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GB2LFIT: Stata module to fit Generalized Beta of the Second Kind distribution by maximum likelihood (log parameter metric)

Author

Listed:
  • Stephen P. Jenkins

    (London School of Economics and Political Science)

Programming Language

Stata

Abstract

gb2lfit fits by ML the 4 parameter Generalized Beta distribution of the second kind (GB2) to sample observations on a random variable. gb2pred calculates statistics summarizing a GB2 distribution which has been fitted using gb2fit. Unit record data are assumed (rather than grouped data). The Singh-Maddala (1976) distribution is the special case when parameter p = 1, and the Dagum (1977, 1980) distribution is the special case when parameter q = 1. The GB2 distribution has been shown to provide a good fit to data on income but, of course, it might also be suitable for describing any skewed variable, not only income. Compared to gb2fit (q.v.), gb2lfit has the following features: (i) parameters are estimated in the logarithmic metric (but reported in the original metric); (ii) data may be right-censored or left-truncated; (iii) there are improved options for calculating inequality measures implied by the parameter estimates (with SEs); (iv) in particular, estimates of the Gini coefficient are reported.

Suggested Citation

  • Stephen P. Jenkins, 2014. "GB2LFIT: Stata module to fit Generalized Beta of the Second Kind distribution by maximum likelihood (log parameter metric)," Statistical Software Components S457897, Boston College Department of Economics.
    • Handle: RePEc:boc:bocode:s457897
    Note: This module should be installed from within Stata by typing "ssc inst gb2lfit". 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.
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    File URL: http://fmwww.bc.edu/repec/bocode/g/gb2lfit.hlp
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