One of the regulars was kvetching on here a day or so back about the need to use “real statistics.” Suppose I wanted to get “real statistics” on the size of the shadow inventory; varied reports suggest it lies anywhere on the range from 1m to 10m or so, depending on the definition and data used.
Where would one find such “real statistics” on the size of the shadow inventory if one wanted them?
Wednesday, January 11, 2012
Michael Olenick: 9.8 Million Shadow Inventory Says Housing Market is a Long Way From the Bottom
By Michael Olenick, founder and CEO of Legalprise, and creator of FindtheFraud, a crowd sourced foreclosure document review system (still in alpha). You can follow him on Twitter at @michael_olenick
“Shadow inventory,” the number of homes that are either in foreclosure or are likely to end up in foreclosure, creates substantial but hidden pressure on housing prices and potential losses to banks and investors. This is a critical figure for policymakers and financial services industry executives, since if the number is manageable, that means waiting for the market to digest the overhang might not be such a terrible option. But if shadow inventory is large, housing prices have a good bit further to go before they hit bottom, which has dire consequences for communities, homeowners, and the broader economy.
Yet estimates of shadow inventory, and even the definition of what constitutes shadow inventory property, vary widely. For example, the Wall Street Journal published a Nov. 11, 2011 article, “How Many Homes Are In Trouble?” where values varied from 1.6 million (CoreLogic), to “about 3 million” (Barclays Capital), to 4 million (LPS Applied Analytic), to 4.3 million (Capital Economics), to LPS Applied Analytics, to between 8.2 million and 10.3 million (Laurie Goodman, Amherst Securities).
Why do these numbers vary so much? Even though CoreLogic is generally considered to have one of the best databases of loans, its estimates of loan performance and odds of default are based on credit scores, which is a badly lagging indicator. Laurie Goodman is seen by many as having the most carefully though out model, even though industry insiders are keen to attack her bearsish-looking forecast.
I have a large database of my own, and am familiar with housing and mortgage information sources. I’ve come up with my own tally of shadow inventory and have also tried to analyze — OK — take a stab at – what I call “shadow liability,” meaning the amount of money taxpayers, investors, banks, will be lose if those homes are liquidated. Assumptions using those terms are also in the attached spreadsheet. My analysis comes up with a total close to that of Goodman’s range, 9.8 million using a narrower definition than Goodman’s of what constitutes shadow inventory.
Put more simply, things are actually worse than any of the prevailing estimates indicates, although Goodman is very close to the mark. Current loss experience suggests that this figure is staggering, easily in the $1 trillion range.
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Definition of ‘Shadow Inventory’
A term that refers to real estate properties that are either in foreclosure and have not yet been sold or homes that owners are delaying putting on the market until prices improve. Shadow inventory can create uncertainty about the best time to sell (for owners) and when a local market can expect full recovery. Also, shadow inventory typically causes reported data on housing inventory to understate the actual number of inventory in the market.
Investopedia explains ‘Shadow Inventory’
With the unprecedented number of foreclosures stemming from the subprime mortgage meltdown of 2007-2008 and the overall housing market collapse during that crisis, lenders were left with significant real estate holdings. Many lenders were slow to put their inventory up for sale for fear of flooding the market and further driving down prices, which would in turn lower their potential ROI.
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