Doctoral Dissertation Research in Economics and Public Policy: Employer Preference for Applicants based on Geographic Location - A Resume Audit

经济学与公共政策博士论文研究：基于地理位置的雇主对申请人的偏好 - 简历审核

• 批准号: 2018750
• 负责人: Brian Kovak
• 金额: $ 3.9万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-08-01 至 2024-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2018750&HistoricalAwards=false
• 关键词: Doctoral; Dissertation; Research; Economics; Public; Doctoral; Dissertation; Research; Economics; Public

AbstractThere is significant and persistent heterogeneity in unemployment rates and labor earnings across labor markets in the US, contributing to overall economic inequality. Developments since the 1990s indicate that migration has declined even as job postings through websites expanded access to and awareness of employment opportunities beyond a worker’s location of origin. This project explores the geographic aspects of online job postings by exploring access to job opportunities for job seekers who are local and non-local. The research investigates employer preference for job applicants by considering whether applicants reside close by the job site or farther away. The project conducts a correspondence experiment that randomly assigns the resumes of fictitious candidates with different geographical locations to employers who are actively seeking employees. The project examines employer callback rates by considering the distance of candidates from job locations to understand differential employer preference for employees’ location of origin. The project further constructs a descriptive and mathematical theory for why employers may prefer local workers over non-local workers.Residents of depressed local labor markets often incur welfare costs associated with remaining in these areas, and migration in favor of expected income gains may serve as an important mechanism for equalization across regions. This research project investigates labor market opportunities in relation to the geographic origin of job applicants. The project employs a resume audit study to understand employers’ hiring preferences in relation to spatial factors by randomly assigning fictitious applicants to job postings, by reflecting varying locations of residence, level of education, and gender of applicants. The project develops a theoretical model that rationalizes potential mechanisms for why employers engage in place-based discrimination and prefer local applicants. By embedding these mechanisms in the resume audit research design, the project explores heterogeneous effects of applicant location on employer hiring preferences.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

AbstrackThere具有重要意义，并且在美国劳动力市场的失业率和劳动收入中持续存在异质性，这导致了整体经济不平等。自1990年代以来的事态发展表明，即使通过网站发布职位发布，移民也有所下降。该项目通过探索本地和非本地求职者的工作机会来探索在线工作发布的地理方面。该研究通过考虑申请是居住在工作现场还是更远的地方来调查员工对工作申请的偏好。该项目进行了一个相应的实验，将具有不同地理位置的虚拟候选人的简历随机分配给积极寻找雇员的雇主。该项目考试通过考虑候选人与工作地点的距离来了解不同雇主对员工原产地点的偏爱，从而使员工回调费率。该项目进一步构建了一种描述性和数学理论，说明雇主为什么偏爱当地工人而不是非本地工人。沮丧的地方劳动力市场的居民经常会遇到与这些领域剩余的福利成本相关的福利成本，而对预期收入收益的移民可能是整个地区均衡的重要机制。该研究项目调查了与工作应用的地理起源有关的劳动力市场机会。该项目采用简历审核研究，通过反映居住地，教育水平和应用程序的性别来理解雇主对空间因素的雇用偏好。该项目开发了一个理论模型，该模型合理化了雇主为何基于位置歧视并更喜欢本地应用的潜在机制。通过将这些机制嵌入简历审计研究设计中，该项目探讨了应用位置对雇主雇用偏好的异构影响。该奖项反映了NSF的法定任务，并被认为是通过基金会的智力优点和更广泛影响的评估来评估的珍贵支持。