K+S model with private R&D collaborations
Name of the model: K+S model with private R&D collaborations
Reference paper: Spinola, D., T. Treibich, F. Lamperti, P. Mohnen and A. Roventini (2021) ``Private R&D collaboration, innovation and competition - an agent-based exploration’’, Growinpro deliverable 4.2.
In this paper we investigate the role of private R&D collaboration configurations on market and aggregate dynamics, building on the K+S family of models (Dosi et al., 2010). Our model explains emergent aggregate productivity and economic growth processes from the interaction between private actors, and their impact on the creation and diffusion of technology within the economy. In this framework, we study the effect of different experiments and policies affecting the characteristics of entrant firms (comparing Schumpeter Mark I and II contexts), competition dynamics and the appropriability of knowledge.
Firms in the capital-good sector can decide to collaborate in their R&D efforts and then look for a partner whose technology is sufficiently close to theirs. This increases their chances to innovate and adopt a new vintage of machines, but due to spillovers across partners, they can also more easily imitate and be imitated by the collaborating firm.
Overall, our results convey a positive effect of R&D collaboration on innovation and productivity performance at the firm level, but minor or not significant at the aggregate level. In addition, in a context with active collaborations by small ``start-ups" (highly productive entrants, see our Schumpeter Mark I experiment), GDP growth further increases while the concentration rate decreases. Further policy experiments align with previous results concerning the negative impact of patenting, even in the presence of a patent premium, and the positive impact of antitrust policies on innovation and growth.
Policy Implications / Questions
What is the impact of IPR policy on innovation in the context of R&D collaborations among private firms? How do antitrust and technology policies interact and affect innovation patterns and economic growth?
Collaboration decisions depend on a set of parameters, which are subject to a sensitivity analysis:
- phi_i (sensitivity of collaboration breaks to past performance and random shock)
- imm_td (sensitivity of imitation rate of collaborating firms to change in imitation intensity)
- cRD (sensitivity of collaboration rate to change in weight of market share growth)
Relevant firm-level outcome variables
- Collaboration length, breaks and rate
- Innovation and imitation rates
Relevant aggregate variables
- GDP growth
- Concentration rate (HHI)