Recursion is teaming up with Lincoln Institute of Land Policy and Rice University to work on the Underserved Mortgage Markets Coalition project and the Social Policy Analysis Capstone Course (“SOPA”). 

It’s always interesting to look at the underlying dynamics within the mortgage market to get a deeper handle on the forces behind recent trends and to gain insights into the market impact of policy changes. This time we will look at a breakdown of the market between the cash window and swaps. Simply, in a swaps transaction the lender sends loans to one of the Enterprises, Fannie Mae or Freddie Mac, and in return obtains a security which it can keep as an investment (mostly in the case of banks) or else sell into the market (both banks and nonbanks). The alternative is to sell the loans directly to the Agencies for cash. This is important to nonbanks in particular as this cash is used as a funding source for running their businesses.
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As it turns out, neither GSE reports the path by which a loan is obtained in their loan-level disclosures. However, in the case of Freddie Mac, cash loans are placed in their own pools with distinct prefixes.  As a result we can unpack these pools and perform a matching exercise with the loan tape and assign these accordingly. This allows us to perform queries on this characteristic across our loan-level querying tool Cohort Analyzer. Below find the share of deliveries made to Freddie Mac from the Cash Window by loan purpose.

​The recent unprecedented surge in home prices to a record 18% jump on a year-year basis as measured by the FHFA purchase-only index brings affordability front and center to the current housing policy debates. In May 2021, indexed home prices stood 15.5% above indexed aggregate earned income, a bit less than half of the peak house price overvaluation of 29.0% reached in December 2005, just before the onset of the Global Financial Crisis.

The topic of affordability is very broad, and will be the subject of much further commentary, but in this post we look briefly at this topic through the distribution of the purchase mortgage market across securitization agencies, notably FHA and the GSE’s.

Looking at the distribution between the GSEs and FHA is informative in this issue because the FHA program is aimed at low-income borrowers. According to 2020 HMDA data, the weighted average household income for FHA borrowers of purchase mortgages was $85K while for those in conforming mortgages the figure was $228K.
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Since the onset of the Covid-19 pandemic in early 2020, the share of FHA purchase mortgages of the total[1] delivered to agency pools as been in general decline, on both a loan count and outstanding balance basis:

​With a base consisting of relatively lower-income borrowers, it makes sense that the borrowers in this program are struggling to qualify for loans in a skyrocketing market. To check this out, we calculate the change in the distribution of loans between FHA and the GSE programs by original loan sizes:

Intuitively, larger loans comprise a greater share of the distribution of purchase loans in both programs between January 2020 and July 2021.
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Over this period, FHA lost a bit over 5% in market share to the GSE’s in this category. The change in share by loan size bucket and the contribution of each of these to the total loss in share is given below:

​In fact, it turns out that about three quarters of the loss in FHA’s purchase market share comes from losses in loan sizes less than $250,000. Further analysis is needed to look at the fundamental and structural factors that are behind this result.

The new FHFA Acting Director Sandra Thompson has lost no time in implementing new policies designed to support homeownership with the aim of creating greater wealth equality. This is the basis of the New Housing Policy we described in a recent post[1]. At first, this involved extending foreclosure moratoriums for distressed families until the end of the year[2]. Then recently, the GSE regulator announced a change in its modification policy to broaden the eligibility for rate mods to any qualifying household that were previously only available to those with a mortgage greater than or equal to 80% of the current home valuation (Current LTV>=80)[3]. This program is designed to allow as many credit-worthy borrowers to stay in their homes as possible.
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The LTV limit is significant because the surge in house prices we have witnessed over the past year has meant that a relatively small share of loans should have Current LTVs greater than or equal to 80. Our loan-level data set allows us to examine this question by looking at over 25 million GSE loans. Below finds a snapshot of the total combined June books of the GSEs broken down in this manner:

​Once again, we look at the release of house price data with a sense of shock:

Recently, the Federal Reserve released its May 2021 Financial Stability Report[1], with a particular emphasis on asset valuations. Valuations are raised as a concern as “Prices of risky assets have generally increased since November with improving fundamentals, and, in some markets, prices are high compared with expected cash flows”. While not cited as a matter of high alarm the report commented that “House price growth continued to increase, and valuations appear high relative to history.”
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On May 25, FHFA released the purchase-only house price index for March, showing a record-high growth rate of 13.9%, far above the bubble-era peak of 10.7% attained in 2005[2]. Housing fundamentals are of course supportive with mortgage rates below 3% and economic activity rebounding as vaccine optimism spreads. The unique factor now in housing is the impact of the pandemic on preferences for housing away from density and towards suburban and smaller-urban centers. This new fundamental can easily be seen via booming housing demand during the pandemic as measured here by purchase mortgage deliveries to Freddie Mac[3].

On January 19, the Federal Housing Finance Agency (FHFA) issued a Request for Information (RFI) on “Climate and Natural Disaster Risk Management at the Regulated Entities”[1]. This RFI was issued as “A growing body of research is studying the risks that climate change and natural disasters pose to the stability of the economy, the financial system, the national housing finance markets, and FHFA’s regulated entities.” There are two main policy topics in which FHFA is seeking comment:

  1. Identifying and Assessing Climate and Natural Disaster Risk

• This includes the identification of “methodologies, datasets, variables, assumptions, future climate scenarios, and measurement tools are used to measure and monitor climate risk to the national housing finance markets”.​

  2. Enhancing FHFA’s Supervisory and Regulatory Framework

• This includes the question “Are there policies the regulated entities could pursue to mitigate such adverse effects for minority borrowers exposed to climate and natural disaster risk?”

Recursion joined with a consortium of experts in this field, including the Lincoln Institute of Land Policy, the Roosevelt Institute, the Carbon-Free Buildings Program and the Vulnerable Communities Initiative Inc that submitted a comment letter to FHFA Director Calabria on April 19[2].

This letter spelled out a statement of principles that reflect Recursion’s mission of building “Data Democracy”, including:

• Decision making must be data-driven. High-quality data is a prerequisite for any accurate analysis, projection, and decision. This includes not only quantitative statistics but also qualitative data, such as case studies, interviews and lessons learned that capture the meaning and context of information.
• Make data free, transparent, and accessible. Government, Enterprise and FHLBank-produced data are public goods and they create maximized economic benefits when they are open. Equal access to high-quality climate-risk data helps level the playing field for the average consumer and local communities to make better decisions. Determine the specifications for disclosures of loan-level mortgage data (e.g. geography, demographics, underwriting) needed to align with climate-risk data to ensure that the information needed to accomplish climate policy goals is available. Researchers can provide valuable feedback to help maintain the dataset’s quality and improve government’s data management practices.

We are pleased to work with such distinguished colleagues on this important topic.

​Recursion Co recently provided commentary in response to a Request for Information (RFI) regarding appraisal policies, practices, and processes. We comment on how big data technology can be applied to monitor the performance of loans where appraisals have been waived compared to a benchmark of eligible loans where traditional appraisals have been utilized. In addition, we provide a framework for analyzing how these tools can address issues such as the impact of new processes on fairness and the safety and soundness of the system of mortgage finance from such topics as environmental vulnerability.