mlsanityData to 14 Oct 2026

Principal-Agent Hypothesis Testing

arXiv 2205.06812 ↗First posted 13 May 2022cs.GT cs.LG cs.MAcited by 14

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Abstract (arXiv)

Consider the relationship between a regulator (the principal) and an experimenter (the agent) such as a pharmaceutical company. The pharmaceutical company wishes to sell a drug for profit, whereas the regulator wishes to allow only efficacious drugs to be marketed. The efficacy of the drug is not known to the regulator, so the pharmaceutical company must run a costly trial to prove efficacy to the regulator. Critically, the statistical protocol used to establish efficacy affects the behavior of a strategic, self-interested agent; a lower standard of statistical evidence incentivizes the agent to run more trials that are less likely to be effective. The interaction between the statistical protocol and the incentives of the pharmaceutical company is crucial for understanding this system and designing protocols with high social utility. In this work, we discuss how the regulator can set up a protocol with payoffs based on statistical evidence. We show how to design protocols that are robust to an agent's strategic actions, and derive the optimal protocol in the presence of strategic entrants.

Key facts. Cited by 14 papers in the map (data through 14 Oct 2026). Builds on 7 of its 49 references that are in the map. First posted on arXiv 13 May 2022.

Builds on

7 of 49 references.

References · 7

  1. 2019Safe Testingcited by 101
  2. 2014Adaptive Contract Design for Crowdsourcing Markets: Bandit Algorithms for Repeated Principal-Agent Problemscited by 46
  3. 2018Simple versus Optimal Contractscited by 33
  4. 2020Contracts under Moral Hazard and Adverse Selectioncited by 21
  5. 2020The Complexity of Contractscited by 16
  6. 2021Bayesian Agency: Linear versus Tractable Contractscited by 12
  7. 2021Contracts with Private Cost per Unit-of-Effortcited by 12

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2022: 2; 2023: 5; 2024: 1; 2025: 3; 2026: 3.

14 papers.

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