What factors drive the Russian banks license withdrawal
AbstractThe binary and multinomial logit models are applied for prediction of the Russian banks defaults (license withdrawals) using data from bank balance sheets and macroeconomic indicators. Significantly different models correspond to the two main grounds for license withdrawal: financial insolvency and money laundering. Analysis of data for the period 2005.2–2008.4 for accurate prediction of a bank’s financial insolvency, which is the focus of interest for the Russian Deposit Insurance Agency, demonstrates that the multinomial model doesn’t outperform the binary model.
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Bibliographic InfoPaper provided by University Library of Munich, Germany in its series MPRA Paper with number 41507.
Date of creation: 2011
Date of revision:
Multinomial logit model; binary logit model; probability of default; Russian banks; money laundering; bank supervision;
Find related papers by JEL classification:
- C50 - Mathematical and Quantitative Methods - - Econometric Modeling - - - General
- G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
- G33 - Financial Economics - - Corporate Finance and Governance - - - Bankruptcy; Liquidation
- G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
- G20 - Financial Economics - - Financial Institutions and Services - - - General
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