Abstract
We investigate the role played by an entrepreneurship culture and the historical knowledge base of a region in current levels of new business formation in innovative industries. The analysis is for German regions and covers the years 1907–2016. We find a pronounced positive relationship between high levels of historical self-employment in science-based industries and new business formation in innovative industries today. This long-term legacy effect of an entrepreneurial tradition indicates the prevalence of a regional culture of entrepreneurship. Moreover, local presence and geographic proximity to a technical university founded before the year 1900 is positively related to the level of innovative start-ups more than a century later. The results show that a considerable part of the knowledge that constitutes an important source of entrepreneurial opportunities is deeply rooted in history. We draw conclusions for policy and for further research.
This chapter is based on Fritsch and Wyrwich (2018).
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Notes
- 1.
For an overview of studies that find long-term persistence of entrepreneurship, see Fritsch and Wyrwich (2017b). Most studies that investigate the sources of regional knowledge and entrepreneurship (e.g., Grabher 1993; Saxenian 1994, and the contributions in Braunerhjelm and Feldman 2006) are on a case-study basis so that the results can hardly be generalized. Recent quantitative approaches based on larger sets of regions analyze the evolution of industries and industrial path-dependencies in regions in the medium run (e.g., Klepper 2009; Boschma 2017).
- 2.
Saxenian’s (1994) comparison of the computer industry in Silicon Valley and the East Coast provides an impressive example of the role of entrepreneurship for the successful commercialization of knowledge.
- 3.
Based on an empirical analysis of the development of the German Ruhr area, which is dominated by large-scale industries, Grabher (1993) argues that the old established incumbents may show a tendency to suppress the emergence of novel ideas and entrepreneurship.
- 4.
There were three classical universities founded between 1900 and 1925 (University of Frankfurt/M. in 1914, University of Cologne in 1919 and University of Hamburg in 1919). These university foundings are not considered in order to keep the indicator consistent for the years 1907 and 1925.
- 5.
A main aim of the initiatives to upgrade technical colleges was to overcome the lower social status of engineers as compared to university graduates. Moreover, upgrading technical colleges to technical universities was regarded an important means for improving the education of engineers (see König 2006).
- 6.
At the same time, we agree that there could have been differences in the quality of universities in the early twentieth century which we cannot measure. Please note that there is no regional variation in literacy levels in Germany between 1907 and 1925, since schooling was compulsory.
- 7.
For a correlation matrix, see Fritsch and Wyrwich (2018, Table A2).
- 8.
Patents (per 10,000 working population) are taken from the REGPAT data base, and are assigned to the region where the inventor has his or her residence. If a patent has more than one inventor, the count is divided by the number of inventors and each inventor is assigned his or her share of that patent.
- 9.
Data on the share of R&D employees is from the German Employment Statistics, which covers all employees subject to compulsory social insurance contributions (Spengler 2008). R&D employees are defined as those with tertiary degrees working as engineers or natural scientists.
- 10.
The coalfields considered are those in the Ruhr area, the Saarland, and the Middle German field (Halle-Leipzig) (see Châtel and Dollfus 1931).
- 11.
This information is available from historical university statistics (Deutsche Hochschulstatistik 1929).
- 12.
Due to the rather small number of observations, one should not over interpret the results of the distinction made between small/large universities. The classification of universities by size is provided in Table A1 in Fritsch and Wyrwich (2018). The results of the empirical analysis are shown in Table A3 of the respective article.
- 13.
Again, all estimated coefficients can be interpreted as elasticities that indicate the relative importance of the respective measure since all continuous variables are log-transformed.
- 14.
As a robustness check, we also interacted the historical self-employment measures with a dummy variable indicating a location in East Germany. There is a significant positive effect for science-based entrepreneurship in the 1925 specifications of the base line models. There is no difference when controlling for the employment share in science-based industries (see Table A4 and A5 in Fritsch and Wyrwich 2018). Since the interaction variables remained insignificant in general, we conclude that the historical self-employment effect is not moderated by the substantial difference in entrepreneurship policies during German separation. Apart from that, a positive interaction for those regions where economic structure and institutions were destroyed to a larger degree indicates that persistent effects of historical self-employment predating these changes are due to cultural not structural components.
- 15.
In a robustness check we added the two academies of mining (Bergakademie Clausthal and Bergakademie Freiberg) to the technical universities that existed in the year 1900 (see Table A6 in Fritsch and Wyrwich 2018). Both institutions are borderline cases of a technical university in the year 1900. Considering both institutions as technical universities does not change the results in a meaningful way.
- 16.
We ran models with only one interaction term to rule out that the results are driven by using more than one interaction term. This method does not change the results. Splitting the sample of classical universities and technical universities into smaller and larger institutions reveals that the persistent effect of regional knowledge is driven by larger universities (see Table A7 and A8 in the Appendix of Fritsch and Wyrwich 2018).
- 17.
The plots can be found in the Appendix of Fritsch and Wyrwich (2018). This includes Figure A1 to A16 including a supportive table for reading the plots.
- 18.
To err on the side of caution, we run all models without the employment share in manufacturing as a robustness check. The results of this exercise reveal no meaningful differences to the set of models presented in Tables 7.3 and 7.4 (see Table A9 and A10 in the Appendix of Fritsch and Wyrwich 2018).
- 19.
For results, see Table A11, and A12 in the Appendix of Fritsch and Wyrwich (2018).
- 20.
For results, see Table A14 and A15 in Fritsch and Wyrwich (2018).
- 21.
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Fritsch, M., Wyrwich, M. (2019). The Role of Knowledge. In: Regional Trajectories of Entrepreneurship, Knowledge, and Growth. International Studies in Entrepreneurship, vol 40. Springer, Cham. https://doi.org/10.1007/978-3-319-97782-9_7
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