Abstract
This paper studies the general principal-agent framework in which the principal aims to implement his first-best action that is monotone in the unknown state. The principal privately selects a signal structure of the agent whose payoff depends on the principal’s action, the state, and the privately known type. The agent privately observes the generated signal and reports it to the principal, who takes action. We show that by randomizing between two perfectly informative signal structures, the principal can elicit perfect information from the agent about the state and implement his first-best action regardless of the agent’s type. As to the economic application, we consider the bilateral trade model with non-quasilinear preferences and private multi-dimensional information of the buyer, and show that the seller can extract full surplus by privately designing the buyer’s signal structures.
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I am thankful to the Associate Editor and the anonymous referee for their insightful comments. I am also grateful to Kalyan Chatterjee, Mikhail Drugov, Seungjin Han, Peicong Hu, Vijay Krishna, Ming Li, Wooyoung Lim, Elliot Lipnowski, Vitor Farinha Luz, Tatiana Mayskaya, Alan Miller, Alessandro Pavan, Sergei Severinov, Joel Sobel, Chen Zhao, Charles Zheng, and the audiences at Concordia University, Western University, University of British Columbia, Canadian Economic Theory Conference 2022, Canadian Economic Association Meetings 2022, Stony Brook International Conference on Game Theory 2022, EEA-ESEM 2022 Conference, Econometric Society European Winter Meeting 2022, FES-ICEF-NES seminar, and CUHK-HKU-HKUST Joint Theory Seminar for helpful comments. A part of this work was written while I visited the University of Toronto. I especially thank Heski Bar-Isaac for hospitality and insightful discussions. This work was supported by the Canadian Social Sciences and Humanities Research Council (SSHRC) Insight Grant 435-2022-0137. All errors are mine.
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Ivanov, M. Perfect robust implementation by private information design. Econ Theory (2024). https://doi.org/10.1007/s00199-023-01548-3
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DOI: https://doi.org/10.1007/s00199-023-01548-3