A Review of Recent Literature

Personality Traits of Entrepreneurs:A Review of Recent LiteratureSari Pekkala KerrWilliam R. KerrTina Xu Working Paper 18-047Working Paper 18-047Copyright © 2017 by Sari Pekkala Kerr, William…

Personality Traits of Entrepreneurs:A Review of Recent LiteratureSari Pekkala KerrWilliam R. KerrTina Xu

Working Paper 18-047Working Paper 18-047Copyright © 2017 by Sari Pekkala Kerr, William R. Kerr, and Tina XuWorking papers are in draft form. This working paper is distributed for purposes of comment and discussion only. It maynot be reproduced without permission of the copyright holder. Copies of working papers are available from the author.

Personality Traits of Entrepreneurs:A Review of Recent LiteratureSari Pekkala KerrWellesley CollegeWilliam R. KerrHarvard Business SchoolTina XuWellesley College

1Personality Traits of Entrepreneurs:A Review of Recent LiteratureSari Pekkala Kerr, Wellesley CollegeWilliam R. Kerr, HBS & NBERTina Xu, Wellesley CollegeNovember 2017Abstract: We review the extensive literature since 2000 on the personality traits of entrepreneurs.We first consider baseline personality traits like the Big-5 model, self-efficacy and innovativeness,locus of control, and the need for achievement. We then consider risk attitudes and goals andaspirations of entrepreneurs. Within each area, we separate studies by the type of entrepreneurialbehavior considered: entry into entrepreneurship, performance outcomes, and exit fromentrepreneurship. This literature shows common results and many points of disagreement,reflective of the heterogeneous nature of entrepreneurship. We label studies by the type ofentrepreneurial population studied (e.g., Main Street vs. those backed by venture capital) toidentify interesting and irreducible parts of this heterogeneity, while also identifying places wherewe anticipate future large-scale research and the growing depth of the field are likely to clarifymatters. There are many areas, like how firm performance connects to entrepreneurial personality,that are woefully understudied and ripe for major advances if the appropriate cross-disciplinaryingredients are assembled.Key Words: Entrepreneurs, venturing, personality traits, characteristics, Big-5, risk attitudes,success, goals, demographics, skillsJEL Codes: L26; D03, D81, D86, M13, O30Acknowledgements: Comments are appreciated and can be sent to [email protected] Thisresearch is generously supported by the Alfred P. Sloan Foundation, the Kauffman Foundation,the National Science Foundation, the Smith Richardson Foundation, and Harvard Business School.William Kerr is a Research Associate of the Bank of Finland and thanks the Bank for hosting himduring a portion of this project.2Table of ContentsIntroduction1. Personality traits1.1 Prevalence of characteristics in entrepreneurs vs. other populations1.1.1 Big-5 model1.1.2 Self-efficacy and innovativeness1.1.3 Locus of control1.1.4 Need for achievement1.2 Correlation of personality traits with venture phases1.2.1 Probability of entry into entrepreneurship1.2.2 Growth and success as an entrepreneur1.2.3 Probability of exiting entrepreneurship1.3 Moderating traits and environmental factors2. Risk attitudes2.1 Methods of measuring risk attitudes2.2 Risk attitudes of entrepreneurs vs. other populations2.3 Effect of risk attitudes in the startup process2.3.1 Probability of entry into entrepreneurship2.3.2 Growth and success as an entrepreneur2.3.3 Probability of exiting entrepreneurship2.4 Entrepreneurial self-efficacy, risk attitudes, and optimism3. Goals and aspirations3.1 Reasons for deciding to start a business3.2 Entrepreneurial goals4. ConclusionsAppendix. Other characteristics of entrepreneursA1.1 DemographicsA1.2 Financial assets and wealthA1.3 Industry experience and educationA1.4 Entrepreneurial regionsOnline Appendix. Detailed survey methodologies and study notesA: Summary tables of studies by topicB: Typical Big-5 inventory utilized in entrepreneurship studiesC: Representative examples of survey questions and measures related to risk attitudes3IntroductionEntrepreneurial firms and the founders behind these ventures are in vogue everywhere.Cities across the United States are sprouting new incubators and accelerators and introducingprograms to attract innovative talent. Foreign countries are also quite active, with nations rangingfrom China to Chile experimenting in new ways to foster new firm formation. The fascination withentrepreneurs is not brand new, of course, and a literature dating to the 18th century explores whatdrives entrepreneurs and whether their traits matter for the outcomes of their ventures. Thisliterature now spans many fields and has introduced multiple concepts and methods related to theanalysis of entrepreneurial characteristics. In this review, we collect and organize the latestfindings on the prevalence of various personality traits among the entrepreneurial population andtheir impact on venture performance. We cover academic work ranging from economics topsychology to management studies, with a focus on studies published after 2000.Many studies consider the “traits of entrepreneurs” or the “traits that make entrepreneurssuccessful.” As Åstebro et al. (2014) highlight, the publication in 1921 of Frank Knight’s bookRisk, Uncertainty and Profit marked a key launching point into rigorous and careful research onthe personalities of entrepreneurs that set them apart from general business managers. In thedecades that followed, research has continued to investigate specific individual traits that promptpeople to become entrepreneurs, as well as personal motivations and preferences that keepentrepreneurs on their chosen path. These studies have often focused on high-growth settings orfirms financed by venture capital (VC), where entrepreneurs face a high probability of theirbusiness failing, a very small probability of extremely positive outcomes, and a possibly lowaverage return to the monetary and time investments made into their businesses. Standardeconomic theory must be augmented to explain such a pursuit, and many scholars have tried tounderstand the “homo entreprenaurus” (a moniker introduced by Uusitalo, 2001).Yet, the term “entrepreneur” is also applied in academic research to many groups beyondthe founders of Silicon Valley startups. The studies that we document in this review range in termsof their definitions of entrepreneurship to also include creators of “Main Street” small businessesor even young college students attending an entrepreneurship class. While these groups are allconnected to entrepreneurial activity, recent work shows the remarkable degree to which thesesubpopulations behave differently (e.g., Hurst and Pugsley, 2011, Levine and Rubenstein, 2017),and the typical personality traits of individuals will vary greatly by form of entrepreneurial activity.In our review, we attempt to pay close attention to the group under the microscope of each studyand note where subpopulations are generating different results.We conduct this survey with an applied empirical researcher in mind, although we hopethis review is useful for many others too. Applied researchers today have access to data formeasuring entrepreneurship that was unthinkable a decade ago. Most noticeably, researchers cannow utilize large-scale administrative datasets built on employer-employee data to model4entrepreneurial transitions. Taking the United States as one example, while cutting-edge work inthe 2000s often used firm-level entry rates measured in datasets like the Census of Manufacturesor Venture Xpert, we increasingly have researchers accessing comprehensive panel data onindividuals like the Linked Employer-Household Database to model entrepreneurial transitions.Other countries further hold frontier administrative datasets that combine founding behavior withanything from the prescription drug histories of individuals to their stock portfolios. Beyondadministrative datasets, researchers now build their own specialized datasets: tracking cohortsfrom entrepreneurial training programs; accessing gig economy transactions from a leading onlineplatform; crafting from LinkedIn profiles of entrepreneurs receiving venture financing; conductingcustomized surveys of entrepreneurs in co-working spaces; and much more. This wealth ofopportunity has led to a flowering of research that measures career histories and individual-leveltraits that predict entrepreneurship.While these frontier datasets afford opportunities to ask exciting new questions, researchersmust also confront new challenges. As one considers individual-level factors that promote entry,questions arise as to when and how the personalities of founders should be considered. Some aredirectly interested in the phenomenon, wanting to study for example the risk tolerance of foundersof high-growth startups. For others, the research question lies elsewhere, but there is a worry aboutpersonality being an important omitted factor that biases empirical results. For yet others,personality could be the channel or mechanism through which some studied events produce shortand long-run effects. While some classic studies have looked at how personality traits impacttransitions into self-employment, this new work covers a much broader and more heterogeneousterrain, ranging from the opening of small-scale service businesses to high-growthentrepreneurship. As the options continue to proliferate for modeling individual- and team-levelentrepreneurship, it becomes more important to have a perspective of the personality traitsassociated with entrepreneurship and how they influence the research being conducted.Three decades ago, in a very influential article, Gartner (1988) criticized the study ofentrepreneurial personality traits, arguing instead for a focus on how organizations emerge.Gartner disapproved of the varying definitions being used for entrepreneurship, preferring to focuson a definition that emphasized the functional creation of new organizations. Gartner alsoquestioned collecting traits of entrepreneurs using survey methodologies to discern an “ideal”personality for entrepreneurial performance. The shadow of this critique has been on the literaturefor a long time, and it is far from clear that these new efforts will overcome the challenges thatGartner (1988) outlined, as we re-surface many of these same challenges throughout this review.Yet, the better recognition of heterogeneity among entrepreneurs and powerful new data sourcessuggest it might be fruitful to reexamine some of these areas again, some 30 years later. After all,the focus for many is now on describing how personality may influence the creation of neworganizations, addressing at least some of Gartner’s concern.5We focus our survey on three core themes: (1) the personality traits of entrepreneurs andhow they compare to other groups; (2) the attitudes towards risk that entrepreneurs display; and(3) the overall goals and aspirations that entrepreneurs bring to their pursuits. These themescover most of the main theoretical contributions to the entrepreneurial traits literature, which arequite diverse, while at the same time enabling the identification of common concerns acrossapparently separate research streams. There are some personality traits and cognitive biases thatwe spend less time on, such as over-confidence and how it differs from risk attitudes. This wasnot due to a prejudice against these traits, but mainly the literature-driven foundation of ourinquiry that we describe in the next section. With a few exceptions, we concentrate on empiricalstudies and meta reviews of them to give a flavor of the recent applied work in this field,spending limited time on lab or experimental studies.An appendix to our survey provides a short discussion of some major factors influencingentrepreneurial decisions beyond personality: demographics, household assets and financingconstraints, measurable skills like work experience and education, and local environment. Thisauxiliary discussion is short and far from comprehensive, meant only to provide some backgroundhelpful for understanding the “soft data” covered in this review and how they interact. For thoseinterested in measuring entrepreneurial risk attitudes and personality traits in their own work, anadditional online appendix documents some of the survey instruments commonly utilized. Thisappendix also provides more detailed notes on the research papers that we review.We do not pretend to uncover a once-and-for-all synthesis with this review, and nor do wepretend to resolve longstanding debates like whether entrepreneurs are “born or made.” Theheterogeneity across entrepreneurs within just Cambridge, Massachusetts suggests that a uniqueset of factors does not exist, much less the vast differences in entrepreneurial pursuits acrosscountries, industries, and similar. Few applied researchers when confronted with massiveempirical datasets would even contemplate such grandiose aims. Instead, we provide a unifieddiscussion of the vast body of research related to these three key topics and embrace theheterogeneity where it exists. An accurate and unvarnished depiction of the variance in studies isimportant for contemplating how academic work can provide better empirical insights that informentrepreneurship training programs, policy initiatives designed to bolster startup activity, and soon.In our opinion, the state-of-the art study on entrepreneurial characteristics is one that (1)utilizes longitudinal data on a large and representative sample of individuals, (2) measurespersonality traits before entry decisions are made, and (3) carefully measures individual traits suchas risk aversion and entrepreneurial self-efficacy. These conditions are necessary for statisticallyprecise comparisons of entrepreneurs to other employee and managerial groups, better insight intodifferences across types of entrepreneurs (e.g., self-employed vs. growth-oriented employers), andin-depth analysis of subsequent startup performance. The literature is especially weak on this6performance dimension. These conditions are not sufficient for assigning causal roles forpersonality traits—a very daunting task—but they are probably necessary ingredients. Ahn (2010)and Levine and Rubenstein (2017) are examples of innovative and impressive studies that utilizethe National Longitudinal Survey of Youth (NLSY), although the NLSY’s small sample generatesconstraints. Hvide and Panos (2014) and Caliendo et al. (2014) also show frontier examples thatbuild upon longitudinal administrative records and national surveys. Even with this gold standardin mind, the practical limits of building such platforms—especially the off-the-shelf tradeoff ofusing administrative records that provide universal employment histories but limited collection ofpersonality traits—suggest that there is still much to gain from carefully conducted surveys thatfocus on narrow and clearly specified groups of interest and define a relevant comparison groupthat entrepreneurs are contrasted with.We hope this survey provides a useful input into several complementary streams of work.There are often four-fold or larger differences in entrepreneurship rates across U.S. cities (e.g.,Glaeser et al., 2015), and those for venture capital are even sharper (e.g., Samila and Sorenson,2011). Moreover, the rate of new business formation is declining in the United States (e.g., Deckeret al., 2014). Many business leaders and policy makers are looking to build better environments tosupport entrepreneurship, and this review highlights softer personality traits and risk attitudes thatcan be considered along with more typical factors like financing conditions. As Chatterji et al.(2014) describe, successful interventions to build the entrepreneurial base need to activate the localpopulation, versus just relying on attracting entrepreneurs from afar, and research on these softerelements is of first-order importance in designing quality initiatives and policy experiments.The findings related to personality characteristics and other attributes of entrepreneurs, aswell as the correlation of those characteristics with business performance, also imply that theremay be scope for including some personality development modules in entrepreneurship education.Many academic institutes have introduced entrepreneurship training, ranging from high schools toexecutive programs, but these programs have to date focused more on hard skills rather thanpersonality mapping and softer preparations. While some personality traits are fixed, Rauch (2014)provides some examples of how, for example, self-efficacy and achievement motivation can beinfluenced with relatively simple interventions. A clearer understanding of the specific traits ofentrepreneurs and their heterogeneity may help to better match potential entrepreneurs to settingsthat are most closely aligned with their strengths.Finally, we hope to connect to future academic work. There are very few scholars in thediverse entrepreneurial literature that regularly read the full range of academic output describedbelow, much less utilize it in shaping their own research (including ourselves). Yet, these interfacesare precisely where we need the most urgent attention. To give an example, the very sparse numberof studies that connect firm performance outcomes to the personality traits of entrepreneurs are asignificant limitation to our capacity to describe the quality margin of entrepreneurial ideas.7Applied microeconomics researchers that utilize administrative and longitudinal data have anexcellent toolkit to model these startup outcomes, but they are among the least exposed to the latestperspectives on personality traits. A goal of this survey is to help close these information gaps andencourage more cross-disciplinary work in this area.1. Personality traitsResearch on the personality traits of entrepreneurs took off in the mid-20th century,unifying approaches from economics, psychology, sociology, and business management to answerthe questions: Who is an entrepreneur? What drives them? What traits define them? The first fewdecades faced many conceptual challenges as researchers struggled to develop a solid theoreticalframework and appropriate measurement tools. In 1971, economist Peter Kilby famouslycompared the entrepreneur to A.A. Milne’s Heffalump, a fictional elephant that all investigatorsapproached with improvised proxies from their disciplines, each asserting that they had discoveredthe ever-elusive creature’s behavior.0F1 In the 1980s, this discordance in the literature led someresearchers to conclude that there was no correlation between personality and entrepreneurship(e.g., Brockhaus and Horwitz, 1986; Gartner, 1988).However, since the start of the 21st century and with the notable rise of public andintellectual fascination with startup culture, the entrepreneurial personality literature has enjoyeda resurgence and convergence toward an increasingly consistent set of theoretical frameworks,with meaningful insights toward innovation policy and business education. The bulk of recentliterature seeks to answer two main questions: (1) Do certain traits predict an individual’slikelihood of becoming an entrepreneur, and (2) Do certain traits predict an entrepreneur’slikelihood of achieving “successful” outcomes? These answers are pursued by investigating theprevalence of personality characteristics in entrepreneurs versus other populations, as well as byanalyzing the correlation of these characteristics with entrepreneurial performance factors such asbusiness survival and growth (e.g., Baron, 2004).While personality theory remains rife with its own set of contentions, researchers haveprimarily gravitated over the last few decades to the Big-5 factor personality model. Severaladditional traits have been fused into the Big-5 for entrepreneurial work, including self-efficacy,innovativeness, locus of control, and risk attitudes (which we reserve for individual discussion inthe second part of this literature review). Researchers often mix and match these traits to describea multidimensional “entrepreneurial orientation.” In this literature review, we mostly focus ourdiscussion on literature published after 2000 to detail the newest wave of personality research andthe cutting-edge questions. Rauch et al. (2009), Rauch (2014) and Patterson and Kerrin (2014)provide reviews of some of the seminal contributions that came earlier.1 Kilby (1971) and A.A. Milne, Winnie the Pooh (1926) and The House at Pooh Corner (1928).81.1 Prevalence of personality traits in entrepreneurs vs. other populationsMany researchers compare the traits of entrepreneurs to employed workers or the generalpopulation to identify characteristics that define entrepreneurs as a group. It may seem a foolish orunnecessary task to compare Steve Jobs or Elon Musk to the average person, and many booksdescribe the special biographies and personalities of these great entrepreneurs. Here, however, theliterature has a very different focus. For every Jobs or Musk, we have thousands of entrepreneursseeking growth-oriented businesses and many more seeking to build a business for themselves asself-employed proprietors. The collective impact of these individuals on our economy is enormous,even if they don’t start Apple or SpaceX. This literature is concerned with investigating anddefining the regularities and differences in the personalities of these entrepreneurs.For this review, we combed through hundreds of studies on J-Stor, Econstor, and the online journal databases available at Harvard Business School and Wellesley College, coveringjournal articles and dissertations spanning economics, psychology, and management studies. Werestricted our focus to articles published after 2000, as a resurgence of interest into entrepreneurialbehavior generated a new crop of studies that had not been meaningfully summarized. Data usedin the studies came from the United States, Canada, Australia, New Zealand, Germany, France,Italy and other European economies. We considered articles with various definitions ofentrepreneurs, most commonly self-employed individuals or business owner-managers. Weexcluded studies looking solely at subsistence entrepreneurship, partially because these studies areso sparse. Many of the personality questionnaires were conducted with business-track universitystudents, while other studies used national data sets including all fields and industries ofemployment. While Frese (2009) highlights how entrepreneurial action extends to efforts beyondfor-profit firm creation (e.g., social activism), we focus this survey on the venture creation processin the private sector. We purposefully spend less time on the variations of overconfidence,optimism, and risk taking given the detailed recent review of Åstebro et al. (2014) on these issues.Studies on risk attitudes were searched using the keywords “risk preference,” “riskpropensity,” “risk aversion,” and “risk tolerance.” We included risk measures of various kinds,including self-reported answers in longitudinal surveys, hypothetical gambling situations, andinvestment history metrics. Studies on personality traits were searched using keywords such as“personality,” “traits,” and “orientation,” as well as the specific trait names covered in this survey.We included the most commonly used personality concepts (Big-5, need for achievement, internallocus of control, innovativeness, and self-efficacy). In a few studies that used composite measuresof “entrepreneurial orientation,” we turned to the reported underlying data for disaggregation ofindividual variables. We excluded personality traits for which there was too little literature tosummarize meaningfully: need for autonomy, stress/uncertainty tolerance, tenacity, self-esteem,discipline, delay of gratification, and so on.9After combing through research databases for the relevant and academically rigorousarticles, we compiled them into a set of tables (contained in the online appendix). The first seriesof tables list studies by risk attitudes (28 studies). The second series list studies by personalitytraits: Big-5 (10), need for achievement (12), locus of control (13), self-efficacy/proactivity (11),innovativeness (12), stress/uncertainty tolerance (4) and need for autonomy (4). The third serieslist studies by the stage of business they apply to: career choice/business creation (14),survival/success (14), and exit (1). The final series list studies by other types of comparisons:comparing demographics (11) and comparing with environmental factors (6). These tables formthe starting point of our summary of each subset of literature, as well as comparisons on themethodologies, conceptual tools, findings, and efficacy of each approach.Before reviewing these studies, it is important to identify broad caveats and limitations tothis literature stream. First, many studies lack the preferred structure outlined in the Introduction,with the unfortunate result that it is often unclear as to whether individuals with a given set ofpersonality traits selected into entrepreneurship, or whether the traits were developedendogenously by individuals after becoming entrepreneurs. This reverse causality concern isespecially prominent for cross-sectional surveys and data tabulations. Additionally, even when themeasurement of personality traits does precede entrepreneurial choices, this does not guaranteethat this trait was the causal factor. For example, individuals from wealthy families may score highon risk tolerance levels because they have the security of their family’s money, and perhapsavailability of financial resources is the true factor that prompts entrepreneurship, independent ofrisk tolerance. Without observing and measuring the wealth of individuals, we are liable tomismeasure the role of risk tolerance for decisions. This concern over omitted variable bias is truefor individual studies, and it is compounded when comparing studies drawn from countries andsettings that have differing cultural factors that are also known to influence personality traits, suchas entrepreneurial motivation and achievement orientation (Stewart and Roth, 2007). Finally,survey-based analyses often have small sample sizes, which may explain some of the variation inresults seen across studies.Understanding these caveats, we proceed with a summary of the main personality-relatedresults. The online appendix to this review contains additional details for most of the papersmentioned. The collected information includes country of coverage, personality traits anddemographics considered, measurement approach, data sources and sample size, outcomes andfindings (including reference group), and the population of entrepreneurs considered. While firstdeveloped for our own use, we hope this is a useful resource for those wishing to dig deeper onthese diffuse literatures.101.1.1 Big-5 modelThe Big-5 model is a multidimensional approach towards defining personality, throughmeasuring openness, conscientiousness, extraversion, agreeableness, and neuroticism. It has beenthe predominant model for personality traits since the 1980s, and the Big-5 traits have been foundto influence career choice and work performance (e.g., Costa and McCrae, 1992; Digman, 1990;Goldberg, 1990; John et al., 2008; Rauch, 2014). The five “macro traits” cover a distinct set ofcharacteristics, as described in John et al. (2008, p. 138):• Openness to experience: describes the breadth, depth, originality, and complexityof an individual’s mental and experimental life• Conscientiousness: describes socially prescribed impulse control that facilitatestask- and goal-orientated behavior• Extraversion: implies an energetic approach toward the social and material worldand includes traits such as sociability, activity, assertiveness, and positiveemotionality• Agreeableness: contrasts a prosocial and communal orientation toward others withantagonism and includes traits such as altruism, tender-mindedness, trust, andmodesty• Neuroticism: contrasts emotional stability and even-temperedness with negativeemotionality, such as feeling anxious, nervous, sad, and tenseDifferences between entrepreneurs and managersThe bulk of the existing studies comparing the prevalence of Big-5 traits betweenpopulations of entrepreneurs and managers occurred between 1960 and 2000. Managers arefrequently used as a comparison point for entrepreneurs given the potential need of both groups todirect workers and manage multiple tasks. In a meta-analysis of 23 studies conducted from 1970to 2002 in a variety of countries and reported in English-language journals, Zhao and Seibert(2006) find entrepreneurs to be more open to experience, more conscientious, similar forextraversion, less agreeable, and less neurotic (or in the Big-5 lingo, O+, C+, E, A-, N-). Manyindividual studies, of course, show deviations from this pattern. For example, in a survey by Envickand Langford (2000) of 218 entrepreneurs and managers in a large Canadian city, the authors findentrepreneurs to be significantly less conscientious and agreeable than managers and lessextraverted (O+, C-, E-, A-, N-), while confirming the other patterns observed in the meta study.These characteristic differences between entrepreneurs and the average employed personare often theoretically ascribed to the “attraction-selection-attrition model” (Schneider, 1987).According to this model, workers are attracted to jobs whose demands and opportunities matchtheir talents, motives, and personality traits; employers or financiers then select applicants whoseaptitudes and motives fit their criteria; and workers then stay in their occupational group when11they find their professional situation more rewarding than alternative positions. We review nexteach of these five traits as they would be presented in this model.Entrepreneurs are consistently found to be more open to experience than managers (O+).Researchers hypothesize that in the context of a business venture, an entrepreneur is likely to beattracted to constantly changing environments and the novelty of new challenges. Individuals whothrive on challenges and novel environments are those who present creative solutions, businessmodels, and products, and the openness of entrepreneurs may aid these functions. Meanwhile,managers are often selected by their superiors for their ability to execute and deliver high-qualityand low-variance results for a given set of directions rather than seek out original solutions. Thus,researchers theorize that both the environment and job requirements of an entrepreneur select forindividuals who are more open to experience.Zhao and Seibert (2006) suggest that higher conscientiousness is the most significantdifference between entrepreneurs and managers (C+). Conscientiousness is a composite ofachievement motivation and dependability. Zhao and Seibert (2006) find that entrepreneurs andmanagers are similar in dependability, but entrepreneurs score significantly higher than managersin the achievement facet. In a meta-analysis of 41 studies, Collins et al. (2004) also conclude thatindividuals who pursue entrepreneurial careers are significantly higher in achievement motivationthan individuals who pursue other types of careers, and Stewart and Roth (2007) similarly concludethat entrepreneurs are more achievement-oriented than managers. It is frequently hypothesized thatthose with high achievement motivation are drawn to environments in which success is moreclosely attributed to their own efforts, rather than a larger institutional setting in which businesssuccess or failure is less a function of one’s individual efforts.There is a lack of consensus on whether entrepreneurs score higher than managers onextraversion (E). This trait measures the extent to which one is dominant, energetic, active,talkative, and enthusiastic (Costa and McCrae, 1992). Some researchers hypothesize thatextraversion could be more important for entrepreneurs than managers since entrepreneurs act assalespeople for their ideas to investors, partners, employees, and customers. Zhao and Seibert(2006) conclude, however, that no reliable difference emerges in the literature. Envick andLangford (2000), who found that entrepreneurs were less extraverted than managers, suggestedthat many entrepreneurs may run small businesses from their homes to be away from largebureaucracies that demand one to be relentlessly sociable. This is an area where the definition of“entrepreneur” matters greatly: self-employed persons and growth-oriented founders tend toexhibit very different characteristics.Finally, entrepreneurs are often found to have modestly smaller amounts of agreeablenessand neuroticism (A-, N-) but these differences measured are quite small between entrepreneursand managers. Some researchers hypothesize that, because most entrepreneurs eventually becomethe CEOs of their own ventures, they do not need to worry about pleasing other people around12them, whereas managers must at least please their own bosses. Zhao and Seibert (2006) findentrepreneurs to be less neurotic than managers, suggesting that this is because entrepreneursrequire exceptional self-confidence to take on the risks of starting a venture. Overall, however,there is not a strong pattern of significant results in the current literature on these two dimensions.Differences across entrepreneurial populationsRecent work seeks to measure these traits across different types of entrepreneurs ordifferent levels of intent, and these variations are as exciting and policy relevant as the macro-leveldepiction of entrepreneurs versus the average person. Antoncic et al. (2015) conduct 62 face-toface interviews at firms and 501 questionnaires at educational institutions in Slovenia, classifyingpeople into four groups: practicing entrepreneurs who already own a firm (30.2% of responses);potential entrepreneurs who intend to establish their own firm in the following three years (9.9%);maybe-entrepreneurs who might establish their own firm sometime in the future (46.7%); or nonentrepreneurs who never intend to set up their own firm (13.2%). The study finds variations thatmirror the meta-survey results for openness: practicing entrepreneurs are the most open toexperience, potential entrepreneurs slightly less open, maybe-entrepreneurs even less open, andnon-entrepreneurs the least open. The surveyed entrepreneurs are also less agreeable, but thepatterns in meta-analyses are not reflected for conscientiousness and neuroticism (in total, O+, C,E+, A-, N). Antoncic et al. (2015) corroborates the broad consensus that entrepreneurs tend to bemore open to experience than the general population, while the other traits are harder to determine.What lies behind this latter uncertainty? Much of the variation across individual studiescan be attributed to the small sample sizes, which usually only capture a few hundred respondents(Envick and Langford, 2000; Antoncic et al., 2015). But small sample sizes are unlikely to be theonly answer, as the patterns in meta-analyses like Zhao and Seibert (2006) and Zhao et al. (2010)overlap but are also not fully congruous. This limitation for meta-analyses may in part reflect theinfluence of environment on each entrepreneurial population’s traits, such that generalizationsacross populations, industry, and culture are an impossible task. Necessity- versus opportunitydriven entrepreneurs certainly bring different personality traits, and even the opportunity-drivenentrepreneurs in New York City might be different from those in Silicon Valley. Perhaps as morestudies are conducted, we will become better equipped to separate the noise of small samples fromthe actual differences in personality traits for entrepreneurship across environments, which wouldbe a major accomplishment.Another critique of the Big-5 framework is the overly general nature of these macropersonality traits, such that they cannot easily predict situation-specific behaviors of entrepreneurs;also, an understanding of a person’s Big-5 personality may not help in understanding the specificmechanisms through which personality impacts entrepreneurial attitudes and actions (e.g. Kanfer,1992; Rauch, 2014). Frustrated by these limitations of the Big-5 framework to describe a coherentportrait of the entrepreneur, researchers have shifted toward creating a multidimensional13personality framework that incorporates other qualities like self-efficacy, innovativeness, locus ofcontrol, and need for achievement. We describe these next.1.1.2 Self-efficacy and innovativenessIn the uncertain and competitive environment of new venture creation, many researchershypothesize that entrepreneurs thrive on a strong sense of personal self-efficacy to execute theirvisions and a keen eye for innovation to identify new products and markets. Self-efficacy describesa person’s “belief that he/she can perform tasks and fulfill roles, and is directly related toexpectations, goals and motivation” (Cassar and Friedman, 2009). High self-efficacy correlateswith work-related performance (Stajkovic and Luthans, 1998), small business growth (Baum andLocke, 2004), academic performance (Hacket and Betz, 1989; Luszczynska et al., 2005), andcareer choice (Lent and Hackett, 1987). Self-efficacy is measured on two levels of specificity,either as generalized self-efficacy or domain-specific Entrepreneurial Self-Efficacy (ESE). Mostresearchers focus on the more situation-relevant ESE measure.Chen et al. (1998) define ESE as a composite of self-efficacy toward five tasks: innovation,risk-taking, marketing, management, and financial control. Surveying students in three businessstudy programs, they find that entrepreneurship students have a higher ESE average in marketing,management, and financial control than did organizational psychology and management students.Perhaps entrepreneurship programs draw students who feel confident in many areas due to thediverse demands of being an entrepreneur, or it could be that study of entrepreneurship instills thisESE. Chen et al. (1998) also finds that business founders have a higher ESE in innovation andrisk-taking than non-founders, even as the locus of control remains the same across the twopopulations. In addition, researchers hypothesize that entrepreneurial types may also simply bemore confident, which would induce them to score themselves higher across the board in thesubjective surveys typically used to collect data. We discuss evidence related to this point below.Rather than evaluating whether entrepreneurs have a greater ESE than other groups (which seemsa somewhat tautological question), most researchers have focused on the effect of ESE on firmperformance. This evidence will be considered in section 1.2.Utsch and Rauch (2000) examine innovativeness and initiative as mediators ofachievement orientation, which in this case is a composite measure of self-efficacy, higher-orderneed strength, need achievement, and internal locus of control. Their surveys and interviewscapture 201 German entrepreneurs defined as founders, owners, and managers of a small businesswith less than 50 employees. Innovativeness is found to be a mediator, while initiative is not. (Thepsychology literature talks about “mediators,” which for an economist roughly means a mechanismvia which one thing impacts another.) Likewise, innovativeness correlates positively andsignificantly with the personality traits of self-efficacy, higher-order need strength, and needachievement, but not with internal locus of control.14In general, innovativeness refers to how individuals respond to new things (Goldsmith andFoxall, 2003). Innovativeness can be considered as a global or domain-specific personality trait,or as a behavioral concept such as the adoption of new products by consumers. Different ways tomeasure innovativeness have been suggested at least since the 1970s (Hurt et al., 1977), but nouniform measure exists across the studies reviewed here. In one study, Marcati et al. (2008) arguethat domain-specific innovativeness of founders completely mediates their general innovativenessin a sample of 188 entrepreneurs of small- and medium-sized firms of various industries. Bothforms of innovativeness display generally consistent correlations with Big-5 traits, not indicatingmajor differences in their origins.Kickul and Gundry (2002) analyze the relationship between 107 small-firm ownermanagers’ strategic orientation, personality, and innovation. They adopt the Miles and Snowstrategic orientation typology, which divides business strategies into prospector, defender,analyzer, and reactor strategies.1F2 Kickul and Gundry (2002) find that the prospector strategicorientation mediates proactive personality and three types of innovations: innovative targetingprocesses, innovative organizational systems, and innovative boundary supports. They likewisefind that those with proactive personalities are more likely to both take on a prospector strategyorientation and innovate in their work, which is to be expected.Given the vast number of Big-5 and risk attitude studies (the latter of which are discussedbelow in Section 2), it is quite surprising how little attention has been paid to the innovativenessof entrepreneurs as it relates to their personalities. This is a place where the biographies of SteveJobs alone likely outnumber the formal academic studies! Nevertheless, scholars likely agree thatentrepreneurs need to be able to tolerate some risk and to create or recognize new businessopportunities, perhaps also innovating new products and concepts that can be brought to market.Related industry-level evidence certainly supports this, with industries showing high rates of entryby small firms also tending to have high rates of innovation and high productivity growth (Parker,2009).One explanation for this gap may be related to the measurement of “innovativeness”: wesimply do not have an agreed-upon set of survey questions to measure someone’s innovativenessin the way that we can measure risk preferences or Big-5 traits. As such, the metrics used in theliterature are scattered, and universal, domain-specific measures of entrepreneurial innovativenessremain elusive. Another explanation is that the identification of ESE traits is especially sensitiveto the reverse causality and omitted variable bias concerns described earlier, raising the difficulty2 Barney and Griffin (1992): “A prospector strategy constantly seeks out new markets and opportunities; a defenderstrategy concentrates on protecting current markets and maintaining stable growth; an analyzer strategy both tries tomaintain market share and seek out new market opportunities; a reactor strategy fails to anticipate or influence eventsin the environment.”15in studying it or in interpreting results (Bandura, 1997; Forbes, 2005). Consequently, scholars maybe reluctant to pursue it for fear of limited publication possibilities.2F3Cassar and Friedman (2009) compare nascent entrepreneurs in the startup phase of newventures with a control group drawn from the general working-age population. A nascententrepreneur is defined by the Panel Study of Entrepreneurial Dynamics (PSED) as anyone whois currently trying to start a new business, expects to be an owner or part owner of the firm, andhas been active in doing so for the past 12 months. Cassar and Friedman (2009) assert that theirdata, drawn from the PSED and interview and survey responses of 431 American nascententrepreneurs, overcome inference challenges due to venture survivorship and recall bias. Theypresent evidence that higher ESE increases the likelihood of being a nascent entrepreneur as wellas the successful founding of an operating business.To sum, theory and a limited dose of empirical evidence suggest that entrepreneurs possesshigher self-efficacy than managers and non-entrepreneurs (Chen et al., 1998). This is perhapspartly due to proactive personalities being more likely to innovate (Kickul and Gundry, 2002).Innovativeness, in turn, can mediate one’s achievement motivation in a way that mere initiativedoes not (Utsch and Rauch, 2000). In a longitudinal study, Cassar and Friedman (2009) confirmthat those with high ESE are more likely to become nascent entrepreneurs and successful founders.However, the limits of this literature should not be downplayed. There is still a clear lack of studiessuccessfully isolating the pre-founding characteristics of to-be entrepreneurs on these dimensions,as well as longitudinal studies that track characteristics of individuals over time. Given the highpotential for endogenous ESE, this is a large caveat to be addressed.1.1.3 Locus of controlAn important trait in the entrepreneurship literature is locus of control (LOC). A personwith an internal LOC conceptualizes that their own decisions control their lives, while those withan external LOC believe the true controlling factors are chance, fate, or environmental featuresthat they cannot influence. Rotter’s (1954) theory of social learning first introduced the LOCconcept. Persons with internal LOC believe that they can influence outcomes through their ownability, effort, or skills, rather than external forces controlling these outcomes. Previous researchhas linked belief in internal control to the likelihood of engaging in entrepreneurial activity (e.g.,Shapero, 1975; Brockhaus, 1982; Gartner, 1985; Perry, 1990; Shaver and Scott, 1991).3 Many studies instead focus on the “innovativeness” of the firm rather than on that of the founder, basing theiranalyses on patents, R&D efforts, reported product and process innovations, and similar measurable firm traits. Weabstract away from those studies, which are obviously important in their own way, to maintain the survey focus onthe personality findings. Hyytinen et al. (2015) provide a strong survey of this parallel literature and analyze Finnishsurvey data combined with official business register data. They find a positive correlation between the innovativenessof the firm and its survival, although a causal interpretation is not established. For risk-loving entrepreneurs, anypositive impact of firm innovativeness turns negative.16Many researchers emphasize LOC in their work. Barrick and Mount (2005) claim that“specific ‘traits rely on explicit description of entrepreneurial activities that may be situated intime, place and role,’ which is why specific characteristics such as risk tolerance, need forachievement, or locus of control are more useful in predicting entrepreneurial performance thanthe Big Five.” Caliendo et al. (2009) re-evaluate that assertion and, along with other researchers,suggest that traits such as LOC can be more directly extrapolated onto decision-making in theprofessional field.Notably, LOC is considered to be a culturally dependent trait. Mueller and Thomas (2000)find that countries with more individualistic cultures (as opposed to collectivist cultures) showgreater internal LOC, and that LOC and innovativeness are both learned traits.3F4 This culturalvariance is affirmed by Tajeddini and Mueller (2009), who find that LOC is higher in Britishentrepreneurial populations than Swiss entrepreneurial populations in the high-tech industry. Theauthors argue that the difference could be related to the Hofstede’s (1980) defined variations incultural characteristics such as individualism, uncertainty avoidance, and risk propensity.Many researchers find internal LOC to be stronger in entrepreneurial populations than inother populations. Levine and Rubenstein (2017) find in NLSY longitudinal data that those whobecome a self-employed person running an incorporated business display a strong internal LOCprior to founding their firm than those who are employed by others or self-employed inunincorporated businesses. This echoes earlier findings by Evans and Leighton (1989), and manystudies find parallel results. In a cross-sectional study, Korunka et al. (2003) measure that Austrianentrepreneurs (defined as “successful new owner-managers”) have a strong internal LOCcompared to “nascent entrepreneurs.” Gürol and Atsan (2006) find that Turkish students who aremore entrepreneurially inclined have a higher LOC. Caliendo et al. (2014) argue that internal LOCis among the personality traits that best predicts entrepreneurial entry and exit decisions.Hansemark (2003) finds in tracking Swedish entrepreneurship students over 11 years that LOCpredicts entry into entrepreneurship for men but not for women.Looking within entrepreneurial populations, a higher internal LOC is further associatedwith venture growth. Rauch and Frese (2007) find in their meta-analysis that an internal LOC hasa significant correlation with business creation and eventual business success. Surveying 168Chinese entrepreneurs in small and medium-sized enterprises in Singapore, Lee and Tsang (2001)find internal LOC positively correlates with venture size and growth rates. At the same time, Leeand Tsang (2001) note that personality traits are less important than industrial and managerialexperience and skills in explaining firm growth in their sample. Overall, the LOC personality traitfinds extensive support and is rather homogeneous across types of entrepreneurs.4 The Hofstede (1980) index places countries such as the United States, United Kingdom, Canada and Ireland to theindividualist end of the spectrum, and countries such as China and Singapore to the collectivist end of the spectrum.See also Thomas and Mueller (2000).171.1.4 Need for achievementThe need for achievement refers to an individual’s desire for significant accomplishment,mastering of skills, and attaining challenging goals. Researchers hypothesize that entrepreneursmight hold a high need for achievement, as building a business from scratch demonstrates one’sindividual abilities in ways that are often hard to match when working within a system in whichresponsibility is diffuse. Along with LOC, this important role for need for achievement finds strongsupport in the literature along several dimensions.Need for Achievement (nAch) is a concept based on McClelland (1985) “acquired-needstheory” and is one of the dominant needs affecting individual actions in a workplace context. Theconcept was first introduced by Murray (1938), and later developed and popularized byMcClelland (1961, 1985). Many researchers have found that a high need for achievement predictsentry into entrepreneurship, although this finding is sometimes challenged in specific contexts.Among the settings discussed above, the higher need for achievement is evident in the studies ofthe Austrian entrepreneurs (Korunka et al., 2003) and the Turkish students (Gürol and Atsan,2006), but not in the study of Swedish entrepreneurship students (Hansemark, 2003). Comparingfour Austrian studies, Frank et al. (2007) conclude that the need for achievement selectsindividuals for entry into entrepreneurship. Turning to comparative analyses across countries,Stewart and Roth (2007) conclude from a meta-analysis of 18 studies and 3,272 subjects thatentrepreneurs exhibit a higher achievement motivation than managers regardless of country or typeof instrumentation (“projective” or “objective”).4F5 Further differences are also evident across subgroups of venture founders. Mueller and Thomas (2000) find that Swiss entrepreneurs have ahigher need for achievement than U.K. entrepreneurs, suggesting that the trait varies acrosscultures and countries.Some researchers also identify a link between the need for achievement and businessperformance. For example, the meta-analysis of Collins et al. (2004) finds that both projective andself-reported measures of achievement motivation predict entrepreneurial intentions andperformance. Rauch and Frese (2007) find similar results. However, Frank et al. (2007) argue thatthe need for achievement, along with other personality factors, is much less relevant thanenvironmental resources and many “process configurations” (such as the set of managementfunctions including planning, organization, and human resource practices) in explainingentrepreneurial performance.5 Projective instruments utilize unstructured stimuli to get respondents to reveal underlying or hidden emotions orinternal conflicts (e.g., Holzman inkblot tests), whereas objective tests utilize comprehensive personality instruments.181.2 Correlation of personality traits with venture phasesWe noted in the Introduction that research has mostly investigated how personalitycharacteristics correlate with probability of entry into and exit out of entrepreneurship, as well aswith various measures of success as an entrepreneur (including venture creation, venture growth,and long-term venture survival). By contrast, academic work is only beginning to scratch thesurface of how personality characteristics link to specific phases in the venture process or toconsider narrower topics like industry-specific innovation or business plan quality.1.2.1 Probability of entry into entrepreneurshipEntry into entrepreneurship is often defined as the act of starting a new business venture.The correlation between personality traits and probability of successful entry into entrepreneurshipis typically measured in two ways. First, taking advantage of university settings, many researchersanalyze student personalities in correlation with their current entrepreneurial intent, their perceivedlearning, perceived ability, and personal investment. Second, studies use national longitudinalpanel datasets like the PSED or the German Socioeconomic Panel (GSOEP) to track whethermeasured personality traits in those large-scale surveys predicted later business founding.Cross-sectional studies and meta-analysesResearch teams surveying student populations focus by necessity on future careerintentions and early developmental views of entrepreneurship. For example, Singh and DeNoble(2003) examine the relationship between the Big-5 traits and entrepreneurial intent, perceivedability, and personal investment among 342 students at a large state university on the west coastof the United States. They find that openness is positively related to perceived ability and personalinvestment, whereas neuroticism negatively relates to intent and ability. They also test forvariability between studies that had defined entrepreneurs as founders versus business leaders,finding no significant differentiation between the two categories. Synthesizing 60 studiesdescribing the relationship between Big-5 traits and entrepreneurial intentions and performance,Zhao et al. (2010) find that entrepreneurial intentions are positively related to openness toexperience, conscientiousness, extraversion, emotional stability, and risk propensity, and that onlyagreeableness was irrelevant in explaining entrepreneurial intentions (O+, C+, E+, A, N-). Amongthese, risk propensity garners the strongest support, followed by openness and emotional stability.Looking to non-Big-5 traits, Korunka et al. (2003) survey 1,169 nascent entrepreneurs andnew business owner-managers in Austria to study their action patterns. Of 627 new businessowner-managers, 153 who meet success criteria also display a high need for achievement, highinternal LOC, and medium risk-taking propensity. The study also considered three startupconfigurations for nascent entrepreneurs to combine analysis of personality traits with situationalfactors. The first configuration, “nascent entrepreneurs against their will,” consists of those with a19strong push factor and comparatively little social or network support. This group holds acomparatively low need for achievement, low internal LOC, and low personal initiative. The“would-be nascent entrepreneurs” have unfavorable financial situations but otherwise strong selfrealization motives and internal LOC. Finally, “networking nascent entrepreneurs with riskavoidance patterns” have supportive environments and strong resources, yet high risk-avoidance.In a sample of 265 Master of Business Administration (MBA) students across fiveAmerican universities, Zhao et al. (2005) find that individuals are most likely to formentrepreneurial intentions directly because they have high ESE, which in turn is influenced bylearning and experience, and to a lesser degree, by risk propensity. However, even as gender wasnot related to ESE, women reported lower entrepreneurial career intentions, suggesting that therelationship of gender to entrepreneurial intentions is likely quite complex. As pointed out byMiao, Qian, and Ma (2016) in their meta-analysis of ESE, most other studies also find a positiverelationship between ESE and entrepreneurial intentions and/or venture creation.5F6To summarize these cross-sectional studies and meta-analyses, students who displaycertain Big-5 traits (i.e., more open to new experiences, more conscientious, more extraverted, andless neurotic) and higher levels of ESE, internal LOC, and need for achievement are the groupmost likely to enter entrepreneurship after graduating from university. These studies also highlightthe environmental and gender factors that influence these choices.Longitudinal studiesTo move from entrepreneurial intentions to actual business formation, researchers need totrack a group over time. For example, Hansemark (2003) tracks students from a Swedishentrepreneurship program over an 11-year period by matching psychological data with Swedishregistries of new businesses. The author measures the predictive validity of initially measuredpersonality characteristics toward becoming an entrepreneur at some point in the future, relativeto a matched control group. Internal LOC has predictive validity for men but not for women;somewhat surprisingly the need for achievement is not predictive for either gender. These resultsare inconsistent with those of Korunka et al. (2003) and two studies discussed next.Kessler et al. (2012) interview 227 Austrian business founders three times between 1998and 2005. The authors find that personality traits of need for achievement, LOC, and risk takingpredict early success, measured by first sales revenues, but not longer-term business survival. Therelevance of internal LOC is also observed in the Caliendo et al. (2014) study of 10 waves of theGSOEP from 2000 through 2009. More broadly, the GSOEP study finds that some personalitytraits, such as openness to experience, extraversion, and risk tolerance, predict entry, but entirelydifferent ones, such as agreeableness or other levels of risk tolerance, govern exit choices from6 In addition to studies already mentioned, see also Miner (2000), Müller and Gappisch (2005), Barbosa, Gerhardt,and Kickul (2007), and Wilson, Kickul, and Marlino (2007).20self-employment. Only internal LOC holds a similar influence on both the entry and exit decisions.Caliendo et al. (2014) report that these personality traits can explain 30% of the overall variance,with risk tolerance, LOC, and openness leading the way.Two studies specifically consider the impact of ESE on various phases of theentrepreneurial process. First, Cassar and Friedman (2009) find in the PSED sample that ESEincreases the likelihood of creating an operating business. Second, Brinckmann and Kim (2015)report that ESE facilitates the development of formal business plans, while entrepreneurialperseverance tends to promote engagement in business planning studies.To summarize, recent literature mostly agrees that internal LOC and need for achievementare important predictors of entry into entrepreneurship. Risk-taking is also found to correlate withbusiness founding but not necessarily with performance or exit. Finally, there also seems to be alink between ESE and business founding, as well as with specific related functions such as businessplanning skills.1.2.2 Growth and success as an entrepreneurMost researchers and policymakers are interested in not only what traits predict entry intoentrepreneurship, but what traits contribute to successful venture performance measures such asgrowth, investment, long-term survival, and self-reported success. The literature becomes rathersparse and idiosyncratic over these various metrics, so we cycle quickly across them and providesome sample findings. (In addition, it is worth recalling that some studies would consider theinnovativeness discussed above as a personality trait as a possible outcome metric.)Firm growth is one of the most common measures of venture success. In their sample of201 German founders, Utsch and Rauch (2000) find that measures of innovativeness predictemployment growth and profit growth, while measures of initiative correlate only with profitgrowth. Additionally, they find a positive interaction effect between innovation and ESE.6F7 Baumand Locke (2004) conduct a six-year longitudinal study of North American architecturalwoodwork firms. They find that situationally specific motivations of goals, self-efficacy, andcommunicated vision have direct effects on venture growth, mediating other traits like passion,tenacity, and new resource skill.In some settings, researchers can study how personality traits correlate with firminvestment. Cassar and Friedman (2009) find that ESE increases the amount of personal resourcesan entrepreneur invests into a venture, as measured by proportion of personal wealth invested inthe venture and number of hours per week devoted to the venture. This type of personal investment7 Miao et al. (2016) synthesize 26 studies in their meta-analysis of ESE and firm performance to find a moderatelysized positive correlation (0.309) between these variables.21is also reflected at the student level, with Singh and DeNoble (2003) finding that personality couldpredict the amount of time students spent preparing for future business efforts.Another popular measure is the long-term survival of the firm, as it can be readily measuredthrough techniques as simple as business registers, web presence, or phone directories. Ciavarellaet al. (2004) find that high conscientiousness is positively related to long-term venture survival(eight years or more), compared to a negative relationship for the entrepreneur’s openness toexperience and no relationship for the other Big-5 personality traits.Many surveys ask entrepreneurs to rate their success. Different entrepreneurs may havevery different views as to how successful their ventures are, and the typical proxies used byresearchers (e.g., growth and survival) may not correlate very well with the self-defined successor performance. For example, Poon et al. (2006) assess performance among 96 Malaysianentrepreneurs by asking respondents to rate their company’s growth, sales volume, market share,and profit using a scale ranging from ‘very poor’ (1) to ‘very good’ (5). Respondents rate thesefour performance criteria relative to that of competitors and their own expectations, yielding an 8-item performance scale. The study finds that internal LOC is positively connected to firmperformance, but lesser support exists for ESE and achievement motivations.Finally, researchers summarize the relationship between personality traits and successfulventure performance through meta-analyses. For example, Rauch and Frese (2007) identify thatthe traits most significantly correlated with business success include the need for achievement(.30), innovativeness (.27), “proactive personality” (.27), generalized self-efficacy (.25), stresstolerance (.20), need for autonomy (.16), locus of control (.13), and risk-taking (.10). The authorsnote that these relationships are of moderate magnitude and that heterogeneity across the differentstudies allow the possibility of moderators, which could be included for future studies. Anothermeta-analysis by Zhao et al. (2010) finds that conscientiousness, openness to experience,emotional stability, and extraversion are positively related to entrepreneurial firm performance asmeasured by firm survival, growth, and profitability. While risk taking is positively related tobusiness foundation, it does not correlate with eventual business growth and success.Additional studies focus on how intelligence interacts with the personality traits. Oneexample is the Baum and Bird (2010) field study of 143 U.S.-based founders of high-growthprinting industry firms. The authors find that “successful intelligence,” which is defined by themto consist of practical, analytical, and creative elements, combines with high ESE to promoteventure growth over four years. Likewise, Hmieleski and Corbett (2008) find that improvisationalbehavior combined with high ESE has a positive relationship with sales growth. It is often difficultto bring much conceptual order to these studies as they combine personality traits with differentempirical constructs, and the results are sometimes counterintuitive. We worry most about studieswhere individuals define whether they are successful, and such statements are very subjective andcan only be evaluated against initial goals for the business, which vary substantially.221.2.3 Probability of exiting entrepreneurshipWhile many researchers scrutinize the decision to start a firm, very few consider howpersonality characteristics relate to decisions to exit from entrepreneurship. As a rare exception,Caliendo et al. (2014) find using the GSOEP panel dataset that agreeableness increases thelikelihood of exit from entrepreneurship, and an internal LOC makes exits less likely. The authorsnote that risk tolerance also had a non-monotonic relationship with the exit decision.1.3 Moderating traits and environmental factorsPersonality characteristics correlate with each other, while at the same time being impactedand shaped by environmental forces. Researchers in all disciplines frequently describe howpersonality factors interact with or are moderated by other individual traits (e.g., gender, education)and external conditions (e.g., industry dynamics, city traits). For example, we noted earlier theTajeddini and Mueller (2009) study that compares 133 Swiss entrepreneurs with 120 Britishentrepreneurs in the high-tech industry. U.K. techno-entrepreneurs scored higher on surveys inautonomy, risk propensity, and LOC, while Swiss techno-entrepreneurs scored higher onachievement need, tolerance for ambiguity, innovativeness, and confidence. Because thetechnology industries in both countries are quite similar in terms of development and institutionalsupport, Tajeddini and Mueller (2009) attribute the variation to cultural differences rather thanother environmental factors.Similarly, Hmieleski and Baron (2008) examine a three-way interaction of ESE,dispositional optimism, and environmental dynamism on firm performance (e.g., revenue growthand employment growth). The researchers define environmental dynamism as the rate ofunpredicted change occurring within a given industry, following approaches of Dess and Beard(1984) and Sharfman and Dean (1991). They find that high ESE improved firm performance indynamic environments when combined with moderate optimism, but was detrimental whencombined with high optimism. In stable environments, ESE’s effects are weak and not moderatedby optimism. Hmieleski and Baron (2008) conclude that high ESE is not always beneficial forentrepreneurs and that environment and industry difference may interact strongly with personalitytraits in terms of their impact for venture outcomes.Researchers in some disciplines (but rarely economics) go further than the study ofinteractions to construct “a complex process model of the entrepreneur,” in which the relationshipsamong these variables are mapped out and ultimately govern venture success. The followingdiagram is adapted from Frese (2009) and Brandstätter (2011) to illustrate this process.23Entrepreneurship does not occur in a vacuum, and personality traits, human capital, andenvironment weave the context for each attempt to start and operate a new business. Regardless ofdiscipline, this complex and integrated nature of entrepreneurship suggests that researchers mustapproach their setting carefully to reach reliable conclusions and be careful to consider how muchthe results of any one study can port across locations.2. Risk attitudesThe world of business venturing is incredibly risky, especially for those seeking highgrowth opportunities. Åstebro et al. (2014) report that over half of startups are no longer operatingafter six years, and 75% of entrepreneurs exit with no equity. What is it then that draws 400,000individuals in the United States every year to start a firm with at least one employee? Oneprominent explanation is risk tolerance, which we explore in this section.Discussions of risk and entrepreneurship date back to Knight (1921), who proposes thatentrepreneurs are differentiated from others by their astuteness toward perceiving and acting onopportunity despite uncertainty and risk. Knight further separates risk, where the probability offuture states of the world are knowable if beyond one’s control, from uncertainty, where it is hardto even describe exactly what the future states might be. Pure risk can often be priced anddiversified away, while Knight identifies entrepreneurs as those who can handle well this business24uncertainty. Despite the intuitive and important nature of this distinction, most subsequent workhas continued to meld together risk and uncertainty.7F8Khilstrom and Laffont (1979) develop a very popular theory model which predicts that themost risk-averse people will become employees while those with low risk aversion will becomeentrepreneurs; Feng and Rauch (2015) provide simpler forms and extensions of this very technicalmodel. Åstebro et al. (2014, p. 55) summarize the standard expected utility model of riskpreference as such: “Risk preferences are defined by the utility function over wealth in the standardexpected utility framework. Most people have utility functions that imply risk aversion, and suchpeople are more willing to take work with regular and less-variable pay. However, a smallerproportion of people—who exhibit less curvature in their utility functions over wealth, and thusless risk aversion—are more likely to be attracted to the possibility of large gains from highly riskyventures such as entrepreneurial activity. Thus, holding constant other factors such asentrepreneurial ability and financing constraints, the individual’s preferences over risk can play acritical role in determining the entry decision.”Risk attitudes are described in the literature as risk preferences, risk tolerance, riskaversion, and risk propensity. All usages of the concept attempt to answer the question of whethersomething in an individual’s personality predisposes them to take on the risky conditions ofentrepreneurship and the impact of this personality trait on outcomes.2.1 Methods of measuring risk attitudesOne approach toward measuring risk attitudes uses self-reported metrics. These questionsvary on levels of specificity, as many are derived from longitudinal surveys that are not specificallytailored toward entrepreneurship. For example, the GSOEP used by Caliendo et al. (2009) includesthe general risk-attitude question, “How do you see yourself: Are you generally a person who isfully prepared to take risks or do you try to avoid taking risks?” Ekelund et al. (2005), who use theNorthern Finland 1966 Birth Cohort Study, study more indirect questions about general riskattitudes, such as “I usually feel tense and worried when I have to do something new andunfamiliar” and “Most of the time I would prefer to do something a little risky (like riding in anautomobile over steep hills and sharp turns)—rather than having to stay quiet and inactive for afew hours.” Block et al. (2015) use a self-scoring question that asks, “In your entrepreneurialdecisions, are you prepared to take risks, or do you try to avoid taking risks?”The most obvious criticism of self-reported risk-aversion measures is that incompleteknowledge of oneself may lead a respondent to see him/herself differently than he/she appears to8 In some sense, the portrait of the risk-taking entrepreneur can also be traced back to Schumpeter’s (1935) notion thatentrepreneurs take advantage of existing opportunities by converting a new idea or invention into a “successfulinnovation,” which inherently sounds like a risky and uncertain activity. However, Schumpeter states that the risk isborne by the investor or the “capitalist,” not the entrepreneur.25others. Entrepreneurs are frequently found to be overconfident (Åstebro et al., 2014), possiblyskewing self-reported results. Additionally, general attitudes may not transfer to attitudes towardthe startup process, as one’s risk attitude toward driving a fast car could be unrelated to one’s riskattitude toward one’s career or finances. Some researchers address this by presenting hypotheticalbut business-specific scenarios (or “vignettes”) to measure risk attitudes. Where possible, otherresearchers who worry about the self-confidence or self-knowledge gap turn to directly examiningentrepreneurs’ investment portfolios and indices of demonstrated action that could be indicativeof their attitudes to risk.Among hypothetical situational questions used to measure risk attitudes, there is variationbetween questions on general financial risk-taking and more entrepreneurship-specific settings.Some surveys present a question about career choices with an either/or answer. For example, thePSED asks: “Assuming you are the sole owner, which situation would you prefer? (1) A businessthat would provide a good living, but with little risk of failure, and little likelihood of making youa millionaire, or (2) A business that was much more likely to make you a millionaire but had amuch higher chance of going bankrupt.” The NLSY79 asks: “Suppose that you are the only incomeearner in the family, and you have a good job guaranteed to give you your current (family) incomeevery year for life. You are given the opportunity to take a new and equally good job, with a 50–50 chance that it will double your (family) income and a 50–50 chance that it will cut your (family)income by a third. Would you take the new job?” These situational questions that directly engageone’s disposition toward risk propensity in business venturing are more reliable than general riskattitude questions.Some risk-attitude questions allow a wider range of responses beyond an either/ordichotomy using a hypothetical lottery or investment opportunity. For example, the study by Blocket al. (2015) asks: “Imagine you have won $100,000 in a lottery. After having received the money,you have the possibility to invest the money in an entrepreneurial activity. With a probability of50%, you double the amount. With a probability of 50%, you would lose half the invested money.How much money obtained from the lottery would you invest?”Finally, other studies circumvent the self-confidence and self-knowledge gap by lookingdirectly at the demonstrated investment metrics of individuals and firms or other behaviors thatwould reveal risk preferences (e.g., Puri and Robinson, 2007; Brown et al., 2006; Uusitalo, 2001).On the individual level, Hvide and Panos (2014) measure risk preference through stock marketparticipation, personal leverage, and the fraction of wealth invested in the stock market. Lazear(2005) uses the standard deviation of industry-wide earnings in the individual’s first job to measurehow willing the person is to tolerate earnings-related risk. At the firm level, Caggese (2012) usesR&D expenditure behavior to measure risk attitudes under the assumption that research forintroducing new products is riskier than investing in improving existing products.26Although individual investment data are limited and do not represent the entireentrepreneurial population (e.g., a small convenience store owner may not have an extensive stockportfolio), it avoids the concern that people act differently than how they answer in hypotheticalself-report surveys. Similarly, at the firm level, Hall and Woodward (2010) use a model-basedapproach to back out what the relative risk aversion of an entrepreneur has to be for a given wealthlevel and external guaranteed earnings option, given the wide distribution of exit outcomes(ranging from failure to highly successful sales and public offerings) for VC-backed companies.2.2 Risk attitudes of entrepreneurs vs. other populationsStudies compare the risk attitudes of entrepreneurs to managers within the same industrialsectors, the general population, and other groups of entrepreneurs with varying levels of skills anddifferent types of motivation. Lazear (2005) uses a large sample of over 5,000 Stanford GSBgraduates for whom questionnaire data can be combined with student transcripts. The author’sproxy measure for risk tolerance—the variation of industry-level earnings among first jobselected—is positively correlated with the probability of later entering entrepreneurship (althoughfor Lazear, this metric is a control variable given the study’s focus on the breadth of skillsetsimportant for entrepreneurship).Using a very different approach, Hall and Woodward (2010) agree that entrepreneurs musthave a relatively high risk tolerance. Their study uses proprietary data for many VC-backedcompanies, analyzes the realized distribution of exit outcomes, and then infers what the relativerisk aversion of entrepreneurs involved in these businesses must be compared to asset levels andguaranteed employment options. For example, someone with a coefficient of relative risk aversionequal to two (a common assumed value) and with assets worth $188,949 would be indifferentbetween starting their own VC-backed firm versus being employed at market salary. Individualswith lower risk aversion and/or higher assets would value the entrepreneurial opportunity morethan wage employment.The most controversial findings relate to the risk attitudes of entrepreneurs versus businessmanagers, and here the evidence has been inconclusive if not contradictory. While it isstraightforward to understand why entrepreneurs may be more risk tolerant than managers, someargue that other attributes, like the high need for achievement that both groups possess, equalizeor obscure the simplest predictions (e.g., Atkinson, 1957). In a meta-analysis of 14 studies, Stewartand Roth (2001) find that the risk propensity of entrepreneurs is greater than that of managers.This conclusion is challenged, for example, by Miner and Raju (2004), who present data from 14other studies that used projective techniques to measure risk preferences rather than self-reportmeasures. The latter study finds entrepreneurs appear more risk avoidant than managers andhighlights the unsettled nature of these questions. See also the Stewart and Roth (2004) response.27Xu and Ruef (2004) further examine the “myth of the risk-tolerant entrepreneur.” Theycompare the risk attitudes of American entrepreneurs to the general population, using PSED datato analyze the reactions of 1,261 nascent entrepreneurs and general population participants in aseries of vignettes concerning business investment decisions. Within these vignettes, they utilizetwo models. One is a “strategic” model of risk tolerance based on investment choices, whichcaptures situational risk tolerance in taking a specific strategy or executing a specific action. Theother is a “non-strategic” model of risk tolerance based on information bias about business success,which captures pre-dispositional risk tolerance. The researchers conclude that the PSEDentrepreneurs are significantly more risk-averse than the general population, proposing that riskaverse individuals enter highly risky endeavors mostly because they value “identity fulfillment”and their autonomy more highly than any pecuniary benefits.Other researchers measure heterogeneity within entrepreneurial groups. Both Stewart andRoth (2001) and Miner and Raju (2004) find that there are large differences between entrepreneurswhose primary goal is venture growth versus those whose focus is on producing family income.Block et al. (2015) expand on these distinctions by comparing opportunity and necessitymotivations among a sample of 1,526 German entrepreneurs via an email questionnaire, in whichparticipants are asked to indicate their willingness to take risks with regards to startups and theamount they would invest in a hypothetical investment lottery. The study finds that opportunityentrepreneurs are more willing to take risks than necessity entrepreneurs, and those who aremotivated by creativity are more risk tolerant than other entrepreneurs.To sum up, while the literature on entrepreneurial risk attitudes is sizeable and growing,there is no uniform consensus as to how risk preferences should be elicited and how they differbetween populations. Perhaps a new and more complete synthesis lurks around the corner, butprogress to such an end is not evident in recent studies. More work could be done on narrowlydefined populations to better understand the degree of risk aversion among entrepreneurs. We alsoneed to continually bear in mind and explore differences between actual risk taken on byentrepreneurs and the perceptions of the risk they hold (e.g., Palich and Bagby, 1995). It is notentirely clear whether risk attitudes can be separated from over-optimism and over-confidence inmeasurement, a distinction that is meaningful theoretically (Parker, 2009).2.3 Effect of risk attitudes in the startup process2.3.1 Probability of entry into entrepreneurshipNot surprisingly, there is a large literature looking at the impact of entrepreneurial riskattitudes on the likelihood of starting a venture and on the eventual success of that venture. Thissection briefly summarizes some key recent studies. There is a considerable heterogeneity in thesamples studied by different scholars, and our illustrations reflect this range.28Cramer et al. (2002) consider 1,500 individuals from the 1952, 1983, and 1993 DutchBrabant surveys, allowing a long time span for entrepreneurial choices to come about.8F9 While thestudy finds evidence that risk aversion reduces entrepreneurial entry, the researchers did not feelconfident enough in the link to deem it a causal relationship. In a very different setting, Gürol andAtsan (2006) administer a 40‐item questionnaire to a random sample of 400 fourth-year universitystudents from two Turkish universities. The sample of students who intend to start their ownbusiness ventures show higher risk-taking propensity than non-inclined students. Similarly, usingthe income gamble questions asked in the two years of the NLSY79 panel, Ahn (2010) finds thatrelative risk tolerance has a large, positive, and statistically significant effect on the probability ofentering self-employment. An individual whose level of risk tolerance is one standard deviationabove the mean is 13% more likely to enter self-employment than is an otherwise identical person.The author notes that the estimated effect of risk tolerance is dramatically understated (by about90%) if the measurement error is not considered.9F10 In another U.S.-based study that utilizes 14,305observations from the Panel Study of Income Dynamics, Brown et al. (2011) measure thatwillingness to take financial risk is positively associated with future self-employment. Otherinternational studies include Ekelund et al. (2005), who analyze psychometric data from theFinnish 1966 Birth Cohort Study to examine “harm avoidance” as measure for risk aversion.10F11They find that harm avoidance carries a negative effect on the individual’s probability of beingself-employed. Caliendo et al. (2009) observe in the GSOEP that individuals with lower riskaversion are more likely to become self-employed if they are coming out of regular employment,but risk aversion does not explain entry for those coming out of unemployment or inactivity.Across the studies, the weight of the evidence suggests individuals with greater risktolerance are more likely to enter entrepreneurship. That said, much more work could be doneusing the same measures of risk aversion for different populations of potential entrepreneurs andcomparison groups to improve our estimates of the relationship, which are more directional thanquantitative in nature. The realities of business venturing (and subsequent rates of failure) make itquite reasonable that a would-be entrepreneur needs to be one who can tolerate a lot of risk, but itis very important to push onwards. For examples, when designing unemployment insurancebenefits or future universal basic income schemes, it would aid policy makers to have an accurateunderstanding of the relative degrees of risk tolerance in their population. Individuals who are risktolerant may be more likely to exit unemployment by starting their own business, versus lookingfor paid work, if getting small incentives from the government (e.g., Hombert et al., 2017).9 The Brabant survey covers 5,800 people who were interviewed and tested at the age of 12 in 1952, while attendingthe last grade level of elementary school in the Dutch province Noord-Brabant. In so far as they could be traced, theywere subsequently re-interviewed in 1983 and 1993. The data cover a rich set of aptitude scores, parental backgroundvariables, and later labor market outcomes, including detailed information on entrepreneurship experiences.10 The lifetime gamble questions are asked in 1993, 2002, 2004, and 2006 waves of the NLSY79.11 Harm Avoidance is measured as one of the four subscales of the temperament dimension of the Temperament andCharacter Inventory (TCI), a 240-item, self-reported questionnaire. The other three subscales are Novelty Seeking,Reward Dependence, and Persistence. An example of a survey question from Ekelund et al. (2005) is “I usually staycalm and secure in situations that most people would find physically dangerous.”292.3.2 Growth and success as an entrepreneurIn contrast to the strong consensus among researchers that risk tolerance supports venturecreation, it is unclear whether risk attitudes impact long-run business success. In a meta-analysisof 60 studies, Zhao et al. (2010) find that risk propensity is positively associated with earlyentrepreneurial intentions but does not relate to entrepreneurial performance, defined throughstudy-level indications of firm survival, growth, and profitability. Similar results are found byKessler et al. (2012) among Austrian founders for assessed venture success and business survival.Hvide and Panos (2014) hypothesize that the businesses of risk-tolerant individuals mightunderperform over the long run, on average, because more of these individuals select intoentrepreneurship (thus bringing more mediocre ideas) than among risk-averse individuals (whothus might only be tempted to start firms with the very best ideas). The authors assemble animpressive dataset that combines the investment data of 400,000 males in Norway who were fullyemployed in 1993-1994, and the researchers identified 6,300 who subsequently becameentrepreneurs, defined as having a majority stake in a new firm incorporated between 2000 and2007. Investment data show that common-stock investors, who are known to take on individualfinancial risks, are about 50% more likely to subsequently start a firm, but their firms have roughly25% lower sales and 15% lower return on assets during the annual observation period between2000 and 2010, supporting their hypothesis. This type of study represents an important frontier inthis area of research.Korunka et al. (2003) survey and compare 314 nascent entrepreneurs and 627 new businessowner-managers in the European Union, mostly drawing from German-speaking countries, andfind that those who become successful (self-assessed) displayed a medium risk-taking propensity.It is possible that while the high risk-takers are not the most successful, some degree of risk-takingpropensity is helpful toward business success. This hypothesis of a non-monotonic relationshipbetween risk tolerance and firm performance is worthy of study in larger samples.Hyytinen et al. (2015) use an innovative approach that combines interview data from anearly startup period with national business register data to track firm survival over time. Their maininterest is in the innovativeness of the firm (rather than that of the entrepreneur) but they also askabout the risk attitudes of the entrepreneur. They find that risk-loving entrepreneurs that operateinnovative firms are much less likely to have their firms survive over a three-year follow-up periodcompared to similarly risk-loving entrepreneurs running less innovative operations. The maineffect for risk-attitude is not significant in the firm survival models without this business model(i.e., “innovativeness”) interaction, while the interacted model displays a positive partialcorrelation between entrepreneurial risk preference and firm survival.30In contrast, Cucculelli and Ermini (2013) find that firms run by risk-loving entrepreneurstend to perform better in their sample of 178 entrepreneurs running Italian manufacturing firms in2007. The authors compare firms that introduce new products with those without new productinnovations. Risk attitudes are measured with a hypothetical lottery question, and are then matchedwith firm-level product portfolios and other financial data. A separate analysis of risk-averseversus risk-loving entrepreneurs reveals that the introduction of a new product affects firm growthpositively (and significantly) only in the sample of firms owned by risk-loving individuals. Therisk-loving entrepreneurs are also somewhat more likely to introduce new products in the firstplace, showing that they may indeed stimulate firm growth through innovation.2.3.3 Probability of exiting entrepreneurshipCaliendo et al. (2010) measure in GSOEP datasets that risk attitudes have a non-monotonicrelationship with entrepreneurial survival, as the exit rates of medium risk takers are 40 percentlower than those for low and high risk takers. While a positive relationship emerges from theliterature regarding risk taking and initial entry into self-employment, there appears to be a morecomplex relationship between risk taking and growth/exit choices. These early results need furtherverification using data from other countries and different entrepreneurial populations.2.4 Entrepreneurial self-efficacy, risk attitudes, and optimismMany researchers investigate the relationship between ESE and risk propensity. Forexample, Zhao et al. (2005) find in a survey sample of 265 MBA students that the effects of riskpropensity (as well as perceived learning from entrepreneurship-related courses and previousentrepreneurial experience) is fully mediated by an individual’s ESE. Similarly, Densberger (2014)considers whether risk propensity is a side effect of high ESE. In 49 in-person interviews withentrepreneurs in three American cities, the author concludes that high ESE allows entrepreneursto be comfortable taking risks. Barbosa et al. (2007) take a more complex approach by consideringthe roles of risk preference and cognitive style on four types of ESE and entrepreneurial intentions.Surveying 528 entrepreneurship program students in Russia, Norway, and Finland, they find thathigh risk-preference students hold higher levels of entrepreneurial intentions and opportunityidentification efficacy. Meanwhile, individuals with low risk preference had higher levels ofrelationship efficacy and tolerance efficacy. These outcomes appear to support claims that higherrisk preferences select for entrepreneurial qualities, while lower risk preferences select formanagerial qualities.Researchers also consider that entrepreneurs may enter the risky world of businessventuring because they over-assess their likelihood of positive returns. In a comprehensiveliterature review of the topic, Åstebro et al. (2014) examine the relationship between optimism,overconfidence, and entrepreneurial activity. Optimism refers to a general disposition towardhaving unrealistic beliefs in good outcomes, while Åstebro et al. (2014) use Moore and Healy’s31(2008) framework of overconfidence as expressions of overestimation and over-placement.Overestimation refers to estimating one’s abilities to be greater than they really are, while overplacement refers to estimating one’s abilities to be greater than they really are relative to anothergroup. Both versions of overconfidence appear to encourage people to enter entrepreneurship athigher rates than average, and they may also encourage people to make riskier decisions. Åstebroet al. (2014) point out that while it is often difficult to distinguish between the effects of optimism,overestimation, and over-placement, the effects psychologically operate on different levels ofspecificity. Optimism applies to all situations, while overestimation applies to a set of situationsthat reference a specific skill, and over-placement applies in a specific situation that involves aspecific reference group, such as a certain market. Because of these differences, Åstebro et al.(2014) assert that it is important to understand their distinctions for effective policymaking.11F12Researchers measure the correlation between general optimism and entrepreneurial activityusing various survey forecasting answers compared to later outcomes. For example, one researchquestion is whether entrepreneurs are good at forecasting in general. Shane (2009) finds thatentrepreneurs are generally overconfident in their performance estimates. Using data from theGlobal Entrepreneurship Monitor (GEM), Shane finds that U.S.-based entrepreneurs believe fivetimes more often than occurs in reality that they will have at least $10 million in sales. In contrast,Bengtsson and Ekeblom (2014) examine monthly survey data of 153 Swedish entrepreneurs andnon-entrepreneurs regarding their beliefs about future nationwide economic conditions that spans13 years. Comparing forecasts to economic reality, these researchers find that entrepreneurs havehigher optimism about the economy, but less forecasting error. However, the forecasting errorcomponent of this study may be inconclusive given the economic growth between 1996 and 2009that generally exceeded expectations of the general public (apart from the very last year).Additionally, this study compares entrepreneurs to the general population, who may be lessinformed about economic trends than entrepreneurs whose very work requires them to considereconomic conditions.The general trend in this line of research appears to be that while optimistic people aremore likely to enter into entrepreneurship, they make riskier entrepreneurial decisions and incurgreater losses to income. Puri and Robinson (2007) compare self-estimates of life expectancy fromthe Survey of Consumer Finance with actuarial tables. Those who overestimate their lifespan aremore likely to be entrepreneurs, and the most optimistic are more likely to make high-risk financialdecisions. Landier and Thesmar (2009) compare French entrepreneurs’ own expectations of futureincome with linked panel data, finding that overconfident entrepreneurs are more likely to useshort-term debt financing. Perhaps due to riskier decision-making, the optimistic entrepreneursearn less than pessimistic entrepreneurs. Dawson et al. (2014) compare earning expectations from12 Åstebro et al. (2014) also review the connected peer effects and entrepreneurship literature (e.g., Giannetti andSimonov, 2009; Nanda and Sorensen, 2011; Lerner and Malmendier, 2013). While we skip this literature in thisreview, it is important to note that peers influence some personality traits like perception of risk.32the British Household Panel Study 1991-2008 with future earnings as an entrepreneur. Controllingfor ability and environmental factors, the researchers report that optimistic entrepreneurs earn lessthan pessimistic entrepreneurs, with the difference being highest at the top of the earning scale andinsignificant at the bottom.However, it is more difficult to ascertain whether forecasts stem from general optimism oroverconfidence within a more specific context or a market. Åstebro et al. (2007) attempt to teaseapart the effects of optimism and overconfidence by comparing 820 inventor-entrepreneurs withnon-entrepreneurs in Canada with two scales—the forecasting of one’s score on a generalknowledge test and a general belief that “good things will happen.” Inventor-entrepreneurs tend toboth overestimate their scores and be more optimistic in general. The researchers then comparemeasures of optimism and overconfidence with data from the Inventors’ Assistance Program atthe Canadian Innovation Centre that advised inventor-entrepreneurs to either terminate efforts orcontinue through with launch. While overestimation does not affect investment of time and money,optimism increases expenditures of time and money even when prospects are said to be limited.Entrepreneurs may enter competitive markets with a small chance of venture success dueto overestimation of their own abilities vis-à-vis competitors or because they simply enjoycompetitive environments. Camerer and Lovallo (1999) present a scenario to university studentsin which pay depends on rank. When asked whether they would like to receive their rank randomlyor based on performance on a trivia quiz, those with high estimations of their abilities are morelikely to select the trivia quiz. Interestingly, Holm et al. (2013) use a similar approach and find thatChinese entrepreneurs are more likely to enter skill-based competitions even if they do not overplace themselves, suggesting that entrepreneurs may be more generally drawn to competitionregardless of overconfidence. Bernardo and Welch (2001) describe herding behavior forentrepreneurship.In conclusion, research provides clear hypotheses as to why entrepreneurs tend to beoptimistic and overconfident, and at the same time, why these traits may be deleterious forentrepreneurial performance. Overall, while plenty of room remains for further inquiry andsharpening of results, this part of the literature is more developed and cohesive than many otherareas of the entrepreneurial characteristics research.3. Goals and aspirationsMost entrepreneurship scholars measure business success by looking at observable eventsin the firm history, such as firm survival, exit, and growth. Different entrepreneurs, however, holdvery different goals and aspirations when starting and operating their firms, and this will impactmany decisions made and outcomes experienced. Research on these topics is, however,surprisingly slim compared to other aspects that we have reviewed. One bright spot, if contentious,is the work to examine non-pecuniary motivations (“be my own boss”) for starting businesses,33which has seen a surge of influential activity within the economics literature. We close this reviewwith some recent work on this topic that parallels the personality literature. It is quite likely thatthe personality traits of entrepreneurs differ significantly by the goals and aspirations thatentrepreneurs bring to the business, and future research can benefit by bringing tighter alignmentof these two literature strands.3.1 Reasons for deciding to start a businessOne key source of longitudinal data on entrepreneurial motivations is the Panel Survey ofEntrepreneurial Dynamics (PSED), which asks nascent entrepreneurs the open-ended question,“Why did you want to start this business?” Hurst and Pugsley (2011) organize the original 44motivations into five categories: non-pecuniary reasons, to generate income, to realize a goodbusiness idea, lack of employment options, and other.12F13 The authors find that the vast majority ofsmall businesses do not intend to innovate or expand their operations, but are instead content toremain at their current size and scope. They further measure that non-pecuniary motivations aremost frequent driver of new firm birth. Their classification is not standardized, and there are almostas many motivation typologies as there are studies. For example, Kuratko et al. (1997) use a fourfactor structure of goal statements identified based on responses from 234 entrepreneurs: extrinsicrewards, independence/autonomy, intrinsic rewards, and family security. Nevertheless, theimportance of non-pecuniary benefits is now well documented and robust in the literature.There is a second version of this theme in the entrepreneurial finance literature. In a famouspaper, Hamilton (2000) estimates that U.S. entrepreneurs have both lower initial earnings andlower earnings growth than in paid employment, with a median earnings differential of 35 percentfor individuals in business for 10 years. This differential persists across three alternative measuresof self-employment earnings and across industries, and cannot be explained by selection of lowability employees into self-employment. Thus, Hamilton concludes that there must be substantialnon-pecuniary benefits to self-employment. In parallel, Moskowitz and Vissing-Jorgensen (2002)examine entrepreneurial investment, finding that investment in U.S. private businesses isextremely concentrated and non-diversified, yet returns to private equity are no higher than thereturns to public equity. The researchers conclude that households are willing to invest substantialamounts in single privately held firms with a seemingly far worse risk-return trade-off due to nonpecuniary benefits, a preference for skewness, or an overestimation of survival probability.13 In their scheme, non-pecuniary reasons include desire for autonomy, independence, flexibility, and various measuresof self-fulfillment. Pecuniary reasons, by contrast, classify different motivations to earn money, whether to generateadditional income or to leave wealth for one’s children. Having a good business idea includes various urges to takeadvantage of a new opportunity, whether one is utilizing a new technology or building on one’s talents or experiences.Lack of other employment options suggests that one is otherwise unemployed, disabled, or retired. Finally, otherreasons may include belief in the value of the work, contributing to a community, or aiding in economic development.34These influential studies undergird the conventional wisdom that entrepreneurs sacrificeearnings to be entrepreneurs, indicating that non-pecuniary motivations must be also present. Overthe last decade, however, a stream of work questions whether entrepreneurs actually earn less. Thechallenges include underreporting of income by entrepreneurs (e.g., Hurst et al., 2014; Sarada,2016), failure to capture the option value of entrepreneurship and the returns present in future wageemployment (e.g., Manso, 2016; Dillon and Stanton, 2016; Galina and Hopenhayn, 2009; Kerr etal., 2014), and the failure to separate entrepreneurship into types (e.g., Åstebro et al., 2011; Levineand Rubenstein, 2017; Hegde and Tumlinson, 2016). Kartashova (2014) likewise revisits theprivate equity premium puzzle and finds it sensitive to the time periods used by Moskowitz andVissing-Jorgensen (2002). Thus, the entrepreneurial finance literature now questions whetherentrepreneurs earn less than paid workers in expectation. However, this does not obscure thebroader fact that non-pecuniary reasons, including desire for autonomy and self-fulfillment, arenow accepted to be an integral part of many choices to create new businesses, and thus measuresof venture returns or growth may mismeasure the true returns that these entrepreneurs experience.This will undoubtedly remain an important research topic for many years to come.3.2 Entrepreneurial goalsEntrepreneurs driven by pecuniary versus non-pecuniary benefits often have drasticallydifferent goals for their companies. Hurst and Pugsley (2011) find that most entrepreneurs, beingdriven by non-pecuniary benefits, have little intention to innovate or expand their market share.Hurst and Pugsley (2011, 2016) argue that those who receive large non-pecuniary benefitsnaturally gravitate toward industries where the natural scale of production is small (e.g.,accounting, plumbing). Bhide (2000) describes case studies of fast-growing firms that connect theactions and behaviors of founders to their firm growth, including some shifts in motivation withtime and experience. Ardagna and Lusardi (2010) measure from the GEM survey that the averageentrepreneurship rate is much higher in low- and middle-low income countries (14%) than highincome countries (6.7%); at the same time, two-thirds of entrepreneurs in poor countries arenecessity-driven entrepreneurs, compared to 22% in high-income countries. Notably, opportunitydriven entrepreneurs provide greater economic growth.Thus, the literature is increasingly categorizing two broad types of entrepreneurs: growthdriven entrepreneurs who seek opportunity and innovation and necessity-driven entrepreneurs thatopen new businesses when options are meager. Schoar (2010) further describes this partition in areview of the entrepreneurship and development literature. The recognition of this heterogeneityis important progress, as these distinctions of entrepreneurial heterogeneity are paramount tounderstanding entrepreneurial goals and their role in shaping the economy. On the other hand,researchers need to be diligent in remembering that entrepreneurial motivations are not so binaryin nature. Just as the average performance of an entrepreneur is proving to be a poor conceptualtarget in earning estimations, these two sub-groups are likely still too aggregated for the best longterm foundation, even if they allow good progress today.35There is ample research looking at specific industries where non-pecuniary motivationsdefine entrepreneurial goals. For example, Bergevoet (2005) finds that the goals and attitudes ofentrepreneurs are determinants of strategic and entrepreneurial behavior in the Dutch dairy farmingindustry. Entrepreneurial competencies and instrumental goals (such as having a large and modernfarm) correlate to self-scored success and larger farm size, and non-pecuniary goals explain muchof the variation in job satisfaction. Santos-Requejo and Gonzalez-Benito (2000) conduct 85 indepth interviews and learn that the objectives of subsistence businesses are highly influenced bysocio-cultural attributions such as family values, goals, and motivation to stay in business. In avery different setting, Reijonen and Komppula (2007) show in two Finnish studies of microbusinesses in the craft and rural tourism industries how entrepreneurs measure their performanceby non-pecuniary criteria and find success in job satisfaction and satisfied customers. Haber andReichel (2005) identify similar performance measures of small ventures in the tourism industry ofIsrael. In their study, the most important subjective performance measures include the perceivedcustomer satisfaction and the perceived profitability relative to competitors, while the keyobjective performance measures are related to firm growth (e.g., employment and revenue).Some researchers consider the role of gender in entrepreneurial goals. Justo et al. (2006)draw data from 1,236 Spanish entrepreneurs in the 2005 GEM survey to compare gender andparental status on intrinsic and independence measures of success. Intrinsic measures of successare generally more valued by women, while independence measures of success are valued equallyby men and women. However, the study finds that parental status alters women’s notions ofsuccess, with independence measures of success overcoming intrinsic measures of success amongwomen with dependent children. There is no such shift for men with dependent children. Ininterviews with 129 successful women entrepreneurs in the United States, Buttner and Moore(1997) distinguish between corporate climbers, who emphasize gaining managerial experience,from intentional entrepreneurs who emphasize the importance of technical competence.While goals for entering entrepreneurship and starting a business are considered on apersonal level, such as generating profit or retaining autonomy, there is little academic examinationinto self-defined measures of success for ventures. Large-scale surveys have not, to ourknowledge, asked whether an entrepreneur’s individual goal for the venture is to reach a publicoffering, grow the venture until acquisition by another firm, or to stay on as a Founder-CEO forthe long term. At the same time, these entrepreneurial decisions shape the entrepreneuriallandscape, and the alignment of founding teams and their investors on these goals is vital forventure success (e.g., Wasserman, 2011).To sum up, much work remains to be done in this largely unexplored area, and much ofthe initial research needs to focus on data collection via surveys and interviews. Policymakers havemuch to gain from understanding the specific goals of growth-oriented entrepreneurs who disruptand develop the broader economy. At the same time, most entrepreneurs have multiple non36pecuniary goals, and policy makers need to understand and support this important part of theeconomy too. Efforts to bridge the literatures on entrepreneurial personality and motivations mayprove very fruitful in the years to come.4. ConclusionThe topic of personality/psychological traits of entrepreneurs is of great importance forthe study of entrepreneurship in a multitude of contexts, including the examination of thedeterminants of occupational choice (entrepreneurship vs. paid employment), the predictors ofentrepreneurial success, the evaluation of the effects of entrepreneurship policies, and the designand assessment of different approaches to entrepreneurship education. While many theories andempirical analyses have approached the concept, the literature remains arguably underdevelopeddue to the conceptual and empirical challenges faced by researchers. Our review and assessmentof recent work is built with an eye to catching up on the recent literature and the outline of futureopportunities for applied researchers.Entrepreneurs are a very heterogeneous bunch, and so it is not surprising that studies oftheir personalities are mixed. This review highlights places where empirical findings areconsistent, while also embracing the heterogeneity where it is evident. Some of this varianceappears due to small sample sizes and selected subgroups, and so bigger studies and meta-analyseswill likely yield a clearer picture in the long-term. The multi-disciplinary nature of theentrepreneurial characteristics and personality literature also means that the terminology is notwell standardized, and the research dialogue does not easily lend itself to learning from pastresearch and making incremental progress as a field. The sheer number of journals publishingresearch related to entrepreneurial characteristics, as well as the large differences across them interms of academic field and quality, also complicates the ability to have a linear, chronologicallyprogressive research dialogue. This challenge too is likely to diminish with time, as the greaterdepth and specialization of the emerging field begins to provide returns to scale.Other heterogeneity will be irreducible as it pertains to the type of venture created, and wehave no reason to think the geeky personality of a 20-something tech founder will be tightly alignedwith that of a 50-something immigrant founder that is opening a Main Street convenience storewith her family members. We should, however, start to build the necessary language and taxonomyto better label these studies and their subpopulations, using the heterogeneity to our advantage.Accurate portraits of this heterogeneity will, in the long-term, prove truly valuable tounderstanding entrepreneurship: the differences between our two hypothetical founders above andtheir businesses can be every bit as informative as the comparison of them to people engaged inwage work. Our opinion is that future work in this regard is likely to be more productive than aone-size-fits-all portrait of the entrepreneur.37We believe a productive path forward exists utilizing universal administrative datasets thatcharacterize new firm creation and identify the founders of ventures. These data allow researchersto model directly the heterogeneous types of firms created, ranging from self-employed nannies toVC-backed startups, and to measure performance and venture success in objective ways.Moreover, the data provide insight into the careers that founders have before starting theircompanies, ranging from past business success/failure to the peers who they work with, and theydescribe the founding team that comes together. Powerful tools are also capturing digital signalsabout the growth intentions of founders when they set out (e.g., Guzman and Stern, 2017). Thesedata are already being matched with additional personal-level information ranging from stockportfolios to personality assessments.It has been 30 years since the critique of Gartner (1988), and perhaps the next 30 years willalso be unkind to progress on personality traits for entrepreneurship. Yet, the economics literatureholds such a deep focus on the creation of ventures—the “doing” in Gartner’s critique—that it maymiss fruitful opportunities to learn from personality studies and contribute to them. Administrativedata already afford much potential in terms of empirical assessment, and more data are continuallycoming online. Studies can combine these high-quality employer-employee filings with insight onpersonality traits that are measured before entrepreneurial spells commence, which would be animportant first step for observing which traits are exogenous predictors versus endogenousoutcomes. In more specialized settings, it may even be possible to build time-varying measures ofpersonality traits by looking before and after interventions like enrollment in an entrepreneurialtraining program. It is hard to envision a setting where one will obtain widespread and exogenousvariation in personality, but substantial progress can be made with pre-determined traits only.This survey has repeatedly surfaced gaps between the theory of personality traits and howwe can measure them, with our empirical tools frequently falling short of being able to disentanglecomplex and overlapping psychological traits to assign causal roles. Significant opportunities andchallenges for research on entrepreneurial traits lie in developing theoretical approaches andconstructs that can be empirically measured in a way that allows for the determination of causalitybetween psychological traits and entrepreneurial outcomes. The literature is often unclear as towhether individuals with a given set of personality traits selected into entrepreneurship, or whetherindividuals developed the traits endogenously after becoming entrepreneurs. The increasingavailability of detailed longitudinal information on demographic characteristics of entrepreneurs,including their human and financial capital endowments, as well as on entrepreneurialenvironments (regions and ecosystems) provides an opportunity to reduce both heterogeneity andendogeneity in studies of entrepreneurial traits. This requires the development of theoreticalconstructs and measurement procedures that align with detailed longitudinal coverage of people,but this task seems promising.38ReferencesAhn, T. (2010). Attitudes toward risk and self-employment of young workers. Labour Economics, 17(2),434-442.Antoncic, B., T. Bratkovic Kregar, G. Singh & A.F. DeNoble. (2015). The big five personality–entrepreneurship relationship: Evidence from Slovenia. 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The relationship of personality to entrepreneurial intentionsand performance: A meta-analytic review. Journal of Management, 36, 381–404.47Appendix 1: Other characteristics of entrepreneursA large literature investigates the non-personality traits of entrepreneurs. It is not possibleto do full justice to that literature, especially in an international scope, within the confines of thisreview. We only seek here to provide a brief commentary that draws on mostly U.S.-based studiesto afford a flavor of these findings. Parker (2009) provides a more extensive summary of thesedeterminants of entrepreneurship.A1.1 DemographicsResearch tends to measure that entrepreneurship is more prevalent among men, youngerpeople, non-minorities, and immigrants. These basic regularities are broadly consistent across subgroups of entrepreneurs like self-employed individuals, the most documented case, and growthoriented entrepreneurs, although the details certainly will differ by the domain studied.13F14 Wesummarize the key studies making these conclusions. Importantly, with respect to this study’sprimary focus on personality traits, these demographic characterizations have been mostlydeveloped in parallel and fruitful research can combine the streams (e.g., whether personalitydifferences explain higher rates of entrepreneurship across some immigrant nationalities comparedto others).Contrary to popular perceptions, entrepreneurship is not just the domain of 20-somethings.Studies document that young people are more inclined towards entrepreneurship, but that thecompeting effects of better capabilities and resources to start new ventures (encouraging entry)with higher opportunity costs and family commitments (discouraging entry) tend to prevent majordifferences across age ranges in terms of entrepreneurship rates. Many studies that look for nonlinear patterns document an inverted U-shaped relationship between age and rate ofentrepreneurship, with perhaps a peak point in the range of age 45.14F15 One’s definition ofentrepreneurship matters here. For example, many older, late-career individuals enter selfemployment as a form of semi-retirement, but it is rarer that someone in the age range pursueshigh-growth VC investment, and Glaeser and Kerr (2009) highlight the spatial differences in thesepatterns. To contrast, Hsu et al. (2007) survey 45,000 MIT alumni since the 1930s and show thatthe average age of a founder has dropped from 40 (in the 1950s) to 30 (in the 1990s).Women are less likely than men to enter entrepreneurship and this difference has remainedquite persistent over the last several decades. Following the rise of female labor force participation,studies find mixed evidence for whether rates of female entrepreneurship are continuing to grow14 Globally, GEM-based measurements find opportunity-driven entrepreneurs to also be slightly younger, male, moreeducated, more confident in their skills and abilities, and less afraid of failure.15 Examples of work in this literature include Bates (1995), Cowling (2000), Reynolds et al. (2002), Blanchflower andOswald (2009), Parker (2009), Bönte et al. (2009), and Liang et al. (2014). The Kauffman Index on startup activityindicates that slightly less than half of the new founders are aged under 45.48faster than those for men. Female entrepreneurs are highly represented in some sectors such asservices and sales, while notably absent from other sectors such as construction.15F16 Data from theSurvey of Business Owners in 2007 suggest that female business owners are more prevalent intwo-owner firms, with the implication that women are more likely to engage in entrepreneurshipthrough a family business or cofounded venture rather than as the sole owner of a firm. Anemerging area of research documents how women entrepreneurs tend to be more spatially isolatedwithin local areas and less networked than male entrepreneurs, and consequently depend uponother female-owned firms more (e.g., Rosenthal and Strange, 2012; Ghani et al., 2013).16F17Research finds that African Americans and Latinos are less likely to become entrepreneurscompared to whites (e.g., Fairlie and Meyer, 1996, 2000; Kauffman Index, 2016). A rare exceptionis the PSED-based study of Reynolds et al. (2004) that finds that minority groups are more likelyto be “nascent entrepreneurs” than their white comparison groups. The rate for Asians seems tomore closely track that of whites, although some studies suggest that Asian entrepreneurship ratesnow exceed those of whites (e.g., Fairlie and Robb, 2008; Kauffman Index, 2016).Recent studies document that immigrants start a disproportionate number of firms in theUnited States, with about a quarter of entrepreneurs being immigrants compared to an overallimmigrant workforce share of 15%. This difference moreover appears to be expanding in the lasttwo decades (e.g., Fairlie, 2012; Kauffman Index, 2016; Kerr and Kerr, 2016). There are largedifferences across groups of immigrants in terms of their entrepreneurial inclinations, withMexican and Latin American immigrants showing lower rates than many Asian groups.17F18 Thisdisproportionate contribution appears equally present for self-employed entrepreneurs as for hightech entrepreneurs. For example, Indian and Chinese entrepreneurs are prevalent in the tech sector,while many of the Latino entrepreneurs can be found in the service sector. Moreover, thisimmigrant entrepreneurial behavior is often highly clustered at industry-level by ethnic group (e.g.,Vietnamese nail care salons, Korean dry cleaners) as described in Kerr and Mandorff (2015), andit would be interesting to explore how this clustering influences personality factors like optimismand perceptions of risk. Fairlie and Lofstrom (2014) and Kerr and Kerr (2016) provide greaterdetails.16 Examples of work in this literature include Bates (1995), Reynolds et al. (2004), Budig (2006), Wellington (2006),Greene et al. (2007), Parker (2009), and Kauffman Index (2016).17 Connected to optimism described before, there is also evidence that female entrepreneurship increases in developingeconomies as conditions improve, peer networks take root, and women observe inspiring examples (Ghani et al., 2014;Field et al., 2015).18 Examples of work in this literature include Fairlie and Meyer (1996), Clark and Drinkwater (1998), Bates (2006),Wadhwa et al. (2007), Parker (2009), Fairlie and Woodruff (2010), Fairlie (2012), and Hunt (2011). Some of thesegaps can be explained by differing demographics, education levels, and wealth.49A1.2 Financial assets and wealthThe impact of wealth and financial assets on the probability of starting a business has beenstudied extensively, with influential early work by Evans and Jovanovic (1989) and Evans andLeighton (1989). There is clearly a positive correlation between wealth and entry, and theperceived wisdom for a long time was that substantial financial constraints exist for entrepreneurs,which holds very important policy implications. Subsequent work utilized unexpected changes inwealth (e.g., inheritances, home price increases, exchange rate fluctuations) that are arguablyuncorrelated with individual-level abilities and wealth from previous entrepreneurship in an effortto establish a causal relationship (e.g., Blanchflower and Oswald, 1998), generally findingsupporting evidence.Recent work challenges this past wisdom following the contrarian finding of Hurst andLusardi (2004). These authors first showed that entry rates are very non-linear over the wealthdistribution, with the rate of entry only jumping up in the top 10% of wealth levels or higher. Thisposes problems for explaining differences in entrepreneurship across the broad workforce, and thebusinesses started by these very wealthy individuals are frequently of a low capital intensity suchthat the owners could have opened the business at lower wealth levels had they wanted to.Moreover, studies have shown that the seemingly solid instruments for wealth changes are oftenconfounded (e.g., entry might rise upon the expectation of a windfall inheritance gain, well inadvance of actual wealth increases). Since Hurst and Lusardi (2004), it is safe to conclude that theliterature has been very mixed on the presence and importance of financing constraints.Parker (2009) and Kerr and Nanda (2011) provide complete reviews of this work. We wishto mostly emphasize one point of connection to our present review. Attitudes towards risk, as wellas the actual relative riskiness of a gamble, can change substantially with higher levels ofindividual wealth. Middle income families will often balk at a $25,000 business bet (e.g., the sizeof a typical angel investment into a startup), but that bet won’t cause multi-millionaires to losesleep. Kerr et al. (2015) describe these complex and ambiguous relationships in the context ofhome equity gains and entry behavior by home owners, with a critical point being that rising wealthlevels can influence these personality traits in several ways: adjustments in risk perceptionsconsistent with growing wealth, adjustments in risk perceptions or other behavior that are morebehavioral (i.e., playing with the “house money”), pursuit of entrepreneurship as a luxury good(i.e., the newly rich buy a Porsche and semi-retire into self-employed entrepreneurship), and soon. Separating these is very tricky, but substantial improvements in wealth data around the worldforeshadow a productive decade ahead for researchers. Dunn and Holtz-Eakin (2000) contrastfinancial transfers over generations with those of human capital, which will certainly receivecontinued attention with data improvements.50A1.3 Industry experience and educationThe skill distribution of entrepreneurs versus the general population is also important.Academic studies typically measure skills through formal education and work experience,although these are far from complete. Studies often measure a positive relationship betweeneducation and business ownership, but the evidence does not yield very strong relationships (e.g.,van der Sluis et al., 2008). Parker (2009) estimates that about 60 percent of studies find a significantpositive relationship between educational attainment and entrepreneurship. Lofstrom et al. (2014)postulate that this may be due to entrepreneurs sorting into industries based on entry barriers, asthose with greater education levels are more likely to enter higher-barrier industries that also offerhigher returns. Interestingly, Hunt (2011, 2015) shows that a good portion of the higher immigrantpropensity towards entrepreneurship can be explained by educational attainments and field ofstudy. The findings regarding work experience are similar. Parker (2009) discusses these studiesin more detail, emphasizing the importance of separating types of prior experience: general workexperience, industry expertise, prior startup experience, and so on. Prior studies also suggest thateducated business owners run more successful businesses, generate more innovation, and growtheir firms faster over time (e.g., Unger et al., 2011). While the traits are interesting in their ownright, future research should target joint analysis with personality characteristics.A1.4 Entrepreneurial regionsRecent work in the entrepreneurship literature considers why some places are endowedwith a greater number of entrepreneurs than others. Chinitz (1961) first formulates this question inhis attempt to explain why post-war New York was experiencing more economic success thanpost-war Pittsburgh. This literature strongly emphasizes how the past industrial legacies of citiescan lead to lasting cultures that favor or hinder entrepreneurship.18F19 These lasting legaciespotentially impact industrial organization (e.g., Fallick et al., 2006; Audretsch and Feldman, 2012;Carlino and Kerr, 2015), and are reflected in the higher degree to which entrepreneurs operate inthe regions of their birth than wage workers (e.g., Michelacci and Silva, 2007). At a broader level,work since Baumol (1990) and Murphy et al. (1991) highlights the degree to which a society’sinstitutions, laws, and norms lead talented individuals to pursue productive or rent-seekingopportunities to maximize their returns under the given set of conditions. To date, there has beenlittle attention given to how these powerful forces operate through the differing composition ofpersonalities in places, exogenously or endogenously via migration, or are independent of them.19 Prominent examples include Saxenian (1994), Kenney (2000), Audretsch and Feldman (2003), and Florida (2004),and recent empirical work includes Falck et al. (2011), Audretsch et al. (2012), Glaeser et al. (2015), Stuetzer et al.(2015), Obschonka et al. (2015), and Sorenson (2017).

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