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@PHDTHESIS{Zhao:996754,
      author       = {Zhao, Yifan},
      othercontributors = {Lontzek, Thomas Siegmund and Schmedders, Karl},
      title        = {{P}references under uncertainty in integrated assessment
                      models of the climate and the economy},
      school       = {Rheinisch-Westfälische Technische Hochschule Aachen},
      type         = {Dissertation},
      address      = {Aachen},
      publisher    = {RWTH Aachen University},
      reportid     = {RWTH-2024-10802},
      pages        = {1 Online-Ressource : Illustrationen},
      year         = {2024},
      note         = {Veröffentlicht auf dem Publikationsserver der RWTH Aachen
                      University; Dissertation, Rheinisch-Westfälische Technische
                      Hochschule Aachen, 2024},
      abstract     = {Climate change poses significant challenges that require
                      economic modeling to guide policy decisions. This thesis
                      explores the integration of preferences for uncertainty
                      aversion in climate-economic models. First, we review
                      various frameworks that model risk aversion, such as
                      time-additive CRRA utility, Epstein—Zin preferences, and
                      risk-sensitive preferences, and highlight their advantages
                      and shortcomings through illustrative examples. We
                      specifically investigate two different notions of
                      risk-sensitive preferences, which we refer to as full-path
                      and per-stage robustness. Then, we propose an integrated
                      assessment model of the climate and the economy by extending
                      the Ramsey—Cass—Koopmans economic growth model to
                      include a climate component and accounting for uncertain
                      climate damages in persistent disaster states. The optimal
                      carbon tax is then calculated for different
                      uncertainty-averse preferences. We find that, in our
                      specific climate-economic model, using any of the full-path
                      robust preferences, per-stage robust preferences, or
                      Epstein—Zin preferences results in higher social costs of
                      carbon (SCC) compared to time-additive CRRA utility, with
                      the effect being highest for full-path robust preferences.
                      We denote the difference in SCC between any of the robust
                      preferences and time-additive CRRA utility as the
                      "robustness premium". For our baseline calibration with
                      full-path robust preferences and a rather low robustness
                      parameter of k=5, the SCC is around USD 162 per ton of CO2
                      in 2020, with a robustness premium of USD 2.20 per ton of
                      CO2. However, we see that depending on the type of robust
                      preferences, the robustness premium can be as high as USD
                      78.55 per ton of CO2.},
      cin          = {811110},
      ddc          = {330},
      cid          = {$I:(DE-82)811110_20140620$},
      pnm          = {BMBF 01LS2106A - CDR: Direct Air Capture —
                      Transdisziplinäre Bewertung unter Einbeziehung von Labor,
                      Umwelt, Wirtschaft und Gesellschaft (DAC-TALES) (01LS2106A)},
      pid          = {G:(BMBF)01LS2106A},
      typ          = {PUB:(DE-HGF)11},
      doi          = {10.18154/RWTH-2024-10802},
      url          = {https://publications.rwth-aachen.de/record/996754},
}