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Leveraging entrepreneurship through private investments: does gender matter?


Using project data from a random sample of Phase II research awards from the National Institutes of Health SBIR program, we estimate the relative probability that woman-owned firms are able to attract private investments to fund the transition of the technology developed under the sponsorship of the SBIR program to an innovation to enter the market. We find that women-owned firms are as much as 16% points less likely to attract private investment dollars compared to male-owned firms, factors excluding the size of the SBIR award held constant. Women-owned firms that received larger awards performed substantially better. Although the SBIR program has a legislated directive to increase the participation of woman-owned firms in the program, our findings suggest that it might not be sufficient to overcome market perceptions about the profitability of such investments actually bringing a developed technology to market.

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  1. The term Valley of Death is generally attributed to Congressman Vernon Ehlers (1998, p. 40). Branscomb and Auerswald (2002) refer to the Valley of Death as the transition stage from science-based invention to commercial innovation during which venture capital is the primary alternative source of investment. According to Wessner (2007, p. 7): “The difficulty of attracting investors to support an imperfectly understood, as yet-to-be-developed innovation is especially daunting. Indeed, the term ‘Valley of Death’ has come to describe this challenging transition when a developing technology is deemed promising, but too new to validate its commercial potential and thereby attract the capital necessary for its development.”

  2. According to Schumpeter (1934, p. 78), the entrepreneur is the person who innovates, who makes new combinations in production: “everyone is an entrepreneur only when he actually ‘carries out new combinations,’ and loses that character as soon has he has built up his business, when he settles down to running it as other people run their business.” Thus, bridging the Valley of Death is an entrepreneurial responsibility. See Hébert and Link (2006, 2009).

  3. The Diana Project, named after the Roman goddess of the hunt and thus symbolizing women’s hunt for the rewards of entrepreneurial effort, was a multi-university research program to identify factors that support and enable high growth in women-led ventures. This project was funded by the Kauffman Foundation, the U.S. Small Business Administration, the National Women’s Business Council, and the Swedish Institute for Small Business Research (Gatewood et al. 2009).

  4. As Wessner (2009) has shown with regard to entrepreneurial firms in the United States funded by Small Business Innovation Research awards, the focal data in this paper, venture capital is an infrequently available source of alternative private investments.

  5. Gompers and Lerner (2004) also review the literature related to each of these factors.

  6. For a theoretical justification of the role of the SBIR, see Link and Scott (2010, 2011).

  7. Being considered under the current temporary reauthorization of the SBIR program (to November 18, 2011 under H.R. 2608) are caps on Phase I awards of $150,000 and $1,000,000 on Phase II awards. These caps are effective under a March 30, 2010 amended SBIR policy directive initiated by the U.S. Small Business Administration. These caps are expected to be made when the program is reauthorized.

  8. See also Levin et al. (1988), Johnson and Powell (1994), Barsky et al. (1997), Jianakoplos and Bernasek (1998), Sundén and Surette (1998), and Borghans et al. (2009). Schubert et al. (1999) present findings that question the prevalence of such a gender-specific risk attitude. However, research in the field of psychology shows that men and women are equal in terms of their innate creativity (Baer and Kaufman 2008).

  9. This lack of risk taking could be related to a lack of self-confidence, and Brana (2011) discusses the latter in the context of gender and entrepreneurial ventures.

  10. This argument suggests that one should compare the probability of a research project being supported by private investment between projects funded and not funded by SBIR. While a matched pairs analysis would be interesting, such data are not available in the NRC database, and may not be available at all. Although Lerner (1999) has compared a large sample of SBIR awardees and matching firms, finding that the SBIR recipients have higher employment growth, Lerner and Kegler (2000, p. 321) explain that it is difficult with the matched pairs analysis “to disentangle whether the superior performance of the awardees is due to the selection of better firms or the positive impact of the awards.”

  11. There are 1,677 projects in the full NIH random survey population, of which 495 (29.5%) respond to the survey and 323 (19.3%) are used to estimate Eq. 1 (see Table 1).

  12. There are 22 different agencies within the NIH that funded the 323 projects in the main estimation sample. The agencies that funded the most projects are the National Cancer Institute (53 projects) and the National Heart, Lung and Blood Institute (37 projects).

  13. Since this variable conveys similar information to the Phase II award amount, it is not surprising that including it slightly reduces the absolute value of the coefficients on Award and Award·Female: to −0.0095 and 0.3393, respectively.

  14. The most likely reason is that, similar to private investment for Phase III research, pre-Phase II funding is also highly correlated with gender. Of the projects in the sample, 21% of male firm owners received private research funding prior to the Phase II award, compared to only 6% of female firm owners. This difference is statistically significant.

  15. We also re-estimated the model with a polynomial in Age and did not find a relationship. These results are available from the authors upon request.

  16. The mean and standard deviation conditional on positive investment are 4.8425 and 15.1991, respectively.

  17. The results from the specifications in columns (1) and (2) in Table 5 are available on request from the authors.

  18. These coefficients show how the dependent variable changes when we change the X variables when Private investment equals 1, ignoring the changes in the probability of receiving Phase III funding associated with changes in the independent variables.


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This paper has benefitted from the comments and suggestions of Steve Bendar, Barry Hirsch, Donald Siegel, Mike Wright, and anonymous referees.

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Correspondence to Albert N. Link.

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Gicheva, D., Link, A.N. Leveraging entrepreneurship through private investments: does gender matter?. Small Bus Econ 40, 199–210 (2013).

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  • Innovation
  • Entrepreneurship
  • SBIR program
  • Venture capital
  • Gender discrimination

JEL Classifications

  • O31
  • L26
  • J16
  • G11