(Non) consistency of the Beta Kernel Estimator for Recovery Rate Distribution
In this paper, we explain why a nonparametric approach based on a betakernel [Renault, Scaillet (2004)] will lead to significant bias when appliedto recovery rate distributions. This is due to a specific feature of thesedistributions, which admit strictly positive weights at 100 % correspondingto full recovery (and also at 0 % corresponding to total loss). Moreover, fordistributions without point mass at 0% and 100%, the beta kernel approachfeatures significant bias in finite sample. In large sample the method isconsistent, but other competing approaches presented in the paper providemore accurate results.
Year of publication: |
2006
|
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Authors: | Gourieroux, Christian ; Monfort, Alain |
Institutions: | Centre de Recherche en Économie et Statistique (CREST), Groupe des Écoles Nationales d'Économie et Statistique (GENES) |
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