About

Paul Milgrom is the Shirley and Leonard W. Ely, Jr. Professor of Humanities and Sciences in the Department of Economics at Stanford University. He also holds courtesy appointments at the Department of Management Science and Engineering and the Graduate School of Business. Recognized as a leading figure in auction design, Milgrom has significantly contributed to the development of auction theory and its practical applications, notably designing many auctions for radio spectrum worldwide, including those conducted by the U.S. Federal Communications Commission. His work has helped establish new ways for economists to interact with the broader world through applied auction design and consulting. Milgrom's theoretical contributions span a broad range of microeconomic theory, including foundational insights into auction theory, exemplified by his influential 1982 paper with Weber. In 2020, he was named a Distinguished Fellow of the American Economic Association and was awarded the Sveriges Riksbank Prize in Economic Sciences, along with Robert Wilson, for improvements to auction theory and the invention of new auction formats. His research continues to push forward the frontiers of economic knowledge, and he is highly cited within the field.

Research topics

• Economics
• Mathematical economics
• Mathematics
• Microeconomics
• Computer Science
• Econometrics
• Operations research
• Neoclassical economics

Selected publications

• Essays on mechanism design

  Stanford Digital Repository · 2026-05-19

  dissertationOpen access
  PublisherDOI

• Market design with externalities and monitoring

  Stanford Digital Repository · 2026-04-29

  dissertationOpen access
  PublisherDOI

• Incentive Auction Design Alternatives: A Simulation Study

  Management Science · 2024-02-13 · 2 citations

  article

  This paper revisits the descending clock “reverse” auction design used in the U.S. Federal Communications Commission’s 2016–2017 “incentive auction.” We use extensive computational simulations to investigate the quantitative significance of various aspects of the design, leveraging a reverse auction simulator and realistic models of bidder values. This paper was accepted by Gabriel Weintraub, revenue management and market analytics. Funding: This work was supported by the Defense Advanced Research Projects Agency [Grant FA8750-19-2-0222 CFDA\# 12.910], the Canadian Institute for Advanced Research [Canada AI Research Chair at the Alberta Machine In], the National Science Foundation [Grant 1525730], and the Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada [Discovery Grant, Discovery Grant Supplement]. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2020.02489 .

  PublisherDOI

• Market Design for Surface Water

  SSRN Electronic Journal · 2024-01-01 · 3 citations

  articleOpen accessSenior author
  PublisherDOI

• Kenneth Arrow's Last Theorem

  Journal of Mechanism and Institution Design · 2024-12-15

  articleOpen access1st authorCorresponding

  In Kenneth Arrow's last week of life at age 95, he reported that "I began my research career with an impossibility theorem. If I had time now, my last theorem would be an impossibility theorem about social choice for environmental policy." This paper completes the formalization, proof, and discussion of the theorem that Arrow then described.

  PublisherDOI

• Algorithmic Mechanism Design With Investment

  Econometrica · 2023-01-01 · 8 citations

  articleSenior author

  We study the investment incentives created by truthful mechanisms that allocate resources using approximation algorithms. Some approximation algorithms guarantee nearly 100% of the optimal welfare in the allocation problem but guarantee nothing when accounting for investment incentives. An algorithm's allocative and investment guarantees coincide if and only if its confirming negative externalities are sufficiently small. We introduce fast approximation algorithms for the knapsack problem that have no confirming negative externalities and guarantees close to 100% for both allocation and investment.

  PublisherDOI

• Taming the Communication and Computation Complexity of Combinatorial Auctions: The FUEL Bid Language

  Management Science · 2022 · 10 citations

  • Computer Science
  • Computer Science
  • Operations research

  Combinatorial auctions have found widespread application for allocating multiple items in the presence of complex bidder preferences. The enumerative exclusive OR (XOR) bid language is the de facto standard bid language for spectrum auctions and other applications, despite the difficulties, in larger auctions, of enumerating all the relevant packages or solving the resulting NP-hard winner determination problem. We introduce the flexible use and efficient licensing (FUEL) bid language, which was proposed for radio spectrum auctions to ease both communications and computations compared with XOR-based auctions. We model the resulting allocation problem as an integer program, discuss computational complexity, and conduct an extensive set of computational experiments, showing that the winner determination problem of the FUEL bid language can be solved reliably for large realistic-sized problem instances in less than half an hour on average. In contrast, auctions with an XOR bid language quickly become intractable even for much smaller problem sizes. We compare a sealed-bid FUEL auction to a sealed-bid auction with an XOR bid language and to a simultaneous clock auction. The sealed-bid auction with an XOR bid language incurs significant welfare losses because of the missing bids problem and computational hardness, the simultaneous clock auction leads to a substantially lower efficiency than FUEL because of the exposure problem. This paper was accepted by Axel Ockenfels, behavioral economics and decision analysis. Funding: This work was supported by Deutsche Forschungsgemeinschaft [Grant BI 1057-1/8]. P. Milgrom gratefully acknowledges support from the U.S. National Science Foundation [Grant SES-1947514]. M. Bichler and G. Schwarz was supported by the German Research Foundation [Grants BI 1057 I-9 and 277991500]. Supplemental Material: The data files are available at https://doi.org/10.1287/mnsc.2022.4465 .

  PublisherDOI

• Linear Pricing Mechanisms for Markets without Convexity

  Proceedings of the 23rd ACM Conference on Economics and Computation · 2022-07-12 · 3 citations

  article1st authorCorresponding

  We introduce two linear pricing mechanisms for quasilinear economies in which market-clearing prices may not exist. Electricity markets, fisheries markets, and many others include producers with start-up costs, ramping costs, or other fixed costs that fail the convexity assumptions traditionally used to prove that clearing prices exist.

  PublisherDOI

• When Should Control Be Shared?

  Management Science · 2022-03-18 · 1 citations

  preprint

  A common pattern of control in firms is for management to retain a broad set of rights, whereas the remaining stakeholders’ contracts provide them with targeted veto rights over specific classes of decisions. We explain this pattern of control sharing as an efficient organizational response that balances the need to encourage management to account for stakeholders’ interests against the need to prevent self-interested stakeholders from blocking valuable proposals. Enforceable obligations of good faith and fair dealing play an essential role in facilitating undivided management control of many decisions. With these legal protections (but not without them), shared control is more likely when the parties are more symmetrically informed and hence, better able to bargain to efficient decisions. This paper was accepted by Joshua Gans, business strategy. Funding: Financial support for the research of P. Milgrom was provided by the National Science Foundation [Grants ITR-0427770 and SES-1947514].

  PublisherDOI

• Extended proper equilibrium

  Journal of Economic Theory · 2021 · 6 citations

  1st authorCorresponding
  • Mathematical economics
  • Economics
  • Mathematics
  PublisherDOI

Recent grants

• Auction Market Design

  NSF · $242k · 2015–2019

• ITR: Collaborative Research: (EVS + ASE) - Soc + int): Electronic Auction Markets

  NSF · $440k · 2004–2007

• Auction Design for Complex Centralized Markets

  NSF · $277k · 2020–2024

Frequent coauthors

• John Roberts

  33 shared

• Lawrence M. Ausubel

  University of Maryland, College Park

  19 shared

• Jonathan Levin

  RAND Corporation

  17 shared

• Peter Cramton

  16 shared

• Robert J. Weber

  13 shared

• Ilya Segal

  13 shared

• Robert E. Hall

  10 shared

• Justin Wolfers

  University of Michigan–Ann Arbor

  10 shared

Education

• B.A., Economics

  Stanford University

  1979

• Ph.D., Economics

  Stanford University

  1983

Awards & honors

• 2020 Distinguished Fellow of the American Economic Associati…
• 2020 Nobel Prize in Economics (Sveriges Riksbank Prize in Ec…
• John J. Carty Award for the Advancement of Science