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The effectiveness of TARP-CPP on the US Banking Industry: a new copula-based approach

Calabrese, Raffaella and Degl’Innocenti, Marta and Osmetti, Silvia Angela (2016) 'The effectiveness of TARP-CPP on the US Banking Industry: a new copula-based approach.' European Journal of Operational Research. ISSN 0377-2217

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Following the 2008 financial crisis, regulatory authorities and governments provided distressed banks with equity infusions in order to strengthen national banking systems. However, the effectiveness of these interventions for financial stability has not been extensively researched in the literature. In order to understand the effectiveness of these bailouts for the solvency of banks this paper proposes a new model: the Longitudinal Binary Generalised Extreme Value (LOBGEV) model. Differing from the existing models, the LOBGEV model allows us to analyse the temporal structure of the probability of failure for banks, for both those that received a bailout and for those that did not. In particular, it encompasses both the flexibility of the D-vine copula and the accuracy of the generalised extreme value model in estimating the probability of bank failure and of banks receiving approval for capital injection. We apply this new model to the US banking system from 2008 to 2013 in order to investigate how and to what extent the Troubled Asset Relief Program (TARP)- Capital Purchase Program (CPP) reduced the probability of the failure of commercial banks. We specifically identify a set of macroeconomic and bank-specific factors that affect the probability of bank failure for TARP-CCP recipients and for those that did not receive capital under TARP-CCP. Our results suggest that TARP-CPP provided only short-term relief for US commercial banks.

Item Type: Article
Uncontrolled Keywords: Binary data; D-vine copula model; Banking; TARP-CPP; Failure
Subjects: H Social Sciences > HB Economic Theory
H Social Sciences > HG Finance
Divisions: Faculty of Social Sciences > Economics, Department of
Depositing User: Jim Jamieson
Date Deposited: 29 Jul 2016 14:35
Last Modified: 27 Jul 2018 01:00

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