BUS614: International Finance

In the empirical work below, we relate two variables using market prices to the systemic bank size and national public finance variables. Using stock price data, we first construct bank's market-to-book ratio as the market value of the bank's common equity divided by the book value of common equity. The market value of a bank's common equity is available from Datastream. The market-to-book ratio should reflect any costs or benefits of systemic bank size to bank shareholders. The market-to-book has a sample mean of 1.45 in the overall sample, as seen in Table 4.   

Table 4. Summary statistics on bank and country variables

This table presents summary statistics of variables. Market-to-book is market value of common equity divided by book value of common equity. CDS is annual average of daily credit default spreads for 5 -year contracts. Assets is natural logarithm of total assets in constant 2000 US dollars. Pre-tax profits is pre-tax profits divided by total assets. Earning assets is earning assets divided by total assets. Leverage is liabilities divided by total assets. GDP per capita is GDP per capita in constant 2000 dollars. Past crisis is dummy variable that is one if country is not currently experiencing a banking crisis but has experienced a banking crisis before and zero otherwise. Past fiscal cost is fiscal cost of resolving most recent but not current banking crisis divided by GDP. Public debt is central government debt divided by GDP. Fiscal balance is ratio of central government revenues minus expenses and minus depreciation of capital to GDP. Bank stock risk is annualized standard deviation of weekly dividend-inclusive bank stock returns. $Z$-score is Index of bank solvency constructed as $\frac{R O A+C A R}{S R O A}$ where ROA is return on assets, CAR represents capital assets ratio and SROA stands for standard deviation of return on assets. Liabilities is bank liabilities divided by GDP. Sum liabilities is sum of bank liabilities in a country divided by GDP. Other liabilities is sum of the liabilities of other banks in a country divided by GDP. Liabilities sq is square of ratio of bank liabilities to GDP. Big 0.1, Big 0.25 and Big 1 are dummy variables. They are equal to 1 if Liabilities-to-GDP ratio is greater than or equal to 0.1,0.25, and 1 respectively, and they otherwise equal 0.

Our second dependent variable is a bank's CDS spread. We construct a bank's yearly CDS spread as the average of daily CDS spreads, provided that there are at least 100 daily CDS spreads. We obtain CDS information from Markit. Typically, several CDS contracts are traded for a given major bank differing in the duration of the contract and in the definition of the deliverable bank liabilities in case of a specified credit event. Following Jorion and Zhang (2007), we consider 5-year CDS contracts as these contracts are the most liquid and constitute the majority of the entire CDS market. We further select on CDS contracts for senior unsecured debt with a modified restructuring (MR) clause.  Contracts can be denominated in dollars, euros or another major currency, with the currency of denomination selected in this order in case there are contracts in multiple currencies. 

The CDS spread provides a market indicator of expected credit losses on bank liabilities, as the seller of the CDS contract takes on the obligation to purchase specified bank liabilities at par in the event of a bank credit event, as set out in the CDS contract. CDS spreads provide direct market estimates of credit losses, as opposed to bond yield spreads that in addition contain a liquidity component . CDS spreads appear to reflect available information on credit future losses well, as they tend to anticipate debt downgrades, and may reflect insider information (see Acharya and Johnson (2007)), and as price discovery takes place primarily in the CDS market.  Knaup and Wagner (2009) have found that the correlation between bank stock returns and an index of corporate CDS spreads provides a good indication of bank asset risk exposure during the financial crisis of 2008. 

In practice, we have CDS spreads from 2001 to 2008, with CDS spreads available for a total of 59 banks in 2008, as seen in Table 5. In this table, we further see that the mean CDS spread per year has been extremely low for most years with a minimum of 0.23 percent in 2004, reaching a peak of 1.20 percent in 2008. The mean CDS spread for the entire sample is 0.43 percent, as seen in Table 4. 

In the subsequent analysis, we include several additional bank-level and country-level variables. Starting with the bank-level variables, assets are the logarithm of total bank assets in millions of dollars. This variable measures a bank's absolute size - rather than its size relative to its national economy. Bank size may matter to bank shareholders and liability holders because of technological and managerial economies (or diseconomies) of scale. In addition, bank size can affect a bank's expected access to a country's financial safety net on account of too-big-to-fail considerations, independently of the bank's size relative to the national economy.  

Next, pre-tax profits are the ratio of a bank's pre-tax profits to assets. Banks that are more profitable are expected to have a higher market-to-book ratio. Earning assets, in turn, is the ratio of earning assets to total assets, which proxies for a bank's business model. Specifically, a bank with a high earning assets variable may derive a large share of its income from traditional lending activities, rather than from fee-generating activities, such as advisory services, and trading on its own account. At a time of depressed values for traditional bank assets such as mortgage loans, this variable could negatively affect the market-to-book ratio, while the impact on the CDS spread may be positive. An additional bank-level variable is leverage, defined as the ratio of total bank liabilities to total assets. The market-to-book ratio may be positively related to leverage due to higher implicit subsidies from the financial safety net or alternatively because of the deductibility of interest from the corporate tax base, but a negative relationship may also exist since higher leverage may increase expected bankruptcy costs. Similarly, the CDS spread may be positively related to leverage, if high leverage implies relatively large expected credit losses on bank liabilities.  

A country's past experience with banking crises may affect the financial support that will be available to banks in any future financial crisis. Therefore, we control for the occurrence and fiscal cost of past banking crises. Specifically, past crisis is a dummy variable that equals one if a country has emerged from a previous banking crisis, and it is zero otherwise. In the table, we see that the mean value of this variable is 0.79, which implies that 79 percent of banks are located in a country that has suffered a banking crisis. In addition, past fiscal cost represents the ratio of the fiscal cost - relative to GDP - of resolving the most recent past banking crisis. This variable is zero, if the country has not emerged from any past banking crisis. The information used to construct these variables is taken from Laeven and Valencia (2008).   

The table also provides summary statistics on the government debt and fiscal balance variables. The fiscal balance is the net fiscal balance, computed as revenues minus expenses and depreciation of public capital. The mean government debt and fiscal balance ratios in the sample are 49.4 and -2.1 percent, respectively. 

To represent bank risk, we construct the bank stock risk variable as the annualized standard deviation of weekly returns on bank stock holdings, based on returns information from Datastream. As an alternative index of bank riskiness, we use the Z-score, which is a bank's distance from default, computed as the sum of the bank's contemporaneous return on assets and capital assets ratio, divided by the standard deviation of the return on assets. A higher Z-score indicates higher bank stability.   

Finally, the table provides summary statistics on the indicators of a banks' systemic size. Liabilities are a bank's liabilities-to-GDP ratio, with a mean of 3.7 percent. Sum of liabilities is the ratio of banking-system liabilities to GDP, with a mean of 1.11. Other Liabilities is the difference between Sum of Liabilities and an individual bank's own Liabilities variable, while Liabilities sq is the square of Liabilities. The variables Big 0.1, Big 0.25, Big 0.5 and Big 1.0 are dummy indicators of systemic size. For instance, Big 0.1 is a dummy variable that equals 1 if a bank's total liabilities exceed 10 percent of GDP, while it is zero otherwise. Big 0.25, Big 0.5 and Big 1.0 are defined analogously. In the tables, we see, for instance, that 5.5 percent of banks have a liabilities-to-GDP ratio that exceeds 0.1.  

To conclude this section, it is interesting to see how systemically important banks tend to differ from smaller banks. To this effect, Table 6 provides the means of our set of variables in 2008 separately for banks with a liabilities-to-GDP ratio exceeding 0.5 and for smaller banks. The table shows that systemically important banks have significantly lower CDS spreads. The larger banks further have a higher average earning assets ratio and higher leverage. The larger banks in addition tend to be located in countries that experienced fewer banking crises with correspondingly lower past fiscal costs of banking crises, while on average they are located in countries with lower fiscal balances for the year 2008.