Complex system policy modelling approaches for policy advice – comparing systems thinking, system dynamics and agent-based modelling

Abstract

Policy assessment is often limited to the evaluation of the physical effectiveness or economic efficiency. To analyse how policies intervene in the complex reality, qualitative and quantitative complex system modelling approaches from the field of Systems Thinking (STM), System Dynamics (SDM) or Agent-based modelling (ABM) can provide valuable insights. This article aims to illuminate the opportunities and limitations of these three exploratory modelling approaches for policy assessment. It addresses stakeholders in policy advices and decision makers designing policies and gives an overview of modelling approaches to evaluate the complex and social impact of policies including side-effects and non-linear system behaviour. After a short review of policy modelling in general, we compare STM, SDM and ABM regarding their methodology, modelling process and applicability in practical policy advice. We suggest that STM as a qualitative modelling approach is applicable to foster short-term policy design processes. In contrast, SDM and ABM as a time-resolved quantitative technique enable deeper system insights but requires more effort regarding model quantification. They are ideal to analyse how policies affect long-term societal problems like sustainability transformations. Finally, we propose first measures to establish such complex system modelling approaches, which today represent only a niche in policy evaluation.

Keywords

• Policy modelling
• complex social systems
• behavioural public policy
• social simulation
• policy assessment