A new approach to measure systemic risk: A bivariate copula model for dependent censored data

Raffaella Calabrese () and Silvia Angela Osmetti

European Journal of Operational Research, 2019, vol. 279, issue 3, 1053-1064

Abstract: We propose a novel approach based on the Marshall–Olkin (MO) copula to estimate the impact of systematic and idiosyncratic components on cross-border systemic risk. To use the data on non-failed banks in the suggested method, we consider the time to bank failure as a censored variable. Therefore, we propose a pseudo-maximum likelihood estimation procedure for the MO copula for a Type I censored sample. We derive the log-likelihood function, the copula parameter estimator and the bootstrap confidence intervals. Empirical data on the banking system of three European countries (Germany, Italy and the UK) shows that the proposed censored model can accurately estimate the systematic component of cross-border systemic risk.

Keywords: OR in banking; Copula models; Pseudo-maximum likelihood estimation; Censored sampling; Systemic risk (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (10)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ejores:v:279:y:2019:i:3:p:1053-1064

DOI: 10.1016/j.ejor.2019.06.027

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