Computational Economics

Professors: Strong and Welburn
Units: 1.0
Elective Course
Concentration: Economic Analysis

This course introduces the concepts and methods of computational economics and their application to economic policy. The course reviews optimization methods from Lagrange to nonlinear programming (NLP) and the Mixed Complementarity Problem (MCP) in addition to computational methods such as Newton’s method. Input-output models (including social accounting matrices and combinations with other data) and optimization in GAMS are also introduced.

The second half of the course applies the tools of computational economics in five key areas:

  1. constructing endowment economies as MCPs (e.g., Robinson Crusoe economies, dynamics)
  2. Spatial models (e.g., Von Thunen, Jun Jie Wu, Real estate markets, and Endogenous public good provision)
  3. using MPSGE models
  4. an overview of macroeconomic models (e.g., Solow, Ramsey, Markusen examples, overlapping generation models, and weakening assumptions), and
  5. trade models (e.g., two country models, multi country models, and climate change models).