A lot of negative news on housing, working hard to find something positive. TKS
by Tom Lawler
If one were to assume that the current “excess supply” of housing was around 1.75 million, and that the net housing stock lost to demolitions is about 225,000 per year, then here is a “matrix” of how many years it would take to absorb that excess supply for different combinations of housing production and household formations.
|Years to Absorb 1.75 million “excess supply” of housing units|
|Household Growth (thousands)|
|Housing Production (thousands)||900||1,000||1,100||1,200||1,300||1,400||1,500||1,600|
E.g., if housing production (completions plus MH placements) ran at around 600,000 per year, and household formations increased to 1.2 million per year, it would take a little over two years to absorb a “reasonable but possibly low” estimate of the current “excess” supply of homes – unless, of course, the number of homes “lost” to demolition, conversion, etc., ran above 225,000 per year.
It is easy to see why many housing economists view the current “low” level of housing production as a plus for the overall health of the housing market, even before allowing for the current high number of residential mortgage loans either seriously delinquent or in some stage of foreclosure. It is also easy to understand why competent housing analysts believe that any government policies designed to encourage additional construction of housing units would be “dumber than dishwater,” and that the only government policies designed to encourage increased “AD&C” activity would NOT be acquisition, development, and construction lending, but instead “acquisition, destruction, and or conversion” of existing vacant housing units.
Of course, the “matrix” above was for the nation as a whole, and estimates of the “excess supply” of housing would vary massively by states. Using the “official” Census gross vacancy rates, there was an increase of over three percentage points from 2000 to 2010 in eight states: (in order) Nevada, Florida, Michigan, Georgia, Rhode Island, South Carolina, Ohio, and Arizona. And, of course, within states with overall “modest” vacancy rate increases there were huge increases in some counties – California being one of many examples.) Some state data are shown in the table at the end of this report. In addition, the matrix doesn’t account for the “types” of homes that are vacant versus the “types” of households that might be formed.