Modeling complexity: Using dynamic simulation to link regression and case studies

The success or failure of programs typically depends on how numerous variables interact over time. Individuals adjust their strategies continuously on the basis of prior events. Unintended consequences abound. And the very meaning of success or failure may change over time. Yet the studies that command the most influence in the policy community are typically based on multiple regression, a technique whose capacity to capture these complexities is sharply limited. Accordingly, findings based on regression studies and findings based on the study of individual cases commonly conflict. Dynamic simulation modeling can serve as a methodological bridge between case studies and regression-based studies of policy systems. The results of some early experiments along these lines indicate how the bridge can be fashioned.