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Autor
Serwa Dobromił (Warsaw School of Economics, Poland)
Tytuł
Using nonperforming loan ratios to compute loan default rates with evidence from european banking sectors
Źródło
Econometric Research in Finance, 2016, vol. 1, nr 1, s. 47-65, tab., wykr., bibliogr. 14 poz.
Słowa kluczowe
Sektor bankowy, Strategia banku
Banking sector, Banking strategy
Uwagi
JEL clasiffication: C15, C22, G21, G31
summ.
Abstrakt
This research is the first attempt to calibrate default rates of loan portfolios using raw data on nonperforming loans and some additional information on the maturity structure of the loan portfolios. We applied a simple model of loan quality, controlling for loan maturities and dynamics of loan supply. Results for nine national aggregate indices of nonperforming housing loans in the Czech Republic, Greece, Ireland, Hungary, Latvia, Poland, Portugal, Romania, and Spain revealed strong differences in the dynamics of calibrated default probabilities between countries. Calibrated default rates were correlated with macroeconomic factors, but the linkages depended on the markets investigated.(original abstract)
Dostępne w
Biblioteka SGH im. Profesora Andrzeja Grodka
Pełny tekst
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Bibliografia
Pokaż
  1. Aman, H., Miyazaki, H. (2009). Valuation effects of new equity issues by banks: evidence from Japan. "Applied Financial Economics", 19(8):635-645.
  2. Cihak, M. , Schaeck, K. (2010). How well do aggregate prudential ratios identify banking system problems? "Journal of Financial Stability", 6(3):130 - 144.
  3. Coricelli, F., Mucci, F., Revoltella, D. (2006). Household Credit in the New Europe: Lending Boom or Sustainable Growth? CEPR Discussion Papers 5520, C.E.P.R. Discussion Papers.
  4. Festic, M., Repina, S., Kavkler, A. (2009). The Up-Coming Crisis and the Banking Sector in the Baltic States. "Swiss Journal of Economics and Statistics" (SJES), 145(III):269-291.
  5. Hasan, I., Wall, L. D. (2004). Determinants of the Loan Loss Allowance: Some Cross- Country Comparisons. "Financial Review", 39(1): 129-152.
  6. Jin, J. Y., Kanagaretnam, K., Lobo, G. J. (2011). Ability of accounting and audit quality variables to predict bank failure during the financial crisis. "Journal of Banking and Finance", 35(11):2811 - 2819.
  7. Lizal, L., Svejnar, J. (2002). Investment, Credit Rationing, And The Soft Budget Con- straint: Evidence From Czech Panel Data. "The Review of Economics and Statistics", 84(2):353-370.
  8. Meeker, L. G., Gray, L. (1987). A note on non-performing loans as an indicator of asset quality. "Journal of Banking and Finance", 11(1): 161 - 168.
  9. Mendoza, E. G., Terrones, M. E. (2008). An Anatomy Of Credit Booms: Evidence From Macro Aggregates And Micro Data. NBER Working Papers 14049, National Bureau of Economic Research, Inc.
  10. Pinto, R. L., Vivan, G. F. A. (2013). Converting the NPL Ratio into a Comparable Long Term Metric. Working Papers Series 309, Central Bank of Brazil, Research Department.
  11. Podpiera, R. (2006). Does Compliance with Basel Core Principles Bring Any Measurable Benefits? IMF Staff Papers, 53(2):5.
  12. Serwa, D. (2013). Measuring Non-Performing Loans During (and After) Credit Booms. "Central European Journal of Economic Modelling and Econometrics", 5(3): 163-183.
  13. Tornell, A., Westermann, F. (2002). Boom-Bust Cycles in Middle Income Countries: Facts and Explanation. NBER Working Papers 9219, National Bureau of Economic Research, Inc.
  14. Whalen, G. W. (2010). Are Early Warning Models Still Useful Tools for Bank Supervisors? Economics Working Paper 2010-3, Office of the Comptroller of the Currency, Washington DC.
Cytowane przez
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ISSN
2451-1935
2451-2370
Język
eng
URI / DOI
https://doi.org/10.33119/ERFIN.2016.1.1.3
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