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Andrea Eisfeldt

Andrea Eisfeldt

· Laurence D. and Lori W. Fink Endowed Chair in Finance and Professor of Finance

University of California, Los Angeles · Finance

Active 2002–2026

h-index31
Citations4.4k
Papers11730 last 5y
Funding

Academic metrics are sourced from OpenAlex and public funding records; values may differ from Google Scholar.

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About

Andrea L. Eisfeldt is the Laurence D. and Lori W. Fink Endowed Chair in Finance and a professor of finance at UCLA Anderson, where she has been teaching since 2010. She spent her first 10 years of her academic career as an assistant professor and then a tenured associate professor at the Kellogg School of Management at Northwestern University. Her research focuses on macroeconomics and finance, including market liquidity, the role of intangibles in asset pricing, bank valuation, and over-the-counter markets. Eisfeldt's work has earned several awards, such as the Smith Breeden Distinguished Paper prize and the Jensen Prize, and she has received research grants from notable institutions. She has also enjoyed practical experience through asset management consulting for Structured Portfolio Management and AQR, applying her expertise in fixed-income and equity portfolio strategies. She is actively involved in the academic community, serving on the boards of the American Finance Association and the Society for Financial Studies Cavalcade, and holds editorial roles at prominent economic journals.

Research topics

  • Economics
  • Finance
  • Business
  • Econometrics
  • Computer Science
  • Keynesian economics
  • Actuarial science
  • Monetary economics
  • Demographic economics
  • Industrial organization

Selected publications

  • Generative AI and Firm Values

    National Bureau of Economic Research · 2023-05-01 · 121 citations

    reportOpen access1st authorCorresponding

    What are the effects of recent advances in Generative AI on the value of firms? Our study offers a quantitative answer to this question for U.S. publicly traded companies based on the exposures of their workforce to Generative AI. Our novel firm-level measure of workforce exposure to Generative AI is validated by data from earnings calls, and has intuitive relationships with firm and industry-level characteristics. Using Artificial Minus Human portfolios that are long firms with higher exposures…

  • American Economic Journal: Macroeconomics

    AEA Papers and Proceedings · 2020 · 81 citations

    Macroeconomics (AEJ Macro) is to publish "studies of aggregate fluctuations and growth and the role of policy in that context."The mandate also recognizes that research in macroeconomics interacts closely with and borrows from several other fields, and that AEJ Macro therefore welcomes papers in other fields that make a contribution to macroeconomics.The editors interpret this mandate flexibly-in line with the view that research progress in macroeconomics proceeds from many directions and encomp…

  • The Deposit Business at Large vs. Small Banks

    National Bureau of Economic Research · 2023-11-01 · 32 citations

    reportOpen access

    The deposit business differs at large versus small banks.We provide a parsimonious model and extensive empirical evidence supporting the idea that much of the variation in deposit-pricing behavior between large and small banks reflects differences in "preferences and technologies."Large banks offer superior liquidity services but lower deposit rates, and locate where customers value their services.In addition to receiving a lower level of deposit rates on average, customers of large banks exhibi…

  • AI and Finance

    National Bureau of Economic Research · 2024-10-01 · 21 citations

    reportOpen access1st authorCorresponding
  • OTC Intermediaries

    Review of Financial Studies · 2022 · 17 citations

    1st authorCorresponding

    Abstract We study the effect of dealer exit on prices and quantities in a model of an over-the-counter market featuring a core-periphery network with bilateral trading costs. The model is calibrated using regulatory data on the entire U.S. credit default swap (CDS) market between 2010 and 2013. Prices depend crucially on the risk-bearing capacity of core dealers, yet unlike standard models featuring a dealer sector, we allow for heterogeneity in dealer risk-bearing capacity. This heterogeneity i…

Frequent coauthors

  • Andrew Atkeson

    University of California, Los Angeles

    88 shared
  • Pierre-Olivier Weill

    86 shared
  • Timothy Cogley

    Federal Reserve Bank of Minneapolis

    26 shared
  • Stephanie Schmitt–Grohé

    Center for Economic and Policy Research

    26 shared
  • Christina Arellano

    Federal Reserve Bank of Minneapolis

    26 shared
  • Joseph P. Kaboski

    The Ohio State University

    26 shared
  • Jesús Fernández‐Villaverde

    26 shared
  • Kristina Kiritchenko

    Federal Reserve Bank of Minneapolis

    25 shared

Awards & honors

  • Smith Breeden Distinguished Paper prize (2004)
  • Jensen Prize (second place) (2008)
  • Smith Breeden First Place Paper award (2013)

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