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WIREs Clim Change
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Modeling myths: On DICE and dynamic realism in integrated assessment models of climate change mitigation

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Abstract We analyze how stylized Integrated Assessment Models (IAMs), and specifically the widely‐used Dynamic Integrated Climate‐Economy model (DICE), represent the cost of emissions abatement. Many assume temporal independence—that abatement costs in one period are not affected by prior abatement. We contrast this with three dimensions of dynamic realism in emitting systems: (i) inertia, (ii) induced innovation, and (iii) path dependence. We review key evidence from the last quarter century on each of these three components. Studies of stock lifetime, dynamics of diffusion and past transitions suggest typical transition timescales of at least 20–40 years for the bulk emitting systems. The evidence that substantial innovation is induced by both prices and market deployment is unambiguous. Finally, both data and a rapidly growing literature demonstrate substantial path dependence in general, and specifically “carbon lock‐in and lock‐out.” Some stylized models in the past decade have incorporated technology learning, and others have considered inertia, but the combination of these factors is important and not yet evident. More complex hybrid IAMs with technology‐rich energy‐system models incorporate these factors, but their complexity has limited the wider understanding and influence of their underlying insights. Few if any global models fully represent path dependence. We conclude with likely implications drawing upon the empirical and modeling evidence accumulated, including results from extending DICE with a highly stylized representation of such dynamic factors. This suggests that dynamic interdependencies could multiply several‐fold the optimal level of initial abatement expenditure. This is because early abatement then also directly facilitates subsequent emission savings. The diversity of dynamic linkages across sectors and technologies also implies more nuanced policy than a single global carbon price. Thus, the issues explored in this review can radically change the general policy conclusions drawn from models, which, like DICE, neglect dynamic realism. This article is categorized under: Climate Economics > Aggregation Techniques for Impacts and Mitigation Costs
Optimal trajectory of CO2 emissions, abatement expenditure, GDP, and climate damages from DICE 2016 with three damage functions (standard, 5*standard, and Weitzman)
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DICE‐PACE result for transition time of 30 years
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Primary energy and CO2 emissions per capita plotted against per‐capita income, for the 13 richest (GDP) OECD countries
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Top‐down and bottom‐up marginal abatement cost curves (MACC)
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Cost trends in solar (a1) and wind (a2) electricity compared to cost ranges for new coal plants, (from IRENA, 2020) and (b) PV costs compared to projections
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Shape and rate of diffusion of technologies in their initial markets. (From Bento and Wilson (2016)). The graph shows rising market shares in the initial markets, from the point when each technology passed a threshold of 0.1% of its eventual maximum installed capacity in that initial (geographic) market11
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