This study examines the role of public investments in inducing small firms to develop risky, early-stage technologies. It contributes to expanding our understanding of the consequences of high-technology policies by investigating in more depth the effect of the Small Business Innovation Research (SBIR) program on the innovation effort and ability to attract external capital of small business start-ups using a new sample and estimation approach. The authors found empirical evidence that the public cofinancing of private research and development has a positive effect on the innovation propensity of small high-tech start-ups. However, contrary to theoretical expectations, they did not find any significant “certification effect” of receiving an SBIR award on attracting follow-on investment. What the authors discovered is a different certification effect: SBIR recipient firms are more likely to attract external patents. This finding confirms that enterprises need to orchestrate a portfolio of internal and external knowledge assets to produce innovations with unique competitive advantage.
AcsZ. J.AudretschD. B. (1990). Innovation and small firms. Cambridge: MIT Press.
2.
AertsK.SchmidtT. (2008). Two for the price of one? Additionality effects of R&D subsidies: A comparison between Flanders and Germany. Research Policy, 37, 806-822. doi:10.1016/j.respol.2008.01.011
3.
AlmeidaP.KogutB. (1997). The exploration of technological diversity and geographic localization in innovation: Start-up firms in the semiconductor industry. Small Business Economics, 9, 21-31. doi:10.1023/a:1007995512597
4.
ArrowK. J. (1962). Economic welfare and the allocation of resources for invention. In NelsonR. R. (Ed.), The rate and direction of inventive activity (pp. 609-625). Princeton, NJ: Princeton University Press.
5.
AudretschD. B.LinkA. N.ScottJ. T. (2002). Public/private technology partnerships: Evaluating SBIR-supported research. Research Policy, 31, 145-158. doi:10.1016/S0048-7333(00)00158-X
6.
AudretschD. B.WeigandJ.WeigandC. (2002). The impact of the SBIR on creating entrepreneurial behavior. Economic Development Quarterly, 16, 32-38. doi:10.1177/089124240201600104
7.
AuerswaldP. E.BranscombL. M. (2003). Valleys of death and Darwinian seas: Financing the invention to innovation transition in the United States. Journal of Technology Transfer, 28, 227-239. doi:10.1023/a:1024980525678
8.
BerubeC.MohnenP. (2009). Are firms that receive R&D subsidies more innovative?Canadian Journal of Economics, 42, 206-225. doi:10.1111/j.1540-5982.2008.01505.x
9.
BorrusM.StowskyJ. (1999). Technology policy and economic growth. In BranscombL. M.KellerJ. H. (Eds.), Investing in innovation: Creating a research and innovation policy that works (pp. 40-63). Cambridge: MIT Press.
10.
BranscombL. M.KellerJ. (Eds.). (1999). Investing in innovation: Creating a research and innovation policy that works. Cambridge: MIT Press.
CameronA. C.TrivediP. K. (2005). Microeconometrics: Methods and applications. New York, NY: Cambridge University Press.
13.
ChesbroughH. W. (2003). Open innovation: The new imperative for creating and profiting from technology. Boston, MA: Harvard Business School Press.
14.
ClarysseB.WrightM.MustarP. (2009). Behavioural additionality of R&D subsidies: A learning perspective. Research Policy, 38, 1517-1533. doi:10.1016/j.respol.2009.09.003
15.
CollierD.BradyH.SeawrightJ. (2004). Sources of leverage in causal inference: Toward an alternative view of methodology. In BradyH.CollierD. (Eds.), Rethinking social inquiry: Diverse tools, shared standards (pp. 229-266). Oxford, England: Rowman & Littlefield.
16.
CooperR. S. (2003). Purpose and performance of the Small Business Innovation Research (SBIR) program. Small Business Economics, 20, 137-151. doi:10.1023/A:1022212015154
17.
CozzensS. E.MelkersJ. E. (1997). Use and usefulness of performance measurement in state science and technology programs. Policy Studies Journal, 25, 425-435. doi:10.1111/j.1541-0072.1997.tb00032.x
18.
CzarnitzkiD.LichtG. (2006). Additionality of public R&D grants in a transition economy. Economics of Transition, 14, 101-131.
19.
DavidP. A.HallB. H.TooleA. A. (2000). Is public R&D a complement or substitute for private R&D? A review of the econometric evidence. Research Policy, 29, 497-529.
20.
DehejiaR. H.WahbaS. (1999). Causal effects in nonexperimental studies: Reevaluating the evaluation of training programs. Journal of the American Statistical Association, 94, 1053-1062.
21.
DehejiaR. H.WahbaS. (2002). Propensity score-matching methods for nonexperimental causal studies. Review of Economics and Statistics, 84, 151-161.
22.
FeldmanM. P.KoglerD. F. (2008). The contribution of public entities to innovation and technological change. In ShaneS. (Ed.), Handbook of technology and innovation management (pp. 431-459). Chichester, England: John Wiley.
23.
GalopeR. V. (2014). What types of start-ups receive funding from the Small Business Innovation Research (SBIR) program? Evidence from the Kauffman Firm Survey. Journal of Technology Management & Innovation, 9, 17-28. doi:10.4067/S0718-27242014000200002
24.
GelmanA.HillJ. (2007). Data analysis using regression and multilevel/hierarchical models. New York, NY: Cambridge University Press.
25.
GeorghiouL. (2002). Impact and additionality of innovation policy. In BoekholtP. (Ed.), Innovation policy and sustainable development: Can public innovation incentives make a difference (pp. 57-66)? Brussels, Belgium: IWT Observatory.
26.
GeroskiP. (1995). Markets for technology: Knowledge, innovation and appropriability. In StonemanP. (Ed.), Handbook of the economics of innovation and technological change (pp. 90-132). Oxford, England: Blackwell.
27.
GlazermanS.LevyD. M.MyersD. (2003). Nonexperimental versus experimental estimates of earnings impacts. ANNALS of the American Academy of Political and Social Science, 589(1), 63-93. doi:10.1177/0002716203254879
28.
GonzálezX.PazóC. (2008). Do public subsidies stimulate private R&D spending?Research Policy, 37, 371-389.
29.
GreenbergD. H.MichalopoulosC.RobinsP. K. (2006). Do experimental and nonexperimental evaluations give different answers about the effectiveness of government-funded training programs?Journal of Policy Analysis and Management, 25, 523-552. doi:10.1002/pam.20190
30.
GuoS.FraserM. W. (2010). Propensity score analysis: Statistical methods and applications. Thousand Oaks, CA: Sage.
31.
HeckmanJ. J.IchimuraH.ToddP. (1998). Matching as an econometric evaluation estimator. Review of Economic Studies, 65, 261-294.
32.
HeinrichC. J. (2007). Evidence-based policy and performance management: Challenges and prospects in two parallel movements. American Review of Public Administration, 37, 255-277. doi:10.1177/0275074007301957
33.
HoD. E.ImaiK.KingG.StuartE. A. (2007). Matching as nonparametric preprocessing for reducing model dependence in parametric causal inference. Political Analysis, 15, 199-236.
34.
HollandP. W. (1986). Statistics and causal inference. Journal of the American Statistical Association, 81, 945-970.
35.
HubbardR. G. (1998). Capital-market imperfections and investment. Journal of Economic Literature, 36, 193-225.
36.
KhandkerS. R.KoolwalG. B.SamadH. A. (2010). Handbook on impact evaluation: Quantitative methods and practice. Washington, DC: World Bank.
37.
KletteT. J.MøenJ.GrilichesZ. (2000). Do subsidies to commercial R&D reduce market failures? Microeconometric evaluation studies. Research Policy, 29, 471-495.
38.
KogaT. (2005). R&D subsidy and self-financed R&D: The case of Japanese high-technology start-ups. Small Business Economics, 24, 53-62. doi:10.1007/s11187-005-3096-z
39.
LeeE. Y.CinB. C. (2010). The effect of risk-sharing government subsidy on corporate R&D investment: Empirical evidence from Korea. Technological Forecasting and Social Change, 77, 881-890. doi:10.1016/j.techfore.2010.01.012
40.
LernerJ. (1999). The government as venture capitalist: The long-run impact of the SBIR program. Journal of Business, 72, 285-318.
41.
LewisD. (1973). Causation. Journal of Philosophy, 70, 556-567.
42.
LinkA. N.ScottJ. T. (2000). Estimates of the social returns to Small Business Innovation Research projects. In WessnerC. W. (Ed.), The small business innovation research program. (pp. 275-290). Washington, DC: National Academy Press.
43.
LinkA. N.ScottJ. T. (2010). Government as entrepreneur: Evaluating the commercialization success of SBIR projects. Research Policy, 39, 589-601. doi:10.1016/j.respol.2010.02.006
44.
MetcalfeS. (1995). The economic foundations of technology policy: Equilibrium and evolutionary perspectives. In StonemanP. (Ed.), Handbook of the economics of innovation and technological change (pp. 409-557). Oxford, England: Blackwell.
45.
MorganS. L.WinshipC. (2007). Counterfactuals and causal inference: Methods and principles for social research. New York, NY: Cambridge University Press.
46.
NelsonR. R.WinterS. G. (1982). An evolutionary theory of economic change. Cambridge, MA: Harvard University Press.
47.
ÖzçelikE.TaymazE. (2008). R&D support programs in developing countries: The Turkish experience. Research Policy, 37, 258-275.
48.
PearlJ. (2009). Causality: Models, reasoning and interference (2nd ed.). New York, NY: Cambridge University Press.
RosenbaumP. R. (2005). Heterogeneity and causality: Unit heterogeneity and design sensitivity in observational studies. The American Statistician, 59, 147-152.
51.
RosenbaumP. R.RubinD. B. (1983). The central role of the propensity score in observational studies. Biometrika, 70, 41-55.
52.
RubinD. B. (1974). Estimating causal effects of treatments in randomized and nonrandomized Studies. Journal of Educational Psychology, 66, 688-701.
53.
SekhonJ. S. (2008). The Neyman-Rubin model of causal inference and estimation via matching methods. In Box-SteffensmeierJ. M.BradyH. E.CollierD. (Eds.), The Oxford handbook of political methodology (pp. 271-299). Oxford, England: Oxford University Press.
54.
ShaneS. (2000). Prior knowledge and the discovery of entrepreneurial opportunities. Organization Science, 11, 448-469. doi:10.1287/orsc.11.4.448.14602
55.
ShapiraP.KuhlmannS. (2003). Learning from science and technology policy evaluation: Experiences from the United States and Europe. Cheltenham, Gloucestershire, England: Edward Elgar.
56.
SiegelD. S.WessnerC.BinksM.LockettA. (2003). Policies promoting innovation in small firms: Evidence from the US and UK. Small Business Economics, 20, 121-127.
57.
TasseyG. (2007). The technology imperative. Cheltenham, Gloucestershire, England: Edward Elgar.
58.
TeeceD. J. (1986). Profiting from technological innovation: Implications for integration, collaboration, licensing and public policy. Research Policy, 15, 285-305. doi:10.1016/0048-7333(86)90027-2
59.
TeeceD. J. (2009). Dynamic capabilities and strategic management: Organizing for innovation and growth. New York, NY: Oxford University Press.
60.
TooleA. A.CzarnitzkiD. (2007). Biomedical academic entrepreneurship through the SBIR program. Journal of Economic Behavior & Organization, 63, 716-738.
61.
TooleA. A.TurveyC. (2009). How does initial public financing influence private incentives for follow-on investment in early-stage technologies?Journal of Technology Transfer, 34, 43-58. doi:10.1007/s10961-007-9074-7
62.
WallstenS. J. (2000). The effects of government-industry R&D programs on private R&D: The case of the Small Business Innovation Research program. RAND Journal of Economics, 31, 82-100.
