Career Experiences and Firm Foundings

Scott Shane (University of Maryland) Rakesh Khurana (MIT)

January 4, 2000

Abstract

Because of methodological and theoretical obstacles, sociological research on

organizational foundings has largely focused on societal and population level

factors to explain firm foundings. This paper takes the view that understanding

firm foundings also requires linking to micro-level processes. We suggest that

careers are a useful way to link individual-level processes to firm foundings.

The career experiences of potential founders impacts organizational foundings

by influencing expectations of the liability of newness. We test our explanation

on the population of inventions patented by the Massachusetts Institute of

Technology over the 1980-1996 period and examine the effect of inventors’ prior

experiences on the probability that an invention will be commercialized through

the founding of a new organization.

INTRODUCTION

Sociologists have long been interested in examining the factors that influence firm

foundings. Considered from the societal level, general factors such as literacy, special-

ized schooling, urbanization, and a money-based economy are argued to affect a soci-

ety’s capacity to develop and support new organizations (Stinchcombe 1965). More

recent work specifies the role of ecological factors, such as the nature of technological

1

change (Nelson and Winter, 1982) and the dynamics of organizational populations

(Hannan and Freeman 1984), in affecting firm foundings.

While considerable insights have been generated from examining the relationship

between these macro-level factors and firm foundings, sociological inquiry on this topic

has been limited in its ability to incorporate lower-levels of analysis in its exploration

of this phenomenon. One reason for the lack of research on these lower-level factors

is that the absence of an organization prior to founding makes it impossible to use

organizational attributes to explain foundings. Moreover, sample selection issues

plague efforts to provide individual level explanations. Researchers do not generally

observe corresponding non-entrepreneurs1 in the same decision making setting as

entrepreneurs. The difficulty of finding non-entrepreneurs who are comparable to

entrepreneurs imposes a selection bias that interferes with efforts to test individual-

level explanations for firm foundings2.

The methodological obstacles not withstanding, linking lower-level factors to orga-

1Our use of the term entrepreneur is not limited to persons founding business organizations, as

a similar functions has been identified in the creation of social movements, voluntary associations,

or public institutions. We will use the term entrepreneur and founder interchangeably throughout

the paper.2Researchers in the field of entrepreneurship often argue that new firms are formed when opportu-

nities are discovered by individuals who possess certain attributes (Brockhaus and Horowitz, 1986).

However, empirical work to support this argument has had extremely poor explanatory power (see

Low and MacMillan, 1988; Busnitz and Barney, 1997). Moreover, even when the empirical evidence

is supportive, the results are often questionnable because the empirical tests confound the influence

of opportunities and individuals by comparing entrepreneurs who have discovered opportunities with

managers who have not (see Chen et al, 1998; Busnetz and Barney, 1997; Kaish and Gilad, 1987).

In addition, these studies do not account for the transitory nature of entrepreneurship, but argue

that stable traits account for the discrete decision to start a company (Carroll and Mosakowski,

1987). Finally, most of these studies are based on small samples drawn from undefined populations,

limiting the ability to generalize to a wider population (Aldrich, 1990).

2

nizational foundings is critical to a sociological perspective on organizations. Even

Stinchcombe (1965) began his seminal essay on social structure and organizations by

stressing the role of individuals’ social experiences in the decision to found an organi-

zation. As Freeman (1982) notes, firms do not arise spontaneously from opportunities

in the absence of human action, but rather are founded through the organizing efforts

of individuals. Consequently, any sociological theory of firm foundings must specify

how individual experiences within the social structure influence the probability that

they will found firms (Aldrich and Zimmer 1986).

In our discussion of how individual experiences affect organizational foundings, we

extend a critical mechanism used to account for firm mortality to explain firm found-

ings — the liability of newness (Stinchcombe 1965). An individual’s experience, prior

to the decision to found an organization, influences their expectations of the liability

of newness and, thus, their willingness to create a new organization in response to an

organizing opportunity. Similarly, these experiences influence external expectations

about a particular individual’s ability to overcome a new organization’s liability of

newness. Specifically, we argue that differences in the career experiences of individu-

als lead to differences in the ability of potential entrepreneurs to: (1) access resources

that help them start organizations; (2) adapt to the role of entrepreneurs and; (3)

exploit reputations to obtain the legitimacy necessary to influence the reallocation of

resources from old to new uses.

To support our argument, we explore how career experiences shape the founding

of new technology firms. We use a unique dataset of 1397 inventions patented by

the Massachusetts Institute of Technology over the 1980-1996 period to examine the

effect of inventors’ prior founding experience on the probability that an invention will

be commercialized through the founding of a new organization.

Sociological research in this domain has a rich history, since technology has long

been thought to be at the intersection between individual and broader societal out-

3

comes. For Marx (1954), technology was a primary predictor of social relations.

For Schumpeter (1934), technology influenced social structure by upsetting the old

arrangements in a dynamic process of creative destruction. For organizational theo-

rists, technology has been seen as a major determinant of work, power, and political

dynamics (Perrow 1979; Barley 1990). Our findings suggest that the career experi-

ences of individuals are crucial determinants of the decision to found a new firm.

Before discussing the specifics of the theory and the data, it may be helpful to

distinguish our research from previous empirical work on the topic. We are not

aware of prior research that specifically examines the relationship between individual

career experiences and the founding of technology companies. While there is a small

literature on factors affecting self-employment (Carroll and Mosakowski 1987; Evans

1989), we believe that our research linking career experiences to the founding of

technology firms is distinct from this earlier work for several reasons.

First, the companies that are formed to exploit new technologies have significantly

greater aggregate effect on society than do individual decisions to engage in self-

employment. These companies are usually larger in absolute size, employ larger

numbers of workers, and have a greater impact on overall economic productivity.

Therefore, examination of the founding of high technology firms has the potential to

explicate a phenomenon that has wide ranging impact on social and economic change.

Second, self-employment does not necessarily require the founding of firms. Much

of the data on self-employment includes the examination of people who adopt inde-

pendent contractor status. Since much of the literature on organizational ecology

examines the foundings of firms, rather than on self-employment, the examination of

the effect of experience on the founding of technology companies provides a useful

link to other strands of sociological theory in ways not possible with research on the

self-employment decision.

Third, we suggest that experience in founding firms is potentially distinct from

4

other types of self-employment career experiences. As Thorton (1999) notes, our focus

on founding experiences entails “a shift from thinking of a business as a relatively

permanent lifestyle to considering it a time-limited, successive endeavor. Such a shift

implies a change in the entrepreneur’s identity and career path (i.e., to that of serial

entrepreneur) and, concomitantly, an increased chance of new ventures (Gartner and

Shane 1995). These conjectures await formal testing.”

In the following sections, we develop a perspective for linking the career experiences

of individuals to the founding of firms. We then describe the nature of the dataset

and the measurements. Next, we present evidence supporting our claims that career

experience significantly influences the probability of new firm foundings. We conclude

with a discussion of the theoretical implications of this research.

ORGANIZATIONAL FOUNDINGS AND SOCIOLOGY: MISSING

CONNECTIONS

The ecological approach developed by Hannan and Freeman (1989) and their col-

leagues directs attention to the importance of understanding organizational foundings

for social theory. Their empirical finding that organizational foundings vary with the

number of existing organizations in the population and with environmental condi-

tions is one of the most robust findings in sociology (see Hannan and Carroll 1992

for a review). Yet, despite the established research demonstrating the importance of

these population-level factors on firm foundings, researchers in this arena seek a more

complete understanding of the founding process. Indeed, even Hannan (1988), one

of the key intellects behind the development of the ecological perspective, acknowl-

edges a theoretical gap in the organizational literature when he writes that existing

sociological theory often treats organizational dynamics as exogenous to micro-level

factors. Citing Olson (1986 pp. 178), Hannan (1988) summarizes the problem:

5

Some organization theory is a little bit like a murder mystery in which

the victim is killed for no reason at all. That is to say, one doesn’t get any

sense of the reasons or individual motives that account for the existence

of a particular organization and the characteristics it has.

Sociologists, however, have been reluctant to emphasize the role of individuals in

organizational foundings. This reluctance is not without justification. In a review of

the entrepreneurship literature, Shane and Venkatarman (1999) write that “by defin-

ing the field of entrepreneurship in terms of the individual alone, entrepreneurship

researchers have generated a variety of incomplete definitions that do not withstand

the scrutiny of other scholars.” The authors conclude that the existing literature on

firm foundings is vastly undersocialized and that its focus on the traits of founders,

such as the need for achievement (McClelland 1961), leads to an incomplete under-

standing of the founding process.

While it is likely that some firm foundings are influenced by heterogeneity among

an individual’s traits, as well as differences in initial conditions such as family origins,

extant theories describing the role of individuals in firm foundings imply that founding

propensity is constant over an individual’s life and, thus, operates independently

of factors that change over the individual’s life course. This static explanation of

firm foundings is unlikely to be accurate for several reasons. First, the decision

to found a firm is episodic, making it unlikely that the decision to found a firm is

explained solely by a time-constant individual attribute. Second, the self-employment

literature shows, for example, that propensity toward self-employment varies with

a range of time-varying individual and social level factors (Carroll and Mosakowski

1987). Third, estimates of the number of people who engage in some type of founding

behavior during their career range from 20 percent of the population (Reynolds and

White 1997) to over 50 percent (Aldrich 1999). Since such a diverse group of people

engage in firm founding activities, it is unlikely that the decision to found firms

6

could be explained solely by reference to stable individual characteristics that divide

entrepreneurial from non-entrepreneurial types.

The present analysis addresses the existing gaps in the founding literature by ex-

amining the role of individual career experiences in the firm founding decision. We

argue that careers are an important class of social processes which link individuals to

firm foundings (Haveman and Cohen 1994). As Hannan (1988: pp. 171) writes: “an

obvious but easily overlooked fact is that new firms and new organizational forms are

created by individuals trying to fashion careers.”

Our focus on individual careers as an explanatory mechanism for understanding

firm foundings is distinct from most prior individualist-based explanations. In con-

trast to psychological treatments of organizational founding activity, which attempt

to link stable individual characteristics to founding activity, we treat founding propen-

sity as a factor that varies over an individual’s life course.

Unlike psychological traits, careers are dynamic. They can be seen as a series of

choices individuals make between the opportunities available to them (Burt 1992;

Hughes 1958). Which opportunities are available to which people is a function of

where they are in the social structure, and how they got there. Past career histories,

therefore, constrain or open available opportunities. Specifically, we will suggest that

the career experiences of individuals affects their ability to overcome a critical problem

in the founding of new organizations, the liability of newness.

FIRM FOUNDINGS AND THE LIABILITY OF NEWNESS

To found firms, individuals must obtain resources, evaluate opportunities, and es-

tablish organizational roles and relationships with and between other actors. These

factors, in turn, are affected by the social structure and an individual’s position within

it (Stinchcombe 1965). Moreover, because firm foundings are embedded in a social

context, differences in the career experiences of individuals influence the probability

7

that they will found firms.

Several strands of sociological theory point to individual career experience as a

central factor influencing firm founding. Careers influence people’s position in the

social structure, which, in turn, provides access to both opportunities and resources

(Granovetter 1974). Frazier (1949), for example, found that prior business experience

accounts for why immigrant groups are more likely than native born Blacks to found

firms. Similarly, Borjas (1986) argued that immigrants enter into self-employment

because alternative employment is not available to them3. In the organizational liter-

ature, researchers have argued that entrepreneurship is an organizationally generated

phenomenon in which existing firms are the breeding grounds for new organizations

(Freeman 1982; Sorensen, Burton, and Beckman 1997). Consequently, people tend

to start businesses in industries and technical fields in which they have prior experi-

ence (Freeman 1982). Moreover, knowledge learned and relationships forged in prior

employment influence the subsequent strategies of firms that people found (Boeker

1987; Baron, Hannan, and Burton, 1996).

One particularly important mechanism through which of career experience should

influence firm founding is by mitigating the liability of newness (Stinchcombe 1965).

Young organizations and the individuals in them have to learn new roles as social ac-

tors. Organizations expend a significant amount of resources both socializing individ-

uals into these new roles and coordinating among these roles to achieve organizational

objectives. Because established organizations have access to a developed network of

resources, existing processes for socializing individuals to their roles, and institu-

tionalized external legitimacy, they have a survival advantage over newly founded

organizations.

Although not usually used to discuss organizational dynamics prior to founding,

3Reviewing the research on immigrant work, Aldrich andWaldinger (1990) found broad support

for this phenomenon.

8

the liability of newness is generalizable to the process of organizational founding.

Starting a new organization is fraught with difficulties. Inexperienced founders do

not have a set of stable ties to resource holders, who are often relied upon to provide

the resources necessary to found an organization. The organizational founder usually

needs to learn new roles and acquire new skills in the course of structuring of the new

organization. The process of learning these roles and structuring a new organization

is resource and time intensive and therefore can protract the inefficiency of a new

organization. Finally, inexperienced founders are faced with the challenging task

of convincing others to reallocate resources in non-traditional ways. Those actors

who possess the necessary legitimacy are better able to obtain these resources than

are actors who do not exhibit certain basic characteristics and thus are difficult to

evaluate (Hannan and Freeman 1989; Zuckerman 1999). We discuss each of these

factors in greater detail below.

Access to Resources

Founding an organization usually requires the acquisition of resources from other

social actors. An individual’s ability to access such resources often depends on the

nature of their relationships with these resource providers. To create organizations,

potential entrepreneurs must establish trustworthy relationships with resource sup-

pliers, but these relations of trust are much more fragile and scarce among inexperi-

enced individuals than among experienced individuals. Prior experience in gathering

resources enhances the strength of these relationships. Aldrich and Zimmer (1986) ex-

plain that prior dealings can form the basis for a trustworthy relationship that makes

it easier to obtain resources from the same party a second time around. In addition

to capital and labor, these resources include ties to customers who will buy products

and suppliers who will provide needed raw materials. Larson (1992) provides a fine

grained process analysis which demonstrates how repeated interaction between en-

9

trepreneurs and resource providers leads to the creation of a trustworthy relationship

that facilitates the ability to obtain future resources. The literature on immigrant

entrepreneurship also has shown the importance of prior kinship an co-ethnic ties

on resource acquisition in the firm formation process (Waldinger, Aldrich and Ward

1990). Similarly, Shane and Cable (1998) provide evidence that the ability to obtain

these resources in high technology settings also increases with experience. They show

that social relationships are an important source of funding for new enterprises, and

prior experience in starting a company is an important predictor of the ability to

obtain funds for a new venture. Thus, prior firm financing experience provides social

ties which facilitate the creation of relationships useful to the formation of new firms.

New Roles and Skills

As Stinchcombe (1965: pp. 263) writes: “New organizations, especially new types

of organizations, generally involve new roles, which have to be learned.” The role

challenges for the organizational entrepreneur exists at two levels: the role of the

entrepreneur and the role of others in the organization.

For the entrepreneur, previous experience in founding organizations provides role

familiarity and skills that cannot easily be developed through more traditional career

processes. Inexperienced potential founders suffer the liability of not being socialized

to act in ways consistent with the role of expectations of others. As the career research

of Hughes (1958) and others has shown, career experiences are important because they

are staged shifts from one social role to another. The transition to entrepreneur is an

example of this role shift and as such involves a change in how one presents oneself

to others, a change in how one is treated by others, and in many instances a change

in one’s interactional partners (Cressey 1932; Hughes 1958; Strauss 1959; Barley

1989). In his study of Boston’s Route 128, Nohria (1992) points out the advantages

that experienced entrepreneurs have over novice entrepreneurs. He discusses how

10

experienced entrepreneurs are more comfortable in their roles, conveying a sense of

confidence to others, and more easily attract them to their new ventures.

An individual’s experience or inexperience in founding affects not only the mastery

of their own roles, but also their ability to effectively structure the roles of others.

When firms are first founded, entrepreneurs do not know how structure relationships

between organization members in a way that is as productive as that of established

firms. Over time, the liability of newness dissipates as people learn these role rela-

tionships (Hannan and Freeman 1984). If liabilities of newness dissipate over time,

then it stands to reason that entrepreneurs who have prior experience in the firm

creation process build up organizing skills that minimize these future liabilities of

newness. As Carroll and Mosakowski (1987: pp. 574) explain, “those who engage

in self-employment build up a unique kind of human capital that may be valuable in

later self-employment.” Therefore, prior firm founding experience reduces the liabili-

ties of newness in organizing role relationships and makes the firm formation process

easier.

Legitimacy

To create new organizations, entrepreneurs must often shift resources away from

other uses. However, the creation of new enterprises is an inherently uncertain pro-

cess, with a high probability of failure. Thus, the process of resource reallocation

exposes entrepreneurs’ plans to the scrutiny of others, who compare their novel ideas

against existing wisdom (Hannan, Burton and Baron 1995)

The ability to convince others that a new approach should be adopted in contrast

to established ways of doing things requires the proposer to have legitimacy with

external stakeholders. Because the quality of a new venture is always a matter some

debate, the decision of external resource providers to invest their resources in a new

organization is one that must be made under considerable uncertainty regarding the

11

organization’s future prospects (Stuart, Hoang and Hybels 1998). In such situations,

resource providers look at other attributes when unambiguous measures of quality are

not easily observed. In the case of firm founding, social status provides legitimacy

to the entrepreneur’s activities and makes is easier for a potential entrepreneur to

motivate others to reallocate resources in ways counter to established norms. In

the case of a new invention, for example, evaluators will rely on the status of the

inventor in making decisions about the opportunity (Merton 1973; Latour 1987).

Those inventors of high social status will be more likely to found firms than inventors

of low social status because their status makes external stakeholders to believe in the

viability of the uncertain ideas they are proposing.

RESEARCH SETTING: THE FOUNDING OF TECHNOLOGY

ORGANIZATIONS

Inventors face a choice in commercializing their inventions. They can choose to

do nothing, license the technology to existing firms, or they can create new firms.

While licensing involves less risk, it usually generates less value to the entrepreneur.

We argue that the choice between these outcomes is influenced not only by the char-

acteristics of the opportunity, but by the characteristics of the individuals making

the decision. Different people will respond differently to the same technological op-

portunities because they have a different set of experiences from which to evaluate

that opportunity. If a person has more founding experience, better relationships with

resource providers, and greater legitimacy with important actors, we expect that he

or she will better able than others to generate value by founding a new firm to exploit

the technology. Therefore, we expect that the probability that a person would found

a firm to exploit a new technology opportunity depends, in part, on the founder’s

prior firm career experience.

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DATA, MEASUREMENT, AND METHODS

Sample

We have collected all of the U.S. patents assigned to the Massachusetts Institute

of Technology (MIT) for 17 years, from 1980-1996. The population of inventions

includes all inventions made by faculty, staff or students of the university which made

material use of MIT property during the course of their development.

We examine this setting over this time period for several reasons. First, by looking

at patents, we can examine the decision to found firms in a setting in which we have

information about both the decision maker and the opportunity itself. This mitigates

the problem of specifying the risk set because university inventors form a distinct

population in which firm founders and non-founders are comparable along a variety

of important dimensions which influence the likelihood of firm founding. By focus-

ing on a single setting, we are controlling for a variety of unobserved characteristics

that may affect firm foundings in a multiple-setting study4. Second, the population

of patented inventions is recorded, mitigating selection biases that plague much of

the survey or case study work on firm foundings. Third, patents have been studied

in many contexts other than firm creation, providing comparability of the findings

about firm creation to findings about other aspects of technological change. Fourth,

we examine the 1980-1996 period because in 1980 Federal law changed to grant uni-

versities the property rights to federally funded inventions. Given the preponderance

4Readers should also note that this advantage for internal validity may restrict the genralizability

of the empirical findings. Because the data examine only firms founded to exploit university-assigned

inventions, we do not observe firms founded to exploit inventions by MIT entrepreneurs that by-

passed the university technology licensing office. While we do not observe such foundings, our

discussions with both inventors, the heads of the major laboratories, and the licensing office, leads

us to believe that the number of such firms is few since any inventions that made use of any university

resources need to be filed with the licensing office.

13

of university inventions that result from Federal funding (roughly 70 percent), this

change drastically altered the environment for university technology commercializa-

tion (Henderson, Jaffe, and Trajtenberg, 1998).

Analysis.–

To test our arguments, we model the probability of firm founding for each patent.

Each spell begins when a patent is issued and ends when a firm is founded. Following

Podolny and Stuart (1995), we utilize Cox’s proportional hazards model. Because we

make no claims about the function of time dependence, the Cox model offers the best

approach for modeling time dependence.

The destination state of interest if whether a firm is founded or not founded.

Patents which did not result in a firm founding are treated as censored observa-

tions. Once a patent is issued, firm foundings can occur at any point in time and our

theoretical discussion suggests that there are both time-constant and time-varying

factors influencing the founding event. The model is specified as:

r(t) = h(t) exp[XB + Y (t)S],

where r(t) refers to firm founding and h(t) is an unspecified baseline rate for the

transition. X is a matrix of time-constant covariates, Y (t) is the matrix of time-

varying covariates5.

Dependent Variable: Firm Founding.–

To measure firm founding, we model the probability that an invention assigned

to MIT was licensed to a company which was incorporated to exploit the invention.

5One problem that confounds event-history analyses is the problem of left censoring. Left cen-

soring is potentially problematic because our founding experience and firm financing variables are

censored to the 1980 starting date. To address this issue, we also ran the analyses using patents

issued only after 1985 and prior career experiences dating from 1980. We found no significant

differences in the results in either direction or magnitude.

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This variable was coded 1 if the invention led to the founding of a new company,

0 otherwise. The university maintains records of its inventions and the outcome of

those inventions, in particular whether or not the invention was licensed and, if it

was licensed, the identity of the licensee. MIT records contain detailed information

about the legal status of the licensee, including the date of firm incorporation. If the

MIT records revealed that the licensee did not exist as a legal entity prior to receiving

the license, the patent was defined as a new company patent. Of the 1397 inventions

in our sample, 24% percent were licensed to organizations founded to exploit the

inventions.

Predictor Variable.–

Firm Founding Experience. To measure firm founding experience, we calculated

the average number of prior MIT inventions that led to the founding of a new orga-

nization across the set of inventors who filed for the patent.

Firm Financing Experience. To measure firm financing experience, we calculated

the average number of prior MIT inventions that led to the successful financing of a

new organization across the set of inventors who filed for the patent.

Social Status. To measure social status, we calculated the maximum university

rank across the set of inventors who filed for the patent6. We coded rank as 0 for

6We used rank as the measure of social status based on the extensive literature in the sociology

of science demonstrating that advancement in the organizational hierarchy is the a critical indicator

of an individual’s position in the professional hierarchy. As Merton (1973a; 1973b) has discussed,

status in science is commonly measured by organizational rewards such as deparmental affiliation

and rank in the department. He emphasized that rank in the department indicates the regard the

organization has for the individual and influences the treatment of him or her in such areas of work

resource allocation and deference to particular ideas. Neyman (1977) has found that university rank

15

students; 1 for post-doctoral fellows and research staff; 2 for assistant professors; 3

for associate professors without tenure; 4 for associate professors with tenure; 5 for

full professors; 6 for department chairs and research center directors; 7 for Institute

Professor7.

Control Variables.–

Since many factors other than the experience of the entrepreneur may influence

firm foundings, we control for factors which previous research argues should explain

high technology firm foundings.

Experience. Because people with more patents would be more likely to have had

more patents that led to new companies, we control for the average number of prior

patents possessed by the inventors making the exploitation decision.

Entrepreneurial Type. There are two explanations for the empirical finding that

an individual who experienced an event in the past is more likely to experience a

similar event in the future. The first is that prior experience alters the individual’s

decision model. The second explanation is that individuals may differ in unmeasured

characteristics that influence the probability of experiencing this event (Heckman,

1979). To distinguish between these effects, we include an inventor level fixed-effect

to control for unobserved heterogeneity on the probability of experiencing the event.

We included a dummy variable of 1 for any of the set of inventors who filed for the

patent had previous patents that were commercialized through the founding of the

is highly correlated with other types of status indicators such as scientific productivity, membership

in scientific associations, membership in the editorial bodies of scientific journals, and the external

acclaim commanded by the scientist such as in the political scene as an expert or diplomat.7Institute Professor is the highest honor accorded to a faculty member at MIT.

16

firm.8

Radicalness. Previous research has argued that more radical inventions are more

likely to be exploited through the creation of new firms because these inventions are

competence destroying (Tushman and Anderson 1986) and because existing firms

have less incentive to invest in the development of radical technologies (Henderson

1993). Further, existing firms may be more reluctant to invest in a technology that

sharply deviates from its established niche and thus draws question to its claims on

specific technical domains. We measure the radicalness of patents, as the count of

the number of different three-digit patent classes from which the invention draws its

citations.

There are approximately 600 “three-digit” classes, which represent distinct techno-

logical areas (Jaffe, et al. 1997). The assignment of a patent to a particular patent

class represents the U.S. Patent and Trademark Office’s (USPTO) assessment that a

patent belongs within a particular technical field because it builds upon prior work

in this area. When patent citations are to patents in a greater variety of techni-

cal fields, this assignment represents the USPTO’s assessment that the technology

does not draw on a single technical paradigm but builds upon multiple technologi-

cal paradigms. Following previous research (Jaffe and Trajtenberg 1998), we argue

8The problem of distinguishing between true and spurious experience dependence is of consid-

erable research interest. Research on unemployment, in particular, has focused on this issue. To

further explore this issue we also utilized the maximum-likelihood probit estimation with selection

techniques suggested by Heckman (1981) in his research on female labor force participation.

The probit procedure involved fitting the data to various multivariate probit models to investigate

the importance of controlling for heterogeneity in the panel analysis. Likelihood-ratio test statistics

(twice the difference of the log-likelihood value) robustly indicated the acceptance of experience as

an important determinant of firm founding even when controlling for individual heterogeneity of a

very general type.

17

that patents which cite other patents in fewer three-digit technical fields are more

incremental than patents which cite patents in numerous three-digit technical fields

because they draw on a narrower set of technological paradigms. This definition is

supported by Jaffe and Trajtenberg’s (1998) analysis, in which they find that the

average patent is 100 times more likely to cite a patent in the same technological

class than to cite a random patent in another technology class.

Importance. Previous researchers have argued that new firms are more likely

to be founded when technological developments are more important because people

will choose to become entrepreneurs when the potential return from firm formation

exceeds their opportunity cost of wage employment and a premium for investing in

illiquid new ventures and bearing their uncertainty (Venkataraman 1997). Previous

researchers have shown that more heavily cited patents are more economically im-

portant than are less heavily cited inventions (Henderson et al. 1998). Following

Podolny and Stuart (1995), we measure importance of a patent as the count of the

total number of citations received across all subsequent US patents.

Age of Technical Field. The age of the technical field will influence the proba-

bility that a new firm is founded to exploit an invention. Older technical fields are

likely to be more crowded fields with little room for additional players and technolo-

gies that undermine the existing technical regimes. Therefore, we expect that there

will be more foundings in younger technical fields. We measure age of the technical

field as the number of years since the three-digit patent class was established by the

United States Patent and Trademark Office (USPTO).

Capital Availability. Capital availability will influence the probability that a

new firm will be founded to exploit an invention. Capital availability encourages

entrepreneurs to create new firms since the creation of a new technology firm often

18

involves start-up costs that must be financed (Cohen and Levin 1989). Since the major

source of capital to start new technology companies is equity capital, we examined the

amount of venture capital funding relative to the market size in the three-digit SIC

code in which the technology is most likely to be commercialized using data obtained

from Securities Data Corporation’s venture capital database.9

Number of Firms. The number of firms in the industry will influence the proba-

bility that a new firm will be founded to exploit an invention since it is an indication

of the carrying capacity of a particular niche (Hannan and Freeman, 1989). Prior re-

search has shown that probability of firm founding follows a non-monotonic pattern

with the existing number of firms in the industry. When the number of firms is few,

the probability of firm founding increases. When the number of firms is many, the

probability of firm founding decreases. We measured number of firms as the count

of the number of firms in the 3-digit SIC code, provided by the Census of Manufac-

tures and Annual Survey of Manufactures. For years in which data was not available,

a straight-line extrapolation was used to determine the variable’s value, using the

nearest known values.

Technical Fields. Using dummy variables for drugs, mechanical inventions, elec-

trical inventions, and chemical inventions, we control for the general technical field of

the invention. For purposes of analysis, the base case is chemical inventions. We con-

trol for the technical field for two reasons. First, citation patterns vary by technical

field, requiring the field to be controlled to get an accurate measure of invention im-

portance (Henderson et al. 1998). Second, the mode of invention commercialization

varies substantially by technical field.

9To determine the SIC code in which a patent would be exploited we used the USPTO concor-

dance. This concordance matches patents to three-digit SIC codes on the basis of six-digit patent

classes.

19

Time. Using dummy variables for the year in which the patent was issued (except

1996), we control for time for two reasons: First, citation patterns vary over time,

requiring the field to be controlled to get an accurate measure of invention importance

(Henderson et al. 1998). Second, changes in Federal law and MIT policy over time

have changed the incentives for economic actors to start companies to exploit uni-

versity inventions. In 1984, Congress revised the Bayh-Dole Act to give universities

expanded rights to federally funded inventions. In 1987, MIT agreed to take equity in

partial lieu of royalties but would not grant exclusive licenses to companies in which

a faculty member held equity. In 1990, MIT decided that founders taking equity in a

company could retain their share of MIT’s cash royalties.

Results

Descriptive statistics and bivariate correlations for the independent variables are

reported in Tables 1 and 2 respectively. Table 1 shows that the technologies vary

across technical field and that inventive activity varies over time. Consequently, it is

valuable to control for time and technical field in the analyses. Table 2 demonstrates

a significant correlation between the average number of prior start-up patents and

the average number of prior patents, indicating the importance of controlling for the

base rate of patenting in testing the effect of the average number of prior start-up

patents on the probability of firm founding. This table also shows that problems of

multicollinearity are likely to be manifest between financing experience and founding

experience. Because the two measures are highly correlated and potentially likely to

bias standard errors, we use the residuals of founding experience for our analysis. This

involves formalizing the relationship to model the overlap between the two measures

and using the residuals as the predictor. This measure separates out the financing

effects from the founding effects. This is a standard technique when correcting for

multicollinearity (Kennedy 1992). The assumption here is that multicollinearity arises

20

from an actual approximate linear relationship among some of the regressors, which

in the case of financing and founding may be true. Consequently, this relationship is

formalized and the estimation then proceeds in the context of a simultaneous equation

estimation problem.

Table 3 reports the effects of career experience on the likelihood of firm founding.

We provide three models. Model 1 predicts the likelihood of firm foundings on the

basis of the control variables alone. As Model 1 shows, the control variables have

effects consistent with prior research on the likelihood of firm founding, lending con-

fidence to our analysis. First, as demonstrated by ecological research, the number

of firms has a positive effect on firm founding (B=5.31e5, p<.10) and the number of

firms squared has a negative effect on firm founding (B=-7.63e10, p<.10).

Second, the age of the technology class (B = - 0.01, p <.01) has a negative effect

on the likelihood of firm founding. This result is consistent with the literature on

technology cycles and firm foundings (Utterback 1994).

More important (B = 0.01, p<0.10) and more radical (B = 0.13, p < 0.01) tech-

nologies are also more likely to be exploited through firm founding. These results are

consistent with findings in the technology management literature, which has shown a

relationship between the nature of technological change and firm founding (see Utter-

back 1994). Additionally, inventions made by entrepreneurial types were more likely

to lead to firm foundings (B=2.81, p<.01). This supports the individual differences

view of entrepreneurial propensity (Roberts 1991). These results show the impor-

tance of measuring both attributes of individuals and attributes of opportunities in

explaining firm foundings, and provide additional evidence for the methodological

problems inherent in the cross-sectional comparison of entrepreneurs and managers

used by applied entrepreneurship scholars to predict firm foundings.

The type of technology also influenced the likelihood of firm foundings. Relative

to the omitted category of chemical inventions, mechanical (B=0.47, p<.05) and

21

drug inventions (B=0.73, p<.01) were more likely to lead to firm foundings and

electrical inventions (B=-.54, p<.01) were less likely to lead to firm foundings. One

interpretation of these results is that the efficacy of drugs and mechanical inventions

are more easily evaluated than electrical or chemical technologies thereby increasing

the likelihood of firm foundings in these areas.

Finally, the year effects are significant and demonstrate a robust pattern of in-

creasing likelihood of firm foundings over time. This finding is consistent with prior

research that shows an increasing amount of entrepreneurial activity in the economy

(Gartner and Shane 1995).

Model 2 includes our three predictor variables along with the control variables.

The inclusion of measures of individual career experience improves the overall fit of

the model for predicting firm founding (chi-square = 28.24, p<.01). This result is

consistent with our argument that individual career experiences are critical factors

affecting the decision to found a firm.

Specifically, the results show that founding experience has a positive effect on the

likelihood of firm founding (B=0.08, p<.01). This measure is significant, even after

the inclusion of the control for entrepreneurial type (B=2.70, p<.01), demonstrating

that the likelihood of founding increases with increasing founding experience10. If

the likelihood of firm founding was a function only of an individual’s entrepreneurial

propensity and not influenced by founding experience, we would have expected the

10This intepretation was supported by Chamberlain (1978). Chamberlain recognized that a key

difference between true dependence and serial correlation arising from spurious experience depen-

dence is whether or not there is a dynamic response to an intervention. He argued that effects that

are changing as experience accumulates are evidence of true experience effects whereas effects that

are constant suggest unobserved heterogeneity and thus spurious experience effects. An intervention

that affects the probability of y in period t will continue to affect the probability of y in period t+1,

even though the intervention was present only in period t. An interpretation of serial correlation

arising from unobserved variables is that these effects will remain constant over time.

22

measure for founding experience to be insignificant when including the dummy vari-

able for entrepreneurial type. However, our findings that both the type and experience

variables are significant provides evidence that individuals’ career experiences play a

role in their evaluation of organizing opportunities and thus their subsequent decision

on whether to exploit these opportunities through the founding of a new firm.

The results for Model 2 also show that prior financing experience increases the

likelihood of firm founding (B= 0.10, p<.05). This result suggests that prior relation-

ships with resource suppliers provides advantages in obtaining access to resources in

the future.

Contrary to our expectations, we did not find a significant effect of social status on

the likelihood of firm foundings (B=0.01, p>.10). One explanation for this null finding

is that social status is important only for opportunities in which the technological

development is highly uncertain. When opportunities are uncertain, the legitimating

effect of social status makes it possible for the entrepreneur to obtain the necessary

resources from external stakeholders. For example, Podolny (1994) notes that when

the quality of technology cannot be easily evaluated, perceptions of that technology

are contingent on the status of the actor associated with the invention. Radical

inventions are more difficult to evaluate than incremental inventions because they

do not conform to established and legitimated categories (Kuhn 1962). Similarly,

inventions in new technical fields are more difficult to evaluate than are inventions in

older technical fields because they do not conform to established technical trajectories

or categories (Stuart, et al. forthcoming). Consequently, we examined whether status

would interact with the radicalness of the technology and age of the technical field in

affecting the likelihood of firm founding in Models 3 and 4.

The results in Model 3 provide support for the interaction between status and

radicalness of the invention (B=0.02, p<.05). Holding constant the radicalness of an

invention, the greater the inventors’ status, the higher the likelihood of firm founding.

23

We interpret the results of Model 2 and Model 3 to show that status does not exert

a direct effect on firm founding but rather is mediated through the radicalness of the

invention.

The results in Model 4 provide further support for the interaction between status

and radicalness. The interaction between status and age of the technical field suggests

that the newer the technology, the greater the impact of the inventor’s status on the

likelihood of firm founding11.

CONCLUSION

We have shown how prior career experience affects the probability that an inven-

tion will be commercialized through firm founding. Using a unique dataset that ob-

served corresponding non-founders in the same decision making setting as founders,

our analysis provides strong evidence of the linkage between career histories and

firm foundings. These results support our argument that prior career experience en-

ables potential founders to mitigate problems associated with the liability of newness.

Specifically, prior experience provides at least three advantages that make people

more likely to found firms in the future. First, experience provides for existing social

relationships that make it easier for founders to obtain needed resources. Second,

experience provides firm organizing skills and role familiarity. Third, when an oppor-

tunity departs from established categories or trajectories, career experience provides

the legitimacy necessary to motivate others to reallocate resources in ways counter to

existing norms.

The evidence that career experience leads people to have differential probabilities

of founding new firms in response to the discovery of a technological opportunity has

11We also measured social status using a series of dummy variables rather than a continuous

variable. We found no significance for any one status category over the others. That is, no one rank

in status was more likely to start a firm than another.

24

implications for several strands of sociological research. First, the link between tech-

nology firm foundings and career experience is important to work on firm foundings.

Much of the dominant work on firm foundings does not account for the role of the in-

dividual in the process, but focuses instead on macro-level factors. While illuminating

certain aspects of the firm founding process, this approach constrains our micro-level

understanding of firm foundings (Thornton 1999). As Freeman (1982) and Hannan

(1988) explain, a theoretical mechanism that links individuals to firm foundings is

critical to our understanding of firm foundings since firms do not arise spontaneously

from opportunities in the absence of human action. Organizational ecologists have

rightly criticized the traditional personality-centered explanations of firm founding as

inconsistent with observed data about the founding process (Carroll and Mosakowski

1987). We proposed and provided support for an alternative mechanism by which

individual-level factors are linked to firm foundings — career experience. Careers, we

argued, are a useful construct for studying the interaction of individuals and organiza-

tions and usefully capture the processes by which these interactions affect individual

decisions to found firms. By explicitly linking career experience to the ability of an

individual to overcome the liability of newness in firm founding, we demonstrated that

individuals vary in their ability to take advantage of firm organizing opportunities.

Second, the role that career experience plays in overcoming liabilities of newness

in firm foundings provides an important extension to this theoretical construct. The

liability of newness is one of the most robust empirical findings in the literature on

organizational mortality. A wide variety of studies have shown that new firms have

a higher propensity to fail than older firms (Hannan and Carroll 1992). Despite the

power of this construct to explain firm mortality, to date this construct has had no

analog in the explanation of firm founding. This is theoretically unsatisfying since

virtually all of the other constructs used to account for organizational mortality play

a role in explaining foundings. For example, the institutional environmental, com-

25

petitive dynamics and density dependence arguments that influence firm mortality

also influence firm foundings. By describing how career experience influences the

social relationships, founding skills, and legitimacy of potential entrepreneurs, we

demonstrated that career experience provides a mechanism through which liabilities

of newness influence firm foundings in a similar way to their effect on firm mortal-

ity. Individuals’ variance in career experience impacts their ability to successfully

organize a new firm in response to the discovery of an entrepreneurial opportunity12.

This individual-level variation in the assets that people would bring to bear in a new

firm creates variation in the degree of liability of newness that their firms, if founded,

would face. Expectations about the liability of newness influences their willingness

to organize a firm in response to the discovery of an opportunity as well as the sup-

port that they would obtain from external stakeholders in such an effort. Therefore,

liability of newness influences firm founding in a parallel way to its influence on firm

mortality, just as other dimensions of ecological theory have parallel influences on

foundings and mortality.

Third, the role of career experience on firm foundings has important implications

for research on technical change. Much of the contemporary research on this topic has

pointed to the importance of attributes of industry and technological opportunities in

explaining new firm founding (Hannan and Freeman 1989; Acs and Audretsch 1990).

However, our empirical findings demonstrate that a pure focus on the macro-level

factors provides only a partial explanation that neglects the role of agency. Eco-

nomic studies of firm foundings have assumed away individual differences in firm

founding ability and have modeled the firm formation decision solely in terms of

profit maximization by equally able parties (Caves 1998). However, firm founding

involves a significant component of learning by doing (Carroll and Mosakowski 1987).

Consequently, who obtains decision rights over a new technology can influence the

12At the individual career level this can, perhaps, be thought of as “the liability of inexperience.”

26

probability that a new firm will be created to exploit that invention. This obser-

vation implies that human agency is central to the process of technological change

and that theories of technological change need to incorporate heterogeneity between

individuals.

Fourth, our results suggest that career experience represents several related factors

— social ties, skills, and reputation. This evidence is important because it suggests a

holistic approach of sociologists to the concept of how careers influence human action.

While Granovetter (1974) argues that careers are important because of their impact

on social ties, we argue that careers are not just important because of their impact

on social relationships, but because they also provide skills not easily learned through

other means (Carroll and Mosakowski 1987). Careers are also a signal of legitimacy

that allow some people to take actions that others cannot take.

Finally, our results have useful implications for sociological research on careers.

Sociology has developed a wide range of useful theories to explain the career paths of

individuals within established organizations. However, today the rate of firm founding

in the economy is higher than at any time since the mid-1800’s (Gartner and Shane

1995). Moreover, at any given time, approximately four percent of the work force is

engaged in the process of firm founding and over twenty percent of the population

will engage in this activity at some time during their careers (Reynolds and White

1998). Research on the sociology of careers has not kept pace with this economic

transformation. While a few studies have begun to test whether theories that are

used to explain careers in large, established organizations are relevant for careers

that involve small, new organizations (Baron et al, 1996 and Burton, et al. 1998

are important examples), we do not yet know what boundary conditions from these

theories explain the role of careers that involve activity in a new entrepreneurial

economy. Our basic observation that career experience with firm foundings influences

the subsequent founding of new firms suggests that sociologists have only begun to

27

examine careers in these new settings.

This work is not without limitations. We focused exclusively on the decision of

inventors about how to commercialize their inventions. While inventors are potential

entrepreneurs, they may not be representative of the total population of potential

entrepreneurs. Thus, caution must be exercised in generalizing about firm foundings

from this sample. Nevertheless, we believe that the processes we have observed in

this context are generalizable to other settings since ours is a study of the manner in

which career experiences affect the decision to found firms.

In summary, by showing that individual differences matter to firm foundings, even

after attributes of industry and technological opportunities are controlled, we high-

light that individuals matter to firm foundings in ways not presently discussed in the

literature. Our research shows that the decision to found firms is not determined

solely by the characteristics of the opportunities themselves, but by the confluence of

enterprising individuals and valuable opportunities. An account of the role of indi-

viduals in the firm founding process is critical for advancing theory on firm foundings.

As Baumol (1968:66) eloquently remarked: the study of firm foundings without a role

for the founders is like the study of Shakespeare in which “the Prince of Denmark

has been expunged from the discussion of Hamlet.” We hope to have made one step

toward advancing this understanding.

28

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Table 1. Descriptive Statistics.=============================================================

Variable Mean S.D. Min Max

IndustryNumber of Firms 17,623.56 14,561.58 4,762.00 50,911.00Ven. Cap. (% market) 0.00 0.01 0.00 0.04Age of Class (years) 22.25 22.62 0.00 96.00

Technology OpportunityRadicalness 2.04 1.63 0.00 15.00Importance 6.80 9.72 0.00 117.00

Technical FieldChemical Invention 0.35 0.48 0.00 1.00Electrical Invention 0.36 0.48 0.00 1.00Mechanical Invention 0.05 0.22 0.00 1.00Drug Invention 0.14 0.35 0.00 1.00

Year Issued1980 0.08 0.27 0.00 1.001981 0.10 0.30 0.00 1.001982 0.07 0.26 0.00 1.001983 0.06 0.23 0.00 1.001984 0.06 0.24 0.00 1.001985 0.04 0.19 0.00 1.001986 0.05 0.21 0.00 1.001987 0.06 0.24 0.00 1.001988 0.05 0.22 0.00 1.001989 0.07 0.26 0.00 1.001990 0.07 0.26 0.00 1.001991 0.05 0.23 0.00 1.001992 0.06 0.23 0.00 1.001993 0.04 0.19 0.00 1.001994 0.03 0.19 0.00 1.001995 0.02 0.14 0.00 1.00

Inventor AttributesEntre. Type (dummy) 0.22 0.41 0.00 1.00Previous Patents 5.75 6.71 0.00 39.00Founding Experience 0.58 1.92 0.00 21.00Funding Experience 0.49 1.81 0.00 21.00Status 2.49 2.39 0.00 7.00

=============================================================

Table 2. Bivariate correlations for the independent variables (N=9002).------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Var. 1 2 3 4 5 6 7 8 9 10 11 12 13 14

1. Founding experience 1.002. Funding experience 0.97 1.003. Status 0.15 0.16 1.004. Entrepreneurial type 0.58 0.52 0.13 1.005. Previous patents 0.60 0.59 0.30 0.55 1.006. Importance -0.07 -0.06 -0.03 0.01 0.05 1.007. Radicalness -0.02 -0.03 -0.08 0.05 -0.01 -0.00 1.008. Class age -0.10 -0.10 -0.03 -0.08 -0.13 -0.10 0.03 1.009. Number of firms -0.07 -0.07 -0.13 -0.04 -0.16 0.02 0.10 0.08 1.0010. Venture capital -0.02 -0.02 -0.11 0.02 -0.02 0.02 0.12 0.05 -0.12 1.0011. Electrical invention -0.10 -0.11 -0.24 -0.04 -0.17 0.03 -0.01 0.11 0.11 0.08 1.0012. Chemical invention -0.09 -0.09 0.16 -0.04 0.07 0.05 0.07 -0.02 -0.06 0.01 -0.55 1.0013. Mechanical invention -0.05 -0.04 -0.10 -0.09 -0.11 -0.05 0.10 0.16 0.28 -0.05 -0.18 -0.17 1.0014. Drug invention 0.28 0.30 0.20 0.11 0.23 -0.09 -0.15 -0.18 -0.26 -0.12 -0.31 -0.30 -0.10 1.00

---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------Note: For reasons of space, the year dummy variables are excluded from the correlation matrix.

Table 3. Cox regressions predicting new firm founding: 1980-1996.============================================================================================

Model 1 Model 2 Model 3Variable B (S.E.) Exp(B) B (S.E.) Exp(B) B (S.E.) Exp(B)

Predictor VariablesFounding experience # 0.08 (0.02) 1.09**** 0.09 (0.02) 1.09****Financing experience # 0.10 (0.05) 1.11* 0.10 (0.05) 1.10*Status # 0.01 (0.02) 1.01 -0.04 (0.03) 0.96Status X radicalness # # 0.02 (0.01) 1.02*Status X classage # # #

Control VariablesNumber of firms 5.31e5 (2.97e5) 1.00† 5.17e5 (2.98e5) 1.00† 4.79e5 (2.99e5) 1.00†Number of firms squared -7.63e10 (4.90e10) 1.00† -7.57e10(4.92e10) 1.00† -6.87e10(4.94e10) 1.00Venture capital -37.66 (24.58) 1.60 -36.33 (24.68) 1.66 -37.32 (24.62) 1.19Class age -0.01 (0.00) 0.99**** -0.01 (0.00) 0.99*** -0.01 (0.00) 0.99***Previous patents -0.01 (0.01) 0.99 -0.03 (0.01) 0.97** -0.03 (0.01) 0.97***Entrepreneurial type 2.81 (0.15) 16.58**** 2.70 (0.15) 14.95**** 2.70 (0.15) 14.91****Radicalness 0.13 (0.02) 1.14**** 0.14 (0.02) 1.15**** 0.08 (0.04) 1.08*Importance 0.01 (0.01) 1.01† 0.01 (0.01) 1.01* 0.01 (0.01) 1.01*Electrical invention -0.54 (0.13) 0.58**** -0.57 (0.14) 0.57**** -0.57 (0.14) 0.56****Mechanical invention 0.47 (0.25) 1.60† 0.40 (0.26) 1.49 0.37 (0.25) 1.45Drug invention 0.73 (0.14) 2.08**** 0.64 (0.15) 1.90**** 0.64 (0.15) 1.90****1980 -1.26 (0.42) 0.28** -1.11 (0.42) 0.33** -1.08 (0.42) 0.34*1981 -1.31 (0.34) 0.27**** -1.15 (0.34) 0.32*** -1.14 (0.34) 0.32***1982 -1.97 (0.39) 0.14**** -1.69 (0.39) 0.19**** -1.64 (0.39) 0.19****1983 -1.16 (0.29) 0.31*** -1.02 (0.29) 0.36*** -1.01 (0.29) 0.36***1984 -0.37 (0.24) 0.69 -0.33 (0.25) 0.72 -0.31 (0.25) 0.731985 -0.44 (0.30) 0.64 -0.48 (0.30) 0.62 -0.47 (0.30) 0.631986 -0.88 (0.27) 0.38** -0.95 (0.28) 0.39*** -0.93 (0.28) 0.39***1987 -0.89 (0.31) 0.41** -0.81 (0.32) 0.44** -0.80 (0.31) 0.44*1988 -0.92 (0.33) 0.40** -0.75 (0.33) 0.47* -0.73 (0.33) 0.48*1989 -0.22 (0.25) 0.80 0.07 (0.25) 0.93 -0.05 (0.25) 0.95

1990 -0.79 (0.26) 0.46** -0.60 (0.27) 0.55* -0.63 (0.27) 0.53*1991 -0.32 (0.27) 0.72 -0.22 (0.27) 0.80 -0.19 (0.27) 0.831992 -0.00 (0.24) 1.00 0.09 (0.25) 1.10 0.08 (0.24) 1.081993 0.45 (0.25) 1.57† 0.48 (0.26) 1.62† 0.50 (0.26) 1.65*1994 0.83 (0.26) 2.30** 0.77 (0.27) 2.17** 0.79 (0.27) 2.21**1995 0.89 (0.29) 2.44** 0.76 (0.30) 2.13* 0.75 (0.30) 2.11*

-2 LL 7020.14 6991.89 6987.74Chi-square 1579.69**** 1186.64**** 1190.80****Chi-square of change # 28.24**** 4.16*===========================================================================================

Key: ****= p<.0001;***= p<.001;**= p<.01;*= p<.05;†= p<.10; # = not included; two-tailed tests. 9002 case-years and 363 events.

Table 3. Cox regressions predicting new firm founding: 1980-1996 (Continued).===========================================================================================

Model 4Variable B (S.E.) Exp(B)

Founding experience 0.08 (0.02) 1.08****Financing experience 0.10 (0.05) 1.10*Status 0.06 (0.03) 1.06†Status X radicalness #Status X classage -0.01 (0.01) 0.99*

Control VariablesNumber of firms 4.79e5 (2.98e5) 1.00†Number of firms squared -6.92e10 (4.92e10) 1.00Venture capital -36.00 (24.89) 2.31Class age -0.01 (0.00) 0.99Previous patents -0.03 (0.01) 0.97***Entrepreneurial type 2.70 (0.15) 14.93****Radicalness 0.14 (0.02) 1.14****Importance 0.01 (0.01) 1.01*Electrical invention -0.56 (0.13) 0.57****Mechanical invention 0.29 (0.26) 1.33Drug invention 0.63 (0.15) 1.87****1980 -1.06 (0.42) 0.35*1981 -1.15 (0.34) 0.32***1982 -1.63 (0.39) 0.20****1983 -1.00 (0.29) 0.37***1984 -0.31 (0.25) 0.731985 -0.47 (0.31) 0.631986 -0.92 (0.28) 0.40**1987 -0.80 (0.32) 0.45*1988 -0.71 (0.33) 0.49*1989 -0.03 (0.25) 0.971990 -0.57 (0.27) 0.56*1991 -0.21 (0.27) 0.81

1992 0.10 (0.25) 1.101993 0.51 (0.26) 1.61*1994 0.80 (0.27) 2.23**1995 0.77 (0.30) 2.15*

-2 LL 6986.41Chi-square 1192.12****Chi-square of change 11.49***============================================================================================

Key: ****= p<.0001;***= p<.001;**= p<.01;*= p<.05;†= p<.10; # = not included; two-tailed tests. 9002 case-years and 363 events.