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Beyond innovation: the Small Business Innovation Research program as entrepreneurship policy

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Abstract

Entrepreneurship or new firm formation plays an increasingly important role in knowledge-based economic development. Public policy to encourage new firm formation has not focused on high quality, high potential firms, and the search for entrepreneurship policy with high economic impact is still needed. This research evaluates the efficacy of the US Small Business Innovation Research (SBIR) program from the perspective of promoting high technology entrepreneurship. In particular, we examine whether the local presence of SBIR awards is associated with increased new firm formation rates in the high technology sector. Although the primary objective of SBIR is to facilitate technological commercialization in small businesses, our policy analysis based on spatial multivariate methods suggests that this program may also serve as an effective entrepreneurship policy.

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Notes

  1. A detailed introduction of the SBIR program, including the information about the changes made in reauthorizations and extensions, can be found in Link and Scott (2010).

  2. A full list of high technology industries is available from the authors upon request, or can be found at Hecker (2005).

  3. We use new single-unit establishments (with at least one employee) as a proxy for new firms, since new firm data are not directly available.

  4. In terms of the number of SBIR grants, the three dropped metro counties (Middlesex, MA; Los Angeles, CA; San Diego, CA) are the only ones with a z score above 10 (i.e., more than 10 standard deviations above the mean); In terms of the high technology new firm formation rate, the three dropped metro counties (Fairfax City, VA; Falls Church, VA; Carson City, NV) are the only ones with a z score above 5.

  5. The forms of these two statistics, both following an asymptotic χ2(1) distribution, can be found in Anselin (2001) and Acs et al. (2002).

  6. The OLS model and the maximum likelihood spatial lag model are estimated in GeoDa; the 2SLS spatial lag model is estimated in GeoDaSpace (alpha version).

  7. To check robustness of our results, we also tried 3-nearest neighbors and 4-nearest neighbors to construct the spatial weights matrix and used more advanced spatial econometric techniques such as the generalized method of moments (GMM) estimation proposed by Durkker et al. (2013) and Kelejian and Prucha (2010) that addressed spatial lag dependence, spatial error dependence and heteroschedasticity in a single model. The results were similar with Table 5 especially in term of the effect of SBIR. In addition, we tried to control for state effects by adding 48 state dummy variables. Again, the effect of SBIR remained very similar.

  8. This result is based on a sample excluding the three counties that had the largest numbers of Phase-I SBIR grants (and a z score above 10) and the three counties that exhibited the highest high technology new firm formation rates (and a z score above 5). When these outlier counties are included for regressions, the SBIR variable is no longer significantly associated with high technology entrepreneurship, despite still presenting a positive coefficient. Therefore, the result of this research should be read in the context of excluding these “star” counties.

  9. The SBDC program is a federal initiative administrated by the SBA. Details about this program can be found at: http://www.sba.gov/about-offices-content/1/700/about-us/714.

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Acknowledgments

The authors would like to thank Editor Albert Link and two anonymous reviewers for their constructive comments. This research was in part supported by a grant from the U.S. Department of Agriculture (Contract No. 2008-55401-04487). Access to venture capital data was made possible by the Center for Economic Development, Cleveland State University. All errors are of our own.

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  1. Maxine Goodman Levin College of Urban Affairs, Cleveland State University, 2121 Euclid Ave., UR 315, Cleveland, OH, 44115, USA

    Haifeng Qian

  2. School of Public Policy, George Mason University, 3351 Fairfax Dr., MS 3B1, Arlington, VA, 22201, USA

    Kingsley E. Haynes

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  1. Haifeng Qian
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Qian, H., Haynes, K.E. Beyond innovation: the Small Business Innovation Research program as entrepreneurship policy. J Technol Transf 39, 524–543 (2014). https://doi.org/10.1007/s10961-013-9323-x

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