The lectures will introduce students to the principles of quantitative policy analysis, namely the methods to predict and evaluate the social, economic, and environmental effects of alternative strategies to achieve public objectives. A series of individual assignments, and one group project, will give students an opportunity for students to apply those methods to a set of case studies
The objectives of this course are to develop the following key skills necessary for policy analysts: - Identifying the critical quantitative factors that are of importance to policy makers in a range of decision-making situations. - Developing conceptual models of the types of processes and relationships governing these quantitative factors, including stock-flow dynamics, feedback loops, optimization, sources and effects of uncertainty, and agent coordination problems. - Develop and program numerical models to simulate the processes and relationships, in order to identify policy problems and the effects of policy interventions. - Communicate the findings from these simulations and associated analysis in a manner that makes transparent their theoretical foundation, the level and sources of uncertainty, and ultimately their applicability to the policy problem. The course will proceed through a series of policy analysis and modeling exercises, involving real-world or hypothetical problems. The specific examples around which work will be done will concern the environment, energy, health, and natural hazards management.
Performance assessment information (valid until the course unit is held again)