Big data and the labor market: A text-based analysis of job vacancies and skill requirements

Project Summary:

The polarization of the labor market into high- and low-skill jobs is one of the most popular explanations for the increase in income inequality. This project will explore how much skill polarization actually happened by creating a novel new dataset of job openings by skill level spanning multiple decades. The researchers will create these data by mining the text of job advertisements in newspapers and online job sites. The new data will help researchers better understand the change in skill requirements for jobs over the long run, as well as changes during recoveries and economic expansions. This research will improve our understanding of how inequalities in human capital contribute to broader economic inequality.


Daniel Tannenbaum is a postdoctoral scholar at the Becker Friedman Institute at the University of Chicago. His primary research fields are focused on labor economics, public economics, and experimental economics. He received his Ph.D. in economics from the University of Chicago in 2014, and received a B.A. in economics and mathematics from Columbia University.