Corporate Risk
4.6 Credit Risk. Bankruptcy Model
4.6.1 Previous Research on Bankruptcy Models
This item has been explained in this chapter 4, section 4.5.1.
4.6.2 Data and Resources
The data used in the research come from several sources. Company data are from the Standard & Poor’s Bankruptcy File (1864 Companies). After data cleaning the final sample compiles 1440 Companies, 20 years by cross-section (1983-2002). The total number of observations in the panel is 28800.
Net sales have been adjusted to constant 2002 US Dollars with the PPI-Producer Price Indexes for every sector supplied by the US Bureau of Labour Statistics, and all the other variables by the GDP deflator for fixed non-residential investment supplied by the Bureau of Economic Analysis.
Software used is Stata-SE, release 8.0.
The enclosed table summarizes the correlation or covariance matrix for the group of variables to be considered in the econometric model. The first coefficient higher than 0.5 in absolute value relates the EBIT interest coverage and EBITDA interest coverage. We prefer to keep a cash flow variable before depreciations like the EBITDA interest coverage, which is more homogeneous in financial comparisons. High correlation can also be found between Total debt to capitalization and Long term debt to Capitalization and we keep the first due to its higher significance.
Table 4.6 Correlation or covariance matrix of the explanatory variables 4.6.3 The Bankruptcy Model
As previously stated, the main objective is to regress and test industry variables to a proposed dependent one to analyse the capability of the credit ratings variables to predict bankruptcy and how their parameters are impacted.
A Bankruptcy situation is faced when the assets value falls below the value of the firm’s liabilities. Based on this fact, we adopt the log of the year end Total Assets to Total Liabilities ratio as the dependent variable, and the industry variables as the independent ones. It has the advantage that we trace the evolution of the financial situation of one company with the Industry variables, then, if the situation is worsening, we do not need to change variables to find out with the Z-Score, and we continue working with the same set of industry variables.
The Bankruptcy model can be expressed as the log of the Total Assets to Liabilities ratio against the industry variables, expressed in a generic notation (Xit) for simplicity, and estimated through a fixed effects OLS robust estimation132. The model is as follows:
Ln(AT/LT)it =
α
i +β
iXit +ε
it (4.6.3.1)Where the dependent variable is (See Appendix 6a for a fuller variables description):
Ln(AT/LT)it = Natural logarithm of year end Total Assets to Total Liabilities and the independent or industry variables are:
EBIT Interest Coverage EBITDA Interest Coverage
132 Greene, W., 2000,“Heteroscedasticity consistent covariance matriz estimation”, Econometric Analysis, Prentice Hall, 14, 579.
Total Assets EBIT Interest EBITDA Funds from Free Operat. Pretax Oper. Income Long term Total Debt to Liabilities coverage Interest Operations to Cash Flow Return on bef. Deprec. Debt to to
ln(AT/LT) Coverage Total Debt to Total Debt Capital to Sales Capitalization Capitalization Total Assets to Liabilities 1.000
EBIT Interest Coverage -0.032 1.000
EBITDA Interest Coverage 0.025 0.939 1.000
Funds from Operations To Debt 0.056 0.189 0.227 1.000
Free Oper. Cash Flow to Debt -0.121 0.464 0.464 0.216 1.000
Pretax Return on Capital 0.378 0.149 0.151 0.157 0.061 1.000
Oper. Income bef. Depr. To Sales 0.039 0.178 0.182 0.044 0.086 0.267 1.000
Long term Debt to Capitalization -0.072 0.006 0.001 0.001 0.005 0.000 0.000 1.000
Total Debt to Capitalization -0.114 0.006 0.000 0.001 0.007 -0.008 0.006 0.806 1.000
Funds from Operations to Total Debt Free Operating Cash Flow to Total Debt Pretax Return on Capital
Operating Income before Depreciation to Sales Long Term Debt to Capitalization
Total Debt to Capitalization
4.6.4 Detailed discussion of the Econometric estimates
We started running the fixed and random effects estimators, and the Hausman test with chi2(table)=15.51 < Statistic=96.23. This means that the null hypothesis of “Ho: Individual effects are uncorrelated with other regressors” is rejected, and the consistent estimator is a fixed effects OLS.
If we regress the Total Assets to Total Liabilities against all the above mentioned variables, and proceed with eliminations due to multicollinearity and low significance of some variables, we get the following final results:
Variable Definition Fixed Effects OLS-areg Robust
Explanatory Variable Coeff. & (t-Student) EBITDA Interest Coverage 0.00001
(+2.18) Pretax Return on Capital 0.00157
(+7.97) Free Operating cash Flow to
Total Debt.
-0.00006 (-2.27) Total Debt to Capitalization -7.45e-06
(-3.49)
Constant 4.95782 (+401.57)
F-Statistic 22.65 R-squared 0.5889
Adj R-squared 0.5242
Number of Observations 2171
Table 4.7 The Bankruptcy Model estimates (t-values in parentheses)
The EBITDA Interest Coverage, and the Pretax Return on Capital show a significant positive contribution to the log of the Total Assets to Liabilities. The Free Operating Cash Flow to Total Debt and the Total Debt to Capitalization show a significant negative contribution to the log of the Total Assets to Liabilities.
In consequence, EBITDA Interest Coverage, Pretax Return on Capital, Free Operating Cash Flow to Total Debt, and the Total Debt to Capitalization are the key variables to predict Bankruptcy based on the Industry Credit Ratings variables.
Additionally we can compare the Coefficients and the t-Student significance of parameters between the Default Probability and the Bankruptcy Model ones. We find the following:
Variables Definition Default Probability Model Bankruptcy Model
Dependent Variable Ln(DPit/100) Ln(AT/LT)it
Explanatory Variable Coeff. & (t-Student) Coeff. & (t-Student) EBITDA Interest Coverage -5.66e-06
(-2.11)
0.00001 (+2.18) Pretax Return on Capital -0.0207
(-7.62)
Total Debt to Capitalization -7.45e-06
(-3.49) Table 4.8 The Default Probability and Bankruptcy models (t-values in parentheses)
Two equal independent variables have been identified as significant in the two models.
The differences are very important and are clearly due to the different dependent variables and the information data coming from the different considered databases.
The EBITDA Interest Coverage and Pretax Return on Capital are significant in both models. The Default Probability Model emphasizes the Operating Income and Long Term Debt, whereas the Bankruptcy one is more related to the generation of Free Operating Cash Flow and the level of Total Debt.
Beaver (1966)133 found Cash (defined as Funds) Flows to Total Debt to be the best univariate predictor. In our research Pretax Return on Capital shows the highest significance, and Free Operating Cash Flow to Total Debt is also identified as a significant variable.
Gentry (1985) found the Dividends Flow as the most significant variable. The Capital Expenditures, and Debt Financing were among the variables that were not significant in his studies. He also found that models based on combined cash flow and financial ratios were much better than models based on cash flow or financial ratios alone. We can emphasize that none of these variables are commonly considered among the Industry ones.