- About
- Events
- Calendar
- Graduation Information
- Cornell Learning Machines Seminar
- Student Colloquium
- BOOM
- Spring 2025 Colloquium
- Conway-Walker Lecture Series
- Salton 2024 Lecture Series
- Seminars / Lectures
- Big Red Hacks
- Cornell University / Cornell Tech - High School Programming Workshop and Contest 2025
- Game Design Initiative
- CSMore: The Rising Sophomore Summer Program in Computer Science
- Explore CS Research
- ACSU Research Night
- Cornell Junior Theorists' Workshop 2024
- People
- Courses
- Research
- Undergraduate
- M Eng
- MS
- PhD
- Admissions
- Current Students
- Computer Science Graduate Office Hours
- Advising Guide for Research Students
- Business Card Policy
- Cornell Tech
- Curricular Practical Training
- A & B Exam Scheduling Guidelines
- Fellowship Opportunities
- Field of Computer Science Ph.D. Student Handbook
- Graduate TA Handbook
- Field A Exam Summary Form
- Graduate School Forms
- Instructor / TA Application
- Ph.D. Requirements
- Ph.D. Student Financial Support
- Special Committee Selection
- Travel Funding Opportunities
- Travel Reimbursement Guide
- The Outside Minor Requirement
- Robotics Ph. D. prgram
- Diversity and Inclusion
- Graduation Information
- CS Graduate Minor
- Outreach Opportunities
- Parental Accommodation Policy
- Special Masters
- Student Spotlights
- Contact PhD Office
Speaker
Monday, April 21, 2025 - 15:45 to 17:00
Gates 114 and streaming via Zoom
Host:
Eva Tardos
Categories:
Title: Good Data and Bad Data: The Welfare Effects of Price Discrimination
Abstract: The rise of big data technologies has revived the longstanding debate on who reaps the economic benefit of more information, firms, or consumers. We study the welfare consequences of monopoly pricing across all possible segmentations of a given family of demand curves. We provide necessary and sufficient conditions on this family of demand curves under which the monopolist's use of information never always depress versus always improve consumer welfare despite the ensuing price discrimination. Our classification provides insights to guide the recent policy discussion in use of consumer data and sheds light on the type of information that can be allowed in price discrimination. Joint work with Nima Haghpanah and Ali Shourideh.
Bio: Maryam Farboodi is the Jon D. Gruber Career Development Associate Professor of Finance at the MIT Sloan School of Management. She is an applied theorist whose research focuses on the economics of big data with applications to finance and macroeconomics. She has developed methodologies to estimate the value of data. In addition, Farboodi studies intermediation and network formation among financial institutions, and the spillovers to the real economy. She is also interested in how information frictions shape local and global economic cycles through the credit market structure. She has most recently worked on understanding the Covid-19 pandemic and associated policies.
Farboodi received her masters in computer science from University of Maryland, College Park and her PhD in financial economics joint between the Department of Economics and the Booth School of Business at the University of Chicago in 2014. She is the recipient of the Elaine Bennett Research prize in 2024 and Sloan Research Fellowship from the Alfred P. Sloan Foundation 2024-2026. She is a Research Fellow at the National Bureau of Economic Research and at the Center for Economic and Policy Research.