IDEAS home Printed from https://ideas.repec.org/p/ecl/riceco/15-006.html
   My bibliography  Save this paper

Banking Crises, Early Warning Models, and Efficiency

Author

Listed:
  • Almanidis, Pavlos

    (Ernst & Young LLP)

  • Sickles, Robin C.

    (Rice U)

Abstract

This paper proposes a general model that combines the Mixture Hazard Model with the Stochastic Frontier Model for the purposes of investigating the main determinants of the failures and performances of a panel of U.S. commercial banks during the financial crisis that began in 2007. The combined model provides measures of the probability and time to failure conditional on a bank's performance and vice versa. Both continuous-time and discrete-time specifications of the model are considered in the paper. The estimation is carried out via the expectation-maximization algorithm due to incomplete information regarding the identity of at-risk banks. In- and out-of-sample predictive accuracy of the proposed models is investigated in order to assess their potential to serve as early warning tools.

Suggested Citation

  • Almanidis, Pavlos & Sickles, Robin C., 2015. "Banking Crises, Early Warning Models, and Efficiency," Working Papers 15-006, Rice University, Department of Economics.
  • Handle: RePEc:ecl:riceco:15-006
    as

    Download full text from publisher

    File URL: http://economics.rice.edu/file/713/download?token=3TomELDP
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Cole, Rebel A. & Gunther, Jeffery W., 1995. "Separating the likelihood and timing of bank failure," Journal of Banking & Finance, Elsevier, vol. 19(6), pages 1073-1089, September.
    2. Meyer, Bruce D, 1990. "Unemployment Insurance and Unemployment Spells," Econometrica, Econometric Society, vol. 58(4), pages 757-782, July.
    3. Berger, Allen N. & Mester, Loretta J., 2003. "Explaining the dramatic changes in performance of US banks: technological change, deregulation, and dynamic changes in competition," Journal of Financial Intermediation, Elsevier, vol. 12(1), pages 57-95, January.
    4. Richard S. Barr & Thomas F. Siems, 1994. "Predicting bank failure using DEA to quantify management quality," Financial Industry Studies Working Paper 94-1, Federal Reserve Bank of Dallas.
    5. Wheelock, David C & Wilson, Paul W, 1995. "Explaining Bank Failures: Deposit Insurance, Regulation, and Efficiency," The Review of Economics and Statistics, MIT Press, vol. 77(4), pages 689-700, November.
    6. Berger, Allen N. & Mester, Loretta J., 1997. "Inside the black box: What explains differences in the efficiencies of financial institutions?," Journal of Banking & Finance, Elsevier, vol. 21(7), pages 895-947, July.
    7. Deakin, Eb, 1972. "Discriminant Analysis Of Predictors Of Business Failure," Journal of Accounting Research, Wiley Blackwell, vol. 10(1), pages 167-179.
    8. Brenda González-Hermosillo & Ceyla Pazarbaşioğlu & Robert Billings, 1997. "Determinants of Banking System Fragility: A Case Study of Mexico," IMF Staff Papers, Palgrave Macmillan, vol. 44(3), pages 295-314, September.
    9. DeYoung, Robert, 2003. "The failure of new entrants in commercial banking markets: a split-population duration analysis," Review of Financial Economics, Elsevier, vol. 12(1), pages 7-33.
    10. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    11. 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.
    12. Robert DeYoung, 1999. "Birth, growth, and life or death of newly chartered banks," Economic Perspectives, Federal Reserve Bank of Chicago, vol. 23(Q III), pages 18-35.
    13. Martin, Daniel, 1977. "Early warning of bank failure : A logit regression approach," Journal of Banking & Finance, Elsevier, vol. 1(3), pages 249-276, November.
    14. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    15. 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.
    16. Rebel Cole & Jeffery Gunther, 1998. "Predicting Bank Failures: A Comparison of On- and Off-Site Monitoring Systems," Journal of Financial Services Research, Springer;Western Finance Association, vol. 13(2), pages 103-117, April.
    17. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    18. Sickles, Robin C & Taubman, Paul, 1986. "An Analysis of the Health and Retirement Status of the Elderly," Econometrica, Econometric Society, vol. 54(6), pages 1339-1356, November.
    19. Train,Kenneth E., 2009. "Discrete Choice Methods with Simulation," Cambridge Books, Cambridge University Press, number 9780521747387.
    20. Kenneth Kasa & Mark M. Spiegel, 2008. "The role of relative performance in bank closure decisions," Economic Review, Federal Reserve Bank of San Francisco, pages 17-29.
    21. Judy P. Sy & Jeremy M. G. Taylor, 2000. "Estimation in a Cox Proportional Hazards Cure Model," Biometrics, The International Biometric Society, vol. 56(1), pages 227-236, March.
    22. Battese, George E. & Coelli, Tim J., 1988. "Prediction of firm-level technical efficiencies with a generalized frontier production function and panel data," Journal of Econometrics, Elsevier, vol. 38(3), pages 387-399, July.
    23. Gary Whalen, 1991. "A proportional hazards model of bank failure: an examination of its usefulness as an early warning tool," Economic Review, Federal Reserve Bank of Cleveland, vol. 27(Q I), pages 21-31.
    24. Pitt, Mark M. & Lee, Lung-Fei, 1981. "The measurement and sources of technical inefficiency in the Indonesian weaving industry," Journal of Development Economics, Elsevier, vol. 9(1), pages 43-64, August.
    25. George E. Battese & Greg S. Corra, 1977. "Estimation Of A Production Frontier Model: With Application To The Pastoral Zone Of Eastern Australia," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 21(3), pages 169-179, December.
    26. Kaparakis, Emmanuel I & Miller, Stephen M & Noulas, Athanasios G, 1994. "Short-Run Cost Inefficiency of Commercial Banks: A Flexible Stochastic Frontier Approach," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 26(4), pages 875-893, November.
    27. Efthymios Tsionas & Theodore Papadogonas, 2006. "Firm exit and technical inefficiency," Empirical Economics, Springer, vol. 31(2), pages 535-548, June.
    28. David C. Wheelock & Paul W. Wilson, 2000. "Why do Banks Disappear? The Determinants of U.S. Bank Failures and Acquisitions," The Review of Economics and Statistics, MIT Press, vol. 82(1), pages 127-138, February.
    29. Yildiray Yildirim, 2008. "Estimating Default Probabilities of CMBS Loans with Clustering and Heavy Censoring," The Journal of Real Estate Finance and Economics, Springer, vol. 37(2), pages 93-111, August.
    30. Battese, George E. & Corra, Greg S., 1977. "Estimation Of A Production Frontier Model: With Application To The Pastoral Zone Of Eastern Australia," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 21(3), pages 1-11, December.
    31. Meyer, Paul A & Pifer, Howard W, 1970. "Prediction of Bank Failures," Journal of Finance, American Finance Association, vol. 25(4), pages 853-868, September.
    32. Shumway, Tyler, 2001. "Forecasting Bankruptcy More Accurately: A Simple Hazard Model," The Journal of Business, University of Chicago Press, vol. 74(1), pages 101-124, January.
    33. Cornwell, Christopher & Schmidt, Peter & Sickles, Robin C., 1990. "Production frontiers with cross-sectional and time-series variation in efficiency levels," Journal of Econometrics, Elsevier, vol. 46(1-2), pages 185-200.
    34. Baltensperger, Ernst, 1980. "Alternative approaches to the theory of the banking firm," Journal of Monetary Economics, Elsevier, vol. 6(1), pages 1-37, January.
    35. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    36. Sealey, Calvin W, Jr & Lindley, James T, 1977. "Inputs, Outputs, and a Theory of Production and Cost at Depository Financial Institutions," Journal of Finance, American Finance Association, vol. 32(4), pages 1251-1266, September.
    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. Evžen Kočenda & Ichiro Iwasaki, 2022. "Bank survival around the world: A meta‐analytic review," Journal of Economic Surveys, Wiley Blackwell, vol. 36(1), pages 108-156, February.
    2. Sanchez González, Jim & Restrepo-Tobón, Diego & Ramírez Hassan, Andrés, 2021. "Inefficiency and bank failure: A joint Bayesian estimation method of stochastic frontier and hazards models," Economic Modelling, Elsevier, vol. 95(C), pages 344-360.
    3. Zhiyong Li & Chen Feng & Ying Tang, 2022. "Bank efficiency and failure prediction: a nonparametric and dynamic model based on data envelopment analysis," Annals of Operations Research, Springer, vol. 315(1), pages 279-315, August.

    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. Mai, Nhat Chi, 2015. "Efficiency of the banking system in Vietnam under financial liberalization," OSF Preprints qsf6d, Center for Open Science.
    2. Sanchez González, Jim & Restrepo-Tobón, Diego & Ramírez Hassan, Andrés, 2021. "Inefficiency and bank failure: A joint Bayesian estimation method of stochastic frontier and hazards models," Economic Modelling, Elsevier, vol. 95(C), pages 344-360.
    3. Pavlos Almanidis, 2013. "Accounting for heterogeneous technologies in the banking industry: a time-varying stochastic frontier model with threshold effects," Journal of Productivity Analysis, Springer, vol. 39(2), pages 191-205, April.
    4. Pavlos Almanidis & Mustafa U. Karakaplan & Levent Kutlu, 2019. "A dynamic stochastic frontier model with threshold effects: U.S. bank size and efficiency," Journal of Productivity Analysis, Springer, vol. 52(1), pages 69-84, December.
    5. Massimo Del Gatto & Adriana Di Liberto & Carmelo Petraglia, 2011. "Measuring Productivity," Journal of Economic Surveys, Wiley Blackwell, vol. 25(5), pages 952-1008, December.
    6. Manlagnit, Maria Chelo V., 2015. "Basel regulations and banks’ efficiency: The case of the Philippines," Journal of Asian Economics, Elsevier, vol. 39(C), pages 72-85.
    7. Tim J. Coelli, 1995. "Recent Developments In Frontier Modelling And Efficiency Measurement," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 39(3), pages 219-245, December.
    8. Manlagñit, Maria Chelo V., 2011. "Cost efficiency, determinants, and risk preferences in banking: A case of stochastic frontier analysis in the Philippines," Journal of Asian Economics, Elsevier, vol. 22(1), pages 23-35, February.
    9. Martín Rossi, 2015. "The Econometrics Approach to the Measurement of Efficiency: A Survey," Working Papers 117, Universidad de San Andres, Departamento de Economia, revised Feb 2015.
    10. Guo Li & Lee Sanning & Sherrill Shaffer, 2009. "Statistical opacity in the US banking sector," CAMA Working Papers 2009-16, Centre for Applied Macroeconomic Analysis, Crawford School of Public Policy, The Australian National University.
    11. Cole, Rebel A. & Wu, Qiongbing, 2009. "Is hazard or probit more accurate in predicting financial distress? Evidence from U.S. bank failures," MPRA Paper 24688, University Library of Munich, Germany, revised 01 Aug 2010.
    12. Martin, Sheila Ann, 1992. "The effectiveness of state technology incentives: evidence from the machine tool industry," ISU General Staff Papers 1992010108000011381, Iowa State University, Department of Economics.
    13. Thomas B. King & Daniel A. Nuxoll & Timothy J. Yeager, 2006. "Are the causes of bank distress changing? can researchers keep up?," Review, Federal Reserve Bank of St. Louis, vol. 88(Jan), pages 57-80.
    14. Léopold Simar & Paul W. Wilson, 2015. "Statistical Approaches for Non-parametric Frontier Models: A Guided Tour," International Statistical Review, International Statistical Institute, vol. 83(1), pages 77-110, April.
    15. Guohua Feng & Apostolos Serletis, 2009. "Efficiency and productivity of the US banking industry, 1998-2005: evidence from the Fourier cost function satisfying global regularity conditions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 24(1), pages 105-138.
    16. Williams, Jonathan & Nguyen, Nghia, 2005. "Financial liberalisation, crisis, and restructuring: A comparative study of bank performance and bank governance in South East Asia," Journal of Banking & Finance, Elsevier, vol. 29(8-9), pages 2119-2154, August.
    17. 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.
    18. Luis R. Murillo‐Zamorano, 2004. "Economic Efficiency and Frontier Techniques," Journal of Economic Surveys, Wiley Blackwell, vol. 18(1), pages 33-77, February.
    19. Timothy King & Jonathan Williams, 2013. "Bank Efficiency and Executive Compensation," Working Papers 13009, Bangor Business School, Prifysgol Bangor University (Cymru / Wales).
    20. Sickles, Robin C., 2005. "Panel estimators and the identification of firm-specific efficiency levels in parametric, semiparametric and nonparametric settings," Journal of Econometrics, Elsevier, vol. 126(2), pages 305-334, June.

    More about this item

    JEL classification:

    • C33 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Models with Panel Data; Spatio-temporal Models
    • C41 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Duration Analysis; Optimal Timing Strategies
    • C51 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Model Construction and Estimation
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity
    • G01 - Financial Economics - - General - - - Financial Crises
    • 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:ecl:riceco:15-006. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/dericus.html .

    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.