Fast methods for jackknifing inequality indices

Lynn Karoly (karoly@rand.org) and Carsten Schröder
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Lynn Karoly: RAND Corporation, Arlington, USA

Applied Econometrics, 2015, vol. 37, issue 1, 125-138

Abstract: The 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 develops fast algorithms for jackknifing 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.

Keywords: jackknife; resampling; sampling variability; inequality (search for similar items in EconPapers)
JEL-codes: C81 C87 D30 (search for similar items in EconPapers)
Date: 2015
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http://pe.cemi.rssi.ru/pe_2015_1_125-138.pdf Full text (application/pdf)

Related works:
Working Paper: Fast Methods for Jackknifing Inequality Indices (2014)
Working Paper: Fast Methods for Jackknifing Inequality Indices (2013)
Working Paper: Fast Methods for Jackknifing Inequality Indices (2013)
Working Paper: Fast methods for jackknifing inequality indices (2013)
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