Abstract
Most tenure choice models using cross-sectional data have used either a sample of recent movers or a sample comprising all households. There are problems with estimating both types of models in cross-sectional data. A sample of recent movers oversamples renters, and a sample of all households will yield estimates based on household decisions made in the past. This research designs a method to correct for sample selection in a sample of recent movers. There are large differences in the importance of age, immigrant status, and immigrant length of stay as predictors of homeownership. At the same time, income effects are similar across models.
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