R&D Networks: Theory, Empirics and Policy Implications

Abstract

We study a structural model of R&D alliance networks in which firms jointly form R&D collaborations to lower their production costs while competing on the product market. We derive the Nash equilibrium of this game, provide a welfare analysis and determine the optimal R&D subsidy program that maximizes total welfare. We also identify the key firms, i.e. the firms whose exit would reduce welfare the most. We then structurally estimate our model using a panel dataset of R&D collaborations and annual company reports. We use our estimates to identify the key firms and analyze the impact of R&D subsidy programs. Moreover, we analyze temporal changes in the rankings of key firms and how these changes affect the optimal R&D policy.

Static and dynamic networks in interbank markets

“…For example, in a star-shaped network, the key player will always be the central node, while, in other networks, like the one in Figure 3, it will depend on the magnitude of the systemic risk φ. Indeed, to identify which networks are more or less resilient is a more complicated question that refers to a network design policy (Belhaj et al, 2014;König et al, 2014b). Given what we have shown here, it should be clear that regular networks (such as the complete network or the circle) should be more resilient since the exit of one bank from the market should have a relative lower impact on total activity since all banks have the same activity (and all have the same Katz-Bonacich centralities).…”

Innovation, R&D Spillovers, and the Variety and Concentration of the Local Industry Structure*

“…To the best of my knowledge, Steurs () and König et al . () are the only previous studies to consider spillovers between industries, as well as within them. The Steurs model considers the case of two segmented and identical duopolies with different inter‐ and intra‐industry spillover rates.…”

“…Thus, instead of addressing R&D cooperation in the present study, the reader is directed to Steurs () and König et al . () for further details. In addition, we do not consider the relationship between location choice and R&D strategies, which has been studied by Gersbach and Schmutzler (), Mai and Peng (), Baranes and Tropeano (), Fosfuri and Rønde (), Piga and Poyago‐Theotoky (), and Leppälä (), among others.…”

How Powerful Are Network Effects? A Skill-Biased Technological Change Approach

“…Sectors in which R&D activity is relatively intense, such as pharmaceuticals, chemical, computer software, electronic components, and communication equipments, whose production is relatively intensive in skilled labor, have a relatively high number of cooperations and are intensively connected [Hagedoorn and Duysters (2002), Riccaboni and Pammolli (2002), Powell et al (2005), and Roijakkers and Hagedoorn (2006)]. Firms in these sectors have thus formed R&D cooperation 2 that occurs among firms within the same market product and among firms from other sectors [König et al (2014)], sharing knowledge and becoming more specialized in one technology [Weitzman (1998)]. Cooperation intensity is then an important mechanism through which spillovers flow and allows the propagation of learning, knowledge diffusion, and technological-knowledge spillovers through the network [König et al (2014) and Tomasello et al (2016)].…”

“…Firms in these sectors have thus formed R&D cooperation 2 that occurs among firms within the same market product and among firms from other sectors [König et al (2014)], sharing knowledge and becoming more specialized in one technology [Weitzman (1998)]. Cooperation intensity is then an important mechanism through which spillovers flow and allows the propagation of learning, knowledge diffusion, and technological-knowledge spillovers through the network [König et al (2014) and Tomasello et al (2016)]. 3 The noninternalization of technological-knowledge spillovers reduces R&D incentives, and learning and knowledge diffusion promote R&D. Hence, (R&D) cooperations arise as a mechanism to internalize spillovers and to emphasize learning and knowledge diffusion.…”