This journal article is mostly over my head, but I found the introduction interesting. It talks about the use of equilibrium models most common in economics compared to emerging research into agent based models.
Complexity and the Economics of Climate Change: a Survey and a Look Forward
Mitigation and adaptation to climate change represent governance challenges of an unprecedented scale because of their long-term horizon, their global nature and the massive uncertainties they involve. Against this background, equilibrium models generally used in Integrated Assessment Models (IAM) represent the economy as a system with a unique equilibrium, climate policy as an additional constraint in the optimization problem of the social planner and consider the uncertainty of climate-related damages to be predictable enough to be factored out in the expected utility of a representative agent. There is growing concern in the literature that this picture might convey a false impression of control (seePindyck,2013; Stern, 2013, 2016; Weitzman, 2013; Revesz et al., 2014; Farmer et al., 2015, among manycontributions) and that IAMs might underestimate both the cost of climate change and the benefits resulting from the transition to a low carbon-emission economy (Stern, 2016).
Network and agent-based models have been increasingly advocated as alternatives t to handle out-of-equilibrium dynamics, tipping points and large transitions in socio-economic systems (see e.g Tesfatsion and Judd, 2006; Balbi and Giupponi, 2010; Kelly et al., 2013; Smajgl et al., 2011; Farmer et al., 2015; Stern, 2016; Mercure et al., 2016). These classes of models consider the real world as a complex evolving system, wherein the interaction of many heterogeneous agents possibly reacting across different spatial and temporal scales give rise to the emergence of aggregate properties that cannot be deduced by the simple aggregation of individual ones (Flake, 1988; Tesfatsion and Judd, 2006). The development of agent-based integrated assessment model can overcome the shortfall of equilibrium models and ease stakeholder participation and scenario exploration (Moss et al., 2001; Moss, 2002a). Indeed, the higher degree of realism of ABMs (Farmer and Foley, 2009; Farmer et al., 2015) allows to involve policy makers in the process of the development of the model employed for policy evaluation (Moss, 2002b).