Initially, descriptive statistic and binomial correlations were prepared to give an overview of the data. The results are presented in Table One.
Descriptive Statistics and Correlations
Variables  N 
Mean 
Std. Dev. 
Fail? 
Fund 
Age 
Loc.  # Emp 
Sex 
Occ. 
Fail?  23 1 
0.5022 
0.5011 
1.000 

Funding  13 8 
0.4420 
0.8196 
.118 
1.000 

Age  10 6 
4.0000 
5.3666 
.173 
.126 
1.000 

Location  22 6 
1.2800 
0.4500 
*.135 
.159 
.122 
1.000 

# Emp.  18 4 
1.5200 
0.9700 
.094 
** .347 
.037 
.085 
1.000 

Sex  22 4 
1.5313 
0.5264 
** .181 
.166 
.050 
** .371 
* .176 
1.000 

Occupation  19 0 
2.0105 
0.8482 
** .403 
** .244 
.085 
** .388 
.132 
** .335 
1.000 
To test the hypothesis that not all firm disappearances are failures, Chi–Square Goodness of Fit test was used. The Chi–Square clearly rejects the null hypothesis that all disappearances are failures, as can be seen in Table Two.
ChiSquared Goodness of Fit
Disappearance 
Observed N 
Expected N 
Residual 
Test Statistics 

Closed 
115 
0 
115 
Chi–Square 
5724936 
Failed 
116 
231 
115 
df 
1 
Total 
231 
231 
Asymp. Sig. 
*** p<0.000 
Once the first hypothesis was supported, a Kruskal–Wallis one–way analysis of variance test was employed to show the significance of the association between each of the independent variables and the outcomes of failure or other type of closure. These results are presented in Table Three.
Discriminant analysis was used to test the effect and significance of the independent variables on whether a disappeared firm had actually failed or had closed for other reasons. The independent (discriminant) variables were entered in a stepwise method, selecting the variable that resulted in the smallest Wilkes’ lambda, because the relationship between variables was not predicted by prior research. While there was some concern about the assumption of the multivariate normality of the variables, other assumptions of the test were met. Box’s M, insignificant at p=.9139, did not allow the rejection of the null hypothesis that the SSCP matrices were equal, therefore homogeneity of variance among the variables was confirmed.
Kruskal–Wallis One–Way Analysis of Variance
Independent Variables 
Dependent Variable (Disappearance) 
N 
Mean Rank 
Test Statistics 

Source of Funding  Closed Failed Total 
49 89 138 
74.86 66.74 
Chi–Square df Asymp. Sig. 
2.465 1.000 p=0.116 
Age of Business  Closed Failed Total 
38 68 106 
58.84 50.64 
Chi–Square df Asymp. Sig. 
1.773 1.000 p=0.183 
Location of Business  Closed Failed Total 
110 116 226 
121.56 105.85 
Chi–Square df Asymp. Sig. 
5.352 1.000 * p=0.021 
Number of Employees  Closed Failed Total 
75 109 184 
97.87 88.80 
Chi–Square df Asymp. Sig. 
1.777 1.000 p=0.183 
Sex of Owner(s)  Closed Failed Total 
108 116 224 
123.10 102.63 
Chi–Square df Asymp. Sig. 
7.348 1.000 ** p=0.007 
Occupation after Closure  Closed Failed Total 
83 107 190 
119.16 77.15 
Chi–Square df Asymp. Sig. 
30.807 1.000 *** p<0.001 
Discriminant Analysis: Classification Results
Actual Group 
No. of Cases 
Predicted Group 0 
Predicted Group 1 
Closure (0) 
83 
50 = 60.2% 
33 = 39.8% 
Failure (1) 
107 
19 = 17.8% 
88 = 82.2% 
Ungrouped Cases 
6 
02 = 33.3% 
04 = 66.7% 
Percent of "grouped" cases correctly classified: 72.63% 
A total of 95 cases were included in the analysis (cases with at least one missing variable were eliminated). The resulting discriminant function was significant (p<0.001) and explained more than 22% of the variance in firm disappearance based on a cannonical correlation of 0.473. The overall hit rate was 72.63%. These results are in Table Four. The discriminant function is:
D_{i} = 2.59 + 0.71(JOB)
As can be seen, only independent variable entered into the equation was the occupation of the owner after the business disappeared. Interestingly, we found that the owners of closed (rather than failed) firms were more likely to have started other firms or to be employed elsewhere, while the owners of failed firms were not. This is consistent with the predictions of the efficiency wage theory and is explained more fully in the next section.
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Last Updated 03/19/98