1. Forecasting corporate insolvency
Ewa Orzechowska-Fischer and
Bruce Taplin

2. Background
Lack of capacity to predict the corporate insolvency primary impediment to estimating GEERS (General Employee Entitlement Support Scheme) demand in Australia
A “prototype” model developed by the Canadian Office of the Superintendent of Bankruptcy

3. Dependent variable – insolvency rate

4. Determinants selected to develop the model

5. Data and specification issues
Sample: 1991:1 – 2009:2
Partial adjustment specification
Within and out-of-sample forecasts

6. Estimation results
We’ve investiaged a number of alternative combination of explanatory variables and their lag structures. We chose this particular model as it performed best in term of the model fit and its forecasting ability. As the R-squared shows the combination of

7. Within sample forecasting
MAPE 7.10
Theil 0.04
Bias Prop 0.01
Variance Prop 0.00
Covariance Prop 0.9

8. Out-of-sample forecasting

9. Conclusions
The main determinants of the corporate insolvency rate in Australia are: GDP, average business profits and unemployment rate
The model constructed performs well the within sample forecasts, however quite wide 95% confidence intervals around the out-of-sample forecast mean that considerable uncertainties remain regarding future forecasted levels of corporate insolvencies given the limitations of theory and data.