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Books > Business & Economics > Economics > Economic theory & philosophy
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Agent-Based Computer Simulation of Dichotomous Economic Growth (Hardcover, 2000 ed.)
Loot Price: R4,346
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Agent-Based Computer Simulation of Dichotomous Economic Growth (Hardcover, 2000 ed.)
Series: Advances in Computational Economics, 13
Expected to ship within 10 - 15 working days
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Agent-Based Computer Simulation of Dichotomous Economic Growth
reports a project in agent-based computer stimulation of processes
of economic growth in a population of boundedly rational learning
agents. The study is an exercise in comparative simulation. That
is, the same family of growth models will be simulated under
different assumptions about the nature of the learning process and
details of the production and growth processes. The purpose of this
procedure is to establish a relationship between the assumptions
and the simulation results. The study brings together a number of
theoretical and technical developments, only some of which may be
familiar to any particular reader. In this first chapter, some
issues in economic growth are reviewed and the objectives of the
study are outlined. In the second chapter, the simulation
techniques are introduced and illustrated with baseline simulations
of boundedly rational learning processes that do not involve the
complications of dealing with long-run economic growth. The third
chapter sketches the consensus modern theory of economic growth
which is the starting point for further study. In the fourth
chapter, a family of steady growth models are simulated, bringing
the simulation, growth and learning aspects of the study together.
In subsequent chapters, variants on the growth model are explored
in a similar way. The ninth chapter introduces trade, with a
spacial trading model that is combined with the growth model in the
tenth chapter. The book returns again and again to the key
question: to what extent can the simulations explain' the puzzles
of economic growth, and particularly the key puzzle of
dichotomization, by constructing growth and learning processes that
produce the puzzling results? And just what assumptions of the
simulations are most predictable associated with the puzzling
results?
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