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REDI: Stata module providing a Random Empirical Distribution Imputation method for estimating continuous incomes

Author

Listed:
  • Molly King

    (Santa Clara University)

Programming Language

Stata

Abstract

redi is a method for cold-deck imputation of a continuous distribution from binned incomes, using a real-world reference dataset (in this case, the CPS ASEC). The Random Empirical Distribution Imputation (redi) method imputes discrete observations using binned income data. The user may wish to combine or compare income data across years or surveys, stymied by incompatible categories. The redi package converts categorical to continuous incomes through random cold-deck imputation from a real world reference dataset. The redi method reconciles bins between datasets or across years and handles top incomes. redi has other advantages of computing an income distribution that is nonparametric, bin consistent, area- and variance-preserving, and continuous.

Suggested Citation

  • Molly King, 2022. "REDI: Stata module providing a Random Empirical Distribution Imputation method for estimating continuous incomes," Statistical Software Components S459100, Boston College Department of Economics.
    • Handle: RePEc:boc:bocode:s459100
    Note: This module should be installed from within Stata by typing "ssc install redi". 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/r/redi.ado
    File Function: program code
    Download Restriction: no
    File URL: http://fmwww.bc.edu/repec/bocode/r/redi.sthlp
    File Function: help file
    Download Restriction: no
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