EVALUATING THE ABILITY OF EARNINGS AND CASH FLOWS IN PREDICTING FUTURE CASH FLOW: A CASE STUDY WITH THE NON-FINANCIAL COMPANIES IN QUANG NGAI PROVINCE

Abstract

The purpose of this research is evaluating the predictive ability of future operating cash flow by using earnings and cash flows information in the past. At the same time, compare which information predicts future operating cash flow better. Data were collected from the 41 non-financial companies in Quang Ngai province with audited annual financial statements for the 6-years period from 2017 to 2022. Three statistical methods were used for regression analysis of predicting models and overcoming endogeneity problems that can occur in the models, include Ordinary Least Squares (OLS), Fixed Effects Model (FEM) and dynamic panel data model with the estimation method System-GMM. The findings show that past earnings predicts future operating cash flow than past cash flows. However, when combining both of these information to predict together, the combined model has superior predictive ability than the two individual models that only use earnings or cash flows information.