The Model Dimensionality and Its Impacts on the Strategic and Policy Outcomes in IAMs the Findings from the RICE2020 Model

This paper studies the impacts of regional breakdowns or model dimensionality on the model’s optimal solutions. Using the United States (USA) and China (CHN) as the experimental subject, we test the various solutions related to USA and CHN, such as the Cournot-Nash equilibrium and the Lindahl equili...

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Autor principal: Yang, Zili
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer US 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9288735/
https://www.ncbi.nlm.nih.gov/pubmed/35873881
http://dx.doi.org/10.1007/s10614-022-10292-0
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author Yang, Zili
author_facet Yang, Zili
author_sort Yang, Zili
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description This paper studies the impacts of regional breakdowns or model dimensionality on the model’s optimal solutions. Using the United States (USA) and China (CHN) as the experimental subject, we test the various solutions related to USA and CHN, such as the Cournot-Nash equilibrium and the Lindahl equilibrium, in the RICE2020 model under three regional breakdowns. Their solutions’ invariance and variances across different model dimensionalities indicate that modeling dimensionality may play a role in the strategic interactions among the regions in GHG mitigation. The simulation results also point out the pitfalls of the model comparisons across IAMs for climate change.
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spelling pubmed-92887352022-07-18 The Model Dimensionality and Its Impacts on the Strategic and Policy Outcomes in IAMs the Findings from the RICE2020 Model Yang, Zili Comput Econ Article This paper studies the impacts of regional breakdowns or model dimensionality on the model’s optimal solutions. Using the United States (USA) and China (CHN) as the experimental subject, we test the various solutions related to USA and CHN, such as the Cournot-Nash equilibrium and the Lindahl equilibrium, in the RICE2020 model under three regional breakdowns. Their solutions’ invariance and variances across different model dimensionalities indicate that modeling dimensionality may play a role in the strategic interactions among the regions in GHG mitigation. The simulation results also point out the pitfalls of the model comparisons across IAMs for climate change. Springer US 2022-07-17 /pmc/articles/PMC9288735/ /pubmed/35873881 http://dx.doi.org/10.1007/s10614-022-10292-0 Text en © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.
spellingShingle Article
Yang, Zili
The Model Dimensionality and Its Impacts on the Strategic and Policy Outcomes in IAMs the Findings from the RICE2020 Model
title The Model Dimensionality and Its Impacts on the Strategic and Policy Outcomes in IAMs the Findings from the RICE2020 Model
title_full The Model Dimensionality and Its Impacts on the Strategic and Policy Outcomes in IAMs the Findings from the RICE2020 Model
title_fullStr The Model Dimensionality and Its Impacts on the Strategic and Policy Outcomes in IAMs the Findings from the RICE2020 Model
title_full_unstemmed The Model Dimensionality and Its Impacts on the Strategic and Policy Outcomes in IAMs the Findings from the RICE2020 Model
title_short The Model Dimensionality and Its Impacts on the Strategic and Policy Outcomes in IAMs the Findings from the RICE2020 Model
title_sort model dimensionality and its impacts on the strategic and policy outcomes in iams the findings from the rice2020 model
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9288735/
https://www.ncbi.nlm.nih.gov/pubmed/35873881
http://dx.doi.org/10.1007/s10614-022-10292-0
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