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Title: Median bilinear models in presence of extreme values
Author: Santolino, Miguel
Keywords: Anàlisi de regressió
Estimació d'un paràmetre
Operadors no lineals
Valor (Economia)
Regression analysis
Parameter estimation
Nonlinear operators
Value (Economics)
Issue Date: 17-Nov-2021
Publisher: Institut d'Estadística de Catalunya
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.
Note: Reproducció del document publicat a:
It is part of: Sort (Statistics and Operations Research Transactions), 2021, vol. 46, num. 2, p. 1-18
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ISSN: 1696-2281
Appears in Collections:Articles publicats en revistes (Econometria, Estadística i Economia Aplicada)

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