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Entrepreneurship and Small Business Growth 77

measured variable. This provides ten unknown factor weights. In addition,
15 error variances (E ), two residual error of prediction variances (Di), three
i
variances/covariances of the independent latent variables (F1, and F2), and
five direct latent variable effects were estimated: that is the paths from F1 to
F3, F2 to F4, F3 to F4, F3 to F5, and F4 to F5. With 35 parameters to be es-
timated, there are 85 degrees of freedom. Finally, since the model contains
variables measured in different units, for instance, percentages, and mone-
tary values, standardized values are reported to facilitate comparison of the
effects of the variables included in the model.
Figure 4.1 shows the parameter estimates of the model. The structural
equation programs developed by Bentler (1993) were employed to calibrate
the model. Further information about the model is available in Athiyaman
and Walzer (2007).

NOTE

1. Bentler’s (1993) structural equation algorithm was applied to the data in Ap-
pendix 1. More information about this model can be found in Athiyaman and
Walzer (2007).

REFERENCES

Acs, Zoltan C., and Catherine Armington. 2005. Using census BITS to explore entre-
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Area Development Online. 2005. 20th annual corporate survey. www.area-development
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Association for Enterprise Opportunity (AEO). 2006. About microenterprises. www
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tions for marketing communication strategies. Working Paper, Illinois Institute for
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Athiyaman, Adee, and Norman Walzer. 2007. Entrepreneurship growth in a cross
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