عنوان مقاله [English]
The Walrasian equilibrium model (including the dynamic stochastic general equilibrium model) has been criticized for over-simplification and lack of empirical power. The most important problem with this approach is to model the relationship between micro and macro structure. The economic system is dynamic, adaptive, evolving and complex. Therefore, another approach is needed to model the behavior of this system. With increase in the processing power of computers, it was possible to use agent-based computational methods to study complex economic phenomena and processes. In this approach, there are no limiting and simplistic assumptions existing in the Walrasian approach. This approach addresses the computational study of dynamic and complex economic systems in which heterogeneous agents have interactions with each other. It is a combination of evolutionary economics, cognitive psychology and computer science. Unlike conventional macroeconomics, agent-based macro models are built from bottom to up. Over the past decade, this approach has played a major role in analyzing macroeconomic and policy issues. It is one of the main methods of behavioral economics modeling. Due to high flexibility, agent-based macroeconomics have many applications in various branches of economics, including modeling of electricity markets, the development of institutions and social norms, financial economics, industrial organization, and labor market. In this paper, features, conceptual foundations, modeling components and the advantages and disadvantages of this approach are discussed
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