Skip to main content

Causes and consequences of goodwill impairment losses

Review of Accounting Studies volume 16, pages 745–778 (2011)Cite this article

Abstract

The paper examines the reaction of market participants to the announcement of a goodwill impairment loss, the nature of the information conveyed by the loss, and whether a cause of goodwill impairment can be traced back to overpayment for targets at the time of prior acquisitions. Our evidence suggests that both investors and financial analysts revise their expectations downward on the announcement of an impairment loss. We find that the negative impact of the loss is significant under different reporting regimes, that is, pre-SFAS-142, transition period and post-SFAS-142, though it is lower in the post period. We further show that goodwill impairment serves as a leading indicator of a decline in future profitability. Our tests also reveal that proxies for overpayment for targets can predict the subsequent goodwill impairment. Indirect evidence suggests that firms with potentially impaired goodwill that did not report an impairment loss may have used their managerial discretion to avoid taking the loss.

This is a preview of subscription content, access via your institution.

Access options

Buy single article

Instant access to the full article PDF.

USD 39.95

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Notes

  1. SFAS 121 was later superseded by SFAS 144. FASB standards are now incorporated in the FASB’s Accounting Standards Codification (ASC). The rules relating to goodwill impairment can be found under ASC 350-20-35.

  2. Critics of SFAS 142 were skeptical as to whether new information will be conveyed to the market via the recognition of impairment of existing goodwill, which is essentially a retroactive adjustment (e.g., Moehrle and Moehrle 2001).

  3. In concurrent work, Hayn and Hughes (2006) develop an impairment prediction model using acquisitions made during 1988 through 1998 based on acquisition characteristics and economic indicators of impairment. More recently, Gu and Lev (2008) show that acquisitions made by overpriced buyers are associated with subsequent goodwill write-offs.

  4. We verify the dollar amount of the goodwill impairment loss in the transition and post-SFAS-142 periods obtained from our Factiva search with the amount reported in Compustat; we use the amount reported in the press release when it differs from that reported in Compustat. For the post-SFAS-142 period covering 2003 through 2006, the (after-tax) goodwill impairment loss is reported under data item #250.

  5. We find considerable variation in the range of losses announced by companies, with a few narrow ranges and a few ranges expressed from zero to millions of dollars. We exclude all announcements of ranges because we believe that midpoints of wide ranges are not meaningful and imposing inclusion/exclusion rules would be arbitrary.

  6. We also use an alternative methodology to control for self-selection by including an additional independent variable that equals the inverse Mills ratio from the first-stage probit regression estimating the likelihood of impairment. Our results using this alternative research design are substantially similar to those reported.

  7. Using the value-weighted instead of the equally weighted index obtains substantially similar results.

  8. The inclusion of earnings surprise as an independent variable for firms that do not announce earnings within the impairment announcement window should bias the coefficient estimate on earnings surprise downward. We obtain substantially similar results when we use earnings surprise equal to zero for these firms.

  9. Results of the expected impairment model are available from the authors upon request.

  10. In the interest of brevity, we report results of additional analyses using the full sample only, since results using the I/B/E/S sample are substantially similar.

  11. The insignificant coefficient estimate (in contrast to the significantly positive coefficient on restructuring charges in Francis et al. 1996) may perhaps be due to the fact that our independent variable, unexpected goodwill impairment loss, is just one component of the total restructuring charge used as the independent variable by Francis et al. (1996).

  12. The lower coefficient may also be due to the market perceiving the opportunistic use of managerial discretion in the estimation of goodwill impairment in the post-SFAS-142 period (if our proxies for managerial incentives in estimating expected impairment are inadequate in controlling for managerial discretion). We test the validity of this alternative explanation in our subsequent analysis of future information conveyed by the impairment loss (in Sect. 4.5).

  13. Bens et al. (2007) focus only on the sample of large goodwill write-offs, defined as write-offs in excess of $1 million and 5% of lagged total assets (these form only 32% of our full sample). We find that a high proportion of the sample of large write-offs is subject to the confounding effect of concurrent restructuring charges (20% of the large vs. 9% of the small write-off samples), which may perhaps account for the post-period impact being insignificant in Bens et al. (2007).

  14. We thank an anonymous reviewer for suggesting this line of inquiry.

  15. Note that unexpected impairment equals the negative of the expected impairment when the actual impairment is zero; hence a negative coefficient estimate on unexpected impairment implies a positive effect on stock prices.

  16. A third possibility is that the market revises its expectations of management quality downward due to the reporting of zero impairment by firms with potentially impaired goodwill. In such cases, we may see a significantly positive coefficient estimate on unexpected impairment if the market’s penalty is correlated with the magnitude of unexpected impairment.

  17. We only analyze the post-period since there are few explicit zero impairment announcements in the pre and transition periods. Further, we find that most zero impairment announcements occur within the earnings announcement window.

  18. For the control sample, REV i equals the subsequent quarter’s forecast revision made within a period of 30 days following the earnings announcement date of the matched quarter.

  19. This is slightly higher than the corresponding percentage (84%) of the universe of I/B/E/S firms whose one-quarter-ahead forecasts are revised within 30 days of earnings announcements during the same time period. (Also, note that the number of firms with one-quarter-ahead forecasts [521] differs from the number of firms with forecasts of the impairment quarter [622] reported in Table 2, Panel A.).

  20. Note that when the model is estimated by reporting regime, although the Adj-R 2 declines marginally in some specifications, the raw R 2 increases as expected (unreported). We also note that the Adj-R 2 is quite low when we use the Beatty-Weber measure of unexpected impairment. This measure has significantly higher variance than the “Residual” variable (0.060 vs. 0.037) which could account for the lower Adj-R 2.

  21. The results remain substantially unchanged when we separate goodwill impairments that are announced simultaneously with major restructuring charges (untabulated).

  22. One-year growth rate is used for observations with missing data on sales or operating income in the second year.

  23. We attempt to reconcile the lower market reaction to post-period unexpected impairment (U-ILOSS) with the higher informativeness of post-period impairments (ILOSS) for future operating income growth. We find that the higher negative correlation between ILOSS and future performance in the post-period relative to the pre-period is due more to the expected component of ILOSS than the unexpected component. This corroborates our conjecture that impairment announcements in the post-period have lower “news” value for investors.

  24. Ramanna (2008) finds that firms’ lobbying support for goodwill impairment rules increases systematically with their ability to exercise their reporting discretion, suggesting that the potential for opportunism is retained under SFAS 142.

  25. Typically, the target’s book value is a preliminary indicator that takeover specialists use to find undervalued firms and is considered a “floor” in relation to which the acquirer decides what the acquisition price should be (Gaughan 2002). Hence, acquisition price significantly in excess of the floor could provide a rough indication of overpayment.

  26. Myers and Majluf (1984) find that a bidding firm will offer to pay in stock when its managers believe their firm to be overvalued. If overvalued stock is regarded as cheap currency, acquirers when using this currency as part of the purchase consideration may inflate the purchase price. On the other hand, Huang and Walkling (1987) and Officer (2003) find that cash acquisitions are associated with higher premium to compensate target shareholders for the immediate tax liability.

  27. Alternatively, acquisitions unrelated to the acquirer’s main business may not involve overpayment at the time of the original acquisition but may still lead to subsequent goodwill impairment due to expected synergies not materializing.

  28. We do not include poison pill as an additional variable since almost all targets in our sample do not have a poison pill in place. Also, we do not include “Clean-up” as a control-acquisition variable because, by construction, our sample does not include any acquisitions where the acquirer owns more than 50% of the target prior to the acquisition.

  29. The significance of Excess and Premium remain substantially the same when we introduce (the log of) goodwill at the beginning of the impairment year as an additional independent variable.

References

  • Ali, A., Klein, A., & Rosenfeld, J. (1992). Analysts’ use of information about permanent and transitory earnings components in forecasting annual EPS. The Accounting Review, 67, 183–198.

    Google Scholar 

  • Amihud, Y., & Lev, B. (1981). Risk reduction as a managerial motive for conglomerate mergers. The Bell Journal of Economics, 12, 605–617.

    Article  Google Scholar 

  • Beatty, A., & Weber, J. (2006). Accounting discretion in fair value estimates: An examination of SFAS 142 goodwill impairments. Journal of Accounting Research, 44, 257–288.

    Article  Google Scholar 

  • Bens, D., Heltzer, W., & Segal, B. (2007). The information content of goodwill impairments and the adoption of SFAS 142. Working paper, University of Arizona. http://www.papers.ssrn.com/sol3/papers.cfm?abstract_id=1001744.

  • Berkovitch, E., & Narayanan, M. (1993). Motives for takeovers: An empirical investigation. Journal of Financial and Quantitative Analysis, 28, 347–379.

    Article  Google Scholar 

  • Betton, S., & Eckbo, B. (2000). Toeholds, bid-Jumps, and expected payoffs in takeovers. Review of Financial Studies, 13, 841–882.

    Article  Google Scholar 

  • Bradley, M., Desai, A., & Kim, E. (1988). Synergistic gains from corporate acquisitions and their division between the stockholders of target and acquiring firms. Journal of Financial Economics, 21, 3–40.

    Article  Google Scholar 

  • Chen, C., Kohlbeck, M., & Warfield, T. (2004). Goodwill valuation effects of the initial adoption of SFAS 142. Working paper, University of Wisconsin. http://www.papers.ssrn.com/sol3/papers.cfm?abstract_id=534484.

  • Churyk, N. (2005). Reporting goodwill: Are the new accounting standards consistent with market valuations? Journal of Business Research, 58, 1353–1361.

    Article  Google Scholar 

  • Dimson, E. (1979). Risk measurement when shares are subject to infrequent trading. Journal of Financial Economics, 7, 197–226.

    Article  Google Scholar 

  • Elliot, J., & Hanna, D. (1996). Repeated accounting write-offs and the information content of earnings. Journal of Accounting Research, 34, 135–155.

    Article  Google Scholar 

  • Fowler, D., & Rorke, C. H. (1983). Risk measurement when shares are subject to infrequent trading: Comment. Journal of Financial Economics, 12, 279–283.

    Article  Google Scholar 

  • Francis, J., Hanna, D., & Vincent, L. (1996). Causes and effects of discretionary asset write-offs. Journal of Accounting Research, 34, 117–134.

    Article  Google Scholar 

  • Gaughan, P. (2002). Mergers, acquisitions, and corporate restructurings. Wiley, New York: 3.

    Google Scholar 

  • Gu, F., & Lev, B. (2008). Overpriced shares, ill-advised acquisitions, and goodwill impairment. Working paper, New York University. http://www.papers.ssrn.com/sol3/papers.cfm?abstract_id=1130940.

  • Hayn, C., & Hughes, P. (2006). Leading indicators of goodwill impairment. Journal of Accounting Auditing & Finance, 21, 223–266.

    Google Scholar 

  • Henning, S., Lewis, B., & Shaw, W. (2000). Valuation of the components of purchased goodwill. Journal of Accounting Research, 38, 375–386.

    Article  Google Scholar 

  • Henning, S., & Stock, T. (1997). The value-relevance of goodwill write-offs. Working paper, Southern Methodist University. http://www.papers.ssrn.com/sol3/papers.cfm?abstract_id=30242.

  • Huang, Y., & Walkling, R. (1987). Target abnormal returns associated with acquisition announcements. Journal of Financial Economics, 19, 329–349.

    Article  Google Scholar 

  • Moehrle, S., & Moehrle, J. (2001). Say good-bye to pooling and goodwill amortization. Journal of Accountancy, 192, 31–38.

    Google Scholar 

  • Morck, R., Shleifer, A., & Vishny, R. (1990). Do managerial objectives drive bad acquisitions? Journal of Finance, 45, 31–48.

    Article  Google Scholar 

  • Myers, S., & Majluf, N. (1984). Corporate financing and investment decisions when firms have information that investors do not. Journal of Financial Economics, 13, 187–221.

    Article  Google Scholar 

  • Officer, M. (2003). Termination fees in mergers and acquisitions. Journal of Financial Economics, 69, 431–467.

    Article  Google Scholar 

  • Ramanna, K. (2008). The implications of unverifiable fair-value accounting: Evidence from the political economy of goodwill accounting. Journal of Accounting and Economics, 45, 253–281.

    Article  Google Scholar 

  • Ramanna, K., & Watts, R. (2010). Evidence on the use of unverifiable estimates in required goodwill impairment. Working paper, Harvard Business School. http://www.papers.ssrn.com/sol3/papers.cfm?abstract_id=1134943.

  • Rees, L., Gill, S., & Gore, R. (1996). An investigation of asset write-downs and concurrent abnormal accruals. Journal of Accounting Research, 34, 157–169.

    Article  Google Scholar 

  • Riedl, E. (2004). An examination of long-lived asset impairments. The Accounting Review, 79, 823–852.

    Article  Google Scholar 

  • Roll, R. (1986). The hubris hypothesis of corporate takeovers. Journal of Business, 59, 197–216.

    Article  Google Scholar 

  • Shleifer, A., & Vishny, R. (1988). Value maximization and the acquisition process. Journal of Economic Perspectives, 2, 7–20.

    Google Scholar 

  • Watts, R. (2003). Conservatism in accounting Part I: Explanations and implications. Accounting Horizons, 17, 207–221.

    Article  Google Scholar 

Download references

Acknowledgments

We thank the editor, two anonymous reviewers, Hemang Desai, Peter Easton, Wayne Landsman, K. Ramanna, K. Ramesh, Judy Rayburn, Katherine Schipper, the participants of the University of Minnesota Empirical Accounting Conference, AAA Financial Accounting and Reporting Section Mid-Year Conference, Financial Economics and Accounting Conference, and workshop participants at Baruch College, Duke University, Penn State University, and Southern Methodist University for valuable comments and suggestions. We gratefully acknowledge the financial support provided by the Accounting Research Center of the Carlson School of Management at the University of Minnesota.

Author information

Authors and Affiliations

  1. Southern Methodist University, PO BOX 750333, Dallas, TX, 75275, USA

    Zining Li & Ramgopal Venkataraman

  2. University of Minnesota, Carlson School of Management, 321 19th Ave. South, Minneapolis, MN, 55455, USA

    Pervin K. Shroff & Ivy Xiying Zhang

Authors
  1. Zining Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Pervin K. Shroff
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Ramgopal Venkataraman
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Ivy Xiying Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Pervin K. Shroff.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Li, Z., Shroff, P.K., Venkataraman, R. et al. Causes and consequences of goodwill impairment losses. Rev Account Stud 16, 745–778 (2011). https://doi.org/10.1007/s11142-011-9167-2

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11142-011-9167-2

Keywords

  • Goodwill write-off
  • SFAS 121
  • SFAS 142
  • Acquisitions
  • Managerial discretion

JEL Classification

  • G14
  • G34
  • M41
  • M48