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Pension accounting reform and future cash flow predictability

*Corresponding author for this work
Scholary Output:
Contribution to journal
Article
Peer-review

Abstract

Purpose: This paper aims to examine the association of accruals and disaggregated pension components with future cash flows and also to investigate whether investors distinguish between pension information that is recognized (SFAS 158) versus disclosed (SFAS 132). Design/methodology/approach: Regression analysis is used with a proxy for expected future cash flows as the dependent variable, and the components of pension disclosures as well as controls for the 2008-2009 financial crisis as the independent variables. Findings: The results reveal that incorporating disaggregated pension components increases the ability to predict future cash flows, and that investors attach different pricing multiples to the various components in the models. The authors also find that during the 2008-2009 financial crisis, the signs of the coefficients on these components changed. Finally, the results indicate that investors assign more significance to pension accounting information that is recognized, as opposed to disclosed, and that disclosure affects the allocation of pension assets. Originality/value: The authors provide empirical support for the conjecture posited by Amir and Benartzi (1998) that the prediction of future cash flows will be enhanced by the incorporation of the components of pension assets and liabilities. Importantly from a standard setting perspective, the authors also find evidence that investors assign more significance to pension accounting information that is recognized in the financial statements than to pension information that is disclosed.

Publication Information

Output type

Scholary Output:
Contribution to journal
Article
Peer-review

Original language

English (US)

Pages from-to (Number of pages)

Pages 86-108 (23 pages)

Journal (Volume, Issue Number)

Journal of Financial Economic Policy (Volume 9, Issue 1)

Publication milestones

  • Published - 01/01/2017

Publication status

Published - 01/01/2017

ISSN

1757-6385

Publication IDs

  • Scopus: 85016811774

Publication metrics

Metrics

SciVal
Author count
3
SciVal
Paper percentile
25
Fractional count
2
Fractional count
0.67
Fractional count
1
Fractional count
0.33
Fractional count
2
Fractional count
1