Demographic Adjustments to Quits
It occurred to me that another area where demographics (the baby boomers) would be skewing a statistical trend is the JOLTS data. Older workers have longer durations of unemployment and lower unemployment rates, which suggests that older workers tend to have much lower employment churn than younger workers. This should mean that, all else equal, current quit rates should be lower than we might have seen in earlier time periods.
Now that I have an age-specific model, I can adjust the quits data for changes in age distribution. This graph compares actual quits to the quits we might be seeing if age demographics had remained as they were in December 2000, when JOLTS data started:
This is not quite as stark a difference as I had expected. But, demographics is creating a sizable downward shift in the quit rate of a little more than 200,000 quits per month, or about 0.15%, compared to what we would likely see with a younger labor force.
Whereas the previous graph showed Quits with labor force age distribution held equal to December 2000, this graph shows Quits with everything else held equal and only labor force age distribution changing. This gives us a kind of full-employment demographic trend line for Quits. Again, there is a small drop in expected quits, though not as much as we see from demographic effects on the labor force participation rate.
Quits Compared to the Unemployment Rate
So, demographics are probably skewing labor churn down a little bit, but the basic narrative from quits isn't overwhelmingly changed by it. In either case, we are roughly back to the nadir of the quits rate in the previous recession. We do need to keep in mind, though, that the previous recession was pretty shallow in terms of labor disruptions. Unemployment topped out at 6.3%. (I've reviewed in many previous posts why a declining labor force does not negate this fact.) So, while quits look weak in absolute terms, they are quite strong in relation to the unemployment rate. Quits have recovered to the same level they were in 2003 when the unemployment rate was only 6%.
As I have discussed before, recent minimum wage hikes and Emergency Unemployment Insurance (EUI) may have inflated the current unemployment rate, currently by around 1 1/2%. That would leave an unemployment rate of 5.5% related to non-MW and non-EUI factors. If we think about the effect of these legislative policies on quits, this could explain an unexpectedly strong quits rate. Low-wage workers who are legislatively priced out of labor markets and workers with extra incentives for extending their duration of unemployment would provide less competition to quitting workers. So, if my estimates are somewhat accurate, we would expect that last 1 1/2% worth of unemployed workers to exert less downward pressure on the quits rate, although they would still exert some.
All in all, I would say that the quits data makes me more confident about my estimates regarding the causes and level of current unemployment, and their effect on the labor market.
Here is a scatter graph of the quits rate over time compared to the unemployment rate:
The quits rate compared to the unemployment rate (in blue) looks to me like it has been following a pretty stable relationship. If I adjust quits for demographic effects (the red line), quits look especially strong coming out of the deepest point of the recent recession. If I adjust quits for demographics and also adjust unemployment for the distortions caused by MW and EUI (the purple line), then the relationship is similar to the relationship that we see without any adjustments. This could be a coincidence, or it could mean that my estimates of structural distortions of Quits and Unemployment are both fairly accurate, or it could mean that my estimates are both similarly inaccurate.
In all three cases, I don't see any evidence of an especially weak quits rate. In the time series above, the trend in growth rate of quits does appear to be lower in the current recession than it had been in the previous recession, but I suspect that this has to do with the inverse relationship between quits rates and the unemployment rate. This will only be answered with new data as the unemployment rate drops further. Quits might actually accelerate in 2014, which would be another tailwind for markets next year. Regardless of whether we use the raw labor numbers or my adjusted ones, the Quits rate looks pretty normal, even a little strong, compared to the trend that would smoothly lead Quits back to normal recovery levels.
This may be a case where the demographic adjustment is important. The unadjusted quits data may not look as strong as quits in the previous recovery, due to the older labor force. This may be one of many indicators where a bullish cyclical signal will be retarded by demographic effects.
Forgetting Half of Supply and Demand
I think this is another context where analysts ignore the role and the power of labor supply as an influence on the labor market. There are two factors pressing downward on the Quits rate.
One is a dearth of labor demand, signaled through an elevated unemployment level. This is the influence typically cited. But, this is only half the story.
The other influence is the aging of the labor force. Here, it is the relatively powerful position of labor suppliers that is pushing quits down. Older workers have less churn because they have lower unemployment rates and longer unemployment durations. This is the case because they have more control over their work, more seniority, more income and wealth, less to gain from a career shift, and more frictions in job searching because they tend to have more specialized and senior positions.
The demographic influence isn't huge, in absolute numbers, but if we compare where quits are now, at about 2350 per month, to where we would expect them to be as we neared full employment, around 2800 per month, the supply factor and the demand factor each seem to be contributing about 50% of the difference.
This is one more case where the tendency to view labor markets as if laborers are powerless causes commentators to come to easy conclusions about these issues too quickly.