Dec

5

 We have gone almost a year with the two percent additional payroll tax reinstated. The results are worse than expected.

What would have been expected is an increase in employment, but not enough to offset the effective tax increase. The reason you would expect an employment increase is because Americans are a resilient lot and get bored with sitting around. Sooner or later they find a way to get back to work. That is not what we have: The growth in payroll taxes is now negative, indicating a net loss in payrolls. The data is effectively "cap-weighted" so it might mean a loss in the number of jobs or switching to lower pay, as when a nuclear engineer becomes a sanitation engineer.

Philosophically, tax rate increases for individuals generate increases in tax revenue for governments. This is exactly what is expected by government, but the problem is that government does not know where to stop. They expect further rate increases to result in commensurate increases in revenue. But government neglects that individuals have a say in this: the latter can vote with their feet by leaving the workforce. America is now on the wrong side of the Laffer Curve.

Additional amounts taxed (N.B. the PPACA has been ruled by the Supremes as a tax) will have a continued negative effect.

A fellow Spec-Lister suggested I look for structural/secular changes in the employment data. My initial thought was that humans are skilled at obtaining freebies, and the disability payments coming from Social Security seemed a perfect target. Consider, faced with a lay-off, why not see a doctor, claim clinical depression and get yourself on disability? The long-term advantage of doing so may mean that you never have to work again, which would not be the case with unemployment benefits. But is my conspiratorial claim borne out by the data?
The short answer is "No". However there is more, should you feel inclined.

Firstly, which data does one use? Social Security Administration issues a report showing claimants for disability and the average claim. Multiply the two and you get the total value of disability benefits paid. Alternatively, you can go to the Treasury website and see their ledger of what actually was paid. Although the two sources (Soc.Sec. and Treasury) mimic one another, they are decidedly not identical. Of specific concern is that they differ by an odd order of magnitude, and one which is not relatively constant. So then one might posit which source does one trust.

Chart of Disability Benefits Paid

Chart of the 12-month rates of change of benefits paid

My experience suggests that the Social Security data looks as though it has been manipulated or "cleaned up". The Treasury data looks as though it contains a degree of static, which is more realistic. My guess would be that the Treasury data is "raw", while the Social Security data is "adjusted". In general my personal preference is for raw data if I cannot reverse engineer the adjustments. Both data sources indicate a relative decline in the yearly rate of change, decidedly counter to my pre-supposed conspiracy claim.

If you look a little deeper into the Treasury data you find a profound cyclic influence:

Cyclic disability benefits

This was a surprise. I did not assume the claimant had much control over the process, but the data indicates that summer is a key time to receive benefits. Oh, the joy of it all. [Skeptics should note that the cyclicality is not related to the number of days in the various months.] The cyclicality also suggests that disabled persons do return to the workplace. (I would have lost that bet.)

What is the current trend?

trend slope in disability benefits paid

For whatever reason, the drift of disability benefits is not increasing. One might optimistically believe that because conditions are not worsening, they must get better. Such logic could cost an investor a lot of his wealth.

Rocky Humbert replies: 

There was a Washington Post story yesterday that adds some color to this discussion. It notes a fact: 1.3 Million workers will have their "emergency" unemployment benefits end on December 28, unless Congress renews this aid program. This is a big number. And I was unaware of this fact. And as I consider myself somewhat informed about stuff, I'd guess relatively few market participants are aware of this fact either.

The writer then looks at the probability that a lot of these folks will file for disability claims. The author cites a study (which I have not read) which suggests that they won't. I have no opinion except that people respond to incentives. And some number of these 1.3 Million will surely find their way back into the reported labor force. This will likely distort the tax revenue, payroll, and other data to some degree in the first months of 2014.

I am raising this point not because I have any view about the currently big number of people receiving disability or what it means. (That's HR Rogan's job.) Rather, I am raising this, because the employment and tax numbers will, I believe, look really odd in January and February. (HR=hand wringer)

The story can be found here:  "Where Will Workers Go After Their Jobless Benefits Expire? Probably Not on Disability"

Jeff Rollert adds: 

Just to add another vector to the discussion, I would also argue that, since 2000 (the benchmark year in the article), the entry into the global labor pool of hundreds of millions of smart, motivated Chinese workers (not to mention Vietnamese, etc) has had a significant impact.

From the MIT Technology Review: "How Technology Is Destroying Jobs":

Given his calm and reasoned academic demeanor, it is easy to miss just how provocative Erik Brynjolfsson's contention really is. ­Brynjolfsson, a professor at the MIT Sloan School of Management, and his collaborator and coauthor Andrew McAfee have been arguing for the last year and a half that impressive advances in computer technology—from improved industrial robotics to automated translation services—are largely behind the sluggish employment growth of the last 10 to 15 years. Even more ominous for workers, the MIT academics foresee dismal prospects for many types of jobs as these powerful new technologies are increasingly adopted not only in manufacturing, clerical, and retail work but in professions such as law, financial services, education, and medicine.

That robots, automation, and software can replace people might seem obvious to anyone who's worked in automotive manufacturing or as a travel agent. But Brynjolfsson and McAfee's claim is more troubling and controversial. They believe that rapid technological change has been destroying jobs faster than it is creating them, contributing to the stagnation of median income and the growth of inequality in the United States. And, they suspect, something similar is happening in other technologically advanced countries.

Perhaps the most damning piece of evidence, according to Brynjolfsson, is a chart that only an economist could love. In economics, productivity—the amount of economic value created for a given unit of input, such as an hour of labor—is a crucial indicator of growth and wealth creation. It is a measure of progress. On the chart Brynjolfsson likes to show, separate lines represent productivity and total employment in the United States. For years after World War II, the two lines closely tracked each other, with increases in jobs corresponding to increases in productivity. The pattern is clear: as businesses generated more value from their workers, the country as a whole became richer, which fueled more economic activity and created even more jobs. Then, beginning in 2000, the lines diverge; productivity continues to rise robustly, but employment suddenly wilts. By 2011, a significant gap appears between the two lines, showing economic growth with no parallel increase in job creation. Brynjolfsson and McAfee call it the "great decoupling." And Brynjolfsson says he is confident that technology is behind both the healthy growth in productivity and the weak growth in jobs.
 


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