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Early warning models in real time

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Author Info
Jeffery W. Gunther
Robert R. Moore
Abstract

Each quarter, banks file a call report, or Report of Condition and Income, containing hundreds of accounting items pertaining to their financial condition. Because call reports are filed quarterly, whereas banks are typically examined about once every twelve to eighteen months, statistical early warning models using call report data potentially provide a more up-to-date picture of a bank's condition than on-site exams alone. Often neglected, however, is the fact that call report data are subject to revision. We find evidence of a strong relationship between on-site exams and call report revisions. In addition, we evaluate a major class of early warning models using both originally published and revised data to assess whether model accuracy in real time is appreciably lower than accuracy measured using revised data. The findings indicate revised data overstate the accuracy of early warning models. The substantial effect of revisions on the accuracy of early warning models, coupled with the finding of a relationship between revisions and exams, points to a substantial auditing role for on-site exams. More generally, our findings point to the need for care in the use of call report data for research in which the real-time flow of financial information is of some concern.

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File URL: http://www.dallasfed.org/banking/fiswp/fiswp0001.pdf
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Paper provided by Federal Reserve Bank of Dallas in its series Financial Industry Studies Working Paper with number 00-01.

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Date of creation: 2000
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Handle: RePEc:fip:feddfi:00-01

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Keywords: Econometrics ; Banks and banking - Accounting ; Bank supervision;

References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:

  1. Rebel Cole & Jeffery Gunther, 1998. "Predicting Bank Failures: A Comparison of On- and Off-Site Monitoring Systems," Journal of Financial Services Research, Springer, vol. 13(2), pages 103-117, April. [Downloadable!] (restricted)
  2. Rebel A. Cole & Jeffery W. Gunther, 1995. "FIMS: a new monitoring system for banking institutions," Federal Reserve Bulletin, Board of Governors of the Federal Reserve System (U.S.), issue Jan, pages 1-15.
  3. Larry D. Wall & Timothy W. Koch, 2000. "Bank loan-loss accounting: a review of theoretical and empirical evidence," Economic Review, Federal Reserve Bank of Atlanta, issue Q2, pages 1-20. [Downloadable!]
  4. Berger, Allen N. & King, Kathleen Kuester & O'Brien, James M., 1991. "The limitations of market value accounting and a more realistic alternative," Journal of Banking & Finance, Elsevier, vol. 15(4-5), pages 753-783, September. [Downloadable!] (restricted)
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(explanations, Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.)

  1. Douglas Evanoff & Larry Wall, 2001. "Sub-debt Yield Spreads as Bank Risk Measures," Journal of Financial Services Research, Springer, vol. 20(2), pages 121-145, October. [Downloadable!] (restricted)
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  2. John Krainer & Jose A. Lopez, 2003. "How might financial market information be used for supervisory purposes?," Economic Review, Federal Reserve Bank of San Francisco, pages 29-45. [Downloadable!]
  3. R. Alton Gilbert & Andrew P. Meyer & Mark D. Vaughan, 2002. "Could a CAMELS downgrade model improve off-site surveillance?," Review, Federal Reserve Bank of St. Louis, issue Jan., pages 47-63. [Downloadable!]
  4. Andrew Stone & Sharon Wardrop, 2002. "Real-time National Accounts Data," RBA Research Discussion Papers rdp2002-05, Reserve Bank of Australia. [Downloadable!]
  5. Julapa Jagtiani & James Kolari & Catharine Lemieux & Hwan Shin, 2003. "Early warning models for bank supervision: Simpler could be better," Economic Perspectives, Federal Reserve Bank of Chicago, issue Q III, pages 49-60. [Downloadable!]
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