A new GLO Discussion Paper finds that the comparative assessment of correction methods indicates that most methods are able to partially correct for missing data biases. Sample reweighting based on probabilities on non-response produces inequality estimates quite close to true values in most simulated missing data patterns.
GLO Discussion Paper No. 1138, 2022
GLO Fellow Paolo Verme
Author Abstract: The measurement of income inequality is affected by missing observations, espe- cially if they are concentrated on the tails of an income distribution. This paper conducts an experiment to test how the different correction methods proposed by the statistical, econometric and machine learning literature address measurement biases of inequality due to item non response. We take a baseline survey and artificially corrupt the data employing several alternative non-linear functions that simulate pat- terns of income non-response, and show how biased inequality statistics can be when item non-responses are ignored. The comparative assessment of correction methods indicates that most methods are able to partially correct for missing data biases. Sample reweighting based on probabilities on non-response produces inequality estimates quite close to true values in most simulated missing data patterns. Matching and Pareto corrections can also be effective to correct for selected missing data patterns. Other methods, such as Single and Multiple imputations and Machine Learning meth- ods are less effective. A final discussion provides some elements that help explaining these findings.
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Vol. 35, Issue 4, October 2022: Journal of Population Economics (JOPE): 15 articles
Just released: CiteScore of JOPE moves up from 3.9 (2020) to 6.5 (2021)! LINK
Similar, its Impact Factor is now 4.7 (2021) after 2.8 (2020)! LINK
GLO Discussion Papers are research and policy papers of the GLO Network which are widely circulated to encourage discussion. Provided in cooperation with EconStor, a service of the ZBW – Leibniz Information Centre for Economics, GLO Discussion Papers are among others listed in RePEc (see IDEAS, EconPapers). Complete list of all GLO DPs – downloadable for free.
The Global Labor Organization (GLO) is an independent, non-partisan and non-governmental organization that functions as an international network and virtual platform to stimulate global research, debate and collaboration.