Computational Methods for Economic Modeling

Catalog description

Modern economics increasingly relies on computational methods to study mechanisms, simulate systems, and explore dynamic behavior. This course introduces undergraduate students to computational modeling using Artificial Intelligence (AI) and Machine Learning (ML) as an economic reasoning tool. In this course, students learn how to express economic ideas through algorithms, simulation, and computational thinking. Upon completion, students will: (1) understand how to translate economic mechanisms into algorithms; (2) build simulations of markets, dynamic systems, and stochastic processes; (3) solve microeconomic optimization problems computationally; (4) explore how economic outcomes emerge from simple rules; and (5) gain practical coding skills for modern empirical and theoretical economic work. This course is designed for students who enjoy economics and want to see economic systems in motion. It is ideal for students who appreciate structured problem-solving and want to use computational tools to explore microeconomic, macroeconomic, and social dynamics. Prereq: ECON 102 and ( OPRE 207 or ANTH 319 or SOCI 307 or STAT 201 or STAT 301 or STAT 312 ).