Dissertation by fanzhongqing

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									                         DOCTORAL DISSERTATION PROPOSAL




             Credit Sources, Founders, and New Firms
                                                    Version X




                                             John M. Mueller
                                    M.B.A., University of Illinois, 1999
                                B.B.A., Southern Methodist University, 1992


                                                A Dissertation
                                      Submitted to the Faculty of the
                               Graduate School of the University of Louisville
                                 in Partial Fulfillment of the Requirements
                                              for the Degree of


                                             Doctor of Philosophy



                             Department of Management and Entrepreneurship
                                         University of Louisville
                                          Louisville, Kentucky


                                                 January 2011



Keywords: new firms, founders, entrepreneurial finance, debt financing, credit sources




* The author is grateful to the Ewing Marion Kauffman Foundation for financial support and access to the Kauffman
Firm Survey data. The author would also like to thank participants that attended the brown bag session at the
University of Louisville for their valuable comments and suggestions in Spring 2008.
Credit Sources, Founder, and New Firms                                                                                                 2011-01


                                                     TABLE OF CONTENTS


ACKNOWLEDGEMENTS ................................................................................................................... 3

ABSTRACT ....................................................................................................................................... 4

LIST OF FIGURES AND TABLES ....................................................................................................... 5

1. INTRODUCTION ........................................................................................................................... 6

2. THEORY DEVELOPMENT .......................................................................................................... 14
   2.1. DEBT FINANCING, USE OF MULTIPLE CREDIT SOURCES, AND AMOUNT OF DEBT ................... 15
   2.2. MULTIPLE CREDIT SOURCES AND FOUNDING TEAM CHARACTERISTICS .................................. 26
      2.2.1. SIZE OF FOUNDING TEAM .......................................................................................... 28
      2.2.2. EDUCATION OF THE FOUNDERS ................................................................................. 29
      2.2. 3. WORK EXPERIENCE OF THE FOUNDERS ................................................................... 30
   2.3 SURVIVAL .............................................................................................................................. 30
   2.4 GROWTH ............................................................................................................................... 31

3. RESEARCH METHOD................................................................................................................. 31
   3.1. DATA ................................................................................................................................... 31
   3.2. ANALYSIS ............................................................................................................................. 33
      3.3. VARIABLES ..................................................................................................................... 34
   4. RESULTS ................................................................................................................................. 37
   4.1. ROBUSTNESS CHECKS ........................................................................................................... 41
      5. DISCUSSION AND CONCLUSION ........................................................................................ 42
   5.1. LIMITATIONS ........................................................................................................................ 45
   5.2. FURTHER RESEARCH ............................................................................................................ 47

REFERENCES ................................................................................................................................. 48

APPENDICES .................................................................................................................................. 57

APPENDICES .................................................................................................................................. 57
   SIMULATION MODEL CONFIGURATION ......................................................................................... 57

FIGURES AND TABLES .................................................................................................................. 62

CURRICULUM VITAE .................................................................................................................... 72




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Credit Sources, Founder, and New Firms            2011-01

ACKNOWLEDGEMENTS

       …




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Credit Sources, Founder, and New Firms                                                            2011-01

ABSTRACT

        Banks ration credit and thus put limits on access to credit for new firms in part due to

information asymmetry issues that arise from the principal-agent relationships between the banks

and new firms. It seems obvious the use of alternative credit sources is a means for firms to get

around credit limits imposed by banks. Using the Kauffman Firm Survey data set of new firms,

my dissertation examines if multiple alternative credit sources are used by new firms to alleviate

the credit limits imposed by banks. The results indicate that new firms obtain additional debt by

using multiple alternative credit sources, suggesting that the use of multiple alternative credit

sources are a means for new firms to overcome credit limits imposed by banks. A discussion of

the effects of firm survival as it relates to the use of multiple alternative credit sources is

included.




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Credit Sources, Founder, and New Firms            2011-01

LIST OF FIGURES AND TABLES

Figure 1



Table 1




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1. INTRODUCTION

       Financial capital is one of the fundamental resources needed to start and operate a

business (Cooper, Gimeno-Gascon, & Woo, 1994). However, entrepreneurs tend to be

constrained financially when trying to start and operate a new firm, and as a result they look for

external financing (Evans & Jovanovic, 1989; Evans & Leighton, 1989; Lindh & Ohlsson,

1996). Retained earnings (i.e. internally generated equity), debt, and equity are all forms of

financing that a new firm could use to finance operations. Based upon the pecking order theory,

firms will finance their operations first with equity, then debt, and lastly with external equity

(Myers, 1984; Myers & Majluf, 1984). The theory suggest that this order of financing options

will be used by firms because it is more difficult to convince banks to provide collateralized

debt, and even more difficult to convince investors to invest without collateral, due to the

information asymmetry between the external financers and the new firm. New firms do not

generate much, if any, internal equity. Thus, debt becomes the first sizeable financing option

available to new firms.

       Banks provide capital to assist entrepreneurs with the financial constraints they face when

operating a business. As a financial intermediary used regularly by small established firms

(Berger & Udell, 1995, 1998), banks are unique in their ability to gather information and monitor

established small borrowers (Diamond, 1984, 1991; Fama, 1985; Ramakrishnan & Thakor,

1984). New firms tend to start out small (Audretsch & Mahmood, 1995; Birley, 1987), but by

definition are not established. Even though banks have evolved to work successfully with small

established firms, they have difficulty accurately determining which new firms will be able to

repay their debt in full due to high information asymmetry prevalent in the principal-agent

relationship between banks and new firms. Because new firms likely have greater information




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Credit Sources, Founder, and New Firms                                                      2011-01

asymmetry than older firms, it is more likely that banks ration credit to new firms (Stiglitz &

Weiss, 1981).

       Credit rationing could be harmful to a new firm’s growth and survival. The presence of

credit rationing means that banks will not lend money, or will lend less than the optimal amount,

to positive net present value projects (Keeton, 1979). With the possibility that banks ration

credit and thus turn down requests for funds by entrepreneurs operating firms that objectively

should be able to service the debt, banks make it difficult for entrepreneurs to successfully

operate their new firms (post-entry).   This suggests that new firms require additional sources of

external financing when their bank imposes credit limits on them. In many cases, the inability of

obtaining additional external sources of financing could result in the firm shutting down entirely.

However, entrepreneurs are a breed of individuals that are persistent and tend to persevere

(Cardon, Zietsma, Saparito, Matherne, & Davis, 2005; Gimeno, Folta, Cooper, & Woo, 1997;

Sexton & Bowman-Upton, 1991), especially when they plan (Delmar & Shane, 2003; Liao &

Gartner, 2006). This suggests that entrepreneurs look for other funding options to survive when

they are rationed credit by banks.

       Studies of small established firms have suggested that firms will access alternative credit

sources when banks impose credit limits. These alternative credit sources include loans from

non-bank institutions, the government, and family and friends, as well as trade credit, lines of

credit, and credit cards (e.g. Astebro & Bernhardt, 2003; Berger & Udell, 1995; Danielson &

Scott, 2004; Huyghebaert & Van de Gucht, 2007; M. A. Petersen & Rajan, 1997; Robb &

Robinson, 2010). Alternative credit sources tend to be a more expensive option of external

funding for new firms than bank loans (Danielson & Scott, 2004; Huyghebaert & Van de Gucht,

2007). Since these alternative credit sources tend to be more expensive than bank loans, provide

smaller amounts of credit, and are not as skilled as banks in gathering information and


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Credit Sources, Founder, and New Firms                                                          2011-01

monitoring, it would then be relevant to investigate if new firms are able to use multiple credit

sources to get around credit limits that are imposed by banks.

       This leads to my first set of research questions concerning the use of multiple credit

sources. Do new firms use multiple alternative credit sources to get around the credit limits that

banks impose on them? Does greater use of alternative credit sources mean more debt is

available to new firms, or does it mean that the same amount of debt is spread over multiple

alternative credit sources as the firm ages?

       This first set of questions invoke further interest of what factors would determine whether

or not the entrepreneur facing such rationing exploits additional sources of credit. Based upon

social capital theory (Burt, 1995; Coleman, 1988; Granovetter, 1973) and human capital theory

(Schultz, 1959, 1961), I hypothesize that the characteristics of the founders, including the

education level and work experience of the founders, as well as the size of the founding team,

affect the use of alternative credit sources and the level of debt a new firm decides to use.

       New firms are based around and highly dependent upon the founder. Each founder

brings with him/her characteristics that are not easily detached from the firm he/she starts. Each

founder starts his/her business with different levels of social and human capital which affect the

outcome of their firm (Davidsson & Honig, 2003). Since new firms are inherently small they

usually have limited resources, and thus the characteristics of the founder tend to be

representative of the nature of the firm initially. Along with being small, new firms do not have

a track record as they do not have any operational or financial history, which puts even more

importance on the characteristics of each founder. These characteristics include their education

and work experience. These elements of human and social capital of a founder can play an

important role in a bank’s decision to provide a loan to the new firm, or at least change the terms

of the bank loan (Hart and Moore, 1994). Thus, human and social capital could play a role in the


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likelihood that new firms look at using additional credit sources to finance the operations in their

initial years of existence.

        Even though much of the entrepreneurship literature looks at individual entrepreneurs,

starting a business is generally a collaborative activity involving several partners (Gartner,

Shaver, Gatewood, & Katz, 1994). The founding team might provide a venture with access to a

wider array of human and social capital, which in turn could lead to additional financial

resources (Burt, 1995; Granovetter, 1973; Parker & Van Praag, 2006; Ucbasaran, Lockett,

Wright, & Westhead, 2003). It would then be logical that a team of individuals starting a new

venture will have more valuable resources than a single individual founder (Kor & Mahoney,

2000). In the terms of social networking theory, which social capital theory is encompassed,

individuals in society have strong and weak ties with other members in society (Granovetter,

1973). Strong ties are relationships in which individuals have a close relationship and thus

require a larger time commitment; whereas weak ties are relationships where individuals are not

closely related. External financiers are considered weak ties in many cases. Therefore, larger

founding teams might have more access to external financiers as opposed to individual

entrepreneurs. Since lenders require collateral from individuals, and not from the firm, a larger

number of individuals could possibly borrow more than an individual founder. Thus, the size of

the founding team may determine whether the firm has to look at additional credit sources to

finance the operations in the initial years.

        As the firm starts to generate revenue and accumulate assets, the firm begins to have a

track record. The firm is more able to sustain itself, or even try to grow. If the firm is trying to

grow then it will most likely require more funds. Additional credit sources can be used to

acquire more funds. As well, some firms might want to stabilize their operations and move debt

from their founder’s personal liability to the liability of the business. With a firm able to borrow


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Credit Sources, Founder, and New Firms                                                         2011-01

using its own balance sheet, and presumably able to borrow more than what the individual

founders could borrow, the amount of debt per credit source should decrease. In that case,

lenders are more willing to take a chance of lending more to the business. Thus, the trend of the

number of credit sources used over time might become less reliant on the characteristic of the

founder and more reliant on the characteristics of the business.

       This leads to my second set of research questions. Are there founder characteristics that

lead to the new firm using more or less credit sources? How and why are founders able to

alleviate the pressure on their personal characteristics when financing the new firm?

       Survival is a priority for founders of new firms (Shane, 2003), and the growth of new

firms being a large factor in job growth (Haltiwanger, Jarmin, & Miranda, 2009). New firms

tend to have limited resources, including financial resources. As such, many new firms are

undercapitalized when they are started (Evans & Jovanovic, 1989). This undercapitalization can

ultimately lead to firm failure. Undercapitalization is a larger factor of failure for firms during

their early years of existence as opposed to when they are older (Cressy, 2006a). A large number

of new firms fail within five years (Cressy, 2006b; Phillips & Kirchhoff, 1989). With the failure

of new firms, jobs in those firms disappear. However, new firms that survive tend to show a

higher growth rate than those that fail (Phillips & Kirchhoff, 1989). This leads to my final set of

research questions that revolves around the use of multiple alternative credit sources. Does the

usage of multiple alternative credit sources to overcome credit limits increase the chances of the

survival of a new firm? And does the usage of multiple alternative credit sources help or impede

the growth of a new firm?

       In summary, the research questions in my dissertation revolve around the financing

decisions of entrepreneurs after they have started their firm and have been rationed credit.

Specifically, the research questions focus on investigating factors that affect the use of multiple


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Credit Sources, Founder, and New Firms                                                        2011-01

credit sources by new firms, and if the use of multiple credit sources affect survival and

growth of new firms. I use the pecking order theory to explain why firms exhaust debt options

prior to soliciting and accepting equity options. To support debt financing outside of banks debt,

I use the credit rationing theory. And I use social capital theory and human capital theory to

explain the predictors that affect the use of multiple alternative credit sources by new firms. To

conclude the study, I use a logical argument to explain why multiple alternative credit sources

affect the survival and growth of new firms.

       Seeking answers to the research questions posed, my dissertation examined the use of

alternative credit sources by new firms to determine if they overcome the credit limits possibly

imposed by banks. I use a mixed method strategy to test if credit rationing is occurring and test

the hypotheses, while inturn answering the research questions that I have posed. The mixed

method consists of incorporating simulation using agent-based computational economics

modeling (Tesfatsion, 2006), growth curve modeling using hierarchical linear modeling

(Raudenbush & Bryk, 2002), and survival analysis using a Cox proportional hazard regression

model (Cox, 1972). Agent-based modeling is used to ensure and to understand how a new firm

changes its capital structure over time. The simulation model serves two purposes. First, the

developed simulation model ensures consistency of the developed hypotheses. Second, the

resulting simulation model is run numerous times to compare the resulting trends with actual

data. Doing so helps to confirm or disconfirm the simulation model.

       Data from the Kauffman Firm Survey (KFS) will be used to examine the use of credit

sources and debt over a six year period starting from the first year of a firm’s existence while

controlling for various factors that could affect the firm’s capital structure decisions, including

the characteristics of the founders. Using a growth curve modeling method, I measure how the




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change of credit source usage affects the change in debt usage over time for a firm. Thus,

meaningful data was not be lost but is analyzed properly in a dynamic fashion.

       In growth curve modeling, longitudinal data are modeled from variables that describe a

mean trend for the population while allowing for between firm differences (T. E. Duncan, S. C.

Duncan, & Strycker, 2006). Growth curve modeling provides several advantages over cross

sectional methods when analyzing trends, including flexibility, practicality, and its robustness to

model development processes and outcomes of change (Muthen, 1991). Growth curve modeling

is able to capture important changes in variables over time that allows the researcher to study the

development at the aggregate level of firms (i.e. young firms), while also capturing individual

firm differences in levels and trends over time (Muthen & Curran, 1997).

       Multiple models will be run using variables in the KFS dataset, including related

financing variables (e.g. debt, equity), performance and size variables (e.g. revenue, profit,

assets), predictor variables (e.g. founding team size, work experience, and education), and

control variables (e.g. level of firm technology, product / service, credit score, race, gender).

Along with primary models that were used for testing the hypotheses, additional models were

run to try to ensure the robustness of the analysis.

       Primary data collected via interviews with a sample of founders and entrepreneurs of new

firms will be performed to focus on answering why new firms use multiple credit sources. The

data will be used for multiple purposes. First, the data will be used to test the hypotheses

associated with answering the question why new firms use multiple credit sources. Second, the

data from the interviews will be used to verify and validate the inputs and configuration of the

simulation model. In addition, follow-up interviews with founders and entrepreneurs from the

same sample as the initial interviews will be conducted after performing the statistical analysis

and obtaining the general trend of the outcome from the simulation model. Performing such


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interviews will serve the purpose of obtaining explanations for possible outlier results or

contradicting findings. The founders and entrepreneurs that will be interviewed will have similar

characteristics to the respondents of the KFS data set. Thus, the sampling frame used to identify

possible respondents will need to correspond to the KFS data set demographics.

       As part of the analysis, initial settings based upon the KFS data will be inputted into the

simulation model. Numerous runs will be performed to obtain a general trend of the results.

These outcomes will be a result of the model that is developed in the theory development stage

of the study, and will show how the factors in the model interact to arrive at a general trend in

the outcome. The general trend will then be compared to the results in the KFS data and be

interpreted accordingly.

       The dissertation will contribute to academic research, entrepreneurs, and policy makers.

Understanding the financing decisions and whether financing decisions have an impact on

survival and growth of new firms has important economic implications for a variety of

stakeholders. As such, the contribution of this dissertation is relevant to researchers,

entrepreneurs, and policy makers. This study is longitudinal and offers a dynamic view of new

firms, which is important in entrepreneurship research since new firms change rapidly

(Davidsson, Low, & Wright, 2001; Low & Macmillan, 1988). From a researcher’s perspective,

it is novel to model the use of alternative credit sources over time for new firms. Doing so will

help us better understand the financing decisions of new firms over time. This is important

because the financing of new firms changes rapidly and past research has missed this change and

only examined the results of the change using static methods (e.g. Astebro & Bernhardt, 2003;

Berger & Udell, 1995; Danielson & Scott, 2004; Huyghebaert, 2006; Huyghebaert et al., 2007;

Peterson & Rajan, 1997; Robb & Robinson, 2008). However, how a new firm attains its capital

structure is important to understand. By performing the analysis in a longitudinal fashion and


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Credit Sources, Founder, and New Firms                                                       2011-01

confirming it with a simulation model, a dynamic view of debt usage will be observed. The code

from the resulting simulation model will be made available in the public domain so researchers

can test the assumptions of the model and make changes to the assumptions to determine how the

outcomes change. It will be helpful for entrepreneurs to know if it is helpful to seek and/or use

multiple alternative credit sources to improve their firms’ chance of survival and to grow the

firm. It will help to know if entrepreneurs are setting themselves up for failure when they use

multiple credit sources or does the use of multiple credit sources help the survival and/or growth

of their new firm. Policy makers will be interested in this aspect as they will learn how

entrepreneurs persist and determine if making available additional and multiple credit source

options help firms survive and/or grow. Alternatively, policy makers will learn if providing

additional credit options prolong the inevitable closure of the firm and leave entrepreneurs with a

heavier debt load personally.

       I proceed in this dissertation by first explaining the theoretical framework which is used

to develop testable hypotheses. Then, I discuss the sample which is used to test my hypotheses,

the methods used to analyze the data, and the results from the analysis. I conclude the

dissertation with a discussion of the results, the limitations of the data and analysis, and suggest

further research areas to pursue based upon the findings.

2. THEORY DEVELOPMENT

       The purpose of this study is to examine the effects of using multiple credit sources on the

growth and survival of new firms, and what factors of the founders affect the use of multiple

credit sources. However, before examining the effect of using multiple credit sources on new

firm survival and growth, I build the theoretical argument of new firms using multiple credit

sources. So I first look at the theoretical framework that explains why new firms use debt and

subsequently why banks put credit limits on new firms that cause new firms to have to use



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Credit Sources, Founder, and New Firms                                                       2011-01

multiple credit sources as opposed to using one bank loan to fulfill their external financing needs.

By providing this theoretical framework I am then able to explain why new firms use multiple

credit sources to alleviate the problem of banks imposing credit limits on them.

2.1. DEBT FINANCING, USE OF MULTIPLE CREDIT SOURCES, AND AMOUNT OF DEBT

       New firms require external funds, either from the founders, external creditors, or external

equity investors (Blanchflower & Oswald, 1998; Evans & Jovanovic, 1989; Holtz-Eakin,

Joulfaian, & Rosen, 1994; Lindh & Ohlsson, 1996). Even though firms’ capital structure

decisions are not completely understood, there are several theories that explain the widespread

use of debt financing. Two of the main theories in capital structure are the pecking order theory

and the static trade-off theory (also known as the optimal capital structure theory). The static

trade-off theory assumes that firms try to balance interest tax shields with the costs of financial

distress (Modigliani & Miller, 1958, 1963). New firms usually do not show a profit, so there is

no tax shield available to them; hence debt is at a disadvantage to them, relative to profitable

firms. As well, new firms usually do not have internally generated funds and hence require

external financing. This would suggest the static trade-off theory does not fit into the context of

new firms.

       In contrast, the pecking order theory is based upon information asymmetry between firms

and external financiers. Information asymmetry arises from insiders being more informed than

outsiders of firms since the insiders have access to information about the activities and situation

of the firm (Williamson, 1975). Since new firms often require outsiders, external financers, to

help finance the operations, information asymmetry is prevalent in new firms. It can be argued

that information asymmetry is more prevalent in new firms than in established small and large

firms due to less information about new firms. The new firms lack of track records and have less

resources available to signal to the market the quality of the firm to outsiders (Chiang &



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Venkatesh, 1988; Diamond & Verrecchia, 1991). Thus, it would seem that the pecking order

theory fits into the new firm context since it is based on the assumption of information

asymmetry.

       The pecking order theory suggests that there is an orderly priority that managers, as well

as entrepreneurs, will follow to determine what type of financing to use for their firm (Myers,

1984; Myers & Majluf, 1984). This theory says that internal funding is used first (i.e. retained

earnings), followed by debt, and then by equity. The logic behind this order of funding sources is

based upon information asymmetry issues arising from the principal-agent relationship between

the lender and the new firm. When a firm uses its own funds to finance its operations there is no

information asymmetry problem because the principal and the agent are the same entity: the

firm. If the firm uses external funding, either via debt or equity, there is a chance that the firm

will not be able to convince these external fund providers that it will be profitable and be able to

service its debt. Between debt and external equity, debt has less prevalent information

asymmetry issues than equity since there are more contractual terms and structure in debt

facilities (along with penalties) than equity has in investor agreements (Myers, 1984; Myers &

Majluf, 1984). With external financiers wanting to minimize the information asymmetry issue,

this would support that new firms will be able to obtain external debt before being able to obtain

external equity.

       Even though it fits well into the new firm context, most research on the pecking order

theory has been on large and small, established firms. Some researchers have sought to establish

whether the pecking order hypothesis applies to small firms (e.g. Berggren, Olofsson, & Silver,

2000; Cassar & Holmes, 2003; Chittenden, Hall, & Hutchinson, 1996; Holmes & Kent, 1991;

Howorth, 2001; Norton, 1991). Not much research has been done on new firms concerning their

use of pecking order factors when making financing decisions. However, the pecking order


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theory should hold with new firms as well. First, the issue of information asymmetry, which

underpins the pecking order theory, is particularly acute in new firms as explained earlier.

Second, given that the desire to be one’s own boss can be an important motivation behind

starting a business (Caird, 1991; Hisrich, 1986), many entrepreneurs exhibit strong preferences

for those financing options that minimize the intrusion of others into their businesses (Ang,

1992; Holmes & Kent, 1991; Tucker & Lean, 2003). Third, entrepreneurs tend to be overly

optimistic about their chances of succeeding in the business, and thus tend to use debt because

they do not want to share the upside with investors (Landier & Thesmar, 2009). This is

supported by Berger & Udell (1995, 1998) and Bates (1997) who find that the main source of

debt for small firms is loans from banks. However, the ability of entrepreneurs to obtain debt

financing may be constrained when they are unable to offer sufficient security. The problem is

exacerbated with new firms since most banks value asset-backed collateral to ensure the loan is

covered (Stanworth & Gray, 1991).

       Even though banks tend to be the largest provider of credit to new firms (Bates, 1997;

Berger & Udell, 1995, 1998), new firms still feel constrained financially. In a perfect capital

market with no taxes, all firms should be able to find the funds to invest in positive net present

value projects (Fazzari, Hubbard, & B. Petersen, 1988). Such a capital market assumes that

information is symmetrical; meaning that the financier and borrower have the same information

about the potential of the firm. However, information is not symmetric in the relationship

between the banker and a new firm as mentioned in the discussion about the pecking order

theory. Thus, banks cannot easily identify a good entrepreneur from a bad entrepreneur, nor a

good project from a bad project. This suggests that good entrepreneurs may not be able to easily

access external funds even when the new firm is a positive net present value project. Due to

credit rationing, banks can easily be barriers for new firms that could be successful if they were


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Credit Sources, Founder, and New Firms                                                          2011-01

provided the funds that they need, and thus there is a possible failure in the financial markets for

new firms.

         New firms usually start small (Audretsch & Mahmood, 1995; Birley, 1987), with only a

minority that grow to any substantial size (Acs, Arenius, Hay, & Minniti, 2005; Reynolds, 2007).

Small, new firms differ from large firms because they do not have a track record, do not have

internal generated funds from operations, and usually have very few resources on the balance

sheet.

         Reputation, length of relationship, and signaling dominate the literature on the

relationship between firms and banks. The better reputation the firm has, the better signaling the

firm can provide the bank, and the longer relationship the firm has with the bank tends to lead to

better access to credit from the bank and at lower interest rates (Boot & Thakor, 1994; M. A.

Petersen & Rajan, 1994, 1995). Banks acquire information about the firm over the course of the

relationship. They use this information to set contractual terms (Berger & Udell, 1995). Loan

interest rates tend to decrease as the relationship matures between the bank and the borrowing

firm (M. A. Petersen & Rajan, 1995). As well, the collateral requirements on loans will be lower

the longer the relationship between the bank and the borrower (Boot & Thakor, 1994).

         Unlike established firm, new firms can not use reputation and length of reputation. They

might be able to use signaling indirectly from founders. New firms do not have an established

reputation or an established relationship with banks as they are new. The founder(s) might have

a relationship with the bank but that reputation is separate from the reputation of the firm.

Founders might signal to banks the quality of the firm by using their personal assets as collateral

to secure loans from the firm. However, the founder(s) personal collateral is usually less than

what the new firm requires as new firms are usually under capitalized (Evans & Jovanovic, 1989;

Evans & Leighton, 1989).


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Credit Sources, Founder, and New Firms                                                          2011-01

        Even though one bank might put a limit on credit provided to a new firm, the new firm

could possibly approach additional banks to obtain the additional debt financing. Additional

banks would imply that there is competition amongst banks to compete to provide funding to

new firms. Competition amongst banks to provide loans to firms is beneficial for new firms for

several reasons. First, it possibly helps lower the interest rate that banks charge new firms. This

is simply a function of supply and demand. The more supply of funds that is available in the

market relative to demand, the lower the price (interest rate) will be. In addition, superior

information enables a single bank to extract excessive rents from the firm through future loans

with the firm. Competition from additional credit sources eliminates these excessive rents

(Rajan, 1992; Sharpe, 1990). Second, more supply from multiple banks mean that there might

be a surplus of money, which would increase the odds of firms receiving funds as banks would

require less of a return on their loan. The result is both the possibility of a lower interest rate as

well as an increase in the probability of being funded as the banks have lowered the threshold for

approving a loan for a firm. This finding is supported by Thakor (1996), who finds that firms

seeking financing from multiple banks reduce the chance of being denied credit – as long as the

firms limit their search to just a few banks. This would suggest that it is in the best interest for

new firms to use multiple banks to provide them debt.

        As shown above, it may not be optimal for a firm to rely on a single bank relationship.

Thus, one would suspect that new firms would use multiple banks for their debt financing.

However, small firms often use only a single bank to obtain a bank loan as opposed to obtaining

multiple bank loans from multiple banks (M. A. Petersen & Rajan, 1995). It could be that banks,

through various means, limit firms to a single banking relationship. In doing, banks might be

rationing credit to firms that require additional debt to operate.




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Credit Sources, Founder, and New Firms                                                        2011-01

       Credit rationing should not be evident in efficient financial markets, even when a project

is a high risk. Some suggest that a banker should raise interest rates to cover for higher risk, and

thus allow a borrower to obtain as large a loan as they wish (Miller, 1962). Assuming a bank can

raise interest rates and not lose business because competing banks keep their interest rate lower,

the banker could cover their risk by increasing the interest rate and allowing the risky borrower

to take out as large a loan as the borrower is willing to. However, this strategy does not work for

profit-maximizing bankers since the borrower can default on their loan and lose only their

collateral. So if the loan is higher than the value of collateral the bank loses the difference

between the loan amount and the value of the collateral. Thus, the bank does not loan more than

the value of the collateral even when the project is a positive net present value project. Therefore

the banker who maximizes the expected profit on a loan will ration credit when the borrower

needs more money than the borrower has in collateral (Freimer & Gordon, 1965). The collateral

requirement is also confirmed by studies that find riskier borrowers can borrow more on a

secured basis than on an unsecured basis (Klapper, 2001). In addition, a higher interest rate can

distort the entrepreneur's incentives and persuade them to choose the risky project. This means

that adverse selection can lead to moral hazard that in turn can lead to credit rationing (Stiglitz &

Weiss, 1981).

       Most of the past literature assumes one source of credit, namely a bank. Then the

literature that does distinguish different credit sources categorizes the debt in ways such as

outside and inside debt, and formal and informal debt. However, in reality there are multiple

types of credit sources. Just like with equity sources, credit sources are different. Different

types of credit sources use different contracting mechanisms and possibly have different motives

for financing a new firm (Cassar, 2004). Entrepreneurs can obtain equity funds by mortgaging




                                               Page 20
Credit Sources, Founder, and New Firms                                                      2011-01

personal assets like a house or car, borrowing from friends or relatives, a personal bank loan, or

credit cards (Roberts & Stevenson, 1992).

       Lines of Credit. Another option is a line of credit, which is similar to a bank loan and is

usually provided by banks (Berger & Udell, 1995). Lines of credit represent a forward

commitment to provide working capital financing under predetermined terms. As opposed to

bank loans, these predetermined terms are easier to adjust, and in many cases are adjusted on a

scheduled basis by the financial institution that is providing the line of credit.

       Lines of credit may be extended as either secured or unsecured. Lines of credit that are

secured by accounts receivables are a form of inside collateral. These lines of credit are repaid

from previously generated and observed sales, which is based upon the trade credit that the

borrower has provided their customers. As such, lenders that use account receivables as a means

to secure the amount lent to borrowers care more about the ability of the borrower’s customer to

pay than the borrower’s ability to continue to generate new sales (Klapper, 2001).

       Trade Credit. The role of trade credit in a firm’s capital structure is depending on if the

firm can pay off the outstanding balances with suppliers within the discount period. If the firm is

able to make timely payments to the suppliers, then trade credit can be a complement to bank

loans. However, if the firm can not pay off the outstanding balances with suppliers, then trade

credit can be an expensive source of funding and would be a substitute for bank loans (Danielson

& Scott, 2004).

       Initially trade credit was thought to be used as a means for suppliers to secure more sales.

It has since been found that supply and demand both affect the use of trade credit. Trade credit

has been said to be used by new firms as an alternative to bank debt. This is the case since new

firms have no established relationships with banks and other firms, including suppliers.

Huyghebaert (2006) found support for this when she found new firms use trade credit more when


                                               Page 21
Credit Sources, Founder, and New Firms                                                       2011-01

financial constraints are large. Basically her results suggest that financial constraints increase

trade credit use. As well, she found that that when ownership is highly concentrated with the

entrepreneurs, that firms borrow more from their suppliers. Suppliers tend to be more lenient

towards firms in financial distress.

         M. A. Petersen & Rajan (1997) found a decrease in the length of banking relationship

resulted in an increase in trade credit used.

         Credit Cards. It has been suggested the credit cards are an option increasing access to

funds when banks limit credit on the loans to the firm (Danielson & Scott, 2004). Sergey Brin

and Larry Page started Google by charging $x on their credit cards to buy servers with terabytes

of storage. Then they received $100,000 equity investment from an individual, who happened to

be a venture capital. After that, they received funds from venture capital firms. And the rest is

history, with their IPO being done on xxxx (date). The firm is now valued at $xxxx (as of xxxxx

date).

         Personal vs Business. If finance-based theories are correct, credit sources should not

mean anything for firms, including new firms. It should not make a difference where the money

comes from, but only the amount that can be borrowed and the actual cost of that debt.

However, most of the research in finance is based on established firms, namely large established

firms. In these large established firms the owners and managers tend to be separate from one

another. As well, there are assets on the balance sheet and financial and operational history

which to base future decisions on. New firms are different than established firms. New firms do

not have a financial or operational track record, nor do we see owners and managers separate

from one another. Thus, the personal collateral of the owner-managers tends to be used to have

access to debt for the new firm. It could be that new firms use personal debt to get initial debt or

to access additional debt since banks have limited the firm from borrowing additional amounts.


                                                Page 22
Credit Sources, Founder, and New Firms                                                        2011-01

Established firms usually do not have an issue with personal debt, especially large established

firms, since such firms have an identity separate from the owners. As well, potential investors

would take debt rather than equity to shield some of their losses. And these investors feel more

comfortable in having the person take the debt. They cannot invest in equity in a person, just in

an organization. And since there is business debt, it could still be considered personal since the

founders have to use their own personal collateral to collateralize the business debt.

       Entrepreneurs try to do several things to obtain financing to show to lenders that their

project / firm is less risky (Roberts & Stevenson, 1992). One, the entrepreneur uses personal

collateral to secure the loan. Two, entrepreneurs promise to pay the money back in a shorter

period of time, thus enabling the investor to evaluate the health of the firm over a shorter period

of time and to be able to reevaluate the firm after it has a track record. Three, use strict covenants

in the debt agreements.

       Personal debt provides additional access to debt because it is outside financing; whereas,

additional business debt is inside financing. Thus, if the firm is able to have their founders

borrow funds for the purpose of the firm, it should increase the amount of debt the firm is able to

access, which also increases the number of credit sources used for the purpose of the firm. As

well, investors interested in investing in the new firm might be more wiling to provide a loan to

the business as opposed to provide funds via equity to the business since debt has a lower risk of

losing all of the investor’s funds. This is the case because debt holders have a claim on the firm’s

collateral. As well, the potential investor might be willing to loan more to the founders on a

personal level since the firm does not have collateral on their balance sheet and the founder does

as assets which they can use for collateral. As well, the investor might trust the founder as

opposed to the firm. There are less moving parts with the person than with the firm, and more




                                               Page 23
Credit Sources, Founder, and New Firms                                                        2011-01

things the founder can control personally as opposed to the firm which has multiple stakeholders

involved.

       A large amount of bank loans to small businesses are collateralized (Berger & Udell,

1995). Collateral can come from the firm’s balance sheet or from outside of the firm. As such, a

distinction can be made between debt that is provided from inside or outside the firm. Debt that

is from inside the firm tends to use the firm’s collateral to obtain the debt. Debt that is from

outside the firm tends to use individual borrower’s collateral to obtain the debt for the firm.

These individuals are namely the owner of the firm, in which they pledge their own personal

collateral to obtain the debt. Inside debt changes the priority of the claims of the creditors,

whereas outside debt produces additional assets for secured creditors to claim. These additional

assets which secured creditors can claim are from the individual’s own assets.

       Capital structure decisions are context specific. Just as new firms make different

financing decisions than do established firms (Harris & Raviv, 1991), the decision of level and

composition of debt are made at the same time (Huyghebaert & Van de Gucht, 2007). This

suggests that firms think about the source of debt when deciding how much debt they should use.

If this is the case, then we should see a relationship between the number of credit sources used

by new firms and the amount of debt by new firms.

       When making financing decisions, new firms take into account both the level and

composition of debt at the same time (Huyghebaert & Van de Gucht, 2007). Different types of

credit sources represent different types of debt, which are reflected in a firm’s composition of

debt. This suggests that new firms think about the source of credit when deciding how much

debt they need. If this is the case, then we should see a relationship between the number of

credit sources used by new firms and the amount of debt by new firms both initially and over

time. We should see that during the first year of operations new firms have access to and use


                                               Page 24
Credit Sources, Founder, and New Firms                                                       2011-01

multiple credit sources as a means of obtaining additional funds that banks will not provide them.

If banks impose credit limits on new firms, these new firms would use these additional credit

sources. They would look at these additional credit sources before tapping into equity based on

the premise of the pecking order theory. Thus, we hypothesize the following:

       Hypothesis 1: The number of credit sources used increases over time during their early

       years of the firm’s existence

       If new firms are able to access multiple credit sources during their early years of

existence, and since firms usually require more resources as they grow, emerge, and mature

(Aldrich & Ruef, 2006; Greiner, 1972), it would be logical that new firms would continue to

utilize more credit sources as they come available over time for the purpose of obtaining

additional funds as the firm ages. Over time, new firms start to mature and show assets on the

balance sheet which they can borrow against (Berger & Udell, 1998). This provides new firms

possible access to more bank loan debt. However, new firms, which are usually small, tend to

not use multiple bank loans (M. A. Petersen & Rajan, 1995). With banks possibly rationing

credit (Stiglitz & Weiss, 1981), new firms have to look elsewhere for adequate amounts of funds.

Firms will try to exhaust their debt options first before tapping into equity options (Myers, 1984;

Myers & Majluf, 1984). This would suggest that as new firms age they start to leverage their

relationships with multiple credit sources, not just banks. New firms can leverage the positive

signal of a bank loan to obtain more debt from multiple credit sources since banks produce

valuable information about new firms (e.g. James, 1987; Lummer & McConnell, 1989; Shockley

& Thakor, 1997). Thus, we hypothesize the following:

       Hypothesis 2: The amount of debt used increases over time during their early years of the

       firm’s existence




                                              Page 25
Credit Sources, Founder, and New Firms                                                       2011-01

       These credit sources might not communicate with one another. The new firm’s financial

statements are the only common mode of communication that the multiple credit sources have.

Thus, there is an increased information asymmetry between the credit sources as the financial

statements do not provide a large amount of information which the credit sources can

communicate with one another. Thus, by having multiple credit sources, the new firm can

increase their debt levels as opposed to using one credit source to increase their usage of debt.

This results in more credit sources being used along with more debt used by new firms over time.

Thus, we hypothesize the following:

       Hypothesis 3: An increase in the growth rate of the number of credit sources used over

       time increases the growth rate of the amount of debt used over time during the early

       years of the firm’s existence

2.2. MULTIPLE CREDIT SOURCES AND FOUNDING TEAM CHARACTERISTICS

       New firms are based around and highly dependent upon the founder or founding team

members. Since new firms are inherently small they usually have limited resources, and thus the

characteristics of these individuals (founders) tend to be representative of the nature of the firm

initially. Along with being small, new firms do not have a track record as they do not have any

operational or financial history, which puts even more importance on the resources of the

founders.

       Founders bring with them characteristics that are not easily detached from the firm they

are starting. These characteristics include their education and work experience. These elements

of human capital of the founders, since they are not easily detached from the firm, can cause

banks not to lend to them or at least change the terms of the bank loans (Hart and Moore, 1994).

Also since firms cannot use the full value of their future returns as backing to their financial

claims (Diamond, 1990, 1991a, 1991b), new firms require outside collateral and debt. Thus it is



                                               Page 26
Credit Sources, Founder, and New Firms                                                         2011-01

important to look at the characteristic of the founders when looking at alternative credit sources,

including outside debt sources.

        Entrepreneurship research has suggested that founding teams, more education, and more

work experience improves the success of new firms. The entrepreneurship research has

suggested that companies started by founding teams, as opposed to a single entrepreneur, are

more successful. The reason is because multiple founders can compliment each other’s skills.

As well, when things get rough in the business each founding team can pull up the other

founding team psychologically. In addition, the entrepreneurship research has suggested that the

education level of founders is important in determining if new firms will be successful. The

studies suggest that the more educated a founder or the founders are the better chance of survival

for the firm. Then findings from entrepreneurship research also suggest that prior work

experience of the founders is important in determining if new firms will be successful, especially

work experience in the industry that the new firm will operate in. They suggest that the more

work experience a founder or the founders have, the better chance of survival for the firm.

        The success (or lack of success) of the firm will affect the funding needs of the firm. If

the firm is able to generate positive cash flow due to its success, then the firm can use retained

earnings (i.e. internal funds) to fund future operations. If the firm is growing too quickly, then

they will need to obtain funds externally. Or they might want to recapitalize. In many cases,

firms are started by founders providing personal collateral to get the funds via debt that they need

to start the firm. Then once the firm is on its feet, and the firm has tangible assets on its balance

sheet, then the firm can consolidate their debt as well as transfer the debt from the personal to the

firm.

        As well, it has been said that building a relationship with a bank will allow easier access

to funds, and lower interest rates possibly.


                                               Page 27
Credit Sources, Founder, and New Firms                                                         2011-01

2.2.1. SIZE OF FOUNDING TEAM

       Even though much of the entrepreneurship literature looks at individual entrepreneurs,

starting a business is generally a collaborative activity involving several partners (Gartner,

Shaver, Gatewood, and Katz, 1994). The founding teams provide a venture with access to a

wider array of human capital, social, and financial resources (Ucbasaran, Lockett, Wright, and

Westhead, 2003). So it would be logical that a team of individuals starting a new venture will

have more valuable resources than a single individual founder (Kor and Mahoney, 2000). This is

supported in social networking theory where founding teams have stronger networks than

individual entrepreneurs (xx), with the weak ties being the most beneficial to the firm (Burt,

1995; Granovetter, 1973). External financiers are considered weak ties in many cases. Larger

founding teams will have more access to external financiers as opposed to individual

entrepreneurs. Thus it is hypothesized that firm with a larger number of founders will be able to

access more credit sources.

       Since lenders require collateral from individuals, and not from the firm (as well the firm

doesn’t have a track record nor many assets in many cases), a larger number of individuals can

lend more. So the larger the founding team, the more chance the firm can get started by

borrowing money from more credit sources.

       Thus, I hypothesize the following:

       Hypothesis 3a: The number of founders is positively associated with the initial number of

       non-bank credit sources used by new firms

       As firms start to generate revenue and accumulate assets, the firm beings to have a track

record. The firm is trying to grow or stabilize itself. If the firm is trying to grow then it will

most likely require more funds. Additional credit sources can be used to acquire more funds.

AS well, some firms might want to stabilize their operations and move debt from their founder’s



                                               Page 28
Credit Sources, Founder, and New Firms                                                      2011-01

personal accounts to the business account. With the firms able to borrow using its own balance

sheet, and presumably can borrow more than what the individual founders could borrow, the

amount of debt per credit sources should decrease. The founders can start to take the debt

burden off them personally and put it in the business. The lenders can also take a chance of

lending the business more. So the trend of the number of credit sources used will not be

dependent on the size of the founding team.

       Thus, I hypothesize the following:

       Hypothesis 3b: The number of founders will not affect the change in the number of non-

       bank credit sources used by new firms over time

2.2.2. EDUCATION OF THE FOUNDERS

       Higher educated entrepreneurs receive more credit (Astebro and Bernhardt, 2003; Parker

and van Praag, 2006). Banks will lend more to founders that have a higher education level. Look

at the CV of two founders, and the one that has a higher level of education, all else being equal,

will have a better probability of obtaining the funding. [ add a social networking theory

argument in here ]


       Each additional year of schooling decreases capital commitments (Parker and van Praag,

2006). Thus firms founded by more educated persons should see a higher initial level of debt

usage than firms founded by less educated persons.


       Hypothesis 4a: The average level of education of the founders is positively associated

       with the initial number of non-bank credit sources used by new firms

       Hypothesis 4b: The average level of education of the founders is negatively associated

       with the decline in the number of non-bank credit sources used by new firms over time




                                              Page 29
Credit Sources, Founder, and New Firms                                                    2011-01

2.2. 3. WORK EXPERIENCE OF THE FOUNDERS

       Banks will lend more to founders that have more work experience in the industry of the

business. If a banker had a choice between a founder with no work experience and a founder

with twenty years of work experience, the banker will most likely choose the founder with

twenty years of work experience. Again, there might be a threshold where an additional year will

not add value. For example, when looking at older persons, one might not think that they can use

computers. So even though they have more experience in that industry, their knowledge might

hinder them from seeing the change in the industry. For example a person that has been in the

computer industry for 30 years might not be up to speed on the Internet technology as someone

that has 10 years of experience in the computer industry. The work experience of the founding

team members exposes the firm to a network of employees, customers, suppliers, as well as

financiers (Campbell, 1992).


       Hypothesis 5a: The average number of years of prior work experience in the industry by

       the founders is positively associated with the initial number of credit sources used by new

       firms

       Hypothesis 5b: The average number of years of prior work experience in the industry by

       the founders is negatively associated with the decline in the number of credit sources

       number of credit sources used by new firms over time initially

2.3 SURVIVAL

       Banks tend to be unique from other credit sources (Diamond, 1984, 1991; Fama, 1985;

Ramakrishnan & Thakor, 1984), and the bank loan market tends to differ from other debt

markets (Carey, Prowse, Rea, & Udell, 1993). Banks are financial intermediaries that exist

because they enjoy economies of scale and comparative advantages in the production of

information about borrowers, namely for borrowers with high information asymmetries


                                             Page 30
Credit Sources, Founder, and New Firms                                                      2011-01

(Diamond, 1984, 1991; Fama, 1985; Ramakrishnan & Thakor, 1984). When costly information

asymmetries exist between external financiers and firm insiders, a bank becomes the optimal

financial institution for channeling funds from savers to borrowers (Diamond, 1984). Banks tend

to be better at monitoring and handling information asymmetry issues as compared to non-bank

institutions. Other credit sources have not developed the tools in as much detail as banks and

thus have less sophisticated means of obtaining information from and monitoring of new firms to

be able to determine if new firms are able to service their debt. This would mean that banks are

rational in their reasons for not lending additional money to new firms when the new firms are

asking for additional funds. Therefore, with new firms that acquire additional funds from

multiple credit sources to overcome credit limits imposed by banks, the survival rate should be

higher if banks are more rational than other credit sources. Thus, we hypothesize the following:

       Hypothesis 4: New firms that obtain additional debt through additional credit sources

       have a lower survival rate

2.4 GROWTH

       …

       Hypothesis 5: New firms that obtain additional debt through additional credit sources

       have a lower growth rate

3. RESEARCH METHOD

3.1. DATA

       Data used for this study were from the private version of the data from the Kauffman

Firm Survey (KFS), which is a longitudinal survey conducted by the Ewing Marion Kauffman

Foundation. 32,469 firms were randomly sampled from Dun and Bradstreet’s database of all

firms started in 2004 in the United States to achieve a sample set of 4,928 firms (Robb et al.,

2010). The sample excluded non-profit firms, firms owned by existing firms, and firms inherited



                                              Page 31
Credit Sources, Founder, and New Firms                                                                      2011-01

from another individual. The KFS research team initially interviewed founders of the 4,928

firms between July 2005 and July 2006, representing a response rate of 43% from the original

sampling frame after the sampling weights were applied (Ballou et al., 2007). These firms were

then interviewed on an annual basis thereafter. This study uses data through 2008, which is the

latest data available at the time of this study.

         In this paper, we are trying to determining what entrepreneurs do when banks put credit

limits on them. So we only look at firms that received bank loans initially. Thus, we only

include in the data set the firms that were able to obtain and actually take out a bank loan in their

first year of operations. This enables us to test for Type I credit rationing which occurs when a

part of the borrowers receive less than they need or desire1 (Keeton, 1979; Parker, 2009). By

examining only firms that receive bank loans the first year, we can determine if these firms

obtain additional debt from the same number of banks, receive bank loans from additional banks,

or if they receive additional debt from other credit sources.

         Firms that closed were removed from the data set. There were 1,294 firms that closed

between 2004 and 2008. These firms were removed from the sample as all the fields need to be

answered through the 2008 survey. If a firm went out of business, they were not able to provide

answers for questions in every year of the survey. Therefore, there was missing data for these

firms in the sample which justified the removal of these firms. Of the 3,634 firms that survived

through 2008, 395 firms took out a bank loan in the first year. Then firms that did not provide

answers to all the credit source usage and debt questions for all five years were removed from

the sample. This resulted in removing 23 firms due to missing data. In addition, 5 outliers were

removed based upon unrealistic levels of use for credit sources (e.g. # of credit sources greater



1
  There are two types of credit rationing. Type I credit rationing is explained in the text above. Type II credit
rationing occurs when borrowers are denied a loan at random altogether despite being identical in characteristics to
other borrowers.

                                                      Page 32
Credit Sources, Founder, and New Firms                                                      2011-01

than 50). This left 367 firms that provided valid responses and which could be used in the

growth model analysis. Table 1 shows the data sample reduction.

                                 ―――――――――――――

                                     Table 1 goes about here

                                 ―――――――――――――

3.2. ANALYSIS

       To test the three hypotheses, multiple growth curve models using structural equations

modeling are used. Hypothesis four is tested using an two-sample (independent) t-test. In

growth curve modeling, longitudinal data are modeled from variables that describe a mean trend

for the population while allowing for between firm differences (Duncan, Duncan, Strycker,

2006). Growth curve modeling provides several advantages over other methods when analyzing

trends, including flexibility, practicality, and its robustness to model development processes and

outcomes of change (Muthen, 1991). Growth curve modeling is able to capture important

changes in variables over time that allows the researcher to study the development at the

aggregate level of firms (i.e. young firms), while also capturing individual firm differences in

levels and trends over time (Muthen & Curran, 1997). Growth curve models can be used to

model growth as a factor of repeated observations of a single variable, as well as with multiple

variables. It is possible to use growth curve modeling to determine whether development in one

variable covaries with the development of another variable (T. E. Duncan et al., 2006). Such

models are considered multivariate growth curve model, which are models depicting two trends

affecting one another. These models provide a more dynamic view of the correlates of change as

compared to a univariate growth curve model or cross-sectional studies which both offer static

views of the data (T. E. Duncan et al., 2006; Muthen, 1991; Muthen & Curran, 1997).




                                              Page 33
Credit Sources, Founder, and New Firms                                                         2011-01

Longitudinal studies and dynamic views are important in entrepreneurship research since new

firms are changing rapidly (Davidsson et al., 2001; Low & MacMillan, 1988).

        When analyzing the growth of a variable over time using growth curve models, a sample

size of 200 is strongly recommended so that the estimated model adequately fits the observed

data (Kline, 2005). Since this study has 367 cases, the sample size is more than sufficient for

this analysis.

3.3. VARIABLES

        Number of Credit Sources Used. The first variable being examined over time in the

growth curve model is the number of credit sources a firm uses during its first five years. Since

all firms in the sample started in 2004, it can be interpreted that the debt usage is from the first

year of the firm’s existence. There were 11 questions in the survey that asked the respondents

about the number of different credit sources their firm used. The different types of credit sources

included loans from commercial banks, non-financial institutions, government agencies, family

members, owners, employees, and other business and individuals (i.e. friends or angel investors).

As well, credit sources included credit cards and lines of credit. The credit sources included only

debt in the name of the business. Table 2 shows the credit source options. All of the credit

source option variables were then added together to calculate the total number of different types

of debt financing options a firm used in a given year. The number of credit sources used by each

firm is calculated for each of the years that the survey was administered: 2004 - 2008. The

variable was found to be normally distributed, so no transformation was need. Table 3 shows the

distribution of number of credit sources used broken out by the type of credit source used.

                                  ―――――――――――――

                                      Table 2 goes about here

                                  ―――――――――――――



                                               Page 34
Credit Sources, Founder, and New Firms                                                      2011-01

                                 ―――――――――――――

                                     Table 3 goes about here

                                 ―――――――――――――

       Amount of Debt. The second variable being examined over time in the growth curve

model is the dollar amount of debt that a firm uses during its first five years. This was one

variable for each year that looked at the amount of debt the firm used. Since this variable was

not normally distributed in its native form, this variable was transformed using the natural

logarithmic function. Table 4 shows the distribution of the dollar amount of debt used broken

out by the type of credit source used.

                                 ―――――――――――――

                                     Table 4 goes about here

                                 ―――――――――――――

       Table 5 shows the descriptive statistics and correlations for the variables used in the

growth curve models. The variance inflation factor (VIF) was less than 10 for all the variables

presented in the full model. This suggests that multicollineraty is most likely not an issue with

the variables (Judge, Hill, Griffths, Lutkepohl, and Lee, 1988).

                                 ―――――――――――――

                                     Table 5 goes about here

                                 ―――――――――――――

       Number of Founders. The number of founders for each firm was calculated as the number

of owner-operators in the firm during the first year of the firm’s existence (2004). Using owner-

operators as opposed to owners ensures that investor-only types are not included in the number

of founders. The number of founders ranged from 1 to 10, with the average being 1.43. Most of

the firms had a single founder (67.8%). Even new firms have at least one founder. So zero is


                                              Page 35
Credit Sources, Founder, and New Firms                                                     2011-01

not meaningful for this variable. Therefore this variable was grand mean centered to provide a

meaningful zero.


       Average Level of Education of Founders. The highest level of education for each founder

in 2004 was reported, ranging from 1 (less than 9th grade) to 10 (professional school or

doctorate). The average level of education of the founders was measured by summing the years

of education of each founder and divided by the total number of founders. This provided a

measure of average education of the founders that could be compared across the firms in the

sample. The average level of education for each firm was 6.22, which is equivalent to an

associate’s degree based upon the scale used in the survey.


                                 ―――――――――――――

                                     Table 4 goes about here

                                 ―――――――――――――

       Average Work Experience of Founders. Each founder in the firm reported the number of

years of work experience in the industry which the firm operated in. Their responses ranged

from 1 to 40+ (more than 40 years) for the lead founder, from 1 to 35+ (more than 35 years) for

the second founder, and from 1 to 25+ (more than 25 years) for the remaining founders. Since

the responses for the different founders had different scales and the work experience variable

was going to be an average of the founder’s education, the individual founder work experience

variables needed to be rescaled to be the same. Thus, the work experience variables were

rescaled to into 6 categories: 0 = 0, 1-5 = 1, 6-10 = 2, 11-15 = 3, 16-20 = 4, 20-24 = 5, and 25+ =

6. After the rescaling, the average work experience of the founders was 2.75, which equates to

the category of 11-15 years of work experience if rounded up to category 3.


                                 ―――――――――――――


                                              Page 36
Credit Sources, Founder, and New Firms                                                        2011-01

                                      Table 5 goes about here

                                  ―――――――――――――

       Descriptive statistics and correlations of the variables are provided in Table 6.


                                  ―――――――――――――

                                      Table 6 goes about here

                                  ―――――――――――――

       Since we are looking at the growth trajectory of credit sources, a graph of the data for

means and a random sample of 16 individual firms were used to see the shape of the individual

firm growth trajectories. This is shown in Figures 2 and 3. As can be seen from looking at these

figures, the growth is non-linear. So when modeling the data, the non-linearity will be taken into

account.


                                  ―――――――――――――

                                      Figure 2 goes about here

                                  ―――――――――――――

                                  ―――――――――――――

                                      Figure 3 goes about here

                                  ―――――――――――――

4. RESULTS

       A series of growth curve models were tested using the software package, LISREL

(Joreskog & Sorbom, 1998). The linear and non-linear conditional growth models of the number

of credit sources (model 1 and model 1a) and debt (model 2 and model 2a) were first tested

separately to determine the viability of the data as it relates to a linear growth curve pattern. In

these models, the intercept represents information concerning the mean and variance of the



                                               Page 37
Credit Sources, Founder, and New Firms                                                        2011-01

collection of individual intercepts for each firm’s growth curve. The basic terms of the intercept

are fixed to 1, while the basic terms of the slope are fixed to 0-4 to represent a linear growth

trend in the number of credit sources and debt used by the firms from 2004 to 2008, with a

quadratic function added to represent a non-linear change (0, 1, 4, 9, 16). All variables have one

indicator per latent variable. As such, there is no confirmatory factor analysis required to ensure

that the indicators measured the latent variables.

       For the credit sources growth model, it was determined that the non-linear estimated

model fit (model 1a) the observed data the best and that the number of credit sources used by

firms in the sample did change over the five years. The model 2 = 7.372 (df = 6) was not

statistically significant (p = 0.288). This suggests an acceptable fit as the observed and estimated

matrices did not differ significantly (Hair, Anderson, Tatham, and Black, 1998). However, in

looking at other measures of overall fit, the root mean square of approximation (RMSEA), a

measure of the discrepancy between observed and estimated covariances adjusted for degrees of

freedom, equaled 0.025. This is acceptable as it is below the cutoff maxim of 0.08 (Hair,

Anderson, Tatham, and Black, 1998). The confirmatory fit index (CFI) was 0.995. This measure

of overall fit compared the estimated model to a null model and values above 0.95 were

considered to be acceptable (Hu and Bentler, 1999). The normed fit index and non-normed fit

index, an overall measure of fit comparing the estimated model to a null model, were acceptable

(NFI = 0.973, NNFI = 0.991) as they were greater than 0.95 (Hair, Anderson, Tatham, and

Black, 1998). The goodness of fit index (GFI = 0.992) and adjusted goodness of fit (AGFI =

0.981) were both acceptable as they were above 0.90 (Sharma, Mukherjee, Kumar, Dillon, 2005;

Tabachnick and Fidell, 2007). Mean levels of credit sources used on the intercept was 1.704 and

statistically significant (t-value = 19.429). The linear portion of the slope was 0.485 and

statistically significant (t-value = 4.494), with the quadratic function of the slope being -0.093


                                               Page 38
Credit Sources, Founder, and New Firms                                                        2011-01

and statistically significant (t-value = -3.304). These results indicate that on average that new

firms used 1.704 credit sources in their first year of existence and that they increased the number

of credit sources over time at a declining rate from 2004 to 2008. Thus, hypothesis 1 is

supported. Variances at the individual firm level was statistically significant for the intercept

(1.129, t-value = 2.283), but was not statistically significant for the linear slope (0.117, t-value =

0.220) and the quadratic function of the slope (-0.018, t-value = -0.539). Thus, suggesting there

was a significant variation among firms in their initial credit source usage (intercept) but not in

their trend (slope and quadratic function) from 2004 to 2008. So the number of credit sources

used in the first year of existence did not affect the number of credit sources used over time.

Figure 1 shows a representation of the growth curve model for the number of credit sources used.

                                  ―――――――――――――

                                      Figure 1 goes about here

                                  ―――――――――――――

                                  ―――――――――――――

                                    Tables 6 and 7 go about here

                                  ―――――――――――――

       As with the credit sources growth model, it was determined that the non-linear growth

model of debt usage (model 2a) fit the observed data the best and that the amount of debt used by

firms in the sample did change over the five years. In this model, the fit was 2 = 5.277, p =

0.509 (df = 6), RMSEA = 0.000, CFI = 1.000, NFI = 0.975, NNFI = 1.005, GFI = 0.996, and

AGFI = 0.989. This suggests an acceptable fit as the observed and estimated matrices did not

differ significantly. Mean levels of debt used on the intercept was 4.967 and statistically

significant (t-value = 11.626). The linear portion of the slope was 1.641 and statistically

significant (t-value = 3.765), with the quadratic function of the slope being -0.338 and


                                               Page 39
Credit Sources, Founder, and New Firms                                                         2011-01

statistically significant (t-value = -3.340). Variances at the individual firm level was not

statistically significant for the intercept (13.831, t-value = 1.608), the slope (2.799, t-value =

0.354), nor the quadratic function of the slope (0.091, t-value = 0.222). These results indicate

that on average there was an increase in debt used from 2004 to 2008. Thus, hypothesis 2 was

supported. There was not a significant variation among firms in their initial debt usage

(intercept), nor their linear slope and the quadratic effect on the slope from 2004 to 2008. Figure

2 shows a representation of the unconditional growth curve model for debt used.

                                  ―――――――――――――

                                      Figure 2 goes about here

                                  ―――――――――――――

The next model tested was a model (model 3) that included both growth trends of credit sources

and debt used. In this model, the fit was 2 = 138.956, p < 0.001 (df = 28), RMSEA = 0.103,

CFI = 0.877, NFI = 0.856, NNFI = 0.803, GFI = 0.931, and AGFI = 0.864. The estimated model

did not fit the data well for this model, which indicates that the trend in the number of credit

sources does not change the trend in the amount of debt. Thus, hypothesis 3 is not supported.

Since the model did not fit the data, the results of the effects of the trend of the number of credit

sources on the trend of debt are not reported.

       To test hypothesis 4, which states that firms that obtain a bank loan in their first year and

then obtain additional debt from additional credit sources will have a lower survival rate, we

performed a two-sample (independent) t-test. The sample included the firms that failed and

which were not included in the growth curve model, but still took out a bank loan within the first

year of operations. The resulting sample size was 462, since there were 90 firms that closed their

operations between 2004 and 2008. The results are mixed depending on if the maximum number

of credit sources is used or if the average number of credit sources is used. There is a statistical


                                                 Page 40
Credit Sources, Founder, and New Firms                                                       2011-01

significance between the means when using the maximum number of credit sources used (t-value

= -2.058, df = 163.055, p = 0.41). However, it is in the opposite direction that we predicted.

New firms that went out of business had a maximum number of credit sources used that was less

than the maximum number of credit sources used by firms that survived on average. When using

the average number of credit sources used to compare the two groups of firms, there is not a

statistical significance between the means when using the average number of credit sources used

(t-value = 1.428, df = 112.376, p = 0.156). The variances are not equal based upon the Levene’s

test of equality of variances. Thus, the statistically figures reported do not assume equality and

therefore report differ degrees of freedom. Table 8 shows the results of the t-test.

                                 ―――――――――――――

                                      Table 8 goes about here

                                 ―――――――――――――

4.1. ROBUSTNESS CHECKS

       These results suggest that new firms use multiple credit sources to alleviate the credit

limits by banks. However, there could be alternative explanations. Since we included the bank

loan debt in the total amount of debt, it could be that new firms are obtaining more funds from

bank loans over time. Thus, we ran a growth curve model that only included the bank loan debt.

The model fit the data well (2 = 8.827, p =0.116, df = 5, RMSEA = 0.454, CFI = 0.710, NFI =

0.539, NNFI = 0.652, GFI = 0.992, and AGFI = 0.984). The results showed that bank loan

amounts do not significantly change over the 5 year period (slope = 0.153, std error = 0.221, t-

value = 0.691). As well, we looked at the number of bank loans used. The model fit the data

well and the results showed that the number of banks loans do not change over time for firms

that had a bank loan in their first year of operations. So this would support the findings that new




                                              Page 41
Credit Sources, Founder, and New Firms                                                      2011-01

firms are not able to obtain more debt via bank loans, but are able to obtain more debt by using

multiple alternative credit sources.

       In the theory development section, we built the argument that founders of new firms

prefer debt over equity supported by the pecking order theory. Another explanation could be that

firms that received a bank loan could signal their quality easier to equity investors and thus be

able to obtain equity as opposed to debt. Investors look to banks to monitor firm cash flows and

thus avoid duplicating the monitoring activities and mitigating the moral hazard problem that

would exist if there were free standing cash for the founders to use inappropriately (Diamond,

1984). Thus we ran a latent growth model to determine if equity changed significantly over the 5

year period for the firms. The results suggest [ … ].

5. DISCUSSION AND CONCLUSION

       If credit rationing by banks was not an issue, we would have expected to have seen in the

results the number of credit sources not change when the amount of debt changed. Or if debt

does not change we would have seen the number of credit sources decrease over time. However,

we see the number of credit sources increase over time along with debt levels increasing. After

performing robustness checks, it would suggest that new firms do use multiple alternative credit

sources to alleviate the credit limits imposed by banks.

       Is it better for firms to use one source or multiple sources? Relying on one funding

source could be risky. If the funding source requires funds to be repaid sooner than planned,

then the firm will have to look for other sources of funding prematurely. As well, more power is

in the lender’s hands. Spreading out the credit sources would spread out the power where not

one source has a large amount of power. Competition between professional credit sources drives

down the interest rates.




                                              Page 42
Credit Sources, Founder, and New Firms                                                          2011-01

        However, multiple relationships could be detrimental to a new firm. Relationships take

time to keep in good standing. New firms have limited resources. An increase in the number of

credit sources over time for new firms requiring additional resources to maintain the relationship.

These multiple credit sources can result in additional funds but multiple create sources could also

over extend the limited resources of new firms. This could lead to a less than optimal usage of

the resources and could lead to firm failure

        From a performance perspective of the firm, we find that using multiple credit sources

impacts the survival rate of new firms. Our results suggest that the use of multiple alternative

credit sources decrease the survival rate of new firms. Therefore, it could be that the bank is in

fact rational in limiting credit to new firms properly as those new firms they limit credit to

eventually fail. By using additional credit sources, the firms just fail at a latter stage than if they

had not received additional debt from additional credit sources. This would suggest that new

firms should cease operations when banks limited credit to them since they are not pursing a

positive net present value project. The bank is doing the new firms a favor to not prolong their

failure. However, entrepreneurs are overly optimistic and persistent. Thus we see the irrational

pursuit of a negative present value project.

        The argument we make in the theory development section is that credit rationing takes

place and that one credit source (i.e. a bank) will not give a new firm all of the funds they need.

Thus, the new firm looks at alternate credit sources to obtain additional funds that the bank

would not provide to the new firm. However, there could be an alternative explanation. It could

be that the bank is willing to provide more funds to the firm and that the new firm does not want

to rely solely on one bank or credit source. They want to distribute the power of the external

financiers and do not want to have one funding source be too powerful. If the one credit source

becomes too powerful then that could possibly result in the one source increasing the interest rate


                                                Page 43
Credit Sources, Founder, and New Firms                                                        2011-01

or calling in the debt. This could increase the new firm’s costs and/or force the firm to shut

down. However, if that is the case we would have seen an increase also in the number of banks

used per firm. When looking at the raw data most firms did not increase the number of banks

they borrowed money from.

         However, multiple banks might not be willing to loan new firms money because there is

not enough room for multiple banks based upon the new firms’ small amount of collateral. Thus,

alternative credit sources could be used to alleviate the credit limits imposed by banks and

possibly provide competition to the bank to keep the interest rates low. More young firms obtain

external financing in concentrated markets than in competitive markets (M. A. Petersen & Rajan,

1995). Competition from the creditors is a factor in if firms get financing from creditors.

Creditors are more likely to finance credit-constrained firms when credit markets are

concentrated. The reason is because these firms can "internalize" the benefits of assisting the

firms.

         There are positive and negative aspects to new firms using multiple credit sources. One

line of reasoning suggests that entrepreneurs will want to get the lowest cost of capital they can

get. In many cases, that would mean that they would go to one source and borrow all of their

money from that source. The lender will give them a lower interest rate because of economies of

scale. However, the main goal for new firms is to survive (Gimeno et al., 1997; Phillips &

Kirchhoff, 1989), thus the new firms do not necessarily focus on improving their cost of capital.

Therefore, interest rates are of less concern. As well, the entrepreneur wants to have to only deal

with one person when they need money and not have to go around to multiple entities to keep

them happy, especially when things go wrong. In addition, using multiple credit sources could

signal to the market place (i.e. lenders) that there is something wrong with the firm.




                                              Page 44
Credit Sources, Founder, and New Firms                                                           2011-01

       Even though multiple sources distribute the power, separating out the credit to too many

sources could result in a negative effect. Higher capital costs could result since the lenders are

not able to capitalize on economies of scale. Economies of scale are important for lenders to

small and new firms since it costs so much to gather information from these firms and because of

the high default risk associated with these firms. Using numerous credit sources could send a

bad signal to the market. The market might think the firm has to use numerous credit sources

since they can not obtain funds from the main credit source. Thus, the market would think the

firm is a high risk. This suggests there is an optimal level of multiple sources to improve the

performance of new firms.

5.1. LIMITATIONS

       As with any study, this study has limitations. One limitation relates to casualty.

Although my data is longitudinal, the credit source – debt model can not convincingly interpret

causality. One prerequisite for interpreting causality is the time order effect. We interpret the

results of the credit source – debt model as the number of credit sources affecting the debt level

change. However, debt level could affect the change of credit sources due to other factors not in

the model, a sign of omitted variable bias.

       Another limitation is that we might not be capturing the new firms that try to get bank

loans in their first year but were turned down even before they could obtain a bank loan. So in

such cases, this would imply that credit was not provided at all to the firms, resulting in Type II

credit rationing. Thus, with this sample we are only able to comment on the results for Type I

credit rationing, where the bank lends only a portion of the amount the firm requires to operate

with. As well, the selected sample does not capture if the entrepreneur turned down a bank loan

because the interest rate was too high or that the covenants were too strict (i.e. requiring a

personal guarantee or collateral).



                                               Page 45
Credit Sources, Founder, and New Firms                                                                      2011-01

         One of the strengths of the study is that controlled for age since all of the firms were from

the same cohort (i.e. started in 2004). However, we only looked at one period which is 2004-

2008. This period could be different than other periods because of economic issues during 2004-

2008. For example, the average interest rate varied from 3.87% to 5.03%2, which is low

historically for the United States within the past 40 years. Since debt is tied to the interest rate, if

the interest rate changes, it could affect the decision made by founders when starting new firms

and their financing decisions and options. Therefore, the sample could be biased to debt since

the interest rates were historically low.

         Common method variance is another possible limitation in my study (P. M. Podsakoff,

MacKenzie, Jeong-Yeon Lee, & N. P. Podsakoff, 2003; P. M. Podsakoff & Organ, 1986).

Intercorrelations between the variables were moderate and ranged from [ xxx to xxx ]. Thus we

can rule out common method variance as a limitation in the study.

         Even with these limitations, the strengths of this study should not be overlooked. First,

this study is a longitudinal study of new firms. There are few longitudinal studies on new firms

in which they are able to examine the change of multiple financial variables. Second, the use of

growth curve modeling to analyze the longitudinal data is appropriate and is a strength of this

study. The results show that the trend the number of credit sources and the trend of debt usage

are both non-linear. Thus would not have been captured if static or cross-sectional analysis was

used. Using growth curve modeling, we were able to examine the long-term changes from an

overall trend point of view. As well, we were able to see the changes to the […].

         If the firm approaches numerous banks to obtain funds, then the probability of obtaining

funds from a bank decreases because it sends a negative signal to the market. In addition,

Castelli, Dwyer, and Hasan (2005) found that return on equity and return on assets decrease as

2
  Source: treasurydirect.gov. The average interest rate is based upon the total of marketable and non-marketable
interest-bearing debt.

                                                      Page 46
Credit Sources, Founder, and New Firms                                                         2011-01

the number of bank relationships increase. So it could be in the best interest of the new firm to

limit the number of relationships it has with banks, but at the same time obtain additional debt

from other credit sources if they are not able to obtain all the funds they need from one bank.

5.2. FURTHER RESEARCH

       This paper only examined alternative credit sources in aggregate and the characteristics

of founders as predictors of use of the trend of multiple alternative credit sources usage and trend

of debt usage. However in further research, it would be interesting to drill down further into the

detail to see if specific characteristic of founders lead to certain alternative credit sources used by

new firms. As well, further research needs to examine credit sources used in personal debt to

finance new firms. In this paper we only examined the business debt of new firms. However,

new firms do not have a financial or operational track record, nor do we see owners and

managers separate from one another. The personal collateral of the owner-managers is used by

new firms to access to debt. It could be that new firms use personal debt to get initial debt or to

access additional debt since banks have limited the firm from borrowing additional amounts.

This needs to be looked at to see if multiple credit sources from personal debt play a role in a

new firm’s capital structure and alleviating credit limits imposed by banks.




                                               Page 47
Credit Sources, Founder, and New Firms                                                     2011-01

REFERENCES

Acs, Z. J., Arenius, P., Hay, M., & Minniti, M. 2005. Global entrepreneurship monitor: 2004

       executive report. Babson Park, London.

Aldrich, H. E., & Ruef, M. 2006. Organizations evolving (2nd ed.), Sage Publications Ltd.

Ang, J. S. 1992. On the theory of finance for privately held firms. Journal of Small Business

       Finance, 1(3): 185-203.

Astebro, T., & Bernhardt, I. 2003. Start-up Financing, Owner Characteristics, and Survival.

       Journal of Economics and Business, 55(4): 303-319.

Audretsch, D. B., & Mahmood, T. 1995. New Firm Survival: New Results Using a Hazard

       Function. The Review of Economics and Statistics, 77(1): 97-103.

Ballou, J., Barton, T., DesRoches, D., Potter, F., Zhao, Z., Santos, B., et al. 2007. Kauffman

       Firm Survey (KFS) Baseline Methodology Report, Kauffman Foundation.

Bates, T. 1997. Financing small business creation: The case of Chinese and Korean immigrant

       entrepreneurs. Journal of Business Venturing, 12(2): 109-124.

Berger, A. N., & Udell, G. F. 1995. Relationship Lending and Lines of Credit in Small Firm

       Finance. Journal of Business, 68(3): 351.

Berger, A. N., & Udell, G. F. 1998. The Economics of Small Business Finance: The Roles of

       Private Equity and Debt Markets in the Financial Growth Cycle. Journal of Banking and

       Finance, 22(6-8): 613-673.

Berggren, B., Olofsson, C., & Silver, L. 2000. Control Aversion and The Search for External

       Financing in Swedish SMEs. Small Business Economics, 15(3): 233-242.

Birley, S. 1987. New Ventures and Employment Growth. Journal of Business Venturing, 2(2):

       155-165.

Blanchflower, D. G., & Oswald, A. J. 1998. What makes an entrepreneur? Journal of Labor



                                             Page 48
Credit Sources, Founder, and New Firms                                                    2011-01

       Economics, 16(1): 26-60.

Boot, A. W. A., & Thakor, A. V. 1994. Moral hazard and secured lending in an infinitely

       repeated credit market game. International Economic Review, 35(4): 899.

Burt, R. S. 1995. Structural Holes: The Social Structure of Competition, Harvard Univ Pr.

Caird, S. 1991. The enterprising tendency of occupational groups. International Small Business

       Journal, 9(4): 75.

Cardon, M. S., Zietsma, C., Saparito, P., Matherne, B. P., & Davis, C. 2005. A Tale of Passion:

       New Insights into Entrepreneurship from a Parenthood Metaphor. Journal of Business

       Venturing, 20(1): 23-45.

Carey, M. S., Prowse, S., Rea, J., & Udell, G. F. 1993. The economics of the private placement

       market. Staff Studies.

Cassar, G. 2004. The Financing of Business Start-ups. Journal of Business Venturing, 19(2):

       261-283.

Cassar, G., & Holmes, S. 2003. Capital Structure and Financing of SMEs: Australian Evidence.

       Accounting and Finance, 43(2): 123-147.

Chiang, R., & Venkatesh, P. C. 1988. Insider holdings and perceptions of information

       asymmetry: A note. Journal of Finance, 1041-1048.

Chittenden, F., Hall, G., & Hutchinson, P. 1996. Small firm growth, access to capital markets

       and financial structure: review of issues and an empirical investigation. Small Business

       Economics, 8(1): 59-67.

Coleman, J. S. 1988. Social Capital in the Creation of Human Capital. The American Journal of

       Sociology, 94: S95-S120.

Cooper, A. C., Gimeno-Gascon, J., & Woo, C. Y. 1994. Initial Human and Financial Capital as

       Predictors of New Venture Performance. Journal of Business Venturing, 9(5): 371-395.


                                            Page 49
Credit Sources, Founder, and New Firms                                                  2011-01

Cox, D. R. 1972. Regression Models and Life-tables. Journal of the Royal Statistical Society.

       Series B (Methodological), 34(2): 187-220.

Cressy, R. 2006a. Why Do Most Firms Die Young? Small Business Economics, 26(2): 103-116.

Cressy, R. 2006b. Determinants of Small Firm Survival and Growth. In The Oxford Handbook

       of Entrepreneurship: 161-193, Oxford: Oxford University Press.

Danielson, M. G., & Scott, J. A. 2004. Bank Loan Availability and Trade Credit Demand. The

       Financial Review, 39(4): 579-600.

Davidsson, P., & Honig, B. 2003. The Role of Social and Human Capital among Nascent

       Entrepreneurs. Journal of Business Venturing, 18(3): 301-331.

Davidsson, P., Low, M. B., & Wright, M. 2001. Low and MacMillan Ten Years On:

       Achievements and Future Directions for Entrepreneurship Research. Entrepreneurship:

       Theory & Practice, 25(4): 5.

Delmar, F., & Shane, S. 2003. Does Business Planning Facilitate the Development of New

       Ventures? Strategic Management Journal, 24(12): 1165-1185.

Diamond, D. W. 1984. Financial Intermediation and Delegated Monitoring. The Review of

       Economic Studies, 51(3): 393-414.

Diamond, D. W. 1991. Debt Maturity Structure and Liquidity Risk. Quarterly Journal of

       Economics, 106(3): 709-737.

Diamond, D. W., & Verrecchia, R. E. 1991. Disclosure, Liquidity, and the Cost of Capital.

       Journal of Finance, 46(4): 1325-1359.

Duncan, T. E., Duncan, S. C., & Strycker, L. A. 2006. An Introduction to Latent Variable

       Growth Curve Modeling: Concepts, Issues, and Applications (2nd ed.), Lawrence

       Erlbaum Associates.

Evans, D. S., & Jovanovic, B. 1989. An Estimated Model of Entrepreneurial Choice Under


                                            Page 50
Credit Sources, Founder, and New Firms                                                   2011-01

       Liquidity Constraints. The Journal of Political Economy, 97(4): 808.

Evans, D. S., & Leighton, L. S. 1989. Some Empirical Aspects of Entrepreneurship. The

       American Economic Review, 79(3): 519-535.

Fama, E. F. 1985. What's Different About Banks? Journal of Monetary Economics, 15(1): 29-

       39.

Fazzari, S., Hubbard, R. G., & Petersen, B. 1988. Investment, Financing Decisions, and Tax

       Policy. American Economic Review, 78(2): 200.

Freimer, M., & Gordon, M. J. 1965. Why bankers ration credit. The Quarterly Journal of

       Economics, 79(3): 397-416.

Gartner, W. B., Shaver, K. G., Gatewood, E. J., & Katz, J. A. 1994. Finding the Entrepreneur in

       Entrepreneurship. Entrepreneurship Theory and Practice, 18(3): 5-9.

Gimeno, J., Folta, T. B., Cooper, A. C., & Woo, C. Y. 1997. Survival of the Fittest?

       Entrepreneurial Human Capital and the Persistence of Underperforming Firms.

       Administrative Science Quarterly, 42(4): 750-783.

Granovetter, M. S. 1973. The Strength of Weak Ties. The American Journal of Sociology,

       78(6): 1360-1380.

Greiner, L. 1972. Evolution and revolution as organizations grow. Harvard Business Review,

       50(4).

Haltiwanger, J. C., Jarmin, R. S., & Miranda, J. 2009. Who Creates Jobs? Small vs. Large vs.

       Young, NBER.

Harris, M., & Raviv, A. 1991. The Theory of Capital Structure. Journal of Finance, 46(1): 297-

       355.

Hisrich, R. D. 1986. Entrepreneurship, Intrapreneurship, Venture Capital, Lexington, MA:

       Lexington Books.


                                             Page 51
Credit Sources, Founder, and New Firms                                                    2011-01

Holmes, S., & Kent, P. 1991. An empirical analysis of the financial structure of small and large

       Australian manufacturing enterprises. Journal of Small Business Finance, 1(2): 141-

       154.

Holtz-Eakin, D., Joulfaian, D., & Rosen, H. S. 1994. Entrepreneurial decisions and liquidity

       constraints. The RAND Journal of Economics, 25(2): 334-347.

Howorth, C. A. 2001. Small firm’s demand for finance: a research note. International Small

       Business Journal, 19(4): 78-86.

Huyghebaert, N. 2006. On the Determinants and Dynamics of Trade Credit Use: Empirical

       Evidence from Business Start-ups. Journal of Business Finance & Accounting, 33(1-2):

       305-328.

Huyghebaert, N., & Van de Gucht, L. 2007. The Determinants of Financial Structure: New

       Insights from Business Start-ups. European Financial Management, 13(1): 101-133.

James, C. 1987. Some evidence on the uniqueness of bank loans. Journal of Financial

       Economics, 19(2): 217-235.

Joreskog, K. G., & Sorbom, D. 1998. LISREL 8: Structural Equation Modeling with the

       SIMPLIS Command Language, Scientific Software International.

Keeton, W. R. 1979. Equilibrium Credit Rationing, Garland Publishing.

Klapper, L. F. 2001. The Uniqueness of Short-term Collateralization, World Bank Policy

       Research Working Paper No. 2544, World Bank.

Kline, R. B. 2005. Principles and Practice of Structural Equation Modeling (2nd ed.), New

       York, NY, USA: The Guilford Press.

Kor, Y. Y., & Mahoney, J. T. 2000. Penrose’s Resource-Based Approach: The Process and

       Product of Research Creativity. Journal of Management Studies, 37(1): no.

Landier, A., & Thesmar, D. 2009. Financial Contracting with Optimistic Entrepreneurs. Review


                                             Page 52
Credit Sources, Founder, and New Firms                                                  2011-01

       of Financial Studies, 22(1): 117.

Liao, J., & Gartner, W. B. 2006. The Effects of Pre-venture Plan Timing and Perceived

       Environmental Uncertainty on the Persistence of Emerging Firms. Small Business

       Economics, 27(1): 23-40.

Lindh, T., & Ohlsson, H. 1996. Self-employment and Windfall Gains: Evidence from the

       Swedish Lottery. The Economic Journal, 106(439): 1515-1526.

Low, M. B., & MacMillan, I. C. 1988. Entrepreneurship: Past Research and Future Challenges.

       Journal of Management, 2: 139-161.

Lummer, S. L., & McConnell, J. J. 1989. Further evidence on the bank lending process and the

       capital-market response to bank loan agreements. Journal of Financial Economics,

       25(1): 99-122.

Miller, M. H. 1962. Credit Risk and Credit Rationing: Further Comment. The Quarterly Journal

       of Economics, 76(3): 480-488.

Modigliani, F., & Miller, M. H. 1958. The Cost of Capital, Corporation Finance and the Theory

       of Investment. American Economic Review, 48(3): 261.

Modigliani, F., & Miller, M. H. 1963, June. Corporate Income Taxes and the Cost of Capital: A

       Correction.,

       http://search.ebscohost.com/login.aspx?direct=true&db=buh&AN=8743472&site=ehost-

       live, American Economic Association.

Muthen, B. O. 1991. Analysis of Longitudinal Data Using Latent Variable Models with Varying

       Parameters. In Best Methods for the Analysis of Change: Recent Advances,

       Unanswered Questions, Future Directions: 1-17, Washington. D.C.

Muthen, B. O., & Curran, P. J. 1997. General Longitudinal Modeling of Individual Differences

       in Experimental Designs: A Latent Variable Framework for Analysis and Power


                                           Page 53
Credit Sources, Founder, and New Firms                                                     2011-01

       Estimation. Psychological Methods, 2(4): 371-402.

Myers, S. C. 1984. The Capital Structure Puzzle. Journal of Finance, 39(3): 575-592.

Myers, S. C., & Majluf, N. S. 1984. Corporate Financing and Investment Decisions when Firms

       have Information that Investors do not have. Journal of Financial Economics, 13(2):

       187-221.

Norton, E. 1991. Capital Structure and Small Public Firms. Journal of Business Venturing,

       6(4): 287-303.

Parker, S. C. 2009. The Economics of Entrepreneurship, Cambridge University Press.

Parker, S. C., & Van Praag, C. M. 2006. Schooling, Capital Constraints and Entrepreneurial

       Performance: The Endogenous Triangle. Journal of Business and Economic Statistics,

       24: 416-31.

Petersen, M. A., & Rajan, R. G. 1994. The benefits of lending relationships: Evidence from

       small business data. The Journal of Finance, 49(1): 3-37.

Petersen, M. A., & Rajan, R. G. 1995. The effect of credit market competition on lending

       relationships. The Quarterly Journal of Economics, 110(2): 407-443.

Petersen, M. A., & Rajan, R. G. 1997. Trade Credit: Theories and Evidence. The Review of

       Financial Studies, 10(3): 661-691.

Phillips, B. D., & Kirchhoff, B. A. 1989. Formation, Growth and Survival; Small Firm Dynamics

       in the U.S. Economy. Small Business Economics, 1(1): 65-74.

Podsakoff, P. M., MacKenzie, S. B., Jeong-Yeon Lee, & Podsakoff, N. P. 2003. Common

       Method Biases in Behavioral Research: A Critical Review of the Literature and

       Recommended Remedies. Journal of Applied Psychology, 88(5): 879.

Podsakoff, P. M., & Organ, D. W. 1986. Self-Reports in Organizational Research: Problems and

       Prospects. Journal of Management, 12(4): 531.


                                            Page 54
Credit Sources, Founder, and New Firms                                                  2011-01

Rajan, R. G. 1992. Insiders and Outsiders: The Choice between Informed and Arm's-Length

       Debt. Journal of Finance, 47(4): 1367-1400.

Ramakrishnan, R. T., & Thakor, A. V. 1984. Information Reliability and a Theory of Financial

       Intermediation. Review of Economic Studies, 51(166): 415.

Raudenbush, S. W., & Bryk, A. S. 2002. Hierarchical Linear Models: Applications and Data

       Analysis Methods, Sage Publications, Inc.

Reynolds, P. D. 2007. Entrepreneurship in the United States: The future is now, Springer

       Verlag.

Robb, A., Ballou, J., DesRoches, D., Potter, F., Zhao, Z., & Reedy, E. J. 2010. An Overview of

       the Kauffman Firm Survey–Results from the 2004-2008 Data. Kauffman Foundation.

Robb, A. M., & Robinson, D. T. 2010. The Capital Structure Decisions of New Firms, Working

       Paper, Duke University.

Roberts, M. J., & Stevenson, H. H. 1992. Alternative Sources of Financing. In The

       Entrepreneurial Venture: 171-178.

Schultz, T. W. 1959. Investment in Man: An Economist's View. The Social Service Review,

       109-117.

Schultz, T. W. 1961. Investment in Human Capital. The American Economic Review, 1-17.

Sexton, D. L., & Bowman-Upton, N. B. 1991. Entrepreneurship: Creativity and Growth,

       MacMillan New York.

Shane, S. A. 2003. A General Theory of Entrepreneurship: The Individual-Opportunity

       Nexus, Edward Elgar Pub.

Sharpe, S. A. 1990. Asymmetric Information, Bank Lending, and Implicit Contracts: A Stylized

       Model of Customer Relationships. Journal of Finance, 45(4): 1069-1087.

Shockley, R. L., & Thakor, A. V. 1997. Bank Loan Commitment Contracts: Data, Theory, and


                                            Page 55
Credit Sources, Founder, and New Firms                                                   2011-01

       Tests. Journal of Money, Credit & Banking, 29(4): 517-534.

Stanworth, J., & Gray, C. 1991. Bolton 20 years on: the small firm in the 1990s, Paul Chapman

       London.

Stiglitz, J. E., & Weiss, A. 1981. Credit Rationing in Markets with Imperfect Information. The

       American Economic Review, 71(3): 393-410.

Tesfatsion, L. 2006. Agent-based Computational Economics: A Constructive Approach to

       Economic Theory. Handbook of Computational Economics, 2: 831-880.

Thakor, A. V. 1996. Capital Requirements, Monetary Policy, and Aggregate Bank Lending:

       Theory and Empirical Evidence. Journal of Finance, 51(1): 279-324.

Tucker, J., & Lean, J. 2003. Small firm finance and public policy. Journal of Small Business

       and Enterprise Development, 10(1): 50-61.

Ucbasaran, D., Lockett, A., Wright, M., & Westhead, P. 2003. Entrepreneurial Founder Teams:

       Factors Associated with Member Entry and Exit. Entrepreneurship: Theory & Practice,

       28(2): 107-127.

Williamson, O. E. 1975. Markets and Hierarchies, Analysis and Antitrust Implications, New

       York, NY, USA: The Free Press.




                                            Page 56
Credit Sources, Founder, and New Firms                                                         2011-01

APPENDICES

SIMULATION MODEL CONFIGURATION

Notes: This model is only a demand-side model. The supply-side of the model is set as part of
the initial configurations of the model. So the supply-side of the model can be changed with
different initial configurations. But the supply of credit will not change in the model in terms of
the additional credit sources being added to the market as the simulation is run. This is to
simplify the model for this study.




                            Source: http://www.pbs.org/now/shows/302/alternative-energy.html


1. Agents

1.1. Firms

       Notes

               This agent represents the firm. A firm could also be looked at as a project. So it
               is not necessarily a legal entity. But for simplistic purposes, I will say it is a firm.

       Type: Static / Dynamic (mix)

       Variables (Static)

               Industry
               Product / Service
               Location (determines where the firm is located; this important to determine if the
               firm can see / access certain credit sources)

                                                      Page 57
Credit Sources, Founder, and New Firms                            2011-01


       Variables (Dynamic)

              Revenue ($)
              Profit / Loss ($)
              Growth Rate in Sales ($) – calculated

              Credit Source: Bank ($)
              Credit Source: Bank Debt ($)
              Credit Source: Non-Bank ($)
              Credit Source: Lines of Credit ($)
              Credit Source: Credit Card ($)
              Credit Source: Other (Business) ($)
              Credit Source: Government ($)
              Credit Source: Owners ($)
              Credit Source: Employee ($)
              Credit Source: Family ($)
              Credit Source: Other Individuals ($)
              Credit Source: Other Sources ($)
              Credit Source: Trade Financing ($)

              Credit Source: Bank (#)
              Credit Source: Bank Debt (#)
              Credit Source: Non-Bank (#)
              Credit Source: Lines of Credit (#)
              Credit Source: Credit Card (#)
              Credit Source: Other (Business) (#)
              Credit Source: Government (#)
              Credit Source: Owners (#)
              Credit Source: Employee (#)
              Credit Source: Family (#)
              Credit Source: Other Individuals (#)
              Credit Source: Other Sources (#)
              Credit Source: Trade Financing (#)

              Cash Balance ($) – calculated

              Total Debt ($) – calculated
              Number of Credit Sources Used – calculated
              Number of Unique Credit Sources Used – calculated

              Assets – optional
              Liability (minus total debt) – optional
              Number of Employees – optional

              Total Equity ($) – optional

       Assumptions

                                             Page 58
Credit Sources, Founder, and New Firms                                                     2011-01


               Assuming that firms have a good credit rating, and that all the credit sources will
               be using is balance sheet. Not looking at if the idea is good or bad or if the
               management is good or bad. It is assumed that firms want to survive and grow.

1.2. Founder –Founding Team

       Notes

               This agent represents the characteristics of the founders of the firm. There could
               be one founder or more than one founder. Thus, this level is called “Founder –
               Founding Team” to explain that a firm could have one founder or more than one
               founder. There is a one-to-one relationship between “Founder – Founding Team”
               and “Firm”. So, even when there is more than one founder for a firm, there is still
               only one entity for the “Founder – Founding Team” agent.

       Type: Static (a proto agent, since the agent will not make decisions)

       Variables

               Number of Founders
               Average Work Experience (years)
               Average Education (years)

1.3. Credit Source

       Notes

               This agent represents the credit sources available in the model.

       Type: Static / Dynamic (mix)

       Variables (Static)

               Type of Credit Source (Bank, Non-Bank, Lines of Credit, etc.)
               Location

       Variables (Dynamic)

               Available Funds (funds that can be loaned to firms)
               Outstanding Credit (“Loans”)
               Criteria to loan money for a project
               Interest Rate
               # of Months to Pay the Money Back

       Assumptions




                                             Page 59
Credit Sources, Founder, and New Firms                                                    2011-01

               Assuming that the credit source will provide credit to the firms that contact them
               if the credit source has available funds. Also, credit sources do not fail. So the
               number of credit sources available in year 1 will be constant throughout each tick
               / period.


2. Behaviors

2.1. Firms

2.1.1. Evaluate Financing Needs

2.1.2. Pay Back Debt

2.1.3. Decide how much Debt is Needed

2.1.4. Scan Environment for Available Credit Sources

2.1.5. Decide which Credit Source to Use

2.1.6. Request Money from the Selected Credit Source

2.1.7. Borrow Money from the “Best” Credit Source that Said Yes

2.1.8. In Case of Credit Source Calling Loan, Search for Other Credit Source to Replace
Previous Credit Source

2.1.8. Decide to Close / Fail

2.2. Credit Sources

2.2.1. Evaluate Outstanding Loans

2.2.2. Decide which Firms are Not Paying

2.2.3. Call Poor Performing Loans

2.2.4. Loan Money to Firms


3. Interactions

3.1. Firms Borrow Money from Credit Sources

3.2. Firms Pay Back Credit to Credit Sources

3.3. Credit Sources Loan Money to Firms


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Credit Sources, Founder, and New Firms                                                2011-01

3.4. Credit Sources Call Credit from Firms


4. Ticks / Periods

       Monthly for 5 years (60 ticks)


5. General Configuration Settings

       Credit Sources can not provide credit across state borders (Yes / No)
       Number of each type of Credit Source in each state
       Interest rate for each type of Credit Source (range)
       # of Months for Payoff for each type of Credit Source (range)
       Number of Bank Loans Firm can Have at One Time (i.e. 1, 2, 3, etc.)


6. Output

       Total Number of Firms Founded in Year 1
       Number of Available Credit Sources in the Environment in Year 1
       Number of Firms Closed / Exited (each year)
       Sales Each Year for Firms
       Same Variables that are in the KFS that I use for Growth Curve Modeling

       Which Firms Survive?; Which Firms Grow?

Is the use of multiple credit sources stalling the inevitable failing of the firm?
Or is the use of multiple credit sources good to improve growth? Need more because more
money is needed as one source can’t provide all the money?...nor do they want to take the risk
(syndication)….can debt be syndicated with new firms? And should debt be syndicated to new
firms (i.e. do the numbers work for banks and new firms)?

Additional questions:

Are new firms leveraged less or more by firms that have received venture capital or angel
investments (i.e. like MBOs)? …but with a smaller balance sheet




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Credit Sources, Founder, and New Firms                                                                                                                    2011-01

FIGURES AND TABLES


         Figure 1: Representation of the Growth Curve Model for Credit Sources Used



                                                                                  1




                                                                                                0.485
                            1.704                                                               (4.494)                          -0.093
                            (19.429)
                                            Initial Status                  Linear Change                      Quad Change       (-3.304)
                                             (Intercept)                     (Slope)                         (Slope)
                                       




              1             0          0          1          1   1              1       2   4             1       3     9        1          4        16

      Credit Sources Used               Credit Sources Used               Credit Sources Used              Credit Sources Used          Credit Sources Used
             (2004)                            (2005)                            (2006)                           (2007)                       (2008)



              y1                                y2                                  y3                             y4                           y5




Notes:
   Fit Statistics: 2 = 7.372, df = 6, p = 0.288 ; RMSEA = 0.025, CFI = 0.995, NFI = 0.973, NNFI = 0.991, GFI = 0.992,
    AGFI = 0.981
   Estimates shown are unstandardized estimates
   t-values shown in parenthesis




                                                                                Page 62
Credit Sources, Founder, and New Firms                                                                                                            2011-01


                    Figure 2: Representation of the Growth Curve Model for Debt



                                                                            1




                                                                                          1.641
                      4.967                                                               (3.765)                      -0.338
                      (11.626)
                                      Initial Status                Linear Change                        Quad Change   (-3.340)
                                       (Intercept)                   (Slope)                           (Slope)
                                 




             1        0          0          1          1   1             1        2   4             1      3     9     1          4          16

            Debt                         Debt                                 Debt                         Debt                        Debt
           (2004)                       (2005)                               (2006)                       (2007)                      (2008)



             y1                           y2                                   y3                           y4                          y5




Notes:
   Fit Statistics: 2 = 5.277, df = 6, p = 0.0.509; RMSEA = 0.000, CFI = 1.000, NFI = 0.975, NNFI = 1.005, GFI = 0.996,
    AGFI = 0.989
   Estimates shown are unstandardized estimates
   t-values shown in parenthesis




                                                                         Page 63
Credit Sources, Founder, and New Firms                                          2011-01

         Table 1: Sample used for Analysis using Growth Curve Modeling in SEM


                                                                   Firms


        Initial Sample                                     4,928

        Removed
           Firms that Closed during the Time Period

                In 2005                                    260

                In 2006                                    273

                In 2007                                    390

                In 2008                                    371

                                                           1,294       3,634


            Firms that Didn't Have Bank Loan in Year 1     3,239       395


            Variables with Missing Data                    23          372


            Outliers                                       5           367



        Final Sample (N)                                   367




                                          Page 64
Credit Sources, Founder, and New Firms                                              2011-01

                               Table 2: Credit Source Options


   #    Label Name                                    Variable Name
   1    How many business loans from a commercial     f11b_bus_loans_bank_numused_
        bank did business use?
   2    How many loans from a non-bank financial      f11b_bus_loans_nonbank_numused_
        institution did business use?
   3    How many business lines of credit did         f11b_bus_cred_line_numused_
        business use?
   4    How many business credit cards did the        f11b_bus_credcard_numused_
        business use?
   5    How many loans from other businesses did      f11a_busloans_otherbus_numused_
        business use?
   6    How many loans from government agencies       f11b_bus_loans_govt_numused_
        did business use?
   7    How many business loans from owner did        f11b_bus_loans_owner_numused_
        business use?
   8    How many loans from employees did business    f11b_bus_loans_emp_numused_
        use?
   9    How many loans from family did business       f11b_bus_loans_fam_numused_
        use?
  10    How many loans from other individuals did     f11b_businloans_otherind_numused_
        business use?
  11    How many loans from other sources did         f11b_bus_other_numused_
        business use?
  12    Did business make any purc                    f13_trade_fin_
        hases through trade financing?




                                          Page 65
Credit Sources, Founders, and New Firms                                                                                                                          2011-01



                                          Table 3: Distribution of Number of Credit Sources Used by Type

                             2004                          2005                          2006                          2007                          2008
         Type       Mean     Std Dev      %       Mean     Std Dev      %       Mean     Std Dev      %       Mean     Std Dev      %       Mean     Std Dev        %
Bank                 0.417       0.715    45.1%    0.461       0.928    35.7%    0.409       0.762    30.7%    0.461       0.741    37.2%    0.362       0.755      31.5%
Non-Bank             0.046       0.235     5.0%    0.027       0.207     2.1%    0.055       0.458     4.1%    0.065       0.475     5.3%    0.033       0.321       2.8%
Lines of Credit      0.281       0.720    30.4%    0.349       0.692    27.1%    0.411       1.001    30.9%    0.390       0.617    31.5%    0.409       0.707      35.5%
Credit Card          0.461       0.461    49.9%    0.736       1.301    57.1%    0.793       1.603    59.5%    0.768       1.286    62.1%    0.673       1.483      58.5%
Other (Business)     0.011       0.104     1.2%    0.011       0.104     0.8%    0.003       0.052     0.2%    0.003       0.052     0.2%    0.011       0.165       0.9%
Government           0.035       0.199     3.8%    0.022       0.146     1.7%    0.022       0.194     1.6%    0.011       0.128     0.9%    0.022       0.233       1.9%
Owners               0.027       0.220     2.9%    0.016       0.164     1.3%    0.011       0.165     0.8%    0.011       0.128     0.9%    0.011       0.165       0.9%
Employee             0.005       0.104     0.6%    0.003       0.052     0.2%    0.014       0.173     1.0%      -           -       0.0%      -           -         0.0%
Family               0.016       0.147     1.8%    0.055       0.326     4.2%    0.046       0.399     3.5%    0.030       0.260     2.4%    0.019       0.156       1.7%
Other Individuals    0.008       0.090     0.9%    0.008       0.090     0.6%      -           -       0.0%      -           -       0.0%    0.005       0.074       0.5%
Other Sources        0.014       0.138     1.5%    0.003       0.052     0.2%    0.016       0.221     1.2%    0.003       0.052     0.2%    0.003       0.052       0.2%
Trade Financing      0.346       0.476    37.5%    0.436       0.497    33.8%    0.428       0.495    32.1%    0.411       0.493    33.3%    0.406       0.492      35.3%
Total                0.924               100.0%    1.289               100.0%    1.332               100.0%    1.237               100.0%    1.150                 100.0%
Credit Sources, Founders, and New Firms                                                                                                                                    2011-01


                                                        Table 4: Distribution of Debt ($) by Type

                              2004                           2005                              2006                            2007                            2008
         Type       Mean      Std Dev      %       Mean      Std Dev      %         Mean       Std Dev      %       Mean       Std Dev      %       Mean       Std Dev        %
Bank                 95,721    393,187    107.8%    58,314    298,125     33.4%      85,766     689,300     28.9%   127,000     942,006     37.8%   111,995     612,037       25.8%
Non-Bank              4,048     33,305      4.6%     9,158    132,339      5.3%       4,839      42,575      1.6%     6,657      60,428      2.0%     6,294      81,216        1.4%
Lines of Credit      17,077    122,416     19.2%    23,659    129,437     13.6%      28,488     127,713      9.6%    53,826     442,811     16.0%    60,561     395,379       13.9%
Credit Card           1,655       7,351     1.9%     4,210     21,356      2.4%       3,886      16,650      1.3%     3,605      13,603      1.1%     3,787      13,170        0.9%
Other (Business)      2,788     39,007      3.1%       668       7,931     0.4%         327        6,264     0.1%       163        3,132     0.0%     3,218      58,705        0.7%
Government            7,015     68,982      7.9%     7,856     79,780      4.5%       9,332     133,610      3.1%     4,659      88,739      1.4%     3,384      51,597        0.8%
Owners                8,856    132,204     10.0%       695       7,100     0.4%       2,071      23,158      0.7%     2,095      36,596      0.6%    11,185     176,863        2.6%
Employee                 14         261     0.0%        49         668     0.0%         177        2,672     0.1%       -            -       0.0%       163        3,132       0.0%
Family                1,853       1,804     2.1%     4,365     41,800      2.5%       1,749      21,563      0.6%     1,407      16,800      0.4%       441        4,133       0.1%
Other Individuals       940       9,807     1.1%     1,522       2,282     0.9%         -            -       0.0%       -            -       0.0%       422        6,907       0.1%
Other Sources         1,126     13,142      1.3%       608       6,502     0.3%       1,785      30,293      0.6%       -            -       0.0%       681      13,050        0.2%
Trade Financing      64,580    392,847     72.7%   154,418    642,842     88.5%     277,706   1,317,870     93.5%   324,099   2,258,130     96.4%   411,087   2,598,520       94.6%
Total                88,826               100.0%   174,389               100.0%     297,033                100.0%   336,029                100.0%   434,370                  100.0%




                                                                                  Page 67
Credit Sources, Founders, and New Firms                                                                                                                                                     2011-01



                              Table 5: Descriptive Statistics and Correlations for Variables used in Growth Curve Modeling in SEM

      Variable                                              Mean     SD       (1)           (2)              (3)            (4)           (5)           (6)           (7)        (8)        (9)

1.    Credit Sources Used (2004)                             2.668   1.690        --
2.    Credit Sources Used (2005)                             2.125   2.178    0.309    **       --
3.    Credit Sources Used (2006)                             2.207   2.386    0.191    **   0.285    **           --
4.    Credit Sources Used (2007)                             2.153   2.027    0.156    **   0.331    **       0.278    **       --
5.    Credit Sources Used (2008)                             1.953   2.294    0.133    *    0.269    **       0.214    **   0.303    **       --
6.    Debt (2004)                                            4.769   8.743    0.596    **   0.138    **       0.066         0.116    *    0.076             --
7.    Debt (2005)                                            6.511   8.105    0.228    **   0.531    **       0.217    **   0.230    **   0.248    **   0.205    **       --
8.    Debt (2006)                                            6.771   8.100    0.118    *    0.184    **       0.424    **   0.158    **   0.200    **   0.171    **   0.337 **       --
9.    Debt (2007)                                            6.735   8.184    0.112    *    0.164    **       0.168    **   0.480    **   0.161    **   0.152    **   0.253 **   0.272 **       --
10.   Debt (2008)                                            6.127   8.656    0.104    *    0.138    **       0.178    **   0.247    **   0.494    **   0.122    *    0.310 **   0.310 **   0.306 **


N = 367
** Correlation is significant at the 0.01 level (2-tailed)
* Correlation is significant at the 0.05 level (2-tailed)


Note: Debt is shown after the transformation using the natural log function




                                                                                                          Page 68
Credit Sources, Founders, and New Firms                                                                                           2011-01


                                                    Table 6: Fit Statistics



                                                    2             df        p       RMSEA     CFI      NFI      NNFI     GFI     AGFI

Models for Main Hypotheses Testing

Model 1:    Number of Credit Sources - Linear        18.886        10       0.042      0.049    0.965    0.930    0.965   0.991     0.987
Model 1a:   Number of Credit Sources - Non-Linear     7.372        6        0.288      0.025    0.995    0.973    0.991   0.992     0.981
Model 2:    Debt ($) - Linear                        19.213        10       0.038      0.050    0.958    0.914    0.958   0.993     0.989
Model 2a:   Debt ($) - Non-linear                     5.277        6        0.509      0.000    1.000    0.975    1.005   0.996     0.989
Model 3:    Debt ($) / Number of Credit Sources     138.956        28      < 0.001     0.103    0.877    0.856    0.803   0.931     0.864

Models for Robostness Checks

Model 4:    Debt ($) - Bank Only - Linear                8.827      5      0.116       0.045    0.710    0.539    0.652   0.992     0.984
Model 5:    Debt (#) - Bank Only - Linear
Model 6:    Equity - Linear
Model 6a:   Equity - Non-Linear
Model 7:    Debt / Equity




                                                                 Page 69
Credit Sources, Founders, and New Firms                                                2011-01


                      Table 7: Estimates, Standard Errors, and t-values


                                              2004                      2004-2008
                                            Intercept
                                             (2004)         Slope                   Quad

 Model 1a: Number of Credit Sources - Non-linear

     Estimate                                   1.704           0.485                  -0.093
     Standard Error                             0.088           0.108                   0.028
     t-value                                   19.429 **        4.494 **               -3.304 **

     Estimate                                   1.129           0.117                  -0.018
     Standard Error                             0.494           0.529                   0.033
     t-value                                    2.283 **        0.220 **               -0.539 **

 Model 2a: Debt ($) - Non-linear

     Estimate                                   4.967           1.641                  -0.338
     Standard Error                             0.427           0.436                   0.101
     t-value                                   11.626 **        3.765 **               -3.340 **

     Estimate                                  13.831           2.799                  0.091
     Standard Error                             8.599           7.916                  0.410
     t-value                                    1.608 *         0.354                  0.222



 Notes:
  • estimates shown are completely standardized estimates
  • ** p < 0.01, * p < 0.05




                                              Page 70
Credit Sources, Founders, and New Firms                                              2011-01

                      Table 8: Two-sample (Independent) t-Test Results




                                                      N         Mean       Std Dev

      Maximum Number of Credit Sources Used

          Survived                                        372      4.446        3.656
          Closed (Out of Business)                         90      3.700        2.932

          t-value = -2.058, df = 163.055, p = 0.041

      Average Number of Credit Sources Used

          Survived                                        372      2.118        1.615
          Closed (Out of Business)                         90      2.476        2.240

          t-value = 1.428, df = 112.376, p = 0.156




                                               Page 71
Credit Sources, Founders, and New Firms             2011-01

CURRICULUM VITAE




                                          Page 72
                                               John Martin Mueller
                                     3100 Houston Blvd, Louisville, Kentucky 40220
                                     p: 303-435-1859, e: john.mueller@louisville.edu

EDUCATION

          PhD          University of Louisville, expected 2012
                       Doctoral Candidate in Entrepreneurship

                       Doctoral Dissertation: “Credit Sources, Founders, and New Firms”
                       Chair: David Dubofsky

          MBA          University of Illinois at Urbana-Champaign, August 1999
                       Finished course work at the University of Texas at Austin

          BBA          Southern Methodist University, December 1992
                       Major: MIS | Minor: Economics

WORK EXPERIENCE – ACADEMIC

University of Louisville                                                                    Research Assistant & Instructor
Louisville, Kentucky                                                                                       2008 - Present

RESEARCH

Research Interests
- Entrepreneurial finance, small business finance, and micro-finance
- Opportunity discovery, recognition, and creation                  - Virtual organizations and outsourcing
- Technology entrepreneurship                                       - Small business sustainability

Presentations
- Mueller, John M. and David Dubofsky. Multiple Credit Sources and New Firms. AOM Kauffman Firm Survey Workshop.
  Montreal, Canada (2010)
- Mueller, John M. Outsourcing in Young Firms: A Stepping Stone in Building a Resource or a Method of Survival. USASBE
  Conference. Nashville, Tennessee (2010)
- Mueller, John M. Opportunity Discovery and Novice Entrepreneurs: An Attention-Based Perspective. Southern Management
  Association Conference. Asheville, North Carolina (2009)

Working Papers
- Meek, William, John M. Mueller, and Diane M. Sullivan. Gender Differences in Franchisee Performance: The Role of Trust
  and Conflict in Relation to Multiple Performance Metrics (submitted to ET&P)
                                                                                                              st
- Ahuja, Manju, Randy Kuhn, and John M. Mueller. IT Control Weakness and Company Financial Health (ISM - 1 rd R&R)
- Ahuja, Manju, Randy Kuhn, and John M. Mueller. Business Value of IT: A Research Agenda for the Post-SOX Era (target:
  ISR)
- Ahuja, Manju, Randy Kuhn, and John M. Mueller. IT Control Weakness and the Market Value of Firms (target: MISQ)
- Mueller, John M. Opportunity Discovery and Novice Entrepreneurs: An Attention-Based Perspective
- Mueller, John M. Outsourcing in Young Firms: A Stepping Stone in Building a Resource or a Method of Survival?
- Mueller, John M. Embracing Environmental Uncertainty in Entrepreneurship Research
- Mueller, John M. and David Dubofsky. Effects on Entrepreneurial Orientation and Performance after an IPO
- Bell, Greg and John M. Mueller. Entrepreneurial Orientation and IPO Performance

Honors and Awards
-   Accepted to attend the AOM Entrepreneurship Division Doctoral Consortium in Montreal, Canada (2010)
-   Awarded Kauffman-sponsored seat to the NORC enclave to access the private version of the Kauffman Firm Survey (2010)
-   Best reviewer, Entrepreneurship track, Southern Management Association Conference (2010)
-   Awarded grant to attend the Gateway Entrepreneurship Research Conference in St. Louis, MO (2010
-   Awarded grant to attend the Southern Management Association Conference Doctoral Consortium in Asheville, N.C. (2009)
-   Awarded grant from the Kauffman Foundation to develop and be an editor of the Kauffman Firm Survey Data Wiki (2009)

                                                           Page 73
      Credit Sources, Founders, and New Firms                                                                 2011-01


TEACHING

- FIN 490 – Entrepreneurial Finance (Fall 2011)
- ENT 340 – Entrepreneurial Creativity and Innovation (Fall 2010, Spring 2011)
- MGMT 433 – Strategy, shadowing Melissa Baucus (2010)

SERVICE

-   Reviewer: AOM (2010), SMA (2009, 2010), USASBE (2011)
-   Discussant / Session Chair: SMA (2009), USASBE (2010)
-   Ad hoc reviewer, JDE (2010), IEMJ (2010)
-   AOM – NDSC finance committee (2010)
-   DECA judge / speaker, Louisville (2010)

WORK EXPERIENCE – INDUSTRY

Colorado Software Architects, Inc.                                                                         Owner, Director
Longmont, Colorado                                                                                           2004 - 2008

SmartBond, Inc.                                                                                           Founder, Director
Longmont, Colorado                                                                                            2000 - 2008

GolfSolutions.com, LLC                                                                                  Founder, President
Longmont, Colorado                                                                                            1998 - 2008

Paragon Construction International (Golden Bear Golf)                                        VP of Business Development
North Palm Beach, Florida                                                                                    1997 - 1998

Other industry experience

      o   Capstone Strategic Inc, Washington D.C., Subject Matter Expert, 2002 – 2006
      o   Aldare Capital Partners, Colorado, Operations and Business Development Specialist, 2000
      o   Montsi & Associates, South Africa, Business Advisor, 1996 – 1997
      o   Bank of Nova Scotia, Illinois, Credit Analyst Intern, 1996
      o   Global Consult, Kuwait, Middle East Manager, 1994 – 1995
      o   Arthur Andersen, Kuwait, Staff Consultant, 1993 – 1994

OTHER HONORS AND ACTIVITIES
-   MBA Management Leadership Grant (University of Illinois)
-   Graduate Associate Grant (University of Illinois)
-   Big 10 MBA Case Study Competition - Best Speaker (University of Illinois)
-   OSBI / IBC Consulting Partner and Project Team Member (University of Illinois)
-   Illinois MBA, Tech Transfer Office, and National Center for Supercomputing Applications (NCSA) Research Team
-   Free Market Development Advisers Program (Institute of International Education and USAID - South Africa)
-   Study Abroad: Denmark International Studies - DIS (SMU)
-   EDS Scholarship for Outstanding MIS Student (SMU)
-   Varsity Golf Scholarship (SMU)
-   Teaching Assistant (SMU)

REFERENCES
David Dubofsky                        Paul Magelli                                 John Slocum
University of Louisville              University of Illinois at Urbana-Champaign   Southern Methodist University
Louisville, Kentucky                  Urbana, Illinois                             Dallas, Texas

                                                           Page 74
        John Martin Mueller
3100 Houston Blvd, Louisville, Kentucky 40220
p: 303-435-1859, e: john.mueller@louisville.edu




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