RESEARCH COLLOQUIUM ON COMPUTATIONAL SOCIAL SCIENCE/DATA SCIENCES – Katherine Anderson – Skill Networks and Measures of Complex Human Capital

October 25, 2019 @ 3:00 pm – 4:00 pm
Karen Underwood

Research Colloquium on Computational Social Science/Data Science

Katherine Anderson
Visiting Assistant Professor
Department of Informatics and Networked Systems
School of Computing and Information
University of Pittsburgh

Skill Networks and Measures of Complex Human Capital

Friday, October 25, 3:00 p.m.
Center for Social Complexity Suite, 3rd Floor Research Hall

All are welcome to attend.

The relationship between worker skills and wages is a problem of tremendous economic interest, making it critical to have effective measures of the skills, knowledge, and experience that a worker brings to production: a bundle of worker characteristics that economists refer to as human capital. Traditional models of human capital measures either divide workers into broad categories (e.g., laborers and management) or treat skills as a uni-dimensional measure of speed, education, or experience. However, in knowledge based production, the value a worker brings to production depends on both her individual skills and the interaction between them. Here, I present a network-based method for characterizing worker skills. I construct a human capital network, in which nodes are skills and two skills are connected if a worker has both or both are required for the same job. A worker’s human capital can be measured according to the position of her skills on the network. I illustrate this method using a novel dataset, gathered from an online freelance labor market. I show that workers with diverse skills earn higher wages than their peers with more specialized skills, and that those who use their diverse skills in combination earn the highest wages of all. I also show that network-based measures of human capital capture variation in wages beyond that captured by the skills individually. Finally, I will show how these same techniques can be used outside of the economic context, to quantify the relationship between the skills of collaborators.
Kate is a visiting assistant professor at the University of Pittsburgh Department of Informatics and Networked Systems, in the School of Computing and Information. She uses the tools of network analysis and computational modeling to look at how skills and ideas interact in collaborative environments.