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⢠Predicting future land use patterns is of interest to policy makers, developers, transportation planners and engineers, and other groups. Residential development accounts for approximately 60% of developed land. Res- idential location choice is fundamental to land use plan- ning and travel demand forecasting. The availability of parcel- level data sets and geographic information sys- tems (GIS) provides the ability to examine residential location issues in more detail than was previously possible. ⢠The study examined where new households would locate in Austin assuming a 25% percent increase in pop- ulation. The study framework was based on random uti- lization maximization and bid- rent theory. Location choice behavior suggests that households choose the res- idential location offering the highest utility. Further, households trade off housing prices relative to annual income and commute costs. The housing market equili- bration includes the demand side of individual house- holds competing for spaces and the supply side of landowners selling homes to the highest bidders. ⢠The project examined single- family residential developments based on a microscopic equilibrium of the housing market for recent moves in Austin. Each home- seeking household was allocated to the location that offered the highest utility, and each new home was occu- pied by the highest bidder. The approach ensures opti- mal allocation of land, as each household chooses a home that most satisfies the household, and developers and landowners maximize profits. ⢠The data used in the study were obtained from a 2005 survey of home buyers in Travis County, which includes the City of Austin. Half of the home buyers were included in the sample, and a total of 900 completed sur- veys were returned, accounting for approximately 12% of all home buyers. The data set contains information on household demographics, housing characteristics, rea- sons for relocation, and preferences related to different housing and location choice scenarios. This information was used in the location choice model. ⢠A GIS- encoded parcel map was used in the analy- sis. Microsimulation of single- family residential develop- ments for housing market equilibrium was applied to the City of Austin and its 2-mile, extraterritorial jurisdic- tion, which accounts for 420 square miles. Both the sup- ply of homes and the demand for homes were modeled explicitly. On the supply side, the cityâs land use parcel map was used to draw a 10% random sample from the 16,750 undeveloped parcels in the area in 2000. The dis- tribution of existing single- family residential parcel sizes resembles a chi- square distribution. Large undeveloped parcels were assumed to subdivide according to this dis- tribution. The newly generated single- family sitesâ defined by home size, parcel- specific unit price per interior square foot, and distance to employment sites and shopping centersâ were allocated to individual households based on rent- maximizing and utility- maximizing action principles. ⢠On the demand side, the 7,600 future households were distributed into five income levels. The new house- holds were assumed to be demographically distributed according to the 2002 American Community Survey. Based on a 10% random sample of undeveloped land parcels and a 25% population increase, there were 1,500, 1,200, 1,200, 2,300, and 1,400 households allo- cated to the five income levels, respectively. The loca- tions of 114 employment centers with at least 500 jobs and 18 retail centers were identified. ⢠The process focused on reaching market equilib- rium for new home buyers in an iterative manner for six scenarios. Parcels located close to employment sites had higher average equilibrium unit price for households with higher values of travel time. No clear relationship emerged between the average equilibrium unit price and the distance or travel time to employment sites for house- holds with low values of travel time. ⢠Additional research examining more household types and residential choices, such as single- family dwelling versus apartment, would be beneficial. Other areas for further research include simultaneous simula- tion of job locations and examining the spatial allocation of single- family, multifamily, and nonresidential uses. William Upton, Oregon Department of Transportation, moderated this session. 23DATA AND SYNTHETIC POPULATIONS
