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TWOPARTLOG: Stata module to estimate two-part log regression model with an optimal zero-handling constant for independent variables containing zeros

Author

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  • Dereje Fedasa Hordofa

    (Dire Dawa University, Ethiopia)

Programming Language

Abstract

twopartlog implements the two-part regression framework proposed by Donald Lien, Yue Hu, and Long Liu (2025) to handle regression analysis where the independent variable contains zeros. It generalizes the Started Logarithm (GSLT) and Inverse Hyperbolic Sine (GIHST) transformations by estimating the optimal constant c via concentrated non-linear least squares, treats zero values as a separate group via indicator variables, computes average elasticities, and conducts continuity tests at x = 0.

Suggested Citation

  • Dereje Fedasa Hordofa, 2026. "TWOPARTLOG: Stata module to estimate two-part log regression model with an optimal zero-handling constant for independent variables containing zeros," Statistical Software Components S459940, Boston College Department of Economics.
    • Handle: RePEc:boc:bocode:s459940
    Note: This module should be installed from within Stata by typing "ssc install twopartlog". The module is made available under terms of the MIT license (https://opensource.org/licenses/MIT).
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    File URL: http://fmwww.bc.edu/repec/bocode/t/twopartlog.ado
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    File URL: http://fmwww.bc.edu/repec/bocode/t/twopartlog.sthlp
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