Predicting bivariate binary rare events responses using generalised extreme value regression model and copula function

Silvia Angela Osmetti, Raffaella Calabrese

Risultato della ricerca: Contributo in libroContributo a convegno

Abstract

A new bivariate Generalised Linear Model (GLM) is proposed for binary rare events, i.e. binary dependent variables with a very small number of ones. In a bivariate GLM model we suggest the quantile function of the Generalised Extreme Value (GEV) distribution. In this way, the drawback of the underestimation of the probability of the rare event in GLM models is overcome. The dependence between the response variables is modelled by the copula function. We explore different copula functions that provide a rich and flexible class of structures to derive joint distributions for bivariate binary data. Finally, we apply the proposed model to estimate the joint probability of defaults of UK and Italian small and medium enterprises.
Lingua originaleEnglish
Titolo della pubblicazione ospitePROGRAMME AND ABSTRACTS 7th International Conference on Computational and Financial Econometrics (CFE 2013) and 6th International Conference of the ERCIM (European Research Consortium for Informatics and Mathematics) Working Group on Computational and Methodological Statistics (ERCIM 2013)
Pagine176
Numero di pagine1
Stato di pubblicazionePubblicato - 2013
Evento6th International Conference of the ERCIM WG on Computational and Methodological Statistics (ERCIM 2013) - Londra
Durata: 14 dic 201316 dic 2014

Convegno

Convegno6th International Conference of the ERCIM WG on Computational and Methodological Statistics (ERCIM 2013)
CittàLondra
Periodo14/12/1316/12/14

Keywords

  • COPULA
  • generalized extreme value distribution

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