by Sanjukta Chaudhuri
DEED’s capacity to communicate detailed labor market data has recently been greatly enhanced by an inter-agency collaboration with the Minnesota Department of Public Safety. The agreement grants DEED access to age and gender data which we can link to the administrative records of Minnesota's Unemployment Insurance program. The outcome is a brand new and unique dataset spanning a 13 year time frame (2003-2015), with quarterly data on demographic, regional, and labor force variables. This new dataset will enable the LMI office to bring to stakeholders demographic labor market data that previously had only limited availability. The use of this dataset will follow strict codes of confidentiality of information. Only medians will be calculated and published.
Taking advantage of the new dataset, the LMI office is working energetically towards launching a new data tool - Quarterly Employment Demographics (QED). To be unveiled in the coming months, the QED is being designed as a four step guided process that will allow users to customize, extract, and view quarterly employment demographics for Minnesota.
What the QED data tool will provide: The QED data tool will display percent job distribution, median hourly wage, and median hours per quarter. This information will be summarized by quarter and annual total, and users can choose how they want to see the data presented by selecting from a range of possible combinations of four variables – region, year, demographic group (age or gender), and industry.
As an example, if the selections made in the four steps are Minnesota (region), 2015 (year), male and female (demographic-gender), and Education and Health Services (industry), then the following information will be displayed:
|Table 1. Example of QED data tool display|
|Education and Health Services|
|Year/QTR||Median hourly wage ($)||Median hours per quarter|
The new dataset will reveal important historical trends in industry, geographical and employment patterns, wage trends, and labor market churn. Quarterly analysis at the new more granular level will be possible, and this has the significant advantage of revealing underlying seasonal patterns of the labor market not previously available.