An Estimation of the Coastal Premium for Residential Housing Prices in San Diego County

Abstract

The authors attempt to estimate the "coastal premium"-additional value conferred on a residence from being located near the coast-of single family homes in San Diego County, while controlling for other locational and structural characteristics. A previous investigation published in 2001 for south Orange County found that moving away from the coast by one mile was associated with a $42,000 lower housing price. Intrigued by this finding, we investigate whether (a) a similar coastal premium exists for all of San Diego County and (b) the premium varies by incremental distance from the coast (e.g., for 500-feet increments). Using data from 9,755 San Diego County home sales in 2006, results presented here suggest that for a median-priced home ($540,000) at the mean distance from the coast (approximately 9 miles-and considerably farther than the Orange County estimate) a onemile increase in distance from the coast would reduce the sale price by approximately $8,680. Specifying by specific distance increments, we find that the coastal premium is approximately 101.9% for houses within 500 feet of the coast (i.e., their value is 101.9% higher than similar homes located beyond six miles of the coast), falling to 62.8% for homes between 500 and 1,000 feet, declining to approximately 3.3% for homes located between five and six miles of the coast, disappearing entirely beyond around six miles. Since average comparisons of the sort initially considered in this analysis can be very misleading, researchers should consider the nonlinear incremental distance effects in model specifications.

Estimating School Proximity Effects on Housing Prices: the Importance of Robust Spatial Controls in Hedonic Estimations

“…The log transformation of the dependent variable is considered to be the most appropriate form for almost all hedonic pricing models in the recent housing literature (see Turnbull and Dombrow 2007;Conway et al 2010;Conroy and Milosch 2011). The variable, Struct ij , is the jth structural variable for observation i, Spat ik is the k th spatial variable for observation i, SQ il is the l th type of school quality variable.…”

“…These investigations are particularly relevant here since schools may confer some benefits that are qualitatively similar to parks, green spaces, beaches and golf courses. Research involving spatial or neighborhood amenities has provided clear evidence of a net positive benefit or "proximity premium" for housing located near open space (Irwin 2002), the Pacific Coast (Conroy and Milosch 2011), historically-designated places (Narwold 2008), golf courses (Do and Grudnitski 1995), green space (Conway et al 2010) and nature or water views (Benson et al 1998). For housing located near highways/freeways/expressways, the net effect on valuation is somewhat mixed.…”

“…or neighborhood controls. We improve upon Des Rosiers et al (2001) and Emerson (1972) by also including neighborhood controls plus distance to freeways, downtown, and the coast (Conroy and Milosch 2011) and including school quality measures not available in the Quebec study.…”

Valuing Visual Accessibility of Scenic Landscapes in a Single Family Housing Market: A Spatial Hedonic Approach

“…Among different types of waterfronts, homes in proximity of oceans with well-developed beaches had the highest price premium and ranged over 101.9% (Conroy and Milosch 2011). This premium was found to be even higher of 147% when both proximity and view of ocean were available from homes (Benson et al 1997).…”

The Pricing Effects of Open Space Amenities

“…Similarly, Gibbons et al (2014) use hedonic model and find positive value attached to the proximity to environmental amenities in England. Conroy and Milosch (2009) focus on water amenity value and use hedonic model to estimate the value attached to proximity to coastal areas. They find non-linear pricing effects of coastal proximity in San Diego County.…”