WH ERE T H E J O BS A R E
Using the job search
capability, it is possible
to do a keyword search
for all currently listed
positions within a
distance of a zip code.
While poking around
using the Sutton’s Law
approach might be a
useful start, a more
systematic approach
seems appropriate.
The idea of a metropolitan area seemed to
be a good place to start, but what does that include (or leave out)? The U.S. government’s Office of Management and Budget (OMB) defines
a number of statistical areas that might provide
a useful framework. There are 388 metropolitan
statistical areas (MSAs) with population greater
than 50,000, and 541 micropolitan statistical areas (mSAs), with population between 10,000
and 50,000. There is also a grouping of adjacent
MSAs and mSAs based on social and economic
ties and incorporate commuting patterns; these
169 combined statistical areas (CSAs) seemed
a good place to start, but initial exploration revealed that this list does not include MSAs that
have only one urban core and therefore omits
places like San Diego, Calif., Phoenix, Ariz.,
Tampa, Fla., and San Antonio, Texas. As these
locations may be of interest to jobseekers in the
analytics field, another approach is warranted.
Further searching revealed a list of 574 (unofficial but commonly used) groupings called primary statistical areas (PSAs), which include all
169 CSAs, 122 (of the 388) MSAs, and 283 (of
the 541 mSAs). As this assemblage seems to
have been developed for studies like this one, the
569 PSAs in the United States (but not Puerto
Rico) were considered in this analysis.
LET’S COLLECT SOME DATA
While LinkedIn provides a straightforward
search capability (for people, groups and jobs),
there is also an advanced search capability.
Exploring the advanced query indicates that a
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