Do Higher Wages Reduce Knowledge Worker's Job Mobility? Evidence for Swedish Inventors

Abstract

Based on linked employer-employee panel data on all Swedish inventors, this paper analyses how wages affect inventors' job mobility. It is commonly assumed that higher wages reduce mobility because they reduce the value of outside opportunities. We argue that higher wages also send performance signals to potential employers, who raise their wage offers in response. By disentangling the effects of higher wages, we show evidence of a utility and an opportunity cost effect, which reduce mobility, and a performance-signalling effect, which increases mobility. In our data, the effects cancel each other out, with no effects of wages on mobility rates on average. We find, however, that for star inventors, who have sufficiently strong alternative performance signals (e.g., strong patent records), the performance signal sent by wages is crowded out by the alternative signals. Accordingly, for star inventors we find that higher wages decrease mobility.

Engineer/scientist careers: Patents, online profiles, and misclassification bias

“…Incumbent employers may reward and recognize engineers and scientists who achieve high productivity and impact in patents, and who contribute to teamwork (co‐inventorship). Our conjecture of targeted retention is supported by evidence that, in Sweden, star inventors are so highly compensated that their mobility is reduced (Ejermo and Schubert, ). It is related to employers' use of litigation to retain high‐value engineers and scientists (Ganco et al , ).…”

Knowledge Worker Mobility in Context: Pushing the Boundaries of Theory and Methods

“…We summarize the papers in the Special Issue in Table I. The papers reflect the different contextual dimensions of mobility, sometimes covering more than one aspect: organizational (Rocha, Carneiro and Varum, 2017;Park, Howard, and Gomulya, 2017;Brymer and Sirmon, 2017); geographical and spatial (Franzoni, Scellato and Stephan, 2017); social (Brymer and Sirmon, 2017;Daniel, DiDomenico and Nunan, 2017); and institutional and cultural (Rocha, Carneiro and Varum, 2017;Ejermo and Schubert, 2017;Franzoni, Scellato and Stephan, 2017).…”

“…These results suggest that, in certain contexts (e.g., pusheddriven startups), hiring former coworkers may be a choice partly driven by necessity, which may reduce the quality of initial human resources, and, consequently, limit future growth prospects, especially in rigid labor markets. learning-by-hiring theory (Franzoni, Scellato and Stephan, 2017;Park, Howard, and Gomulya, 2017), theory on mobility to spinoffs (Rocha, Carneiro and Varum, 2017), utility theory and matching theory in labour markets (Ejermo and Schubert, 2017), and context-emergent turnover (CET) theory (Brymer and Sirmon, 2017). The articles that we publish here also provide strong methodological contributions by incorporating a variety of methods and datasets including econometric modelling of firmlevel spin-off data (Rocha, Carneiro and Varum, 2017) or post-acquisition patent data (Park, Howard, and Gomulya, 2017), and large team-level, cross-country survey datasets (Franzoni, Scellato and Stephan, 2017).…”

“…The articles that we publish here also provide strong methodological contributions by incorporating a variety of methods and datasets including econometric modelling of firmlevel spin-off data (Rocha, Carneiro and Varum, 2017) or post-acquisition patent data (Park, Howard, and Gomulya, 2017), and large team-level, cross-country survey datasets (Franzoni, Scellato and Stephan, 2017). In addition to analyses of novel firm-level and team-level data, other studies in this special issue investigate their research questions using individual-level data such as the employer-employee dataset of Swedish inventors (Ejermo and Schubert, 2017), and the data of partners in US based law firms (Brymer and Sirmon, 2017). Lastly, we include an in-depth qualitative study in this issue (Daniel, DiDomenico and Nunan, 2017).…”

“…The papers push the theoretical boundary of the current literature on KWM by including a variety of theory testing and building. The special issue papers contribute to paradox theory (Daniel, DiDomenico and Nunan, ), knowledge combination and learning‐by‐hiring theory (Franzoni, Scellato and Stephan, ; Park, Howard, and Gomulya, ), theory on mobility to spinoffs (Rocha, Carneiro and Varum, ), utility theory and matching theory in labour markets (Ejermo and Schubert, ), and context‐emergent turnover (CET) theory (Brymer and Sirmon, ).…”