Économie computationnelle

The Social Compression Hypothesis

A Pre-Registered Test of Coordination Demand, Institutional Capacity, and Instability in Historical and Modern Societies, with a Formal Framework and Agent-Based Experiments

Simon-Pierre Boucher · Cahiers de recherche UQO · novembre 2026 · v1.0

Institutions, standards, records and administrative hierarchies can be read as devices that lower the communication cost of coordinating many people: a form of compression. This paper states that reading formally, derives what it does and does not imply, and tests its empirical corollary, that a mismatch between a…

The Invisible Hand of Machines: Price Discovery in Markets Populated by LLM Agents

Simon-Pierre Boucher · Cahiers de recherche UQO · octobre 2026 · v1.0

What happens to price discovery when a growing share of the traders in a market are autonomous language-model agents? The paper builds an event-sourced continuous double-auction exchange with exact accounting, a latent dividend process that separates fundamental value from public value and transaction price, seven…

When AI Agents Become Economic Agents: An Agentic General Equilibrium Theory

Simon-Pierre Boucher · Cahiers de recherche UQO · octobre 2026 · v1.0

Households and firms are beginning to delegate economic decisions to autonomous agents built on a few shared foundation models. This paper studies what this does in general equilibrium. A human's decision error is idiosyncratic and averages out; an AI agent's error is common to every principal that uses the same…

From Labor to Capital: Artificial General Intelligence, General Equilibrium, and Asset Valuation

Simon-Pierre Boucher · Cahiers de recherche UQO · octobre 2026 · v1.0

Restrepo (2025) shows that once artificial general intelligence lets compute perform every task, output becomes linear in compute, wages converge to the value of the compute a worker saves, and the labor share goes to zero. This paper extends his task economy by treating compute as a reproducible, priced, depreciating…