Human capital research delves even deeper into entrepreneurs’ specific characteristics and demographic traits. The questions of who chooses a particular path in the first place and who gets ahead and why lead this discussion of human capital and entrepreneurship.
The body of research on the relationship between founder background and entrepreneurial success is in many ways similar to the bodies of research look at the relationship between individual backgrounds and career outcomes among any other subgroup – students, corporate executives, political leaders, sports figures, entertainers, scientific and engineering stars, and even career criminals. The broad research question is always "who gets ahead and why?"
Scholarly inquiry into the question of success can organized into two broad approaches – one emphasizes individual characteristics, the other emphasizes situational characteristics. Among scholars focused on individual characteristics, it is possible to further distinguish between those who emphasize innate (or ascribed) characteristics – race, gender, religion, ethnicity, nationality, family background, personality, genetics – and those who emphasize achieved characteristics – those that are the products of choices and investments such as education and experience. The situational factors of interest to scholars tend to be shaped by the disciplinary training of the researcher and include everything from cultural values, political climate, and the regulatory environment to industry and organizational competitiveness and population demography.
But there is an important prior question – who chooses a particular path in the first place? While there is a growing recognition that different processes may impact selection into a particular occupation and performance within the occupation once the choice has been made, there has been relatively little progress in linking questions of entry and of success.
Interestingly, the research literature on human capital and entrepreneurship is already broadly organized into these two different questions – 1) Who becomes an entrepreneur? and 2) Who succeeds as an entrepreneur? More than 25 years of research examines both questions. We outline some of the key findings and provide selected citations below.
Education and Native Ability
- Entrepreneurs appear to be drawn from the tails of the ability distribution (Blanchflower 2000) (Astebro and Thompson 2011) – an idea consistent with the notion that some are pushed into entrepreneurship because they lack other options (Borjas and Bronars 1989) (Joona and Wadensjö 2013) (Dencker Gruber, and Shah 2009), whereas others pursue entrepreneurial opportunities when they perceive the potential rewards to be greater than those obtained from wage employment (Gimeno, Folta, Cooper, and Woo 1997) (Hartog, van Praag, and Van Der Sluis 2010) (Lofstrom, Bates, and Parker 2014).
- There appear to be innate individual differences—possibly grounded in genetics, but certainly manifested in personality and psychological differences—that are associated with entrepreneurial propensities (Nicolaou and Shane 2009). [Note that I do note review this literature extensively – it seemed outside of the scope of human capital research.]
- Although there is no evidence of a relationship between years of schooling and entrepreneurial entry, there is a strong positive relationship between years of schooling and entrepreneurial performance (Van der Sluis, van Praag and Vijverberg 2008).
Gender and Family Circumstances
- Gender and family circumstances are correlated with entrepreneurial entry, with men showing greater propensities towards entrepreneurship than women, and married people having higher entry rates than single people (Parker 2008) (Berglann, Moen, Røed, and Skogstrøm 2011).
- People from entrepreneurial families have a higher likelihood of becoming entrepreneurs (Dunn and Holtz-Eakin 2000) (Aldrich and Kim 2007) (Fairlie and Robb 2007) (Roberts 1991) (Sørensen 2007).
- While there was a long-standing perception that that female-owned businesses are less successful than male-owned busineses (e.g. Shane 2008), recent evidence reveals that after controlling for differences in the type and scale of businesses started by women and the effort they expend towards building the businesses, there are no observable gender differences in entrepreneurial performance (Robb and Watson 2012).
- We do not yet have a clear picture of the relationships between wealth and entrepreneurship. While scholars have investigated whether "liquidity constraints" deter would-be entrepreneurs, there is evidence going both ways (Holtz-Eakin, Joulfaian, and Rosen 1994) (Hurst and Lusardi 2004) (Fairlie and Krashinsky 2012) (Chatterji and Seamans 2012).
- Most entrepreneurs have experience working in established firms prior to founding a startup (Freeman 1986).
- People with broader experiences and skills are both more likely to become entrepreneurs and more likely to succeed (Lazear 2004) (Lazear 2005) (Astebro and Thompson 2011).
- Founders with prior startup experience and prior managerial experience tend to be more successful than those without (Stuart and Abetti 1990) (Delmar and Shane 2006) (Gompers, Kovner, Lerner, and Scharfstein 2006) (Unger, Rauch, Frese, and Rosenbusch 2011) (Eesley and Roberts 2012) (Chen 2013). Research suggests that this is in part due to the experienced founders' greater ability to secure financial resources (Bates 1990) (Parker and van Praag 2006) (Beckman, Burton, and O'Reilly 2007) (Hsu 2007) and to recruit and retain other educated and experienced people to join the firm (Beckman and Burton 2008).
- The literature focuses on entrepreneurs who found businesses in industries (and geographies) where they have prior experience (Sorenson and Audia 2000) (Klepper and Sleeper 2005) (Sorenson and Dahl 2012). Experience—either in the same industry, or with similar technology—
is associated with venture success (Brüderl, Preisendörfer, and Ziegler 1992) (Delmar and Shane 2006) (Gompers, Kovner, and Scharfstein 2006) (Eesley and Roberts 2012); however, the empirical evidence is ambiguous as to the shape and strength of the relationship (Parker 2013) (Toft-Kehler, Wennberg, and Kim 2014).
- The literature on the career backgrounds of founders largely focuses on experience as an employee of firm in the same or closely related industry (see prior bullet point); however, two subfields of the entrepreneurship literature highlight additional sources of pre-entry knowledge that deserve further examination, particularly in high technology industries: academic entrepreneurship (Bercovitz and Feldman 2006) (Stuart and Ding 2006) (Shane 2004) and user entrepreneurship (Shah and Tripsas 2007). Knowledge sourced from university, non-profit, or government research labs or use is highly specialized and has given rise to new ventures. Scholars are currently working to understand how these distinct sources of pre-entry knowledge shape firm-level outcomes (Agarwal and Shah 2014).
- Some firms—particularly smaller firms (Cooper 1971) (Elfenbein Hamilton, and Zenger 2010) (Gompers, Lerner, and Scharfstein 2005) (Sørensen 2007) and firms that have a culture of entrepreneurship and innovation (Franco and Filson 2006) (Burton, Sørensen, and Beckman 2002) (Klepper and Sleeper 2005)—generate more entrepreneurs. In other words, some firms seem to be better spawning grounds for future entrepreneurs than others (see Sørensen and Fassiotto 2011 for a careful review.)
- The prospects of both the parent and progeny firms are likely to be intertwined (Phillips 2002) (Chatterji 2009) (Carnahan, Agarwal and Campbell 2012).
From all of the accumulated evidence on these two questions, there is broad consensus that human capital matters for entrepreneurship; however, it is important to recognize that while the correlational evidence linking human capital and entrepreneurship is quite strong, the causal relationship is poorly understood.
There is little agreement on how much human capital matters for entrepreneurial entry or success. There are debates as to whether the most important components of a founder's background that are related to entrepreneurship are ascribed (family of origin, race, gender, ethnicity, etc.) or achieved (work experience, social capital, personal wealth). There are persistent debates over whether the correlates of entrepreneurial entry and entrepreneurial success are driven by situational factors (things about the time period, region, culture, or environment) or by individual factors (including human capital). Finally, and perhaps more importantly, even after 25 years of effort we still have little understanding of the mechanisms that drive the observed relationships between human capital and entrepreneurial performance.
Much of the causal ambiguity arises from the fact that there are selection and sorting processes that shape both entrepreneurial entry and entrepreneurial success, and these selection and sorting processes are likely to be strongly correlated with human capital and are probably situated in particular places and times.
One interesting debate along these lines is whether a "Matthew Effect" (the rich get richer and the poor get poorer) explains the relationship between human capital and entrepreneurial performance. (Azoulay, Stuart and Wang 2014). The core idea is that the observed relationships are not the result of real differences in underlying ability, but instead the product of a flawed system that relies on status and prestige as signals (Roberts and Sterling 2012).
Obviously, disentangling the causal relationships between human capital, entrepreneurial entry, and entrepreneurial success is extraordinarily difficult, but a crucial first step is to link the two canonical questions about entrepreneurial entry and entrepreneurial performance and investigate them together.
For example, do we observe fewer successful female and minority entrepreneurs because women and minorities lack the ability or motivation or because they face stronger barriers and constraints? Consider also that ascribed human capital characteristics (the things you get from your birth lottery) are well-known to be associated with achieved ones. Do the observed patterns of well-educated and experienced white men being more likely to succeed convincingly demonstrate the importance of human capital for entrepreneurial success, or would these effects disappear if we adequately handled selection effects?
- Treat entrepreneurship in the broader context of careers and consider how spells of entrepreneurship are the product of prior spells. Examine both the antecedents and consequences of entrepreneurship spells for individuals and for organizations.
- Look more closely at the employees of entrepreneurial firms. We know that entrepreneurial firms are creating jobs (Haltiwanger, Jarmin, and Miranda 2013), but are they good jobs?
- Examine the effects of the career histories of founders in great detail. Founders stemming from different "knowledge contexts," for example, university or non-profit research labs, users, or established firms bring different knowledge and social resources to the firm. These differences in knowledge may be a key predictor and shaper of firm-level outcomes.
- To date, much of the literature on human capital and entrepreneurship looks at firm survival as an outcome, largely for reasons having to do with data availability. Survival is operationalized as a binary variable, where acquisition, mergers, and exit are all bundled together. However, for the field to progress, (1) the survival variable should be unpacked, and competing risks models that examine successful (profitable) and failed ("fire sale") acquisitions considered, (2) additional outcome measures should be considered. These might include technological impact and job creation. An implicit assumption in the literature is that the goal of a firm is to survive and be profitable; however, entrepreneurs each have different goals and different skills—and outcomes other than survival can benefit society—hence, broadening our study of outcomes would improve the field's ability to make policy prescriptions.
The best data for studying entrepreneurial entry is undoubtedly longitudinal matched employer-employee data.
One of the challenges of conducting research in this field is the lack of databases compiling information on individual career history, entrepreneurial undertakings, and firm-level entrepreneurial outcomes. To date, much work in the field relies on painstakingly, hand-collected datasets.
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