When people lose their job, labor market programs help them get back to work. But administrative burdens can hinder enrollment in such programs. We report results from a mixed‐method project to increase enrollment in employment services during the first 3 months of the COVID‐19 pandemic. First, we interviewed jobseekers and frontline staff to uncover administrative burdens. Second we worked with staff to co‐design a behavioral “nudge” intervention. Finally, in a large field experiment (N = 14,008), we evaluate the impact of this intervention on participation in employment services. We present two main findings. First, reducing administrative burden triples enrollment in the program within the first 30 days. Second, we test two motivational frames—one emphasizing social norms, another using checklist messaging. We find that message framing drives engagement with communications, such as email open rates and website click‐throughs. However, framing generates no statistically significant difference in enrollment rates. Our results demonstrate the potential for applied behavioral science to improve implementation of labor market policy. We also contribute to current debates about the effectiveness of nudging to increase take‐up of public services.

中文翻译：

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助推增加了就业服务的使用：来自大型现场实验的证据


当人们失业时，劳动力市场计划可以帮助他们重返工作岗位。但行政负担可能会阻碍此类项目的入学。我们报告了一个混合方法项目的结果，该项目旨在在 COVID-19 大流行的前 3 个月内增加就业服务的入学人数。首先，我们采访了求职者和一线员工，以揭示行政负担。其次，我们与员工共同设计了行为“助推”干预措施。最后，在一项大型现场实验（N = 14,008）中，我们评估了这种干预对就业服务参与的影响。我们提出两个主要发现。首先，减少管理负担在前 30 天内使该计划的注册人数增加两倍。其次，我们测试了两种动机框架——一个强调社会规范，另一个使用清单消息传递。我们发现消息框架可以提高沟通的参与度，例如电子邮件打开率和网站点击率。然而，框架在入学率方面没有产生统计学上的显着差异。我们的结果证明了应用行为科学改善劳动力市场政策实施的潜力。我们还为当前关于推动增加公共服务使用率的有效性的辩论做出了贡献。