Single Imputation Methods and Confidence Intervals for the Gini Index Álvarez Verdejo, Encarnación Moya Fernández, Pablo José Muñoz Rosas, Juan Francisco Missing data Variance estimation Coverage Inequality Non-response mechanism This research has been partially supported by the Ministry of Economy, Industry and Competitiveness, the Spanish State Research Agency (SRA) and European Regional Development Fund (ERDF) (project reference ECO2017-86822-R). This research has been partially supported by the Ministry of Economy, Industry and Competitiveness, the Spanish State Research Agency (SRA) and European Regional Development Fund (ERDF) (project reference ECO2017-84138-P). The problem of missing data is a common feature in any study, and a single imputation method is often applied to deal with this problem. The first contribution of this paper is to analyse the empirical performance of some traditional single imputation methods when they are applied to the estimation of the Gini index, a popular measure of inequality used in many studies. Various methods for constructing confidence intervals for the Gini index are also empirically evaluated. We consider several empirical measures to analyse the performance of estimators and confidence intervals, allowing us to quantify the magnitude of the non-response bias problem. We find extremely large biases under certain non-response mechanisms, and this problem gets noticeably worse as the proportion of missing data increases. For a large correlation coefficient between the target and auxiliary variables, the regression imputation method may notably mitigate this bias problem, yielding appropriate mean square errors. We also find that confidence intervals have poor coverage rates when the probability of data being missing is not uniform, and that the regression imputation method substantially improves the handling of this problem as the correlation coefficient increases. 2022-02-03T11:45:05Z 2022-02-03T11:45:05Z 2021-12-15 info:eu-repo/semantics/article Álvarez-Verdejo, E.; Moya-Fernández, P.J.; Muñoz-Rosas, J.F Single Imputation Methods and Confidence Intervals for the Gini Index. Mathematics 2021, 9, 3252. [https://doi.org/10.3390/math9243252] http://hdl.handle.net/10481/72640 10.3390/math9243252 eng http://creativecommons.org/licenses/by/3.0/es/ info:eu-repo/semantics/openAccess Atribución 3.0 España MDPI