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AStA Wirtschafts- und Sozialstatistisches Archiv
Published in: AStA Wirtschafts- und Sozialstatistisches Archiv 3-4/2018

23-11-2018 | Originalveröffentlichung

Estimation of sample quantiles: challenges and issues in the context of income and wealth distributions

Author: Ann-Kristin Kreutzmann

Published in: AStA Wirtschafts- und Sozialstatistisches Archiv | Issue 3-4/2018

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Abstract

Means, quantiles and extreme values are common statistics for the description of distributions. However, estimating sample quantiles with the default definition in different software programs leads to unequal results. This is due to the fact that software programs use different quantile definitions. Since most practitioners are not aware of this fact and use different quantile definitions interchangeably, this work compares the default definitions in the software programs SPSS, R, SAS™ software, and Stata and additional quantile definitions that are suggested by the literature. The work especially focuses on how the quantile estimators perform in the context of describing the distribution of income and wealth. Furthermore, the possibilities of considering sampling weights in the quantile estimation and methods for producing variance estimates using the above-mentioned software are discussed.
previous article A note on how to normalise the Geary-Khamis index of purchasing power parity
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Appendix
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Metadata
Title
Estimation of sample quantiles: challenges and issues in the context of income and wealth distributions
Author
Ann-Kristin Kreutzmann
Publication date
23-11-2018
Publisher
Springer Berlin Heidelberg
Published in
AStA Wirtschafts- und Sozialstatistisches Archiv / Issue 3-4/2018
Print ISSN: 1863-8155
Electronic ISSN: 1863-8163
DOI
https://doi.org/10.1007/s11943-018-0234-z

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