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Economic Strength Rankings - 2012

By William H. Fruth 

Economic strength is the long term tendency for an area to
consistently grow in both size and quality.

2013 Economic Strength Rankings will be posted April 1, 2013.  This is two months earlier than normal.

Table for links regarding metropolitan area rankings.

 

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Rankings

Metropolitan Statistical Areas

Micropolitan Statistical Areas

Methodology

Definitions and Maps

State maps which show the geographic definitions of the metropolitan and micropolitan areas.

 

Definitions and Maps

Metropolitan Statistical Areas 

Micropolitan Statistical Areas

Combined Statistical Areas

Old Metropolitan Statistical Areas

     

POLICOM addresses the condition of an economy from the viewpoint of  it's impact upon the “standard of living” of the people who live and work in an area.

The economic strength rankings are created so POLICOM can study the characteristics of strong and weak economies. The highest ranked areas have had rapid, consistent growth in both size and quality for an extended period of time. The lowest ranked areas have been in volatile decline for an extended period of time.

POLICOM has created economic strength rankings for all Metropolitan Statistical Areas and all Micropolitan Statistical Areas.

Metropolitan Statistical Areas have at least one urbanized area with a population of at least 50,000, plus adjacent territory (counties) which have a high degree of social and economic integration with the core as measured by commuting ties. They must have at minimum one county but most often include several counties.

There are 366 Metropolitan Statistical Areas (MSA).

Micropolitan Statistical Areas did not exist prior to the new definitions.

Once looked upon as quasi rural areas, a Micropolitan Statistical Area must have an urbanized area (city) with a population of at least 10,000 but less than 50,000 population. They must be at least one county and most are. The OMB has identified 576 MICROS in the United States.

Economic Strength Methodology
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The formulas 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 Residences
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 - Earnings
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 Maintenance (Welfare)
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 high basis.

The Ames, IA MSA had the 4th highest percentage growth rate (12.1%) in Per Capita Income Maintenance from 2000 – 2009 among the 366 areas. However, its Per Capita Income Maintenance in 2009 was $368, ranking 358th. While the rate of growth is high, “twice nothing is still nothing.”

The reverse is also sometimes true. The McAllen-Edinburg-Mission, TX MSA has the highest Per Capita Income Maintenance ($1,525) among the metropolitan areas, but it growth rate of 6.5% ranked 307th.

There are, of course, the extremes. The Springfield, MA MSA had the 19th fastest growth rate (10.8%) and also has the 14th highest actual Per Capita Income Maintenance of $1,182.

If only these criteria were used, the example MSA’s would be ranked in the following order: Ames, McAllen, and Springfield.

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 the data.

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 timers.

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 rankings.

The average annual increase is calculated for each of the items for three time periods. (2010 data was released by the Bureau of Economic Analysis in April, 2012)

Last five years: 2010-2006 – Weighted once.
Last ten years: 2010-2001 – Weighted twice.
Previous Ten Years: 2000-1991 – 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 in size.

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

Simply identifying 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 percentage increase.

The first graph depicts a Mythical Area, which had an Average Annual Percentage Increase (AAI) in Construction Jobs of 2.5% from 2001 through 2009 (2001 is the first year NAICS based data was published). 

Mythical Area had a 2.5% increase from 2002 to 2003.  From 2003 to 2004 it again had a 2.5% increase. Each and every year, the area increased exactly 2.5%. This means construction employers, each and every year, increased the number of people they employed by 2.5%.

As a result, by averaging the nine-year history, the Mythical Area, obviously, had a 2.5% average annual percentage increase (AAI).

Most importantly, 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 Great Falls, MT MSA for the same element. Great Falls, during the same nine years had an AAI in Construction Jobs of 2.5%. This rate of growth ranked 35th highest among the 366 metropolitan areas for the nine-year period.

The graph shows the percentage increase or decline each year. You can see the rate of growth is not absolutely stable.

While over the nine years it averages 2.5%, there are obvious fluctuations year by year. From 2001-2002, there was a 7.5% decline in construction employment. The next year a 6.2% increase. The next year a 6.3% increase, so on and so forth.

For the nine years, the average of the annual increases is 2.5%. However, the rate of growth is not nearly as stable as the Mythical Area. The growth line is not straight but goes up and down.

While the rate of growth of Construction Jobs for Great Falls is not absolutely consistent, it is considerably more stable than the Sebastian – Vero Beach, FL metropolitan area.

As with Great Falls and the Mythical Area, Sebastian – Vero Beach had an average annual increase of 2.5% over the nine years. As you can see in the graph, the rate of growth was extremely volatile.

From 2001-2002, the Sebastian – Vero Beach area gained 11%, the next year gained 21%, then 14% then 20%. However, in 2007 it lost 16% of its construction jobs, then 15%, then 21%.

Yes, the average of all of these years is 2.5%.  How it happened is considerably different than Great Falls.

Obviously, simply relying upon economic growth percentages is not sufficient in order to determine the character of a local economy. Economic stability must be considered.

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.

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