This paper developed a two-stage modeling framework for analyzing residential and work location choices with probabilistic choice sets. In the first stage, a household (or a worker) was assumed to select a neighborhood (such as central business district, urban, suburban etc.) to live (or work). In the second stage, the household (or worker) was assumed to choose a specific zone conditional on the selected neighborhood. The neighborhood choice model component takes the form of Manski model with latent choice sets. The model was used to analyze residential and work location decisions in Nashville, Tennessee. The model results indicate significant heterogeneity in the consideration probability of different neighborhood alternatives both in the residential and work location choices. The latent class neighborhood models were found to outperform standard MNL models that assume all decision-makers consider the universal choice set in their decision-making.
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