Bayesian Incentive Compatibility

Bayesian Incentive Compatibility is a solution concept in mechanism design requiring that each agent’s expected utility, given their private information and beliefs about others’ types, is maximized by truthfully reporting their type under a Bayesian equilibrium.

98

Publications

10K

Citations

177

Authors

94

Institutions

Publications per year

2017–2026

15

Variants

Bic

Authors

177

  1. SM
    S. Matthew Weinberg

    Princeton University, United States

    7 publications · 294 citations

    7

    h-index

  2. JD
    Jason D. Hartline

    Northwestern University, United States

    5 publications · 210 citations

    5

    h-index

  3. YC
    Yang Cai

    Massachusetts Institute of Technology, United States

    5 publications · 272 citations

    5

    h-index

  4. CD
    Claude d’Aspremont

    UCLouvain, Belgium

    4 publications · 146 citations

    4

    h-index

  5. DM
    Dipjyoti Majumdar

    Indian Statistical Institute, India

    3 publications · 86 citations

    3

    h-index

1–5 of 177

Venues

  1. RePEc: Research Papers in Economics

    Repository · 9 publications · 329 citations

    9

    h-index

  2. Econometrica

    7 publications · 2.6K citations

    7

    h-index

  3. Journal of Economic Theory

    JET · 6 publications · 404 citations

    6

    h-index

  4. SSRN Electronic Journal

    Repository · 4 publications · 524 citations

    4

    h-index

  5. American Economic Review

    3 publications · 1.9K citations

    3

    h-index

1–5