Combining Stochastic Optimization and Monte Carlo Simulation to Deal with Uncertainties in Climate Policy Assessment

Babonneau, Frédéric Louis François; Haurie, Alain; Loulou, Richard; Vielle, Marc

doi:10.1007/s10666-011-9275-1

Cited by 29 publications

(24 citation statements)

References 32 publications

(43 reference statements)

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“…There are different sources of uncertainties, some are linked to exogenous assumptions (like GDP growth and world energy prices), others are related to the cost of technologies that are into account (in Markal or in GEMINI-E3 (through elasticities of substitution or the nested CES functions)), finally the climate target is itself uncertain. In Haurie, Tavoni, and van der Zwaan (2011) the authors stress several recommendations to integrate uncertainties in modeling climate policies, in the case of Computable General Equilibrium models one solution is to use Monte Carlo simulations, this option for example has been applied to the GEMINI-E3 model in Babonneau et al (2011). …”

Section: Discussionmentioning

confidence: 99%

Assessment of Acceptable Swiss post-2012 Climate Policies

Sceia

Altamirano-Cabrera

Vielle

et al. 2012

Swiss J Economics Statistics

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a This work has been undertaken with the support of NSF-NCCR climate and Federal Office for the Environment grants. We are very grateful to Martin Peter, Carten Nathani and the Federal Office of Statistics for providing us with disaggregated input-output tables. We also would like to thank Jacqueline Hug, Thorsten F. Schulz, Philippe Thalmann, Hal Turton as well as the two anonymous referees for their helpful comments. Remaining errors are under the sole responsibility of the authors.

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Section: Discussionmentioning

confidence: 99%

Assessment of Acceptable Swiss post-2012 Climate Policies

Sceia

Altamirano-Cabrera

Vielle

et al. 2012

Swiss J Economics Statistics

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“…Like other CGE models they are based on literature review. The uncertainty surrounding these parameters and the impact on the results could be analysis by performing stochastic analysis, as for example in Babonneau et al (2012) and Labriet et al (2012). As regards future changes in cooling and heating, their estimation is based on a fixed threshold temperature (18 • C), reflecting the temperature usually used for HDD and CDD computation.…”

Section: Macro-economic Impact Of Changes In Both Heating and Coolingmentioning

confidence: 99%

Worldwide impacts of climate change on energy for heating and cooling

Labriet¹,

Joshi

Vielle

et al. 2013

Mitig Adapt Strateg Glob Change

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The energy sector is not only a major contributor to greenhouse gases, it is also vulnerable to climate change and will have to adapt to future climate conditions. The objective of this study is to analyze the impacts of changes in future temperatures on the heating and cooling services of buildings and the resulting energy and macro-economic effects at global and regional levels. For this purpose, the techno-economic TIAM-WORLD (TIMES Integrated Assessment Model) and the general equilibrium GEMINI-E3 (General Equilibrium Model of International-National Interactions between Economy, Energy and Environment) models are coupled with a climate model, PLASIM-ENTS (Planet-Simulator -Efficient Numerical Terrestrial Scheme). The key results are as follows. At the global level, the climate feedback induced by adaptation of the energy system to heating and cooling is found to be insignificant, partly because heating and cooling-induced changes compensate and partly because they represent a limited share of total final energy consumption. However, significant changes are observed at regional levels, more particularly in terms of additional power capacity required to satisfy additional cooling services, resulting in increases in electricity prices. In terms of macro-economic impacts, welfare gains and losses are associated more with changes in energy exports and imports than with changes in energy consumption for heating and cooling. The rebound effect appears to be non-negligible.To conclude, the coupling of models of different nature was successful and showed that the energy and economic impacts of climate change on heating and cooling remain small at the global level, but changes in energy needs will be visible at more local scale.

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“…Larger-scale models, which capture the main interrelationships between human and natural systems, have incorporated uncertainty only partially owing to computational limitations. Therefore, uncertainty is mostly treated by means of multi-model ensembles 16,17 , or by single models performing Monte Carlo simulations 18,19 . When accounting for all the key sources of uncertainty, the selection of optimal climate policy has been shown to be more sensitive to uncertainty about mitigation costs and impacts than to uncertainty about warming 20 .…”

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Selection of climate policies under the uncertainties in the Fifth Assessment Report of the IPCC

2015

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Strategies for dealing with climate change must incorporate and quantify all the relevant uncertainties, and be designed to manage the resulting risks 1 . Here we employ the best available knowledge so far, summarized by the three working groups of the Fifth Assessment Report of the Intergovernmental Panel on Climate Change (IPCC AR5; refs 2-4), to quantify the uncertainty of mitigation costs, climate change dynamics, and economic damage for alternative carbon budgets. We rank climate policies according to di erent decision-making criteria concerning uncertainty, risk aversion and intertemporal preferences. Our findings show that preferences over uncertainties are as important as the choice of the widely discussed time discount factor. Climate policies consistent with limiting warming to 2• C above preindustrial levels are compatible with a subset of decision-making criteria and some model parametrizations, but not with the commonly adopted expected utility framework.Many of the uncertainties surrounding climate change are difficult to quantify and depend on the judgement of experts and on the type of model used to generate future scenarios. Each model produces a distribution over the possible states of nature (for example, cost of mitigation, temperature increase, or economic damage from climate change), and these distributions might differ from model to model. How should we select climate policy in the face of these uncertainties? This paper addresses this question using a framework that accounts for both state uncertainty (for example, the distribution over states of nature) and model uncertainty (for example, the different models (or experts) which generate distributions over states) 5 . We investigate a variety of preferences and assumptions over these two types of uncertainty. A special case is the subjective expected utility 6 framework, traditionally used in economic evaluations. However, an expected utility setting might not work when the information is incomplete and ambiguous, which is clearly the case for climate change 7 . Moreover, people are known to approach risks and uncertainties differently 8 . The proposed setting allows us to explore additional decision-making criteria to deal with uncertainty, in the spirit of refs 7,9. Alternative statistical techniques, consistent with Bayesian approaches, have been developed to cope with model uncertainty 10 . Model weighting is an active topic in climate research 11 , where historical observations provide a basis for model evaluation, although it is not commonly used 12 . Although our framework is sufficiently flexible to accommodate different prior probability measure over the set of possible models, our baseline model assumes a uniform prior with equal model weights.The literature on the role of uncertainty in climate policy making has mostly relied on either analytical or simplified integrated assessment models (IAMs), such as DICE (ref. 13). In such contexts, different decision-making criteria and preferences over risks have been shown to have a sig...

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Combining Stochastic Optimization and Monte Carlo Simulation to Deal with Uncertainties in Climate Policy Assessment

Cited by 29 publications

References 32 publications

Assessment of Acceptable Swiss post-2012 Climate Policies

Assessment of Acceptable Swiss post-2012 Climate Policies

Worldwide impacts of climate change on energy for heating and cooling

Selection of climate policies under the uncertainties in the Fifth Assessment Report of the IPCC

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