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Maryam Farboodi

Maryam Farboodi

· Associate ProfessorVerified

Massachusetts Institute of Technology · Finance

Active 2013–2026

h-index23
Citations1.7k
Papers8645 last 5y
Funding
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About

Maryam Farboodi is an 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 and studies intermediation and network formation among financial institutions, as well as the spillovers to the real economy. Her work also explores how information frictions shape local and global economic cycles through credit market structures, including recent research on understanding the Covid-19 pandemic and associated policies. Farboodi received her PhD in financial economics joint between the Department of Economics and the Booth School of Business at the University of Chicago in 2014. Her contributions have been recognized through awards such as the Elaine Bennett Research Prize in 2024 and the Sloan Research Fellowship from the Alfred P. Sloan Foundation for 2024-2026. She is a Research Fellow at the National Bureau of Economic Research and at the Center for Economic and Policy Research.

Research topics

  • Economics
  • Finance
  • Political Science
  • Microeconomics
  • Computer Science
  • Econometrics
  • Monetary economics
  • Business
  • Financial economics
  • Medicine
  • Industrial organization
  • Public economics
  • Law
  • Market economy
  • Financial system

Selected publications

  • Bank Opacity and Deposit Rates

    SSRN Electronic Journal · 2026-01-01

    preprintOpen access
  • Bank Opacity and Deposit Rates

    National Bureau of Economic Research · 2026-01-01

    reportOpen access

    Banks face a dual mandate of raising cheap deposits while avoiding liquidity risk.We propose a novel mechanism whereby banks use portfolio opacity to meet this objective.Specifically, banks choose opaque portfolios to secure cheap long-term funding while trading off insolvency and illiquidity.We show that while opacity lowers deposit rates, it also leaves depositors with only noisy information about the bank's solvency, making them cautious about keeping their funds in the bank-particularly when interest rates are high.We show that opacity raises bank profits, sometimes at the cost of exposure to high probability of illiquidity.In particular, in high-rate environments, banks adopt excessive opacity to further reduce deposit rates-at the cost of more frequent early failures.

  • Do Markets Believe in Transformative AI?

    SSRN Electronic Journal · 2025-01-01

    preprintOpen accessSenior author
  • Do Markets Believe in Transformative AI?

    National Bureau of Economic Research · 2025-09-01 · 1 citations

    reportOpen accessSenior author
  • Good Data and Bad Data: The Welfare Effects of Price Discrimination

    2025-07-02

    articleOpen access1st authorCorresponding

    The rise of big data technologies, allowing firms to collect detailed consumer data to estimate their willingness to pay, has reignited the longstanding debate on the welfare implications of price discrimination. A significant difficulty in regulating data collection practices is that it is close to impossible to perfectly monitor and control how firms use consumer data, which makes highly targeted regulation impractical. Often the relevant question is if data collection should be permitted, without knowing how much information the firm already has nor how much additional information it might be able to collect.

  • Good Data and Bad Data: The Welfare Effects of Price Discrimination

    ArXiv.org · 2025-02-05 · 1 citations

    preprintOpen access1st authorCorresponding

    We study how a monopolist's use of consumer data for price discrimination affects welfare. To answer this question, we develop a model of market segmentation subject to residual uncertainty. We fully characterize when data usage monotonically increases or decreases welfare or when the effect is non-monotone. The characterization reduces the problem to one with only two demand curves, and gives a condition for the two-demand-curves case that highlights that information affects welfare in three distinct ways. In the non-monotone case, we provide tight bounds on the welfare effects of information and identify the best local direction for providing additional information.

  • Good Data and Bad Data: The Welfare Effects of Price Discrimination

    SSRN Electronic Journal · 2025-01-01

    preprintOpen access1st authorCorresponding
  • Intermediation as rent extraction

    Journal of Economic Theory · 2025-05-16 · 3 citations

    article1st authorCorresponding
  • Good Data and Bad Data: The Welfare Effects of Price Discrimination

    National Bureau of Economic Research · 2025-11-01

    reportOpen access1st authorCorresponding

    We study how a monopolist's use of consumer data for price discrimination affects welfare.To answer this question, we develop a model of market segmentation subject to residual uncertainty.We fully characterize when data usage monotonically increases or decreases welfare or when the effect is non-monotone.The characterization reduces the problem to one with only two demand curves, and gives a condition for the two-demand-curves case that highlights that information affects welfare in three distinct ways.In the non-monotone case, we provide tight bounds on the welfare effects of information and identify the best local direction for providing additional information.

  • Information and Market Power in DeFi Intermediation

    SSRN Electronic Journal · 2024-01-01

    articleOpen accessSenior author

Frequent coauthors

Labs

Awards & honors

  • Elaine Bennett Research Prize (2024)
  • Sloan Research Fellowship from the Alfred P. Sloan Foundatio…
  • Outstanding Paper Award from the Swiss Finance Institute (20…
  • Young Researcher Award from the SCOR-PSE Chair on Macroecono…
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