Union Reform, Performance Pay, and New Teacher Supply: Evidence from Wisconsin's Act 10

Abstract

This study examines the impact of performance pay on teacher selection. I exploit a shift toward performance pay in Wisconsin induced by the enactment of Act 10, which gave school districts autonomy to redesign their compensation schemes. Following the law, half of Wisconsin school districts eliminated salary schedules and started negotiating pay with individual teachers based on performance. Comparing the quantity of teaching degrees in Wisconsin institutions before and after Act 10, and relative to those in similar states, I find that Act 10 led to a 20 percent increase in teaching degrees. This effect was entirely driven by selective universities.

Humans Versus Chatbots: Scaling-Up Behavioral Interventions to Reduce Teacher Shortages

“…3 Second, our paper contributes to the literature on teacher supply (Hoxby and Leigh, 2004;Corcoran et al, 2004;Boyd et al, 2006;Bacolod, 2007;Boyd et al, 2013) and career motivation (Han et al, 2018). While much of the literature has focused on the effects of monetary incentives, such as salary increases, on teacher supply and retention (see, for instance, Clotfelter et al (2008b); Falch (2011); Baron (2021); De Ree et al ( 2018)), we explore the effectiveness of a non-monetary intervention to encourage high-performing high school students to pursue a career in education. Although emerging evidence suggests that students' motivations to pursue careers in education are influenced by various factors such as extrinsic, intrinsic, and prestige concerns (see Han et al (2018); Perryman and Calvert (2020)), there is limited research on the teacher supply impact of interventions based on these motivations (Ajzenman et al, 2021).…”

“…First, it relates to the emerging literature on scaling up experimental evidence (Muralidharan and Niehaus, 2017;Vivalt, 2020;DellaVigna and Linos, 2022). Several papers, such as Al-Ubaydli, List, LoRe and Suskind (2017); Al-Ubaydli et al (2020, 2021, have elaborated on several threats that experimental projects can face when scaled up and, in some cases, propose more effective designs to overcome scale issues. We contribute to this literature by testing the effects of a program and a scalable counterpart in the same experiment, using technology (Chatbots) to standardize the treatment, thus reducing the probability of incorrect delivery.…”