Monica Zhong specializes in providing rigorous data analysis and economic research in the areas of class certification, antitrust, and consumer protection analysis. Ms. Zhong’s work spans a wide range of industries including consumer goods, agricultural products, telecommunications, technology products, and direct selling. Ms. Zhong is skilled at developing and analyzing large and complex datasets for antitrust litigation cases and providing economic insights to clients facing legal disputes through rigorous analysis.

Ms. Zhong has experience working with clients managing and assessing large scale databases from multiple sources, conducting statistical testing of econometric models related to class certification issues, and evaluating the economics of market allocation. Ms. Zhong also has extensive experience managing project teams in preparation of expert analysis in various regulatory matters.

Case Highlights

Case Highlights

Insights & News

Edgeworth Insights

  • Blog, 05.14.2024

    At the 72nd ABA Antitrust Spring Meeting panel “The Price is Right (Or Is It?),” panelists discussed concerns related to “dark patterns,” specifically focusing on pricing and disclosure practices such as “junk fees,” automatic renewals, and negative options.

  • Blog, 12.04.2023

    On November 9, 2023, the American Bar Association Antitrust Law Section held its annual Fall Forum focused on the theme “Can Antitrust and Consumer Protection Keep Up with Artificial Intelligence (AI)?” This exciting program brought together computer scientists performing cutting-edge AI research, policymakers considering proper legislation for regulating these new technologies, and practitioners navigating the implications of this changing legal landscape in the scope of antitrust, privacy, and consumer protection.

  • Blog, 10.11.2023

    Artificial intelligence (“AI”) has long been a hot topic across various industries, including the legal sector, especially with the recent breakthrough of innovative generative AI system—Large Language Model (“LLM”) applications like ChatGPT that can process and generate humanlike text in real-time. These technologies can revolutionize the way legal cases are managed, making it more critical than ever for professionals in the legal industry to learn how to harness the power of generative AI to their advantage—and to understand the limits of its capabilities.

  • Blog, 10.05.2023

    U.S. District Judge Barbara Lynn's decision in Federal Trade Commission v. Neora LLC in the U.S. District Court for the Northern District of Texas last week marks a landmark victory for the direct selling industry.[1]

  • Blog, 10.04.2022

    Regression analysis is a statistical tool used by economists, statisticians, and others to “understand the relationship between or among two or more variables.”  Any attorney new to the antitrust space will invariably encounter regression analysis frequently. In this article, we provide a brief introduction to the regression methodology.


Monica received her Bachelor's degree in Economics and Mathematics from the University of Wisconsin-Madison and her Master's in Economics from the University of Virginia.

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