In oligopsonistic labour markets, firms have some market power, and a wedge is created between wages and marginal product. When oligopsonistic firms' production technology requires generally trained workers, firms may therefore receive part of the returns to general training and be willing to...

Adam Smith alleged that secret employer collusion to reduce labor earnings is common. This paper examines an important case of such behavior: no-poach agreements through which technology companies agreed not to compete for each other’s workers. Exploiting the plausibly exogenous timing of a US...

A large body of evidence suggests that social comparisons matter for workers' valuation of the wage they receive. The consequences of social comparisons in imperfectly competitive labor markets are less well understood. We analyze an oligopsonistic model of the labor market where workers derive...

Using data on the near-universe of online US job vacancies collected by Burning Glass Technologies in 2016, we calculate labor market concentration using the Herfindahl-Hirschman index (HHI) for each commuting zone by 6-digit SOC occupation. The average market has an HHI of 3,953, or the...

A product market is concentrated when a few firms dominate the market. Similarly, a labor market is concentrated when a few firms dominate hiring in the market. Using data from the leading employment website CareerBuilder.com, we calculate labor market concentration for over 8,000...

We evaluate the impact of the Washington State Attorney General's enforcement campaign against employee no-poaching clauses in franchising contracts, which unfolded from 2018 through early 2020. Implementing a staggered difference-in-differences research design using Burning Glass Technologies...

The subdued wage growth observed in many countries has spurred interest in monopsony views of regional labour markets. This study measures the extent and robustness of employer power and its wage implications exploiting comprehensive matched employer-employee data. We find average...