The trade-off between private lots and public open space in subdivisions at the urban-rural fringe.

Several econometric issues must be addressed in estimating the hedonic model. In a study focusing on farmland and forested lands, Irwin (2002) discusses the problem of possible endogeneity of these kinds of open space. Since we are focusing on the amount of open space inside the subdivision in this study, it is unlikely that endogeneity is a serious concern. Moreover, all subdivisions since 1993 have had minimum open space requirements. We also assume households know and accept county rules, which require that subdivision open space has a permanent easement barring future development.

We consider the issue of unobserved spatial correlation in the error term, a common source of inefficiency and inappropriate covariance estimates in spatial models. To partially address this problem, we have included dummy variables for the thirty-one census block groups in our sample to account for any unexplained effect of different neighborhoods on prices. (4) In addition, we tested for spatial autocorrelation and rejected the null hypothesis that it is not present, even with block group dummies. (5) Therefore, to account for spatial correlation caused by misspecification of the regression function (e.g., omitted variables), we specify the error term with a standard firs[order AR process. The errors are assumed to depend on the weighted average of the errors of "neighboring" houses, which we define to be houses that are in the same or adjacent subdivisions. (6) The results are shown in table 2. We tested the sensitivity of our results by estimating the model with an alternative weighting scheme where all houses within one mile of each other were considered neighbors. (7) This latter specification yielded coefficients of similar magnitude and significance as the results presented in table 2.

Results: Preferences for Lot Size and Subdivision Open Space Amenities

Households have a consistent preference for larger lots, ceteris paribus. We calculate the marginal willingness to pay for additional private acreage and subdivision open space by the partial derivatives of the price function with respect to each attribute, evaluated at the mean values of the relevant interaction variables. The elasticity estimates at the bottom of table 2 summarize the results of that calculation. We find that a 10% increase in private lot size is associated with an approximately 0.6% increase in house price, ceteris paribus. This suggests that for an average priced house in 2004 (about $300,000), an increase in lot size from 1 to 1.5 acres would increase price by about $9,000 (year 2000 dollars). The magnitude of this estimate is robust across various specifications of the model, including one with subdivision fixed effects.

The amount of open space in the subdivision, given subdivision size, is also statistically significant, and its effect on house prices is positive, but small. A 10% increase in subdivision open space leads to a 0.1% increase in average house price, ceteris paribus. This result was also robust to alternative specifications of the model. This suggests that increasing open space acreage from 20 to 30 acres would increase sales price by 0.5 percent, or $1,500 per house (evaluated at an average of $300,000), ceteris paribus. Of course, all houses in the subdivision would be affected if open space increased.

The significant, negative interaction term between the amount of open space and own lot size provides evidence that residents will trade off their own lot size for the amount of open space in the subdivision. Adjacency to subdivision open space also has a positive effect on house prices, but the magnitude of the effect depends on how much of the open space is in steep slopes. The greater the percentage of open space that is steep, the smaller the impact that adjacency has on house prices. (8)

Perhaps our most surprising result is that we find households unwilling to trade off their own lot size to be adjacent to open space. One explanation for this may be a result from the literature that suggests that proximity to open space is less valuable than having a view of forested or undeveloped areas (e.g., Patterson and Boyle 2002).

Results: Other Variables

Most of the other explanatory variables in the model are significant and of the expected sign. All of the variables describing house characteristics and variables measuring proximity to commuting routes are significant at the 99% or 95 % level. The northern edge of the county marks the closest point in the county to urban centers of Washington, DC, and Baltimore; moving the average house one mile farther south reduces house price by a little more than 1%. Locating farther from the major highway in the county, Route 2/4, also significantly reduces sales price. Larger and newer subdivisions tend to have slightly higher-priced houses.

Some of the other amenities and surrounding land uses are important in explaining house prices while others are not. Being on the water is highly valuable: sales prices of waterfront houses (on the Patuxent River or Chesapeake Bay) are found to be 30% higher than prices of other houses. However, being adjacent to parkland, privately owned preserved farmland, or the open space area of another subdivision does not significantly affect housing prices. (9)

Simulating the Effect of Clustered Subdivisions on House Prices

We can illustrate the overall effects of changes in subdivision configuration by a simple simulation. We start with a representative subdivision in our sample: 134 acres in size, with about 30 acres of open space and an average lot size of 1.5 acres. Holding total subdivision size and the number of lots constant, doubling the amount of open space to about sixty acres would require average lot size to fall to 1.1 acres. Based on the results in table 2, we find that such an increase in clustering (from about 22% to 44%) would decrease the average house price by 1.2% (for a house not adjacent to open space). The loss in value from the smaller lot size dominates any increased value from more subdivision open space. The additional clustering may also increase the probability of a house being adjacent to the open space area, however, and this adds some value. For houses on lots that become adjacent to subdivision open space as a result of the increased clustering, we find the change in sale price is minimal, decreasing by only 0.3%.

Conclusions

Our results suggest why we may not see many clustered subdivisions on the urban--rural fringe without government regulations requiring such clustering. Households appear to strongly value their own private lots. While we do find in our analysis that households also value having more open space in their subdivisions, or having a lot that is adjacent to subdivision open space, they do not value these amenities nearly as much as a larger lot. Thus, reducing private acreage to provide more public subdivision open space tends to lead to overall reductions in house prices, all else equal.

One of the most important questions we wanted to address in this study is whether households would be willing to trade off the size of their own lot for open space in the subdivision. Clustering subdivision development is being viewed as a way to reduce the development footprint and preserve open space in fringe communities. Our findings suggest that there is some small willingness to trade off lot size for more subdivision open space. One caveat to our findings is that they may be specific to the community we were examining--one on the urban-rural fringe with very large average lot sizes and a great deal of surrounding open space and farmland. It is possible that households in these areas value their large lots and also have adequate substitutes for subdivision open space.

Our analysis only attempts to measure the effects of subdivision open space on property values within the subdivision. The external benefits of subdivision open space, such as aesthetic values, and ecological and environmental benefits, may accrue to the larger community. These benefits will not be capitalized into subdivision property values, and to the extent they are important, suggest additional reasons why the private market may underprovide open space and government intervention may be necessary.

Land-Use Policy Experiments at the Rural-Urban Interface (Lori Lynch, University of Maryland, Organizer)

References

Arendt, R. 1992. "'Open Space' Zoning: What It Is and Why It Works." Planning Commissioners Journal 5 (July), pp. 1-9, http:// www.plannersweb.com/articles/are015.html.

Berke, R, J. McDonald, N. White, M. Holmes, K. Oury, and R. Ryznar. 2003. "Greening Development to Protect Watersheds." Journal of the American Planning Association 69:397-413.

Daniels, T.L. 1997. "Where Does Cluster Zoning Fit in Farmland Protection?" Journal of the American Planning Association 63:129-37.

Hardie, I., E. Lichtenberg, and C. Nickerson. 2006. "Regulation, Open Space, and the Value of Land Undergoing Residential Subdivision." University of Maryland.

Irwin, E.G. 2002. "The Effects of Open Space on Residential Property Values." Land Economics 78:465-80.

Kaplan, R., M.E. Austin, and S. Kaplan. 2004. "Open Space Communities: Resident Perceptions, Nature Benefits, and Problems with Terminology." Journal of the American Planning Association 70:300-12.

Kearney, A.R. 2006. "Residential Development Patterns and Neighborhood Satisfaction, Impacts of Density and Nearly Nature." Environment and Behavior 38:112-39.