owners, which is not surprising since entrepreneurs are more likely to need innovative offerings to establish a foothold in the market.

FIGURE 26 Longitudinal Trends in Percentage of Total Entrepreneurial Activity and New Business Ownership with New Product-Market Innovations SOURCE OF DATA GEM 2002–2015

Figure 26: Longitudinal Trends in Percentage of Total Entrepreneurial Activity and New Business Ownership with New Product/Market Innovations, 2002–2015

Source:GlobalEntrepreneurshipMonitorUnitedStates2015AdultPopulationSurveyTechnologyNewbusinessescanfindfertilegroundinsellingproductsorserviceswithatechnologyemphasis,andpolicymakersgenerallyencouragethistypeofbusinessactivityatthemacrolevel.Figure27showstrendsregardingearly-stagebusinessessellingproductsorservicesbasedonnewtechnology.Thiscanincludenon-technologyfirmsthatusethelatesttechnologyinsomeaspectofthebusiness:forexample,insalesorproduction.Since2002,thisindicatorhasfluctuatedwidely,rangingfromalowof4%inthepost-recessionperiod(2009)toahighof13%(2004and2007).However,since2010,thisindicatorhasbeenonagradualupwardtrend.Thepercentageofearly-stagebusinessesusingnewtechnologyrosefrom8%in2014to10%in2015. Figure 27: Longitudinal Trends in Percentage of Total Entrepreneurial Activity Offering Products or Services Based on New Technology (2002–2015)

Source:GlobalEntrepreneurshipMonitorUnitedStates2015AdultPopulationSurvey

32%

28% 27% 27%30%

36%

26%25%

28%

34% 34% 34%37% 36%

12%15%

17%14%

21%

16% 15%

12%14% 13%

18%

13%

18% 18%

0%

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2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

TEA EstablishedBusinessOwnership

12%

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13%

8%

7%

13%

6%

4%

7%

9%

7%

11%

8%10%

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6%

8%

10%

12%

14%

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

40

TECHNOLOGY

New businesses can find fertile ground in selling products or services with a technology emphasis, and policy makers generally encourage this type of business activity at the macro level. Figure 27 shows trends regarding early-stage businesses selling products or services based on new technology. This can include non-technology firms that use the latest technology in some aspect of the business: for example, in sales or production. Since 2002, this indicator has fluctuated widely, ranging from a low of 4% in the post-recession period (2009) to a high of 13% (2004 and 2007). However, since 2010, this indicator has been on a gradual upward trend. The percentage of early-stage businesses using new technology rose from 8% in 2014 to 10% in 2015.

INTERNATIONALIZATION

The United States offers a highly competitive but dynamic environment for entrepreneurs, constantly revealing gaps that can be filled by entrepreneurial offerings. The market is large and diverse, with customers who are willing to try entrepreneurial solutions. Although the entrepreneurship ecosystem is not perfect, U.S. entrepreneurs can more predictably rely on the institutional and other factors that influence their efforts, compared to other unfamiliar international terrains. Perhaps for these and other reasons, U.S. entrepreneurs appear to see little reason to venture outside U.S. soil. Internationalization has remained low among U.S. entrepreneurs since 2009, with between 11% and 13% of entrepreneurs reporting 25% or more international customers. Although this indicator edged up to nearly 15% in 2014, the percentage dropped to just under 12% in 2015.

SUMMARY COMMENTS

In 2015, the impact of entrepreneurship in the United States varied based on different dimensions. Entrepreneurs continued a longer-term trend toward an increased level of technology-based businesses and a replacement of capital-intensive manufacturing with knowledge-intensive services and more consumer-oriented businesses. Near-term indicators to watch are job creation potential and the level of business service activity, which dipped from last year, and internationalization, which dropped back to its low post-recession levels. Compared to 2014, fewer established business owners added jobs last year, and a smaller number expected to be profitable in 2015.

CHAPTER 5

Figure 26: Longitudinal Trends in Percentage of Total Entrepreneurial Activity and New BusinessOwnership with New Product/Market Innovations, 2002–2015


TechnologyNewbusinessescanfindfertilegroundinsellingproducts or services witha technology emphasis, andpolicy makers generally encourage this type of business activity at the macrolevel. Figure 27 showstrends regarding early-stage businesses selling products or services basedonnew technology. This canincludenon-technology firms that use the latest technology insome aspect of the business: for example,in sales or production. Since2002, this indicator has fluctuated widely, rangingfrom alow of 4% in thepost-recessionperiod(2009) toa highof 13% (2004and 2007). However, since2010, this indicator hasbeenona gradual upwardtrend. The percentage of early-stage businesses using new technology rosefrom 8% in 2014to 10% in 2015.

Figure 27: Longitudinal Trends in Percentage of Total Entrepreneurial Activity Offering Products orServices Based on New Technology (2002–2015)

Source:Global EntrepreneurshipMonitor UnitedStates 2015 Adult PopulationSurvey

32%

28% 27% 27%30%

36%

26%25%

28%

34% 34% 34%37% 36%

12%15%

17%14%

21%

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12%14% 13%

18%

13%

18% 18%

0%

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2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

TEA EstablishedBusinessOwnership

12%

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9%

7%

11%

8%10%

0%

2%

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6%

8%

10%

12%

14%

2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015

FIGURE 27 Longitudinal Trends

in Percentage of Total Entrepreneurial

Activity Offering Products or Services

Based on New Technology


41

Chapter 6Financing Entrepreneurship

Globalization, changes in technology and social awareness have provided an impetus to develop capital flows from diverse sources. While traditional forms of entrepreneurial finance, such as self-funding and borrowing from friends and family continue, other financing sources such as peer-to-peer lending, including crowdfunding and microfinance, have increased. These changes have been supported by new legislation. In October 2015, the U.S. Securities and Exchange Commission adopted rules to permit companies to offer and sell securities through crowdfunding,1 opening the door to peer-to-peer lending on an unprecedented level and permitting companies to raise up to $1 million over a 12-month period. Many entrepreneurs in the United States are quickly adopting new financing methods, and this trend will likely continue.

The focus on entrepreneurship in the United States is on the rise largely through the development of its entrepreneurial ecosystem, which benefitted from the attention of government, educational programs and popular culture through communications media such as television, radio, and digital and print content. In 2010, the U.S. Office of Innovation and Entrepreneurship (OIE) was created in the Department of Commerce through the America Competes Act of 2010.2 The Small Business Administration (SBA) has increased the scope and breadth of skill-building workshops for entrepreneurs and of special programs targeted at women and veterans.3

Colleges and universities have emphasized cultivating venture accelerators and entrepreneurship curricula, in some cases partnering with corporations on projects. Corporations, such as Johnson & Johnson, have initiated innovation labs in support of independent entrepreneurial efforts. Incubators and maker movement facilities and resources are on the rise. A culture of innovation is being fostered in the popular press, as seen by the growth in the number of articles, magazines, and television and radio programs dedicated to the topic. Finance is an important facilitator of entrepreneurship, complementing these efforts to increase the visibility and impact of America’s start-ups.

Entrepreneurs needed a median level of $17,500 to start their businesses and funded 57% of this from their own money. To gather the rest of the financing, entrepreneurs turned to a variety of sources. They drew from their personal networks; 24% obtained start-up money from family, 15% from friends, and 16% from employers or work colleagues (see Figure 28).

Private equity or venture capital, often considered the key source of funding for new ventures, provided capital to 24% of entrepreneurs. More notably, while banks are often considered a less viable source of entrepreneurial finance, mainly because they are considered too conservative and require immediate and ongoing payments of principal and interest, they nonetheless represent the most popular source of financing start-ups in America, other than one’s own personal funds. Banks were cited as a funding source by 36% of entrepreneurs. This may come as less of a surprise when considering that the more typical start-up in the United States, as in most countries, is not the fast-growing technology venture often highlighted in the media. Additionally, banks may be an easier source to tap in the early stages, for the relatively small amount needed to get started.

Government funding is important to entrepreneurship in the United States, as 21% of entrepreneurs gained financial support from the government. Crowdfunding, a relatively new source of start-up finance, was used by 12% of entrepreneurs.

1 “Title III of the JOBS Act created a federal exemption under the securities laws so that this type of funding method can be used to offer and sell securities.” U.S. Securities and Exchange Commission, October 30, 2015. https://www.sec.gov/news/pressrelease/2015-249.html

2 The OIE “promotes and supports high-growth entrepreneurship, accelerates commercialization of federally funded research, works with other agencies and the White House to collaborate on policies and programs to support entrepreneurship and commercialization, supports the National Advisory Council on Innovation and Entrepreneurship (NACIE), and leads the Regional Innovation Strategies Program. https://www.eda.gov/oie/

3 https://www.sba.gov

42

CHAPTER 6

43

CHAPTER 6

Necessity entrepreneurs, motivated by the need to find work, required an average of $22,000 to start ventures—more funding than opportunity entrepreneurs needed. Motivated by the desire for independence or to increase or maintain their income, opportunity entrepreneurs needed $15,000 on average. Perhaps necessity entrepreneurs needed to acquire even the most basic resources to start their businesses. Opportunity entrepreneurs, on the other hand, might be able to take advantage of assets they could readily access, such as working space, computers and supplies.

Women reported needing half as much funding to start companies as men, $10,000 and $20,000 respectively, suggesting that women felt they could accomplish what they needed with fewer resources, or simply have fewer resources to apply to their businesses. In addition, as Chapter 5 revealed, women most often started consumer-oriented businesses, which typically have lower capital requirements than knowledge- or capital-intensive ventures.

Women are also likely to self-fund their businesses: 61% of their total business capital was self-funded, whereas men self-funded 50%. Gender differences in funding sources are most apparent in male entrepreneurs using banks more frequently and women entrepreneurs obtaining funds from family more frequently, as Figure 29 illustrates.

FIGURE 29 Sources of Funding by Gender for Entrepreneurs in the United States (by percentage of entrepreneurs using each funding source) SSOURCE OF DATA GEM 2015

typicalstart-upintheUnitedStates,asinmostcountries,isnotthefast-growingtechnologyventureoftenhighlightedinthemedia.Additionally,banksmaybeaneasiersourcetotapintheearlystages,fortherelativelysmallamountneededtogetstarted.GovernmentfundingisimportanttoentrepreneurshipintheUnitedStates,21%ofentrepreneursgainedfinancialsupportfromthegovernment.Crowdfunding,arelativelynewsourceofstart-upfinance,wasusedby12%ofentrepreneurs.

Infographic: Investment Required to Start a Business in the United States: $17,500

Infographic: Percentage of Start-up Funding Provided by the Entrepreneurs’ Personal Sources: 57%

Figure 28: Sources of Funding for Entrepreneurs in the United States (by percentage of entrepreneurs using each funding source), GEM 2015

Necessityentrepreneurs,motivatedbytheneedtofindwork,requiredanaverageof$22,000tostartventures—morefundingthanopportunityentrepreneursneeded.Motivatedbythedesireforindependenceortoincreaseormaintaintheirincome,opportunityentrepreneursneeded$15,000onaverage.Perhapsnecessityentrepreneursneededtoacquireeventhemostbasicresourcestostarttheirbusinesses.Opportunityentrepreneurs,ontheotherhand,mightbeabletotakeadvantageofassetstheycouldreadilyaccess,suchasworkingspace,computersandsupplies.Womenreportedneedinghalfasmuchfundingtostartcompaniesasmen,$10,000and$20,000respectively,suggestingthatwomenfelttheycouldaccomplishwhattheyneededwithfewerresources,orsimplyhavefewerresourcestoapplytotheirbusinesses.Inaddition,asChapter5revealed,womenmostoftenstartedconsumer-orientedbusinesses,whichtypicallyhavelowercapitalrequirementsthanknowledge-orcapital-intensiveventures.

12%

15% 16%

22%24% 24%

36%

0%

5%

10%

15%

20%

25%

30%

35%

40%

Crowdfunding Friends Employers Government Private/VC Family Banks

FIGURE 28 Sources of Funding for Entrepreneurs in the United States (by percentage of entrepreneurs using each funding source) SSOURCE OF DATA GEM 2015

Womenarealsolikelytoself-fundtheirbusinesses:61%oftheirtotalbusinesscapitalwasself-funded,whereasmenself-funded50%.Genderdifferencesinfundingsourcesaremostapparentinmaleentrepreneursusingbanksmorefrequentlyandwomenentrepreneursobtainingfundsfromfamilymorefrequently,asFigure29illustrates. Figure 29: Sources of Funding by Gender for Entrepreneurs in the United States (by percentage of entrepreneurs using each funding source), GEM 2015

Start-upcapitalrequirementsbyagegroupshowthehighestleveloffundingneedsareamong45to54yearolds,asFigure30reveals.Thissuggeststhatthesizeofventurespeoplestartinmid-careertendstotakemoreresources,perhapsbecauseofthescaleoftheefforts.Whilethisagegroupstartsatalowerlevelthanthoseinthe25-to34-and35-to44-yearagegroups,theymaybestartingbusinesseswithgreatercapitalrequirements.Theymaybeleveragingfinancialresourcestheyaccumulatedduringtheircareerandmayhaveaccesstoothercapitalsources.Forexample,43%inthisagegroupstatedtheyobtainedbankfinancingfortheirventures,versus30%of35to44yearolds.Interestingly,thisagegrouphasthehighestproportionofnecessitymotives,whichthischapteridentifiedasneedingahigherlevelofstart-upfunding.

13%15% 16%

25%

21%

39%

19%

10%

15% 16%

21% 22%

31% 32%

0%

5%

10%

15%

20%

25%

30%

35%

40%

45%

Crowdfunding FriendsorNeighbors

EmployerorWork

Colleagues

PrivateInvestorsorVCs

Govt.Programs BankorFinancialInsptupons

Family

Male Female

44

Start-up capital requirements by age group show the highest level of funding needs are among 45 to 54 year olds, as Figure 30 reveals. This suggests that the size of ventures people start in mid-career tends to take more resources, perhaps because of the scale of the efforts. While this age group starts at a lower level than those in the 25- to 34-year and 35- to 44-year age groups, they may be starting businesses with greater capital requirements. They may be leveraging financial resources they accumulated during their career and may have access to other capital sources. For example, 43% in this age group stated they obtained bank financing for their ventures, versus 30% of 35 to 44 year olds. Interestingly, this age group has the highest proportion of necessity motives, which this chapter identified as needing a higher level of start-up funding.

PERCENTAGE OF AGE CATEGORIES SEEKING FINANCING FROM SOURCES:

1=Family, 2=Friends, 3=Work, 4=Bank, 5=Private/VC, 6=Government, 7=Crowd

FIGURE 30 Start-up Capital

Requirements by Age Group for

Entrepreneurs in the United States


FIGURE 31 Sources of Venture

Financing by Age of Entrepreneurs


2015 Family Friends or Neighbors

Employer or Work

Colleagues

Bank or Financial

Institutions

Private Investors or

VCs

Govt. Programs

CrowdFunding

18-34 26.3% 19.5% 14.9% 37.8% 32.4% 27.4% 20.0%35-54 25.4% 11.1% 18.8% 35.3% 17.8% 18.4% 6.0%55-74 15.0% 10.0% 7.3% 22.5% 14.6% 14.6% 7.3%

Source of Fund

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

18-34 35-54 55-74

Family FriendsorNeighbors

EmployerorWorkColleagues BankorFinancialInsEtuEons

PrivateInvestorsorVCs Govt.Programs

CrowdFunding

Figure 30: Start-up Capital Requirements by Age Group for Entrepreneurs in the United States, GEM20

Belowwillbereplacedbyagraphwith10yearagecategories.

Figure 31: Sources of Venture Financing by Age of Entrepreneurs, GEM 2015

Percentageof Age Categories Seeking Financing from Sources:1=Family, 2=Friends, 3=Work, 4=Bank, 5=Private/VC, 6=Government, 7=Crowd

Looking across industries, the extractive industry, companies thatextract raw materials such as metals,minerals and aggregates such as oil and gas, mining, andsoon, requiredthe largest amount of funds tostart up at $347,000, dueto thelargeinvestment in capital equipment needed to operate. Transforming

$10,000

$16,494

$10,000

$67,187

$31,035

$10,052

$-

$10,000

$20,000

$30,000

$40,000

$50,000

$60,000

$70,000

$80,000

18-24yearolds* 25-34yearolds 35-44yearolds 45-54yearolds 55-64yearolds 65+yearolds

32

27

12

46

36

25

2022

1816

35

3129

21

26

16

21

30

17 18

9

23

4

17

43

18 19

2

16

12

6

26

18

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6

12

0

11 11

0

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12

0

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40

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50

1 2 3 4 5 6 7

18-24 25-34 35-44 45-54 55-64 65-74

CHAPTER 6

45

Figure 31 shows the percentage of entrepreneurs citing various financing sources in three age categories. As this figure shows, younger entrepreneurs are more likely than the other age groups to seek bank and government financing, and private investors or venture capital. Crowdfunding is particularly popular with the 18 to 34 year olds, with one in five citing this source, compared to fewer than one in 13 older entrepreneurs. While those in mid-career are most likely to tap employers as a funding source, younger entrepreneurs are more likely to seek out friends to finance their businesses.

Looking across industries, the extractive industry, companies that extract raw materials such as metals, minerals and aggregates such as oil and gas, mining, and so on, required the largest amount of funds to start up at $347,000, due to the large investment in capital equipment needed to operate. Transforming industries, which take raw materials and create something new with labor and overhead, required $25,000 to begin, whereas business services required an average of $20,000. Consumer-oriented businesses needed only $11,216; as discussed in this chapter and elsewhere in the report, these businesses typically have low barriers to entry, yet are difficult to differentiate amid crowds of “me-too” businesses (for example, retail stores, restaurants, beauty salons and health clubs).

Entrepreneurs with higher growth ambitions need financial resources to achieve their goals. Those entrepreneurs projecting that their ventures would create six or more jobs in the next five years stated that they needed $50,000 in start-up funding, whereas those who projected creating five jobs or fewer averaged $10,000 in funding requirements.

In the United States, 6% of the population has acted as an informal investor in an entrepreneurial venture, providing an average of just over $4,000. Women represented 41% of these investors, providing an average of $2,000 in funding. Men more frequently did this type of investing, with an average amount of $5,000. Most of this informal funding went to people the investors knew: friends (39%), family (36%) and colleagues at work (10%). However, a notable number of informal investors (15%) provided funds to entrepreneurs they were not acquainted with. This signifies not only that are investors willing to invest in entrepreneurs they are not personally connected with, but also that information about ventures may increasingly be flowing beyond personal networks.

SUMMARY COMMENTS

Entrepreneurial finance still depends on bootstrapping and support from family and friends, but options for funding entrepreneurial ventures are increasing in the United States, particularly with the growth in crowdfunding and the prevalence of informal investors in the landscape of an improving economy. Americans are investing in entrepreneurs, and although these entrepreneurs are usually people they know, they are increasingly supporting entrepreneurs based on perceptions of the merit of the entrepreneur and venture rather than on personal relationships. Entrepreneurship is in the mainstream of American culture, and is supported by activities at all levels of the U.S. government, and by the private sector, education and other communities. Start-up activity in the United States benefits from widespread recognition of the role entrepreneurship plays in increasing employment and improving the economic health of the nation.

CHAPTER 6

46

Chapter 7Entrepreneurship in Five States

Over the past several years, GEM U.S. has oversampled certain bellwether states to gain additional insights on entrepreneurship across the country. The states examined in 2015 are in different geographic regions, have varied asset bases and take disparate approaches to business policy and the economy. Together, this special focus on California, Florida, New York, Ohio and Texas looks at five states that account for approximately 36% of the U.S. population and 40% of the total U.S. gross domestic product (GDP). Additionally, these states were also oversampled in 2012 (Florida and Ohio) or 2013 (California, New York and Texas), and this chapter reviews changes over time for some key indicators in these states.

Supplementing the GEM data, Table 1 highlights some key demographic and economic statistics on the five states. As we have reported in the past, California’s size, diversity and unique demographic, social and political attributes make it a bit of a conundrum. It is the largest state in the United States, has high household income, is often ranked as one of the top 10 economies in the world, yet it struggles with relatively high unemployment and is always ranked near the bottom of the nation for business climate.

Ohio appears typical of many former “Rust Belt” states and continues to try to diversify its industrial base and build a more entrepreneurial economy. Dormant population growth and relatively high unemployment work against the state, but a strong manufacturing base and a GDP per Capita that is growing at a rate close to the national average provide impetus for entrepreneurial activity.

New York reports the highest GDP per Capita among the five states, and median household income is second only to California. However, the state still suffers from a poor business climate (only New Jersey is worse) and it also experiences low population growth as many Northerners migrate South.

Florida, on the other hand, is experiencing high population growth and low unemployment. Although household incomes are below average, residents pay no state income tax. It is also the best place to do business among the five states, ranked fourth in the country.

Texas is another state among the best places to do business, ranking number 10 in the country. Again, like Florida, an absence of state tax helps as does continued population growth, high household income and a relatively large manufacturing base.

United States

California Florida New York Ohio Texas

2010 population (millions) 308 37.3 18.8 19.3 11.5 25.1 census.gov

2015 population estimate (millions) 321 39.1 20.2 19.8 11.6 27.5 census.gov

Change in population (2010-2015) 4.2% 4.8% 7.4% 2.6% 0.9% 9.6%

Household annual income (2013) $52,520 $60,190 $46,036 $57,369 $48,018 $51,704 census.gov

Share of U.S. GDP (2014) 13.4 4.9 8.1 3.3 9.5 bea.gov

Percentage increase in GDP per capita, 2014 (2009 dollars)

1.5 1.3 1.2 2.4 1.2 2.7 bea.gov

Percentage of workforce in manufacturing (2016)

7.9 4.2 4.9 12.7 7.3 nam.org

State income tax rate (2016) 1% to 12.3%

0% 4% to 8.82%

0.495%to 4.997%

0 taxadmin.org

State business tax climate score (range 3.36 to 7.6)

3.75 6.92 3.62 4.43 5.82 taxfoundation.org

Tax climate rank by state (out of 50; 1 is best)

48 4 49 42 10 taxfoundation.org

Unemployment rate (April 2016) 5 5.3 4.8 4.9 5.2 4.4 bls.gov

Unemployment rank (April 2016 32 27 29 30 21 bls.gov

47

Chapter 7Entrepreneurship in Five States

TABLE 1: DEMOGRAPHIC AND ECONOMIC STATISTICS FOR FIVE STATES

United States

California Florida New York Ohio Texas

2010 population (millions) 308 37.3 18.8 19.3 11.5 25.1 census.gov

2015 population estimate (millions) 321 39.1 20.2 19.8 11.6 27.5 census.gov

Change in population (2010-2015) 4.2% 4.8% 7.4% 2.6% 0.9% 9.6%

Household annual income (2013) $52,520 $60,190 $46,036 $57,369 $48,018 $51,704 census.gov

Share of U.S. GDP (2014) 13.4 4.9 8.1 3.3 9.5 bea.gov

Percentage increase in GDP per capita, 2014 (2009 dollars)

1.5 1.3 1.2 2.4 1.2 2.7 bea.gov

Percentage of workforce in manufacturing (2016)

7.9 4.2 4.9 12.7 7.3 nam.org

State income tax rate (2016) 1% to 12.3%

0% 4% to 8.82%

0.495%

to 4.997%0 taxadmin.org

State business tax climate score (range 3.36 to 7.6)

3.75 6.92 3.62 4.43 5.82 taxfoundation.org

Tax climate rank by state (out of 50; 1 is best)

48 4 49 42 10 taxfoundation.org

Unemployment rate (April 2016) 5 5.3 4.8 4.9 5.2 4.4 bls.gov

Unemployment rank (April 2016 32 27 29 30 21 bls.gov

48

CHAPTER 7

Entrepreneurial ActivityTotal entrepreneurial activity (TEA) in California,Florida, New York, Ohio and Texas combined isconsistent with theU.S. average, which has been in the range of 12%to 14% each year.AsFigure32shows,theaverageofthefivestatesisrightin linewiththenationalaverage for 2015, but whenonelooksdeeper, there are some interesting items tonote. For instance, despite the reputations of SiliconValleyin CA andSiliconAlleyin NY—andtheir proximityto so much financialcapital—these two statesare“only” right on theaverage. Texas is abit aboveaverageand Floridais 17% abovethenationalaverage.

There also appears to be significantly more churn in Texas and Floridabecause these twostates reporthigher thanaverage business exit rates. Ohioappears more stable withboththe highest establishedbusiness ownershiprate andthe lowest percentage of exits. Eachstate is similar withrespect toits levelof entrepreneurial activity withinalready establishedbusinesses (EEArate).Florida again stands apart from the otherfourstates with respect toentrepreneurial intentions andis aminimum of four percentage points higher than each of theothers. As prior GEM reports have shown,economies with high intentions also tend to beassociated with high start-up activity.24

Figure 32: Phases of Business Activity in the United States and in Five States, GEM 2015

Entrepreneurial Attitudes

24 GEM 2014 Global Report:http://gemconsortium.org

12% 12%

7%

5%

2%

14%

12%

7%

4%

1%

18%

14%

7%

5%

3%

11% 10%

6%5%

2%

10% 10%9%

5%

1%

14%13%

5% 5%4%

EntrepreneurialInten\ons*

TEARate EstablishedBusinessOwnershipRate

EEARate Exit(businessessnotcon\nued)

Na\onal California Florida NewYork Ohio Texas

ENTREPRENEURIAL ACTIVITY

Total entrepreneurial activity (TEA) in California, Florida, New York, Ohio and Texas combined is consistent with the U.S. average, which has been in the range of 12% to 14% each year. As Figure 32 shows, the average of the five states is right in line with the national average for 2015, but when one looks deeper, there are some interesting items to note. For instance, despite the reputations of Silicon Valley in CA and Silicon Alley in NY—and their proximity to so much financial capital—these two states are “only” right on the average. Texas is a bit above average and Florida is 17% above the national average.

There also appears to be significantly more churn in Texas and Florida because these two states report higher than average business exit rates. Ohio appears more stable with both the highest established business ownership rate and the lowest percentage of exits. Each state is similar with respect to its level of entrepreneurial activity within already established businesses (EEA rate).

Florida again stands apart from the other four states with respect to entrepreneurial intentions and is a minimum of four percentage points higher than each of the others. As prior GEM reports have shown, economies with high intentions also tend to be associated with high start-up activity.1

1 GEM 2014 Global Report: http://gemconsortium.org

FIGURE 32 Activity in the United

States and in Five States


* for the non-entrepreneur population

49

FIGURE 33 Entrepreneurial Attitudes in the U.S. Working-Age Population: United States and Five States SOURCE OF DATA GEM 2015

CHAPTER 7

ENTREPRENEURIAL ATTITUDES

It is interesting to see in Figure 33 that people in these five big, important economic states perceive significantly fewer opportunities to start businesses than the national average. Across the United States, nearly one out of every two people has perceived an entrepreneurial opportunity, but the average for these five states is only 35%. Texas is the only one of the five states that is close to the national average, coming in at 45%.

Given this, it makes sense that individuals in these states also report entrepreneurial abilities lower than the average rate. As Figure 33 shows, individuals in these five states report having the perceived capabilities to start a business at a rate of about 10 percentage points lower than the national average with only Florida coming close to the national average. Fear of failure is on par with the national average, with the highest level reported in New York.

Having a model for entrepreneurship is important, and therefore, it is not surprising to see that Florida, which has the highest TEA rate and the highest entrepreneurial intentions, also reports the highest percentage of individuals who know an entrepreneur. While each of the other states is right around the national average, Florida is above average here: Knowing an entrepreneur likely inflates one’s intentions to be an entrepreneur and the overall TEA rate.

NECESSITY- AND OPPORTUNITY-DRIVEN ENTREPRENEURSHIP

Figure 34 displays rates of opportunity-driven entrepreneurship in each of the five states and nationwide. As the descriptor connotes, opportunity-driven entrepreneurs start ventures based on an opportunity they perceive. Necessity-driven entrepreneurs, on the other hand, engage in entrepreneurial activity out of necessity (few job prospects due to regional economic downturns, terminated from a job, lack of skills relative to those needed in the economy, etc.). Simply stated, necessity-driven entrepreneurs engage in entrepreneurial activity because they have few or no alternatives and are more likely to start lower-growth, less sustainable businesses. Opportunity-driven entrepreneurs are more likely to start and grow higher-potential businesses, so a prevalence of these entrepreneurs can serve as a leading indicator of future economic attainment.

Texas and Ohio are at either end of the opportunity spectrum, with Texas reporting 86% of its entrepreneurs with opportunity motives, while just 77% have these motives in Ohio. This indicator is also above the national average in California and Florida and just below the national level in New York. Interestingly, California, Florida and Texas show TEA rates just at or above national levels; combined with high proportions of opportunity motives, this suggests a prevalence of opportunity-motivated entrepreneurs. In contrast, New York and Ohio, with proportionately fewer entrepreneurs, also seem to lack opportunity motives; this is supported by low societal perceptions in these states about the presence of opportunities.

ItisinterestingtoseeinFigure33thatpeopleinthesefivebig,importanteconomicstatesperceivesignificantlyfeweropportunitiestostartbusinessesthanthenationalaverage.AcrosstheUnitedStates,nearlyoneoutofeverytwopeoplehasperceivedanentrepreneurialopportunity,buttheaverageforthesefivestatesisonly35%.Texasistheonlyoneofthefivestatesthatisclosetothenationalaverage,cominginat45%.Giventhis,itmakessensethatindividualsinthesestatesalsoreportentrepreneurialabilitieslowerthantheaveragerate.AsFigure33shows,individualsinthesefivestatesreporthavingtheperceivedcapabilitiestostartabusinessatarateofabout10percentagepointslowerthanthenationalaveragewithonlyFloridacomingclosetothenationalaverage.Fearoffailureisonparwiththenationalaverage,withthehighestlevelreportedinNewYork.Havingamodelforentrepreneurshipisimportant,andtherefore,itisnotsurprisingtoseethatFlorida,whichhasthehighestTEArateandthehighestentrepreneurialintentions,alsoreportsthehighestpercentageofindividualswhoknowanentrepreneur.Whileeachoftheotherstatesisrightaroundthenationalaverage,Floridaisaboveaveragehere:Knowinganentrepreneurlikelyinflatesone’sintentionstobeanentrepreneurandtheoverallTEArate. Figure 33: Entrepreneurial Attitudes in the U.S. Working-Age Population: United States and Five States, GEM 2015

Necessity- and Opportunity-Driven Entrepreneurship Figure34displaysratesofopportunity-drivenentrepreneurshipineachofthefivestatesandnationwide.Asthedescriptorconnotes,opportunity-drivenentrepreneursstartventuresbasedonanopportunitytheyperceive.Necessity-drivenentrepreneurs,ontheotherhand,engageinentrepreneurialactivityoutofnecessity(fewjobprospectsduetoregionaleconomicdownturns,terminatedfromajob,lackofskillsrelativetothoseneededintheeconomy,etc.).Simplystated,necessity-drivenentrepreneursengageinentrepreneurialactivitybecausetheyhavefewornoalternativesandaremorelikelytostartlower-growth,lesssustainablebusinesses.Opportunity-driven

47%

56%

29% 30%32%

44%

26%27%

36%

53%

27%

34%

30%

46%

34%

28%

33%

42%

33%

28%

45%

49%

31%29%

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PerceivedOpportuni\es PerceivedCapabili\es FearofFailure* KnowEntrepreneurs


* for those seeing opportunities

50

FIGURE 34 Percentage of

Entrepreneurs with Opportunity Motives in the United States

and in Five States


CHAPTER 7

WOMEN AND MEN ENTREPRENEURS

While the data reflect challenges for New York and Ohio with respect to low TEA rates and a low percentage of opportunity-driven entrepreneurship, an analysis by gender suggests that low overall TEA rates are due to low participation by males in this activity. In fact, all five states report female TEA rates that are at or above the national average. However, only California and Florida have male rates equal to or greater than the overall U.S. level. In the other three states, low participation among males leads to low gender gaps. Nationwide, there are 60% more men than women entrepreneurs. New York shows an equal mix of both women and men engaged in entrepreneurial activities. Texas is close to equal and has the highest rate of women entrepreneurs, and Ohio also reports relatively balanced numbers.

A number of issues may underlie these gender differences. For example, ethnic make-up, immigration patterns and age demographics may go hand-in-hand with gender variations. Additional explanations may lie in the environment for entrepreneurship and focused initiatives or programs.

Figure 35: Total Entrepreneurial Activity Rates in the United States by Gender, GEM 2015

Entrepreneurship Rates by Age GroupFigure36 compares entrepreneurshipbyagegroupamongthefive states. Asthis figure illustrates,Florida has a highprevalence of young entrepreneurs and is theonly stateof thesefiveto beabovethenational average. Amongthemid-career population, NewYorkandOhio,andtosomeextentCalifornia,lagbelow thenational average, whileTexas and Floridaareaboveaverage. It is interestingto notethatall fivestates areat or abovetheaveragefor entrepreneurial activity in the55-plus age group. Californiais doublethenational averagein this population.AnexaminationoftheagedistributionofTEAacrossthestatesshowsasimilarpatterninFlorida andTexas, where entrepreneurship levels peak in the middle age group. Californiaexhibits aflatter versionof this pattern, withless difference betweenthe age groups. InNew York, the highest rates occur intheyoungest age groupanddecline after that. Ohioshows a more dramatic dropfrom highyoung adultrates tolow rates inthe middle age group, witha more gradual dropin the older group.

Figure 36: Age Patterns in Total Entrepreneurial Activity in the United States and in Five States, GEM2015

15% 15%

18%

10%11%

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9% 9%11% 10%

9%

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4%

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18to34 35to54 55+


entrepreneurs aremorelikely to start and grow higher-potential businesses, soa prevalence of theseentrepreneurs can serveas aleadingindicator of futureeconomic attainment.

TexasandOhioareateitherendoftheopportunity spectrum, withTexas reporting 86% of itsentrepreneurswithopportunitymotives,whilejust77%havethesemotivesinOhio.ThisindicatorisalsoabovethenationalaverageinCaliforniaandFloridaandjustbelow the national level inNew York.Interestingly, California, Floridaand Texas show TEA rates just at or abovenational levels; combinedwithhighproportions of opportunity motives, this suggests a prevalence of opportunity-motivatedentrepreneurs. In contrast, New York and Ohio, with proportionately fewer entrepreneurs, alsoseem tolack opportunity motives; this is supported by low societal perceptions in thesestates about thepresence of opportunities.

Figure 34: Percentage of Entrepreneurs with Opportunity Motives in the United States and in FiveStates, GEM 2015

Women and Men Entrepreneurs While the data reflect challenges for New York andOhiowithrespect tolow TEArates and a lowpercentage of opportunity-drivenentrepreneurship, ananalysis by gender suggests that low overallTEArates are due tolow participationby males inthis activity. Infact, all fivestates report femaleTEA ratesthat are at or above the national average. However, only California andFlorida have male rates equal toor greater thanthe overall U.S. level. In theother threestates, low participation amongmales leads tolow gender gaps. Nationwide, thereare60% moremen than women entrepreneurs. New York shows anequal mix of both women andmenengaged in entrepreneurial activities. Texas is closetoequal andhasthe highest rate of womenentrepreneurs, andOhioalsoreportsrelativelybalancednumbers.

A number of issues may underlie these gender differences. For example, ethnic make-up, immigrationpatterns andage demographics may gohand-in-handwithgender variations. Additional explanationsmay liein theenvironment for entrepreneurship and focused initiatives or programs.

82%

85% 85%

80%

77%

86%

70%

72%

74%

76%

78%

80%

82%

84%

86%

88%


FIGURE 35 Total Entrepreneurial Activity Rates in the

United States by Gender


51

ENTREPRENEURSHIP RATES BY AGE GROUP

Figure 36 compares entrepreneurship by age group among the five states. As this figure illustrates, Florida has a high prevalence of young entrepreneurs and is the only state of these five to be above the national average. Among the mid-career population, New York and Ohio, and to some extent California, lag below the national average, while Texas and Florida are above average. It is interesting to note that all five states are at or above the average for entrepreneurial activity in the 55-plus age group. California is double the national average in this population.

An examination of the age distribution of TEA across the states shows a similar pattern in Florida and Texas, where entrepreneurship levels peak in the middle age group. California exhibits a flatter version of this pattern, with less difference between the age groups. In New York, the highest rates occur in the youngest age group and decline after that. Ohio shows a more dramatic drop from high young adult rates to low rates in the middle age group, with a more gradual drop in the older group.

FIGURE 36 Age Patterns in Total Entrepreneurial Activity in the United States and in Five States SOURCE OF DATA GEM 2015

Figure 35: Total Entrepreneurial Activity Rates in the United States by Gender, GEM 2015

Entrepreneurship Rates by Age Group Figure36comparesentrepreneurshipbyagegroupamongthefivestates.Asthisfigureillustrates,Floridahasahighprevalenceofyoungentrepreneursandistheonlystateofthesefivetobeabovethenationalaverage.Amongthemid-careerpopulation,NewYorkandOhio,andtosomeextentCalifornia,lagbelowthenationalaverage,whileTexasandFloridaareaboveaverage.Itisinterestingtonotethatallfivestatesareatorabovetheaverageforentrepreneurialactivityinthe55-plusagegroup.Californiaisdoublethenationalaverageinthispopulation.AnexaminationoftheagedistributionofTEAacrossthestatesshowsasimilarpatterninFloridaandTexas,whereentrepreneurshiplevelspeakinthemiddleagegroup.Californiaexhibitsaflatterversionofthispattern,withlessdifferencebetweentheagegroups.InNewYork,thehighestratesoccurintheyoungestagegroupanddeclineafterthat.Ohioshowsamoredramaticdropfromhighyoungadultratestolowratesinthemiddleagegroup,withamoregradualdropintheoldergroup. Figure 36: Age Patterns in Total Entrepreneurial Activity in the United States and in Five States, GEM 2015

15% 15%

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18to34 35to54 55+


CHAPTER 7

52

ENTREPRENEURSHIP RATES BY EDUCATION

Although entrepreneurship may have a complex relationship with education, the majority of entrepreneurs are highly educated in the United States. As shown in Figure 37, 80% of entrepreneurs nationally have a college degree or higher level of education. Like in 2013, Texas shows the largest share of entrepreneurs with post-secondary education among the five states, although the difference between Texas, Ohio, New York and California is very small and statistically marginal. But the more interesting fact is that New York has the largest share of entrepreneurs with graduate-level education and the smallest with college-level education. This is in large contrast to the other states and the national level. It is interesting that New York (along with California) also stood out in that respect in the 2013 survey. A high level of human-capital-intensive industries in the state of New York, such as finance and insurance, could be the reason behind this disparity.

INNOVATION

Across the innovation-driven economies, the United States has among the highest rates of innovative entrepreneurship, measured as the percentage of TEA with new product/market combinations. Figure 38 shows that Ohio and New York are the leaders among the five states in this measure. The measure is more than 10 percentage points (roughly 40%) larger for these two states. These states have lower TEA rates than the national average, yet those who do become entrepreneurs are less likely to be opportunity motivated, but at the same time, are more likely to offer innovative products or services.

The remaining three states have lower proportions of innovative entrepreneurs. Texas and Florida have higher entrepreneurship rates than Ohio and New York, providing a different profile of this activity than their Northern and Eastern peers. California is a curious case as it is the world capital of Internet companies, and higher innovation rates for this state might be expected. But one should also consider that California is a large and diverse state. It has a major agricultural sector with many non-innovative traditional entrepreneurs in that and other industries.

CHAPTER 7

FIGURE 37 Percentage of Entrepreneurs

with a Post-Secondary

Degree and with Graduate

Experience in the United States and

in Five States


Entrepreneurship Rates by EducationAlthoughentrepreneurshipmay haveacomplexrelationshipwitheducation,the majority ofentrepreneurs arehighly educated in theUnited States. As shown in Figure37, 80% of entrepreneursnationally have acollegedegreeorhigherlevelofeducation.Likein 2013, Texas shows thelargest shareof entrepreneurs withpost-secondary educationamong the five states, althoughthe differencebetweenTexas, Ohio, New York andCalifornia is very small andstatistically marginal. But the moreinterestingfact is that New York has the largest share of entrepreneurs withgraduate-level educationandthesmallest with college-level education. This is in largecontrast to theother states and thenational level. It is interesting that New York (along withCalifornia) also stood out in that respect in the2013survey. A high level of human-capital-intensiveindustries in thestateof New York, such as financeandinsurance, could be the reasonbehindthis disparity.

Figure 37: Percentage of Entrepreneurs with a Post-Secondary Degree and with GraduateExperience in the United States and in Five States, 2015

InnovationAcross the innovation-driveneconomies, the UnitedStates has among the highest rates of innovativeentrepreneurship, measured as thepercentageof TEAwithnew product/market combinations. Figure38shows that Ohio andNew York are the leaders among the five states in this measure. The measure ismorethan 10 percentage points (roughly 40%) larger for thesetwo states. Thesestates have lower TEArates than thenational average, yet thosewho do becomeentrepreneurs areless likely to beopportunity motivated, but at the same time, aremorelikely to offer innovative products or services.

60% 64%55%

40%59% 66%

20% 14%15% 38%

19%15%

0%10%20%30%40%50%60%70%80%90%


%TEAwithatLeastSomeGraduateExperience

%TEAwithPost-SecondaryEduca\on

53

INTERNATIONALIZATION

Internationalization, measured as the share of entrepreneurs with more than 25% of their business sales to customers residing outside the United States, is highest in Florida—nearly twice the national average (see Figure 39). Florida is also the only state of the five with a higher percentage of international-oriented established business owners, compared to the national average. These results in Florida could be due to its popularity as a tourist destination and as a major hub for export to Latin American and Caribbean economies. New York and Ohio rank second and third among the five states; it is particularly interesting that these two states have higher internationalization levels than California. This is in contrast to 2013 when California had substantially higher internationalization rates than New York.

FIGURE 38 Percentage of Total Entrepreneurial Activity with New Product/Market Innovations in the United States and in Five States SOURCE OF DATA GEM 2015

Theremainingthreestateshavelowerproportionsofinnovativeentrepreneurs.TexasandFloridahavehigherentrepreneurshipratesthanOhioandNewYork,providingadifferentprofileofthisactivitythantheirNorthernandEasternpeers.CaliforniaisacuriouscaseasitistheworldcapitalofInternetcompanies,andhigherinnovationratesforthisstatemightbeexpected.ButoneshouldalsoconsiderthatCaliforniaisalargeanddiversestate.Ithasamajoragriculturalsectorwithmanynon-innovativetraditionalentrepreneursinthatandotherindustries.Figure 38: Percentage of Total Entrepreneuria l Act iv i ty with New Product/Market Innovat ions in the United States and in Five States, 2015

Internationalization Internationalization,measuredastheshareofentrepreneurswithmorethan25%oftheirbusinesssalestocustomersresidingoutsidetheUnitedStates,ishighestinFlorida—nearlytwicethenationalaverage(seeFigure39).Floridaisalsotheonlystateofthefivewithahigherpercentageofinternational-orientedestablishedbusinessowners,comparedtothenationalaverage.TheseresultsinFloridacouldbeduetoitspopularityasatouristdestinationandasamajorhubforexporttoLatinAmericanandCaribbeaneconomies.NewYorkandOhioranksecondandthirdamongthefivestates;itisparticularlyinterestingthatthesetwostateshavehigherinternationalizationlevelsthanCalifornia.Thisisincontrastto2013whenCaliforniahadsubstantiallyhigherinternationalizationratesthanNewYork.Figure 39: Percentage of TEA and Establ ished Business Owners with at Least 25% Internat ional Customers in the United States and in Five States, GEM 2015

36%

27%25%

38%

44%

28%

0%

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25%

30%

35%

40%

45%

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CHAPTER 7

FIGURE 39 Percentage of TEA and Established Business Owners with at Least 25% International Customers in the United States and in Five States SOURCE OF DATA GEM 2015

5454

FINANCE

Figure 40 reports the amount of funding that entrepreneurs required to start their businesses as well as the amount they provided personally. Entrepreneurs in Florida require a median level of $10,000 to start, with all of this provided by the entrepreneur. On the other end of the spectrum, the funding required in Texas is substantially larger than funding needed in the other states. Additionally, the largest amount of personal funding can be found among Texas entrepreneurs. Entrepreneurs in Ohio require a higher amount of funding than the national average, but provide less of their own money than reported at the national level. California is on par with the national median level regarding the use of personal funds for a business, and New York is on par with the national median on overall funding.

LONGITUDINAL ANALYSIS OF KEY GEM INDICATORS

Changes in several GEM indicators were assessed over a three-year period for Florida and Ohio (between 2012 and 2015) and a two-year period for California, New York and Texas (between 2013 and 2015).1 What is remarkable about this analysis is that, while these indicators changed very little at the national level, there were varied and sometimes quite marked shifts in the states. Fluctuations in entrepreneurship do occur over time at the national level, as shown by GEM data collected over the 2008–2011 period during and after the recession.However, in relatively stable times, national level indicators may change very little or only gradually, as GEM surveys revealed in 2012 through 2015. This stability could be relatively uniform around the United States. But our analysis of these five large states from different regions of the country suggests otherwise.

National-level TEA rates stayed the same from 2012 to 2013, but dropped by one percentage point to 12% in 2015 (see Figure 41). TEA rates remained the same in California, while New York, Ohio and Texas saw a similar percentage point drop as the national level. There was a slightly larger drop in Florida, but this state also showed higher TEA rates than national levels in both years.

1 Results on these states are covered in chapters of the 2012 and 2013 Global Entrepreneurship Monitor United States Report. These reports can be accessed at http://gemconsortium.org.

FinanceFigure 40 reports the amount of funding thatentrepreneurs required to start their businesses as well asthe amount they providedpersonally. Entrepreneurs in Florida require a medianlevel of $10,000 tostart,withallofthisprovidedbytheentrepreneur. Ontheotherendofthespectrum,thefundingrequiredin Texas is substantially larger thanfundingneeded in theotherstates.Additionally,thelargestamount of personal funding can be found among Texas entrepreneurs. Entrepreneurs in Ohio requireahigher amount of funding thanthe national average, but provide less of their ownmoney thanreportedatthenationallevel. Californiais onparwiththenationalmedian levelregardingtheuseof personalfunds for a business, and New York is on parwiththenationalmedianon overallfunding.

Figure 40: Start-up Funding Required and Amount of Own Funds Provided in the United States andin Five States, GEM 2015

12% 13%

21%

18%17%

15%

8%6%

13%

7% 7% 8%

0%

5%

10%

15%

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25%


TEA EB

$10,000 $10,000 $10,000 $6,361 $7,382 $16,791$-

$5,000

$10,000

$15,000

$20,000

$25,000

$30,000

$35,000

$40,000

$45,000

$50,000

Na\onal NewYork Ohio TexasCalifornia Florida

OwnMoneyProvided* OtherFunding

$17,500$20,152

$10,000

$17,315

$25,000

$47,069FIGURE 40

Start-up Funding Required and

Amount of Own Funds Provided in the United States and in Five States


CHAPTER 7

* Median Value

5555 55

FIGURE 41 Changes over Time in TEA and Intentions for the United States and Five States SOURCE OF DATE GEM 2012–2015

CHAPTER 7

Opportunity motives at the national levels rose in 2015, and this was also the case in the states, with the exception of Ohio, which reported no change from 2012 to 2015. Texas already had a high proportion of opportunity-motivated entrepreneurs in 2013; with a more modest increase, this state nonetheless reached the highest level of the cohort on this indicator.

Changes in intentions varied much more than TEA. California saw a drop similar to national levels. Florida and Texas both started at high levels of intentions, but Texas exhibited a steeper decline. New York also dropped relatively steeply to a level below the national average. Ohio showed little change from an already low level.

While attitudes at the national level show relative stability (see Figure 42), substantially large shifts can be seen in the states. All of the states saw declines in opportunity perceptions, most markedly in Texas, which started at a high level in 2013. Capabilities perceptions at the national level are, for the most part, constant at 56% from year to year. But in the five states, these perceptions dropped, indicating that people feel less confident about their abilities in 2015. Less volatile was fear of failure, with the exception of New York, which saw a jump of nearly 10 percentage points in this indicator.

Longitudinal Analysis of Key GEM Indicators ChangesinseveralGEMindicatorswereassessedoverathree-yearperiodforFloridaandOhio(between2012and2015)andatwo-yearperiodforCalifornia,NewYorkandTexas(between2013and2015).25Whatisremarkableaboutthisanalysisisthat,whiletheseindicatorschangedverylittleatthenationallevel,therewerevariedandsometimesquitemarkedshiftsinthestates.Fluctuationsinentrepreneurshipdooccurovertimeatthenationallevel,asshownbyGEMdatacollectedoverthe2008–2011periodduringandaftertherecession.However,inrelativelystabletimes,nationallevelindicatorsmaychangeverylittleoronlygradually,asGEMsurveysrevealedin2012through2015.ThisstabilitycouldberelativelyuniformaroundtheUnitedStates.Butouranalysisofthesefivelargestatesfromdifferentregionsofthecountrysuggestsotherwise.National-levelTEAratesstayedthesamefrom2012to2013,butdroppedbyonepercentagepointto12%in2015(seeFigure41).TEAratesremainedthesameinCalifornia,whileNewYork,OhioandTexassawasimilarpercentagepointdropasthenationallevel.TherewasaslightlylargerdropinFlorida,butthisstatealsoshowedhigherTEAratesthannationallevelsinbothyears.Opportunitymotivesatthenationallevelsrosein2015,andthiswasalsothecaseinthestates,withtheexceptionofOhio,whichreportednochangefrom2012to2015.Texasalreadyhadahighproportionofopportunity-motivatedentrepreneursin2013;withamoremodestincrease,thisstatenonethelessreachedthehighestlevelofthecohortonthisindicator.ChangesinintentionsvariedmuchmorethanTEA.Californiasawadropsimilartonationallevels.FloridaandTexasbothstartedathighlevelsofintentions,butTexasexhibitedasteeperdecline.NewYorkalsodroppedrelativelysteeplytoalevelbelowthenationalaverage.Ohioshowedlittlechangefromanalreadylowlevel.Figure 41: Changes over Time in TEA and Intentions for the United States and Five States

25Resultsonthesestatesarecoveredinchaptersofthe2012and2013GlobalEntrepreneurshipMonitorUnitedStatesReport.Thesereportscanbeaccessedathttp://gemconsortium.org.

17% 17%

12%

18%

14%

23%

18% 18%

11%12%

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13% 13% 12% 12% 12%

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2012 2013 2015 2013 2015 2012 2015 2013 2015 2012 2015 2013 2015


EntrepreneurialInten\ons* TEARate

* non-entrepreneur population

TEAlevelsbygenderchangedlittleatthenationallevel,withfemaleratesdroppingonlyslightly(seeFigure43).Infourofthefivestates,however,maleratesdroppedwhilefemaleratesstayedthesameoredgedupward.Inthesestates,declinesinTEAratescouldbeexplainedbyadropinmaleactivity.InCalifornia,however,adifferentpatternemerges.Adropinfemaleratesisoffsetbyanincreaseinmaleratesinthisstate,resultinginnochangeinTEAoverall,butopeningupawidegendergap

Figure 43: Changes over Time in Male and Female TEA Rates for the United States and Five States

Intermsofbusinesscharacteristics,morespecificallyindustryparticipation,it’sworthmentioningchangesinthetransformingsectorinfourofthestates.InOhio,theproportionofentrepreneursstartingmanufacturingbusinessesdroppedto10%,one-thirdthelevelreportedin2012.Inthisstate,thedeclineinmanufacturingentrepreneurshipwasoffsetbyastarkincreaseinconsumer-orientedbusinesses(from33%to55%).Californiashowedadropinthetransformingsectorfrom2013to2015(from24%to18%),andlikeOhio,thiswasoffsetbyanincreaseinconsumeractivity(from42%to49%).

InFlorida,entrepreneurshipactivitydroppedinbothtransforming(28%to19%)andconsumer(44%to38%)sectorsduringthe2012–2015period;thiswasreplacedbyanincreaseinbusinessservicesactivity.Texasalsoshowedanincreaseinbusinessservicesentrepreneurship(from24%to28%)from2013to2015,whichdisplacedadeclineinthetransformingsector(from26%to19%).NewYorkwastheonly

44% 47% 47% 47%

32%

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56% 56% 56% 53%

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2012 2013 2015 2013 2015 2012 2015 2013 2015 2012 2015 2013 2015


PerceivedOpportuni\es PerceivedCapabili\es FearofFailure*

15% 15% 15%12%

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2012 2013 2015 2013 2015 2012 2015 2013 2015 2012 2015 2013 2015


Male Female

* among those seeing opportunities

FIGURE 42 Changes over Time in Attitudes (perceived opportunities and capabilities, fear of failure) for the United States and Five States SOURCE OF DATA GEM 2012–2015

CHAPTER 7

FIGURE 43 Changes over Time in Male

and Female TEA Rates for the

United States and Five States


56

TEA levels by gender changed little at the national level, with female rates dropping only slightly (see Figure 43). In four of the five states, however, male rates dropped while female rates stayed the same or edged upward. In these states, declines in TEA rates could be explained by a drop in male activity. In California, however, a different pattern emerges. A drop in female rates is offset by an increase in male rates in this state, resulting inno change in TEA overall, but opening up a wide gender gap.

In terms of business characteristics, more specifically industry participation, it’s worth mentioning changes in the transforming sector in four of the states. In Ohio, the proportion of entrepreneurs starting manufacturing businesses dropped to 10%, one-third the level reported in 2012. In this state, the decline in manufacturing entrepreneurship was offset by a stark increase in consumer-oriented businesses (from 33% to 55%). California showed a drop in the transforming sector from 2013 to 2015 (from 24% to 18%), and like Ohio, this was offset by an increase in consumer activity (from 42% to 49%).

In Florida, entrepreneurship activity dropped in both transforming (28% to 19%) and consumer (44% to 38%) sectors during the 2012–2015 period; this was replaced by an increase in business services activity. Texas also showed an increase in business services entrepreneurship (from 24% to 28%) from 2013 to 2015, which displaced a decline in the transforming sector (from 26% to 19%). New York was the only state of the five that showed a decline in business services activity (from 43% to 36%), with small increases in the other three sectors.

Job expectations jumped in California (from 40% to 47%) and Ohio (from 34% to 43%), while remaining stable at the national level, declining moderately in New York (from 39% to 34%), and changing little in the other two states.

Internationalization patterns were quite erratic in the states, despite changing little at the national level. Florida increased slightly from already high levels, while New York and Ohio essentially doubled their international rate. California and Texas, on the other hand, dropped from high levels.

While attitudesatthenationallevelshowrelativestability(seeFigure42),substantiallylargeshiftscanbe seeninthe states. All of the states saw declines inopportunity perceptions, most markedly inTexas,whichstartedat a highlevel in2013. Capabilities perceptions at the national level are, for the most part,constant at 56% from year to year. But in thefivestates, theseperceptions dropped, indicatingthatpeople feel less confident about their abilities in2015. Less volatile was fear of failure, withtheexceptionofNewYork,whichsawa jump of nearly 10 percentage points in this indicator.

Figure 42: Changes over Time in Attitudes (perceived opportunities and capabilities, fear of failure) forthe United States and Five States

TEA levels by gender changed little at the national level, withfemale rates dropping only slightly (seeFigure43). In four of thefivestates, however, malerates dropped whilefemalerates stayed thesameoredged upward. In thesestates, declines in TEA rates could beexplained by adrop in maleactivity.InCalifornia, however, a different patternemerges. Adropinfemale rates is offset by anincrease inmalerates inthis state, resulting innochange inTEAoverall, but opening upa wide gender gap

Figure 43: Changes over Time in Male and Female TEA Rates for the United States and Five States

Intermsofbusinesscharacteristics,morespecificallyindustryparticipation,it’sworthmentioningchanges in thetransformingsector in four of thestates. In Ohio, theproportion of entrepreneursstarting manufacturing businesses droppedto10%, one-thirdthelevelreportedin2012.Inthisstate,

44% 47% 47% 47%

32%

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43%

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64%

45%

56% 56% 56% 53%

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2012 2013 2015 2013 2015 2012 2015 2013 2015 2012 2015 2013 2015


PerceivedOpportuni\es PerceivedCapabili\es FearofFailure*

15% 15% 15%12%

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2012 2013 2015 2013 2015 2012 2015 2013 2015 2012 2015 2013 2015


Male Femalethe decline inmanufacturing entrepreneurshipwas offset by a stark increase inconsumer-orientedbusinesses (from 33% to55%). California showeda dropinthe transforming sector from 2013 to 2015(from24%to18%),andlikeOhio,thiswasoffsetbyanincreaseinconsumeractivity(from42%to49%).

In Florida, entrepreneurship activity dropped in both transforming (28% to 19%) and consumer (44% to38%) sectors during the 2012–2015period;thiswasreplacedbyanincreaseinbusinessservicesactivity.Texas alsoshowedanincrease inbusiness services entrepreneurship(from 24% to28%) from 2013 to2015,whichdisplacedadeclineinthetransforming sector(from26%to19%).NewYorkwastheonlystateofthefivethatshowedadeclineinbusinessservicesactivity(from43%to36%),withsmallincreases in theother threesectors.

Job expectations jumped in California(from 40% to47%)andOhio(from 34% to43%), while remainingstableatthenationallevel,decliningmoderatelyinNewYork(from39%to34%),andchanginglittleinthe othertwo states.

Internationalization patterns werequiteerratic in thestates, despitechanginglittleat thenationallevel.Florida increased slightly from already high levels, while New York and Ohio essentially doubled theirinternational rate. Californiaand Texas, on theother hand, dropped from high levels.

Figure 44: Changes Over Time in Internationalization Rates (Percentage of TEA) for the United Statesand Five States

Summary CommentsThisexaminationoffivestates(California,Florida,NewYork,OhioandTexas)in2015andcomparisonswithprior years reveals considerable variations across the states:anotablecontrastwithstableorincrementally changingindicators at thenational level. Opportunity andcapability perceptions inthegeneral population in each of the five states are lower than the national average in 2015, and theseindicators have declinedfrom prior years, raising concerns about future entrepreneurshipefforts at thestatelevel.FloridastillhashighintentionstostartandhighTEArates. Yet entrepreneurs in that stateseemtostartsmallerbusinesses,atleastatfirst,requiring only a medianlevel of $10,000 andtending tofinanceall of this themselves. Texas entrepreneurs, on theother hand, raiseover $47,000to start.NewYorkandOhioexhibitlowerthanthenationalaverageintentionsandTEA.Thesestatesalsoreportlow opportunity motives amongentrepreneurs compared to theother threestates and thenationalaverage. Low participationamong the middle age groups alsocontributestothelowratesinthesetwostates,whereas the other three states andthe nationexhibitthehighest middleagerates comparedtoyounger andolder cohorts.

12% 11% 12%

17%13%

19%21%

9%

18%

9%

17%19%

15%

0%5%10%15%20%25%

2012 2013 2015 2013 2015 2012 2015 2013 2015 2012 2015 2013 2015


FIGURE 44 Changes

over Time in Internationalization Rates (Percentage

of TEA) for the United States and

Five States


CHAPTER 7

57

SUMMARY COMMENTS

This examination of five states (California, Florida, New York, Ohio and Texas) in 2015 and comparisons with prior years reveals considerable variations across the states: a notable contrast with stable or incrementally changing indicators at the national level. Opportunity and capability perceptions in the general population in each of the five states are lower than the national average in 2015, and these indicators have declined from prior years, raising concerns about future entrepreneurship efforts at the state level. Florida still has high intentions to start and high TEA rates. Yet entrepreneurs in that state seem to start smaller businesses, at least at first, requiring only a median level of $10,000 and tending to finance all of this themselves. Texas entrepreneurs, on the other hand, raise over $47,000 to start.

New York and Ohio exhibit lower than the national average intentions and TEA. These states also report low opportunity motives among entrepreneurs compared to the other three states and the national average. Low participation among the middle age groups also contributes to the low rates in these two states, whereas the other three states and the nation exhibit the highest middle age rates compared to younger and older cohorts.

Low TEA rates in New York and Ohio also have a gender explanation. While female entrepreneurship rates in each of the five states are equal to or greater than the national average, in Ohio and New York, male TEA rates are not much more than two-thirds the national rate of 15%. In California, male TEA rates increased while female rates decreased in California, opening up a gender gap in 2015. The opposite pattern occurred in the other four states, where male rates dropped and female rates increased or stayed the same.

Although Ohio and New York have lower TEA rates than the national average, those who do become entrepreneurs are more likely to offer innovative products or services. The remaining three states have low innovation levels compared to the national average. But all five states have higher internationalization levels than the national average, with particularly high levels in Florida. This follows an increase in four states, while California declined from previously high levels. While the United States tends toward low international sales in general, certain states may provide greater opportunities and enablers for global trade and host entrepreneurs with the ambitions and other means to venture outside the United States with their products and services.

Since 1999, the Global Entrepreneurship Monitor has conducted annual adult population surveys (APS) in economies around the world. In 2015, more than 190,000 individuals were surveyed across 62 economies, including 5,944 in the United States. National teams in each participating economy administer the surveys with central oversight by the GEM coordination team. The GEM U.S. team is based at Babson College in Massachusetts, in partnership with Baruch College in New York.

GEM was founded on the precept that, despite growing recognition of the importance of entrepreneurship to economic development, there was little understanding about the individuals who start businesses around the world. GEM surveys address individuals who run both formal and informal businesses, sidestepping problems with studies focused on firm registrations. GEM tracks entrepreneurship through a range of stages and assesses societal attitudes about this activity. In addition, GEM research examines characteristics of entrepreneurs, such as their profiles, motivations, and impact on society.

Drawing on 16 years of data collection, GEM can track longitudinal changes in the rate and nature of entrepreneurship in many economies. Through GEM’s harmonization processes, comparisons can be made among participating economies. GEM provides a comprehensive look at entrepreneurship around the world and over time, with valuable insights for academics, policy-makers, educators, and practitioners.

58

The Global Entrepreurship Monitor (GEM)

59 59

GEM MEASURES

GEM’s entrepreneurship indicators are illustrated in Figure 45. These include societal attitudes about entrepreneurship, participation in multiple phases of the entrepreneurship process, and profile and impact indicators. Contained within this figure is a key measure of GEM: early-stage TEA, which comprises nascent entrepreneurs in the process of starting a business as well as new business owners.

FIGURE 45 The GEM Model of Entrepreneurship Attitudes, Phases and Profile

The Global Entrepreurship Monitor

60

Sponsors

GERA AND GEM

The Global Entrepreneurship Research Association (GERA) is, for formal constitutional and regulatory purposes, the umbrella organization that hosts the GEM project. GERA is an association formed of Babson College, London Business School and representatives of the Association of GEM national teams.

The GEM program is a major initiative aimed at describing and analyzing entrepreneurial processes within a wide range of countries. The program has three main objectives:

• To measure differences in the level of entrepreneurial activity between countries

• To uncover factors leading to appropriate levels of entrepreneurship

• To suggest policies that may enhance the national level of entrepreneurial activity

New developments—and all global, national and special topic reports—can be found at www.gemconsortium.org.

BABSON COLLEGE

Babson College is a founding institution and lead sponsor of the Global Entrepreneurship Monitor (GEM). Located in Wellesley, Massachusetts, USA, Babson is recognized internationally as a leader in entrepreneurial management education. U.S. News & World Report has ranked Babson #1 in entrepreneurship education for 18 years in a row. Babson grants B.S. degrees through its innovative undergraduate program and offers M.B.A. and M.S. degrees through its F.W. Olin Graduate School of Business. The School of Executive Education offers executive development programs to experienced managers worldwide. Babson’s student body is globally diverse, hailing from 45 U.S. states and 57 countries. (Non-U.S. students comprise more than 20% of undergraduates and 40% of full-time M.B.A. students.) Students can choose from more than 100 entrepreneurship courses offered each year, taught by 17 tenured or tenure-track faculty, all with entrepreneurship experience, seven faculty from other divisions around the college, and highly accomplished business leaders who serve as adjunct faculty.

BARUCH COLLEGE

Baruch College has a 160-year history of excellence in public higher education with an emphasis on business. A senior college in the City University of New York system, Baruch College offers undergraduate and graduate programs of study through its three schools: the Zicklin School of Business, the Weissman School of Arts and Sciences and the School of Public Affairs. Housed at the Zicklin School, the Lawrence N. Field Center for Entrepreneurship is a model of entrepreneurship education built around the collaboration of an institution of higher education, government and the private sector. For information, visit www.baruch.cuny.edu.

61

About The Authors

DONNA J. KELLEY, PH.D.

Donna J. Kelley, Ph.D.s Professor of Entrepreneurship at Babson College and holds the Frederic C. Hamilton Chair of Free Enterprise. She has taught and conducted research in the United States, China and Korea, and has worked in Indonesia as a Fulbright Specialist. Dr. Kelley is a board member of the Global Entrepreneurship Research Association (GERA) and leader of the GEM U.S. team. She has co-authored GEM reports on global entrepreneurship, women’s entrepreneurship, entrepreneurship education and training, and entrepreneurship in the United States, the Republic of Korea and Africa.

ABDUL ALI, PH.D.

Abdul Ali, Ph.D is Associate Professor of Marketing and Entrepreneurship at Babson College. He served as Chair of the Marketing Division from 2000 to 2006 at Babson College. Dr. Ali’s research, teaching and consulting focus on entrepreneurial marketing, new product management, marketing analytics, marketing strategy and marketing high-tech products. His work has appeared in leading innovation management and marketing journals. Dr. Ali has been Area Editor of Marketing and Entrepreneurship for the Journal of Asia Business Studies since 2006.

CANDIDA BRUSH, PH.D.

Candida Brush, Ph.D., is Professor of Entrepreneurship and Chair of the Entrepreneurship Division. She holds the Franklin W. Olin Chair in Entrepreneurship and serves as Director of the Arthur M. Blank Center at Babson College. She holds an honorary doctorate from Jonkoping University in Sweden and is a Visiting Adjunct Professor at Nordlands University in Bodo, Norway. Dr. Brush is a founding member of The Diana Project International and winner of the 2007 Global Award for Outstanding Research in Entrepreneurship. Her research investigates women’s growth businesses, angel investing and strategies of emerging ventures. She has authored nine books, 120 journal articles and other publications. She serves as editor for Entrepreneurship Theory and Practice and is an angel investor and board member for several companies and organizations.

62

ANDREW C. CORBETT, PH.D.

Andrew C. Corbett, Ph.D., is a Babson Research Scholar and Associate Professor of Entrepreneurship at Babson College. He is the general editor of the Journal of Management Studies and serves on the editorial board of other entrepreneurship journals. His research on entrepreneurship has been published in leading outlets around the globe, including the Harvard Business Review, the Journal of Business Venturing, Strategic Entrepreneurship Journal, and Entrepreneurship: Theory & Practice.

CAROLINE DANIELS, PH.D.

Caroline Daniels, Ph.D., is Senior Lecturer of Entrepreneurship at Babson College. Her research covers future trends and also entrepreneurial and innovation strategy. She has worked on development of global business and technology strategies for numerous start-ups and corporations in the technology, energy, financial, consumer goods, pharmaceutical, publishing, safety, and services industries. She has facilitated multi-client studies for The Economist Group and several corporations on the future of business. Her work appears in leading publications including The Economist, Economist Intelligence Unit, Financial Times, Wall Street Journal, and Forbes. She has published several books on globalization and information technology with McGraw-Hill and the Pearson Group (Addison-Wesley). She is a frequent speaker at conferences on the future of business.

PHILLIP H. KIM, PH.D.

Phillip H. Kim, Ph.D., is Associate Professor of Entrepreneurship at Babson College. His research has been published in leading entrepreneurship, management, and sociology journals such as Journal of Business Venturing, Harvard Business Review, and the American Behavioral Scientist. His views on entrepreneurship and innovation have appeared in the Wall Street Journal, New York Times, Forbes, and other leading media outlets.

ABOUT THE AUTHORS

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THOMAS S. LYONS, PH.D.

Thomas S. Lyons, Ph.D., is the Lawrence N. Field Family Chair in Entrepreneurship and Professor of Management in the Zicklin School of Business at Baruch College of the City University of New York. His research focus is entrepreneurship and its role in community and regional economic development. Dr. Lyons has authored, co-authored or edited 11 books and numerous articles, book chapters and technical reports on entrepreneurship, enterprise development, business incubation, and state and local economic development. He was the 2011 recipient of the Community Development Society’s Ted K. Bradshaw Outstanding Research Award. He teaches courses in social entrepreneurship and entrepreneurship and community development. Dr. Lyons holds a Ph.D. in Urban and Regional Planning from the University of Michigan at Ann Arbor and has worked as a practicing planner and as an entrepreneur.

MAHDI MAJBOURI, PH.D.

Mahdi Majbouri, Ph.D., has been Assistant Professor of Economics at Babson College since August 2010, when he received his Ph.D. from the University of Southern California. He has a B.S. in Mechanical Engineering and an M.B.A. from Sharif University of Technology in Tehran, Iran. Developmental entrepreneurship and labor economics are his main areas of research. His past work covers topics in finance, real estate economics, and microeconomic theory. His work has been published in The Journal of Real Estate Finance and Economics and The Quarterly Review of Economics and Finance.

EDWARD G. ROGOFF, PH.D.

Edward G. Rogoff, Ph.D., is the Lawrence N. Field Professor of Entrepreneurship in the Narendra Paul Loomba Department of Management of the Zicklin School of Business at Baruch College of the City University of New York. He is Chair of the Department of Management, where he teaches and conducts research in entrepreneurship, particularly relative to minority and later-life issues. Dr. Rogoff was named the 2010 Outstanding Entrepreneurship Educator of the Year by the United States Association of Small Business and Entrepreneurship. He is the author of Bankable Business Plans, co-author of both The Entrepreneurial Conversation, and The Second Chance Revolution: Becoming Your Own Boss After 50. He has published in The Journal of Business and Entrepreneurship, The Journal of Developmental Entrepreneurship, Family Business Review, and Journal of Small Business Management.

ABOUT THE AUTHORS

Contacts

For more information on the Global Entrepreneurship Monitor 2015 United States Report, contact:

Donna J. Kelley [email protected]

GEM global reports, national team reports, public data sets (and Google Data Explorer), events information, and related materials are available on the GEM website: www.gemconsortium.org.

Researchers from economies not currently represented in the GEM Consortium may inquire about joining and request information by e-mailing GEM Executive Director Mike Herrington at [email protected].

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