IDEAS home Printed from https://ideas.repec.org/a/bla/reviec/v19y2011i1p189-206.html
   My bibliography  Save this article

EU Banks Rating Assignments: Is There Heterogeneity between New and Old Member Countries?

Author

Listed:
  • Guglielmo Maria Caporale
  • Roman Matousek
  • Chris Stewart

Abstract

We model EU countries' bank ratings using financial variables and allowing for intercept and slope heterogeneity. Our aim is to assess whether "old" and "new" EU countries are rated differently and to determine whether "new" ones are assigned lower ratings, ceteris paribus, than "old" ones. We find that country-specific factors (in the form of heterogeneous intercepts) are a crucial determinant of ratings. Whilst "new" EU countries typically have lower ratings than "old" ones, after controlling for financial variables we also discover that all countries have significantly different intercepts, confirming our prior belief. This intercept heterogeneity suggests that each country's rating is assigned uniquely, after controlling for differences in financial factors, which may reflect differences in country risk and the legal and regulatory framework that banks face (such as foreclosure laws). In addition, we find that ratings may respond differently to the liquidity and operating expenses to operating income variables across countries. Typically ratings are more responsive to the former and less sensitive to the latter for "new" EU countries compared with "old" EU countries.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Guglielmo Maria Caporale & Roman Matousek & Chris Stewart, 2011. "EU Banks Rating Assignments: Is There Heterogeneity between New and Old Member Countries?," Review of International Economics, Wiley Blackwell, vol. 19(1), pages 189-206, February.
  • Handle: RePEc:bla:reviec:v:19:y:2011:i:1:p:189-206
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Other versions of this item:

    References listed on IDEAS

    as
    1. Feng, D. & Gourieroux, C. & Jasiak, J., 2008. "The ordered qualitative model for credit rating transitions," Journal of Empirical Finance, Elsevier, vol. 15(1), pages 111-130, January.
    2. 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.
    3. Altman, Edward I. & Rijken, Herbert A., 2004. "How rating agencies achieve rating stability," Journal of Banking & Finance, Elsevier, vol. 28(11), pages 2679-2714, November.
    4. Caporale, Guglielmo Maria & Matousek, Roman & Stewart, Chris, 2012. "Ratings assignments: Lessons from international banks," Journal of International Money and Finance, Elsevier, vol. 31(6), pages 1593-1606.
    5. David F. Hendry & Carlos Santos, 2005. "Regression Models with Data‐based Indicator Variables," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 67(5), pages 571-595, October.
    6. Amato, Jeffery D. & Furfine, Craig H., 2004. "Are credit ratings procyclical?," Journal of Banking & Finance, Elsevier, vol. 28(11), pages 2641-2677, November.
    7. Manzoni, Katiuscia, 2004. "Modeling Eurobond credit ratings and forecasting downgrade probability," International Review of Financial Analysis, Elsevier, vol. 13(3), pages 277-300.
    8. Meyer, Paul A & Pifer, Howard W, 1970. "Prediction of Bank Failures," Journal of Finance, American Finance Association, vol. 25(4), pages 853-868, September.
    9. Carmen M. Reinhart, 2002. "An Introduction," The World Bank Economic Review, World Bank, vol. 16(2), pages 149-150, August.
    10. Ohlson, Ja, 1980. "Financial Ratios And The Probabilistic Prediction Of Bankruptcy," Journal of Accounting Research, Wiley Blackwell, vol. 18(1), pages 109-131.
    11. 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.
    12. Stefanescu, Catalina & Tunaru, Radu & Turnbull, Stuart, 2009. "The credit rating process and estimation of transition probabilities: A Bayesian approach," Journal of Empirical Finance, Elsevier, vol. 16(2), pages 216-234, March.
    13. David F. Hendry, 2001. "Modelling UK inflation, 1875-1991," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 255-275.
    14. James Kolari & Michele Caputo & Drew Wagner, 1996. "Trait Recognition: An Alternative Approach to Early Warning Systems in Commercial Banking," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 23(9-10), pages 1415-1434, December.
    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. Vincenzo D’Apice & Giovanni Ferri & Punziana Lacitignola, 2016. "Rating Performance and Bank Business Models: Is There a Change with the 2007–2009 Crisis?," Italian Economic Journal: A Continuation of Rivista Italiana degli Economisti and Giornale degli Economisti, Springer;Società Italiana degli Economisti (Italian Economic Association), vol. 2(3), pages 385-420, November.
    2. Themistokles Lazarides & Evaggelos Drimpetas, 2016. "Defining the factors of Fitch rankings in the European banking sector," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 6(2), pages 315-339, August.
    3. Salvador, Carlos & Pastor, Jose Manuel & Fernández de Guevara, Juan, 2014. "Impact of the subprime crisis on bank ratings: The effect of the hardening of rating policies and worsening of solvency," Journal of Financial Stability, Elsevier, vol. 11(C), pages 13-31.
    4. Alexander Karminsky & Richard Hainsworth & Vasily Solodkov, 2013. "Arm’s Length Method for Comparing Rating Scales," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 3(2), pages 114-135, December.
    5. Indermit S Gill & Naotaka Sugawara & Juan Zalduendo, 2014. "The Center Still Holds: Financial Integration in the Euro Area," Comparative Economic Studies, Palgrave Macmillan;Association for Comparative Economic Studies, vol. 56(3), pages 351-375, September.
    6. Salvador, Carlos & Fernández de Guevara, Juan & Pastor, José Manuel, 2018. "The adjustment of bank ratings in the financial crisis: International evidence," The North American Journal of Economics and Finance, Elsevier, vol. 44(C), pages 289-313.
    7. Ballis, Antonis & Ioannidis, Christos & Sifodaskalakis, Emmanouil, 2024. "Structural shifts in bank credit ratings," Journal of Financial Stability, Elsevier, vol. 73(C).
    8. Ozturk, Huseyin & Namli, Ersin & Erdal, Halil Ibrahim, 2016. "Modelling sovereign credit ratings: The accuracy of models in a heterogeneous sample," Economic Modelling, Elsevier, vol. 54(C), pages 469-478.
    9. Volkova, Olga (Волкова, Ольга) & Lvova, Irina (Львова, Ирина), 2016. "The bank's rating, the rating agencies, Basel II of, financial indicator, the econometric model [Влияние Финансовых Показателей На Международные Рейтинги Российских Банков]," Ekonomicheskaya Politika / Economic Policy, Russian Presidential Academy of National Economy and Public Administration, vol. 1, pages 177-195, February.
    10. Shen, Chung-Hua & Huang, Yu-Li & Hasan, Iftekhar, 2012. "Asymmetric benchmarking in bank credit rating," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 22(1), pages 171-193.

    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. Caporale, Guglielmo Maria & Matousek, Roman & Stewart, Chris, 2012. "Ratings assignments: Lessons from international banks," Journal of International Money and Finance, Elsevier, vol. 31(6), pages 1593-1606.
    2. Kimmel, Randall K. & Thornton, John H. & Bennett, Sara E., 2016. "Can statistics-based early warning systems detect problem banks before markets?," The North American Journal of Economics and Finance, Elsevier, vol. 37(C), pages 190-216.
    3. Zhivaikina, A. & Peresetsky, A., 2017. "Russian Bank Credit Ratings and Bank License Withdrawal 2012-2016," Journal of the New Economic Association, New Economic Association, vol. 36(4), pages 49-80.
    4. Psillaki, Maria & Tsolas, Ioannis E. & Margaritis, Dimitris, 2010. "Evaluation of credit risk based on firm performance," European Journal of Operational Research, Elsevier, vol. 201(3), pages 873-881, March.
    5. Alexander M. Karminsky & Ella Khromova, 2016. "Modelling banks’ credit ratings of international agencies," Eurasian Economic Review, Springer;Eurasia Business and Economics Society, vol. 6(3), pages 341-363, December.
    6. Alexander Karminsky, 2016. "Rating models: emerging market distinctions," Papers 1607.02422, arXiv.org.
    7. Balios, Dimitris & Thomadakis, Stavros & Tsipouri, Lena, 2016. "Credit rating model development: An ordered analysis based on accounting data," Research in International Business and Finance, Elsevier, vol. 38(C), pages 122-136.
    8. Jaspreet Kaur & Madhu Vij & Ajay Kumar Chauhan, 2023. "Signals influencing corporate credit ratings—a systematic literature review," DECISION: Official Journal of the Indian Institute of Management Calcutta, Springer;Indian Institute of Management Calcutta, vol. 50(1), pages 91-114, March.
    9. Anatoly Peresetsky & Alexandr Karminsky & Sergei Golovan, 2011. "Probability of default models of Russian banks," Economic Change and Restructuring, Springer, vol. 44(4), pages 297-334, November.
    10. 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.
    11. Peresetsky, A. A., 2011. "What factors drive the Russian banks license withdrawal," MPRA Paper 41507, University Library of Munich, Germany.
    12. Zeineb Affes & Rania Hentati-Kaffel, 2016. "Predicting US banks bankruptcy: logit versus Canonical Discriminant analysis," Post-Print halshs-01281948, HAL.
    13. Abhijit Sharma & Diara Md. Jadi & Damian Ward, 2021. "Analysing the determinants of financial performance for UK insurance companies using financial strength ratings information," Economic Change and Restructuring, Springer, vol. 54(3), pages 683-697, August.
    14. Zeineb Affes & Rania Hentati-Kaffel, 2016. "Predicting US banks bankruptcy: logit versus Canonical Discriminant analysis," Documents de travail du Centre d'Economie de la Sorbonne 16016, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    15. Rosati, Nicoletta & Bellia, Mario & Matos, Pedro Verga & Oliveira, Vasco, 2020. "Ratings matter: Announcements in times of crisis and the dynamics of stock markets," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 64(C).
    16. Papanikolaou, Nikolaos I., 2018. "To be bailed out or to be left to fail? A dynamic competing risks hazard analysis," Journal of Financial Stability, Elsevier, vol. 34(C), pages 61-85.
    17. repec:zbw:bofitp:2004_021 is not listed on IDEAS
    18. Anatoly Peresetsky & Alexandr Karminsky & Sergei Golovan, 2011. "Probability of default models of Russian banks," Economic Change and Restructuring, Springer, vol. 44(4), pages 297-334, November.
    19. Hwang, Ruey-Ching & Chung, Huimin & Chu, C.K., 2010. "Predicting issuer credit ratings using a semiparametric method," Journal of Empirical Finance, Elsevier, vol. 17(1), pages 120-137, January.
    20. Brian BARNARD, 2017. "Rating Migration and Bond Valuation: Decomposing Rating Migration Matrices from Market Data via Default Probability Term Structures," Expert Journal of Finance, Sprint Investify, vol. 5(1), pages 49-72.
    21. Пересецкий А.А., 2007. "Методы Оценки Вероятности Дефолта Банков," Журнал Экономика и математические методы (ЭММ), Центральный Экономико-Математический Институт (ЦЭМИ), vol. 43(3), июль.

    More about this item

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • C52 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Evaluation, Validation, and Selection
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages

    Statistics

    Access and download statistics

    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:bla:reviec:v:19:y:2011:i:1:p:189-206. 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: Wiley Content Delivery (email available below). General contact details of provider: http://www.blackwellpublishing.com/journal.asp?ref=0965-7576 .

    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.