Table 9 Logit re-estimated models’...

Table 9

Logit re-estimated models’ accuracy out-of-sample

Model	Altman		Ohlson		Zmijewski
Company	Non-B.	Bankrupt	Non-B.	Bankrupt	Non-B.	Bankrupt
Sample	9,337	87	9,337	87	9,337	87
Predicted	8,310	66	8,264	70	7,963	71
Cut-off	≤0.5	>0.5	≤0.5	>0.5	≤0.5	>0.5
False	1,027	21	1,073	17	1,374	16
Type I error		24.14%		19.54%		18.39%
Type II error	11.00%		11.49%		14.72%
Accuracy	88.88%		88.43%		85.25%
AUC-ROC	0.91		0.93		0.92

Model	Altman		Ohlson		Zmijewski
Company	Non-B.	Bankrupt	Non-B.	Bankrupt	Non-B.	Bankrupt
Sample	9,337	87	9,337	87	9,337	87
Predicted	8,310	66	8,264	70	7,963	71
Cut-off	≤0.5	>0.5	≤0.5	>0.5	≤0.5	>0.5
False	1,027	21	1,073	17	1,374	16
Type I error		24.14%		19.54%		18.39%
Type II error	11.00%		11.49%		14.72%
Accuracy	88.88%		88.43%		85.25%
AUC-ROC	0.91		0.93		0.92

Note(s): AUC-ROC means the Area Under the ROC Curve. Non-B. is the number of non-bankrupt companies. Bankrupt is the number of bankrupt companies. Type I error is the percentage of bankrupt companies classified by the model as non-bankrupt, and Type II error is the percentage of non-bankrupt companies classified as bankrupt. Accuracy is the percentage of correctly predicted types in the total sample

Source(s): Authors’ own elaboration

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