Visualization: Occupational employment statistics

Salary data presented in an interactive visualization by occupation, and by metropolitan area.

This is an experimental visualization.

The Bureau of Labor Statistics, an agency of the United States Department of Labor, gathers data on employment and wages in a program titled Occupational Employment Statistics. BLS describes the program:

The OES program produces employment and wage estimates for over 800 occupations. These are estimates of the number of jobs in certain occupations, and estimates of the wages paid to them. These estimates are available for the nation as a whole, for individual States, and for metropolitan statistical areas (MSAs), metropolitan divisions, and nonmetropolitan areas; national occupational estimates for specific industries are also available. 1

OES data is gathered through a semi-annual mail survey of non-farm establishments. Data is released annually in May using three years of data to improve reliability. For example, “The May 2017 employment and wage estimates were calculated using data collected in the May 2017, November 2016, May 2016, November 2015, May 2015, and November 2014 semi-annual panels.” 2

OES jobs category illustration. Click for larger.

BLS presents data in a hierarchy. 3 At the tops are groups, like “13-0000 Business and Financial Operations Occupations” in the nearby example.

There are then one or more subgroups like “13-1020 Buyers and Purchasing Agents.” Then, there are actual occupations, like “13-1021 Buyers and Purchasing Agents, Farm Products” and “13-1022 Wholesale and Retail Buyers, Except Farm Products.”

Drilling down. Click for larger.
The visualization I created uses the hierarchical nature of the data: Groups, Subgroups, and Occupations. In the visualization, when you hover the mouse of a column heading, a “+” or “-” may appear. Click on these to expand or contract the data. This is also known as “drill down.”

In the Table by Area, the differential between each city and the highest-salaried city is shown in dollars and percent.

When looking at data using the Group or Subgroup level, the salary data is summarized by computing the average. This may not be the proper technique, and is why I classify this visualization as experimental.

Comparing average salaries for groups of occupations in different cities has problems. One is the number of workers in occupations. Considering management occupations, there are few chief executive officers but many other managers. The weight of the number of workers needs to be considered.

Also, the magnitude of salaries is an issue. Chief executive officer salaries vary widely, by tens of thousands of dollars. The data tells us that a CEO in Wichita earns $65,400 less than in Des Moines. That variation is greater than the average salary across all occupations.

Data is for the May 2017 release, the most current available.

Click here to access the visualization.

Example from the visualization. Click for larger.


Notes

  1. Bureau of Labor Statistics. Occupational Employment Statistics. Available at https://www.bls.gov/oes/oes_ques.htm#overview.
  2. Bureau of Labor Statistics. Occupational Employment Statistics. Available at https://www.bls.gov/oes/oes_ques.htm#overview.
  3. Bureau of Labor Statistics. May 2017 Occupation Profiles. Available at https://www.bls.gov/oes/current/oes_stru.htm.

Individual liberty, limited government, economic freedom, and free markets in Wichita and Kansas

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