Editing IPCC:AR6/WGIII/Chapter-1 (section)

==== 1.7.1.3 Disequilibrium, Complex Systems and Evolutionary Approaches ====

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Other approaches to aggregate evaluation draw on various branches of intrinsically non-equilibrium theories (e.g., [[#Chang--2014|Chang 2014]] ). These including long-standing theories from the 1930s (e.g., Schumpeter 1934; [[#Keynes--1936|Keynes 1936]] ) to understand situations of structurally underemployed resources, potential financial instabilities ( [[#Minsky--1986|Minsky 1986]] ), and related economic approaches which emphasise time dimensions (e.g., recent reviews in [[#Legrand--2017|Legrand and Hagemann 2017]] ; [[#Stern--2018|Stern 2018]] ). More recently developing have been formal economic theories of endogenous growth building on, for example, [[#Romer--1986|Romer (1986)]] , and developments of Schumpeterian creative destruction ( [[#Aghion--2021|Aghion et al. 2021]] ) and evolutionary economic theories which abandon any notion of full or stable resource utilisation even as a reference concept ( [[#Nelson--1982|Nelson and Winter 1982]] ; [[#Freeman--1988|Freeman and Perez 1988]] ; [[#Carlsson--1991|Carlsson and Stankiewicz 1991]] ; Freeman and Louçã 2001; [[#Perez--2001|Perez 2001]] ).

The latter especially are technically grounded in complex system theories (e.g., [[#Arthur--1989|Arthur 1989]] , [[#Arthur--1999|1999]] ; [[#Beinhocker--2007|Beinhocker 2007]] ; [[#Hidalgo--2009|Hidalgo and Hausmann 2009]] ). These take inherently dynamic views of economies as continually evolving systems with continuously unfolding and path-dependent properties, and emphasise uncertainty in contrast to any predictable or default optimality. Such approaches have been variously applied in policy evaluation ( [[#Walton--2014|Walton 2014]] ; Moore et al. 2018), and specifically for global decarbonisation (e.g., [[#Barker--2014|]] [[#Barker--2014|Barker and Crawford-Brown 2014]] ) using global simulation models. Because these have no natural reference ‘least lost’ trajectory, they illustrate varied and divergent pathways and tend to emphasise the diversity of possibilities and relevant policies, particularly linked to innovation and potentially ‘sensitive intervention points’ ( [[#Farmer--2019|Farmer et al. 2019]] ) ( [[#1.7.3|Section 1.7.3]] ). They also illustrate that different representations of innovation and financial markets together can explain why estimated impacts of mitigation on GDP can differ very widely (potentially even in sign), between different model types (Chapter 15, [[#15.6.3|Section 15.6.3]] and Box 15.7).

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