Simulation-based Estimation

Simulation-Based Estimation is a methodological approach within discrete choice modeling that uses simulated data to approximate likelihood functions or choice probabilities when analytical solutions are intractable, thereby enabling parameter estimation through repeated stochastic sampling.

304

Publications

25.5K

Citations

844

Authors

405

Institutions

Publications per year

2017–2026

59

Authors

844

  1. MP
    Michael P. Keane

    University of Technology Sydney, Australia

    10 publications · 1.8K citations

    10

    h-index

  2. LA
    Leonard A. Stefanski

    North Carolina State University, United States

    4 publications · 941 citations

    4

    h-index

  3. JC
    J.R. Cook

    Merck & Co., Inc., Rahway, NJ, USA (United States), United States

    4 publications · 1.3K citations

    4

    h-index

  4. SH
    Stephane Hess

    University of Leeds, United Kingdom

    4 publications · 87 citations

    4

    h-index

  5. CR
    Chandra R. Bhat

    The University of Texas at Austin, United States

    4 publications · 1.9K citations

    4

    h-index

1–5 of 844

Venues

  1. SSRN Electronic Journal

    Repository · 13 publications · 279 citations

    11

    h-index

  2. Journal of Econometrics

    9 publications · 1.7K citations

    9

    h-index

  3. Management Science

    8 publications · 466 citations

    8

    h-index

  4. RePEc: Research Papers in Economics

    Repository · 8 publications · 316 citations

    8

    h-index

  5. Journal of Marketing Research

    6 publications · 2.3K citations

    6

    h-index

1–5