Median bilinear models in presence of extreme values
Santolino, Miguel (Universitat de Barcelona. Departament d'Econometria)

Date:	2021
Abstract:	Bilinear regression models involving a nonlinear interaction term are applied in many fields (e. g. , Goodman's RC model, Lee-Carter mortality model or CAPM financial model). In many of these contexts data often exhibit extreme values. We propose the use of bilinear models to estimate the median of the conditional distribution in the presence of extreme values. The aim of this paper is to provide alternative methods to estimate median bilinear models. A calibration strategy based on an iterative estimation process of a sequence of median linear regression is developed. Mean and median bilinear models are compared in two applications with extreme observations. The first application deals with simulated data. The second application refers to Spanish mortality data involving years with atypical high mortality (Spanish flu, civil war and HIV/AIDS). The performance of the median bilinear model was superior to that of the mean bilinear model. Median bilinear models may be a good alternative to mean bilinear models in the presence of extreme values when the centre of the conditional distribution is of interest.
Rights:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades.
Language:	Anglès
Document:	Article ; recerca ; Versió publicada
Subject:	Outliers ; Quantile regression ; Single factor models ; Nonlinear ; Multiplicative
Published in:	SORT : statistics and operations research transactions, Vol. 45 Núm. 2 (July-December 2021) , p. 163-180 (Articles) , ISSN 2013-8830

Adreça alternativa: https://raco.cat/index.php/SORT/article/view/394437
DOI: 10.2436/20.8080.02.114

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