Written by: Heath Hayward
Do you need information on the changing composition of the workforce through the recent recession? Or evidence of the job creation ability of young firms? Answer questions like these and many more with the Quarterly Workforce Indicators (QWI) dataset available through the new Local Employment Dynamics (LED) Extraction Tool.
The LED Extraction Tool makes all 30 indicators (which include measures on employment, turnover, hiring, job creation, job destruction, average monthly earnings, and many more) available through an intuitive query-building interface. Rather than having to download large and cumbersome tables from the Virtual Research Data Center on the Cornell University’s website, users can now extract the exact rows they need for analysis directly from the Census Bureau.
Economic development analysts, policy-makers and academics can analyze the raw comma-separated value (csv) QWI data by geography (i.e. State, County, Metro/Micro Area, or Workforce Investment Area), firm characteristics (i.e. firm age/size and industry classification), worker characteristics (i.e. age, sex, race, ethnicity, educational attainment), and time. Users can extract geographic or industry clusters in a few simple steps without having to download entire raw data files.
What are Quality Workforce Indicators used for?
These data have played a significant role in uncovering demographic and longitudinal trends in the nation’s changing labor force. A recent study by the Ewing Marion Kauffman Foundation using QWIs found that young firms are leading the recovery through increased hiring and job creation. Another study done by Oregon Employment Department utilized QWI data by examining the changes in Oregon’s employment by gender through the recession and subsequent recovery. In addition, an article in Local Insights, which is a publication that provides economic and labor market analysis of the Wasatch Front North Area in Utah, addressed different aspects of the educational attainment of workers, including the industry to which they are attached, the average monthly wages, and wage differences according to gender.
In future updates, other data products showing local employment dynamics will be made available through the LED Extraction Tool, including the LEHD Origin-Destination Employment Statistics (LODES) dataset/ If you would like to learn more, visit the LEHD homepage.