Agent-based computational (ABC) modeling is a relatively new approach to research in the social sciences. In ABC modeling, societal phenomena such as the emergence of social institutions, segregation, and the spread of innovations are studied from the ‘bottom up’, by modeling the behavior and interactions of the individuals that make up society. In recent years, this approach has also been applied to a number of demographic issues, from fertility to migration to union formation dynamics, generating novel and important insights that are usually difficult to obtain with more traditional methods. Unfortunately, the spread of the approach within the discipline has been comparatively slow, given that population researchers often lack the knowledge and skills that are necessary to develop and analyze agent-based models.

The course will provide participants with the knowledge and skills that are necessary to implement ABC models. In particular, participants will:

• learn about the benefits of ABC models and the type of research questions that can be addressed with such models;
• get to know existing ABC models in population studies and other social sciences;
• learn to develop their own basic model of population dynamics with the modeling platform NetLogo;
• learn how to design and analyze systematic computational experiments.
• The course will be useful for researchers and doctoral students working or studying in the fields of demography, sociology, and related disciplines.

For more information see https://tinyurl.com/abm2019.