Project repo for data and society course (DAT 4500)!
Click the above title to read our final report!
- The Urban Institute data science team used data from the US Bureau of Labor Statistics, IPUMS 2012-2018 ACS microdata, and Urban’s 2018 Census LODES data, in order to estimate the number of low-income jobs lost because of COVID-19 by industry for every census tract in the US based on the residence of workers. Low income those with (<$40,000 salary).
- Within the data, it provides 20 names of the different work industries so that we can compare the job loss index by state and by county across the country and see how they're different to each other.
- The numbers represent the count workers who live in which state, county, and the CBSA (Core-based statistical area: which is the geographic area that consists of one or more counties) who lost their job.
- How did different states respond to the COVID-19 pandemic, and how do their responses impact the workfroce in the state?
- QoL: Quality of life index.
- LIJ: Low income jobs.
- QoL Index: We tried to explore the quality of life changes in every state between 2018 (pre-pandemic) and 2021 (mid-pandemic) in the hopes of finding some correlation between the quality of life of the whole state and the low income jobs lost due to COVID-19. Our exploration has not shown any significant correlation between quality of life and the LIJs lost. We also didn't find a strong correlation between fiscal stability, economic ranking, and the opportunity metric of each state and the estimated LIJs lost in the state.
- Demographics impacted by LIJs lost: We explored some patterns based on race and gender. After some analysis, we pivoted down a different path.
- Patterns in job loss by industry: We pivoted away from this path.
- Yarra A.
- Zach J.
- Janelle A.
- Timothy C.