Gonzalo Ballestero

Publications

Strategic Algorithmic Monoculture: Experimental Evidence from Coordination Games
with Hadi Hosseini, Samarth Khanna, and Ran I. Shorrer
Proceedings of the 27th ACM Conference on Economics and Computation (EC '26), Extended Abstract, April 2026
Abstract ArXiv

AI agents increasingly operate in multi-agent environments where outcomes depend on coordination. We distinguish primary algorithmic monoculture (baseline action similarity) from strategic algorithmic monoculture, whereby agents adjust similarity in response to incentives. We implement a simple experimental design that cleanly separates these forces, and deploy it on human and large language model (LLM) subjects. LLMs exhibit high levels of baseline similarity (primary monoculture) and, like humans, they regulate it in response to coordination incentives (strategic monoculture). While LLMs coordinate extremely well on similar actions, they lag behind humans in sustaining heterogeneity when divergence is rewarded.

Algorithmic Collusion under Sequential Pricing and Stochastic Costs
International Journal of Industrial Organization, June 2026
Abstract SSRN Replication Code

The use of pricing algorithms raises concerns about algorithmic collusion. This paper considers a sequential pricing model where marginal cost fluctuates over time. I find that Q-learning algorithms autonomously collude even under cost uncertainty. Collusion is sustained by strategies that involve reward-punishment schemes. It suggests that cost uncertainty is not an obstacle to autonomous algorithmic collusion.

Work in Progress

Brain Drain by Design

The Pitfalls of Preferential Admission Policies

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Policy Briefs

Cheating in the Medical Residency Entrance Exam (in Spanish), July 2025

Redesigning the Medical Match in Argentina: Toward More Equitable Access (in Spanish), June 2025
with Mariana Gudiño and Nahir Lera
Media: Clarín La Nación Penn State News