Cash Flow from Operations and Earnings as Predictors of Future Cash Flows - Under IFRS

Abstract

This study examines the predictive ability of various earnings measures and CFO for predicting future cash flows under IFRS. The analysis is based on a comprehensive and balanced panel dataset of annual reports from Swedish listed companies on Nasdaq Stockholm covering the period from 2006 to 2023, ensuring the reliability and robustness of the results. Applying a similar methodological approach to Ball and Nikolaev (2022), this analysis compares the predictive ability of three accrual-based earnings measures: Net Income, EBIT, and EBITDA, relative to CFO. The analysis is based on cross-sectional and pooled OLS regression, industry-specific estimations, and fixed-effects models. The findings consistently show that EBITDA outperforms the other metrics as the most reliable predictor of future cash flows across all model configurations and time frames. By directly comparing different earnings-based measures, this study provides new insights into the informativeness of intermediate versus bottom-line earnings metrics when forecasting future cash flows. This contribution to the literature identifies a clear hierarchy in predictive accuracy among earnings measures, providing a deeper understanding of the relative usefulness of each metric. Addressing the impact of estimation uncertainty and the limitations of accrual-based earnings measures is crucial, especially concerning the growing focus on intangible assets under IFRS, which highlights their potential to influence the reliability and comparability of earnings measures. Furthermore, this context is relevant due to the upcoming implementation of IFRS 18 on Presentation and Disclosure in Financial Statements, mandatory for reporting periods on or after 1 January 2027. This thesis enhances the international literature on the predictive ability of financial performance metrics by both expanding the empirical context beyond the U.S. and clarifying how specific earnings measures perform under IFRS. The results are relevant not only for researchers but also for policymakers and standard-setters such as the IASB, by informing ongoing discussions about the relevance and decision-usefulness of financial reporting.