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Record Nr. |
UNINA9910788332503321 |
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Autore |
Loukoianova Elena |
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Titolo |
Banking Crises and Crisis Dating : : Theory and Evidence / / Elena Loukoianova, Gianni De Nicolo, John Boyd |
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Pubbl/distr/stampa |
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Washington, D.C. : , : International Monetary Fund, , 2009 |
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ISBN |
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1-4623-9007-2 |
1-4527-2282-X |
9786612843556 |
1-4518-7288-7 |
1-282-84355-9 |
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Descrizione fisica |
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1 online resource (52 p.) |
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Collana |
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Altri autori (Persone) |
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Soggetti |
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Bank failures - Econometric models |
Banks and banking - Econometric models |
Economic indicators |
Banks and Banking |
Financial Risk Management |
Macroeconomics |
Money and Monetary Policy |
Banks |
Depository Institutions |
Micro Finance Institutions |
Mortgages |
Financial Institutions and Services: Government Policy and Regulation |
Monetary Policy, Central Banking, and the Supply of Money and Credit: General |
Financial Crises |
Foreign Exchange |
Banking |
Economic & financial crises & disasters |
Monetary economics |
Deposit insurance |
Bank credit |
Banking crises |
Currency crises |
Banks and banking |
Crisis management |
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Credit |
Financial crises |
United States |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Nota di contenuto |
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Contents; I. Introduction and Summary; II. Major Classifications of Banking Crises; III. BC Indicators an d Their Discrepancies; IV. A Simple Banking Model; V. Evidence from Cross-Country Data: Benchmark Specifications; A. Logit Regressions with BC Indicators as Dependent Variables; B. SBS indicators Predict BC indicators; C. Logit Regressions with SBS Indicators as Dependent Variables; VI. Market Structure and Deposit Insurance; A. Bank Market Structure and Competition; B. Deposit Insurance; VII. Currency and "Twin" Crises; A. BC and SBS Indicators as Dependent Variables |
B. Currency Crises as Dependent VariablesVIII. Evidence from Bank-Level Data; A. Measures of Systemic Bank Shocks; B. SBS indicators Predict BC indicators; C. Market Structure, Deposit Insurance and External Shocks; VI. Conclusion; References; Tables; 1. BC Indicators; 2. Logit Regressions with Start Date BC Indicators (crisis dates after the first crisis year excluded); 3. Logit Regressions with BC Indicators (all observations with crisis dating); 4. Logit Regressions: Do SBS Lending Indicators Predict BC Indicators?; 5. Logit Regressions: Do SBS Deposit Indicators Predict BC Indicators? |
6. Logit Regressions with SBS Indicators ad Dependent Variables7. Logit Regressions: BC Indicators and Bank Concentration Measures; 8. Logit Regressions: SBS Indicators and Bank Concentration Measures; 9. Logit Regressions: BC Indicators, SBS Indicators and Deposit Insurance; 10. Logit Regressions: BC Indicators, SBS Indicators, Deposit Insurance Features and Quality of Institutions; 11. Logit Regressions: BC Indicators, Currency and Twin Crises; 12. Logit Regressions: SBS Indicators, Currency and Twin Crises; 13. Logit Regressions: Currency Crises and SBS Indicators |
14. Bank Level Data, Random Effect Logit Regressions: SBS Indicators Predict BC Indicators15. Bank Level Data, Random Effect Logit Regressions: Determinants of SBS and BC Indicators; A1. ""Systemic"" Banking Crises and Crisis Dating in Different Classifications |
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Sommario/riassunto |
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Many empirical studies of banking crises have employed "banking crisis" (BC) indicators constructedusing primarily information on government actions undertaken in response to bank distress. Weformulate a simple theoretical model of a banking industry which we use to identify and constructtheory-based measures of systemic bank shocks (SBS). Using both country-level and firm-level samples, we show that SBS indicators consistently predict BC indicators based on four major BCseries that have appeared in the literature. Therefore, BC indicatorsactually measure lagged government responses to systemic bank shocks, rather than the occurrence of crises per se. We re-examine the separate impact of macroeconomic factors, bank market structure, deposit insurance, andexternal shocks on the probability of a systemic bank shocks and on the probability of governmentresponses |
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to bank distress. The impact of these variables on the likelihood of a government responseto bank distress is totally different from that on the likelihood of a systemic bank shock.Disentangling the effects of systemic bank shocks and government responses turns out to be crucial inunderstanding the roots of bank fragility. Many findings of a large empirical literature need to be re-assessed and/or re-interpreted. |
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