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Differences in the value relevance of identifiable intangible assets

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Abstract

Motivated by investor criticisms of current accounting standards, this study investigates whether differences exist in how acquired identifiable intangible assets relate to investors’ expectations about the entity’s cash flow prospects. Some investors assert that all acquired intangibles should be subsumed within goodwill, while others prefer separate recognition of identifiable intangibles only when they are strategically important sources of future cash flows. Still other investors call for separate recognition from goodwill only when identifiable intangibles are separable from the business, have defined useful lives, and have identifiable revenue streams (i.e., “wasting” intangibles). Consistent with some investor views, we find cross-sectional variation in the value relevance of identifiable intangibles based on differences in underlying asset characteristics. Our primary findings suggest that strategically important and wasting intangibles provide information different from that provided by goodwill. These findings inform standard setters as they evaluate recognition and disclosure alternatives for identifiable intangible assets.

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Notes

  1. For that asset class, we fail to find consistent evidence that coefficients differ from zero, which suggests expensing rather than capitalizing those intangibles.

  2. For example, see Aboody and Lev (1998), Barth et al. (1998), Barth and Clinch (1998), Chalmers et al. (2011), Bauman and Shaw (2018), Kallapur and Kwan (2004), Kimbrough (2007), Sahut et al. (2011), Tsoligkas and Tsalavoutas (2011), and Wangerin (2019).

  3. Investors’ dependence on information sources beyond accounting is increasing with the growing availability of timelier sources of forward-looking information. Still investors have noted that does not negate the value of accounting information if it confirms the information used to set security prices (Papa 2018). If investors use other timelier sources of information, then the confirmatory value of financial reporting information increases relative to predictive value. Investors also have reported that this confirmatory value enables them to have governance over other timelier sources of information by enabling assessments of its reliability and consistency across various management communication platforms both non-GAAP and GAAP (Papa 2018). Therefore it is not necessary for financial statement disclosures to have a direct causal effect on investors’ judgments (i.e., provide decision-relevant information) to conclude accounting information is relevant.

  4. This research relies on extensive evidence in the accounting and finance literatures that equity markets efficiently impound publicly available information in prices. Prior research shows that, when potential market inefficiencies exist, any bias to parameter estimates in price-level regressions is not economically significant. Therefore those estimates support reliable inferences (Aboody et al. 2002; Barth 2007).

  5. Prior research also operationalizes the value relevance of asset values in alternative ways, including studies that associate recognized asset values with future income (e.g., Aboody and Lev 1998) and operating cash flows (e.g., Deng and Lev 2006). However, it is important to recognize that there is significant heterogeneity in the pattern over which future cash flows and earnings arise from different types of intangible assets. For example, Clarke (1976) estimates the benefits to marketing-related intangibles (e.g., tradenames, brands, etc.) are realized between three and 15 months. In contrast, Healy et al. (2002) propose that a commercialized pharmaceutical can generate cash inflows while under patent for upwards of 10 years.

  6. Failing to find differences between coefficients on certain types of intangibles and goodwill also could be due to a lack of statistical power.

  7. According to the measurement guidance in SFAS 157 (FASB 2006; codified and currently active in ASC Topic 820), fair values for identifiable intangibles are generally Level 2 or Level 3 estimates because there are rarely identical assets traded in active markets. Most fair value estimates for intangible assets use Level 3 inputs, but there are certain cases where transactions involving similar (but not identical) assets are observable. In these cases, Level 2 inputs are most commonly available for internet domain names, FCC licenses, and carbon emission rights (AICPA 2012).

  8. We use the term “outcome uncertainty” to be consistent with the IASB’s Conceptual Framework, which defines it as uncertainty arising from unknown amounts, timing, or both of future cash inflows and outflows from an asset or liability (IASB 2018). This differs from measurement uncertainty in the IASB’s Conceptual Framework, which is defined as arising when prices are unobservable in an active market and therefore must be estimated. However, to be consistent with how measurement uncertainty often is described in prior research, outcome uncertainty also could be viewed to be an additional dimension of measurement uncertainty.

  9. Easton and Sommers (2003) show that biased coefficients in price-levels regressions can arise due to the effects of outliers concentrated among large firms. Therefore we also follow the recommendation of Easton and Sommers (2003) to use market capitalization as an alternative scalar in price-level regressions (untabulated). Regression diagnostic statistics indicate outliers are concentrated among the largest firms in our sample. This suggests that scaling by market capitalization (rather than shares outstanding) within our sample of acquirers also is not sufficient to produce unbiased coefficients.

  10. Leone et al. (2019) recommend examining studentized residual and DFIT statistics to identify potentially influential observations in the data. Such an examination using equation (1) (described in the next section) identifies 65 potentially influential observations in our data with absolute studentized residuals greater than 2.0 and 93 potentially influential observations in our data with absolute DFIT statistics greater than 2*(p/n)1/2, where p is the number of parameters (24) and n is the number of observations (2,560). Robust regression helps ensure that our results are not driven by outliers.

  11. We also validate our classification of wasting and organically replaced intangibles by regressing changes in future sales and future advertising expenses on these variables. We expect that both wasting and organically replaced intangibles will be associated with future sales but only organically replaced intangibles will be associated with future advertising expenses because only organically replaced intangibles require future expenditures to maintain or enhance their value. In untabulated validation tests, we find results that confirm our expectations.

  12. To provide evidence on whether the recent financial crisis affects inferences, we re-ran our primary analyses on firm-years that Compustat assigns an FYEAR of 2010 or higher. Inferences are unchanged in this analysis (untabulated).

  13. There are 633 firm-year observations reporting negative earnings in the acquisition year, which represents approximately 25% of our sample. Therefore we re-estimated our primary tests allowing the coefficient on earnings to vary for loss firms. Inferences are unchanged.

  14. When using the industry-based (asset-type) classification, there are 708 (829) observations with no strategically important intangibles and 508 (496) observations with more than one strategically important intangible (untabulated).

  15. We do not report adjusted R2 statistics because they are not meaningful goodness-of-fit measures in robust regressions (Leone et al. 2019). When estimating our models in weighted least squares using weights obtained from robust regressions, we obtain adjusted R2 statistics of 0.66 or better (untabulated).

  16. We show, in Appendix 2, that the identifiable intangibles management discloses as strategic are the same as those identified by our measures, suggesting both approaches may consistently identify the same assets.

  17. We omit industry fixed effects because our changes specifications examine first differences of all dependent and independent variables of interest. Therefore factors that do not vary over time, such as industry, are implicitly controlled for (Greene 2012, pp. 355–356; Wooldridge 2013, pp. 459–474).

  18. We limit our analyses to the strategically important cross-section because our previous cross-sectional results indicate that nonstrategic organically replaced intangibles are not consistently associated with equity prices and, therefore not relevant to investors.

  19. Prior to the release of the purchase price allocation disclosure, we expect that some investors may have formed expectations about the amounts allocated to intangibles based on other publicly available information. However, without some observable measure of such investor expectations, it is not possible to determine whether a particular recognized amount should have a positive or negative effect on signed returns over short windows surrounding the release of purchase price allocations.

  20. The press release and 10-K referenced in this paragraph can be found at https://www.sec.gov/Archives/edgar/data/0000821002%0b/000157104916016767/0001571049-16-016767-index.htm and https://www.sec.gov/cgi-bin/viewer?action=view&cik=821002&accession_number=0001571049-17-003132&xbrl_type=v, respectively.

  21. The press release and 10-K referenced in this paragraph can be found at https://www.sec.gov/Archives/edgar/data/0000882095/000119312511317733/0001193125-11-317733-index.htm and https://www.sec.gov/cgi-bin/viewer?action=view&cik=882095&accession_number=0000882095-13-000015&xbrl_type=v#, respectively.

  22. The press release and 10-K referenced in this paragraph can be found at https://www.sec.gov/Archives/edgar/data/0000018230/000001823010000534/0000018230-10-000534-index.htm and https://www.sec.gov/cgi-bin/viewer?action=view&cik=18230&accession_number=0001104659-12-011331&xbrl_type=v#, respectively.

  23. The press release and 10-K referenced in this paragraph can be found at https://www.sec.gov/Archives/edgar/data/0000091419/000129993311001505/0001299933-11-001505-index.htm and https://www.sec.gov/Archives/edgar/data/0000091419/000119312512282260/0001193125-12-282260-index.htm, respectively.

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Acknowledgements

We thank Mary Barth, Christine Botosan, **a Chen, Jenny Chu, David Erkens, Allison Koester, Lubomir Litov, Clay Partridge, Richard Price, Richard Sloan (editor), Ron Shalev (discussant), Andrea Tillet, Qian Wang (discussant), Erika Wheeler, Kevin Ow Yong, two anonymous reviewers, workshop participants at Georgetown University, Singapore Management University, and University of Wisconsin-Madison, participants at the 2020 HARC Conference, the 2020 SARAC Conference, and the 2020 PCOB Workshop on Valuation and Accounting for Intangible Assets for helpful comments. Linsmeier and Wangerin both acknowledge financial support from the Wisconsin School of Business and the University of Wisconsin-Madison Office of Research and Graduate Education.

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  1. University of Wisconsin – Madison, 975 University Avenue, Madison, WI, 53706, USA

    Zachary King, Thomas J. Linsmeier & Daniel D. Wangerin

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  1. Zachary King
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  3. Daniel D. Wangerin
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Correspondence to Daniel D. Wangerin.

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Appendices

Appendix 1: Variable Descriptions

Variable

Description

Price i,t

Acquiring firm stock price three months after the end of fiscal year t.

Aggregate_II i,t

The aggregated acquisition date book values of all identifiable intangible assets recorded for firm i in year t in the Houlihan Lokey data, scaled by shares outstanding three months after the end of fiscal year t.

Wasting_II i,t

The acquisition date book values of all wasting identifiable intangible assets recorded for firm i in year t in the Houlihan Lokey data, scaled by shares outstanding three months after the end of fiscal year t. Wasting identifiable intangible assets are defined as those assets classified by the Houlihan Lokey data as developed technology or contract-related.

Organic_II i,t

The acquisition date book values of all organically replaced identifiable intangible assets recorded for firm i in year t in the Houlihan Lokey data, scaled by shares outstanding three months after the end of fiscal year t. Organically replaced identifiable intangible assets are defined as those assets classified by the Houlihan Lokey data as customer-related, trademarks, trade names, or in-process R&D

Definite_II i,t

The acquisition date book values of all identifiable intangible assets classified by U.S. GAAP as definite-lived and recorded for firm i in year t in the Houlihan Lokey data, scaled by shares outstanding three months after the end of fiscal year t.

Indefinite_II i,t

The acquisition date book values of all identifiable intangible assets classified by U.S. GAAP as indefinite-lived and recorded for firm i in year t in the Houlihan Lokey data, scaled by shares outstanding three months after the end of fiscal year t.

SI_II_Ind i,t

The acquisition date book values of all identifiable intangible assets classified for firm i in year t as strategically important based on industry as described in Figure 1, scaled by shares outstanding three months after the end of fiscal year t.

Non-SI_II_Ind i,t

The acquisition date book values of all identifiable intangible assets not classified for firm i in year t as strategically important based on industry, scaled by shares outstanding three months after the end of fiscal year t.

SI_II_AType i,t

The acquisition date book values of all identifiable intangible assets classified for firm i in year t as strategically important based on asset-type as described in Figure 1, scaled by shares outstanding three months after the end of fiscal year t.

Non-SI_II_AType i,t

The acquisition date book values of all identifiable intangible assets not classified for firm i in year t as strategically important based on asset-type, scaled by shares outstanding three months after the end of fiscal year t.

BV i,t

Book value of common equity (CEQ in Compustat) less the book values of all acquired identifiable intangible assets and goodwill recorded for firm i in year t in the Houlihan Lokey data, scaled by shares outstanding three months after the end of fiscal year t.

NI i,t

Net income before extraordinary items (IB in Compustat) for firm i in year t, scaled by shares outstanding three months after the end of fiscal year t.

Goodwill i,t

The acquisition date book value of all goodwill recorded for firm i in year t in the Houlihan Lokey data, scaled by shares outstanding three months after the end of fiscal year t.

|AbRET[t-1;t+i]|

The absolute value of total returns less CRSP’s equally weighted market return from day t-1 to day t+i. Total returns is measured as market value of equity on day t+i less market value of equity on day t-1, divided by market value of equity on day t-1.

AbVOL[t-1;t+i]

Log of average daily trading volume from day t-1 to day t+i divided by average daily trading volume from day t-41 to day t-11. Daily trading volume equals shares traded divided by total shares outstanding.

AbBV i,t

Unadjusted I/B/E/S actual BPS less the latest median consensus forecast of BPS before the earnings announcement date, scaled by market value of equity the day before the first release of the purchase price allocation. If I/B/E/S data is unavailable, AbBVi,t equals book value of common equity (CEQQ in Compustat) less book value of common equity for the same quarter one year ago, scaled by market value of equity the day before the first release of the purchase price allocation. AbBVi,t equals zero if the preliminary earnings announcement date in Compustat precedes the day before the first release of the purchase price allocation.

AbNI i,t

Unadjusted I/B/E/S actual EPS less the latest median consensus forecast of EPS before the earnings announcement date, scaled by market value of equity the day before the first release of the purchase price allocation. Our I/B/E/S definition of AbNIi,t is consistent with the definition of forecast errors in Campbell et al. (2022). If I/B/E/S data is unavailable, AbNIi,t equals quarterly income before extraordinary items (IBQ in Compustat) less quarterly income before extraordinary items for the same quarter one year prior, scaled by market value of equity the day before the first release of the purchase price allocation. AbNIi,t equals zero if the preliminary earnings announcement date in Compustat precedes the day before the first release of the purchase price allocation.

Appendix 2: Examples of Strategically Important Identifiable Intangibles

Listed below are excerpts from SEC filings for several acquisitions in our sample that illustrate the outcomes of our methods for classifying identifiable intangible assets as either strategically important or nonstrategic. Each acquisition in this appendix generally resulted in the recognition of more than one identifiable intangible asset. For each acquisition, one or more identifiable intangible assets are classified as strategically important under our procedures, and the book values of those assets are included in either SI_II_Indi,t, SI_II_ATypei,t, or both. The book value of identifiable intangible assets excluded from SI_II_Indi,t (SI_II_ATypei,t) is included in Non-SI_II_Indi,t (Non-SI_II_ATypei,t). Identifiable intangible assets classified as strategically important are indicated using red boxes and, unless otherwise noted, meet the requirements to be classified as such under both of our strategic measures, SI_II_Indi,t and SI_II_ATypei,t. We have used boldface italics to add emphasis throughout.

Panel A: G-III Apparel Acquires Donna Karan International

This transaction represents an acquisition of a competing fashion merchandise company that expands the acquirer’s brand portfolio to include DKNY brands. In the press release announcing the acquisition, G-III notes: “Donna Karan International is an iconic global fashion company. … providing incremental growth on top of our portfolio of some of the best fashion brands in the world…We believe the DKNY brand has a dynamic position in the market.” The identifiable intangible corresponding to the DKNY brand is classified as strategically important. This asset is recognized as “trade names” in the G-III Apparel purchase price allocation disclosure below.Footnote 20

Panel B: Gilead Sciences Acquires Pharmasset

In this acquisition, Gilead Sciences acquired Pharmasset, a company focused on the clinical development of new treatments for chronic hepatitis C virus (HCV). As noted by Gilead’s chairman and CEO, Dr. John Martin: “The acquisition of Pharmasset represents an important and exciting opportunity to accelerate Gilead’s effort to change the treatment paradigm for HCV-infected patients by develo** all-oral regimens for the treatment of the disease regardless of viral genotype… Pharmasset presented compelling Phase 2 data earlier this month further characterizing the strong efficacy and safety profile of PSI-7977. The compound, together with Pharmasset’s other pipeline candidates, represents a strong strategic fit with Gilead’s vision, pipeline and capabilities.” Pharmasset’s HCV treatments in the development pipeline were recognized by Gilead as in-process R&D and this asset is classified as strategically important.Footnote 21

Panel C: Caterpillar Acquires Bucyrus

This transaction represents an acquisition of an established manufacturer and dealer of mining equipment. According to the company’s acquisition announcement press release, “The acquisition is based on Caterpillar’s key strategic imperative to expand its leadership in the mining equipment industry.” Caterpillar’s former chairman and CEO, Doug Oberhelman, describes how the acquisition will expand the company’s product offerings to customers in the mining industry: “For several years, mining customers have been asking us to expand our range of products and services to better serve their increasingly complex requirements … This announcement says to those customers, we heard you loud and clear.” The customer relationships and intellectual property intangibles are classified as strategically important. The customer relationship intangibles represent existing relationships with Bucyrus mining customers, and the intellectual property corresponds to Bucyrus’ mining equipment products.Footnote 22

The following table is a summary of the fair value estimates of the acquired identifiable intangible assets, weighted—average useful lives, and balance of accumulated amortization as of December 31, 2011:

Panel D: The J.M. Smucker Company Acquires Rowland Coffee Roasters

This transaction represents an acquisition of two well-known coffee brands, expanding Smucker’s coffee business to reach a specific class of consumers in specific areas of the United States with established distribution channels in retail and food service. As described by former Chairman and CEO Richard Smucker, “The addition of the Café Bustelo® and Café Pilon coffee brands, each with a rich heritage, provides us with a unique opportunity to establish a strong presence in coffee with Hispanic consumers in the U.S.” In addition, the acquisition press release points out that “Rowland Coffee’s products are primarily sold under the leading Hispanic Café Bustelo® and Café Pilon brands with distribution in retail and foodservice channels concentrated in the northeastern U.S. and southern Florida.” Customer relationships corresponding to Rowland Coffee Roasters’ distribution channels are classified as strategically important by SI_II_Indi,t and SI_II_ATypei,t. However, trademarks are only classified as strategically important by SI_II_ATypei,t (denoted below in the box with the dashed border).Footnote 23

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King, Z., Linsmeier, T.J. & Wangerin, D.D. Differences in the value relevance of identifiable intangible assets. Rev Account Stud (2023). https://doi.org/10.1007/s11142-023-09810-8

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