Separation and Hires: The key to understanding labor force dynamics.

The JOTLS data (find the data here) produced by the BLS gives insight into the recent job losses. As Robert Shimer, a professor at the University of Chicago, showed some time ago, unemployment can go up either because workers become more likely to lose their jobs (the separation rate) or because unemployed workers have a more difficult time finding new jobs (the hires or matching rate). The BLS only began collecting data in late 2000, much too late for us to compare the current downturn to previous episodes. Bob Shimer, however, has computed separation and matching rates going back to 1947 (his data is here). The data is not strictly comparable but I think we can use the lessons from Shimer’s data and apply them to the current episode.

I have spent a lot of time working with his data lately. The cyclical behavior of matching and separation rates is remarkable and should provide the key to the next level of understanding in business cycle research. Matching rates, the probability of finding a job conditional on unemployment, begin to fall well before recessions begin and continue to fall well after the recession ends. Separation rates tend to rise at the beginning of recessions and tend to fall well before the end of the recession. Not surprisingly, the worst recessions in the post-war era (1958, 1982) are characterized by large changes in both rates.

In every post-war recession, the separation rate returned to more-or-less its long term average 4-to-monhts before the trough. The fall in separation rates also coincides with a rise in consumption. Apparently, consumption begins to rise once employed households no longer fear unemployment – a rational outcome. Consumption rises before unemployment falls because unemployed workers continue to have trouble finding work long after the recession ends.

As a result of this research, I am beginning to have more faith in the signals emitted by the JOLTS data. First, take a look at the picture below. The picture shows the number of hires each month in the JOLTS data from late 2000 to January 2009. Amazingly, the number of hires began to fall as early as January 2006, the same month the housing market turned South.
This is the clearest piece of data I have yet come across to indicate that the collapse of the housing market was not a random event. The decline in hire rates reduces the permanent income of households. People realize that conditional on losing their job, new work will be harder to find. Households also seem to know that this trend tends to have long cyclical properties – a decline in the series today is likely to signal a long period of increasingly lower matching rates.

Of course, I am looking for indications of turning points. I want to know when the economy is going to recover, in which case we need to look at the separation rate. The picture below is puzzling at first. It shows that the number of separations has been steadily falling since early 2007. This data alone would indicate that flows into unemployment should be falling, quite the opposite of what seems to be happening.

The problem with the data on total separations is that it does not control for the voluntary versus involuntary separation. If I quit my job today, knowing I had a new job in the bag, I would show up first as a separation then as a hire. But this type of turnover is not actually of interest. We care only about involuntary separation. To get the real picture, I subtract the number of monthly quits from the total. The resulting picture, shown below, gives a completely different view of the state of the labor market.
The level of separations in January 2009 was 28 percent higher than its 2001-07 average level. Keeping in mind that half of that time period was during bad labor markets, this statistic is quite stunning. More importantly, however, for those looking for a near-term recovery, the series was still rising in January. If the separation rate fell sharply in February, I would expect a recovery in mid-2009. It’s possible, but we don’t see any evidence of that yet. If anything, the data indicate a worsening in the separation rate: Through the first week of March, initial claims for unemployment insurance were still rising.

Casey Mulligan, another one of those Chicago economists, notes in his blog that consumer spending is falling even in the face of rising disposable income. He attributes the fall to the sharp fall in asset values. I believe in wealth effects but most estimates are actually quite small. So, while I agree with his assessment and think the change in asset prices is playing a role, I believe the decline in consumption can be more directly attributed to changes in the labor market.
Even as current income continues to rise, the high separation and low matching rates have sharply reduced permanent income for households – they are faced with greater probability of job loss and lower odds of getting a new job if they do lose their job. And, labor income is far and away the largest portion of permanent income for the vast majority of Americans.