Mapping employee mobility and employer networks using professional network data - Patrick Breithaupt; Hanna Hottenrott; Christian Rammer; Konstantin Römer (ZEW - Leibniz-Zentrum für Europäische Wirtschaftsforschung, 2023)
The availability of social media data is growing and represents a new data source for economic research. This paper presents a detailed study on the use of data from a careeroriented social networking platform for measuring employee flows and employer networks. The employment data are exported from user profiles and linked to the Mannheim Enterprise Panel (MUP). The linked employer-employee (LEE) data consists of 14 million employments for 1.5 million employers. The platform-based LEE data is used to create annual employer networks comprised of data from 9 million employee flows. Plausibility checks confirm that career-oriented social networking data contain valuable data about employment, employee flows, and employer networks. Using such data provides opportunities for research on employee mobility, networks, and local ecosystems' role in economic performance at the employer and the regional level.
Keywords: C81; J60; L14; 330; social networks; platform data; lee data; labour mobility; network analysis