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D ATA A N D S Y N T H E T I C P O P U L AT I O N S 23
· Predicting future land use patterns is of interest to City of Austin and its 2-mile, extraterritorial jurisdic-
policy makers, developers, transportation planners and tion, which accounts for 420 square miles. Both the sup-
engineers, and other groups. Residential development ply of homes and the demand for homes were modeled
accounts for approximately 60% of developed land. Res- explicitly. On the supply side, the city's land use parcel
idential location choice is fundamental to land use plan- map was used to draw a 10% random sample from the
ning and travel demand forecasting. The availability of 16,750 undeveloped parcels in the area in 2000. The dis-
parcel-level data sets and geographic information sys- tribution of existing single-family residential parcel sizes
tems (GIS) provides the ability to examine residential resembles a chi-square distribution. Large undeveloped
location issues in more detail than was previously parcels were assumed to subdivide according to this dis-
possible. tribution. The newly generated single-family sites--
· The study examined where new households would defined by home size, parcel-specific unit price per
locate in Austin assuming a 25% percent increase in pop- interior square foot, and distance to employment sites
ulation. The study framework was based on random uti- and shopping centers--were allocated to individual
lization maximization and bid-rent theory. Location households based on rent-maximizing and utility-
choice behavior suggests that households choose the res- maximizing action principles.
idential location offering the highest utility. Further, · On the demand side, the 7,600 future households
households trade off housing prices relative to annual were distributed into five income levels. The new house-
income and commute costs. The housing market equili- holds were assumed to be demographically distributed
bration includes the demand side of individual house- according to the 2002 American Community Survey.
holds competing for spaces and the supply side of Based on a 10% random sample of undeveloped land
landowners selling homes to the highest bidders. parcels and a 25% population increase, there were
· The project examined single-family residential 1,500, 1,200, 1,200, 2,300, and 1,400 households allo-
developments based on a microscopic equilibrium of the cated to the five income levels, respectively. The loca-
housing market for recent moves in Austin. Each home- tions of 114 employment centers with at least 500 jobs
seeking household was allocated to the location that and 18 retail centers were identified.
offered the highest utility, and each new home was occu- · The process focused on reaching market equilib-
pied by the highest bidder. The approach ensures opti- rium for new home buyers in an iterative manner for six
mal allocation of land, as each household chooses a scenarios. Parcels located close to employment sites had
home that most satisfies the household, and developers higher average equilibrium unit price for households
and landowners maximize profits. with higher values of travel time. No clear relationship
· The data used in the study were obtained from a emerged between the average equilibrium unit price and
2005 survey of home buyers in Travis County, which the distance or travel time to employment sites for house-
includes the City of Austin. Half of the home buyers were holds with low values of travel time.
included in the sample, and a total of 900 completed sur- · Additional research examining more household
veys were returned, accounting for approximately 12% types and residential choices, such as single-family
of all home buyers. The data set contains information on dwelling versus apartment, would be beneficial. Other
household demographics, housing characteristics, rea- areas for further research include simultaneous simula-
sons for relocation, and preferences related to different tion of job locations and examining the spatial allocation
housing and location choice scenarios. This information of single-family, multifamily, and nonresidential uses.
was used in the location choice model.
· A GIS-encoded parcel map was used in the analy-
sis. Microsimulation of single-family residential develop- William Upton, Oregon Department of Transportation,
ments for housing market equilibrium was applied to the moderated this session.
