Abstract
Using a large representative German data set and various concepts of self-employment, this paper tests the “jack-of-all-trades” view of entrepreneurship by Lazear (Am Econ Rev 94(2): 208–211, 2004). Consistent with its theoretical assumptions we find that self-employed individuals perform more tasks and that their work requires more skills than that of paid employees. In contrast to Lazear’s assumptions, however, self-employed individuals do not just need more basic but also more expert skills than employees. Our results also provide rather limited support for the idea that human capital investment patterns differ between those who become self-employed and those ending up in paid employment.
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Notes
In a modification of the Lazear model Benz (2009) also takes non-monetary benefits into account and thus focuses on overall utility rather than solely on income. While this implies that there will be a positive supply of entrepreneurship even if no profits can be made, it does not change the central prediction that entrepreneurs should be generalists and employees should be specialists.
These hypotheses should not only apply to entrepreneurs in a narrow sense—such as innovators or “founders of a new small restaurant”, the example given by Lazear (2004, p. 208)—but to (almost) all individuals in self-employment. For a more detailed discussion of entrepreneurship and self-employment, see Sect. 3.
In a recent study using the same data set but not explicitly designed to test the assumptions of Lazear's theory, Bublitz and Noseleit (2011) also ran regressions with the number of expert skills as the dependent variable, hypothesizing that the number of expert skills is higher for entrepreneurs than for employees (contrary to our hypothesis 4).
Note that this theory also implies a seventh hypothesis, namely, that “[i]ndividuals with more balanced skill sets are more likely to become entrepreneurs” (Lazear 2005, p. 651). Data limitations and the problem of finding a convincing indicator of skill balance preclude us from directly investigating this hypothesis (although the results of testing hypotheses 5 and 6 may provide some indirect evidence). Studies that aim to directly test the balancing hypothesis are Lazear (2004, 2005), who uses the extent of special versus general courses of Stanford students; Backes-Gellner and Moog (2008), who construct a composite indicator of relative length of different types of work experience and extend this indicator to include human as well as social capital; Hartog et al. (2010), who investigate the impact of various cognitive and social abilities; Hsieh et al. (2011), who multiply the generality of degree majors and grade variance to obtain an indicator of skill balance; and Orazem et al. (2012) who use the number of courses in the major minus the average number of courses taken in other departments.
Note that our data set does not include apprentices and that we exclude helping family members and freelance collaborators from our analysis since they are neither entrepreneurial nor typical employees. The share calculated from the microcensus data excludes helping family members but includes freelance collaborators and apprentices. Also note that we are not making use of the weighting factors provided in the data set. Our results do not change substantially if we do.
Note that our empirical results are virtually the same and our insights do not change if we make use of count data models (such as NegBin) rather than OLS in these and the following estimations (results are available from the first author on request). Count data models analyze the number of occurrences of a certain event within a certain interval (of time). We, however, count the number of singular occurrences of different events over uncertain intervals. Therefore, using standard count data methods might be regarded as similarly inappropriate as using OLS, but we are not aware of better ways to analyze our data. For a similar approach using both methods see Bublitz and Noseleit (2011).
Note that a simple univariate OLS regression of the number of total skills required on the number of tasks occurring sometimes or often shows that about one-third of the variance in the number of skills can be traced back to the number of tasks.
One explanation could be that expert skills act as a positive signal to capital lenders so that it makes sense for entrepreneurs to acquire (more) expert skills rather than just basic skills. However, individuals in our survey were explicitly asked about skills required in their current occupation, so that it seems likely that they actually need these expert skills at work and not just as a signal. Another explanation might be that entrepreneurs must have (more) expert skills since the market infrastructure for complementary inputs and services is not well developed, but in a market economy it is quite unlikely that this should occur on a large scale.
Employees aiming for self-employment may be working exceedingly in small firms, which have been found both to provide jobs demanding higher skill diversity and to spawn more entrepreneurs than larger firms (see, e.g., Elfenbein et al. 2010 and the literature cited therein, and Bublitz and Noseleit 2011 for a related discussion). This is one more reason for taking account of firm size in a robustness check (see below).
While risk aversion is usually thought to deter individuals from becoming self-employed, Hsieh et al. (2011) argue that individuals with higher risk aversion might want to invest in balanced skills in order to diversify their human capital, making them more likely to become entrepreneurs.
Putting this insight in terms of the theory of the firm, entrepreneurs seem to be better characterized as multifaceted specialists rather than as mere coordinators (see also Hart and Moore 2005, p. 697).
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Acknowledgments
For helpful comments and suggestions we would like to thank an anonymous referee of this journal as well as Udo Brixy, Michael Fritsch, Monika Jungbauer-Gans, Joachim Wagner, and participants in seminars at the Universities of Hannover and Erlangen-Nuremberg, in the IECER Conference in Regensburg, 2012, and in the 3rd IZA Workshop on Entrepreneurship Research in Potsdam, 2012. We further thank Anja Hall, Josef Hartmann and Holger Alda for assistance with data set related questions.
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Lechmann, D.S.J., Schnabel, C. Are the self-employed really jacks-of-all-trades? Testing the assumptions and implications of Lazear’s theory of entrepreneurship with German data. Small Bus Econ 42, 59–76 (2014). https://doi.org/10.1007/s11187-012-9464-6
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DOI: https://doi.org/10.1007/s11187-012-9464-6