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The most difficult thing about working with BLS data is gaining a clear understanding on what data are available and what they represent. Some of the more popular data sets can be found on the BLS Databases, Tables & Calculations website. The selected examples below do not include all series or databases.
The first step in analyzing any of these data in R is to install the blscrapeR package from CRAN.
Current Population Survey (CPS)
The CPS includes median weekly earnings by occupation, among other things.
For example, we can use blscrapeR to pull data from the API for the median weekly earnings for Database Administrators and Software Developers.
Occupational Employment Statistics (OES)
The OES contains similar wage data found in the CPS, but often has more resolution in certain geographic areas. Unlike the CPS, the OES is an annual survey and does not keep time series data.
For example, we may want to compare the average hourly wage of Computer and Information Systems Managers in Orlando, FL to those in San Jose, CA. Notice, below the survey only returns values for 2015.
Another OES example would be to grab the most recent Annual mean wage for All Occupations in All Industries in the United States.
Employer Cost for Employee Compensation
This data set includes time series data on how much employers pay for employee benefits as a total cost and as a percent of employee wages and salaries.
For example, if we want to see the total cost of benefits per hour work and also see what percentage that is of the total compensation, we could run the following script.
National Compensation Survey-Benefits
This survey includes data on how many Americans have access to certain benefits. For example, we can see the percentage of those who have access to paid vacation days and those who have access to Health insurance through their employers.
If you want more mapping options, there is more information in the blscrapeRpackage vignettes.
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