The Journal of Technology Transfer

, Volume 41, Issue 2, pp 220–249 | Cite as

Multilevel public funding for small business innovation: a review of US state SBIR match programs

  • Lauren LanahanEmail author


US State governments invest in early-stage innovative activity as an economic development strategy. Nevertheless, attention directed at the public sector’s role in this capacity has been placed on federal policy actions overlooking the growing role of states. The primary aims of this paper are two-fold: (1) to articulate the motivations for multilevel public support for small business innovative activity, placing emphasis on state level incentives directed towards entrepreneurial activity; and (2) to empirically evaluate the State Match Phase I (SMP-I) program. The SMP-I program is a diffuse state level policy designed to complement the federal Small Business Innovation Research (SBIR) program by offering noncompetitive matching funds to the state’s successful SBIR Phase I recipients. This offers an opportunity to examine the marginal impact of public R&D given the state intervention. This paper employs a state and year fixed effects model and considers two outcome variables—SBIR Phase II success rates and SBIR Phase I application activity. To account for industrial heterogeneity, the data are stratified by the federal mission agencies. Results from the empirical analysis indicate that the state match increases the Phase II success rates for firms participating in the National Science Foundation SBIR program.


SBIR Innovation policy State government Small business Program evaluation 

JEL Classification

O32 O38 



This research was funded in part by the Ewing Marion Kauffman Foundation and the UNC Graduate School. The origins of this line of work builds upon Maryann P. Feldman’s NSF Grant (0947814): State Science Policies: Modeling Their Origins, Nature, Fit, and Effects on Local Universities. The contents of this publication are solely the responsibility of the author. This research is part of the author’s dissertation project, The Multilevel Innovation Policy Mix: State SBIR Matching Programs. I would like to thank my advisor, Maryann Feldman, for her thoughtful comments and guidance on this research project. Additionally, I would like to thank Alexandra Graddy-Reed, Jeffrey Schroeder, Daniel Smith and four anonymous reviewers for reviewing earlier versions of this paper. Jeremy Moulton and Jade Marcus Jenkins both offered valuable feedback on the empirical analysis.


  1. Abadie, A., Diamond, A., & Hainmueller, J. (2010). Synthetic control methods for comparative case studies: Estimating the effect of California’s tobacco control program. Journal of the American Statistical Association, 105(490), 493–505.CrossRefGoogle Scholar
  2. Almeida, P., & Kogut, B. (1997). The exploration of technological diversity and geographic localization in innovation: Start-up firms in the semiconductor industry. Small Business Economics, 9(1), 21–31.CrossRefGoogle Scholar
  3. Angrist, J. D., & Pischke, J. S. (2009). Mostly harmless econometrics: An empiricist’s companion. Princeton: Princeton University Press.Google Scholar
  4. Arellano, M., & Bond, S. (1991). Some tests of specification for panel data: Monte Carlo evidence and an application to employment equations. The Review of Economic Studies, 58(2), 277–297.CrossRefGoogle Scholar
  5. Arora, A., Fosfuri, A., & Gambardella, A. (2004). Markets for technology: The economics of innovation and corporate strategy. Massachusetts: The MIT Press.Google Scholar
  6. Audretsch, D. B., & Feldman, M. P. (2004). Chapter 61 knowledge spillovers and the geography of innovation. In J. V. Henderson & T. Jacques-François (Eds.), Handbook of regional and Urban economics (Vol. 4, pp. 2713–2739). Amsterdam: Elsevier.Google Scholar
  7. Audretsch, D. B., Link, A. N., & Scott, J. T. (2002). Public/private technology partnerships: Evaluating SBIR-supported research. Research Policy, 31(1), 145–158.CrossRefGoogle Scholar
  8. Belenzon, S., & Schankerman, M. (2013). Spreading the Word: Geography, policy, and knowledge spillovers. Review of Economics and Statistics, 95(3), 884–903.CrossRefGoogle Scholar
  9. Berglund, D., & Coburn, C. (1995). Partnerships: A compenduim of state and federal cooperative technology programs. Columbus: Battelle Press.Google Scholar
  10. Berry, F. S., & Berry, W. D. (1990). State lottery adoptions as policy innovations: An event history analysis. The American Political Science Review, 84(2), 395–415.CrossRefGoogle Scholar
  11. Blume-Kohout, M. E., Kumar, K. B., & Sood, N. (2009). Federal Life Sciences Funding and University R&D. National Bureau of Economic Research Working Paper Series, No. 15146.Google Scholar
  12. Bradley, S. R., Hayter, C. S., & Link, A. N. (2013). Models and methods of university technology transfer. Foundations and Trends in Entreprenuership, 9(6), 1.Google Scholar
  13. Bush, V. (1980). Science–the endless frontier: A report to the President on a program for postwar scientific research. Washington, D.C.: National Science Foundation. Reprinted May 1980.Google Scholar
  14. Cameron, A. C., & Trivedi, P. K. (2009). Microeconometrics using stata (Vol. 5). College Station: Stata Press.Google Scholar
  15. Chatterji, A., Glaeser, E. L., & Kerr, W. R. (2013). Clusters of entrepreneurship and innovation: National Bureau of Economic Research, No. 19013.Google Scholar
  16. Cohen, W. M., & Levinthal, D. A. (1990). Absorptive capacity: A new perspective on learning and innovation. Administrative Science Quarterly, 35(1), 128–152.CrossRefGoogle Scholar
  17. Cohen, W. M., Nelson, R. R., & Walsh, J. P. (2002). Links and impacts: The influence of public research on industrial R&D. Management Science, 48(1), 1–23.CrossRefGoogle Scholar
  18. Combes, R. S., & Todd, W. J. (1996). From henry grady to the georgia research alliance: A case study of science-based development in Georgia. Annals of the New York Academy of Sciences, 798(1), 59–77.CrossRefGoogle Scholar
  19. Cozzens, S. E., & Melkers, J. E. (1997). Use and usefulness of performance measurement in state science and technology programs. Policy Studies Journal, 25(3), 425–435.CrossRefGoogle Scholar
  20. David, P. A., Hall, B. H., & Toole, A. A. (2000). Is public R&D a complement or substitute for private R&D? A review of the econometric evidence. Research Policy, 29(4–5), 497–529.CrossRefGoogle Scholar
  21. Diamond, A. M. (1999). Does federal funding “crowd in” private funding of science? Contemporary Economic Policy, 17(4), 423–431.CrossRefGoogle Scholar
  22. Downs, A., & Corporation, Rand. (1967). Inside bureaucracy (p. 264). Boston: Little, Brown.Google Scholar
  23. Feldman, M. P., & Audretsch, D. B. (1999). Innovation in cities: Science-based diversity, specialization and localized competition. European Economic Review, 43(2), 409–429.CrossRefGoogle Scholar
  24. Feldman, M. P., & Lanahan, L. (2010). Silos of small beer: A case study of the efficacy of federal innovation programs in a key midwest regional economy. In S. Progress (Ed.), (Vol. September 23, 2010). Washington, DC: Center for American Progress.Google Scholar
  25. Feldman, M. P., & Lanahan, L. (2014). State Science Policy Experiments. In A. Jaffe & B. Jones (Eds.), The changing frontier: Rethinking science and innovation policy. Chicago: University of Chicago Press.Google Scholar
  26. Feldman, M. P., Lanahan, L., & Lendel, I. (2014). Experiments in the laboratories of democracy: State scientific capacity building. Economic Development Quarterly, 28(2), 107–131.CrossRefGoogle Scholar
  27. Feller, I. (1997). Federal and state government roles in science and technology. Economic Development Quarterly, 11(4), 283–295.CrossRefGoogle Scholar
  28. Flanagan, K., Uyarra, E., & Laranja, M. (2011). Reconceptualising the ‘policy mix’ for innovation. Research Policy, 40(5), 702–713.CrossRefGoogle Scholar
  29. Gagnon, M. A., & Lexchin, J. (2008). The cost of pushing pills: A new estimate of pharmaceutical promotion expenditures in the United States. PLoS Medicine, 5(1), e1.CrossRefGoogle Scholar
  30. Georghiou, L., & Roessner, D. (2000). Evaluating technology programs: Tools and methods. Research Policy, 29(4–5), 657–678.CrossRefGoogle Scholar
  31. Glaeser, E. L., & Kerr, W. R. (2009). Local industrial conditions and entrepreneurship: How much of the spatial distribution can we explain? Journal of Economics and Management Strategy, 18(3), 623–663.CrossRefGoogle Scholar
  32. Gompers, P., & Lerner, J. (2001). The venture capital revolution. Journal of Economic Perspectives, 15(2), 145–168.CrossRefGoogle Scholar
  33. Graham, S. J. H., Merges, R. P., Samuelson, P., & Sichelman, T. (2009). High technology entrepreneurship and the patent system: Results of the 2008 Berkeley patent survey. Berkeley Technology Law Journal, 24(4), 1255–1327.Google Scholar
  34. Greenstone, M., Hornbeck, R., & Moretti, E. (2010). Identifying agglomeration spillovers: Evidence from winners and losers of large plant openings. The Journal of Political Economy, 118(3), 536–598.CrossRefGoogle Scholar
  35. Griliches, Z. (Ed.). (1998). Issues in Assessing the contribution of research and development to productivity growth. Chicago: University of Chicago Press.Google Scholar
  36. Hannan, M. T., & Freeman, J. (1984). Structural inertia and organizational change. American Sociological Review, 49(2), 149–164.CrossRefGoogle Scholar
  37. Hardin, J. W. (2012). Office of science and technology: Continuation review report. Raleigh: North Carolina Department of Commerce.Google Scholar
  38. Hecker, D. E. (2005). Occupational employment projections to 2014. Monthly Laboratory Review, 128, 70.Google Scholar
  39. Holmes, T. J. (2010). Structural, experimentalist, and the descriptive approaches to empirical work in regional economics. Journal of Regional Science, 50(1), 5–22.CrossRefGoogle Scholar
  40. Howell, S. (2015) Financing constraints as barriers to innovation: Evidence from R&D grants to energy startups. Job market paper (working paper).Google Scholar
  41. Hsu, D. H., & Ziedonis, R. H. (2013). Resources as dual sources of advantage: Implications for valuing entrepreneurial-firm patents. Strategic Management Journal, 34(7), 761–781.CrossRefGoogle Scholar
  42. Jaffe, A., Trajtenberg, M., & Fogarty, M. (2000). Knowledge spillovers and patent citations: Evidence from a survey of inventors. The American Economic Review, 90(2), 215–218.CrossRefGoogle Scholar
  43. Jaffe, A. B., Trajtenberg, M., & Henderson, R. (1993). Geographic localization of knowledge spillovers as evidenced by patent citations. The Quarterly Journal of Economics, 108(3), 577–598.CrossRefGoogle Scholar
  44. Keller, M. R., & Block, F. (2013). Explaining the transformation in the US innovation system: The impact of a small government program. Socio-Economic Review, 11(4), 629–656.CrossRefGoogle Scholar
  45. Kennedy, P. (2003). A guide to econometrics. Cambridge: MIT press.Google Scholar
  46. Koizumi, K.(2008). Historical trends in federal R&D. AAAS Report XXXIII: Research and development FY 2009. Washington DC: AAAS.Google Scholar
  47. Lanahan, L., & Feldman, M.P. (2015). Multilevel Innovation Policy Mix: A Closter Look at State Policies that Augment the Federal SBIR Program. Manuscript tentatively accepted at Research Policy.Google Scholar
  48. Lerner, J. (1999). The government as venture capitalist: The long-run impact of the SBIR program. Journal of Business, 72(3), 285–318.CrossRefGoogle Scholar
  49. Lerner, J. (2009). Boulevard of broken dreams: Why public efforts to boost entrepreneurship and venture capital have failed–and what to do about it. Princeton: Princeton University Press.CrossRefGoogle Scholar
  50. Link, A. N., & Scott, J. T. (2012). Employment growth from public support of innovation in small firms. Economics of Innovation and New Technology, 21(7), 655–678.CrossRefGoogle Scholar
  51. Madison, J. (2002). Powers and continuing advantages of the states. In B. F. Wright (Ed.), The federalist (pp. 324–329). New York: MetroBooks.Google Scholar
  52. Mazzucato, M. A. (2013). The entrepreneurial state: Debunking public vs private sector myths. London: Anthem Press.Google Scholar
  53. McCann, P., & Ortega-Argilés, R. (2013). Smart specialization, regional growth and applications to European Union cohesion policy. Regional Studies,. doi: 10.1080/00343404.2013.799769.Google Scholar
  54. Melkers, J. (2004). Assessing the Outcomes of state science and technology organizations. Economic Development Quarterly, 18(2), 186–201.CrossRefGoogle Scholar
  55. Melkers, J., & Willoughby, K. (1998). The State of the states: Performance-based budgeting requirements in 47 out of 50. Public Administration Review, 58(1), 66–73.CrossRefGoogle Scholar
  56. Muller, A., Valikangas, L., & Merlyn, P. (2005). Metrics for innovation: Guidelines for developing a customized suite of innovation metrics. Strategy and Leadership, 33(1), 37–45.CrossRefGoogle Scholar
  57. Osborne, D. (1988). Laboratories of democracy. Boston: Harvard Business School Press.Google Scholar
  58. Payne, A. A. (2001). Measuring the effect of federal research funding on private donations at research universities: Is federal research funding more than a substitute for private donations? International Tax and Public Finance, 8(5), 731–751.CrossRefGoogle Scholar
  59. Plosila, W. H. (2004). State science- and technology-based economic development policy: History, trends and developments, and future directions. Economic Development Quarterly, 18(2), 113–126.CrossRefGoogle Scholar
  60. Porter, M. E. (1996). Competitive advantage, agglomeration economies, and regional policy. International regional science review, 19(1–2), 85–90.Google Scholar
  61. Porter, M. E., & Stern, S. (2001). Location matters. Sloan Management Review, 42(4), 28–36.Google Scholar
  62. Ruegg, R. T., & Feller, I. (2003). A toolkit for evaluating public R & D investment : Models, methods, and findings from ATP’s first decade. US Department of Commerce, Technology Administration, National Institute of Standards and Technology.Google Scholar
  63. Saxenian, A. L. (1996). Regional advantage: Culture and competition in silicon valley and route 128. Cambridge: Harvard University Press.Google Scholar
  64. Scotchmer, S. (2004). Innovation and incentives. Cambridge: MIT press.Google Scholar
  65. Shadish, W. R., Campbell, D. T., & Cook, T. D. (2002). Experimental and quasi-experimental designs for generalized causal inference. Boston: Houghton Mifflin.Google Scholar
  66. Solow, R. M. (1956). A contribution to the theory of economic growth. The Quarterly Journal of Economics, 70(1), 65–94.CrossRefGoogle Scholar
  67. Stephan, P. (2012). How economics shapes science. Cambridge: Harvard University Press.CrossRefGoogle Scholar
  68. Storey, D. J. (1994). Understanding the small business sector. University of Illinois at Urbana-Champaign’s Academy for Entrepreneurial Leadership Historical Research Reference in Entrepreneurship.Google Scholar
  69. Taylor, C. D. (2012). Governors as economic problem solvers a research commentary. Economic Development Quarterly, 26(3), 267–276.CrossRefGoogle Scholar
  70. Tibbetts, R. (2001). The importance of small high-technology firms to economic growth… and how to nurture them through SBIR. Industry and Higher Education, 15(1), 24–32.CrossRefGoogle Scholar
  71. Toole, A. A., & Czarnitzki, D. (2007). Biomedical academic entrepreneurship through the SBIR program. Journal of Economic Behavior and Organization, 63(4), 716–738.CrossRefGoogle Scholar
  72. Wallsten, S. J. (2000). The effects of government-industry R&D programs on private R&D: The case of the Small Business Innovation Research program. The Rand Journal of Economics, 31(1), 82–100.CrossRefGoogle Scholar
  73. Wessner, C. (2008). An Assessment of the SBIR Program. Washington, DC: The National Academies Press.Google Scholar
  74. Wilson, D. J. (2009). Beggar thy neighbor? The in-state, out-of-state, and aggregate effects of R&D tax credits. Review of Economics and Statistics, 91(2), 431–436.CrossRefGoogle Scholar
  75. Yu, J., & Jackson, R. (2011). Regional innovation clusters: A critical review. Growth and Change, 42(2), 111–124.CrossRefGoogle Scholar
  76. Zabala-Iturriagagoitia, J. M., Voigt, P., Gutiérrez-Gracia, A., & Jiménez-Sáez, F. (2007). Regional innovation systems: How to assess performance. Regional Studies, 41(5), 661–672.CrossRefGoogle Scholar
  77. Zhao, B., & Ziedonis, R. (2012). State Governments as Financiers of Technology Startups: Implications for Firm Performance. Available at SSRN 2060739.Google Scholar

Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  1. 1.Department of Management, Lundquist College of BusinessUniversity of OregonEugeneUSA

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