Richard Florida
by Richard Florida
Wed Jul 29th 2009 at 10:00am UTC

Housing and the Crisis, Part IV

Yesterday, we looked at the relationship between housing prices and income. Today, we turn to the relationship between housing prices and wages. Wages are a useful way to gauge regional housing prices because they only count money that is earned by doing work. Income, on the other hand, counts any and all earnings from investments, interest, dividends transfers, and other sources.

The graph below plots housing prices in 2009 against wage levels for 2008 (the most recent data available).

There is a clear, positive, linear, and significant relationship between wages and housing values – the correlation is 0.71 and the R2 0.51. Metros above the fitted line had higher housing prices than wages relative to national levels, while those beneath the line had lower than expected housing prices.

Near the top we see many of the same regionsĀ as in yesterday’s analysis. Honolulu is once again the greatest outlier, with housing prices exceeding wage levels with a differential of $384,290. Metros in California once again play a prominent role at the top of the list, including San Diego ($87,365), Los Angeles ($63,340), and San Francisco ($60,148). New York also registers a substantial differential of $76,896; Miami ($46,128) also has a considerable differential.

On the other hand, there are metros where housing prices were less than their incomes would predict based on the national trend. In Decatur, IL, for example, housing prices were $131,344 less than what its wage level could support based on the national trend. In Michigan, both Saginaw ($123,140) and Lansing ($119,334) had differentials over $100,000, as did two Ohio cities, Akron ($105,447) and Cleveland ($105,386). Atlanta ($86,079), Washington, D.C. ($65,446), and Dallas ($51,896) all had differentials of greater than $50,000, while Houston ($48,874), Chicago ($48,794), and Boston ($42,834) all had differentials of greater than $40,000. The difference was more modest in Philadelphia ($20,520). We’ve again omitted Detroit because it failed to report housing price data for 2009.

2 Responses to “Housing and the Crisis, Part IV”

  1. Buzzcut Says:

    Do a multiple regression, and control for average daytime temperature in February. Your correlation coefficient will be like 0.9. ;)

  2. RS Says:

    I would guess that the deviation of the observations around the line are more likely a function of the supply of housing. Hence, those places above the line have a more limited supply of housing than do those below the line.