The goal of this course is to help students transition from formal training in Econometrics and Theory to practical applications. The course will cover computational methods for solving economic models numerically, programming econometric methods, and presenting empirical results. The course begins with foundational methods, including iterative techniques, numerical integration, and optimization, followed by advanced inference methods and function approximation. Applications will cover both microeconomic models, such as discrete choice and dynamic Markov decision processes, and macroeconomic models, including dynamic programming, market-clearing price determination, life cycle models, social security tax changes, and heterogeneous agent problems with aggregate uncertainty.

This course is ideal for students aiming to conduct research in applied microeconomic fields or for those interested in macroeconomic models involving strategic interactions and heterogeneous agents.