Comparison of the Accuracy of Direct and Indirect Methods of Cash Flow Models in Predicting Future Profits

Financial reports are part of the financial reporting process. Complete financial statements usually include balance sheets, income statements, statements of changes in financial position (which can be presented in various ways, for example, as cash flow statements, or cash flow statements), notes and other reports and explanatory material that are an integral part of the financial statements. . The purpose of this study is to provide empirical evidence whether a model with a direct cash flow component has a more accurate predictive ability than a model with an indirect cash flow component to predict future earnings. The parameters of this research model were estimated using panel data regression. This study considers 4 regression methods of penel data, namely (1) linear regression model (OLS), (2) covariance model (FEM), (3) error components (ECM) model, (4) time series autocorrelation model (GLS) ( Thiono, 2007). The results of the analysis of this study are the direct method cash flow component is more accurate than the indirect method cash flow component in predicting future earnings in manufacturing companies, finding that the direct method component is more accurate than the indirect method. Then for the cash flow component model the direct method is more accurate than the model with the indirect method cash flow component in predicting future earnings in non-manufacturing companies, finding that the cash flow components of the direct method and the indirect method do not differ in their accuracy in predicting future earnings.