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Economic Strength Methodology      
2017 Metropolitan Area Rank      
2017 Micropolitan Area Rank      

2017 Economic Strength Rankings - Methodology

  • Data from 1996 to 2015 was used to create the 2016 rankings.

  • Based upon area definitions as of January 1, 2017.

Click the links in the header above to review the rankings and definitions for the Metropolitan and Micropolitan areas. These are large files and might not load immediately.

OLICOM 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 382 Metropolitan Statistical Areas (MSA) as of January 1, 2017.

Micropolitan Statistical Areas are typically quasi rural areas. A Micro must have an urbanized area (city) with a population of at least 10,000 but less than 50,000 population and must be at least one county and most are. The OMB has identified 551 Micropolitan Areas in the United States.

Click the links in the header above to review the rankings and definitions for the Metropolitan and Micropolitan areas.

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2017 Economic Strength Rankings

Current Area Definitions
Used for 2017 Rankings

Economic Strength Methodology

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 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 - 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 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 Flint, MI 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 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. (2015 data was released by the Bureau of Economic Analysis in October of 2015)

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 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 2.3% from 2004 through 2013. 

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).

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 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.

The 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%.

For the ten years, 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.

While the rate of growth of Construction Jobs for Fargois not absolutely consistent, it is considerably more stable than the Hammond, LA metropolitan area.

As with Fargo 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 Fargo.

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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