Default risk drivers in shipping bank loans

Manolis Kavussanos () and Dimitris Tsouknidis

Transportation Research Part E: Logistics and Transportation Review, 2016, vol. 94, issue C, 71-94

Abstract: This paper proposes a credit scoring model for the empirical assessment of default risk drivers of shipping bank loans. A unique dataset, consisting of the credit portfolio of a ship-lending bank is used to estimate a logit model with two-way clustered adjusted standard errors, ensuring robust inferences. Industry specific variables, captured through current and expected conditions in the extremely volatile global shipping freight markets, the risk appetite of borrowers–the shipowners – expressed through the chartering policy they follow – and a pricing variable, are shown for the first time to be the important factors explaining default probabilities of bank loans.

Keywords: Default risk; Bank loans; Credit scoring models; Shipping (search for similar items in EconPapers)
JEL-codes: C25 G21 G33 (search for similar items in EconPapers)
Date: 2016
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Citations: View citations in EconPapers (14)

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DOI: 10.1016/j.tre.2016.07.008

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