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The market pricing of negative special items through time: an unintended consequence of regulation change?

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Abstract

Prior research concludes that the implications of negative special items (NSIs) for future earnings are more fully reflected than earnings before NSIs. Our evidence suggests that US regulatory changes resulted in dramatic increases (decreases) in NSI reporting frequency (magnitude). We find that the advantage in pricing NSIs relative to other components of earnings disappears for the average firm post-regulation and for high frequency NSI reporters regardless of time period. Our evidence suggests that regulations governing the financial reporting of NSIs resulted in unintended consequences by impairing the ability of market participants to understand the future earnings implications of these items.

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Notes

  1. According to the Compustat manual, special items represent “unusual or nonrecurring items” reported above the line.

  2. Frequency refers to the number of times an item is reported within a certain time frame while future earnings implications refers to the effect a current item has on future earnings. Higher frequency or greater future earnings implications implies items are less transitory. Future earnings implications is often referred to as persistence, but we use the former for clarity as persistence becomes convoluted in the context of negative items and earnings transfer.

  3. Several recent studies suggest a recent temporal shift in the reporting of NSIs (e.g., Riedl and Srinivasan 2010; Johnson et al. 2011; Lee 2014).

  4. “Other” special items are actually the third most frequent category (24%), but include many different charges.

  5. The BJS sample covers years 1982–1997. Our sample starts in 1988 because our tests require cash flow data.

  6. We examine years after the 2002 because the interim period (1998–2002) includes a number of new regulations, in particular SFAS 142, 144, and 146 as well as a massive market bubble and bust that potentially impact the reporting and pricing of NSIs (particularly pricing which is the main focus of our study).

  7. Though Lee (2014) and Johnson et al. (2011), and others discuss an increase in frequency and decrease in magnitude, their analyses do not specifically test this supposition and are mainly focused on other questions. Our study is also focused on the greater question of the change in pricing, though we believe the tests of frequency, magnitude, and future earnings implications are necessary predecessors to our main tests in order to understand any change in the reporting environment of NSIs as a result of regulation changes.

  8. SFAS No. 144—Accounting for the Impairment or Disposal of Long-Lived Assets, Summary.

  9. Emerging Issues Task Force Issue No. 94-3, Liability Recognition for Certain Employee Termination Benefits and Other Costs to Exit an Activity (including Certain Costs Incurred in a Restructuring).

  10. SFAS No. 146—Accounting for Costs Associated with Exit or Disposal Activities, Summary.

  11. Lee (2014) does not specifically test the impact of frequency on the restructuring charge valuation multiple. He conjectures that the higher valuation multiple he finds is consistent with increased reporting frequency.

  12. Domestic and Global are defined in detail in Sect. 4. All further hypotheses relate only to Domestic firms.

  13. The increase in frequency in 2001 is slightly early for the direct effect of SFAS 142, 144, and 146. However, evidence suggests the increase in frequency along with the increase in magnitude in 2001 (see Figs. 3 and 4 which we discuss below) is most likely driven by the non-recurring charges stemming from the terrorist attack on September 11, 2001. Subsequent to 2001 we find that frequency remained constant (i.e., high) while magnitudes clearly decrease after the market settled consistent with the expected effects from SFAS 142, 144, and 146.

  14. We rely on annual NSI reporting for Domestic versus Global comparisons because the quarterly data for Global firms is not consistently reported until after 2006. Relying on Global quarterly data would have resulted in a very low number (less than 1/3 of the overall sample) of usable observations until 2007.

  15. This approach has been used in many studies (e.g., Dechow et al. 2008; Hanlon 2005; BJS; Soffer and Lys 1999; Rangan and Sloan 1998; Sloan 1996; Ball and Bartov 1996; among others) to estimate the amount of the information incorporated by the market from the expectation of earnings components.

  16. Kraft et al. (2007) document that OLS and the Mishkin test generate virtually identical coefficient estimates and inferences in accounting settings. That is, they demonstrate that in large sample accounting research settings, the Mishkin test is asymptotically equivalent to OLS when testing the rational pricing of accounting numbers. We rely on the Mishkin test as our primary empirical methodology to maintain comparability to the empirical tests reported by BJS. However, in additional testing (not tabulated) we estimate OLS versions of each of our test models and results of this additional testing yield quantitatively and qualitatively identical results to our tabulated tests.

  17. Whether market prices the information in earnings correctly is a very different question from how the market prices earnings. This is highlighted by the fact that we find no difference in implied to actual ratios for SUPREt despite a substantial difference in the actual SUPREt coefficients (i.e., − 0.324 vs − 0.221) between low and high frequency reporters. In contrast, both Elliott and Hanna (1996) and Cready et al. (2010) report significantly higher contemporaneous response coefficients on the earnings of low frequency reporters.

  18. We thank an anonymous reviewer for suggesting this analysis.

  19. We suggest these changes are precipitated by SFAS 142, 144, and 146 because these regulations have specific consequences for NSIs. To the extent SOX or other regulations concurrently affected NSI reporting and pricing is beyond the scope of this study.

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Acknowledgements

We thank Steve Lin, Ovee Barua, Terry Shevlin, Jenny Tucker Wu, Partha Mohanram, Kelvin Liu and workshop participants at Florida International University, Oklahoma State University, Shanghai University of Finance and Economics, the 2012 AAA Annual Meeting, especially discussant Jim Naughton, and the 2013 McMaster University Accounting Symposium, for comments on early drafts of this manuscript.

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Correspondence to Craig A. Sisneros.

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Lopez, T.J., Sisneros, C.A. & Sorensen, T. The market pricing of negative special items through time: an unintended consequence of regulation change?. Rev Quant Finan Acc 54, 753–777 (2020). https://doi.org/10.1007/s11156-019-00806-7

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