Economics at your fingertips  

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: G21 G33 C25 (search for similar items in EconPapers)
Date: 2016
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8) Track citations by RSS feed

Downloads: (external link)
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link:

Ordering information: This journal article can be ordered from
http://www.elsevier. ... 600244/bibliographic

DOI: 10.1016/j.tre.2016.07.008

Access Statistics for this article

Transportation Research Part E: Logistics and Transportation Review is currently edited by W. Talley

More articles in Transportation Research Part E: Logistics and Transportation Review from Elsevier
Bibliographic data for series maintained by Haili He ().

Page updated 2020-11-26
Handle: RePEc:eee:transe:v:94:y:2016:i:c:p:71-94