Across the country, one of the main reasons commuter trip lengths are increasing and trafficconditions are deteriorating is because people do not, or cannot, live near their jobs. Thephysical distance between the location of jobs and appropriate housing can be significant. Oftenthe only feasible alternative for workers who cannot work from home is to commute by car totheir job location. Congested freeways and rush hours provide ample evidence of this spatialseparation. When jobs and housing are located in close proximity, the need for long commutesmay be reduced.This study uses journey-to-work data from metropolitan census tracts across the countryto investigate whether people’s choices to live and work in an area is related to the presence ofjobs, or whether it is related to the type of job. Ordinary least squares regression is used togenerate a model that relates the number of people who live and work in the same area to theearned wages of resident and nonresident workers, as well as the number of resident workers tonon-resident workers. The results indicate that more people who live and work in the same areaif there is a balance between earned wages of resident and non-resident workers. This model fitsthe data better than previously published models that relate travel outcomes to jobs and housing.Since metropolitan census tracts from across the nation were used, the models derived from thisresearch should be widely generalizable. This research provides planners the capability topredict how employment and housing affect whether people can live and work in the same area.
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