While employment has recovered to an extent in low debt counties; it has badly lagged in high household debt counties. For Konczal and many other researchers, this is evidence that the presence of high levels of debt (particularly mortgage debt) remains a causal factor preventing the recovery. Evidence of this sort is used as arguments for radical measures to reduce household debt — including mass refinancing or mortgage modifications (for e21’s views on these plans, click here).
Because these treatments frequently involve large taxpayer losses, it’s worth thinking through what the demonstration means. While it’s true that household debt and employment are correlated; it’s not clear that lowering household debt would automatically raise employment.
Erik Hurst presents an alternate explanation: that areas of high investment in real estate are experiencing high unemployment due to difficulties in re-allocating resources to other uses. He presents evidence suggesting that states which had a high share of employees in construction or finance saw greater increases in unemployment during the recession:
This relationship is consistent with the idea that certain parts of the country – including the states of Florida, Arizona, and Nevada at the top-right corner of the graph – were overinvesting in residential construction, and have faced difficulties in retraining laid off construction workers in new fields. In fact, Hurst finds that as many as 35% of the unemployed in 2009 in Nevada were formally in fields relating to residential construction.
Both explanations – household debt and construction employment – place the housing boom as central to explaining why employment has lagged during the recession. However, the housing debt story suggests the possibility of easy fixes to employment by reducing aggregate debt levels. The construction employment story, on the other hand, paints a more difficult picture: employment may have lagged during the recession simply due to the difficulty of retraining residential construction workers for new fields. Figuring out which story better matches the facts is important for figuring out the scope for policies to deal with the unemployment problem.