How can one evaluate the effectiveness of HIV prevention programs? How many drug treatment slots are required to provide treatment on demand? Does capital punishment deter homicide? And what do the above questions have in common? The answer to the last query is simple: these problems and more are considered in Policy Modeling. Building on earlier coursework in quantitative analysis and statistics, Policy Modeling provides an operational framework for exploring the costs and benefits of public policy decisions. The techniques employed include “back of the envelope” probabilistic models, Markov processes, queuing theory, and linear/integer programming. With an eye towards making better decisions, these techniques are applied to a number of important policy problems. In addition to lectures, assigned articles and text readings, and short problem sets, students will be responsible for completing a take-home midterm exam and a number of cases. In some instances, it will be possible to take a real problem from formulation to solution, and compare your own analysis to what actually happened. Prerequisites: A demonstrated proficiency in quantitative methods.