WITCH - A World Induced Technical Change Hybrid Model

Bosetti, Valentina; Carraro, Carlo; Galeotti, Marzio; Massetti, Emanuele; Tavoni, Massimo

doi:10.2139/ssrn.948382

Cited by 272 publications

(253 citation statements)

References 11 publications

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“…WITCH is a regional integrated assessment model designed to provide normative information on the optimal responses of world economies to climate damages and to model the channels of transmission of climate policy into the economic system (see Bosetti, Carraro, Galeotti, Massetti and Tavoni, 2006). It is a hybrid model because it combines features of both top-down and bottomup modelling: the top-down component consists of an intertemporal optimal growth model, in which the energy input of the aggregate production function has been expanded to yield a bottomup description of the energy sector.…”

Section: The Witch Modelmentioning

confidence: 99%

Optimal Energy Investment and R&D Strategies to Stabilise Greenhouse Gas Atmospheric Concentrations

et al. 2007

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. The stabilisation of GHG atmospheric concentrations at levels expected to prevent dangerous climate change has become an important, global, long-term objective. It is therefore crucial to identify a cost-effective way to achieve this objective. In this paper we use WITCH, a hybrid climate-energy-economy model, to obtain a quantitative assessment of some cost-effective strategies that stabilise CO2 concentrations at 550 or 450 ppm. In particular, this paper analyses the energy investment and R&D policies that optimally achieve these two GHG stabilisation targets (i.e. the future optimal energy mix consistent with the stabilisation of GHG atmospheric concentrations at 550 and 450 ppm). Given that the model accounts for interdependencies and spillovers across 12 regions of the world, optimal strategies are the outcome of a dynamic game through which inefficiency costs induced by global strategic interactions can be assessed. Therefore, our results are somehow different from previous analyses of GHG stabilisation policies, where a central planner or a single global economy are usually assumed. In particular, the effects of free-riding incentives in reducing emissions and in investing in R&D are taken into account. Technical change being endogenous in WITCH, this paper also provides an assessment of the implications of technological evolution in the energy sector of different stabilisation scenarios. Finally, this paper quantifies the net costs of stabilising GHG concentrations at different levels, for different allocations of permits and for different technological scenarios. In each case, the optimal long-term investment strategies for all available energy technologies are determined. The case of an unknown backstop energy technology is also analysed. Terms of use: Documents inJEL Code: H4, O3, Q4.

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Section: The Witch Modelmentioning

confidence: 99%

Optimal Energy Investment and R&D Strategies to Stabilise Greenhouse Gas Atmospheric Concentrations

et al. 2007

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“…A subset of IAMs (e.g. DICE (Nordhaus 2008), WITCH (Bosetti et al 2006), REMIND (Luderer et al 2013)) apply normative decision theory to determine (welfare) optimal decisions to avoid dangerous anthropogenic interference with the climate system, as called for by the United Nations Framework Convention on Climate Change (UNFCCC).…”

Section: Introductionmentioning

confidence: 99%

Operationalizing climate targets under learning: An application of cost-risk analysis

2014

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Cost-Effectiveness Analysis (CEA) determines climate policies that reach a given climate target at minimum welfare losses. However, when applied to temperature targets under climate sensitivity uncertainty, decision-makers might be confronted with normatively unappealing negative expected values of future climate information or even infeasible solutions. To tackle these issues, Cost-Risk Analysis (CRA), that trades-off the costs for mitigating climate change against the risk of exceeding climate targets, has been proposed as an extension of CEA under uncertainty. Here we build on this proposition and develop an axiomatically sound CRA for the context of uncertainty and future learning. The main contributions of this paper are: (i) we show, that a risk-penalty function has to be non-concave to avoid counter-intuitive preferences, (ii) we introduce a universally applicable calibration of the cost-risk trade-off, and (iii) we implement the first application of CRA to a numerical integrated assessment model. We find that for a 2°-target in combination with a 66 % compliance level, the expected value of information in 2015 vs. 2075 is between 0.15 % and 0.66 % of consumption every year, and can reduce expected mitigation costs by about one third. (iv) Finally, we find that the relative importance of the economic over the risk-related contribution increases with the target probability of compliance. Electronic supplementary material The online version of this article

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“…WITCH (World Induced Technical Change Hybrid) is a regional integrated assessment model structured to provide normative information on the optimal responses of world economies to climate damages (Bosetti et al 2006(Bosetti et al , 2009bBosetti, Massetti and Tavoni, 2007).…”

Section: Short Model Descriptionmentioning

confidence: 99%

The Optimal Climate Policy Portfolio When Knowledge Spills Across Sectors

Massetti

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2010

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This paper studies the implications for climate policy of the interactions between environmental and knowledge externalities. Using a numerical analysis performed with the hybrid integrated assessment model WITCH, extended to include mutual spillovers between the energy and the non-energy sector, we show that the combination between environmental and knowledge externalities provides a strong rationale for implementing a portfolio of policies for both emissions reduction and the internalisation of knowledge externalities. Moreover, we show that implementing technology policy as a substitute for stabilisation policy is likely to increase global emissions. JEL-Code: C72, H23, Q25, Q28, O31, O41, Q54.

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WITCH - A World Induced Technical Change Hybrid Model

Cited by 272 publications

References 11 publications

Optimal Energy Investment and R&D Strategies to Stabilise Greenhouse Gas Atmospheric Concentrations

Optimal Energy Investment and R&D Strategies to Stabilise Greenhouse Gas Atmospheric Concentrations

Operationalizing climate targets under learning: An application of cost-risk analysis

The Optimal Climate Policy Portfolio When Knowledge Spills Across Sectors

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