Congrats Matt! Beyond well-deserved!

It's an amazing dataset. Thanks for your work on it!

We hope this paper opens the door to other researchers who want to explore related research questions! Instructions for accessing the API are here (www.census.gov/data/develop...) and there’s a R package for accessing the API as well (tidyqwi). 7/7

We also explore labor market trends by educator characteristics (e.g., race, ethnicity, educational attainment) and show that the education labor market is weaker for educators who are non-White and did not graduate college. Finally, we briefly explore variation in pandemic local labor markets. 6/7

Of course, education labor market measures typically compare a specific school year to the prior school year. We show that our procedure using QWI data produces labor market measures of turnover and net-negative job loss that are strongly correlated with state data (R>0.73). 5/7

BTW please send me related papers so that I can cite them. QWI measures are created using changes in quarter-to-quarter counts. For example, job leavers are the number of employees who worked at a specific school district in 2024 Q1 and then did not in 2024 Q2. 4/7

Our objectives with this paper are to (1) hype up the QWI dataset to everyone studying teacher/education labor markets and (2) to develop school year level measures that we create using the quarter level QWI data. There are shockingly few examples of K12 labor market research that uses the QWI. 3/7

In my view the QWI is a highly under used tool created by Census Bureau using worker level unemployment insurance data. I suspect this is because the most useful data is available only through the API and the QWI’s website obscures the depth/breadth of the publicly available data. 2/7

I hope we can agree that everyone is a winner when Dan Snyder is upset.