The effect on economic development of creative class versus human capital: panel evidence from German regions

ABSTRACT

The creative class thesis considers the creative class, compared to human capital, as a better driver of regional economic development. We test this thesis for Germany. We measure creative class and human capital by occupation and education, respectively using classification codes from The Sample of Integrated Labor Market Biographies (SIAB), and proxy regional economic development by per capita income and employment. Our panel estimation results with system GMM show that the human capital effect on per capita income is substantially stronger than the creative class, while the creative class drives employment far better than human capital does. The evidence does not support the notion that the creative class drives development better than human capital.

KEYWORDS:

• Creative class
• human capital
• economic development
• per capita income
• employment
• system GMM

Subject classification codes (JEL):

• R11
• J21
• J24
• O31

Acknowledgements

We would like to thank Joachim Möller, Udo Brixy, Katja Wolf, Dana Müller, Klara Kaufman, Jorg Heining, Philipp vom Berge, and Wolfgang Dauth of the Institute for Employment Research (IAB) for their useful insights in the initial phase of the paper.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Notes

1 Industrial codes or classifications would underestimate the presence of artists tout court. Standard Occupational Codes (SOC) are argued to be best positioned to measure creative occupations vis à vis conventional industrial measures (i.e. Standard Industrial Code, SIC). Likewise, occupational codes would be preferred in this approach with respect to education and regional performance (Becker 1960; Schultz 1962). This literature, unlike CC theory, generally measures human capital through education and tests its effects on households’ economic conditions and implications at the macro level.

2 More information on the construction of the creative class using occupation type along with the corresponding knowledge for each occupation is presented in Appendix A. 

3 See Appendix B for methodological details.

4 The lag length is determined using autoregressive estimation. It is found that the first three lags have robust impact on the current value.

5 Up-to-date information on the nature of the data and on data validity certifies the reliability of the statistics.

6 Florida’s work evidences that about 40% of the labor force in the United States can be considered as CC (aggregate of CCO and CPR).

Additional information

Funding

This work was supported by the University of Trento, Italy [grant number LDGD Ph.D. Scholarship].