On the inefficiency of non‐competes in low‐wage labour markets

Author:

Potter Tristan1,Hobijn Bart2,Kurmann André1

Affiliation:

1. Drexel University

2. Federal Reserve Bank of Chicago

Abstract

We study the efficiency of non‐compete agreements (NCAs) in an equilibrium model of labour turnover. The model is consistent with empirical studies showing that NCAs reduce turnover and average wages for low‐wage workers. The model also predicts that, by reducing turnover, NCAs raise recruitment and employment. We show that optimal NCA policy: (i) is characterized by a Hosios‐like condition that balances the benefits of higher employment against the costs of inefficient congestion and poaching; (ii) depends critically on the minimum wage; and (iii) alone cannot always achieve the constrained‐efficient allocation—a result that also holds for optimal minimum wage policy—yet with both policies, efficiency is always attainable. To guide policymakers, we derive a sufficient statistic in the form of an easily computed employment threshold above which NCAs are necessarily inefficiently restrictive, and show that employment levels in current low‐wage US labour markets typically exceed this threshold. Finally, we calibrate the model and show that Oregon's 2008 NCA ban for low‐wage workers increased welfare modestly (by roughly 0.1%), and that if policymakers had also raised the minimum wage to its optimal level conditional on the enacted NCA ban (a 30% increase), then welfare would have increased more substantially—by over 1%.

Publisher

Wiley

Reference47 articles.

1. Tenure, Experience, Human Capital, and Wages: A Tractable Equilibrium Search Model of Wage Dynamics

2. Does Anyone Read the Fine Print? Consumer Attention to Standard-Form Contracts

3. On-the-Job Training

4. Bilal A.andLhuillier H.(2022).Outsourcing inequality and aggregate output. NBER Working Paper no. 29348.

5. Fifty ways to leave your employer: relative enforcement of noncompete agreements, trends, and implications for employee mobility policy;Bishara N.;University of Pennsylvania Journal of Business Law,2011

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3