In September, 1979, the Financial Accounting Standards Board issued FASB Statement No. 33, which required certain corporations to issue specified supplementary information based on constant dollars and current costs. This information is intended to show the impact of inflation on the reported earnings and capital of business enterprises. Opponents of Statement No. 33 claim that the required supplementary information is difficult to interpret and, therefore, will not be used. Proponents contend that the information is self-explanatory and would highlight the impact of inflation on the performance of business enterprises. Thus, they conclude the supplementary data will be useful to various user groups and will be used. This dissertation's primary objective was to determine whether the supplementary data will be used by financial analysts in the Dallas/Fort Worth and Houston regions in evaluating an enterprise's operating performance and its ability to maintain physical operating capability and the general purchasing power of financial capital.

The main purpose of this study is to develop a bankruptcy prediction model for the small business firm. Data was collected from the Dallas Small Business Administration (SBA), making this study specific to its decision makers. Existing research has produced models which predominately use financial ratios and information measures either independently or combined, and a few research models have used economic trends. This study varies from past studies in that it includes regional economic variables from the states of Texas. A sample of three-year data for 138 firms included fifteen bankrupt firms. This proportion of bankrupt/nonbankrupt firms approximates the proportion of repayed/defaulted loans in the SBA. Stepwise regression, set at the .15 level of significance, reduced a total of fifty-three variables to nine. These nine variables were then used to test twelve predictive models. All twelve models tested improved the SBA repayment rate and only two of the twelve would have caused the SBA to deny loans to applicants who eventually repaid. The study determined the model that included financial ratios, information measures, and Texas economic variables as best. It was also demonstrated that some of the variables used in this model could be eliminated without decreasing the predictive power …