I thought it would be interesting to look at some other occupational categories and see how their experiences compared. So I turned to the same database, the Occupational Employment Survey, and identified the metros where occupations in education exceeded 10 percent of the wage-and-salary workforce; where computer and mathematical occupations exceeded 5 percent; and where engineering occupations exceeded 4 percent.
Here are the metros where these occupations dominate:
Metro
Area
|
Education
Occupations |
Ithaca,
NY
|
15.5%
|
Gainesville,
FL
|
13.3%
|
Hinesville-Fort
Stewart, GA
|
13.2%
|
Champaign-Urbana,
IL
|
12.9%
|
Corvallis,
OR
|
12.8%
|
Blacksburg-Christiansburg-Radford,
VA
|
12.3%
|
Merced,
CA
|
11.7%
|
Lafayette,
IN
|
11.5%
|
College
Station-Bryan, TX
|
10.8%
|
Auburn-Opelika,
AL
|
10.7%
|
Ann
Arbor, MI
|
10.6%
|
Athens-Clarke
County, GA
|
10.5%
|
Yuba
City, CA
|
10.4%
|
McAllen-Edinburg-Mission,
TX
|
10.4%
|
Metro
Area
|
Computer
&
Mathematical Occupations |
San
Jose-Sunnyvale-Santa Clara, CA
|
11.6%
|
Washington-Arlington-Alexandria,
DC-VA-MD-WV
|
7.4%
|
Boulder,
CO
|
6.7%
|
Seattle-Tacoma-Bellevue,
WA
|
6.6%
|
Huntsville,
AL
|
6.5%
|
Durham-Chapel
Hill, NC
|
6.2%
|
Austin-Round
Rock-San Marcos, TX
|
5.7%
|
Trenton-Ewing,
NJ
|
5.5%
|
San
Francisco-Oakland-Fremont, CA
|
5.5%
|
Madison,
WI
|
5.5%
|
Raleigh-Cary,
NC
|
5.2%
|
Colorado
Springs, CO
|
5.1%
|
Metro
Area
|
Engineering
Occupations |
Huntsville,
AL
|
8.3%
|
Columbus,
IN
|
8.1%
|
San
Jose-Sunnyvale-Santa Clara, CA
|
5.7%
|
Warner
Robins, GA
|
5.2%
|
Norwich-New
London, CT-RI
|
5.0%
|
Bremerton-Silverdale,
WA
|
5.0%
|
Kennewick-Pasco-Richland,
WA
|
4.8%
|
Palm
Bay-Melbourne-Titusville, FL
|
4.5%
|
Detroit-Warren-Livonia,
MI
|
4.4%
|
Holland-Grand
Haven, MI
|
4.3%
|
Next, I graphed the 2007–2014 earnings of professionals in the metros where they are concentrated and also nationwide. Here’s what I found:
The most obvious common element is that the workers in all of the occupationally-concentrated metros experienced earnings downturns during the recession years, whereas across the nation the same kinds of workers experienced no such downturns. Therefore, it appears that what I found for health-care workers last week is not unique to them. Perhaps any concentration of a particular type of worker (and therefore of an industry) increases the wage instability of a metro area.
But I found one interesting way in which the experiences of
these occupations differed: For health-care and education professionals, average
wages were higher nationwide than in the metros where the workers are
concentrated. On the other hand, for computer and engineering professionals,
areas where the workers are concentrated offer higher wages.
This finding is consistent with what the urban theorist Richard
Florida has written about the “creative class”: Highly creative workers,
such as engineering and computer professionals, tend to be most productive where
they can work collaboratively. That is why, even with the marvels of 21st-century
communication, the industries that employ creative workers tend to concentrate
geographically. Thus we find Silicon Valley for high tech, Hollywood for
movies, and Nashville for music. And where these workers are concentrated and
more productive, they earn more. The same does not seem to be true for
educators and health-care professionals.
I’m not saying that educators and health-care professionals
are not creative, but the nature of their work does not demand constant
creativity to the degree that engineering and computer careers do. As a result,
concentration of these workers may actually lower wages by increasing competition.