Occupation earnings data comes from the BLS’s OES dataset. It is collected from the employer’s perspective, meaning earnings data is pre-tax (individual employees’ tax withholdings will vary, so earnings are reported pre-tax). Because it is collected from the employer’s perspective, earnings data is also counted by the place of the employee’s work, not the employee’s residence. Occupations have average hourly earnings as well as percentile earnings for five percentiles (10th, 25th, 50th (median), 75th, and 90th).
Average earnings are determined by dividing the total earnings for the occupation by the number of jobs in the occupation. Percentile earnings indicate what percent of the jobs in the occupation earn that amount or less. For example, 10th percentile earnings of $12/hr. indicate that 10% of the workers in that occupation make $12/hr. or less. Median earnings of $15/hr. would mean that half of workers in that occupation make more than $15/hr., and half make less than $15/hr. 10th percentile earnings are often used as a proxy for entry level wages, as they represent some of the lowest earnings in the occupation.
Earnings are reported in terms of hourly income rather than annual income for all but a handful of occupations. For occupations with earnings reported annually, we divide by 2080 (number of hours in a working year) to determine hourly earnings.
Occupation earnings include the following:
Cost of living allowances
Occupation earnings do not include the following:
Holiday premium pay
Jury duty pay
Meal and lodging payments
Weekend premium pay
OES provides definitions for all the categories listed above.
Canada source: Lightcast’s industry data, regional occupation data from the Labour Force Survey (LFS), and regional staffing patterns taken from the Census.
A Word about Percentile Earnings
Various reports within Lightcast’s Analyst and Developer tools allow users to combine occupation percentile earnings for various occupations or regions. These combinations are powered by a proprietary occupation aggregation methodology that represents the combined wage curves of various occupations better than a weighted average. For this reason, users should not expect to be able to combine percentile earnings by hand and match combined percentile figures as displayed in Analyst. More information on Lightcast’s occupation percentile earnings aggregation can be found here.
Source: Lightcast’s proprietary employment data, relying heavily on occupational earnings reported in OES.