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

听说一份工作：劳动力市场中的网络、信息和隔离

• 批准号: 0351834
• 负责人: Katherine Stovel
• 金额: $ 14.85万
• 依托单位: University of Washington
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2004
• 资助国家: 美国
• 起止时间: 2004-04-01 至 2006-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0351834&HistoricalAwards=false
• 关键词: Hearing; About; Job; Networks; Information

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.

该项目研究劳动力市场中的隔离情况。 经验证据表明，劳动力市场往往在种族、民族和性别等固有属性方面存在高度隔离。 对这种隔离的大多数解释可以分为“供给方”（工人资格或偏好）或“需求方”（工作要求或雇主歧视）。 然而，这些方法都没有解决连接潜在工人和雇主的信息结构，或者参与者如何评估他们确实获得的信息。 这是不幸的，因为潜在工人如何得知空缺职位，以及雇主如何看待推荐的员工，是招聘过程的关键部分，影响个人的机会，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形式化为两个附加机制。 第一个依赖于信息获取的限制：如果有关工作的信息仅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聘用空缺职位，并且由相似的人组成的网络因此可以在工作或公司内部产生和维持隔离，而个体雇主不会采取任何歧视性行动。 或者，如果评估候选人的潜力很困难，那么来自受信任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，雇主可能更愿意雇用由现任雇员推荐的工人；同样，如果网络被隔离，劳动力市场就会被隔离。 先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，该项目的核心是开发劳动力市场模拟，使我们能够将每种类型的“机制”（供给方、需求方和信息相关）实施为一组结构和一组规则。 我们将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，以生成有关每种机制、其他劳动力市场特征以及特定类型劳动力市场的隔离程度之间关系的可检验假设。 该项目应该具有几个广泛的影响：它将展示模拟方法作为解决实质性重要但经验上困难的问题的工具的效用；模拟的见解可用于集中后续的实证研究；最重要的是，我们希望这项研究能够帮助我们确定可以有效减少劳动力市场中种族、民族和性别隔离的实用策略。