Elena G. Irwin

The Effects of Open Space on Residential Property Values

The marginal values of different open space attributes are tested using a hedonic pricing model with residential sales data from central Maryland. The identification problems that arise due to endogenous land use spillovers and unobserved spatial correlation are addressed using instrumental variables estimation with a randomly drawn subset of the data that omits nearest neighbors. Results show a premium associated with permanently preserved open space relative to developable agricultural and forested lands and support the hypothesis that open space is most valued for providing an absence of development, rather than for providing a particular bundle of open space amenities. (JEL R52)

Theory, data, methods: developing spatially explicit economic models of land use change

Questions of land use/land cover change have attracted interest among a wide variety of researchers concerned with modeling the spatial and temporal patterns of land conversion and understanding the causes and consequences of these changes. Among these, geographers and natural scientists have taken the lead in developing spatially explicit models of land use change at highly disaggregate scales (i.e. individual land parcels or cells of the landscape). However, less attention has been given in the development of these models to understanding the economic process — namely, the human behavioral component — that underlies land use change. To the extent that researchers are interested in explaining the causal relationships between individual choices and land use change outcomes, more fully articulated economic models of land use change are necessary. This paper reviews some of the advances that have been made by geographers and natural scientists in developing these models of spatial land use change, focusing on their modeling of the economic process associated with land use change. From this vantage point, it is argued that these models are primarily “ad hoc,” developed without an economic theoretical framework, and therefore are susceptible to certain conceptual and estimation problems. Next, a brief review of traditional economic models of land use determination is given. Although these models are developed within a rigorous economic framework, they are of limited use in developing spatially disaggregate and explicit models of land use change. Recent contributions from economists to the development of spatially explicit models are then discussed, in which an economic structural model of the land use decision is developed within a spatially explicit framework and from which an estimable model of land use change is derived. The advantages of this approach in terms of simulating policy scenarios and addressing econometric issues of spatial dependency and endogeneity are discussed. We use some specific examples from ongoing research in the Patuxent Watershed, Maryland, USA to illustrate our points. The paper concludes with some summary remarks and suggestions for further research.

The evolution of urban sprawl: Evidence of spatial heterogeneity and increasing land fragmentation

We investigate the dynamics and spatial distribution of land use fragmentation in a rapidly urbanizing region of the United States to test key propositions regarding the evolution of sprawl. Using selected pattern metrics and data from 1973 and 2000 for the state of Maryland, we find significant increases in developed and undeveloped land fragmentation but substantial spatial heterogeneity as well. Estimated fragmentation gradients that describe mean fragmentation as a function of distance from urban centers confirm the hypotheses that fragmentation rises and falls with distance and that the point of maximum fragmentation shifted outward over time. However, rather than outward increases in sprawl balanced by development infill, we find substantial and significant increases in mean fragmentation values along the entire urban–rural gradient. These findings are in contrast to the results of Burchfield et al. [Burchfield M, Overman HG, Puga D, Turner MA (2006) Q J Econ 121:587–633], who conclude that the extent of sprawl remained roughly unchanged in the Unites States between 1976 and 1992. As demonstrated here, both the data and pattern measure used in their study are systematically biased against recording low-density residential development, the very land use that we find is most strongly associated with fragmentation. Other results demonstrate the association between exurban growth and increasing fragmentation and the systematic variation of fragmentation with nonurban factors. In particular, proximity to the Chesapeake Bay is negatively associated with fragmentation, suggesting that an attraction effect associated with this natural amenity has concentrated development.

The Problem of Identifying Land Use Spillovers: Measuring the Effects of Open Space on Residential Property Values

development, such as traffic congestion and air pollution. Several willingness-to-pay studies have demonstrated the positive amenity value of open space (Halstead; Beasley, Workman, and Williams), but evidence of the value of open space from revealed preference methods--namely, from hedonic models--is limited and mixed. In this article, we consider the issue of estimating open space spillovers using a hedonic pricing model with residential property sales and offer an explanation for why the positive amenity value of open space effects, even if it exists, may not always be empirically detected. The estimation problems that we consider are ones of identification, which arise in a hedonic residential price model when the open space land is privately held and developable.1 Under these circumstances, land parcels counted as open space are part of the market for residential land and therefore subject to the same economic forces that determine a locations residential value.

Determinants of Residential Land-Use Conversion and Sprawl at the Rural-Urban Fringe

We estimate a probit model of residential land conversion using parcel-level data from a rural-urban county in Ohio. Spatial landscape pattern metrics are used to quantify land-use patterns and to link patterns of residential sprawl with factors estimated to influence parcel-level land conversion. Findings indicate that the location of new residential development is influenced by preferences for lower density areas that nonetheless are close to existing urban development. Combined, these forces have generated a moderated pattern of residential sprawl. Spatial error autocorrelation is controlled using a spatial sampling technique that enables consistent estimation of the probit model.

Comparison of empirical methods for building agent-based models in land use science

The use of agent-based models (ABMs) for investigating land-use science questions has been increasing dramatically over the last decade. Modelers have moved from ‘proofs of existence’ toy models to case-specific, multi-scaled, multi-actor, and data-intensive models of land-use and land-cover change. An international workshop, titled ‘Multi-Agent Modeling and Collaborative Planning—Method2Method Workshop’, was held in Bonn in 2005 in order to bring together researchers using different data collection approaches to informing agent-based models. Participants identified a typology of five approaches to empirically inform ABMs for land use science: sample surveys, participant observation, field and laboratory experiments, companion modeling, and GIS and remotely sensed data. This paper reviews these five approaches to informing ABMs, provides a corresponding case study describing the model usage of these approaches, the types of data each approach produces, the types of questions those data can answer, and an evaluation of the strengths and weaknesses of those data for use in an ABM.

New Directions for Urban Economic Models of Land Use Change: Incorporating Spatial Dynamics and Heterogeneity

We review the usefulness of urban spatial economic models of land use change for the study and policy analysis of spatial land use–environment interactions. We find that meaningful progress has been made in econometric and monocentric models extended to account for multiple sources of spatial heterogeneity and in the development of general equilibrium models with spatial dynamics. Despite these advances, more work is needed in developing models with greater realism. Most agent-based computational models of urban land use change currently lack economic fundamentals, but provide a flexible means of linking microlevel behavior and interactions with macrolevel land use dynamics. In combination with empirical methods to identify parameters, this framework provides a promising approach to modeling spatial land use dynamics and policy effects.

A Century of Research on Rural Development and Regional Issues

Rural North America has undergone a major economic transformation over the past century due to labor-saving technological progress, reductions in transport costs, and rising household incomes. The results are greater rural economic diversity, selected rural population decline, increased rural--urban interdependence, emergent exurban areas, and amenity-led rural growth. We summarize key research insights and provide a selected review of the economics literature over the past 100 years with a focus on this economic transformation of rural places, its implications for rural communities, and key modeling innovations and applications. The many important contributions by agricultural economists are highlighted. Copyright 2010, Oxford University Press.

Modeling and Managing Urban Growth at the Rural-Urban Fringe: A Parcel-Level Model of Residential Land Use Change

As many local and state governments in the United States grapple with increasing growth pressures, the need to understand the economic and institutional factors underlying these pressures has taken on added urgency. From an economic perspective, individual land use decisions play a central role in the manifestation of growth pressures, as changes in land use pattern are the cumulative result of numerous individual decisions regarding the use of lands. In this study, the issue of growth management is addressed by developing a spatially disaggregated, microeconomic model of land conversion decisions suitable for describing residential land use change at the rural-urban fringe. The model employs parcel-level data on land use in Calvert County, Maryland, a rapidly growing rural-urban fringe county. A probabilistic model of residential land use change is estimated using a duration model, and the parameter estimates are employed to simulate possible future growth scenarios under alternative growth management scenarios. Results suggest that “smart growth” objectives are best met when policies aimed at concentrating growth in target areas are implemented in tandem with policies designed to preserve rural or open space lands.

The Effects of Farmland, Farmland Preservation, and Other Neighborhood Amenities on Housing Values and Residential Growth

Using data from a conjoint instrument, we estimate compensating variation for the presence of neighboring land that is dedicated to agricultural use (versus developed uses), the preservation of surrounding farmland as permanent cropland, and key neighborhood characteristics such as neighborhood parks, commute times, school quality, and safety. We find that rural-urban fringe areas that are located within commuting distance of urban areas and that have an abundance of farmland could attract residential development. Typical preservation efforts, featuring small parcels of preserved farmland, would induce further residential growth only for areas with short commutes and small amounts of remaining farmland. (JEL R14, Q15)