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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
