Structural Unemployment Arguments Lose Again, Interstate Mobility Edition.

One reason I’ve been watching the so-called “structural unemployment” debate so closely is the result of recent trends in moving rates between states and within counties. If you go to the Census Webpage here you can get data from the CPS on mobility rates (here’s a historical pdf).

And if you chart out the percent of total movers, movers who move in-between states, and movers who move within the same county, you see this:

This isn’t the easiest graph to read (but because it is percent of total population, small moves make major differences), but the percent of the population that moved to a different state dropped in 2006 and stayed downward.  Those moving within country took a slight uptick and bounced, while the overall continued downward.

The quick read was that everyone, post bubble-popping, was abandoning their properties and moving across the town to live with their parents and friends while looking for a new local job to save their house, a house they couldn’t sell because they were underwater.  Also that this collapse in state mobility was going to be a “structural” problem for the recovery.  Or at least it was something I considered, which is why this blog spends a lot of time thinking about the relationship between unemployment and housing variables like being underwater and foreclosures (see: our review of an IMF study on this, and foreclosures and state budgets, for instance).

Turns out this is less of a case than I thought, as that 2006 drop is the result of a data bug. From Greg Kaplan and Sam Schulhofer-Wohl, Interstate Migration Has Fallen Less Than You Think: Consequences of Hot Deck Imputation in the Current Population Survey, Minnesota Fed (my bold):

We show that the significant drop in the annual interstate migration rate between the 2005 and 2006 Current Population Surveys is a statistical artifact. The Census Bureau’s imputation procedure for dealing with missing data before the 2006 survey year inflated the estimated interstate migration rate…The change in imputation procedures explains 90 percent of the reported decrease in interstate migration between 2005 and 2006, and 42 percent of the decrease between 2000 (the recent high-water mark) and 2010. After we remove the effect of the change in procedures, we find that the annual interstate migration rate follows a smooth downward trend from 1996 to 2010. The 2007–2009 recession is not associated with any additional decrease in interstate migration relative to trend….

Figure 3(b) shows that the change in imputation procedures had little effect on the total migration rate, because the decrease in imputed interstate moves in 2006 cancels out an increase in imputed within-county moves.

Huh. Everything I believed was a lie. Boo. But it also turned out that the strongest argument for the “structural unemployment” was based on a glitch in recording the data. Go figure.   It could be that, like it is necessary for home ownership rates to go down, it will be necessary for mobility rates to increase.   And again, this could be very relevant to the places that have very high unemployment and very large housing problems (Nevada, California, Florida, etc.).   But to whatever extent it contributed to 9.6% unemployment, it contributes less now.

Additional material for advanced readers.

About that post 1996 downward trend. There’s a paper by Rangan Gupta and Stephen M. Miller, “Ripple Effects” and Forecasting Home Prices in Los Angeles, Las Vegas and Phoenix, which finds granger causality between the housing prices in LA, Vegas and Phoenix. Ryan Avent summarizes the paper here.

Implicit in the model is the idea that to take advantage of housing price appreciation (HPA) you need to move from one place to another.  That’s how, in theory, LA lead to Vegas’s housing bubble which lead to Phoenix’s housing bubble. The model the paper presumes gains explanatory power from migration (“The migration explanation requires that households move from one metropolitan area to another to take advantage of regional house price differences.”), equity conversion (“In order to cash out that wealth, residents of Southern California must sell their home and move to a lower cost region where they can buy a similar quality house for a lower price and pocket the residual equity”) and spatial arbitrage.

Yet we had a nationwide housing bubble during a large-scale decline in total moving rates.   Think about that.   It makes sense if the wave of refinancing, junior-liens and financial industry changes allowing for HLTV allowed people to take advantage of HPA without moving.   Instead of having to shuffle around in order to spin up housing prices, you could do it without leaving your couch.   How does that work alongside conventional models of equity conversion?   I think there’s a lot of work to be done in that question.

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5 Responses to Structural Unemployment Arguments Lose Again, Interstate Mobility Edition.

  1. David Wiczer says:

    The way to read this is: push to homeownership during the 1990s increases the fixed cost of moving, so general geographic mobility decreases. In the housing bust, houses become less liquid, so that fixed cost should rise still more, but with more economic turbulence, there’s more incentive to move as well.

    So what you’re seeing is an equilibrium outcome: the total number of people who moved didn’t veer much off the trend because the costs and the benefits to moving both changed in opposite ways. But I can’t look at that picture and conclude everything’s rosy. If the story I just told is true, then there are people that would have wanted to move, but didn’t and you have more geographic mis-allocation than otherwise.

  2. sraffa says:

    Is there any real evidence of structural employment?

    I’ve seen it debunked so many times and yet it won’t die. I guess right-wing ideological convenience trumps any attempt to consider all economic evidence to the contrary. Maybe there needs to be a prize or something.

    The best I’ve seen is the Beveridge curve which is somewhat vertical now. Though even that goes out the window once you realize countercyclical loops are common.

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