The Bid-rent Land Use Model of the simple,efficient, elegant,and effective model of land use and transportation

Integrated land use/transportation forecasting models add significant policy and infrastructure alternatives analysis capabilities to the urban planning process. The financial, time, and staff requirements to develop these models has put them beyond the reach of most small to medium sized urban areas. This paper presents the land use allocation submodel of the Simple, Efficient, Elegant, and Effective model of land use and transportation (SE³M), an integrated land use and transportation forecasting model founded upon Economic Base Theory and Bid-rent Theory. The Bid-rent Land Use Model (BLUM) is an agent based, spatial competition model utilizing unique utility curves for willingness to pay and incomes for budget constrained abilities to pay for each agent. The model structure, estimation, calibration, implementation, and validation are presented. With a single year of land use data available, the validation approach used the Kappa Index of Agreement to spatially check model outputs against base year control data while controlling for agreement by chance. The U.S. territory of Guam is used as the case study/proof of concept implementation for this model framework. Once calibrated, BLUM could solve the spatial competition problem on Guam in less than two minutes of processing time with over 90% accuracy.     

On joint railway and housing development strategy

Transit Oriented Development (TOD) with railway service is recognized as a sustainable mode of development for highly dense megacities. In addition to providing safe and efficient transit services, reducing auto dependence and therefore less need for highway expansions, the improved accessibility of TOD influences commuters’ residential location choices and the resultant housing value. Traditionally, statistical approaches have been used to estimate the relationship between railway development and housing value for individual sites. To some degree, TOD has also been studied with integrated land-use transport models. While useful, they lack an analytical framework to study the region-wide impacts of TOD on residential location and travel choices and the resultant land value changes. In this study, the joint railway and housing development strategy is modeled based on a combined equilibrium formulation with the bid-rent process. The problem is formulated as a mathematical program with equilibrium constraints, in which the upper level optimizes the objective for the joint development strategy by deciding on the combination of housing supplies and railway service levels. Analytical results are obtained for a single corridor in a multi-modal transport network, which are further illustrated by sensitivity analyses. A numerical example is constructed to demonstrate the approach and compare with other separate development strategies. The results generally confirm the synergy between railway and housing developments.     

Optimal housing supply in a bid-rent equilibrium framework

In this study, we examine how the spatial distribution of housing supply impacts people’s residential choices and developers’ profitability. By optimally providing housing supply in a region, developers attempt to maximize their profits; on the other hand, if residents were given a chance to decide on housing supply, what patterns of housing supply they would prefer in order to maximize their consumer surpluses. This paper studies the interplay between these two perspectives. A nested multinomial-logit choice structure that encapsulates the bid-rent process is used to capture residents’ location and travel choices simultaneously, and the resultant rents at different locations. To investigate the optimal housing supply for these two stakeholders, we conduct sensitivity analyzes to explore the impact of different housing supply patterns on total rental profit and total consumer surplus. Specifically, analytical results are derived for a simple linear network with two residential locations and one destination under homogeneous and heterogeneous value(s) of time. The results of the sensitivity analyzes indicate that segregation of housing supplies at different locations for different income classes is, surprisingly, a “preferred” outcome by residents under consumer surplus maximization, whereas creating housing supply shortages at convenient locations is a natural outcome under housing profit maximization. These results provide insights on revealing the differences and tradeoffs in performance between these two different perspectives, and on where land use regulations may be needed to balance these two objectives.