The article "Simulating Institutional Heterogeneity in Sustainability Science" by Michael R. Davidson, Tatiana Filatova, Wei Peng, Liz Verbeek, and Fikri Kucuksayacigil explores the impact of institutional heterogeneity on sustainability outcomes. The authors compare three modeling approaches—integrated assessment modeling (IAM), engineering-economic optimization (EEO), and agent-based modeling (ABM)—to understand how institutions, both formal and informal, influence sustainability transitions. They conduct experiments on climate mitigation systems to assess the effects of specific institutional factors, such as formal policies, institutional coordination, and informal attitudes and norms. The results show that incorporating institutional details can significantly affect aggregate and distributional impacts, with more politically meaningful distributional impacts being large across various actors. The study highlights the importance of including institutional heterogeneity in sustainability models to better understand and address real-world sustainability challenges. The authors call for joint efforts between sustainability modelers and social scientists to bridge the gap between modeling, theories, and empirical evidence on social institutions, emphasizing the need for more dynamic and endogenous representations of institutional change in sustainability science models.The article "Simulating Institutional Heterogeneity in Sustainability Science" by Michael R. Davidson, Tatiana Filatova, Wei Peng, Liz Verbeek, and Fikri Kucuksayacigil explores the impact of institutional heterogeneity on sustainability outcomes. The authors compare three modeling approaches—integrated assessment modeling (IAM), engineering-economic optimization (EEO), and agent-based modeling (ABM)—to understand how institutions, both formal and informal, influence sustainability transitions. They conduct experiments on climate mitigation systems to assess the effects of specific institutional factors, such as formal policies, institutional coordination, and informal attitudes and norms. The results show that incorporating institutional details can significantly affect aggregate and distributional impacts, with more politically meaningful distributional impacts being large across various actors. The study highlights the importance of including institutional heterogeneity in sustainability models to better understand and address real-world sustainability challenges. The authors call for joint efforts between sustainability modelers and social scientists to bridge the gap between modeling, theories, and empirical evidence on social institutions, emphasizing the need for more dynamic and endogenous representations of institutional change in sustainability science models.