Friday Links – 03 April 2009

It’s been a while since I’ve done a “links”post, but there are a few stories of particular interest this week.

Daniel Nairn visually shows one hundred years of growth in Charlottesville/Albemarle.

Charlottesville Tomorrow says that a Crozet-Charlottesville commuter train may be viable. And … people may be willing to pay (a little bit) for it.

Dave Mcnair with the Hook shows that you just can’t compete against the government without retribution. Sometimes, government just can’t do things as well as the private sector – their processes and motives often aren’t aligned with reality.

If you haven’t caught any of Charlottesville’s Design Week, you’ve missed out.

VARBuzz points to a new NY Fed study that demonstrates out that reverse redlining may be a sham (remember this story from last year?)

This is important: whatever you know or don’t know about research, the garbage-in, garbage-out mantra applies here moreso than almost any other endeavor. And I’ve long been bothered by the notion that the analysis of HMDA data lacked any insight into the borrower’s credit risk profile.

All of which makes the findings of this study, which looked at more than 70,000 subprime 2/28s originated in 2005, an absolute barn-burner for anyone in the mortgage space:

In contrast to previous findings, our results show that if anything, minority borrwers get slightly favorable terms, although the size of these effects are quite small. Black and Hispanic borrowers pay very slightly lower initial mortgage rates than other borrowers — about 2.5 basis points (0.0025 percent) compared with a mean initial mortgage rate of 7.3 percent. Black and Hispanic borrowers also have slightly lower margins (about 1.7 to 5 basis points, or 0.0017 to 0.005 percent) compared to a mean margin of 5.9 percent. Asian borrowers pay slightly higher initial rates and reset margins (about 3 basis points). We find no appreciable differences in lending terms by the gender of the borrower. These results control for the mortgage risk characteristics and neighborhood composition. While many of these differences are statistically significant, they are economically insignificant.

A second important finding is that 2/28 mortgages were cheaper in Zip Codes with a higher percentage of Asian, black and Hispanic residents, as well as in counties with higher unemployment rates, once we control for the individual risk characteristics of the borrower.

I can’t state this clearly enough: this is a stake in the heart of the argument, made by most consumer groups, that lenders used predatory practices to target minorities for the worst loans. And on the surface, any of us should know this without the need for hard data: during the boom, loans were being made to anyone and everyone that could fog up a window. And I mean everyone — why do you think we’re now seeing such strong and swift performance deterioration in prime jumbo mortgages? The argument suggesting that minorities were disproportionately targeted and offered comparatively more onerous loan terms shouldn’t have passed the smell test for anyone that actually worked in the mortgage industry during those go-go years.

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1 Comment

  1. Jim Duncan April 3, 2009 at 12:29

    From a commenter who wishes to remain anonymous:

    “After college in the early 1990’s I was with a mortgage company and for a period of hell, I was the compliance officer in charge of overseeing a HMDA review of every loan mortgage loan over a 3 year period. It sucked. Big time… We did not risk price. Meaning that if you applied the rate was x.xx% that day PERIOD. If you qualified, great. If not, too bad. But we did not tell someone they could have the loan at a higher rate because of their credit or down payment…
    That said, there is no doubt in my mind having looked through the credit files of hundreds of borrowers that African Americans in particular got approved at a higher rate. While one could say that we were serving their community better, I argue that we were putting them in greater risk of default, etc… Had we denied these loans, we would have been discriminatory.
    It all sucks all around. We should either 100% automate the loan process and not allow for any deviation, or just admit that there will be bias in our lending. We are humans and we are not perfect.”


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