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Alex Imas

Alex Imas

· Roger L. and Rachel M. Goetz Professor of Behavioral Science, Economics and Applied AI and Vasiliou Faculty Scholar

University of Chicago · Applied AI

Active 2008–2025

h-index27
Citations4.0k
Papers11346 last 5y
Funding

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

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About

Alex studies the economics of artificial intelligence and technological change. His research explores how AI reshapes productivity, labor markets, and creative work, how people and organizations adopt AI tools; and how agentic systems interact with existing economic and social institutions. He also studies behavioral economics, with a focus on how people understand and mentally represent the choices they are facing — including how they learn and make decisions under risk and uncertainty. Alex's work utilizes a variety of methods, including controlled laboratory experiments, field experiments, analysis of observational data and theoretical modeling.

Research topics

  • Computer Science
  • Economics
  • Political Science
  • Social psychology
  • Microeconomics
  • Psychology
  • Artificial Intelligence
  • Business
  • Econometrics
  • Mathematics

Selected publications

  • Inaccurate Statistical Discrimination: An Identification Problem

    The Review of Economics and Statistics · 2023 · 97 citations

    Abstract We study inaccurate beliefs as a source of discrimination. Economists typically characterize discrimination as stemming from a taste-based (preference) or accurate statistical (belief-based) source. Although individuals may have inaccurate beliefs about how relevant characteristics (e.g., productivity, signals) are correlated with group identity, fewer than 7% of empirical discrimination papers in economics consider the possibility of such inaccurate statistical discrimination. Using th…

  • Ownership, Learning, and Beliefs

    The Quarterly Journal of Economics · 2021 · 96 citations

    Senior authorCorresponding

    Abstract We examine how owning a good affects learning and beliefs about its quality. We show that people have more extreme reactions to information about a good they own compared with the same information about a nonowned good: ownership causes more optimistic beliefs after receiving a positive signal and more pessimistic beliefs after receiving a negative signal. Comparing learning to normative benchmarks reveals that people overextrapolate from signals about goods they own, which leads to an…

  • Biased by Choice: How Financial Constraints Can Reduce Financial Mistakes

    Review of Financial Studies · 2021 · 76 citations

    Senior authorCorresponding

    Abstract We show that constraints can improve financial decision-making by disciplining behavioral biases. In financial markets, restrictions on leverage limit traders’ ability to borrow to open new positions. We demonstrate that regulation that restricts the provision of leverage to retail traders improves trading performance. By increasing the opportunity cost of postponing the realization of losses, leverage constraints improve traders’ market timing and reduce their disposition effect. We re…

  • Dynamic Inconsistency in Risky Choice: Evidence from the Lab and Field

    American Economic Review · 2024-12-30 · 12 citations

    article

    We document a robust dynamic inconsistency in risky choice. Using a unique brokerage dataset and a series of experiments, we compare people's initial risk-taking plans to their subsequent decisions. Across settings, people accept risk as part of a loss-exit strategy—planning to continue taking risk after gains and stopping after losses. Actual behavior deviates from initial strategies by cutting gains early and chasing losses. More people accept risk when offered a commitment to their initial st…

  • Systemic Discrimination: Theory and Measurement

    The Quarterly Journal of Economics · 2025-05-01 · 10 citations

    articleOpen accessSenior author

    Abstract Economists often measure discrimination as disparities arising from the direct effects of group identity. We develop new tools to model and measure systemic discrimination, capturing how discrimination in other decisions indirectly contributes to disparities. A novel experimental design, the iterated audit, identifies systemic discrimination. We illustrate these new tools in two field experiments. The first experiment shows how racial discrimination can accumulate across multiple rounds…

Frequent coauthors

  • J. Aislinn Bohren

    105 shared
  • Kareem Haggag

    88 shared
  • Devin G. Pope

    86 shared
  • Ayelet Gneezy

    University of California, San Diego

    30 shared
  • Ania Jaroszewicz

    20 shared
  • Uri Gneezy

    15 shared
  • Kristóf Madarász

    Laser Scan Engineering (United Kingdom)

    13 shared
  • Michael Kuhn

    13 shared

Labs

Awards & honors

  • 2023 Alfred P. Sloan Research Fellowship
  • Review of Financial Studies Rising Scholar Award
  • New Investigator Award from the Behavioral Science and Polic…
  • Hillel Einhorn New Investigator Award from the Society of Ju…
  • Distinguished CESifo Affiliate Award

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