Using job histories from millions of individuals, scientists have created the world’s first labor flow map. They propose that the map offers valuable insights into global economic growth.
Researchers at Indiana University in the United States teamed up with LinkedIn, the world’s largest professional networking platform, to produce the map.
The study analyzed employment data from more than 500 million LinkedIn users. Credit: pixabay 2297835
They suggest that the study reveals extensive links between people and industries around the world.
The team describes the work in a recent Nature Communications paper.
Labor flow map spans 4 million firms worldwide
The study used 25 years of employment histories from more than 500 million LinkedIn users who underwent a total of 130 million job changes.
From that massive amount of data, the team created a labor flow map spanning 4 million firms around the world.
The map “captures individual-level labor flow between firms across the world.”
The researchers suggest that the new tool will help the study “geo-industrial clusters” such as Silicon Valley and Wall Street in a novel way.
Policymakers, for example, could use the labor flow map to help overcome skill gaps and link workers to new local opportunities.
The theory behind the map is that the movement of workers from job to job is a key driver of geo-industrial clusters, “thanks to knowledge spillover and labor market pooling.”
The researchers were surprised to find some unexpected links between economic sectors.
For example, they found that the credit card and airline industries have some strong connections.
Definition and structure of geo-industrial clusters
One of the issues the team had to address when developing the labor flow map was to revisit the definition of geo-industrial cluster.
They found that the conventional use of the term did not properly reflect the whole global economy.
Often, researchers tend to confine the study of a geo-industrial cluster to a group of firms in a particular geographic area, without considering connections to other clusters.
In the new study, the investigators widened the idea of the geo-industrial cluster to encompass relationships with other clusters. They see it as an important part of understanding the whole picture.
Another important feature of the labor flow map is that it examines the hierarchical structure of geo-industrial clusters.
It shows that geo-industrial clusters feature stronger links between the “influx of educated workers and financial performance” than what you see in more traditional groupings.
“Furthermore,” note the authors, “our analysis of the skills of educated workers reveals richer insights into the relationship between the labor flow of educated workers and productivity growth.”
The team used the labor flow map to identify growing and declining industries between 2010 and 2014.
For example, tracking the flow of team management and project management skills showed that pharmaceutical and oil and gas industries grew in that period, while retail and telecommunications industries waned.
First study author Jaehyuk Park, of the School of Informatics, Computing, and Engineering at Indiana University, says in a blog post that the labor flow map should help to “verify the importance of region and industry in labor mobility.”
He also envisages the map being useful in studies of the relationship between different skills, patterns of movement among workers with similar skills, and how the skills flowing into a geo-industrial cluster relate to its growth.
As well as the study paper, Park’s blog post contains a detailed graphic illustration of how the labor flow map reveals specific features of geo-industrial clusters.