Abstract
Hedonic pricing, estimating the value of housing characteristics through the use of transactions data, is one of the most common tasks performed by real estate researchers. However, transaction frequency varies over time, locations, and other factors. In contrast, two-thirds of homeowners have mortgages that they pay each month. This manuscript explores the use of mortgage payment data as an alternative or supplemental means to derive the value of housing characteristics. Insofar as price affects default and housing characteristic values determine price, housing characteristic values affect default. The implicit housing characteristic values come from parameter values that fit observed patterns of payments and defaults. We find a strong correlation (0.74−0.92) between the transaction-based and the implicit approaches. In addition, the Monte Carlo simulation indicates that the mortgage based pricing model has potential to help reveal housing market information especially during low sales activity and/or high default rate situations.
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