REDI: Stata module providing a Random Empirical Distribution Imputation method for estimating continuous incomes
Molly King ()
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Molly King: Santa Clara University
Statistical Software Components from Boston College Department of Economics
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.
Language: Stata
Requires: Stata version 16
Keywords: data management; imputation; income (search for similar items in EconPapers)
Date: 2022-07-13
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.
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http://fmwww.bc.edu/repec/bocode/r/redi.ado program code (text/plain)
http://fmwww.bc.edu/repec/bocode/r/redi.sthlp help file (text/plain)
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Persistent link: https://EconPapers.repec.org/RePEc:boc:bocode:s459100
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