Using Network Analysis of Job Transitions to Inform Career
Advice
Name
clochard_axellecb_sm_tpp_eecs_2022.pdf
Description
Thesis PDF
Size
3.42 MB
Format
Adobe PDF
Checksum (MD5)
57fad4a649b407115d6e8a2e0b53ccbb
Author(s)
Clochard, Axelle
Advisor(s)
Westerman, George
O'Reilly, Una-May
Date Issued
February 2022
Publisher
Massachusetts Institute of Technology
Abstract
The importance of good career advice has become especially salient as the COVID-19 pandemic forces millions of displaced workers to look for stable employment. This research hopes to add to the career advice literature by using network analysis of U.S. job transitions data to model the universe of career paths available from a first job. By linking together the occupations that are connected by significant flows of workers and focusing on the paths that lead from precarious occupations, we can identify areas of the labor market that offer dependable channels to upward mobility and areas that do not, where workers could benefit from additional guidance. Overall, we find that, although there exist opportunities for workers of various educational attainment, upward mobility prospect are generally curtailed for workers without a Bachelor’s degree. What’s more, low-wage or shrinking occupations appear to offer limited access to stable, high-wage employment. Still, there are a number of bright spots occupations that can provide low-wage workers with dependable access to sustainable employment down the line. We hope to use this knowledge to inform the nature of advice given to workers by suggesting careers that are associated with living wages and stability in the long term.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
Massachusetts Institute of Technology. Institute for Data, Systems, and Society
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In Copyright - Educational Use Permitted
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