Abstract
In this paper we describe the use of computer simulation in the social sciences and economics. These sciences deal with complex systems in which large numbers of components influence each other in a large variety of ways, and some of these influences are stochastic or can best be modeled as stochastic. After a short overview of the history of simulation in the social sciences and economics, two types of simulation are characterized, simulation as numerical treatment of mathematical models otherwise unsolvable, and computer simulation in its own right, where real world entities are mapped on programming language objects. We describe the steps in which modeling and simulation usually proceed, and then turn to a discussion of different purposes of simulation, using a number of simulation examples which at the same time serve to give a first impression of different simulation techniques, to show qualitative and quantitative aspects of simulation and to introduce problems which arise in estimation,
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Troitzsch, K.G. (1999). Simulation as a Tool to Model Stochastic Processes in Complex Systems. In: Brenner, T. (eds) Computational Techniques for Modelling Learning in Economics. Advances in Computational Economics, vol 11. Springer, Boston, MA. https://doi.org/10.1007/978-1-4615-5029-7_2
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DOI: https://doi.org/10.1007/978-1-4615-5029-7_2
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