Robust Estimation of the Tail Index of a Single Parameter Pareto Distribution from Grouped Data

Chudamani Poudyal ()
Additional contact information
Chudamani Poudyal: Department of Mathematical Sciences, University of Wisconsin-Milwaukee, Milwaukee, WI 53211, USA

Risks, 2024, vol. 12, issue 3, 1-13

Abstract: Numerous robust estimators exist as alternatives to the maximum likelihood estimator (MLE) when a completely observed ground-up loss severity sample dataset is available. However, the options for robust alternatives to a MLE become significantly limited when dealing with grouped loss severity data, with only a handful of methods, like least squares, minimum Hellinger distance, and optimal bounded influence function, available. This paper introduces a novel robust estimation technique, the Method of Truncated Moments (MTuM), pecifically designed to estimate the tail index of a Pareto distribution from grouped data. Inferential justification of the MTuM is established by employing the central limit theorem and validating it through a comprehensive simulation study.

Keywords: claim severity; exponential distribution; grouped data; Pareto distribution; relative efficiency; robust estimation; truncated moments (search for similar items in EconPapers)
JEL-codes: C G0 G1 G2 G3 K2 M2 M4 (search for similar items in EconPapers)
Date: 2024
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/2227-9091/12/3/45/pdf (application/pdf)
https://www.mdpi.com/2227-9091/12/3/45/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jrisks:v:12:y:2024:i:3:p:45-:d:1349342

Access Statistics for this article

Risks is currently edited by Mr. Claude Zhang

More articles in Risks from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().