Finite sample behaviour of classical and quantile regression estimators for the Pareto distribution

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Abstract

The Pareto distribution is a well known and important model in Statistics. It has been used to study large incomes, city population size, size of losses, stock price fluctuations, number of citations received by papers and other similar phenomena. In this work we compare the finite sample performance of several estimation methods, namely the Moment, Maximum Likelihood and Quantile Regression methods. The comparison will be made through a Monte-Carlo simulation study.

Original languageEnglish
Title of host publicationProceedings of the International Conference on Numerical Analysis and Applied Mathematics 2014, ICNAAM 2014
PublisherAmerican Institute of Physics Inc.
Volume1648
ISBN (Electronic)978-0-7354-1287-3
DOIs
Publication statusPublished - 10 Mar 2015
EventInternational Conference on Numerical Analysis and Applied Mathematics 2014, ICNAAM 2014 - Rhodes, Greece
Duration: 22 Sep 201428 Sep 2014

Conference

ConferenceInternational Conference on Numerical Analysis and Applied Mathematics 2014, ICNAAM 2014
CountryGreece
CityRhodes
Period22/09/1428/09/14

Keywords

  • Maximum likelihood estimator
  • Moment estimator
  • Monte-Carlo method
  • Pareto distribution
  • Quantile regression estimator

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