Technology and Investment, 2013, 4, 244-254
Published Online November 2013 (
Open Access TI
The Capital Structure of Business Start-Up: Is There a
Pecking Order Theory or a Reversed Pecking Order?
Evidence from the Panel Study of Entrepreneurial Dynamics
Hédia Fourati, Habib Affes
Faculty of Economics and Management, University of Sfax, Sfax, Tunisia
Received May 12, 2013; revised June 12, 2013; accepted June 19, 2013
Copyright © 2013 Hédia Fourati, Habib Affes. This is an open access article distributed under the Creative Commons Attribution
License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Using the Panel Study of Entrepreneurial Dynamics, we study if the problems of asymmetry and opacity of information,
asset specificity, agency problem and signaling theory predict the financial structure at inception. Thus, we conduct a
study in two steps. First, by analyzing the descriptive statistics, we find that novice entrepreneurs turn first to internal
sources of finance. Then, they apply to external debts and finally to equity finance. We prove then the applicability of
the Pecking order theory in case of entrepreneurial firms. Second, by analyzing the role of financial theory in predicting
the capital structure of entrepreneurial firms we find the following results. In fact, evidence from analyzing the role of
information opacity, asset specificity and signaling theory, proves that the main source of finance is equity rather than
debt. In the majority of the cases, depth interviews show from studying the financial theory an inverted pecking order.
Two main reasons for this pattern can be established. First, entrepreneurs consider debt as a personal liability as it re-
quires to be underwritten by personal guarantees. Entrepreneurs place a self-imposed limit on the extent to which they
are prepared to mortgage their assets. Second, entrepreneurs deliberately seek out equity investment as a means of ob-
taining added value. This external equity which has been viewed as expensive is viewed as good value. A well chosen
investor can add business skills and social capital in the form of commercial contacts and access to relevant networks.
Keywords: Pecking-Order Theory; Capital Structure; Asset Specificity; Signaling Theory; Moral Hazard; Credit
Rationing; Information Opacity
1. Introduction
One of the most fundamental questions of enterprise re-
search: “How business start-ups are financed?” In fact,
theoretical principles underlying the capital structure and
financing choices can be generally described in terms of
static trade-off or in term of Pecking-order framework.
Nevertheless, researchers have demonstrated that the
Trade-off theory is not profitable for young firms, [1].
Static trade-off includes the tax benefits of leverage and
bankruptcy costs, [2]. Young firms have less tax benefits
which are associated with more debt use, (Day et al.,
1983). The second component of the trade-off theory is
the bankruptcy cost. In fact, “young firms are more fail-
ure prone than older ones” [3]. Nevertheless, bankruptcy
costs are insufficient for proving the negative association
between risk and leverage, [4]. Entrepreneur is more con-
cerned with debts than its tax benefits. Thus, researchers
demonstrated that the Pecking-order theory is more suit-
able for justifying the financial choice of new firm. This
result is attributable to the importance of internal/external
debts vs. internal/external equity for the entrepreneur,
[5,6]. To the best of our knowledge little empirical vali-
dation of pecking order prediction has been previously
developed for a sample of business start-up, [7]. In fact,
[8] used a sample of new technology based firms; the
study of [5] investigates a sample of business start-up.
The latter studied the problem of information opacity,
asset specificity and human capital as determinants of
capital structure of business start-up. The originality of
this paper is in testing in more depths how the financial
theories (information opacity, agency problem, transac-
tion costs, signaling theory and human capital) may pre-
dict the capital structure. As our knowledge we find oth-
ers research doing so but for a sample of SME not for
business start-up, [9].
By the present research, we aim to study in one hand
the possible application of the Pecking order Theory and
in another hand the role of financial theory in predicting
the capital structure of entrepreneurial firms. The organi-
zation of this paper is as follows: Section 2 is the study
of the applicability of the pecking order theory; Section 3
is a summary of the role of financial theory in explaining
the capital structure, Section 4 introduces the model con-
struction, including selection of variables, data resources,
model formulation as well as the estimation method and
results and Section 5 draws conclusions and results.
2. Related Literatures
The literature introduced two opposite frameworks rele-
vant to the financing hierarchy of business start-ups: a
standard POT, following the spirit of Myers and Majluf,
(1984) and a reversed POT where external equity is pre-
ferred over external debt. Recent theoretical work has shown
this pecking order is reversed where investors have supe-
rior knowledge about the commercialization process of an
entrepreneur’s invention, and/or add value to the entre-
preneur’s project, [10]. However, the empirical works test-
ing these theories have one substantial limit, [11]. In fact,
the capital structure is investigated by descriptive statis-
tics relevant to the amount of different financing sources.
Comparing the magnitude of each source, a financial hi-
erarchy can be verified. This approach prevents us from
understanding the capital structure dynamics and determi-
nants. Therefore we maintain to contribute with a more
robust, explicit and comparative testing of the pecking or-
der theory on the one hand by investigating the descrip-
tive statistics and on the other hand by studying the role
of financial theory in justifying the financial structure of
start-up activities. We aim to respond to the following ques-
tion: Is there a Pecking order theory or a reversed Pecking
order of the capital structure of business start-ups?
3. The Pecking Order Theory in Case of
Entrepreneurial Firm’s
In fact, the Table 1 presents the different options of fi-
Table 1. Different sources of fun ding, $ value and percen tage of firms .
Means Source of funding
N1 %
2 Value3
By the entrepreneur 886 73%12291.02
Personal savings By others owners 330 27.2%85390.37
Internal equity Of the entrepreneur 558 46%12,686
Others sources by the entrepreneur 5 0.4%48.33
Others sources by others owners 7 0.6%3241
Personal debt to the new business 68 5.6 85,796
Personal debt
Other personal loans to the new business in the first year that must be paid back 49 4% 46,636
Personal debt from relatives and family 159 13.1%2857.49
Personal debts of others owners from their family 40 3.3%3033
Personal debts of others owners from colleagues and employers 18 1.5%369
Personal debts from colleagues and employers 57 4.7%1478.77
Debts of the activity from the entrepreneur 369 30.4%12296.85
Debts of the activity from others owners 149 12.3%296605.94
Debts from others 12 1% 246
Personal debts from relatives in the first year 5 0.4%566
Personal credit for employees who do not share the ownership of the business during the first year 1 0.1%9
Internal debt
Debts of other individuals in the first year 15 1.2%38,585
Total debts - 589449.77
Total of internal finance - 602135.77
Venture capitalist 1 - 203
Credit card of the entrepreneur 122 10%775.00
Credit card of others owners 28 2.3%1164.14
Bank debt by the entrepreneur 97 8% 3744.29
Bank debt by others owner 43 3.5 10296.51
Asset backed loan like a second mortgage or car loan by the entrepreneur 49 4% 1778.58
asset backed loan like a second mortgage or car loan by others owners 22 1.8 38980.73
Leasing 13 1.1%8212.4
Bank line of credit, credit to finance working capital 13 1.1%2941.18
Debt from supplier 13 1.2%871
Credit card of the activity 17 1.4%1444
Bank debt of the new activity 11 0.9%14,250
Bank loans by SBA guarantee 24 0.2%2637
Asset backed loan 121 10%95,215
Others loans 5 0.4%2123
External debts
Others debts 1141 94%41794.31
Total external financing 225226.83
Total external debts 225023.83
Total 828386$
1This is the number of companies that adopt this modality of financing; 2Is the percentage of firms whose value financing modality is greater than zero; 3This is the
average value in $.
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nance to entrepreneurial firms; their average value and
the percentage of firms that use each modality.
Table 1 produces a set of thirty-three sources of fund-
ing that may be adopted by new entrepreneurs in the
USA. 46% of the newly created firms have some equity
stake. The average of this contribution is in the order of
12,686$. In fact, 73% of entrepreneurs contribute to fi-
nancing the activity by their personal savings and its av-
erage value is about 12,291$ against 27% as a contribu-
tion in personal savings by other owners whose average
contribution is about 85,390$. Thus, the personal debt
has a minimal role. In fact, one quarter of the companies
adopt this type of financing. The majority of personal
debt adopted by entrepreneurs is in the form of bank
credit card. The average contribution of this type of fund-
ing is about 775$. 90% of entrepreneurs use some bank
loans for financing new venture. Nevertheless, most per-
sonal contribution of the entrepreneur is by their personal
savings. Indeed, more than half of entrepreneurial activi-
ties use this type of financing. It is mobilized through an
equity stake.
Internal debt is preferred to internal equity (the con-
tribution of business owners). Similarly, external debt is
preferred rather than external equity mobilized by ven-
ture capitalists. Venture capitalists provide an average of
203$. Indeed, only 121 new companies were able to at-
tract the participation of investors.
Taking into account the role of insiders, the contribu-
tion of the entrepreneur is mobilized by half of the sample.
In addition, internal debt is a source of funding that
should not be overlooked. The average contribution of
this category of funding is by 326,048$. This funding
takes the form of debt from family, friends, colleagues,
former employers and the contribution of the entrepre-
neur as a credit for the new venture. For example, 43%
of start-ups adopt this type of financing to launch its busi-
ness; its average contribution is about 308,908$. Thus,
personal savings of the founder is a source of financing
which is adopted by the majority of entrepreneurs. In fact,
weight intervention funding by the founding entrepreneur
is higher than that of other partners for all types of inter-
nal financing.
We are going now to compare the financial structure
by “insiders” and “outsiders”.
In fact, 12% of the entrepreneurs adopt a financing by
bank loans. This contribution is about 14,041$. 6% of the
entrepreneurs use a bank loan financing backed by an
asset. This contribution is an average of 40,759$. Indeed,
the importance of bank debt with guarantee in the launch
phase is quite crucial [12]. It turns out that companies with
more tangible assets have less financial constraints, [13].
For instance, Leasing, lines of credit and credit providers
have a relatively the lowest percentage 1% and their av-
erage values are successively: 8212$, 2941$ and 871$.
Taking into account the role of indebtedness for fi-
nancing new firms creation, we find that this type of fi-
nancing choice is adopted with low percentages: 1%.
This debt comes from bank loans, the government debt
and bank loans with SBA1 guarantee.
In fact, internal debt is a source of financing which is
very considerable than external debt. It has a double in
One point to admit in entrepreneurial finance is that
the entrepreneur lacks access to formal capital market.
The table above reflects the terms of the applicability
of entrepreneurial finance in terms of financial choices.
The newly created firms have an average capital of about
828,386$. Half of it comes from internal debt and the
quarter from external debt.
The majority of funds come from external bank loans
backed by asset and from credit cards. If we relate the
total credit card of the entrepreneur to the credit card
company, we find that it is the seventh. This result con-
firms that the majority of funding comes from the entre-
On this way, we can suggest some “Pecking Order”
which describes the capital structure of business start-up.
If we treat the equity contribution and personal debt as
internal funds, we find that many companies consider their
internal funds, fewer companies relate to debt and less to
venture capitalists. This confirms the message which is
transmitted by Myers and Majluf, (1984) about the “Peck-
ing Order”. Some authors introduced the need to revise
the POT, since they found evidence that both retained
earnings and external equity are quite unusual means of
financing for new firms; debt also seems to be disre-
garded compared to internal funds [14]. Literature has
recently introduced a revised version of the POT, where
external equity is preferred over external debt in the case
of innovative firms [15]. According to his study the
pecking order theory in the case of innovative firms is
reversed as follows: 1) Insider Capital, informal private
equity and easy-term financing (seed); 2) Venture capital
financing (start-up); 3) Self financing, banks and or busi-
ness credit (early growth); 4) Direct issue of bonds and
public equity (sustained growth).
Is there a Pecking order theory or a reversed Pecking
order if we consider a more dynamic approach that ana-
lyzes the role of information opacity, asset specificity
and signaling theory in predicting the capital structure of
4. The Financial Theory as a Determinant of
the Capital Structure of Business Start-Up
We study the role of information opacity, agency prob-
1The Small Business Administration (SBA) is a United States govern-
ment agency that provides support to entrepreneurs and small busi-
nesses. SBA loans are made through banks, credit unions and other
lenders who partner with the SBA. The SBA provides a govern-
ment-backed guarantee on part of the loan, Wikipédia, 2012.
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lems, signaling theory and transaction costs in defining
the existence of a POT or a reversed POT for business
4.1. Information Opacity and Capital Structure
of Entrepreneurial Firms
Previous studies demonstrated that new firms have no
historical and no reputational effects. Thus, business is
informationally opaque. This informational problem makes
the external financing not available at start-up phase, [16].
Under this problem, a Pecking order will take place.
Firstly, personal savings, secondly short-term debt, then
long-term debt, and ultimately and the least preferred is
the role of external investors, [17]. Given the difficulty in
obtaining external financing, entrepreneurs rely heavily
on internal funds, [18]. Under the condition of informa-
tion opacity, after internal funds, the firm must resort to
bank borrowings then to equity contributions. Indeed, a
relationship of debt is based on “soft” information gener-
ated by the banking experience with the lender and by a
continuous contact bank-owner by providing some fi-
nancial services, [19], p. 645. Some studies have demon-
strated the importance of the relationship of debt in grant-
ing loans to small businesses, Hanley and Crook, (2005).
Due to this informational problem, internal financing is
the primary source of funding followed by external debt
and ultimately a limited amount of external equity. The
following hypotheses regarding the problem of informa-
tion opacity are proposed:
H1: information opacity is positively correlated with
the probability of using internal funds in financing new
venture creation;
H2: Information opacity is negatively associated with
the probability of using bank debts in financing new ven-
H3: Information opacity is negatively associated with
the probability of financing the new venture by external
Nevertheless, information problem may create some
agency problems. In the following section, we analyze
the role of moral hazard problem and credit rationing in
justifying some financial choice of the entrepreneurial
4.2. Agency Problems and Capital Structure of
the Entrepreneurial Firms
The provision of loan by investor to the entrepreneur will
create an agency relationship between the entrepreneur
(the agent) and the investor, who is the principal, [20].
Agency problems are more developed in small entrepre-
neurial firms than their counterparts large firms. In fact,
collecting information by financial intermediary is rare
and expensive, [21]. The sharing in capital with the ven-
ture capitalist involves establishing a cooperative rela-
tionship between the investor and the entrepreneur, [22].
*Moral hazard and capital structure of the entrepre-
neurial firms
Due to the inability to write complete contracts speci-
fying the benefits right under any liquidation act, the
entrepreneur has interest to expropriate funds after sign-
ing the contract with the bank, Huyghebaert and Van De
Gucht, (2007). The moral hazard problem leads therefore
to a first incentive to undertake riskier projects and in-
centives of underinvestment in projects with positive net
present value.
*Credit rationing and capital structure of the entre-
preneurial firms
There are two theoretical models emphasizing credit
rationing, [23]. Indeed, these models are those of (Stieglitz
and Weiss, 1981) and [24]. Due to the problem of credit
rationing, loan applicants are generally the firms with
good quality. For those who come to borrow, the bank
increases the value of the debt and/or increase the matur-
ity of the credit. Credit rationing affects only the decision
of bank financing, and will have no effect on debt, Huy-
ghebaert and Van De Gucht, (2007). This discussion
leads to the following hypothesis:
H4: agency problems must be negatively associated
with the probability of using bank debt in financing new
4.3. Asset Specificity and Capital Structure of
the Entrepreneurial Firms
The theory of transaction costs defined by Williamson,
(1988) implies that the specific assets generate quasi-
rents for business. The asset specificity is a source of
competitive advantage in the market, [25]. Assets of an
entrepreneurial project may be specific to it and the op-
timal financial contract is one that minimizes transaction
costs. The asset specificity for start-ups gives rise to two
main problems. The first is related to the lowest net asset
value. The second is related to the “hold-up problem”
due to the specific human capital which gives rise to the
opportunism problem. In business start-up, the entrepre-
neur will contribute not only by his managerial skills but
also contribute with his financial capital, his knowledge
and his human capital, [26]. The relative importance of
the intangible assets does not always allow banks to have
guarantees, [27].
Such assets have high transaction-costs and do not al-
low bankers to hedge against the risk of bankruptcy. Thus
external investors and especially lenders may be reluctant
to finance such projects. New venture that has more spe-
cific assets should primarily be financed through equity
and secondly through a public offering and finally by
external debt, Huyghebaert and Van De Gucht, (2007).
One proposed solution to this problem of “hold-up” is to
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grant control rights to the entity that has specific re-
sources, [28]. Based on our review of the role of asset
specificity in new venture financing, we propose to test
the following hypothesis:
H5: Asset specificity must be negatively correlated with
the probability of using external debts;
H6: Asset specificity must be positively associated with
the probability of using internal fund for new venture
H7: asset specificity must be positively associated with
the probability of using external equity for new venture
4.4. The Signaling Theory and the Capital
Structure of Entrepreneurial Firms
Following the literature the contribution of the entrepre-
neur in the project serves as a signal of its quality, [29].
In fact, the capital of the entrepreneur is engaged as a
credit guarantees and has a signal effect, [30]. Indeed, the
willingness of the lender to fund new projects is posi-
tively related to the personal guarantee of the entrepre-
neur especially regarding the personal funds that are in-
vested, [31]. The size of the ratio of debt to guarantee
exceeds the unity for 85% of small businesses in the UK,
[32]. In fact, the underlying asset has different roles for
the financial institution. Warranty can cover the contrac-
tor to overcome the problem of moral hazard, [33]. It is a
signal to the bank stating that the contractor perceives
that his project will win. Similarly, the guarantee consti-
tutes a solution of the problem of information asymmetry
and reduces the problem of credit rationing, [34]. The
underlying asset allows the renegotiation of the contract
in case of financial distress, [35]. Regarding the role of
the signaling theory in explaining the financial decision
of entrepreneur we aim to test the following research
H8: An increase in equity contribution of the entre-
preneur and the other owners is a signal to increase the
probability of financing by bank debt;
H9: An increase in the entrepren e urs and other own-
erspersonal guarantees of the business are a signal to
increase the probability of financing by bank deb.
4.5. Characteristics of the Activity and the
Capital Structure of Entrepreneurial Firms
*The role of size
Previous studies explained the existence of a positive
correlation between long-term debt and size. In fact, smaller
firms employ less long-term debt due to scale effects.
This positive relationship may also be accounted for by
collateral effects, as the natural logarithm of total assets
is commonly employed as a proxy variable for size. This
finding is consistent with the view that smaller firms are
heavily reliant on short-term debt. Thus firms are un-
willing or unable to use long-term debt because of the
relatively higher transaction costs, Mac an Bhaird, (2010).
*The legal form of organization
The legal form of the organization provides a specific
form of financing. It is a signal that indicates credibility
and formality of operations and ensures future growth as
noted by Cassar, (2004). There is, then, a positive corre-
lation between debt and organization in incorporation,
[36]. However, the legal organization ensures more bank
debt. Under this discussion the following research hy-
pothesis are proposed:
H10: An increase in the size of activity reduces the
probability of financing the entrepreneurial projects by
H11: The legal form of organization inincorpora-
tionis increase the probability of financing the entre-
preneurial project by external debt and bank debt.
4.6. The Entrepreneur’s Attributes and the
Capital Structure of the Entrepreneurial
The personal characteristics include gender, education [37]
and experience.
H12: The individual characteristics of an entrepreneur
increase the probability of financing new venture by debts.
5. Data
Our analysis uses the detailed data in the Panel Study of
Entrepreneurial Dynamics (PSED). The description of
the background and the sampling methodology are pre-
sented by, [38]. The PSED is a longitudinal database
selecting the period 2005-2010. PSED was started in
2005 with the selection of a cohort of 1214 nascent en-
trepreneurs chosen from a representative sample of 31,845
adults. In the first year, a follow-up interview was com-
pleted with 1214 entrepreneurs (80% of the original co-
hort): 87% of the interviewed persons are “novice” en-
trepreneur; 60% of them have accepted to participate to a
second interview after one year.
5.1. Model and Measure of Variables
In our model the dependent variable is dichotomous
(i.e., whether or not an individual use the mean of fi-
nance in internal or external funds). Accordingly, we use
the logistic regression methodology to estimate the coef-
ficients. The generalized form for the response probabili-
ties for the model is given in the following equation:
45 6
(financing )
inf opacityagencyasset specificity
signalingentrepreneu attributesActivity
 
 
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financingi, is a dichotomous variable that measures if
the entrepreneur adopt one of the modalities of fi-
nancing in 1) the owner resource, 2) internal finance,
3) external finance, 4) bank finance and 5) the outside
“Information opacity”: Is a vector that explain the
existence or not of certain information opacity.
Agency problem: Is a vector that explains the exis-
tence or not of an agency problem in moral hazard
and credit rationing.
Asset specificity: Is a vector that explains the exis-
tence or not of an asset specificity.
Signaling: Explains the owner’s contribution to col-
lateralize and/or to finance the entrepreneurial project.
*Measure of variables
Table 2 explains the different items of the dependent
and the independent variables. Information opacity is
measured by a home based activity, if the entrepreneur is
a serial one. Asset specificity is measured by the entre-
preneurial experience, the industrial experience, the value
of tangible assets and the existence of an intellectual
property. Agency problems consist in credit rationing
and moral hazard. The signaling theory is measured by
the value of the entrepreneur’s asset and his contribution
to finance the activity in equity finance. Control variables
are in the entrepreneur’s attributes and the characteristics
of activity.
Table 2. Measure of variables of the model.
Variables Labels Measures
Dependent variables
Internal equity PCINTERNE Dichotomous variable coded “1” if the share of capital retained by
the entrepreneur exceeds or equal 50%.
Internal debts DETEINTERNE Dichotomous variable coded “1” if the entrepreneur use some debts from family,
friends and others personal resources.
External debts DETEXTERNE Dichotomous variable coded “1” if the entrepreneur have some debts from banks,
credit cards, suppliers and others external debts.
Bank debts CREDIBANC Dichotomous variable coded “1” if the entrepreneur uses some bank debts
for financing the new venture.
Bank debt
with guaranty CREDIBANGAR Dichotomous variable coded “1” if the entrepreneur uses some secured bank debts.
External equity PCEXTERNE Dichotomous variable coded “1” if the entrepreneur uses some external equity.
Independent variables
Home based RESIDENCE Dichotomous variable coded “1” if the venture is based in the home of the founder.
Serial SERIAL The total numbers of the activities which are started by the owners of this venture.
expérience EXPERIENCE_ENTREPREN Number of years of the entrepreneurial experience in the same industry.
Industrial experience EXPERIENCEINDUS Number of years of industrial experience.
Tangible LOG-TANG
Value of cash available to the contractor which can be used as a collateral
for obtaining credit (value of physical properties of the contractor machinery,
Intellectual property PREOPRIETE-INTELLECTUELLEDichotomous variable coded “1” if the entrepreneur has some intellectual property,
(patents, copyrights, and trademarks).
Moral hazard RISQUMORAL Dichotomous variable coded “1” if the entrepreneur responds “no” to the following
question: “Are all funds deposited in a bank account in the name of the company?”
Credit rationning RATIONNEMENT The percent of new venture which starts without looking for bank debts.
Personal equity LOG-PARTICIP Value of personal contribution to the new venture.
Tangible LOG-TANG Value of tangible assets.
Age AGE Age of the principal founder.
Gender GENRE Dichotomous variable coded “1” if the entrepreneur is a man.
Education BAC Dichotomous variable coded “1” if the entrepreneur has a level education.
Dichotomous variable coded “1” if the startup is a limited liability company,
a subchapter S-corporation, a C-corporation, a general partnership, or a
limited partnership company.
Size TAILLE Number of employees in the start-up year.
5.2. The Logistic Regression and the Results
The econometric estimation of the logistic regression is
presented in Tabl e 3 and reveals the following results for
each financial problem. Since most firms are financed
primarily by only one type of finance, we use discrete
variables (for example, the binary 0, 1)2, when describing
the financial structure for each firm. For our main as-
sessment of the PSED in the financial structure, we con-
sider the four-way financial sources: internal equity, in-
ternal debt, external equity, and external debt, and then
the six-way decomposition that focuses on the types of
external debt.
From Table 3 we find that in term of information
opacity, serial entrepreneurs have some reputation. New
activities, that are home-based and installed by a “habit-
ual” entrepreneur, are more exposed to problems of in-
formation opacity. For these activities, internal resources
dominate the financial structure and then external debt
and little equity finance. In fact, information opacity for
business start-up prevents any source of external financ-
ing in the form of debt or equity, [39].
Taking into account the variables that measure the in-
formation opacity, the activities installed in own homes
have the most information opacity. They are more likely
to be financed by equity contribution. These entrepre-
neurs have less than 38% chance of having a bank debt
and less than 30% chance of having external equity in
their capital structure. Nevertheless there is a positive
correlation with internal equity. The serial entrepreneur
is more likely to finance the new venture activity by in-
ternal and external equity due to the availability of in-
formation of the owner. We show a positive correlation
between a serial entrepreneur and the probability of using
internal debt. The serial entrepreneur does not attract the
investors in our sample. In fact, they have 68% less
chance of having some external equity. With regard to
the availability of information, they are more likely to
have an external debt.
Table 3. Logistic regression for determinants of capital structure of business start-up.
Internal equity
(Model 1) Internal debt
(Model 2) External debt
(Model 3) Bank debt
(Model 4) Secured bank loan
(Model 5) External equity
(Model 6)
Home based activity 0.041 0.34* 0.317 0.386* 0.22 0.28
Serial 0.14 0.018 0.158 0.067 0.10 0.68
experience 0.025 0.937 0.015 0.227 0.282 0.337
Industrial experience 0.001 0.0034 0.0049 0.011 0.012 0.013
Log (tangible asset) 0.012 0.1500*** 0.242*** 0.144*** 0.023 0.139
Intellectual property 0.175 0.210 0.104 0.016 0.343 0.217
Moral hazard 0.499*** 0.91*** 0.19
Credit rationning 0.174 0.44*** 1.28
Log (owner equity) 0.009 0.059*** 0.020 0.069*** 0.0007 0.012
Age 0.007 0.015*** 0.007 0.005 0.013 0.01
Gender 0.117 0.019 0.335* 0.234 0.06 0.468
Éducation 0.532*** 0.212 0.19 0.049 0.208 0.639
Size 0.003 0.003 0.0002 0.006 0.03 0.047
Incorporation 0.766*** 0.020 0.102 0.356** 0.47 1.32***
C 0.596* 0.273 1.192 3.138*** 3.702* 4.95**
R-squared = 4%
McFadden R
squared = 3.3%
R-squared = 7%
R-squared = 12.5%
R-squared = 2%
R-squared = 9%
2Empirical work on established firms often uses the share of different types of financing instead of the 0-1 binary choice. However, for the startup
financial data, the 0-1 choice variable is superior because some of the shares are small while others are at such extremes that there would not be a
normal distribution for the share variable.
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Taking into account the extent of asset specificity, an
increase in asset tangibility increases the probability of
having some external debt and bank debt in its financial
structure. Indeed, the tangible assets are important in the
eyes of creditors. The Pecking-order theory also provides
the same conclusions. Indeed, a firm having more tangi-
ble assets will be less sensitive to asymmetry of informa-
tion. Tangible assets are less exposed to the problem of
information asymmetry and lose, in case of liquidation,
less value than the intangible assets.
Predictions based on the information opacity are clas-
sified, based on the characteristics of assets for the ma-
jority of new start-ups. For this type of business, the en-
trepreneur does not only have managerial expertise of the
business but also produces a certain human and financial
capital. This type of specific human assets cannot be trans-
ferred to alternative uses due to the problem of informa-
tion opacity. As noted by Sanyal and L. Mann, (2010).
The activity that has the most specific asset is primarily
financed by the entrepreneur’s own resources and through
his participation in external capital and lastly by external
Other activities acquired by the entrepreneur, may be
used as collateral for financing new activities. The value
of the intellectual property is less certain and brings low
net asset value. We believe that a start-up with high hu-
man capital is primarily funded by internal resources and
specifically by internal equity. In fact, many tangible
assets increase the probability of having some internal
debt by 15%, and increase the probability of having a
bank debt by 14%. Nevertheless, increasing the probabil-
ity of having some intellectual property reduces the prob-
ability of having an external debt by 10%. The intellec-
tual property reduces the probability of being financed by
external funding sources. It decreases the probability of
financing by bank debt.
High industrial experience (as a component of specific
human capital) increases the probability of using the in-
ternal equity in financing venture activities. This effect is
negative and insignificant for using external debt. The
influence of industry knowledge increases the secured
bank loan. Nevertheless, an increase in the knowledge of
the activity mobilized by the entrepreneurial experience
decreases the probability of having a debt in its external
structure. This negative correlation between the entre-
preneurial experience and external debt can be attributed
to a loser entrepreneurial experience. The latter generates
negative information about the reputational capital of the
Nevertheless, it appears that the past entrepreneurial
experience helps to attract the external investors.
In term of agency problem, credit rationing is nega-
tively associated with bank debt. We notice that an in-
crease in credit rationing decreases the use of bank debt
by 44%. We find also the existence of a positive correla-
tion between credit rationing and bank loans. This result
confirms those of Huyghebaert and Van De Gucht, (2007).
The latter showed that bank increases the maturity of the
debt when credit rationing occurs to reduce the problem
of adverse selection. Moral hazard is negatively associ-
ated with external debt and bank debt. The existence of
moral hazard problem reduces the use of external debt by
50% and the use of bank debt by 93%.
The owner’s characteristics are a determinant of the
capital structure and the financial characteristics of the
new activities. Age, education and gender produce a sig-
nal on the quality of the human capital. Better human
capital is associated with a viable business. Therefore ac-
cess to debt as noted by Storey, (1994) is more important
for this type of business. An increase in equity by the
owner is a signal to outsiders by providing an increase in
external debt, especially bank debt. This increase is in
order of 7%. Taking into account the variable log-tangi-
ble as a signal for personal guarantees, the latter is posi-
tively associated with bank loans which are secured or
unsecured. The newly founded activities by older entre-
preneur are less financed by internal, external and bank
debt. Many educated entrepreneurs are 20% more likely
to be funded by bank debt and secured external debt.
Contrary to the results of Sanyal and L. Mann, they are
50% more likely to be financed by internal or external
equity contributions. This is associated with the condi-
tion that they have sufficient financial knowledge to be
aware of the sources of bank financing and government,
[40]. Venture activities founded by men are 35% more
likely to be financed by external debt.
Characteristics of the activity are quite crucial to de-
fine the financial structure of the business. Banks per-
ceive corporation serve as a signal that describes the
credibility and indicates the future growth opportunities.
For example there is a positive correlation between debt
and the legal form. It suggests that it leads to more bank
debt. The legal form is positively and significantly asso-
ciated with bank loan. Indeed, the legal organization in-
creased 36% chance of using bank debt. It constitutes a
signal and attracts the external investors. It increases the
probability of using external finance and by 76% the prob-
ability of using internal funds.
Taking into account the three funding scenarios flow,
external debt and equity contribution to various external
and financial problems of opacity information, asset speci-
ficity in agency problems and the role of signaling theory,
we test the possible existence of a Pecking-order or a
reversed Pecking order for justifying the financial struc-
ture of new entrepreneurial projects. We take into con-
sideration the sign of association and the existence of a
more or less elastic coefficient. Taking into account the
problem of opacity information, the entrepreneur has
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more probability of being financed by personal saving,
then by external equity and less chance of being financed
by external debt. Indeed in term of opacity of informa-
tion, we retain reversed version of the Pecking-Order.
And we retain the following classification: internal funds,
external equity and external debt. In terms of asset speci-
ficity, from all items, we also prove the existence of a
reversed Pecking-order. Taking into account the role of
signaling theory, in term of personal contribution to the
venture activity and the role of tangible assets, external
debts are more preferred to external equity for financing
new venture creations and we prove the Pecking order
6. Conclusion
Our study is conducted on the PSED database. We are
interested in studying the decisive weight of the financial
problems in information opacity, asset specificity, agency
problems and signaling theory in the decision of the capi-
tal structure of the new entrepreneurial projects. From a
logistic regression of binary variables that defined the
sixth funding scenarios of finance, we have drawn the
following conclusions. New entrepreneurial activities are
more likely to have some external debt in their capital
structures if they have more tangible assets that serve as
collateral and if they have a legal form in incorporation.
Due to the lowest value of human capital, the entrepre-
neurial activities in more human capital are less likely to
have some external debt and more likely to be financed
by internal finance. Home based activities are more likely
to be financed by internal equity contributions, less by
external debt and attracting less outside investors. More
educated entrepreneurs contract more external debt and
attract more investors. In fact, external debts bring some
transaction costs. Then we studied the applicability of the
POT in a context of entrepreneurial firms. We conduct
two different studies. The first study is interested in some
descriptive statistics of different means of finance. Then,
we conclude the applicability of Pecking order theory in
defining the capital structure of entrepreneurial firms.
The second study is more analytic and parts from study-
ing the role of financial theory in defining the capital
structure of entrepreneurial firms. Thus, we conclude from
the logistic regression the existence of a reversed Peck-
ing order defining the capital structure of business start-
up except of signaling theory. The introduction of exter-
nal equity into a start-up business can be seen by an
owner as a dilution of control, [41]. Our results corre-
spond to a response to the critics of Cassar, (2004) the
studies of the capital structure of the entrepreneurial pro-
jects. The first method has the limit of time of using the
different modalities of finance. In fact, some methods of
financing are used by entrepreneur. Nevertheless, others
modalities are incurred in the name of the business and
after one year of the inception. Then, we explain this result
by the problem of responses bias for some means of fi-
nance and especially in terms of the role of the external
equity. In this paper, the sample of entrepreneurs has the
limit of collecting external equity and non responses bias.
This limit does not allow us treating the entire roles and
issues associated with the Pecking order theory. The study
conducted on the same sample leads to conclude that
novice and more rich American entrepreneurs face more
financial constraints, [42]. It would, therefore, be useful
to chart the experience of entrepreneurs who face finan-
cial constraints. In their search for finance did they fol-
low the sequence suggested by either the POH or of the
reversed pecking order?
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