Institute for Technology and Innovation Management at RWTH Aachen, Germany
Policy-induced innovation ecosystems have recently emerged as a promising tool to boost local innovation, competitiveness, and growth. However, there remains a substantial lack of evidence regarding their effectiveness. Addressing this gap is critical for the efficient allocation of government resources and the design of impactful policies. This study contributes to the literature by empirically examining the effects of German policy-induced innovation ecosystems on organizations’ innovation activity and growth, utilizing job posting data from 2014–2023. The program aims to establish innovation ecosystems across various industries and innovation fields to promote local development in underprivileged regions. The main econometrical challenge is the potential selection bias, as firms that opt to participate in funding may differ systematically from those that do not. To mitigate this endogeneity concern, we leverage quasi-experimental variation introduced by the program’s two-phase application process. Specifically, we compare organizations accepted for the final funding phase with those that were only accepted for the initial concept development phase. Using Difference-in-Differences models, we find that organizations participating in these ecosystems anticipate increased innovation activity, demonstrated by a rise in STEM-related job postings and positions requiring innovation-related skills. Additionally, participating firms expect to grow, as indicated by a significant increase in job postings, particularly for high-skilled positions.
