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respectively. Three VOTT scenarios were designed to examine the impact of how VOTT may affect spatial allo- cation of residences. The low, medium, and high VOTTs for each of the five household types were assumed to be as follows: (a) low VOTTs of $1.40/h, $3.50/h, $5.30/h, $9.00/h, and $10.60/h; (b) medium VOTTs of $2.80/h, $7.00/h, $10.50/h, $18.00/h, and $21.30/h; and (c) high VOTTs of $5.50/h, $14.00/h, $21.00/h, $36.00/h, and $42.50/h, respectively. [The low, medium, and high VOTTs were taken to be 25%, 50%, and 100% of employed membersâ wage (assuming one full- time employed person in the first four types of households and two full- time employed persons in the last type of house- hold.)] These households compete for homes that offer them the highest utilities. Due to this competition, home prices are bid up until the market reaches equilibrium. Essentially, individual households are assumed to evaluate all new (single- family) residential parcels as a function of their price, size, and site accessibility (in rela- tion to travel costs, distances to employment centers and shopping malls, or both). When a home is selected as the best choice by more than one household, the imbalance in both competition and supplyâdemand should increase the unit price. Following such price increases, the previ- ous best choice becomes unaffordable or at least less preferable due to the price increase, and other, relatively more preferred homes may emerge. Through this implicit price mechanism, households withdraw from competi- tion over home sites that are experiencing high demand. Ultimately, the model presumes that land developers sell the home or home site to the highest bidder at the mar- ket equilibriumâs highest price. Equilibration Results The market equilibrium for new home buyers (consider- ing 10% of the presently undeveloped land in Austin) was reached in an iterative fashion. The starting home value was assumed to be low, at just $100 per interior (built) square foot (or $25/ft2 of parcel land). Each house- hold was assumed to consider 20 randomly selected alter- native homes or home sites with specific sizes and accessibilities. IID Gumbel error terms were associated with each competing household and its set of considered alternatives. Knowing price and size, households were assumed to choose those offering the highest utilities as defined by the location choice model. Prices rose in steps of $1/ft2 when a home was desired by more than one household. When each household finally was aligned with a single, utility- maximizing home site, each occu- pied house was allocated to the household that tendered the highest bid. At this stage, the housing market (for new buyersâmovers) is said to have reached equilibrium. In this way, Austinâs single- family residential development was simulated for each of six scenarios: the three sets of VOTTs for a study area having either a single employ- ment center [the central business district (CBD)] or multi- ple employment centers (with each of 114 such centersâ housing at least 500 jobsâ located within the study area in Year 2000). Figure 2 illustrates the locations of these employment centers, the CBD, and the locations of the 18 shopping centers as well. The new householdsâ working members were assumed to be allocated job sites according to the scenario (i.e., either all worked at the CBD or at sites nearest to their chosen homes). In each simulation, the average equilibrium unit price for each (large or subdivided) parcel was computed by averaging the unit prices of the occupied pieces that were subdivided from the parcel, and average occupant income was calculated as the average annual income of house- holds that chose to reside on the parcel. Figure 3 plots the average equilibrium unit price against the distance to the CBD or to the nearest employment center, depending on the scenario setup. As expected, the resulting plots illumi- nated how undeveloped parcels located near employment sites enjoyed higher average equilibrium unit prices. When VOTTs were low, there was no clear relationship between the average equilibrium unit price and the distance or travel time to employment sites. As VOTTs increased, the 66 INNOVATIONS IN TRAVEL DEMAND MODELING, VOLUME 2 FIGURE 2 Locations of Austinâs employment centers, cen- tral business district, and shopping centers.