Mallesh Pai

About

My research focuses on mechanism design and auction theory, and their applications to the design of blockchains and decentralized finance (DeFi) protocols. I have also worked on the economics of privacy, social networks, social learning, and statistical decision theory.

Research topics

• Computer Science
• Machine Learning
• Algorithm
• Microeconomics
• Economics
• Mathematics
• Business

Selected publications

• Frontiers: Algorithmic Collusion: Supra-competitive Prices via Independent Algorithms

  Marketing Science · 2021 · 117 citations

  Senior authorCorresponding

  We show that the long-run prices from independent machine learning algorithms depend on the informational value of price experiments. If low, the long-run prices are consistent with the static Nash equilibrium; however, if high, the long-run prices are supra-competitive.

  DOI

• Competing Models

  The Quarterly Journal of Economics · 2022-03-16 · 24 citations

  articleOpen access

  Abstract Different agents need to make a prediction. They observe identical data, but have different models: they predict using different explanatory variables. We study which agent believes they have the best predictive ability—as measured by the smallest subjective posterior mean squared prediction error—and show how it depends on the sample size. With small samples, we present results suggesting it is an agent using a low-dimensional model. With large samples, it is generally an agent with a…

  PublisherOA PDFDOI

• Testing Alone Is Insufficient

  SSRN Electronic Journal · 2020 · 14 citations

  DOI

• The Centralizing Effects of Private Order Flow on Proposer-Builder Separation

  arXiv (Cornell University) · 2023-01-01 · 9 citations

  preprintOpen access

  The current Proposer-Builder Separation (PBS) equilibrium has several builders with different backgrounds winning blocks consistently. This paper considers how that equilibrium will shift when transactions are sold privately via order flow auctions (OFAs) rather than forwarded directly to the public mempool. We discuss a novel model that highlights the augmented value of private order flow for integrated builder searchers. We show that private order flow is complementary to top-of-block opportun…

  PublisherOA PDFDOI

• Taxing Externalities Without Hurting the Poor

  2023-07-07 · 6 citations

  article1st authorCorresponding

  When consumption of a good causes externalities, market outcomes may be inefficient. Economists have long recognized this and suggested as a remedy a "Pigouvian tax" equal to the monetary equivalent of the harm done to others. Despite their intuitive appeal, Pigouvian taxes are rarely seen in practice. Conversely, public discourse often involves regulations such as consumption caps or even prohibition of the activity, which economists consider "non-market" solutions. Can natural preferences of t…

  PublisherDOI

Recent grants

• AF: Medium: Collaborative Research: Foundations of Fair Data Analysis

  NSF · $250k · 2018–2023

Frequent coauthors

• Aaron Roth

  30 shared

• Rahul Deb

  Wildlife Institute of India

  22 shared

• Rakesh Vohra

  18 shared

• Matthew Mitchell

  Deakin University

  11 shared

• Manuel Mueller‐Frank

  Pearson (United States)

  11 shared

• Michael Kearns

  10 shared

• Jonathan Ullman

  Northeastern University

  9 shared

• Chang Hwa Lee

  Korea Atomic Energy Research Institute

  7 shared

Education

• Ph.D., Managerial Economics and Strategy

  Kellogg School of Management

• B.S., Computer Science and Engineering

  Indian Institute of Technology, Delhi

Similar researchers at Rice University

• Vivian Hoh-38
• Flávio Cunhah-37
• Isabelle Perrigneh-31