Despite a large amount of empirical evidence about discrimination in labor markets, the underlying mechanisms that result in lower earnings for women and other groups remain poorly understood. Part of the problem relates to methodological limitations for teasing out the complexities of various labor market dynamics. In particular, the inability to directly observe hiring and salary bargaining practices limits the ability to make causal inferences about the determinants of labor market outcomes. For example, to what extent are gender pay gaps driven by discrimination by employers or by differences in bargaining strategies and career preferences between men and women?
Online labor platforms provide a unique looking glass through which to examine these questions. This projects examines the dynamics of hiring and resulting wages in digital platforms for contract work. In particular, it seeks to understand the mechanisms that result in differentiated gains for workers depending on gender and country of origin. The methodology combines big data analytics with traditional survey and experimental methods. The results seek to contribute to theorizing about information signals in labor markets as well as policy debates about work in the digital economy.
This project is funded by the International Development Research Centre (IDRC – Canada), and is implemented in collaboration with the Center for Distributive, Labor and Social Studies (CEDLAS) at Universidad Nacional de La Plata (UNLP) in Argentina.