Title: Auditing Effects on Employment Hiring: Evidence from the New York City Algorithmic Bias Audit Law

Speaker:Hao Ma(the Stockholm School of Economics)

Time: 10:00(Friday) , June 26, 2026

Venue: Room1007, Mingde Business Building (Zhongguancun Campus)

Language: English

 

ABSTRACT:

This paper examines the effect of algorithmic bias audits on workforce diversity by exploiting New York City's (NYC) pioneering Bias Audit Law (Local Law 144). The law requires third-party audits for NYC employers that use algorithm-driven hiring tools to examine instances of disparate impact in recruiting. Using a difference-in-differences analysis, we find that bias audit requirements lead to almost a two percentage-point reduction in the share of male hiring, while having no significant effects on white employee hiring. The effects of decreased male hires are particularly pronounced among firms that directly or indirectly obtain an audit and have greater pre-audit gender imbalances. The decline is also concentrated in lower to mid-tier positions and applies to both public and private companies. We also document costs in the form of increased human resource staff hires and longer times to fill vacancies. Finally, we find evidence of subsequent improvement in performance using financial analysts’ forecast accuracy as a setting. Our results provide the first large-scale empirical evidence on the effectiveness of mandated algorithmic bias audits, highlighting a trade-off between levelling the playing field for job seekers and reduced recruitment efficiency.

SHORT BIOGRAPHY:

Hao Ma is an Assistant Professor at the Stockholm School of Economics. She obtained her PhD degree from ESSEC Business School. During her PhD, she visited Yale University. Prior to joining ESSEC Business School, she earned a Master's degree in Economics from Peking University and a Bachelor's degree in Economics from Sichuan University. Her primary research interests lie in accounting, auditing, labor, and AI.