When leaders face political economy constraints, is it best to delay all decarbonization initiatives until a sectorally coordinated strategy can be implemented, or is it preferable to implement an approach where sectors’ decarbonization strategies are uncoordinated? This question underscores a crucial trade-off—here coined the “timing versus allocation” trade-off—for politically constrained climate policymakers: whether to sacrifice the optimal timing of climate policies to preserve the optimal allocation of emissions across economic sectors, or to preserve the optimal timing of abatement investment at the expense of emissions allocation across sectors. This paper systematically explores this trade-off by presenting a modeling framework that elucidates the economic implications of various sub-optimal policy approaches to decarbonization that involve relaxing or delaying efforts in a subset of sectors or economy-wide. The analysis shows that the cost difference between an economy-wide, coordinated decarbonization strategy and an uncoordinated approach with heterogeneous carbon prices is smaller than the cost of delaying action and implementing a coordinated policy in the future. This finding implies that it is preferable to implement some policy in each sector, insofar as this is politically feasible, with less politically challenged sectors compensating with a marginal increase in policy ambition. Furthermore, the paper highlights that sectors with high annual emission rates, such as energy, are more costly to delay in comparison to their mid- to low-emission counterparts, such as industry, despite the latter being nominally more expensive to decarbonize.
Repository name | Type | URI |
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Reproducible Research Repository (World Bank) | https://reproducibility.worldbank.org | |
BHM-pol-econ-reprod | Github | https://github.com/adam-bauer-34/BHM-pol-econ-reprod |
Paper exhibits were reproduced on a computer with the following specifications:
• OS: Windows 10 Enterprise, version 22H2
• Processor: Intel(R) Xeon(R) Gold 6132 CPU @ 2.60GHz 2.60 GHz (2 processors)
• Memory available: 128 GB
• Software version: Python 3.11, Gitbash 2.47.0
Runtime: 3 hours
To successfully replicate this package, new users must follow these steps: a. replicating the programming environment using the file pol_econ.yml ; b. running the main run_all.sh in Git Bash.
All data sources are publicly available and included in the reproducibility package.
Author | Affiliation | |
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Adam Michael Bauer | University of Illinois Urbana-Champaign | adammb4@illinois.edu |
Stephane Hallegatte | World Bank | shallegatte@worldbank.org. |
Florent McIsaac | World Bank | fmcisaac@worldbank.org |
2024-11
Location | Code |
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World | WLD |
The materials in the reproducibility packages are distributed as they were prepared by the staff of the International Bank for Reconstruction and Development/The World Bank. The findings, interpretations, and conclusions expressed in this event do not necessarily reflect the views of the World Bank, the Executive Directors of the World Bank, or the governments they represent. The World Bank does not guarantee the accuracy of the materials included in the reproducibility package.
Name | URI |
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Modified BSD3 | https://opensource.org/license/bsd-3-clause/ |
Name | Affiliation | |
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Adam Michael Bauer | University of Illinois Urbana-Champaign | adammb4@illinois.edu |
Reproducibility WBG | World Bank | reproducibility@worldbank.org |
Name | Abbreviation | Affiliation | Role |
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Reproducibility WBG | DIME | World Bank - Development Impact Department | Verification and preparation of metadata |
2024-11-21
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