About Quarterly Employment Demographics
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The QED data tool displays percent job distribution, median hourly wage, and median hours per quarter by gender and age cohort. Users can select from a range of possible combinations to compare employment conditions by gender and age across regions, time and industries.
The use of administrative records for economic analysis has grown dramatically as a source of information that is often more detailed than what is available from sample-based surveys. DEED’s Labor Market Information Office has been providing employment and wage data compiled from administrative Minnesota Unemployment Insurance Program records at extremely detailed levels for years.
A data sharing agreement with the Minnesota Department of Public Safety (DPS) allows us to link these employee records with the date of birth and gender data contained in driver’s license records. This provides information on the demographic characteristics of our workforce that has not been available before.
The impact that an aging population is having on our labor markets is a topic of considerable importance. These linked data allow the user to identify which regions (counties, planning regions and economic development regions) and industries are likely to be impacted most severely by this demographic trend by virtue of having larger shares of their workforce in the older age cohorts.
Gender differences in earnings and hours worked are also a vital issue. Here again, comparisons across regions and industries provide information on where gender pay gaps are most acute.
The availability of such detailed information on the demographic characteristics of our workforce also illustrates the importance of administrative records for economic analysis, and the benefits of secure, limited interagency sharing of these administrative records.
By linking DEED employment records with DPS driver’s license records in a way that ensures strict adherence to confidentiality requirements, we are now able to provide clear answers to significant questions that we had to guess at previously.