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BIC: Stata module to evaluate the statistical significance of variables in a model

Author

Listed:
  • Paul Millar

    (University of Calgary)

Programming Language

Stata

Abstract

bic is a post-estimation command that uses the Bayesian Information Criterion (BIC) for estimating the probability that a variable is part of a model, the equivalent of the statistical significance of a variable's effect. bic estimates models based on all possible combinations of the independent variables - it is computationally intensive. For each of these models it calculates the BIC statistic. It then calculates the probability of each of these models, based on Bayesian principles as first proposed by Schwarz (1978) and further developed by Raftery (1995).

Suggested Citation

  • Paul Millar, 2005. "BIC: Stata module to evaluate the statistical significance of variables in a model," Statistical Software Components S449507, Boston College Department of Economics, revised 14 Apr 2011.
    • Handle: RePEc:boc:bocode:s449507
    Note: This module should be installed from within Stata by typing "ssc install bic". The module is made available under terms of the GPL v3 (https://www.gnu.org/licenses/gpl-3.0.txt). Windows users should not attempt to download these files with a web browser.
    as

    Download full text from publisher

    File URL: http://fmwww.bc.edu/repec/bocode/b/bic.ado
    File Function: program code
    Download Restriction: no
    File URL: http://fmwww.bc.edu/repec/bocode/b/bic.hlp
    File Function: help file
    Download Restriction: no
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    Citations

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    Cited by:

    1. Shahram Amini & Christopher F. Parmeter, 2011. "Bayesian Model Averaging in R," Working Papers 2011-9, University of Miami, Department of Economics.

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