The role of industry classification in estimating discretionary accruals

The role of industry classification in estimating discretionary accruals This study compares the properties of the Global Industry Classification Standard (GICS) with three alternatives: Standard Industrial Classification, North American Industry Classification System, and Fama–French classification. First, we demonstrate that GICS results in more reliable industry groupings for financial analysis and research; in particular, we find that estimations of performance-adjusted discretionary accruals (PADA) based on GICS significantly outperform estimates derived using each of the three alternative classifications systems in capturing discretionary accruals. Second, we show that the difference between GICS and the other systems can provide significantly different results, and hence different inferences, in empirical studies that rely on industry classification. Specifically, we revisit findings by Teoh et al. (J Financ 53[6]:1935–1970, 1998a) and assess the conclusion that initial public offering (IPO) issuers with high abnormal accruals during the IPO year experience subsequent poorer long-term stock performance than issuers with low discretionary accruals do. We find that this result disappears when PADA estimates are based on GICS. Our results call for serious consideration of using GICS classifications in research, either in the primary analysis or as a necessary corroboration. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Review of Quantitative Finance and Accounting Springer Journals

The role of industry classification in estimating discretionary accruals

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Publisher
Springer US
Copyright
Copyright © 2011 by Springer Science+Business Media, LLC
Subject
Economics / Management Science; Finance/Investment/Banking; Accounting/Auditing; Econometrics; Operations Research/Decision Theory
ISSN
0924-865X
eISSN
1573-7179
D.O.I.
10.1007/s11156-011-0268-6
Publisher site
See Article on Publisher Site

Abstract

This study compares the properties of the Global Industry Classification Standard (GICS) with three alternatives: Standard Industrial Classification, North American Industry Classification System, and Fama–French classification. First, we demonstrate that GICS results in more reliable industry groupings for financial analysis and research; in particular, we find that estimations of performance-adjusted discretionary accruals (PADA) based on GICS significantly outperform estimates derived using each of the three alternative classifications systems in capturing discretionary accruals. Second, we show that the difference between GICS and the other systems can provide significantly different results, and hence different inferences, in empirical studies that rely on industry classification. Specifically, we revisit findings by Teoh et al. (J Financ 53[6]:1935–1970, 1998a) and assess the conclusion that initial public offering (IPO) issuers with high abnormal accruals during the IPO year experience subsequent poorer long-term stock performance than issuers with low discretionary accruals do. We find that this result disappears when PADA estimates are based on GICS. Our results call for serious consideration of using GICS classifications in research, either in the primary analysis or as a necessary corroboration.

Journal

Review of Quantitative Finance and AccountingSpringer Journals

Published: Dec 30, 2011

References

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