Evaluating Employment Data

Nonlinear non-monotonic oversights
In America we tend to interpret numbers from a linear monotonic mindset - in simple terms we think "more is better." But in nature nothing really works that way, same in the economy. More is not always better. Both beneficial and harmful forces can push common measures in either direction. Here, we will look at how both employment and unemployment fail to be reliable linear (monotonic) measures of our economy.

Draft: Dec 2012

 

 

Part 1 Employment:
On the surface increased employment would appear to be a good thing. We all need opportunity and employment is the primary, but not solitary, measure of opportunity. But let's look deeper what forces can increase employment
Up:

  • Increased opportunity - If more possibilities are created more jobs will exist for people to take. This is what we assume we are measuring when we hear employment reports.
  • Increased population - A rising population creates more people needing jobs and more tasks serving people that need to be done. Rising population can lead to rising gross employment without creating an actual rise in opportunity, quality of life, or even drop in unemployment.
  • Decreased community - When real community decreases more people need employment and will seek employment. The obvious example of this is the divorce of a traditional family. The housekeeper needs to enter the workforce to support a separate household.
  • Increased desperation - When extended recession persists people start taking any job out of desperation. This is not a measure of increased opportunity it is a measure of decreased hope.

Clearly, negative factors can drive employment up. Conversely, not all the factors that drive employment down are negative.
Down:

  • Decreased opportunity - Declining opportunity will drive employment down. This is obvious during a recession or factory shutdown.
  • Increased security - When families feel secure and have enough funds a member of the family may delay searching for new employment. This drop in total employment would actually indicate an increase in the quality of life.
  • Increased community and family support -If an individualistic society switches their mindset to a more communal mindset (e.g.: young men quit playing around then settle down and get married then their wives become housekeepers) total employment may decline. Again, this drop in employment may actually indicate an increase in the quality of life.

We see some of this play out with families. Before children both parents work. During the children's early years one parent stays home. When the children are old enough the homemaker may return to work. The choice to return to work may be driven by opportunity (good economy) or need (stagnating wages for the primary breadwinner.) The fluctuation in the numbers fails to indicate real qualitative changes in the economy.

Part 2: Unemployment
As a result, we might guess that unemployment reports are a better measure. But again, multiple factors make the unemployment relationships nonlinear. Both positive and negative factors can push the measure either up or down.
Up:

  • Jobs lost - Unemployment goes up when many jobs are lost.
  • Rapid population change - Unemployment also rises when a rapid influx of new workers (e.g.: teenagers) enter the workforce.
  • Increased security - Unemployment may also rise when potential workers feel secure enough to wait out low quality job offers for a better offer. *

Down:

  • Jobs found - Increased employment can reduce the unemployment rate. We initially assume that this is what we are measuring.
  • Hopelessness - When people lose hope and give up trying they cease to be listed as unemployed. Unemployment drops without employment actually rising.
  • Rapid retirement - If a large number of elderly qualify for retirement benefits during a recession the unemployment rate may drop as that cohort chooses retirement over employment.

So neither employment nor unemployment constitutes a reliable monotonic indicator of how things really are. Changes in either direction fail to indicate on their own declines or improvements in the economy.

Definitions:

Linear relationship: an increase in one unit of one variable always results in the same increase in a dependent variable.

monotonic relationship: an increase in one variable always results in an increase in the other

non-monotonic: an increase in one variable may result in either an rise or drop in the dependent variable

 

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*The election of 2012 provided us an interesting example of this when Ann Romney spoke about how they didn't have to work as a young couple because they were living off of inheritance. Had they been from middle class or poor families they would not have had the security to wait for a better opportunity.

 

  Part 3: The Historical Measures
 
Current growth in total jobs is at the level projected from the 20 year trend.  
 
The current annual growth rate is at the level projected by the 35 year trend.  
 
Jobs as a percent of population is stable after the combined declines 2001-2002 and 2007 - 2009. This level is still about the level seen during the boom economy of the late 1960s - early 1970s.  

We see a high growth rate from the early 1960s through the early 1980s. But even with this high growth the jobs to population ratio is about the same in 1982 as it was in 1966. Most of this growth represents the baby boom entering the job market.
After roughly 1980 we see a rapid rise in the employment to population ratio. This era was characterized by a few negatives that could lead to employment growth. During this time America saw the collapse of its industrial base - many good paying labor jobs disappeared. As a result two incomes became necessary to maintain the same standard of living previously gained by workers with just one income. The share of GDP going to workers declined. Divorce increased rapidly and community support systems collapsed rapidly. Philosophies of materialism and status replaced community and family - leading to the creation of the term "yuppie." Many people attempting to gain status worked longer and harder and spent significantly less time with family. For many, this growth in employ actually correlated to a drop in quality of life.
Since the peak in 1977 annual growth has been steadily declining. Since the peak in 2000 the employment to population ratio has been declining. It is not clear what caused these trends. They correlate to lower taxes on the rich and a higher share of the wealth going to the top 1%.

Data Sources

Short term trend notes

  • 1967 down: oil embargo
  • 1973 down: oil embargo
  • 1979-1980 down: oil embargo
  • 1989-1991 down: tax cuts & war drives up oil prices
  • 2000 -2001 down: dot com bubble bursts, tax cuts, fear & war
  • 2003 - 2008 up: investment bubble & oil prices rise exponentially
  • 2008-2009 down: bubble burst

 

 

Summation:

Employment, like all other real measures, does not directly correlate to quality of life. The relationship, at best, is not only non-linear it is non-monotonic. A rise in employment could indicate either a general rise in quality of life or a drop. We cannot tell for sure without checking other variables.

Footnotes:

Job vs. work: Americans work very much, so we must distinguish between a job and work. Consider a traditional extended family with two matriarchs taking care of the family and one breadwinner. A lot of work is being done, but only one job exists. Now, consider a two income family with children in daycare who eat out frequently because they don't have time to cook. In this case 3 or 4 jobs exist even while the amount of work being done is about the same. Americans also do massive amounts of uncompensated work - the obvious example being websites such as this. The number of jobs fails to measure either quality of life or actual work being done.

 


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