Fast methods for jackknifing inequality indices
AbstractThe jackknife is a resampling method that uses subsets of the original database by leaving out one observation at a time from the sample. The paper outlines a procedure to obtain jackknife estimates for several inequality indices with only a few passes through the data. The number of passes is independent of the number of observations. Hence, the method provides an efficient way to obtain standard errors of the estimators even if sample size is large. We apply our method using micro data on individual incomes for Germany and the US. --
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Bibliographic InfoPaper provided by Christian-Albrechts-University of Kiel, Department of Economics in its series Economics Working Papers with number 2013-04.
Date of creation: 2013
Date of revision:
Jackknife; Resampling; Sampling Variability; Inequality;
Find related papers by JEL classification:
- C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
- C87 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Econometric Software
- D3 - Microeconomics - - Distribution
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- Yitzhaki, Shlomo, 1991. "Calculating Jackknife Variance Estimators for Parameters of the Gini Method," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(2), pages 235-39, April.
- Ogwang, Tomson, 2000. " A Convenient Method of Computing the Gini Index and Its Standard Error," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 62(1), pages 123-29, February.
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