We consider general utility models and information structures of the agents and illustrate when economic conclusions for designing simple mechanisms in classical settings extends for general environments. We show that whether economic conclusions can be generalized depends on the details of the generalizations. For example, in single-item auction, competition and non-anonymity are not crucial factors for revenue maximization when agents have linear utilities [Yan, 2011, Alaei et al., 2018], and these conclusions extend for broad classes of non-linear utilities. In comparison, the economic conclusions we derived for exogenous information settings often fail when the information is endogenous. For example, in multi-dimensional information acquisition problems, scoring the agent separately is without loss when the signals are exogenous, but suffers a great loss when the signals are endogenous. In selling information problems, price discrimination and commitment to revealing partial information are crucial for revenue maximization if the agent has an exogenous signal about the unknown state [Bergemann et al., 2021]. However, pricing for full information is approximately optimal when the signal is endogenous.

Creator

• Li, Yingkai

DOI

• https://doi.org/10.21985/n2-ggy3-xv18

Subject

• Computer science

Language

• en

Alternate Identifier

• etdadmin_upload_894020
• http://dissertations.umi.com/northwestern:15991

Keyword

• Algorithmic Game Theory
• Mechanism Design
• Simple Mechanisms

Date created

• 2022-01-01

Resource type

• Dissertation

Rights statement

• In Copyright