Journal article
On the inefficiency of non-competes in low-wage labour markets
Economica (London)
07 Feb 2024
Featured in Collection : UN Sustainable Development Goals @ Drexel
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%.
Metrics
Details
- Title
- On the inefficiency of non-competes in low-wage labour markets
- Creators
- Tristan Potter - Drexel UniversityBart Hobijn - Federal Reserve Bank of ChicagoAndre Kurmann - Drexel University
- Publication Details
- Economica (London)
- Publisher
- Wiley
- Number of pages
- 51
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Economics (School of Economics)
- Web of Science ID
- WOS:001157560200001
- Scopus ID
- 2-s2.0-85184394015
- Other Identifier
- 991021854903804721
UN Sustainable Development Goals (SDGs)
This publication has contributed to the advancement of the following goals:
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- Web of Science research areas
- Economics