Employment per 1,000 jobs and location quotient

Wages tell you what an occupation pays in a place; two other OEWS figures tell you how much of that place’s workforce does the job. Both appear on the state and metro pages of this site, and both are published directly by BLS, not derived here.

Employment per 1,000 jobs

This is the number of workers in an occupation for every 1,000 jobs in the area, across all occupations. BLS computes it as the occupation’s employment in the area divided by total employment in the area, multiplied by 1,000. An area with 2 million jobs and 40,000 registered nurses has 20 registered nurses per 1,000 jobs.

The figure is useful because raw employment is dominated by area size. California has more of almost every occupation than Wyoming does. Per-1,000 figures remove size and leave composition: what share of the area’s work is this kind of work. BLS publishes the measure for states and metropolitan areas; nationally it is blank, because the national figure is the base everything else is compared with.

Location quotient

The location quotient goes one step further and compares the area’s share with the nation’s. It is the occupation’s share of area employment divided by the occupation’s share of national employment. A location quotient of 1.0 means the occupation is exactly as common in the area as in the country as a whole; 2.0 means twice as common; 0.5 means half as common.

Because the national share is the denominator, the national location quotient of every occupation is 1.0 by construction, and BLS leaves it blank in the national file.

Reading the values

Large values mark specialization. Petroleum engineers in Texas, actuaries in Connecticut, or gaming dealers in Nevada show location quotients well above 2, meaning the state’s economy employs those occupations far more intensively than the country does. The “most concentrated occupations” list on a state page is sorted by this measure.

Small values mark relative absence. A location quotient below 0.5 for an occupation that exists everywhere, such as retail salespersons, would be surprising; for an occupation tied to a resource or an industry cluster it is normal.

Two cautions. First, a high location quotient does not mean high employment: a small state can have a quotient of 3 for an occupation with a few hundred workers. Read the quotient alongside employment. Second, the measure is about jobs, not wages. An area can be highly specialized in an occupation and pay it less than average, or the reverse. The occupation pages show the top-paying and highest-employing states separately for that reason.

Where the numbers come from

Both measures are computed by BLS from the same OEWS estimates as the wages, so they carry the same sampling error and the same coverage limits: wage and salary workers in nonfarm establishments, around May of the reference year. Where employment for an occupation in an area is withheld, both measures are withheld with it; see suppressed cells.

How they are used on this site

The state and metro pages list the occupations with the highest location quotient as “most concentrated here,” and the occupation pages list the states with the highest and lowest employment per 1,000 jobs. The explorer shows the published location quotient as a column. Nothing is recomputed from employment totals on this site; the published value is shown, with the reference month, or left blank where BLS left it blank.

The measures answer a different question from pay. If you want to know where a job is, read these two. If you want to know what it pays there, read the percentile table, and remember that the minimum wage in the state sets a floor under the bottom of it.