Saved in:
| Main Authors: | , , , , , |
|---|---|
| Format: | Preprint |
| Published: |
2024
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2411.10768 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1866908407523442688 |
|---|---|
| author | Eftekhari, Aryan Folini, Doris Friedl, Aleksandra Kübler, Felix Scheidegger, Simon Schenk, Olaf |
| author_facet | Eftekhari, Aryan Folini, Doris Friedl, Aleksandra Kübler, Felix Scheidegger, Simon Schenk, Olaf |
| contents | We introduce a framework for developing efficient and interpretable climate emulators (CEs) for economic models of climate change. The paper makes two main contributions. First, we propose a general framework for constructing carbon-cycle emulators (CCEs) for macroeconomic models. The framework is implemented as a generalized linear multi-reservoir (box) model that conserves key physical quantities and can be customized for specific applications. We consider three versions of the CCE, which we evaluate within a simple representative agent economic model: (i) a three-box setting comparable to DICE-2016, (ii) a four-box extension, and (iii) a four-box version that explicitly captures land-use change. While the three-box model reproduces benchmark results well and the fourth reservoir adds little, incorporating the impact of land-use change on the carbon storage capacity of the terrestrial biosphere substantially alters atmospheric carbon stocks, temperature trajectories, and the optimal mitigation path. Second, we investigate pattern-scaling techniques that transform global-mean temperature projections from CEs into spatially heterogeneous warming fields. We show how regional baseline climates, non-uniform warming, and the associated uncertainties propagate into economic damages. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2411_10768 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Building Interpretable Climate Emulators for Economics Eftekhari, Aryan Folini, Doris Friedl, Aleksandra Kübler, Felix Scheidegger, Simon Schenk, Olaf Econometrics Computational Engineering, Finance, and Science Machine Learning We introduce a framework for developing efficient and interpretable climate emulators (CEs) for economic models of climate change. The paper makes two main contributions. First, we propose a general framework for constructing carbon-cycle emulators (CCEs) for macroeconomic models. The framework is implemented as a generalized linear multi-reservoir (box) model that conserves key physical quantities and can be customized for specific applications. We consider three versions of the CCE, which we evaluate within a simple representative agent economic model: (i) a three-box setting comparable to DICE-2016, (ii) a four-box extension, and (iii) a four-box version that explicitly captures land-use change. While the three-box model reproduces benchmark results well and the fourth reservoir adds little, incorporating the impact of land-use change on the carbon storage capacity of the terrestrial biosphere substantially alters atmospheric carbon stocks, temperature trajectories, and the optimal mitigation path. Second, we investigate pattern-scaling techniques that transform global-mean temperature projections from CEs into spatially heterogeneous warming fields. We show how regional baseline climates, non-uniform warming, and the associated uncertainties propagate into economic damages. |
| title | Building Interpretable Climate Emulators for Economics |
| topic | Econometrics Computational Engineering, Finance, and Science Machine Learning |
| url | https://arxiv.org/abs/2411.10768 |