Markets with only a few firms are called oligopolies. Tirole showed that in such markets companies can manipulate prices and output in ways traditional monopoly-or-perfect-competition models cannot capture. He also focused on the problem of asymmetric information, where regulators do not fully know firms’ costs or technologies. By designing a “menu of contracts,” regulators can let firms choose the option that matches their true cost structure while still pushing them to cut costs. These ideas have shaped real policies such as railway price caps and interconnection fees for telecom operators.

Tirole’s work is groundbreaking because it applies game theory and contract theory to the strategic interaction between regulators and multiple firms. In the Laffont–Tirole (1986) framework, firms self-select among alternative contracts (e.g., fixed fee plus sliding marginal payments) according to their cost type, thereby mitigating asymmetric information. In dynamic settings he showed that short-term contracts can create a ratchet effect that weakens incentives, and that multi-tier regulation is vulnerable to collusion between agencies and firms. He also pioneered two-sided market theory and the analysis of vertical restraints, providing foundations for optimal platform fees and exclusive technology licenses. These results feed directly into EU competition guidelines and national public-utility rate reviews.

Tirole formalized regulation under asymmetric information as a screening problem, deriving optimal two-part tariffs and nonlinear prices for natural monopolies such as railways and electricity. Dynamic extensions analyze Bayesian equilibria where effort and cost types evolve endogenously, showing how optimal regulation asymptotically identifies cost parameters. In two-sided markets he proved that welfare-maximizing fee structures must internalize cross-group externalities, while in vertical restraints he showed that exclusivity and foreclosure can both distort competition and enhance investment incentives. These theories underpin price-cap formulas (e.g., RPI-X) and incentive-quality indices, and have motivated structural estimation with preference correlation in antitrust impact assessments.