Abstract
We incorporate the concept of social identity into entrepreneurship and analyze the determinants of having entrepreneurial intentions. We argue that an entrepreneurial identity results from an individual’s socialization. This could be parental influence but, as argued in this paper, also peer influence. Based on Programme for International Student Assessment (PISA) 2006 data in which students report their entrepreneurial intentions at the age of 15, we find that having an entrepreneurial peer group has a positive effect on an individual’s entrepreneurial intentions. We find that the strength of the peer effect in a country is moderated by prevailing values, namely individualism.
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Notes
For instance, Kihlstrom and Laffont (1979) analyze occupational choice with regard to an individual’s risk aversion, Lucas (1978) considers innate abilities, and Lazear (2005) stresses the importance of an individual’s mix of skills. Yet others analyze the impact of external constraints (e.g., Holtz-Eakin et al. 1994; Michelacci and Silva 2007) and social contacts (e.g., Bauernschuster et al. 2008; Stuart and Sorenson 2005). For an extensive overview, see Parker (2004).
With the exception of ruling out fields in which firm succession of children is more common (e.g., agriculture), we do not attempt to distinguish between the intergenerational transmission of identity either stemming from work experience in the parental business or from parental role modeling. We focus, instead, on the role of peers in the formation of an entrepreneurial identity.
“Because of its explanatory power, numerous scholars in psychology, sociology, political science, anthropology, and history have adopted identity as a central concept. This paper shows how identity can be brought into economic analysis, allowing a new view of many economic problems” (Akerlof and Kranton 2000, 716).
An exemption is the work by Sen (1977).
In support of this statement, note that Oosterbeek et al. (2010) find that a leading entrepreneurship education program has no effect on college students’ intention to become an entrepreneur. Their empirical analysis is based on difference-in-differences methodology.
“The power of example to activate and channel behavior has been abundantly documented. … One can get people to … converse on particular topics, to be inquisitive or passive, to think innovatively or conventionally, and to engage in almost any course or action by having such conduct exemplified” (Bandura 1986, 206).
However, it is important to note that independent research from the fields of developmental psychology and neuroscience emphasizes the role of early childhood experiences as well (cf. Heckman 2006).
This assumption is also in line with findings by the Harvard Center for Entrepreneurial History. Miller (1952) and Neu and Gregory (1952) find that the most influential businessmen during the period of the great American industrialization (1870–1910) came from landowning or entrepreneurial families.
“The people with whom one regularly associates, either through preference or imposition, delimit the behavioral patterns that will be repeatedly observed, and hence, learned most thoroughly” (Bandura 1986, 55).
The entrepreneur’s job is “to locate new ideas and to put them into effect. He must lead, perhaps even inspire; he cannot allow things to get into a rut and for him today’s practice is never good enough for tomorrow. … He is the individual who exercises what in the business literature is called ‘leadership’” (Baumol 1968, 65).
To ensure that our results are not driven by individual sectors, we performed robustness tests where we dropped each additional narrower category, 1312–1319, from the analysis one at a time. Results are fully robust in these regressions. In further robustness tests, we looked at students’ intentions to choose other creative occupations, such as artist, teacher or doctor, as well as becoming the manger of a large enterprise. For all these occupations, the relationship between a student’s occupational intention and the peers’ occupational intentions becomes weak.
We also dropped one student from the final sample who was in grade 13—compared with the majority of students who were in grades 9, 10 or 11 at age 15—since a robustness check of our analysis revealed this observation as an outlier.
The selection of the initial set of control variables follows Fuchs and Woessmann (2007) who estimate an educational production function using PISA 2000 data. The following control variables were tested, but then removed because they did not enter Eq. 2 significantly: individual and family background variables (language spoken at home, a set of grade dummies, and an indicator for grade repetition), school background variables (school size, share of girls at school), school resource variables (number of students per teacher, an index of teacher shortage, number of computers for instruction per student, index of quality of school educational resources), school and grade composition (school and grade average student performance in science and mathematics), institutional characteristics (ability grouping for all subjects within school, academic selectivity of school admittance, private management and the proportion of school funding from government sources, an indicator for a high level of competition, and one for perceived parental pressure as several measures of school accountability and school autonomy; indicators of businesses influence on the curriculum as well as career guidance offered at school).
To ensure that our results are not driven by individual keywords (e.g., the chef of a restaurant might be a wage employee), we performed robustness tests in which we dropped the narrower business activities from the keywords list one at a time. Results are fully robust in these regressions.
This information is taken from a filter question where respondents were asked whether there is an actual job they want to do. We assume that teenagers did not have any job intentions if they negated this question.
We also estimated probit models. The estimated marginal effects evaluated at the sample mean were not different from the coefficients of the ordinary least squares (OLS) regressions in all specifications. We therefore do not report the probit results.
Because of the incidental parameters problem that arises when estimating fixed effects in nonlinear models when group sizes are small (Neyman and Scott 1948), we prefer to report results from linear probability models. However, we also estimated the country fixed-effects specification using probit and logit models, which yielded similar results in terms of direction and significance. These results are available from the authors upon request.
In the last part of our analyses, we investigate whether the peer group influence on entrepreneurial intentions varies with the degree of individualism prevailing in each country, as measured by a country average of two items. We regard each country as one observation of the degree of individualism, which should therefore be given equal weight in these analyses.
Note that this derivation holds when students are missing at random, and under the weaker assumption that missing students are drawn from a different distribution than observed students, as long as this distribution is independent of assignment to grade levels (for details, see Ammermueller and Pischke 2009, 333).
Ten OECD countries administered the parent questionnaire, namely Germany, Denmark, Iceland, Italy, South Korea, Luxembourg, New Zealand, Poland, Portugal, and Turkey. In this ten-country subsample, 23.5% of the observations contain missing values for parental occupation.
The 14 countries are Australia, Austria, Belgium, Canada, the Czech Republic, Germany, Spain, Hungary, Italy, Luxembourg, The Netherlands, Portugal, Slovakia, and Turkey.
See Table 8 in the Appendix for full estimation results.
In the World Values Survey (2005), both items are measured on a four-point scale (1 = strongly agree, 2 = agree, 3 = disagree, 4 = strongly disagree).
The 16 participating countries are Australia, Canada, Germany, Spain, Finland, Great Britain, Italy, Japan, South Korea, Mexico, The Netherlands, Norway, New Zealand, Poland, Sweden, Turkey, and the USA.
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Acknowledgments
We are grateful to David Audretsch, Lee Flemming, Oliver Kirchkamp, Adam Lederer, Mirjam van Praag, Simon Parker, Olav Sorenson, and Ludger Wößmann for helpful comments on an earlier version of this manuscript. We also thank the conference participants at the Spring 2009 Meeting of Young Economists in Istanbul, the International Institute of Public Finance (IIPF) 2009 conference in Capetown, and the 2009 Conference of the German Economic Association (Verein fuer Socialpolitik) in Magdeburg for many helpful comments. Daniel Erdsiek provided capable research assistance. Oliver Falck is indebted to the Program on Education Policy and Governance (PEPG), Kennedy School of Governance, Harvard University, and in particular to Paul Peterson and Edward Glaeser for their hospitality during the research visit that allowed work on this research, and to the Fritz Thyssen Foundation for partial funding of the research visit. Stephan Heblich received funding for the research leading to these results from the European Community’s Seventh Framework Programme (FP7/2007–2013) under Grant No. 216813.
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Falck, O., Heblich, S. & Luedemann, E. Identity and entrepreneurship: do school peers shape entrepreneurial intentions?. Small Bus Econ 39, 39–59 (2012). https://doi.org/10.1007/s11187-010-9292-5
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DOI: https://doi.org/10.1007/s11187-010-9292-5