Tag Archives: Bing Bai

Understanding Homeownership

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The Housing Finance Policy Center at the Urban Institute released its House Finance at a Glance Chartbook for December. It states that financial education “can help reduce barriers to homeownership.” As I argue below, I do not think that financial education is the right thing to emphasize when trying to get people to enter the housing market.

The Introduction makes the case for financial education:

While mortgage debt has been stable to marginally increasing, other types of debt, particularly auto and student loan debt have increased far more rapidly. Our calculations, based on The Federal Reserve Bank of New York’s Quarterly Report on Household Debt and Credit, show that over the past 5 years (Q3 2012 to Q3 2017), mortgage debt outstanding has grown at an annualized rate of 1.3 percent, while non-mortgage debt (which includes credit card debt, student loan debt, auto debt, and other debt) has grown by 6.8 percent annualized rate. Student loan debt has grown by 7.3 percent per year while auto debt has been growing by 9.6 percent per year. In Q3 2012, the number of accounts for mortgage loans and auto loans are very close (84 million vs 82 million). By Q3 2017, the number of accounts for mortgages had fallen to 80 million consistent with declining homeownership rate, while the number of accounts for auto loans had increased to 110 million.

Another metric where auto loans have diverged from mortgages is delinquency rates. Over the past 5 years, mortgage delinquencies have plummeted (pages 22 and 29) while the percent of auto loans that is more than 90 days late is roughly flat despite an improving economy. However, the percent of auto loans transitioning into serious delinquency has risen from 1.52 percent in Q3 2012 to 2.36 percent in Q3 2017. While these numbers remain small, the growth bears monitoring.

When we looked at the distribution of credit scores for new auto origination and new mortgage origination, we found no major change in either loan category; while mortgage credit scores are skewed higher, the distribution of mortgage credit scores (page 17) and the distribution of auto credit scores have been roughly consistent over the period. Our calculations based off NY Fed data shows the percent of auto loan origination balances with FICOs under 660 was 35.9% in Q3, 2012, it is now 31.7%; similarly the percent of auto origination with balances under 620 has contracted from 22.7 percent to 19.6 percent. There have been absolutely more auto loans with low FICOs originated, but this is because of the increased overall volume.

So what might explain the differences in trends in the delinquency rate and loan growth between these two asset classes? A good part of the story (in addition to tight mortgage credit) is that many potential low- and moderate-income borrowers do not believe they can get a mortgage. As a result, many don’t even bother to apply. We showed in our recently released report on Barriers to Accessing Homeownership that survey after survey shows that borrowers think they need far bigger down payments than they actually do. And there are many down payment assistance programs available. Moreover, it is still less expensive at the national level to own than to rent. This suggests that many LMI borrowers who are shying away from applying for a mortgage could benefit from financial education; with a better grasp of down payment facts and assistance opportunities, many of these families could be motivated to apply for mortgages and have the opportunity to build wealth. (5)

I am not sure if financial education is the whole answer here. Employment instability as well as generalized financial insecurity may be playing a bigger role in home purchases than in car purchases. The longer time horizon as well as the more serious consequences of a default with homeownership may be keeping people from stepping into the housing market. This is particularly true if renters have visions in their heads of family members or friends suffering during the long and lingering foreclosure crisis.

Your Lender, The Federal Reserve Board

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photo by United States Federal Reserve

Federal Reserve Chair Yellen

Laurie Goodman and Bing Bai at the Urban Institute have posted Normalizing the Federal Reserve’s Balance Sheet The Impact on the Mortgage-Backed Securities Market. It is quite extraordinary to realize that the Federal Reserve owns nearly a third of outstanding residential mortgage-backed securities. When we think about the appropriate role of the government in the housing finance market, we cannot forget about this type of involvement. The paper opens,

During the crisis, the Federal Reserve found the traditional tools for monetary policy insufficient to stimulate the economy. From December 2008 to December 2015, the Fed’s primary policy tool, the target Fed funds rate, was set between 0 and 0.25 percent. But the economy remained weak, and there was no room to cut rates further. As a result, the Fed began to purchase large quantities of assets from the private sector. These programs are referred to as quantitative easing or large-scale asset purchases. The Fed owned $1.77 trillion of agency mortgage-backed securities (MBS) and $2.45 trillion of US Treasury securities (Treasuries) in late September 2017 and began to reduce the amount of these portfolio holdings in October 2017.

Some background: Since the Great Recession, the Fed has done three rounds of quantitative easing. From November 2008 to March 2010, it purchased $1.75 trillion in long-term Treasuries, Fannie Mae and Freddie Mac agency debentures, and agency mortgage-back securities (comprising Ginnie Mae, Fannie Mae, and Freddie Mac issuances). From November 2010 to June 2011, the Fed purchased an additional $600 billion of Treasuries. From September 2012 to September 2014, the Fed engaged in its third round of quantitative easing, initially purchasing $85 billion a month in Treasuries and agency debt and MBS, with $40 billion of agency MBS. The Fed began to taper its purchases in December 2013 and ended the program in October 2014. From October 2014 through September 2017, the Fed has reinvested its runoff. Through these actions, the Fed owned $1.77 trillion of agency MBS, nearly 29 percent of all outstanding MBS as of late September 2017.

The Federal Open Market Committee announced on September 20, 2017, that it would begin to normalize its balance sheet in October 2017. The committee has been transparent about the course. It will begin by reducing the reinvestment rates on its portfolio. In months 1 through 3, the Fed would let the System Open Market Account (SOMA) portfolio run off by $10 billion each month, increasing to $20 billion in months 4 through 6, $30 billion in months 6 through 9, $40 billion in months 10 through 12, and $50 billion a month thereafter. The maximum runoff in each month, if met, would comprise 60 percent Treasuries and 40 percent MBS. If there is not enough runoff in that month, the Fed will not sell to meet these targets.

Although this timetable is clear, additional questions arise about the MBS portfolio that the Fed should shed some light on. The largest questions include the following: What size and mix of assets does the Fed eventually want to hold? And how does it intend to get there? In this brief, we argue that this is not an academic exercise. When the Fed reaches its desired balance sheet size, it will hold approximately $1.18 trillion in mortgage assets. It will take a long time for these to run off if there is no selling. This may be fine, but the Fed has made several comments that indicate it could sell the “residual.” For example, the minutes of the September 2014 meeting includes the following statement:

The Committee currently does not anticipate selling agency mortgage-backed securities as part of the normalization process, although limited sales might be warranted in the longer run to reduce or eliminate residual holdings. The timing and pace of any sales would be communicated to the public in advance.

It is not at all clear what constitutes a “residual.”

This brief has four sections. The first shows that under assumptions reasonably close to what the Fed has used, there will still be close to $1.18 trillion of MBS on its books when the Fed balance sheet normalizes. We then review the arguments about the Fed’s long-term desired portfolio mix. If it is Treasuries only, this raises questions about whether and how quickly the Fed should change its mortgage and treasury mix to avoid making asset allocation decisions that distort financial markets. In the third section, we argue that the Fed should do some active portfolio management while they are still doing a small amount of reinvestment. Finally, we make the case that the Fed could play a costless and helpful role in launching the single government-sponsored enterprise (GSE) security. (1-2)

The paper raises some important policy questions:

There has been considerable discussion on what role mortgages should play in the Fed’s portfolio. There is general but not universal agreement that the Fed should not be in the asset allocation business over the long term because it distorts financial market prices. Lawrence White has stated that “government programs that divert credit away from the most productive uses, as evaluated by the marketplace, are inherently wasteful, even if policymakers have the best of intentions.” Charles Plosser, a former president of the Federal Reserve Bank of Philadelphia, sees additional dangers, noting that holding securities other than Treasuries opens the door for Congress (or the Fed) to use the balance sheet for political purposes. The Fed’s balance sheet could be “a huge intermediary and supplier of taxpayer subsidies to selected parties through credit allocation.” For example, if there was an infrastructure bill, the funds could be used to purchase the bonds that support the infrastructure initiative. Similarly, the funds could be used to purchase bonds to keep a municipality from defaulting. (9, citations omitted)

The Fed should address these policy questions head on, before any unintended consequences of such a dramatic policy intervention make themselves known.

Women Are Better Than Men,

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photo by Matt Neale

Greeks vs Amazons, Mausoleum of Halicarnassus, British Museum

at least at paying their mortgages. This is according to an Urban Institute research report that found that

It’s a fact: women on average pay more for mortgages. We are not the first people to have noticed this; a small number of other studies have also pointed it out (e.g., Cheng, Lin, and Liu 2011). One possible explanation is that women, particularly minority women, experience higher rates of subprime lending than their male peers (Fishbein and Woodall 2006; Phillips 2012; Wyly and Ponder 2011). Another explanation is that women tend to have weaker credit profiles (Van Rensselaer et al. 2013). We find that both these explanations are true and largely account for the higher rates.

Looking at loan performance for the first time by gender, however, we find that these weaker credit profiles do not translate neatly into weaker performance. In fact, when credit characteristics are held constant, women actually perform better than men. Nonetheless, since pricing is tied to credit characteristics not performance, women actually pay more relative to their actual risk than do men. Ironically, despite their better performance, women are more likely to be denied a mortgage than men. Given that more than one-third of female only borrowers are minorities and almost half of them live in low-income communities, we need to develop more robust and accurate measures of risk to ensure that we aren’t denying mortgages to women who are fully able to make good on their payments. (1)

This second paragraph undercuts the catchy title of the report, Women Are Better than Men at Paying Their Mortgage, because it is only true when comparing single women to single men and when credit characteristics are held constant.

The report confines its analysis to sole female and sole male borrowers, excluding two-borrower households. This limitation is compounded by the fact that the credit characteristics of men and women are not the same (as men have better credit characteristics as a group).  As a result of these limitations, I think the title of the report goes too far. The authors also acknowledge that the stakes are not that high because the “inequality does not translate into a significant amount that single women overpay for their mortgages: less than $150 per female-only borrower per loan.” (15)

That point aside, the report does raise an important issue about whether credit characteristics metrics are biased against women: “the dimensions we rely on to assess credit risk today do not adequately capture all the differences. This omission has real consequences.” (15) This is certainly true, but lenders will have to carefully navigate fair lending laws as they seek to capture all of those differences.

Did Dodd-Frank Make Getting a Mortgage Harder?

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Christopher Dodd

Christopher Dodd

Barney Frank

 

 

____________________________________________________________

The short answer is — No. The longer answer is — No, but . . .

Bing Bai, Laurie Goodman and Ellen Seidman of the Urban Institute’s Housing Finance Policy Center have posted Has the QM Rule Made it Harder to Get a Mortgage? The QM rule was originally authorized by Dodd-Frank and was implemented in January of 2014, more than two years ago. The paper opens,

the qualified mortgage (QM) rule was designed to prevent borrowers from acquiring loans they cannot afford and to protect lenders from potential borrower litigation. Many worry that the rule has contributed to the well-documented reduction in mortgage credit availability, which has hit low-income and minority borrowers the hardest. To explore this concern, we recently updated our August 2014 analysis of the impact of the QM rule. Our analysis of the rule at the two-year mark again finds it has had little impact on the availability of mortgage credit. Though the share of mortgages under $100,000 has decreased, this change can be largely attributed to the sharp rise in home prices. (1, footnotes omitted)

The paper looks at “four potential indicators of the QM rule’s impact:”

  1.  Fewer interest-only and prepayment penalty loans: The QM rule disqualifies loans that are interest-only (IO) or have a prepayment penalty (PP), so a reduction in these loans might show QM impact.
  2. Fewer loans with debt-to-income ratios above 43 percent: The QM rule disqualifies loans with a debt-to-income (DTI) ratio above 43 percent, so a reduction in loans with DTIs above 43 percent might show QM impact.
  3. Reduced adjustable-rate mortgage share: The QM rule requires that an adjustable-rate mortgage (ARM) be underwritten to the maximum interest rate that could be charged during the loan’s first five years. Generally, this restriction should deter lenders, so a reduction in the ARM share might show QM impact.
  4. Fewer small loans: The QM rule’s 3 percent limit on points and fees could discourage lenders from making smaller loans, so a reduction in smaller loans might show QM impact. (1-2)

The authors find no impact on on interest only loans or prepayment penalty loans; loans with debt-to-income ratios greater than 43 percent; or adjustable rate mortgages.

While these findings seem to make sense, it is important to note that the report uses 2013 as its baseline for mortgage market conditions. The report does acknowledge that credit availability was tight in 2013, but it implies that 2013 is the appropriate baseline from which to evaluate the QM rule. I am not so sure that this right — I would love to see some modeling that shows the impact of the QM rule under various credit availability scenarios, not just the particularly tight credit box of 2013.

To be clear, I agree with the paper’s policy takeaway — the QM rule can help prevent “risky lending practices that could cause another downturn.” (8) But we should be making these policy decisions with the best possible information.