Journal of Business Venturing 21 (2006) 610 – 632

Entrepreneur opportunity costs and intended

venture growth
Gavin Cassar *
The Wharton School, University of Pennsylvania, Philadelphia, PA 19104, USA

Received 1 January 2004; received in revised form 1 January 2005; accepted 1 February 2005

Abstract

This study investigates how entrepreneur opportunity costs influence the intended future size of
new ventures. In particular, using a survey of nascent entrepreneurs in the process of starting a
venture, this paper examines how intended future sales revenue is influenced by entrepreneur current
household income, education, and managerial experience. Consistent with opportunity cost and
human capital arguments, it is found that individuals with higher current household income and
greater supervisory experience have higher levels of intended firm size in 5 years time. While this
study finds that entrepreneur stated preferences for growth also influence intended future sales of the
venture, the association between nascent entrepreneur opportunity costs and venture scale is
complementary to these stated preferences.
D 2005 Elsevier Inc. All rights reserved.

Keywords: Growth; Human capital; Nascent entrepreneurs; Opportunity costs; Start-ups

1. Executive summary

Only a small proportion of new ventures grow to become substantially large in terms of
revenues and employment. From an academic and policy perspective, there is an interest to
determine why some ventures become large, while others achieve little growth. This paper
investigates what determines the growth intention, in particular the scale of venturing
activity intended, of entrepreneurs.

* Tel.: +1 215 8982023.

E-mail address: cassar@wharton.upenn.edu.

0883-9026/$ - see front matter D 2005 Elsevier Inc. All rights reserved.
doi:10.1016/j.jbusvent.2005.02.011
 G. Cassar / Journal of Business Venturing 21 (2006) 610–632 611

I argue that an entrepreneur’s opportunity costs are a significant determinant of the

intended scale of venturing activity. Opportunity costs are the foregone benefit of the
next available alternative as a consequence of making a choice. In this paper’s setting,
opportunity costs represent the income that can be earned from paid employment rather
than through venturing activity. To investigate the relationship between opportunity costs
and intended scale of venturing, I utilize data from the Panel Study of Entrepreneurial
Dynamics (PSED). This data set provides a representative sample of intentions of
growth from nascent entrepreneurs, without survivorship or recall biases influencing
results.
Consistent with opportunity costs arguments, this paper finds that entrepreneurs with
high opportunity costs, such as individuals with high current household income and
managerial experience, intend on being involved in ventures with larger future sales
revenue. Interestingly, aside from managerial experience, the other proxies for human
capital were not significantly associated with the scale of venturing activity. The role of
household income, as a measure of opportunity costs, upon scale of venturing activity is
further highlighted by the insignificance of household income as a predictor of intended
venture size when considering employment size rather than sales size. Opportunity cost
arguments are more likely to explain variations in venture sales than employment due to
the stronger association between sales and future returns from venturing to the
entrepreneur.
Interestingly, household wealth generally does not have significant explanatory power
in predicting future venture size. The fact that wealth is not a significant predictor of
venturing scale even after excluding household income, suggests that the opportunity costs
of the entrepreneur rather than financial capital of the entrepreneur drives the intended
scale of venturing activity. An explanation for the non-significance of household wealth is
the relatively small up-front outlays associated with starting ventures, thereby reducing the
importance of entrepreneur financial capital.
The documented link between opportunity costs and intended scale of venturing
activity reported in this study complements the prior literature that has investigated the
choice between employed-work versus self-employment. The empirical evidence from this
employment choice research has generally been inconclusive. An explanation for the
mixed findings is that the variable of interest, self-employment, is represented in these
studies as a dichotomous variable. Thereby, such research fails to consider the variation in
the scale of venturing undertaken within the self-employment choice. By specifically
examining nascent entrepreneurs rather than a random sample of the population as
undertaken by dichotomous self-employment studies, this study can answer the research
question: Given a commitment to start a new firm, how do opportunity costs influence
intended firm size? The positive association between opportunity costs and size
expectations documented in this study provides an explanation of why previous research
investigating career choice decisions has produced mixed findings.
This study also finds that stated entrepreneurial preferences for growth also influences
intended future sales of the venture. However, the results from combining both
opportunity cost proxies of the entrepreneur with the stated preferences of the entrepreneur
in a joint model to explain intended scale of venturing suggest that opportunity costs are
complementary to entrepreneurial preferences, and that both provide separate explanatory
612 G. Cassar / Journal of Business Venturing 21 (2006) 610–632

power to predict venture scale choices of the entrepreneur. Overall, these findings suggest
that nascent entrepreneur opportunity costs are an important determinant of the scale of
intended venturing activity.

2. Introduction

It is estimated that 700,000 new ventures are started every year in the US alone (Acs
and Armington, 1998). Of these, only a small proportion grow to become substantially
large in terms of revenues and employment (Birch, 1987; Bhide, 2000; Acs and
Armington, 2003). Explanations for why some ventures become large, while others
achieve little growth are focused upon two broad areas of investigation. The first is the
intention for growth by the entrepreneur, and the second are the human, financial, and
social resources that enable growth to be achieved (Birley and Westhead, 1994; Cooper et
al., 1994). This paper investigates this first question: What determines the growth
intention, in particular the scale of venturing activity intended, of entrepreneurs?
This paper argues that an entrepreneur’s opportunity costs are a significant determinant
of the intended scale of venturing activity. Opportunity costs are the foregone benefit of
the next available alternative as a consequence of making a choice. In this paper’s setting,
opportunity costs represent the income that can be earned from paid employment rather
than through venturing activity. The application of opportunity costs is not novel in
entrepreneurial research, with researchers applying these arguments in investigations of
the choice between being employed and self-employment.
To investigate the relationship between opportunity costs and intended scale of
venturing, I utilize data from the Panel Study of Entrepreneurial Dynamics (PSED). The
main advantage of utilizing this data set is that a representative sample of intentions of
growth from entrepreneurs can be obtained, without survivorship or recall biases
influencing results. In addition, the PSED provides a wide range of demographic and
perceptual measures to enable a thorough investigation of how various factors influence
growth intentions.
Consistent with opportunity costs arguments, this paper finds that entrepreneurs with
high opportunity costs, such as entrepreneurs with high current household income and
managerial experience, intend on being involved in ventures with larger future sales
revenue. This result is robust to alternative definitions of sales but does not apply for future
employment size of the venture. While this study finds that entrepreneurial stated
preferences for growth also influences intended future sales of the venture, the association
between nascent entrepreneur opportunity costs and venture scale is complementary to
these stated preferences. Overall, these findings suggest that opportunity costs are an
important determinant of the scale of intended venturing activity.
The following section provides the main hypothesis and current empirical research that
has applied opportunity costs in an entrepreneurial setting. Section 3 details the sample,
selection criteria and variable definitions. The findings from how opportunity costs affect
intended scale are provided in Section 4. Section 5 reports the joint roles of opportunity
costs and stated preferences upon intended venture growth. The implications are discussed
in Section 6. Section 7 concludes.
 G. Cassar / Journal of Business Venturing 21 (2006) 610–632 613

3. Background

It is recognized that ventures are not started by chance, and that venturing activity and
creation can be characterized as a form of planned behavior (Ajzen, 1991). Within the
decision to undertake venturing, involves determining the type and nature of venturing
activity to be pursued. Underlying this process are the attitudes, subjective norms and
perceived behavioral controls of the entrepreneur that shape their intentions, such as
growth aspiration for the venture or scale of intended venturing (Ajzen, 1988).
Understanding these intentions are important as the aspirations for growth by
entrepreneurs play a crucial role in the actual growth achieved by ventures (Covin and
Slevin, 1991; Wiklund and Shepherd, 2003). Indeed, many ventures that are started do not
achieve substantial size and growth, simply because the entrepreneur does not intend their
venture to achieve substantial size and growth (Davidsson, 1989; Kolvereid, 1992).
Therefore, understanding why some entrepreneurs have a greater propensity for growth
willingness and intend to build large ventures, will provide valuable insight into why some
ventures grow large in scale and others do not.
The framework that this study utilizes to explain how intentions for scale and growth
differs between nascent entrepreneurs is based upon human capital. Every individual has a
different endowment of skill, ability and experience. Those attributes labeled bhuman
capitalQ describe the extent to which an individual has invested in their knowledge and can
subsequently apply such knowledge to tasks as required. Investments in human capital can
be made through accumulating knowledge both through experience and education. Human
capital may be either general or task specific in nature, in that some skills and learning may
be easily applied in many settings, and consequently transferable, such as education and
general work experience, while some human capital may be of a specialized nature which
can only be applied in specific settings, such as experience or technical skills within a
particular industry (Becker, 1964).
Human capital investments should improve an individual’s ability to perform tasks. For
example, in a venturing setting, general human capital such as education may provide
skills to understand the business environment, deal with stakeholders, make better or more
informed decisions, or allow the application of technical knowledge to operational or
business functions. However, it is also evident that such investments should also result in
individuals being able to apply such knowledge in non-venturing environments, such as in
paid employment. Thus, human capital not only allows individuals to achieve tasks in a
more productive or successful manner, but also provides a signal to the labor market as to
their increased ability to perform required tasks (Spence, 1973; Mincer, 1974). Given the
increased productivity, or increased potential to undertake tasks effectively, human capital
is valued by the labor market, resulting in individuals with high human capital being able
to earn greater income commensurate to their ability and investment in training.
Opportunity costs are the foregone benefit of the next available alternative. Different
human capital endowments result in every individual having different opportunity costs. In
the case of a nascent entrepreneur, opportunity costs represent the income that can be
earned from paid employment rather than through venturing activity. Additionally, it can
represent the benefits from all other potential venturing activity which would be forgone as
a result of undertaking a particular venture.
614 G. Cassar / Journal of Business Venturing 21 (2006) 610–632

It is posited that individuals choose an occupation or employment that maximizes the

present value of economic and psychic benefits over their lifetimes (Gimeno et al., 1997).
Whether or not to undertake a particular venturing opportunity or activity must be weighed
up against the benefits from alternative course of action (Shane and Venkataraman, 2000).
Individuals with relative high levels of human capital have better alternatives available to
them, and therefore are subject to higher opportunity costs. Consequently, the larger the
alternative compensation, the more attractive must be the expected reward associated with
venturing (Amit et al., 1995). Therefore, individuals who face high opportunity costs are
likely to pursue venturing activities with large returns that are commensurate with their
opportunity costs (Bhide, 2000).
In regard to the preference of scale or growth desired by the nascent entrepreneur,
it is not necessary that human capital influences the actual likelihood that the indi-
vidual succeed from venturing activity. While both general and specific human capital
related to venturing undertaken appears to provide the entrepreneur with a greater
ability to achieve success, the role of the entrepreneurs’ human capital in this setting
is that it allows the individual to achieve greater economic and psychic benefits from
alternative employment. Thereby individuals with greater human capital will require a
scale of venturing activity that is commensurate to the other alternatives available to
them.
Main hypothesis. That entrepreneur opportunity costs are positively associated with
intended scale venturing activity.
Examinations of scale and growth intentions have generally focused upon the
entrepreneur’s motivation for undertaking venturing, their attitudes towards growth and
perceived consequences associated with venture growth. While preferences for growth
have been the subject of several empirical investigations, there is little evidence to support
the influence of opportunity costs upon the scale of venturing activity (Davidsson, 1989;
Kolvereid, 1992; Birley and Westhead, 1994; Amit et al., 2000; Gundry and Welsch,
2001). This research highlights the importance of other, more intrinsic explanations for
intentions for growth, generally at the expense of economic explanations. For example,
Wiklund et al. (2003) investigating expected consequences of growth, suggest that non-
economic concerns are very important, and may be more important than expected financial
outcomes in determinants of entrepreneur attitudes toward growth. Therefore, this growth
intention research, while not investigating opportunity costs explicitly, suggests that given
these other influences, opportunity costs may not be a significant influence upon intended
scale of venturing activity.
Opportunity cost arguments, however, have been applied in investigations of the
choice between employed-work and self-employment, with mixed results. For example,
Evans and Leighton (1989) found that people moving from wage work to self-
employment were generally those with lower opportunity costs, in that they generally
received lower wages, and experienced relatively higher periods of unemployment. Amit
et al. (1995) also found empirical support that the lower the opportunity costs of
individuals, the more likely they are to undertake entrepreneurial activity. However,
Hamilton (2000) found that while people in self-employment have both lower initial
earnings and lower earnings growth, this is not caused by the selection of low-ability
 G. Cassar / Journal of Business Venturing 21 (2006) 610–632 615

employees into self-employment. In contrast, Robinson and Sexton (1994) and

Davidsson and Honig (2003) found education and work experience to be associated
with the choice of being self-employed. Kim et al. (2003) using the PSED found little
support for income or wealth influencing the decision to become an entrepreneur,
however they found several human capital variables such as education and full-time
work experience influencing this choice, suggesting individuals with greater human
capital are more likely to become nascent entrepreneurs and consequently self-employed.
An explanation for the ambiguity in findings in the employment choice literature is the
nature of the variable investigated. The dependent variable, self-employment is
represented in these studies as a dichotomous variable. Therefore, regardless of whether
an entrepreneur is involved in a $100 or $100 million annual sales venture, the
dichotomous representation is the same. This ambiguity is also recognized in the
arguments for how opportunity costs should affect self-employment choice, in that
individuals with relatively high human capital and consequently higher opportunity costs
have greater employment prospects, yet also should be more likely and able to undertake
more promising ventures (Bhide, 2000; Davidsson and Honig, 2003; Kim et al., 2003). As
a result, these conflicting forces make interpretation of opportunity cost influences upon
venturing choice difficult.
By specifically examining nascent entrepreneurs rather than a random sample of the
population as undertaken by self-employment studies, this study looks beyond how
opportunity costs influence the dichotomous choice between career-employment and self-
employment, to answer the following question: Given a commitment to start a new firm,
how do opportunity costs influence intended firm size? Therefore by avoiding the
ambiguity associated with opportunity costs upon employment choice, this study provides
a cleaner test of the influence of opportunity costs upon venture initiation choice through
the investigation of the intended growth of the venture.
There has also been research that has investigated how entrepreneur human capital
influences the actual size and growth of ventures.1 The majority of evidence from this
research suggests that entrepreneur human capital is positively associated with both actual
scale and growth (Cooper et al., 1989, 1994; Cressy, 1996). However, it is recognized that
observed venture size and growth are a function of both the aspiration of the entrepreneur
to achieve growth and the ability of the entrepreneur to achieve growth (Wiklund and
Shepherd, 2003). These studies, by investigating actual size and growth determinants, are
implicitly testing two unique constructs of aspiration and ability jointly. By investigating
nascent entrepreneurs in the process of undertaking venturing, the intention for growth or
venture selection can be clearly ascertained from the factors which allow intentions for

1
The author is aware of one published manuscript that has investigated explanations for the intended scale of
venturing. Delmar and Davidsson (1999) modeled firm employee size and growth expectations, upon several
facets including human capital, personal and business goals, environmental and business contexts and gestation
activities. Due to limited initial size and growth intentions within their sample, the dichotomous dependent
variables from the study were based upon whether the venture: (1) intended to start with one or more than one
employees; and (2) intended to grow by one or more than one employees over the next 5 years. As a consequence
of the limited variation in intended size and growth, the explanatory ability of the models predicting size and
growth intentions was relatively low.
616 G. Cassar / Journal of Business Venturing 21 (2006) 610–632

growth to be achieved (Bruderl et al., 1992). Thereby this study can investigate intended
scale and growth separately from how entrepreneur human capital influences the
performance of new ventures.

4. Method

4.1. Sample

To examine how opportunity costs influence venture growth intentions of entrepre-

neurs, I utilize data from the Panel Study of Entrepreneurial Dynamics (PSED). The
primary feature of this data set is that it obtains responses from nascent entrepreneurs that
are concurrently in the process of starting new ventures. Therefore, research utilizing this
data set overcomes issues associated with survivorship biases associated with analyzing
entrepreneurs who have already established business. Investigating existing business
owners fails to represent the proportion of entrepreneurs who consider not continuing the
venturing process or entrepreneurs in ventures that subsequently failed. In addition,
surveying entrepreneurs while in the venturing process overcomes the potential for recall
biases influencing the study findings. The likelihood of survivorship and recall biases
affecting study findings increases as the temporal period between venturing activity and
surveying becomes greater.
The nascent entrepreneurs were identified through random digit dialing methodology,
with over 30,000 adults surveyed. The sample frame included individuals 18 years of age or
older throughout the United States, with the initial surveys being undertaken in several
waves during 1998 to 1999. Specifically, to be classified as a nascent entrepreneur and
included in this study a respondent had to answer byesQ and then bnoQ to the following
questions: (1) Are you, along or with others, now trying to start a new business?; (2) Are
you, along or with others, now starting a new business or new venture for your employer?
An effort that is a part of your job assignment? In addition, the respondent had to exhibit the
following three characteristics: (1) they expect to have at least some ownership in the new
firm; (2) they had to be actively trying to start the new firm in the past 12 months; and (3) the
venture they are currently involved in is still in the start-up phase and is not an infant firm.
From the screening surveys, a sample of 1494 nascent entrepreneurs was eligible for
further phone interviews, of which by the time subsequent contact was made, 932 nascent
entrepreneurs were eligible. Six hundred sixty-nine nascent entrepreneurs completed the
detailed phone interview, and a further sub-set of 482 nascent entrepreneurs completed a
detailed mail questionnaire. While the PSED also follows these entrepreneurs longitudi-
nally for several years, for the purposes of this study, only responses from Wave 1 is
required for the empirical investigation, with most of the analyses relying upon the
information in the detailed phone interview.2
The descriptive statistics report the results from all nascent entrepreneurs which
undertook the detailed phone interview. However, given the varying requirements for each

2
For a detailed description of the PSED, its features, and sampling procedures see Reynolds (2000).
 G. Cassar / Journal of Business Venturing 21 (2006) 610–632 617

empirical analysis, the number of observations available for analysis does vary across the
alternative specifications.3 For the base regression (with industry and location variables),
the number of nascent entrepreneur observations was 500 (490). Given the sampling
procedure, the PSED deliberately over-samples some of the entrepreneurs undertaking
venturing activity, such as females and minorities. Therefore, reflective of the sampling
procedure, all statistical analyses were undertaken using weighted analyses.

4.2. Independent variables

Previous research, when investigating opportunity costs, has generally relied upon
proxies of income earning potential alone. Due to the broad surveying of entrepreneurs in
the PSED, this study is able to utilize both actual income and proxies of income earning
potential. This study’s primary measure of opportunity costs is household income
(HHIncome). Income should be associated with intended venture scale, as it provides a
representation of the remunerative status of the individual in the market for labor, and
therefore the potential opportunity costs the individual is exposed to should they choose
venturing over career employment.
The use of household data is advantageous with regard to investigations of the impact
of financial resources, as financial capital at the household level can be utilized for
venturing activity. One disadvantage of using household level data is that the income
measure may be capturing other household members’ earnings potential. This creates
noise in the income measure and may bias subsequent tests against finding significant
income influences upon intended venture scale.4 For household income, all values are
log10 transformed, with all income values $1 and below coded as 0.
For both household income and other financial measures I utilize the adjusted financial
capital data developed by Kim et al. (2004). Under their approach they apply a series of
decision rules to enable a larger proportion of respondents having income and net wealth
data available for analysis. These decision rules involve relying initially on the most
reliable financial data available, such as sum of individual components of personal assets
and liabilities, then on the next most reliable, such as a single value of personal wealth or
midpoints from a range of personal wealth, and so forth, until an income and wealth value
is achieved.

3
For example, information concerning career motivations in the mail survey was completed by substantially
fewer nascent entrepreneurs than those furnishing growth intention information in the detailed phone interview,
resulting in a smaller number of observations for empirical models that include career motivations.
4
Unfortunately, information relating to individual wage income is not available from the PSED. The use of
household rather than individual income as a measure of individual opportunity costs, all things being equal,
should result in a coefficient for household income being larger and more significant for males than females.
Given that in the United States, males are more likely to work than females, and males are more highly
compensated for work, the HHIncome variable will more likely capture male opportunity costs rather than female
opportunity costs in each household. In unreported results, when portioning the sample by gender, the coefficient
on HHIncome is positive for both males and females, however, the HHIncome coefficient is larger in magnitude
and stronger in statistical significance for males. This is consistent with the conjectured bias caused by the use of
household income rather than individual wage income as a measure of entrepreneurial opportunity costs.
618 G. Cassar / Journal of Business Venturing 21 (2006) 610–632

Two measures which have been used in previous research to represent human capital
are experience and education (Evans and Leighton, 1989; Amit et al., 1995; Birley and
Westhead, 1994; Blanchflower and Oswald, 1998; Hamilton, 2000). Greater managerial
experience should be associated with greater human capital, resulting in the
entrepreneur being exposed to higher opportunity costs when making a venture
creation choice. The managerial experience variable (Managerial Exp) is obtained from
the response to bFor how many years, if any, did you have managerial, supervisory, or
administrative responsibilities?Q I use managerial experience rather than number of
years work experience generally or in a specific field, as this measure is more likely to
capture earnings potential due to the highly skilled nature of work, and the incentives
associated with choosing larger scaled venture activity (Bhide, p. 93, 2000).5
Education is operationalized by a series of dummy variables denoting the highest level
of educational attainment of the entrepreneur, being: (1) up to high school; (2) technical/
vocational; (3) some college including associates degree; (4) bachelors degree; and (5)
post college. These categorizations are applied to be consistent with previous research
using the PSED (Kim et al., 2003). In addition to the categorical dummy representation of
education, an ordinal measure of education is also used in the study to facilitate correlation
analyses. This measure (Education) simply takes the value of d1T for up to high school
education and so forth up to d5T for post college education.

4.3. Control variables

I included several control variables for the prediction of intended future venture size.
While the opportunity cost proxies above should capture the effects of earnings potential
more directly than these measures, the inclusion of these variables should capture
systematic effects beyond the opportunity costs, thereby reducing potential omitted
variable bias. The control variables utilized in the analyses relate to the household wealth,
age, gender and ethnicity of the entrepreneur.
Bhide (2000, p. 93) argues that individuals born into extreme wealth or who have
become extremely wealthy will tend to try something that is large enough to make a
difference to their wealth. Additionally, greater wealth means greater financial resources
which allows entrepreneurs to undertake larger-scale venturing before using outside
sources of funding, thereby overcoming liquidity constraints. Including household wealth
in conjunction with household income allows distinction between the capacity of the
entrepreneur to create wealth and actual financial capital available to the entrepreneur. For
the wealth variable (HHWealth), all entrepreneurs with reported net wealth of less than $1
were coded as having $1 wealth. This was done to abstract away from negative values of

5
The spearman correlation between managerial experience (Managerial Exp) and general work experience
(Work Exp) is r = 0.63. As shown below I also include a measure of entrepreneur age, which should capture more
general experience influences and preferences (Hamilton, 2000). The Spearman correlation between general work
experience (Work Exp) and the age of the entrepreneur (Age) is r = 0.75, suggesting that including all three
measures in a model would lead to problems with multicollinearity. Such concerns were confirmed in a full model
examining the condition index and variance inflation factors when all three variables were included.
Consequently, general work experience is excluded from the empirical analysis.
 G. Cassar / Journal of Business Venturing 21 (2006) 610–632 619

wealth influencing the study findings. Therefore, this measure treats entrepreneurs with
negative net wealth as if they had no net wealth.6 This household wealth value was then
log-transformed.
Age of the entrepreneur is represented by a continuous variable (Age). Entrepreneur
age should capture the varying growth preferences associated with age, while holding
human capital effects aside, due to the other human capital variables represented in the
modeling of intention of venture scale. The gender of the entrepreneur is represented by a
dichotomous variable (Female), which takes the value 0 if the entrepreneur is male, and 1
if the entrepreneur is female. Several researchers have shown that venture size and growth
differs due to gender, with females generally being involved in lower, smaller scaled
ventures. Differences in scale related to gender may be caused by different motivations
towards starting ventures, perceived difficulties in assembling resources, or different
maximum sized thresholds for ventures (Cooper et al., 1989; Cliff, 1998; Carter et al.,
2003). Finally, for this study the ethnicity of the entrepreneur is represented by a series of
dummy variables denoting: White, Black, Latino, and Other.

4.4. Dependent variable—intended future firm sales

Sales are the primary measure used as a proxy of venture size intentions. While
the PSED allow an examination of employment size, I focus upon sales as the
opportunity costs arguments, which are associated with returns from venturing such as
from income and profits, should be more reflected in sales size rather than
employment size.7 In particular, this study’s measure of intended future firm size is obtained
from the response to the question, bWhat would you expect the total sales, revenues, or fees to
be in the fifth year of operation?Q While the PSED allows investigation of 1 or 5 years
intended sales, I focus upon 5 years for two reasons. Firstly, the early revenues from the
ventures, such as in the first year, may not be reflective of intended future size of the venture,
with in many cases very little revenues being received in the initial stages on operations.
Secondly, using fifth year revenues abstracts from potential variation in growth in the very
early stages of the venture, which may be a function of industry, speed of gestation and
venture strategy. Therefore, whether a venture is intended to start large and maintain relatively
low levels of growth, or start relatively small with high growth in the early stages, is not
captured by this size measure.
All responses that had missing sales or predicted zero sales in the fifth year of operation
were excluded. Given the raw form of the intended size variable was significantly skewed,
the intended size measure was log-transformed to make it suitable for parametric analysis.

6
An alternative approach for dealing with negative wealth values is that adopted by Kim et al. (2003). This
involves transforming the raw wealth variable into a positive integer by adding all values by the most negative
wealth variable plus one, and then log-transforming this alternative wealth variable (KAKWealth). The findings
under both wealth approaches result in the same inferences, and are consequently not reported.
7
A superior measure to examine economic preferences of the entrepreneur is the expected returns from the
intended venturing to be undertaken. Unfortunately, information related to intended returns, profits, drawings and
their timeliness is not available from the PSED. However, future research should consider measures such as
expected returns when investigating economic motives for venturing activity.
620 G. Cassar / Journal of Business Venturing 21 (2006) 610–632

A summary of all the dependent and explanatory variables applied in this study is
presented in Appendix A.

5. Intended scale and opportunity costs results

5.1. Descriptive statistics

Table 1 provides the descriptive statistics of the variables utilized in the analysis. All the
dependent variables in their raw forms are substantially positively skewed, with the log-

Table 1
Descriptive statistics
Mean Standard Minimum 25% Median 75% Maximum
deviation
Panel A: Dependent variables
Raw
Intended firm size (US$) 1,390,056 6,858,049 1 40,000 100,000 400,000 80,000,000
Intended firm size 623,525 2,766,311 0.1 25,000 70,000 250,000 40,800,000
owned (US$)
Intended employment 20 111 1 2 5 11 2000
Logged
Intended firm size 5.06 0.95 0.00 4.60 5.00 5.60 7.90
Intended firm size owned 4.89 0.92 1.00 4.40 4.85 5.40 7.61
Intended employment 0.72 0.57 0.00 0.30 0.70 1.04 3.30

Panel B: Continuous independent variables

Raw
HHIncome (US$) 59,369 82,751 1 30,000 45,000 70,000 1,800,000
HHWealth (US$) 225,408 718,056 1 17,000 70,000 180,000 13,270,000
KAKWealth (US$) 600,759 719,139 1 395,001 448,001 558,001 13,648,001
Managerial experience 8.69 8.55 0 2 6 13 53
Age 40.41 11.21 18 32 40 49 74
Logged
HHIncome 4.63 0.41 0.00 4.48 4.65 4.85 6.26
HHWealth 4.39 1.61 0.00 4.23 4.85 5.26 7.12
KAKWealth 5.70 0.29 0.00 5.60 5.65 5.75 7.14

Panel C: Categorical independent variables

Education Gender
Up to high school 17.3% Male 49.2%
Technical/vocational 5.6% Female 50.8%
Some college 36.3% Growth intention
College degree 24.6% Large as possible 21.0%
Post college 16.2% Manageable 79.0%
Ethnicity Risk–return preference
White 64.1% Low risk–return 82.4%
Black 26.5% High risk–return 17.6%
Latino 6.6%
Other 2.8%
 G. Cassar / Journal of Business Venturing 21 (2006) 610–632 621

transformation assisting in reducing the degree of skewness. The mean and median
intended future revenue in the fifth year of operation was $1,390,056 and $100,000 USD,
respectively. Table 1 also shows that raw household income, and especially household
wealth is positively skewed, with the mean (median) household income being $59,369
USD ($45,000), while the mean (median) household net wealth is $225,408 USD
($70,000). Table 2 reports the correlations between the independent variables used in the
study. The main points of interest from this table are the expected strong positive
correlation between income and wealth, and the positive correlations between the
experience and age measures.

5.2. Main results

Table 3 provides the main regression findings for the relationship between
opportunity costs and intended venture size. The coefficient of household income
is .408 (t = 3.25, p = .001), which suggests that doubling current household income
increases the intended future revenues of the venture by 39%. This is consistent with
the main hypothesis that opportunity costs influence intended venture size. In
contrast, the coefficient of household wealth (HHWealth) is relatively small and
insignificant, suggesting that financial capital does not appear to influence intended
venture size.
Of the several variables previously used to proxy income earning potential and human
capital (Amit et al., 1995; Hamilton, 2000), it appears that managerial experience is
positively related to intended size, with each year’s worth of experience being associated
with an increase in future venture revenues of 6.4%. Entrepreneur age appears to be
negatively related to venture size, while females are significantly more likely to have lower
intended firm revenues than males (h =  0.332, t = 3.84, p = .000). Overall, the positive
significant coefficients on household income and managerial experience are consistent
with the main hypothesis that entrepreneurial opportunity costs are positively related to
intended venture scale.8 Interestingly, the models do not support education influencing
intended venture size, even excluding household income effects, with negative rather than
positive coefficients as predicted.
Notably, the above regression does not control for potential industry and geographical
influences. For example, industry effects may influence intended venture size due to
variations in viable or efficient scale of ventures across different industries (Bates, 1995;

8
Given the continuous nature of the dependent variable, the main regression can determine the degree to which
opportunity costs influence future intended venture sales. However, an alternative question to ask is, how do
opportunity costs affect the likelihood of intending to create a substantially large venture? To address this
alternative question, I transformed the dependent variable into a dichotomous measure, which takes the value b1Q
if the intended future sales in five years time is greater than a particular threshold and b0Q otherwise. The
thresholds examined were one, two, and five million dollars respectively. Overall, the results from the logistic
regression model are consistent with the main findings and consequently are not reported. This suggests that the
continuous measure of intended scale captures not only the variation across the whole sample in predicting future
venture size, but also is able to identify those nascent entrepreneurs that intend to be involved in the small
proportion of firms that intend to achieve high growth in sales.
 622
Table 2
Pearson and Spearman correlations between independent variables
1 2 3 4 5 6 7 8 9 10

G. Cassar / Journal of Business Venturing 21 (2006) 610–632

(1) Intended firm size – 0.152 0.061 0.250 0.117 0.061 0.011 0.236 0.197 0.256
(0.000) (0.153) (0.000) (0.005) (0.155) (0.800) (0.000) (0.000) (0.000)
(2) HHIncome 0.212 – 0.282 0.089 0.111 0.042 0.232 0.043 0.048 0.064
(0.000) (0.000) (0.024) (0.004) (0.285) (0.000) (0.265) (0.219) (0.161)
(3) HHWealth 0.163 0.488 – 0.162 0.188 0.173 0.069 0.001 0.003 0.003
(0.000) (0.000) (0.000) (0.000) (0.000) (0.072) (0.720) (0.418) (0.951)
(4) Managerial Exp 0.219 0.209 0.261 – 0.614 0.580 0.239 0.010 0.043 0.059
(0.000) (0.000) (0.000) (0.000) (0.000) (0.000) (0.009) (0.257) (0.199)
(5) Work Exp 0.096 0.169 0.253 0.591 – 0.776 0.129 0.134 0.077 0.005
(0.022) (0.000) (0.000) (0.000) (0.000) (0.001) (0.000) (0.043) (0.910)
(6) Age 0.043 0.121 0.289 0.496 0.734 – 0.192 0.017 0.069 0.045
(0.316) (0.002) (0.000) (0.000) (0.000) (0.000) (0.657) (0.075) (0.329)
(7) Education 0.030 0.288 0.197 0.246 0.120 0.167 – 0.033 0.053 0.175
(0.473) (0.000) (0.000) (0.000) (0.002) (0.000) (0.378) (0.665) (0.000)
(8) Female 0.303 0.002 0.065 0.040 0.074 0.071 0.039 – 0.098 0.228
(0.000) (0.962) (0.090) (0.289) (0.051) (0.064) (0.303) (0.010) (0.000)
(9) Preference for 0.218 0.066  0.039 0.087 0.096 0.087  0.073 0.107 – 0.168
unconstrained growth (0.000) (0.090) (0.311) (0.024) (0.012) (0.025) (0.055) (0.005) (0.000)
(10) High risk–return 0.259 0.026 0.043 0.058 0.022 0.058 0.151 0.232 0.198 –
preference (0.000) (0.570) (0.350) (0.208) (0.619) (0.208) (0.001) (0.000) (0.000)
Pearson weighted correlations are displayed in the top right, Spearman correlations are displayed in the bottom left.
p-values associated with the correlations are in parenthesis.
Correlations reported use the full sample of nascent entrepreneurs from the PSED; cell sizes differ due to non-responses.
 G. Cassar / Journal of Business Venturing 21 (2006) 610–632 623

Table 3
Results of regression model predicting intended future venture revenue size
Without industry/location controls With industry/location controls
Coefficient jt-valuej Coefficient jt-valuej
HHIncome 0.408** 3.25 0.454*** 3.37
HHWealth 0.002 0.08 0.038 1.27
Managerial Exp 0.027*** 4.50 0.030*** 4.54
Age 0.005 1.03 0.006 1.18
Education
Technical/vocational 0.168 0.80 0.069 0.31
Some college 0.189 1.47 0.071 0.50
College degree 0.099 0.74 0.011 0.07
Post college 0.369* 2.38 0.311 1.75
Ethnicity
Black 0.144 1.27 0.147 1.19
Latino 0.115 0.65 0.029 0.16
Other 0.386 1.66 0.691** 2.72
Female 0.332*** 3.84 0.178 1.84
Constant 3.367*** 5.56 3.393*** 3.40
Industry controls No Yes
Location controls No Yes
N 500 490
R2 0.123 0.260
Adjusted R 2 0.102 0.132
F-statistic 5.70*** 2.03***
Reference categories: Education (up to high school); Ethnicity (White).
* Significant at 0.05.
** Significant at 0.01.
*** Significant at 0.001.

Mata and Machado, 1996). Further, location may need to be controlled for due to
geographic clustering of industries or differences in venturing activity across location.
When including these controls the research question of interest can be described as
follows: given the initial choice of a particular industry and geographic location, are
entrepreneur opportunity costs positively associated with intended scale of venturing
activity. However, there are also arguments against the inclusion of industry and
geographical controls. If entrepreneurs are able to choose different industries or locations
to start their venture, these industry choices may be a function of intended scale, rather
than the other causal direction. For example, an individual may choose the scale of
venturing, the expected returns or profits, and then choose the industry or location of the
venture to achieve the returns required. Entrepreneurs in many cases have flexibility as to
what industry and location they operate their venture, which is a function of several factors
including their human capital and the human capital required for each particular venture.
Therefore industry and location may also be capturing part of the venture scale choice
of the entrepreneur. In summary, there is a trade-off between not controlling for
industry/geographic differences which may mask the scale-return relationship and
controlling for these effects which may mask entrepreneur preferences regarding venture
scale.
624 G. Cassar / Journal of Business Venturing 21 (2006) 610–632

To examine the influence of industry and geographic influences upon the study
findings, included in the right columns of Table 3 is an additional model with both
geographical and industry controls. For industry controls, the model includes 52 two-
digit SIC code dummies representing each unique industry in the sample. For
geographical controls, the model includes dummy variables for the nine US census
regions. Examining the coefficients of the model with industry and geographical
controls, the coefficients for both household income and managerial experience are
very similar to the model without these controls, with the coefficient of household
income being .454 (t = 3.37, p = .001). Therefore the results with industry and
geographical controls included are consistent with the opportunity costs being
positively related to intended venture size.

5.3. Robustness of main findings

This subsection reports different robustness examinations of the main findings. These
tests relate to interactions with intended ownership and intended size, and the use of
employment rather than sales as a measure of size.
Firstly, the dependent variable in its original form asks specifically about the ventures
intended revenues, which I apply as a proxy for the intended firm size of the entrepreneur.
However, this variable fails to consider the individual potential claims that the
entrepreneur has upon these revenues and subsequent profits. For example, holding
venture size constant, there is a substantial difference between being a 100% owner or a
5% owner of a venture. Therefore this variation may lead to different inferences than using
the original measure. To address this, I calculated an adjusted intended size measure for
entrepreneur i, as follows:

Intended Venture Size Ownedi ¼Log 10 ðIntended Salesi  Intended % Ownedi Þ:

ð1Þ

Therefore this adjusted measure is the expected fifth year sales multiplied by the
percentage of the firm that the entrepreneur personally expects to own five years after the
firm begins operations. Thereby this measure captures the future sales revenues and
subsequent profits which the entrepreneur intends to have claims to, as a result of the
venturing activity. Again, this measure is logged transformed to allow for parametric
analysis.
As shown in Table 4, the results from using this adjusted intended ownership
measure is similar to the original results, with household income and managerial
experience being positively related to future sales the entrepreneur intends to have
claims to. Again, all the education dummy variables are negative, with post college
education attainment having significantly lower revenue expectations than entrepre-
neurs with up to a high school education, once controlling for current household
income and other demographic variables. Therefore, it can be concluded that
whether concerned with future sales or the proportion of future sales intended to be
 G. Cassar / Journal of Business Venturing 21 (2006) 610–632 625

Table 4
Robustness results of regressions predicting intended future venture size
Intended future sales*intended ownership Intended employment size
Coefficient jt-valuej Coefficient jt-valuej
HHIncome 0.314* 2.49 0.045 0.06
HHWealth 0.002 0.17 0.005 0.02
Managerial Exp 0.027*** 4.42 0.011* 2.46
Age 0.005 1.11 0.006 1.77
Education
Technical/vocational 0.164 0.78 0.213 1.42
Some college 0.172 1.33 0.069 0.72
College degree 0.131 0.97 0.113 1.16
Post college 0.387* 2.49 0.115 1.07
Ethnicity
Black 0.115 1.00 0.268*** 3.41
Latino 0.139 0.78 0.305* 2.43
Other 0.393 1.70 0.060 0.44
Female 0.269** 3.08 0.116 1.79
Constant 3.632*** 5.97 0.664 1.80
N 488 322
R2 0.103 0.105
Adjusted R 2 0.081 0.070
F-statistic 4.56*** 3.02***
Reference categories: Education (up to high school); Ethnicity (White).
* Significant at 0.05.
** Significant at 0.01.
*** Significant at 0.001.

owned by the entrepreneur, opportunity costs are positively related to intended firm
size.
As a second robustness test, I examined the effect of using intended employment size
rather than sales size. Aside from robustness, one benefit from examining employment is
the major focus of government policy upon employment, in particular from new
ventures. The results from the intended employment analysis are presented in the right-
most column of Table 4. Interestingly, the model does not support the view that
household income is related to intended employment size, with the coefficient of 0.045
(t = 0.63, p = .532) being insignificant at conventional levels. This suggests that the
explanations for intended size and employment utilizing entrepreneur characteristics are
quite different, even given the strong positive correlation between the two size measures
(r = .49, p =.000).
An explanation for the difference in findings between intended sales and
employment is that the opportunity cost arguments specifically relate to economic
incentives that are most likely best represented through sales to due its more direct
relationship to profits and returns, than employment. Sales less expenses represent the
net income of the venture, which may be retained and used to finance existing or
further investment. Alternatively, the net income can be drawn out by the entrepreneur
for personal use. Further, current sales and income are important inputs to forecast
626 G. Cassar / Journal of Business Venturing 21 (2006) 610–632

future income and returns of existing ventures. The nexus between employment size of
the venture and the future returns for the entrepreneur or venture valuation is far more
ambiguous.
Another reason for the inconclusiveness of the influence of opportunity costs on
intended employment size is due to variations in business models and the organization
of labor within ventures. For example, two ventures in the same industry and with the
same revenues might be very different in terms of employee size, because one may
subcontract large parts of its activities, whereas the other might be vertically
integrated. Therefore, variation in the extent of activities undertaken by the firm
may mask or artificially create considerable differences in the financial indicators of
venture scale. Regardless, the results from this study do suggest that when making
inferences about future venture size, what size measure is applied may significantly
alter the inferences made.

6. Intended growth, stated preferences and opportunity costs results

Many of the findings from this study may be caused specifically by the stated
preferences of the entrepreneur for the venture. There is potential for the preferences
of the nascent entrepreneur to be spuriously causing the association between
opportunity costs and intended venture growth given the linkages between
entrepreneurs, their capital endowments, their preferences and intentions. For example,
large intended future sales may be associated with a greater willingness to grow the
venture as large as possible rather than keep the firm within a manageable and
controllable size. Further, risk–return preferences of nascent entrepreneurs and career
reasons as to why nascent entrepreneurs undertake business venturing, could influence
stated intended scale of the nascent entrepreneur. For example, entrepreneurs with
higher opportunity costs, may generally have lower risk aversion, resulting in larger
scaled venturing, all else being equal. Therefore whether the previous findings
observed are caused by systematic differences in stated preferences or a function of
entrepreneur opportunity costs is unclear.
To investigate the role of preferences upon the main findings I combined the
previous opportunity cost and human capital proxies of the entrepreneur with the stated
preferences of the entrepreneur in a joint model to explain intended venture size, which
I label as the bkitchen sinkQ regression. Including all these variables into one model
reduces potential omitted variable biases, however, it does potentially expose the results
to issues of simultaneity. For growth willingness the PSED provides a categorical
measure that asked bWhich 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?Q, which I coded as b1Q for large as
possible and b0Q respectively. To determine risk–return preference, I utilized the
response to the following PSED question: bAssuming you are the sole owner, which
situation would you prefer? 1) A business that would provide a good living, but with
little risk of failure, and little likelihood of making you a millionaire, or 2) A business
that was much more likely to make you a millionaire but had a much higher chance of
 G. Cassar / Journal of Business Venturing 21 (2006) 610–632 627

going bankruptQ, which I coded respectively as b0Q and b1Q for high risk–return
preference.
For career reasons, in particular the importance of financial success, I adopted
the same financial success factor as developed by Carter et al. (2003). This factor
was developed from eighteen item responses, each on a five-point likert scale, to
the question: bTo what extent are the following reasons important to you in
establishing this new business?Q The financial success factor is one of six empirical
career reasons determined. I adopt the financial success factor as previous research
suggests it is positively associated with intended growth intentions (Davidsson,
1989).
The results of the kitchen sink model as presented in Table 5 show that growth
willingness, high risk–return preference, and importance placed upon financial success
are all positively associated with intended future sales of the firm. While the
preferences of the entrepreneur do significantly influence the intended future sales of
the venture, consistent with all the findings presented throughout the paper, household
income and managerial experience are still significantly positively related to the
intended growth of the venture. This suggests that opportunity costs are comple-
mentary to entrepreneurial preferences, and that both provide separate explanatory
power to predict venture scale choices of the entrepreneur. Overall, these future size
preferences suggest that while entrepreneurs with high opportunity costs generally

Table 5
bKitchen sinkQ regression model predicting intended future venture size
Coefficient jt-valuej p-value
HHIncome 0.381 3.42 0.0003
HHWealth 0.025 1.05 0.6393
Managerial Exp 0.028 5.04 0.0000
Age 0.002 0.48 0.3409
Education
Technical/vocational 0.179 0.87 0.3416
Some college 0.105 0.89 0.3208
College degree 0.018 0.14 0.9664
Post college 0.031 0.22 0.6412
Ethnicity
Black 0.030 0.26 0.8687
Latino 0.252 1.44 0.1682
Other 0.127 0.43 0.5701
Female 0.260 3.20 0.0007
Preference for unconstrained growth 0.244 2.37 0.0494
High risk–return preference 0.339 3.33 0.0082
Motivation score for financial success 0.092 2.01 0.0167
Constant 2.920 5.04 0.0000
N 353 R2 0.270
F-statistic 8.29* Adjusted R 2 0.237
Reference categories: Education (up to high school); Ethnicity (White).
* Significant at 0.001.
628 G. Cassar / Journal of Business Venturing 21 (2006) 610–632

intend on having larger firms, this is not attributable to stated attitudes to growth,
risk preferences or underlying motivations of nascent entrepreneurs for starting a
venture.

7. Discussion

This study provides empirical evidence of how intentions of venture scale vary
systematically by the favorability of the alternative opportunities available to the
entrepreneur. Utilizing the PSED dataset, this study was able to apply both actual
household income and proxies for income earning potential, for measures of
entrepreneur opportunity costs. The primary results, when using household income,
are consistent with hypothesized arguments for opportunity costs influencing intended
venturing scale. Interestingly, aside from managerial experience, the other proxies for
income earning potential were not significantly associated with the scale of venturing
activity. The non-significance of other explanatory variables occurred both when
including and (in unreported results) excluding household income in the explanatory
model. The role of household income, as a measure of opportunity costs, and scale of
venturing activity is further highlighted by the insignificance of household income as
a predictor of intended venture size when considering employment size rather than
sales size. Opportunity cost arguments are more likely to explain variations in venture
sales than employment, as a result of the stronger association between sales and future
returns from venturing to the entrepreneur.
The documented link between opportunity costs and intended scale of venturing
activity reported in this study complements the prior literature that has investigated
the choice between employed-work versus self-employment. The empirical evidence
from the employment choice literature has generally been inconclusive. An
explanation for the mixed findings is due to greater entrepreneurial human capital
generally being associated with greater opportunity costs and greater venturing
opportunities. By specifically examining nascent entrepreneurs rather than a random
sample of the population as undertaken by dichotomous employment choice studies,
this study provides empirical evidence of how expectations of size are affected by
opportunity costs, given the commitment to start a new firm. The positive
association between opportunity costs and size expectations provides an explanation
as to why previous research investigating career choice decisions have produced
mixed findings. In particular, by constraining the scale or returns from venturing
activity to be consistent across all entrepreneurs, studies investigating the choice of
undertaking venture activity mask an important dimension of the choice to become
an entrepreneur.
Interestingly, household wealth generally does not have significant explanatory
power in predicting future venture size. In separate analyses, when removing
household income variable from the main regression model, household wealth is
still not a significant positive predictor of intended venture size. The fact that
wealth is not a significant predictor of venturing scale even after excluding
household income, a proxy for opportunity costs, suggests that opportunity costs
 G. Cassar / Journal of Business Venturing 21 (2006) 610–632 629

rather than financial capital drives the intended scale of venturing activity. An
explanation for the non-significance of household wealth is the relatively small up-
front outlays associated with starting ventures, thereby reducing the importance of
entrepreneur financial capital (Bates, 1995; Kim et al., 2003; Hurst and Lusardi,
2004).
A limitation of this research is that I do not investigate the actual sales achieved by
the venture. Obviously, there will be differences between planned growth and actual
growth achieved. In addition, of the entrepreneurs surveyed, not all will persist in the
venturing process to the point where sales are achieved. While these limitations are
noted, the utilization of perceived future sales rather than actual sales is a more
appropriate measure to investigate the research question in this paper. I focus upon
perceptions of growth, as the entrepreneur will make his decision to start the venturing
process and choose a venture, based upon the perception of future sales rather than
actual sales subsequently achieved. In addition, the subsequent performance of new
ventures appears to be influenced by the same human and financial capital variables
investigated in this study to explain size preferences (Cooper et al., 1994; Robinson and
Sexton, 1994). Therefore, by examining perceptions rather than actuals, I avoid the
influence of these same variables upon the venture size measure. How realistic these
growth perceptions are, and how these perceptions of future sales reflect actual sales is a
question for future research.

8. Conclusion

This study investigates which entrepreneurs intend to pursue larger venturing

activities. The results suggest that opportunity costs significantly influence the intended
growth of new ventures, with individuals with higher current household incomes and
supervisory experience intending on being involved in ventures with larger future sales
revenue. The findings are robust to alternative definitions of sales, but do not apply for
the future intended employment size of the venture. While this study finds that
entrepreneurial preferences for growth also influences intended future sales of the
venture, the association between nascent entrepreneur opportunity costs and venture
scale is complementary to these stated preferences. Overall, these findings suggest that
opportunity costs are an important determinant of the scale of intended venturing
activity.

Acknowledgements

The author would like to thank Philip Kim, Howard Aldrich and Lisa Keister for their
help with the PSED wealth and income data. The author would also like to thank seminar
participants from Jönköping International Business School, Lund University, Stockholm
School of Economics, and the University of Newcastle for their helpful comments. This
research would not be possible without the efforts of the Entrepreneurship Research
Consortium.
630 G. Cassar / Journal of Business Venturing 21 (2006) 610–632

Appendix A

Summary of the variable names, definitions, and source PSED variables utilized in the study
Variable Definition PSED variable description
Dependent variables
Intended venture size Intended total revenues in fifth year Log10 (Q317a)
Intended venture size owned Intended total revenues in fifth Log10 (Q317a*Q323/100)
year*intended proportion of venture
personally owned
Intended employment Intended total employment (FT) in Log10 (Q320)
fifth year

Opportunity cost variables

HHIncome Household income Log10(rincome)
HHWealth Household wealth Log10(cwealth)
KAKWealth Adjusted household wealth Log10(cwealth + 378,001)
Education Education of entrepreneur Q343 (up to high school, technical/
vocational, some college, college
degree, post college)
Managerial experience Years of managerial, supervisory, Q341
or administrative responsibilities

Control variables
Age Age of entrepreneur ITRWAGE
Race Ethnicity of entrepreneur ITRWRACE (White, Black, Latino,
Other)
Gender Gender of entrepreneur (Female = 1) If LBGENDER = 2

Supplemental variables
Growth intention Entrepreneur’s size intention of (Large as possible = 1) If Q322 = 1
venture
Risk–return Risk–return preference of (Low = 0) If QH9 = 1
entrepreneur
Financial success Earn a larger personal income; (QG1k + QG1g + QG1n + QG1j)/4
financial security; build great wealth,
high income; build business children
can inherit
Rincome and cwealth have been derived from PSED data using the approach detailed from Kim et al. (2004).

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