Dodd-Frank: Can we really calculate the cost?
American Banker recently called for a data-driven analysis of the economic impacts of the Dodd-Frank Act and related regulations. We welcome the call for an empirical assessment of regulatory impact. At the same time, we caution against the belief that a single number or set of numbers can quantify the impact of a complicated law on a complex system.
Since the Housing Finance Policy Center’s inception last October, we’ve made it our primary focus to dive deeply into the data to better understand the interplay of market forces, regulations, laws and other factors. To note a few recent examples:
- We’ve explored the number of “missing mortgages”-- loans that would have been made in 2012 if credit was as available as it was in 2001.
- We’ve written about the local impact of changes in FHA loan limits, and the likely effect of HAMP resets.
- And we’re carefully following all the data we can get our hands on to understand the impact of the Qualified Mortgage rule (QM).
This work has reminded us that assessing impact is extremely difficult, turning on a mix of factors that is often hard, indeed occasionally impossible, to disentangle.
Take all those missing loans, for example. Our work indicates that they are the result of a mix of factors that are difficult to isolate, including the overcorrection of institutions understandably nervous about risk coming out of the crisis and a similar overcorrection by agencies trying to recover the losses they suffered from bad underwriting and to protect against similar practices going forward. How much of it is one, how much the other, how much something else entirely? It’s literally impossible to say.
Interestingly, though, the two factors most commonly blamed, Dodd-Frank and Basel III, cannot be responsible for the 2012 results, which predate implementation of both.
And what about QM, where the impact of Dodd-Frank should be clear? So far, we have not found any impact at all. Part of this may be limited access to data (at least until the 2014 Home Mortgage Disclosure Act data comes out in late 2015) about loans made by smaller lenders and held in portfolio. And of course, it’s always hard to prove why something isn’t happening.
But we suspect that the real reason we can’t see QM impact may be that the current credit box is already extremely tight. So tight that the QM rules are not making it any tighter. A major challenge in figuring out the ultimate impact of QM will be to make some judgment about what the credit box “should” have looked like in January 2014, before the rules took effect. We’ll try, but we’re sure our answer will only be one of many.
The positive impact of some regulations shouldn’t be overlooked either. Last week, we published our analysis of FHA and VA lending, demonstrating that additional regulation applicable to VA loans—the residual income test— was the most likely cause of VA lending consistently performing better than FHA lending, notwithstanding VA loans’ higher LTVs and lower credit scores.
So how does one measure the positive impact of rules like those in Dodd-Frank against whatever costs are found, particularly where the positive impacts are likely years out and potentially even more difficult to quantify than the costs? Indeed, how do you assess the positive impact that Dodd-Frank rules will have on increased financial stability and consumer safety in a system whose collapse recently cost the world’s economy trillions of dollars?
While we applaud the call for more and better analysis, we recommend humility in the face of complexity and perhaps a healthy dose of skepticism, especially about results in the form “the regulations cost consumers—or businesses—‘X’ dollars a year.” As the problems these rules are intended to address don’t lend themselves to simple solutions, the rules’ impact on our complex economy is not likely to be easy to discern.
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Photo: Chris Dodd and Barney Frank during the Dodd-Frank during the Dodd-Frank Wall Street Reform and Consumer Protection signing ceremony. (AP Photo/Charles Dharapak, File)