[2601.01279] Collusive Pricing Under LLM

Economics > Theoretical Economics arXiv:2601.01279 (econ) [Submitted on 3 Jan 2026 (v1), last revised 22 Mar 2026 (this version, v2)] Title:Collusive Pricing Under LLM Authors:Shengyu Cao, Ming Hu View a PDF of the paper titled Collusive Pricing Under LLM, by Shengyu Cao and 1 other authors View PDF HTML (experimental) Abstract:We study how delegating pricing to large language models (LLMs) can facilitate collusion in a duopoly when both sellers rely on the same pre-trained model. The LLM is characterized by (i) a propensity parameter capturing its internal bias toward high-price recommendations and (ii) an output-fidelity parameter measuring how tightly outputs track that bias; the propensity evolves through retraining. We show that configuring LLMs for robustness and reproducibility can induce collusion via a phase transition: there exists a critical output-fidelity threshold that pins down long-run behavior. Below it, competitive pricing is the unique long-run outcome. Above it, the system is bistable, with competitive and collusive pricing both locally stable and the realized outcome determined by the model's initial preference. The collusive regime resembles tacit collusion: prices are elevated on average, yet occasional low-price recommendations provide plausible deniability. With perfect fidelity, full collusion emerges from any interior initial condition. For finite training batches of size $b$, infrequent retraining (driven by computational costs) further amplifie...