Hearing About A Job: Networks, Information, and Segregation in Labor Markets

University Of Washington, Seattle WA

Investigators

Abstract

This project examines segregation in labor markets. Empirical evidence reveals that labor markets are often highly segregated with respect to ascribed attributes such as race, ethnicity, and gender. Most explanations of this segregation can be classified as either 'supply-side' (worker qualifications or preferences) or 'demand-side' (job requirements or discrimination by employers). Yet neither of these approaches addresses the structure of information that links potential workers and employers, or how actors evaluate the information they do acquire. This is unfortunate, since how potential workers hear about vacant jobs, and how employers view referred employees, are crucial parts of the hiring process that have implications for individuals' opportunities and, potentially, for the level of segregation in labor markets. We formalize information-related aspects of the matching process into two additional mechanisms. The first rests on constraints on access to information: if information about jobs flows only through networks linking potential workers, then the structure and composition of those networks will influence who hears about--and is hired into--vacant jobs, and networks composed of similar people could therefore produce and maintain segregation within jobs or firms, without any discriminatory action on the part of individual employers. Alternatively, if evaluating a candidate's potential is difficult, information from trusted employees may be more valuable than information from strangers. In this situation, employers may prefer to hire workers who are referred by their current employees; again, to the extent that networks are segregated, the labor market will be segregated. Previous scholars have found it difficult to tease apart the relative impact of each explanation in empirical studies; therefore, the core of this project is the development of a labor market simulation that allows us to implement each of these types of 'mechanisms' (supply-side, demand-side, and information-related) as a set of structures and a set of rules. We will calibrate the simulation model with data describing empirical labor markets and then use it as an experimental framework to generate testable hypotheses about the relationship between each mechanism, other labor market characteristics, and the level of segregation in particular types of labor markets. The project should have several broad impacts: it will demonstrate the utility of simulation method as a tool to address substantively important yet empirically difficult problems; insights from the simulation may be used to focus subsequent empirical studies; and, most importantly, we hope that this study will help us identify practical strategies that might effectively reduce racial, ethnic, and gender segregation in labor markets.