Economic Strength Methodology
used to determine economic strength measure how the economy has behaved, not
what has caused it to perform.
The following are the data
sectors used to create the rankings.
Group 1 – These sectors
reflect the overall growth in size and quality. The “quality” of the economy
is based upon what people earn, as this influences their “standard of
living” more than anything.
All Workers - Earnings
All Workers - Jobs
All Workers – Wages
Per Capita Total Worker Earnings
Per Capita Personal Income
Earnings by Place of Residence
Per Capita Earnings by Residence
Wage & Salaried Workers - Earnings
Wage & Salaried Workers - Jobs
Wage & Salaried Workers - Wages
Group 2 – These sectors
reflect how the economy is behaving. Small businesses and the construction
and retail industries are extremely reactive to the “flow of money” coming
into an area. They typically grow or decline in direct proportion to the
condition of the economy. There are, of course, exceptions. Areas which have
become destinations for retirement age individuals will have high growth
numbers in both construction and retail, while they might not have a strong
economy. (No system is perfect.)
Non Farm Proprietors -
Non Farm Proprietors - Jobs
Non Farm Proprietors - Wages
Construction - Worker Earnings
Construction - Jobs
Construction - Wages
Retail - Worker Earnings
Retail - Jobs
Retail - Wages
Group 3 – These
sectors are negative sectors. Growth in these reflect a poor economy.
Per Capita Income
Actual Per Capita Income Maintenance (Welfare)
Per Capita Medical Assistance for the Poor - (Medicaid)
Actual Per Capita Medical Assistance for the Poor – (Medicaid)
“Redundancy” and “counter
balances” are built into the criteria which compensate for anomalies which
might occur in one or two of the items.
As an example, an area
might have a very high percentage growth rate in Per Capita Income
Maintenance. This might mean the economy is on decline. However, percentages
are funny things and can sometimes be misleading. It is much easier for an
area with a low basis to have high percentage increases than an area with a
The Ames, IA MSA had the 8th
fastest percentage growth rate (18.9%) in Per Capita Income Maintenance from
2007-2011 among the 366 areas. However, its Per Capita Income
Maintenance in 2011 was $429, ranking 362nd. While the rate
of growth is high, “twice nothing is still nothing.”
The reverse also occurs. The El Centro, CA
MSA had the 7th the
highest Per Capita Income Maintenance ($1,599) among the metropolitan areas,
but it growth rate of 7.9% was very slow, ranking 362nd.
Of course there are the extremes. The
State College, PA MSA had the lowest Per Capita Income Maintenance and the 6th
slowest rate of growth. The
MSA has the 6th
highest Per Capita and the 33rd fast growth rate.
If only these criteria were used, the MSA’s would be ranked in the following
order: State College, Ames, El Centro, and Flint.
POLICOM is also aware of
anomalies in labor data. It has found economies which are on decline
sometimes have a very high growth rate in the number of people employed in
Retail Trade. Retail is a reactive industry, which grows and declines in
direct proportion to the condition of the economy.
So how can retail jobs grow
in a declining economy? It is because labor data counts full and part-time
jobs all as “jobs.” This means two part-time jobs are counted as two jobs in
When an area is in decline,
retailers switch from full-time workers to part-time workers. A small
retailer might have four full time workers. If the retailer lays off three
full time people but hires five part-timers to replace them, there is a
statistical gain in the labor data of two jobs. The retailer now has six
workers, in the data, which is a 50% increase from when he had four full
To counter balance or
compensate, the total earnings and wages are included. Under the above
scenario, both earnings and wages will decline; bringing down the area in
The average annual increase
is calculated for each of the items for three time periods.
(2015 data was released by the Bureau of Economic Analysis in October of
Last five years: 2011-2015
– Weighted once.
Last ten years: 2006-2015
– Weighted twice.
Previous Ten Years: 1996-2005 – Weighted once.
The percentage increases
are then adjusted mathematically for consistency. Data sectors which reflect
wages are counted twice, giving equal emphasis to quality as to the growth
The growth rates are then
ranked. The rankings are totaled. The areas are then ranked for economic
strength based on their total overall rankings.
Consistency of Growth
the areas that have the fastest or slowest growth rates is insufficient when
trying to determine the character of a local economy. The rate, consistency,
or stability of the growth is equally important.
Areas with unstable,
boom and bust economies are difficult places to conduct business. Residents
of these areas are subject to economic uncertainty and stress.
A merchant may lease
extra floor space following three or four great years, only to go bankrupt
after a subsequent economic decline. Residents might make long term
financial commitments based upon rapid increases in earnings and employment,
only to loose everything due to a sudden downturn causing massive layoffs.
To better understand
the nature of economic stability, we will examine the consistency of the
construction industry for three areas which had the same average annual
The first graph depicts a Mythical Area, which had an Average Annual
Percentage Increase (AAI) in Construction Jobs of 2.3% from 2004 through
Mythical Area had a
2.3% increase in 2004.
In 2005 it again had a 2.3%
increase. Each and every year, the area increased exactly 2.3%. This means
construction employers, each and every year, increased the number of people
they employed by 2.3%.
As a result, by
averaging the ten-year history, the Mythical Area, obviously, had a 2.3%
average annual increase (AAI).
the area had perfect consistency as depicted by the straight
horizontal line on the graph. The flow of money into the area, which
supports this industry, grew in an absolutely consistent manner. This is a
perfect situation. However, this is myth, not reality.
Let us examine the
economic stability of the Fargo, ND MSA for the same element.
Fargo, during the same ten years had an AAI in Construction Jobs of 2.3%.
This rate of growth ranked 16th among the 381 metropolitan areas for
the ten-year period.
graph shows the percentage increase or decline each year. You can see the
rate of growth is not absolutely stable.
While over the ten years it averages 2.3%,
there are obvious fluctuations year by year. In 2004
there was a 8.6% increase in
construction employment. However, in 2009 employment declined
8%. In 2013 there was an increase of 6.8%.
the average of the annual increases is 2.3%. However, the rate of growth is
not nearly as consistent as the Mythical Area. The growth line is not straight
but goes up and down.
the rate of growth of Construction Jobs for Fargois not absolutely
consistent, it is considerably more stable than the
Hammond, LA metropolitan area.
and the Mythical Area, Hammond had an average annual increase
of 2.3% over the ten years. As you can see in the graph, the rate of growth
was extremely volatile.
In 2005, Hammond gained 14%
and the next year gained 28.2%. in 2008
it lost 4.5% and lost 18.4% in 2009.
Yes, the average of
all of these years is 2.3%. How it happened
is considerably different than
relying upon economic growth percentages is not sufficient in order to
determine the character of a local economy. Economic stability must be
To measure economic
stability, the difference or deviation in each successive year's percentage
of growth is calculated (absolute number) and averaged, creating the Average
Deviation from Previous Year (DEV).
To determine the
measurable consistency of growth, the DEV is subtracted from the AAI. This
number is used for POLICOM's economic strength rankings. Inconsistent
economies area ranked lower than consistent economies.