Showing results 1 to 9 of approximately 9.(refine search)
Liquidity Crises in the Mortgage Market
Non-banks originated about half of all mortgages in 2016, and 75% of mortgages insured by the FHA or VA. Both shares are much higher than those observed at any point in the 2000s. We describe in this paper how non-bank mortgage companies are vulnerable to liquidity pressures in both their loan origination and servicing activities, and we document that this sector in aggregate appears to have minimal resources to bring to bear in a stress scenario. We show how the same liquidity issues unfolded during the financial crisis, leading to the failure of many non-bank companies, requests for ...
Equity extraction and mortgage default
Using a property-level data set of houses in Los Angeles County, I estimate that 30% of the recent surge in mortgage defaults is attributable to early home-buyers who would not have defaulted had they not borrowed against the rising value of their homes during the boom. I develop and estimate a structural model capable of explaining the patterns of both equity extraction and default observed among this group of homeowners. In the model, most of these defaults are attributable to the high loan-to-value ratios generated by this additional borrowing combined with the expectation that house ...
Stress Testing Household Debt
We estimate a county-level model of household delinquency and use it to conduct "stress tests" of household debt. Applying house price and unemployment rate shocks from Comprehensive Capital Analysis Review (CCAR) stress tests, we find that forecasted delinquency rates for the recent stock of debt are moderately lower than for the stock of debt before the 2007-09 financial crisis, given the same set of shocks. This decline in expected delinquency rates under stress reflects an improvement in debt-to-income ratios and an increase in the share of debt held by borrowers with relatively high ...
Search, Matching and Training
We estimate a partial and general equilibrium search model in which firms and workers choose how much time to invest in both general and match-specific human capital. To help identify the model parameters, we use NLSY data on worker training and we match moments that relate the incidence and timing of observed training episodes to outcomes such as wage growth and job-to-job transitions. We use our model to offer a novel interpretation of standard Mincer wage regressions in terms of search frictions and returns to training. Finally, we show how a minimum wage can reduce training opportunities ...
The Effects of Mortgage Credit Availability : Evidence from Minimum Credit Score Lending Rules
Since the housing bust and financial crisis, mortgage lenders have introduced progressively higher minimum thresholds for acceptable credit scores. Using loan-level data, we document the introduction of these thresholds, as well as their effects on the distribution of newly originated mortgages. We then use the timing and nonlinearity of these supply-side changes to credibly identify their short- and medium-run effects on various individual outcomes. Using a large panel of consumer credit data, we show that the credit score thresholds have very large negative effects on borrowing in the short ...
The Decline in Lending to Lower-Income Borrowers by the Biggest Banks
Data collected under the Home Mortgage Disclosure Act (HMDA) reveal that the largest banks have significantly reduced their share of mortgage lending to low- and moderate-income (LMI) households in recent years.
Residential Mortgage Lending in 2016: Evidence from the Home Mortgage Disclosure Act Data
This article provides an overview of the 2016 data reported under the Home Mortgage Disclosure Act of 1975 and analyzes mortgage market activity over time as well as lending patterns across different demographic groups and lender types. The number of home-purchase originations was about 10 percent higher in 2016 than in 2015, and the number of refinance loans was 16 percent higher. The increase in lending was broad based across demographic and income categories.
Using Data on Seller Behavior to Forecast Short-run House Price Changes
We construct a new "list-price index" that accurately reveals trends in house prices several months before existing sales price indices like Case-Shiller. Our index is based on the repeat-sales approach but for recent months uses listings data, which are available essentially in real time, instead of transactions data, which become available with signiffcant lags. Our index methodology is motivated by a simple model of the home-selling problem that shows how listings variables such as the list price and marketing time help predict the final sales price. In a sample of three large MSAs over ...
Are Rising Home Values Restraining Homebuying for Lower-Income Families?
Since bottoming out in 2012, house prices in the U.S. have recovered rapidly. According to Zillow, the median home value has been growing about 6 percent per year. While incomes have also been recovering, they have not quite kept pace with home prices. This note uses data reported under the Home Mortgage Disclosure Act (HMDA), along with income data from the ACS, and house price data from Zillow, to explore whether families in such areas, particularly lower-income families, are being priced out of homeownership as a result.