Expert Insights

Rui Huang* and Pian Chen** |  June 12, 2026

This article is the first part of our data science crash courses — Causal Methods in the Courtroom and the C-Suite. The courses introduce fundamental methods that economists, statisticians, and data scientists use to make causal inference. We write for two groups: (1) lawyers who want to understand whether challenged conduct caused harm and how to quantify damages and (2) business leaders who make product, pricing, and marketing decisions. This article focuses on experimental methods for causal inference. Later installments in this series will cover the statistical, econometric, and machine-learning methods that have been tested in the courtroom or have been used by business leaders.

Aleks Schaefer and Pian Chen  |  June 8, 2026

For most of the history of U.S. antitrust enforcement, merger review has been framed primarily as a question of consumer welfare. The central inquiries have concerned whether a merged firm would raise prices, whether product or service quality would decline, and whether new entry would discipline post-merger conduct. Workers, on the other side of the firm's market, have received comparatively little attention. The 2023 Merger Guidelines, issued jointly by the FTC and the DOJ, formally incorporated labor-market effects as a component of merger review. This new requirement has created demand for rigorous empirical evidence on how mergers and consolidation affect labor markets.

Chanyuan (Abigail) Parker and Pian Chen |  May 22, 2026

PCAOB Auditing Standard 1000 requires auditors to obtain reasonable assurance that financial statements are free of material misstatements. Material misstatements are errors that meaningfully distort the information in financial statements. When discovered, they are typically corrected through restatements, which are disclosed via Item 4.02 of Form 8-K, a requirement by the SEC since 2005.[1]

Pian Chen and Rui Huang | April 22, 2026

Contract prices for NAND flash memory have risen sharply in the second half of 2025 as enterprise storage demand has accelerated alongside AI infrastructure investment. Prices are expected to double in 2026.[1] Despite rising demand and prices, Samsung and SK Hynix are planning production reductions in 2026 by 4.5% and 10.5%, respectively.[2] This raises key questions: Does Samsung and SK Hynix's announced supply reductions in 2026 raise antitrust concerns?

Becky Zhang and Pian Chen | April 23, 2026

In high-stakes litigation, a large damages award on paper may yield far less in the hands of plaintiffs. Treble damages sound powerful, but class actions routinely settle for less than single damages when defendants cannot cover their full exposure. Before committing significant capital and thousands of billable hours to a multi-year case, a critical threshold question must be answered: is there actually something to recover?

Pian Chen and Rui Huang | April 22, 2026

The adoption of AI and machine learning models to support pricing decisions has become widespread across industries. Property management, hospitality, retail, ride-sharing, and airline revenue management all now rely on algorithmic tools that process large volumes of data to generate pricing recommendations. These tools can create genuine efficiencies: they reduce the information burden on individual firms, allow faster responses to market conditions, and can improve resource allocation. But they also introduce a structural antitrust risk that traditional frameworks were not designed to address.

Rui Huang and Pian Chen | April 24, 2026

Multi-sided platforms have become a defining feature of modern commerce. Millions of businesses, large and small, participate in them every day. Amazon accounts for 35.7% of the $1.2 trillion U.S. e-commerce sales, and its third-party sellers generated approximately $575 billion in gross merchandise volume in 2025. Shopify powers 14% of U.S. e-commerce market and processed $378 billion in gross merchandise volume in 2025.[1] In short-term lodging, Airbnb commands approximately 44% of the global short-term rental market with revenue of $183 billion in 2024.[2] A growing range of other sectors, such as online travel and ride-sharing, also use multi-sided platforms to connect sellers and buyers.