Abstract
New businesses are an important source of economic growth (Fritsch 2013), especially those start-ups that pose a competitive threat to incumbent firms by introducing a significant innovation. The available data suggest that only a small fraction of all start-ups is of such quality and that their geographic distribution is highly uneven (Fritsch 2011). According to the knowledge spillover theory of entrepreneurship (Acs et al. 2009), new businesses in general, and highly innovative start-ups in particular, are manifestations of knowledge spillover from extant knowledge sources. Hence, the number and the types of new business are shaped considerably by the regional knowledge base, and the emergence of innovative start-ups can be especially expected in regions with significant amounts of knowledge, private or public.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
- 2.
Harhoff’s (1999) analysis is limited to start-ups in electrical machinery and the mechanical engineering industry. Audretsch and Lehmann (2005) and Audretsch et al. (2005) focus on 281 firms that made an initial public offering (IPO) in Germany between March 1997 and March 2002. Since these firms may have been set up considerably in advance of making an IPO, their founding date is only vaguely defined.
- 3.
- 4.
- 5.
This corresponds to the observation that founders are likely to set up their business in the industry in which they previously worked (Fritsch and Falck 2007).
- 6.
Since many service firms do not have a standardized product program but provide customer-specific services, they are not innovative in the same sense as manufacturing firms. Hence, service industries that may be relevant for innovation are defined as such based on the knowledge intensity of their inputs. These knowledge-intensive service industries include, for example, “computer services,” “research and development in natural sciences and engineering,” and “business consultancy.” For definitions of these groups of industries, see Grupp and Legler (2000) and OECD (2005). For a review of different methods of identifying innovative businesses, see Fritsch (2011).
- 7.
- 8.
The reason for these mixed results may be high correlation among the different indicators (see Sect. 2.4).
- 9.
A study of the USA by Bania et al. (1993) shows that there may also be considerable differences in the effect of different regional knowledge sources among four-digit industries that are classified as highly innovative.
- 10.
An indication for different effects of size and quality-related university indicators is provided by Fritsch and Slavtchev (2007), who find that only the volume of external funds has a positive effect on regional innovation activity; no such positive effect can be found for indicators that are related to size, such as the number of professors and academic personnel or the number of students and of graduates.
- 11.
See Fritsch (2011) for the classification of German industries as “innovative,” “technologically advanced,” or “technology-intensive services.”
- 12.
For an official translation for the German administrative divisions, see EC-DGT (2014).
- 13.
All institutes of the four large public research organizations in Germany are accounted for, i.e., the Fraunhofer, the Helmholtz, the Leibnitz, and the Max Planck Society. Data have been collected from different sources, mainly from publications of these organizations and the Federal Ministry of Education and Research. Since a number of these institutes have several locations, the publicly available information about their budgets and number of personnel cannot be meaningfully assigned to regions.
- 14.
If a patent has more than one inventor, the count is divided by the number of the inventors involved and each inventor is registered with his or her share of that patent.
- 15.
This common classification of German regions by the Federal Office for Building and Regional Planning is based on a region’s population density and settlement structure. For details, see Federal Office for Building and Regional Planning (2003).
- 16.
The highest number of HEIs can be found in Berlin (34 HEIs), followed by Munich (19), Hamburg (17), and Stuttgart (10). The regions with the highest number of non-university institutions for public research are Berlin (26), Munich (20), and Dresden (17).
- 17.
A plausible assumption for the selection of “true” zero values could be that the emergence of an innovative start-up in a region requires the presence of at least one university or of a non-university public research institute. This assumption, however, is not unproblematic because it already implies the general hypothesis that innovative start-ups emerge from public research. Running a zero-inflated negative binomial model with the variable “presence of a university or non-university public research institute in the region” for the selection of the “true” zero values, reveals a Vuong test suggesting that doing so is not a significant improvement over a standard negative binomial model.
- 18.
A great deal of the financing and legal framework for universities and non-university public research institutes is the responsibility of the Federal States in Germany. Most of the Federal States also operate their own programs for promoting entrepreneurship.
- 19.
- 20.
Employment in industry groups and small-firm employment are entered in the regressions as shares in overall regional employment because including these numbers would lead to double counting with the overall number of employees and cause multicollinearity.
- 21.
It is not distinguished between patents registered by HEIs, non-university public research institutes, or the private sector for several reasons. One reason is that universities and other public research institutes in Germany are to different degrees selective with respect to patenting inventions so the number of patents is not a meaningful indicator of innovative output. A second reason is a change in the legal framework for university patenting that led to considerable change in patenting behavior during the period of analysis (for details, see Proff et al. 2012).
- 22.
The correlation coefficient between the aggregate indicator for the regional HEIs (the number of non-university public research institutes) and the number of private-sector R&D employees is 0.465 (0.596); see Table A.2 in the Appendix. The correlation between the regional number of private-sector R&D employees and the aggregate indicator for HEIs (the number of non-university public research institutes) in adjacent regions is 0.323 (−0.021).
- 23.
See Tables A.6–A.14 in the Appendix.
- 24.
The coefficient of correlation between these two indicators in the overall sample is 0.488 (see Table A.2 in the Appendix).
References
Acs ZJ, Braunerhjelm P, Audretsch DB, Carlsson B (2009) The knowledge spillover theory of entrepreneurship. Small Bus Econ 32:15–30
Acs ZJ, Audretsch DB, Lehmann E (2013) The knowledge spillover theory of entrepreneurship. Small Bus Econ 41:767–774
Adams JD (2002) Comparative localization of academic and industrial spillovers. J Econ Geogr 2:253–278
Akaike H (1974) A new look at the statistical model identification. IEEE Trans Autom Control 19:716–723
Anselin L, Varga A, Acs ZJ (1997) Local geographic spillovers between university research and high technology innovations. J Urban Econ 42:422–448
Asheim BT, Gertler MS (2005) The geography of innovation: regional innovation systems. In: Fagerberg J, Mowery DC, Nelson RR (eds) The Oxford handbook of innovation. Oxford University Press, Oxford, pp 291–317
Åstebro T, Bazzazian N (2011) Universities, entrepreneurship and local economic development. In: Fritsch M (ed) Handbook of research on entrepreneurship and regional development. Elgar, Cheltenham, pp 252–333
Audretsch DB, Lehmann EE (2005) Does the knowledge spillover theory of entrepreneurship hold for regions? Res Policy 34:1191–1202
Audretsch DB, Lehmann EE, Warning S (2005) University spillovers and new firm location. Res Policy 34:1113–1122
Audretsch DB, Keilbach M, Lehmann EE (2006) Entrepreneurship and economic growth. Oxford University Press, Oxford
Bade F-J, Nerlinger EA (2000) The spatial distribution of new technology-based firms: empirical results for West-Germany. Papers Region Sci 79:155–176
Bania N, Eberts RW, Fogerty MS (1993) Universities and the startup of new companies can we generalize from Route 128 and Silicon Valley? Rev Econ Stat 75:761–766
Baptista R, Mendonça J (2010) Proximity to knowledge sources and the location of knowledge-based start-ups. Ann Region Sci 45:5–29
Baptista R, Lima F, Mendonça J (2011) Establishment of higher education institutions and new firm entry. Res Policy 40:751–760
Bonaccorsi A, Colombo MG, Guerini M, Rossi-Lamastra C (2014) How universities contribute to the creation of knowledge-intensive firms: detailed evidence on the Italian case. In: Bonaccorsi A (ed) Knowledge, diversity and performance in European Higher Education—A changing landscape. Edward Elgar, Cheltenham, pp 205–230
Boschma R (2005) Proximity and innovation: a critical assessment. Region Stud 39:61–74
Bosma N, Hessels J, Schutjens V, van Praag M, Verheul I (2012) Entrepreneurship and role models. J Econ Psychol 33:410–424
Carree MA (2002) Does unemployment affect the number of establishments? A regional analysis for US states. Region Stud 36:389–398
Carree MA, Della-Malva A, Santarelli E (2014) The contribution of universities to growth: empirical evidence for Italy. J Technol Transf 39:393–414
Dahl MS, Sorenson O (2009) The embedded entrepreneur. Eur Manag Rev 6:172–181
EC-DGT: European Commission; Directorate-General for Translation (2014) Country compendium: a companion to the English style guide. EC Directorate-General for Translation, Brussels
Elfenbein DW, Hamilton BH, Zenger TR (2010) The small firm effect and the entrepreneurial spawning of scientists and engineers. Manag Sci 56:659–681
Federal Office for Building and Regional Planning (Bundesamt für Bauwesen und Raumordnung) (2003) Aktuelle Daten zur Entwicklung der Städte, Kreise und Gemeinden, vol 17. Federal Office for Building and Regional Planning, Bonn
Feldman MP (2001) The entrepreneurial event revisited: firm formation in a regional context. Indus Corp Change 10:861–891
Figueiredo O, Guimaraes P, Woodward D (2002) Home-field advantage: location decisions of Portuguese entrepreneurs. J Urban Econ 52:341–361
Fritsch M (2011) Start-ups in innovative industries—Causes and effects. In: Audretsch DB, Falck O, Heblich S, Lederer A (eds) Handbook of innovation and entrepreneurship. Elgar, Cheltenham, pp 365–381
Fritsch M (2013) New business formation and regional development—A survey and assessment of the evidence. Found Trends Entrepreneurship 9:249–364
Fritsch M, Falck O (2007) New business formation by industry over space and time: a multidimensional analysis. Region Stud 41:157–172
Fritsch M, Slavtchev V (2007) Universities and innovation in space. Industry Innov 14:201–218
Gehrke B, Schasse U, Rammer C, Frietsch R, Neuhäusler P, Leidmann M (2010) Listen wissens- und technologieintensiver Güter und Wirtschaftszweige. Studien zum deutschen Innovationssystem, 19, Frauenhofer ISI, NIW, ZEW
Greene WH (2012) Econometric analysis, 7th edn. Pearson Prentice Hall, Upper Saddle River, NJ
Grupp H, Legler H (2000) Hochtechnologie 2000: Neudefinition der Hochtechnologie für die Berichterstattung zur technologischen Leistungsfähigkeit Deutschlands. Karlsruhe and Hannover, FhG, ISI, NIW
Harhoff D (1999) Firm formation and regional spillovers – Evidence from Germany. Econ Innov New Technol 8:27–55
Hülsbeck M, Pickavé EN (2014) Regional knowledge production as determinant of high-technology entrepreneurship: empirical evidence for Germany. Int Entrepreneurship Manag J 10:121–138
Klepper S (2009) Spinoffs: a review and synthesis. Eur Manag Rev 6:159–171
Lasch F, Robert F, Le Roy F (2013) Regional determinants of ICT new firm formation. Small Bus Econ 40:671–686
Markusen A, Glasmeier A, Hall P (1986) High tech in America—The what, how, where, and why of the sunrise industries. Allen & Unwin, Boston, MA
OECD: Organisation for Economic Co-operation and Development (2005) OECD handbook on economic globalization indicators. OECD, Paris
Parker SC (2009) Why do small firms produce the entrepreneurs? J Socio-Econ 38:484–494
Piva E, Grilli L, Rossi-Lamastra C (2011) The creation of high-tech entrepreneurial ventures at the local level: the role of local competences and communication infrastructures. Industry Innov 18:563–580
Proff S v, Buenstorf G, Hummel M (2012) University patenting in Germany before and after 2002: what role did the professors’ privilege play? Industry Innov 19:23–44
Reynolds PD, Storey DJ, Westhead P (1994) Cross-national comparisons of the variation in new firm formation rates. Region Stud 28:443–456
Spengler A (2008) The establishment history panel. Schmollers Jahrbuch/J Appl Social Sci Stud 128:501–509
Sternberg R (2009) Regional dimensions of entrepreneurship. Found Trends Entrepreneurship 5:211–340
Storey DJ, Tether BS (1998) New technology-based firms in the European Union: an introduction. Res Policy 26:933–946
Sutaria V, Hicks DA (2004) New firm formation: dynamics and determinants. Ann Region Sci 38:241–262
Zentrum für Europäische Wirtschaftsforschung (ZEW) (2011) Die Bereitstellung von Standardauswertungen zum Gründungsgeschehen in Deutschland für externe Datennutzer. ZEW, Mannheim
Author information
Authors and Affiliations
Rights and permissions
Copyright information
© 2016 Springer International Publishing Switzerland
About this chapter
Cite this chapter
Aamoucke, R. (2016). Regional Public Research, Higher Education, and Innovative Start-Ups. In: Innovative Start-Ups and the Distribution of Human Capital. Contributions to Economics. Springer, Cham. https://doi.org/10.1007/978-3-319-44462-8_2
Download citation
DOI: https://doi.org/10.1007/978-3-319-44462-8_2
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-44461-1
Online ISBN: 978-3-319-44462-8
eBook Packages: Economics and FinanceEconomics and Finance (R0)