Micro-Macro Explanations with Data Driven Agent-Based Models
Micro-Macro Explanations with Data Driven Agent-Based Models
Thursday, 10 July 2025: 13:00-14:45
Location: FSE024 (Faculty of Education Sciences (FSE))
RC45 Rational Choice (host committee) Language: English
Agent-Based Models (ABM) represent a significant advancement in the study of the micro-macro link. Theoretical models enable causal modeling of micro-level mechanisms and the analysis of their dynamic macro-consequences. With data becoming amply available in the digital age (easy access to surveys, social network data, digital trace data, registry data, etc.), we face the opportunity to enhance realism and explanatory power of ABMs through empirical calibration and validation. In sociology, however, only a few attempts have been made to integrate empirical data into ABMs so far. Moreover, there is a need for guidance and standardized procedures on how to integrate data and ABM for theoretically grounded work.
This session seeks to open the debate around how to integrate data into ABM. We invite contributions that demonstrate innovative approaches to integrating data into ABM, highlight methodological advancements, or provide case studies showcasing how empirical calibration or validation can enhance ABMs’ realism and explanatory power. The aim of this session is also to offer room for theoretical discussions about challenges and opportunities of data driven ABM. Thus, we also welcome contributions that address those challenges and solutions or establish standard procedures for empirical calibration and validation.
Session Organizers:
Oral Presentations