Knowledge Spillover on Complex Networks
Most growth theories have focused on R&D activities. Although R&D significantly influences economic growth, the spillover effect also has a considerable influence. In this paper, we study knowledge spillover among agents by representing it as network structures. The objective of this study is to construct a framework to treat knowledge spillover as a network. We introduce a knowledge spillover equation, solve it analytically to find a workable solution. It has mainly three properties: (1) the growth rate is common for all the agents only if they are linked to the entire network regardless of degrees, (2) the TFP level is proportional to degree, and (3) the growth rate is determined by the underlying network structure. We compare growth rate among representative networks: regular, random, and scale-free networks, and find the growth rate is the greatest in scale-free network. We apply this framework, i.e., knowledge spill over equation, to the problem of firms forming a network endogenously and show how distance and region size affect the economic growth. We also apply the framework to network formation mechanism. The aim of our paper is not just showing results, but in constructing a framework to study spillover by network.
|Date of creation:||Jan 2010|
|Date of revision:|
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