Assessing model equifinality for robust policy analysis in complex socio-environmental systems. (December 2020) - Williams, T.G.; Guikema, S.D.; Brown, D.G.; Agrawal, A.
Abstract: Equifinality—a situation in which multiple plausible explanations exist for a single outcome—presents a challenge for socio-environmental systems modeling. When equifinality is ignored in model calibration, subsequent policy analyses may mis-estimate the range of potential policy effects. In this paper, we present and demonstrate an approach—called DMC-RPA—for generating a set of diverse model calibrations (DMC) to enable more robust policy analysis (RPA). The optimization-based approach maximizes diversity in the model parameters and/or structural configurations to efficiently represent any equifinality in the model set. We demonstrate the approach for an agent-based model that is used to compare resilience-enhancing strategies in a smallholder farming system. Results over the set of diverse model calibrations demonstrate consistent policy effects, enabling stronger conclusions than a single model analysis. Going forward, this approach can be applied in the development of socio-environmental systems models to facilitate more robust policy analysis and inference. Graphical abstract: Image 1 Highlights: Equifinality exists when multiple plausible models explain the same calibration data. Model-based policy analyses in SES should acknowledge model equifinality. We present a model calibration approach that identifies a set of plausible models. The approach maximizes diversity in the parameters and/or structures in the model set. Our approach facilitates more robust model design and ex-ante policy analysis.