Artikel
Log-normal or over-dispersed poisson?
Although both over-dispersed Poisson and log-normal chain-ladder models are popular in claim reserving, it is not obvious when to choose which model. Yet, the two models are obviously different. While the over-dispersed Poisson model imposes the variance to mean ratio to be common across the array, the log-normal model assumes the same for the standard deviation to mean ratio. Leveraging this insight, we propose a test that has the power to distinguish between the two models. The theory is asymptotic, but it does not build on a large size of the array and, instead, makes use of information accumulating within the cells. The test has a non-standard asymptotic distribution; however, saddle point approximations are available. We show in a simulation study that these approximations are accurate and that the test performs well in finite samples and has high power.
- Sprache
-
Englisch
- Erschienen in
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Journal: Risks ; ISSN: 2227-9091 ; Volume: 6 ; Year: 2018 ; Issue: 3 ; Pages: 1-37 ; Basel: MDPI
- Klassifikation
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Wirtschaft
- Thema
-
non-nested testing
encompassing
chain-ladder
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Harnau, Jonas
- Ereignis
-
Veröffentlichung
- (wer)
-
MDPI
- (wo)
-
Basel
- (wann)
-
2018
- DOI
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doi:10.3390/risks6030070
- Handle
- Letzte Aktualisierung
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10.03.2025, 11:44 MEZ
Datenpartner
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Objekttyp
- Artikel
Beteiligte
- Harnau, Jonas
- MDPI
Entstanden
- 2018
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