Despite recent advances in geosimulation, empirical land-use change modeling, and regional spatial dynamic theories, basic knowledge regarding how regional economic growth and decline impact the spatial and temporal dynamics of exurban land-use patterns remains rudimentary. This is due in large part to a continued reliance on assumptions of instantaneous price adjustments to a long-run spatial equilibrium in conventional urban economic models that omit consideration of short-run dynamics and local spatial interactions. To address these theoretical limitations, this research project will develop a dynamic spatial model of exurban land markets that explicitly accounts for key features of exurban areas to explain observed exurban land-price and development pattern dynamics (Objective 1). The model will incorporate local land use feedbacks, such as open space and congestion spillovers, to investigate how incorporation of these endogenous local spillovers influences land-price and land-use dynamics (Objective 2). The model will also be used to explore the potential impacts of income shocks on exurban land demand, supply, and land-use patterns and the time scales over which these changes occur (Objective 3). The project will accomplish these research objectives by developing a new theoretical model of exurban land markets that accounts for the relative demand and supply of spatially differentiated land. The investigators will use an auction model to derive optimal household bids and an optimal timing model to derive landowner reservation rents. Spatial agent-based computational modeling will be used to simulate market interactions and derive spatially varying market land prices and land development patterns over time. Extensive spatial data on parcel-level land development and residential location decisions will be used to empirically specify the key model parameters and MatLab and C++ codes will be used for implementation. The expectation is that the model will generate new hypotheses regarding the role of spatial arbitrage in exurban land markets and will provide a new theoretical and simulation-based framework for studying spatial land-use dynamics.

Rapid exurban growth and the characteristic low density and scattered urbanization patterns that accompany it have greatly extended America's urban footprint and transformed many rural areas. Since the onset of the housing bust in 2006, a new set of challenges has emerged for many exurban areas that appear to have declined more rapidly than their urban and suburban counterparts. Both trends raise essential questions about the sustainability of exurban regions. By developing a dynamic spatial model of exurban land markets, this project will address these fundamental questions of exurban growth, decline, and sustainability. Despite the economic and ecological importance of the exurbs, no one has fully conceptualized or developed a spatial dynamic model of exurban land markets. By doing so, this project will make a fundamental theoretical contribution to land-change science and provide new insights into urban spatial patterns. The empirical applications proposed in this project will generate new knowledge that will have tangible benefits to policy makers confronted with urban sustainability management challenges. By furthering collaboration among scientists from regional science and physics, this project will advance the involvement of spatial scientists in interdisciplinary research and provide new interdisciplinary training opportunities for graduate students in complex systems and spatial economic modeling.

Project Report

We develop a spatial dynamic simulation model of exurban land development. In contrast to traditional economic land-use models, it adapts the long-run-equilibrium assumption, representative of urban areas, to fit rural land markets. Maintaining these markets’ essential long-run characteristics, the model provides a novel way of capturing the short-run dynamics particular to rural areas, an issue especially important to policy analysis. This new model is capable of simulating transitional dynamics toward long-run equilibrium in exurban land market. This model bridges the standard urban economic land use models with the latest development in agent-based modeling of Geosciences. The model has several innovative features: it can utilize spatially referenced data and it can incorporate both static and dynamically changing characteristics at both the parcel and neighborhood level. The integration auction theory and land use modelling is one of the key methodological contributions. Coded in C++, the model has been tested on a number of computing platforms. It lays the groundwork for a wide variety of interesting future research, such as a simulation of land-use policy impacts and an integration of structural modeling with empirical analysis of land-use changes. The dynamic and spatially explicit feature of the simulation tool facilitates its integration with land-use-change models in other disciplines. This is important for informing land-use policies related to water quality and climate change. To date, two papers from this research are under journal review.

National Science Foundation (NSF)
Division of Behavioral and Cognitive Sciences (BCS)
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Thomas J. Baerwald
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Oregon State University
United States
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