Discrete choice models can be applied to predict the location decisions of households and firms as a result of a change in an area’s transportation system. Such models can predict the probability that a given household would move to a different residential location, on the basis of household characteristics such as age of household head, presence of children, number of workers, housing tenure, and ratio of housing costs to income, and the physical and social characteristics of a community. Similarly, employment relocation choice can be predicted using a discrete choice framework, as a
function of business characteristics (such as industry size), characteristics of potential zones for land-use development (such as accessibility, density, and employment levels),and characteristics of vacant land (quantity and cost). Levine (1998) employed discrete choice modeling to assess the relationship between residences and jobs. A limitation of this approach is that individual-level data that are required can generally be obtained only through surveys
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