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John J. Horton

medium confidence · updated 2026-04-06

Economist at MIT Sloan and NBER research associate; one of the most prolific empirical researchers in the economics of online labor markets and now in the economics of AI agents. Co-author of the 2025 'Coasean Singularity?' chapter (Shahidi, Rusak, Manning, Fradkin, Horton) and multiple agent-economy working papers (Wiles & Horton on AI résumé assistance and labor-market matching efficiency; Rusak, Manning, Horton on agent-enabled market designs). His prior work on Upwork-style labor markets makes him the natural bridge between the existing platform-economics literature and the agentic-economy frontier.

John J. Horton is an economist who works at the intersection of online labor markets, market design, and the economics of AI agents. He is an Associate Professor at the MIT Sloan School of Management and a Research Associate at the National Bureau of Economic Research.

Research

Horton's earlier research concentrates on online labor markets such as Upwork-style freelancing platforms, where he studies search costs, matching efficiency, and congestion. His more recent work applies that platform-economics background to the economics of AI agents, including résumé flooding, AI-mediated bargaining, and agent-platform pricing.

He is a co-author of "The Coasean Singularity? Demand, Supply, and Market Design with AI Agents" (2025) (Shahidi, Rusak, Manning, Fradkin, Horton), a chapter offering an economic-theory framing of the agentic transition. The chapter frames AI agents through Coase's transaction-cost lens (Transaction Costs (Coase) and the Agentic Economy); develops the BYO/Bowling-Shoe × Horizontal/Vertical agent-supply typology (Agent Supply Archetypes (BYO/Bowling-Shoe × Horizontal/Vertical)); articulates a Pigouvian framing for Cloudflare's pay-per-crawl mechanism; and surveys the regulatory frontier across market power, autonomy and liability, security and privacy, and data rights.

Several related working papers from the same research cluster bear on labor-market and matching-market consequences of AI agents:

  • Wiles & Horton (2025), "Generative AI and labor market matching efficiency" (SSRN 5187344), the empirical anchor for the congestion-externality argument, which holds that AI-generated résumés flood employers and raise screening costs.
  • Wiles, Munyikwa & Horton (2025), "Algorithmic Writing Assistance on Jobseekers' Resumes Increases Hires" (Management Science), empirical evidence that AI advisory services improve job-application outcomes.
  • Rusak, Manning & Horton (2025), "AI Agents Can Enable Superior Market Designs" (working paper), on how foundation models that parse natural-language preferences make deferred-acceptance and other theoretically superior matching mechanisms practical.

Horton's combination of familiarity with the existing platform-economics literature (search costs, matching efficiency, congestion) and empirical engagement with agent-economy phenomena (résumé flooding, AI-mediated bargaining, agent-platform pricing) positions his co-authored work within research on labor displacement, hiring markets, and matching mechanisms in the agentic era.

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