Working Paper: NBER ID: w24282
Authors: Paul R. Milgrom; Steven Tadelis
Abstract: In complex environments, it is challenging to learn enough about the underlying characteristics of transactions so as to design the best institutions to efficiently generate gains from trade. In recent years, Artificial Intelligence has emerged as an important tool that allows market designers to uncover important market fundamentals, and to better predict fluctuations that can cause friction in markets. This paper offers some recent examples of how Artificial Intelligence helps market designers improve the operations of markets, and outlines directions in which it will continue to shape and influence market design.
Keywords: Artificial Intelligence; Machine Learning; Market Design
JEL Codes: D44; D82; L15
Edges that are evidenced by causal inference methods are in orange, and the rest are in light blue.
| Cause | Effect |
|---|---|
| AI and machine learning (C45) | improved market operations (E52) |
| AI tools (C45) | optimal reserve prices in online advertising auctions (D44) |
| AI (C45) | demand and supply forecasting in electricity markets (Q47) |
| AI and machine learning (C45) | better allocation of resources (D61) |
| AI and machine learning (C45) | stabilization of prices (E64) |