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Valuation of loss firms in a knowledge-based economy

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Abstract

Recent research in accounting has documented a substantial increase in the number of loss firms. Existing theories on the valuation of loss firms are based on adaptation/abandonment options or limited liability, assuming that these firms are operationally distressed. In this paper, we show that many loss firms do not fit this stereotype and identify the primary value drivers of this new type of loss firms. Our analysis helps resolve the puzzling negative relation between earnings and market value documented in prior research. Overall, our findings underscore the importance of “hidden assets” or intangibles in the study of loss firms.

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Notes

  1. Based on income before extraordinary items (item #18 in Compustat).

  2. To be precise, we mean by a “loss firm” a firm that posts a negative earning in a particular year (i.e., firm-year observation).

  3. In fact, Collins, Maydew, and Weiss (1997) document that the value relevance of earnings in general has declined (while that of book values has increased) over time due, among others, to the increasing frequency of losses. See also Basu (1997); Elliott and Hanna (1996); and Hayn (1995).

  4. See Hayn (1995), Berger, Ofek, and Swary (1996), Collins et al. (1999), Core and Schrand (1999), and Wysocki (2003).

  5. Hand (2003) documents a similar “nonlinear” relation for Internet stocks.

  6. Firms with positive profits have survived for 6.33 years on average.

  7. A similar observation was made by Joos and Plesko (2005). They document that firms with “persistent” losses have become more numerous and show that these persistent losses are increasingly caused by large R&D outlays.

  8. Hillegeist, Keating, Cram, and Lundstedt (2004) report that the overall corporate bankruptcy rate fluctuate with business cycles, but ranged from .48% to 2.25% for the period 1980 to 2000. There is, however, a substantial variation across industries.

  9. Because total assets are less sensitive to current losses than BVE, the effect of scaling for loss firms is less severe.

  10. If and when the bias reverses in the future, the numbers will be biased upward.

  11. In an excellent discussion on conservative accounting, Zhang (2000) uses simulation to show that such a phenomenon is possible.

  12. Of course, from the second year on, we need to consider the impact of amortization of capitalized R&D expenditures (Kothari, Laguerre, & Leone, 2002; Lev & Sougiannis, 1996, 1999). Capitalization, however, requires one to use a long history of data and to specify capitalization rates. Since loss firms tend to be younger, the data requirement would reduce the sample substantially. For these reasons, we simplify our approach by using the linear specification (8).

  13. See the discussion of big bath in Burgstahler and Dichev (1997) and Kirschenheiter and Melumad (1998). Francis, Hanna, and Vincent (1996) examine the issue of earnings management through discretionary asset write-offs. Another possible motive for taking a large write-off is top management’s desire to increase their bonuses (Healy, 1985).

  14. See Bartov, Mohanram, and Seethamraju (2001) for valuation of internet firms. Since they often do not have profits, investors tend to rely on sales in valuing these firms.

  15. The cost of developing a new drug has become more expensive over time. DiMasi, Hansen, and Grabowski (2003) estimate that the average R&D cost of a new drug increased from $231 million in 1987 to $802 million in 2000.

  16. For example, Celgene states in their 2002 annual report: “We have sustained losses in each year since our inception as an independent biopharmaceutical company in 1986.” Their operation has been sustained partially by product sales, research contracts, and license payments, but mostly by the proceeds from an IPO in 1987, an SEO in 2000, and licensing agreements, such as the one with Novartis, for the development of new drugs.

  17. We do not use measures such as Altman’s Z-score, since they are designed to predict a firm’s probability of bankruptcy in the future and moreover contain price and earnings. The analysis containing other variables of Altman’s Z produced coefficient estimates that are insignificant.

  18. Table 1 partitions firms by beginning book values, while Table 2 Panels A, B by ending BVE. Therefore, the number of firms in each BVE category is similar but not identical.

  19. The R&D expenditures for 1973 and 1974 are not comparable to those for other years, since the R&D expensing requirement became effective in 1975.

  20. The two largest industries, but with few loss firms and low RDI, are depository institutions (SIC 60) and electric, gas, and sanitary services (49), both of which have been highly regulated.

  21. Although we do not report the details, we also carry out our analysis using capitalized R&D (Lev & Sougiannis, 1996). The results are essentially the same.

  22. Because Eq. 9 is scaled by beginning total assets, SGR in (9) is multiplied by A t-1.

  23. We do not include dividends since loss firms rarely pay dividends.

  24. Another difference is that CPX includes dividends in earnings. However, since loss firms pay few dividends, this difference in definition does not materially affect the result.

  25. Empirically, it can be shown that the number of shares is approximately proportional to the square root of market values.

  26. The coefficients are significant at 10% for firms with BVE > $10 million and at 1% for firms with BVE ≤ $10 million, respectively.

  27. Controlling for firms with special items implies that the regression coefficient is determined by the firms without special items. Thus, it must be the case that the firms that do not have special items have more negative relation.

  28. The t-ratio (untabulated) for testing that \({\gamma_{42}=1}\) of our regression equation is 2.20 for Model 5 and 3.93 for Model 7 for firms with BVE > $10 million.

  29. These researchers have used the relative-pricing-error (RPE) method. The SPRE is the symmetrized version of RPE so that the estimate is independent of the direction of price deviation.

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Acknowledgments

We thank the useful comments made by Sudipta Basu, Donal Byard, and Peter Joos. We also acknowledge the research support from PSC-CUNY.

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  1. Baruch College-CUNY, One Bernard Baruch Way, New York, NY, 10010, USA

    Masako Darrough & Jianming Ye

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  1. Masako Darrough
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  2. Jianming Ye
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Correspondence to Masako Darrough.

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Darrough, M., Ye, J. Valuation of loss firms in a knowledge-based economy. Rev Acc Stud 12, 61–93 (2007). https://doi.org/10.1007/s11142-006-9022-z

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