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THE EFFECT OF EMPLOYER PROMINENCE ON EMPLOYEE

ENTREPRENEURSHIP

NAVID BAZZAZIAN HEC Paris

1 Rue de la Libération Jouy en Josas 78351

France

ANDERS BROSTRÖM Royal Institute of Technology

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THE EFFECT OF EMPLOYER PROMINENCE ON EMPLOYEE

ENTREPRENEURSHIP

NAVID BAZZAZIAN HEC Paris

1 Rue de la Libération Jouy en Josas 78351

France

ANDERS BROSTRÖM Royal Institute of Technology

ABSTRACT We study the effect of employer prominence on entrepreneurial transition of employees. We highlight two mechanisms that lead to high rate of departure from prominent firms to entrepreneurship: sorting and influence. Sorting refers to the systematic selection of high ability employees to prominent firms whereas influence refers to the added value of being employed in the prominent firm in terms of learning. Our empirical results using an employer-employee matched dataset from Sweden confirm our hypothesis. Employees are more likely to leave prominent firms to entrepreneurship. Learning knowledge and skills seems to be more important for transition to entrepreneurship than sorting.

AKNOWLEDGMENTS Navid Bazzazian greatly acknowledges funding from the HEC Leadership Center. All errors remain ours.

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INTRODUCTION

Employees of incumbent firms often leave their employers (spin-out) to establish their

own organizations. Although in general entrepreneurship is a relatively rare phenomenon1,

employee entrepreneurship is remarkably widespread in a variety of industries such as

semiconductors (Braun and Mcdonald, 1978; Brittain and Freeman, 1986), disk drives

(Christensen, 1993; Agarwal et al., 2004), lasers (klepper and Sleeper, 2005), biotechnology

(Mitton, 1990; Stuart and Sorenson, 2003), medical devices (Chatterji, 2009), automobiles

(Klepper, 2007), and professional services (Campbell et al. 2011, Carnahan, Agarwal, & Franco,

2011). A stylized fact common to the employee entrepreneurship literature attributes a

significant premium to being in the employ of the leading firms in the industry (Klepper, 2007;

Gompers, Lerner, & Scharfstein, 2005; Agarwal et al., 2004; Romanelli, 1989) or in general

prominent firms (Burton, Sorensen, & Beckman, 2002). Employees of prominent firms seem to

be more likely to transition to entrepreneurship than employees of less prominent firms (Klepper,

2007; Burton, Sorensen, & Beckman, 2002). In other words prominent firms spin-out more

entrepreneurial ventures than others. Although extant literature generally acknowledges the

greater numbers of spin-outs emerging from prominent firms, with a few exceptions (Burton,

Sorensen, & Beckman, 2002) the cause and consequences of incumbent prominence on

employee entrepreneurship has remained largely unexplored. This paper makes an effort to

address this gap. 1 Entrepreneurship for instance is a less common feature of the economy compared to inter-firm mobility of employees, hiring, and turnover.

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In this paper we intend to systematically analyze the prominent firm effect on employee

entrepreneurship and investigate its antecedents. In particular we juxtapose two alternative

explanations with respect to prominent firm effect, sorting and influence, both of which may

explain why employees frequently leave prominent incumbents to entrepreneurship. Sorting

refers to the ex-ante matching of best and brightest employees with prominent firms much like

the classic assortative matching in the marriage market (Becker,1973), however applied to the

labor market. Sorting therefore emphasizes pre-dispositional characteristics of individuals as the

determinant of entrepreneurship. Influence, instead, refers to the effect of context and the value

added by the prominent firm. In other words influence implies that by being in the employ of a

prominent firm, employees learn valuable knowledge about the industry and get access to better

entrepreneurial opportunities. Our results show that indeed employees are more likely to

transition to entrepreneurship from prominent firms. The effect prominence appears positive and

significantly related to transition to entrepreneurship. Both sorting and influence explain

transition to entrepreneurship albeit with different intensity. Being in the employ of a prominent

firm significantly reduces the inter-firm mobility of employees but if they move they are more

likely to transition to entrepreneurship instead of joining another incumbent.

Findings of this research have several contributions. First, by examining employee

entrepreneurship from the lens of influence and sorting we delve into the micro-foundations of

strategy by unpacking the process that leads to employee entrepreneurship from prominent firms.

Understanding this particular entrepreneurship process goes to the center of the debate in

strategy about the sources of the capabilities of new firms. Second, current emphasis of the

theory of entrepreneurial spawning is on the learning and knowledge inheritance. Learning

theories highlight that employees of incumbent firms, especially prominent ones, learn valuable

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knowledge about the industry, gain superior access to their parent firms’ resources, obtain access

to financial networks, and identify opportunities better and in a timely manner. Therefore

employees’ probability of departing and starting their own firm is shaped by learning various

kinds of knowledge at the parent firm. Nevertheless, learning theories neglect sorting effects of

the labor market. Sorting argument thus reflects dispostional characteristics of employees that

are correlated with their choice of an employer and their subsequent decision to engage in

entrepreneurship. Evaluating the magnitude of learning and sorting will inform which

mechanism contributes more to entrepreneurial spawning and how these two mechanisms may

combine together to create synergies. Third, findings of this research have implications for

employing firms as well. If sorting proves to be the dominant mechanism in entrepreneurial

spawning, then parent firms can use variety of practices to retain their best employees that they

hire. For instance, such employees may value non-pecuniary benefits more than monetary

incentives. If learning mechanism predicts entrepreneurial spawning more than sorting, then

parent firms should be aware that their knowledge will spill over through the mobility of

employees. And that their routines and procedures that were deeply embedded in their employees

through repeated and long term exposure are likely to be replicated by them in their new venture

(Wezel, Cattani, and Pennings, 2006). Therefore departure of these employees will act as a

double edge sward harming the parent firm not only through loosing the talent but also through

threats of knowledge leakage and replication of routines.

In the reminder of this article, we will first review the literature in employee

entrepreneurship, define the gap in the current stream of research, and highlight the importance

of the mobility of individuals in the labor market that in some instance will transcend into

systematic sorting patterns. Next we will move on to elaborate on the theory. we will then

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present the data and methodology to test the predictions of the theory. Immediately after the data

description and methodology we will present the results and finally conclude with a discussion

and conclusion.

LITERATURE REVIEW

Entrepreneurship by ex-employees of incumbent firms has been the subject of research in

strategy, economics, and organizational sociology. Prior work shows that there is considerable

heterogeneity in the rate of spin-out generation among incumbent firms. Some firms are simply

more fertile than others. A classic example of such a fertile firm in early days of semiconductor

industry is Fairchild with 24 spin-outs among which Intel, National Semiconductor, and

Advanced Micro Devices are notable ones (Klepper, 2007; Brittain & Freeman, 1986).

Furthermore, Gompers, Lerner, and Scharfstein (2005) provide some examples of spawning rates

among public companies listed in COMPUSTAT: among computer programming and office

equipment industries, IBM, Sun Microsystems, and Apple Computer are at the top of the chart

with 70, 50, and 48 venture capital backed spin-outs respectively. In telecommunication AT&T

leads with 60 spin-outs. Johnson & Johnson spawned 21 firms, Genentech spawned 14 firms,

and Pfizer spawned 13 entrepreneurial firms in drugs industry. All of the above firms are well

known companies in their respective industries and yet they spawn most entrepreneurial

ventures.

Theoretical and empirical work in prior literature highlights several characteristics of

incumbent firms that are related to their spawning intensity. For example, Agarwal et al. (2004)

emphasize information advantages that are accrued to employees of pioneering firms in the

industry. As Stinchcombe (1965) notes information exerts considerable influence on individuals’

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decision to found organizations. Therefore, firms that are market pioneers create knowledge

corridors that put their employees in an advantageous position to recognize entrepreneurial

opportunities in the industry. In addition, Gompers, Lerner, and Sharfstein (2005) show that

firms with larger stocks of knowledge have higher spawning intensity. Firms with abundant

knowledge are likely to be associated with greater likelihood of spin-out generation particularly

because knowledge cannot be guarded perfectly against appropriation (Arrow, 1962) by those

who have access to it. Employees of incumbent firms with abundant knowledge therefore may

walk out of the door with the knowledge they have acquired from their employer to start their

own venture. Moreover, Sorensen (2007) argue that bureaucratic context of incumbent firms

impede employee entrepreneurship by creating job stability, rigid mental dispositions in

employees, and less varied skills and knowledge necessary for entrepreneurship (Lazear, 2005).

In a similar fashion, Elfenbein, Hamilton, and Zenger (2010) argue that both context and

individual traits operate simultaneously in a way that makes some firms more fertile in

entrepreneurial spawning than others. Their empirical paper shows that the high rate of spin-outs

from small firms compared to large firms is because labor market sorts individuals with

entrepreneurial inclination to work environment offered in small firms and that small firms

bestow varied skills and access to a wide network of contacts with customers, suppliers, and

resource providers.

Although these literatures inform us about various specific characteristics of incumbent

firms that may affect the intensity of spin-out generation, except for Elfenbein, Hamilton, and

Zenger (2005) and Burton, Sorensen, and Beckman (2002), none correspond precisely to the

structural position of an incumbent firm among other established firms on which recruitment and

entrepreneurial mobility of employees are integrated. In fact individuals make conscious

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decisions about their choice of an employer for advancement in paid employment well before

departing for entrepreneurship just as firms decide who to recruit. Therefore we believe that any

study that attempts to precisely understand why employees leave some incumbents more often to

entrepreneurship should also integrate why those employees chose to work for those incumbents

in the first place and which job market candidates are selected to work for those incumbents. In

particular we argue that prominent firms, those that are highly productive, are more likely to

generate spin-outs for two reasons: first, prominent firms add more value to their employees in

terms of learning valuable industry knowledge and access to networks of customers and resource

providers, second, labor market matching sorts best and brightest employees, who are likely to

maximize their career advancement rewards via entrepreneurship, in prominent firms.

THEORY AND HYPOTHESIS

Inheritance of knowledge from parent firm is probably the most compelling theory that

prior literature has attributed to spin-out generation. The origin of knowledge inheritance as a

theory is traced back to models and metaphors from biological evolution. Biological models of

evolution are increasingly being used in analysis of organizations (Aldrich, 1999), business

strategy (Barnett and Burgelman 1996), and economic models of industrial competition (Nelson

and Winter, 1982). Apart from variation and selection which are fundamental concepts in

theories of biological evolution and have occupied much space in models of industrial

competition, another important element of biological theories of evolution is heredity which

involves reproduction and transmission of genes to offspring (Nelson, 1995; Klepper and

Sleeper, 2005). In recent studies heredity is used to explain the sources of knowledge and

capabilities of spin-out firms as well as their performance outcomes (Klepper and Sleeper, 2005;

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Agarwal et al. 2004, Chatterji 2009). In this view knowledge is transferred from parent firm to

the spin-out firm through mobility of employees from parent to progeny, where knowledge is

thought of as the industrial counterpart of genes.

Above statements delineate general advantages of being employed in an incumbent firm.

Nevertheless, as said before incumbent firms differ in several dimensions like innovativeness,

network of resources and structural position in the competitive market (e.g. size, age) as

described by economic sociologists (Burton, Sorensen, Beckman, 2002; Phillips, 2002).

Therefore it is not hard to conceive that employees’ knowledge and abilities to succeed in an

industry is largely shaped by the knowledge, capabilities, and resources of their employer

(Klepper and Simons, 2000). In fact Stinchcombe (1965) notes that pre-founding conditions

imprint an organization along various dimensions including technology, routines, strategy, and

structure. We focus on one of the structural dimensions of firms that capture their prominence

namely their productivity2. Productivity refers to the amount of value that a firm can generate

with a given stock of resources. Highly productive firms are likely to be the ones that have

developed superior routines and procedures that allow them to generate greater output from their

given set of resources. Superior routines and abilities of highly productive firms will also affect

customers’ willingness to pay for their services. Their superior knowledge base and their ability

to absorb and assimilate external knowledge in order to create new knowledge will probably

create an environment that allow their employees to imbibe greater knowledge about the industry

(Agarwal et al. 2004), learn knowledge generation routines, and obtain better access to resources

(Burton, Sorensen, Beckman, 2002) and entrepreneurial opportunities. It should be noted that

conceiving the prominent firm as a superior learning environment allows us to relax the

2 We use prominence and productivity interchangeably in this paper.

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assumption that entrepreneurial opportunities are equally distributed among firms. Relaxing the

assumption of arrival of homogenous entrepreneurial opportunities therefore means that

prominent firms provide greater access to entrepreneurial opportunities to their employees and

knowledge required to succeed in entrepreneurship. Being employed in a prominent firm

increases both the quality and quantity component of learning and resources that an employee

can inherit. Nevertheless just as collective learning where accumulation of collective mind-sets

and shared understanding of routines and procedures unfold and become shaped overtime

(Wezel, Cattani, & Pennings, 2006), learning about firm’s routines and knowledge about

procedural and functional capabilities is subject to time compression diseconomies as well. In

other words, although prominent firms have developed superior routines and capabilities,

effective learning of those routines and capabilities requires repeated interaction and exposure of

actors to those routines. In addition, routines and capabilities that make a firm more prominent

among other group of firms are likely to be more complex that can only be replicated if they are

well absorbed and learned by actors exposed to them. Once the knowledge about routines and

capabilities are imbibed by actors, they may use that knowledge to exploit opportunities for

advancement. Employees of prominent firms therefore are at a risk set of exposure to valuable

routines and knowledge about the industry, however, effective assimilation of such knowledge

require repeated exposure. Hence the influence of prominent firm on its employees will unfold

over time and by the duration of time that individuals are in the employ of that firm.

As a result, the likelihood of spinning-out is affected by the added value of being

employed in a more prominent firm. The above arguments suggest that prominent parent firms

enhance the skills and knowledge of their employees more than less prominent parent firms.

Also prominent parent firms may be disproportionately more endowed with entrepreneurial

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opportunities than less prominent firms. All together the added value of being employed in a

prominent parent firm will result in greater likelihood of spinning out. Therefore we hypothesize:

H1: keeping everything else constant, employees of prominent firms are more likely to

transition to entrepreneurship.

H2: greater exposure to routines and knowledge in prominent firms increases the

likelihood of transition to entrepreneurship.

Nevertheless, as stated earlier, composition of the workforce is likely to be different

among firms with different structural positions among established firms. Just as employers have

preferences over job candidates, job candidates also have preferences for employers to advance

in their careers before any entrepreneurship opportunity arises.

Job market candidates have heterogeneous abilities. A priori, abilities of these individuals

are shaped either by their extensive work experience, education, or by their innate capabilities.

There are several reasons to expect that high ability employees with strong preferences for

maximizing their rewards are likely to be employed in prominent firms before departing for

entrepreneurship where the reward to their ability riches its peak. Highly productive and

prominent firms have greater knowledge assets and their productive output per resource input is

considerably more than other firms. Such productive firms may obtain greater visibility not only

among outside evaluators, customers, and investors but also among prospective employees.

Therefore it should be natural to assume that job market candidates will be aware of qualities of

firms and will be able to distinguish prominent firms from less prominent ones. Although we

don’t argue that prominence of firms completely eliminates friction in the labor market but the

assumption that prominence and visibility of firms increases efficiency in labor market matching

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seems to hold in a modern economy where many firms operate alongside each other and search

costs can be markedly reduced to enable fine grained sorting (wheeler, 2001). As a result we

assume that availability of differentiated firms along the dimension of productivity enhances

efficiency in labor market matching.

Although the above argument gives a slight hint about the increase in the efficiency of

labor market, it doesn’t say much about why prominent firms are more likely to obtain highly

able employees from the labor market and why employees prefer to work for innovative firms.

We present a stylized analysis of the sorting process under two conditions: the first is when there

is no complementary in the skill of a prospective employee and the skills of the prominent firm’s

workforce to achieve a particular output and the second is when this assumption is relaxed and

skills of employees become complementary to each other. We show that under both scenarios

best employees are likely to be matched with prominent firms.

Employer-employee match without skill complementarities

The employer-employee matching process without skill complementarities refers to the

situation where the recruitment decision of an employee does not depend on the skill

composition of the employer’s workforce. In other words, it is assumed that the contribution of

each employee on the production output of the firm is independent from each other and

employees are paid according to their own marginal productivity. This matching process thus

resembles the type of the matches observed in college admission process (Gale and Shapley,

1962) or in the market for financial resources where venture capital firms match with

entrepreneurial firms (Sorensen 2007). With this matching logic at equilibrium the best is

matched with the best and the worst is matched with the worst. Gale and Shapley (1962)

illustrate this matching process with the college admission model. Extending Gale and Shapley’s

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(1962) matching process to the labor market, the employer-employee matching process

resembles to that of college admission model for it is a one-to-many matching model. Each firm

can match with several employees, but each employee can only match with a single firm at each

point in time. Employees rank firms according to a preference dimension (prominence) and

employers rank employees based on their abilities. The result of the matching process will be

that prominent firms are matched with high ability employees and less able employees are

pushed down to match with less prominent firms. If entrepreneurial opportunities arrive at a

constant rate to both prominent and less prominent firms, and assuming that exploitation of those

opportunities requires combination of the individual knowledge with information about those

opportunities (Shane 2000) then it is easily observed that more prominent firms will spawn more

entrepreneurial ventures simply because they are stocked with employees with greater human

capital. In other words since employees of prominent firms possess greater human capital they

are more likely to recognize outside entrepreneurial opportunities than employees of less

prominent firms.

Employer-employee match with skill complementarities

In this scenario we assume that an employee’s productivity in and on itself doesn’t

determine the output of the firm and the returns to the employee but the value of the skill of an

employee manifests through the efforts and skills of other employees. In other words skills of

employees complement each other. This type of production process is well illustrated in Kremer

(1993) and Kremer and Maskin (1996). In fact it is not hard to believe that production process in

firms is done by several employees collaborating with each other and each undertakes several

interdependent tasks and that the output depends on the “weakest link.”

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In the matching scenario with skill complementarities there is positive incentive for both

employees and employers to form an assortative matching (Becker, 1973). When there are

complementarities in skills, the marginal productivity of an employee stays positive with respect

to the skill level of the other employees. As result firms that have employees of high ability

benefit more by creating a near homogenous workforce (Kremer, 1993). Highly productive firms

therefore place the highest bid for employees of high abilities and in equilibrium like in Becker’s

(1973) marriage model workers of the same skills will be matched together. Since the increase in

the output of a firm reflects higher wages as well it follows that high ability workers will be paid

higher wages if they are employed in firms that appreciate their level of skill.

Overall above arguments suggest that high ability employees are more likely to be

matched with prominent firms and since these employees are compensated according to their

marginal productivity it is likely that advancement opportunities for them through wage

employment in other firms is severely limited (Sorensen and Sharkey, 2011), and therefore they

will select into entrepreneurship when the opportunity arises. As a result we shall observe more

entrepreneurial transition of high ability employees from prominent firms.

H3: high ability employees are more likely to be employed in prominent firms.

H4: high ability employees are more likely to transition to entrepreneurship from

prominent firms.

DATA AND METHODOLOGY

Data for this analysis comes from a special extract (professional service firms) from two

matched longitudinal data sources. The first is the longitudinal integrated database for medical

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insurance and labor studies (LISA) provided by Statistics Sweden. LISA is a large database

pooling multiple governmental registers of individuals who are 16 years or older in Sweden.

LISA contains a wealth of information characterizing the entire population of Sweden and

currently covers 17 years from 1990 to 2008. Variables that are included in LISA covers

comprehensive information about individuals with respect to their demographics, educational,

employment, and their earnings. Second data source comes from FES, which tracks financial

information for each firm and is submitted annually to the fiscal authorities for taxation

purposes. Complete financial information for firms is only available from years 1997 onwards.

Therefore our final sample for analysis ranges from 1997 to 2008.

The focus on professional service firms which include firms active in legal service

industries, accounting and tax consultancy, and business and management consultancy is for

several reasons. First professional services industries typically have low barriers to mobility and

exclude non- compete clauses (Carnahan, Agarwal, & Campbell, 2011) and rates of

entrepreneurship are relatively high. Second professional service industries are extremely human

capital intensive and productivity of the firms depends highly on the quality and ability of their

workforce. Hence recruitment in these sectors resembles a lot to college admission models where

employers and employees rank their preferences based on prominence and ability, respectively.

Third, prominence of firms in the professional service industries is likely to be reflected with

their productivity and the amount that customers are willing to pay for their services. Earlier

research suggests that the amount of money that an agent is willing to forgo to acquire the

services of a firm indicates the prominence of that firm (Sorensen, 2007).

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Measures

Firm Prominence. We define firm prominence by its productivity. Productivity refers to the

value generated from a given set of inputs. In the professional service industries productivity is

directly related to the contribution of human assets and is reflected in the customers’ willingness

to pay for the services of those firms. We calculate productivity by revenue minus costs divided

by the number of employees. Therefore productivity with this calculation specifies the value of

the firm’s output generated per employee.

Employee mobility. To test the effect of firm prominence on mobility of employees we create the

dependent variable employee mobility which is coded 1 if the employee had changed the

employer since previous year and 0 otherwise.

Entrepreneurial mobility. To test the effect of firm prominence on the likelihood of employees

departing to entrepreneurship and to see the transition of high ability employees to

entrepreneurship from prominent firms, we create the entrepreneurial mobility variable that takes

the value of 1 if the employee had changed the employer since the last year and became the

founder or owner of the new firm and 0 otherwise.

Tenure. To test the effect of exposure to routines and knowledge at the incumbent firm and in

general the influence of the parent firm on employee entrepreneurship we use tenure at the parent

firm.

High and low ability employees. Prior work documents high correlation between individual

performance and earnings (Parsons, 1977). Hence exploit the compensation data to identify

employee ability. We identified high and low ability employees using their own industry as

referents. Following Carnahan et al. (2011) we employ a wage residual approach in identifying

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high and low ability employees of the industry. Therefore we identify high and low ability

employees as those individuals belonging to the top 10 percent and bottom 10 percent of the

residual of the following wage equation:

𝐿𝑜𝑔 𝑤𝑖𝑡 = 𝛽0 + 𝛽1𝑋𝑖𝑡 + 𝛽2𝑍𝑗𝑡 + 𝛾𝑚𝑢𝑛𝑖𝑐𝑖𝑝𝑎𝑙𝑖𝑡𝑦 + 𝛿𝑖𝑛𝑑𝑢𝑠𝑡𝑟𝑦 + 𝑦𝑡 + 𝑢𝑖𝑡

Where 𝑤𝑖𝑡 is the income of individual in year t. 𝑋𝑖𝑡 is the vector of individual characteristics

including demographic variables, tenure, and educational level. 𝑍𝑖𝑡 is a vector of firm level

characteristics including size (number of employees), age, revenue, productivity, total financial

investments, number of establishments, number of different industries that a firm is active in.

𝛾𝑚𝑢𝑛𝑖𝑐𝑖𝑝𝑎𝑙𝑖𝑡𝑦,𝛿𝑖𝑛𝑑𝑢𝑠𝑡𝑟𝑦, 𝑦𝑡 are dummy variables capturing the municipality of the employee’s

firm, the main industry of the firm, and the year of observation respectively.

Empirical strategy

We test our hypothesis using both linear probability models and conditional logit models.

In the linear probability model we included firm-year fixed effects to absorb any unobserved

variation that is constant within firm-years. We present our results both for mobility to an

existing incumbent and entrepreneurial mobility conditional on mobility. As noted earlier our

final sample form analysis is consisting of an 11 year panel starting from 1997. To account for

non-random sample attrition in our data, we limited the analysis to individuals who were

between the ages of 20 to 50 in 1997. By limiting the sample to these ages we are minimizing the

risk of losing individuals early on in our sample due retirement for instance. In addition, in order

to have a homogenous risk set among individuals we limited our analysis to those individuals

who were new employees on incumbent firms in 1997.

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Table 1 reports the descriptive statistics on sample means for the variables used in our

study. Mobility in our sample is nearly 10 percent with approximately 1 percent transition to

entrepreneurship rather than staying with their employer or moving to another firm. Average age

in our sample is around 1 with near equal representation of men and women. Table 2 shows the

correlation matrix for our entire sample.

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Table 1 and 2 about here

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RESULTS

Table 3 reports the result of linear probably model and logit regression on employee

mobility. The results of this table serve as a base line to investigate the general departure of

employees from prominent firms. The relationship of control variables is consistent with the

turnover literature. High ability employees, those that are at the top 10 percent of the wage

residual distribution, are less likely to exit firms. On the contrary, low ability employees, those

that are at the top 10 percent of the wage residual distribution, are more likely to exit firms.

Prominence of incumbent firms, measured by their productivity, has a significant and negative

relationship with employee mobility implying that employees are less likely to leave prominent

employers. When ability of employees are interacted with the prominence of their employer, the

logit model shows that low ability employees are significantly less likely to leave prominent

firms possibly because they receive greater rewards in excess of their contribution to the output

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of their firm. High ability employees on the other hand seem to have no difference in rates of

departure from prominent firms.

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Table 3 about here

-----------------------------

Table 4 reports the tests of our hypothesis about employee entrepreneurship. Again the

result of linear probability model is reported alongside the conditional logit model. Estimation is

limited to the sample of employees who left the incumbent firms to found their own venture or

became the owner of a new venture. Hypothesis 1 stated that employees of prominent incumbent

firms are more likely to transition to entrepreneurship. In fact, the coefficient of firm prominence

is positive and significant which supports our hypothesis. Note that the effect of prominence with

respect to employee mobility was negative and significant however, conditional on mobility

having a prominent parent increases the likelihood of entrepreneurship. This result therefore

confirms earlier speculations of the literature that prominent firms are more likely to generate

spin-outs. Hypothesis 2 indicated that exposure to knowledge and routines of prominent firms

increase the likelihood of mobility to entrepreneurship. We tested hypothesis 2 by interacting

duration of tenure at the parent firm with the prominence (productivity) of the parent firm. First

note that the main effect of tenure on employee entrepreneurship is negative and significant in

the logit model. The result of the interaction of employee tenure and parent firm prominence is

positive and significant in the conditional logit model. This result therefore provides strong

support for our hypothesis. Prominent firms influence the knowledge and capabilities of their

employees. This finding is consistent with the earlier literature suggesting that employees learn

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valuable knowledge about the industry and gain superior skills and capabilities at prominent

firms.

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Table 4 about here

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Returning to hypothesis regarding the sorting argument, hypothesis 4 stated that high

ability employees are more likely to transition to entrepreneurship from prominent firm because

the opportunities for advancement reaches its peak in entrepreneurship. We tested this argument

by interacting the dummy variable of being in top 10 percent of industry wage residual with firm

prominence. Results are shown in table 4. Neither the linear probability model nor the logit

model shows significant differences in their likelihood of transition to entrepreneurship although

the coefficients have the positive direction. To see whether high ability employees are likely to

be over-presented in prominent firms (hypothesis 3) we regress the prominence measure of firms

on the dummy variable indicating that employee belongs to the top 10 percent of the industry

wage residual. The results of the OLS regression is reported in table 5. Coefficient of the dummy

variables pertaining to top and bottom of the ability distribution are not significant which shows

no sign of contribution of those employees to the prominence of firms. In other words whether

the employee is considered as high ability in its respective industry has no effect on its employer

being a prominent firm in that industry. Therefore hypothesis 3 stating that high ability

employees will be in the employ of prominent firms is rejected.

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----------------------------

Table 5 about here

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DISCUSSION AND CONCLUSION

The analysis in the previous section aimed at understanding three issues pertaining to the effect of

parent firm prominence on employee entrepreneurship and its route causes. Clearly prominent firms,

those that have higher productivity compared to their counterparts, have higher rates of spin-out

generation. Employees are more likely to leave prominent firms to start their own business. This result is

shown alongside the fact that mobility out of the prominent firms in general (whether to an existing

incumbent firm or to an entrepreneurial start-up) is significantly lower from mobility out of the less

prominent firms. Connection of the mobility and entrepreneurship from prominent firms shows that both

phenomenon of turnover and entrepreneurship should be looked in tandem in order for understanding why

and how individuals choose entrepreneurship versus dependent employment as means of getting ahead

(Sorensen and Fassiotto, 2011). Being in the employ of a prominent firm lets individuals to advance in

their careers, maximize their pecuniary benefits, and absorb the reputation and prestige of working for

such firms. Such pecuniary and non-pecuniary benefits of being in the employ of a prominent firm

impede their departure to another incumbent. However, our analysis shows that if such departures from

prominent firms take place it would more likely be to an entrepreneurial firm. In other words, employees

of prominent firms are more likely to choose self employment to advance in their careers compared to

joining another incumbent.

Especial structural position of prominent firms among other firms implies that they are endowed

with superior routines, capabilities and knowledge regarding procedures and functional attributes of the

industry. Therefore employees of prominent firms are naturally placed in an advantageous position to

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imbibe the superior routines and knowledge of the industry and exploit that to start their own business.

Our results, indeed, show that learning from prominent firms increases the likelihood of transition to

entrepreneurship. This is in accordance with the existing theoretical arguments about knowledge

inheritance and transition to entrepreneurship. Learning of routines and industry knowledge requires

repeated exposure and time therefore we don’t observe immediate departures from prominent firm to

entrepreneurship. Departures to entrepreneurship increases with the interaction of employees’ tenure and

the prominence of their employer suggesting that the learning routines and knowledge is probably

explaining why individuals leave prominent firm more often to start their own venture. Nevertheless, as

stated earlier, especial structural position of prominent firms not only is the indicator of their superior

routines and knowledge but it is also an indicator of their attractiveness to the labor market. Job

candidates have preferences over firms and just as students rank universities for admission, job candidates

also rank employers. We argued that prominence of a firm increases its attractiveness for prospective

employees and therefore there should be an over-representation of high ability employees in prominent

firms. Individuals with highest abilities are likely to be closer to their attainment ceiling and are likely to

choose both employment in a prominent firm and entrepreneurship during their career history as means of

closing the gap between the rewards and their abilities. Therefore transition to entrepreneurship from

prominent firms would also be the result of the systematic sorting of high ability employees in prominent

firms ex-ante. Our initial results shows that high ability employees are more likely to transition to

entrepreneurship from prominent firms but such transition doesn’t seem to be related to the sorting in the

labor market. We were unable to find the over-presentation of high ability employees in prominent firms.

Nevertheless it should be noted that our analysis of sorting is possibly not fully revels the sorting of high

ability employees in prominent firms and the results should interpreted with caution. Taken together our

results corroborates with the influence argument that prominent firms add more value to their employees’

knowledge about the industry and entrepreneurial opportunities.

23

In sum we reiterate that we started with a stylized fact in the employee entrepreneurship literature

regarding the effect of firm prominence on transition to entrepreneurship. Our results suggests that

prominence of the employer increases the likelihood of employees departing for entrepreneurship and that

such departure is because of the superior learning environment of their prior employer not their innate

abilities.

24

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Table 1: Descriptive Statistics

Mean Standard Deviation Employee mobility 0.111 0.3141 Entrepreneurial mobility 0.0107 0.1029 Individual attributes High ability (top 10% of ability distribution) 0.099 0.299 Low ability (bottom 10% of ability distribution) 0.099 0.299 Wage 391,388.20 426,338.80 Age 41.24 8.682 Female 0.4859 0.4998 Tenure 2.943 3.492 firm attributes No. of employees 318.1 614.9 Revenue 654,534.10 2,408,029 Prominence (productivity) 279,018 943,994 No. of establishments 13.35 30.08 No. Of industries 1.113 0.5252 Age 6.688 6.2

Note: Number of observations are 444,538 from 1997 to 2008

29

Table 2: Correlation table

1 2 3 4 5 6 7 8 9 10 11 12 13 14 1 Employee mobility 1.00 2 Entrepreneurial mobility 0.30 1.00 3 High ability (top 10% of ability distribution) -0.02 0.02 1.00 4 Low ability (bottom 10% of ability distribution) -0.02 -0.01 -0.11 1.00 5 Wage 0.00 0.01 0.33 -0.15 1.00 6 Age -0.11 0.03 0.27 -0.12 0.15 1.00 7 Female 0.00 -0.02 -0.31 0.23 -0.23 -0.04 1.00 8 Tenure -0.12 0.00 0.14 -0.07 0.05 0.27 0.01 1.00 9 No. of employees -0.03 -0.03 0.00 -0.06 -0.02 -0.05 0.01 0.11 1.00

10 Revenue -0.01 -0.01 0.02 -0.05 0.00 0.00 0.00 -0.04 0.32 1.00 11 Prominence (productivity) -0.03 -0.01 0.06 -0.06 0.03 0.02 0.01 0.02 0.43 0.79 1.00 12 No. of establishments -0.04 -0.02 -0.02 -0.02 -0.04 -0.02 0.01 0.19 0.83 0.14 0.29 1.00 13 No. of industries 0.00 -0.01 -0.04 0.00 -0.03 -0.04 -0.04 -0.07 0.27 0.16 0.06 0.20 1.00 14 Firm age -0.12 -0.02 0.08 -0.10 0.03 0.11 0.05 0.62 0.26 0.00 0.09 0.36 -0.03 1.00

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Table 3: Individual and firm effects on employee mobility

Linear probability model Logit

Dependent variable: Employee Mobility coefficients standard errors

coefficients standard errors

Individual level variable High ability (top 10% of ability distribution) -0.02302*** (0.0020) -0.19333*** (0.0227) Low ability (bottom 10% of ability distribution) 0.00507** (0.0023) 0.09867*** (0.0260) Wage 4.68E-09** (0.0000) 0.545E-08*** (0.0000) Wage^2 -4.04E-17 (0.0000) -8.92E-16 (0.0000) Age -0.00860*** (0.0005) -0.03244*** (0.0056) Age^2 7.52E-05*** (0.0000) 0.00010 (0.0000) Female -0.00260** (0.0011) -0.01527 (0.0122) Tenure -0.01411*** (0.0004) -0.14303*** (0.0049) Tenure^2 0.00108*** (0.0000) 0.00997*** (0.0004) Firm level variables Prominence -2.45E-08*** (0.0000) -2.45E-07*** (0.0000) Number of employees -1.72E-05*** (0.0000) -0.00014*** (0.0000) Revenue 8.23E-09*** (0.0000) 6.22E-08*** (0.0000) Number of establishments 0.00034*** (0.0000) 0.00275*** (0.0004) Number of industries involved -0.01041*** (0.0011) -0.0954*** (0.0131) age -0.00551*** (0.0001) -0.05702*** (0.0013) Interactions High abilityXprominence 3.55E-09** (0.0000) 2.33E-08 (0.0000) Low abilityXprominence 7.09E-08*** (0.0000) -1.09E-06*** (0.0000) Dummy variables Individual educational levels YES YES Working municipality YES YES sector within professional services YES YES Individual is a owner or founder of the parent firm YES YES

No. of observations 444,538 444,538 R^2 0.0536 0.0778(pseudo)

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Table 4: Individual and firm effects on mobility to entrepreneurship

Linear probability model Conditional Logit

Dependent Variable: Entrepreneurial Mobility coefficients standard errors coefficients standard errors Individual level variable High ability (top 10% of ability distribution) 0.05702*** (0.0059) 058086*** (0.0687) Low ability (bottom 10% of ability distribution) -0.03061*** (0.0067) -0.49682*** (0.1038) Wage -1.64E-08*** (0.0000) -1.75E-07** (0.0000) Wage^2 7.73E-16** (0.0000) 8.53E-15* (0.0000) Age 0.00945*** (0.0014) 0.30089*** (0.0236) Age^2 -8.21E-05*** (0.0000) -0.00311*** (0.0002) Female -0.01308*** (0.0030) -0.18228*** (0.0432) Tenure -0.00113 (0.0007) -0.02757*** (0.0085) Tenure^2 Firm level variables Prominence 2.06E-08*** (0.0000) 8.71E-07*** (0.0000) Number of employees -2.88E-05*** (0.0000) -0.00064*** (0.0001) Revenue -6.00E-09*** (0.0000) -4.10E-07*** (0.0000) Number of establishments -5.31E-05 (0.0001) 0.00164 (0.0018) Number of industries involved -0.00375 (0.0034) -0.12275* (0.0680) age 0.00232*** (0.0003) 0.03211*** (0.0046) Interactions High abilityXprominence 3.49E-09 (0.0000) 2.41E-08 (0.0000) Low abilityXprominence 1.03E-07*** (0.0000) 2.51E-06*** (0.0000) TenureXprominence 1.77E-10 (0.0000) 2.55E-08** (0.0000) Dummy variables Individual educational levels YES YES Working municipality YES YES sector within professional services YES YES Individual is a owner or founder of the parent firm YES YES

No. of observations 41,314 41,314 R^2 0.203 0.214(pseudo)

32

Table 5: employment likelihood in prominent firms

Dependent Variable: Prominence OLS

coefficients standard errors Individual level variable High ability (top 10% of ability distribution) 0.17520 (16.011) Low ability (bottom 10% of ability distribution) -1.03740 (20.237) Wage 6.44E-06 (0.0000) Wage^2 -4.33E-13 (0.0000) Age -1.52881 (4.0447) Age^2 0.01866 (0.0488) Female 7.6803 (8.8813) Tenure -4.0923 (3.8434) Tenure^2 0.2407 (0.2984) Firm level variables Number of employees 323.43*** (4.2117) Revenue 0.2316*** (0.0000) Number of establishments 1733.8*** (71.373) Number of industries involved 22016.1*** (836.87) age 378.15*** (24.773) Dummy variables Individual educational levels YES Working municipality YES sector within professional services YES Individual is a owner or founder of the parent firm YES