Computational Economics

Computational Economics is a research discipline at the intersection of computer science and economics that involves the design and application of computational algorithms and simulations to solve complex economic problems. It addresses questions that are often intractable with traditional mathematical and econometric methods by employing techniques such as agent-based modeling to simulate market behavior, numerical methods to solve dynamic systems, and machine learning for forecasting and policy analysis. This approach allows economists to build and test more realistic models of economic phenomena, providing deeper insights into the behavior of markets, firms, and individuals.

1. Introduction to Computational Economics
   1. Defining Computational Economics
      1. Core Definition and Scope
      2. Boundaries of the Field
      3. Distinction from Econometrics
      4. Distinction from Mathematical Economics
      5. Distinction from Operations Research
   2. Historical Development
      1. Early Computational Approaches in Economics
      2. Key Milestones in the Field
      3. Influence of Computing Technology Advances
      4. Evolution of Computational Methods
   3. Role of Computation in Economic Analysis
      1. Computational Modeling of Economic Systems
      2. Simulation versus Analytical Solutions
      3. Empirical Analysis Enhancement
      4. Policy Analysis Applications
   4. Comparison with Traditional Methods
      1. Advantages of Computational Approaches
      2. Limitations of Computational Methods
      3. Integration with Traditional Econometrics
      4. Complementarity with Mathematical Economics
   5. Key Research Areas
      1. Representative versus Heterogeneous Agent Models
      2. Complexity and Nonlinearity
      3. Policy Evaluation
      4. Counterfactual Analysis