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| The Folly of Simplistic Measures |
| Written by Jonathan Smoke | |
| 03.14.2008 | |
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Discuss this article on the forums. (0 posts) The Wall Street Journal’s “The Numbers Guy,” Carl Bialik, had an interesting column in today’s paper regarding the misleading nature of the reading level scores provided by Microsoft Word. The column explains how that written English is so complex, that simplistic calculations made by programs like Word have their limitations in measuring and assessing the readability or reading levels of text. “A 1935 paper laid out more than 200 variables that affect readability. Most formulas incorporate just two, and not because they are the most important but because they are the easiest to measure.”
My takeaway from reading the column is that for the sake of ease and simplicity, crude measures can be grossly inaccurate and can mislead. The same can be said of the few metrics that are widely available about housing and residential real estate. In fact, almost every expert’s quote in this column could be slightly revised to apply to simplistic and misleading analysis highlighted in this very paper. For example, here’s my edit of a quote in the article. My edits are in brackets and I edited the name and location: “Everyone is waiting for this magic bullet that's very easy [to predict home prices based on incomes]," says Jane Doe, who runs an Atlanta, Ga., housing market research company. But her experience with clients who have overly relied on these formulas have suggested that "maybe it's just a stupid idea.”
Perhaps the columnists at The WSJ should share their own insights. In yesterday’s “Ahead of the Tape” column, Scott Patterson instructed readers to “Mind the Gap” that exists between home prices and incomes. The conclusion is that nationally, changes in incomes and home prices are so “out of whack” that home prices must fall 9 to 12% more to get back in line, and they may even fall 15% or more to overshoot.  What grade level is this type of analysis? While incomes and changes in incomes do have an impact on home prices, they are but one of many variables. Worse still, relying on a crude measure of incomes like median household incomes has even less of a direct connection.The national median household income in 2006 was $48,201. But based on our calculations using consumer segmentation data, the average household income of homeowners was more than twice as much at $98,391. Why is this? Quite simply, homeowners and homebuyers are not represented by the total population or the median. Homeownership rises with income. So, just because median incomes are moving at x%, above median incomes aren’t constrained to the same level of growth. Indeed, higher rates of growth in upper income levels can explain much of the home price growth in non-bubble markets where speculation didn’t play a role. Back to the language analogy, here’s a way to put this observation in language a first grader can understand: The rich get richer. I wish that the vanguards of finance would apply more science to understand housing instead of shoveling simplistic analysis that can mislead otherwise informed and rational investors. You cannot understand the housing market without understanding the complex nature of the consumer groups that are the source of demand. Medians just don’t cut it. Back to the readability article, here’s another quote that doesn’t need editing—I’ll leave it in its language context, but I think you can clearly get my concluding point: Even neurolinguist G. Harry McLaughlin says of his own, widely used SMOG Readability Formula, "The theoretical basis is c---.”
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