as “ _PEP_ ”; (3) by foreign shareholders—either foreign government or private shareholders—the bank is classified as _foreign-_ owned; and (4) by the Kazakhstan government, the bank is classified as “ _state local_ .” Table 2 reports the total number of observations in the sample and the breakdown over time of the number of banks by ownership type.

A sufficiently important bank can be rescued because of the large ramifications within the banking system (Freixas and Rochet, 2013). Systemic importance is a multidimensional concept (Financial Stability Board et al., 2009) that is often proxied using bank size (Drehmann and Tarashev, 2011), computed as the natural logarithm of bank total assets ( _size_ ). We follow this practice in the literature. We also include a measure of severity of banking system troubles computed as the total number of banks in distress in each year to control for the potential presence of a Too-Many-To-Fail effect that affects the regulatory response (Acharya and Yorulmazer, 2007; Brown and Dinç, 2011).

We also include additional controls that may explain the likelihood and severity (cost) of resolution. To that effect, we employ the traditional _CAMEL_ framework.<sup>t</sup> Through _C_ , we account for _capital_ adequacy using the variable total regulatory capital to risk-weighted assets. Through _A_ , we control for _asset_ quality measured by the ratio of loan loss provisions to total gross loans. Through _M,_ we control for _management_ quality using the ratio of overhead costs to total income. Through _E_ , we control for _earning_ s (profitability) using interest margin divided by total assets. Through _L_ , we control for _liquidity_ which is captured through the ratio of liquid assets to deposits. Due to the lag structure of the empirical model, data for CAMEL variables are drawn from 2008 through 2020. Furthermore, we compute annual averages for the indicators for each bank using the monthly information. Finally, we include macroeconomic variables to account for the overall economic conditions of the economy that may explain a rise in systemic risk. To keep a parsimonious specification, we source the data through the World Bank’s Development Indicators and consider real GDP growth and inflation rate.

**Table 2: Bank ownership in Kazakhstan between January 2009 and August 2021 (# of banks)**

|**Ownership**|**2009**|**2010**|**2011**|**2012**|**2013**|**2014**|**2015**|**2016**|**2017**|**2018**|**2019**|**2020**|**2021**|**Total**|
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
|Private|14|11|12|11|13|13|14|15|13|12|8|5|4|145|
|PEP|4|5|5|5|5|6|7|7|8|7|7|8|8|82|
|Foreign|15|17|17|17|15|14|13|12|11|12|12|13|13|181|
|State|4|5|5|5|5|5|4|1|1|1|1|1|1|39|
|Total|37|38|39|38|38|38|38|35|33|32|28|27|26|447|

Source: Own elaboration using data from the audited financial statements of the banks supplemented with news reports.

Note: The number of banks is taken over each year, i.e., if a bank exits the market in a year, it is still counted in the total number of banks per category in that year.

The sample of banks subject to at least one event of distress is smaller (253 observations) and the incidence of cases of resolution of distress is around 21 percent (see Table A3 in the

> t See Mare (2015) for a detailed explanation of the CAMEL framework.

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