Strategic Interactions in Science and Technology Networks: Substitutes or Complements?

TL;DR

This paper develops a network-based theory of scientific and technological peer effects, empirically demonstrating that collaboration centrality boosts productivity in both domains, with scientific output positively influencing technological innovation.

Contribution

It introduces a simultaneous equation network model capturing cross-activity peer effects and provides the first empirical evidence of their joint dynamics in science and technology.

Findings

Network centrality increases productivity in science and technology.

Scientific output significantly boosts technological innovation.

Technological output does not reciprocally affect scientific productivity.

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.