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Federal Reserve Bank of Chicago

A Conversation with 590 Nascent
Entrepreneurs
Jeffrey R. Campbell and Mariacristina De Nardi

WP 2007-20

A Conversation with 590 Nascent Entrepreneurs∗
Jeffrey R. Campbell† Mariacristina De Nardi‡
November, 2007

Abstract
This paper summarizes interviews from 1998 with 590 individuals trying to create
a business centered around five questions: “Who are you?”, “What are you trying to
accomplish?”, “What have you and others put into the business?”, “What have you
accomplished?”, “What remains to be done?” There is a great deal of heterogeneity
across these Nascent entrepreneurs, but they tend to have more education than the
general population. Growing up in a family in which one or both parents had a business
does not seem to be an important determinant of entry into entrepreneurship for males,
while it seems to be of some importance for females. Most of the nascent businesses are
in retail and consumer services, and about 50 percent of nascent entrepreneurs expect to
become employers within five years of the business’s birth. Most nascent entrepreneurs
have already made personally-significant investments of time and money in their firms;
and nearly all of them are saving for their firms out of non-business income. For
about half of the sample, these investments have yielded a fully-specified product;
and the remainder are still in the product development stage. Family and friends are
an importance source of seed money for many Nascent Entrepreneurs. Formal credit
markets have been requested for funds only by a minority of Nascent Entrepreneurs,
and almost half of these applicants have been denied loans. About 40% of the Nascent
Entrepreneurs believe that their businesses require significantly greater equity before
they can attract external funds.
JEL Classification: L26, M13
Keywords: Panel Study of Entrepreneurial Dynamics, Entry, Business Credit

∗
The views expressed in this paper are those of the authors and do not reflect those of the Federal
Reserve Bank of Chicago, the Federal Reserve System, or its Board of Governors. Katherine Meckel provided
superlative research assistance. A replication file is available at http://www.nber.org/˜jrc/psed
†
Federal Reserve Bank of Chicago and NBER. E-mail: jcampbell@frbchi.org
‡
Federal Reserve Bank of Chicago and NBER. E-mail: denardim@nber.org

1

Introduction

We are interested in individuals or groups of individuals deciding to start a new firm. We
think of this process as the choice of a technology subject to constraints. The different
technologies that one can chose from differ in terms of capital and labor intensity, the labor
that the founders have to put in to run the technology most efficiently, the founders’ abilities,
and the risk and return trade-off. A person or group of people starting off with some
human capital and financial resources and facing borrowing constraints will choose a different
technology depending on their endowments, abilities, willingness to work on the business,
and how much they can borrow.
We use a new data set, The Panel Study of Entrepreneurial Dynamics (PSED) to better
understand the new business start-up process. We organize our analysis as a conversation
with these nascent entrepreneurs, and our questions are composed of five building blocks:
“Who are you?”, “What are you trying to accomplish?”, “What have you and others put
into the business?”, “What have you accomplished?”, “What remains to be done?” Understanding these factors is crucial to inform how to best model entrepreneurial behavior and
to discuss policy changes and interventions.
We summarize our main findings for each of our questions.
1. Who are you? Mid-career and middle-aged men tend to shun entrepreneurship,
while the opposite is true for middle-aged women. Nascent Entrepreneurs have somewhat better educational qualifications than their non-entrepreneurial counterparts, so
“entrepreneurship” does not merely substitute for “labor-market loser”. Family business background seems to be unimportant for whether a man becomes a nascent entrepreneur but quite important for the same choice of women.
2. What are you trying to accomplish? Most Nascent Entrepreneurs plan to open
a retail store or a restaurant or provide a health or education-related service, and a
sizeable minority of women plan to begin manufacturing something. The vast majority of nascent businesses are independent start-ups and are organized either as sole
proprietors or general partnership. Most of them also plan on their business making a
substantial contribution to household income. However, the respondents’ anticipated
business sizes differ greatly. Nearly half of them plan to employ nobody but themselves. The majority of the remainder plan to become significant employers within five
years. Women tend to have plans for smaller businesses than men do.
3. What have you and others put into the business? We study time inputs by the
Nascent Entrepreneur, capital investment by all of the owners involved in the start-up,
and funds provided by others.
1

Time. The average Nascent Entrepreneur has been thinking about starting this new
business for three to four years, with males putting in more time than females. The
average Nascent Entrepreneur has already put in more than six months of full time work
to get the business started. An analysis of how Nascent Entrepreneurs are currently
splitting their time reveals a large degree attachment to the labor market or housework.
A comparison of the male and female labor supply patterns reveals a significant gender
gap: a larger fraction of men put in more market work, but little effort in the house,
while the opposite is true for women.
Funds Most NEs either have saved or are currently saving to start their business, and
the vast majority have invested their own money in their own business. Looking at
the size of the owners’ capital investments reinforces the view that women aspire at
running businesses that are smaller and require less capital: female NEs have put in
half as much capital as male NEs throughout the whole distribution of funds invested.
It also shows that even though the median investment made so far by male NEs is
just $5,000, there is a long tail in the distribution. An analysis of the other sources
of funds shows that informal credit markets (such as the provision of funds by family
and friends) are the first source of funds (after one’s own savings) that one asks for,
with 42% of the sample having done so. Even for this kind of loans, however, asking is
no guarantee of receiving, with an acceptance rate that varies between 84% for one’s
spouse, 66% for one’s family and friends, and 33% for one’s employer. Conditional
on receiving one such loan, the amounts are modest, but not negligible ($14,000 is
the average total amount received by male NEs and $3,000 is the corresponding figure
for female NEs). Only 25% of our male NEs and 16% of our female NEs apply for
formal business loans, and only 4% to 14% of the applicants are granted such a loan.
Conditional on receipt, these loans are at least two times as large as those provided by
the informal credit network.
4. What have you accomplished? By survey design our Nascent entrepreneurs have
not had revenues to exceed costs for more than three months., but our sample still
shows a good deal of heterogeneity in their stage of product development. About 45%
of our sample has a product or service that is ready for delivery, while 20% is at the
prototype stage. Only 12% of our NEs are employers already, and of this minority,
only 30% have two employees or more. About 40% of the sample have already received
some revenue from operating their business.
5. Who remains to be done? The survey also asks the NEs what thy think is a business
size at which their firms is self-sufficient to generate revenue to cover costs, and at
what size their firm is large enough to attract funding from the established business
2

community. Ten percent of our NEs say that their firm is already self-sustaining, while
only 5% say that their firm already has received funds from the established financial
community. A significant fraction, 23%, still faces a lot of uncertainty about both
questions, and does not know how to answer them.
A comparison of the two distributions indicates that business size needed for selfsufficiency is larger than business size needed to borrow from the established financial
community. This could indicate that in many cases the NEs believe that they can start
formal kind of borrowing before their business reaches its self-sustaining size.
Looking at the distributions of the ratios between the capital that the new business
owners have already invested in their business and these two measures of business selfsufficiency gives us some idea of how far these business need to go before they really
become operational. These distributions reveal that 30% of the male NEs think that
their business is already large enough to be self-sustaining, compared to 40% of the
female NEs. In terms of borrowing, 50% of the male NEs believe that their firm is not
yet big enough to attract funding from the established financial community, compared
with 40% of the female NEs.
Section 2 describe the sampling strategy and the main characteristics of the data set.
Section 3 address the question “Who are you?”, Section 4 refers to “What are you trying to
do?”, Section 5 studies “What have you and others put into the business?”, Section 6 looks
at “What have you accomplished?”, Section 7 refers to “What remains to be done?” and
Section 8 concludes.

2

Data Collection

Nascent entrepreneurs are in the middle of two processes central to economic mobility and
growth: the movement of their signatures’ to the paycheck’s front and the creation of a
new good or service. Little is known about their activities because they they typically start
with neither employees nor sales and therefore fall through the cracks of administrative data
collection. The Panel Study of Entrepreneurial Dynamics (PSED) was a data collection
project undertaken by the Entrepreneurial Research Consortium (ERC) to fill the resulting
need for observations of nascent entrepreneurs.1
Gathering such data presents the challenge of finding potential entrepreneurs. For this,
ERC relied on a weekly commercially-conducted telephone survey.2 During July, August,
1

Here, we provide only a brief overview of their collection. Reynolds (2000) provides a more complete
description.
2
See Market Facts (2001) (available at http://www.synovate.com/knowledge/research-on-research/ for
a description of the random procedure used for the selection of telephone numbers.

3

November, and December of 1998 and April of 1999; the surveyors asked each of 15, 118
respondents
Are you, alone or with others, now trying to start a new business?
For those answering “yes”, the surveyors followed with
Will you own all, part, or none of this new business?
Unless the respondent answered with “all” or “part”, the interviewer then asked
In the past twelve months, have you done anything to help start this new business,
such as looking for equipment or a location, organizing a start-up team, working
on a business plan, beginning to save money, or any other activity that would
help launch a new business?
The market research firm identified those who answered affirmatively as Nascent Entrepreneurs.
Of those, 87 percent agreed to have their first names and phone numbers forwarded to the
University of Wisconsin for further questioning. These form the initial sample of Nascent
Entrepreneurs. The market research firm also forwarded first names and telephone numbers
of a sample who were not asked about their business activities but agreed to be contacted
for “a study of the work and career patterns of all Americans, including those not currently
working.” Sixty two percent of those asked agreed to be contacted. The ERC used these to
collect data from a comparison group. The ERC contracted with the University of Wisconsin Survey Research Laboratory to conduct telephone interviews of both samples. For the
overwhelming majority of sampled individuals, the phone interview occurred within three
months of the initial screening interview.
For the Nascent Entrepreneurs, the interviews began by asking whether the business’s
revenues were sufficient to cover the salaries of manager/owners. If so, the ERC considered
the firm to be an established business and the interview terminated. This screen eliminated
about 27 percent of the initial NE sample. Seven percent of those left could not be contacted,
and twenty percent refused to be interviewed. The remaining 446 identified and screened
Nascent Entrepreneurs cooperated with the survey. The survey of the comparison group
yielded exactly half as many responses.3
In mid 1998 the National Science Foundation funded the ERC to over sample Women
Nascent Entrepreneurs. The screening interviews for this sample occurred in the last four
months of that year (concurrently with the initial representative sample) and the telephone
interviews occurred quickly thereafter. This sample contains 223 interviews. Curiously, 52
of them are male. Some of these seem to have arisen when a husband answered the interview
3

These figures come from Reynolds (2000) and Gartner et al. (2004).

4

Table 1: PSED samples observation counts
Males
NE CG
All Records
275 104
272 104
with Age Recorded
over 20 Years Old
263 102
with Education Recorded 261 102
with Experience Recorded 260 102

Females
NE CG
342 119
337 119
335 116
334 116
330 115

“NE” and “CG” denote Nascent Entrepreneurs and members of the Comparison Group.

about a husband-wife business partnership, but answers to other questions rule out this
explanation for the others. Our analysis excludes these male members of the female over
sample.
We begin with the 171 female NE’s from the over sample and the 446 NE’s from the
initial sample. To better understand who these NE’s are, we employ the 223 comparison
group observations.4 Before proceeding with the analysis, we apply a few simple screens.
We keep only those observations with age, education, and experience recorded who were
over twenty years old. Table 1 shows the number of observations each screen keeps. The
final sample has 590 Nascent Entrepreneurs promised in this paper’s title and a comparison
group of 227. The predominance of women among the Nascent Entrepreneurs arises from the
female over sample. Women are a minority of the randomly-selected Nascent Entrepreneurs,
a fact which creates research and policy interests in female entrepreneurship.
Many of our tables report data for three different samples. The column “All” refers to the
initial representative sample, which includes both male and female NE. The column “Males”
reports data for the males in the representative sample. The column “Females” refers to all
female NEs, both in the representative sample and in the female oversample.

3

Who are you?

A casual encounter with a stranger begins with assessing her or his age. If a conversation
arose and it became more personal, you would begin by talking about the person’s spouse
(if one exists) and children. A longer conversation would then turn to the person’s schooling
and career path. You might learn about someone’s family background after some time, and
personal financial details could be forthcoming if you had earned a great deal of trust. Our
4

The data set also contains a small minority over sample which we do not use. The ERC collected it in
late 1999 and early 2000.

5

Figure 1: Comparison of Demographic Characteristics
Men

Women
45

Single
30’s
Kids 7 to 12

31

40’s
50’s
Kids ≤ 6
20’s
Kids 13 to 18

20

5

Nascent Entrepreneurs

Nascent Entrepreneurs

45

60+
9

22
36
Comparison Sample

Kids ≤ 6
21

Kids 7 to 12

Single

Kids 13 to 18

50’s
20’s
60+

1

45

40’s

31

2

21
28
Comparison Sample

45

Note: Each axis gives the fraction of the indicated sample falling into the given category. All axes are
expressed in percentage points.

conversation with the 590 Nascent Entrepreneurs follows this general pattern. To make
their answers more meaningful, we hold the same conversation with the 217 members of the
comparison group and compare the two samples’ answers.

3.1

Demographics

The PSED data contain answers to basic demographic questions regarding the person’s
age, marital status, and the presence of children. To summarize the respondents’ ages, we
break them into decades (20-29, 30-39,. . .,60 and over). We say that people who are neither
married nor cohabitating are single, and we summarize their parental responsibilities with
indicators for the presence of children in three age ranges, 6 and under, 7 to 12, and 13
to 18. Figure 1 compares the averages of these data across Nascent Entrepreneurs and the
Comparison Group. In each of the gender-specific panels, the x-axis gives the percentage of
the comparison group with the relevant dummy variable equal to one. The y-axis gives the
analogous percentage for the control group. Each indicator variable has a data point, and a
label accompanies each one. Points close to or on the 45 degree line indicate that the two
groups have roughly the same percentage of respondents in the NE and the corresponding
control group.
Begin with age. For both genders the fraction of people over 60 is lower among the
NE than in the comparison group. This is generally consistent with people starting to retire
around that age. Once we set this older cohort aside, the male and female NE display opposite

6

patterns. While women in their 30s and 40s are more likely to be NE then their younger
and older sisters, men in their 40s are under represented among the NE. This is consistent
with the choice of different career paths for men and women due to the responsibility of
childcare. Men rationally accumulate large amounts of on-the-job experience not foreseeing a
family oriented-interruption of their career and are thus less likely to enter entrepreneurship
once their career is full swing. The historically observed patterns of female labor force
participation over the lifecycle show that the fraction of women of childbearing age drops
due to the withdrawal of women with small children. Women rationally foreseeing this
interruption have a lower return to job-specific human capital and are thus more attracted
to entrepreneurship in their thirties and forties after they return to work. The possibility
also exists that, at that point in their life, they might choose to start a business to have a
more flexible schedule. We examine this below.5
Proceeding to marital and parental status, Nascent Entrepreneurs from both groups are
much less likely to be single than their counterparts in the Comparison Group. Single
women comprise 43 percent of the comparison group but only 31 percent of the Nascent
Entrepreneurs. The difference for the men is smaller (36 percent versus 32 percent) but
nevertheless substantial.
There is one notable differences between the two samples’ parenting obligations. Male
Nascent Entrepreneurs are less likely to have teenaged children in the home. Among men,
22 percent of the control group and 16 percent of the Nascent Entrepreneurs have teenagers.
Female Nascent Entrepreneurs, instead, are more likely to have teenaged children in the
home, with 29 percent compared to 24 percent in the control group. These patterns line up
with the relative absence or abundance of the 40 year old among male and female NEs.

3.2

Education and Experience

The conversation now moves on to educational background and experience. The PSED
interviewers asked respondents in both samples
How many total years of full time, paid work experience in any field have you
had?
We divide the answers into decades (0 to 9, 10 to 19, 20 to 29, and 30 or more) and tabulate
each sample’s distribution across them. The PSED assigns respondent’s education into prespecified bins. We condense these bins into three by combining grade school and less then
5

Another demographic characteristic of potential interest is racial background. We have also examined
differences in the racial backgrounds of Nascent Entrepreneurs with the Comparison Group. We found little
worth reporting.

7

Figure 2: Comparison of Education and Work Experience
Women

HS

51

Nascent Entrepreneurs

Nascent Entrepreneurs

Men

College
10−19
27.5

0−9
30+

3

Worked for Parents
20−29

Less Than HS
3

26.5
Comparison Sample

HS

57
College
10−19 0−9
Worked for Parents

31

20−29
30+
3

55

4

Less Than HS
26.5
Comparison Sample

62

Note: Each axis gives the fraction of the indicated sample falling into the given category. Numerical ranges
refer to work experience in years. All axes are expressed in percentage points.

high school into “Less then High School”, high-school and more then high school into “High
School Grad”, and college and post-college into “College Grad”.
Figure 2 displays the comparison of these variables in the same format as Figure 1.
Although we measure actual experience and not potential experience (which is just a transformation of age), the patterns for experience follow the patterns for age in figure 1 closely.
The sample of Nascent Entrepreneurs has relatively few men with 20 to 29 years of experience
(34 percent versus 23 percent). The only notable difference in work experience between the
Women Nascent Entrepreneurs from their Comparison Group is an under-representation of
women with 0 to 9 years of work experience (37 percent versus 33 percent). The educational
indicators clearly indicate that Nascent Entrepreneurs tend to be better educated than the
Comparisons. Those with education of an high school degree or less are if anything, under
represented among the NEs. Moreover, those with a college degree comprise a larger fraction
of both genders’ samples of Nascent Entrepreneurs. The differences are 3 and 5 percentage
points for men and women. One view of entrepreneurship holds that it is primarily a euphemism for underachievement in the regular labor market. These Nascent Entrepreneurs’
accumulated work experience and education give no support for that hypothesis.

3.3

Family Business Background

For our conversation with entrepreneurs, we want the discussion about family background
to drift towards parents’ and other family members’ entrepreneurship. Much of the previous

8

Figure 3: Comparison of Family Business Backgrounds
Men
Neighbor Family Business

Nascent Entrepreneurs

Nascent Entrepreneurs

80

Women

Extended Family Business
Family Business
38
18

Self Emp. ≥ 5 Years
Worked for Parents
Employed ≥ 5
Owned > 1 Business
19

44
Comparison Sample

Neighbor Family Business

71

Extended Family Business
Family Business
Self Emp. ≥ 5 Years

47

Worked for Parents
Employed ≥ 5
Owned > 1 Business

21

74

14

43
Comparison Sample

69

Note: Each axis gives the fraction of the indicated sample with positive responses in percentage points.

literature on entrepreneurship has speculated on the transmission of entrepreneurship-specific
human capital from parents to children. For example, Lentz and Laband (1990) show that
about 50 percent of their sample of business owners had at least one self-employed parent.
Whether this is remarkable depends on the analogous frequency for non-Entrepreneurs. The
PSED surveyors asked both samples a variety of questions about the presence, scale, and
longevity of family businesses during the respondent’s youth. We use these to determine
whether or not entrepreneurial families tend to produce Nascent Entrepreneurs.
With the PSED data, we determine the respondent’s answers to the following questions:
• Did either or both of your parents ever manage a business owned by the family?
• Did any business owned by your family ever employ five or more people (including paid
family members)?
• Were either of your parents self-employed for five years or more?
• Did either of your parents own more than one business?
• Did you ever work for one or both of your parents?
• Did anyone in your extended family own a business?
• Did any close friends or neighbors own a business?
Together, these questions measure the entrepreneurial skills of the respondents’ parents
and their potential exposure to it. Figure 3 displays the results for the comparison of
9

the two samples. Just as in Lentz and Laband (1990), fifty percent of male NE’s and
55 percent of female NE’s had parents who owned at least one business. However, about
48.5 percent of the comparison groups of both sexes also had parents who were once active
business owners. This is hardly a very large difference. For the men’s comparison, the
frequencies line up on or slightly below the 45 degree line with one exception (the presence
of entrepreneurs among neighbors and close friends). That is, Male Nascent Entrepreeurs
have no observable advantage in intergenerational entrepreneurial skill acquisition over the
members of the comparison sample.
Moving on to the women, the story changes. The female NEs are much more likely
to come from families in which at least one of the parents was running a business, thus
indicating that being exposed to the operation of a family business, or working for a family
business, has a much greater effect on the propensity of females to start up a new business
rather than on the one for males. This is an interesting hypothesis, which deserves further
investigation.

3.4

Financial Background

Financial questions usually evoke guarded reactions. Surprisingly, the PSED respondents
were more forthcoming about their income and wealth than expected. When asked
What was your total household income from all sources and before taxes last
year? Be sure to include income from work, government benefits, pensions, and
all other sources.
only 77 of the 840 respondents refused to answer. These non-respondents were then asked a
sequence of bracketing questions, such as
Then, would you tell me, is your households total annual income, before taxes,
over $50,000 per year?
Only 20 of the 77 refused to participate in the bracketing questions, so arguably sample
selection has only a small impact on the PSED income data. The respondents were less
cooperative with questions on wealth (about 3/4 of the respondents gave answers), but most
of those who did not answer the direct questions were willing to bracket their wealth.
Figure 4 uses these variables to compare Nascent Entrepreneurs’ financial backgrounds
with those of the Comparison Group. So that we can use the responses of those who only
gave brackets for their income and wealth, we define dummies for high income (≥ $50, 000),
very high wealth (≥ $500, 000), and high wealth (≥ $100, 000). The figure also plots the
frequencies of home ownership, mortgage debt, and non-mortgage debts exceeding $5, 000.
For the men, the figure shows clearly that the Nascent Entrepreneurs are somewhat less
10

Figure 4: Comparison of Financial Backgrounds
Men

Women
Homeowner

68

Nascent Entrepreneurs

Nascent Entrepreneurs

80
Other Debt ≥ $5000

53

Mortgagor Income ≥ $50k
Wealth ≥ $100k

11

Wealth ≥ $500k
15

56
Comparison Sample

77

80
71

Homeowner
Other Debt ≥ $5000

54

8

Income ≥ $50k

Mortgagor
Wealth ≥ $100k

Wealth ≥ $500k
4

48
Comparison Sample

70

Note: Each axis gives the fraction of the indicated sample with positive responses in percentage points.

financially well-endowed than their counterparts in the Comparison Group. Only 52 percent of the male NE’s have household incomes exceeding $50, 000, while 59 percent of the
comparison group does. These NE’s are less likely to have wealth over $100, 000 (42 percent
versus 51 percent) or over $500, 000 (11 percent versus 15 percent). The two groups frequencies of mortgage debt both approximately equal 55 percent, but the rate of home ownership
among the Nascent Entrepreneurs is ten percentage points lower. Thus, home ownership
without mortgage debt is less frequent among the NEs. Finally, NE’s are more likely to have
non-mortgage debts exceeding $5, 000 (65 percent versus 57 percent).
One obvious possible explanation for these results is the over representation of young men
among the NE’s. Examining the same statistics for the women gives that a quick plausibility
check. Indeed, female NE’s are much more likely to come from high-income households (52
percent versus 41 percent) and much more likely to come from very-high wealth households
(8 percent versus 4 percent). The two samples of women have about the same frequencies
of home ownership, mortgage debt, and high wealth. The only financial statistic which
indicates a financial disadvantage for female NE’s is the frequency of non-mortgage debt
exceeding $5, 000. This debt could be financing for the new business, which we explore in
more detail below.

3.5

Summary

The 590 Nascent Entrepreneurs in the PSED did not answer “Who are you?” with a great
deal of uniformity. Men and women of all ages and backgrounds try to start businesses. Nevertheless some patterns do emerge when comparing the NE’s responses to those from the com11

parison group. First, mid-career and middle-aged men tend to shun entrepreneurship, while
the opposite is true for middle-aged women. Nascent Entrepreneurs have somewhat better
educational qualifications than their non-entrepreneurial counterparts, so “entrepreneurship”
does not merely substitute for “labor-market loser”. Family business background seems to
be unimportant for whether a man becomes a nascent entrepreneur but quite important for
the same choice of women. Finally, any substantial differences in the incomes or assets of
those who decide to become Nascent Entrepreneurs are too subtle to manifest themselves in
basic summary statistics.
With the answer to our conversation’s first question in place, we now discard the comparison group and henceforth focus on the nascent entrepreneurs.

4

What are you trying to accomplish?

The conversation now continues with a discussion of what the Nascent Entrepreneurs are
trying to accomplish. Their business plans can vary on many dimensions, but some seem
particularly relevant: type of product or service, intended scale, intended duration, potential
importance for household income, and expected legal organization. The PSED respondents’
answers to questions on these specific subjects give us a useful answer to this section’s
eponymous question.

4.1

Industry

The product or service to be sold determines many of the opportunities and constraints
facing the Nascent Entrepreneur. The PSED interviewers asked the respondents to place
their business into one of twenty categories. These do not replicate any standard industry
classification system, because the survey designers correctly anticipated that some industries
(like Food Service) would have very high frequencies.
Table 2 tabulates the Nascent Entrepreneurs’ answers. A large fraction of the men (35%)
is starting a business in Health, Education, and Social services. Among the female NE this
is also a strong category (20%). One might wonder if this high percentage reflects medical
professionals beginning independent practices. The very low percentage of respondents with
MD’s or equivalent post-graduate degrees (about 3 percent) indicates that this explanation
is wrong. Retail and Restaurants account for 28 percent of the men and 45 percent of the
women. The final stand-out category surprised us: manufacturing. Fifteen percent of the
women and 8 percent of the men chose this field. Together, these leading four categories
add to 80 percent of the women and 61 percent of the men. The remaining NEs of both
sexes spread themselves fairly uniformly over the others. Two categories’ small frequencies

12

Table 2: Industry Choices

Retail
Restaurant
Customer Service
Health, Education, Social Services
Manufacturing
Construction
Agricolture
Mining
Wholesale Distribution
Transportation
Utilities
Communications
Finance
Insurance
Real Estate
Law or Accounting
Computer Programming
Business Consulting
Business Services
Business Consulting or Service, Unspec.

13

All Men Women
12
9
16
22
19
29
4
5
4
28
35
20
11
8
15
4
4
3
2
2
2
2
2
1
0
0
0
3
3
2
0
0
1
3
3
2
1
1
1
0
0
0
2
2
1
0
0
1
0
1
0
1
1
1
1
1
0
2
3
1

Table 3: Sponsorship of Start-up Effort

Independent Start-Up
Purchase/Takeover
Franchise
Sponsored Start-Up

All Males Females
85
84
86
3
2
3
6
10
4
6
4
7

went against our prior: The sum of Business Services and Business Consulting or Service,
Unspecified only equals 4 percent for the men and 1 percent for the women. We speculate that
these businesses require very little gestation time and so are likely to be under represented
a sample of Nascent Entrepreneurs relative to a sample of new businesses.

4.2

Business Organization

A decision closely related to product choice is the business’s sponsorship. Existing firms can
sponsor a startup through franchise or a less routine cooperation agreement. Furthermore,
the possibility exists that some NE’s are actually purchasing (and possibly overhauling) a
business rather than beginning from scratch. Table 3 reports the frequencies of these three
kinds of sponsorship along with the frequency of independent start-ups. Only 10 percent of
the men and 4 percent of the women are starting a franchised business, and sponsorships
from existing firms account for another 4 percent of the men and 7 percent of the women.
Only 2 to 3 percent of these Nascent Entrepreneurs are purchasing a business, so the vast
majority of them are independent of any sponsorship.
A business’s legal organization provides a contracting structure. It also determines
whether or not the business pays taxes, whether or not it can raise equity funds from the
general public, and the liability of its shareholders for the business’s activities and debts.
With a Sole Proprietorship, equity financing is impossible and the single individual owning the business is indistinguishable from the business itself. A General Partnership also
cannot raise equity financing and must pass through its profits to its owners for taxation.
The partners together are also liable for the business’s activities and debts (typically jointly
and severally). Other forms of legal organization offer protection from business liability and
access to equity-based capital markets in return for additional reporting or business taxation. A Limited Partnership is like a General Partnership with the ability to accept equity
financing from one or more Limited Partners who are not liable for the business’s actions.
Limited Liability Partnerships (which were very new at the time of the PSED survey) and
S-corporations take this one step further by eliminating the General Partners from a Limited

14

Table 4: Legal Form

Sole Proprietorship
General Partnership
Limited Partnership
Corporation
Subchapter Corporation
Limited Liability Company
Not yet determined

All Males Females
49
48
56
19
17
21
6
7
5
9
11
6
7
9
5
4
4
3
5
4
5

Partnership. That is, all of the business’s owners enjoy limited liability. However, they face
limits in their ability to raise equity capital. Finally, C-corporations are familiar from the
world of big business. They can raise equity in public markets, and their shareholders only
pay income tax on dividends received. In return for these abilities, they must pay corporate
income tax.6
Table 4 reports the percentages of the Nascent Entrepreneurs who expect to chose or
already have chosen each legal form. Very small businesses with little need for capital or
liability protection should obviously chose to be Sole Proprietorships, so it is unsurprising
that about half of the Nascent Entrepreneurs will go with this organization. General Partnerships account for another twenty percent, and five percent of the respondents have not yet
determined their legal form. Only 25 percent of the Nascent Entrepreneurs plan to obtain
some form of limited liability, and their choices are spread out fairly evenly across the four
legal forms.
All partnerships bring two or more people with different resources and skills together
for a common purpose. A relevant dimension of heterogeneity for new business partners is
family affiliation.
A partner from outside the Nascent Entrepreneur’s household brings labor and possibly
some financial resources, and he shares the risks of the business venture. However, because
complete contracts are hard to write, such cooperation potentially expose the partners to
risks such as each others’ illnesses, personal financial problems, or simple under performance.
For a Nascent Entrepreneur in a conventional nuclear family, the only available business
partner from within the household is the spouse. When couples pool financial resources,
adding a spouse as an active business partner only dedicates more of the household time
endowment to the business. However, this this comes at little cost. Although traditional
marriage vows do not mention under performance, they explicitly bind the couple to share
6

See for more information on the choice of corporate form.

15

Table 5: Partnerships

with
with
with
with
with

Spouse only
Spouse and other Family
other Family only
Family and Non-Family
Non-Family only

All

Men

Women

27.2
0.3
0.0
8.6
14.3

26.7
0.4
0.0
7.3
21.4

27.5
0.3
0.0
9.7
8.8

Note: (i) This panel gives the distribution of the number of non-spouse partners conditional on having at
least one.

health and financial risks whether or not they partner together in business.7 Moreover, better
information and the costs of breaking a long-term relationship lower the costs of incomplete
contracting. A family member living outside the respondent NE’s household lies between
these two extremes. Family members come from similar financial backgrounds, but they still
can bring labor and capital to a new business. Separating from your brother or sister is
easier than leaving your spouse, but ongoing familial relationships can still mitigate costs of
incomplete contracts.
Table 5 gives an empirical perspective on these choices by reporting the frequency of
partnerships for the respondent Nascent Entrepreneurs by family affiliation. Its top line
gives the overall partnership frequency, which approximately equals 56 percent for men and
46 percent for women. A little over half of these partnerships only involve the Nascent
Entrepreneur’s spouse. Thus, only about 1/4 of the Nascent Entrepreneurs have partnered
with somebody from outside of the home. A trivial percentage has added other family
members to a partnership with the spouse, and none of the respondents report partnering
only with family members living outside of the household. About 7 percent of the men and
10 percent of the women mix partners from within and outside the family.8 The table’s final
line reports the frequency of partnerships without family members, 21.4 percent for men and
8.8 percent for women. This is the major gender difference in the table. Although only a
minority of Nascent Entrepreneurs has a partner from outside of the household, men turn
non-family contacts into business partnerships more frequently than women do.

16

Table 6: Anticipated Business Size

Wants Large Business
Expects Employment ≥ 1 in
First Year
Fifth Year
Expects Employment ≥ 5 in
First Year
Fifth Year
Will the firm operate in five years?
Maybe
Yes
Will the firm become your family’s primary income source?
Maybe
Yes

4.3

Men
22

Women
15

56
60

41
47

29
43

18
29

51
45

50
46

58
34

65
25

Size

With the exception of those entering Manufacturing, few in our sample could possibly be
planning to create a steel mill or similarly large employer. Retailers’ and Restaurants’
typical scales are much more modest than this. The high frequency of Sole Proprietorships
and General Partnerships also suggests that these Nascent Entrepreneurs are creating small
businesses. Nevertheless, two open dimensions of the nascent businesses’ intended scale
interest us. Its potential economic importance for others (particularly prospective employees)
and its possible long-term contribution to household income. We begin examining the first
with the Nascent Entrepreneurs’ answers to
Which of the following two statements best describes your preference for the
future size of this business: 1) I want the business to be as large as possible, or
2) I want a size I can manage myself or with a few key employees?
The first line of Table 6 reports the fraction of each gender giving the first answer. A
significant fraction of NEs aspire to become tycoons with management delegated to others,
with more men (22%), than women (15%) doing so. However, most NEs harbor more
realistic modest ambitions. The PSED interviewers also asked more specific questions about
the entrepreneurs’ expected employment in the first and fifth years of operation. The table’s
7

For example: I, (Bride/Groom), take (you/thee) (Groom/Bride), to be my (wife/husband), to have and
to hold from this day forward, for better or for worse, for richer, for poorer, in sickness and in health, to love
and to cherish; and I promise to be faithful to you until death parts us.(Source: Wedding Central Australia)
8
These family members come from both within and outside the respondent’s household.

17

next two lines report the fraction of each sample planning to employ one or more people in
the first and fifth years.9 About 60% of male NEs expect to become employers over the first
five years of operation, compared with only 41% for the first year, and 47% for the fifth year
for female NEs. For those who wish to define entrepreneurs as employers to distinguish them
from the “merely” self-employed, these numbers do so. Apparently, about 40 percent of men
and 50 percent of women have no intention of designing a job for anybody but themselves.
The NE’s aspirations for employing five or more people confirm this apparent tendency of
women to plan smaller businesses. Thirty percent of men anticipate hiring five or more
people during the business’s first year, and 43 percent plan to do so within five years. The
analogous percentages for women are 18 and 29 percent.
The second dimension of size is relative to the household’s balance sheet. For this, one
question asked of the respondents seems relevant,
On a scale of zero to one hundred, where 0 means completely unlikely and 100
means absolutely certain, what is the likelihood that this business will become
the primary source of your familys income?
The answer to this question clusters at three points, 0, 50, and 100. With this in mind,
we divided the answers into three categories, “No” (< 50), “Maybe” (≥ 50 and < 100) and
“Yes” (100 exactly). Table 6 reports the frequencies of “Maybe” and “Yes” for both men
and women. About one third of the men and one quarter of the women said they were
absolutely certain that their business will become the primary family income. The high
actual failure rate for new businesses implies that these individuals either did not interpret
the question probabilistically, refuse to acknowledge publicly the possibility of failure, or have
overly optimistic expectations. Nevertheless this answer clearly indicates that these Nascent
Entrepreneurs believes that their business could become their households primary income.
Forty-four percent of the men and 47 percent of the women gave an answer between 50 and
99 inclusive. Again, these respondents harbor a substantial hope of becoming self-sustaining
entrepreneurs. Overall, most of these Nascent Entrepreneurs believe that they are creating
something financially significant for their household.

4.4

Summary

Just as with the demographic questions, the Nascent Entrepreneurs did not characterize their
planned businesses with one voice. They do share some common threads. Most of them plan
to open a retail store or a restaurant or provide a health or education-related service, and a
sizeable minority of women plan to begin manufacturing something. About half of our NEs
9

Many respondents reported “Don’t Know”, and we consider these to have no definite plans regarding
their firm’s size. They are included in the denominator when calculating these fractions.

18

plan on being sole proprietors, a quarter are choosing some form of limited liability. Most
of them also plan on their business making a substantial contribution to household income.
However, the respondents’ anticipated business sizes differ greatly. Nearly half of them plan
to employ nobody but themselves. The majority of the remainder plan to become significant
employers within five years. Women also tend to have plans for smaller businesses than do
men.

5

What have you and others put in so far?

With the Nascent Entrepreneur’s goals established, we now turn to what has been done
so far to turn ambitions into reality. Resources for business development can come from
the respondent Nascent Entrepreneur and from any business partners. The two NEs most
significant investments are their time and their money. The PSED interviewers asked the
respondents about their own investments of time and money as well as those of any active
business partners.

5.1

Time investments

We being with an examination of the entrepreneur’s use of time during the interview week,
and we then proceed in studying the amount of time elapsed since business conception, and
concludes by studying time invested in the business by the respondent and available partners.
5.1.1

Use of Nascent Entrepreneur’s time

The development of a business requires time at work. If switching between working for one’s
self and for others is easy, then we would expect many of our entrepreneurs to concentrate
their time on their new businesses. However, labor market frictions can make quitting a job to
work on an ultimately failed business much costlier than the foregone earnings. In that case,
we expect those with unproven business plans to hedge their bets by continuing to work for
pay while developing the business. Financial frictions that impede a Nascent Entrepreneur
from smoothing consumption during an extended period of business development without
other remuneration give another reason to continue working for others. In either case, the
market work delays the new firm’s birth.
The PSED interviewers asked each respondent detailed questions about their use of time
during the interview week, and Table 7 reports statistics from the answers relevant for
measuring the concentration of the respondents’ time on their new businesses. Its first line
reports the fraction of respondents claiming to work 35 hours or more per week on their
new businesses. The interviewers defined this to be “full time”. This equals 31 percent for
19

Table 7: Time allocation
All Men Women
FT NE
29
31
25
Some paid Work 67
70
62
49
55
39
FT paid work
Some housework 70
60
86
18
8
34
FT housework
Any FT work
80
82
78

men and 25 percent for women. For a hard worker, such effort does not exclude maintaining
an attachment to the labor market. The table’s second line indicate that large majorities
of both sexes do so by working for others for pay. One might speculate that most of this
is part-time work, so the third line reports the fraction of respondents who report working
full time for pay (again defined as at least 35 hours). Of the 70 percent of men working for
pay, 55 percent did so full time. The analogous statistics for women are 62 and 39 percent.
Apparently, about half of Nascent Entrepreneurs have hardly moved away from market work.
Home production also takes up a substantial fraction of a typical household’s time endowment. Substituting away from home work while keeping the consumption of goods produced
in the home unchanged requires finding someone from outside the household to assume these
tasks, which usually requires paying them. Thus, both labor market frictions and financial
constraints can also impede Nascent Entrepreneurs’ time investments in their businesses.
The final two lines of Table ?? report the fraction of Nascent Entrepreneurs who do some
housework (here defined as at least six hours per week) and full time housework. Just as
with market work, the majority of the respondents do some housework. The fraction of
men doing housework full time is unsurprisingly low, but for women this fraction equals one
third. Overall, only a minority of Nascent Entrepreneurs shows anything like a single-minded
dedication to business development. The majority either perceives such specialization to be
unwise or financially infeasible.
5.1.2

Time Since Conception

Understanding how long Nascent Entrepreneurs have been thinking about their start-ups
helps place all of their activities into perspective. The PSED interviewers asked the respondents (in two questions)
In what year and month did you start to think about this new business?
We assign this date to the business’s conception. The first two rows of Table 8 report mean
and standard deviation (in years) of the time elapsed from the business’s conception to the
20

Table 8: Time Since Conception
All Males Females
Average
3.7
4.2
3.3
Std. Deviation 5.0
5.9
4.1
Percentiles
10
0.4
0.5
0.4
20
0.8
0.8
0.7
1.2
1.3
1.1
30
40
1.7
1.8
1.5
2.1
2.3
2.0
50
60
2.7
3.0
2.3
3.5
3.8
3.3
70
80
5.2
5.3
5.1
8.5
10.3
7.8
90

interview date, and its remaining rows report this distribution’s percentiles. On average,
the sampled men have had the opportunity to work on their business for 4.2 years. For the
women this average is 3.3 years. The percentiles reveal that the difference between men and
women arises from differences between their distributions’ right tails. The median time since
conception equals 2.3 years for men and 2 years for women, and the 80th percentiles are 5.3
years and 5.1 years. A substantial minority of men who seem to never give up raise the
90th percentile to 10.3 years. The 90th percentile for women is only 7.8 years. Thus, both
distributions have a thick tail, but that for men is thicker.
It seems that the tail of Nascent Entrepreneurs who never get their businesses off of the
ground but also never give up disproportionately influence both statistics. To get a sense
of how time since conception is distributed once we exclude this tail, we have recalculated
the statistics in Table 8 after first dropping all observations with time since conception
exceeding five years. As expected, eliminating the right tail makes men and women much
more similar. The average durations for men and women are 2 and 1.7 years, and their
medians are slightly less (1.8 and 1.5 years). Suppose that all new businesses took exactly
x years to complete with efficient investments of time and money. Then the distribution of
time since business conception in any sample should be uniform with mean (and median) x/2
√
and standard deviation x/ 12. Given the sample means for these Nascent Entrepreneurs,
the predicted standard deviations are 1.15 for men and 0.98 for women. The actual standard
deviations equal 1.3 and 1.2 years. This relatively close match leads us to conclude that this
constant time-to-build model has promise for fitting these data after eliminating the tail of
very persistent but heretofore unsuccessful Nascent Entrepreneurs.

21

5.1.3

Time Spent on Business Development

When a business combines the resources of two or more active partners, they both contribute
their time. This combination can increase the total time spent on the project or merely split
it across the partners. We compare hours spent in the business by Solo owners, and total
hours worked on partnerships to evaluate this aspect.
The PSED interviewers asked each respondent to estimate the total time spent on the
start-up by the respondent and each active partner. We use this information to gauge total
time invested in the business, and we also use the time since business conception to compute
hours invested in the business per week.
Begin examining the table 9 that reports data for solo NEs. The average entrepreneur
in our sample put in 1,104 hours since the start. The median time investment is far less
than that (455 hours), which we would expect from any distribution with a thick right tail.
This overall average masks substantial difference between men and women. Throughout the
whole distribution women have worked about half as many total hours as men.
The three rightmost columns of this table give the summary statistics pertaining to hours
worked per week since business conception. The average amount of weekly time invested for
our sample is under nine hours, a very small amount of time. Even those that have worked
most intensively have not worked full time since the conception of the business. Since about
30% of our sample declare to be currently working full time for the business (see table 7), it
must be the case that they have not done so continuously since the business’ conception.
Men’s average hours of work per week equals 11, and women’s is 8. This discrepancy
is smaller than the one for total hours reflecting the observation that time since conception
is on average lower for the respondent women (see table 8). Accounting for time elapsed
since conception brings the distribution of weekly labor input for men and women very close
together.
With solo NEs the respondent’s time investments by definition equals the total time
invested by the owners in the business. Not so for NEs with partners. Table 10 reports
summary statistics for total hours worked on partnership startups. The average total hours
for all of the NEs partnerships in our sample equals 2,019. This almost two times the
analogous average for solo NEs. So clearly, partners do not merely replace the respondent’s
time in getting the business started. A look at the average hours per week reveals that this
gap is even more substantial when we take into account time since conception. Businesses
with partners take off much faster, so average hours per week for partnerships is 21, compared
to 9 for solo NEs. The last notable feature of table 10 is that the respondent’s gender matters
much less for time invested in partnerships.

22

Table 9: Hours Worked on the Startup, Solo NEs
Total
per Week
Percentile
All Men Women All Men Women
Average
1104 1568
797 8.8 10.6
7.6
Std. Deviation 1702 2183
1203 12.8 15.6
10.4
Percentiles
10
16
20
12 0.2
0.2
0.2
20
60 100
50 0.6
1.0
0.6
100 200
80 1.4
1.4
1.4
30
40
217 400
150 2.6
2.8
2.6
50
455 600
300 4.0
4.9
3.5
692 1000
500 5.8
7.2
5.7
60
70
1000 2000
800 9.2 11.5
8.1
80
2000 2080
1070 14.4 17.3
10.9
90
3000 4000
2080 24.9 29.3
23.1

Table 10: Total Hours Worked on Partnership Startups
Total
per Week
All Men Women All Men Women
Percentile
Average
2019 1989
2048 20.9 23.1
18.8
Std. Deviation 3634 3742
3537 40.4 51.6
24.8
Percentiles
10
80 100
80 0.8
0.7
0.8
20
160 190
150 1.8
2.1
1.7
30
260 358
210 3.1
3.2
3.1
500 540
400 5.4
5.1
6.6
40
50
800 800
800 9.2
9.4
9.2
60
1316 1275
1384 12.7 12.9
12.5
70
2000 2000
2003 19.2 19.6
19.2
80
3000 3072
2800 30.4 29.6
30.6
90
4450 4385
5000 51.3 50.4
51.7

23

Table 11: Monetary Investments of Solo Nascent Entrepreneurs
All
Men Women
Average
6695 7541
6144
Std. Deviation 15856 12087
17908
Percentiles
10
15
0
50
20
500
500
425
30
700 1000
600
40
1000 2000
1000
50
2000 3000
2000
3500 5000
3000
60
70
5000 6000
4000
80
8000 10000
5750
20000 20000
15000
90

5.2

Capital Investments

We now turn to the monetary investments. Adding a partner might be a way to obtain
easier or cheaper financing, thus alleviating financial constraints that would otherwise limit
the size of the business10 . Table 11, reports the averages, standard deviations, and percentiles
of these investments for solo NEs. Table 12 reports the corresponding numbers for all owners’
investments in partnership start-ups.
A comparison of these two tables reveals that the bottom of the distributions of monetary
investments for solo entrepreneurs and partners are very small and very similar to each other.
Starting from the 40th percentile, however, a gap opens up between these distributions, with
partners investing far more money in the business than solo NEs. The difference is about a
factor of four for the top two deciles in the distribution of business monetary investments.
These tables thus contain one striking pattern: Nascent Entrepreneurs with partners tend
to invest more of their own money than those operating alone.
These tables are also consistent with the previous evidence that women aspire to run
smaller businesses. The median female solo entrepreneurs investment equals about two
thirds of her male counterpart’s, and this ratio equals about three fifths for those NE’s with
partners. Of course, these distributions have very thick tails. This brings the averages far
above the medians, but more for women than for men. Thus, measuring the investment
difference between the sexes with averages makes it smaller.
10

See Basaluzzo (2004) for an in-depth analysis of partnership financing.

24

Table 12: Monetary Investments in Partnership Startups
All
Men Women
Average
33817 38567
29228
Std. Deviation 116976 126171 107575
Percentiles
10
0
0
0
20
200
300
31
30
1000
1400
550
40
2200
3000
1800
50
4000
5000
3200
7500 12000
5000
60
70
15000 20000
10000
80
30000 40000
20000
70000 100000
50000
90

5.3

External Finance

Financial markets are imperfect, but they do exist. The previous analysis has shown that
most NE engage in a good deal of saving to start off their new firms. What are the other
sources of funds that they can tap into?
Table 13 provides an overview of the sources of other start-up funds. For each broad
category of funding we report the fraction of NEs that report having asked for credit in
that given category, and the amount received, conditional to such amount being positive.
At this stage of business development the single largest source that our NEs tap into is the
informal loan market, which refers to spouses, friends, and employers. Interestingly, the
fraction of males and females asking for this sort of funding is quite similar: 42% and 46%,
but the females obtain much smaller amounts from informal sources: only $3,000 compared
to $14,000 for male NEs. Only one quarter of our male NEs have applied for formal business
loans, compared to an even lower 16% for the females. Conditional on obtaining such a loan,
the amounts are significant, and larger for females than males, that is $40,000 for females
and abot $32,000 for males. A large fraction of both males and females, around one-third
of our samples ask for a credit card loan to finance their start-ups, and those who obtain it
have a credit of about two to three thousand dollars from this source. Only a tiny fraction
takes out a second mortgage, but we do not know if they reduce their equity in their first
mortgage to finance the business. Overall, 65% of our NEs have asked for some source of
external funds, and the average amount among those that have received any such fund is
much larger for males: $13,000, than for females: $3,500.
Tables 14 and 15 disaggregate informal and formal sources of funds in more detail, and

25

Table 13: Sources of Funds
Sources
Informal Loans
Formal Business Loans
Credit Cards
Second Mortgage
Any Source

Males
Females
Fraction Amount Fraction Amount
42
14000
46
3000
25
32500
16
40000
28
3000
34
2000
5
15000
2
40000
65
13000
65
3500

“Fraction” is the share of the respondents that report having asked for funding. “Amount” is the median
amount expected, conditional on positive amounts.

also report the fraction of applicants that has been turned down in each source of funds. The
table on the informal sources of funds shows that the chance of receiving such a loan is far
from being one even conditional on asking. Spouses are more likely to accept to provide such
a loan (over 80% for NEs’s spouse). Family and friends accept such requests with about 70%
probability, while employers (of males NEs at least) are less likely to grant money for their
employees to start a new firm. The table also shows that in the majority of cases female
NEs receive smaller loans. This does not necessarily means that they face tighter financing
constraints, but could be related to the fact that they want to implement smaller businesses.
Table 15 disaggregates the formal sources of funds. Interestingly, not only a tiny fraction
of NEs has asked for a formal business loan by now, but the acceptance rate conditional on
asking is even smaller than for family and friends. Those that ask, and obtain one of these
loans, obtain amounts that are large compared to the ones obtained in the informal credit
market. These are likely to be the business that are more promising and more ambitious.
This table also shows that banks are by far the largest sources of funds, and that venture
capitalists provide large loans to only a negligible fraction of NEs in our sample.

6

What have you accomplished?

Given the survey design, all of our NEs have not had revenues to exceed costs for more than
three months, but table 16 shows that there is still a good deal of heterogeneity in their
stage of pre-market development. About 45% of our sample has a product or service that is
completed and ready for delivery and about 20% is at the prototype stage. Another 20% is
developing a model or procedure to sell, while 15% still has not done any work or does not
know at what stage they are at.
Only 12% of our nascent entrepreneurs are currently employing managers or employees

26

Table 14: Informal Sources of Funds
Sources
Spouse
Own
Partner’s
Family and Friends
Own
Partner’s
Employer

Applied

Males
Accepted

Applied

Females
Accepted

Amount

Amount

46
58

84
78

9000
20000

66
76

83
63

2000
5000

15
9
13

66
64
33

8000
8000
25000

12
5
5

73
75
75

3000
13000
40000

“Fraction” is the share of the respondents that report having applied for funding. “Amount” is the median
amount expected, conditional on positive amounts.

Table 15: Formal Sources of Funds
Sources

Males
Females
Applied Accepted Amount Applied Accepted Amount
Banks
14
53
41000
10
68
40000
SBA
5
33
30000
3
27
35000
Venture Capitalists
5
38
150000
2
29
60000
Personal Finance Co.
4
45
22500
1
67
8000
Others
8
48
13000
2
25
30000
“Fraction” is the share of the respondents that report having applied for funding. “Amount” is the median
amount expected, conditional on positive amounts.

Table 16: Stage of Product Development

Complete
Prototype
Development
Idea/No Work

All Males Females
45
42
48
21
22
17
20
21
19
15
14
16

27

in their business. Of this minority of employers, 30% have only one employee, 30% have two.
The largest employers, those at the 90th percentile of the employment distribution have 7
employees, so have fairly large business already.
The PSED also asks “How would you describe the location where this new business is
being developed? Is it a residence or personal property, like a home, garage, farm, or vacation
home; is it on the site of an existing business; is it a special location for this start-up, like
rented space, an incubator, or something like that; or is it not developed to the point where a
specific location is needed?” We compute the fractions of male and female NEs that already
have a special location for the start-up. We see this choice as a signal of a more ambitious
business plan, and potentially of a more capital-intensive business. Consistently with the
evidence that we have previously analyzed, we find that male NEs are more likely to already
have a special location for the start-up, with 27% of males having done so compared with
22% of the females.
The PSED also asks “Has the new business received any money, income, or fees from the
sale of goods and services?” In our sample, 41% of the male NEs have already received some
revenue from operating this business, compared to 47% of the female NEs. These fractions
are very similar to those having finished developing a product or service to sell.
Another interesting piece of information comes from the following question “Does the
monthly revenue now exceed the monthly expenses?”. The fraction of male and female NEs
answering yes are remarkably similar, with 36% of the male and 34% of the female NEs
responding yes, and is thus smaller than for the previous question, indicating that even after
starting to sell their product, most business still need some time to make enough to cover
their operating costs.

7

What remains to be done?

The PSED includes some very interesting and novel questions about NE’s perceptions of
how big the firm needs to be to become “self-sufficient” and to attract external financing.
The exact wording of these questions is “How much in total funds, loan and equity will
the new business need before it becomes self-sustaining - that is, before income is greater
than all monthly expenses, salaries, supplies or parts, inventory, interest, taxes, and other
expenses?” “Businesses usually require some money before they receive financial support
from the established community, such as bank loans or purchases of ownership or equity.
How much money do you think that the business will need before it can expect any funds
from the established financial community?”.
It is interesting to first look at the magnitude at of the responses of the NEs to these
questions and to then compute the ratio of the capital that is already in place in the nascent
28

business to these perceived capital needs to see how far along these business are along these
dimensions.
Ten percent of our NEs say that their business is already self-sustaining, while 23% do not
know how to answer this question. Regarding the second question, 5% of our sample already
has received such funds, while 23% do not know what is the threshold to receive financial
support from the established financial community. The small fraction of NEs already having
received funds from the established financial community is consistent with Table 15, which
shows a small fraction of our sample having already applied for such funds, and an even
smaller fraction having already received them. The large fraction of NE responding “Don’t
Know” to these questions simply reflects the fact that they are still in the process of starting
up a business and that there is a lot of uncertainty involved about it.
Table 17 displays the deciles of distributions for those male and female NEs that answer
each question with a dollar amount. The information from this table confirms our previous
findings that female NEs wish to implement smaller businesses, since both the self-sustaining
business size and minimal firm size needed for borrowing are uniformly smaller for female
NEs than for male NEs.
The distribution of business capitalization necessary for self-sufficiency shows 30% of the
male NEs aim at implementing businesses than are self-sustaining at or below a business size
of $10,000, while 40% of the female NEs are implementing a business with the same kind
of capitalization requirements. About 20% of our sample think that their business needs to
fairly well capitalized before it can generate enough revenue to be self-sustaining. This size
is $300,000 for male NEs and $175,000 for female NEs.
Among the respondents reporting a dollar amount for business money needed to attract
financial support, 30% of both male and female NEs do not think that they need any amount
of money to be able to receive financial support from the established financial community.
It is interesting that despite the fact that this 30% of NE think that they could have already
obtained such financing, most of them have not applied for it, and a large fraction of those
that have applied have been turned down for it (see Table 15). It would be interesting to
investigate this discrepancy more. One possible explanation could be that the respondents
have some personal collateral (such as a house or a car) that they think that they could use
directly to obtain credit for the business, but that does not necessarily needs to belong to
the business balance sheet.
For the rest of the distribution, the data confirm that female NEs expect to have to put
in less money to reach that point than male NEs. Some NE’s, however, do think that they
do need significant amounts of money to receive such kind of lending, with 30% of the male
NEs and 20% of the female NEs thinking that they need at least $25,000 to that goal. It
would be interesting to analyze more the balance sheets of these NEs and their perceived

29

Table 17: Distributions of Business Size Needed for Self-Sufficiency or for Borrowing

Percentile
10
20
30
40
50
60
70
80
90

Self-Sufficiency
Men
Women
1000
600
4500
2000
8500
5000
10000
6000
20000
10000
40000
25000
80000
40000
300000
175000
8.89e+07 8.89e+07

Borrowing
Men
Women
0
0
0
0
0
0
5000
100
10000
2000
15000
5000
25000
10000
50000
25000
500000 100000

Table 18: Distributions of the Ratios of Total Capital Invested to Business Size Needed for
Self-Sufficiency or for Borrowing

Percentile
10
20
30
40
50
60
70

Self-Sufficiency
Borrowing
Men Women Men Women
0.00
0.01
0.00
0.00
0.06
0.12
0.02
0.06
0.22
0.30
0.20
0.40
0.40
0.50
0.44
≥1
0.50
0.75
≥1
≥1
0.97
≥1
≥1
≥1
≥1
≥1
≥1
≥1

need for business capitalization to see if, for example, these answers are correlated to their
ability to collateralize other wealth in their balance sheet, and, more in general, what are
the observable determinants to these perceived need of business collateral.
A comparison of the distributions indicates that business size needed for self-sufficiency
is larger than business size needed to borrow from the established financial community.
This could indicate that in many cases the NEs believe that they can start formal kind of
borrowing before their business reaches its self-sustaining size.
Next, for each NEs that reports a dollar amount to capital invested and either business
self-sufficient size (or minimal business size needed for borrowing) we compute the ratio of
total capital invested in their business to each measure of required business size. For those
that report already having self-sufficient businesses, or already having borrowed from the
established financial community, we set this ratio at 1. Table 18 thus reports the distributions
30

of the capitalization ratios for female and male NEs for all of the respondent that do not say
“don’t know” to each pair of questions for which we compute a given ratio.
Analyzing these ratios we can see that 30% of the male NEs think that their business
is already large enough to be self-sustaining, compared to 40% of the female NEs. These
fractions are consistent with the ones for revenues that we have seen in the section “What
have you accomplished”.
In terms of borrowing, 50% of the male NEs believe that their firm is not yet big enough
to attract funding from the established financial community, compared with 40% of the
female NEs.

8

Conclusions

This paper analyzes interesting facts about new business start-up processes using a novel
data set. In order to be able to use these facts to better understand new entrepreneur’s
economic decisions, and to write down a model that is consistent with some key aspects of
the data, more work is needed.
We mentioned at the outset that choosing to be in an entrepreneur amounts to choosing
a production technology among a feasible set, under some financing constraints.
More work is needed to construct a good (and parsimonious) model of the various technologies, and to identify the possible technologies using observable variables.
More work is required to understand what kind of financing constraints entrepreneurs
face, and how these choices interact with preferences to determine the choice of a given
production technology, and hence entrance into self-employment, optimal investment and
continuation decisions.
For example, technologies that have the benefit of requiring little capital, little pre-market
time investment, and somewhat flexible labor input (such as a home daycare) might be little
hampered by borrowing constraints, and might be the preferred choice of some female NEs
with small children. On the other hand, the development of a new green technology might
require considerable capital and time investment before any benefit is seen from the project,
and it might be thus much more difficult to implement such a technology in presence of
financing constraints. Clearly, these two choices are very different, and should not lumped
together into the same model to be used for policy intervention. We see identifying observable, key, dimensions of technology choice and borrowing constraints as a fundamental
step to disentangle technology and constraints and to better set the stage for a more useful
understanding and modelling of entrepreneurship.

31

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