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Computational economics is an advanced research field 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 nonlinear and dynamic system like the financial market, computational economics finds numerical solutions to multifaceted problems in the areas of public finance, game theory, and macroeconomics. By building virtual economy systems, researchers can further 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 purely from economic reasoning rarely correlate with reality. Many computer economics software packages with preprogrammed optimization routines, such as Gaussian or Conopt, allow economists to take advantage of expanding computing resources 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 then developed based on the interaction of a variety of factors. 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 be agents. Researchers select a given 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 certain processes, organizations, or policies virtually before they are instituted, to ensure that the results are socially beneficial. They feature a variety of actors such as consumers, producers, regulatory agencies, and other relevant factors, all with private motivations and learning capabilities, and allow these actors to virtually interact and develop over time. The main question that the researchers try to answer is whether the strategic behavior of any of the agents can produce an unfair advantage, inefficiency or disorder in the system. In this way, investigators can identify deficiencies in a policy, plan or system before its implementation.
Another goal of computational economics is the identification of regularities and patterns within an economic system, which at first glance may seem completely random. The researchers try to explain the observed regularities by tracking recurring patterns of interaction between agents. Using computer simulations, economists were able to decipher recurring patterns in business cycles, market procedures, and trade networks. Advances in programming methodology, statistical analysis, and visualization have expanded the ability of computational economists to understand economic phenomena and generate theories about their causes.