Did Dodd-Frank Make Getting a Mortgage Harder?

Christopher Dodd

Christopher Dodd

Barney Frank

 

 

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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.

Wednesday’s Academic Roundup

Mortgage Leverage and Bubbles

Albert Alex Zevelev has posted Regulating Mortgage Leverage: Fire Sales, Foreclosure Spirals and Pecuniary Externalities to SSRN. The abstract reads,

The US housing boom was accompanied by a rise in mortgage leverage. The subsequent bust was accompanied by a rise in foreclosure. This paper introduces a dynamic general equilibrium model to study how leverage and foreclosure affect house prices. The model shows how foreclosure sales, through their effect on housing supply, amplify and propagate house price drops. A calibration to match the bust shows consumption and housing need to be sufficiently complementary to fit the data. Since leverage plays a key role in foreclosure, a regulator can reduce systemic risk by placing a cap on leverage. Counterfactual experiments show that in a world with less leverage, the same economic shock leads to less foreclosure and less severe, shorter busts in house prices. A 90% cap on loan-to-value ratios in 2006 predicts house prices would have fallen 12% rather than 18% as in the data. The regulator faces a trade-off in that less leverage means less housing for constrained households, but also fewer foreclosures and less severe busts in house prices. A regulator with reasonable preference parameters would choose a cap of 95%.

This is pretty important stuff as it attempts to model the impact of different LTV ratios on prices and foreclosure rates. Now Zevelev is not the first to see these interactions, but it is important to  model how consumer finance regulation (for instance, loan to value ratios) can impact systemic risk. This is particularly important because many commentators downplay that relationship.

I am not in a position to evaluate the model in this paper, but its conclusion is certainly right: “Leverage makes our economy fragile by increasing the risk of default. It is clear that
foreclosure has many externalities and they are quantitatively significant. Since borrowers
and lenders do not fully internalize these externalities, there is a case for regulating mortgage leverage.” (31)