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“Living on the edge”: Estimating the economic cost of sea level rise on coastal real estate in the Tampa Bay region, Florida

  • University of Florida
  • Wuhan University

Research output: Contribution to journalArticlepeer-review

34 Scopus citations

Abstract

Climate change and especially sea level rise are posing unprecedented pressure on coastal communities through enhanced coastal flooding and saltwater intrusion. Thus, adapting to its impacts has drawn global attention. Since the cost-efficiency of adaptation alternatives is crucial in decision making, accurately estimating the economic cost of sea level rise is an imperative task for coastal planners and managers. This study employed a spatial hedonic approach to estimate the economic cost due to inundation by future sea level rise. The applied methodology provides better estimates of the economic losses due to sea level rise by accounting for lost coastal amenities, and the results generated can also be utilized for cost-benefit analysis. In 2050, it is estimated that the inundation of 3-foot sea level rise could cost Hillsborough and Pinellas County over 300 and 900 million dollars respectively for the real estate market alone. Local coastal planners and managers may find this methodology useful in estimating the potential economic cost due to sea level rise and support making adaptation decisions. We also stressed the importance of such studies to support local decision making and enhance adaptation planning for the climate change and sea level rise in the coastal communities.

Original languageEnglish
Pages (from-to)11-17
Number of pages7
JournalOcean and Coastal Management
Volume133
DOIs
StatePublished - 1 Dec 2016
Externally publishedYes

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 8 - Decent Work and Economic Growth
    SDG 8 Decent Work and Economic Growth
  2. SDG 13 - Climate Action
    SDG 13 Climate Action

Keywords

  • Adaptation planning
  • Economic analysis
  • Hedonic price model
  • Sea level rise
  • Spatial regression

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