🤖 AI Summary
This study investigates how individual scientific and technological productivity is shaped by collaborators’ behavior and network position, and clarifies whether scientific and technological collaboration act as complements or substitutes. Leveraging a simultaneous-equation network framework, the authors construct a two-layer collaboration network integrating co-authored papers and co-invented patents. Identification relies on a modified Katz-Bonacich centrality measure, an instrumental variable approach exploiting exogenous dyadic attributes to predict link formation, and community fixed effects. The analysis provides the first joint dynamic evidence of peer effects in both science and invention, revealing an asymmetric mechanism through which science drives innovation: network centrality significantly enhances both types of output, and scientific productivity positively spurs technological output, whereas the reverse effect is statistically insignificant. These findings offer a microfoundation for policies promoting synergistic innovation.
📝 Abstract
This paper develops a theory of scientific and technological peer effects to study how individuals'productivity responds to the behavior and network positions of their collaborators across both scientific and inventive activities. Building on a simultaneous equation network framework, the model predicts that productivity in each activity increases in a variation of the Katz-Bonacich centrality that captures within-activity and cross-activity strategic complementarities. To test these predictions, we assemble the universe of cancer-related publications and patents and construct coauthorship and coinventorship networks that jointly map the collaboration structure of researchers active in both spheres. Using an instrumental-variables approach based on predicted link formation from exogenous dyadic characteristics, and incorporating community fixed effects to address endogenous network formation, we show that both authors'and inventors'outputs rise with their network centrality, consistent with the theory. Moreover, scientific productivity significantly enhances technological productivity, while technological output does not exert a detectable reciprocal effect on scientific production, highlighting an asymmetric linkage aligned with a science-driven model of innovation. These findings provide the first empirical evidence on the joint dynamics of scientific and inventive peer effects, underscore the micro-foundations of the co-evolution of science and technology, and reveal how collaboration structures can be leveraged to design policies that enhance collective knowledge creation and downstream innovation.