Accruals and the Prediction of Future Cash Flows

53 Pages Posted: 7 Dec 1999

See all articles by Mary E. Barth

Mary E. Barth

Stanford University - Graduate School of Business

Donald P. Cram

State University of New York, Oswego

Karen K. Nelson

Texas Christian University - Department of Accounting

Multiple version iconThere are 2 versions of this paper

Date Written: November 1999

Abstract

We compare the predictive abilities of earnings and cash flows for future cash flows. We base our predictions on a model of the relation between future cash flows and past earnings and its components, including cash flows. As predicted, we find that current and past earnings explain significantly more variation in future cash flows than current and past cash flows, but only after permitting the cash and accrual components of earnings to have different multiples. As predicted, disaggregating the accrual component of earnings significantly further enhances the predictive ability of earnings for future cash flows. Contrary to claims in the popular press, the depreciation and amortization components of earnings have significant predictive ability for future cash flows. Our inferences are robust to controlling for operating cycle and industry membership.

JEL Classification: G12, M41

Suggested Citation

Barth, Mary E. and Cram, Donald P. and Nelson, Karen K., Accruals and the Prediction of Future Cash Flows (November 1999). Available at SSRN: https://ssrn.com/abstract=194931 or http://dx.doi.org/10.2139/ssrn.194931

Mary E. Barth (Contact Author)

Stanford University - Graduate School of Business ( email )

655 Knight Way
Stanford, CA 94305-5015
United States
650-723-9040 (Phone)
650-725-0468 (Fax)

Donald P. Cram

State University of New York, Oswego ( email )

307 Rich Hall
Oswego, NY 13126
United States
315-312-2533 (Phone)

Karen K. Nelson

Texas Christian University - Department of Accounting ( email )

M.J. Neeley School of Business
TCU Box 298530
Fort Worth, TX 76129
United States
817-257-7567 (Phone)

Do you have negative results from your research you’d like to share?

Paper statistics

Downloads
4,459
Abstract Views
18,944
Rank
4,133
PlumX Metrics