Abstract for: Multi-effect Evaluation of Policy Intervention in System Dynamics: A Data Envelopment Analysis Approach

This article proposes a novel methodology that integrates System Dynamics (SD) and Data Envelopment Analysis (DEA) to model and evaluate the impacts of policy interventions. SD is a useful tool for simulating the non-linear impacts of policy interventions, while DEA is an empirical method that investigates the efficiency of comparable peers based on limited resources consumed and desirable or undesirable outputs generated. However, SD lacks an explicit method for aggregating multi-faceted outcomes, and DEA does not explicitly consider the dynamic impacts of policy interventions. The proposed approach overcomes these limitations by integrating SD and DEA to provide an explicit understanding of implementation strategies and time, while mapping complex implications of policy interventions on the Pareto-Koopmans frontier. This enables a rich exploration of the policy landscape with easier interpretation for policymakers. The authors demonstrate the value of the proposed methodology through a case study based on Ghaffarzagean's work, showing that it allows for exploring a wide range of policy interventions and ranking them based on their impacts. This approach contributes to the recently growing ex-ante DEA literature and can help policymakers make more informed decisions.