Incidental Parameters Problem

The "Incidental Parameters Problem" is a statistical estimation challenge arising in panel data models with fixed effects, where the number of nuisance parameters grows with the sample size, leading to inconsistent maximum likelihood estimates due to the incidental parameters interfering with the consistent estimation of structural parameters.

87

Publications

8.3K

Citations

108

Authors

89

Institutions

Publications per year

2017–2026

13

Variants

Neyman-scott Problem

Authors

108

  1. IF
    Iván Fernández‐Val

    Boston University, United States

    8 publications · 773 citations

    8

    h-index

  2. JH
    Jinyong Hahn

    University of California, Los Angeles, United States

    7 publications · 866 citations

    7

    h-index

  3. MW
    Martin Weidner

    University College London, United Kingdom

    6 publications · 621 citations

    6

    h-index

  4. WH
    William H. Greene

    New York University, United States

    4 publications · 1.1K citations

    4

    h-index

  5. PC
    Peter C.B. Phillips

    Yale University, United States

    3 publications · 91 citations

    3

    h-index

1–5 of 108

Venues

  1. Journal of Econometrics

    7 publications · 1.8K citations

    7

    h-index

  2. RePEc: Research Papers in Economics

    Repository · 6 publications · 421 citations

    6

    h-index

  3. SSRN Electronic Journal

    Repository · 6 publications · 220 citations

    6

    h-index

  4. Econometrica

    4 publications · 645 citations

    4

    h-index

  5. 4

    h-index

1–5