Seung Gyu Kim

Spatial and Temporal Variation in the Housing Market Values of Lot Size and Open Space

This research analyzes spatial and temporal variation in the effects of lot size and proximity to open space on residential home values in a single Tennessee county. The findings show that the value of proximity to greenways, parks, and water bodies increased over time, while the value of lot size and proximity to golf courses fell. Proximity to open space is found to be a substitute for lot size, although the degree of substitutability has weakened over time. Geographic variation in the marginal effects of lot size and proximity to open space is analyzed using locally weighted regression analysis. (JEL C31, Q51)

Extreme Coefficients in Geographically Weighted Regression and Their Effects on Mapping

This study deals with the issue of extreme coefficients in geographically weighted regression (GWR) and their effects on mapping coefficients using three datasets with different spatial resolutions. We found that although GWR yields extreme coefficients regardless of the resolution of the dataset or types of kernel function: (1) GWR tends to generate extreme coefficients for less spatially dense datasets; (2) coefficient maps based on polygon data representing aggregated areal units are more sensitive to extreme coefficients; and (3) coefficient maps using bandwidths generated by a fixed calibration procedure are more vulnerable to the extreme coefficients than adaptive calibration.

Relationship between value of open space and distance from housing locations within a community

This research uses a sequence of hedonic spatial regressions for a metropolitan housing market in the Southeastern United States to explore a new procedure that establishes the relationship between the value attributable to open space and distance from housing locations (a “distance-decay function”) within a given community. A distance-decay function allows identification of the range of distance over which open space affects housing values and the estimation of a proxy for the value added to nearby houses resulting from hypothetical open space preservation. Ex post analyses of the open-space regression coefficients suggest marginal implicit price functions for three types of open space that decay as open space area increases with respect to house location. After controlling for other factors in the spatial hedonic model, simple distance-decay functional relationships were established between the implicit prices of developed open space, forest-land open space, and agriculture-wetland open space and the buffer radius of the open-space areas surrounding a given housing location. The proposed method may be useful for identifying the range over which preferences for different types of open space are exhibited.

Measuring the value of air quality: application of the spatial hedonic model

This study applies a hedonic model to assess the economic benefits of air quality improvement following the 1990 Clean Air Act Amendment at the county level in the lower 48 United States. An instrumental variable approach that combines geographically weighted regression and spatial autoregression methods (GWR-SEM) is adopted to simultaneously account for spatial heterogeneity and spatial autocorrelation. SEM mitigates spatial dependency while GWR addresses spatial heterogeneity by allowing response coefficients to vary across observations. Positive amenity values of improved air quality are found in four major clusters: (1) in East Kentucky and most of Georgia around the Southern Appalachian area; (2) in a few counties in Illinois; (3) on the border of Oklahoma and Kansas, on the border of Kansas and Nebraska, and in east Texas; and (4) in a few counties in Montana. Clusters of significant positive amenity values may exist because of a combination of intense air pollution and consumer awareness of diminishing air quality.

Valuation of Spatial Configurations and Forest Types in the Southern Appalachian Highlands

Site-specific estimates of the values of spatial configuration and forest composition are presented. Amenity values of forest patches are found to vary the most by urban and sprawling development patterns of specific areas and forest types. For example, smaller patches of deciduous forest are more highly valued in the urban and sprawling areas of Greensboro, North Carolina, whereas larger patches of deciduous forest are more highly valued in the urban and sprawling areas of Greenville, South Carolina. Within the Greenville and Greensboro areas, visible landscape complexity is highly valued for deciduous and evergreen forest patches, whereas lower visible landscape complexity, i.e., smoothly trimmed forest patch boundaries, is highly valued for mixed forest patches.

Spatial Analysis of Rural Economic Development Using a Locally Weighted Regression Model

This study uses locally weighted regression to identify county-level characteristics that serve as drivers of creative employment throughout the southern United States. We found that higher per capita income, greater infrastructure investments, and the rural nature of a county tended to promote creative employment density, while higher scores on a natural amenity index had the opposite effect. We were also able to identify and map clusters of rural counties where the marginal effects of these variables on creative employment density were greatest. These findings should help rural communities to promote creative employment growth as a means of furthering rural economic development.

Demand for Open Space and Urban Sprawl: The Case of Knox County, Tennessee

Urban sprawl is often blamed for causing negative environmental effects from unsustainable land consumption and increased traffic congestion. While there is no generally accepted definition of urban sprawl, the process is well-described as the expansion of urban development into rural areas surrounding major cities, and the leapfrogging of development beyond the city’s outer boundary into smaller rural settlements (Hanham and Spiker 2005). Many studies have pointed toward the lifestyle choices of the economically affluent society for the rapid growth of urban sprawl (Brueckner 2000; Carruthers and Ulfarsson 2002; Frumkin 2002; Gordon and Richardson 1998, 2000, 2001a,b; Krieger 2005; Nechyba and Walsh 2004; Skaburskis 2000; Stone and Gibbins 2002). These lifestyle choices include preferences for larger homes and lot sizes, low density housing, mobility afforded by private vehicles, and the demand for open space. This kind of growth has raised concern about the potential negative impacts, especially the loss of benefits provided by farmland and open space, and higher costs of infrastructure and community services. Concerns about the negative consequences of urban sprawl have led local policymakers and nongovernmental activists to turn to urban and suburban open space conservation as potential mechanisms to counter urban sprawl. One example of these mechanisms includes “smart growth” policies. Smart growth policies are development initiatives that protect open space and farmland, revitalize communities, keep housing affordable, and provide more transportation choices (International City/County Management Association 2008). Local governments have incorporated “smart growth” principles designed to encourage compact development and preserve open space to curtail urban sprawl (Tracy 2003). Compact development is a key component of most smart growth policies. A large body of planning literature has addressed a variety of local strategies that are grouped under the rubric of “smart growth” (e.g., Blakely 1994; Daniels 2001; Handy 2005; Weitz 1999).

Impact of a Two-Rate Property Tax on Residential Densities

Municipalities sometimes reform property tax schedules in an effort to increase suboptimal residential densities. One such approach is to reduce the tax rate applied to building values and increase the tax rate applied to land, known as a two-rate property tax (TPT). This paper evaluates the impact of a TPT on residential density in Nashville-Davidson County, Tennessee where a conventional property tax schedule prevails during 2006--2007. When land taxes are proportionally higher than taxes on structures, 1.07 to 1 and 1.25 to 1 for general and urban service districts, respectively, ex ante simulations suggest that housing density increases by 18% in general services districts and 83% in urban services districts. Copyright 2013, Oxford University Press.

Interrelationship between poverty and the wildland--urban interface in metropolitan areas of the Southern US

This research disentangles the relationship between Wildland–Urban Interface (WUI) area and poverty in metropolitan areas of the Southern US where urban sprawl has intensified and high-poverty regions have persisted. Results confirm that the enlargement of WUI areas increases urban poverty, which in turn causes WUI areas to expand. This finding validates the underlying hypothesis: expansion of the WUI excludes people in poor inner-city neighbourhoods from educational and economic opportunities that occur in suburban areas and the problems related to inner-city poverty push the rich away from the inner city.

Developing an amenity value calculator for urban forest landscapes

Abstract The goal of this research is to develop a framework that can be used by landscape and urban planners to implement an “amenity value calculator” for urban forest landscapes across a metropolitan county. By balancing the pros and cons of using typical hedonic frameworks versus urban forest inventory and management software systems, we (1) construct a data-driven approach to estimate the total amenity value associated with access to, views of, and existence of a particular forest landscape from among all available forest sites in a community and (2) develop a framework for an amenity value calculator for numerous community forest landscapes within a metropolitan county, using the amenity values generated from objective (1), that can be accessed and understood by anyone who is interested in the benefits provided by nearby community forests. Our research suggests that (i) residential household’s amenity value per acre of forest landscape decreases asymptotically towards zero as the driving time from a residential house increases, (ii) an amenity value calculator can be developed to sum the amenity values across all detached single-family houses within a range of driving times from any selected forest landscape, and (iii) a user-friendly, web-based application, that allows users to view the estimated amenity values of forest landscapes that interest them, can be created to better inform the public about the values of forest landscapes of interest to them.