This paper presents an agent-based simulation model (ABM) for assessing the effect of public Research & Development (R&D) policy on companies’ R&D activity. This may question the common wisdom suggesting that larger R&D externality effects should be more likely to arise when few central champions receive a support. Since the aggregated firm idiosyncratic R&D (i.e., the part of total R&D independent of spillovers) is slightly increasing, we conclude that positive cross-firm spillover effects - in the presence of a given amount of support - have a sizeable impact within less centralized networks, where fewer hubs emerge. More specifically, the suggested simulation experiment shows that a larger “hubness” of the network is more likely accompanied with a decreasing median of the aggregated total R&D performance of the system. We set out by illustrating the behavioural structure and the computational logic of the proposed model then, we provide a simulation experiment where the pattern of the total level of R&D activated by a fixed amount of public support is analysed as function of companies’ network topology. This paper presents an agent-based micro-policy simulation model assessing public R&D policy effect when R&D and non-R&D performing companies are located within a network.
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