Bank failures and mergers in Turkey: 1992-2014
Keywords:Bank crisis, Bank policy making, Capitalization, Duration model, Mergers & acquisitions (M&A).
AbstractThe Turkish banking system went through a period of crisis in 1999-2001. As a result, reforms were instituted and the banking system was consolidated. The system was then only mildly affected by the global crisis in 2008. This study examines the process of bank failures and mergers and acquisitions during this period in Turkey. A proportional hazard is used to determine the bank-specific accounting ratios that predict bank defaults and mergers and acquisitions in Turkey. The focus is on capitalization, a key regulatory tool. Capitalization decreases the failure rate, as expected, and does so at a decreasing rate. This is consistent with regulatory policy that focuses on capitalization. For banks at risk, income is a good short-run predictor of default. The results for mergers and acquisitions imply that under-capitalized banks are more likely to be acquired. Finally, the implied “frontier” for the trade-off between return and equity and default risk is calculated.
Andersen, H., 2008. Failure prediction of Norwegian banks: A logit approach. Norges Bank Working Paper 2.
Arena, M., 2008. Bank failures and bank fundamentals: A comparative analysis of Latin America and East Asia during the nineties using bank-level data. Journal of Banking & Finance, 32: 299-310.
Avkiran, N. K. & Cai, L. C., 2012. Predicting bank financial distress prior to crises. Working Paper.
Barr, R. S.; Seifors, L. M. & Siems, T. F., 1994. Forecasting bank failure: A non-parametric frontier estimation approach. Working Paper.
Basel Committee on Banking Supervision 2004. International convergence of capital mea- surement and capital standards: A revised framework, Technical report, Bank for International Settlements.
Basel Committee on Banking Supervision 2012. Core principles for banking supervision, Technical report, Bank for International Settlements.
Canbas, S., & Cabuk, K., 2005. Prediction of commercial bank failure via multivariate statistical analysis of financial structures: The Turkish case. European Journal of Operational Research, 166(2): 528–546.
Carree, M., 2003. A hazard rate analysis of Russian commercial banks in the period 1994-1997. Economic Systems, 255–269.
Cole, R. A., & White, L., 2012. Deja vu all over again: The causes of US commercial bank failures this time around. Journal of Financial Services Research, 42: 5–29.
Cox, D., 1972. Regression models and life-tables. Journal of the Royal Statistical Society, B34:187–220.
DeYoung, R., 2003. De novo bank exit. Journal of Money, Credit, and Banking, 35(5): 711–728.
Estrella, A.S.P., & Peristiani, S., 2000. Capital ratios as predictors of bank failure. Economic Policy Review, 6: 33–52.
Fiordelisi, F., & Mare, D.S., 2013. Probability of default and efficiency in cooperative banking. Journal of International Financial Markets, Institutions and Money, 26:30–45.
Gepp, A., & Kumar, K., 2008. The role of survival analysis in financial distress prediction. International Research Journal of Finance and Economics, Issue 16: 13–34.
Gomez-Gonzalez, J., & Kiefer, N.M., 2009. Bank failure: Evidence from the Colombian financial crisis. The International Journal of Business and Finance Research, 3: 15–31.
Gonzalez-Hermosillo, B., Pazarbasioglu, C., and Billings, R., 1996. Banking system fragility: Likelihood versus timing of failure: an application to the Mexican financial crisis. IMF Working Paper.
Gonzalez-Hermosillo, B., Pazarbaşioglu, C. and Billings, R., 1997. Determinants of Banking System Fragility: A Case Study of Mexico. Staff Papers - International Monetary Fund 44: 295-314.
Kiefer, N. M., 1988. Economic duration data and hazard functions. Journal of Economic Literature, XXVI: 646–679.
Lancaster, T., 1990. The Econometric Analysis of Transition Data. Cambridge University Press.
Lane, W. S. L., & Wansley, J., 1986. An application of the cox proportional hazards model to bank failure. Journal of Banking and Finance, 10: 511–531.
Maggiolini, P., & Mistrulli, P. E., 2005. A survival analysis of de novo co-operative credit banks. Empirical Economics, 30: 359–378.
Mannasoo, K., & Mayes, D. G., 2009. Explaining bank distress in Eastern European transition economies. Journal of Banking & Finance, 33(2): 244–253.
Molina, C., 2002. Predicting bank failures using a hazard model: The Venezuelan banking crisis. Emerging Markets Review, 3: 31–50.
Peek, J., Rosengren, E.,1995. Bank regulation and the credit crunch. Journal of Banking and Finance, 19: 679–692.
Schoenfeld, D., 1982. Partial residuals for the proportional hazards regression model. Biometrika, 69(1): 239–241.
Tatom, J., & Houston, R., 2011. Predicting failure in the commercial banking industry. Networks Financial Institute, Working Paper No. 2011/27.
Therneau, T., & Lumley, T., (2008) S original survival: Survival analysis, including penalised likelihood, R package version 2.
Van den Heuvel, S., 2004. The Bank Capital Channel of Monetary Policy. Wharton School University of Pennsylvania.
Weelock, D., & Wilson, P., 2000. Why do banks disappear? The determinants of U.S. bank failures and acquisitions. The Review of Economics and Statistics, 1: 127–138.
Whalen, G., 1991. A proportional hazards model of bank failure: An examination of its usefulness as an early warning tool. Economic Review, 27: 21–30.
Authors who publish with this journal agree to the following terms:
- Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
- Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
- Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) after official publication, as it can lead to productive exchanges as well as greater citation of published work (See The Effect of Open Access).