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

== 1.7 Four Analytic Frameworks for Understanding Mitigation Response Strategies ==

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Climate change is unprecedented in its scope (sectors, actors and countries), depth (major transformations) and time scales (over generations). As such, it creates unique challenges for analysis. It has been called ‘the greatest market failure in history’ ( [[#Stern--2007|Stern 2007]] ); the ‘perfect moral storm’ ( [[#Gardiner--2006|Gardiner 2006]] ) and a ‘super wicked problem’ ( [[#Lazarus--2009|Lazarus 2009]] ; [[#Levin--2012|Levin et al. 2012]] ) – one which appears difficult to solve through the traditional tools and assumptions of social organisation and analysis.

To complement the extensive literature on risks and decision-making under uncertainty reviewed in AR6 WGII (notably, Chapter 19), this section summarises insights and developments in key analytic frameworks and tools particularly relevant to understanding specific mitigation strategies, policies and other actions, including explaining the observed if limited progress to date. Organised partly as reflected in the quotes above, these include ''aggregated'' (principally, economic) frameworks to evaluate system-level choices; ''ethical'' perspectives on values and equity including stages of development and distributional concerns; and ''transition'' frameworks which focus on the processes and actors involved in major technological and social transitions. These need to be complemented by a fourth set of approaches which shine more light on ''psychological/behavioural and political'' factors. All these frameworks are relevant, and together they point to the multiple perspectives and actions required if the positive drivers of emission reduction summarised in Section 4 are to outweigh the barriers and overcome the constraints.

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=== 1.7.1 Aggregated Approaches: Economic Efficiency and Global Dynamics of Mitigation ===

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Some of the most established and influential approaches to understanding the ''aggregate'' causes and consequences of climate change and mitigation across societies, draw upon economic theories and modelling to generate global emission pathways in the absence of climate policies and to study alternative mitigation pathways (described in detail in [[IPCC:Wg3:Chapter:Chapter-3#3.2.5|Section 3.2.5]] , and Appendix 3). The underlying economic concepts aggregate wealth or other measures of welfare based on utilitarian ethical foundations, and in most applications, a number of additional assumptions detailed in AR5 (Chapters 2 and 3).

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<span id="cost-benefit-analysis-and-cost-effectiveness-analysis"></span>
==== 1.7.1.1 Cost-benefit Analysis and Cost-effectiveness Analysis ====

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Such global aggregate economic studies coalesce around two main questions. One, as pioneered by Nordhaus (1992, 2008) attempts to monetise overall climate damages and mitigation costs so as to strike a ‘cost-benefit optimum’ pathway. More detailed and empirically-grounded ‘cost-effectiveness analysis’ explores pathways that would minimise mitigation costs ( [[#Ekholm--2014|Ekholm 2014]] ; [[#IPCC--2014a|IPCC 2014a]] [[IPCC:Wg3:Chapter:Chapter-2#2.5|Section 2.5]] ; [[#Weyant--2017|Weyant 2017]] ) for given targets (e.g., as agreed in international negotiations, see [[IPCC:Wg3:Chapter:Chapter-3#3.2|Section 3.2]] in Chapter 3). Bothapproaches recognise that resources are limited and climate change competes with other priorities in government policymaking, and are generally examined with some form of Integrated Assessment Model (IAM) ( [[#1.5|Section 1.5]] and Appendix III). Depending on the regional disaggregation of the modelling tools used and on the scope of the analyses, these studies may or may not address distributional aspects within and across nations associated with climate policies ( [[#Bauer--2020|Bauer et al. 2020]] ).

For at least 10 to 15 years after the first computed global cost-benefit estimate ( [[#Nordhaus--1992|Nordhaus 1992]] ), the dominant conclusions from these different approaches seemed to yield very different recommendations, with cost-benefit studies suggesting lenient mitigation compared to the climate targets typically recommended from scientific risk assessments ( [[#Weyant--2017|Weyant 2017]] ). Over the past 10 to 15 years, literature has made important strides towards reconciling these two approaches, both in the analytic methods and the conclusions arising.

'''Damages and risks.''' Incorporating impacts which may be extremely severe but are uncertain (known as ‘fat tails’ ( [[#Weitzman--2009|Weitzman 2009]] , 2011)), strengthens the economic case for ambitious action to avoid risks of extreme climate impacts ( [[#Ackerman--2010|Ackerman et al. 2010]] ; [[#Fankhauser--2013|Fankhauser et al. 2013]] ; [[#Dietz--2015|Dietz and]] [[#Stern--2015|Stern 2015]] ). The salience of risks has also been amplified by improved understanding of climate ‘tipping points’ ( [[#Lontzek--2015|Lontzek et al. 2015]] ; [[#Lenton--2019|Lenton et al. 2019]] ); valuations should reflect that cutting emissions reduces not only average expected damages, but also the risk of catastrophic events ( [[#IWG--2021|IWG 2021]] ).

'''Discounting.''' The role of time discounting in weighting future climate change impacts against today’s costs of mitigating emissions has been long recognised ( [[#Weitzman--1994|Weitzman 1994]] , 2001; [[#Nordhaus--2007|Nordhaus 2007]] ; [[#Stern--2007|Stern 2007]] ; [[#Dasgupta--2008|Dasgupta 2008]] ). Its importance is underlined in analytical Integrated Assessment Models (IAMs) ( [[#Golosov--2014|Golosov et al. 2014]] ; [[#van%20den%20Bijgaart--2016|van den Bijgaart et al. 2016]] ; [[#van%20der%20Ploeg--2019|van der Ploeg and Rezai 2019]] ) (Annex III). Economic literature suggests applying risk-free, public, and long-term interest rates when evaluating overall climate strategy ( [[#Weitzman--2001|Weitzman 2001]] ; [[#Dasgupta--2008|Dasgupta 2008]] ; [[#Arrow--2013|Arrow et al. 2013]] ; [[#Groom--2017|Groom and Hepburn 2017]] ). Expert elicitations indicate values around 2% (majority) to 3% ( [[#Drupp--2018|Drupp et al. 2018]] ). This is lower than in many of the studies reviewed in earlier IPCC assessments, and many IAM studies since, and by increasing the weight accorded to the future would increase current ‘optimal effort’. The US Interagency Working Group on the Social Cost of Carbon used 3% as its central value ( [[#IAWG--2016|IAWG 2016]] ; [[#Li--2018|Li and Pizer 2018]] ; [[#Adler--2017|Adler et al. 2017]] ). Individual projects may require specific risk adjustments.

'''Distribution of impacts.''' The economic damages from climate change at the nationally aggregated and sub-national level are very diverse ( [[#Moore--2017|Moore et al. 2017]] ; [[#Ricke--2018|Ricke et al. 2018]] ; [[#Carleton--2020|Carleton et al. 2020]] ). A ‘global damage function’ necessarily implies aggregating impacts across people and countries with different levels of income, and over generations, a process which obscures the strategic considerations that drive climate policymaking ( [[#Keohane--2016|Keohane and Oppenheimer 2016]] ). Economics acknowledges there is no single, objectively defined ‘social welfare function’ ( [[#IPCC--1995|IPCC 1995]] , 2014a). This applies also to the distribution of responses: both underline the relevance of equity (next section) and global negotiations to determine national and collective objectives.

Obvious limitations arise from these multiple difficulties in assessing an objective, globally acceptable single estimate of climate change damages (e.g., [[#Arrow--2013|Arrow et al. 2013]] ; [[#Pindyck--2013|Pindyck 2013]] ; [[#Auffhammer--2018|Auffhammer 2018]] ; [[#Stern--2021|Stern et al. 2021]] ), with some arguing that agreement on a specific value can never be expected ( [[#Rosen--2015|Rosen and Guenther 2015]] ; [[#Pezzey--2018|Pezzey 2018]] ). A new generation of cost-benefits analysis, based on projections of actual observed damages, results in stronger mitigation efforts as optimal ( [[#Glanemann--2020|Glanemann et al. 2020]] ; [[#Hänsel--2020|Hänsel et al. 2020]] ). Overall, the combination of improved damage functions with the wider consensus on low discount rates (as well as lower mitigation costs due to innovation) has increasingly yielded ‘optimal’ results from benefit-cost studies in line with the range established in the Paris Agreement (Cross-Working Group Box 1 in Chapter 3).

'''Hybrid cost-benefit approaches''' that extend the objective of the optimisation beyond traditional welfare, adding some form of temperature targets as in [[#Llavador--2015|Llavador et al. (2015)]] and [[#Held--2019|Held (2019)]] also represent a step in bridging the gap between the two approaches and result in proposed strategies much more in line with those coming from the cost-effectiveness literature. Approaching from the opposite side, cost-effectiveness studies have looked into incorporating benefits from avoided climate damages, to improve the assessment of net costs ( [[#Drouet--2021|Drouet et al. 2021]] ).

Cost-benefit IAMs utilise damage functions to derive a social cost of CO 2 emissions’ (SCC – the additional cost to society of a pulse of CO 2 emissions). One review considered that ‘the best estimate’ of the optimal (near-term) level ‘still ranges from a few tens to a few hundreds of dollars per ton of carbon’ ( [[#Tol--2018|Tol 2018]] ), with various recent studies in the hundreds, taking account of risks (Taconet et al. 2019), learning ( [[#Ekholm--2018|Ekholm 2018]] ) and distribution ( [[#Ricke--2018|Ricke et al. 2018]] ). In addition to the importance of uncertainty/risk, aggregation, and realistic damage functions as noted, on which some progress has been made, some reviews additionally critique how IAMs represent abatement costs in terms of energy efficiency and innovation (e.g., [[#Farmer--2015|Farmer et al. 2015]] ; [[#Rosen--2015|Rosen and Guenther 2015]] ; [[#Keen--2021|Keen 2021]] ) (Sections 1.7.3 and 1.7.4). IAMs may better reflect associated ‘rebound’ at system level ( [[#Saunders--2021|Saunders et al. 2021]] ), and inefficient implementation would raise mitigation costs ( [[#Homma--2019|Homma et al. 2019]] ); conversely, ''co-benefits'' – most extensively estimated for air quality, valued at a few tens of USD per tCO 2 -eq across 16 studies ( [[#Karlsson--2020|Karlsson et al. 2020]] ) – complement global with additional local benefits (Table 1.2).

Whereas many of these factors affect primarily cost-benefit evaluation, discounting also determines the cost-effective trajectory: [[#Emmerling--2019|Emmerling et al. (2019)]] find that, for a remaining budget of 1000 GtCO 2 , reducing the discount rate from 5% to 2% would more than double current efforts, limit ‘overshoot’, greatly reduce a late rush to negative emissions, and improve intergenerational justice by more evenly distributing policy costs across the 21st century.

'''Table 1.2 | Potential for net co-benefits arising from synergies and trade-offs, opportuni''' '''ties and risks.'''

{| class="wikitable"
|-
!
! '''Positives'''

! '''Negatives'''

|-
| Broadly known (e.g., air pollution, distributional).

| Synergies

| Trade-offs

|-
| Deep uncertainties (e.g., radical innovations).

| Opportunities

| Risks

|-
|
|-
|
| Select options with maximum synergies, and foster and exploit opportunities.

| Ameliorate trade-offs (e.g., revenue redistribution), and minimise or allocate risks appropriately.

|-
| rowspan="2"|
| colspan="2"|
|-
| colspan="2"| '''Net co-benefits from appropriate mit''' '''igation choices'''

|}

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==== 1.7.1.2 Dynamic Efficiency and Uncertainty ====

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Care is required to clarify what is optimised ( [[#Dietz--2019|Dietz and Venmans 2019]] ). Optimising a path towards a given temperature goal ''by a fixed date'' (e.g., 2100) gives time-inconsistent results backloaded to large, last-minute investment in carbon dioxide removal (CDR). ‘Cost-effective’ optimisations generate less initial effort than ''equivalent'' cost-benefit models ( [[#Dietz--2019|Dietz and Venmans 2019]] ; [[#Gollier--2021|Gollier 2021]] ) as they do not incorporate benefits of reducing impacts earlier.

‘Efficient pathways’ are affected by inertia and innovation. Inertia implies amplifying action on long-lived investments and infrastructure that could otherwise lock-in emissions for many decades ( [[#Vogt-Schilb--2018|Vogt-Schilb et al. 2018]] ; [[#Baldwin--2020|Baldwin et al. 2020]] ). [[IPCC:Wg3:Chapter:Chapter-3|Chapter 3]] ( [[IPCC:Wg3:Chapter:Chapter-3#3.5|Section 3.5]] ) discusses interactions between near-, medium- and long-term actions in global pathways, particularly vis-à-vis inertia. Also, to the extent that early action induces low-carbon innovation, it ‘multiplies’ the optimal effort (for given damage assumptions), because it facilitates subsequent cheaper abatement. For example, a ‘learning-by-doing’ analysis concludes that early deployment of expensive PV was of net global economic benefit, due to induced innovation ( [[#Newbery--2018|Newbery 2018]] ).

Research thus increasingly emphasises the need to understand climate transformation in terms of dynamic, rather than static, efficiency ( [[#Gillingham--2018|Gillingham and Stock 2018]] ). This means taking account of inertia, learning and various additional sources of ‘path-dependence’. Including induced innovation in stylised IAMs can radically change the outlook ( [[#Acemoglu--2012|Acemoglu et al. 2012]] , 2016), albeit with limitations ( [[#Pottier--2014|Pottier et al. 2014]] ); many more detailed-process IAMs now do include endogenous technical change (as reviewed in [[#Yang--2018|Yang et al. 2018]] and [[#Grubb--2021b|Grubb et al. 2021b]] ) (Annex III).

These dynamic and uncertainty effects typically justify greater upfront effort ( [[#Kalkuhl--2012|Kalkuhl et al. 2012]] ; [[#Bertram--2015|Bertram et al. 2015]] ), including accelerated international diffusion ( [[#Schultes--2018|Schultes et al. 2018]] ), and strengthen optimal initial effort in cost-benefit models ( [[#Baldwin--2020|Baldwin et al. 2020]] ; [[#Grubb--2021b|Grubb et al. 2021b]] ). Approaches to risk premia common in finance would similarly amplify the initial mitigation effort, declining as uncertainties reduce ( [[#Daniel--2019|Daniel et al. 2019]] ).

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==== 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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=== 1.7.2 Ethical Approaches ===

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Gardiner’s (2011) book on climate change as ‘The Perfect Moral Storm’ identified three ‘tempests’. Its ''global'' dimension, in a world of sovereign states which have only fragmentary responsibility and control, makes it ‘difficult to generate the moral consideration and necessary political will’. Its impacts are ''intergenerational'' but future generations have no voice in contemporary affairs, the usual mechanism for addressing distributional injustices, amplified by the intrinsic inequity of wealthy big emitters impacting particularly poorer victims. He argues that these are exacerbated by a third, ''theoretical'' failure to acknowledge a central need for ‘moral sensitivity, compassion, transnational and transgenerational care, and other forms of ethical concern to rise to the surface’ to help guide effective climate action. As noted in [[#1.4.6|Section 1.4.6]] , however, equity and ethics are both a driver of and constraint on mitigation.

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==== 1.7.2.1 Ethics and Values ====

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A large body of literature examines the critical role of values, ethics, attitudes, and behaviours as foundational frames for understanding and assessing climate action, sustainable development and societal transformation ( [[#IPCC--2014a|IPCC 2014a]] Chapter 3). Most of this work is offered as a counterpoint or critique to mainstream literature’s focus on the safeguarding of economic growth of nations, corporations and individuals ( [[#Castree--2017|Castree 2017]] ; [[#Gunster--2017|Gunster 2017]] ). These perspectives highlight the dominance of economic utilitarianism in western philosophical thought as a key driver for unsustainable consumption and global environmental change ( [[#Hoeing--2015|Hoeing et al. 2015]] ; Popescu 2016).

Entrenching alternative values that promote deep decarbonisation, environmental conservation and protection across all levels of society is then viewed as foundational component of climate-resilient and sustainable development and for achieving human rights, and a safe climate world ( [[#Evensen--2015|Evensen 2015]] ; [[#Jolly--2015|Jolly et al. 2015]] ; Popescu 2016; Tàbara et al. 2019). The UN Human Rights Office of the High Commissioner has highlighted the potentially crucial role of human rights in relation to climate change (UNHCR 2018). While acknowledging the role of policy, technology, and finance, the ‘managerialist’ approaches, that emphasise ‘technical governance’ and fail to challenge the deeper values that underpin society, may not secure the deep change required to avert dangerous climate change and other environmental challenges ( [[#Hartzell-Nichols--2014|Hartzell-Nichols 2014]] ; [[#Steinberger--2020|Steinberger et al. 2020]] ).

Social justice perspectives emphasise the distribution of responsibilities, rights, and mutual obligations between nations in navigating societal transformations (Gawel and Kuhlicke 2017; [[#Leach--2018|Leach et al. 2018]] ; [[#Patterson--2018|Patterson et al. 2018]] ). Current approaches to climate action may fail to match what is required by science because they tend to circumvent constraints on human behaviour, especially constraints on economic interest and activity. Related literature explores governance models that are centred on environmental limits, planetary boundaries and the moral imperative to prioritise the poor in earth systems governance ( [[#Carley--2020|Carley and Konisky 2020]] ; [[#Kashwan--2020|Kashwan et al. 2020]] ), with emphasis on trust and solidarity as foundations for global cooperation on climate change ( [[#Jolly--2015|Jolly et al. 2015]] ). A key obstacle is that the economic interests of states tend to be stronger than the drivers for urgent climate action ( [[#Bain--2017|Bain 2017]] ).

Short-term interests of stakeholders are acknowledged to impede the reflection and deliberation needed for climate mitigation and adaptation planning ( [[#Hackmann--2016|Hackmann 2016]] ; [[#Sussman--2016|Sussman et al. 2016]] ; [[#Schlosberg--2017|Schlosberg et al. 2017]] ; [[#Herrick--2018|Herrick 2018]] ). Situationally appropriate mitigation and adaptation policies at both national and international level may require more ethical self-reflection ( [[#Herrick--2018|Herrick 2018]] ), including self-transcendent values such as universalism and benevolence, and moderation which are positively related to pro-environmental behaviours ( [[#Jonsson--2014|Jonsson and Nilsson 2014]] ; [[#Katz-Gerro--2015|Katz-Gerro et al. 2015]] ; [[#Braito--2017|Braito et al. 2017]] ; [[#Howell--2017|Howell and Allen 2017]] ).

Another strong theme in the literature concerns recognition of interdependence including the intimate relationship between humans and the non-human world ( [[#Hannis--2016|Hannis 2016]] ; [[#Gupta--2018|Gupta and Racherla 2018]] ; [[#Howell--2017|Howell and Allen 2017]] ), with such ecological interdependence offered as an organising principle for enduring transformation to sustainability. A key policy implication of this is moving away from valuing nature only in market and monetary terms to strongly incorporating existential and non-material value of nature in natural-resource accounting ( [[#Neuteleers--2015|Neuteleers and Engelen 2015]] ; [[#Shackleton--2017|Shackleton et al. 2017]] ; [[#Himes-Cornell--2018|Himes-Cornell et al. 2018]] ). There has been increasing attention on ways to design climate policy frameworks to help reconcile ecological virtue (with its emphasis on the collective) with individual freedoms and personal autonomy ( [[#Kasperbauer--2016|Kasperbauer 2016]] ; [[#Nash--2017|Nash et al. 2017]] ; [[#Xiang--2019|Xiang et al. 2019]] ). In such a framework, moderation, fairness, and stewardship are all understood and promoted as directly contributing to the ‘good life’. Such approaches are deemed vital to counteract tendencies to ‘free ride’, and to achieve behavioural changes often associated with tackling climate change ( [[IPCC:Wg3:Chapter:Chapter-5#5.2.1|Section 5.2.1]] ).

Some literature suggests that attention to emotions, especially with regards to climate communication, could help societies and individuals act in ways that focus less on monetary gain and more on climate and environmental sustainability ( [[#Bryck--2016|Bryck and Ellis 2016]] ; [[#Chapman--2017|Chapman et al. 2017]] ; [[#Nabi--2018|Nabi et al. 2018]] ; [[#Zummo--2020|Zummo et al. 2020]] ).

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==== 1.7.2.2 Equity and Representation: International Public Choice Across Time and Space ====

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Equity perspectives highlight three asymmetries relevant for climate change ( [[#Okereke--2016|Okereke and Coventry 2016]] ; [[#Okereke--2017|Okereke 2017]] ) ( [[#1.4.6|Section 1.4.6]] ). ''Asymmetry in contribution'' highlights different contributions to climate change both in historical and current terms, and applies both within and between states as well as between generations ( [[#Caney--2016|Caney 2016]] ; [[#Heyward--2016|Heyward and Roser 2016]] ). ''Asymmetry in impacts'' highlights the fact that the damages will be borne disproportionately across countries, regions, communities, individuals and gender; moreover, it is often those that have contributed the least that stand to bear the greatest impact of climate change ( [[#IPCC--2014a|IPCC 2014a]] ; [[#Shi--2016|Shi et al. 2016]] ). ''Asymmetry in capacity'' highlights differences of power between groups and nations to participate in climate decision and governance, including the capacity to implement mitigation and adaptation measures.

If attention is not paid to equity, efforts designed to tackle climate change may end up exacerbating inequities among communities and between countries ( [[#Heffron--2018|Heffron and McCauley 2018]] ). The implication is that to be sustainable in the long run, mitigation involves a central place for consideration of justice, both within and between countries (Chapters 4 and 14). Arguments that the injustices following from climate change are symptomatic of a more fundamental structural injustice in social relations, are taken to imply a need to address the deeper inequities within societies ( [[#Routledge--2018|Routledge et al. 2018]] ).

Climate change and climate policies affect countries and people differently, with the poor likely to be more affected ( [[#1.6.1|Section 1.6.1]] ). Ideas of Just Transitions (outlined in [[#1.8.2|Section 1.8.2]] .) often have a national focus in the literature, but also imply that mitigation should not increase the asymmetries between rich and poor countries, implying a desire for transitions which seek to reduce (or at least avoid adverse) distributional affects. Thus, it comes into play in the timing of zero emissions (Chapters 3 and 14). International climate finance in which rich countries finance mitigation and adaptation in poor countries is also essential for reducing the asymmetries between rich and poor countries ( [[#1.6.3|Section 1.6.3]] and Chapter 15).

Equity across generations – the distribution between the present and future generations – also matters. One aspect is discounting ( [[#1.7.1|Section 1.7.1]] ). Another approach has been to study the burdens on each generation following from the transition to low-carbon economies ( [[#IPCC--2014a|IPCC 2014a]] Chapter 3) (Cross-Working Group Box 3 in Chapter 12). Suggestions include shifting more investments into ‘natural capital’, so that future generations will inherit less physical capital but a better environment, or financing mitigation efforts today using governmental debt redeemed by future generations ( [[#Heijdra--2006|Heijdra et al. 2006]] ; [[#Broome--2012|Broome 2012]] ; [[#Karp--2014|Karp and Rezai 2014]] ; [[#Hoel--2019|Hoel et al. 2019]] ).

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=== 1.7.3 Transition and Transformation Processes ===

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This report uses the term ''transition'' as the process, and ''transformation'' as the overall change or outcome, of large-scale shifts in technological, economic and social systems, called socio-technical systems in the innovation literature. Typically, new technologies, ideas and associated systems initially grow slowly in absolute terms, but may then ‘take-off’ in a phase of exponential growth as they emerge from a position of niche into mainstream diffusion, as indicated by the ‘S-curve’ growth in Figure 1.7 (lower panel). These dynamics arise from interactions between innovation (in technologies, companies and other organisations), markets, infrastructure and institutions, at multiple levels ( [[#Geels--2017|Geels et al. 2017]] ; [[#Kramer--2018|Kramer 2018]] ). Consequently, interdisciplinary perspectives are needed ( [[#Turnheim--2015|Turnheim et al. 2015]] ; [[#Geels--2016|Geels et al. 2016]] ; [[#Hof--2020|Hof et al. 2020]] ). Beyond aggregated economic perspectives on dynamics ( [[#1.7.1.2|Section 1.7.1.2]] ), these emphasise the multiple actors and processes involved.

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[[File:f69e9c211dc11199272b865435374c00 IPCC_AR6_WGIII_Figure_1_7.png]]

'''Figure 1.7 | Transition dynamics: levels, policies and processes.''' Note: the lower panel illustrates growth of innovative technologies or practices, which if successful emerge from niches into an S-shape dynamic of exponential growth. The diffusion stage often involves new infrastructure and reconfiguration of existing market and regulatory structures (known in the literature as the ‘socio-technical regime’). During the phase of more widespread diffusion, growth levels off to linear, then slows as the industry and market matures. The processes displace incumbent technologies/practices which decline, initially slowly but then at an accelerating pace. Many related literatures identify three main levels with different characteristics, most generally termed micro, meso and macro. Transitions can be accelerated by policies appropriately targeted, which may be similarly grouped and sequenced (upper panel) in terms of three corresponding pillars of policy ( [[#1.7.3|Section 1.7.3]] ): generally all are relevant, but their relative importance differs according to the stage of the transition.

''Technological Innovation Systems (TIS)'' frameworks ( [[#16.4|Section 16.4]] ) focus on processes and policies of early innovation and ‘emergence’, which combine experimentation and commercialisation, involving ''Strategic Niche Management'' ( [[#Rip--1998|Rip and Kemp 1998]] ; [[#Geels--2006|Geels and Raven 2006]] ) ''.'' Literatures on the wider processes of transition highlight different stages (e.g., Cross-Chapter Box 12 in Chapter 16) and scales across three main levels, most generally termed ''micro, meso and macro'' ( [[#Rotmans--2001|Rotmans et al. 2001]] ).

The widely-used ''Multi-Level Perspective'' or MLP ( [[#Geels--2002|Geels 2002]] ) identifies the meso level as the established ‘socio-technical (ST) regime’, a set of interrelated sub-systems which define rules and regulatory structures around existing technologies and practices. The micro level is an ecosystem of varied niche alternatives, and overlaying the ST regime is a macro ‘landscape’ level. Transitions often start with niche alternatives ( [[#Grin--2010|Grin et al. 2010]] ; [[#Köhler--2019|Köhler et al. 2019]] ), which may break through to wider diffusion (second stage in Figure 1.8), especially if external landscape developments ‘create pressures on the regime that lead to cracks, tensions and windows of opportunity’ ( [[#Rotmans--2001|Rotmans et al. 2001]] ; [[#Geels--2010|Geels 2010]] ); an example is climate change putting sustained pressure on current regimes of energy production and consumption ( [[#Kuzemko--2016|Kuzemko et al. 2016]] ). There are continual interactions between landscape, regime and niches, with varied implications for ''Transition Management'' ( [[#Rotmans--2001|Rotmans et al. 2001]] ; [[#Loorbach--2010|Loorbach 2010]] ).

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[[File:03716b46e132d8dba442aa1f8d13fe38 IPCC_AR6_WGIII_Figure_1_8.png]]

'''Figure 1.8 | Feasibility and related dimensions''' '''of assessment.'''

In contrast to standard economic metrics of marginal or smooth change (e.g., elasticities), transition theories emphasise interdisciplinary approaches and the non-linear dynamics, social, economic and environmental aspects of transitions to sustainability ( [[#Cherp--2018|Cherp et al. 2018]] ; Köhler et al. 2018). This may explain persistent tendencies to underestimate the exponential pace of change now being observed in renewable electricity (Chapters 2 and 6) and emerging in mobility (Chapter 10).

Recent decades have seen parallel broadening of economic perspectives and theories. Building also on the New Institutional Economics literatures, Building on the New Institutional Economics literature ( [[#Williamson--2000|Williamson 2000]] ), Grubb et al. (2014, 2015) classify these into three ‘domains of economic decision-making’ associated with different branches of economic theory, respectively (i) ''behavioural and organisational'' ; (ii) ''neoclassical and welfare'' ; and (iii) ''evolutionary and institutional'' . Like MLP, these are related to different social and temporal scales, as applied also in studying the ‘adaptive finance’ in UK electricity transition ( [[#Hall--2017|Hall et al. 2017]] ). There are significant differences but these approaches all point to understanding the characteristics of different actors, notably, individuals/local actors; larger corporate organisations (public or private); and (mainly) public authorities, each with different decision-making characteristics.

Sustainability may require purposeful actions at the different levels to foster the growth of sustainable technologies and practices, including support for niche alternatives ( [[#Grin--2010|Grin et al. 2010]] ). The middle level (established ‘socio-technical regime’) tends to resist major change, reforms generally involve pressures from the other two levels. Thus, transitions can be accelerated by policies appropriately targeting relevant actors at the different levels ( [[#Köhler--2019|Köhler et al. 2019]] ), the foundations for ‘three pillars of policy’ ( [[#Grubb--2014|Grubb et al. 2014]] ), which logically evolve in the course of transition (Figure 2.6a). Incumbent industries have to adapt if they are to thrive within the growth of new systems. Policy may need to balance existing socio-technical systems with strategic investment and institutional development of the emerging niches (e.g., the maintenance of energy provision and energy security with the development of renewables), and help manage declining industries ( [[#Koasidis--2020|Koasidis et al. 2020]] ).

There is usually a social dimension to such transitions. Key elements include capacity to transform ( [[#Folke--2010|Folke et al. 2010]] ), planning, and interdisciplinarity ( [[#Woiwode--2013|Woiwode 2013]] ). The Second World War demonstrated the extent to which crises can motivate (sometimes positive) change across complex social and technical systems, including industry, and agriculture which then doubled its productivity over 15 years ( [[#Roberts--2019b|Roberts and Geels 2019b]] ). In practice, climate change may involve a combination of (reactive) transformational adaptation, and (proactive) societal transformation ( [[#Feola--2015|Feola 2015]] ), the latter seen as reorientation (including values and norms) in a sustainable direction ( [[IPCC:Wg3:Chapter:Chapter-5#5.4|Section 5.4]] ), including, for example, ‘democratisation’ in energy systems ( [[#Sorman--2020|Sorman et al. 2020]] ). Business change management principles could be relevant to support positive social change ( [[#Stephan--2016|Stephan et al. 2016]] ). Overall, effective transitions rest on appropriate enabling conditions, which can also link socio-technical transitions to broader development pathways (Cross-Chapter Box 12 in Chapter 16).

Transition theories tend to come from very different disciplines and approaches compared to either economics or other social sciences, with less quantification, notwithstanding evolutionary and complex system models ( [[#1.7.1.3|Section 1.7.1.3]] ). However, a few distinct types of quantitative models of ‘socio-technical energy transition’ ( [[#Li--2015|Li et al. 2015]] ) have emerged. For policy evaluation, transitions can be viewed as processes in which dynamic efficiency ( [[#1.7.2|Section 1.7.2]] ) dominates over static allocative efficiency, with potential ‘positive intervention points’ ( [[#Farmer--2019|Farmer et al. 2019]] ). Given inherent uncertainties, there are obvious risks (e.g., [[#Alic--2016|Alic and Sarewitz 2016]] ). All this may make an evaluation framework of ''risks and opportunities'' more appropriate than traditional cost-benefit ( [[#Mercure--2021|Mercure et al. 2021]] ), and (drawing on lessons from renewables and electric vehicles) create foundations for sector-based international ‘positive sum cooperation’ in climate mitigation ( [[#Sharpe--2021|Sharpe and Lenton 2021]] ).

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=== 1.7.4 Approaches From Psychology and Politics of Changing Course ===

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The continued increase in global emissions to 2019, despite three decades of scientific warnings of ever-greater clarity and urgency, motivates growing attention in the literature to the psychological ‘faults of our rationality’ ( [[#Bryck--2016|Bryck and Ellis 2016]] ), and the political nature of climate mitigation.

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==== 1.7.4.1 Psychological and Behavioural Dimensions ====

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The AR5 emphasised that decision processes often include both deliberate (‘calculate the costs and beneﬁts’) and intuitive thinking, the latter utilising emotion- and rule-based responses that are conditioned by personal past experience, social context, and cultural factors (e.g., [[#Kahneman--2003|Kahneman 2003]] ), and that laypersons tend to judge risks differently than experts – for example, ‘intuitive’ reactions are often characterised by biases to the status quo and aversion to perceived risks and ambiguity ( [[#Kahneman--1979|Kahneman and Tversky 1979]] ). Many of these features of human reasoning create ‘psychological distance’ from climate change ( [[#Spence--2012|Spence et al. 2012]] ; [[#Marshall--2014|Marshall 2014]] ). These can impede adequate personal responses, in addition to the collective nature of the problem, where such problems can take the form of ‘uncomfortable knowledge’, neglected and so becoming ‘unknown knowns’ ( [[#Sarewitz--2020|Sarewitz 2020]] ). These decision processes, and the perceptions that shape them, have been studied through different lenses from psychology ( [[#Weber--2016|Weber 2016]] ) to sociology ( [[#Guilbeault--2018|Guilbeault et al. 2018]] ), and media studies ( [[#Boykoff--2011|Boykoff 2011]] ). [[#Karlsson--2020|Karlsson and Gilek (2020)]] identify science denialism and ‘decision thresholds’ as key mechanisms of delay.

Experimental economics ( [[#Allcott--2011|Allcott 2011]] ) also helps explain why cost-effective energy efficiency measures or other mitigation technologies are not taken up as fast or as widely as the benefits might suggest, including procrastination and inattention, as ‘we often resist actions with clear long-term benefits if they are unpleasant in the short run’ ( [[#Allcott--2010|Allcott and Mullainathan 2010]] ). Incorporating behavioural and social dynamics in models is required particularly to better represent the demand side ( [[#Nikas--2020|Nikas et al. 2020]] ), for example, [[#Safarzyńska--2018|Safarzyńska (2018)]] demonstrates how behavioural factors change responses to carbon pricing relative to other instruments. A key perspective is to eschew ‘either/or’ between economic and behavioural frameworks, as the greatest effects often involve combining behavioural dimensions (e.g., norms, social influence networks, convenience and quality assurance) with financial incentives and information ( [[#Stern--2010|Stern et al. 2010]] ). Randomised, controlled field trials can help predict the effects of behavioural interventions ( [[#Levitt--2009|Levitt and List 2009]] ; [[#McRae--2016|McRae and Meeks 2016]] ; [[#Gillan--2017|Gillan 2017]] ). [[IPCC:Wg3:Chapter:Chapter-5|Chapter 5]] explores both positive and negative dimensions of behaivour in more depth, including the development of norms and interactions with the wider social context, with emphasis upon the services associated with human well-being, rather than the economic activities per se.

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==== 1.7.4.2 Socio-political and Institutional Approaches ====

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Political and institutional dynamics shape climate change responses in important ways, not least because incumbent actors have frequently blocked climate policy ( [[#1.4.5|Section 1.4.5]] ). Institutional perspectives probe networks of opposition ( [[#Brulle--2019|Brulle 2019]] ) and emphasise that their ability to block – as well as the ability of others to foster low-carbon transitions – are structured by specific institutional forms across countries ( [[#Lamb--2020|Lamb and Minx 2020]] ). National institutions have widely been developed to promote traditionally fossil fuel-based sectors like electricity and transport as key to economic development, contributing to carbon lock-in ( [[#Seto--2016|Seto et al. 2016]] ) and inertia ( [[#Rosenschöld--2014|Rosenschöld et al. 2014]] ).

The influence of interest groups on policymaking varies across countries. Comparative political economy approaches tend to find that countries where interests are closely coordinated by governments (‘coordinated market economies’) have been able to generate transformative change more than those with a more arms-length, even combative relationship between interest groups and governments (‘liberal market economies’) ( [[#Lachapelle--2013|Lachapelle and Paterson 2013]] ; [[#Ćetković--2016|Ćetković and Buzogány 2016]] ; [[#Zou--2016|Zou et al. 2016]] ; [[#Meckling--2018|Meckling 2018]] ). ‘Developmental states’ often have the capacity for strong intervention but any low-carbon interventions may be overwhelmed by other pressures and very rapid economic growth ( [[#Wood--2020a|Wood et al. 2020a]] ).

Institutional features affecting climate policy include levels and types of democracy ( [[#Povitkina--2018|Povitkina 2018]] ), electoral systems, or levels of institutional centralisation (federal vs unitary states, presidential vs parliamentary systems) ( [[#Lachapelle--2013|Lachapelle and Paterson 2013]] ; [[#Steurer--2018|Steurer and Clar 2018]] ; [[#Clulow--2019|Clulow 2019]] ). Countries that have constructed an overarching architecture of climate governance institutions (e.g., cross-department and multi-level coordination, and semi-autonomous climate agencies), are more able to develop the strategic approaches to climate governance needed to foster transformative change ( [[#Dubash--2021|Dubash 2021]] ).

Access of non-governmental organisations (NGOs) to policy processes enables new ideas to be adopted, but too close an NGO-government relation may stifle innovation and transformative action ( [[#Dryzek--2003|Dryzek et al. 2003]] ). NGO campaigns on fracking ( [[#Neville--2019|Neville et al. 2019]] ) or divestment ( [[#Mangat--2018|Mangat et al. 2018]] ) have raised attention to ideas such as ‘stranded assets’ in policy arenas ( [[#Green--2018|Green 2018]] ; [[#Piggot--2018|Piggot 2018]] ; Newell et al. 2020; [[#Paterson--2021|Paterson 2021]] ). Attempts to depoliticise climate change may narrow the space for democratic participation and contestation, thus impacting policy responses ( [[#Swyngedouw--2010|Swyngedouw 2010]] , 2011; [[#Kenis--2014|Kenis and Lievens 2014]] ). Some institutional innovations have more directly targeted enhanced public deliberation and participation, notably in citizens’ climate assemblies ( [[#Howarth--2020|Howarth et al. 2020]] ) and in the use of legal institutions to litigate against those opposing climate action (Peel and Osofksy 2020). This literature shows that transformative pathways are possible within a variety of institutional settings, although institutional innovation will be necessary everywhere to pursue zero carbon transitions ( [[IPCC:Wg3:Chapter:Chapter-4#4.4|Section 4.4]] , [https://www.ipcc.ch/report/ar6/wg3/chapter/chapter-13 Chapter 13] and Cross-Chapter Box 12).

Balancing the forces outlined in [[IPCC:Wg3:Chapter:Chapter-4#4.6|Section 4.6]] in [[IPCC:Wg3:Chapter:Chapter-4|Chapter 4]] typically involves building coalitions of actors who benefit economically from climate policy ( [[#Levin--2012|Levin et al. 2012]] ). Policy stability is critical to enabling long-term investments in decarbonisation ( [[#Rietig--2017|Rietig and Laing 2017]] ; [[#Rosenbloom--2018|Rosenbloom et al. 2018]] ). Policy design can encourage coalitions to form that sustain momentum by supporting further policy development to accelerate decarbonisation ( [[#Roberts--2018|Roberts et al. 2018]] ), for example, by generating concentrated benefits to coalition members ( [[#Bernstein--2018|Bernstein and Hoffmann 2018]] ; [[#Meckling--2019|Meckling 2019]] ; [[#Millar--2020|Millar et al. 2020]] ), as with renewable feed-in tariffs (FiTs) in Germany ( [[#Michaelowa--2018|Michaelowa et al. 2018]] ). Coalitions may also be sustained by overarching framings, especially to involve actors (e.g., NGOs) for whom the benefits of climate policy are not narrowly economic. However, policy design can also provoke coalitions to oppose climate policy, as in the FiT programme in Ontario ( [[#Stokes--2013|Stokes 2013]] ; [[#Raymond--2020|Raymond 2020]] ) or the yellow vest protests against carbon taxation in France ( [[#Berry--2019|Berry and Laurent 2019]] ). The Just Transitions frame can thus also be understood in terms of coalition-building, as well as ethics, as the pursuit of low-carbon transitions which spread the economic benefits broadly, through ‘green jobs’, and the redistributive policies embedded in them both nationally and globally ( [[#Healy--2017|Healy and Barry 2017]] ; [[#Winkler--2020|Winkler 2020]] ). Appropriate policy design will be different at different stages of the transition process ( [[#Meckling--2017|Meckling et al. 2017]] ; [[#Breetz--2018|Breetz et al. 2018]] ).

'''Integration.''' Politics is ultimately the way in which societies make decisions – which in turn, reflect diverse forces and assumed frameworks. Effective policy requires understandings which combine economic efficiency, ethics and equity, the dynamics and processes of large-scale transitions, and the role of psychology and politics. No one framework is adequate to such a broad-ranging goal, nor are single tools. [https://www.ipcc.ch/report/ar6/wg3/chapter/chapter-13 Chapter 13] (Figure 13.6) presents a ‘framing’ table for policy instruments depending on the extent to which they focus on mitigation per se or wider socio-economic development, and whether they aim to shift marginal incentives or drive larger transitions. Holistic analysis needs to bridge modelling, qualitative transition theories illuminated by case studies, and practice-based action research ( [[#Geels--2016|Geels et al. 2016]] ).

These analytic frameworks also point to arenas of potential synergies and trade-offs (when broadly known), and opportunities and risks (when uncertainties are greater), associated with mitigation. This offers theoretical foundations for mitigation strategies which can also generate co-benefits. Climate policy may help to motivate policies with beneficial synergies (such as the consumer cost savings from energy efficiency, better forest management, transitions to cleaner vehicles) and opportunities (such as stimulating innovation), by focusing on options for which the positives outweigh the negatives, or can be made to be, through smart policy (e.g., [[#Karlsson--2020|Karlsson et al. 2020]] ). More broadly, climate concerns may help to attract international investment, and help overcoming bureaucratic or political obstacles to better policy, and support synergies between mitigation, adaptation, and other SDGs, a foundation for shifting development pathways towards sustainability ( [https://www.ipcc.ch/report/ar6/wg3/chapter/chapter-17 Chapter 17] and [[#1.6.1|Section 1.6.1]] ).

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