Animate the cluster or subsidize collaborative R&D? A multiple overlapping treatments approach to assess the impacts of the French cluster policy
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8 mai 2021
- handle: 10670/1.t183td
- hal: hal-03222070
- doi: 10.1093/icc/dtab002
- WOS: 000728179400001
Ce document est lié à :
info:eu-repo/semantics/altIdentifier/doi/10.1093/icc/dtab002
Mots-clés
Cluster policy R&D Economic performance SME Innovation O - Economic Development, Innovation, Technological Change, and Growth/O.O3 - Innovation • Research and Development • Technological Change • Intellectual Property Rights/O.O3.O32 - Management of Technological Innovation and R&D O - Economic Development, Innovation, Technological Change, and Growth/O.O3 - Innovation • Research and Development • Technological Change • Intellectual Property Rights/O.O3.O38 - Government Policy C - Mathematical and Quantitative Methods/C.C1 - Econometric and Statistical Methods and Methodology: General/C.C1.C14 - Semiparametric and Nonparametric Methods: General C - Mathematical and Quantitative Methods/C.C2 - Single Equation Models • Single Variables/C.C2.C21 - Cross-Sectional Models • Spatial Models • Treatment Effect Models • Quantile RegressionsSujets proches
Technological change Breakthroughs, Technological Innovations, Industrial Technological breakthroughs Technical innovations Innovations, TechnologicalCiter ce document
Modou Mar et al., « Animate the cluster or subsidize collaborative R&D? A multiple overlapping treatments approach to assess the impacts of the French cluster policy », HAL-SHS : économie et finance, ID : 10.1093/icc/dtab002
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Résumé
This article examines the effectiveness of the French cluster policy on R&D and innovation in terms of the economic performance of participating SMEs. Based on an original dataset, we built different measures of treatment and extended the DiD methodology to a multiple overlapping treatments approach. Joining a cluster’s association allows firms to benefit from low-cost animation actions and common services, while participating in R&D projects offers substantial financial support. Our findings indicate a complementarity between the two types of instruments since the policy is most effective when the two treatments are simultaneously used. Interestingly, they also show that belonging to a cluster alone induces much stronger positive impacts on R&D spending and on both the R&D and total employment of SMEs than participating in R&D collaborative projects alone. Therefore, to achieve its impact on SMEs, the cluster policy should not overlook low-cost instruments such as animation actions and common services, both as a standalone instrument and as an effective complement to subsidy policies for collaborative R&D projects.