Information, Perceptions, and Beliefs in the Labor Market
Paper Session
Friday, Jan. 3, 2025 8:00 AM - 10:00 AM (PST)
- Chair: Zoe Cullen, Harvard University
Pay Transparency and the Efficacy of Collective Bargaining: Evidence from Hollywood
Abstract
Under the premise that pay transparency would strengthen unions’ bargaining position, the U.S. National Labor Relations Act jointly legalized the right to unionize and the right to share salary information. In this paper, we ask how pay transparency and pay inequality affect support for collective bargaining. We conduct a survey experiment with over 1,500 screenwriters and directors at the point where the Hollywood Guilds were renegotiating their multi-year contracts with the major U.S. Studios. We find that Guild members highly value information about others’ pay but the Guild proactively limits access to their pay data. When we introduce pay transparency, we find that it erodes the perception that the Guild demands will meet member needs in the ongoing contract negotiation. In line with our empirical results, we propose a theoretical framework whereby benevolent unions withhold pay information to sustain member participation in collective bargaining.Labor Shortages and Firm Search
Abstract
Employers report labor shortages even among low skill jobs. Why don't wages adjust dynamically to clear market demand? Exploiting randomized variation in wages for 1% of job postings on a large staffing platform, we show that a 10% increase in wages would increase the fill rate by around 30% for a wide range of employers. Despite this, we find that many firms do not raise wages even when vacancies remain unfilled. A firm-side RCT shows that firms have strong underlying demand for marketplace intermediaries guide wage adjustment for unfilled jobs. The gap between manual wage adjustments and chosen automated wage adjustments appears driven by employer uncertainty about the state of the labor market, and adjustment costs. The RCT shows firms dynamically update their beliefs about the state of the labor market when vacancies go unfilled, but several parameters of the labor market shift simultaneously, generating conflation between labor shortages and mispricing. Our results suggest unfilled vacancies could fall by 20% with automated dynamic wages by marketplace intermediaries.How Much Can You Make? Misprediction and Biased Memory in Gig Jobs
Abstract
Flexibility is an increasingly prominent feature of many jobs. In the gig economy, workers can choose their work hours and face wages that vary across hours and weeks. This increased complexity adds challenges to predicting and understanding job outcomes. Incomplete information or behavioral biases can then lead to inaccurate beliefs about pay and labor supply. We test this hypothesis by collecting novel survey data on 454 delivery and ride share gig workers in the United States. Comparing gig workers’ beliefs with data on their actual job performance, we find they overestimate their predictions (43%) and their recalls (31%) of weekly pay, despite it being reported prominently in their earnings statements. Furthermore, gig workers underestimate expenses and overestimate hours worked. The results are consistent with selective recall: when forming and updating their beliefs in noisy environments, workers overweight past high-paying periods. We then examine how biased beliefs affect labor market decisions. We derive predictions from a behavioral labor supply model and test them using survey data and a randomized de-biasing intervention. We find that job choices and labor supply decisions are significantly affected by mistaken beliefs in flexible gig jobs.Discussant(s)
Kory Kroft
,
University of Toronto
Suresh Naidu
,
Columbia University
JEL Classifications
- J2 - Demand and Supply of Labor
- J3 - Wages, Compensation, and Labor Costs