IDEAS home Printed from https://ideas.repec.org/a/eee/proeco/v171y2016ip3p438-452.html
   My bibliography  Save this article

Performance drivers of shipping loans: An empirical investigation

Author

Listed:
  • Mitroussi, K.
  • Abouarghoub, W.
  • Haider, J.J.
  • Pettit, S.J.
  • Tigka, N.

Abstract

Credit risk is a major issue for lenders and borrowers, threatening the reliability of global logistics operations. Enhanced mechanisms of credit risk analysis are needed to safeguard banks and the flow of goods in supply chains. Little emphasis has been given to the contextual examination of such factors, either in terms of market conditions or the particular characteristics of different industries. This paper investigates the varying importance of a number of factors connected with the performance of corporate bank loans during times of financial turbulence in the shipping industry. Little extant literature exists on default risk drivers for loans made to shipping companies for new build vessels or second-hand ship purchases. A binary logit model is used to examine the criteria for assessing the security of shipping loans issued by banks. Thirty shipping loans made during the period 2005–2009 are examined. Results suggest that financial factors, non-financial factors, shipowners׳ experience, and employability and market risk indicators are the best criteria for evaluating the performance of shipping loans during turbulent market conditions and periods when financing options are restricted. The paper makes a specific contribution to the literature on risk management with regard to credit risk analysis by highlighting shipping specific factors and their importance for risk measurement. The results are of interest to banks seeking to accurately assess the credibility of shipping loans; shipowners, who can identify credit risk factors on which to focus; and supply chain participants where unfulfilled bank financing can cause disruptions to their logistics operations.

Suggested Citation

  • Mitroussi, K. & Abouarghoub, W. & Haider, J.J. & Pettit, S.J. & Tigka, N., 2016. "Performance drivers of shipping loans: An empirical investigation," International Journal of Production Economics, Elsevier, vol. 171(P3), pages 438-452.
  • Handle: RePEc:eee:proeco:v:171:y:2016:i:p3:p:438-452
    DOI: 10.1016/j.ijpe.2015.09.041
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0925527315003801
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.ijpe.2015.09.041?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Graham, John R. & Li, Si & Qiu, Jiaping, 2008. "Corporate misreporting and bank loan contracting," Journal of Financial Economics, Elsevier, vol. 89(1), pages 44-61, July.
    2. Grammenos, Costas Th. & Arkoulis, Angelos G., 2003. "Determinants of spreads on new high yield bonds of shipping companies," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 39(6), pages 459-471, November.
    3. DeYoung, Robert, 1997. "A diagnostic test for the distribution-free efficiency estimator: An example using U.S. commercial bank data," European Journal of Operational Research, Elsevier, vol. 98(2), pages 243-249, April.
    4. Yurdakul, Mustafa & Ic, Yusuf Tansel, 2004. "AHP approach in the credit evaluation of the manufacturing firms in Turkey," International Journal of Production Economics, Elsevier, vol. 88(3), pages 269-289, April.
    5. Zhang, Guoqiang & Y. Hu, Michael & Eddy Patuwo, B. & C. Indro, Daniel, 1999. "Artificial neural networks in bankruptcy prediction: General framework and cross-validation analysis," European Journal of Operational Research, Elsevier, vol. 116(1), pages 16-32, July.
    6. Manolis G. Kavussanos & Ilias D. Visvikis, 2006. "Shipping freight derivatives: a survey of recent evidence," Maritime Policy & Management, Taylor & Francis Journals, vol. 33(3), pages 233-255, July.
    7. Somerville, R. A. & Taffler, R. J., 1995. "Banker judgement versus formal forecasting models: The case of country risk assessment," Journal of Banking & Finance, Elsevier, vol. 19(2), pages 281-297, May.
    8. Grunert, Jens & Norden, Lars & Weber, Martin, 2005. "The role of non-financial factors in internal credit ratings," Journal of Banking & Finance, Elsevier, vol. 29(2), pages 509-531, February.
    9. Manolis Kavussanos, 1997. "The dynamics of time-varying volatilities in different size second-hand ship prices of the dry-cargo sector," Applied Economics, Taylor & Francis Journals, vol. 29(4), pages 433-443.
    10. Grammenos, Costas Th. & Alizadeh, Amir H. & Papapostolou, Nikos C., 2007. "Factors affecting the dynamics of yield premia on shipping seasoned high yield bonds," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 43(5), pages 549-564, September.
    11. Jimenez, Gabriel & Saurina, Jesus, 2004. "Collateral, type of lender and relationship banking as determinants of credit risk," Journal of Banking & Finance, Elsevier, vol. 28(9), pages 2191-2212, September.
    12. Bonfim, Diana, 2009. "Credit risk drivers: Evaluating the contribution of firm level information and of macroeconomic dynamics," Journal of Banking & Finance, Elsevier, vol. 33(2), pages 281-299, February.
    13. Blome, Constantin & Schoenherr, Tobias, 2011. "Supply chain risk management in financial crises--A multiple case-study approach," International Journal of Production Economics, Elsevier, vol. 134(1), pages 43-57, November.
    14. Ran Barniv & Anurag Agarwal & Robert Leach, 2002. "Predicting Bankruptcy Resolution," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 29(3&4), pages 497-520.
    15. Ran Barniv & Anurag Agarwal & Robert Leach, 2002. "Predicting Bankruptcy Resolution," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 29(3‐4), pages 497-520, April.
    16. Morris A. Cohen & Suman Mallik, 1997. "Global Supply Chains: Research And Applications," Production and Operations Management, Production and Operations Management Society, vol. 6(3), pages 193-210, September.
    17. Grammenos, C.Th. & Nomikos, N.K. & Papapostolou, N.C., 2008. "Estimating the probability of default for shipping high yield bond issues," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 44(6), pages 1123-1138, November.
    18. Amir H. Alizadeh & Nikos K. Nomikos, 2009. "Shipping Derivatives and Risk Management," Palgrave Macmillan Books, Palgrave Macmillan, number 978-0-230-23580-9, December.
    19. Altman, Edward I. & Haldeman, Robert G. & Narayanan, P., 1977. "ZETATM analysis A new model to identify bankruptcy risk of corporations," Journal of Banking & Finance, Elsevier, vol. 1(1), pages 29-54, June.
    20. Roberto Blanco & Simon Brennan & Ian W. Marsh, 2005. "An Empirical Analysis of the Dynamic Relation between Investment‐Grade Bonds and Credit Default Swaps," Journal of Finance, American Finance Association, vol. 60(5), pages 2255-2281, October.
    21. Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, September.
    22. Sudheer Chava & Dmitry Livdan & Amiyatosh Purnanandam, 2009. "Do Shareholder Rights Affect the Cost of Bank Loans?," The Review of Financial Studies, Society for Financial Studies, vol. 22(8), pages 2973-3004, August.
    23. Beatty, Anne & Ramesh, K. & Weber, Joseph, 2002. "The importance of accounting changes in debt contracts: the cost of flexibility in covenant calculations," Journal of Accounting and Economics, Elsevier, vol. 33(2), pages 205-227, June.
    24. H. K. Leggate, 2000. "A European perspective on bond finance for the maritime industry," Maritime Policy & Management, Taylor & Francis Journals, vol. 27(4), pages 353-362.
    25. Stephen X. Gong & Heng-Qing Ye & Yvonne Yiyi Zeng, 2013. "Impacts of the recent financial crisis on ship financing in Hong Kong: a research note," Maritime Policy & Management, Taylor & Francis Journals, vol. 40(1), pages 1-9, January.
    26. Pal, Rudrajeet & Torstensson, Håkan & Mattila, Heikki, 2014. "Antecedents of organizational resilience in economic crises—an empirical study of Swedish textile and clothing SMEs," International Journal of Production Economics, Elsevier, vol. 147(PB), pages 410-428.
    27. Yui-Yip Lau & Adolf K. Y. Ng & Xiaowen Fu & Kevin X. Li, 2013. "Evolution and research trends of container shipping," Maritime Policy & Management, Taylor & Francis Journals, vol. 40(7), pages 654-674, December.
    28. Chaffai, Mohamed E., 1997. "Estimating input-specific technical inefficiency: The case of the Tunisian banking industry," European Journal of Operational Research, Elsevier, vol. 98(2), pages 314-331, April.
    29. Meyer, Paul A & Pifer, Howard W, 1970. "Prediction of Bank Failures," Journal of Finance, American Finance Association, vol. 25(4), pages 853-868, September.
    30. Hendry, David F. & Richard, Jean-Francois, 1982. "On the formulation of empirical models in dynamic econometrics," Journal of Econometrics, Elsevier, vol. 20(1), pages 3-33, October.
    31. Edward I. Altman, 1968. "The Prediction Of Corporate Bankruptcy: A Discriminant Analysis," Journal of Finance, American Finance Association, vol. 23(1), pages 193-194, March.
    32. Amir Alizadeh & Wayne Talley, 2011. "Microeconomic determinants of dry bulk shipping freight rates and contract times," Transportation, Springer, vol. 38(3), pages 561-579, May.
    33. Amir H. Alizadeh & Nikos K. Nomikos, 2011. "Dynamics of the Term Structure and Volatility of Shipping Freight Rates," Journal of Transport Economics and Policy, University of Bath, vol. 45(1), pages 105-128, January.
    34. repec:wly:soecon:v:80:2:y:2013:p:540-561 is not listed on IDEAS
    35. Hau L. Lee & Christopher S. Tang, 1997. "Modelling the Costs and Benefits of Delayed Product Differentiation," Management Science, INFORMS, vol. 43(1), pages 40-53, January.
    36. Campbell, Tim S & Dietrich, J Kimball, 1983. "The Determinants of Default on Insured Conventional Residential Mortgage Loans," Journal of Finance, American Finance Association, vol. 38(5), pages 1569-1581, December.
    37. Wayne R. Archer & Peter J. Elmer & David M. Harrison & David C. Ling, 2002. "Determinants of Multifamily Mortgage Default," Real Estate Economics, American Real Estate and Urban Economics Association, vol. 30(3), pages 445-473.
    38. John A. Buzacott & Rachel Q. Zhang, 2004. "Inventory Management with Asset-Based Financing," Management Science, INFORMS, vol. 50(9), pages 1274-1292, September.
    39. Xu, Jane Jing & Yip, Tsz Leung & Marlow, Peter B., 2011. "The dynamics between freight volatility and fleet size growth in dry bulk shipping markets," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 47(6), pages 983-991.
    40. Morris A. Cohen & Hau L. Lee, 1988. "Strategic Analysis of Integrated Production-Distribution Systems: Models and Methods," Operations Research, INFORMS, vol. 36(2), pages 216-228, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Marina Maniati & Evangelos Sambracos, 2017. "Decision-making process in shipping finance: A stochastic approach," Cogent Economics & Finance, Taylor & Francis Journals, vol. 5(1), pages 1317083-131, January.
    2. Alexandridis, George & Kavussanos, Manolis G. & Kim, Chi Y. & Tsouknidis, Dimitris A. & Visvikis, Ilias D., 2018. "A survey of shipping finance research: Setting the future research agenda," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 115(C), pages 164-212.
    3. Nurul Izzaty Hasanah Azhar & Norziana Lokman & Md. Mahmudul Alam & Jamaliah Said, 2021. "Factors determining Z-score and corporate failure in Malaysian companies," International Journal of Economics and Business Research, Inderscience Enterprises Ltd, vol. 21(3), pages 370-386.
    4. Kavussanos, Manolis G. & Tsouknidis, Dimitris A., 2016. "Default risk drivers in shipping bank loans," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 94(C), pages 71-94.
    5. Jane Haider & Zhirong Ou & Stephen Pettit, 2019. "Predicting corporate failure for listed shipping companies," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 21(3), pages 415-438, September.
    6. Mark Clintworth & Dimitrios Lyridis & Evangelos Boulougouris, 2023. "Financial risk assessment in shipping: a holistic machine learning based methodology," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 25(1), pages 90-121, March.
    7. Agata Lozinskaia & Andreas Merikas & Anna Merika & Henry Penikas, 2017. "Determinants of the probability of default: the case of the internationally listed shipping corporations," Maritime Policy & Management, Taylor & Francis Journals, vol. 44(7), pages 837-858, October.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Alexandridis, George & Kavussanos, Manolis G. & Kim, Chi Y. & Tsouknidis, Dimitris A. & Visvikis, Ilias D., 2018. "A survey of shipping finance research: Setting the future research agenda," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 115(C), pages 164-212.
    2. Kavussanos, Manolis G. & Tsouknidis, Dimitris A., 2016. "Default risk drivers in shipping bank loans," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 94(C), pages 71-94.
    3. Jane Haider & Zhirong Ou & Stephen Pettit, 2019. "Predicting corporate failure for listed shipping companies," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 21(3), pages 415-438, September.
    4. Mark Clintworth & Dimitrios Lyridis & Evangelos Boulougouris, 2023. "Financial risk assessment in shipping: a holistic machine learning based methodology," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 25(1), pages 90-121, March.
    5. Rassoul Yazdipour & Richard Constand, 2010. "Predicting Firm Failure: A Behavioral Finance Perspective," Journal of Entrepreneurial Finance, Pepperdine University, Graziadio School of Business and Management, vol. 14(3), pages 90-104, Fall.
    6. fernández, María t. Tascón & gutiérrez, Francisco J. Castaño, 2012. "Variables y Modelos Para La Identificación y Predicción Del Fracaso Empresarial: Revisión de La Investigación Empírica Reciente," Revista de Contabilidad - Spanish Accounting Review, Elsevier, vol. 15(1), pages 7-58.
    7. Erkki Laitinen, 2011. "Assessing viability of Finnish reorganization and bankruptcy firms," European Journal of Law and Economics, Springer, vol. 31(2), pages 167-198, April.
    8. Sunghwa Park & Hyunsok Kim & Janghan Kwon & Taeil Kim, 2021. "Empirics of Korean Shipping Companies’ Default Predictions," Risks, MDPI, vol. 9(9), pages 1-17, September.
    9. Şaban Çelik, 2013. "Micro Credit Risk Metrics: A Comprehensive Review," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 20(4), pages 233-272, October.
    10. Francesco Ciampi & Valentina Cillo & Fabio Fiano, 2020. "Combining Kohonen maps and prior payment behavior for small enterprise default prediction," Small Business Economics, Springer, vol. 54(4), pages 1007-1039, April.
    11. Drobetz, Wolfgang & Haller, Rebekka & Meier, Iwan, 2016. "Cash flow sensitivities during normal and crisis times: Evidence from shipping," Transportation Research Part A: Policy and Practice, Elsevier, vol. 90(C), pages 26-49.
    12. Kavussanos, Manolis G. & Tsouknidis, Dimitris A., 2014. "The determinants of credit spreads changes in global shipping bonds," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 70(C), pages 55-75.
    13. Cochran, James J. & Darrat, Ali F. & Elkhal, Khaled, 2006. "On the bankruptcy of internet companies: An empirical inquiry," Journal of Business Research, Elsevier, vol. 59(10-11), pages 1193-1200, October.
    14. Gropp, R. & Grundl, C. & Guttler, A., 2012. "Does Discretion in Lending Increase Bank Risk? Borrower Self-Selection and Loan Officer Capture Effects," Other publications TiSEM bfec5360-2a2b-47e4-ba3f-d, Tilburg University, School of Economics and Management.
    15. Filipe, Sara Ferreira & Grammatikos, Theoharry & Michala, Dimitra, 2016. "Forecasting distress in European SME portfolios," Journal of Banking & Finance, Elsevier, vol. 64(C), pages 112-135.
    16. Alina Mihaela Dima & Simona Vasilache, 2016. "Credit Risk modeling for Companies Default Prediction using Neural Networks," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(3), pages 127-143, September.
    17. Hu, Yu-Chiang & Ansell, Jake, 2007. "Measuring retail company performance using credit scoring techniques," European Journal of Operational Research, Elsevier, vol. 183(3), pages 1595-1606, December.
    18. Kolari, James & Glennon, Dennis & Shin, Hwan & Caputo, Michele, 2002. "Predicting large US commercial bank failures," Journal of Economics and Business, Elsevier, vol. 54(4), pages 361-387.
    19. Ha-Thu Nguyen, 2015. "How is credit scoring used to predict default in China?," EconomiX Working Papers 2015-1, University of Paris Nanterre, EconomiX.
    20. Vladislav V. Afanasev & Yulia A. Tarasova, 2022. "Default Prediction for Housing and Utilities Management Firms Using Non-Financial Data," Finansovyj žhurnal — Financial Journal, Financial Research Institute, Moscow 125375, Russia, issue 6, pages 91-110, December.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:proeco:v:171:y:2016:i:p3:p:438-452. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ijpe .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.