About the Center on Social Dynamics and Policy
The Brookings Center on Social Dynamics and Policy applies complex systems science to the study of social dynamics and their implications for policy, mainly through the use of computational modeling and simulation. In a policy setting, complexity refers to situations in which responses to policy change may not be uniform or intuitive, due in part to feedback effects, time delays, interconnectedness, and non-linearity. In such situations, approaches from complex systems science can offer important advantages for the understanding of emergent social phenomena and the crafting of effective policy.
Agent-Based Modeling
A central technique used at CSDP is agent-based computational modeling (ABM). This approach uses artificial societies, constructed on computers, to study how key social dynamics may be generated “from the bottom up” and how such dynamics may respond to policy changes. Data generated in the ABM models can be directly compared to, and validated against, real-world data. This bottom-up approach often provides important insights into the causal mechanisms driving the outcomes of interest, and also provides a powerful and unique computational laboratory for policy experimentation. The computational environmental allows researchers to quickly and cost-effectively design and test a wide range of policy interventions.
Application to Policy Research
To design effective policies in an increasingly complex, interdependent world, better understanding of causal mechanisms is needed—we must understand not just what factors play a role in a given phenomena, but how and why these factors matter. Social dynamics are key drivers in the systems underlying many policy challenges--from the obesity epidemic to financial reform to ethnic conflict—and understanding such dynamics is the central focus of CSDP.
Research Agenda
The Center's research is based on the work of a number of Brookings Scholars and a broader network of external researchers.
- CSDP is part of the research network of the National Collaborative on Childhood Obesity Research (NCCOR), a joint project of the National Institutes of Health, the Centers for Disease Control, the Robert Wood Johnson Foundation, and the United States Department of Agriculture to address the problem of childhood obesity in America. CSDP Director Hammond serves on the steering committee of the network’s Computational Modeling group (CompMod).
- CSDP participates in National Institutes of Health's Models of Infectious Disease Agent Study (MIDAS), a collaboration of research and informatics groups to develop computational models of the interactions between infectious agents and their hosts, disease spread, prediction systems, and response strategies.
- CSDP Director Hammond is a member of the newly formed multidisciplinary National Institutes of Health Network on Inequality, Complexity, and Health (NICH). The network’s goal is to apply state-of-the-art conceptual and computational models to the understanding of the origins of health disparities, and to the design of policy interventions to reduce such disparities.
- CSDP research studies the important role social networks can play in both infectious and chronic public health challenges, from obesity and smoking to influenza pandemics
- CSDP has ongoing research on the determinants and dynamics of public trust—in institutional, in government, and in public health. Low trust can undermine the effectiveness of institutional reforms, of efforts to reduce corruption or conflict, and of both pharmaceutical and non-pharmaceutical public health interventions
- With collaborators from the Santa Fe Institute, CSDP researchers are exploring novel approaches to understanding the complex inter-relationship between humans and their ecosystems, and the impact different public policy may have on such dynamics
- CSDP collaborates with the Brookings Center on Children and Families to study the growth of single-parent families caused by early unwed childbearing and the decline of marriage.