Thursday, November 22, 2012

Estimating the economic value of cultural ecosystem services in an urbanizing area using hedonic pricing

Abstract: A need exists to increase both knowledge and recognition of the values associated with ecosystem services and amenities. This article explores the use of hedonic pricing as a tool for eliciting these values. We take a case study approach, valuing several services provided by ecosystems, namely aesthetic quality (views), access to outdoor recreation, and the benefits provided by tree cover in Dakota County, Minnesota, USA. Our results indicate that these services are valued by local residents and that hedonic pricing can be used to elicit at least a portion of this value. We find that many aspects of the aesthetic environment significantly impact home sale prices. Total view area as well as the areas of some land-cover types (water and lawn) in views positively influenced home sale prices while views of impervious surfaces generally negatively influenced home sale price. Access to outdoor recreation areas significantly and positively influenced home sale prices as did tree cover in the neighborhood surrounding a home. These results illustrate the ability of hedonic pricing to identify partial values for ecosystem services and amenities in a manner that is highly relevant to local and regional planning. These values could be used to increase policy-maker and public awareness of ecosystem services and could improve their consideration in planning and policy decisions.
► We use hedonic pricing to elicit the values of cultural ecosystem services.
► Aspects of aesthetic quality impact home prices (e.g., view area, composition).
► Access to outdoor recreation areas positively influences home sale prices.
► Tree cover in the local neighborhood positively influences home sale prices.
► Hedonic pricing is found to able to estimate values for these and other services.
The coefficients for nearly all neighborhood variables were significant and of the expected sign. Distance to the central business districts of Minneapolis and St. Paul was negatively related to home sale price such that homes located closer to a central business district sold for more than comparable homes located further away.

The mean area of impervious surface within 500 m of a home was also positively related to home sale price, indicating that homes in areas with more impervious surface and thus higher development
intensities sold for more than homes with lower levels. This result is surprising and may indicate a preference for living in more developed areas which might incorporate more amenities (e.g., restaurants, shopping and fitness centers, day care providers, schools) or simply may be a function of the tendency of homes to be located in more intensively-developed areas in Dakota County. This
might be perceived as indicating that increasing development is valued, but this study did not consider very high-density forms of residential development (e.g., townhomes, apartment buildings),
so it is difficult to comment upon this. However, as the values of these properties tend to be lower than those of single-family housing, one might speculate that higher intensity development is valued only to a certain point, after which it may become a disamenity.
Both variables indicating a property’s access to outdoor recreation areas significantly impacted home sale prices. Road distance to parks greater than 1-ha in area had a significant and negative relationship to home sale price, such that the marginal implicit price of a 100-m decrease in distance to such a park evaluated at the mean home sale price of $319,073 from an initial distance of 1-km was $13.16 (0.040%). Euclidean distance to lakes also was significantly and negatively related to home sale price, although the impact of lakes was greater than that of parks, with a marginal implicit price for a 100-m decrease in distance calculated as above of $129 (0.041%). Thus, the owners of single-family properties in Dakota County pay more to live near to these outdoor recreation areas.

The results of the hedonic pricing model also indicate that some aspects of views significantly influence home sale prices in Dakota County. View area, for example, significantly and positively impacts home sale prices such that a 1-ha (10,000-m2) increase in view area from the mean view area (33.26-ha) calculated at the mean home sale price corresponds to a home sale price increase of $181 (0.057%). The areas of two built land-cover types in views, 26e 50 percent impervious surface and 51e75 percent impervious surface, had significant and negative relationships to home sale price, such that a 1-ha increase in each of these land-cover types from their mean values (0.44 and 2.98-ha, respectively) resulted in a decrease in home sale price of $831 (0.260%) and $1035 (0.324%) respectively. The coefficients for other built land-cover types (i.e., 5e10 percent impervious, 11e25 percent impervious, and 76e100 percent impervious) were also negative, but were generally smaller and not significant. This indicates that the owners of single-family homes may prefer homes with views that include lower levels of impervious surface, below the 26 percent level.

The failure of views with very high (76e100 percent impervious) levels of impervious surface to significantly impact home prices may indicate that the owners of homes in highly developed areas value something else about these areas, for instance, their urban character, and that this offsets the negative value of highly-developed views under other circumstances. However, the coefficient for this variable was relatively high and negative (0.00000024, p¼ 0.15), suggesting a tendency on the part of home buyers to pay less for homes with high levels of impervious surface in their views. Additionally, in combination with the positive values placed on increased levels of neighborhood impervious surface described above, the negative values for many impervious landcover types in views may indicate a preference for living in more intensely-developed areas, but not actually being able to see them, for example, in situations where barriers such as slopes obstruct views of local impervious surfaces. It may also indicate that homeowners make a trade-off between the level of development in their neighborhood which may provide them with access to amenities and the level of impervious surfaces in their views.

Two other land-cover types in views, lawn and water, significantly and positively influenced home sale prices. Evaluated at the mean home sale price, a 1-ha increase in the area of lawn from the mean value (2584-m2) in a home’s viewshed corresponded to a sale price increase of $1742 (0.55%) while an equal increase in the area of water from its mean value (4904-m2) corresponded to a sale price increase of $81 (0.03%). This indicates a preference on the part of single-family homeowners for views of grassy areas such as golf courses, parks, or large-lot residential housing and a lower preference for views of water. The areas of all other land-cover types in views (i.e., agriculture, maintained tall grassland, forest, shrubs, grassland, emergent vegetation, and woody wetlands) did not significantly impact home sale prices in the study area. It should be noted that forest land cover includes areas explicitly identified as forest (i.e., areas of contiguous trees with no interruption by other land cover types) and does not include, for example, urbanized land covers with high percentages of tree cover. Thus, the lack of a significant impact on homes sale prices for the area of forest in viewsheds does not imply a lack of value for tree cover.

The mean percentage of tree cover in most neighborhood areas significantly and positively influenced home prices. Notably, the mean percentage of tree cover on the parcel itself was not significantly related to home sale price, indicating that homeowners are not concerned about the level of tree cover on their parcel itself. However, the mean tree cover percentages within the 100-m, 250-m, 500-m, and 750-m neighborhoods showed significant and positive relationships to home sale price such that homes with more tree cover in these areas experienced higher sale prices. The marginal implicit prices for a 10-percent increase in tree cover within each of these four neighborhoods from their mean values (13.60%, 13.40%, 14.00%, and 14.57%, respectively) evaluated at the mean home sale price were $1853 (0.581%), $1030 (0.323%), $1947 (0.610%), and $1102 (0.345%), respectively. The level of tree cover in the 1000-m neighborhood was not significantly related to home sale price. This indicates that, while home purchasers are not particularly influenced by tree cover on their own parcel, they are influenced by tree cover in its surrounding neighborhood to a distance of approximately 750-m.
The values estimated in this and other studies in the region for the same time period (Sander and Polasky, 2009; Sander et al., 2010) can help us to better understand the values of ecosystem services and amenities in the TCMA as well as how they vary with locational context (Table 1). All three studies indicate that decreasing the distance between homes and lakes that suitable for outdoor recreation increases home sale prices. The benefit is highest ($216/100 m closer, 0.084%) in the most highly urbanized area (Ramsey County) and is lowest ($129/100mcloser, 0.0041%) in less heavily-developed Dakota County. This may be due to the higher relative difficulty of accessing these features by driving in more urban areas which makes proximity to them more valuable as it increases walkability. The value associated with decreasing the distance between homes and large parks differs greatly between the two counties (by $123), indicating that urban residents value these recreational open space features much more highly, likely due to their scarcity and the desirability of accessing them on foot in urban areas. Distances to trails and streams were omitted from the current study due to multicollinearity, so we cannot draw conclusions regarding the values of these features in the region.

The values associated with tree cover are somewhat higher ($482/10% increase in the 100-m buffer and $194/10% increase in the 250-m buffer) in the present study than in the other study that examined them in both Dakota and Ramsey Counties (Sander et al., 2010) and extend to a larger neighborhood area (750-m as opposed to 250-m). This may result from higher overall scarcity of tree cover in more agricultural Dakota County (mean tree cover is 11.87%) as compared to Ramsey County where mean tree cover is somewhat higher (18.58%). This scarcity could cause tree cover to be more highly valued in Dakota County.

by Heather A. Sandera, Corresponding author contact information, E-mail the corresponding author and Robert G. Haightb, 1, E-mail the corresponding author 
a Conservation Biology Graduate Program, University of Minnesota, 187 McNeal Hall, 1985 Buford Avenue, St. Paul, MN 55108, USA 
b U.S. Forest Service Northern Research Station, 1992 Folwell Ave., St. Paul, MN 55108, USA
Volume 113, 30 December 2012, Pages 194–205 
Keywords: Ecosystem services; Economic valuation; Hedonic pricing; Spatial econometrics

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