In line with other studies (Quercia, McCarthy, and Wachter 2003), we measure mortgage consumption in two ways: (1) as the dollar amount of the monthly mortgage payment, and (2) as the ratio of the monthly mortgage payment to monthly household income, referred to here as the front-end ratio. The monthly mortgage payment is derived from administrative data at the time of origination, and includes principal, interest, taxes, insurance, and private mortgage insurance.
As shown in Table 2, the average mortgage payment for borrowers in our sample is $815, based on an average purchase price of $102,007, with a resulting average front-end ratio of 22.6% (ranging from 7.7% to 51.6%).
To explore the relationship between perceived and actual borrowing capacity and mortgage debt, we first estimate a series of OLS models with the full monthly mortgage payment as the dependent variable (Table 4, columns 1 and 2), and then the front-end ratio as the dependent variable (Table 4, columns 3 and 4).
First, as would be expected, an increase in monthly DTI is significantly associated with a decrease in mortgage payment and the front-end ratio across all specifications, highlighting the importance of nonmortgage borrowing capacity for mortgage consumption.
While both of these studies analyzed the correlation between the back-end ratio and default risk, an analysis of 179 FHA loans originated in Utah between 2000 and 2001 estimated the impact of a borrower's front-end ratio as well.
(93.) The mean back-end ratio is 38.53 with a standard deviation of .07, whereas the mean front-end ratio is 29.42 with a standard deviation of 7.25.