Public cluster policy and performance

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Abstract

While the conditions for creating clusters and modalities of how clusters should be configured have been investigated intensively, evidence about the performance evaluation of public cluster policy is scarce. This paper addresses this issue and investigates the promotion of ‘leading-edge clusters’ by the German federal government in 2007 as a part of the “High-Tech Strategy 2020”. Based on a unique balanced panel including all 150 German metropolitan areas ranging from 1998 to 2012, we apply treatment and difference-in-differences estimation techniques to evaluate this kind of governmental cluster policy. These leading-edge clusters, selected and intensively supported by the government, encompass 21 of the total 150 German metropolitan areas. In particular, we evaluate whether the treated clusters show a different performance path compared to the control group. Our results strongly support the effect of an active public cluster policy measured by regional GDP growth, yet highlight the importance of robust evaluation approaches and techniques. Our results also shed light on the complementary effects of pre-existing entrepreneurial and innovative ecosystems to spur regional wealth and make cluster policy successful at work.

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Notes

  1. 1.

    See Kuratko and Menter (2017) for a more in-depth description of recent public policies in Germany, especially the leading-edge cluster competition.

  2. 2.

    In total, there have been three rounds of competition, leading to an additional set of five clusters after the last round. These clusters have been nominated in January 2012. Official statistics of our main variables are almost available with certain time lags, ending our dataset in 2012. So we decided to exclude the clusters from the final round from our empirical estimation procedure.

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Correspondence to Matthias Menter.

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Lehmann, E.E., Menter, M. Public cluster policy and performance. J Technol Transf 43, 558–592 (2018). https://doi.org/10.1007/s10961-017-9626-4

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Keywords

  • Public cluster policy
  • Strategic management of places
  • University-industry collaborations
  • Regional clusters
  • Knowledge spillover theory
  • Evaluation

JEL Classification

  • I23
  • O32
  • O38
  • R11