Purpose and organization

The purpose of this course is to introduce students of the social and policy sciences to conceptual and computational models. We start with diagrams, charts, mathematical "ballparking," and decision trees, and then consider cost-benefit analysis and discounting, and finally several classic modeling techniques (e.g., Stock & Flow, Monte Carlo, Markov, Queues, Linear Programming).


  1. The learning goals of this course include
  2. Developing an appreciation for what we mean by "model" and where this fits in the work of the social scientist or policy analyst.
  3. Developing a repertoire of models with which you are familiar enough to apply to actual problems you encounter in your work.
  4. Develop a style of thinking in which you "apply" models heuristically even if not in all their mathematical glory.
  5. Develop an informed skepticism about models based in an understanding of their assumptions, limitations, and problems.
  6. Significant increase in the technical skills used in modeling
  7. Acquisition of a mentality oriented toward contextualized utilization of tools rather than blind technocratic application of tools.


Lectures are organized pedagogically. We begin with the motivation for a given model or technique and then present an example. This is generally followed by a preliminary exposition of the conditions under which the technique is appropriate, how one carries out the technique, and a set of basic problems with solutions. Next there is a presentation of intermediate materials and problems with solutions. Chapters conclude with checklist summaries and review problems.


For the purposes of this course, we assume you have an understanding of efficiency as a concept and that you know that talking about efficiency is not an endorsement of it as an ultimate end. We assume you understand that any real situation involves both efficiency considerations and distributional considerations. We assume you have taken courses in which you have encountered the idea that inequality exists, that different groups in any society have different interests, and that politics are messy.

This Course is Not

This course is intended as a complement to others in the social science and public policy curriculum. For the most part, we will bracket the concerns raised in those courses. We will not, for example, talk about statistical inference, the resolution of conflicts via political means, how to collect or interpret qualitative or quantitative data, or the ethical questions raised by policy alternatives. We will also not explore a realm that is perhaps the prime locus of modeling in the social sciences, game theory (see

Complementary Courses

Statistics, Econometrics
Game Theory
Research Methods

See Also