Housing Market Segmentation: A Finite Mixture Approach

This paper investigates the usefulness of adding a discrete choice model to the hedonic model via a finite mixture approach. Our approach leads to different hedonic models for different housing market segments based on household information. As such, the proposed method goes beyond measuring the average price of housing attributes. As a case study, we estimate the finite mixture model for the Miami and Louisville metropolitan areas using information on race, ethnicity, and income from the American Housing Survey. We find that the model outperforms the standard hedonic model or a model with linear interaction terms between demographics and housing characteristics. Moreover, market segmentation is based on a complex combination of race, ethnicity, and income. For Louisville, Black households need 2.5 times higher income than White households to advance to a higher market segment and even at high incomes tend to occupy their own segment. For Miami, low-income, non-Hispanic households live in their own segment even if occupying the same dwelling size as households in other segments.