Abstract
We use the historical self-employment rate and take it as an instrument to analyze the effect of entrepreneurship on economic growth in recent periods. The results indicate that German regions with a high level of entrepreneurship in the early twentieth century have higher start-up rates at the end of the century. The remarkable long-term effect of historical self-employment rates indicates the presence of a regional culture of entrepreneurship that is an important resource for the persistence of entrepreneurship. Furthermore, when using historical self-employment rates as an instrument for start-up activity, we find that there is a significant effect of start-up activity on regional employment growth.
Parts of this chapter are based on Fritsch and Wyrwich (2017).
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Notes
- 1.
This follows the labor market approach for calculating start-up rates (Audretsch and Fritsch 1994). We do not include the number of unemployed because this information is not available at a regional level for the early years of our analysis. Not including the unemployed in the denominator of the start-up rate should not lead to any serious distortion because unemployed persons who set up a business typically do so out of necessity and are unlikely to have dependent employees. Since our data captures start-ups with at least one employee, most of the businesses set up by unemployed are not included anyway.
- 2.
We estimate log(emp(t = 2010)/emp(t = 1976)) which is the same as log emp(t = 2010) – log emp(t = 1976).
- 3.
The coalfields considered are those in the Ruhr area, the Saarland, and the Middle German field (Halle-Leipzig). The information is based on the atlas by Châtel and Dollfus (1931).
- 4.
Additionally, hosting a mine might have caused problems of structural change and negatively affect regional development over time.
- 5.
The results of our analyses are similar when using voter turnout as an alternative indicator for social capital (e.g., Putnam 1993). The election data are based on the publicly available raw data as provided by Falter and Haenisch (1990). The share of right wing votes in 1928 includes the number of votes for the DNVP (Deutsche Nationale Volkspartei) and the NSDAP (Nationalsozialistische Deutsche Arbeiterpartei), which is the party that emerged out of the “Hitler movement”. In alternative models we use only the share of NSDAP votes and the share of right-wing votes in 1924 that comprises votes for DNVP and NSFP (Nationalsozialistische Freiheitspartei), which was a sort of predecessor of the NSDAP.
- 6.
The industry controls account for the regional structure of manufacturing and comprise the employment share in the public sector, in mining, construction, and the remaining manufacturing industries within the region. We did not consider the share of agriculture because this would introduce severe multicollinearity problems due to its extremely high correlation with population density. We did not consider current industry shares because they are presumably more likely to be an outcome of entrepreneurial culture and start-up activity since 1925 than a “control”.
- 7.
There is evidence that innovation inputs and access to finance are highly concentrated, even if controlling for population density (e.g. Audretsch and Feldman 1996; Furman et al. 2002; Carlino et al. 2007). However, in our context all variables to capture innovation inputs and access to finance are highly correlated with population density making the latter indeed a reasonable “catch-all” variable.
- 8.
We also considered an interaction of the share of expellees with the start-up rate in 1925 in the first stage to check whether the first stage relationship is weaker in locations with important in-migration. The interaction does not affect our main results. The definition of variables, summary statistics, and a correlation matrix are provided in Table 6.7 to Table 6.9 in the Appendix.
- 9.
There is a significant positive effect for this variable found in earlier work that analyze start-up rates in later years (Fritsch and Wyrwich 2014). There is also a positive relationship between the share of R&D employees and start-up activity for the period between 1990 and 2010 (not reported). A possible reason for the differences in the results may be an increase of R&D activities in smaller firms over the last decades that might be more likely to induce start-up activity as compared to R&D-activities in large firms. Unfortunately, we cannot test this conjecture with the dataset at hand.
- 10.
A 10% change in the start-up rate reflects 48% of its standard deviation at the sample mean (mean = 4.215; S.D. = 0.8828; 10% of mean = 0.421; 10% of mean/S.D. = 0.477 ~ 48%).
- 11.
In the second stage models, the level of employment at the beginning of the period of analysis is not statistically significant. The coefficient for population density is significantly negative, reflecting a general employment trend of agglomerations in West Germany during the period under investigation (see, e.g. Suedekum 2006). The effect of the measure of market potential is significantly positive, indicating the economic benefits of a more central location. Prior employment growth between 1925 and 1976, as well as the share of self-employed expellees in 1950, have no robust statistically significant effect. The historical control variables are also not related to employment growth.
- 12.
Alternatively, we adjusted the start-up rate based on the industry structure in 1925. The respective sector-adjusted start-up rate captures differences in start-up activity that are not due to initial differences in industry structures in 1925. There is a strong first-stage as well as a second-stage relationship for this version of the start-up rate.
- 13.
One may argue that employees in the private sector are more likely to start firms than employees in the public sector. Hartog et al. (2002) provide empirical evidence for a higher level of risk aversion of civil servants that probably results in a lower propensity to set up a business (see also Özcan and Reichstein 2009). It could, however, also be the case that the level of private sector employment in the mid-1970s is an outcome of a historically high self-employment rate. The results do not change when focusing on private sector employment growth only.
- 14.
For measuring full-time equivalents, we assumed a weight of 0.5 to part-time employees and added full-time employees and weighted part-time employment.
- 15.
As stated earlier, the interplay between high levels of social acceptance of entrepreneurship, widespread self-employment, and the resulting role model effects can make a regional entrepreneurship culture—once established—self-perpetuating. It should be noted here that the prevalence of local entrepreneurial role models is captured by the historical self-employment rate but not by the “entrepreneurial residual” in 1925.
- 16.
It turns out that there is a positive and significant relationship between this residual and growth in OLS estimation. This relationship becomes, however, insignificant when introducing the start-up rate into the regression model.
- 17.
Note that it also accounts for different entry conditions across industries.
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Fritsch, M., Wyrwich, M. (2019). Regional Entrepreneurship Culture and Growth. 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_6
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