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Gender differences in entrepreneurship and intrapreneurship: an empirical analysis

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Abstract

This study examines the gender gap in start-up activities to determine whether it is family status or employment status that is responsible for the observed gender gap. We consider independent entrepreneurship and intrapreneurship as two different start-up modes: While intrapreneurship is conducted within an established organization, independent entrepreneurship is solely an independent activity. This study focuses on this fundamental distinction to identify the parameters of our empirical model. Using nationally representative US data, we find that the effects of being a part-time worker on the likelihood of becoming an independent entrepreneur differ across genders. The obtained results suggest similar findings for intrapreneurship, but in opposite directions. Furthermore, our decomposition results suggest that for both entrepreneurship and intrapreneurship, the gender differences in the employment-related variables are more significant than those in the family-related variables in affecting the observed gender gap negatively (for entrepreneurship) or positively (for intrapreneurship).

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Notes

  1. See https://www.sba.gov/offices/headquarters/wbo (accessed July 2016).

  2. Parker (2009, p. 31) also states that “[d]ependent spin-offs are ventures formed in collaboration with an incumbent firm (sometimes termed ‘intrapreneurship’), whereas independent spin-offs are pursued entirely separately from an incumbent (‘entrepreneurship’).” Intrapreneurship is sometimes called “corporate entrepreneurship.” In this study, we use “intrapreneurship” and “intrapreneurs” throughout because we do not view intrapreneurship as specific to corporations.

  3. See, e.g., Miller (1983), Pinchot (1985), Rule and Irwin (1988), Hisrich (1990), Covin and Slevin (1991), Lumpkin and Dess (1996), Morris and Sexton (1996), Antoncic and Hisrich (2001, 2003), Antoncic (2007), Hellmann (2007), and Baruah and Ward (2015).

  4. In this study, we do not describe the details of this organizational decision process. In the conceptual framework proposed in Sect. 4.1 below, we assume that an individual chooses one of the three alternatives that give him/her the best utility. If an individual who wants to be an intrapreneur cannot become one because of limited capacities, he/she does not always choose the best alternative. We do not model such frictions mainly because of data limitations. In some cases, an employee may be “ordered” to be an intrapreneur within a company against his/her will. However, De Clercq et al. (2011) argue that being selected as an intrapreneur is usually financially rewarding. Thus, we would not lose much validity even if we assume that an individual chooses the alternative that gives him/her the highest level of utility.

  5. See Bethlehem et al. (2011) for an argument of why the bivariate probit model with sample selection (“double selection” ) is better than other models such as the multinomial logit, nested logit, and multilevel models.

  6. See, e.g., Evans and Leighton (1989a, b), Evans and Jovanovic (1989), Holtz-Eakin et al. (1994a, b), Hamilton (2000), Parker (2000), Kawaguchi (2003), Hurst and Lusardi (2004), Kan and Tsai (2006), Buera (2009), Mondragón-Vélez (2009), Malchow-Møller et al. (2010), Fairlie and Krashinsky (2012), and McCann and Folta (2012). Rybczynski (2009) examines an issue similar to the one central to this study and finds that a gender gap in self-employment earnings can mostly be ascribed to liquidity constraints.

  7. However, this is not to say that intrapreneurs are not incentivized; if they fail, it becomes difficult for them to be promoted or rewarded financially.

  8. However, it is possible to use the follow-up part for the purpose of identifying who actually started a business after statement in the initial screening process. Our main results do not change significantly even if we use the follow-up part. The details are available upon request.

  9. In a different vein, Moriano et al. (2014) examine how managerial leadership styles affect intrapreneurial behavior and find that transformative leadership—in which, e.g., a mission is shared, mentoring is provided, and innovative thinking is encouraged—is more effective to intrapreneurship than transactional leadership—in which, e.g., employees are extrinsically incentivized, and job scopes are predetermined. See Honig (2001), Monsen et al. (2010), and Zhang and Bartol (2010) for other psychological studies of intrapreneurship.

  10. For other studies that compare different groups of start-up participants, see Sardy and Alon (2007) on franchise and nascent entrepreneurs, Renko (2013) on social and conventional entrepreneurs, Kim et al. (2015) on leisure-based and conventional entrepreneurs, and Parker (2014) on serial and portfolio entrepreneurs.

  11. In this paper, we do not distinguish between risk aversion and uncertainty aversion, as opposed to Knight’s (1921) emphasis on this distinction. Skeptical views toward Knight’s (1921) distinction can be found in, e.g., Schultz (1980), LeRoy and Singell (1987), Demsetz (1988), and Runde (1998).

  12. Croson and Gneezy (2009) point out the following three reasons for these gender differences: (1) emotions (according to psychological studies, women react to uncertain situations more emotionally and fear adverse outcomes more than men do), (2) overconfidence (men are more overconfident than women), and (3) perception of risk as challenges or threats.

  13. PSED II is freely downloadable at http://www.psed.isr.umich.edu/. For general references for PSED II, see Reynolds and Curtin (2009), Davidsson and Gordon (2012), and Gartner and Shaver (2012).

  14. More specifically, these values take $10,000, $20,000, $27,500, $32,500, $37,500, $45,000, $55,000, $67,500, $87,500, and $125,000.

  15. This method of "data fusion" is justifiably strengthened by the fact that PSED II uses the 2005 March CPS to compute the weight variable, “WT_SCRN” (see page 2 of http://www.psed.isr.umich.edu/psed/download_node/157).

  16. The reason for statistical significances in the age groups would be ascribed to the fact that on average women live longer than men do.

  17. In line with our conceptual framework described here, our empirical analysis does not make a distinction between the self-employed and business owners and treats them as entrepreneurs. In addition, the qualification “nascent” is dropped for simpler expressions.

  18. See the references in Footnote 6 above, as well as, e.g., Fan and White (2003), Berkowitz and White (2004), Paik (2013), Rohlin and Ross (2016), and Cerqueiro and Penas (2016) for bankruptcy exemption and entrepreneurship, and Blanchflower and Oswald (1998), Taylor (2001), Adelino et al. (2015), and Schmalz et al. (2016) for housing and entrepreneurship.

  19. This additional state-level information was merged with the original PSED II at the Institute of Social Research, University of Michigan, as per our request. See http://www.psed.isr.umich.edu/psed/home for a procedure (accessed July 2016).

  20. We do not use household income as an explanatory variable in fear of its possible correlation with \(\epsilon _{1i}\) or \(\epsilon _{2i}\).

  21. We also considered information on the presence of pre-school children. However, it did not yield significant results.

  22. This issue would be further pursued if a measure of voluntary part-time work is available. We thank Kate Rybczynski for pointing this out.

  23. Rybczynski (2015), using Canadian data, arrives at a similar conclusion, namely, that the number of children negatively affects the continuation of women’s self-employment. See also Okamuro and Ikeuchi (2012) for a study of the relationship between women’s self-employment and work–life balance.

  24. To consider the possibility that intrapreneurship may mean different things across firm sizes, we estimate the two equations with a subsample of those who work for a firm with fewer than 100 workers and with a subsample of the others. We also conduct the same exercise by dividing the sample into those who work for a firm with fewer than 25 workers (this is the minimum number for the firm size categorization) and others. We find that overall, the parameter estimates (available upon request) are similar across the subsamples.

  25. Our implementation is based on Sinning et al. (2008). Following Oaxaca and Ransom (1994), we do not include the gender dummy when we obtain the estimates. This issue has not been settled in the literature. For example, Elder et al. (2010) recommend the inclusion of the group variable, whereas Lee (2015) opposes it.

  26. For other aspects of gender differences in entrepreneurship, Leoni and Falk (2010) focus on areas of university graduates’ majors, and Bönte and Piegeler (2013) consider gender differences in preferences toward competitive situations.

  27. Notice that it is possible to compute the actual and counterfactual (when all women acquire the same characteristics as men) rates of the non-involved for men and for women as in Table 12. Unfortunately, however, it is not possible to predict how the three rates for men would change because we do not model interactions among individuals.

  28. For example, Fairlie and Robb (2009) find that the lower performances of women-owned businesses are explained by both less human and financial capital that are specific to starting a business. See also Robb and Watson (2012) on gender differences in the performance of new ventures, Fairlie (1999) and Ahn (2011) on racial differences in the duration of entrepreneurship, and Oe and Mitsuhashi (2013) on the effects of founders’ experiences on the profitability of start-ups.

  29. The URL is http://www.bls.gov/news.release/archives/srgune_03012006 (accessd July 2016).

  30. However, in 2006, Delaware set $50,000 for its homestead exemption.

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Acknowledgments

We thank Rui Baptista (editor-in-charge) and two anonymous referees for invaluable suggestions. We are also grateful to Taehyun Ahn, Andrew Ching, Yuji Honjo, Hiroaki Ino, Masa Kato, Mizuki Komura, Eiji Mangyo, Hitoshi Mitsuhashi, Akira Nagae, Ryo Nakajima, Hikaru Ogawa, Fumio Ohtake, Atsushi Ohyama, Hiroyuki Okamuro, Lars Osberg, Hideo Owan, Kate Rybczynski, Koji Shirai, Taiki Susa, Hidenori Takahashi, Ryuichi Tanaka, Masa Tsubuku, Shintaro Yamaguchi, Weina Zhou, and seminar and conference participants at Chuo, Dalhousie, Hitotsubashi, Keio, Kwansei Gakuin, Sogang, the 42nd Annual Conference of the European Association for Research in Industrial Economics, the Kansai Research Group for Econometrics, the Tokyo Labor Economics Workshop, the Kansai Labor Research Group, the 50th Annual Conference of the Canadian Economics Association, and the 2016 Spring Meeting of the Japanese Economic Association for helpful comments and discussions on earlier versions of the paper. Special thanks are also due to Rebecca McBee for helping us construct data used in this paper. Adachi acknowledges Grants-in-Aid for Scientific Research (A) (23243049) and (C) (15K03425) from the Japan Society for the Promotion of Science. Any remaining errors are our own.

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  1. School of Economics, Nagoya University, 1 Furo-cho, Chikusa, Nagoya, 464-8601, Japan

    Takanori Adachi

  2. Graduate School of Economics, Osaka University, 1-7 Machikaneyama, Toyonaka, Osaka, 560-0043, Japan

    Takanori Hisada

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  1. Takanori Adachi
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Appendix: Variables of the financial environment

Appendix: Variables of the financial environment

Since the PSED II was conducted from September 2005 to February 2006, we set 2005 as the base year. To measure state-varying bankruptcy exemptions, we use homestead exemptions in 2005, and this information is based on Table 1 of Corradin et al. (2016). To capture the local housing market, we use the median value of owner-occupied housing units in 2005, and this variable comes directly from the 2005 American Community Survey (Variable B25077; owner-occupied housing units). The state-specific unemployment rate is the annual average in 2005 (available at the Web page of the US Bureau of Labor StatisticsFootnote 29). Finally, we consider three tax rates: individual income, corporate income, and sales taxes in 2005. The information is taken from the Tax Foundation’s Webpage (http://taxfoundation.org/tax-topics/state-taxes; accessed July 2016). Following Rohlin and Ross (2016), we use the highest marginal rate for individual income and corporate income taxes.

Table 13 presents the state-level data for the financial environment. All these variables have sufficient variations. Table 14 shows that the correlations among these variables are weak, except for the one between individual income tax and corporate income tax. There are seven states that do not set an exemption level. In Table 13, such a state is deemed “unlimited,” and in our empirical analysis, we impute $500,000, the maximum amount from the rest of the states, for these states’ exemption level. The federal level of exemption in 2005 was $36,900, and for states that had a lower amount but allowed their residents to opt out for the federal level, the amount is set at $36,900. However, 17 states continued to have a lower amount than $36,900. In particular, there are two states (Delaware and Maryland) that did not permit any homestead exemption.Footnote 30

Table 13 State-level data
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Table 14 Correlations between institutional variables
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Adachi, T., Hisada, T. Gender differences in entrepreneurship and intrapreneurship: an empirical analysis. Small Bus Econ 48, 447–486 (2017). https://doi.org/10.1007/s11187-016-9793-y

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