Using Job Posting and Resume Data to Better Understand the Future of Work

Awarded Scholars:
Siwei Cheng, New York University
Michael Hout, New York University
Project Date:
Feb 2020
Award Amount:

Most research on the future of work relies on government survey data, which can identify economy-wide trends. But surveys lack detail about tasks and occupations that can reveal changes in how work is organized. Sociologists Siwei Cheng and Michael Hout will examine the nature of occupations, including the variation within categories and the connections across categories, to better understand how jobs organize tasks and coalesce into occupations. They will also investigate how occupations, in turn, function as signals of skills, tasks, opportunities for advancement, and job quality. Cheng and Hout will analyze millions of job postings and resumes collected by Burning Glass Technologies (BG) to address three aims: 1) they will create a detailed picture of the skill and task dynamics of the labor market by comparing the text of online job postings and incumbents’ descriptions of their jobs in survey data; 2) they will examine the trends and sources of various dimensions of job quality in existing and emerging occupations; and 3) they will use employment history on resumes to construct job-to-job transitions on the individual level and examine how the mobility of workers corresponds to the skill and task dynamics of the workplace and how these patterns vary by workers’ background characteristics.


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