Dynamic Adverse Selection

Dynamic Adverse Selection is a theoretical framework in information economics that models the escalation of informational asymmetry over time, distinguishing itself from static adverse selection by incorporating sequential decision-making and evolving agent types in repeated contractual or market interactions.

175

Publications

10.5K

Citations

285

Authors

194

Institutions

Publications per year

2017–2026

25

Authors

285

  1. HZ
    Hao Zhang

    University of Southern California, United States

    4 publications · 119 citations

    4

    h-index

  2. ST
    Steven Tadelis

    University of California, Berkeley, United States

    4 publications · 744 citations

    4

    h-index

  3. GS
    Gideon Saar

    Cornell University, United States

    3 publications · 331 citations

    3

    h-index

  4. MN
    Mahesh Nagarajan

    University of British Columbia, Canada

    3 publications · 105 citations

    3

    h-index

  5. AB
    Antje Berndt

    Australian National University, Australia

    3 publications · 284 citations

    3

    h-index

1–5 of 285

Venues

  1. SSRN Electronic Journal

    Repository · 19 publications · 896 citations

    14

    h-index

  2. Journal of Economic Theory

    JET · 9 publications · 343 citations

    9

    h-index

  3. The Review of Economic Studies

    8 publications · 461 citations

    8

    h-index

  4. Journal of Health Economics

    7 publications · 490 citations

    7

    h-index

  5. American Economic Review

    5 publications · 1.2K citations

    5

    h-index

1–5