This paper reports an exploratory study of statistical modelling of historical financial reporting and analysis in a sample of small growth enterprises. The study sought to identify those factors that determine whether particular financial reporting and analysis practices are undertaken, and to represent these explanatory factors in expressions that reflect their relative and combined influence. Dichotomous logistic regression is employed to model financial analysis and polytomous logistic regression is used to model financial reporting. The models developed seem moderately encouraging in terms of the statistical significance and predictive ability. The overall classification success for financial analysis is a modest 65 percent; but identifying users of financial ratio analysis is achieved with just below 90 percent accuracy. The overall classification success for a trichotomous financial reporting scale exceeds 70 percent; with anticipation of financial reporting at the highest level being as accurate as 90 percent. External validation of the models remains an important priority.
Financial Reporting, Small Growth, Low Growth
McMahon, Richard G. P.; Davies, Leslie G.; and Bluhm, Nicholas M.
"Exploratory Modelling of Financial Reporting and Analysis Practices in Small Growth Enterprises,"
Journal of Small Business Finance:
3, pp. 199-214.
Available at: https://digitalcommons.pepperdine.edu/jef/vol3/iss3/2