On the House: Wading through housing data
Every Friday evening for five years, I watched a CBS program called Numb3rs. It was an interesting show, but the main reason I watched was that it was filmed at the California Institute of Technology in Pasadena while my older son was there getting his doctorate in planetary science.
Every Friday evening for five years, I watched a CBS program called
It was an interesting show, but the main reason I watched was that it was filmed at the California Institute of Technology in Pasadena while my older son was there getting his doctorate in planetary science.
As the actors talked math or crime or whatever, I focused on the scenery, to figure out where on campus they were filming and whether I could place it.
The math? Well, I've learned more about it since I left school than when I was there. I prefer practical applications to theory: balancing my checkbook; finding the proper angle for a compound miter cut; changing Celsius to Fahrenheit; collimating my telescope.
Real estate writers need math to wade through sales statistics and mortgage rates, in much the same way that I used it when I covered small suburban towns and wrote about how they determined their tax rates.
I've learned enough, or so I thought, to wade through data analysis by the Philadelphia Fed. Poring over one report, squinting at footnotes, I got the sense that all these complex calculations were performed by giant computers, fed statistics by the shovelful by a robotic arm.
I assumed that, even though I've seen people at the Federal Reserve Bank - mostly helping me figure out which door to leave by.
So when the Fed called about a story I had written about delinquency rates among recent FHA borrowers, there were people on the line.
Despite my use of mathematics in everyday applications, theory goes right past me, and I pick and choose the terminology.
For example, I'm a fan of matched pairs, but not of cohorts, which, in my historian's mind, is one of 10 units that make up a Roman legion, not a group with a common defining characteristic - FHA borrowers in 2006-2009.
So, from the beginning of this particular report, I made assumptions based on what I was reading that might not have been the right ones.
What I read was that the quality of FHA borrowers was improving because, among other things, credit scores were rising. The reason: Conventional lenders raised credit-score limits, and people who once easily qualified for conventional loans were going with FHA.
Though that is likely true, when it started happening and how many loans were involved are the issues.
So I'm handing the next few paragraphs of this column over to an explanation by Harriet Newberger of the Fed of what the data mean:
The performance of FHA's national loan portfolio as a whole was deteriorating over the time period covered by the Fed study, and has only recently begun to improve (in 2010).
The report looks at the performance of four cohorts of loans, specifically loans originated in 2006, 2007, 2008, and 2009, and examines each cohort (group) separately for each cohort rather than "in the aggregate."
With us so far?
As it turns out, performance was about the same for 2008 purchase loans as it was in 2006, despite the higher mean credit scores, while performance of 2008 refinance loans was worse than performance of 2006 refinance loans.
The source for the data on mean credit scores, as well as loan performance, was Lender Processing Services Applied Analytics Inc., she said.
I'll admit that once the Fed explained things, I got a clearer picture.
I believe it was Helen Lenoir, wife of Richard D'Oyly Carte, who, after observing Sir William Gilbert's bad behavior remarked, "The more I know of men, the more I prefer dogs."
I'm beginning to feel that way about real estate data.
On the House:
Inquirer real estate writer Alan J. Heavens is the author of "Remodeling on the Money" (Kaplan Publishing). His home improvement column appears Fridays in Home & Design.