Monopsony and Labor Markets
Paper Session
Saturday, Jan. 6, 2024 10:15 AM - 12:15 PM (CST)
- Chair: Julie Holland Mortimer, University of Virginia
Labor and Product Market Effects of Mergers
Abstract
We use a two-level vertical supply chain model to examine the labor market effect of product market mergers under different labor market configurations. In the model, firms and workers collectively bargain over wages upstream, and firms sell differentiated products and engage in Bertrand competition downstream. We examine multiple channels through which a merger changes both firm and worker leverage, and explore how merger effects vary when production takes place in one or more labor markets. We conduct a series of numerical simulations to identify the situations in which mergers most affect worker welfare. We find that when product and labor markets completely coincide workers' welfare is reduced the most, however, consumers often benefit as reduced wages are partially passed thru in the form of lower final goods prices. Finally, we find that merger simulations that focus only on downstream competition can frequently identify those mergers that harm workers.Driving the Drivers: Algorithmic Wage-Setting in Ride-Hailing
Abstract
Firms can now use algorithms to regulate workers’ time and activities more stringently than ever before. Using rich transaction data from a ride-hailing company in Asia, we document algorithmic wage-setting and study its impact on worker behavior. The algorithm profiles drivers based on their working schedules. Our data show that drivers favored by the algorithm earn 8% more hourly than non-favored drivers. To quantify the welfare effects of such preferential algorithms, we construct and estimate a two-sided market model with time-varying demand and dynamic labor supply decisions. Results show that removing the preferential algorithm would, in the short term, reduce platform revenues by 12% and total surplus by 7%. In the long run, raising rider fares re-balances demand and supply, resulting in minimal welfare loss. Without the preferential algorithm, an additional 10% of drivers would switch to flexible schedules. Lastly, young, male, local drivers benefit more from the non-preferential algorithm.Bidding for Talent: A Test of Conduct in a High-Wage Labor Market
Abstract
We develop a procedure for adjudicating between models of firm wage- setting conduct. Using data on workers’ choice sets and decisions over real jobs from a U.S. job search platform, we first estimate workers’ rankings over firms’ non-wage amenities. We document three key findings: 1) On average, workers are willing to accept 12.3% lower salaries for a 1-S.D. improvement in amenities. 2) Between-worker preference dispersion is equally large, indi- cating that preferences are not well-described by a single ranking. 3) High- paying firms have better amenities. Following the modern IO literature, we use these estimates to formulate a test of conduct based on exclusion restrictions. Oligopsonistic models incorporating strategic interactions between firms and tailoring of wage offers to workers’ outside options are rejected in favor of sim- pler monopsonistic models featuring near-uniform markdowns. Misspecifica- tion has meaningful consequences: while our preferred model predicts average markdowns of 19.5%, others predict average markdowns as large as 26.6%.Discussant(s)
Jingyi Huang
,
Brandeis University
Bradley Setzler
,
Pennsylvania State University
Nicholas Buchholz
,
Princeton University
Peter Newberry
,
University of Georgia
JEL Classifications
- J3 - Wages, Compensation, and Labor Costs
- L4 - Antitrust Issues and Policies