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Knowledge Exchange, Matching, and Agglomeration

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  • Marcus Berliant
  • Robert R Reed
  • Ping Wang

Abstract

Despite wide recognition of their significant role in explaining sustained growth and economic development, uncompensated knowledge spillovers have not yet been fully modeled with a microeconomic foundation. This paper illustrates the exchange of knowledge as well as its consequences for agglomerative activity in a general-equilibrium search-theoretic framework. Agents, possessing differentiated types of knowledge, search for partners to exchange ideas in order to improve production efficacy. When individuals’ types of knowledge are too diverse, a match is less likely to generate significant innovations. We demonstrate that the extent of agglomeration has significant implications for the patterns of information flows in economies. By simultaneously determining the patterns of knowledge exchange and the population agglomeration of an economy, we identify additional channels for interaction between agglomerative activity and knowledge exchange. The main implications of the model are a negative correlation between city population and diversity of knowledge exchange and a positive correlation between city population and per capita knowledge or patent output. Contrary to previous work in urban economics and growth theory, it is possible that a decentralized equilibrium is under-populated or over-populated and under-selective or over-selective in knowledge exchange, compared to the social optimum. By allowing for perpetual knowledge accumulation, we find that population agglomeration is generally accompanied by higher growth. The main findings remain qualitatively unchanged even if we allow individual knowledge types to change over time, though the creation of new types of knowledge may result in multiple equilibria.

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Paper provided by UCLA Department of Economics in its series Levine's Bibliography with number 666156000000000395.

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Date of creation: 26 Nov 2003
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Handle: RePEc:cla:levrem:666156000000000395

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