Hedonic house price models typically impose a constant price structure on housing characteristics throughout an entire market area. However, there is increasing evidence that the marginal prices of many important attributes vary over space, especially within large markets. In this paper, we compare two approaches to examine spatial heterogeneity in housing attribute prices within the Tucson, Arizona housing market: the spatial expansion method and geographically weighted regression (GWR). Our results provide strong evidence that the marginal price of key housing characteristics varies over space. GWR outperforms the spatial expansion method in terms of explanatory power and predictive accuracy.

This paper examines how the college-educated population-segmented into selective demographic groups, from young adults to the elderly-differentially values quality-of-life (QOL) indicators of metropolitan areas in the United States. Using data from the 2000 Census and the 1997 Places Rated Almanac, out-migration patterns are shown to depend jointly upon stage in the life course, the spatial-demographic setting, and QOL characteristics. An abundance of cultural and recreational amenities lowers out-migration rates of young college-educated. For the older college-educated population, the revealed preferences shift toward concerns for safety and a strong preference for milder climates. The study also finds significantly lower out-migration rates for metropolitan areas with growing human capital. In light of shifting age distributions and rising educational attainment levels, the results have important implications for the emergence of new migration patterns and the concentration of human capital.

The absolute location of each real estate parcel in an urban housing market has a unique location-value signature. Accessibility indices, distant gradients and locational dummies cannot fully account for the influence of absolute location on the market price of housing because there are an indeterminable number of externalities (local and nonlocal) influencing a given property at a given location. Furthermore, the degree to which externalities affect real estate values is not only unique at each location but highly variable over space. Hence, absolute location must be viewed as interactive with other determinants of housing value. We present an interactive variables approach and test its ability to explain price variations in an urban residential housing market. The statistical evidence suggests that the value of location, as embodied in the selling price of housing units, may not be separable from other determinants of value. It is recommended that housing valuation models, therefore, be specified to allow site, structural and other independent attributes to interact with absolute location-{x, y} coordinates-when accounting for intraurban variation in the market price of residential housing. This approach is especially useful when estimating the value of housing for geographic areas where very little is known a priori about the neighborhoods or submarkets. Copyright 2003 by the American Real Estate and Urban Economics Association

The present research examines a structural model of violent crime in Portland, Oregon, exploring spatial patterns of both crime and its covariates. Using standard structural measures drawn from an opportunity framework, the study provides results from a global ordinary least squares model, assumed to fit for all locations within the study area. Geographically weighted regression (GWR) is then introduced as an alternative to such traditional approaches to modeling crime. The GWR procedure estimates a local model, producing a set of mappable parameter estimates and t-values of significance that vary over space. Several structural measures are found to have relationships with crime that vary significantly with location. Results indicate that a mixed model— with both spatially varying and fixed parameters—may provide the most accurate model of crime. The present study demonstrates the utility of GWR for exploring local processes that drive crime levels and examining misspecification of a global model of urban violence.

This paper presents an interdisciplinary review-from the perspectives of geography, economics, and urban planning-of the literature on central place theory (CPT) and its important role in regional science. Along the way, CPT is compared to a more recent description/explanation of the space economy, the new economic geography (NEG). The main arguments of the paper are that for a host of reasons: (i) CPT is ripe for reemergence and; (ii) NEG models are best viewed as complements to, not competitors of, CPT. Some general observations for future research in regional science follow from these conclusions. JEL Classification