Applied Computational Economics

Catalog description

Economists often find themselves in situations where closed-form solutions do not exist or econometric estimation is inappropriate due to data limitations or the nature of the problem. In these cases, numerical approaches, using computer-based methods, may be an economist's best option. In this course, we will explore four topics in the field of computational economics: computable general equilibrium modeling, growth modeling, uncertainty and formal monte carlo analysis, and agent-based modeling. The overall goal of this course is to provide students with an in-depth understanding of computational economics so that they are prepared to build unique mathematical models to address complex situations that have not yet been encountered. Students should have successfully completed a graduate-level course in microeconomic theory prior to enrolling in this course.