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

这个项目考察了劳动力市场中的种族隔离。经验证据表明，劳动力市场往往在种族、民族和性别等归因性属性方面高度隔离。对这种隔离的大多数解释可以归类为“供应方”(工人资格或偏好)或“需求方”(工作要求或雇主歧视)。然而，这两种方法都没有涉及将潜在工人和雇主联系起来的信息结构，或者参与者如何评估他们确实获得的信息。这是不幸的，因为潜在员工如何得知空缺职位，以及雇主如何看待被推荐的员工，这些都是招聘过程中的关键部分，对个人的机会产生影响，并可能影响劳动力市场的隔离程度。我们将匹配过程中与信息相关的方面正式化为两个附加机制。第一个是对信息获取的限制：如果关于工作的信息只通过连接潜在工人的网络流动，那么这些网络的结构和组成将影响谁听说--并被雇用--空缺职位，因此，由相似的人组成的网络可以在工作或公司内部产生并保持隔离，而不会出现个别雇主的任何歧视性行动。或者，如果很难评估候选人的潜力，那么来自值得信赖的员工的信息可能比来自陌生人的信息更有价值。在这种情况下，雇主可能更愿意雇佣由现有员工推荐的工人；同样，在网络被隔离的情况下，劳动力市场也将被隔离。以前的学者发现，在实证研究中很难区分每种解释的相对影响；因此，这个项目的核心是开发一个劳动力市场模拟，允许我们将这些类型的机制(供给侧、需求侧和信息相关)中的每一种作为一套结构和一套规则来实施。我们将使用描述经验劳动力市场的数据来校准模拟模型，然后将其用作实验框架，以生成关于每种机制、其他劳动力市场特征和特定类型劳动力市场隔离程度之间的关系的可检验假设。该项目应该有几个广泛的影响：它将展示模拟方法作为一种工具的实用性，以解决实质上重要但在经验上困难的问题；从模拟中获得的见解可能被用于关注后续的实证研究；最重要的是，我们希望这项研究将帮助我们确定可能有效地减少劳动力市场中种族、民族和性别隔离的实用策略。

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.