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Prepared by Johannes Herderschee and Li Lian Ong.
See empirical evidence in section D.
The Bulgarian Bank Restructuring Company owned the banks prior to privatization and managed the sales.
For example, Bulbank’s share of total banking assets declined from over 25 percent 1999 to under 10 percent in 2003.
Although the strengthening in credit growth started during the course of 2002, we define the credit boom period is as having begun from Q1 2003, as the quality of published financial statements improved with the presentation of more detailed data.
Assuming Fund staff GDP projection at the time, this would be equivalent to a credit flow of 10 percent of GDP, down from 12 percent of GDP in 2004.
However, this restriction would not apply to banks where the ratio of credits (including risk-weighted off-balance-sheet items) minus capital to total deposits—other than those by other financial institutions—was below 60 per cent. Eight banks fell into this category as at end-September 2005.
Normality of returns is assumed.
Ideally, market values of equity, assets and liabilities should be used in the calculations. In the absence of reliable market data, however, accounting values are used in this instance. The ROA is calculated as profit before foreign exchange revaluation, extraordinary and tax items. Typically, foreign exchange revaluation should be included in the profit item, as it is usually part of a bank’s normal operations. In this case, however, the breakdown of the components was not available prior to Q1 2003.
Existing studies generally apply annual data, while Cihak (2004) uses unpublished data of listed banks in Croatia. The panel regression approach is appropriate in that it reduces the amount of time-series data required, but still provides sufficient data for powerful tests; moreover, it exploits any cross-sectional variation in the data (see, for example, Hakkio, 1984; Frenkel and Rose, 1995)
The sharp rise in the Ζ-scores of foreign bank branches in 2005 is attributable to the substantial funding received by one of the 6 branches in this group from its parent.
The inclusion of state-owned banks, foreign branches and bank management corporations are for completeness; the caveat for the reliability of associated results is their relatively small sample sizes.
To enable a clearer interpretation of the resulting dummy coefficients, we assign a dummy variable to all four quarters (SEAS), while constraining the intercept term to zero.
The original Ζ-scores are all transformed by adding a constant to ensure that they are all positive, prior to the application of the natural logarithm. Interestingly, the majority of negative Ζ-scores tend to correspond with the branches of foreign banks. Not surprisingly, non-branch banks with negative Ζ-scores do not “survive” over time.
The results for equation (3) over the period up to Q4 2004 show that the banks increasing their share of the loan market up to that point had experienced a significant increase in solvency, perhaps justifying the implementation of credit ceilings by the authorities in an attempt to improve the soundness of the banking sector.
The pooled OLS results show very high adjusted R-squared coefficients, of greater than 90 percent. This is common for models containing dummy variables designed to capture structural sifts or seasonal factors, as these dummies may play a key role in generating the high R-squared figures (see Kennedy, 1998).
The authorities specifically note that the decline in the Ζ-score levels are not of particular concern at this stage, given that the banking sector as a whole is largely considered to have been over-capitalized.