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In Chang Hwang

Personal Details

First Name:In Chang
Middle Name:
Last Name:Hwang
Suffix:
RePEc Short-ID:phw11
Terminal Degree:2014 School of Business and Economics; Vrije Universiteit Amsterdam (from RePEc Genealogy)

Affiliation

Seoul Development Institute

Seoul, South Korea
http://www.sdi.re.kr/




RePEc:edi:sdirekr (more details at EDIRC)

Research output

as
Jump to: Working papers Articles

Working papers

  1. In Chang Hwang, 2016. "Active learning and optimal climate policy," EcoMod2016 9611, EcoMod.
  2. Hwang, In Chang, 2013. "Stochastic Kaya model and its applications," MPRA Paper 55099, University Library of Munich, Germany.
  3. Hwang, In Chang, 2013. "Anthropogenic drivers of carbon emissions: scale and counteracting effects," MPRA Paper 52224, University Library of Munich, Germany.

Articles

  1. Hwang, In Chang & Reynès, Frédéric & Tol, Richard S.J., 2017. "The effect of learning on climate policy under fat-tailed risk," Resource and Energy Economics, Elsevier, vol. 48(C), pages 1-18.
  2. In Chang Hwang, 2017. "A Recursive Method for Solving a Climate–Economy Model: Value Function Iterations with Logarithmic Approximations," Computational Economics, Springer;Society for Computational Economics, vol. 50(1), pages 95-110, June.
  3. Hwang, In Chang & Tol, Richard S.J. & Hofkes, Marjan W., 2016. "Fat-tailed risk about climate change and climate policy," Energy Policy, Elsevier, vol. 89(C), pages 25-35.
  4. In Hwang & Frédéric Reynès & Richard Tol, 2013. "Climate Policy Under Fat-Tailed Risk: An Application of Dice," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 56(3), pages 415-436, November.

Citations

Many of the citations below have been collected in an experimental project, CitEc, where a more detailed citation analysis can be found. These are citations from works listed in RePEc that could be analyzed mechanically. So far, only a minority of all works could be analyzed. See under "Corrections" how you can help improve the citation analysis.

Working papers

  1. In Chang Hwang, 2016. "Active learning and optimal climate policy," EcoMod2016 9611, EcoMod.

    Cited by:

    1. David Anthoff & Richard S. J. Tol, 2021. "Testing the Dismal Theorem," CESifo Working Paper Series 8939, CESifo.
    2. In Chang Hwang, 2017. "A Recursive Method for Solving a Climate–Economy Model: Value Function Iterations with Logarithmic Approximations," Computational Economics, Springer;Society for Computational Economics, vol. 50(1), pages 95-110, June.

  2. Hwang, In Chang, 2013. "Stochastic Kaya model and its applications," MPRA Paper 55099, University Library of Munich, Germany.

    Cited by:

    1. Paunić, Alida, 2016. "Brazil, Preservation of Forest and Biodiversity," MPRA Paper 71462, University Library of Munich, Germany.

  3. Hwang, In Chang, 2013. "Anthropogenic drivers of carbon emissions: scale and counteracting effects," MPRA Paper 52224, University Library of Munich, Germany.

    Cited by:

    1. Paunić, Alida, 2016. "Brazil, Preservation of Forest and Biodiversity," MPRA Paper 71462, University Library of Munich, Germany.

Articles

  1. Hwang, In Chang & Reynès, Frédéric & Tol, Richard S.J., 2017. "The effect of learning on climate policy under fat-tailed risk," Resource and Energy Economics, Elsevier, vol. 48(C), pages 1-18.

    Cited by:

    1. In Chang Hwang & Richard S.J. Tol & Marjan W. Hofkes, 2013. "Active Learning about Climate Change," Working Paper Series 6513, Department of Economics, University of Sussex Business School.
    2. David Anthoff & Richard S. J. Tol, 2021. "Testing the Dismal Theorem," CESifo Working Paper Series 8939, CESifo.
    3. In Chang Hwang & Richard S. J. Tol & Marjan W. Hofkes, 2019. "Active Learning and Optimal Climate Policy," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 73(4), pages 1237-1264, August.
    4. Yongyang Cai, 2020. "The Role of Uncertainty in Controlling Climate Change," Papers 2003.01615, arXiv.org, revised Oct 2020.
    5. In Chang Hwang, 2017. "A Recursive Method for Solving a Climate–Economy Model: Value Function Iterations with Logarithmic Approximations," Computational Economics, Springer;Society for Computational Economics, vol. 50(1), pages 95-110, June.
    6. Ahlvik, Lassi & Iho, Antti, 2018. "Optimal geoengineering experiments," Journal of Environmental Economics and Management, Elsevier, vol. 92(C), pages 148-168.
    7. Gissela Landa Rivera & Paul Malliet & Aurélien Saussay & Frédéric Reynès, 2018. "The State of Applied Environmental Macroeconomics," Revue de l'OFCE, Presses de Sciences-Po, vol. 0(3), pages 133-149.
    8. Samuel Jovan Okullo, 2020. "Determining the Social Cost of Carbon: Under Damage and Climate Sensitivity Uncertainty," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 75(1), pages 79-103, January.
    9. In Chang Hwang, 2016. "Active learning and optimal climate policy," EcoMod2016 9611, EcoMod.
    10. Hwang, In Chang, 2014. "Fat-tailed uncertainty and the learning-effect," MPRA Paper 53671, University Library of Munich, Germany.
    11. Ekholm, Tommi, 2018. "Climatic Cost-benefit Analysis Under Uncertainty and Learning on Climate Sensitivity and Damages," Ecological Economics, Elsevier, vol. 154(C), pages 99-106.

  2. In Chang Hwang, 2017. "A Recursive Method for Solving a Climate–Economy Model: Value Function Iterations with Logarithmic Approximations," Computational Economics, Springer;Society for Computational Economics, vol. 50(1), pages 95-110, June.

    Cited by:

    1. In Chang Hwang & Richard S. J. Tol & Marjan W. Hofkes, 2019. "Active Learning and Optimal Climate Policy," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 73(4), pages 1237-1264, August.
    2. In Chang Hwang, 2016. "Active learning and optimal climate policy," EcoMod2016 9611, EcoMod.

  3. Hwang, In Chang & Tol, Richard S.J. & Hofkes, Marjan W., 2016. "Fat-tailed risk about climate change and climate policy," Energy Policy, Elsevier, vol. 89(C), pages 25-35.

    Cited by:

    1. David Anthoff & Richard S. J. Tol, 2021. "Testing the Dismal Theorem," CESifo Working Paper Series 8939, CESifo.
    2. Hwang, In Chang & Reynès, Frédéric & Tol, Richard S.J., 2017. "The effect of learning on climate policy under fat-tailed risk," Resource and Energy Economics, Elsevier, vol. 48(C), pages 1-18.
    3. Samuel Jovan Okullo, 2020. "Determining the Social Cost of Carbon: Under Damage and Climate Sensitivity Uncertainty," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 75(1), pages 79-103, January.
    4. Auke Hoekstra & Maarten Steinbuch & Geert Verbong, 2017. "Creating Agent-Based Energy Transition Management Models That Can Uncover Profitable Pathways to Climate Change Mitigation," Complexity, Hindawi, vol. 2017, pages 1-23, December.
    5. In Chang Hwang, 2016. "Active learning and optimal climate policy," EcoMod2016 9611, EcoMod.
    6. Hassler, J. & Krusell, P. & Smith, A.A., 2016. "Environmental Macroeconomics," Handbook of Macroeconomics, in: J. B. Taylor & Harald Uhlig (ed.), Handbook of Macroeconomics, edition 1, volume 2, chapter 0, pages 1893-2008, Elsevier.

  4. In Hwang & Frédéric Reynès & Richard Tol, 2013. "Climate Policy Under Fat-Tailed Risk: An Application of Dice," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 56(3), pages 415-436, November.

    Cited by:

    1. Yi-Ming Wei & Zhi-Fu Mi & Zhiming Huang, 2014. "Climate policy modeling: An online SCI-E and SSCI based literature review," CEEP-BIT Working Papers 58, Center for Energy and Environmental Policy Research (CEEP), Beijing Institute of Technology.
    2. Tomas Havranek & Zuzana Irsova & Karel Janda & David Zilberman, 2015. "Selective reporting and the social cost of carbon," CAMA Working Papers 2015-28, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    3. David Anthoff & Richard S. J. Tol, 2021. "Testing the Dismal Theorem," CESifo Working Paper Series 8939, CESifo.
    4. In Chang Hwang & Richard S. J. Tol & Marjan W. Hofkes, 2019. "Active Learning and Optimal Climate Policy," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 73(4), pages 1237-1264, August.
    5. Vogt-Schilb, Adrien & Meunier, Guy & Hallegatte, Stephane, 2018. "When Starting with the Most Expensive Option Makes Sense: Optimal Timing, Cost and Sectoral Allocation of Abatement Investment," IDB Publications (Working Papers) 8809, Inter-American Development Bank.
    6. Valentini, Edilio & Vitale, Paolo, 2014. "Optimal Climate Policy for a Pessimistic Social Planner," Climate Change and Sustainable Development 166409, Fondazione Eni Enrico Mattei (FEEM).
    7. Hwang, In Chang & Reynès, Frédéric & Tol, Richard S.J., 2017. "The effect of learning on climate policy under fat-tailed risk," Resource and Energy Economics, Elsevier, vol. 48(C), pages 1-18.
    8. W. Botzen & Jeroen Bergh, 2014. "Specifications of Social Welfare in Economic Studies of Climate Policy: Overview of Criteria and Related Policy Insights," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 58(1), pages 1-33, May.
    9. Davidson, Marc D., 2014. "Zero discounting can compensate future generations for climate damage," Ecological Economics, Elsevier, vol. 105(C), pages 40-47.
    10. W. J. Wouter Botzen & Jeroen C. J. M. Van Den Bergh & Graciela Chichilnisky, 2018. "Climate Policy Without Intertemporal Dictatorship: Chichilnisky Criterion Versus Classical Utilitarianism In Dice," Climate Change Economics (CCE), World Scientific Publishing Co. Pte. Ltd., vol. 9(02), pages 1-17, May.
    11. Gissela Landa Rivera & Paul Malliet & Aurélien Saussay & Frédéric Reynès, 2018. "The State of Applied Environmental Macroeconomics," Revue de l'OFCE, Presses de Sciences-Po, vol. 0(3), pages 133-149.
    12. Masako Ikefuji & Jan R. Magnus, 2020. "The perception of climate sensitivity: Revealing priors from posteriors," ISER Discussion Paper 1111, Institute of Social and Economic Research, Osaka University.
    13. Ikefuji, Masako & Laeven, Roger J.A. & Magnus, Jan R. & Muris, Chris, 2020. "Expected utility and catastrophic risk in a stochastic economy–climate model," Journal of Econometrics, Elsevier, vol. 214(1), pages 110-129.
    14. Samuel Jovan Okullo, 2020. "Determining the Social Cost of Carbon: Under Damage and Climate Sensitivity Uncertainty," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 75(1), pages 79-103, January.
    15. Delton B. Chen & Joel van der Beek & Jonathan Cloud, 2017. "Climate mitigation policy as a system solution: addressing the risk cost of carbon," Journal of Sustainable Finance & Investment, Taylor & Francis Journals, vol. 7(3), pages 233-274, July.
    16. In Chang Hwang, 2016. "Active learning and optimal climate policy," EcoMod2016 9611, EcoMod.
    17. Hwang, In Chang, 2014. "Fat-tailed uncertainty and the learning-effect," MPRA Paper 53671, University Library of Munich, Germany.
    18. Jasper N. Meya & Ulrike Kornek & Kai Lessmann, 2018. "How empirical uncertainties influence the stability of climate coalitions," International Environmental Agreements: Politics, Law and Economics, Springer, vol. 18(2), pages 175-198, April.
    19. Hwang, In Chang & Tol, Richard S.J. & Hofkes, Marjan W., 2016. "Fat-tailed risk about climate change and climate policy," Energy Policy, Elsevier, vol. 89(C), pages 25-35.
    20. In Chang Hwang & Richard S.J. Tol & Marjan W. Hofkes, 2013. "Tail-effect and the Role of Greenhouse Gas Emissions Control," Working Paper Series 6613, Department of Economics, University of Sussex Business School.

More information

Research fields, statistics, top rankings, if available.

Statistics

Access and download statistics for all items

Co-authorship network on CollEc

NEP Fields

NEP is an announcement service for new working papers, with a weekly report in each of many fields. This author has had 3 papers announced in NEP. These are the fields, ordered by number of announcements, along with their dates. If the author is listed in the directory of specialists for this field, a link is also provided.
  1. NEP-ENE: Energy Economics (3) 2013-12-20 2014-04-11 2017-04-23. Author is listed
  2. NEP-ENV: Environmental Economics (3) 2013-12-20 2014-04-11 2017-04-23. Author is listed
  3. NEP-GER: German Papers (1) 2014-04-11. Author is listed

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