FN Clarivate Analytics Web of Science
VR 1.0
PT J
AU Wieners, C
   Lamperti, F
   Dosi, G
   Roventini, A
AF Wieners, Claudia
   Lamperti, Francesco
   Dosi, Giovanni
   Roventini, Andrea
TI Policies for rapid decarbonization with steady economic transition and
   employment creation
SO NATURE SUSTAINABILITY
LA English
DT Article
ID CLIMATE-CHANGE; ENERGY; IMPACT; COST
AB A large number of countries have by now pledged to undertake policies aimed at reducing greenhouse gas emissions and achieving carbon neutrality. However, evidence for a suitable policy package to induce an effective and orderly transition is scarce. Recent studies suggest that abrupt and aggressive climate policies may trigger significant transition risks, potentially leading to macroeconomic imbalances. Here we extend a macro-financial agent-based integrated assessment model grounded in evolutionary economics and complex systems science to test a variety of policy packages aimed at rapidly decarbonizing the global economy and study how they affect job creation and economic stability. We show that carbon taxation alone is self-defeating: its role at internalizing environmental costs while triggering rapid decarbonization finds little support. However, an ensemble of industrial regulations and public subsidies coupled with a mild carbon tax is the most promising policy toolkit to support a rapid and orderly transition. Such a policy mix can be designed to have a neutral impact on public finances and to boost job creation during the transition process. Carbon taxation serves primarily as a tool for raising public revenues to support government spending, rather than as a direct driver of rapid decarbonization.
C1 [Wieners, Claudia] Univ Utrecht, Inst Marine & Atmospher Res, Utrecht, Netherlands.
   [Wieners, Claudia] Univ Utrecht, Ctr Complex Syst Studies, Utrecht, Netherlands.
   [Lamperti, Francesco; Dosi, Giovanni; Roventini, Andrea] St Anna Sch Adv Studies, Inst Econ & EMbeDS, Pisa, Italy.
   [Lamperti, Francesco] CMCC Fdn, Euro Mediterranean Ctr Climate Change, Milan, Italy.
   [Lamperti, Francesco] RFF CMCC European Inst Econ & Environm, Milan, Italy.
   [Roventini, Andrea] OFCE Sci Po, Nice, France.
C3 Utrecht University; Utrecht University; Scuola Superiore Sant'Anna;
   Centro Euro-Mediterraneo sui Cambiamenti Climatici (CMCC)
RP Lamperti, F (corresponding author), St Anna Sch Adv Studies, Inst Econ & EMbeDS, Pisa, Italy.; Lamperti, F (corresponding author), CMCC Fdn, Euro Mediterranean Ctr Climate Change, Milan, Italy.; Lamperti, F (corresponding author), RFF CMCC European Inst Econ & Environm, Milan, Italy.
EM f.lamperti@santannapisa.it
RI Wieners, Claudia/IWL-8792-2023; ROVENTINI, Andrea/N-4699-2019
OI Wieners, Claudia/0000-0002-9033-1238; ROVENTINI,
   Andrea/0000-0001-5518-3084; Lamperti, Francesco/0000-0003-4862-646X
FU Economics of Energy Innovation and System Transition (EEIST) Project -
   (United Kingdom Department for Business, Energy and Industrial
   Strategy); European Union (ERC); FIND [101117427, CEF 2023]
FX F.L. and A.R. acknowledge financial support by the Economics of Energy
   Innovation and System Transition (EEIST) Project (funded by United
   Kingdom Department for Business, Energy and Industrial Strategy) and of
   the ECLIPTIC 2022 PRIN project. F.L. acknowledges funding from the
   European Union (ERC, FIND, grant no. 101117427). Views and opinions
   expressed are, however, those of the author(s) only and do not
   necessarily reflect those of the European Union or the European Research
   Council Executive Agency. Neither the European Union nor the granting
   authority can be held responsible for them. We thank R. Buizza, G.
   Pallante and all the participants to FMM 2021, WEHIA 2022, ABM4Policy
   2022, CEF 2023, the Workshop on Macroeconomic Challenges of the Green
   Transition II (Pisa) and the seminar at Queen Mary University of London
   (2025) for helpful comments and suggestions. Any errors remain the sole
   responsibility of the authors.
CR Acemoglu D, 2012, AM ECON REV, V102, P131, DOI 10.1257/aer.102.1.131
   Ackerman F., 2004, PRICELESS KNOWING PR
   [Anonymous], 2018, MANUFACTURING ENERGY
   [Anonymous], 2023, CLIM SCEN CENTR BANK
   [Anonymous], 2021, SCEN ACT PROGR REP G
   [Anonymous], 2022, ACH NET ZER HEAV IND
   [Anonymous], 2018, MISS POSS REACH NET
   Balint T, 2017, ECOL ECON, V138, P252, DOI 10.1016/j.ecolecon.2017.03.032
   Burke M, 2015, NATURE, V527, P235, DOI 10.1038/nature15725
   Campiglio E, 2022, REV ENV ECON POLICY, V16, P173, DOI 10.1086/721016
   Carney M., 2015, BREAK TRAG HOR CLIM
   Cimoli M., 2009, IND POLICY DEV POLIT
   Cozzi L., 2023, TRIPLING RENEWABLE P
   Dawid H, 2018, HANDB COMPUT ECON, V4, P63, DOI 10.1016/bs.hescom.2018.02.006
   DOSI G, 1988, J ECON LIT, V26, P1120
   Dosi G, 2019, J EVOL ECON, V29, P1, DOI 10.1007/s00191-019-00609-y
   Dosi G, 2015, J ECON DYN CONTROL, V52, P166, DOI 10.1016/j.jedc.2014.11.014
   Dosi G, 2012, HBK ECON, V1, P51, DOI 10.1016/S0169-7218(10)01003-8
   Dosi G, 2010, J ECON DYN CONTROL, V34, P1748, DOI 10.1016/j.jedc.2010.06.018
   Energy Technology Perspectives, 2023, TECHN REP
   Fagiolo G., 2019, COMPUTER SIMULATION
   Farmer JD, 2009, NATURE, V460, P685, DOI 10.1038/460685a
   Fischer C, 2008, J ENVIRON ECON MANAG, V55, P142, DOI 10.1016/j.jeem.2007.11.001
   Golosov M, 2014, ECONOMETRICA, V82, P41, DOI 10.3982/ECTA10217
   Goulder LH, 2008, REV ENV ECON POLICY, V2, P152, DOI 10.1093/reep/ren005
   Gross DP, 2023, AM ECON REV, V113, P3323, DOI 10.1257/aer.20221365
   Gunningham N, 2011, J ENVIRON LAW, V23, P169, DOI 10.1093/jel/eqr006
   Hausfather Z, 2020, NATURE, V577, P618, DOI 10.1038/d41586-020-00177-3
   Hepburn C, 2020, EUR ECON REV, V127, DOI 10.1016/j.euroecorev.2020.103440
   Jacoby HD, 2017, CLIM POLICY, V17, P873, DOI 10.1080/14693062.2017.1357528
   Juhasz R., 2023, NEW EC IND POLICY
   Kanzig D. R., 2021, PREPRINT
   Lackner T, 2025, J ECON BEHAV ORGAN, V229, DOI 10.1016/j.jebo.2024.106816
   Lamperti F, 2020, TECHNOL FORECAST SOC, V153, DOI 10.1016/j.techfore.2019.119806
   Lamperti F, 2018, ECOL ECON, V150, P315, DOI [10.2139/ssrn.2944328, 10.1016/j.ecolecon.2018.03.023]
   Lamperti F., 2019, VIERTELJAHRSHEFTE WI, V88, P73, DOI [10.3790/vjh.88.2.73, DOI 10.3790/VJH.88.2.73]
   Lamperti F, 2019, NAT CLIM CHANGE, V9, P829, DOI 10.1038/s41558-019-0607-5
   Lamperti F, 2020, MACROECON DYN, V24, P1861, DOI 10.1017/S1365100518001001
   Martinoli M, 2024, J ECON BEHAV ORGAN, V228, DOI 10.1016/j.jebo.2024.106786
   Mazzucato M, 2018, TECHNOL FORECAST SOC, V127, P8, DOI 10.1016/j.techfore.2017.05.021
   Mercure JF, 2021, GLOBAL ENVIRON CHANG, V70, DOI 10.1016/j.gloenvcha.2021.102359
   Mercure JF, 2018, ENERGY STRATEG REV, V20, P195, DOI 10.1016/j.esr.2018.03.003
   Mercure JF, 2016, GLOBAL ENVIRON CHANG, V37, P102, DOI 10.1016/j.gloenvcha.2016.02.003
   Metcalf GE, 2020, AEA PAP P, V110, P101, DOI 10.1257/pandp.20201081
   Monasterolo I, 2019, ECOL ECON, V163, P177, DOI 10.1016/j.ecolecon.2019.05.012
   Nelson R., 1982, EVOL THEOR
   NORDHAUS WD, 1992, SCIENCE, V258, P1315, DOI 10.1126/science.258.5086.1315
   Nordhaus WD, 2017, P NATL ACAD SCI USA, V114, P1518, DOI 10.1073/pnas.1609244114
   Patt A, 2018, JOULE, V2, P2494, DOI 10.1016/j.joule.2018.11.018
   Peñasco C, 2021, NAT CLIM CHANGE, V11, DOI 10.1038/s41558-020-00971-x
   Portner H.-O., 2022, CLIMATE CHANGE 2022
   Reissl S, 2025, ECOL ECON, V236, DOI 10.1016/j.ecolecon.2025.108641
   Rodrik D, 2014, OXFORD REV ECON POL, V30, P469, DOI 10.1093/oxrep/gru025
   Rosenbloom D, 2020, P NATL ACAD SCI USA, V117, P8664, DOI 10.1073/pnas.2004093117
   Schmidt TS, 2012, ENVIRON INNOV SOC TR, V2, P23, DOI 10.1016/j.eist.2011.12.002
   Shukla P. R., 2023, CLIMATE CHANGE 2022
   Soete L., 2012, EC IND INNOVATION
   Stechemesser A, 2024, SCIENCE, V385, P884, DOI 10.1126/science.adl6547
   Stern N., 2021, 28472 NBER
   Stern N, 2023, IND CORP CHANGE, V32, P277, DOI 10.1093/icc/dtad008
   Stern N, 2022, J ECON METHODOL, V29, P181, DOI 10.1080/1350178X.2022.2040740
   Stiglitz JE, 2019, EUR ECON REV, V119, P594, DOI 10.1016/j.euroecorev.2019.05.007
   Stokes L. C., 2020, SHORT CIRCUITING POL
   Tesfatsion L, 2006, HANDB ECON, V13, P831
   Timilsina GR, 2022, J ECON LIT, V60, P1456, DOI 10.1257/jel.20211560
   van den Bergh J, 2021, CLIM POLICY, V21, P745, DOI 10.1080/14693062.2021.1907276
   van Vuuren DP, 2017, GLOBAL ENVIRON CHANG, V42, P148, DOI [10.1016/j.gloenvcha.2016.10.009, 10.1016/j.gloenvcha.2016.05.009]
   Vogt-Schilb A, 2018, J ENVIRON ECON MANAG, V88, P210, DOI 10.1016/j.jeem.2017.12.001
   Way R, 2022, JOULE, V6, P2057, DOI 10.1016/j.joule.2022.08.009
NR 69
TC 3
Z9 3
U1 32
U2 34
PU NATURE PORTFOLIO
PI BERLIN
PA HEIDELBERGER PLATZ 3, BERLIN, 14197, GERMANY
SN 2398-9629
J9 NAT SUSTAIN
JI Nat. Sustain.
PD JAN
PY 2026
VL 9
IS 1
DI 10.1038/s41893-025-01683-w
EA NOV 2025
PG 17
WC Green & Sustainable Science & Technology; Environmental Sciences;
   Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Science & Technology - Other Topics; Environmental Sciences & Ecology
GA CS1ZZ
UT WOS:001624766000001
DA 2026-06-13
ER

PT J
AU Reissl, S
   Fierro, LE
   Lamperti, F
   Roventini, A
AF Reissl, Severin
   Fierro, Luca E.
   Lamperti, Francesco
   Roventini, Andrea
TI The DSK stock-flow consistent agent-based integrated assessment model
SO ECOLOGICAL ECONOMICS
LA English
DT Article
DE Climate change; Agent-based models; Integrated assessment
ID CLIMATE-CHANGE; FINANCIAL ACCELERATOR; CUMULATIVE CARBON;
   FISCAL-POLICIES; CREDIT; ECONOMICS; FRAGILITY; DYNAMICS; IMPACT; FLIGHT
AB We present an updated, stock-flow consistent version of the 'Dystopian Schumpeter meeting Keynes' agent-based integrated assessment model. By embedding the model in a fully specified accounting system, all balance sheet items and financial flows can be explicitly and consistently tracked throughout a simulation. This allows for improved analysis of climate change and climate policy scenarios in terms of their systemic implications for agent and sector-level balance sheet dynamics and financial stability. We provide an extensive description of the updated model, representing the most detailed outline of a model from the well-established 'Keynes + Schumpeter' family available to date. Following a discussion of calibration and validation, we present a range of example scenarios.
C1 [Reissl, Severin; Lamperti, Francesco] CMCC Fdn, Euro Mediterranean Ctr Climate Change, Lecce, Italy.
   [Reissl, Severin; Lamperti, Francesco] RFF CMCC European Inst Econ & Environm, Milan, Italy.
   [Fierro, Luca E.] Scuola Super Sant Anna, Inst Econ, Pisa, Italy.
   [Fierro, Luca E.] Int Inst Appl Syst Anal, Laxenburg, Austria.
   [Lamperti, Francesco; Roventini, Andrea] Scuola Super Sant Anna, Inst Econ & EMbeDS, Pisa, Italy.
C3 Centro Euro-Mediterraneo sui Cambiamenti Climatici (CMCC); Scuola
   Superiore Sant'Anna; International Institute for Applied Systems
   Analysis (IIASA); Scuola Superiore Sant'Anna
RP Lamperti, F (corresponding author), Scuola Super Sant Anna, Inst Econ & EMbeDS, Pisa, Italy.
EM francesco.lamperti@santannapisa.it
RI ROVENTINI, Andrea/N-4699-2019; FIERRO, LUCA EDUARDO/HZJ-2091-2023
OI ROVENTINI, Andrea/0000-0001-5518-3084; FIERRO, LUCA
   EDUARDO/0000-0002-4378-1375; Reissl, Severin/0000-0002-5614-5669;
   Lamperti, Francesco/0000-0003-4862-646X
FU European Union [101081604]; Bezos Earth Fund [G-2023-201305840];
   European Union (ERC) [101117427];  [101022622];  [870245]; European
   Research Council (ERC) [101117427] Funding Source: European Research
   Council (ERC)
FX S.R. received funding from the European Union's Horizon 2020 research
   and innovation programme under grant agreement No. 101022622 (ECEMF) and
   the Marie Sklodowska-Curie grant agreement No. 870245 (GEOCEP) , the
   European Union's Horizon Europe research and innovation programme under
   grant agreement No. 101081604 (PRISMA) , as well as the Bezos Earth Fund
   under grant ID G-2023-201305840-Navigating Fiscal Challenges of the
   Clean Energy Transition. F.L. acknowledges funding from the European
   Union (ERC, FIND, 101117427). Views and opinions expressed are however
   those of the author (s) only and do not necessarily reflect those of the
   European Union or the European Research Council Executive Agency.
   Neither the European Union nor the granting authority can be held
   responsible for them. The authors would like to thank Elise Kremer,
   Massimo Tavoni, Johannes Emmerling, Laurent Drouet, Gianluca Pallante
   and conference participants at CEF 2023 (Nice) and FMM 2023 (Berlin) for
   helpful comments and suggestions. The usual disclaimer applies.
CR Assenza T, 2015, J ECON DYN CONTROL, V50, P5, DOI 10.1016/j.jedc.2014.07.001
   Balint T, 2017, ECOL ECON, V138, P252, DOI 10.1016/j.ecolecon.2017.03.032
   Bartelsman E, 2005, IND CORP CHANGE, V14, P365, DOI 10.1093/icc/dth057
   Bazzana D, 2024, ENERG ECON, V134, DOI 10.1016/j.eneco.2024.107585
   Bernanke B, 1996, REV ECON STAT, V78, P1, DOI 10.2307/2109844
   Bosetti V, 2006, ENERG J, P13
   Bovari E, 2020, CLIM POLICY, V20, P179, DOI 10.1080/14693062.2019.1698406
   Bovari E, 2018, ECOL ECON, V147, P383, DOI 10.1016/j.ecolecon.2018.01.034
   Burgess S., 2016, Bank Engl. Staff. Work. Pap. No. 614
   Burke M, 2015, NATURE, V527, P235, DOI 10.1038/nature15725
   Byers Edward, 2022, Zenodo
   Caiani A, 2019, J EVOL ECON, V29, P177, DOI 10.1007/s00191-018-0554-8
   Caiani A, 2016, J ECON DYN CONTROL, V69, P375, DOI 10.1016/j.jedc.2016.06.001
   Carnevali E, 2024, REV POLIT ECON, V36, P844, DOI 10.1080/09538259.2023.2217776
   Ciola E, 2023, J ECON DYN CONTROL, V146, DOI 10.1016/j.jedc.2022.104589
   Dafermos Y, 2018, ECOL ECON, V152, P219, DOI 10.1016/j.ecolecon.2018.05.011
   Dafermos Y, 2017, ECOL ECON, V131, P191, DOI 10.1016/j.ecolecon.2016.08.013
   Dawid H., 2016, ISIGrowth Work
   Dawid H, 2018, HANDB COMPUT ECON, V4, P63, DOI 10.1016/bs.hescom.2018.02.006
   Delli Gatti D., 2023, CESifo Work
   Di Benedetto A., 2024, Technical Report
   Dosi G, 2017, J ECON DYN CONTROL, V81, P162, DOI 10.1016/j.jedc.2017.02.005
   DOSI G, 1988, J ECON LIT, V26, P1120
   Dosi G, 2020, ECON INQ, V58, P1487, DOI 10.1111/ecin.12897
   Dosi G, 2019, J EVOL ECON, V29, P1, DOI 10.1007/s00191-019-00609-y
   Dosi G, 2017, J EVOL ECON, V27, P63, DOI 10.1007/s00191-016-0466-4
   Dosi G, 2015, J ECON DYN CONTROL, V52, P166, DOI 10.1016/j.jedc.2014.11.014
   Dosi G, 2013, J ECON DYN CONTROL, V37, P1598, DOI 10.1016/j.jedc.2012.11.008
   Dosi G, 2010, J ECON DYN CONTROL, V34, P1748, DOI 10.1016/j.jedc.2010.06.018
   Ennis H.M., 2001, Economic Quarterly-Federal Reserve Bank of Richmond, V87, P1
   Fagiolo G., 2019, Computer Simulation Validation, P763, DOI [10.1007/978-3-319-70766-2_31, DOI 10.1007/978-3-319-70766-2_31]
   Fagiolo G, 2017, JASSS-J ARTIF SOC S, V20, DOI 10.18564/jasss.3280
   Farmer JD, 2015, ENVIRON RESOUR ECON, V62, P329, DOI 10.1007/s10640-015-9965-2
   Fierro L., 2024, PREPRINT, DOI [10.21203/rs.3.rs-5111841/v1, DOI 10.21203/RS.3.RS-5111841/V1]
   Galanis G, 2025, ECOL ECON, V227, DOI 10.1016/j.ecolecon.2024.108370
   Gatti DD, 2005, J ECON BEHAV ORGAN, V56, P489, DOI 10.1016/j.jebo.2003.10.012
   Gatti DD, 2022, IND CORP CHANGE, V31, P410, DOI 10.1093/icc/dtac002
   Gatti DD, 2010, J ECON DYN CONTROL, V34, P1627, DOI 10.1016/j.jedc.2010.06.019
   Godley W, 2007, MONETARY ECONOMICS: AN INTEGRATED APPROACH TO CREDIT, MONEY, INCOME, PRODUCTION AND WEALTH, P1, DOI 10.1057/9780230626546
   Haldane AG, 2019, J EVOL ECON, V29, P39, DOI 10.1007/s00191-018-0557-5
   Hamilton JD, 2018, REV ECON STAT, V100, P831, DOI 10.1162/rest_a_00706
   Jackson T, 2020, ECOL ECON, V177, DOI 10.1016/j.ecolecon.2020.106787
   Jacques P, 2023, ECOL ECON, V209, DOI 10.1016/j.ecolecon.2023.107832
   Kanzig D. R., 2023, WORKING PAPER NO 312, DOI DOI 10.3386/W31221
   KATZ RW, 1992, CLIMATIC CHANGE, V21, P289, DOI 10.1007/BF00139728
   Lackner T., 2024, Graz Schumpeter Cent. Discuss. Pap, V31
   Lamperti F, 2020, TECHNOL FORECAST SOC, V153, DOI 10.1016/j.techfore.2019.119806
   Lamperti F, 2018, ECOL ECON, V150, P315, DOI [10.2139/ssrn.2944328, 10.1016/j.ecolecon.2018.03.023]
   Lamperti F., 2024, PREPRINT
   Lamperti F, 2022, EUR J ECON ECON POLI, V19, P357, DOI 10.4337/ejeep.2022.0096
   Lamperti F, 2021, J FINANC STABIL, V54, DOI 10.1016/j.jfs.2021.100875
   Lamperti F, 2019, NAT CLIM CHANGE, V9, P829, DOI 10.1038/s41558-019-0607-5
   Lamperti F, 2019, REG ENVIRON CHANGE, V19, P747, DOI 10.1007/s10113-018-1287-9
   Leimbach M, 2010, ENERG J, V31, P109
   Matthews HD, 2012, PHILOS T R SOC A, V370, P4365, DOI 10.1098/rsta.2012.0064
   Matthews HD, 2009, NATURE, V459, P829, DOI 10.1038/nature08047
   Mercure JF, 2018, ENERGY STRATEG REV, V20, P195, DOI 10.1016/j.esr.2018.03.003
   Monasterolo I, 2019, ENERG POLICY, V124, P355, DOI 10.1016/j.enpol.2018.08.051
   Monasterolo I, 2018, ECOL ECON, V144, P228, DOI 10.1016/j.ecolecon.2017.07.029
   Naumann-Woleske K, 2023, Arxiv, DOI arXiv:2301.08135
   Nelson R.R., 2009, An evolutionary theory of economic change
   Nikiforos M, 2017, J ECON SURV, V31, P1204, DOI 10.1111/joes.12221
   Pallante G., 2024, J. Financ. Stab. Forthcom
   Pedrosa I, 2021, J EVOL ECON, V31, P1221, DOI 10.1007/s00191-021-00745-4
   Poledna S, 2023, EUR ECON REV, V151, DOI 10.1016/j.euroecorev.2022.104306
   Ponta L, 2018, ECOL ECON, V145, P274, DOI 10.1016/j.ecolecon.2017.08.022
   Raberto M, 2012, ECONOMICS-KIEL, V6, DOI 10.5018/economics-ejournal.ja.2012-27
   Reissl S, 2020, J ECON BEHAV ORGAN, V177, P109, DOI 10.1016/j.jebo.2020.06.012
   Riccetti L, 2013, J ECON DYN CONTROL, V37, P1626, DOI 10.1016/j.jedc.2013.02.008
   Rogelj J, 2018, P93, DOI [10.1017/9781009157940.004, DOI 10.1017/9781009157940.004]
   Russo A, 2016, J EVOL ECON, V26, P25, DOI 10.1007/s00191-015-0410-z
   Sanders M, 2022, ENVIRON RES LETT, V17, DOI 10.1088/1748-9326/ac7f48
   Savin I, 2023, WIRES CLIM CHANGE, V14, DOI 10.1002/wcc.811
   Schuler Yves S., 2018, Deutsche Bundesbank Discussion Paper No. 03/2018, DOI [10.2139/ssrn.3127430, DOI 10.2139/SSRN.3127430]
   Sensfuss F, 2008, ENERG POLICY, V36, P3086, DOI 10.1016/j.enpol.2008.03.035
   Sterman JD, 2013, ENVIRON MODELL SOFTW, V44, P122, DOI 10.1016/j.envsoft.2012.06.004
   Stern N, 2022, J ECON METHODOL, V29, P181, DOI 10.1080/1350178X.2022.2040740
   STIGLITZ JE, 1981, AM ECON REV, V71, P393
   Taylor J.B., 1993, Carnegie-Rochester conference series on public policy, V39, P195, DOI [10.1016/0167-2231(93)90009-L, DOI 10.1016/0167-2231(93)90009-L, 10.1016/0167-2231(93)90009-l]
   van Vuuren DP, 2017, GLOBAL ENVIRON CHANG, V42, P148, DOI [10.1016/j.gloenvcha.2016.10.009, 10.1016/j.gloenvcha.2016.05.009]
   Zezza F, 2023, ROUTL FRONT POLIT EC, P113, DOI 10.4324/9781003253457-10
NR 81
TC 8
Z9 8
U1 2
U2 8
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0921-8009
EI 1873-6106
J9 ECOL ECON
JI Ecol. Econ.
PD OCT
PY 2025
VL 236
AR 108641
DI 10.1016/j.ecolecon.2025.108641
EA MAY 2025
PG 23
WC Ecology; Economics; Environmental Sciences; Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Business & Economics
GA 3DZ7F
UT WOS:001498083600004
OA Green Accepted, hybrid
DA 2026-06-13
ER

PT J
AU Popoyan, L
   Sapio, A
AF Popoyan, Lilit
   Sapio, Alessandro
TI Prevention first vs. cap-and-trade policies in an
   agent-based integrated assessment model with GHG emissions permits
SO JOURNAL OF EVOLUTIONARY ECONOMICS
LA English
DT Article
DE Climate change; Environmental permits; Emissions trading system;
   Polluter pays principle; Agent-based models; Macro-economic dynamics;
   C63; Q40; Q50; Q54
ID COUPLED CLIMATE; CARBON-CYCLE; GRANGER CAUSALITY; ENERGY EFFICIENCY;
   BUSINESS CYCLES; OUTPUT GROWTH; CO2; POWER; PRODUCTIVITY; RECESSION
AB In this work, we ask whether tradable emissions permits, based on the cap-and-trade principle, provide better climate change and economic projections than alternative regulations for GHG emissions, such as operational permits, which are commonly used to mitigate non-GHG emissions (prevention first principle). Towards this goal, we simulate climate and the economy through a new version of the Dystopian Schumpeter meeting Keynes (DSK) model, extended to include an emission trading system (ETS) and operational permit systems. We show that climatic and economic projections in an ETS scenario need not be superior to those in an operational permit scenario. Which system delivers more encouraging projections on temperature anomalies, the green transition, and economic dynamics depends on institutional details, such as the set of firms for which permits are mandatory; the regulatory requirement of corrective measures; the magnitude of penalties; the stringency of the ETS. An ETS with a declining number of permits emerges as the best-performing system in terms of macroeconomic, microeconomic, and climate outcomes. A system of operational permits mandatory only for large firms (centralised permits) ranks as the second-best system, provided that the regulator imposes corrective measures regarding R&D expenses and machinery replacement.
C1 [Popoyan, Lilit] Queen Mary Univ London, Dept Business Analyt & Appl Econ, Mile End Rd, London E1 4NS, England.
   [Popoyan, Lilit] Scuola Super Sant Anna, Inst Econ LEM, Piazza Martiri Liberta 33, I-56127 Pisa, Italy.
   [Sapio, Alessandro] Univ Naples Parthenope, Dept Business & Econ, Via Parisi 13, I-80133 Naples, Italy.
C3 University of London; Queen Mary University London; Scuola Superiore
   Sant'Anna; Parthenope University Naples
RP Popoyan, L (corresponding author), Queen Mary Univ London, Dept Business Analyt & Appl Econ, Mile End Rd, London E1 4NS, England.; Popoyan, L (corresponding author), Scuola Super Sant Anna, Inst Econ LEM, Piazza Martiri Liberta 33, I-56127 Pisa, Italy.
EM l.popoyan@qmul.ac.uk; alessandro.sapio@uniparthenope.it
RI /I-4153-2012
FU Ministero dell'Istruzione, dell'Universit e della Ricerca; Reggio Emilia
   and Naples "Parthenope"
FX We are grateful for helpful comments and discussions to several
   participants at seminars and conferences where the paper has been
   presented and in particular at the Eastern Economic Association 2025
   Conference (New York, US, 20 February 2025) SITES-GLO Conference
   (Naples, 13 September 2024), 2nd Conference on Sustainable Banking and
   Finance (Naples, 21 June 2024), Conference "Manifesto and research
   frontiers for a Renaissance in Economics" (Perugia, 20-21 June 2024),
   "Climate Challenges, Innovation and Policy Responses" (London, 22
   November, 2023 ), CEF 2023 (Nice, France), IAERE 2023 (Naples, 23-24
   February 2023), EAEPE 2022 (Naples, 7-9 September 2022), WEHIA 2022
   (Catania, 22-24 June 2022), the ABM4Policy workshop (Pisa, 15-16
   November 2022), Seminar Series at the Universities of Modena and Reggio
   Emilia and Naples "Parthenope". We thank Takashi Kanamura for precious
   literature suggestions about carbon pricing. All usual disclaimers
   apply.
CR Albrizio S, 2017, J ENVIRON ECON MANAG, V81, P209, DOI 10.1016/j.jeem.2016.06.002
   Allen L.H., 1995, Biotic Feedbacks in the Global Climatic System: Will the Warming Increase the Warming?, P51
   ALLEN LH, 1990, J ENVIRON QUAL, V19, P15, DOI 10.2134/jeq1990.00472425001900010002x
   [Anonymous], 2019, RENEWABLES 2019
   Arlinghaus J, 2015, OECD ENV WORKING PAP, V87, P1
   Attanasio A, 2012, ATMOS SCI LETT, V13, P67, DOI 10.1002/asl.365
   Ausloos M, 2004, PHYSICA A, V339, P548, DOI 10.1016/j.physa.2004.03.005
   Bartelsman EJ, 2000, J ECON LIT, V38, P569, DOI 10.1257/jel.38.3.569
   Baxter M, 1999, REV ECON STAT, V81, P575, DOI 10.1162/003465399558454
   Bernstein L., 2008, Climate Change 2007: Synthesis Report: An Assessment of the Intergovernmental Panel on Climate Change, DOI DOI 10.1260/095830507781076194
   Bottazzi G, 2003, REV IND ORGAN, V23, P217, DOI 10.1023/B:REIO.0000031366.28559.c1
   Bottazzi G, 2006, RAND J ECON, V37, P235, DOI 10.1111/j.1756-2171.2006.tb00014.x
   Boyd GA, 2000, ENERG POLICY, V28, P289, DOI 10.1016/S0301-4215(00)00016-1
   Bruninx K, 2022, NAT COMMUN, V13, DOI 10.1038/s41467-022-28398-2
   Burns A.F., 1946, MEASURING BUSINESS C
   Caballero RJ, 1999, HBK ECON, V15, P813
   Castaldi C, 2009, EMPIR ECON, V37, P475, DOI 10.1007/s00181-008-0242-x
   Castro J, 2020, WIRES CLIM CHANGE, V11, DOI 10.1002/wcc.647
   Chappin EJL, 2009, TECHNOL FORECAST SOC, V76, P358, DOI 10.1016/j.techfore.2008.08.004
   Claussen M, 2002, CLIM DYNAM, V18, P579, DOI 10.1007/s00382-001-0200-1
   Comin D, 2006, AM ECON REV, V96, P523, DOI 10.1257/aer.96.3.523
   COP, 2015, UN FRAM CONV CLIM CH
   Cox PM, 2000, NATURE, V408, P184, DOI 10.1038/35041539
   DeCanio SJ, 1998, REV ECON STAT, V80, P95, DOI 10.1162/003465398557366
   Doda B, 2014, J MACROECON, V40, P214, DOI 10.1016/j.jmacro.2014.01.003
   Doms M, 1998, REV ECON DYNAM, V1, P409, DOI 10.1006/redy.1998.0011
   Dosi G, 2013, J ECON DYN CONTROL, V37, P1598, DOI 10.1016/j.jedc.2012.11.008
   Dosi G, 2006, PERSPECTIVES ON INNOVATION, P153
   Dosi G, 2010, J ECON DYN CONTROL, V34, P1748, DOI 10.1016/j.jedc.2010.06.018
   Fagiolo G., 2012, Revue de l'OFCE, P67, DOI [DOI 10.3917/REOF.124.0067, DOI 10.3917/RE0F.124.0067]
   Fagiolo G, 2008, J APPL ECONOMET, V23, P639, DOI 10.1002/jae.1003
   Fang CH, 2020, ENERG ECON, V92, DOI 10.1016/j.eneco.2020.104916
   Foos D, 2010, J BANK FINANC, V34, P2929, DOI 10.1016/j.jbankfin.2010.06.007
   FS-UNEP, 2019, GLOBAL TRENDS RENEWA
   FUNG I, 1993, BIOGEOCHEMISTRY OF GLOBAL CHANGE, P166
   Goncalves J, 2022, ECOL ECON, V195, DOI 10.1016/j.ecolecon.2022.107352
   GOUDRIAAN J, 1984, CLIMATIC CHANGE, V6, P167, DOI 10.1007/BF00144611
   Goulder LH, 2013, CLIM CHANG ECON, V4, DOI 10.1142/S2010007813500103
   Green JF, 2021, ENVIRON RES LETT, V16, DOI 10.1088/1748-9326/abdae9
   GREENWALD BC, 1993, Q J ECON, V108, P77, DOI 10.2307/2118496
   Halleux V, 2022, REV IND EMISSIONS DI
   Haya B, 2020, CLIM POLICY, V20, P1112, DOI 10.1080/14693062.2020.1781035
   Heine D., 2019, VIERTELJAHRSHEFTE WI, V88, P29, DOI [10.3790/vjh.88.2.29, 10.3790/vjh.88.2.29, DOI 10.3790/VJH.88.2.29]
   Hintermann B, 2017, ENVIRON RESOUR ECON, V66, P89, DOI 10.1007/s10640-015-9939-4
   Hintermann B, 2010, J ENVIRON ECON MANAG, V59, P43, DOI 10.1016/j.jeem.2009.07.002
   Hong QQ, 2022, ENERG ECON, V110, DOI 10.1016/j.eneco.2022.106025
   Houghton J T., 1997, INTRO SIMPLE CLIMATE, V410
   Huppes G, 2010, PRINCIPLES OF ENVIRONMENTAL SCIENCES, P239
   Kanamura T, 2021, HDB ENERGY EC POLICY, P275
   Kinnunen PHM, 2019, J CLEAN PROD, V228, P153, DOI 10.1016/j.jclepro.2019.04.171
   Koch N, 2014, ENERG POLICY, V73, P676, DOI 10.1016/j.enpol.2014.06.024
   Lamperti F, 2020, TECHNOL FORECAST SOC, V153, DOI 10.1016/j.techfore.2019.119806
   Lamperti F, 2018, ECOL ECON, V150, P315, DOI [10.2139/ssrn.2944328, 10.1016/j.ecolecon.2018.03.023]
   Matthews HD, 2007, GLOBAL CHANGE BIOL, V13, P1068, DOI 10.1111/j.1365-2486.2007.01343.x
   Mendoza EG, 2012, ECON CHIL, V15, P4
   Moosa I.A., 2000, OPEC Rev., V24, P53, DOI [DOI 10.1111/1468-0076.00074, DOI 10.1111/1468-0076.00074., 10.1111/1468-0076.00074]
   Napoletano M., 2006, Rivista italiana degli economisti, V11, P87, DOI DOI 10.1427/23296:Y:2006:I:1:P:87-118
   NORDHAUS WD, 1992, SCIENCE, V258, P1315, DOI 10.1126/science.258.5086.1315
   NSF, 2021, RES DEV US TRENDS IN
   OECD, 2020, RES DEV STAT R D EXP
   OESCHGER H, 1975, TELLUS, V27, P168, DOI 10.1111/j.2153-3490.1975.tb01671.x
   Ozturk I, 2010, ENERG POLICY, V38, P340, DOI 10.1016/j.enpol.2009.09.024
   Peters GP, 2012, NAT CLIM CHANGE, V2, P2, DOI 10.1038/nclimate1332
   Petrick S., 2013, Carbon efficiency, technology, and the role of innovation patterns: Evidence from German plant-level microdata
   Plan ZPA, 2021, PATHWAY HLTH PLANET
   Popoyan L, 2020, J ECON DYN CONTROL, V117, DOI 10.1016/j.jedc.2020.103937
   Reid CT., 2008, CAMB LAW J, V67, P126
   Reis LA, 2022, LANCET PLANET HEALTH, V6, pE40, DOI 10.1016/S2542-5196(21)00259-X
   Richstein JC, 2014, ENERG POLICY, V71, P139, DOI 10.1016/j.enpol.2014.03.037
   Rickels W, 2021, FRONT CLIM, V3, DOI 10.3389/fclim.2021.690023
   Rotemberg J.J., 2008, Behavioral aspects of price setting, and their policy implications
   Rotmans J., 2012, IMAGE INTEGRATED MOD
   Roventini A, 2017, THEORY METHOD EVOLUT, P143
   Sarmiento JL, 1998, NATURE, V393, P245, DOI 10.1038/30455
   SCHNEIDER SH, 1981, J GEOPHYS RES-OCEANS, V86, P3135, DOI 10.1029/JC086iC04p03135
   Sterman John., 2012, Climate interactive: the C-ROADS climate policy model
   Sterman JD, 2013, ENVIRON MODELL SOFTW, V44, P122, DOI 10.1016/j.envsoft.2012.06.004
   STIGLITZ JE, 1981, AM ECON REV, V71, P393
   Stock JH, 1999, HBK ECON, V15, P3
   Stoll C, 2021, ENERGY RES SOC SCI, V77, DOI 10.1016/j.erss.2021.102062
   Tang L, 2015, ENERG POLICY, V81, P152, DOI 10.1016/j.enpol.2015.02.032
   Thoma M, 2004, ENERG ECON, V26, P463, DOI 10.1016/j.eneco.2004.04.006
   Triacca U, 2001, THEOR APPL CLIMATOL, V69, P137, DOI 10.1007/s007040170019
   Tvinnereim E, 2018, ENERG POLICY, V121, P185, DOI 10.1016/j.enpol.2018.06.020
   Verbruggen A, 2019, ENVIRON SCI POLICY, V98, P11, DOI 10.1016/j.envsci.2019.05.001
   Wälde K, 2004, ECON LETT, V82, P91, DOI 10.1016/j.econlet.2003.07.014
   Weidlich A., 2008, Emissions Trading, P91, DOI [10.1007/978-0-387-73653-2_6, DOI 10.1007/978-0-387-73653-2_6]
   Wildgrube Theresa, 2023, Zeitschrift fur Energiewirtschaft, P52, DOI [10.1007/s12398-023-0931-3, 10.1007/s12398-023-0931-3]
   Windrum P, 2007, JASSS-J ARTIF SOC S, V10
   Wright I, 2005, PHYSICA A, V345, P608, DOI 10.1016/j.physa.2004.07.035
   Wullschleger S.D., 1995, Biotic Feedbacks in the Global Climatic System: Will the Warming Feed the Warming?, P85, DOI [DOI 10.1093/OSO/9780195086409.003.0005, 10.1093/oso/9780195086409.003.0005]
   Zaklan A, 2021, CLIM POLICY, V21, P778, DOI 10.1080/14693062.2021.1878999
   Zhao MS, 2010, SCIENCE, V329, P940, DOI [10.1126/science.1192666, 10.1126/science.1189590]
NR 93
TC 0
Z9 0
U1 0
U2 5
PU SPRINGER
PI NEW YORK
PA ONE NEW YORK PLAZA, SUITE 4600, NEW YORK, NY, UNITED STATES
SN 0936-9937
EI 1432-1386
J9 J EVOL ECON
JI J. Evol. Econ.
PD APR
PY 2025
VL 35
IS 2
BP 309
EP 354
DI 10.1007/s00191-025-00896-8
EA MAR 2025
PG 46
WC Economics
WE Social Science Citation Index (SSCI)
SC Business & Economics
GA 2IO5S
UT WOS:001467654200001
OA hybrid
DA 2026-06-13
ER

PT J
AU Anderies, JM
   Barfuss, W
   Donges, JF
   Fetzer, I
   Heitzig, J
   Rockström, J
AF Anderies, John M.
   Barfuss, Wolfram
   Donges, Jonathan F.
   Fetzer, Ingo
   Heitzig, Jobst
   Rockstroem, Johan
TI A modeling framework for World-Earth system resilience: exploring social
   inequality and Earth system tipping points
SO ENVIRONMENTAL RESEARCH LETTERS
LA English
DT Article
DE resilience; transformation; inequality; pathway diversity; World-Earth
   system; tipping elements; modeling
ID SUSTAINABLE USE; ELEMENTS; ANTHROPOCENE
AB The Anthropocene is characterized by the strengthening of planetary-scale interactions between the biophysical Earth system (ES) and human societies. This increasing social-ecological entanglement poses new challenges for studying possible future World-Earth system (WES) trajectories and World-Earth resilience defined as the capacity of the system to absorb and regenerate from anthropogenic stresses such as greenhouse gas emissions and land-use changes. The WES is currently in a non-equilibrium transitional regime of the early Anthropocene with arguably no plausible possibilities of remaining in Holocene-like conditions while sheltering up to 10 billion humans without risk of undermining the resilience of the ES. We develop a framework within which to conceptualize World-Earth resilience to examine this risk. Because conventional ball-and-cup type notions of resilience are hampered by the rapid and open-ended social, cultural, economic and technological evolution of human societies, we focus on the notion of 'pathway resilience', i.e. the relative number of paths that allow the WES to move from the currently occupied transitional states towards a safe and just operating space in the Anthropocene. We formalize this conceptualization mathematically and provide a foundation to explore how interactions between ES resilience (biophysical processes) and World system (WS) resilience (social processes) impact pathway resilience. Our analysis shows the critical importance of building ES resilience to reach a safe and just operating space. We also illustrate the importance of WS dynamics by showing how perceptions of fairness coupled with regional inequality affects pathway resilience. The framework provides a starting point for the analysis of World-Earth resilience that can be extended to more complex model settings as well as the development of quantitative planetary-scale resilience indicators to guide sustainable development in a stabilized ES.
C1 [Anderies, John M.] Arizona State Univ, Sch Sustainabil, Sch Human Evolut & Social Change, Tempe, AZ 85287 USA.
   [Barfuss, Wolfram; Donges, Jonathan F.; Heitzig, Jobst; Rockstroem, Johan] Telegrafenberg, D-14473 Potsdam, Germany.
   [Donges, Jonathan F.; Fetzer, Ingo] Stockholm Univ, Stockholm Resilience Ctr, S-11419 Stockholm, Sweden.
   [Barfuss, Wolfram] Univ Bonn, Transdisciplinary Res Area Sustainable Futures, D-53113 Bonn, Germany.
   [Barfuss, Wolfram] Univ Bonn, Ctr Dev Res ZEF, D-53113 Bonn, Germany.
   [Fetzer, Ingo] Univ Stockholm, Bolin Ctr Climate Res, S-10691 Stockholm, Sweden.
   [Rockstroem, Johan] Univ Potsdam, Inst Earth & Environm Sci Geoecol, Potsdam, Germany.
C3 Arizona State University; Arizona State University-Tempe; Stockholm
   University; University of Bonn; University of Bonn; Stockholm
   University; University of Potsdam
RP Anderies, JM (corresponding author), Arizona State Univ, Sch Sustainabil, Sch Human Evolut & Social Change, Tempe, AZ 85287 USA.
EM m.anderies@asu.edu
RI Donges, Jonathan/HCI-2311-2022; Rockström, Johan/G-1168-2010; Heitzig,
   Jobst/E-8271-2011; Fetzer, Ingo/A-6748-2015
OI Donges, Jonathan/0000-0001-5233-7703; Rockström,
   Johan/0000-0001-8988-2983; Barfuss, Wolfram/0000-0002-9077-5242;
   Heitzig, Jobst/0000-0002-0442-8077; Fetzer, Ingo/0000-0001-7335-5679;
   Anderies, John/0000-0002-0138-8655
FU European Research Council Advanced Grant project ERA (Earth Resilience
   in the Anthropocene) [ERC-2016-ADG-743080]; Leibniz Association; German
   Federal Ministry for Education and Research (project PIK Change)
   [01LS2001A]
FX We are grateful for financial support by the European Research Council
   Advanced Grant project ERA (Earth Resilience in the Anthropocene, Grant
   ERC-2016-ADG-743080), the Leibniz Association (project DominoES), and
   the German Federal Ministry for Education and Research (project PIK
   Change, Grant 01LS2001A). The authors thank S Lade, R Winkelmann and the
   participants of the LOOPS-4 workshop on Earth resilience in the
   Anthropocene held in Bad Belzig, Germany in March 2019 for insightful
   discussions.
CR Alcamo J, 1996, GLOBAL ENVIRON CHANG, V6, P261, DOI 10.1016/S0959-3780(96)00026-X
   [Anonymous], 2015, World Population Prospects, the 2015 Revision
   [Anonymous], 2021, Conversations in Veliko Tarnovo
   Aschemann-Witzel J, 2023, CURR OPIN FOOD SCI, V51, DOI 10.1016/j.cofs.2023.101015
   Bak-Coleman JB, 2021, P NATL ACAD SCI USA, V118, DOI 10.1073/pnas.2025764118
   Barfuss W, 2018, NAT COMMUN, V9, DOI 10.1038/s41467-018-04738-z
   Barfuss W, 2017, EARTH SYST DYNAM, V8, P255, DOI 10.5194/esd-8-255-2017
   Benton T., 2017, Environmental tipping points and food system dynamics: main report
   Berger A, 2016, REV GEOPHYS, V54, P162, DOI 10.1002/2015RG000482
   Bers CV., 2016, 190 CCAFS CGIAR RES
   Bloomberg Green, 2021, BLOOMB GREEN
   Chapin FS III, 2022, AMBIO, V51, P1907, DOI 10.1007/s13280-022-01721-3
   Farmer JD, 2015, ENVIRON RESOUR ECON, V62, P329, DOI 10.1007/s10640-015-9965-2
   Fesenfeld LP, 2022, ONE EARTH, V5, P1100, DOI 10.1016/j.oneear.2022.09.004
   Geier F, 2019, EUR PHYS J-SPEC TOP, V228, P2357, DOI 10.1140/epjst/e2019-900120-4
   Giandrea MD, 2017, MON LABOR REV
   Goldewijk KK, 2010, HOLOCENE, V20, P565, DOI 10.1177/0959683609356587
   Gruber N, 2019, SCIENCE, V363, P1193, DOI 10.1126/science.aau5153
   Heap SPH, 2016, ECON LETT, V146, P4, DOI 10.1016/j.econlet.2016.07.015
   Heitzig J, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10061947
   Kemp L, 2022, P NATL ACAD SCI USA, V119, DOI 10.1073/pnas.2108146119
   Keppo I, 2021, ENVIRON RES LETT, V16, DOI 10.1088/1748-9326/abe5d8
   Klose AK, 2020, ROY SOC OPEN SCI, V7, DOI 10.1098/rsos.200599
   Kopp RE, 2016, EARTHS FUTURE, V4, P346, DOI 10.1002/2016EF000362
   Krishnamurthy RPK, 2022, NAT SUSTAIN, V5, P956, DOI 10.1038/s41893-022-00962-0
   Lade SJ, 2020, ECOL SOC, V25, DOI 10.5751/ES-11760-250319
   Lenton TM, 2008, P NATL ACAD SCI USA, V105, P1786, DOI 10.1073/pnas.0705414105
   Lenton TM, 2018, SCIENCE, V361, P1066, DOI 10.1126/science.aau0427
   Livina VN, 2023, NAT CLIM CHANGE, V13, P15, DOI 10.1038/s41558-022-01573-5
   Mathias JD, 2020, EARTHS FUTURE, V8, DOI 10.1029/2020EF001573
   Mckay DIA, 2022, SCIENCE, V377, P1171, DOI 10.1126/science.abn7950
   Nitzbon J, 2017, ENVIRON RES LETT, V12, DOI 10.1088/1748-9326/aa7581
   Nordhaus WD, 1996, AM ECON REV, V86, P741
   NORDHAUS WD, 1993, RESOUR ENERGY ECON, V15, P27, DOI 10.1016/0928-7655(93)90017-O
   Nyborg K, 2016, SCIENCE, V354, P42, DOI 10.1126/science.aaf8317
   O'Riordan T., 2013, ADDRESSING TIPPING P
   Our World in Data, 2021, CARB EM INT EC
   Piketty Thomas., 2020, CAPITAL IDEOLOGY
   Rasmussen K., 2011, NATL SECURITY HUMAN, ppp 39
   Raworth K., 2012, Oxfam
   Raworth K, 2017, LANCET PLANET HEALTH, V1, pE48, DOI 10.1016/S2542-5196(17)30028-1
   Rockström J, 2021, EARTHS FUTURE, V9, DOI 10.1029/2020EF001866
   Rockström J, 2009, NATURE, V461, P472, DOI 10.1038/461472a
   Steffen W, 2018, P NATL ACAD SCI USA, V115, P8252, DOI 10.1073/pnas.1810141115
   Steffen W, 2015, SCIENCE, V347, DOI 10.1126/science.1259855
   Steffen W, 2011, AMBIO, V40, P739, DOI 10.1007/s13280-011-0185-x
   Stolbova V, 2016, GEOPHYS RES LETT, V43, P3982, DOI 10.1002/2016GL068392
   The Rio Times, 2021, THE RIO TIMES   1109
   The Straits Times, 2021, STRAITS TIMES   1110
   UN Economic Commission for Europe, 2021, CARBON DIOXIDE EMISS
   van Vuuren DP, 2016, EARTH SYST DYNAM, V7, P267, DOI 10.5194/esd-7-267-2016
   Walker B, 2004, ECOL SOC, V9
   Wallerstein I., 1979, The capitalist world economy: Essays by Immanuel Wallerstein
   Wallerstein I.M., 2004, WORLD SYSTEMS ANAL I
   Waters CN, 2016, SCIENCE, V351, P137, DOI 10.1126/science.aad2622
   World Bank, 2021, GROSS NAT PROD
   World Bank, 2021, GROSS SAV
   Wunderling N, 2021, EARTH SYST DYNAM, V12, P601, DOI 10.5194/esd-12-601-2021
NR 58
TC 16
Z9 18
U1 5
U2 45
PU IOP Publishing Ltd
PI BRISTOL
PA TEMPLE CIRCUS, TEMPLE WAY, BRISTOL BS1 6BE, ENGLAND
SN 1748-9326
J9 ENVIRON RES LETT
JI Environ. Res. Lett.
PD SEP 1
PY 2023
VL 18
IS 9
AR 095001
DI 10.1088/1748-9326/ace91d
PG 11
WC Environmental Sciences; Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences
GA O4RH0
UT WOS:001043697100001
OA Green Submitted, gold
DA 2026-06-13
ER

PT J
AU Safarzynska, K
   Di Domenico, L
   Raberto, M
AF Safarzynska, Karolina
   Di Domenico, Lorenzo
   Raberto, Marco
TI The circular economy mitigates the material rebound due to investments
   in renewable energy
SO JOURNAL OF CLEANER PRODUCTION
LA English
DT Article
DE Circular economy; Recycling; Renewable energy; Opinion dynamics
ID AGENT; POLICY; MODEL; EFFICIENCY; COMPLEXITY; CREDIT
AB The current macroeconomic models of the circular economy rely on the unrealistic assumption that materials can be recycled infinitely, often ignoring price and demand adjustments. In reality, most virgin materials are recycled only a few times, while the proliferation of cheap products made from recycled materials is likely to affect final demand. In this paper, we address both of these shortcomings. We propose a novel climate-economy agent-based model of the circular economy combined with the climate cycle and opinion dynamics. Consumers and producers are embedded in co-evolving networks, with preferences of consumers influencing the direction of technological progress and the diffusion of goods made from recycled materials. The main novelty of our study is that we compare the macroeconomic consequences of inputs being recycled once, twice and infinitely. We find that the more times materials are recycled, the more global temperature and resource depletion decrease. In addition, our study shows that the transition to renewable energy leads to the material rebound effect, where more raw materials are used in the manufacturing sector compared to an economy dependent on fossil fuels. Whether the circular economy can mitigate this effect depends on how many times inputs are recycled.
C1 [Safarzynska, Karolina; Di Domenico, Lorenzo] Warsaw Univ, Fac Econ Sci, Dluga 44-50, PL-02241 Warsaw, Poland.
   [Raberto, Marco] Univ Genoa, Via Opera Pia 15, I-16145 Genoa, Italy.
C3 University of Warsaw; University of Genoa
RP Safarzynska, K (corresponding author), Warsaw Univ, Fac Econ Sci, Dluga 44-50, PL-02241 Warsaw, Poland.
EM ke.safarzynska@uw.edu.pl
RI Di Domenico, Lorenzo/NSU-7104-2025; Safarzynska, Karolina/AAZ-9772-2020
OI Di Domenico, Lorenzo/0000-0003-0728-9735; Safarzynska,
   Karolina/0000-0001-5507-9287
FU National Science Centre, Poland [2019/35/B/HS4/00140]
FX The research was supported by the National Science Centre, Poland, grant
   no. 2019/35/B/HS4/00140.
CR Ackerman J.N., 2020, CHALLENGES CIR UNPUB
   Aguilar-Hernandez GA, 2019, RESOUR CONSERV RECY, V151, DOI 10.1016/j.resconrec.2019.104452
   American Iron and Steel Institute, 2003, STEEL IND TECHN ROAD
   [Anonymous], 2015, CIRCULAR EC EC IMPAC
   [Anonymous], 2021, The Role of Critical Minerals in Clean Energy Transitions, DOI DOI 10.1787/FCD94E4E-EN
   [Anonymous], 2017, The Growing Role of Minerals and Metals for a Low Carbon Future, P112, DOI [DOI 10.1596/28312, 10.1596/28312]
   Arthur WB, 2021, NAT REV PHYS, V3, P136, DOI 10.1038/s42254-020-00273-3
   Axtell R., 2021, IN PRESS
   Balint T, 2017, ECOL ECON, V138, P252, DOI 10.1016/j.ecolecon.2017.03.032
   Baptist S, 2013, PHILOS T R SOC A, V371, DOI 10.1098/rsta.2011.0565
   Boin UMJ, 2005, JOM-US, V57, P26, DOI 10.1007/s11837-005-0164-4
   Boyd G., 2010, 1001 DUKE ENV EC
   Brookes L, 2000, ENERG POLICY, V28, P355, DOI 10.1016/S0301-4215(00)00030-6
   Cardaci A, 2015, Working paper 2015-27
   CARROLL CHRISTOPHER D., 2016, Theoretical Foundations of Buffer Stock Saving
   Castro J, 2020, WIRES CLIM CHANGE, V11, DOI 10.1002/wcc.647
   Castro MBG, 2007, RESOUR CONSERV RECY, V52, P219, DOI 10.1016/j.resconrec.2007.01.014
   Ceschi A, 2021, J ENVIRON MANAGE, V294, DOI 10.1016/j.jenvman.2021.112938
   Cincotti S, 2010, ECONOMICS-KIEL, V4, DOI 10.5018/economics-ejournal.ja.2010-26
   Csereklyei Z, 2015, ENERG ECON, V51, P633, DOI 10.1016/j.eneco.2015.08.029
   Dawid H, 2019, J EVOL ECON, V29, P467, DOI 10.1007/s00191-018-0594-0
   Dennig F, 2015, P NATL ACAD SCI USA, V112, P15827, DOI 10.1073/pnas.1513967112
   Dietz S, 2021, P NATL ACAD SCI USA, V118, DOI 10.1073/pnas.2103081118
   Djedjibegovic J, 2020, SCI REP-UK, V10, DOI 10.1038/s41598-020-70205-9
   Donati F, 2021, J IND ECOL, V25, P36, DOI 10.1111/jiec.13046
   Dosi G, 2013, J ECON DYN CONTROL, V37, P1598, DOI 10.1016/j.jedc.2012.11.008
   ECORYS, 2012, MAPP RES PRIC FUT
   Elhacham E, 2020, NATURE, V588, P442, DOI 10.1038/s41586-020-3010-5
   Essoussi LH, 2010, J CONSUM MARK, V27, P458, DOI 10.1108/07363761011063358
   EU, 2020, A new Circular Economy Action Plan
   Farmer JD, 2015, ENVIRON RESOUR ECON, V62, P329, DOI 10.1007/s10640-015-9965-2
   Gaffeo E, 2008, EAST ECON J, V34, P441, DOI 10.1057/eej.2008.27
   Gatti DD, 2009, J ECON INTERACT COOR, V4, P195, DOI 10.1007/s11403-009-0054-x
   Geng Y, 2019, NATURE, V565, P153, DOI 10.1038/d41586-019-00017-z
   Grimm V, 2006, ECOL MODEL, V198, P115, DOI 10.1016/j.ecolmodel.2006.04.023
   Haas W, 2015, J IND ECOL, V19, P765, DOI 10.1111/jiec.12244
   Hafner S, 2020, ECOL ECON, V177, DOI 10.1016/j.ecolecon.2020.106779
   Haupt M, 2017, J IND ECOL, V21, P615, DOI 10.1111/jiec.12506
   Kirchherr J, 2018, ECOL ECON, V150, P264, DOI 10.1016/j.ecolecon.2018.04.028
   Kirchherr J, 2017, RESOUR CONSERV RECY, V127, P221, DOI [10.33002/nr2581.6853.070207, 10.1016/j.resconrec.2017.09.005]
   Korhonen J, 2018, ECOL ECON, V143, P37, DOI 10.1016/j.ecolecon.2017.06.041
   Krausmann F, 2009, ECOL ECON, V68, P2696, DOI 10.1016/j.ecolecon.2009.05.007
   Kuczenski B, 2010, RESOUR CONSERV RECY, V54, P1161, DOI 10.1016/j.resconrec.2010.03.013
   Lamperti F, 2019, NAT CLIM CHANGE, V9, P829, DOI 10.1038/s41558-019-0607-5
   Lange K.P.H., 2021, RESOURCE CONSERV REC, V12, P20055
   Lau WWY, 2020, SCIENCE, V369, P1455, DOI 10.1126/science.aba9475
   Leimbach M, 2017, GLOBAL ENVIRON CHANG, V42, P215, DOI 10.1016/j.gloenvcha.2015.02.005
   McKinsey, 2016, The circular economy: moving from theory to practice, VSpecial
   MOBLEY AS, 1995, PSYCHOL MARKET, V12, P165, DOI 10.1002/mar.4220120302
   Murphy TW Jr, 2022, NAT PHYS, V18, P844, DOI 10.1038/s41567-022-01652-6
   Neveu AR, 2013, J ECON BEHAV ORGAN, V92, P224, DOI 10.1016/j.jebo.2013.06.006
   Nordhaus WD, 2017, P NATL ACAD SCI USA, V114, P1518, DOI 10.1073/pnas.1609244114
   Parrique T., 2019, Decoupling debunked-evidence and arguments against green growth as a sole strategy for sustainability
   Russo A, 2016, J EVOL ECON, V26, P25, DOI 10.1007/s00191-015-0410-z
   Safarzynska K., ENERG POLICY, V108, P12
   Safarzynska K, 2022, ENVIRON RES LETT, V17, DOI 10.1088/1748-9326/ac8b25
   Safarzynska K, 2017, TECHNOL FORECAST SOC, V114, P119, DOI 10.1016/j.techfore.2016.07.033
   Safarzynska K, 2011, ENERG POLICY, V39, P6440, DOI 10.1016/j.enpol.2011.07.046
   Sandin G, 2018, J CLEAN PROD, V184, P353, DOI 10.1016/j.jclepro.2018.02.266
   Scalco A, 2017, UNDERST COMPLEX SYST, P77, DOI 10.1007/978-3-319-46331-5_4
   Skeldon AC, 2018, ENVIRON SCI POLICY, V87, P85, DOI 10.1016/j.envsci.2018.05.011
   Smith Vanessa M., 2004, Journal of Industrial Ecology, V8, P193, DOI 10.1162/1088198041269463
   Sorrell S, 2009, ENERG POLICY, V37, P1456, DOI 10.1016/j.enpol.2008.12.003
   Thurner S, 2013, SCI REP-UK, V3, DOI 10.1038/srep01888
   van den Bergh JCJM, 2020, RESOUR CONSERV RECY, V160, DOI 10.1016/j.resconrec.2020.104898
   Vidal O, 2013, NAT GEOSCI, V6, P894, DOI 10.1038/ngeo1993
   Wang L, 2012, BIORESOURCE TECHNOL, V120, P89, DOI 10.1016/j.biortech.2012.05.130
   Wiebe KS, 2019, ENVIRON SCI TECHNOL, V53, P6362, DOI 10.1021/acs.est.9b01208
   Wijkman A, 2017, A study report at the request of the Club of Rome
   Windrum P, 2005, J EVOL ECON, V15, P123, DOI 10.1007/s00191-004-0226-8
   Windrum P., 1998, Structural Change and Economic Dynamics, V9, P109, DOI 10.1016/S0954-349X(97)00039-8
   Winning M., 2017, Int. Econ. Econ. Policy, V14, P383, DOI [10.1007/s10368-017-0385-3, DOI 10.1007/S10368-017-0385-3, 10.1007/s10368-017-0385-3]
   Xiarchos I.M., 2006, THESIS W VIRGINIA U
   Zink T, 2017, J IND ECOL, V21, P593, DOI 10.1111/jiec.12545
NR 74
TC 24
Z9 26
U1 3
U2 21
PU ELSEVIER SCI LTD
PI London
PA 125 London Wall, London, ENGLAND
SN 0959-6526
EI 1879-1786
J9 J CLEAN PROD
JI J. Clean Prod.
PD MAY 20
PY 2023
VL 402
AR 136753
DI 10.1016/j.jclepro.2023.136753
EA MAR 2023
PG 13
WC Green & Sustainable Science & Technology; Engineering, Environmental;
   Environmental Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Science & Technology - Other Topics; Engineering; Environmental Sciences
   & Ecology
GA A6PB7
UT WOS:000956311300001
DA 2026-06-13
ER

PT J
AU Safarzynska, K
   van den Bergh, JCJM
AF Safarzynska, Karolina
   van den Bergh, Jeroen C. J. M.
TI ABM-IAM: optimal climate policy under bounded rationality and multiple
   inequalities
SO ENVIRONMENTAL RESEARCH LETTERS
LA English
DT Article
DE agent-based modelling; social cost of carbon; climate policy
ID SOCIAL COST; CONSUMPTION INEQUALITY; INCOME INEQUALITY; MODEL;
   EMPLOYMENT; IMPACTS; TAXES; FUEL
AB Despite considerable concern about potentially inequitable effects of climate policy, models fall short in assessing their implications for policy design. To address this issue, we develop an agent-based climate-economy model, agent-based modelling-Integrated Assessment Model, as a disaggregated, behavioural approach to integrated climate assessment. It describes networks of heterogeneous consumers, banks, power plants and firms, and is calibrated on patterns of growth and carbon dioxide emissions generated by the DICE model of Nordhaus. Whereas the latter assumes full employment and abstains from a financial sector and inequality considerations, our approach relaxes these restrictions to obtain a more reliable assessment of climate policy impacts. We show that inequalities in labour and capital income serve as essential but overlooked links between climate-change damages and optimal climate policy. Our result show that lower inequalities of labour income increase the social cost of carbon (SCC), while the impact of capital income inequalities on the SCC depends on the share of population receiving capital rents.
C1 [Safarzynska, Karolina] Warsaw Univ, Fac Econ Sci, Dluga 44-50, PL-00241 Warsaw, Poland.
   [van den Bergh, Jeroen C. J. M.] Univ AuMmoma Barcelona, Inst Environm Sci & Technol, Edifici Z Campus UAB, Bellaterra 08193, Spain.
   [van den Bergh, Jeroen C. J. M.] ICREA, Barcelona, Spain.
   [van den Bergh, Jeroen C. J. M.] Vrije Univ Amsterdam, Sch Business & Econ, Amsterdam, Netherlands.
   [van den Bergh, Jeroen C. J. M.] Vrije Univ Amsterdam, Inst Environm Studies, Amsterdam, Netherlands.
C3 University of Warsaw; ICREA; Vrije Universiteit Amsterdam; Vrije
   Universiteit Amsterdam
RP Safarzynska, K (corresponding author), Warsaw Univ, Fac Econ Sci, Dluga 44-50, PL-00241 Warsaw, Poland.
EM ke.safarzynska@uw.edu.pl
RI van den Bergh, Jeroen/C-7103-2008; Safarzynska, Karolina/AAZ-9772-2020
OI van den Bergh, Jeroen/0000-0003-3415-3083; Safarzynska,
   Karolina/0000-0001-5507-9287
FU National Science Centre of Poland [2016/21/B/HS4/00647]; ERC Advanced
   Grant from the European Research Council (ERC) under the European
   Union's Horizon 2020 Research and Innovation Programme [741087]
FX Safarzynska's research was supported by the National Science Centre of
   Poland, Grant 2016/21/B/HS4/00647. Van den Bergh was supported by an ERC
   Advanced Grant from the European Research Council (ERC) under the
   European Union's Horizon 2020 Research and Innovation Programme (Grant
   Agreement No. 741087).
CR Adler M, 2017, NAT CLIM CHANGE, V7, P443, DOI [10.1038/nclimate3298, 10.1038/NCLIMATE3298]
   Aguiar M, 2015, AM ECON REV, V105, P2725, DOI 10.1257/aer.20120599
   Anthoff D, 2009, ECOL ECON, V68, P836, DOI 10.1016/j.ecolecon.2008.06.017
   Anthoff D, 2019, J ASSOC ENVIRON RESO, V6, P29, DOI 10.1086/701900
   Arthur WB, 2021, NAT REV PHYS, V3, P136, DOI 10.1038/s42254-020-00273-3
   Autor D, 2020, Q J ECON, V135, P645, DOI 10.1093/qje/qjaa004
   Beck M, 2015, RESOUR ENERGY ECON, V41, P40, DOI 10.1016/j.reseneeco.2015.04.005
   Berman Y, 2016, PLOS ONE, V11, DOI 10.1371/journal.pone.0154196
   Botta A, 2021, J ECON BEHAV ORGAN, V183, P998, DOI 10.1016/j.jebo.2019.02.013
   Budolfson M, 2017, CLIMATIC CHANGE, V145, P481, DOI 10.1007/s10584-017-2094-x
   Campiglio E, 2018, NAT CLIM CHANGE, V8, P462, DOI 10.1038/s41558-018-0175-0
   Cardaci A, 2015, Working paper 2015-27
   Carroll C, 2017, QUANT ECON, V8, P977, DOI 10.3982/QE694
   Castro J, 2020, WIRES CLIM CHANGE, V11, DOI 10.1002/wcc.647
   Chan YT, 2020, ENERG POLICY, V146, DOI 10.1016/j.enpol.2020.111809
   Cincotti S, 2010, ECONOMICS-KIEL, V4, DOI 10.5018/economics-ejournal.ja.2010-26
   Cingano F, 2015, VESTN MEZHDUNARODNYK, V10, P97
   Czupryna M, 2020, JASSS-J ARTIF SOC S, V23, DOI 10.18564/jasss.4325
   Dennig F, 2015, P NATL ACAD SCI USA, V112, P15827, DOI 10.1073/pnas.1513967112
   Dietz S, 2021, P NATL ACAD SCI USA, V118, DOI 10.1073/pnas.2103081118
   Dosi G, 2010, J ECON DYN CONTROL, V34, P1748, DOI 10.1016/j.jedc.2010.06.018
   Epstein JM, 2009, NATURE, V460, P687, DOI 10.1038/460687a
   Farmer JD, 2015, ENVIRON RESOUR ECON, V62, P329, DOI 10.1007/s10640-015-9965-2
   Gaffeo E, 2008, EAST ECON J, V34, P441, DOI 10.1057/eej.2008.27
   Gatti DD, 2009, J ECON INTERACT COOR, V4, P195, DOI 10.1007/s11403-009-0054-x
   Gerlagh R, 2018, J EUR ECON ASSOC, V16, P1, DOI 10.1093/jeea/jvx010
   Gerlagh R, 2018, ECON J, V128, P728, DOI 10.1111/ecoj.12436
   Gerst MD, 2013, ENVIRON MODELL SOFTW, V44, P62, DOI 10.1016/j.envsoft.2012.09.002
   Golosov M, 2014, ECONOMETRICA, V82, P41, DOI 10.3982/ECTA10217
   Hänsel MC, 2020, NAT CLIM CHANGE, V10, P781, DOI 10.1038/s41558-020-0833-x
   Hafner S, 2020, ECOL ECON, V177, DOI 10.1016/j.ecolecon.2020.106779
   Hallegatte S, 2017, NAT CLIM CHANGE, V7, P250, DOI 10.1038/NCLIMATE3253
   HAMILTON K, 1994, CAN PUBLIC POL, V20, P385, DOI 10.2307/3551997
   Howarth RB, 2006, ECOL ECON, V58, P209, DOI 10.1016/j.ecolecon.2005.07.007
   Kornek U, 2021, J ENVIRON ECON MANAG, V107, DOI 10.1016/j.jeem.2021.102450
   Krueger D, 2006, REV ECON STUD, V73, P163, DOI 10.1111/j.1467-937X.2006.00373.x
   Kunreuther H, 2014, CLIMATE CHANGE 2014: MITIGATION OF CLIMATE CHANGE, P151
   Lamperti F, 2019, NAT CLIM CHANGE, V9, P829, DOI 10.1038/s41558-019-0607-5
   Leimbach M, 2017, GLOBAL ENVIRON CHANG, V42, P215, DOI 10.1016/j.gloenvcha.2015.02.005
   Mathiesen BV, 2011, APPL ENERG, V88, P488, DOI 10.1016/j.apenergy.2010.03.001
   Metcalf GE, 2009, REV ENV ECON POLICY, V3, P63, DOI 10.1093/reep/ren015
   Milanovic B., 2016, LIS Working Paper Series No. 663
   Neveu AR, 2013, J ECON BEHAV ORGAN, V92, P224, DOI 10.1016/j.jebo.2013.06.006
   Nordhaus W., 2016, 2057 YAL U COWL FDN
   Nordhaus W., 1994, MANAGING GLOBAL COMM
   Nordhaus WD, 1996, AM ECON REV, V86, P741
   Nordhaus W, 2014, J ASSOC ENVIRON RESO, V1, P273, DOI 10.1086/676035
   Nordhaus WD, 2017, P NATL ACAD SCI USA, V114, P1518, DOI 10.1073/pnas.1609244114
   Pearson M., 1991, EUROPEAN CARBON TAX
   Piketty T., 2014, Capital in the twenty-first century, DOI [10.4159/9780674369542, DOI 10.4159/9780674369542]
   Plambeck EL, 1996, ENERG POLICY, V24, P783, DOI 10.1016/0301-4215(96)00064-X
   Ponta L, 2018, ECOL ECON, V145, P274, DOI 10.1016/j.ecolecon.2017.08.022
   POTERBA JM, 1989, AM ECON REV, V79, P325
   Ranaldi, 2021, STONE CTR WORKING PA, V30
   Ranaldi M., 2020, STONE CTR WORKING PA, V25
   Rausch S., 2011, 17087 NBER
   Rengs B, 2020, J ECON BEHAV ORGAN, V169, P332, DOI 10.1016/j.jebo.2019.11.025
   Rezai A, 2016, J ASSOC ENVIRON RESO, V3, P493, DOI 10.1086/686294
   Russo A, 2016, J EVOL ECON, V26, P25, DOI 10.1007/s00191-015-0410-z
   Safarzynska K, 2017, ENERG POLICY, V108, P12, DOI 10.1016/j.enpol.2017.05.042
   Safarzynska K, 2017, TECHNOL FORECAST SOC, V114, P119, DOI 10.1016/j.techfore.2016.07.033
   Saunders HD, 2008, ENERG ECON, V30, P2184, DOI 10.1016/j.eneco.2007.11.006
   Semieniuk G., 2020, WIRES COMPUT STAT, V12, DOI [10.1002/wsbm.1470, DOI 10.1002/WSBM.1470]
   Stern N, 2016, NATURE, V530, P407, DOI 10.1038/530407a
   Taylor L, 2016, ECOL ECON, V121, P196, DOI 10.1016/j.ecolecon.2015.05.015
   Tedeschi G, 2012, PLOS ONE, V7, DOI 10.1371/journal.pone.0052749
   Tol R. S. J., 1995, Environmental and Resource Economics, V5, P353, DOI 10.1007/BF00691574
   Weyant J, 2017, REV ENV ECON POLICY, V11, P115, DOI 10.1093/reep/rew018
   Windrum P, 2005, J EVOL ECON, V15, P123, DOI 10.1007/s00191-004-0226-8
   Windrum P., 1998, Structural Change and Economic Dynamics, V9, P109, DOI 10.1016/S0954-349X(97)00039-8
   Wolff EdwardN., 2014, Household Wealth Trends in the United States, 1962-2013: What Happened Over the Great Recession?
NR 71
TC 15
Z9 17
U1 3
U2 55
PU IOP Publishing Ltd
PI BRISTOL
PA TEMPLE CIRCUS, TEMPLE WAY, BRISTOL BS1 6BE, ENGLAND
SN 1748-9326
J9 ENVIRON RES LETT
JI Environ. Res. Lett.
PD SEP 1
PY 2022
VL 17
IS 9
AR 094022
DI 10.1088/1748-9326/ac8b25
PG 15
WC Environmental Sciences; Meteorology & Atmospheric Sciences
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences
GA 4F2VG
UT WOS:000848372900001
OA Green Submitted, Green Published, gold
DA 2026-06-13
ER

PT J
AU Gerdes, L
   Rengs, B
   Scholz-Wäckerle, M
AF Gerdes, Lena
   Rengs, Bernhard
   Scholz-Waeckerle, Manuel
TI Labor and environment in global value chains: an evolutionary policy
   study with a three-sector and two-region agent-based macroeconomic model
SO JOURNAL OF EVOLUTIONARY ECONOMICS
LA English
DT Article
DE Evolutionary political economy; Agent-based modelling; Unequal exchange;
   Resource extraction; Global value chains; Labor and environmental
   protection; Climate change
ID UNEQUAL ECOLOGICAL EXCHANGE; TRADE; CLIMATE; DYNAMICS; IMPACTS; GROWTH;
   WORLD
AB The world economy crucially depends on multi-layered value chains with high degrees of sector-related specialization. Its final products are of international character and serve the needs and wants of the global citizen. However, many production processes are causing severe damage to the environment and moreover create health hazard for workers and local populations. This research article focuses on the increasing global unequal economic- and ecological exchange, fundamentally embedded in international trade. Resource extraction and labor conditions in the Global South as well as the implications for climate change originating from industry emissions in the North are investigated with an agent-based model. The model serves as a testbed for simulation experiments with evolutionary political economic policies. An international institution is introduced sanctioning the polluting extractivist sector in the Global South as well as the emitting industrial capital good producers in the North with the aim of subsidizing innovation reducing environmental and social impacts. Both regions are modelled as macroeconomic complex adaptive systems where international trade is restricted to a three-sector value chain, originating from mining resources in the South that are traded to capital good producers in the North crafting machinery which is eventually traded to consumer good firms, both in the North and South. The main outcome of the study is that sanctions alone are not effective in countering unequal exchange. They only make a difference in combination with subsidies for innovation activities, which are protecting labor and reducing local pollution in mines as well as reducing carbon-emissions in capital good production.
C1 [Gerdes, Lena] Vienna Univ Econ & Business, Inst Econ Geog, Vienna, Austria.
   [Gerdes, Lena] Vienna Univ Econ & Business, GISci, Dept Socioecon, Vienna, Austria.
   [Rengs, Bernhard] Univ Vienna, Vienna Inst Demog, Wittgenstein Ctr Demog & Global Human Capital, Austria Acad Sci,IIASA,OEAW, Vienna, Austria.
   [Scholz-Waeckerle, Manuel] Vienna Univ Econ & Business, Dept Socioecon, Vienna, Austria.
C3 Vienna University of Economics & Business; Vienna University of
   Economics & Business; International Institute for Applied Systems
   Analysis (IIASA); University of Vienna; Vienna University of Economics &
   Business
RP Scholz-Wäckerle, M (corresponding author), Vienna Univ Econ & Business, Dept Socioecon, Vienna, Austria.
EM lena.gerdes@wu.ac.at; bernhard.rengs@oeaw.ac.at;
   manuel.scholz-waeckerle@wu.ac.at
RI Scholz-Wäckerle, Manuel/AAH-4387-2019
OI Scholz-Wäckerle, Manuel/0000-0002-3137-1782; Rengs,
   Bernhard/0000-0001-8756-5343; Gerdes, Lena/0000-0003-2130-7098
FU Vienna University of Economics and Business (WU); VolkswagenStiftung
   [94899]
FX Open access funding provided by Vienna University of Economics and
   Business (WU). This study was partly funded by VolkswagenStiftung (grant
   number 94899).
CR Acosta A., 2013, DEV ALTERNATIVE VISI, P61
   Albanesi E, 2021, THEORY PRACT LEGIS, V9, P141, DOI 10.1080/20508840.2021.1904553
   Amable B., 2000, Structural Change and Economic Dynamics, V11, P413, DOI 10.1016/S0954-349X(00)00026-6
   Amin Samir., 1974, ACCUMULATION WORLD S
   Caiani A, 2019, J ECON BEHAV ORGAN, V162, P389, DOI 10.1016/j.jebo.2018.12.023
   Caiani A, 2018, IND CORP CHANGE, V27, P1123, DOI 10.1093/icc/dty016
   Caiani A, 2016, J ECON DYN CONTROL, V69, P375, DOI 10.1016/j.jedc.2016.06.001
   Chen Shu-Heng, 2014, EC OPEN ACCESS OPEN, V8, P1, DOI 10.5018/economics-ejournalja.2014-16
   Chiarella C, 2011, J ECON DYN CONTROL, V35, P1151, DOI 10.1016/j.jedc.2011.02.005
   Ciarli T, 2010, METROECONOMICA, V61, P180, DOI 10.1111/j.1467-999X.2009.04069.x
   Cincotti S, 2010, ECONOMICS-KIEL, V4, DOI 10.5018/economics-ejournal.ja.2010-26
   Daly H., 1995, Journal of Evolutionary Economics, V5, P313, DOI [10.1007/BF01198310, DOI 10.1007/BF01198310]
   Dawid H, 2018, J ECON BEHAV ORGAN, V150, P220, DOI 10.1016/j.jebo.2018.03.015
   Dawid H, 2014, J ECON DYN CONTROL, V44, P54, DOI 10.1016/j.jedc.2014.04.004
   Dawid H, 2012, EVOLUTION, ORGANIZATION AND ECONOMIC BEHAVIOR, P103
   de Gerba, 2017, RATIONALISING IRRATI
   Dorninger C, 2021, ECOL ECON, V179, DOI 10.1016/j.ecolecon.2020.106824
   Dosi G, 2021, IND CORP CHANGE, V30, P1011, DOI 10.1093/icc/dtaa057
   Dosi G, 2019, J ECON DYN CONTROL, V101, P101, DOI 10.1016/j.jedc.2019.02.005
   Dosi G, 2010, J ECON DYN CONTROL, V34, P1748, DOI 10.1016/j.jedc.2010.06.018
   Dudka S, 1997, J ENVIRON QUAL, V26, P590, DOI 10.2134/jeq1997.00472425002600030003x
   Eckstein D., 2019, GLOBAL CLIMATE RISK
   Emmanuel Arghiri., 1972, UNEQUAL EXCHANGE
   Fagiolo G, 2010, J EVOL ECON, V20, P479, DOI 10.1007/s00191-009-0160-x
   Faracik Beata., 2017, Implementation of the UN Guiding Principles on Business and Human Rights European Parliament
   Fischer K., 2021, GLOBALE WARENKETTEN
   Foster JB, 2014, J PEASANT STUD, V41, P199, DOI 10.1080/03066150.2014.889687
   Gaffard JL, 2012, J EVOL ECON, V22, P275, DOI 10.1007/s00191-011-0244-2
   Garcia-Herrero A, 2017, EUROPEAN UNION COMMU
   Gatti DD, 2011, NEW ECON WINDOWS, P1
   Giarracca N., 2014, NEW EXTRACTIVISM POS, P47
   Godley W, 2007, MONETARY ECONOMICS: AN INTEGRATED APPROACH TO CREDIT, MONEY, INCOME, PRODUCTION AND WEALTH, P1
   Gudynas Eduardo., 2009, EXTRACTIVISMO POL TI
   HANAPPI H, 2017, FORUM SOCIAL EC, V2
   Hanappi H., 2019, SCIREA J SOCIOL, V3, P102, DOI DOI 10.2139/SSRN.3364903
   Harvey David., 2006, Spaces of Global Capitalism: Toward a Theory of Uneven Geographical Development
   Herrmann-Pillath C, 2006, J EVOL ECON, V16, P383, DOI 10.1007/s00191-006-0022-8
   Hornborg Alf., 2006, GLOBAL SOCIAL CHANGE, P161
   Hornborg Alf., 2007, Rethinking environmental history: world-system history and global environmental change
   Jorgenson AK, 2006, RURAL SOCIOL, V71, P685, DOI 10.1526/003601106781262016
   Jorgenson AndrewK., 2007, RETHINKING ENV HIST, P273
   Kapeller J., 2016, POLICY IMPLICATIONS, P43
   Kapeller J, 2016, REV SOC ECON, V74, P320, DOI 10.1080/00346764.2016.1168033
   Kapp K.William., 1950, SOCIAL COSTPRIVATE
   KAPP KW, 1970, KYKLOS, V23, P833, DOI 10.1111/j.1467-6435.1970.tb01047.x
   Kingston W, 2000, J EVOL ECON, V10, P83, DOI 10.1007/s001910050007
   Krausmann F, 2017, ANNU REV ENV RESOUR, V42, P647, DOI 10.1146/annurev-environ-102016-060726
   Lamperti F, 2018, ECOL ECON, V150, P315, DOI [10.2139/ssrn.2944328, 10.1016/j.ecolecon.2018.03.023]
   Landesmann MA, 2019, STRUCT CHANGE ECON D, V48, P7, DOI 10.1016/j.strueco.2018.04.001
   Lang M, 2013, TRANSNATIONAL I
   Lawrence KS, 2009, INT J COMP SOCIOL, V50, P335, DOI 10.1177/0020715209105145
   Lee S., 2010, INT C ENV SYS, P1, DOI [10.2514/6.2010-6113,6113, DOI 10.2514/6.2010-6113,6113]
   Lengnick M, 2013, J ECON BEHAV ORGAN, V86, P102, DOI 10.1016/j.jebo.2012.12.021
   Lessenich S., 2019, LIVING WELL OTHER SE
   Lorentz A, 2016, J EVOL ECON, V26, P219, DOI 10.1007/s00191-015-0409-5
   Maechler S, 2022, REV INT POLIT ECON, V29, P624, DOI 10.1080/09692290.2020.1831573
   Maggi G., 1993, J EVOLUTIONARY EC, V3, P109, DOI 10.1007/BF01213829
   Mainwaring, 1993, J EVOLUTIONARY EC, V3, P317, DOI [10.1007/BF01194945, DOI 10.1007/BF01194945]
   Mendelsohn R, 2006, ENVIRON DEV ECON, V11, P159, DOI 10.1017/S1355770X05002755
   Moran DD, 2013, ECOL ECON, V89, P177, DOI 10.1016/j.ecolecon.2013.02.013
   Muradian R, 2001, ECOL ECON, V36, P281, DOI 10.1016/S0921-8009(00)00229-9
   OECD, 2021, Average Annual Wages
   Petrovic M., 2017, Technical Report
   Petrovic M, 2020, J ECON DYN CONTROL, V113, DOI 10.1016/j.jedc.2020.103866
   Rengs B, 2020, J ECON BEHAV ORGAN, V169, P332, DOI 10.1016/j.jebo.2019.11.025
   Rengs B, 2019, J EVOL ECON, V29, P229, DOI 10.1007/s00191-018-0592-2
   Rengs B, 2017, ROUTL ADV HETEROD EC, P193
   Rengs B, 2014, IEEE C COMP INTEL FI, P427, DOI 10.1109/CIFEr.2014.6924105
   Ricci A, 2019, REV RADICAL POL ECON, V51, P225, DOI 10.1177/0486613418773753
   Ricetti L., 2013, Economics: The Open-Access, Open-Assessment E-Journal, V7, P1
   Safarzynska K, 2017, TECHNOL FORECAST SOC, V114, P119, DOI 10.1016/j.techfore.2016.07.033
   Schaffartzik A, 2016, ECOL ECON, V122, P101, DOI 10.1016/j.ecolecon.2015.12.007
   Seppecher P, 2012, MACROECON DYN, V16, P284, DOI 10.1017/S1365100511000447
   Shleifer A, 2004, AM ECON REV, V94, P414, DOI 10.1257/0002828041301498
   Smit Lise., 2020, Study on Due Diligence Requirements Through the Supply Chain
   Suwandi Intan., 2019, VALUE CHAINS NEW EC
   Svampa Maristella., 2013, Beyond Development, P117, DOI [10.20446/JEP-2414-3197-28-3-43, DOI 10.20446/JEP-2414-3197-28-3-43]
   Veltmeyer H., 2014, NEW EXTRACTIVISM POS
   Wallerstein Immanuel., 1983, HISTORICAL CAPITALIS
   Wilensky Uri., 1999, NetLogo
   Wolf S, 2013, ENVIRON MODELL SOFTW, V44, P25, DOI 10.1016/j.envsoft.2012.12.012
NR 81
TC 7
Z9 8
U1 2
U2 35
PU SPRINGER
PI NEW YORK
PA ONE NEW YORK PLAZA, SUITE 4600, NEW YORK, NY, UNITED STATES
SN 0936-9937
EI 1432-1386
J9 J EVOL ECON
JI J. Evol. Econ.
PD JAN
PY 2022
VL 32
IS 1
SI SI
BP 123
EP 173
DI 10.1007/s00191-021-00750-7
EA JAN 2022
PG 51
WC Economics
WE Social Science Citation Index (SSCI)
SC Business & Economics
GA ZR4XN
UT WOS:000742245200001
OA hybrid
DA 2026-06-13
ER

PT J
AU Ramanathan, V
   Xu, YY
   Versaci, A
AF Ramanathan, Veerabhadran
   Xu, Yangyang
   Versaci, Anthony
TI Modelling human-natural systems interactions with implications for
   twenty-first-century warming
SO NATURE SUSTAINABILITY
LA English
DT Article
ID LAND-USE; CLIMATE; CARBON; EQUILIBRIUM; MITIGATION; LINKING
AB Most climate change mitigation actions do not fully incorporate the mutual relations between human and natural systems. This study presents an integrated model for understanding the role of human-natural systems interactions in climate change.
   The redesign of energy and economic systems to stabilize climate change is hindered by the lack of quantitative treatment of the role that human-natural systems interactions play in what society can do to tackle climate change. Here we present an integrated socio-energy-ecologic-climate model framework for understanding the role of human-natural systems interactions in climate change. We focus on constraints on climate stabilization imposed by feedbacks between global warming and societal actions to decarbonize energy use and to scale up atmospheric-carbon extraction. The energy-climate feedbacks are modelled through four warming-dependent response times for societal, policy and technological actions inferred from historical data. We show that a lack of societal response beyond 2030 would result in a warming in excess of 3 degrees C. Speeding up societal response times and technology diffusion times by a factor of two along with a dramatic boost in start-up investment in renewables and atmospheric-carbon extraction technologies and short-lived climate pollutants mitigation by 2030 can stabilize the warming below 1.5 degrees C. The model's analytical framework and the analyses presented here reveal the fundamental importance of factoring in the role of human-natural systems interactions in the transition to zero emissions when formulating and designing robust climate solutions.
C1 [Ramanathan, Veerabhadran; Versaci, Anthony] Univ Calif San Diego, Scripps Inst Oceanog, San Diego, CA 92103 USA.
   [Xu, Yangyang] Texas A&M Univ, Dept Atmospher Sci, Coll Geosci, College Stn, TX 77834 USA.
C3 University of California System; University of California San Diego;
   Scripps Institution of Oceanography; Texas A&M University System; Texas
   A&M University College Station
RP Ramanathan, V (corresponding author), Univ Calif San Diego, Scripps Inst Oceanog, San Diego, CA 92103 USA.; Xu, YY (corresponding author), Texas A&M Univ, Dept Atmospher Sci, Coll Geosci, College Stn, TX 77834 USA.
EM vramanathan@ucsd.edu; yangyang.xu@tamu.edu
RI Ramanathan, Veerabhadran/V-6291-2017; Xu, Yangyang/I-1930-2018
FU Edward A. Frieman Endowed Presidential Chair in Climate Sustainability
   at the University of California at San Diego; National Science
   Foundation [AGS-1841308]
FX V.R. is supported by the Edward A. Frieman Endowed Presidential Chair in
   Climate Sustainability at the University of California at San Diego, and
   Y.X. is supported by the National Science Foundation (Climate and
   Large-Scale Dynamics Program; AGS-1841308).
CR Agarwala M, 2021, NAT SUSTAIN, V4, P81, DOI 10.1038/s41893-020-00618-x
   [Anonymous], 2019, INT EN OUTL 2019
   [Anonymous], 2020, HIST CAT CONV
   [Anonymous], 1987, MONTREAL PROTOCOL SU
   [Anonymous], 1998, KYOTO PROTOCOL UN FR
   [Anonymous], 2020, WORLD EN OUTL
   [Anonymous], 2019, REN 2019 GLOB STAT R
   [Anonymous], 2015, THE PARIS AGREEMENT
   [Anonymous], 2020, GISS SURF TEMP AN GI
   [Anonymous], 2021, ACC DEC US TECHN POL
   [Anonymous], 2017, LIGHT BULB REV
   [Anonymous], 2021, STAT REV WORLD EN
   Arneth A, 2014, NAT CLIM CHANGE, V4, P550, DOI [10.1038/nclimate2250, 10.1038/NCLIMATE2250]
   Arrhenius S., 1896, Philos Mag 5th series, P237, DOI [DOI 10.1080/14786449608620846, 10.1080/14786449608620846]
   Ayres, 1988, SELF ORG BIOL EC
   Banerjee R., 2012, GLOBAL ENERGY ASSESS, P3
   Beckage B, 2018, NAT CLIM CHANGE, V8, P79, DOI 10.1038/s41558-017-0031-7
   Bloomberg M. R., 2016, RISK RETURN INVESTIN
   Bond-Lamberty B, 2014, GEOSCI MODEL DEV, V7, P2545, DOI 10.5194/gmd-7-2545-2014
   Callendar GS, 1938, Q J ROY METEOR SOC, V64, P223, DOI 10.1002/qj.49706427503
   Calvin K, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aac642
   Chen JW, 2020, ATMOSPHERE-BASEL, V11, DOI 10.3390/atmos11010095
   Clarke L, 2014, CLIMATE CHANGE 2014: MITIGATION OF CLIMATE CHANGE, P413
   Collins WD, 2015, GEOSCI MODEL DEV, V8, P2203, DOI 10.5194/gmd-8-2203-2015
   Tàbara JD, 2018, CURR OPIN ENV SUST, V31, P120, DOI 10.1016/j.cosust.2018.01.012
   Davis SJ, 2018, SCIENCE, V360, P1419, DOI 10.1126/science.aas9793
   Dellink R, 2017, GLOBAL ENVIRON CHANG, V42, P200, DOI 10.1016/j.gloenvcha.2015.06.004
   Diao CR, 2021, ATMOS CHEM PHYS, V21, P18499, DOI 10.5194/acp-21-18499-2021
   Flatow I., 2012, 50 YEARS AGO BRIGHT
   Fuss S, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aabf9f
   Hanna R, 2021, NAT COMMUN, V12, DOI 10.1038/s41467-020-20437-0
   HEIDORN KC, 1978, B AM METEOROL SOC, V59, P1589, DOI 10.1175/1520-0477(1978)059<1589:ACOIEI>2.0.CO;2
   Houghton RA, 2017, GLOBAL BIOGEOCHEM CY, V31, P456, DOI 10.1002/2016GB005546
   Jackson RB, 2019, ENVIRON RES LETT, V14, DOI 10.1088/1748-9326/ab57b3
   Janssen M, 1998, ECOL ECON, V26, P43, DOI 10.1016/S0921-8009(97)00062-1
   Keeling R. F., SCRIPPS CO2 PROGRAM
   Lamperti F, 2019, REG ENVIRON CHANGE, V19, P747, DOI 10.1007/s10113-018-1287-9
   Le Quéré C, 2018, EARTH SYST SCI DATA, V10, P2141, DOI 10.5194/essd-10-2141-2018
   Lee SY, 2020, PLOS ONE, V15, DOI 10.1371/journal.pone.0236860
   Lelieveld J, 2019, P NATL ACAD SCI USA, V116, P7192, DOI 10.1073/pnas.1819989116
   Liu J, 2015, SCIENCE, V347, P970, DOI 10.1126/science.aaa3145
   MANABE S, 1967, J ATMOS SCI, V24, P241, DOI 10.1175/1520-0469(1967)024<0241:TEOTAW>2.0.CO;2
   Masson-Delmotte V., 2018, SPEC REP GLOB WARM 1
   MOLINA MJ, 1974, NATURE, V249, P810, DOI 10.1038/249810a0
   Otto IM, 2020, P NATL ACAD SCI USA, V117, P2354, DOI 10.1073/pnas.1900577117
   Peng W, 2021, NATURE, V594, P174, DOI 10.1038/d41586-021-01500-2
   Popp A., 2017, Global Environmental Change, V42, P331, DOI 10.1016/j.gloenvcha.2016.10.002
   RAMANATHAN V, 1975, SCIENCE, V190, P50, DOI 10.1126/science.190.4209.50
   Ramanathan V, 2010, P NATL ACAD SCI USA, V107, P8055, DOI 10.1073/pnas.1002293107
   Ritchie H., 2017, TECHNOLOGY ADOPTION
   Rozenberg J, 2015, ENVIRON RES LETT, V10, DOI 10.1088/1748-9326/10/9/095006
   Sanderson BM, 2017, EARTH SYST DYNAM, V8, P827, DOI 10.5194/esd-8-827-2017
   Shahan, 2014, HIST WIND TURBINES
   SMIC, 1971, IN CLIM MOD REP STUD
   van Vuuren DP, 2017, GLOBAL ENVIRON CHANG, V42, P148, DOI [10.1016/j.gloenvcha.2016.10.009, 10.1016/j.gloenvcha.2016.05.009]
   Warszawski L, 2021, ENVIRON RES LETT, V16, DOI 10.1088/1748-9326/abfeec
   Woodard DL, 2019, P NATL ACAD SCI USA, V116, P759, DOI 10.1073/pnas.1805187115
   Xu YY, 2017, P NATL ACAD SCI USA, V114, P10315, DOI 10.1073/pnas.1618481114
NR 58
TC 24
Z9 26
U1 6
U2 115
PU NATURE PORTFOLIO
PI BERLIN
PA HEIDELBERGER PLATZ 3, BERLIN, 14197, GERMANY
SN 2398-9629
J9 NAT SUSTAIN
JI Nat. Sustain.
PD MAR
PY 2022
VL 5
IS 3
BP 263
EP +
DI 10.1038/s41893-021-00826-z
EA DEC 2021
PG 16
WC Green & Sustainable Science & Technology; Environmental Sciences;
   Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Science & Technology - Other Topics; Environmental Sciences & Ecology
GA ZY9JG
UT WOS:000729644200001
DA 2026-06-13
ER

PT J
AU Donges, JF
   Lucht, W
   Cornell, SE
   Heitzig, J
   Barfuss, W
   Lade, SJ
   Schlüter, M
AF Donges, Jonathan F.
   Lucht, Wolfgang
   Cornell, Sarah E.
   Heitzig, Jobst
   Barfuss, Wolfram
   Lade, Steven J.
   Schluter, Maja
TI Taxonomies for structuring models for World-Earth systems analysis of
   the Anthropocene: subsystems, their interactions and social-ecological
   feedback loops
SO EARTH SYSTEM DYNAMICS
LA English
DT Article
ID PLANETARY BOUNDARIES; OPERATING SPACES; DECISION-MAKING; SUSTAINABLE
   USE; CLIMATE-CHANGE; HUMAN-BEHAVIOR; DYNAMICS; FRAMEWORK; EVOLUTION;
   SCIENCE
AB In the Anthropocene, the social dynamics of human societies have become critical to understanding planetary-scale Earth system dynamics. The conceptual foundations of Earth system modelling have externalised social processes in ways that now hinder progress in understanding Earth resilience and informing governance of global environmental change. New approaches to global modelling of the human World are needed to address these challenges. The current modelling landscape is highly diverse and heterogeneous, ranging from purely biophysical Earth system models, to hybrid macro-economic integrated assessments models, to a plethora of models of socio-cultural dynamics. World-Earth models capable of simulating complex and entangled human-Earth system processes of the Anthropocene are currently not available. They will need to draw on and selectively integrate elements from the diverse range of fields and approaches; thus, future World-Earth modellers require a structured approach to identify, classify, select, combine and critique model components from multiple modelling traditions. Here, we develop taxonomies for ordering the multitude of societal and biophysical subsystems and their interactions. We suggest three taxa for modelled subsystems: (i) biophysical, where dynamics is usually represented by "natural laws" of physics, chemistry or ecology (i.e. the usual components of Earth system models); (ii) socio-cultural, dominated by processes of human behaviour, decision-making and collective social dynamics (e.g. politics, institutions, social networks and even science itself); and (iii) socio-metabolic, dealing with the material interactions of social and biophysical subsystems (e.g. human bodies, natural resources and agriculture). We show how higher-order taxonomies can be derived for classifying and describing the interactions between two or more subsystems. This then allows us to highlight the kinds of social-ecological feedback loops where new modelling efforts need to be directed. As an example, we apply the taxonomy to a stylised World-Earth system model that endogenises the socially transmitted choice of discount rates in a greenhouse gas emissions game to illustrate the effects of social-ecological feedback loops that are usually not considered in current modelling efforts. The proposed taxonomy can contribute to guiding the design and operational development of more comprehensive World-Earth models for understanding Earth resilience and charting sustainability transitions within planetary boundaries and other future trajectories in the Anthropocene.
C1 [Donges, Jonathan F.; Lucht, Wolfgang; Barfuss, Wolfram] Potsdam Inst Climate Impact Res, Earth Syst Anal, Telegrafenberg A31, D-14473 Potsdam, Germany.
   [Donges, Jonathan F.; Lucht, Wolfgang; Heitzig, Jobst; Barfuss, Wolfram] Leibniz Assoc, Telegrafenberg A31, D-14473 Potsdam, Germany.
   [Donges, Jonathan F.; Cornell, Sarah E.; Lade, Steven J.; Schluter, Maja] Stockholm Univ, Stockholm Resilience Ctr, Kraftriket 2B, S-10691 Stockholm, Sweden.
   [Lucht, Wolfgang] Humboldt Univ, Dept Geog, Unter Linden 6, D-10099 Berlin, Germany.
   [Lucht, Wolfgang] Humboldt Univ, Integrat Res Inst Transformat Human Environm Syst, Unter Linden 6, D-10099 Berlin, Germany.
   [Heitzig, Jobst] Potsdam Inst Climate Impact Res, Complex Sci, Telegrafenberg A31, D-14473 Potsdam, Germany.
   [Barfuss, Wolfram] Humboldt Univ, Dept Phys, Newtonstr 15, D-12489 Berlin, Germany.
   [Lade, Steven J.] Australian Natl Univ, Fenner Sch Environm & Soc, Bldg 141,Linnaeus Way, Canberra, ACT 2601, Australia.
   [Lade, Steven J.] Stockholm Univ, Bolin Ctr Climate Res, Geosci Bldg & Frescati Campus Svante Arrhenius Va, S-10691 Stockholm, Sweden.
C3 Potsdam Institut fur Klimafolgenforschung; Stockholm University;
   Humboldt University of Berlin; Humboldt University of Berlin; Potsdam
   Institut fur Klimafolgenforschung; Humboldt University of Berlin;
   Australian National University; Stockholm University
RP Donges, JF (corresponding author), Potsdam Inst Climate Impact Res, Earth Syst Anal, Telegrafenberg A31, D-14473 Potsdam, Germany.; Donges, JF (corresponding author), Leibniz Assoc, Telegrafenberg A31, D-14473 Potsdam, Germany.; Donges, JF (corresponding author), Stockholm Univ, Stockholm Resilience Ctr, Kraftriket 2B, S-10691 Stockholm, Sweden.
EM donges@pik-potsdam.de
RI Heitzig, Jobst/E-8271-2011; Cornell, Sarah Elisabeth/F-7003-2014; Lade,
   Steven/AAH-2699-2019; Schlüter, Maja/C-2374-2015; Lucht,
   Wolfgang/G-2180-2011; Donges, Jonathan/HCI-2311-2022
OI Heitzig, Jobst/0000-0002-0442-8077; Cornell, Sarah
   Elisabeth/0000-0003-4367-1296; Lade, Steven/0000-0001-9719-9826;
   Schlüter, Maja/0000-0002-7780-1039; Lucht, Wolfgang/0000-0002-3398-8575;
   Barfuss, Wolfram/0000-0002-9077-5242; Donges,
   Jonathan/0000-0001-5233-7703
FU Leibniz-Gemeinschaft [SAW-2017-PIK-4]; Stordalen Foundation (Planetary
   Boundary Research Network, PB.net), the Earth League ); BMBF; Swedish
   Research Council Formas [2014-589]; Mistra (core grant to the Stockholm
   Resilience Centre); Heinrich Boll Foundation; European Research Council
   under the European Union [283950]; European Union [682472, 743080];
   European Research Council (ERC) [682472, 283950, 743080] Funding Source:
   European Research Council (ERC)
FX This research has been supported by the Leibniz-Gemeinschaft (grant no.
   SAW-2017-PIK-4), the Stordalen Foundation (Planetary Boundary Research
   Network, PB.net), the Earth League (grant no. EarthDoc programme), the
   BMBF (grant no. project GLUES), the Swedish Research Council Formas
   (grant no. 2014-589), the Mistra (core grant to the Stockholm Resilience
   Centre), the Heinrich Boll Foundation (PhD scholarship), and the
   European Research Council under the European Union's Seventh Framework
   Programme (FP/2007-2013/ERC grant agreement no. 283950 SES-LINK) and the
   European Union's Horizon 2020 Research and Innovation programme (ERC
   grant agreement no. 682472 - MUSES, and ERC grant agreement no. 743080
   ERA). The article processing charges for this open-access publication
   were covered by the Potsdam Institute for Climate Impact Research (PIK).
CR Anderies JM, 2013, ENVIRON RES LETT, V8, DOI 10.1088/1748-9326/8/4/044048
   [Anonymous], 2004, EARTH SYSTEM ANAL SU
   [Anonymous], 2012, SAFE JUST SPACE HUMA, DOI DOI 10.5822/978-1-61091-458-1
   [Anonymous], 1987, OUR COMMON FUTURE, V1
   [Anonymous], 1988, Earth System Science: A Closer View, P22, DOI DOI 10.17226/19088
   [Anonymous], 2005, MILLENNIUM ECOSYSTEM
   Arneth A, 2014, NAT CLIM CHANGE, V4, P550, DOI [10.1038/nclimate2250, 10.1038/NCLIMATE2250]
   Arrow Kenneth J., 2013, Resour. Future Discuss. Pap., DOI [DOI 10.2139/SSRN.2199511, 10.2139/ssrn.2199511]
   Barfuss W, 2020, P NATL ACAD SCI USA, V117, P12915, DOI 10.1073/pnas.1916545117
   Barfuss W, 2018, NAT COMMUN, V9, DOI 10.1038/s41467-018-04738-z
   Barfuss W, 2017, EARTH SYST DYNAM, V8, P255, DOI 10.5194/esd-8-255-2017
   BARRETT S, 1994, OXFORD ECON PAP, V46, P878, DOI 10.1093/oep/46.Supplement_1.878
   [Barros V.R. IPCC. IPCC.], 2014, CONTRIBUTION WORKING
   Beckage B, 2018, NAT CLIM CHANGE, V8, P79, DOI 10.1038/s41558-017-0031-7
   Biénabe E, 2006, FOREST POLICY ECON, V9, P335, DOI 10.1016/j.forpol.2005.10.002
   Biggs R, 2012, ANNU REV ENV RESOUR, V37, P421, DOI 10.1146/annurev-environ-051211-123836
   Boysen LR, 2017, GLOBAL CHANGE BIOL, V23, P4303, DOI 10.1111/gcb.13745
   Brondizio ES, 2016, GLOBAL ENVIRON CHANG, V39, P318, DOI 10.1016/j.gloenvcha.2016.02.006
   Brugger J, 2017, GEOPHYS RES LETT, V44, P419, DOI 10.1002/2016GL072241
   Budyko M.I., 1987, History of the Earths Atmosphere
   Calder M, 2018, ROY SOC OPEN SCI, V5, DOI 10.1098/rsos.172096
   Calvin K, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aac642
   Caminade C, 2014, P NATL ACAD SCI USA, V111, P3286, DOI 10.1073/pnas.1302089111
   Castellano C, 2009, REV MOD PHYS, V81, P591, DOI 10.1103/RevModPhys.81.591
   CHARNEY J, 1977, J ATMOS SCI, V34, P1366, DOI 10.1175/1520-0469(1977)034<1366:ACSOTE>2.0.CO;2
   Colding J, 2001, ECOL APPL, V11, P584
   Crutzen PJ, 2002, NATURE, V415, P23, DOI 10.1038/415023a
   Cumming GS, 2017, TRENDS ECOL EVOL, V32, P695, DOI 10.1016/j.tree.2017.06.014
   Dearing JA, 2014, GLOBAL ENVIRON CHANG, V28, P227, DOI 10.1016/j.gloenvcha.2014.06.012
   Di Baldassarre G, 2017, EARTH SYST DYNAM, V8, P1, DOI 10.5194/esd-8-225-2017
   Donges JF, 2015, CLIM PAST, V11, P709, DOI 10.5194/cp-11-709-2015
   Donges JF, 2020, EARTH SYST DYNAM, V11, P395, DOI 10.5194/esd-11-395-2020
   Donges JF, 2017, ANTHROPOCENE REV, V4, P151, DOI 10.1177/2053019617725537
   Donges JF, 2017, ANTHROPOCENE REV, V4, P23, DOI 10.1177/2053019616676608
   Farmer JD, 2009, NATURE, V460, P685, DOI 10.1038/460685a
   Fischer-Kowalski M., 2017, PERSPECTIVES IND ECO, P35
   Fischer-Kowalski M., 1998, J IND ECOL, V2, P107, DOI DOI 10.1162/JIEC.1998.2.4.107
   Fischer-Kowalski M, 2006, MITT OSTERR GEOGR G, V148, P33
   Fischer‐Kowalski M., 1993, Innovation: The European Journal of Social Science Research, V6, P415, DOI [10.1080/13511610.1993.9968370, DOI 10.1080/13511610.1993.9968370]
   Flato GM, 2011, WIRES CLIM CHANGE, V2, P783, DOI 10.1002/wcc.148
   Folke C, 2006, GLOBAL ENVIRON CHANG, V16, P253, DOI 10.1016/j.gloenvcha.2006.04.002
   Folke C, 2016, ECOL SOC, V21, DOI 10.5751/ES-08748-210341
   Folke C, 2011, AMBIO, V40, P719, DOI 10.1007/s13280-011-0184-y
   Gabriel Markus., 2013, Warum es die Welt nicht gibt
   Gaines SD, 2010, P NATL ACAD SCI USA, V107, P18286, DOI 10.1073/pnas.0906473107
   Ganopolski A, 2016, NATURE, V529, P200, DOI 10.1038/nature16494
   Garrett TJ, 2015, EARTH SYST DYNAM, V6, P673, DOI 10.5194/esd-6-673-2015
   Geier F, 2019, EUR PHYS J-SPEC TOP, V228, P2357, DOI 10.1140/epjst/e2019-900120-4
   Gerten D, 2018, EARTH SYST DYNAM, V9, P849, DOI 10.5194/esd-9-849-2018
   Gregory JM, 2009, J CLIMATE, V22, P5232, DOI 10.1175/2009JCLI2949.1
   Haff PK, 2012, EARTH SYST DYNAM, V3, P149, DOI 10.5194/esd-3-149-2012
   Haff P, 2014, ANTHROPOCENE REV, V1, P126, DOI 10.1177/2053019614530575
   Hamilton C, 2015, ANTHROPOCENE REV, V2, P102, DOI 10.1177/2053019615584974
   Harfoot MBJ, 2014, PLOS BIOL, V12, DOI 10.1371/journal.pbio.1001841
   Heck V, 2016, EARTH SYST DYNAM, V7, P783, DOI 10.5194/esd-7-783-2016
   Heitzig J, 2016, EARTH SYST DYNAM, V7, P21, DOI 10.5194/esd-7-21-2016
   Heitzig J, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10061947
   Herrmann-Pillath C, 2020, ECOL ECON, V169, DOI 10.1016/j.ecolecon.2019.106526
   Herrmann-Pillath C, 2018, ECOL ECON, V149, P212, DOI 10.1016/j.ecolecon.2018.03.024
   Jarvis AJ, 2015, EARTH SYST DYNAM, V6, P689, DOI 10.5194/esd-6-689-2015
   Jax K, 2013, ECOL ECON, V93, P260, DOI 10.1016/j.ecolecon.2013.06.008
   Jdonges, 2021, Zenodo, DOI 10.5281/ZENODO.4704936
   Jentoft S, 2007, HUM ECOL, V35, P611, DOI 10.1007/s10745-007-9125-6
   Kates RW, 2001, SCIENCE, V292, P641, DOI 10.1126/science.1059386
   Kellie-Smith O, 2011, PHILOS T R SOC A, V369, P868, DOI 10.1098/rsta.2010.0305
   Keys PW, 2018, EARTH SYST DYNAM, V9, P829, DOI 10.5194/esd-9-829-2018
   Kleidon A., 2016, Thermodynamic Foundations of the Earth System
   Lade SJ, 2018, EARTH SYST DYNAM, V9, P507, DOI 10.5194/esd-9-507-2018
   Lade SJ, 2017, SCI ADV, V3, DOI 10.1126/sciadv.1603043
   Lade SJ, 2015, P NATL ACAD SCI USA, V112, P11120, DOI 10.1073/pnas.1504954112
   Latour Bruno., 2017, FACING GAIA 8 LECT N, V1st
   Lenton TM, 2018, SCIENCE, V361, P1066, DOI 10.1126/science.aau0427
   Lenton TM, 2016, EARTH SYST DYNAM, V7, P353, DOI 10.5194/esd-7-353-2016
   Lenton TM, 2004, NATURE, V431, P913, DOI 10.1038/431913a
   Leontief WW, 1936, REV ECON STATISTICS, V18, P105, DOI 10.2307/1927837
   Lewis SL, 2015, NATURE, V519, P171, DOI 10.1038/nature14258
   Lewis-Beck MS, 2013, ELECT STUD, V32, P489, DOI 10.1016/j.electstud.2013.05.023
   LOVELOCK JE, 1974, TELLUS, V26, P2, DOI 10.1111/j.2153-3490.1974.tb01946.x
   LOVELOCK JE, 1989, REV GEOPHYS, V27, P215, DOI 10.1029/RG027i002p00215
   Lutz W, 2008, DEMOGRAPHIC CHANGE AND INTERGENERATIONAL JUSTICE, P3, DOI 10.1007/978-3-540-77084-8
   Martin R, 2015, FRONT ENV SCI-SWITZ, V3, DOI 10.3389/fenvs.2015.00066
   Masson-Delmotte V., 2018, IPCC SPECIAL REPORT, V1, P1, DOI [10.1017/9781009157926.005, DOI 10.1017/9781009157926.005]
   Masterson VA, 2017, ECOL SOC, V22, DOI 10.5751/ES-08872-220149
   Mengel M, 2018, NAT COMMUN, V9, DOI 10.1038/s41467-018-02985-8
   Milo R, 2002, SCIENCE, V298, P824, DOI 10.1126/science.298.5594.824
   Mooney HA, 2013, P NATL ACAD SCI USA, V110, P3665, DOI 10.1073/pnas.1107484110
   Morton T., 2014, Hyperobjects: Philosophy and Ecology After the End of the World
   Müller-Hansen F, 2017, EARTH SYST DYNAM, V8, P977, DOI 10.5194/esd-8-977-2017
   National Research Council:, 1986, Earth System Science: Overview: A Program for Global Change, DOI DOI 10.17226/19210
   National Research Council:, 2007, Models in environmental regulatory decision making, DOI [10.17226/11972, DOI 10.17226/11972]
   Nelson Gerald C, 2014, Proc Natl Acad Sci U S A, V111, P3274, DOI 10.1073/pnas.1222465110
   Nitzbon J, 2017, ENVIRON RES LETT, V12, DOI 10.1088/1748-9326/aa7581
   NORDHAUS WD, 1992, SCIENCE, V258, P1315, DOI 10.1126/science.258.5086.1315
   Nordhaus WD, 2017, P NATL ACAD SCI USA, V114, P1518, DOI 10.1073/pnas.1609244114
   Ostrom E, 2007, P NATL ACAD SCI USA, V104, P15176, DOI 10.1073/pnas.0701886104
   Ostrom E, 2009, SCIENCE, V325, P419, DOI 10.1126/science.1172133
   Otto C, 2017, J ECON DYN CONTROL, V83, P232, DOI 10.1016/j.jedc.2017.08.001
   Otto IM, 2020, P NATL ACAD SCI USA, V117, P2354, DOI 10.1073/pnas.1900577117
   Otto IM, 2020, ECOL ECON, V167, DOI 10.1016/j.ecolecon.2019.106463
   Perman Roger., 2011, NATURAL RESOURCE ENV, V4th
   Phalan BT, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10061760
   Purves D, 2013, NATURE, V493, P295, DOI 10.1038/493295a
   Reichler T, 2008, B AM METEOROL SOC, V89, P303, DOI 10.1175/BAMS-89-3-303
   Renn J., 2018, HOST J HIST SCI TECH, V12, P1
   Robinson DT, 2018, EARTH SYST DYNAM, V9, P895, DOI 10.5194/esd-9-895-2018
   Rocha JC, 2015, PLOS ONE, V10, DOI 10.1371/journal.pone.0134639
   Rockström J, 2017, SCIENCE, V355, P1269, DOI 10.1126/science.aah3443
   Rockström J, 2009, NATURE, V461, P472, DOI 10.1038/461472a
   Rounsevell MDA, 2014, EARTH SYST DYNAM, V5, P117, DOI 10.5194/esd-5-117-2014
   Schellnhuber HJ, 1998, EARTH SYSTEMS ANALYSIS, P3
   Schellnhuber HJ, 1999, NATURE, V402, pC19, DOI 10.1038/35011515
   Schill C, 2019, NAT SUSTAIN, V2, P1075, DOI 10.1038/s41893-019-0419-7
   Schlüter M, 2012, NAT RESOUR MODEL, V25, P219, DOI 10.1111/j.1939-7445.2011.00108.x
   Schlüter M, 2017, ECOL ECON, V131, P21, DOI 10.1016/j.ecolecon.2016.08.008
   Schneider StephenH., 2004, Scientists debate Gaia: The next century
   Seitzinger SP, 2015, ANTHROPOCENE, V12, P3, DOI 10.1016/j.ancene.2016.01.001
   Sitch S, 2003, GLOBAL CHANGE BIOL, V9, P161, DOI 10.1046/j.1365-2486.2003.00569.x
   Steffen W, 2007, AMBIO, V36, P614, DOI 10.1579/0044-7447(2007)36[614:TAAHNO]2.0.CO;2
   Steffen W, 2020, NAT REV EARTH ENV, V1, P54, DOI 10.1038/s43017-019-0005-6
   Steffen W, 2018, P NATL ACAD SCI USA, V115, P8252, DOI 10.1073/pnas.1810141115
   Steffen W, 2015, SCIENCE, V347, DOI 10.1126/science.1259855
   Stocker T., 2014, Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, DOI [10.1017/cbo9781107415324, 10.1017/CBO9781107415324, DOI 10.1017/CBO9781107415324]
   Stocker TF, 2014, CLIMATE CHANGE 2013: THE PHYSICAL SCIENCE BASIS, P1, DOI 10.1017/cbo9781107415324
   Strnad FM, 2019, CHAOS, V29, DOI 10.1063/1.5124673
   Taylor KE, 2012, B AM METEOROL SOC, V93, P485, DOI 10.1175/BAMS-D-11-00094.1
   Traulsen A, 2010, P NATL ACAD SCI USA, V107, P2962, DOI 10.1073/pnas.0912515107
   Turchin P, 2008, NATURE, V454, P34, DOI 10.1038/454034a
   van Vuuren DP, 2016, EARTH SYST DYNAM, V7, P267, DOI 10.5194/esd-7-267-2016
   van Vuuren DP, 2012, ENVIRON RES LETT, V7, DOI 10.1088/1748-9326/7/2/024012
   VANDIJK J, 1991, J FRANKLIN I, V328, P959, DOI 10.1016/0016-0032(91)90064-A
   Vaughan NE, 2011, CLIMATIC CHANGE, V109, P745, DOI 10.1007/s10584-011-0027-7
   Verburg PH, 2016, GLOBAL ENVIRON CHANG, V39, P328, DOI 10.1016/j.gloenvcha.2015.08.007
   Vernadsky Vladimir., 1986, BIOSPHERE
   Waters C.N., 2016, SCIENCE, V351, DOI DOI 10.1126/science.aad2622
   Watson AJ, 2008, ASTROBIOLOGY, V8, P175, DOI 10.1089/ast.2006.0115
   Weiss H, 2001, SCIENCE, V291, P609, DOI 10.1126/science.1058775
   Wiedermann M, 2015, PHYS REV E, V91, DOI 10.1103/PhysRevE.91.052801
   Williamson OE, 1998, ECONOMIST-NETHERLAND, V146, P23, DOI 10.1023/A:1003263908567
   Winkelmann R, 2015, SCI ADV, V1, DOI 10.1126/sciadv.1500589
   Woroniecki S, 2020, GLOBAL ENVIRON CHANG, V65, DOI 10.1016/j.gloenvcha.2020.102132
   Yearworth M, 2016, SYST RES BEHAV SCI, V33, P45, DOI 10.1002/sres.2315
   Zalasiewicz J, 2017, NEWSL STRATIGR, V50, P205, DOI 10.1127/nos/2017/0385
   Zeebe RE, 2013, PHILOS T R SOC A, V371, DOI 10.1098/rsta.2012.0006
NR 143
TC 26
Z9 28
U1 1
U2 37
PU COPERNICUS GESELLSCHAFT MBH
PI GOTTINGEN
PA BAHNHOFSALLEE 1E, GOTTINGEN, 37081, GERMANY
SN 2190-4979
EI 2190-4987
J9 EARTH SYST DYNAM
JI Earth Syst. Dynam.
PD NOV 12
PY 2021
VL 12
IS 4
BP 1115
EP 1137
DI 10.5194/esd-12-1115-2021
PG 23
WC Geosciences, Multidisciplinary
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Geology
GA WZ7BW
UT WOS:000720120500001
OA Green Submitted, gold
DA 2026-06-13
ER

PT J
AU Donges, JF
   Heitzig, J
   Barfuss, W
   Wiedermann, M
   Kassel, JA
   Kittel, T
   Kolb, JJ
   Kolster, T
   Müller-Hansen, F
   Otto, IM
   Zimmerer, KB
   Lucht, W
AF Donges, Jonathan F.
   Heitzig, Jobst
   Barfuss, Wolfram
   Wiedermann, Marc
   Kassel, Johannes A.
   Kittel, Tim
   Kolb, Jakob J.
   Kolster, Till
   Mueller-Hansen, Finn
   Otto, Ilona M.
   Zimmerer, Kilian B.
   Lucht, Wolfgang
TI Earth system modeling with endogenous and dynamic human societies: the
   copan:CORE open World-Earth modeling framework
SO EARTH SYSTEM DYNAMICS
LA English
DT Article
ID SOCIAL-ECOLOGICAL SYSTEMS; TIPPING POINTS; PLANETARY BOUNDARIES;
   DECISION-MAKING; SUSTAINABLE USE; CLIMATE-CHANGE; HUMAN-BEHAVIOR;
   ANTHROPOCENE; ENVIRONMENT; TECHNOLOGY
AB Analysis of Earth system dynamics in the Anthropocene requires explicitly taking into account the increasing magnitude of processes operating in human societies, their cultures, economies and technosphere and their growing feedback entanglement with those in the physical, chemical and biological systems of the planet. However, current state-of-the-art Earth system models do not represent dynamic human societies and their feedback interactions with the biogeophysical Earth system and macroeconomic integrated assessment models typically do so only with limited scope. This paper (i) proposes design principles for constructing world-Earth models (WEMs) for Earth system analysis of the Anthropocene, i.e., models of social (world)-ecological (Earth) coevolution on up to planetary scales, and (ii) presents the copan:CORE open simulation modeling framework for developing, composing and analyzing such WEMs based on the proposed principles. The framework provides a modular structure to flexibly construct and study WEMs. These can contain biophysical (e.g., carbon cycle dynamics), socio-metabolic or economic (e.g., economic growth or energy system changes), and sociocultural processes (e.g., voting on climate policies or changing social norms) and their feedback interactions, and they are based on elementary entity types, e.g., grid cells and social systems. Thereby, copan:CORE enables the epistemic flexibility needed for contributions towards Earth system analysis of the Anthropocene given the large diversity of competing theories and methodologies used for describing socio-metabolic or economic and sociocultural processes in the Earth system by various fields and schools of thought. To illustrate the capabilities of the framework, we present an exemplary and highly stylized WEM implemented in copan:CORE that illustrates how endogenizing sociocultural processes and feedbacks such as voting on climate policies based on socially learned environmental awareness could fundamentally change macroscopic model outcomes.
C1 [Donges, Jonathan F.; Heitzig, Jobst; Barfuss, Wolfram; Wiedermann, Marc; Kassel, Johannes A.; Kolb, Jakob J.; Kolster, Till; Mueller-Hansen, Finn; Otto, Ilona M.; Zimmerer, Kilian B.; Lucht, Wolfgang] Leibniz Assoc, Potsdam Inst Climate Impact Res, Earth Syst Anal & Complex Sci, Telegrafenberg A31, Potsdam 14473, Germany.
   [Donges, Jonathan F.] Stockholm Univ, Stockholm Resilience Ctr, Kraftriket 2B, Stockholm 11419, Sweden.
   [Barfuss, Wolfram; Kittel, Tim; Kolb, Jakob J.; Kolster, Till] Humboldt Univ, Dept Phys, Newtonstr 15, Berlin 12489, Germany.
   [Kassel, Johannes A.] Max Planck Inst Phys Komplexer Syst, Nothnitzer Str 38, Dresden 01187, Germany.
   [Mueller-Hansen, Finn] Mercator Res Inst Global Commons & Climate Change, EUREF Campus 19,Torgauer Str 12-15, Berlin 10829, Germany.
   [Zimmerer, Kilian B.] Heidelberg Univ, Dept Phys & Astron, Neuenheimer Feld 226, Heidelberg 69120, Germany.
   [Lucht, Wolfgang] Humboldt Univ, Dept Geog, Unter Linden 6, Berlin 10099, Germany.
   [Lucht, Wolfgang] Humboldt Univ, Integrat Res Inst Transformat Human Environm Syst, Unter Linden 6, Berlin 10099, Germany.
C3 Potsdam Institut fur Klimafolgenforschung; Stockholm University;
   Humboldt University of Berlin; Max Planck Society; Ruprecht Karls
   University Heidelberg; Humboldt University of Berlin; Humboldt
   University of Berlin
RP Donges, JF; Heitzig, J (corresponding author), Leibniz Assoc, Potsdam Inst Climate Impact Res, Earth Syst Anal & Complex Sci, Telegrafenberg A31, Potsdam 14473, Germany.; Donges, JF (corresponding author), Stockholm Univ, Stockholm Resilience Ctr, Kraftriket 2B, Stockholm 11419, Sweden.
EM donges@pik-potsdam.de; heitzig@pik-potsdam.de
RI Otto, Ilona Magdalena/GNP-4425-2022; Lucht, Wolfgang/G-2180-2011;
   Heitzig, Jobst/E-8271-2011; Donges, Jonathan/HCI-2311-2022;
   Müller-Hansen, Finn/MTD-0804-2025
OI Lucht, Wolfgang/0000-0002-3398-8575; Kolster, Till/0000-0002-6409-8882;
   Kassel, Johannes Aian/0000-0002-9608-0089; Barfuss,
   Wolfram/0000-0002-9077-5242; Heitzig, Jobst/0000-0002-0442-8077; Donges,
   Jonathan/0000-0001-5233-7703; Müller-Hansen, Finn/0000-0002-0425-1996
FU Stordalen Foundation via the Planetary Boundary Research Network
   (PB.net); Earth League's EarthDoc program; Leibniz Association; European
   Research Council (ERC advanced grant project ERA); German Federal
   Ministry of Education and Research (BMBF, project CoNDyNet); Heinrich
   Boll Foundation; Foundation of German Business; Episcopal Scholarship
   Foundation Cusanuswerk; DFG/FAPESP [IRTG 1740/TRP 2015/50122-0];
   European Regional Development Fund; BMBF; Land Brandenburg; Fundacao de
   Amparo a Pesquisa do Estado de Sao Paulo (FAPESP) [15/50122-0] Funding
   Source: FAPESP
FX This work has been carried out within the framework of PIK's flagship
   project on Coevolutionary Pathways in the Earth system (copan,
   https://www.pik-potsdam.de/research/projects/activities/copan/copan-intr
   oduction, last access: 1 April 2020). We are grateful for financial
   support by the Stordalen Foundation via the Planetary Boundary Research
   Network (PB.net), the Earth League's EarthDoc program, the Leibniz
   Association (project DominoES), the European Research Council (ERC
   advanced grant project ERA), and the German Federal Ministry of
   Education and Research (BMBF, project CoNDyNet). We acknowledge
   additional support by the Heinrich Boll Foundation (WB), the Foundation
   of German Business (JJK), the Episcopal Scholarship Foundation
   Cusanuswerk (JK) and DFG/FAPESP (IRTG 1740/TRP 2015/50122-0, FMH). The
   European Regional Development Fund, BMBF and the Land Brandenburg
   supported this project by providing resources on the high-performance
   computer system at the Potsdam Institute for Climate Impact Research. We
   thank the participants of the three LOOPS workshops
   (https://www.pik-potsdam.de/research/projects/activities/copan/loops/loo
   ps-workshop-series, last access: 1 April 2020) in Kloster Chorin (2014),
   Southampton (2015) and Potsdam (2017) for discussions that provided
   highly valuable in-sights for conceptualizing world-Earth modeling and
   the development of the copan:CORE open simulation modeling framework.
CR Alexander LV, 2014, CLIMATE CHANGE 2013: THE PHYSICAL SCIENCE BASIS, P3
   Anderies JM, 2013, ENVIRON RES LETT, V8, DOI 10.1088/1748-9326/8/4/044048
   Anderies JM, 2019, P NATL ACAD SCI USA, V116, P5277, DOI 10.1073/pnas.1802885115
   [Anonymous], 2014, FUT EARTH FUT EARTH
   [Anonymous], 2012, SAFE JUST SPACE HUMA, DOI DOI 10.5822/978-1-61091-458-1
   [Anonymous], 1972, LIMITS GROWTH
   Arneth A, 2014, NAT CLIM CHANGE, V4, P550, DOI [10.1038/nclimate2250, 10.1038/NCLIMATE2250]
   Auer S, 2015, SCI REP-UK, V5, DOI 10.1038/srep13386
   Barfuss W, 2018, NAT COMMUN, V9, DOI 10.1038/s41467-018-04738-z
   Barfuss W, 2017, EARTH SYST DYNAM, V8, P255, DOI 10.5194/esd-8-255-2017
   Barton M., 2019, OPEN MODELING FDN OP
   Beckage B, 2018, NAT CLIM CHANGE, V8, P79, DOI 10.1038/s41558-017-0031-7
   Berkes F, 2000, LINKING SOCIAL ECOLO
   Betts R.K., 2017, Conflict after the Cold War: arguments on causes of war and peace
   Bierstedt R., 1963, The social order, V2nd
   Cai YY, 2016, NAT CLIM CHANGE, V6, P520, DOI [10.1038/nclimate2964, 10.1038/NCLIMATE2964]
   Calvin K, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aac642
   Cash DW, 2006, ECOL SOC, V11
   Castellano C, 2009, REV MOD PHYS, V81, P591, DOI 10.1103/RevModPhys.81.591
   Crutzen PJ, 2002, NATURE, V415, P23, DOI 10.1038/415023a
   Cumming GS, 2017, TRENDS ECOL EVOL, V32, P695, DOI 10.1016/j.tree.2017.06.014
   Tàbara JD, 2018, CURR OPIN ENV SUST, V31, P120, DOI 10.1016/j.cosust.2018.01.012
   Dermody BJ, 2018, EARTH SYST DYNAM, V9, P103, DOI 10.5194/esd-9-103-2018
   Di Baldassarre G, 2017, EARTH SYST DYNAM, V8, P1, DOI 10.5194/esd-8-225-2017
   Donges J. F., 2018, EARTH SYSTEM DYNAMIC, DOI [10.5194/esd-2018-27, DOI 10.5194/ESD-2018-27]
   Donges JF, 2017, ANTHROPOCENE REV, V4, P151, DOI 10.1177/2053019617725537
   Donges JF, 2017, ANTHROPOCENE REV, V4, P23, DOI 10.1177/2053019616676608
   Donges JF, 2017, GAIA, V26, P182, DOI 10.14512/gaia.26.S1.5
   Edenhofer O., 2015, OXFORD HDB MACROECON
   Eyring V, 2016, GEOSCI MODEL DEV, V9, P1937, DOI 10.5194/gmd-9-1937-2016
   Farmer JD, 2019, SCIENCE, V364, P132, DOI 10.1126/science.aaw7287
   Farmer JD, 2015, ENVIRON RESOUR ECON, V62, P329, DOI 10.1007/s10640-015-9965-2
   Farmer JD, 2009, NATURE, V460, P685, DOI 10.1038/460685a
   Fischer-Kowalski M., 1997, The International Handbook of Environmental Sociology
   Foley AM, 2016, EARTH SYST DYNAM, V7, P119, DOI 10.5194/esd-7-119-2016
   Folke C, 2006, GLOBAL ENVIRON CHANG, V16, P253, DOI 10.1016/j.gloenvcha.2006.04.002
   Gaffney O, 2017, ANTHROPOCENE REV, V4, P53, DOI 10.1177/2053019616688022
   Garrett TJ, 2014, EARTHS FUTURE, V2, P127, DOI 10.1002/2013EF000171
   Geier F, 2019, EUR PHYS J-SPEC TOP, V228, P2357, DOI 10.1140/epjst/e2019-900120-4
   Gerten D, 2018, EARTH SYST DYNAM, V9, P849, DOI 10.5194/esd-9-849-2018
   Gross T, 2008, J R SOC INTERFACE, V5, P259, DOI 10.1098/rsif.2007.1229
   Haff PK, 2012, EARTH SYST DYNAM, V3, P149, DOI 10.5194/esd-3-149-2012
   Haff P, 2014, ANTHROPOCENE REV, V1, P126, DOI 10.1177/2053019614530575
   Heck V, 2016, EARTH SYST DYNAM, V7, P783, DOI 10.5194/esd-7-783-2016
   Heitzig J, 2016, EARTH SYST DYNAM, V7, P21, DOI 10.5194/esd-7-21-2016
   Heitzig J, 2018, NAT CLIM CHANGE, V8, P204, DOI 10.1038/s41558-018-0079-z
   Helbing D, 2012, EUR PHYS J-SPEC TOP, V214, P11, DOI 10.1140/epjst/e2012-01686-y
   Hewitt RJ, 2019, FRONT ENERGY RES, V7, DOI 10.3389/fenrg.2019.00031
   HOLLEY RA, 1975, ANN PROBAB, V3, P643, DOI 10.1214/aop/1176996306
   Jager W, 2000, ECOL ECON, V35, P357, DOI 10.1016/S0921-8009(00)00220-2
   Janssen M, 1998, ECOL ECON, V26, P43, DOI 10.1016/S0921-8009(97)00062-1
   Janssen M., 2002, COMPLEXITY ECOSYSTEM
   Kellie-Smith O, 2011, PHILOS T R SOC A, V369, P868, DOI 10.1098/rsta.2010.0305
   Keys PW, 2018, EARTH SYST DYNAM, V9, P829, DOI 10.5194/esd-9-829-2018
   Kittel T., 2017, ARXIV170604542
   Kopp RE, 2016, EARTHS FUTURE, V4, P346, DOI 10.1002/2016EF000362
   Kriegler E, 2009, P NATL ACAD SCI USA, V106, P5041, DOI 10.1073/pnas.0809117106
   Lade SJ, 2018, EARTH SYST DYNAM, V9, P507, DOI 10.5194/esd-9-507-2018
   Lenton T., 2011, Revolutions That Made The Earth
   Lenton TM, 2008, P NATL ACAD SCI USA, V105, P1786, DOI 10.1073/pnas.0705414105
   Lenton TM, 2019, NATURE, V575, P592, DOI 10.1038/d41586-019-03595-0
   Lenton TM, 2018, SCIENCE, V361, P1066, DOI 10.1126/science.aau0427
   Lenton TM, 2016, EARTH SYST DYNAM, V7, P353, DOI 10.5194/esd-7-353-2016
   Lippe M, 2019, GEOINFORMATICA, V23, P269, DOI 10.1007/s10707-018-00337-8
   Liu JG, 2007, SCIENCE, V317, P1513, DOI 10.1126/science.1144004
   Lucht W., 2004, MENTAL COMPONENT EAR, P341
   Martinez-Alier Joan., 2009, CAPITALISM NATURE SO, V20, P58, DOI DOI 10.1080/10455750902727378
   Masson-Delmotte V., 2018, IPCC SPECIAL REPORT, V1, P1, DOI [10.1017/9781009157926.005, DOI 10.1017/9781009157926.005]
   Menck PJ, 2013, NAT PHYS, V9, P89, DOI 10.1038/nphys2516
   Milkoreit M, 2018, ENVIRON RES LETT, V13, DOI 10.1088/1748-9326/aaaa75
   Motesharrei S, 2014, ECOL ECON, V101, P90, DOI 10.1016/j.ecolecon.2014.02.014
   Müller-Hansen F, 2017, EARTH SYST DYNAM, V8, P977, DOI 10.5194/esd-8-977-2017
   Nagy B, 2013, PLOS ONE, V8, DOI 10.1371/journal.pone.0052669
   Nitzbon J, 2017, ENVIRON RES LETT, V12, DOI 10.1088/1748-9326/aa7581
   Nyborg K, 2016, SCIENCE, V354, P42, DOI 10.1126/science.aaf8317
   O'Neill BC, 2017, GLOBAL ENVIRON CHANG, V42, P169, DOI 10.1016/j.gloenvcha.2015.01.004
   O'Neill DW, 2018, NAT SUSTAIN, V1, P88, DOI 10.1038/s41893-018-0021-4
   Ostrom E., 2015, Governing the Commons: the Evolution of Institutions for Collective Action
   Otto IM, 2020, P NATL ACAD SCI USA, V117, P2354, DOI 10.1073/pnas.1900577117
   Otto IM, 2020, ECOL ECON, V167, DOI 10.1016/j.ecolecon.2019.106463
   Otto IM, 2019, NAT CLIM CHANGE, V9, P82, DOI 10.1038/s41558-019-0402-3
   Otto IM, 2017, REG ENVIRON CHANGE, V17, P1651, DOI 10.1007/s10113-017-1105-9
   Otto IM, 2015, NAT CLIM CHANGE, V5, P503, DOI 10.1038/nclimate2593
   Ringsmuth AK, 2019, P ROY SOC B-BIOL SCI, V286, DOI 10.1098/rspb.2019.1943
   Robinson DT, 2018, EARTH SYST DYNAM, V9, P895, DOI 10.5194/esd-9-895-2018
   Rockström J, 2014, EARTHS FUTURE, V2, P606, DOI 10.1002/2014EF000280
   Rockström J, 2009, NATURE, V461, P472, DOI 10.1038/461472a
   Rounsevell MDA, 2014, EARTH SYST DYNAM, V5, P117, DOI 10.5194/esd-5-117-2014
   Schellnhuber HJ, 2016, HEXAG SER HUM ENVIRO, V10, P267, DOI 10.1007/978-3-319-43884-9_11
   Schellnhuber HJ, 2016, NAT CLIM CHANGE, V6, P649, DOI 10.1038/nclimate3013
   Schellnhuber HJ, 1998, EARTH SYSTEMS ANALYSIS, P3
   Schellnhuber HJ, 1999, NATURE, V402, pC19, DOI 10.1038/35011515
   Schill C, 2019, NAT SUSTAIN, V2, P1075, DOI 10.1038/s41893-019-0419-7
   Schlüter M, 2012, NAT RESOUR MODEL, V25, P219, DOI 10.1111/j.1939-7445.2011.00108.x
   Schlüter M, 2017, ECOL ECON, V131, P21, DOI 10.1016/j.ecolecon.2016.08.008
   Snijders TAB, 2010, SOC NETWORKS, V32, P44, DOI 10.1016/j.socnet.2009.02.004
   Steffen W, 2007, AMBIO, V36, P614, DOI 10.1579/0044-7447(2007)36[614:TAAHNO]2.0.CO;2
   Steffen W, 2018, P NATL ACAD SCI USA, V115, P8252, DOI 10.1073/pnas.1810141115
   Steffen W, 2015, SCIENCE, V347, DOI 10.1126/science.1259855
   van Kan A, 2016, PHYS REV E, V93, DOI 10.1103/PhysRevE.93.042205
   van Vuuren DP, 2016, EARTH SYST DYNAM, V7, P267, DOI 10.5194/esd-7-267-2016
   van Vuuren DP, 2012, ENVIRON RES LETT, V7, DOI 10.1088/1748-9326/7/2/024012
   Verburg PH, 2016, GLOBAL ENVIRON CHANG, V39, P328, DOI 10.1016/j.gloenvcha.2015.08.007
   Wiedermann M., 2019, ARXIV191110063PHYSIC
   Wiedermann M, 2015, PHYS REV E, V91, DOI 10.1103/PhysRevE.91.052801
   Willett W, 2019, LANCET, V393, P447, DOI 10.1016/S0140-6736(18)31788-4
   Williamson OE, 1998, ECONOMIST-NETHERLAND, V146, P23, DOI 10.1023/A:1003263908567
NR 107
TC 41
Z9 48
U1 0
U2 26
PU COPERNICUS GESELLSCHAFT MBH
PI GOTTINGEN
PA BAHNHOFSALLEE 1E, GOTTINGEN, 37081, GERMANY
SN 2190-4979
EI 2190-4987
J9 EARTH SYST DYNAM
JI Earth Syst. Dynam.
PD MAY 4
PY 2020
VL 11
IS 2
BP 395
EP 413
DI 10.5194/esd-11-395-2020
PG 19
WC Geosciences, Multidisciplinary
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Geology
GA LJ1MV
UT WOS:000529937300001
OA Green Submitted, gold
DA 2026-06-13
ER

PT J
AU Bovari, E
   Giraud, G
   McIsaac, F
AF Bovari, Emmanuel
   Giraud, Gael
   McIsaac, Florent
TI Financial impacts of climate change mitigation policies and their
   macroeconomic implications: a stock-flow consistent approach
SO CLIMATE POLICY
LA English
DT Article
DE Ecological macroeconomics; carbon pricing; stock-flow consistency;
   credit rationing; integrated assessment
ID SOCIAL COST; MODEL; EQUILIBRIUM; INEQUALITY; EMPLOYMENT; STABILITY;
   ECONOMICS; DYNAMICS; COLLAPSE; GROWTH
AB To what extent can worldwide carbon pricing foster the transition towards a low-carbon economy and mitigate the effects of global warming? We address this question by assessing the financial impacts and macroeconomic implications of carbon pricing and public subsidies. More specifically, we evaluate the extent to which such policies are sustainable by computing the probability of remaining below two thresholds that we argue to be indicative of the stability of our current economy and climate: (1) a temperature anomaly above +2 degrees C (a commonly acknowledged target, including in the 2015 Paris Agreement, to potentially avoid nonlinearities in the climate system) and (2) a large global debt-to-output ratio of 270%. Key policy insights The upper-bound of the carbon pricing corridor advocated in the High-Level Commission on Carbon Prices (2017. Report of the high-level commission on carbon prices. Washington, DC: World Bank), when implemented together with additional public subsidies on abatement costs in the private sector, is likely to successfully ensure sustainable economic growth by the end of the century. The probability that these climate policies will allow us to cap the average Earth temperature deviation at below +2.5 degrees C by the end of this century is about 50%. Without a strong public commitment, the impact of climate change on gross output and capital, which captures nonlinear effects such as tipping points, appears to be powerful enough to pull the world economy towards a debt-deflationary field, potentially leading to forced degrowth in the second half of the twenty-first century.
C1 [Bovari, Emmanuel; Giraud, Gael] Univ Paris 1 Pantheon Sorbonne, Ctr Econ Sorbonne, Paris, France.
   [Bovari, Emmanuel; Giraud, Gael; McIsaac, Florent] Inst Louis Bachelier, Chair Energy & Prosper, 28 Pl Bourse, F-75002 Paris, France.
   [McIsaac, Florent] AFD, 5 Rue Roland Barthes, F-75012 Paris, France.
RP McIsaac, F (corresponding author), Inst Louis Bachelier, Chair Energy & Prosper, 28 Pl Bourse, F-75002 Paris, France.; McIsaac, F (corresponding author), AFD, 5 Rue Roland Barthes, F-75012 Paris, France.
EM mcisaacf@afd.fr
OI McIsaac, Florent/0000-0002-5169-8256; Bovari,
   Emmanuel/0000-0002-5267-0802
FU Energy and Prosperity Chair; Agence Nationale de la Recherche [DS0207]
FX This work benefited from the support of the Energy and Prosperity Chair
   and the financial support of the Agence Nationale de la Recherche (grant
   number DS0207).
CR [Anonymous], EARTH RISK NATURAL C
   [Anonymous], 2017, Report of the High-Level Commission on Carbon Prices
   [Anonymous], 2014, NBER WORKING PAPERS
   [Anonymous], CLIM CHANG 2013
   Bastidas D, 2019, MATH FINANC ECON, V13, P359, DOI 10.1007/s11579-018-0231-6
   Berg M, 2015, NEW J PHYS, V17, DOI 10.1088/1367-2630/17/1/015011
   Bernardo G, 2016, ENVIRON INNOV SOC TR, V21, P123, DOI 10.1016/j.eist.2016.04.006
   Bovari E., 2018, Int. Econ., V155, P92, DOI [DOI 10.1016/J.INTECO.2018.02.002, 10.1016/j.inteco.2018.02.002]
   Bovari E, 2018, ECOL ECON, V147, P383, DOI 10.1016/j.ecolecon.2018.01.034
   Brander JA, 1998, AM ECON REV, V88, P119
   Burke M, 2015, NATURE, V527, P235, DOI 10.1038/nature15725
   Campiglio E, 2016, ECOL ECON, V121, P220, DOI 10.1016/j.ecolecon.2015.03.020
   Dafermos Y, 2018, ECOL ECON, V152, P219, DOI 10.1016/j.ecolecon.2018.05.011
   Dafermos Y, 2017, ECOL ECON, V131, P191, DOI 10.1016/j.ecolecon.2016.08.013
   DALY HE, 1991, LAND ECON, V67, P255, DOI 10.2307/3146415
   Dietz S, 2015, ECON J, V125, P574, DOI 10.1111/ecoj.12188
   Feenstra RC, 2015, AM ECON REV, V105, P3150, DOI 10.1257/aer.20130954
   Geanakoplos J, 2014, ECON THEOR, V56, P443, DOI 10.1007/s00199-013-0797-4
   Giraud G, 2021, J ECON BEHAV ORGAN, V183, P901, DOI 10.1016/j.jebo.2019.03.002
   Godley Wynne., 2012, Monetary economics: an integrated approach to credit, money, income, production and wealth, VSecond
   Grasselli MR, 2012, MATH FINANC ECON, V6, P191, DOI 10.1007/s11579-012-0071-8
   Grasselli MR, 2018, STRUCT CHANGE ECON D, V44, P1, DOI 10.1016/j.strueco.2018.01.003
   Grasselli MR, 2015, J RISK FINANC MANAG, V8, P285, DOI 10.3390/jrfm8030285
   Hardt L, 2017, ECOL ECON, V134, P198, DOI 10.1016/j.ecolecon.2016.12.027
   Huu AN, 2014, J MATH ANAL APPL, V419, P48, DOI 10.1016/j.jmaa.2014.04.035
   Jackson Tim., 2009, Prosperity Without Growth; Economics for a Finite Planet
   KEEN S, 1995, J POST KEYNESIAN EC, V17, P607, DOI 10.1080/01603477.1995.11490053
   Knutti R, 2017, NAT GEOSCI, V10, P727, DOI [10.1038/NGEO3017, 10.1038/ngeo3017]
   Knutti R, 2016, NAT GEOSCI, V9, P13, DOI 10.1038/NGEO2595
   Lamperti F, 2018, ECOL ECON, V150, P315, DOI [10.2139/ssrn.2944328, 10.1016/j.ecolecon.2018.03.023]
   Lima BC, 2014, STRUCT CHANGE ECON D, V30, P30, DOI 10.1016/j.strueco.2014.02.003
   Mankiw N.Gregory., 2010, MACROECONOMICS, V7th
   Monasterolo I, 2018, ECOL ECON, V144, P228, DOI 10.1016/j.ecolecon.2017.07.029
   Motesharrei S, 2014, ECOL ECON, V101, P90, DOI 10.1016/j.ecolecon.2014.02.014
   Nordhaus W.D., 2013, DICE 2013R INTRO USE
   Nordhaus W.D., 2000, WARMING WORLD EC MOD
   Nordhaus W, 2014, J ASSOC ENVIRON RESO, V1, P273, DOI 10.1086/676035
   Nordhaus WD, 2017, P NATL ACAD SCI USA, V114, P1518, DOI 10.1073/pnas.1609244114
   Raftery AE, 2017, NAT CLIM CHANGE, V7, P637, DOI [10.1038/nclimate3352, 10.1038/NCLIMATE3352]
   SOLOW RM, 1956, Q J ECON, V70, P65, DOI 10.2307/1884513
   Stern N, 2013, J ECON LIT, V51, P838, DOI 10.1257/jel.51.3.838
   Taylor J.B., 1993, Carnegie-Rochester conference series on public policy, V39, P195, DOI [10.1016/0167-2231(93)90009-L, DOI 10.1016/0167-2231(93)90009-L, 10.1016/0167-2231(93)90009-l]
   UNEP, 2017, EM GAP REP
   van Treeck T, 2009, CAMB J ECON, V33, P467, DOI 10.1093/cje/ben039
   Weitzman ML, 2011, REV ENV ECON POLICY, V5, P275, DOI 10.1093/reep/rer006
NR 45
TC 20
Z9 21
U1 1
U2 43
PU TAYLOR & FRANCIS LTD
PI ABINGDON
PA 2-4 PARK SQUARE, MILTON PARK, ABINGDON OR14 4RN, OXON, ENGLAND
SN 1469-3062
EI 1752-7457
J9 CLIM POLICY
JI Clim. Policy
PD FEB 7
PY 2020
VL 20
IS 2
BP 179
EP 198
DI 10.1080/14693062.2019.1698406
EA DEC 2019
PG 20
WC Environmental Studies; Public Administration
WE Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Public Administration
GA KO4SC
UT WOS:000502440700001
DA 2026-06-13
ER

PT J
AU Strnad, FM
   Barfuss, W
   Donges, JF
   Heitzig, J
AF Strnad, Felix M.
   Barfuss, Wolfram
   Donges, Jonathan F.
   Heitzig, Jobst
TI Deep reinforcement learning in World-Earth system models to discover
   sustainable management strategies
SO CHAOS
LA English
DT Article
ID TIPPING ELEMENTS; DYNAMICS; GAME; GO
AB Increasingly complex nonlinear World-Earth system models are used for describing the dynamics of the biophysical Earth system and the socioeconomic and sociocultural World of human societies and their interactions. Identifying pathways toward a sustainable future in these models for informing policymakers and the wider public, e.g., pathways leading to robust mitigation of dangerous anthropogenic climate change, is a challenging and widely investigated task in the field of climate research and broader Earth system science. This problem is particularly difficult when constraints on avoiding transgressions of planetary boundaries and social foundations need to be taken into account. In this work, we propose to combine recently developed machine learning techniques, namely, deep reinforcement learning (DRL), with classical analysis of trajectories in the World-Earth system. Based on the concept of the agent-environment interface, we develop an agent that is generally able to act and learn in variable manageable environment models of the Earth system. We demonstrate the potential of our framework by applying DRL algorithms to two stylized World-Earth system models. Conceptually, we explore thereby the feasibility of finding novel global governance policies leading into a safe and just operating space constrained by certain planetary and socioeconomic boundaries. The artificially intelligent agent learns that the timing of a specific mix of taxing carbon emissions and subsidies on renewables is of crucial relevance for finding World-Earth system trajectories that are sustainable in the long term. Published under license by AIP Publishing.
C1 [Strnad, Felix M.; Heitzig, Jobst] Potsdam Inst Climate Impact Res, FutureLab Game Theory & Networks Interacting Age, Res Dept Complex Sci 4, D-14473 Potsdam, Germany.
   [Strnad, Felix M.] Univ Gottingen, Dept Phys, D-37077 Gottingen, Germany.
   [Barfuss, Wolfram; Donges, Jonathan F.] Potsdam Inst Climate Impact Res, Res Dept Earth Syst Anal 1, FutureLab Earth Resilience Anthropocene, D-14473 Potsdam, Germany.
   [Barfuss, Wolfram] Max Planck Inst Math Sci, D-04103 Leipzig, Germany.
   [Donges, Jonathan F.] Stockholm Univ, Stockholm Resilience Ctr, S-10405 Stockholm, Sweden.
C3 Potsdam Institut fur Klimafolgenforschung; University of Gottingen;
   Potsdam Institut fur Klimafolgenforschung; Max Planck Society; Stockholm
   University
RP Strnad, FM (corresponding author), Potsdam Inst Climate Impact Res, FutureLab Game Theory & Networks Interacting Age, Res Dept Complex Sci 4, D-14473 Potsdam, Germany.; Strnad, FM (corresponding author), Univ Gottingen, Dept Phys, D-37077 Gottingen, Germany.
EM strnad@pik-potsdam.de
RI ; Donges, Jonathan/HCI-2311-2022; Heitzig, Jobst/E-8271-2011
OI Barfuss, Wolfram/0000-0002-9077-5242; Donges,
   Jonathan/0000-0001-5233-7703; Strnad, Felix/0000-0001-6395-8150;
   Heitzig, Jobst/0000-0002-0442-8077
FU European Research Council (via the ERC advanced grant project ERA);
   Stordalen Foundation (via the Planetary Boundaries Research Network
   PB.net); Earth League's EarthDoc program; Leibniz Association (project
   DOMINOES)
FX This work was developed in the context of the COPAN collaboration at the
   Potsdam Institute for Climate Impact Research (PIK). The authors thank
   the COPAN group for helpful discussions and comments. Moreover, F.M.S.
   thanks the participants and organizers of the Eastern European Machine
   Learning (EEML) Summer school for inspiring suggestions to this work. We
   are grateful for financial support by the European Research Council (via
   the ERC advanced grant project ERA), the Stordalen Foundation (via the
   Planetary Boundaries Research Network PB.net), the Earth League's
   EarthDoc program, and the Leibniz Association (project DOMINOES). The
   authors gratefully acknowledge the European Regional Development Fund
   (ERDF), the German Federal Ministry of Education and Research, and the
   Land Brandenburg for providing resources on the high-performance
   computer system at PIK.
CR Amodei Dario., 2016, CORR, DOI DOI 10.48550/ARXIV.1606.06565
   Anderies JM, 2013, ENVIRON RES LETT, V8, DOI 10.1088/1748-9326/8/4/044048
   [Anonymous], 2017, ARXIV171201275
   [Anonymous], 1989, THESIS
   [Anonymous], TECHNICAL REPORT
   [Anonymous], TECHNICAL REPORT
   [Anonymous], 2012, SAFE JUST SPACE HUMA, DOI DOI 10.5822/978-1-61091-458-1
   [Anonymous], 2011, Technical report
   [Anonymous], 2017, ARXIV PREPRINT ARXIV
   [Anonymous], 2015, Financial reporting with XBRL and its impact on the accounting profession
   [Anonymous], THESIS
   [Anonymous], 2018, Mitigation Pathways Compatible with 1.5C in the Context of Sustainable Development
   [Anonymous], ARXIV08050541
   [Anonymous], 2015, ARXIV150902971
   [Anonymous], 2016, PREPRINT
   ARTHUR WB, 1991, AM ECON REV, V81, P353
   Barfuss W, 2019, PHYS REV E, V99, DOI 10.1103/PhysRevE.99.043305
   Barfuss W, 2018, NAT COMMUN, V9, DOI 10.1038/s41467-018-04738-z
   Barfuss W, 2017, EARTH SYST DYNAM, V8, P255, DOI 10.5194/esd-8-255-2017
   Behzadan Vahid, 2017, Machine Learning and Data Mining in Pattern Recognition. 13th International Conference, MLDM 2017. Proceedings: LNAI 10358, P262, DOI 10.1007/978-3-319-62416-7_19
   Bellemare MG, 2017, PR MACH LEARN RES, V70
   BELLMAN R, 1957, J MATH MECH, V6, P679, DOI 10.1512/iumj.1957.6.56038
   Botta N, 2018, EARTH SYST DYNAM, V9, P525, DOI 10.5194/esd-9-525-2018
   Bussieck MR, 2004, APPL OPTIMIZAT, V88, P137
   Donges J.F., 2018, Earth System Dynamics Discussions, P1, DOI DOI 10.5194/ESD-2017-126
   Donges JF, 2017, ANTHROPOCENE REV, V4, P151, DOI 10.1177/2053019617725537
   Haarnoja, 2018, ARXIV181211103
   Hasselt HadoV., 2010, Advances in Neural Information Processing Systems, V23, P2613, DOI DOI 10.5555/2997046.2997187
   Heitzig J, 2016, EARTH SYST DYNAM, V7, P21, DOI 10.5194/esd-7-21-2016
   Heitzig J, 2018, SUSTAINABILITY-BASEL, V10, DOI 10.3390/su10061947
   Heitzig J, 2011, P NATL ACAD SCI USA, V108, P15739, DOI 10.1073/pnas.1106265108
   Hessel M, 2018, AAAI CONF ARTIF INTE, P3215
   Huang S., 2017, INT C LEARN REPR ICL
   Kamien M.I., 2012, DYNAMIC OPTIMIZATION, VSecond
   Kelly D.L., 1999, International yearbook of environmental and resource economics, V2000, P171
   Kingma DP, 2014, ADV NEUR IN, V27
   Kittel T., 2017, ARXIV170604542
   LeCun Y, 2015, NATURE, V521, P436, DOI 10.1038/nature14539
   Leibo JZ, 2017, AAMAS'17: PROCEEDINGS OF THE 16TH INTERNATIONAL CONFERENCE ON AUTONOMOUS AGENTS AND MULTIAGENT SYSTEMS, P464
   Lenton TM, 2008, P NATL ACAD SCI USA, V105, P1786, DOI 10.1073/pnas.0705414105
   Levine S, 2016, J MACH LEARN RES, V17
   Li Y, 2018, ARXIV181006339
   Lin Long-Ji., 1993, REINFORCEMENT LEARNI, DOI 10.5555/168871
   Lindkvist E, 2017, P ROY SOC B-BIOL SCI, V284, DOI 10.1098/rspb.2016.2762
   Lindkvist E, 2014, ECOL ECON, V104, P107, DOI 10.1016/j.ecolecon.2014.04.018
   Mao HZ, 2016, PROCEEDINGS OF THE 15TH ACM WORKSHOP ON HOT TOPICS IN NETWORKS (HOTNETS '16), P50, DOI 10.1145/3005745.3005750
   Mirowski P., 2016, PROC INT C LEARN REP
   Mnih K. Kavukcuoglu., 2013, Playing atari with deep reinforcement learning
   Mnih V, 2015, NATURE, V518, P529, DOI 10.1038/nature14236
   Müller-Hansen F, 2017, EARTH SYST DYNAM, V8, P977, DOI 10.5194/esd-8-977-2017
   Munir A., 2017, ARXIV171209344
   Nagabandi A, 2018, IEEE INT CONF ROBOT, P7579
   Nitzbon J, 2017, ENVIRON RES LETT, V12, DOI 10.1088/1748-9326/aa7581
   Pahl-Wostl C., 2000, INTEGR ASSESS, V1, P267, DOI DOI 10.1023/A:1018927120883
   Papernot N, 2016, 1ST IEEE EUROPEAN SYMPOSIUM ON SECURITY AND PRIVACY, P372, DOI 10.1109/EuroSP.2016.36
   Perolat J., 2017, ADV NEURAL INFORM PR, P3643
   Pindyck RS, 2017, REV ENV ECON POLICY, V11, P100, DOI 10.1093/reep/rew012
   Pong V., 2018, ARXIV180209081
   Rolnick D., 2019, CORR
   Schellnhuber HJ, 2009, P NATL ACAD SCI USA, V106, P20561, DOI 10.1073/pnas.0911106106
   Schellnhuber HJ, 1999, NATURE, V402, pC19, DOI 10.1038/35011515
   Shixiang Gu, 2017, 2017 IEEE International Conference on Robotics and Automation (ICRA), P3389, DOI 10.1109/ICRA.2017.7989385
   Silver D, 2018, SCIENCE, V362, P1140, DOI 10.1126/science.aar6404
   Silver D, 2016, NATURE, V529, P484, DOI 10.1038/nature16961
   Sitch S, 2003, GLOBAL CHANGE BIOL, V9, P161, DOI 10.1046/j.1365-2486.2003.00569.x
   Spaan MTJ, 2012, ADAPT LEARN OPTIM, V12, P387
   Steffen W, 2018, P NATL ACAD SCI USA, V115, P8252, DOI 10.1073/pnas.1810141115
   Steffen W, 2015, SCIENCE, V347, DOI 10.1126/science.1259855
   Stern N, 2008, AM ECON REV, V98, P1, DOI 10.1257/aer.98.2.1
   Sutton RS, 1998, INTRO REINFORCEMENT, V135
   Szegedy Christian, 2013, INTRIGUING PROPERTIE, DOI 10.1364/BOE.8.000579
   TESAURO G, 1995, COMMUN ACM, V38, P58, DOI 10.1145/203330.203343
   van Hasselt H, 2016, AAAI CONF ARTIF INTE, P2094
   van Otterlo M, 2012, ADAPT LEARN OPTIM, V12, P3
   Wiedermann M, 2015, PHYS REV E, V91, DOI 10.1103/PhysRevE.91.052801
   Zhou ZP, 2017, ACS CENTRAL SCI, V3, P1337, DOI 10.1021/acscentsci.7b00492
   Zhu YK, 2017, INT CONF ACOUST SPEE, P5335, DOI 10.1109/ICASSP.2017.7953175
NR 77
TC 19
Z9 21
U1 1
U2 33
PU AIP Publishing
PI MELVILLE
PA 1305 WALT WHITMAN RD, STE 300, MELVILLE, NY 11747-4501 USA
SN 1054-1500
EI 1089-7682
J9 CHAOS
JI Chaos
PD DEC
PY 2019
VL 29
IS 12
AR 123122
DI 10.1063/1.5124673
PG 16
WC Mathematics, Applied; Physics, Mathematical
WE Science Citation Index Expanded (SCI-EXPANDED)
SC Mathematics; Physics
GA KA1MO
UT WOS:000505563100018
PM 31893656
OA Green Submitted
DA 2026-06-13
ER

PT J
AU Lamperti, F
   Bosetti, V
   Roventini, A
   Tavoni, M
AF Lamperti, Francesco
   Bosetti, Valentina
   Roventini, Andrea
   Tavoni, Massimo
TI The public costs of climate-induced financial instability
SO NATURE CLIMATE CHANGE
LA English
DT Article
ID CUMULATIVE CARBON; SOCIAL COST; CREDIT; TEMPERATURE; TRANSITION;
   STABILITY; FRAMEWORK; SCENARIO; POLICIES; DAMAGES
AB Recent evidence suggests that climate change will significantly affect economic growth and several productive elements of modern economies, such as workers and land(1-4). Although historical records indicate that economic shocks might lead to financial instability, few studies have focused on the impact of climate change on the financial actors(5,6). This paper examines how climate-related damages impact the stability of the global banking system. We use an agent-based climate-macroeconomic model calibrated on stylized facts, future scenarios and climate impact functions(7) affecting labour and capital. Our results indicate that climate change will increase the frequency of banking crises (26-248%). Rescuing insolvent banks will cause an additional fiscal burden of approximately 5-15% of gross domestic product per year and increase the ratio of public debt to gross domestic product by a factor of 2. We estimate that around 20% of such effects are caused by the deterioration of banks' balance sheets induced by climate change. Macroprudential regulation attenuates bailout costs, but only moderately. Our results show that leaving the financial system out of climate-economy integrated assessment may lead to an underestimation of climate impacts and that financial regulation can play a role in mitigating them.
C1 [Lamperti, Francesco; Roventini, Andrea] Scuola Super Sant Anna, Inst Econ, Pisa, Italy.
   [Lamperti, Francesco; Roventini, Andrea] Scuola Super Sant Anna, EMbeDS, Pisa, Italy.
   [Lamperti, Francesco; Bosetti, Valentina; Tavoni, Massimo] Ctr Euromediterraneo Cambiamenti Climat, RFF CMCC European Inst Econ & Environm, Milan, Italy.
   [Bosetti, Valentina] Bocconi Univ, Dept Econ, Milan, Italy.
   [Roventini, Andrea] Observ Francais Conjonctures Econ, Dept Innovat & Concurrence, Nice, France.
   [Tavoni, Massimo] Politecn Milan, Dept Management Econ & Ind Engn, Milan, Italy.
C3 Scuola Superiore Sant'Anna; Scuola Superiore Sant'Anna; Bocconi
   University; Polytechnic University of Milan
RP Lamperti, F (corresponding author), Scuola Super Sant Anna, Inst Econ, Pisa, Italy.; Lamperti, F (corresponding author), Scuola Super Sant Anna, EMbeDS, Pisa, Italy.; Lamperti, F (corresponding author), Ctr Euromediterraneo Cambiamenti Climat, RFF CMCC European Inst Econ & Environm, Milan, Italy.
EM francesco.lamperti@eiee.org
RI ; ROVENTINI, Andrea/N-4699-2019; bosetti, valentina/KLY-5840-2024
OI Lamperti, Francesco/0000-0003-4862-646X; ROVENTINI,
   Andrea/0000-0001-5518-3084; tavoni, massimo/0000-0001-5069-4707;
   bosetti, valentina/0000-0003-4970-0027
FU Fondazione Eni Enrico Mattei, FEEM; European Research Council under the
   European Community programme 'Ideas', call identifier ERC-2013-StG/ERC
   [336703]; European Research Council under the European Union's Seventh
   Framework Programme (FP7/2007-2013)/ERC grant [336155]; EU [681228,
   822781]
FX We acknowledge support from Fondazione Eni Enrico Mattei, FEEM. The
   research leading to these results received funding from the European
   Research Council under the European Community programme 'Ideas', call
   identifier ERC-2013-StG/ERC, grant agreement no. 336703, project RISICO
   and from the European Research Council under the European Union's
   Seventh Framework Programme (FP7/2007-2013)/ERC grant agreement no.
   336155, project COBHAM. This paper is also part of a project that has
   received funding from the EU H2020 research and innovation programme
   under the Marie Sklodowska-Curie grant agreement no. 681228, GEMCLIME,
   and from the EU H2020 research and innovation action under grant
   agreement no. 822781, GROWINPRO. We thank T. Treibich and M. Guerini for
   helpful discussions, comments and support. We also thank participants at
   ECOMOD 2018 (Venice), EAEPE 2018 (Nice), the 2018 Workshop on Economic
   and Financial Implications of Climatic Change (Milan), WEHIA 2019 and
   the seminars at IAASA and Universite Paris Pantheon-Sorbonne.
CR Adhvaryu A., 2018, LIGHT HEAT PRODUCTIV
   Allen MR, 2009, NATURE, V458, P1163, DOI 10.1038/nature08019
   [Anonymous], 2011, Basel III: A global regulatory framework for more resilient banks and banking systems
   [Anonymous], 1 BIS BAS COMM BANK
   Auffhammer M, 2018, J ECON PERSPECT, V32, P33, DOI 10.1257/jep.32.4.33
   Balint T, 2017, ECOL ECON, V138, P252, DOI 10.1016/j.ecolecon.2017.03.032
   Batten Sandra., 2018, Climate change and the macro-economy: a critical review, DOI DOI 10.2139/SSRN.3104554
   Battiston S, 2017, NAT CLIM CHANGE, V7, P283, DOI [10.1038/nclimate3255, 10.1038/NCLIMATE3255]
   Bernanke B. S., 1991, CREDIT CRUNCH BPEA
   BERNANKE BS, 1983, AM ECON REV, V73, P257
   Bikker J.A., 2005, J INT FINANCIAL MARK, V15, P141, DOI DOI 10.1016/J.INTFIN.2004.03.004
   Bonabeau E, 2002, P NATL ACAD SCI USA, V99, P7280, DOI 10.1073/pnas.082080899
   Brunnermeier MK, 2009, J ECON PERSPECT, V23, P77, DOI 10.1257/jep.23.1.77
   Burke M, 2015, NATURE, V527, P235, DOI 10.1038/nature15725
   Campiglio E, 2018, NAT CLIM CHANGE, V8, P462, DOI 10.1038/s41558-018-0175-0
   Campiglio E, 2016, ECOL ECON, V121, P220, DOI 10.1016/j.ecolecon.2015.03.020
   Carleton TA, 2016, SCIENCE, V353, DOI 10.1126/science.aad9837
   Carney M., 2015, LLOYDS LONDON
   Chinazzi M., 2015, BANKING INTEGRATION
   Dafermos Y, 2018, ECOL ECON, V152, P219, DOI 10.1016/j.ecolecon.2018.05.011
   Dell M, 2009, AM ECON REV, V99, P198, DOI 10.1257/aer.99.2.198
   Dietz S, 2016, NAT CLIM CHANGE, V6, P676, DOI [10.1038/NCLIMATE2972, 10.1038/nclimate2972]
   Diffenbaugh NS, 2019, P NATL ACAD SCI USA, V116, P9808, DOI 10.1073/pnas.1816020116
   Dosi G, 2015, J ECON DYN CONTROL, V52, P166, DOI 10.1016/j.jedc.2014.11.014
   Dosi G, 2013, J ECON DYN CONTROL, V37, P1598, DOI 10.1016/j.jedc.2012.11.008
   Fagiolo G, 2017, JASSS-J ARTIF SOC S, V20, DOI 10.18564/jasss.3280
   Farmer JD, 2009, NATURE, V460, P685, DOI 10.1038/460685a
   High-Level Expert Group on Sustainable Finance, 2017, FIN SUST EUR EC IN R
   Hsiang S, 2017, SCIENCE, V356, P1362, DOI 10.1126/science.aal4369
   Hsiang SM, 2010, P NATL ACAD SCI USA, V107, P15367, DOI 10.1073/pnas.1009510107
   Jiménez G, 2017, J POLIT ECON, V125, P2126, DOI 10.1086/694289
   Jordà O, 2013, J MONEY CREDIT BANK, V45, P3, DOI 10.1111/jmcb.12069
   Kiyotaki N, 2002, AM ECON REV, V92, P46, DOI 10.1257/000282802320188989
   Kjellstrom T, 2009, ARCH ENVIRON OCCUP H, V64, P217, DOI 10.1080/19338240903352776
   Laeven L., 2012, Systemic Banking Crises Database: An Update, DOI DOI 10.2139/SSRN.2096234
   Lamperti F, 2018, ECOL ECON, V150, P315, DOI [10.2139/ssrn.2944328, 10.1016/j.ecolecon.2018.03.023]
   Lamperti F., 2018, LEM PAPERS SERIES, V2018/14
   Lown C, 2006, J MONEY CREDIT BANK, V38, P1575, DOI 10.1353/mcb.2006.0086
   Martinich J, 2019, NAT CLIM CHANGE, V9, P397, DOI 10.1038/s41558-019-0444-6
   Matthews HD, 2012, PHILOS T R SOC A, V370, P4365, DOI 10.1098/rsta.2012.0064
   Matthews HD, 2009, NATURE, V459, P829, DOI 10.1038/nature08047
   Mercure JF, 2018, NAT CLIM CHANGE, V8, P588, DOI 10.1038/s41558-018-0182-1
   Mercure JF, 2016, GLOBAL ENVIRON CHANG, V37, P102, DOI 10.1016/j.gloenvcha.2016.02.003
   NORDHAUS WD, 1992, SCIENCE, V258, P1315, DOI 10.1126/science.258.5086.1315
   Nordhaus W, 2014, J ASSOC ENVIRON RESO, V1, P273, DOI 10.1086/676035
   Nordhaus WD, 2017, P NATL ACAD SCI USA, V114, P1518, DOI 10.1073/pnas.1609244114
   O'Neill BC, 2014, CLIMATIC CHANGE, V122, P387, DOI 10.1007/s10584-013-0905-2
   Ochoa M, 2016, 22529 NBER
   OECD, 2018, OECD EMPL OUTL 2018, DOI DOI 10.1787/9A815D6B-EN
   Oulton N, 2018, INTERECONOMICS, V53, P63, DOI [10.1007/s10272-018-0723-x, DOI 10.1007/S10272-018-0723-X, 10.1007/s10272-018-0723-x]
   Reinhart CM, 2009, THIS TIME IS DIFFERENT: EIGHT CENTURIES OF FINANCIAL FOLLY, P1
   Reinhart CM, 2009, AM ECON REV, V99, P466, DOI 10.1257/aer.99.2.466
   Riahi K, 2011, CLIMATIC CHANGE, V109, P33, DOI 10.1007/s10584-011-0149-y
   Ricke K, 2018, NAT CLIM CHANGE, V8, P895, DOI 10.1038/s41558-018-0282-y
   Roukny T, 2013, SCI REP-UK, V3, DOI 10.1038/srep02759
   Safarzynska K, 2017, ENERG POLICY, V108, P12, DOI 10.1016/j.enpol.2017.05.042
   Schlenker W, 2009, P NATL ACAD SCI USA, V106, P15594, DOI 10.1073/pnas.0906865106
   Seppanen O., 2006, Lawrence Berkeley National Laboratory Working Paper LBNL-60946
   Seppanen O., 2003, COST BENEFIT ANAL NI
   Stern N, 2016, NATURE, V530, P407, DOI 10.1038/530407a
   Tewari M., 2018, 201869 BFI U CHIC
   Trinks A, 2018, ECOL ECON, V146, P740, DOI 10.1016/j.ecolecon.2017.11.036
   van Vuuren DP, 2017, GLOBAL ENVIRON CHANG, V42, P148, DOI [10.1016/j.gloenvcha.2016.10.009, 10.1016/j.gloenvcha.2016.05.009]
   van Vuuren DP, 2014, CLIMATIC CHANGE, V122, P373, DOI 10.1007/s10584-013-0906-1
   Weyant J, 2017, REV ENV ECON POLICY, V11, P115, DOI 10.1093/reep/rew018
NR 65
TC 133
Z9 153
U1 10
U2 125
PU NATURE PORTFOLIO
PI BERLIN
PA HEIDELBERGER PLATZ 3, BERLIN, 14197, GERMANY
SN 1758-678X
EI 1758-6798
J9 NAT CLIM CHANGE
JI Nat. Clim. Chang.
PD NOV
PY 2019
VL 9
IS 11
BP 829
EP +
DI 10.1038/s41558-019-0607-5
PG 9
WC Environmental Sciences; Environmental Studies; Meteorology & Atmospheric
   Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Meteorology & Atmospheric Sciences
GA JI8TB
UT WOS:000493735100014
OA Green Submitted
DA 2026-06-13
ER

PT J
AU Woodard, DL
   Davis, SJ
   Randerson, JT
AF Woodard, Dawn L.
   Davis, Steven J.
   Randerson, James T.
TI Economic carbon cycle feedbacks may offset additional warming from
   natural feedbacks
SO PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF
   AMERICA
LA English
DT Article
DE carbon cycle feedbacks; climate change; economic damages; integrated
   assessment models; fossil fuels
ID CLIMATE-CHANGE; TEMPERATURE; SENSITIVITY; IMPACT; MODEL
AB As the Earth warms, carbon sinks on land and in the ocean will weaken, thereby increasing the rate of warming. Although natural mechanisms contributing to this positive climate-carbon feedback have been evaluated using Earth system models, analogous feedbacks involving human activities have not been systematically quantified. Here we conceptualize and estimate the magnitude of several economic mechanisms that generate a carbon-climate feedback, using the Kaya identity to separate a net economic feedback into components associated with population, GDP, heating and cooling, and the carbon intensity of energy production and transportation. We find that climate-driven decreases in economic activity (GDP) may in turn decrease human energy use and thus fossil fuel CO2 emissions. In a high radiative forcing scenario, such decreases in economic activity reduce fossil fuel emissions by 13% this century, lowering atmospheric CO2 by over 100 ppm in 2100. The natural carbon-climate feedback, in contrast, increases atmospheric CO2 over this period by a similar amount, and thus, the net effect including both feedbacks is nearly zero. Our work highlights the importance of improving the representation of climate-economic feedbacks in scenarios of future change. Although the effects of climate warming on the economy may offset weakening land and ocean carbon sinks, a loss of economic productivity will have high societal costs, potentially increasing wealth inequity and limiting resources available for effective adaptation.
C1 [Woodard, Dawn L.; Davis, Steven J.; Randerson, James T.] Univ Calif Irvine, Dept Earth Syst Sci, Irvine, CA 92697 USA.
   [Davis, Steven J.] Univ Calif Irvine, Dept Civil & Environm Engn, Irvine, CA 92697 USA.
C3 University of California System; University of California Irvine;
   University of California System; University of California Irvine
RP Woodard, DL; Randerson, JT (corresponding author), Univ Calif Irvine, Dept Earth Syst Sci, Irvine, CA 92697 USA.
EM dwoodard@uci.edu; jranders@uci.edu
RI Randerson, James/Y-2550-2019; Davis, Steven/F-9968-2010
OI Randerson, James/0000-0001-6559-7387; Davis, Steven/0000-0002-9338-0844
FU National Science Foundation Graduate Research Fellowship Program
   [DGE-1321846]; NASA's Interdisciplinary Science Program; NASA's Carbon
   Monitoring System (CMS) Program; Gordon and Betty Moore Foundation [GBMF
   3269]; Reducing Uncertainty in Biogeochemical Interactions Through
   Synthesis and Computation (RUBISCO) Science Focus Area in US Department
   of Energy's Office of Science, Division of Biological and Environmental
   Research
FX This material is based upon work supported by the National Science
   Foundation Graduate Research Fellowship Program under Grant DGE-1321846.
   J.T.R. and S.J.D. received support from NASA's Interdisciplinary Science
   Program. J.T.R. received additional support from NASA's Carbon
   Monitoring System (CMS) Program; the Gordon and Betty Moore Foundation
   (GBMF 3269); and the Reducing Uncertainty in Biogeochemical Interactions
   Through Synthesis and Computation (RUBISCO) Science Focus Area in US
   Department of Energy's Office of Science, Division of Biological and
   Environmental Research.
CR Ackerman F, 2012, ECONOMICS-KIEL, V6, DOI 10.5018/economics-ejournal.ja.2012-10
   Ackerman F, 2009, CLIMATIC CHANGE, V95, P297, DOI 10.1007/s10584-009-9570-x
   Aivalioti S, 2015, ELECT SECTOR ADAPTIO
   [Anonymous], 2014, Quantitative risk assessment of the effects of climate change on selected causes of death, 2030s and 2050s
   Arora VK, 2013, J CLIMATE, V26, P5289, DOI 10.1175/JCLI-D-12-00494.1
   Basha M, 2012, ENRGY PROCED, V14, P558, DOI 10.1016/j.egypro.2011.12.975
   Beckage B, 2018, NAT CLIM CHANGE, V8, P79, DOI 10.1038/s41558-017-0031-7
   Boer GJ, 2010, J CLIMATE, V23, P775, DOI 10.1175/2009JCLI3161.1
   Burke M, 2016, CLIM CHANG ECON, V7, DOI 10.1142/S2010007816500020
   Burke M, 2015, NATURE, V527, P235, DOI 10.1038/nature15725
   Burnard K., 2011, Power Generation from Coal
   Cox PM, 2013, NATURE, V494, P341, DOI 10.1038/nature11882
   Davidson EA, 2006, NATURE, V440, P165, DOI 10.1038/nature04514
   Diffenbaugh NS, 2013, SCIENCE, V341, P486, DOI 10.1126/science.1237123
   Farouk N, 2013, INT J COMPUT SCI ISS, V134, P221
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Friedlingstein P, 2006, J CLIMATE, V19, P3337, DOI 10.1175/JCLI3800.1
   Friedlingstein P, 2014, J CLIMATE, V27, P511, DOI 10.1175/JCLI-D-12-00579.1
   Gregory JM, 2009, J CLIMATE, V22, P5232, DOI 10.1175/2009JCLI2949.1
   Hsiang S, 2017, SCIENCE, V356, P1362, DOI 10.1126/science.aal4369
   Isaac M, 2009, ENERG POLICY, V37, P507, DOI 10.1016/j.enpol.2008.09.051
   Jones C, 2013, J CLIMATE, V26, P4398, DOI 10.1175/JCLI-D-12-00554.1
   Kahn ME, 2005, REV ECON STAT, V87, P271, DOI 10.1162/0034653053970339
   Libecap G.D., 2011, The Economics of Climate Change: Adaptations Past and Present
   McMichael AJ, 2006, LANCET, V367, P859, DOI 10.1016/S0140-6736(06)68079-3
   Mideksa TK, 2010, ENERG POLICY, V38, P3579, DOI 10.1016/j.enpol.2010.02.035
   Moore JK, 2018, SCIENCE, V359, P1139, DOI 10.1126/science.aao6379
   Moss R.H., 2008, Towards New Scenarios for Analysis of Emissions, Climate Change, Impacts, and Response Strategies
   Moss RH, 2010, NATURE, V463, P747, DOI 10.1038/nature08823
   Myhre G., 2019, CLIMATE CHANGE LAND, DOI [DOI 10.1787/9789264088061-EN, DOI 10.1017/CBO9781107415324.024]
   Nordhaus WD, 2017, P NATL ACAD SCI USA, V114, P1518, DOI 10.1073/pnas.1609244114
   Otto IM, 2017, REG ENVIRON CHANGE, V17, P1651, DOI 10.1007/s10113-017-1105-9
   Rose A., 2004, DISASTER PREV MANAG, V13, P307, DOI DOI 10.1108/09653560410556528
   Roson Roberto, 2012, International Journal of Sustainable Economy, V4, P270, DOI 10.1504/IJSE.2012.047933
   Santamouris M, 2015, ENERG BUILDINGS, V98, P119, DOI 10.1016/j.enbuild.2014.09.052
   Sathaye J., 2011, ESTIMATING RISK CALI
   Schuur EAG, 2015, NATURE, V520, P171, DOI 10.1038/nature14338
   Schwinger J, 2014, J CLIMATE, V27, P3869, DOI 10.1175/JCLI-D-13-00452.1
   Thornton PE, 2017, NAT CLIM CHANGE, V7, P496, DOI [10.1038/nclimate3310, 10.1038/NCLIMATE3310]
   Tol RSJ, 2009, J ECON PERSPECT, V23, P29, DOI 10.1257/jep.23.2.29
   van der Mensbrugghe D., 2010, Technical reference guide for ENVISAGE
   Weitzman ML, 2012, J PUBLIC ECON THEORY, V14, P221, DOI 10.1111/j.1467-9779.2011.01539.x
   Woodward DL, 2018, PYTHON MODEL CODE EC
   Zhou YY, 2014, APPL ENERG, V113, P1077, DOI 10.1016/j.apenergy.2013.08.034
NR 44
TC 65
Z9 79
U1 2
U2 67
PU NATL ACAD SCIENCES
PI WASHINGTON
PA 2101 CONSTITUTION AVE NW, WASHINGTON, DC 20418 USA
SN 0027-8424
EI 1091-6490
J9 P NATL ACAD SCI USA
JI Proc. Natl. Acad. Sci. U. S. A.
PD JAN 15
PY 2019
VL 116
IS 3
BP 759
EP 764
DI 10.1073/pnas.1805187115
PG 6
WC Multidisciplinary Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Science & Technology - Other Topics
GA HH3HL
UT WOS:000455610300012
PM 30559196
OA Green Submitted, Bronze
DA 2026-06-13
ER

PT C
AU Liu, SY
   Zhao, L
   Zhang, JL
AF Liu, Siyuan
   Zhao, Lei
   Zhang, Jianlei
GP IEEE
TI Strategy Dynamics with Feedback Control in the Global Climate Dilemma
   Games
SO 2019 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS (SMC)
SE IEEE International Conference on Systems Man and Cybernetics Conference
   Proceedings
LA English
DT Proceedings Paper
CT IEEE International Conference on Systems, Man and Cybernetics (SMC)
CY OCT 06-09, 2019
CL Bari, ITALY
SP IEEE
AB Global warming is becoming a knotty problem that cannot be ignored, making many countries face conflicts of interest and the need for cooperation. Evolutionary game theory provides an effective research framework for this kind of cooperation dilemma. From the perspective of control engineering, the mutual influence of environment and system can be utilized to achieve the purpose of self-adaptive adjustment and temperature control. Here, by combining feedback control and evolutionary game theory, we aim to restrict the global temperature to an expected level. Particularly, the controller is motivated by the threshold public goods game, where whether the threshold is realized or not is directly related to the different benefit states of the system. Results are gained where the temperature and cooperation level can be stabilized at the pre-set level. Moreover, we derive the correlation between the temperature trend and parameter settings, which is an efficient guideline to improve the control performance in global warming problems.
C1 [Liu, Siyuan; Zhao, Lei; Zhang, Jianlei] Nankai Univ, Coll Artificial Intelligence, Dept Automat, Tianjin 300071, Peoples R China.
   [Zhang, Jianlei] Nankai Univ, Tianjin Key Lab Intelligent Robot, Tianjin 300071, Peoples R China.
C3 Nankai University; Nankai University
RP Zhang, JL (corresponding author), Nankai Univ, Coll Artificial Intelligence, Dept Automat, Tianjin 300071, Peoples R China.; Zhang, JL (corresponding author), Nankai Univ, Tianjin Key Lab Intelligent Robot, Tianjin 300071, Peoples R China.
EM jianleizhang@nankai.edu.cn
OI Liu, Siyuan/0000-0001-7810-4393
FU National Natural Science Foundation of China [61603201, 61603199];
   Tianjin Natural Science Foundation of China [18JCYBJC18600]
FX This work was supported by National Natural Science Foundation of China
   (Grants Nos. 61603201 and 61603199)and the Tianjin Natural Science
   Foundation of China (Grant No. 18JCYBJC18600).
CR Caplan AJ, 1999, J ENVIRON ECON MANAG, V37, P256, DOI 10.1006/jeem.1999.1068
   Chang SH, 2018, PHYSICA A, V490, P419, DOI 10.1016/j.physa.2017.08.034
   Chen J, 2018, IEEE T IND INFORM, V14, P292, DOI 10.1109/TII.2016.2618886
   Cheng YS, 2018, ENERGIES, V11, DOI 10.3390/en11020469
   Du JM, 2017, IFAC PAPERSONLINE, V50, P7669, DOI 10.1016/j.ifacol.2017.08.1138
   Du JM, 2018, J STAT MECH-THEORY E, DOI 10.1088/1742-5468/aa9bb6
   Du JM, 2014, EPL-EUROPHYS LETT, V107, DOI 10.1209/0295-5075/107/60005
   Fan SL, 2018, IEEE ACCESS, V6, P27777, DOI 10.1109/ACCESS.2018.2839108
   Gong LL, 2018, IEEE DECIS CONTR P, P3535, DOI 10.1109/CDC.2018.8619801
   Kannayeram G., 2018, International Journal of Business Intelligence and Data Mining, V13, P52, DOI 10.1504/ijbidm.2018.088425
   Li S, 2018, IEEE T NEUR NET LEAR, V29, P1908, DOI 10.1109/TNNLS.2017.2672989
   Li YK, 2018, IEEE-CAA J AUTOMATIC, V5, P771, DOI 10.1109/JAS.2018.7511129
   Ma Y, 2018, IEEE T IND ELECTRON, V65, P6762, DOI 10.1109/TIE.2018.2795578
   PATIL HA, 2006, ADV MATH EC, P134
   Piraisoodi T, 2018, INT J FUZZY SYST, V20, P803, DOI 10.1007/s40815-017-0382-2
   Uzawa H., 1999, ENV EC POLICY STUDIE, V2, P1, DOI DOI 10.1007/BF03353901
   Ward H, 1996, POLIT STUD-LONDON, V44, P850, DOI 10.1111/j.1467-9248.1996.tb00338.x
   Wei FH, 2018, CHIN CONT DECIS CONF, P3167, DOI 10.1109/CCDC.2018.8407669
   Xue L, 2018, IEEE-CAA J AUTOMATIC, V5, P301, DOI 10.1109/JAS.2017.7510466
   Zhang CY, 2018, KNOWL-BASED SYST, V155, P11, DOI 10.1016/j.knosys.2018.04.036
   Zhang F., IEEE T INTELLIGENT T
   Zhang JL, 2015, SCI REP-UK, V5, DOI 10.1038/srep09098
   Zhang YZ, 2018, IEEE PHOTONICS J, V10, DOI 10.1109/JPHOT.2018.2795550
NR 23
TC 3
Z9 3
U1 0
U2 12
PU IEEE
PI NEW YORK
PA 345 E 47TH ST, NEW YORK, NY 10017 USA
SN 1062-922X
BN 978-1-7281-4569-3
J9 IEEE SYS MAN CYBERN
PY 2019
BP 518
EP 522
DI 10.1109/smc.2019.8914568
PG 5
WC Computer Science, Cybernetics; Computer Science, Information Systems
WE Conference Proceedings Citation Index - Science (CPCI-S)
SC Computer Science
GA BO6NM
UT WOS:000521353900084
DA 2026-06-13
ER

PT J
AU Roos, MWM
AF Roos, Michael W. M.
TI Endogenous Economic Growth, Climate Change and Societal Values: A
   Conceptual Model
SO COMPUTATIONAL ECONOMICS
LA English
DT Article
DE Endogenous growth; Societal values; Climate change; Environment; System
   dynamics; Evolutionary economics; Post-materialism
ID ECOSYSTEM SERVICES; ANTI-CONSUMPTION; LIFE-STYLES; MACROECONOMICS;
   POLICY
AB In this paper, I propose an evolutionary model that is an alternative to conventional models of growth and the environment. Global economic growth, the evolution of the human population, CO2 emissions, and the state of the environment are endogenous. Societal values are the main driver of all economic variables. They determine the different types of investment, the level of aggregate consumption and employment. Societal values evolve over time in response to economic and environmental conditions. The model is applied to generate possible scenarios for the twenty-first century. A baseline calibration generates an average global GDP growth rate of 3.6% p.a. and a global population level of 11.2 billion people in 2100. Mean global temperate in 2100 will be 1.77 degrees C higher than in 1995. These results are probably too optimistic. Sensitivity analyses show how these outcomes depend on various parameters. If values respond to environmental conditions only, global warming would reach 2.5 degrees C and a lower impact of investment in carbon efficiency could lead to average temperature increase by 4.8 degrees C. The model is a novel conceptual framework that can be extended in many dimensions.
C1 [Roos, Michael W. M.] Ruhr Univ Bochum, Dept Management & Econ, Chair Macroecon, D-44801 Bochum, Germany.
C3 Ruhr University Bochum
RP Roos, MWM (corresponding author), Ruhr Univ Bochum, Dept Management & Econ, Chair Macroecon, D-44801 Bochum, Germany.
EM Michael.Roos@rub.de
RI Roos, Michael/AAF-6288-2020
OI Roos, Michael/0000-0002-5465-9893
CR [Anonymous], 2014, 5 ASS REP SYNTH REP
   [Anonymous], 2007, 4 ASS REP IMP AD VUL
   [Anonymous], 12009 ECF
   Anthoff D., 2013, Technical Description
   Assenza T, 2013, J ECON DYN CONTROL, V37, P1659, DOI 10.1016/j.jedc.2013.04.010
   Ayres RU, 1998, ECOL ECON, V25, P17, DOI 10.1016/S0921-8009(98)00022-6
   Bardi A, 2003, PERS SOC PSYCHOL B, V29, P1207, DOI 10.1177/0146167203254602
   Bonen A., 2014, 20143 SCHWARTZ CTR E
   Brock W A. e., 2005, Handbook of Economic Growth, V1B, P1749, DOI [DOI 10.1016/S1574-0684(05)01028-2, 10.1016/S1574-0684(05)01028-2]
   Cai Yongyang., 2013, 18704 NBER, DOI [DOI 10.3386/W18704, https://doi.org/10.3886/w18704]
   Costanza R, 1997, NATURE, V387, P253, DOI 10.1038/387253a0
   Costanza R, 1998, ECOL ECON, V25, P67, DOI 10.1016/S0921-8009(98)00019-6
   Davidson P, 2011, POST KEYNESIAN MACROECONOMIC THEORY, 2ND EDITION, P1
   Deissenberg C, 2008, APPL MATH COMPUT, V204, P541, DOI 10.1016/j.amc.2008.05.116
   Delli Gatti D, 2011, MACROECONOMICS BOTTO
   Dosi G, 2013, J ECON DYN CONTROL, V37, P1598, DOI 10.1016/j.jedc.2012.11.008
   Dosi G, 2010, J ECON DYN CONTROL, V34, P1748, DOI 10.1016/j.jedc.2010.06.018
   Eriksson C, 2013, EC GROWTH ENV
   Etzioni A., 2003, SOCIO-ECON REV, V1, P105, DOI DOI 10.1093/SOCECO/1.1.105
   Fairbrother M, 2013, EUR SOCIOL REV, V29, P910, DOI 10.1093/esr/jcs068
   Feenstra RobertC., 2013, The Next Generation of the Penn World Table
   Fischer C, 2013, ANNU REV RESOUR ECON, V5, P197, DOI 10.1146/annurev-resource-091912-151819
   Foley Duncan., 1999, Growth and Distribution
   Foley JA, 2005, SCIENCE, V309, P570, DOI 10.1126/science.1111772
   Gilg A, 2005, FUTURES, V37, P481, DOI 10.1016/j.futures.2004.10.016
   Goldsmith R. E., 2015, COMPREHENSIVE PSYCHO, V4, P2165, DOI [10.2466/09.20.cp.4.4, 10.2466/09.20.CP.4.4, 10.2466/09.20.cp.4.4, DOI 10.2466/09.20.CP.4.4]
   Hartley JamesE., 2002, The representative agent in macroeconomics
   Hitlin S, 2004, ANNU REV SOCIOL, V30, P359, DOI 10.1146/annurev.soc.30.012703.110640
   Hoffmann S, 2016, J CONSUM AFF, V50, P3, DOI 10.1111/joca.12104
   Hope ChrisW., 2011, SOCIAL COST CO2 PAGE, DOI [DOI 10.2139/SSRN.1973863, 10.2139/ssrn.1973863]
   INGLEHART R, 1995, PS, V28, P57, DOI 10.2307/420583
   Inglehart R., 1989, Cultural shift in advanced industrial society
   Inglehart Ronald., 1977, SILENT REVOLUTION
   Inglehart Ronald., 1997, Modernization and postmodernization: Cultural, economic, and political change in 43 societies, V19, DOI DOI 10.2307/591300
   Inglehart RF, 2008, WEST EUR POLIT, V31, P130, DOI 10.1080/01402380701834747
   Janssen M, 1998, ECOL ECON, V26, P43, DOI 10.1016/S0921-8009(97)00062-1
   Kahn ME, 2007, J ENVIRON ECON MANAG, V54, P129, DOI 10.1016/j.jeem.2007.05.001
   KIRMAN AP, 1992, J ECON PERSPECT, V6, P117, DOI 10.1257/jep.6.2.117
   Knight KW, 2012, SOC SCI QUART, V93, P521, DOI 10.1111/j.1540-6237.2012.00846.x
   Konig T., 2008, 404 LEIBN U HANN
   Lavoie M, 2006, EUR J ECON ECON POLI, V3, P87, DOI 10.4337/ejeep.2006.01.08
   Lee MSW, 2016, J CONSUM AFF, V50, P18, DOI 10.1111/joca.12089
   Lemoine D, 2014, AM ECON J-ECON POLIC, V6, P137, DOI 10.1257/pol.6.1.137
   Lengnick M, 2013, J ECON BEHAV ORGAN, V86, P102, DOI 10.1016/j.jebo.2012.12.021
   LUCAS RE, 1976, CARN ROCH CONF SERIE, V1, P19, DOI 10.1016/S0167-2231(76)80003-6
   Maier-Reimer E., 1987, CLIM DYNAM, V2, P63, DOI [10.1007/BF01054491, DOI 10.1007/BF01054491]
   Markowitz EM, 2012, ANAL SOC ISS PUB POL, V12, P167, DOI 10.1111/j.1530-2415.2011.01230.x
   Meadows DH., 2004, LIMITS GROWTH 30 YEA
   Meadows Donella H, 1972, FUTURE NATURE, P101
   Mostafa MM, 2013, SUSTAIN DEV, V21, P385, DOI 10.1002/sd.517
   Nayum A, 2014, J ENVIRON PSYCHOL, V40, P401, DOI 10.1016/j.jenvp.2014.10.001
   Nordhaus W, 2013, HANBOOK COMPUTATIONA, V1A-1B
   Nordhaus W.D., 2013, DICE 2013R INTRO USE
   Norgaard RB, 1998, ECOL ECON, V25, P37, DOI 10.1016/S0921-8009(98)00012-3
   Opschoor JB, 1998, ECOL ECON, V25, P41, DOI 10.1016/S0921-8009(98)00013-5
   Pepper M, 2009, INT J CONSUM STUD, V33, P126, DOI 10.1111/j.1470-6431.2009.00753.x
   Rezai A, 2013, ECOL ECON, V85, P69, DOI 10.1016/j.ecolecon.2012.10.008
   ROMER PM, 1990, J POLIT ECON, V98, pS71, DOI 10.1086/261725
   Roos M., 2015, Ruhr Economic Papers, V592
   Salle I, 2013, ECON MODEL, V34, P114, DOI 10.1016/j.econmod.2013.01.031
   Schwartz S.H., 2012, Online Readings in Psychology and Culture, V2, DOI [DOI 10.9707/2307-0919.1116, 10.9707/2307-0919.1116]
   Seegebarth B, 2016, J CONSUM AFF, V50, P68, DOI 10.1111/joca.12077
   Setterfield M., 2012, 1207 TRIN COLL DEP E
   Stern N., 2006, STERN REV EC CLIMATE
   Weil D. N, 2013, EC GROWTH
   Xepapadeas A, 2005, HANDB ECON, V20, P1219
NR 66
TC 9
Z9 11
U1 1
U2 29
PU SPRINGER
PI DORDRECHT
PA VAN GODEWIJCKSTRAAT 30, 3311 GZ DORDRECHT, NETHERLANDS
SN 0927-7099
EI 1572-9974
J9 COMPUT ECON
JI Comput. Econ.
PD OCT
PY 2018
VL 52
IS 3
SI SI
BP 995
EP 1028
DI 10.1007/s10614-017-9707-3
PG 34
WC Economics; Management; Mathematics, Interdisciplinary Applications
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Business & Economics; Mathematics
GA GV0IJ
UT WOS:000445742700010
OA hybrid
DA 2026-06-13
ER

PT J
AU Lamperti, F
   Dosi, G
   Napoletano, M
   Roventini, A
   Sapio, A
AF Lamperti, F.
   Dosi, G.
   Napoletano, M.
   Roventini, A.
   Sapio, A.
TI Faraway, So Close: Coupled Climate and Economic Dynamics in an
   Agent-based Integrated Assessment Model
SO ECOLOGICAL ECONOMICS
LA English
DT Article
DE Climate change; Agent-based models; Integrated assessment;
   Macro-economic dynamics; Climate damages
ID CARBON-DIOXIDE EXCHANGE; BUSINESS CYCLES; SOCIAL COST; GRANGER
   CAUSALITY; FISCAL-POLICIES; ATMOSPHERIC CO2; OUTPUT GROWTH; RISK;
   UNCERTAINTY; INVESTMENT
AB In this work we develop an agent-based model that offers an alternative to standard, computable general equilibrium integrated assessment models (IAMs). The Dystopian Schumpeter meeting Keynes (DSK) model is composed of heterogeneous firms belonging to capital-good, consumption-good and energy sectors. Production and energy generation lead to greenhouse gas emissions, which affect temperature dynamics. Climate damages are modelled at the individual level as stochastic shocks hitting workers' labour productivity, energy efficiency, capital stock and inventories of firms. In that, aggregate damages emerge from the aggregation of losses suffered by heterogeneous, interacting and boundedly rational agents. The model is run focusing on a business-as-usual carbon-intensive scenario consistent with a Representative Concentration Pathway 8.5. We find that the DSK model is able to account for a wide ensemble of micro- and macro-empirical regularities concerning both economic and climate dynamics. Simulation experiments show a substantial lack of isomorphism between the effects of micro- and macro-level shocks, as it is typical in complex system models. In particular, different types of shocks have heterogeneous impact on output growth, unemployment rate, and the likelihood of economic crises, pointing to the importance of the different economic channel affected by the shock. Overall, we report much larger climate damages than those projected by standard IAMs under comparable scenarios, suggesting possible shifts in the growth dynamics, from a self-sustained pattern to stagnation and high volatility, and the need of urgent policy interventions.
C1 [Lamperti, F.; Dosi, G.; Roventini, A.] Scuola Super Sant Anna, Inst Econ, Piazza Martiri Liberal 33, I-56127 Pisa, Italy.
   [Napoletano, M.] SKEMA Business Sch, OFCE, Nice, France.
   [Napoletano, M.] Univ Cote Azur, Nice, France.
   [Roventini, A.] OFCE, Nice, France.
   [Sapio, A.] Parthenope Univ Naples, Naples, Italy.
C3 Scuola Superiore Sant'Anna; SKEMA Business School; Universite Cote
   d'Azur; Universite Cote d'Azur; Parthenope University Naples
RP Lamperti, F (corresponding author), Scuola Super Sant Anna, Inst Econ, Piazza Martiri Liberal 33, I-56127 Pisa, Italy.
EM f.lamperti@sssup.it; g.dosi@santannapisa.it;
   mauro.napoletano@sciencespo.fr; a.roventini@santannapisa.it;
   alessandro.sapio@uniparthenope.it
RI ; ROVENTINI, Andrea/N-4699-2019
OI SAPIO, Alessandro/0000-0002-1221-5549; Lamperti,
   Francesco/0000-0003-4862-646X; Napoletano, Mauro/0000-0002-8128-6674;
   ROVENTINI, Andrea/0000-0001-5518-3084
FU European Union [603416, 640772, 649186]; Parthenope University of Naples
   "Bando di sostegno alla ricerca individuale per it triennio 2015-2017,
   annualita 2016"
FX FL, GD, AR and AS acknowledge financial support from the European Union
   FP7 grant agreement No. 603416 - Project IMPRESSIONS. GD, MN and AR
   acknowledge financial support from European Union's Horizon 2020 grant
   agreement No. 640772 - Project DOLFINS and No. 649186 - Project
   ISIGrowth. AS also acknowledges financial support from Parthenope
   University of Naples "Bando di sostegno alla ricerca individuale per it
   triennio 2015-2017, annualita 2016". The authors are indebted with
   Valentina Bosetti, Giorgio Fagiolo, Jill Jaeger, Mattia Guerini, Paula
   Harrison, Antoine Mandel, Irene Monestarolo and Willi Semmler for
   valuable comments and discussions that improved the quality of the
   paper. The authors also thank five anonymous referees, an associate
   editor and all the participants to the seminar series at PSE-Universite
   Paris 1 Pantheon-Sorbonne (Paris) and Fondazione Eni Enrico Mattei
   (FEEM, Milan) and to the following conferences or workshops: WEHIA 2015
   (Nice), EMAEE 2015 (Maastricht), WEHIA 2016 (Castellon), CEF 2016
   (Bordeaux), Annual Meeting of the International Schumpeter Society 2016
   (Montreal), the ISEE Workshop on Agent-based Modelling in Ecological
   Economics 2016 (Berlin), iEMS 2016 (Toulouse), 50th SPRU Anniversary
   Conference, Crisis2016 (Ancona), EAEPE 2016 (Manchester) and the first
   Hamburg Workshop on Agent-based Modeling of Environmental Challenges and
   Climate Policy (Hamburg). All the usual disclaimers apply.
CR Ackerman F, 2010, ECOL ECON, V69, P1657, DOI 10.1016/j.ecolecon.2010.03.013
   Albuquerque R, 2015, J MONETARY ECON, V76, pS21, DOI 10.1016/j.jmoneco.2015.09.010
   Allen L.H., 1995, Biotic Feedbacks in the Global Climatic System: Will the Warming Increase the Warming?, P51
   ALLEN LH, 1990, J ENVIRON QUAL, V19, P15, DOI 10.2134/jeq1990.00472425001900010002x
   [Anonymous], H.R. 3765, the Defined Contribution Plan Fee Transparency Act of 2007
   [Anonymous], 2012, EC ORG IND DYNAMICS
   [Anonymous], REV OFCE, DOI DOI 10.3917/reof.124.0067
   [Anonymous], [No title captured], DOI [DOI 10.1076/IAIJ.3.1.63.7407, 10.1076/iaij.3.1.63.7407]
   [Anonymous], 2003, EC IMPERFECT WORLD E
   [Anonymous], 2017, LEM WORKING PAPERS S
   [Anonymous], US Business Cycle Expansions and Contractions
   [Anonymous], LEM WORKING PAPER SE
   [Anonymous], EXTREME WEATHER GLOB
   [Anonymous], LEM PAPERS SERIES
   [Anonymous], 73183 MPRA U LIB MUN
   Assenza T, 2015, J ECON DYN CONTROL, V50, P5, DOI 10.1016/j.jedc.2014.07.001
   Attanasio A, 2012, ATMOS SCI LETT, V13, P67, DOI 10.1002/asl.365
   Ausloos M, 2004, PHYSICA A, V339, P548, DOI 10.1016/j.physa.2004.03.005
   Balint T, 2017, ECOL ECON, V138, P252, DOI 10.1016/j.ecolecon.2017.03.032
   Banerjee A., 1993, COINTEGRATION ERROR, DOI [10.1093/0198288107.001.0001, DOI 10.1093/0198288107.001.0001]
   Barde S, 2017, COMPUT ECON, V50, P281, DOI 10.1007/s10614-016-9617-9
   Bartelsman EJ, 2000, J ECON LIT, V38, P569, DOI 10.1257/jel.38.3.569
   Baxter M, 1999, REV ECON STAT, V81, P575, DOI 10.1162/003465399558454
   Berg M, 2015, NEW J PHYS, V17, DOI 10.1088/1367-2630/17/1/015011
   Berger L, 2017, MANAGE SCI, V63, P749, DOI 10.1287/mnsc.2015.2365
   Bottazzi G, 2003, REV IND ORGAN, V23, P217, DOI 10.1023/B:REIO.0000031366.28559.c1
   Bottazzi G, 2006, RAND J ECON, V37, P235, DOI 10.1111/j.1756-2171.2006.tb00014.x
   Brock W.A., 1988, EC EVOLVING COMPLEX, P77
   Burke M, 2015, NATURE, V527, P235, DOI 10.1038/nature15725
   Burns A.F., 1946, MEASURING BUSINESS C
   Cachon G.P., 2012, Severe weather and automobile assembly productivity, DOI [DOI 10.2139/SSRN.2099798, 10.2139/SSRN.2099798]
   Caporin M, 2017, ENERG ECON, V64, P511, DOI 10.1016/j.eneco.2016.07.024
   Carleton TA, 2016, SCIENCE, V353, DOI 10.1126/science.aad9837
   Castaldi C, 2009, EMPIR ECON, V37, P475, DOI 10.1007/s00181-008-0242-x
   Caves RE, 1998, J ECON LIT, V36, P1947
   Chiang JM, 2008, J INTEGR PLANT BIOL, V50, P1426, DOI 10.1111/j.1744-7909.2008.00749.x
   Ciscar J-C., REV BUSINESS EC LIT, V57, P144
   Ciscar JC, 2011, P NATL ACAD SCI USA, V108, P2678, DOI 10.1073/pnas.1011612108
   Claessens S., 2013, Financial Crises Explanations, Types, and Implications, DOI [10.5089/9781475561005.001, DOI 10.2139/SSRN.2295201]
   Claessens S, 2009, ECON POLICY, P653
   Clarke L, 2014, CLIMATE CHANGE 2014: MITIGATION OF CLIMATE CHANGE, P413
   Clarke L, 2009, ENERG ECON, V31, pS64, DOI 10.1016/j.eneco.2009.10.013
   Cox PM, 2000, NATURE, V408, P184, DOI 10.1038/35041539
   Cunado J, 2014, LAND ECON, V90, P149, DOI 10.3368/le.90.1.149
   Dafermos Y, 2017, ECOL ECON, V131, P191, DOI 10.1016/j.ecolecon.2016.08.013
   Daly H.E., 1991, Steady-State Economics, V2nd
   DeCanio SJ, 1998, REV ECON STAT, V80, P95, DOI 10.1162/003465398557366
   Del Boca A, 2008, J EUR ECON ASSOC, V6, P864, DOI 10.1162/JEEA.2008.6.4.864
   Dell M, 2014, J ECON LIT, V52, P740, DOI 10.1257/jel.52.3.740
   Dell M, 2012, AM ECON J-MACROECON, V4, P66, DOI 10.1257/mac.4.3.66
   Dietz S, 2016, NAT CLIM CHANGE, V6, P676, DOI [10.1038/NCLIMATE2972, 10.1038/nclimate2972]
   Doda B, 2014, J MACROECON, V40, P214, DOI 10.1016/j.jmacro.2014.01.003
   Doms M, 1998, REV ECON DYNAM, V1, P409, DOI 10.1006/redy.1998.0011
   Dosi G., 2006, Computational Economics, V27, P3, DOI 10.1007/s10614-005-9014-2
   DOSI G, 1988, J ECON LIT, V26, P1120
   Dosi G., 2016, 201639 LEM
   Dosi G, 2017, LEM PAPERS SERIES
   Dosi G., 2007, PERSPECTIVES INNOVAT, P1110
   Dosi G, 2017, J EVOL ECON, V27, P63, DOI 10.1007/s00191-016-0466-4
   Dosi G, 2015, J ECON DYN CONTROL, V52, P166, DOI 10.1016/j.jedc.2014.11.014
   Dosi G, 2013, J ECON DYN CONTROL, V37, P1598, DOI 10.1016/j.jedc.2012.11.008
   Dosi G, 2010, J ECON DYN CONTROL, V34, P1748, DOI 10.1016/j.jedc.2010.06.018
   EISNER R, 1972, REV ECON STAT, V54, P297, DOI 10.2307/1937991
   Emmerling J., 2016, The WITCH 2016 model - documentation and implementation of the shared socioeconomic pathways
   EU, 2014, EUR COMP REP 2014 HE
   Fabra N, 2005, INT J IND ORGAN, V23, P155, DOI 10.1016/j.ijindorg.2005.01.004
   Fagiolo G., 2019, Computer Simulation Validation, P763, DOI [10.1007/978-3-319-70766-2_31, DOI 10.1007/978-3-319-70766-2_31]
   Fagiolo G., 2007, COMPUT ECON, V30, P189, DOI [10.1007/s10614-007-9109-z, DOI 10.1007/S10614-007-9109-Z]
   Fagiolo G, 2008, J APPL ECONOMET, V23, P639, DOI 10.1002/jae.1003
   Fagiolo G, 2017, JASSS-J ARTIF SOC S, V20, DOI 10.18564/jasss.3280
   Farmer JD, 2015, ENVIRON RESOUR ECON, V62, P329, DOI 10.1007/s10640-015-9965-2
   Farmer JD, 2009, NATURE, V460, P685, DOI 10.1038/460685a
   FELDSTEIN MS, 1971, REV ECON STAT, V53, P49, DOI 10.2307/1925378
   Field CB, 2014, CLIMATE CHANGE 2014: IMPACTS, ADAPTATION, AND VULNERABILITY, PT A: GLOBAL AND SECTORAL ASPECTS, P1
   Flake G.W., 1988, COMPUTATIONAL BEAUTY
   Fontana G, 2016, ECOL ECON, V121, P186, DOI 10.1016/j.ecolecon.2015.03.017
   Foos D, 2010, J BANK FINANC, V34, P2929, DOI 10.1016/j.jbankfin.2010.06.007
   Friedlingstein P, 2006, J CLIMATE, V19, P3337, DOI 10.1175/JCLI3800.1
   FUNG I, 1993, BIOGEOCHEMISTRY OF GLOBAL CHANGE, P166
   Georgescu-Roegen Nicholas., 1993, VALUING EARTH EC ECO, P75
   Gerst MD, 2013, ENVIRON MODELL SOFTW, V44, P62, DOI 10.1016/j.envsoft.2012.09.002
   Gerst MD, 2010, ENERG POLICY, V38, P4540, DOI 10.1016/j.enpol.2010.04.008
   Ghil M., 2007, WORKING PAPERS
   Gillingham K., 2015, Modeling uncertainty in climate change: a multi-model comparison
   Golosov M, 2014, ECONOMETRICA, V82, P41, DOI 10.3982/ECTA10217
   Goolsbee A, 1998, REV ECON DYNAM, V1, P474, DOI 10.1006/redy.1998.0012
   GOUDRIAAN J, 1984, CLIMATIC CHANGE, V6, P167, DOI 10.1007/BF00144611
   GREENWALD BC, 1993, Q J ECON, V108, P77, DOI 10.2307/2118496
   Guerini M., 2016, METHOD AGENT B UNPUB
   Hallegatte S., 2007, World Economics-Henley on Thames, V8, P131
   Hansen J, 2013, PLOS ONE, V8, DOI [10.1371/journal.pone.0081648, 10.1371/journal.pone.0080954]
   Hardt L, 2017, ECOL ECON, V134, P198, DOI 10.1016/j.ecolecon.2016.12.027
   Harvey D., 1997, INTRO SIMPLE CLIMATE
   Hasselmann K, 2013, ENVIRON MODELL SOFTW, V44, P10, DOI 10.1016/j.envsoft.2012.04.007
   Hope C., 2006, Integrated Assessment Journal, V6, P19
   Hsiang S, 2017, SCIENCE, V356, P1362, DOI 10.1126/science.aal4369
   Jaeger CC, 2011, REG ENVIRON CHANGE, V11, pS15, DOI 10.1007/s10113-010-0190-9
   KATZ RW, 1992, CLIMATIC CHANGE, V21, P289, DOI 10.1007/BF00139728
   Kirman A, 2016, MACROECON DYN, V20, P601, DOI 10.1017/S1365100514000339
   Kirtman B., 2013, CLIMATE CHANGE 2013, DOI [10.1101/2021.02.17.21251867, DOI 10.1017/CBO9781107415324]
   Kuznets Simon., 1966, Modern Economic Growth: Rate, Structure, and Spread
   Lamperti F, 2015, LEM PAPERS SERIES, V2015/02, DOI [10.2139/ssrn.2709577, DOI 10.2139/SSRN.2709577]
   Lamperti F, 2018, ECONOMET STAT, V5, P83, DOI 10.1016/j.ecosta.2017.01.006
   Leary MT, 2009, J FINANC, V64, P1143, DOI 10.1111/j.1540-6261.2009.01461.x
   Lengnick M, 2013, J ECON BEHAV ORGAN, V86, P102, DOI 10.1016/j.jebo.2012.12.021
   Lenton TM, 2013, CLIMATIC CHANGE, V117, P585, DOI 10.1007/s10584-012-0572-8
   Lown C, 2006, J MONEY CREDIT BANK, V38, P1575, DOI 10.1353/mcb.2006.0086
   Mattei C.E., 2016, TECHNICAL REPORT
   Matthews HD, 2007, GLOBAL CHANGE BIOL, V13, P1068, DOI 10.1111/j.1365-2486.2007.01343.x
   Mendoza EG, 2012, ECON CHIL, V15, P4
   Monasterolo I, 2018, ECOL ECON, V144, P228, DOI 10.1016/j.ecolecon.2017.07.029
   Moosa I.A., 2000, OPEC Rev., V24, P53, DOI [DOI 10.1111/1468-0076.00074, DOI 10.1111/1468-0076.00074., 10.1111/1468-0076.00074]
   Moss S, 2002, P NATL ACAD SCI USA, V99, P7267, DOI 10.1073/pnas.092080699
   Moss S., 2001, Integrated Assessment, V2, P17, DOI [DOI 10.1023/A:1011527523183, 10.1023/A:1011527523183]
   Napoletano M., 2006, Rivista italiana degli economisti, V11, P87, DOI DOI 10.1427/23296:Y:2006:I:1:P:87-118
   Naqvi A, 2015, WWWFOREUROPE POLICY, V18
   Nordhaus W.D., 2013, DICE 2013R INTRO USE
   Nordhaus W.D., 2008, QUESTION BALANCE WEI
   Nordhaus WD, 1996, AM ECON REV, V86, P741
   NORDHAUS WD, 1992, SCIENCE, V258, P1315, DOI 10.1126/science.258.5086.1315
   Nordhaus W, 2014, J ASSOC ENVIRON RESO, V1, P273, DOI 10.1086/676035
   Nordhaus WD, 2017, P NATL ACAD SCI USA, V114, P1518, DOI 10.1073/pnas.1609244114
   OESCHGER H, 1975, TELLUS, V27, P168, DOI 10.1111/j.2153-3490.1975.tb01671.x
   Olivier JosG. J., 2015, Trends in Global CO2 emissions: 2015 report
   OSTERWALDLENUM M, 1992, OXFORD B ECON STAT, V54, P461, DOI 10.1111/j.1468-0084.1992.tb00013.x
   Ozturk I, 2010, ENERG POLICY, V38, P340, DOI 10.1016/j.enpol.2009.09.024
   Pachauri R.K., 2007, IPCC fourth assessment report, DOI [10.1111/j.1728-4457.2001.00203.x, DOI 10.1111/J.1728-4457.2001.00203.X]
   Peters GP, 2012, NAT CLIM CHANGE, V2, P2, DOI 10.1038/nclimate1332
   Petrick S., 2013, Carbon efficiency, technology, and the role of innovation patterns: Evidence from German plant-level microdata
   Phelps EdmundS., 1970, Microeconomic Foundations of Employment and In?ation Theory
   Pindyck RS, 2013, J ECON LIT, V51, P860, DOI 10.1257/jel.51.3.860
   Pindyck RS, 2012, J ENVIRON ECON MANAG, V63, P289, DOI 10.1016/j.jeem.2011.12.001
   [Portner H.-O. IPCC IPCC], 2019, Climate change 2022-Impacts, adaptation and vulnerability, DOI [10.1017/9781009325844.001, 10.1017/9781009157926.001, DOI 10.1017/9781009157926.001, DOI 10.1017/9781009325844]
   Reilly J, 2013, CLIMATIC CHANGE, V117, P561, DOI 10.1007/s10584-012-0635-x
   Renton M, 2014, ENVIRON CONSERV, V41, P110, DOI 10.1017/S0376892913000490
   REVELLE R, 1957, TELLUS, V9, P18, DOI 10.1111/j.2153-3490.1957.tb01849.x
   Revesz RL, 2014, NATURE, V508, P173, DOI 10.1038/508173a
   Rezai A, 2013, ECOL ECON, V85, P69, DOI 10.1016/j.ecolecon.2012.10.008
   Riahi K, 2011, CLIMATIC CHANGE, V109, P33, DOI 10.1007/s10584-011-0149-y
   Riccetti L, 2013, J ECON DYN CONTROL, V37, P1626, DOI 10.1016/j.jedc.2013.02.008
   Rogelj J, 2016, NATURE, V534, P631, DOI 10.1038/nature18307
   Rotemberg J.J, 2008, TECHNICAL REPORT
   Rotmans J, 1990, IMAGE INTEGRATED MOD, V1
   Safarzynska K, 2017, TECHNOL FORECAST SOC, V114, P119, DOI 10.1016/j.techfore.2016.07.033
   Sarmiento JL, 1998, NATURE, V393, P245, DOI 10.1038/30455
   Schellnhuber HJ, 2010, CLIMATIC CHANGE, V100, P229, DOI 10.1007/s10584-010-9838-1
   Schleussner CF, 2016, EARTH SYST DYNAM, V7, P327, DOI 10.5194/esd-7-327-2016
   SCHNEIDER SH, 1981, J GEOPHYS RES-OCEANS, V86, P3135, DOI 10.1029/JC086iC04p03135
   Schumpeter JA., 1934, THEORY EC DEV
   Seppanen O, 2006, TECHNICAL REPORT
   Seppanen O., 2003, COST BENEFIT ANAL NI
   Shaver GR, 2000, BIOSCIENCE, V50, P871, DOI 10.1641/0006-3568(2000)050[0871:GWATEA]2.0.CO;2
   Sterman J, 2012, SYST DYNAM REV, V28, P295, DOI 10.1002/sdr.1474
   Sterman JD, 2013, ENVIRON MODELL SOFTW, V44, P122, DOI 10.1016/j.envsoft.2012.06.004
   Stern N, 2016, NATURE, V530, P407, DOI 10.1038/530407a
   Stern N, 2013, J ECON LIT, V51, P838, DOI 10.1257/jel.51.3.838
   STIGLITZ JE, 1981, AM ECON REV, V71, P393
   Stock JH, 1999, HBK ECON, V15, P3
   Tesfatsion L, 2006, HANDB ECON, V13, P831
   Thoma M, 2004, ENERG ECON, V26, P463, DOI 10.1016/j.eneco.2004.04.006
   Thomalla F, 2006, DISASTERS, V30, P39, DOI 10.1111/j.1467-9523.2006.00305.x
   Tidball R., 2010, Contract, V303, P275
   Tol R.S.J., 2015, WORKING PAPER SERIES, V7515
   Tol RSJ, 2009, J ECON PERSPECT, V23, P29, DOI 10.1257/jep.23.2.29
   Tol RichardS.J., 1997, Environmental Modelling and Assessment, V2, P151, DOI [DOI 10.1023/A:1019017529030, 10.1023/A:1019017529030]
   Tol RSJ, 2002, ENVIRON RESOUR ECON, V21, P135, DOI 10.1023/A:1014539414591
   Triacca U, 2001, THEOR APPL CLIMATOL, V69, P137, DOI 10.1007/s007040170019
   van Vuuren DP, 2011, CLIMATIC CHANGE, V104, P255, DOI 10.1007/s10584-009-9764-2
   Wälde K, 2004, ECON LETT, V82, P91, DOI 10.1016/j.econlet.2003.07.014
   Weitzman ML, 2013, J ECON LIT, V51, P873, DOI 10.1257/jel.51.3.873
   Weitzman ML, 2011, REV ENV ECON POLICY, V5, P275, DOI 10.1093/reep/rer006
   Weitzman ML, 2009, REV ECON STAT, V91, P1, DOI 10.1162/rest.91.1.1
   Weyant J, 2017, REV ENV ECON POLICY, V11, P115, DOI 10.1093/reep/rew018
   Windrum P, 2007, JASSS-J ARTIF SOC S, V10
   Wolf S, 2013, ENVIRON MODELL SOFTW, V44, P25, DOI 10.1016/j.envsoft.2012.12.012
   Wright I, 2005, PHYSICA A, V345, P608, DOI 10.1016/j.physa.2004.07.035
   Wullschleger S.D., 1995, Biotic Feedbacks in the Global Climatic System: Will the Warming Feed the Warming?, P85, DOI [DOI 10.1093/OSO/9780195086409.003.0005, 10.1093/oso/9780195086409.003.0005]
   ZARNOWITZ V, 1985, J ECON LIT, V23, P523
   Zhao MS, 2010, SCIENCE, V329, P940, DOI [10.1126/science.1192666, 10.1126/science.1189590]
NR 179
TC 132
Z9 160
U1 5
U2 79
PU ELSEVIER
PI AMSTERDAM
PA RADARWEG 29, 1043 NX AMSTERDAM, NETHERLANDS
SN 0921-8009
EI 1873-6106
J9 ECOL ECON
JI Ecol. Econ.
PD AUG
PY 2018
VL 150
BP 315
EP 339
DI 10.1016/j.ecolecon.2018.03.023
PG 49
WC Ecology; Economics; Environmental Sciences; Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Business & Economics
GA GT2XQ
UT WOS:000444364000028
DA 2026-06-13
ER

PT J
AU Barfuss, W
   Donges, JF
   Lade, SJ
   Kurths, J
AF Barfuss, Wolfram
   Donges, Jonathan F.
   Lade, Steven J.
   Kurths, Juergen
TI When optimization for governing human-environment tipping elements is
   neither sustainable nor safe
SO NATURE COMMUNICATIONS
LA English
DT Article
ID REGIME SHIFTS; INTEGRATED ASSESSMENT; OPERATING SPACES; CLIMATE;
   RESILIENCE; MANAGEMENT; CONSEQUENCES; UNCERTAINTY; FRAMEWORK; DYNAMICS
AB Optimizing economic welfare in environmental governance has been criticized for delivering short-term gains at the expense of long-term environmental degradation. Different from economic optimization, the concepts of sustainability and the more recent safe operating space have been used to derive policies in environmental governance. However, a formal comparison between these three policy paradigms is still missing, leaving policy makers uncertain which paradigm to apply. Here, we develop a better understanding of their interrelationships, using a stylized model of human-environment tipping elements. We find that no paradigm guarantees fulfilling requirements imposed by another paradigm and derive simple heuristics for the conditions under which these trade-offs occur. We show that the absence of such a master paradigm is of special relevance for governing real-world tipping systems such as climate, fisheries, and farming, which may reside in a parameter regime where economic optimization is neither sustainable nor safe.
C1 [Barfuss, Wolfram; Donges, Jonathan F.; Kurths, Juergen] Potsdam Inst Climate Impact Res, D-14473 Potsdam, Germany.
   [Barfuss, Wolfram; Kurths, Juergen] Humboldt Univ, Dept Phys, D-12489 Berlin, Germany.
   [Donges, Jonathan F.; Lade, Steven J.] Stockholm Univ, Stockholm Resilience Ctr, S-11419 Stockholm, Sweden.
   [Lade, Steven J.] Australian Natl Univ, Fenner Sch Environm & Soc, Canberra, ACT 2601, Australia.
   [Kurths, Juergen] Saratov NG Chernyshevskii State Univ, Saratov 410012, Russia.
C3 Potsdam Institut fur Klimafolgenforschung; Humboldt University of
   Berlin; Stockholm University; Australian National University; Saratov
   State University
RP Barfuss, W (corresponding author), Potsdam Inst Climate Impact Res, D-14473 Potsdam, Germany.; Barfuss, W (corresponding author), Humboldt Univ, Dept Phys, D-12489 Berlin, Germany.
EM barfuss@pik-potsdam.de
RI Donges, Jonathan/HCI-2311-2022; Kurths, Juergen/I-4366-2013; Lade,
   Steven/AAH-2699-2019
OI Donges, Jonathan/0000-0001-5233-7703; Lade, Steven/0000-0001-9719-9826;
   Barfuss, Wolfram/0000-0002-9077-5242
FU Heinrich-Boll-Foundation; Stordalen Foundation (Planetary Boundaries
   Research Network PB.net); Earth League's EarthDoc program; Leibniz
   Association (project DOMINOES); Swedish Research Council Formas
   [2014-589]
FX This work was developed in the context of the COPAN project on
   Coevolutionary Pathways in the Earth system at the Potsdam Institute for
   Climate Impact Research. The authors are grateful for financial support
   from the Heinrich-Boll-Foundation, the Stordalen Foundation (via the
   Planetary Boundaries Research Network PB.net), the Earth League's
   EarthDoc program, the Leibniz Association (project DOMINOES) and the
   Swedish Research Council Formas (Project Grant 2014-589). We thank David
   Collste, Jobst Heitzig, Antoine Levesque, Finn Muller-Hansen and Maja
   Schluter for discussions and comments on the manuscript.
CR Ackerman F, 2009, CLIMATIC CHANGE, V95, P297, DOI 10.1007/s10584-009-9570-x
   Altman Eitan., 1999, CONSTRAINED MARKOV D, V7
   Anderies JM, 2007, P NATL ACAD SCI USA, V104, P15194, DOI 10.1073/pnas.0702655104
   [Anonymous], 1987, TECHNICAL REPORT
   Arrow KJ, 2012, ENVIRON DEV ECON, V17, P317, DOI 10.1017/S1355770X12000137
   BELLMAN R, 1957, J MATH MECH, V6, P679, DOI 10.1512/iumj.1957.6.56038
   BELLMAN R, 1966, SCIENCE, V153, P34, DOI 10.1126/science.153.3731.34
   Blaikie P., 1987, Land Degradation and Society, DOI DOI 10.4324/9781315685366
   Branke J., 2008, Multi-objective optimization: interactive and evolutionary approaches
   Caddy JF, 2004, REV FISH BIOL FISHER, V14, P43, DOI 10.1007/s11160-004-3770-2
   Cai YY, 2016, NAT CLIM CHANGE, V6, P520, DOI [10.1038/nclimate2964, 10.1038/NCLIMATE2964]
   Carpenter SR, 2015, P NATL ACAD SCI USA, V112, P14384, DOI 10.1073/pnas.1511804112
   Chadès I, 2017, THEOR ECOL-NETH, V10, P1, DOI 10.1007/s12080-016-0313
   Clark PU, 2016, NAT CLIM CHANGE, V6, P360, DOI 10.1038/NCLIMATE2923
   Costello C, 2008, SCIENCE, V321, P1678, DOI 10.1126/science.1159478
   Crépin AS, 2012, ECOL ECON, V84, P15, DOI 10.1016/j.ecolecon.2012.09.003
   Dasgupta P, 2006, EC NONCONVEX ECOSYST, V4
   De Lara M., 2008, Sustainable management of natural resources. Mathematical models and methods
   Dearing JA, 2014, GLOBAL ENVIRON CHANG, V28, P227, DOI 10.1016/j.gloenvcha.2014.06.012
   Derissen S, 2011, ECOL ECON, V70, P1121, DOI 10.1016/j.ecolecon.2011.01.003
   Donges JF, 2017, ANTHROPOCENE REV, V4, P151, DOI 10.1177/2053019617725537
   Donges JF, 2017, GAIA, V26, P182, DOI 10.14512/gaia.26.S1.5
   Ehrgott M., 2006, Multicriteria Optimization
   Farmer JD, 2015, ENVIRON RESOUR ECON, V62, P329, DOI 10.1007/s10640-015-9965-2
   Fischer J, 2009, TRENDS ECOL EVOL, V24, P549, DOI 10.1016/j.tree.2009.03.020
   Fleurbaey M, 2015, J ENVIRON ECON MANAG, V71, P34, DOI 10.1016/j.jeem.2015.02.005
   Folke C, 2010, ECOL SOC, V15
   Ganopolski A, 2016, NATURE, V529, P200, DOI 10.1038/nature16494
   Gerlagh R, 2017, ECOL ECON, V136, P94, DOI 10.1016/j.ecolecon.2017.02.012
   Greco S., 2005, MULTIPLE CRITERIA DE
   Griggs D, 2013, NATURE, V495, P305, DOI 10.1038/495305a
   Heitzig J, 2016, EARTH SYST DYNAM, V7, P21, DOI 10.5194/esd-7-21-2016
   Horrigan L, 2002, ENVIRON HEALTH PERSP, V110, P445, DOI 10.1289/ehp.02110445
   Hutchings JA, 2004, BIOSCIENCE, V54, P297, DOI 10.1641/0006-3568(2004)054[0297:MFPCCF]2.0.CO;2
   Irwin EG, 2016, ANNU REV RESOUR ECON, V8, P77, DOI 10.1146/annurev-resource-100815-095351
   Kinzig AP, 2006, ECOL SOC, V11
   Lade SJ, 2013, THEOR ECOL-NETH, V6, P359, DOI 10.1007/s12080-013-0187-3
   Lenton TM, 2008, P NATL ACAD SCI USA, V105, P1786, DOI 10.1073/pnas.0705414105
   Lontzek TS, 2015, NAT CLIM CHANGE, V5, P441, DOI [10.1038/nclimate2570, 10.1038/NCLIMATE2570]
   Mäler KG, 2010, ENVIRON DEV ECON, V15, P707, DOI 10.1017/S1355770X10000318
   Martinet V, 2007, RESOUR ENERGY ECON, V29, P17, DOI 10.1016/j.reseneeco.2006.03.003
   Meadows P, 1972, THE LIMITS OF GROWTH, V381
   Möllmann C, 2009, GLOBAL CHANGE BIOL, V15, P1377, DOI 10.1111/j.1365-2486.2008.01814.x
   Neumayer E., 2010, Weak versus strong sustainability : exploring the limits of two opposing paradigms, DOI DOI 10.4337/9781849805438
   Nordhaus WD, 2007, J ECON LIT, V45, P686, DOI 10.1257/jel.45.3.686
   Österblom H, 2007, ECOSYSTEMS, V10, P877, DOI 10.1007/s10021-007-9069-0
   Perman Roger., 2011, NATURAL RESOURCE ENV, V4th
   Petschel- Held G, 1999, CLIMATIC CHANGE, V41, P303, DOI 10.1023/A:1005487123751
   Pezzey J., 1992, World, V1, P45
   Pezzey JCV, 2004, J ENVIRON ECON MANAG, V48, P613, DOI 10.1016/j.jeem.2003.10.002
   Pezzey JCV, 1997, LAND ECON, V73, P448, DOI 10.2307/3147239
   Polasky S, 2011, J ENVIRON ECON MANAG, V62, P229, DOI 10.1016/j.jeem.2010.09.004
   Polasky S, 2011, TRENDS ECOL EVOL, V26, P398, DOI 10.1016/j.tree.2011.04.007
   Puterman M.L., 1994, MARKOV DECISION PROC, V1st, DOI [DOI 10.1002/9780470316887, 10.1002/9780470316887]
   Raffensperger Carolyn., 1999, Protecting Public Health the Environment
   Raworth K, 2017, LANCET PLANET HEALTH, V1, pE48, DOI 10.1016/S2542-5196(17)30028-1
   Rocha J, 2015, PHILOS T R SOC B, V370, DOI 10.1098/rstb.2013.0273
   Rockström J, 2017, SCIENCE, V355, P1269, DOI 10.1126/science.aah3443
   Rockström J, 2009, NATURE, V461, P472, DOI 10.1038/461472a
   Rougé C, 2013, ECOL INDIC, V29, P420, DOI 10.1016/j.ecolind.2012.12.032
   Scheffer M, 2001, NATURE, V413, P591, DOI 10.1038/35098000
   Schellnhuber HJ, 2016, NAT CLIM CHANGE, V6, P649, DOI 10.1038/nclimate3013
   Schellnhuber HJ, 2009, P NATL ACAD SCI USA, V106, P20561, DOI 10.1073/pnas.0911106106
   Schellnhuber HJ, 1999, NATURE, V402, pC19, DOI 10.1038/35011515
   Steffen W, 2015, SCIENCE, V347, DOI 10.1126/science.1259855
   Stern N, 2008, AM ECON REV, V98, P1, DOI 10.1257/aer.98.2.1
   Weyant J, 2014, J BENEFIT-COST ANAL, V5, P377, DOI 10.1515/jbca-2014-9002
   Woodward RT, 2014, ENVIRON MANAGE, V54, P828, DOI 10.1007/s00267-014-0348-1
   Worm B, 2009, SCIENCE, V325, P578, DOI 10.1126/science.1173146
NR 69
TC 36
Z9 40
U1 0
U2 37
PU NATURE PORTFOLIO
PI BERLIN
PA HEIDELBERGER PLATZ 3, BERLIN, 14197, GERMANY
EI 2041-1723
J9 NAT COMMUN
JI Nat. Commun.
PD JUN 15
PY 2018
VL 9
AR 2354
DI 10.1038/s41467-018-04738-z
PG 10
WC Multidisciplinary Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Science & Technology - Other Topics
GA GJ5QV
UT WOS:000435438000004
PM 29907743
OA Green Submitted, gold
DA 2026-06-13
ER

PT J
AU Taylor, L
   Rezai, A
   Foley, DK
AF Taylor, Lance
   Rezai, Armon
   Foley, Duncan K.
TI An integrated approach to climate change, income distribution,
   employment, and economic growth
SO ECOLOGICAL ECONOMICS
LA English
DT Article
DE Demand-driven growth; Climate change; Demand and distribution; Energy
   use; Energy productivity; Labor productivity; Employment
ID INEQUALITY
AB A demand-driven growth model involving capital accumulation and the dynamics of greenhouse gas (GHG) concentration is set up to examine macroeconomic issues raised by global warming, e.g. effects on output and employment of rising levels of GHG; offsets by mitigation; relationships among energy use and labor productivity, income distribution, and growth; the economic significance of the Jevons and other paradoxes; sustainable consumption and possible reductions in employment; and sources of instability and cyclicality implicit in the two-dimensional dynamical system. The emphasis is on the combination of biophysical limits and Post Keynesian growth theory and the qualitative patterns of system adjustment and the dynamics that emerge. (C) 2015 Elsevier B.V. All rights reserved.
C1 [Taylor, Lance; Foley, Duncan K.] New Sch Social Res, Dept Econ, New York, NY 10011 USA.
   [Rezai, Armon] WU Vienna Univ Econ & Business, Dept Socioecon, Vienna, Austria.
   [Rezai, Armon] IIASA, Vienna, Austria.
C3 The New School; Vienna University of Economics & Business; International
   Institute for Applied Systems Analysis (IIASA)
RP Rezai, A (corresponding author), Welthandelspl 1, A-1020 Vienna, Austria.
EM arezai@wu.ac.at
OI Rezai, Armon/0000-0002-6598-7307; Foley, Duncan/0000-0003-3394-8888
FU Institute for New Economic Thinking; OeNB Anniversary Fund [15330]
FX This research was conducted under the Research Project on
   Sustainability, Distribution, and Stability supported by the Institute
   for New Economic Thinking. Rezai also acknowledges financial support
   from the OeNB Anniversary Fund (grant no. 15330).
CR [Anonymous], THAMES PAPERS EC
   Campiglio E, 2016, ECOL ECON, V121, P220, DOI 10.1016/j.ecolecon.2015.03.020
   Carvalho Laura, 2015, CAMB J EC IN PRESS
   Foley DK, 2013, ECON LETT, V121, P90, DOI 10.1016/j.econlet.2013.07.006
   Fontana G, 2016, ECOL ECON, V121, P186, DOI 10.1016/j.ecolecon.2015.03.017
   Goodwin R., 1967, Socialism, Capitalism and Economic Growth
   Hirsch MW, 2013, DIFFERENTIAL EQUATIONS, DYNAMICAL SYSTEMS, AND AN INTRODUCTION TO CHAOS, 3RD EDITION, P1
   Howarth RB, 2016, ECOL ECON, V121, P231, DOI 10.1016/j.ecolecon.2015.10.005
   Jackson T, 2016, ECOL ECON, V121, P206, DOI 10.1016/j.ecolecon.2015.03.019
   Jackson Tim., 2009, Prosperity Without Growth? The Transition to a Sustainable Economy
   Kaldor Nicholas., 1978, FURTHER ESSAYS EC TH
   Kaldor Nicholas, 1957, ECON J, V67, P594
   Kalecki M., 1971, Selected Essays in the Dynamics of the Capitalist Economy 19331970
   Keynes JohnMaynard., 1973, GEN THEORY EMPLOYMEN
   Naqvi S. A. Asjad, 2015, ECOLOGICAL EC PAPERS, V2
   Nordhaus William D., 2010, QUESTION BALANCE WEI
   Rezai A, 2013, ECOL ECON, V85, P69, DOI 10.1016/j.ecolecon.2012.10.008
   Rezai A, 2012, ECON THEOR, V49, P329, DOI 10.1007/s00199-010-0592-4
   Ropke I, 2016, ECOL ECON, V121, P237, DOI 10.1016/j.ecolecon.2015.03.018
   SAMUELSON PA, 1965, AM ECON REV, V55, P486
   Schor J.B., 2010, PLENITUDE NEW EC TRU
   SEN AK, 1966, J POLIT ECON, V74, P425, DOI 10.1086/259198
   Smil V., 2005, Energy at the Crossroads: Global Perspective and Uncertainties, p427 pp
   Taylor L., 2009, Twenty-First Century Macroeconomics. Responding to the Climate Challenge
   Taylor L., 2010, Maynards Revenge: The Collapse of Free Market Macroeconomics
   Victor P.A., 2008, MANAGING GROWTH SLOW
   Waggoner PE, 2002, P NATL ACAD SCI USA, V99, P7860, DOI 10.1073/pnas.122235999
   Zwickl K, 2016, ECOL ECON, V121, P246, DOI 10.1016/j.ecolecon.2015.06.009
NR 28
TC 80
Z9 97
U1 2
U2 68
PU ELSEVIER SCIENCE BV
PI AMSTERDAM
PA PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS
SN 0921-8009
EI 1873-6106
J9 ECOL ECON
JI Ecol. Econ.
PD JAN
PY 2016
VL 121
BP 196
EP 205
DI 10.1016/j.ecolecon.2015.05.015
PG 10
WC Ecology; Economics; Environmental Sciences; Environmental Studies
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Environmental Sciences & Ecology; Business & Economics
GA DD1KL
UT WOS:000369680500020
OA Green Submitted
DA 2026-06-13
ER

PT J
AU Garrett, TJ
AF Garrett, T. J.
TI No way out? The double-bind in seeking global prosperity alongside
   mitigated climate change
SO EARTH SYSTEM DYNAMICS
LA English
DT Article
ID OCEAN CO2 SINK; ATMOSPHERIC CO2; CARBON; EFFICIENT
AB In a prior study (Garrett, 2011), I introduced a simple economic growth model designed to be consistent with general thermodynamic laws. Unlike traditional economic models, civilization is viewed only as a well-mixed global whole with no distinction made between individual nations, economic sectors, labor, or capital investments. At the model core is a hypothesis that the global economy's current rate of primary energy consumption is tied through a constant to a very general representation of its historically accumulated wealth. Observations support this hypothesis, and indicate that the constant's value is lambda = 9.7 +/- 0.3 milliwatts per 1990 US dollar. It is this link that allows for treatment of seemingly complex economic systems as simple physical systems. Here, this growth model is coupled to a linear formulation for the evolution of globally well-mixed atmospheric CO2 concentrations. While very simple, the coupled model provides faithful multi-decadal hindcasts of trajectories in gross world product (GWP) and CO2. Extending the model to the future, the model suggests that the well-known IPCC SRES scenarios substantially underestimate how much CO2 levels will rise for a given level of future economic prosperity. For one, global CO2 emission rates cannot be decoupled from wealth through efficiency gains. For another, like a long-term natural disaster, future greenhouse warming can be expected to act as an inflationary drag on the real growth of global wealth. For atmospheric CO2 concentrations to remain below a "dangerous" level of 450 ppmv (Hansen et al., 2007), model forecasts suggest that there will have to be some combination of an unrealistically rapid rate of energy decarbonization and nearly immediate reductions in global civilization wealth. Effectively, it appears that civilization may be in a double-bind. If civilization does not collapse quickly this century, then CO2 levels will likely end up exceeding 1000 ppmv; but, if CO2 levels rise by this much, then the risk is that civilization will gradually tend towards collapse.
C1 Univ Utah, Dept Atmospher Sci, Salt Lake City, UT 84112 USA.
C3 Utah System of Higher Education; University of Utah
RP Garrett, TJ (corresponding author), Univ Utah, Dept Atmospher Sci, Salt Lake City, UT 84112 USA.
EM tim.garrett@utah.edu
OI Garrett, Timothy/0000-0001-9277-8773
FU Ewing Marion Kauffman Foundation
FX Writing of this article benefited from a helpful review by Carsten
   Hermann-Pillath, discussions about Economics with Steve Bannister, Harry
   Saunders, Clint Schmidt, Todd Kiefer, and Richard Fowles, and Earth
   System Models with Court Strong. This research was funded in part by the
   Ewing Marion Kauffman Foundation whose views it does not represent.
CR AER - Annual Energy Review, 2009, DOEEIA03842009
   Alcott B, 2005, ECOL ECON, V54, P9, DOI 10.1016/j.ecolecon.2005.03.020
   Alcott B, 2010, J CLEAN PROD, V18, P552, DOI 10.1016/j.jclepro.2009.08.001
   Allan RP, 2008, SCIENCE, V321, P1481, DOI 10.1126/science.1160787
   Annila A, 2009, ENTROPY-SWITZ, V11, P606, DOI 10.3390/e11040606
   [Anonymous], REBOUND EFFECT
   Ayres RU, 2003, ENERGY, V28, P219, DOI 10.1016/S0360-5442(02)00089-0
   Bernanke BS, 1997, BROOKINGS PAP ECO AC, P91
   Bouwer LM, 2011, B AM METEOROL SOC, V92, P39, DOI 10.1175/2010BAMS3092.1
   Canadell JG, 2007, P NATL ACAD SCI USA, V104, P18866, DOI 10.1073/pnas.0702737104
   Cox PM, 2000, NATURE, V408, P184, DOI 10.1038/35041539
   Dimitropoulos J, 2007, ENERG POLICY, V35, P6354, DOI 10.1016/j.enpol.2007.07.028
   Etheridge DM, 1996, J GEOPHYS RES-ATMOS, V101, P4115, DOI 10.1029/95JD03410
   Flückiger J, 2002, GLOBAL BIOGEOCHEM CY, V16, DOI 10.1029/2001GB001417
   Garrett TJ, 2011, CLIMATIC CHANGE, V104, P437, DOI 10.1007/s10584-009-9717-9
   Georgescu-Roegen Nicholas., 1993, VALUING EARTH EC ECO, P75
   Hansen J, 2007, ATMOS CHEM PHYS, V7, P2287, DOI 10.5194/acp-7-2287-2007
   Herring H, 2007, TECHNOVATION, V27, P194, DOI 10.1016/j.technovation.2006.11.004
   House of Lords, 2006, 2 HOUS LORDS SEL COM
   Hsiang SM, 2011, NATURE, V476, P438, DOI 10.1038/nature10311
   Jevons W.S., 1865, The Coal Question
   Joos F, 1996, TELLUS B, V48, P397, DOI 10.1034/j.1600-0889.1996.t01-2-00006.x
   Keeling C.D., 2005, ATMOSPHERIC CO2 RECO
   Keller K, 2004, J ENVIRON ECON MANAG, V48, P723, DOI 10.1016/j.jeem.2003.10.003
   Le Quéré C, 2003, TELLUS B, V55, P649, DOI 10.1034/j.1600-0889.2003.00043.x
   Le Quéré C, 2007, SCIENCE, V316, P1735, DOI 10.1126/science.1136188
   Leckebusch GC, 2007, GEOPHYS RES LETT, V34, DOI 10.1029/2006GL027663
   Liou K.N., 2002, INT GEOPHYS SERIES
   Lobell DB, 2011, SCIENCE, V333, P616, DOI [10.1126/science.1204531, 10.1126/science.1206376]
   Lotka AJ, 1922, P NATL ACAD SCI USA, V8, P147, DOI 10.1073/pnas.8.6.147
   Maddison Angus., 2003, The World Economy: Historical Statistics
   Manning MR, 2010, NAT GEOSCI, V3, P376, DOI 10.1038/ngeo880
   Marland G., 2007, TRENDS COMPENDIUM DA
   Mastrandrea MD, 2004, SCIENCE, V304, P571, DOI 10.1126/science.1094147
   Murphy DJ, 2010, ANN NY ACAD SCI, V1185, P102, DOI 10.1111/j.1749-6632.2009.05282.x
   Nordhaus W.D., 2000, WARMING WORLD EC MOD
   Nordhaus WD, 2010, P NATL ACAD SCI USA, V107, P11721, DOI 10.1073/pnas.1005985107
   Owen David, 2010, NEW YORKER, P78
   Pacala S, 2004, SCIENCE, V305, P968, DOI 10.1126/science.1100103
   Parkin M., 2008, NEW PALGRAVE DICT EC
   Patz JA, 2005, NATURE, V438, P310, DOI 10.1038/nature04188
   Pielke R.A., 2008, Natural Hazards Review, V9, P29, DOI [DOI 10.1061/(ASCE)1527-6988(2008)9:1(29), 10.1061/(ASCE)1527-6988(2008)9:1(29)]
   [Portner H.-O. IPCC IPCC], 2019, Climate change 2022-Impacts, adaptation and vulnerability, DOI [10.1017/9781009325844.001, 10.1017/9781009157926.001, DOI 10.1017/9781009157926.001, DOI 10.1017/9781009325844]
   Raupach MR, 2007, P NATL ACAD SCI USA, V104, P10288, DOI 10.1073/pnas.0700609104
   Sarel M, 1996, INT MONET FUND S PAP, V43, P199
   Saunders HD, 2000, ENERG POLICY, V28, P439, DOI 10.1016/S0301-4215(00)00024-0
   Sherwood SC, 2010, P NATL ACAD SCI USA, V107, P9552, DOI 10.1073/pnas.0913352107
   Solomon S, 2009, P NATL ACAD SCI USA, V106, P1704, DOI 10.1073/pnas.0812721106
   SOLOW RM, 1956, Q J ECON, V70, P65, DOI 10.2307/1884513
   Sorrell S, 2010, ENERG POLICY, V38, P5290, DOI 10.1016/j.enpol.2010.04.046
   TRENBERTH KE, 1981, J GEOPHYS RES-OCEANS, V86, P5238, DOI 10.1029/JC086iC06p05238
   Vermeer M, 2009, P NATL ACAD SCI USA, V106, P21527, DOI 10.1073/pnas.0907765106
   Warr B., 2006, Structural Change and Economic Dynamics, V17, P329, DOI 10.1016/j.strueco.2005.04.004
   WIGLEY TML, 1983, CLIMATIC CHANGE, V5, P315, DOI 10.1007/BF00140798
   ,, 2007, Climate change 2007: Synthesis Report. Contribution of Working Group I, II and III to the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Summary for Policymakers
NR 55
TC 21
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PA BAHNHOFSALLEE 1E, GOTTINGEN, 37081, GERMANY
SN 2190-4979
EI 2190-4987
J9 EARTH SYST DYNAM
JI Earth Syst. Dynam.
PY 2012
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IS 1
BP 1
EP 17
DI 10.5194/esd-3-1-2012
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WC Geosciences, Multidisciplinary
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Geology
GA 276NX
UT WOS:000328758100001
OA Green Submitted, gold
DA 2026-06-13
ER

PT J
AU Kellie-Smith, O
   Cox, PM
AF Kellie-Smith, Owen
   Cox, Peter M.
TI Emergent dynamics of the climate-economy system in the Anthropocene
SO PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL
   AND ENGINEERING SCIENCES
LA English
DT Article
DE climate change; economic growth; feedback; instability
ID FEEDBACKS
AB Global CO2 emissions are understood to be the largest contributor to anthropogenic climate change, and have, to date, been highly correlated with economic output. However, there is likely to be a negative feedback between climate change and human wealth: economic growth is typically associated with an increase in CO2 emissions and global warming, but the resulting climate change may lead to damages that suppress economic growth. This climate-economy feedback is assumed to be weak in standard climate change assessments. When the feedback is incorporated in a transparently simple model it reveals possible emergent behaviour in the coupled climate-economy system. Formulae are derived for the critical rates of growth of global CO2 emissions that cause damped or long-term boom-bust oscillations in human wealth, thereby preventing a soft landing of the climate-economy system. On the basis of this model, historical rates of economic growth and decarbonization appear to put the climate-economy system in a potentially damaging oscillatory regime.
C1 [Kellie-Smith, Owen; Cox, Peter M.] Univ Exeter, Coll Engn Math & Phys Sci, Exeter EX4 4QF, Devon, England.
C3 University of Exeter
RP Kellie-Smith, O (corresponding author), Univ Exeter, Coll Engn Math & Phys Sci, N Pk Rd, Exeter EX4 4QF, Devon, England.
EM o.kellie-smith@exeter.ac.uk
RI Cox, Peter/B-3299-2012
OI Cox, Peter/0000-0002-0679-2219
FU Natural Environment Research Council; Met Office; University of Exeter;
   NERC [earth010002] Funding Source: UKRI; Natural Environment Research
   Council [earth010002] Funding Source: researchfish
FX This work was funded by the Natural Environment Research Council, the
   Met Office and the University of Exeter. We would like to thank Prof.
   John Thuburn and the Applied Maths seminar group at the University of
   Exeter for constructive comments.
CR Adger WN, 2007, AR4 CLIMATE CHANGE 2007: IMPACTS, ADAPTATION, AND VULNERABILITY, P717
   [Anonymous], EMISSION SCENARIOS S
   [Anonymous], 200777 UNU WIDER
   [Anonymous], NAT ACC MAIN AGGR DA
   [Anonymous], FOREIGN AFF
   [Anonymous], ICES J MAR SCI, DOI DOI 10.1093/ICESJMS/3.1.3
   Archer D, 2009, ANNU REV EARTH PL SC, V37, P117, DOI 10.1146/annurev.earth.031208.100206
   Barker T., 1995, GLOBAL WARMING ENERG
   Behrens A, 2007, ECOL ECON, V64, P444, DOI 10.1016/j.ecolecon.2007.02.034
   Cox P, 2007, SCIENCE, V317, P207, DOI 10.1126/science.1145956
   Cox PM, 2000, NATURE, V408, P184, DOI 10.1038/35041539
   Eby M, 2009, J CLIMATE, V22, P2501, DOI 10.1175/2008JCLI2554.1
   Forest CE, 2002, SCIENCE, V295, P113, DOI 10.1126/science.1064419
   Hall RE, 1999, Q J ECON, V114, P83, DOI 10.1162/003355399555954
   HANSEN J, 1985, SCIENCE, V229, P857, DOI 10.1126/science.229.4716.857
   Harvell CD, 2002, SCIENCE, V296, P2158, DOI 10.1126/science.1063699
   Jose J.V., 1998, Classical Dynamics: A Contemporary Approach
   Knack S, 1997, Q J ECON, V112, P1251, DOI 10.1162/003355300555475
   Maddison A, 2005, REV INCOME WEALTH, P1
   Marland G., 2006, TRENDS COMPENDIUM DA
   Meadows DH., 2004, LIMITS GROWTH 30 YEA
   Metz B., 2007, Climate change
   Nordhaus W.D., 2008, QUESTION BALANCE WEI
   Sabine CL, 2004, SCIENCE, V305, P367, DOI 10.1126/science.1097403
   Schnellnhuber HansJoachim., 2006, AVOIDING DANGEROUS C
   Soden BJ, 2006, J CLIMATE, V19, P3354, DOI [10.1175/JCLI3799.1, 10.1175/JCLI3990.1]
   Stern N, 2008, AM ECON REV, V98, P1, DOI 10.1257/aer.98.2.1
   Stott PA, 2000, SCIENCE, V290, P2133, DOI 10.1126/science.290.5499.2133
   Strogatz S.H., 2014, NONLINEAR DYNAMICS C
NR 29
TC 29
Z9 30
U1 1
U2 16
PU ROYAL SOC
PI LONDON
PA 6-9 CARLTON HOUSE TERRACE, LONDON SW1Y 5AG, ENGLAND
SN 1364-503X
EI 1471-2962
J9 PHILOS T R SOC A
JI Philos. Trans. R. Soc. A-Math. Phys. Eng. Sci.
PD MAR 13
PY 2011
VL 369
IS 1938
BP 868
EP 886
DI 10.1098/rsta.2010.0305
PG 19
WC Multidisciplinary Sciences
WE Science Citation Index Expanded (SCI-EXPANDED); Social Science Citation Index (SSCI)
SC Science & Technology - Other Topics
GA 713GL
UT WOS:000286723100003
PM 21282151
DA 2026-06-13
ER

EF