Computational economics uses computer tools to solve complex problems in finance, public finance, game theory, and macroeconomics. Agent-based computational economics builds models of economic processes using independent factors or agents. Goals include assessing system performance and identifying regularities and patterns within an economic system.
Computational economics is an advanced field of research in which economists use computational tools to solve analytical problems and predict or model the complex interaction of many agents in financial markets. In a non-linear dynamic system such as the financial market, computational economics finds numerical solutions to multifaceted problems in the areas of public finance, game theory and macroeconomics. By building virtual economic systems, researchers can broaden their understanding of the regularities, norms, and potential behaviors observed within these systems in the real world. On the other hand, formulas and algorithms derived exclusively from economic reasoning rarely correlate with reality. Many computational economics software packages with pre-programmed optimization routines, such as Gauss or Conopt, allow economists to take advantage of expanding computer capabilities to generate solutions to economic problems.
Agent-based computational economics (ACE) is a specialized area of computational economics that builds models of economic processes using fixed initial conditions determined by the researcher, but later developed based on the interaction of several independent factors or agents. Agents can be physical entities, such as the weather, or biological entities, such as livestock or crops. Furthermore, individuals, such as consumers, or institutions, such as a large market, can also constitute agents. Researchers select a specific set of agents for a given formulation based on the problem being studied.
Several critical goals drive computational economics. Some researchers seek to assess the system performance of particular processes, organizations or policies virtually before they are instituted to ensure that the results are socially advantageous. They introduce a variety of actors such as consumers, producers, regulatory agencies and other pertinent factors, all with private motivations and learning capabilities, and allow these actors to virtually interact and develop over time. The main question researchers try to answer is whether the strategic behavior of any of the agents can produce unfair advantage, inefficiency or disorder in the system. In this way, researchers can identify deficiencies in a policy, plan, or system prior to implementation.
Another objective of computational economics is the identification of regularities and patterns within an economic system, which at first glance may seem totally random. The researchers try to explain the observed regularities by tracking recurrent patterns of interaction between agents. Using computer simulations, economists have been able to discern recurring patterns in business cycles, market procedures and trade networks. Advances in programming methodology, statistical analysis, and visualization have enhanced the ability of computational economists to understand economic phenomena and generate theories about what causes them.
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