Using data from the Bureau of Labor Statistics’ Occupational Employment Statistics I put together the following tool to help identify the Metro areas that pay the highest salaries. The chart’s default setting is for all occupations in the “Computer and Mathematical Occupations” category. To view salaries in your industry select the appropriate “Occupation Category” from the drop down list on the right side of the page. To get salary details for a specific occupation you can then select a specific occupation from the “occupation” drop down list.
A couple of other notes on this dashboard:
- You might notice that some metro areas don’t have data prior to 2015. This is because the BLS did not historically collect data for those metro areas. This is the case for Montgomery County-Bucks County-Chester County, PA Metropolitan Division, Gettysburg, Chambersburg-Waynesboro, and several others.
- Some metro areas have been redefined over the years. For example, in 2000, Harrisburg-Carlisle included data for Lebanon. Starting in 2005 for this data set, the BLS collected data for Lebanon as a unique metro area.
- If you look at the primary state drop down filter you’ll notice that the dashboard contains data for a few metro areas from other states (CA, ME, NC, TN, TX, WA, and WI). I included these metros because I believe they have characteristics that make them useful comparisons to Lancaster. For a description of the logic I used see my original Lancaster County post.
- There is a filter option called “Data to Display”. By selecting “Total Employment” the dashboard will show the total estimated number of workers for the occupations selected. By selecting “Employment per 1000” the dashboard will display the number of people employed in that occupation per 1000 people employed. This essentially answers the question: “For every 1000 workers, how many are employed in a specific occupation?” It is particularly helpful in pointing out the relative concentration of workers in a specific industry or occupation. For example, Lancaster county averages about 10 employees in the “Computer and Mathematical Occupation” category. This is relatively low compared to Philly; Montgomery, Bucks, and Chester Counties; and even Harrisburg. The opposite is true when you look at Employment per 1000 in the “Farming, Fishing, and Forestry Occupations” category. A number of inferences can be made from this metric about local economies, and I plan to write a future post exploring them in more details.