Declining Marginal Value of Coastal Proximity - PowerPoint PPT Presentation

paul2
declining marginal value of coastal proximity l.
Skip this Video
Loading SlideShow in 5 Seconds..
Declining Marginal Value of Coastal Proximity PowerPoint Presentation
Download Presentation
Declining Marginal Value of Coastal Proximity

play fullscreen
1 / 14
Download Presentation
Declining Marginal Value of Coastal Proximity
555 Views
Download Presentation

Declining Marginal Value of Coastal Proximity

- - - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript

  1. Declining Marginal Value of Coastal Proximity Kenneth Wehrmann

  2. How is Coastal Property Valued? • How much extra would you pay for a house on the beach? • How much less for a house that was on the second row of houses? • Third?.... MAP of Beach

  3. Research • Previous Hedonic Studies • Rosen • Beginning of Hedonic Method • Islands • Power Plants, Toxic Sites, Pollution • Negative externalities affecting nearby properties • Flood Risk • How consumers discount property due to risk • View • Do consumers consider view when making purchasing decisions? (Coastal)

  4. Theory Coastal homes are highly valued for their close proximity to a scarce resource, our beautiful North Carolina shores. Coastal proximity provides utility to consumers and will therefore demand a premium. This premium will decline as distance to the shore increases and should show signs of diminishing returns.

  5. Theory Graphs PD P Price Differential ∆ Distance to Shore Q Distance to Shore

  6. Data Source • Bin, Okmyung., Tom Crawford, Jamie Kruse, and Craig E. Landry. "Flood Prone with a View: Coastal Housing Market Response to Risk and Aminity." Working Paper. East Carolina University. 2006 • New Hanover County, NC • 1075 Property Sales from 1995 to 2002 • $30,000 to $3,500,000 sales price • 12% were new homes Map of Beaches

  7. Hedonic Model • Goods are broken down into their constituent attributes. These attributes create utility for consumers and therefore hold value. This value can be estimated by quantifying these constituent parts and analyzing their relationships. For the housing industry characteristics are traditionally broken down into three groups; structural, neighborhood, and environmental attributes.

  8. VariablesStructural • Age • 0 81 22.06 • New Home (D) • 12% • Square Footage • 392 8354 1784.08 • Lot Size • # of Bedrooms • 1 8 3.15 • # of Bathrooms • 1 7.5 2.491 • Air Conditioning (D) • 90% • View (Sum of Degrees of View) • 0 178.18 18.36

  9. VariablesNeighborhood • Neighborhood (D) • Figure 8 Island 10% • Kure Beach 34% • Wrightsville Beach 17% • Carolina Beach 40% • Distance to Nearest Highway • Distance to Central Business District

  10. VariablesEnviormental Distance to Nearest Shore Range: 73 Ft to 1 mile Average: 1743 ft or 3/10ths of a mile Distance to Neatest Shore Squared (Diminishing Returns)

  11. Results • Model 1 • T-stat: -4.4 • Consumers do pay a premium for properties with close proximity to the shore • Model 2 • Dist -13.69 • Dist Sq 12.83 • These premiums show evidence of diminishing returns as each foot of distance away from the shore supplies marginally less utility to consumers

  12. Model 3

  13. Future Research • Mountains • View Variable • Distance to CBD (Boone) • Value of being in a gated community

  14. Questions?