A similar classification rule can be used by the MDA, logit, or probit scores (probabilities), but the number of misclassifications with NPDM will be always less than, or equal to, the number of misclassifications obtained by the MDA or logit for an estimation sample.(6)
This sample rule may be employed for the NPDM. BarNiv and Raveh (1989) developed a generalization for equation (4) that takes into consideration misclassification costs and prior probabilities.
They are applicable for MDA, NPDM, LPM, logit, probit, lomit, etc.
Significance tests on individual coefficients are not available with MDA or NPDM, but the relative contribution can be approximated by standardized adjusted coefficients.
However, a substantial computational burden is involved in calculating the NPDM and qualitative response models with so many independent variables.
The NPDM correctly classifies a few more firms for the three base years, but the improvement is insignificant.
Both the NPDM and MDA provide similar results two years prior to insolvency, but the NPDM slightly outperforms MDA one and three years prior to insolvency.(13) Other initial guesses for the NPDM are possible and more efficient coefficients might be produced, which will increase the classification and prediction ability of the NPDM.
The Lomit or Burrit and the NPDM do not assume that the scores (given to the firms) are symmetrically distributed, and therefore they may better fit the data than MDA.