• Medientyp: E-Book
  • Titel: Evaluating the Economic Cost of Coastal Flooding
  • Beteiligte: Desmet, Klaus [VerfasserIn]; Kopp, Robert E. [Sonstige Person, Familie und Körperschaft]; Kulp, Scott A. [Sonstige Person, Familie und Körperschaft]; Nagy, Dávid Krisztián [Sonstige Person, Familie und Körperschaft]; Oppenheimer, Michael [Sonstige Person, Familie und Körperschaft]; Rossi-Hansberg, Esteban [Sonstige Person, Familie und Körperschaft]; Strauss, Benjamin H. [Sonstige Person, Familie und Körperschaft]
  • Körperschaft: National Bureau of Economic Research
  • Erschienen: Cambridge, Mass: National Bureau of Economic Research, 2018
  • Erschienen in: NBER working paper series ; no. w24918
  • Umfang: 1 Online-Ressource; illustrations (black and white)
  • Sprache: Englisch
  • DOI: 10.3386/w24918
  • Identifikator:
  • Reproduktionsnotiz: Hardcopy version available to institutional subscribers
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  • Anmerkungen: System requirements: Adobe [Acrobat] Reader required for PDF files
    Mode of access: World Wide Web
  • Beschreibung: Sea-level rise and ensuing permanent coastal inundation will cause spatial shifts in population and economic activity over the next 200 years. Using a highly spatially disaggregated, dynamic model of the world economy that accounts for the dynamics of migration, trade, and innovation, this paper estimates the consequences of probabilistic projections of local sea-level changes under different emissions scenarios. Under an intermediate greenhouse gas concentration trajectory, permanent flooding is projected to reduce global real GDP by an average of 0.19% in present value terms, with welfare declining by 0.24% as people move to places with less attractive amenities. By the year 2200 a projected 1.46% of world population will be displaced. Losses in many coastal localities are more than an order of magnitude larger, with some low-lying urban areas particularly hard hit. When ignoring the dynamic economic adaptation of investment and migration to flooding, the loss in real GDP in 2200 increases from 0.11% to 4.5%. This shows the importance of including dynamic adaptation in future loss models
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