Audit Probability Modeling

Audit Probability Modeling is a quantitative method within tax compliance research that estimates the likelihood of a taxpayer being selected for a tax audit based on empirical data, behavioral patterns, and risk indicators, distinguishing it from broader audit policy or enforcement frameworks by its focus on predictive statistical modeling.

37

Publications

2.6K

Citations

81

Authors

50

Institutions

Publications per year

2017–2026

6

Parents

Authors

81

  1. IS
    Ira Solomon

    University of Illinois Urbana-Champaign, United States

    3 publications · 189 citations

    3

    h-index

  2. MM
    Michael McKee

    University of New Mexico, United States

    3 publications · 196 citations

    3

    h-index

  3. MW
    Mark W. Nelson

    Cornell University, United States

    2 publications · 159 citations

    2

    h-index

  4. JA
    James Alm

    Tulane University, United States

    2 publications · 137 citations

    2

    h-index

  5. JL
    Jack L. Krogstad

    Creighton University, United States

    2 publications · 123 citations

    2

    h-index

1–5 of 81

Venues

  1. SSRN Electronic Journal

    Repository · 3 publications · 73 citations

    3

    h-index

  2. Public Finance Review

    PFR · 3 publications · 128 citations

    3

    h-index

  3. Contemporary Accounting Research

    CAR · 2 publications · 224 citations

    2

    h-index

  4. National Tax Journal

    NTJ · 2 publications · 128 citations

    2

    h-index

  5. 1

    h-index

1–5