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Manchester Grand Hyatt, Harbor E
Hosted By:
Labor and Employment Relations Association
Using Online Job Vacancy Data to Study Labor Market Dynamics
Paper Session
Sunday, Jan. 5, 2020 1:00 PM - 3:00 PM (PDT)
- Chair: Steven J. Davis, University of Chicago
Application Flows
Abstract
We build a new U.S. database that links 125 million applications to 7.5 million online job postings from 2012 to 2017. The raw data come from DHI Group, Inc., which owns and operates the Dice.com platform for posting vacancies and attracting applications. Postings fall mainly into computer-related occupations, technology sectors, financial services, and other occupations that require technical skills. Two of our key findings are hard to square with standard models of sequential employer search: First, the mean posting duration for single-position openings is 8.9 days, about one-fifth of the mean vacancy duration for comparable jobs in JOLTS data. Second, job seekers display a striking propensity to target new postings, directing two-fifths of applications to openings posted in the past 48 hours. In other findings, job seekers display high propensities to submit many applications on Day 1 of a given search spell and to submit additional batches of applications about once every seven days thereafter, with smaller application numbers in each successive batch. We also show that a major change in platform functionality during our sample period profoundly shifted the distribution of applications across different types of employers.Mismatch in Online Job Search
Abstract
Much attention has been paid to the potential of new private sector data sources as well as the challenges in using these new sources. In this paper we use data from a large online job search website in a way that can particularly complement existing data on the labor market. We focus on labor market mismatch which is an important measure of the health of the economy but is notoriously hard to measure since it requires detailed information on both employer needs and job seeker characteristics. Mismatch is measured as dissimilarity between the distribution of job seekers across a set of predefined categories and the distribution of job vacancies across the same categories. We produce time series measures of mismatch for the US, a set of English-speaking countries, US states, and select US sectors from January of 2014 through June of 2019. We find that title-level mismatch is substantial, hovering at about 33% for the US in the first half of 2019, but that it has slightly declined as the labor market has tightened. Furthermore, over the same time period the mix of job opportunities has shifted substantially but in a way that has made the distribution of jobs more similar to the distribution of job seekers.No Longer Qualified? Changes in the Supply and Demand for Skills within Occupations
Abstract
In this paper, we test the hypothesis that changes in skill requirements within some occupations have reduced matching efficiency within some classes of jobs and contributed to the outward shift in the Beveridge Curve since 2007. We find evidence that supports this hypothesis from a few different sources. First, we extend the framework developed by Sahin et al. (2014) to measure labor market mismatch, decomposing measures of mismatch by the education requirements of the underlying occupations. We find that between 2007 and 2017, high-skill occupations displayed higher mismatch rates than did either middle-skill or low-skill occupations, and high-skill occupations experienced a smaller decline in mismatch rates during the recent recovery. We also describe movements in employer education requirements over time using a novel database of 87 million online job posting aggregated by Burning Glass Technologies. These data offer evidence of relatively permanent upskilling within high-skill occupations, where such upskilling may reflect changes in the technologies that complement such jobs. Together the results suggest that the persistently lower matching efficiency among high-skill jobs may be an artifact of increasing skill requirements within jobs, rather than the result of changes in the relative demand for occupations. Our results imply that workers who accumulate specific human capital targeting a distinct labor market may be chasing a moving target, even as they achieve a high level of educational attainment. Furthermore, our findings suggest that workforce development strategies and education policies could benefit from the use of real-time labor market information on employer demands in the current environment.Discussant(s)
Tara Sinclair
,
George Washington University and Indeed Hiring Lab
Jim Albrecht
,
Georgetown University
JEL Classifications
- J6 - Mobility, Unemployment, Vacancies, and Immigrant Workers