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A Computational Model of Industry Dynamics (Paperback)
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A Computational Model of Industry Dynamics (Paperback)
Series: Routledge Advances in Experimental and Computable Economics
Expected to ship within 12 - 17 working days
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The economics literature on industry dynamics contains a wide array
of empirical works identifying a set of stylized facts. There have
been several attempts at constructing analytical models to explain
some of these regularities. These attempts are highly stylized and
limited in scope to keep the analyses tractable. A general model of
industry evolution capable of generating firm and industry
behaviour that can match the data is needed. This book endeavours
to explain many well-documented aspects of the evolution of
industries over time. It uses an agent-based computational model in
which artificial industries are created and grown to maturity in
silico. While the firms in the model are assumed to have bounded
rationality, they are nevertheless adaptive in the sense that their
experience-based R&D efforts allow them to search for improved
technologies. Given a technological environment subject to
persistent and unexpected external shocks, the computationally
generated industry remains in a perennial state of flux. The main
objective of this study is to identify patterns that exist in the
movements of firms as the industry evolves over time along the
steady state in which the measured behaviour of the firms and the
industry stochastically fluctuate around steady means. The
computational model developed in this book is able to replicate
many of the stylized facts from the empirical industrial
organization literature, particularly as the facts pertain to the
dynamics of firm entry and exit. Furthermore, the model allows
examination of cross-industry variations in entry and exit patterns
by systematically varying the characteristics of the market and the
technological environment within which the computationally
generated industry evolves. The model demonstrates that the
computational approach based on boundedly rational agents in a
dynamic setting can be useful and effective in carrying out both
positive and normative economic analysis.
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