Modeling Complex Systems for Policy Analysis

This course examines policy analysis in contexts where modeling must balance rational-analytic reasoning with the complexities of uncertain, adaptive, and value-laden systems. Students learn best practices for developing cause-effect models that incorporate diverse perspectives, conflicting assumptions, and dynamic interactions.

The course combines conceptual instruction with hands-on work using analytic, system dynamics, agent-based, qualitative, and portfolio-analysis models, exploring how these approaches inform and complement human decision exercises. By the end, students gain the skills to design and evaluate models that address the multifaceted realities of contemporary policy problems.