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Entrepreneurial career paths: occupational context and the propensity to become self-employed

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Abstract

We investigate the relationship between characteristics of an occupation-specific environment and the decision of employees to start an own business. A relatively high occupation-specific unemployment risk and high earnings risk are conducive to opt for self-employment. Also, occupations that are characterized by high self-employment rates foster entrepreneurial choice among their employees. The results suggest that career choices of future entrepreneurs are driven by different motivations than those of non-entrepreneurs. In particular, the expectation of a pronounced financial gain is critical for future entrepreneurs when they make their initial occupational choices in paid employment and it is also relevant for a self-employment choice. We find that when future entrepreneurs enter the labor market, they are more likely to choose occupations that require a relatively high variety of skills.

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Notes

  1. Prominent explanations for this phenomenon are (a) loose hierarchical structures that allow close contact to an entrepreneur who may provide a role model of entrepreneurial career, (b) lower level of labor division and specialization in small firms leads to a larger variety of skills and experiences that may be conducive to entrepreneurial thinking, (c) relatively low wages, low prospects for internal promotion, and relatively low survival chances of smaller firms create an incentive for becoming self-employed, and (d) self-selection of entrepreneurial persons into small firms, for instance, based on individual risk preferences or taste for variety (Parker 2009a).

  2. It should be noted that switchers from paid employment into self-employment are commonly regarded as opportunity-driven start-ups, whereas start-ups out of unemployment are commonly regarded as necessity-driven start-ups. Although we only focus on transitions from paid employment into self-employment, in our empirical setting, we account for different motives for a start-up as far as the data allow.

  3. Numerous studies show that the possibility of financial gain may be an important motive for becoming self-employed (Katz 1994; Venkataraman 1997; Douglas and Shepherd 2000; Shepherd and DeTienne 2005).

  4. This survey was conducted by the German Federal Institute for Vocational Education and Training (Bundesinstitut für Berufsbildung) in cooperation with the German Federal Institute for Occupational Safety and Health (Bundesanstalt für Arbeitsschutz und Arbeitsme-dizin).

  5. The German Micro-Census is an annual representative survey conducted by the Statistical Office that collects information about the personal, household, and socioeconomic status of approximately 820,000 individuals living in 380,000 households in Germany. For more details about self-employment statistics based on the German Micro-Census, see Fritsch et al. (2012b).

  6. The occupation-specific data are classified according to the following aggregation levels of the KldB’92. On the level of Berufsabschnitte, there are 33 occupational groups. Berufsgruppen contains 88 occupational groups and is the second level of aggregation. Berufsordnungen is the third level of aggregation in the KldB’92 and encompasses 369 occupational groups.

  7. These variables are supposed to control for regional differences in income variation.

  8. The Big Five taxonomy was developed by Costa and McCrae (1992), and is a widely used psychological concept of human personality that includes the following dimensions: openness to experience, conscientiousness, extraversion, agreeableness, and neuroticism. For the relationship between the Big Five personality traits and entrepreneurship see Obschonka and Stuetzer (2017).

  9. Information on the following skills is available: natural scientific skills, manual/craft skills, pedagogic skills, legal skills, skills in project management, medical or custodial skills, skills in layout, design, and visualizing, mathematical and statistical skills, German-language skills (writing, spelling), computer skills in application software, technical skills, commercial/managerial skills, and foreign-language skills. Although these data are available at the individual level, there is no possibility to match the individual data with the information taken from the SOEP. Hence, we can only use the aggregate information at the level of occupations. By doing so, we do not measure skill variety of potential entrepreneurs, but rather the potential of a particular occupational environment to be conducive for entrepreneurship.

  10. The corresponding question is: “How likely is it that you will lose your job within the next 2 years?” The respondents could assess this probability on an 11-point scale with 10-point increments ranging from 0 (definitely not) to 100 (definitely).

  11. The question for assessing a person’s general risk attitudes is: “How do you see yourself: Are you generally a person who is fully prepared to take risks or do you try to avoid taking risks?” This question has been included in SOEP every 2 years starting in 2004. For waves when this question was not asked, we impute the values from the previous year under the assumption that willingness to take risk remains constant over short periods of time.

  12. Including the occupation-specific variables separately into the model may result in an omitted variable bias. Hence, in column VIII of Table 2, we report results of an estimation that includes all occupation-specific characteristics at the same time, with the exception of long-term unemployment and average skill variety, since both variables are highly correlated with the short-term unemployment rate. Compared with the models with only one of the occupation-specific variables the main results remain largely unchanged. However, the effect sizes of the short-term unemployment rate and the self-employment rate decrease. It should be noted that this model may suffer from a multicollinearity problem. We, thus, abstain from interpreting the results of this model.

  13. One might argue that unemployment risk affects necessity and opportunity founders differently. Although we only observe new businesses out of paid employment, which can be regarded as opportunity-driven start-ups, we distinguish between business founders who report high risks of losing their job in previous paid employment, which may be at least partly regarded as necessity entrepreneurs. However, the effects of unemployment risk do not differ between necessity and opportunity entrepreneurs distinguished in this way. The results are available from the authors upon request.

  14. The incentive to switch into self-employment may be especially pronounced if the cost of switching occupations in terms of requalification is high. It has been shown that switches between occupations can be rather costly in terms of redundancy of previously acquired occupation-specific skills and the necessity to acquire new skills (Gathmann and Schönberg 2010; Nedelkoska and Neffke 2010).

  15. The effect of short-term unemployment rate increases by the factor of 1.6 and the effect of long-term unemployment increases by the factor of 2.2.

  16. The results are available from the authors upon request.

  17. Some individuals may, however, have specialized in their education before entering the labor market, e.g., by choosing a certain curriculum at university, providing them with considerable profession-specific human capital when entering the labor market for the first time.

  18. For instance, the variable measuring individual risk attitudes was for the first time available in 2004.

  19. We restrict the sample to those individuals who are in the same occupational group (“Berufsabschnitt”) in the period t and at the time of labor market entry. About 45% of all respondents with available information on the first and last occupation currently work in the same occupation as at the time of labor market entry.

  20. The reason for this is that there is no information on the occupation of unemployed individuals.

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Authors and Affiliations

  1. School of Economics and Business Administration, Friedrich Schiller University Jena, Carl-Zeiss-Str. 3, 07743, Jena, Germany

    Alina Sorgner & Michael Fritsch

  2. Kiel Institute for the World Economy, Kiel, Germany

    Alina Sorgner

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  1. Alina Sorgner
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  2. Michael Fritsch
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Correspondence to Alina Sorgner or Michael Fritsch.

Appendix

Appendix

Table 8 Definition of variables
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Table 9 Correlation matrix
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Table 10 Mean values of characteristics of occupational environments of SOEP respondents 2004–2009
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Table 11 Effect of occupation-specific unemployment rate (defined at the level of “Berufsabschnitte”) on the probability of switching into self-employment
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Sorgner, A., Fritsch, M. Entrepreneurial career paths: occupational context and the propensity to become self-employed. Small Bus Econ 51, 129–152 (2018). https://doi.org/10.1007/s11187-017-9917-z

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