Seven academic papers using Burning Glass job-postings data, including two by Burning Glass Chief Economist Bledi Taska, were presented at the American Economic Association’s annual conference this past weekend. The topics ranged from demand for artificial intelligence skills in health care, changing skill demand in STEM hiring, the shifting goalposts for worker qualifications as the economy expands and contracts, and career pathways in the age of re-skilling and lifelong learning.
Established in 1885, the AEA is a nonprofit, nonpartisan, scholarly association dedicated to the discussion and publication of economics research, with a membership of over 20,000.
Real-time jobs data is now a frequent tool of economists, who see the data as providing a faster, more dynamic, and more granular view of the labor market compared to more traditional sources. Burning Glass’ database now includes more than 1 billion current and historical job postings and over 300 million resumes.
The AEA is one of 61 organizations represented at the massive Allied Social Sciences Associations meeting. For more information about the papers and the conference visit ASSA 2020.
Machine Learning and AI: “Machine Learning in Healthcare: Invention of a Method of Invention, General Purpose Technology, or Both?” by Avi Goldfarb, Florenta Teodoridis, and Bledi Taska analyzed several million online job postings to examine how organizations are hiring for machine learning expertise – especially in the health care field. Results showed that AI adoption in health care remains substantially lower than in most other industries, with roughly 1 in 1,250 hospital jobs, or under 3% of hospitals, requiring AI-related skills from 2015-2018.
Income Taxes and Labor Downskilling : “Personal Income Taxes and Labor Downskilling: Evidence from 27 Million Job Postings” by Murillo Campello, Janet Gao, and Qiping Xu focused on the “measurable, negative effects of local personal income taxes on the level of education, experience, and technological skills required by firms when hiring workers (downskilling).” The researchers were able to identify a tax-induced “brain-drain” in states with high personal income taxes, showing higher income taxes have a “detrimental effect on the skill composition of local labor markets.”
Labor Market Competitors: Yukun Liu, and Xi Wu are authors of “Labor Market Competitor Network and the Transmission of Shocks” In the paper, the authors used Burning Glass data to identify networks of companies that compete with each other in the labor market, even if they do not compete for customers. For example, technology and finance firms may compete for programmers but not in products. In fact, the paper showed that the “overlap between firms’ labor market competitors and product market rivals is less than 20 percent.” Findings showed that labor and industry shocks transmit along the network, that firm returns strongly respond to news about other labor-linked firms, and that financial crises such as the recent recession also affect non-financial firms through the labor network.
Persistent Change in Skill Demand: “Structural Increases in Skill Demand After the Great Recession” by David Deming, and Peter Q. Blair found that employer demand for education greatly increased during the Great Recession, and has remained persistently higher through 2019. Deming and Blair also found that professional, managerial, and technical occupations, as well as high-wage cities had the largest increase in educational requirements.
Occupational Mobility: “Occupational Mobility in a Changing Labor Market: Upward Climbs or Crooked Paths?” by Shulamit Kahn, Alicia Modestino, and Yeseul Hyun used 23 million resumes collected by Burning Glass to study occupational transitions over the course of individual careers, and whether transitions correlated with additional training or education, as well as by gender, age, region, and more. Using the resume data, the authors found mobility rates which are significantly higher than when using traditional data like CPS (9% vs 4%). Understanding the frequency and nature of occupational transitions may help guide workforce development policy aimed at re-training workers displaced by technological change.
Labor Market Power and Upskilling: “Concentration in United States Local Labor Markets: Evidence from Vacancy and Employment Data” by Brad Hershbein, Claudia Macaluso, and Chen Yeh characterized the impact of concentration in employment, job creation, and vacancy flows across U.S. local labor markets. Notable findings included “a 1% increase in local labor market concentration is associated with a 0.14% decrease in average hourly wages and an increase in the number of jobs requiring cognitive and social skills equal to 10-13% of the mean (“upskilling”).” The authors go on to discuss the implications of this research, and how the challenge of upskilling workers could be addressed.
No Longer Qualified: “No Longer Qualified: Changes in the Supply and Demand for Skills within Occupations” by Mary Burke, Alicia Modestino, Shahrir Sadighi, Rachel Sederberg, and Bledi Taska examined trends in employer requirements for educational achievement, and specific software skills between 2007 and 2017. Researchers found that upskilling—both in terms of degree requirements and demand for software skills—was “persistent” among high-skill jobs, contributing to occupational mismatch that lasted through economic recovery; by contrast, upskilling trends were either temporary or nonexistent among middle-skill and low-skill occupations, with labor market mismatch mostly eliminated within the low-skill and middle-skill sectors by 2017.
Academic researchers who want to know more about our data may contact our research department.