Financial support for rural communities has been a feature of US economic policy since the Farm Credit System was established as the first GSE in 1916, sixteen years before the Federal Home Loan Banks were established in 1932. This support continues to this day and has expanded to encompass additional programs.
Ginnie Mae Program
While the best-known collateral for Ginnie Mae securities is loans underwritten through the FHA and VA programs, another form is loans underwritten by the US Department of Agriculture Rural Development (RD) Program, launched in 1990 as part of the Farm Bill passed that year. The Single-Family Direct Home Loan Program in particular is designed to provide payment assistance to low- and very-low-income households in rural communities. Of course, FHA and VA provide loans in rural areas under the terms of their programs as well.
GSE Rural Lending
Single-family lending at Fannie Mae and Freddie Mac was handed a mandate to provide liquidity to rural communities through the adoption of the Duty-to-Serve provision of the HERA Act enacted in 2008. This program requires the GSE’s to engage in activities to facilitate liquidity in three underserved markets:
A key feature of this regulation is that FHFA has provided new datasets and tools to enhance the analysis of these markets. In particular,
FHFA's Duty to Serve regulation defines "rural area" as: (1) a census tract outside of a metropolitan statistical area, as designated by the Office of Management and Budget; or (2) a census tract in a metropolitan statistical area, as designated by the Office of Management and Budget, that is outside of the metropolitan statistical area's Urbanized Areas as designated by the U.S. Department of Agriculture's Rural-Urban Commuting Area Code #1, and outside of tracts with a housing density of over 64 housing units per square mile for USDA's RUCA Code #2. Below is a link to the specific geographies which meet the Rural Areas definition.
Using this segmentation, we are now in a position to load their definition into our databases and look at trends in this market segment. Using HMDA data as a base, we produce the following chart:
In a recent post we looked at the evolution of the FHA purchase mortgage market share broken down between areas with a high percentage of Low-Moderate Income (LMI) households and those without. While the overall FHA share has generally declined since the onset of the pandemic, its share has held up in areas with a preponderance of LMI households. There are many factors behind these trends, but a natural consideration is underwriting standards.
To examine this factor, we use the Recursion Matched Dataset, where we create a large sample of loans with characteristics from both HMDA and the Agency disclosure data. A very high share of mortgages can be matched using our proprietary algorithm over the years 2018-2020. The coverage ratio from the Matched Dataset is provided in a previous post.
We proceed by looking at three major underwriting characteristics for LMI and non-LMI areas for FHA and the GSE’s: Credit Score (CS), Loan-to-Value (LTV) and Debt-to-Income (DTI),
Most interesting is Credit Scores:
One of the many recurring themes of these posts is that the shock of the Covid-19 Pandemic and subsequent policy response has resulted in structural changes in behavior that cause loan performance metrics to shift compared to the pre-crisis world. An interesting example of this can be found in the performance of modified loans in Ginnie Mae programs.
Modified loans in these programs are those that have been purchased out of pools by servicers that are past due that subsequently have features such as rate and term adjusted in order to bring households back to a current status. These are then often resecuritized into a new GNM pool.
In a previous post, we mentioned the Recursion Matched data set, which uses a proprietary algorithm to match the loans provided in the monthly Agency loan tapes, with HMDA data. This allows for a broad analysis of loan performance (delinquency and prepayment rates) in terms of both underwriting standards (credit score, DTI, LTV) with demographic and household economic characteristics (income, race, gender, etc). We are always working to improve our algorithm, below find the match rates for Ginnie Mae loans over the 2013-2020 period. HMDA has released more characteristics in recent years, allowing for a greater matching rate.
The economic news in March got off on a strong note with the release of payroll employment data showing a hike of 916,000, a seven-month high. This coincided with the first anniversary of the onset of the Covid-19 Pandemic. The Cares Act forbearance program was launched at the end of March 2020 and was originally designed to last for one year. More recently, the program was extended for six months, but borrowers need to recertify their status as economically impacted by Covid every three months from the 1-year anniversary data.
So naturally the end of March was a time in which many borrowers had to recertify. This was a natural time for households to reassess their financial positions, setting the stage for the possibility that they could begin repaying their mortgage obligations. In fact, they did, and we saw a sizable drop in the number of loans in Covid-related forbearance in April, particularly for Ginnie Mae programs:
The economic fundamental driving this decline is the improvement in the labor market, and a distinct correlation can be seen between declining forbearances and unemployment:
A bit more analysis is in order here. The forbearance data come from loans in agency pools, so there is always the possibility that the number of loans in forbearance decreases because some of those loans were bought out of pools by servicers. To check this, we looked at the disposition of loans in forbearance at the beginning of March that remained in pools at the beginning of April but were not in forbearance. For FHA programs the number was 111,153 loans compared to the one-month decline in the number of loans in forbearance of 125,202. For VA the similar statistic is 27,247 compared with a 26,810 decline in the number of loans in forbearance. It seems clear that improving labor market fundamentals are the primary driver of the decline in the number of loans in forbearance in these programs.
To test the idea that the 12-month renewal period played an important role in this process, below we look at the loan age of those mortgages that left forbearance but stayed in pools in April. For FHA programs, the number with loan age of one month was 79,212 or 71% of the total, while for VA it was 17,863 or 66%. The next important date will be June before the program is scheduled to end at the end of September.
As can be seen from the above table, the vast majority of the number of loans that were recorded as in forbearance in March but not in April did not exit due to buyouts. The data do not precisely add up because other outcomes are possible, including FHA – conventional refis or sales of homes, for which we have no tracking mechanism. But the close match between cures and the declines in forbearance across programs is evidence that the main impetus is improving fundamentals.
 In this blog, we only analyze Covid-related forbearance
On March 30, FHA released its Quarterly Report to Congress on FHA Single-Family Mutual Mortgage Insurance Fund Programs for Q4 2020. The report shows that the MMI fund grew to $82.3 billion from $79.9 billion the prior quarter. However, the year-to-date actual net loss rate on claim activity of 35.2% is higher than the projection of 30.1% percent, as the portfolio-level serious delinquency rate increased in the quarter to 11.9%, from 11.6% percent last quarter. Consequently, Secretary Fudge in a statement indicated stated that “Given the current FHA delinquency crisis and our duty to manage risks and the overall health of the fund, we have no near-term plans to change FHA’s mortgage insurance premium pricing.”
As we have noted previously, the Covid-19 crisis is very distinct from the Global Financial Crisis (GFC) insofar as while both periods experienced high delinquency rates, house prices now are soaring as opposed to collapsing in the earlier crisis.
We have commented previously about housing and the “K-shaped Recovery” in which home prices are booming but rent increases are decelerating. This dichotomy is highly unusual but reflects the flight of households out of dense urban environments due to the Covid-19 pandemic. With rents decelerating, it is not surprising that starts of new multifamily units have been in a trend decline over the past year.