Abstract
This paper develops a dynamic spatial general equilibrium model of urban environments to enable more land-use detail, population growth, and change dynamics and applies it to evaluate impacts of land-use externalities and zoning regulations on land-use markets. The new model specification tracks not just different parcel sizes and access attributes, but also various location externalities that affect household and firm decisions. The model also allows for three sources of spatial dynamics, including demographic change, building stock conversion subject to zoning regulations, and evolving location externalities. The model is calibrated for 38 zones across Austin, Texas; simulations highlight changes in land use, housing demand, and rents, under four scenarios encompassing different assumptions on land-use preferences and regulations. Results suggest that people’s rising demand for mixed-use neighborhoods may improve land-use diversity in suburban areas and lower demand for low-density single-family housing across a region. Low-density zoning regulations in Austin’s outer suburbs may lead to citywide job-housing imbalances and urban sprawl. When the existing low-density zoning regulations cannot be changed in the short term, promotion of mixed-use development may moderate tendencies toward more excessive urban sprawl.
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Notes
- 1.
An updated version, RELU-TRAN2, is developed in Anas and Hiramatsu (2012). When compared to RELU-TRAN, RELU-TRAN2 adds the choice of vehicle fuel economy into consumers’ utility functions and thus internalizes people’s gasoline use.
- 2.
Other sources of agglomeration externalities are endogenized in the model, as they are in the RELU model (Anas and Liu, 2007), including those that come from reducing the costs of moving intermediate goods over space and those that come from reducing the costs of accessing workers (via commuting costs).
- 3.
RELU has a more detailed category of construction and demolition firms than used here, based on different building types.
- 4.
Six types of land use are included: single-family residential, multi-family residential, commercial, industrial, civil, and open space. Among them, the shares of civil and open-space land uses are exogenous. Suppose the proportions of different land uses are \(\varrho_{i} ,i = 1 \ldots 6\), the land-use mix entropy index is calculated as \(\mathop \sum \nolimits_{i = 1}^{6} \varrho_{i} { \ln }\varrho_{i} /{ \ln }6\).
- 5.
For zone i in the outer suburbs, \({\mathbb{Z}}_{i}\) = {low-density single-family housing with FAR = 0.2}, and for zone i in the urban core and inner suburbs, \({\mathbb{Z}}_{i}\) = {low-density single-family housing with FAR = 0.2, high-density single-family. housing with FAR = 0.4, low-density multi-family housing with FAR = 0.6, high-density multi-family housing with FAR = 0.8}
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Zhang, W., Kockelman, K.M., Thill, JC. (2020). City Land Use and Rent Dynamics with Location Externalities and Zoning Regulations: A Dynamic Spatial General Equilibrium Model. In: Thill, JC. (eds) Innovations in Urban and Regional Systems. Springer, Cham. https://doi.org/10.1007/978-3-030-43694-0_9
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