Evidence map›Paper›PMID 40953255›Full record

ArticleProceedings of the National Academy of Sciences of the United States of America2025

The power of bridging decision scales: Model coupling for advanced climate policy analysis.

Tatiana Filatova, Joos Akkerman, Francesco Bosello, Theodoros Chatzivasileiadis, Ignasi Cortés Arbués, Amineh Ghorbani, Olga Ivanova, Nina Knittel, Jan Kwakkel, Francesco Lamperti and 10 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Proceedings of the National Academy of Sciences of the United States of America, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

20 authors.

Tatiana FilatovaMulti Actor Systems Department, Faculty of Technology, Policy and Management, Delft University of Technology, Delft 2628 BX, The Netherlands.ORCID 0000-0002-3546-6930
Joos AkkermanMulti Actor Systems Department, Faculty of Technology, Policy and Management, Delft University of Technology, Delft 2628 BX, The Netherlands.
Francesco BoselloEuro-Mediterranean Center on Climate Change Foundation, Lecce 73100, Italy.ORCID 0000-0001-8492-219X
Theodoros ChatzivasileiadisMulti Actor Systems Department, Faculty of Technology, Policy and Management, Delft University of Technology, Delft 2628 BX, The Netherlands.ORCID 0000-0001-7834-8021
Ignasi Cortés ArbuésMulti Actor Systems Department, Faculty of Technology, Policy and Management, Delft University of Technology, Delft 2628 BX, The Netherlands.ORCID 0009-0007-1210-1924
Amineh GhorbaniMulti Actor Systems Department, Faculty of Technology, Policy and Management, Delft University of Technology, Delft 2628 BX, The Netherlands.
Olga IvanovaPBL Netherlands Environmental Assessment Agency, The Hague 2594 AV, The Netherlands.
Nina KnittelEconomics of Climate and Environmental Change Group, Wegener Center for Climate and Global Change, University of Graz, Graz 8010, Austria.ORCID 0000-0002-0694-3419
Jan KwakkelMulti Actor Systems Department, Faculty of Technology, Policy and Management, Delft University of Technology, Delft 2628 BX, The Netherlands.
Francesco LampertiResources for the Future and Euro-Mediterranean Center on Climate Change Foundation European Institute on Economics and the Environment, Milan 20144, Italy.
Nicholas R MaglioccaDepartment of Geography, University of Alabama, Tuscaloosa, AL 35401-0322.ORCID 0000-0002-0971-0207
Giacomo MarangoniMulti Actor Systems Department, Faculty of Technology, Policy and Management, Delft University of Technology, Delft 2628 BX, The Netherlands.ORCID 0000-0003-3994-380X
Stefan NaberneggEconomics of Climate and Environmental Change Group, Wegener Center for Climate and Global Change, University of Graz, Graz 8010, Austria.ORCID 0000-0003-3785-2103
Anton PichlerInstitute for Transport and Logistics Management, Vienna University of Economics and Business, Vienna 1020, & Complexity Science Hub Vienna, Vienna 1030, Austria.
Adrian PoujonMulti Actor Systems Department, Faculty of Technology, Policy and Management, Delft University of Technology, Delft 2628 BX, The Netherlands.ORCID 0009-0006-8821-8451
Karolina SafarzynskaDepartment of Political Economy, Faculty of Economic Sciences, University of Warsaw, Warsaw 00241, Poland.ORCID 0000-0001-5507-9287
Alessandro TabernaMulti Actor Systems Department, Faculty of Technology, Policy and Management, Delft University of Technology, Delft 2628 BX, The Netherlands.
Mariësse A E van SluisveldPBL Netherlands Environmental Assessment Agency, The Hague 2594 AV, The Netherlands.
Liz VerbeekMulti Actor Systems Department, Faculty of Technology, Policy and Management, Delft University of Technology, Delft 2628 BX, The Netherlands.ORCID 0009-0009-4158-3445
Taoyuan WeiCenter for International Climate Research, Oslo 0318, Norway.ORCID 0000-0002-6007-148X

Funding

EC | ERC | HORIZON EUROPE European Research Council (ERC) 758014Nederlandse Organisatie voor Wetenschappelijk Onderzoek (NWO) 191.015
6 · The paper itself

Abstract

Climate policy faces increasingly complex challenges that span multiple human decision scales in nature-society systems. Contemporary climate policy models, while valuable and increasingly versatile in handling spatial and temporal scales, struggle to capture interacting multiscale decisions on the socioeconomic side. This perspective draws attention to the power of coupling among different modeling families, taking integrated assessment models (IAM), computable general equilibrium models (CGE), and agent-based models (ABM) as examples. Recent computational advances, maturity of models, availability of data, and interdisciplinary expertise make model coupling an increasingly feasible, effective, and useful tool for climate policy analysis. We examine the unique contributions of each modeling approach, highlight synergies from uniting their strengths, and discuss alternatives to and conditions for coupling. In addressing methodological challenges, we present examples of effective coupling of IAM-ABM-CGE, emphasizing the importance of maintaining model integrity while enhancing policy relevance. By bridging human decision scales and leveraging complementary strengths, coupled models can provide nuanced insights into climate-economy interactions, ultimately supporting effective and equitable-not just efficient and optimal-climate policies.

Indexed as

adaptationbehaviorfinanceIAM CGE ABMmitigation

Identifiers

PMID40953255
PMCPMC12478177

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.