Title: Accruals and the prediction of future cash flows
Abstract: Purpose The purpose of this paper is to examine the comparative abilities of current period cash flows and earnings (and its components) to predict one‐year‐ahead cash flow from operations in Egypt. Design/methodology/approach The study uses the cash flow prediction models developed by Barth, Cram, and Nelson to examine the predictive abilities of earnings and cash flows for future cash flows. The first set of prediction models uses cross‐sectional regression to compare the predictive abilities of cash flows and aggregate earnings for one‐year‐ahead cash flow from operations. The second set of prediction models tests whether disaggregating earnings into cash flows and the major components of accruals enhances the predictive ability of earnings for one‐year‐ahead cash flow from operations. Findings The findings of the study reveal that aggregate earnings have superior predictive ability than cash flows for future cash flows. Also, the results reveal that disaggregating accruals into major components – changes in accounts receivable and payable, and in inventory, depreciation, amortization, and other accruals – significantly enhances predictive ability of earnings. Research limitations/implications The study provides empirical evidence on the superiority of earnings in predicting future cash flows. The findings of the study should be considered in explaining the results of value relevance research Egypt. However, owing to relatively small sample size, given the thinness of the Egyptian capital market, these findings should be interpreted with caution. Originality/value The paper contributes to the limited body of research on the superiority of earnings and cash flows in predicting future cash flows by examining the predictive abilities of earnings and cash flows for future cash flows in Egypt as one of many emerging markets.
Publication Year: 2011
Publication Date: 2011-06-21
Language: en
Type: article
Indexed In: ['crossref']
Access and Citation
Cited By Count: 44
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