The Paris Agreement established that global warming should be limited to “well below” 2 ◦C and encouraged efforts to limit warming to 1.5 ◦C. Achieving this goal presents a challenge, especially given (i) adjustment costs, which penalize a swift transition away from fossil fuels owing to, e.g., skilled labor scarcity, and (ii) climate uncertainty that complicates the link between emissions reductions and global warming. This paper presents a modeling framework that explores optimal decarbonization investment strategies with adjustment costs and climate uncertainty. The findings show that climate uncertainty impacts investment in three ways: (i) the cost of policy increases, especially when adjustment costs are present; (ii) abatement investment is front-loaded relative to a scenario without uncertainty; and (iii) the sectors with the largest changes in investment are those that are “hard-to-abate”, such as heavy industry and agriculture, each of which have high investment costs and annual emission rates. The longer learning about climate uncertainty is delayed, the more these impacts are amplified. Each of these effects can be traced back to the carbon price distribution inheriting a “heavy tail” when climate uncertainty is present. The paper highlights how climate uncertainty and adjustment costs combined lead to heightened urgency for near-term investments in decarbonization.
Repository name | Type | URI |
---|---|---|
Reproducible Research Repository (World Bank) | https://reproducibility.worldbank.org | |
BMH-delayed-learning-reprod | Github | https://github.com/adam-bauer-34/BMH-delayed-learning-reprod/ |
Paper exhibits were reproduced on a computer with the following specifications:
• OS: Windows 11 Enterprise, version 21H2
• Processor: Processor Intel(R) Core(TM) Ultra 7 165U, 2100 Mhz, 12 Core(s), 14 Logical Processor(s)
• Memory available: 32 GB
• Software version: Python 3.12, Gurobi 12.0.1
~4 hours runtime
To replicate this package, please follow these steps:
README
.Note: If you are unable to obtain or install Gurobi, the outputs produced by the replicator are included in the packages for reference.
All data sources are publicly available and included in the reproducibility package.
Author | Affiliation | |
---|---|---|
Adam Michael Bauer | University of Illinois Urbana-Champaign | adammb4@illinois.edu |
Florent McIsaac | World Bank | fmcisaac@worldbank.org |
Stéphane Hallegatte | World Bank | shallegatte@worldbank.org |
Working Paper: 2024-04; Journal Article: 2025-05
Location | Code |
---|---|
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.
2
Name | URI |
---|---|
MIT license | https://opensource.org/license/mit/ |
Name | Affiliation | |
---|---|---|
Adam Michael Bauer | University of Illinois Urbana-Champaign | adammb4@illinois.edu |
Reproducibility WBG | World Bank | reproducibility@worldbank.org |
Name | Abbreviation | Affiliation | Role |
---|---|---|---|
Reproducibility WBG | DIME | World Bank - Development Impact Department | Verification and preparation of metadata |
Working Paper: 2024-04-22; Journal Article: 2025-05-09
2